Self-regulated Learning: A Narrative Review

 

Husain Abdulhay

 

Abstract: Issue of self- versus other-regulation is also diligently stressed and applied in contemporary education so as to put person at the helm of situation, not a pawn at the mercy of circumstances. In the same vein, this study aims to draw attention to a newly developed concept of learning which overemphasizes the role of individual learner in attunement of his thought, emotions and strategies to accelerate and escalate the extent of his acquisition. To do so, an overview of this new phenomenon known as self-regulated learning is given at first and evidence attesting to the fruitfulness and utility of such strategy is dispensed in the following.

Keywords: Self-regulated learning, motivation, cognition, metacognition, context

 INTRODUCTION

Self-regulated learning (henceforth SRL) emerged as a result of inquisitiveness into “how students become master of their own learning” (Zimmerman and Martinez-Pons, 1990, p.4). It has been eventuated from inquiry into the process of learning by those learners who have been assiduous and triumphant in their learning despite hindrances to their efforts (ibid).

Self-regulation has gained momentum in educational psychology consonant with constructivism approach to learning to attend more to the role of individual learner and his/her needs for better management of his/her learning. Research in educational domain is likewise exploiting this advancement by highlighting all aspects of individuals which are worth the investigation and consideration for an effective learning to occur.  This prompted researchers to pedagogically extend an operational definition for self-regulated learning.

Self-regulation has come to the fore as learner’s responsibility for learning and taking active role for constructing his own knowledge is much more acknowledged and promulgated in developmental education. Contemporary education acknowledges the centrality of learner and learner’s development and seeks to lend assistance to advance this development by considering all aspects of learning and teaching affecting learners’ progress. Knowledge is not any more transmitted to acquirers; rather, it is obtained in a way, bound and determined by learners, to actualize this entity.

Learners are much more valued in the contemporary educational system in so far as their roles as the builders of knowledge are more gratified. SRL is congruent with constructivism and learner-centered education.  Self-regulated learning is in parallel with constructivist view of learning and teaching in that it puts learner at the epicenter of learning and construction of knowledge and, hence, it merits more heed in contemporary education. Constructivism underscores the importance of individual self in building meaning (Vygotsky, 1978). Learner acts out as an umpire of feeding inlet of knowledge to them.

Disassociation from text-based education and moving towards constructivism seeks learners to be independent self-regulative learners and this is much sooner accomplished in a milieu which supports and provides sufficient altitude for learners to experience and implement their skills and strategies to self regulate their learning. Teachers can provide enough leeway for learners to participate and engage by creating an environment which is secure to experience and maneuver over their learning. Cultivating  a milieu which is encouraging and motivating allow for experiencing and implementing skills and strategies more willingly and get feedback for establishing and if deemed necessary altering their strategies to learn more effectively.

Literature aims to spur teachers and practitioners to reckon at learners’ responsibilities and decision making, congruent with constructivism and schism from transmission of knowledge, rote learning, and spoon-feeding schools of teaching.

 

 

  1. REVIEW OF THE RELATED LITERATURE

 

Self-regulated learning has been in the limelight over the last three decades. It has grabbed attentions among academics and psychologists. It stems from educational psychology and percolates in educational and non-educational studies and instruction. SRL has attracted many fields from psychology to mathematics, health, sport, medic, technology, policy making, and language education. Myriad empirical and non empirical studies exist concerning educational and non educational self-regulation learning.

Effect of self-regulatory strategies on academic success has been well established in many studies (Pintrich & De Groot, 1990; Pintrich, 1990; Zimmerman, 1990). Self-regulated learners indulge much higher self-propulsion in their learning in comparison with those who do not self-regulate. Zimmerman and Martinez-Pons (1990) refer to a growing body of correlational research which denotes higher achievements with greater usage of learning strategies by self- regulated learners than with little utilization of self-directed learning strategies.

Wolters, A. C. (2010) in a review study entitled the relation between the 21st Century and self-regulated learning (SRL), with reference to multiple studies, evinced that however forging students into a self-regulated learner establishes the stepping-stone to volition, motivation, and self-management in them, transferable also to contexts outside of school.

Effect of schooling on the different dimensions of self-regulated learning has been examined in different fields of study. Leutwyler, Bruno & Maag Merki, Katharina (2009) in a longitudinal study extending for almost two years in gymnastic school revealed significant effect of schooling on development of self-regulatory capacity of young learners.

Pratontep and Chinwonno (2008) scrutinized the self-regulated learning strategies of 30 Thai university students in a reading comprehension program. The results uncloaked significant differences between the students’ English reading comprehension, divided into upper and lower level groups based on their competencies in reading comprehension,  especially for the lower level group, in pre- and post-test. Students reported frequent use of metacognitive and performance regulation strategies through the self-regulated learning interview schedule. The students in upper level group actively used self-regulated learning strategies more often than the lower level did to regulate their metacognition and performance. Furthermore, the students’ verbal protocols of reading unveiled the use of self-regulated learning strategies in the performance or volitional control phase more often than in the forethought or self-reflection phases.

The positive effects of interventions studies designed to promote students’ SRL have now been well established. Training programs are carried out and pilot tests are conducted as part of the syllabus or running experiments to enhance self-regulated learning. Cleary and Zimmerman (2004) present an anecdote of a cyclical model of academic self-regulation in a case study program to highlight the primary processes and techniques used by an self-regulation coaching (henceforth SRC) working with a 12-year-old Caucasian student and, eventually, to empower her self-regulation skills. The program was sprouted from social-cognitive theory and research and integrated many of the essential features of the problem-solving model. Interventions used in the Self-regulation empowerment program (SREP) comprising making graphic, cognitive modeling and coaching, and structured practice sessions. The SRC assessed Anna’s motivational profile as well as how she used strategies to self-regulate her learning according to triadic phases of self-regulation and, at the end, after getting a feeble grade in the tests she was offered an intervention approach in an individualized training program to teach her to set goals, to record in person the performance processes (i.e., strategies used) and outcomes (i.e., test grades), and to evaluate goal progress and strategy effectiveness. The intervention programs at the end endorsed her improved test score of 90 as a result of her newly acquired study strategies.

The training program much attended to the psychological side of Anna and encouraged her to press in and press on by recording and monitoring her progress with the help of delivered self-regulation strategies taught by her coach. Taking more responsibility for her learning and modifying her beliefs and motivating herself helped Anna to elevate her grades in school. The studies bear robust evidence of the positive effects of SRL instructional programs on children’s academic achievement. It must also be mentioned that training programs will benefit more students and even educators when they are implemented concurrent with other academic interventions or social programs and when they consider all aspects of learners (affective, cognitive, motivational and cultural) and learning settings and self-regulation stages cannot be applied in a rigid way to every  learning activity (ibid).

Causal-effect study carried out by Liu (2008) showed that self-regulatory capacity of learners can predict learners’ self-perceptions in English achievement that in practice affects their successes. This notifies how the enrichment of self-regulatory capacities in the forms of perceptions and beliefs assists learners to attain success.

 

 

  1. A DEFINITION OF SELF-REGULATED LEARNING

 

Self-regulated learning is a composite concept encapsulating besides cognitive and metacognitve strategy also motivation and affection in its framework. Currently, self-regulation is recognized as an amalgamation of cognition, metacognition, motivation and emotion. Zimmerman (1989) posits that the learner’s decisive self-management of environment, behavior, and personal processes is the most visible indicator of a learner’s degree of self-regulation.

Self-regulated learning with its broadened definition is “multi-component, iterative, self-steering processes that target one’s own cognitions, feelings, and actions, as well as features of the environment for modulation in the service of one’s own goals” (Boekaerts and Karoly, 2005).

Paris and Paris (2001) identify self-regulated learning in its three words as the mobilization of autonomy and control by the individuals steering and regulating their actions toward attainment of the goals.

While self-regulation is defined in its discourse meaning as control process of learning, academic self-regulation is identified as proactively active participation of learners in the process of learning.Theorists have their own set interpretation of self-regulated learning contingent upon tradition and schools they’ve adopted for learners’ learning processes.

The terms “self-regulation” and “self-control” are being used interchangeably, albeit some subtle distinctions are drawn by different researchers. Some use the term self-regulation more broadly to refer to goal-directed behavior whereas “self-control” may be associated specifically with conscious impulse control (Baumeister and Vohs, 2004). To Schmeichel and Baumeister (2004), self-regulation associates well with both conscious and unconscious alteration of responses by the self, while “self-control” implies a more explicit and cognizant process of response alternation. By the same token, it can be said that through self-regulation learners wages into acting of the self to change its own responses.

Zimmerman (1990) asserts that however self-regulated learning  is defined differntly according to adopted theoretical orientations by different  researches but the commen conceptualization shared among them is that self-regulated learners are cognitively, metacognitively, motivationally and behaviorally predisposed to accomplish their goals . To become self-regulated learner means that one becomes adept in orientating his/her learning to reach his/her own goals despite cognitive, motivational and emotional impediments. Self-regulation enacts as an interim gadget for optimizing learning and expediting process of goal achievement. Paris and Paris (2001) propound that each person builds his/her own theory of self-regulation.

Self-regulation appeals for heeding the interplay of context and individual behavior (Bandura, 1986). Many instruments and methods exist and are developed to understand self-regulation (e.g. the Learning and Strategies Study Inventory to assess self-regulation strategies in general; LASSI (Weinstein, 1987) , Scale of English Self-Regulated Learning Strategies originated by Wang, Wang, and  Li, 2007 and Motivated Strategies for Learning Questionnaire, MSLQ originated by Pintrich, Smith, Garcia & McKeachie (1993).

 

 

  1. THEORIES AND MODELS OF SELF-REGULATED LEARNING STRATEGIES (SRLs)

 

SRL is examined against various theoretical perspectives for the inclusion of many facets of control and learning (Paris and Paris, 2001). They name Piaget’s constructivist theory, Vygotsky’s socio-cultural theory, social learning theories, and information-processing theories as the central tenets of these theoretical perspectives to study SRL. Zimmerman (1989) expounds it in terms of phenomenological, social cognitive, Vygotskian and cognitive constructivist theories and volitional.

The most prominent theory which overshadows the self-regulation studies and research is Albert Bandura’s social cognitive theory (Zimmerman and Schunk, 1989). Zimmerman (1995), the avant-garde author on self-regulated learning, pursues social cognitive theory to study self-regulation.

However, social cognitive theory has illuminated self-regulated learning studies by providing a holistic backdrop against which the self processes are enacted. It seeks to emphasize reciprocal interactions between the environment, the person, and his/her behavior (Bandura, 1997). It purveys a theoretical framework to scrutinize learning in its real context. All the contributors, inside and outside of the individual learners, to control and regulate learning is encapsulated in social cognitive theory. Learners, in this theory, are identified with their thorough dimensions in which their thoughts, feelings and actions interact reciprocally in an integrating and molding environment to generate the desired learning.

Social cognitive theory addresses the interrelationship between the learner, the learners’ behaviors, and the social environment of classroom (Bandura, 1997). Social cognitive theory expounds on how learners’ properties are influenced by characteristics of learning environment. It represents a broad spectrum of the factors which influence the learners and learning processes.  With the help of the theory researchers are enabled discern umbilical nexus between the learners and learning environment. The consideration of environment in determining actual learning is urged by social cognitive theory, an assumption akin to Vygotscian view of learning, to swerve the riveted attention on the sole studies of cognitive individual development.

Social cognitive theory regards contextual or situational variables as potent contributors to students’ motivation and self-regulation than personal attributes.  It implies in a sense that the context is influential in individual’s cognitive, behavioral and motivational processes of learning. In this view, the individual’s self-regulated learning is not seen as a stable trait in all situations. However it is liable to alternation and change over the course of time and leaned upon different settings. So as a result of the application of this theory to education, self-motivational beliefs and behaviors will vary depending on the nature of educational setting or the specific tasks which learners are required to do.

There are many models of self-regulated learning each of which originates from a different theoretical perspective. In the domain of academic studies many models of self-regulation have been projected, each of which traces back and is imputed to a different theoretical approach, which categorically overlap in their construct and conceptualization (Wolters 2010). The following showcases some, the most prominent of which is the Zimmerman’s model.

 

  1. The Personal Responsibility Orientation model set forth by Brockett and Hiemstra (1991)
  2. The Effort Management Hierarchy model developed by Thomas and Rohwer (1993)
  3. Zimmerman’s three-phase self-regulation model (Zimmerman, 1990)

 

The Personal Responsibility Orientation model set forth by Brockett and Hiemstra (1991) places self-direction in learning as an overriding theme with two related sub-dimensions. There exists the following two constructs under the umbrella of self-direction: (a) self-directed learning which incorporates the concepts of the adult learner and teaching-learning process set forth by Knowles, and (b) learner self-direction which focuses on characteristics internal to the individual that incline person toward taking self-initiated onus.

According to Thomas and Rohwer (1993), the effort management hierarchy model is based on four hierarchical levels of study activity. These activities include monitoring, self-regulation, planning and evaluating. Thomas and Rohwer purport that learner self-direction occurs in a continuum of activities which range from awareness of needs to individual control of one’s study efforts including concentration, time and effectiveness of learning. They add that the key to self-directed learning is regulation and remediation.

Zimmerman’s triadic self-regulation model introduces self-regulation as a cyclical process involving learner assessment and feedback of personal, behavioral, and environmental factors during three phases of the learning process: (a) the forethought phase during which goal setting and social modeling occur; (b) performance control during which the learner compares their performance to that of other learners and provides self-instruction regarding learning strategy; and (c) self-reflection, the stage of self-evaluation, resultant feedback, and self-reward for performance success (Schunk, 2001).

Pintrich (2000) proposes four assumptions for self-regulation and learning:

The first assumption, active constructive assumption, assumes that all acquirers be active, efficient participants in the learning process. Learners subsume new material and anchor it based on previously internalized information to establish individualized meaning, purposes, and strategies. Secondly, control potential is the assumption that learners have the ability to self-manage their thought processes, motivation and behavior and the environment. Third, goal assumption, assumes that learners set goals and self-regulate their efforts by monitoring thought processes, behavior, and motivation en route to reaching those goal. The fourth assumption, mediation, recognizes the role of learners’ personal, behavioral, and environmental self-regulation processes of learning for adjusting mercurial volatility of the individual, the learning context and goal attainment (ibid).

Paris and Paris (2001) extended a developmental metaphor of self-regulation based on socio-cultural model of learning in which students develop competencies and become more self-regulated. In this model of learning Piagetian tenet is also applied in which behaviors are molded and organized through participation of learners in zone of proximal development and self-regulation is an adaptive representation of this organization demonstrated in a situation than a set of skills to be learnt (ibid.).

 

 

  1. COGNITIVE & METACOGNITIVE FACETS OF SELF-REGULATED LEARNING

 

Metacognition is considered as an effective strategy for putting self-regulation into effect. Positive direct effects of metacognitive self-regulation on deep learning strategies and on self-regulatory strategies was sealed by Al-Harthy and Was (2010).

Metacognition is ken about cognition and regulation of cognition. It refers to ability to mull over and control ones’ own learning (Flavell, 1979, 1981). Knowledge about cognition encompasses three sub-processes facilitating reflective aspect of meta-cognition: declarative, procedural and conditional knowledge. Regulation of meta-cognition includes planning, monitoring, debugging and evaluation of strategies. The metacognitive self-regulation component refers to the awareness of and control over the cognitive processes.

Susimesta (2006), in an attempt to identify the theoretical and empirical boundary line between self-regulation, self-regulated learning and metaconition, concluded that drawing a boundary line between cognition skills and strategies and metacognition skills and strategies is sometimes difficult. Dinsmore, Alexander, and Loughlin (2008), by rehashing and dissecting 225 studies, found that metacognition is so pertained to cognitive orientation while self-regulation more to human action. Duckworth, K., Akerman, R., MacGregor A.,Salter, E., & Vorhaus , J. (2009) endorse that cognitive and non-cognitive skills are entwined.

Zimmerman and Martinez-Pons (1990) purport that, students who are mecognitivley aware show a better performance and are more strategic than those learners who are less informed of. Not to mention, many of the metacognitive knowledge and skills are not necessarily and specifically taught in classroom. As Elliot (1999) puts it, students mould their ideas and reactions gradually and only after undergoing many challenging learning.

 

However, there is some inconsistency between findings in some researches. Pokay and Blumenfeld (1990) evidenced the negative relationship between meatcognitive strategy use and achievement. To quote Zimmerman (1995, p. 217), “it is one thing to possess metacognitive knowledge and skill but another thing to be able to self-regulate its use in the face of fatigue, stressors, or competing attractions”.

 

 

  1. MOTIVATIONAL FACETS OF SELF-REGULATED LEARNING

 

According to Boekaerts, M. (1999) most studies have focused on modifying cognitive dimensions of self-regulation for optimal learning to happen than those of affection, motivation and performance. Zimmerman (1995) claims that self regulation is more than metacognitive ken and thinking skills. It concerns with self efficacy beliefs and the sense of agency and going through motivational and behavioral processes to effectuate the in-place beliefs. However, self-regulation is comprised of a convoluted system of social, motivational and behavioral processes that is inaugurated by individual referenced to self-factor (ibid). He persuades and prevails on researchers to traverse metacognitive knowledge and skill to consider more the motivational and behavioral processes underlying self-efficacy and personal agency for effectuating these self beliefs.

Reaserch  in domain of strategy instruction denotes that strategy awareness is good predictor of learners‘ use of strategies but motivatioenal belief of lerners is good indicator of putting these strategies into use. Motivational studies of self-regulation are escalating as motivational beliefs play a significant part in deployment of metacognitive strategies (Wolters C, A. & Pintrich P, R. 1998;Young, 2005).

Studies on motivation and strategies demonstrate a close link between motivational beliefs and use of strategies. Existing research has documented positive relations between students’ academic self-efficacy and their use of self-regulation strategies (Schunk, 2005). In an early schooling study, Pintrich and De Groot (1990) found that middle school students’ self-efficacy beliefs were positively related to their cognitive engagement and academic performance. The findings documented that school children who believed they were capable of learning were more likely to report use of SRL strategies and to persist longer at difficult academic tasks.

Paulsen and Gentry (1995) examined the relationships among motivational variables (intrinsic and extrinsic goal orientation, task value, control of learning, test anxiety, and self-efficacy), cognitive learning-strategy subcategories (rehearsal, elaboration, and organization), self-regulation subscales (time, study, and effort), and students’ academic performance (final grade) in an Introduction to Financial Management course. They found that all motivational variables were significantly related to the academic performance, final grade in the course, where path analysis revealed the self-efficacy as the strongest predictor of performance.

Motivational beliefs act as cantilevers which strengthen the suspensions of attitudes to sustain effort and persistence for finalizing the goal. Self-regulated learner is tantamount to a self-efficacious learner who persists in his beliefs despite worries and has the adequate will to strive to attain his goals. Self-regulated learner is tantamount to a self-efficacious learner who persists in his beliefs despite worries and has the adequate will to strive to attain his goals. Research denotes that effective self-regulation is pivoted on students’ sense of self-efficacy for self-regulating their learning and taking on actions (Schunk, 1995).

 

 

 

  1. ENVIRONMNETAL FACETS OF SELF-REGULATED LEARNING

 

SRL is conceptualized as a dynamic process enhanced by some contextual features (Boekaerts and Corno, 2005). Social cognitive theory sets great store by interrelated interaction of the environment, the person, and his or her behavior (Bandura, 1986). Social cognitive theorists postulate that student’ social experiences in learning environment, particularly their interactions with teachers, can affect self-regulated learning (Zimmerman, 1989).  An allover calibration of the factors influencing learning overshadowed by social cognitive theory has helped researchers and educators to scrutinize self-regulated learning much scrupulously.

Myriad studies of strategy instruction have shown that cognitive practices along side with non-cognitive support result in higher attainments. Pintrich and De Groot (1990) believe that the importance of classroom contextual factors for instigating key enablers of learning, viz. ‘will’ and ‘skill’ represented as older cognitive models of learning, to succeed is irrefutable.

Zimmerman (1997) recognizes environmental determinants as physical and social attributions. Social experiences in learning are like autonomy support, feedback to self-evaluate, leaner-centered. Influence and contribution of learning and teaching context and domains can be examined at three levels of macro (school) micro (classroom) and personal (individual level) and this study only considers the social aspects of learning and teaching at micro levels. Physical attributions are facilities, equipments, arrangement of classroom and et cetera.

There are multitudes of studies that vindicate the irrefutable effect of the contextual factors on developing self-regulatory capacity of learners (Cleary and Zimmerman, 2004; Lin, 2004; Perry, 1998; Sungur and Gungoren, 2009; Wolters and Pintrich 1998; Yen, 2005; Young, 2005). In a correlational study conducted by Yen (2004) the strength of association between student-teacher interactions and self-regulated learning(r =.36, p <.01) was found to be large which endorsed once again the constructive role of teachers in creating a setting conducive to fostering and spurring student’s self-regulated learning. Young ( 2005) in a study aiming to fathom motivational effect of the classroom environment in facilitating self-regulated learning  found that delivery with high interaction, encouraging feedback, and clear goals that emphasize learning over grades will augment intrinsic motivation and the use of self-regulated learning strategies. Leutwyler and Merki (2009) conducted a longitudinal study in an ecologically valid setting of 20 public and two private high schools in Switzerland (Gymnasium, ISCED 3A) without specific training programs.  The results showed the significant effects of schooling and instructional processes on students’ progress in self-regulated learning though differing in degree of stability contingent upon different features of the school and instructional process. The development of many aspects of cognitive and metacognitive self-regulation was impacted by school process variables, to a greater degree, than students’ extra-curricular experience. The findings implied the effect of various social and didactical factors on the promotion of self-regulation of cognitive, metacognition and motivation. Cognitive and metacognitive self-regulation variances explained by these variables ranged between 1.8 % for transformation strategies and 5.3 % for monitoring strategies and evaluation strategies. Perceived social inclusion played an important role in the positive development of practically all dimensions of motivational self-regulation (βmin = .131; p < .05). With regard to the didactic aspects of classroom instruction, requiring students to elaborate frequently promoted the development of intrinsic motivation (β = .089; p < .05) while teachers’ use of a process orientation showed no effect at all and high self-reliance of learners had a demonstrable effect on only one single case. The degree of transferring orientation in teaching (measured using the scale “elaboration”) illustrated the positive relations with the development of cognitive and metacognitive self-regulation. Only one association between motivational self-regulation and teachers’ use of transfer orientation was demonstrable in isolated cases only. Gender had impacts only on some aspects of cognitive and metacognitive self-regulation, explaining between 12.8 % and 25.3 % of the variance for monitoring strategies and transformation strategies and explained much of the variances in motivational self-regulation both of which accounted for students’ starting conditions.

Critical role of specific contextual and situational variables on students’ motivation and self-regulation has been attested in recent studies. (Lin, Xi-zhe 2004; Linnenbrink & Pintrich, 2002; Young, 2005; Zimmerman, 1989). Classroom environment contributing to students’ motivation and autonomy to have opportunity and take responsibility for personal experience is recommended by Paris and Paris (2001).

Many aspects of learning environment like autonomy support in the form of providing choices and opportunity, teaching programs, teaching approaches, student-teacher interaction, and motivational beliefs have been found to contribute to fostering and development of this skill (Ames, 1992; Lin, 2004).

The optimal conditions for developing self-regulation occur when children and young people have an opportunity to pursue goals that they themselves find meaningful; they will also be invited to develop their skills by selecting their own activities, taking initiative, engaging in challenging and co-operational learning experiences and making their own decisions (Boekaerts and Corno, 2005). Self-regulation, as an indivisible compartment of such professional development, is emphasized by social constructivist theory. This means that knowledge is constructed through social interaction and is a shared experience rather than an individual one (Vygotsky, 1978). Teachers need to be involved in sharing and reflecting on their practices with their colleagues. Teachers leading a solitary practice may not be aware of the need to make changes in their instructional perspectives. Teachers’ collaboration with one another has been widely studied as a remedy to the isolation that many teachers experience. Butler, et al., (2004) propound that cooperation creates a professional learning community that holds members accountable while sustaining momentum during “inevitable challenges”.

Classroom environment contributing to students’ motivation and autonomy to have opportunity and take responsibility for personal experience is recommended by Paris and Paris (2001). So as for learners’ self-regulated learning a supporting and empowering environment is likewise required to be designed and implemented by teachers and educators to motivate learners to deploy self-regulatory strategies.

Harrison and Prain (2009) conducted a case study on 11 year 8 students’ self-regulation of learning beliefs and practices in two English task completion and engagement within an 11 month schooling program influenced by the learning and teaching processes, contextual, organizational factors in an Australian regional secondary school context with a low socio-economic origin. Students were questioned on affective and cognitive strategy uses after completing tasks by the authors and teachers after two or three weeks. students reported use of self-regulatory strategies by honing independent  learning through constructing an environment that cater for their differences in interest and also by harnessing structure of the class  and learning and teaching process.

 

The research comprised part of a tri-schooling study project to obtain self-regulatory capacities of students on lessons, within and in pursuit of task completion activities, by classroom observations and interviewing learners and teachers. Their perceptions and strategies were noted these were coded as the springboard for the further analysis on the self-regulatory development patterns. Engagement was operationalized in respect of cognitive, emotional and behavioral processes.  Within task completion, interview yielded that learners reported affective responses to the tasks and use of strategies.

Among 11 participants, nine showed sundry self-regulatory tactics, alacrity to take responsibility for executing the tasks, seeking help from teachers and classmates and  peer learning and happiness on achieving set goals and also managements of their own times. One of the participants, Albert, having gone through inquiry into his failure on task completion revealed that he had difficulty in implementing the strategies he had shown at other skills than school work at which he was good.

Experiencing transformed organization of the class in a new learning community and teacher’s expectation of students to work independently in inquiry time had significant impact on student’s perceptions and subsequently on their self-regulatory practices. The new learning community brought with it the convolution of each specific environment which had an enabling effect on students’ developments. Support of teachers showed significantly the improvement of self-regulatory strategies. Unscheduled syllabuses in the new learning community dissipated the monotony of the activities while provoking some uncertainty and anxiety over what will come next but axiomatically offering more challenge and responsibility and providing more opportunity in the new environment.

Results had some implications for future reinforcement of self-regulatory capacity of schoolchildren students through caring for students’ differences, providing non-rigid and positive non-competing learning environment, more accurate learning evaluative system, and support for teachers to meet student’s need collaboratively.

 

 

 

  1. 8. IMPORTANCE OF SELF-REGULATED LEARNING IN ACADEMIC ENDEAVORS

 

Self-regulated learning has been introduced in education taking its roots from educational psychology. SRL has grabbed attention of many people from different fields from psychology to mathematics, health, sport, medical, technology, policy making, marketing and language education. It is in line with constructivist epistemology and in parallel with the learner-centered education and gradual schism from teacher-directed learning through providing learners with opportunity and laissez-faire to have control over their learning skills and participating them in decision-making

Educational psychology research has dealt extensively with self-regulation and its significance as a mediating variable for academic performance, success and social competence (Zimmerman, 1990; Magno, 2010). Self-regulated learning is a composite concept encapsulating apart from cognition and metacogniton also motivation and affection in its construct.

 

Effect of self-regulatory strategies on academic success has been well-established galore in many studies (Kitsantas, Steen, and Huie, 2009; Lindner and Harris 1992; Pintrich, 1999; Pintrich and De Groot, 1990; Zimmerman, 1990). In the realm of academic self-regulated learning cross-sectional and longitudinal studies in naturalistic and non naturalistic contexts prevail that do address the development and enhancement of self-regulated learning. Self-regulation is believed to be the best predictor of academic performance on all the outcome measures, suggesting that the use of self-regulatory strategies, such as comprehension monitoring, goal setting, planning, and effort management and persistence is essential for academic performance on different types of actual classroom tasks (Boekaerts and Corno, 2005; Zimmerman and Pons, 1986, 1988).

Previous studies dealt exclusively with pure cognitive models of SRL but by expansion of theories and models research is currently encapsulated other dimensions of self-regulated learning which interplay in self-regulated learning process. Duckworth et al. (2009) state that self-regulation is not concerned with ‘thinking skills’; it also questions the role of emotion, motivational beliefs, self-concept and contextual factors in learning. The word self is more appreciated when it is reflected as a whole enacting and formulating in connection with world. Individual as a whole entity integrated in setting, yields more precise speculations about his thought, motivation and behaviors.

Studies depict that the acquisition of self-regulation skills is not an all or nothing phenomenon learnt overnight. This is not a skill acquired instantaneously and automatically and like other learning needs to be nurtured and practiced by schooling. It is a skill that beings from early schooling and continues to flourish cognitively by age and diminish motivationally at the same time, invigorated and empowered by co- and other-regulation. Hong and O’Neil (2001) revert back to multitudes of studies which evince that it is a trait which is not stable and is subject to fluctuation and oscillation.

While many educators consider self-regulation as a set of skills, some consider it as the deployment of all individual resources to invigorate learning process. Paris and Paris (2001) extended a developmental metaphor of self regulation based on socio-cultural model of learning in which students develop competencies and become more self-regulated. In this model of learning Piagetian tenet is also applied in which behaviors are molded and organized through participation of learners in zone of proximal development and self-regulation is an adaptive representation of this organization demonstrated in a situation than a set of skills to be learnt (ibid.).

Self-regulation is also studied as the state or the trait attributes in relation to the psychological characteristics. With self-regulation as a protean system, trait-related measures are also important in self-regulated learning to be studied in connection with academic performance. Hong and O’Neil (2001) concur that differences of trait and state constructs for self-regulation in individual learners are also in need of consideration both for learning and performance and for offering training programs by instructors. Winne and Perry (2000) maintain that self-regulated learning measure tools can be categorized as an aptitude gauge and an activity (event) gauge. Measurements of aptitude examine stable qualities and properties of students that represent predictable behaviors in the future that come in the form of self-reporting questionnaires, structured interview and teacher judgment or as event gauge which describes state and processes of individuals while they are self-regulating.

The research on self-regulation has not been limited to the traditional settings and are implemented to nontraditional settings like distance education and online learning where personal and self-factors more than social and contextual factors play a definitive role in  prompting academic achievement (Azevedo and Seibert 2004; Susimesta, 2006).

 

In addition, many studies on self-regulated learning have been done in the domain of foreign language learning. English learning skills also have been subject of inquiry in terms of exploitation of self-regulated learning strategies. Usefulness of self-regulation as a strategy for productive learning in second language learning and acquisition discipline is being endorsed by several studies (Harrison and Prain, 2009). Tseng, Dörnyei, and Schmitt (2006) evinced the transferability of self-regulation construct from educational psychology into the field of second language acquisition by examining self-regulatory capacity for vocabulary learning strategies of Taiwanese university and high school students.

However it should be noted that, very few studies exist that systematically delve into how far elements of self-regulation differ by gender (Zimmerman and Martinez-Pons, 1990), or by characteristics of the family such as socio-economic background. Leutwyler and Merki (2009) found that that gender played no role in the deployment of self-efficacy and persistence. Gender was stabilized to explain no variances in cognitive and metacognitive self-regulation (ibid).

 

 

  1. CONCLUSION

 

Taking into account the relevant theories, research, reviews, and meta-analytical studies of the self-regulation literature, it is generally agreed that the findings about the organization of self-regulation and its strong relationship with performance and success are highly reliable (Pintrich and Schunk, 1996). The literature elucidated the value of self-regulated learning and constructive role of learning and teaching environment in its burgeoning and fostering.

With self-regulation skill training programs being incorporated as separate courses in most disciplines in addition to content knowledge teaching programs in today’s education, magnitude of this skill in enabling effective learning is being conveyed. Helping students to reach the point that they have the capacity to regulate their own learning is advised to equip learners to advance their learning. By the same token, other- regulation and co-regulation is a way of propelling learners into self-regulation.

However, trickling learners into academic self-regulation and dispensing gradually with other regulation and co-regulation with teachers and peers seeks a supporting learning environment. Transition from other regulation by teachers and co-regulation by peers to self regulation seeks a fostering learning environment which provides skill and will for self-regulated learning. Paris & Paris (2001) assert that helping students to become self-regulated not only promotes more sui juris, competent, and determined learners, but is also likely to elevate test scores. A supporting and empowering environment is required to be designed and implemented by teachers and educators to motivate learners to deploy self-regulatory strategies. However, despite this strong advocacy of the value of this capacity, teachers still struggle and hesitate to provide learning experiences that support this learning capacity in students (Prain, 2008).

As literature enlightened how cognition, motivation, affect and context are closely intertwined in promoting self-regulation, attending to all these elements in conjunction with teaching of strategies and skills elevates higher achievement and wellbeing of learners. The review made it clear how the enrichment of self-regulatory capacities in the forms of perceptions and beliefs assists learners to attain success. It commands attentions of learners and teachers at collegiate levels and beyond and even more importantly those serving at basic levels of education and primary school to heed more attention to this skill since the development of this capacity appeared to be incremental developing faster and faster after the initial stages of schooling.

The aforesaid studies accentuating the interplay between self-regulation phenomenon and success encourage learners to mull once again over self-regulatory strategies and put this fruitful skill into use.  The concrete data also remind practitioners and educators to rehash and review their content delivery methods, interaction with students, apprehension of self-regulatory behavior of college language learners and thorough insight into learners’ perceptions of motivational beliefs. The evidence provided prevails on educators and curriculum developers to cogitate more on modifying and revising learning and teaching environment. With contextual factors, directly and indirectly, affecting development of this skill more practice en route to enhancing self-regulated learning, which eventually, result in deep learning is suggested.

The literature likewise spur curriculum developers and syllabus designers to revise their materials for incorporating more problem solving tasks and group working activities, intervention programs, strategy training courses for bolstering self-regulated learning which has been shown to be the cornerstone of constructivist learning.

 

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THE EFFECTS OF ACTIVITY -BASED INSTRUCTIONAL APPROACH ON THE ACADEMIC PERFORMANCE OF STUDENT IN INTERGRATED SCINCE EDUCATION IN KATSINA STATE COLLEGE OF EDUCATION NIGERIA

MUHAMMED ABDUL BUGAJE1 AND HAMZA ABUBAKAR2

Abstract

The study investigate the effects of activity based introduction approach on the academic performance of student integrated sciences which focuses on the level of success in using this method and its affectivity in teaching and learning integrated sciences education .the study is attempt to land out the significant differences between activity based instructional strategy and conventional method of teaching (lecture method).   The   research is a pilot study restricted to the department of Integrated Science Education in Katsina  State College of education Nigeria.  The sample comprise thirty (30) students of NCE II randomly selected.  The groups were place into two categories, experimental and control groups.  The experimental and Control groups. The experimental groups were taught using Activity-based approach and the control groups were taught using conventional methods. Quisi-experimetal design is used using pre-test posttest control group deign.  The data collected were analyzed using t-test statistic at P0.05 level of significant.  The instrument used for data collection is integrated science process skills (ISPS) test.  The results obtained shows that there is significant differences between the two approaches which entails the use of Activity-base is effective and efficient methods of teaching and learning science on general.  Recommendations were made for the effective use of Activity-based approach in teaching and learning integrated science education.

Introduction

Pedagogy is the instructional methods methods for strategy teachers adopt to facilitate instructional delivery for the achievement for the achievement of stated curriculum objectives.  Instructional delivery for the achievement of stated curriculum objectives.  Instructional strategy is the major factor in delivery effectiveness for it determines the success of the lesson.  The instructional method that the teachers adopt in teaching a lesson is a vital because this can make students like or dislike the subjects.  Teachers need to adopt teaching methods that will influence students’ interest, enthusiasm and understanding positively in the subject leading to acquisition of the pre-requisite knowledge, skills, value and scientific attitudes.

However the methods a teacher employ depends on the number of factors ranging from the nature of subjects, age, the students, specific objectives, teacher and environmental variable as stated by Etuibon (2014).  There are varieties of instructional methods from which a teacher may select the effectiveness for instructional delivery.   This range from demonstration, conventional, discussion, field trip to more innovative methods like co-operative learning, concept mapping which actively involves students in learning, Ajewole (2010).

The best method of teaching integrated science education is that methods that engage students participation in activities. Active participation in learning concept in integrated science will provide students with their own personal experience that will facilitate learning which many never be forgotten. The activity base approaches enriches the teaching learning process by ensuring the students actively participate in the lesson rather than just being passive listeners in the classroom Eboka, (2014)

Mastropiere & Scruggs (1995) lamented that many students benefit from learning science through activity base approach that reduces the relevance on textbooks, lectures, knowledge of vocabulary and prevail paper test this kind of approach seek to promote that allow them to discover and experiment with science through discovery and inquiring teachers involve students in creating and expanding their knowledge and understanding about content area being studied.

The philosophy of integrated science emphasize and stresses the effectives use of activity base strategy as a tentative method of teaching integrated science in the Nigeria colleges of education as stated by national commission for colleges of education (NCCE) accompanied by science teacher’s association of Nigeria (STAN). The minimum standard for science 2012 edition NCE curriculum outline the philosophy and objective of integrated science.

          The philosophy of the Nigeria certification education (NCE) integrated science is anchored on the following areas:

  • Fundamental unit of science
  • The use of scientific methods as a common approach in problem solving
  • The role and function of science in every day life
  • To prepare students for further students is integrated science.

Objectives NCE (2015) minimum standard

  • Enabling the students gain concept of the fundamental unity of science
  • Installing the student with community of approach to problems of a scientific method.
  • Increasing students understanding of the role and definition of science in every day life and in the world in which they live.
  • Making students well informed and scientifically literate.
  • Enabling student acquire and demonstrate the intellectual commence and professional skills to the teaching of integrated science.
  • Developing students ability to impart and encourage in their pupils the spirit of inquring into living and non living things in the environments.
  • Developing the ability and motivation is students to work and think in an independent way/ manner
  • Enabling students to carry out scientific investigation emphasizing co operation development of appropriate scientific process and skills and improves their written and oral communication skills
  • To develop in students the interest to pursue higher studies in integrated science.

Integrated science is the unity of all knowledge the conceptual unity of the sciences, a unified process of scientific inquiry and an interdisciplinary study as defined by Brow, (1977). The development of process skills and basics skills is an emphasized objective of Nigerian integrated science projects capable for teachers to make use if activity base approach to assist the students to observe carefully and thoroughly, report completely and accurately what is observe. Organize information acquired generalize on the basic of acquired information predict as a result of generally design experiment to check production use models to explain phenomena and continue the process of inquiring when new data do not conform to prediction these can absolutely be acclaimed through the effective use of activity base approaches in teaching learning integrated science.

                    Foecke, (2004) in an article on the education

 of teachers of integrated science observe that how can

we expect teachers who have science only in

                   specialized packages and by methods which

may have stressed lecture and memorization and

avoided direct involvement from this background

                   and teach science in an integrated and

inquiry – oriented manner?.

Pine G. (1989), Define Activity:- based method as a technique adopted by a teachers to emphasize his or her method of teaching through activity in which the students participate rigorously and bring about efficient learning experiences. It’s a child centered approach. It is method in which the child is actively involved in participating mentally and physically learning by doing is the main focus in this method. Learning by doing is imperative in imperative in successful learning. Since its well proved that more the senses are stimulated more a person learns and longer he/she retains

          The corporation of schools of Chennai (2003) which was developed and originated by the pioneer of the method David Horsburgh out line the affectivity of the activity based strategy and lamented that.

Activity:- based approach required actives problem solving by students in finding patterns in the information through their own investigation and Analysis. With continued practice in these processes, students learn not the content of the lesson but also develop many other skills.

Horsburgh D. (2003) out line the importance of activity based method or the main purposes of carrying out activity based approach in the teaching and learning science in generate are:

  • It exchange creative aspect of experience.
  • It give reality for learning.
  • Use all available resources
  • Provide varied experiences to the students to facilitate the acquisition of knowledge, experience, skills and values
  • Builds the students self confidence and develop understanding through works in his/her group.
  • Experiences develop interest, enriches vocabulary and provide stumulus for reading.
  • Develop happy relation ship between students, teachers and students.
  • An activity is said to be language of the child a child who lacks in verbal expression can make up through use of ideas in the activity.
  • Subject of all kind can be taught through activity
  • Social relation provides opportunity to mix with others.

Objective of the study:

  1. To determine the effectiveness of the significant difference between activity-based approach and conventional method (lecture method) of teaching and learning integrated science.
  2. To determine the skills acquired between activity-based approach and conventional method of teaching and learning integrated sconce.
  3. To investigate the role played by the teachers in using activity based approach in instruction of integrated science in the classroom.

Research questions:

  1. What are the effects of using activity based method and conventional method of teaching.
  2. What is the effect of gender when exposed to activity based approach in teaching and learning integrated science.
  3. What is the role of a teacher in organizing effective use of activity base approach in teaching and learning integrated science.

Research Hypothesis

H01. There is no significant difference between activity based approach and conventional (lecture) method of teaching and learning integrated science.

H02. There is no significant difference between the skill obtained in activity based approach and conventional lecture method in teaching and learning integrated science education.

Operational Definition  

  • Nigerian integrated science project ( NISP): Capable of desiring and produced science teaching and learning materials in order to make learning effective and efficient.
  • Nigeria integrated science teacher education project (NISTEP): capable of producing high efficient science teachers through designing the modern approach of pedogoyical teaching and learning through optimum supporting system.
  • Basic science process skills (BSPS) and integrated science process skills (ISPS): Science process approach (SAPA) group science process skills under two headings. The first is called the basic science process skill (BSPS) such as observation measuring and using number and classifying (BSPS) provide the intellectual group work in scientific inquiring walters & soyibo, (2001). These skills are those which must be acquired in the first level of primary and secondary education and letter is called integrated science process skills (ISPS), Such as controlling variable, formulating hypothesis and experimenting. These skills are structured.

Research Methodology:

          In the study pretest and posttest experimental control group design was used. The main study sample comprised 30 students in a total of them of them constituted the control group. When creating the experimental and control group, it was aimed not to cause any district differences between the groups to ensure this SPST had been done before the study and them choices were made randomly in the classes that had similar performances to one another. The study was conducted the one of Katsina State College of education Nigeria. The study was conducted during the two semesters.

          The science process skills test (SPST) was used to measure the integrated science skills the test developed by Nigerian integrated science project (NISP) and Nigerian integrated science teacher education project (NISTER) in collaboration with Nigerian national commission for colleges of education (2002).

          With its 33 items. The ISPST which has 11 eleven dimension 5 items related to formulating hypothesis 6 items related to identifying variable 6 items related to define operationally 6 items related to interpretation of data 3 items related to formulating models and 7 items related to experimenting.

          Pre-test post-test control group design, which is one of the methods of the experimental design is applied all participants attendant the four hours lectures per week in a science course. While the students in the control group were being taught the conventional method (lecture method). The one in the experimental group were supplied some hands activities prepared by the researcher to improve their science process skills. Through out the studies to topics to be studies is in the conformity in the green book of th

 students did 150 hands on activities for a complete semester in order to improve their science process skills they worked in group of atleast 3 and maximum of 5 students. The groups were nitrogenous with respect to their science achievement. The students in the experimental group were trained about activity based teaching method and hands on activities.

          During the student the student were asked some  open-ended questions to attract their orientation to the topic and activities and they were asked to answer them working co – operatively. At that stage, the students were obtain supported by researchers the group were demanded their funding and results attains in writing or verball of when ever they finished working together they write some group report and different students in the work groups provided oral explanations to the rest of the students about each one of those reports the finished were discussed all together to have some specific results to consolidate things.

          All NCE II students the number of the hands on activities the content knowledge relate to the science process skill and instructional time were held constant. Dependent variables of the study were the students achievement scores of ISPST. Independent variables of the study were the different types of instruction employed. When students pretest ISPST for experimental and control group score and post test for experiment and control groups core were used to test the research question and to determine the treatment effects on students. The data collected was analyzed using analysis of variance and it test statues of P< 0.05

Result Analysis   

The raw scores of students of Experimental and Control Groups were arranged and then analyzed  by suing means score, standard deviation and t-test statistical tools.  The analysed data have been interpreted in the following ways:

The tabulated value for 58 degree of freedom at 0.05 level of significance, since  the calculated t (7.90)is less greater than  the critical value (1.684), Ho may be retained. We may conclude that there is significant difference between activity based instruction and conventional methods of teaching. It is indeed, the basic skills were acquired during the experimental studies.  Hence activity based instruction is effective and efficient in teaching and learning science all level of education

Recommendation:

          Learning by students through activity-based teaching strategies on experience you get is at great importance because the education sector, with many goals and the advantages and benefits. The recommendations are as follows:

  • The teachers should increase the students attention and willingness to respond to the educational settings.
  • Guide the development trend of students and their needs and develop their talents and the direction of education is correct.
  • The teachers should employ and emphasize on improvisation which capacitated the acquisition of basic and process skills.
  • Teachers should provide opportunities for students to self-study, where the benefit of the teaching learning situation in their future.
  • Adequate supply of learning and teaching materials should be provided so as to enhance learning and teaching effectively.
  • Adequate funding should be provided by the government.
  • Non-governmental organization should assist the situation through provision of materials and other learning materials.
  • Encourage for work in group for co-operative learning process.
  • Encourage the students to take responsibility of their own learning.
  • Students role towards the development of activity based learning strategies are.

Their personal interest

  • Participate in educational objectives
  • Developing god organizational skills
  • Involve in the programme flow
  • Demonstrate enthusiasm in seeking new knowledge
  • In collaboration with others

The teachers role in the development and use of activity based teaching strategies are:

  • Planning and preparation for
  • Identify outcome
  • Having noted the outcomes of learning using proper strategies
  • Mechanisms within the group
  • Promote co-operation in carry out activities

Conclusion

Activity based teaching strategies describes a range of pedagogical approach to learning teaching its core premises include the requirement that learning should be based on doing some hand experiments.     The idea of activity based approach is rooted in the common notion that children are active learners rather than passive recipients of information. If child is provided the opportunity to explore by their own and provide an optimum learning environment then the learning become joyful and long lasting.

Reference

http//www.best teaching. Com/060510-activity based teaching strategies

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Report by Dr. Anandalakshmi ptf), SSA PP 1-8

Dalhatu H. (2011), a survey of pedagogical content knowledge (PCK) on

NCE students in teaching of experimental skills in physics

Remziye et al, (2011). The effect of enquiry based science teaching onn\

elementary schools students science process skills and science attitudes.

Bulgerian journal of science and education policy (BJSE), Volumes Number

         National Commission for colleges of education curriculum minimum

         stardard revised edition (2012) Green book.

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Book 1 E- Watch print media Ibadan, Zaria.

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Challenges and Delivery in the Higher Institution: A Survey of University Autonomy in Nigeria.

Olakunle Folami

Abstract

Public universities are owned either by the federal or state governments. Corruption, strike, funds and economic doldrums limit the research and teaching capacity of universities in Nigeria. These affect the contribution of university system to the development of the nation. McClelland’s Learned Needs Theory was employed in this paper to explain the desire of the universities to accomplish successfully research and teaching delivery in a competitive environment. Quantitative method of data collection was used in this paper to collect data from the respondents. Questionnaires were administered among one hundred and thirty six respondents from six states and federal universities across the nation. The paper found that both state and federal universities could not meet their financial obligations. Paucity of funds has led to incessant strike, student unrest and brain drain. It was also found that scarcity of funds has affected research and development in the universities. The paper therefore, recommended autonomy and external source of funding for the universities. Internationalisation of the universities research, and public/private partnership were also recommended.

 Keywords: Autonomy, Funding, University, Research.

Introduction

Education, most especially the university education is central to the national development and its importance to individual growth and wellbeing cannot be overemphasised. There is a link reaction between individual development and education. According to Aluko (1996) university is a place where human potentials are developed and refined for the utilisation of national development. Universities provide manpower needed by the nation. The quality of manpower available to a country is largely determined by the standard of its education (Jega, 1994). Funding is a major instrument which determines how well a university achieve its objectives. No matter how lofty the objectives of a university are, inadequate funding is capable of hampering its realisation. Adequate funding promotes research and development, qualitative teaching, good learning environment, and ability of the university to contribute to national development adequately. Education generally in Nigeria receives low attention from government. Olorode (2005) claims that unstable university calendar, strikes, brain-drain, lack of autonomy and low morale among the lecturers contribute to the quality of universities outputs in terms students and research.

In recent times, university system has been overwhelmed with strike, brain-drain, student unrest and closure due to lack of adequate funding. The ability to generate fund privately is hampered by the status that created the university system in Nigeria. Section 106 of the nation’s education policy recognizes that the financing of education is a joint responsibility of the Federal, State and Local government (Onyekwu, 2011).  But in practice the funding is left solely to the owners. It has become difficult for university to secure funds from private organization to support research. Scholarships, grants and bursaries for students and researchers are difficult to come by. Olorode (2005) says that the culture is not simply there among the business organisations to support research and scholarship in Nigeria. The Tertiary Education Fund and Petroleum Technology Development Fund are created by Acts of Government  as compulsory contributions from the business organisations to finance education in Nigeria through a fixed percentage tax deduction from the source (cdnetng.org. n.d).

The proposition the paper seeks to explain is that; first, inadequate funding could result to brain-drain in the universities; and second, there is a relationship between university funding, research and teaching in the universities. The study therefore, sets to examine the extent of funding available to the public universities in Nigeria. It seeks to know the sources of funding available to Nigerian universities. It also examines alternative means available to universities in Nigeria to generate more fund. The study like others in the field of sociology of education and management attempts to link paucity of funds to challenges such as brain-drain, strike, ineffective research and absent of season lecturers in the Nigerian universities.  This article is divided into the following sections; one, needs theory and challenges facing universities; two, strike, brain-drain and university system; three, private sector and funding of university; four, method; and five, results and conclusions.

Needs Theory and Challenges

McClelland’s Learned Needs Theory is used in this study to explain the desire of universities in Nigeria to accomplish moderately performance goals, be successful in competitive situation, assume personal responsibility for fund sourcing and internationalisation of programmes. Three motivational needs were identified by McClelland (1969) including achievement motivation (n-ach); authority/power motivation (n-pow); and affiliation motivation (n-affil). First, the n-ach person is ‘achievement motivated’ and therefore seeks achievement, attainment of realistic but challenging goals, and advancement in the job. There is a strong need for feedback as to achievement and progress, and a need for a sense of accomplishment. Second, the n-pow person is ‘authority motivated’. This driver produces a need to be influential, effective and to make an impact. There is a strong need to lead and for their ideas to prevail. There is also motivation and need towards increasing personal status and prestige. Third, the n-affil person is ‘affiliation motivated’, and has a need for friendly relationships and is motivated towards interaction with other people. The affiliation driver produces motivation and need to be liked and held in popular regard. These people are team players (Businessballs, 2015).

The need for autonomy by the universities to meet the current challenges explains why power with limited moderation over activities by external agencies like state or federal government is desirable. The desire by the universities to conduct their businesses with interferences requires a high ‘socialized power’ in which they seek power for autonomous purpose (Rue and Holland 1986). According to Smelser (1962) universities with a strong affiliation need to form positive relationships with outside world. Donnel and Gibson (1987) says that universities with a high need for achievement make better entrepreneurs because they are able to work autonomously towards the challenging goal of establishing a new source of funding (Sergiovamni and Carver, 2003).

In the modern era, university should encourage partnership with private sector of the economy through research and development. This will provide a strong economic base and a better source of finance for the university (ICAN study kit, 1998). The research output of a university could be sold to a private sector or government agencies (Croft 2004). University must be ready to seek grants and endowed research chair for professors who can attract funds (Olorode, 2005).  These could go a long way to finance its budget if not for lack of autonomy that hampered such ingenuity in Nigeria (Olorode, 2005).

In Nigeria, the annual budgetary allocation to education has dropped from 19.6% in 1993 to 12.4% in 2010. In 1996, OECO countries accounted for 85% of the total R&D investment; China, India, Brazil and East Asia represented 11% and the rest of the world (inclusive of Nigeria that is) only 4% … Nigeria has only 15 scientists and engineers per million persons. This compares with 158 in India and 4,103 in the United States (World Bank, 2002).  Nigeria’s number of scientific publication for 2005 was 711 significantly less than its 1991 output which was 1,062 (Task Force 2010). The country’s low research output probably reflects the low priority accorded to research and development by government. Nigeria’s federal university system spends only 1.3% of its budget on Research (Harnett, 2000).

The introduction of a special agency “Education Trust Fund” to generate funds to finance education in Nigeria has not recorded desired results. Obikwe (2006) said that the funding of Nigeria universities is at all time low, despite the purported efforts of successive government, no much can be shown for the efforts. Onweh (1997) states that there is an urgent need for stakeholders in the country’s education sector to align their different objectives to rescue university system from total collapse. On education, Nigeria spends an estimated 2.4% of its GNP while sub-Saharan Africa as a whole spends 5.1%…. school drop out have continually risen and also, the education standards have reportedly declined. Between 2000 and 2007, for example, the Government Allocation for higher education declined by 27%… even as enrollment grew by 79%. The result is a dramatic fall in the quality of University education and research as implied by the 62% drop in the real value of recurrent expenditure per student during this period (Saint, 2010).

 

Strike, Brain-drain and University System

 

University system continues to experience problems such as strike, closure, irregular academic calendar, brain-drain, low level of research and other problems as a result of small budgetary allocation to education by government in Nigeria. Research into the financial ability of universities has not been taken the central stage until it becomes clear that Federal and State government could not cope with the financing of the nation’s Universities as a result of global economic meltdown and a need to develop decades of infrastructures neglected by successive military governments in Nigeria.  According to Aluko (1996), low academic salaries coupled with more frequently university closure which linked to students’ unrest and government interferences on a number of campuses have prompted numerous university staff to forsake the academic calling. The World Bank notes that some 23,000 qualified academic staffers are emigrating from Africa each year in search of better working conditions. It is estimated that 10,000 Nigerians are now employed in the United States alone. More often, however, it is a neighboring country which beckons, South Africa attracts staff from Malawi, Zambia, and Nigeria, and the universities in Botswana and Swaziland attract Zimbabweans (Aluko, 1996).

The economic doldrums which the country currently witnessed have had serious effects on the university system in Nigeria. The budgetary allocation declines led to the rationalization or cancellation of a number of services rendered by the universities (Olorode, 2005). The services that were affected included support and sponsor of staff to conferences, both local or overseas; inadequate and epileptic supplies of stationary items and other academic materials such as books for the library, chemical for laboratories, drugs for health centers and clinics (Adelemo, 2001). Chalk, in some instances, could not be provided. Information and communication technologies (ICTs) are obviously more expensive and would seldom be among the priority items to preoccupy the attention of the various managements of the universities (Okebukola, 2002). The culmination of the shortage of fund and simultaneous expansion in students’ enrolment, universities had to contend with shortage of accommodation, classrooms, inadequately library books (Olajuwon, 2004). According Salmi (2004) lack of facilities led to lower morale among the staff and those who felt that they could not cope either left Nigeria universities for overseas universities or found a well-paid job in the other sector of the economy. Jega (1994) emphasizes at this juncture that the struggle embarked by the Academic Staff Union of Universities (ASSU) to save the universities in the eighties and the nineties were preceded by those of the students in the sixties and the seventies.

Academic standards have no double measure. Its measurement is international, Olorode (2005) says there is no hide out for Nigerian society than to improve its education standard if it will remain among fast growing economy and fulfill its 2015 Millennium Development Goals. It has become a duty for Academic Staff Union of Universities to fight for better pay and better conditions of service for academic in order to direct government attention to education and to retain the academic staff that are still remain within the system and attract new ones. It is worrisome to note that the perennial strikes embarked by the Academic Staff Union of University (ASUU) in Nigeria were as a result of inadequate funding for the universities from the government. Research and teaching become almost non-existing in the universities as a result of paucity of funds. Truscott (1946) described a university as a society of scholars, all of whom are learning, but the more senior scholars spend part of their time teaching the junior scholars, and they also increase their own knowledge by adding to the store of human knowledge. This they do through research.

Private Sector and Funding of University

 

Funding of education in Nigeria, most especially the university education should not be a sole responsibility of government. Challenges before government to provide social facilities make it problematic to fund education as expected.  The contribution of private sector to the education sector is very important. However, private organisations have not seen education as their primary responsibility.  Private organisations in Nigeria do not patronise home grown knowledge. Research out-puts remain in archive of knowledge begging for adoption by the government and private organizations. According to Flexner (2000) the conservation of knowledge and ideas is and has always been recognised as the business of universities, sometimes, perhaps, as almost their only business. Thus, a university must seek to increase the bounds of knowledge through research, must act as a repository or store of such knowledge through research, and must also disseminate it.

Scarcity of fund in the nation’s education sector calls for public/private partnership which is aimed at injecting private sector know-how into failing public schools. University can choose to contract out specific educational services to private companies in order to access more fund. Paucity of fund can be resolved by a strong based private-sector ideology, competition, experimentation, and incentive. For- profit companies to run school systems more efficiently and produce better outcomes by applying private sector logic. Good teachers would be attracted to teaching and retained-by performance based pay schemes, while under performing teachers could be removed more easily. Composition within and between schools would lead to higher levels of innovation, privatized schools would have more liberty to institutionalize the result of successful research (see Giddens, Duneier and Appelbam, 2005).

Method

This study was carried out in Nigeria. Nigeria is the largest black nation in the world. It has the population of about one hundred and forty million (140million) (see 2006 national population report). Nigeria is divided into six geo-political zones such as Northeast, Northwest, Northcentral, Southeast, Southwest and Southsouth.

Sampling method

Two universities each were selected from the three out of the six geographical zones of the country; Northwest, Southwest and Southeast. Each of these zones has at least a Federal and a State university. The total number of Universities in the country is one hundred and seventeen (2011 UMT Brochure University): Federal Universities twenty-five (36); State Universities twenty (36); and Private Universities twenty-five (45). The following universities were randomly selected: Northwest (University of Sokoto also known as Uthman Dan Fodiyo University and Nasarawa State University); Southwest (University of Ibadan and University of Ado Ekiti); and Southeast (University of Nigeria and Imo State University).

 

Selection of Participants

Participants in this study were drawn from Bursary Department, Registry Department and Academic Planning of the selected Universities. Letter of information was sent to each university administrative council to intimate the university administration about the purpose and objectives of the study. The approved letter with the consent form was given to head of each unit which was signed and passed on to the selected participants. Each participant was also allowed to fill the consent form before filling the questionnaire. The following participants were selected based on informed consent form early signed:

  1. Bursary Department

Deputy Registrar, Chief Accountant, Accountant 1& 11, and Account Technicians.

  1. Registry Department

            Principal Assistant Registrar, Assistant Registrars and Administration

             Officers.

  1. Academic Planning Unit

           Chief academic Planning Officer and Administration Officers.

No name was written on the questionnaires but serial numbers were provided for easy coding and analysis. The participants were given the opportunity to withdraw from filling out the questionnaires. Their responses were immediately destroyed upon withdrawal of intention halfway. The well filled out questionnaires were packed in a sealed envelope and transported to the researcher office for analysis. The Quantitative method of data collection was employed to gather data from one hundred and thirty six respondents out of the two hundred questionnaires that were administered. One hundred and thirty-six returned questionnaires which represented 68% of the total administered questionnaires is adequate for data analysis.

Structured questionnaires that consist of open-ended and close-ended questions were distributed. The followings distributions were obtained: University of Sokoto 27 (55.77%); Nasarawa University 21 (44.23%); University of Ibadan 28 (63.46%); University of Ado Ekiti 20 (36.54%); (University of Nigeria 26 (57.69%) and Imo State University 14 (42.31%). Pilot survey had earlier been carried out in three Universities in the three selected regions to test the reliability and validity of the research instruments. Permission of National University Commission was taken before embarking on the field work. It took the researcher one year and nine months to complete the study. Data collected were analyzed with the aid of simple percentage, cross-tabulation and chi-square. The summary and finding of the survey was sent to the selected university administration and library for documentation.

 

 

 

Results

 

The results obtained from the analysis of data were presented here. Tables of percentages and chi-square were presented as well. Interpretation and conclusion on each table and chi-square were also presented. The paper presents results on the following: years of experience; number of students; amount of subvention in naira; grant received from government and others agencies; grant received from local and international agencies; effects of paucity of fund on the public universities; sources of fund; funding and brain – drain; and funding and teaching.

None of the Universities selected was established less than 10 years ago. The oldest University in Nigeria, University of Ibadan was established sixty-three years ago, University of Nigeria was established fifty-six years ago and also, Uthman Dan Fodiyo University was created thirty-six years ago. These Universities are owned by the Federal Government of Nigeria. They have no autonomy in terms of administration and funding. The other selected three universities such as Nassarawa State University, Ekiti State University and Imo State were established ten, twenty-nine and thirty years ago respectively by the State Government. They also lack autonomy, in spite they were created by concurrent status.

Number of students in each of the universities in the three regions is as follow: Southeast has the highest figure 57,000, University of Nigeria 36,000 and Imo State University 21,000; follow by southwest 24,654, University of Ibadan 12,000 and Ekiti State University 12,654 and, Northwest 21,123, Uthman Dan Fodiyo University 12,007 and Nassarawa State University 10,116.

The above table provides the number of both academic and non-academic staff working in the selected universities. The University of Ibadan has the highest number of staff with 4,197, follow by The University of Nigeria with 3,271 staff and the Uthman Dan Fodiyo University 2,512. The State owned universities have the lowest number of staff: Imo State University 2,752; Ekiti State University 2,223; and, Nassarawa State University 2,512.

Legends:

UDU- Uthman Dan Fodiyo University

NSU- Nasarawa State University

UI-University of Ibadan

ESKU-Ekiti State University

UNN- University of Nigeria, Nnsuka

IMSU-Imo State University

The amounts of subventions such as grants, donations and others accrued to the selected universities are stated below. State owned universities are poorly funded. Their subscription is less than one billion naira ($7million) while the federal Government owned Universities collect a little above one billion naira ($7million for) for both capital and recurrent expenditures in a year.

It is clearly indicated from table one that funds available for Universities are not sufficient 75(55.15). Funds from the Federal and State government, internally generated revenue and funds from other donors are not adequate to run the universities. Also, both the Federal and State Universities demonstrate that funds are lowly sufficient 53 (38.97), sufficient 06 (4.41) and, averagely sufficient 02 (1.47).

Universities are poorly financed in Nigeria. From the above table 04 (2.9%) of the respondents said they received little grant from local and international agencies such as Education Trust Fund, National University Commission, UNESCO and other international donors while 18 (13.3%) of the respondents said that these grants were not sufficient. However, the largest percentages of the respondents 114 (83.8) said that grants are not available at all.

The effects of scarcity of funds on the public Universities are extremely enormous. Table II shows that the effects as follows: Research and Development 33 (24.27), strike 28 (20.59), Brain-drain 25 (18.38), Student Unrest 08 (5.88), teaching capacity 13 (9.56), Sponsorship 09 (6.62), external links 13 (9.56), and community development 07 (5.15).

The possible means by which Universities in Nigeria source for funds were examined in table III. Apart from running grants from governments, 43 (31.62%) of the respondents agreed that funds could be sourced by buying and selling of security, bonds and shares. Also, 29 (21.32%) of the respondents believe that funds could be sourced internally by selling of admission forms, increase in the number of in-takes, increase in school fees, deregulation of accommodation fees and commercialization of universities’ halls of residence. Public/private partnership is another way by which funds could be generated, 28 (20.59%) of the respondents supported this idea. About 19 (13.97%) and 17 (12.50%) of the respondents said that funds could be made available to the universities by the internationalization of university programmes and commercialization of research output respectively.

Funding and Brain – drain

                        Federal                        State                           Total

Yes                              68 (82.93)                    38 (70.37)                    106 (77.94)

No                               14 (17.07)                    16 (29.63)                    30  (22.06)

                                    82(100)                        54 (100)                       136 (100)

x2                                 = 2.36

d.f                                = 1

a                                  = .05

Critical value   = 3.84

The acceptance region for this test using a = .05 and d.f = 1. The critical value is 3.84. Since the critical chi-square value exceeds the observed value of x2, I accept the null hypothesis of independence of the classification and conclude that inadequate funding could lead to brain-drain in the Universities.

Funding and Teaching 

 

                                    Federal                        State                            Total

Yes                                          66 (80.49)                    40(74.07)                     106 (77.94)

No                                           10(12.20)                     08(14.82)                     18 (13.24)

I don’t know                 06 (07.31)                    06(11.11)                     12 (8.82)

 Total                          82 (100)                        54(100)                        136 (100)

x2                                 =          1.86

d.f                                =          2

a                                  =          .05

Critical value   =          5.99

In this text, the chi-square is accepted using a = .05 and d.f = 2. The critical value is 5.99. Since the critical value exceeds the observed value x2 =1.86, I accept the null hypothesis of dependence of the classification and conclude that there is a relationship between University funding and teaching capacity of academic staff.

Conclusion and Recommendation

This study was set to examine the funding of universities in Nigeria and other problems confronting the system. It was found in this paper that grants from the government to the universities either from the federal government or state government was crossly insufficient. The insufficiency of fund for universities has actually led to the inability of the universities to meet with the challenges of education in this globalization era. However, for a university to compete favourably with its counterparts all over the world it must be adequately funded. Education generally in Nigeria is not adequately founded. It was reported that budgetary allocation to education in Nigeria continuously dwindling in the last two decades (Duyilemi, 2007).

The effects of paucity of fund on the universities administration were also examined in this paper. Inadequate funding has bandwagon effects. Regrettably, research and development is grossly affected in the Nigerian universities. Universities lack fund to sponsor research. Private organizations have also failed to help in this direction. Lack of research fund has push some lecturers out of the Universities this actually led to brain-drain experienced in the nation’s ivory towers. Incessant strikes by the university staff – both the academic and non-academic, many of the strikes boiled down on the inability of the university management to meet the demands of its workers as a result of paucity of fund.

It was also concluded in this paper that inadequate funding has led to students’ unrest and the inability to secure capable teaching hands. This is supported by the chi-square test that stated that there is a strong correlation between funding and teaching capacity (see hypothesis 2). Sponsorship for teachers and students to attend conferences, workshops, seminars and training both locally and internationally were also hampering by insufficient funds. However, new development could only be leant by the university professors without attending conference, workshops, seminars and training. More so, external linkage/exchange programme would be difficult to establish because university needs enough fund to accomplish this task. Inadequate fund has affected the ability of universities to contribute meaningfully to the community development because funds available could not go round.

This paper examines way out of perennial shortage of fund in the universities. It is important for a university to source for fund; this could be done both locally and internationally. It was concluded that, practically, universities could raise fund internally from establishment of enterprises, increase in school fees payment, accommodation payment. Also, commercialization of research outputs could be used as a viable source of funding. Research outputs could be sold to private organizations, government and interested international buyers.Buying and selling of government security, shares and bonds could generate funds for universities. Though, this recommendation is not popular with public universities. The autonomy of universities could make this possible. Public/private partnership is a new global initiative that could brings development to moribund institutions in the country. Universities could enter into partnership with private individuals, business organizations and international consortium. Finally, this paper recommended internationalization of university’s degree. The more foreigners patronize a university, the more increases her income. Globalization of the world has made internationalization of education possible and practicable.

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STRATEGY ON HOW  TO REDUCE INDISCIPLINE IN SECONDARY SCHOOLS IN KENYA

Nickson Moseti Ongaki, Dr. Okibo Walter Bichanga & Dr. Willy Muturi

  1. Introduction

This Innovative Programme is based on proper formation and efficient management of school based peer counseling clubs as the best way of reducing indiscipline and also restoring peace among pupils in secondary schools. In most schools the controversial issue of discipline and conflict management to enhance peace among the pupils has been left in the hands of teachers with pupils having no say on most of the issues affecting them at school. However, due to the soaring population and understaffing in most public secondary schools country wide, teachers have either inadequate or no time to deal with growing indiscipline among pupils. Moreover, very few teachers are trained in peer counseling and therefore posses limited skills to cope up with programmes that can restore discipline in secondary schools. More often than not, prefects are used to identify defiant pupils who are later handed to the teachers for appropriate punishment. Most teachers often take the prefects’ word when solving indiscipline cases among pupils and may subsequently ignore other testimonies from non prefects. This stereo type belief that prefects always tell the truth may increase conflicts among pupils rather than solve them. Other pupils may be depressed when they believe that it’s only the prefects who are trusted and believed by the teachers. Prefects are also sometimes given powers to even administer punishment to other smaller children thus increasing acrimony among the learners.

This innovative programme therefore identified a more participatory and efficient ay of discipline management in schools by piloting a way which would involve the children themselves in reducing the growing indiscipline in the school. Through the formation of peer counseling clubs many children would be involved in informing others on the best way to behave while in schools. Members of the school peer counseling clubs would be used as peace ambassadors who would not only enlighten others on the benefit of a peaceful co-existence but also be moulded into responsible models for others to admire.

  1. Problem Statement

Growing indiscipline among secondary school pupils has continued to have a negative impact on efficient education management and administration in Kenya. In Mugai secondary school, the school had the problem of growing indiscipline among the pupils which compromised peace among the learners. I observed frequent fighting and noisy quarrels among the pupils, rampant destruction of school property and poor relationships among the pupils despite punitive intervention measures from the teachers to check the vice. Furthermore, the school prefects were the most hated in the school because they were seen as either spies of the school administration or as representatives of the unjust and corrupt society.

The school administration on its part used non corporal punishment as the best way of restoring discipline among the pupils. The culprits were made to weed the school sugarcane farm the whole afternoon or uproot tree stumps in the school compound or slash tall grass in the playground. Weeding the school Napier grass was also another alternative to punish wrong doers. However, despite all those aforementioned interventions, indiscipline in the school continued to soar. There were more fighting among the pupils and the big pupils did not respect the teachers and the school subordinate staff. The drop out rate in standard six, seven and eight was very high. Some girls got pregnant and stopped coming to school while some boys opted for casual jobs this was may be due to lack of peace in the school.

The school administration involved both parents and guardians of the affected pupils but the results were negative. In most cases most parents and guardians sided with their children, accusing the administration of segregating the children on the basis of social class, gender or ethnic background. This led to a very poor relationship between the school administration and the community. During parents’ meetings, parents would turn such meetings into a finger pointing and shouting match. At times prefects could be waylaid on their way home by bullies and beaten; such issues would be left in the hands of the Provincial administration.

They were two teachers trained in peer counseling in our school but they were almost giving up on their effort to guide and council the growing number of deviant pupils. The purpose of this programme was therefore to use peer counseling club as the best way of restoring discipline among the pupils.

 

  1. Addressing the problem

In January 2009 I sought the permission from the school administration to start a peer counseling club which I was granted. With the help of two teachers trained in peer counseling, we held a two day school based inset in which we sensitized teachers on how the club was to function and the support we needed from them. Some  teachers were very co-operative although some argued that the club could not work in such a harsh environment. Yet others waited to see how we could start so that they could join us.

  The second step I took was to seek advice from other non- teachers who had a vast experience in working with the youth. I got invaluable advice from workers of non governmental organizations like Amkeni, APHIA II Western and members of Straight talk of which I was a coordinator. They gave me a lot of information and resource materials on how to educate the youths on emerging issues. I also held a one week awareness programme among the pupils from standard four to eight. The main objective of this programme was to inform the pupils on the role of peer counseling clubs in helping them cope with the every day’s challenges. The programme also gave them the opportunity to know their role in helping the fellow pupils and members of the peer counseling club in trying to reduce indiscipline. The forum also gave us an opportunity to find the root causes of indiscipline, depression and frustration among the pupils.

Later I formed the peer counseling clubs involving pupils from standard four to standard eight. The steering committee of the club consisted of elected class representatives of the four classes who were a boy and a girl representing each class. Other members were on voluntary basis but had to be disciplined to be maintained in the club. All club members were to be of very high integrity and to be role models to others. Any club member found breaching the club’s code of conduct was to be suspended from the club until he/she reformed.

The club’s meetings took place every Friday after classes. During such meetings, the club’s weekly activities would be evaluated. The meetings also enabled the peer counselors and other available resource people to educate the club members on how to carry out their roles effectively. The club members would also update us on more challenging and emerging issues which required attention from the teachers or peer counselors.

The club members on their part organized to interact with their fellow pupils every Wednesday after classes. With the assistance of teachers, peer counselors and other volunteers, the club members would use this opportunity to create awareness among the fellow pupils on the need to behave well while in school. Situations which were beyond the scope of the club members were referred to the teachers. The teachers also helped in grouping the pupils into manageable groups according to either gender or age; depending on the topic of discussion. Sometimes resource people were also invited to help the peer club members in clarifying the most challenging issues.

The club would also be involved in spreading peace messages in the school through music, drama, poetry, writing articles and drawing cartoons on the school notice board. During various school functions like Education Days, Parents’ Days and School Assembly, club members would get an opportunity to pass the message to the peers. The club members also made a suggestion box where responses from other pupils on their opinions concerning the school were dropped. Such suggestions were thoroughly discussed during club meetings and the necessary actions taken. The council of prefects also met club members once every month where they were advised on how to make fair and just decisions.

The major obstacle at the initial stages of the programime was lack of support from the parents. Most of them objected the idea of their children being tutored by others. They termed this as an attempt by the lazy teachers to delegate their work to minors who were not mature enough to lead. The school management on its part, managed to call a parents’ meeting where we enlightened them on the club’s call. Some parents were satisfied and started supporting the programme while others were still suspicious on the aims of the club. Another big obstacle was instilling confidence in club members. Most pupils were shy and had no exposure of standing and speaking before others; furthermore, some naughty pupils were always ready to humiliate their fellow peer tutors. However, we gave a lot of motivation and confidence to peer counseling club members and prepared them on how to endure the challenges from their friends. Furthermore, the teachers and other counselors were always ready to stand in for issues that would not be handled by the young ones. There also pessimism from some teachers who forecasted doom for the project. They argued that the peer counseling clubs could not have the necessary machinery to cure indiscipline. However, those determined always moved forward with program implementation. Lack of funds to purchase the necessary materials and stationery was also a big obstacle. The club had to rely on the school administration and volunteers for such materials. Moreover the club’s trips were limited to a few neighboring schools which were a walking distance away. With the availability of funds, the club intends to widen its scope to cover as many schools as possible in their campaign.

  1. Outcomes

Six months after initiating this programme, I have realized a lot of changes in the school. The club membership has risen from sixteen to over sixty members. The discipline of the school pupils has started to improve. This can be inferred from the few cases of indiscipline being handled by the teachers of late. The administration has also reported very few cases of culprits being send home on indiscipline grounds and very few pupils are punished for disobeying school rules.

Most parents and guardians have also started changing their attitudes towards the school after realizing what the club has achieved. Most of them report to the teachers that their children have improved their behaviour even at home. During parents’ meetings, many stakeholders still encourage the teachers to maintain the club for the benefit of the whole community.

The school notice board has become active with pupils’ letters, cartoons and articles on the benefit of the responsible youths. This is unlike before where the notice board only had announcements from the school administration. School functions are always lively with pupils’ performances in drama, poetry and music. This has increased the confidence and creativity among the learners. In fact, the school performed well I Choir up to the provincial level in the year 2009.

The attitude of pupils towards prefects has improved tremendously. Most prefects make just and fair decisions, they do not victimize their enemies on mistakes they did not do. Most teachers have now agreed to treat all children fairly, irregardless of the social background, gender or ethnic background. This has restored the confidence of pupils in prefects and teachers.

Teachers have also a very easy time controlling the pupils. They have also reported an improvement in the academic performance among the pupils this has boosted their morale and their perceptions on the behavior and ability of the children.

  1. Findings

The best way of initiating positive changes in the behaviour and perceptions of children is to actively involve them in youths’ awareness campaigns through clubs. The peers spend most of their time together during various activities and it is easier and cheaper to involve them in self-corrections and correcting others than involving the adults. Playmates, for instance, can get corrections from friends and change for the better than when the corrections come from others. When peers correct others, they gain a lot of responsibility and acceptance in the society. They also practice leadership roles when they are still young. This can go along way in reducing indiscipline and strikes witnessed in most public secondary and private secondary schools country wide.

The teachers can use peer counseling clubs as the most efficient way of reducing indiscipline in schools. Use of drama, music and sports in helping children correct their behaviour has a lot of success.

I also encouraged the peer counseling campaign to go beyond the school boundaries and capture the neighbouring schools and the community at large. This was by arranging visits for club members to visit other schools for the awareness campaign. During days such as National AIDS Day and Public Holidays the club members would perform music or plays which stressed on peaceful co-existence among members of the community. This was well received in the community and encouraged. With the availability of funds, the club plans to extend its visits to cover a larger population.

  1. Sustainability

The future plans for the club are to widen the scope of the content of the club’s campaign to include HIV awareness and gender equality campaign among the learners. This will enable the club address the most challenging and contemporary issues facing the youths.

In trying to intensify community participation in the programme, we have scheduled visits in the neighbouring school community. The visits will serve to sensitize parents and guardians on how to help the club achieve its goals. They will be advised on how to support disciplining their children and ensure that they are in good company. Parents will also be updated on their children’s behaviour and how they can help their children to change in the positive. The club is also planning to hold a fundraising targeting parents and other well-wishers. The funds will cover advertising costs for the club’s programmes and visits to other schools to exchange views on emerging challenges.

The formation of peer counseling clubs can be used by schools, colleges or other institutions of higher learning to reduce riots and strikes witnessed in many institutions countrywide. Other stakeholders can also replicate this programme by expanding it to campaign on issues like gender mainstreaming, HIV AIDS awareness and reduction in levels of corruption. This is because peer counseling clubs is the best platform for creating responsible and peace-loving citizens and hence foster the achievement of Vision 2030

CHANGING strategic TRENDS IN STUDENT LEADERSHIP IN public School system IN KENYA

Nickson Moseti Ongaki, Dr. Okibo Walter Bichanga & Dr. Willy Muturi

ABSTRACT

Against the wider background of increasing interest in the improvement of management and leadership practices in public schools, this paper focuses on the involvement of students in leadership beyond the traditional structure of school prefects. It also seeks to show how the school administrators can be retrained in fresher insights into leadership and management in order to make their institutions responsive to changing trends in administration. Furthermore, the paper seeks to interrogate the prefect system of student representation in secondary schools, its process and outcomes. New ways of conceptualizing leadership are discussed in relation to students’ roles as active agents in improving learning especially in light of the April 2001 educational legislation that prohibited school corporal punishment. The abolition of corporal punishment in schools as (Ng’ang’a 2002:4) has argued, has left a gap which cannot be filled and this has led to the prevalence of diverse disciplinary problems in schools. Schools are compelled to operate within the regulatory framework of the Ministry of Education which may at times conflict with their peculiar needs, situations and circumstances. To this end, schools are somewhat constrained in combating the rapidly escalating problems with discipline. Furthermore, parental attitude toward educators and school authorities exacerbate the disciplinary control in schools due to parents’ skepticism towards disciplinary measures. This paper proposes the idea of ‘democratic governance” as one of the novel ideas that can make school system relevant to changing realities. It further introduces the concept of “Leadership by Students” (LbS) to underscore the fundamental need by education authorities to conceptualize a school system where each student is given a leadership role in the school as an important way of ending the prefecture system which is responsible for the school strikes and a skewed view of leadership where a few dominate the majority. This paper argues that a perception of leadership as a relational process of influence rather than a hierarchical power structure gives credence to the view that students’ leadership is developed more within a climate of democratic governance than dictatorship. Schools and networks of schools are suggested as important sites for the enactment of leadership as influence through the lateral modalities of power such as negotiation and persuasion which may contest and change existing structures of student leadership. In recent years the term “student voice” increasingly has been discussed in the school reform literature as a potential avenue for improving both student outcomes and school restructuring (Harber & Meighan, 1989; Harber, 1995; Ruddock & Chaplain, 1996). The concept addresses a core voice that has been missing in the discussion of school reforms – the dilemma of ownership. Student voice initiates public schools to reevaluate who gets to define the problems of a school and who gets to try to improve them (Trafford, 2006; Flutter & Ruddock, 2004; Apple & Beane, 1995; Chapman, 1995).  A key challenge for policy workers is to understand how different school governance structures and educational reforms impact on the role of student leaders and most importantly on the ability of school leadership to provide effective teaching and learning, (Hargreaves, 2003).  Since 2001, Zawadi Leadership Project in Secondary Schools under the auspices of Zawadi Counselling and Research Centre has been conducting research and seminars on LbS in 20 selected schools from Nairobi and its environs. These studies have found out that the school prefecture system in public schools is an important cause responsible for the rising cases of school strikes. These studies have adopted a multi-method approach including both quantitative and qualitative data analysis. This paper looks outward, focusing on the imperatives of student leadership rather than inward, on school heads and governing boards.  (604 words)

Key Words: leadership by students, democratic governance, educational governance, management and leadership practices, negotiation, persuasion, school prefects, school restructuring, student voice.

A. INNOVATIVE STATEMENT

In this paper, WE argue that a lack of democracy in schools coupled by an authoritarian education system which creates a sort of police system of student governance is the main cause of these school strikes and unless this fact is assimilated by education policy makers, there will be no end in school strikes in Kenya. Consequently, this presentation is a condensation of research and training findings spanning a period of 8-years (2001-2009) that interviewed members of school communities who include: headmasters-also referred to as principals, teachers, students, parents, members of board of governors (bogs), prefects and parents. Furthermore, this presentation probes the prevailing school culture defined as “historically transmitted patterns of meaning that include the norms, values, beliefs and myths understood by members of the school community” especially as it pertains the role and place of student leadership in the overall school leadership and management structure. The research question pervading the entire spectrum of this discussion is: How best can the students’ voice be heard in the public school system? And the title for this innovative project is: “Changing Trends in Student Leadership in Public School System: Introducing the Concept of Leadership by Students (LbS)”

 INTRODUCTION

“Democratic Management” is the new concept that ought to be incorporated by schools’ in order for them to fit in the “new school order realities” and in order for the students’ voice to be heard. The word “democratic” is used to stress the openness of schools and educational systems; the term “management” is used to underline the technical and instrumental dimensions of governing. We govern those things or beings, the behaviour of which cannot be predicted totally. We manage things or beings, the behaviour of which is easier to predict. When we govern, we negotiate, persuade, bargain or apply pressure, because we do not have full control of those we govern. When we manage, we tend to instruct and order because we think we have strong and legitimate power to do so. Thus, as schools are becoming more and more open institutions, rooted in specific local social and economic settings, and characterized by a complex array of different needs and interests, then governance rather than management is what should characterize relations with students. And since so many factors cannot be controlled by executive powers alone, an open and democratic approach is the only way to a successful and sustainable leadership in a modern school.

From 2001, Zawadi Counselling Centre has been conducting a series of researches and training seminars on the minority Prefectorial System of governance and management in 20 secondary schools in Nairobi and its environs and how best to improve governance and management in schools. One of the ways in which Zawadi Counselling Centre has helped initiate this concept of democratic management in schools is through the LbS concept which involves all students in leadership and management of their respective schools. Furthermore, such an involvement lends credence to the concept of “the naked public square” where leaders are publicly elected by the majority students to represent the student body under an agreeable formulae as opposed to the culture of secret selection by the few (headmaster and teachers) using an unknown formulae where the select few student leaders make major decisions affecting every student becomes the norm. The LbS concept will make school strikes a thing of the past since dialogue born of democratic governance will be the in-thing in human relations. The LbS idea is an important aspect of the concept of “transformational leadership” which focuses on the importance of teamwork and comprehensive school improvement as an alternative to other modes of leadership. Transformational leadership is contrasted with instructional leadership which encompasses hierarchies and leadership structures and usually excludes teacher development, and, transactional leadership which is based on an exchange of services for various kinds of rewards that the leader controls, at least in part. Advocates of school reforms also usually advocate altering power relations. The problem, explain (Mitchell & Tucker, 1992) is that we have tended to think of leadership as the capacity to take charge and get things done. This view keeps us from focusing on the importance of teamwork and comprehensive school improvements. Thus, “instructional leadership” is “out” and “transformational leadership” is “in”.

The research literature identifies productive high schools as those that educate all of their students well, have a clear vision of their teaching and learning goals, and take action on those goals (Silins et.al., 2000). They also have high expectations for all students. Productive high schools are built on humanized, intellectual relationships for learning. Students are viewed as individuals and they know that the adults in the school care about them both personally and academically. This way of viewing students is reflected by a number of local private secondary schools most of which do not have this Prefectorial System. These private schools are used as control group in Zawadi. Research has shown that school strikes are more pronounced in “prefects run schools” than in “non-prefects run institutions”, where student voice is respected, acknowledged and encouraged (Mangi, Otieno & Ng’ang’a, 2003:30). The concept of democratic governance can benefit schools in primarily preparing young people to become participating, democratic adult citizens. The LbS is in my view, one of the best ways to introduce the culture of democratic governance in our schools.

B. PROBLEM STATEMENT

Research by Zawadi has revealed that many school principals may be ill-prepared to cede ground for a new paradigm shift in student understanding of their role in running of schools. An aspect of this paradigm shift is the flexibility in the learning environment brought about by among other factors the rise and rise of Information and Communication Technology (ICT), which unfortunately seems escape the perceptions of minders of the traditional school system best represented by the public school system in Kenya. The developments in the growing ICT culture among especially secondary school and college going youth is significantly affecting the education culture defined in this context as “shared interpretations about beliefs, values and norms of a learning environment which affect the behaviors of members of a school community”. One area which is being affected by this ICT changes is the move from traditional learning environment focused on the teacher as deliverer of knowledge to new open learning environments focused on the learner as information seeker. The role of the teacher and learner change in the new learning environment; the teacher becomes: a facilitator, coach, guide and co-learner. The learner becomes; an information server, explorer, problem solver, co-teacher. (Grabinge & Dunlop, 2000:8-38).

In other words, the image of the teacher as the sole purveyor of knowledge is fast becoming obsolete and with it, the belief that a few select student administrators famously called “prefects” personify student leadership and can effectively instill student discipline and order. What is generally missing in majority public schools and some private schools is the culture of a data driven school improvement which seeks to answer the ageless question: is it good because we have been doing it for a long time, or is it good because we have tangible evidence of its worth? In other words, can data use improve education? Studies by Zawadi have shown that generally speaking unpopular “good and bright” students are often favored for the positions of school prefects by the school administration (headmaster and teaching staff). But the truth of the matter is that the popular “bad and less bright” students often have the sympathies of the students in general. And because of these sympathies, this category of un-selected student leaders, have the ability to unbalance the school order. Unfortunately, the school system as currently constituted has failed to recognize and utilize their hidden potential for leadership, and where administrators are concerned that their continued stay in school may disturb the status-quo, they have expelled them. The chasm between the traditional model of education and the emerging ICT based model of shared learning was clearly brought to the fore by the infamous school strikes of June 2008 where a reported 300 schools were rocked by violent strikes (Daily Nation, 2008).

What was striking in this national shame was that the mobile phone, a modern product of ICT, was a major culprit in the sense it was used to communicate the strike, student to student and school to school. But what is perplexing was the response by top education officials in explaining the reasons behind the strikes and the panacea for the same.

But even more worrying was the findings by David Koech, the chairman of Parliamentary Committee on Education. According to Koech, “drug use, insecurity schools and parents’ neglect of their children were some of the major reasons behind the strikes in schools”. Furthermore, the House Committee recommended radical changes in the education system which includes among other things, “pocket to be banked with the school to avert cases of drug abuse” (East African Standard, 2008). Earlier on Education Minister Sam Ongeri had introduced tough measures in schools which “banned the use of mobile phones in schools by students and ordered the removal of music systems and DVDs from school buses among other measures” (East African Standard, 2008). These measures are based on partial conclusion of the problem. Conclusions by top education officials failed to recognize the crucial role that can Subordinate Staff play to fuel skirmishes in schools. In fact, little attention has been devoted to the recognition of the office of Subordinate Staff in schools. The traditional triangle concept of describing key actors in a school as consisting of, Teachers, Students and Parents is misleading. Studies by Zawadi have noted the huge influence the Subordinate Staff (Supporting Staff) bear on the school system, given that they tend to stay longer as employees of schools as compared to the triumvirate of Teachers, Students and Parents. This aspect of ‘permanency’ by Subordinate Staff means that they understand better the school culture. And if this cooperation between the Subordinate Staff and students becomes a conspiracy to commit evil, the results can be catastrophic. That is why there is need to reconfigure the triangle of relationships and include the Subordinate Staff as the fourth independent and critical element in the school architecture. To include this segment as a core member of the school community will affect education policies and could eventually become an important step in the democratization of schools. The success of the Zawadi Counselling Centre Leadership initiative was demonstrated during the infamous school strikes of 2008. All the 20 schools which have undergone this leadership and management for change programme did not indulge in this strike.

C. ADDRESSING THE PROBLEM

But how can schools contribute to the (LbS) initiative? From 2001, the Zawadi program conducted a series of researches and trainings in leadership and management in 20 selected schools within Nairobi and its environs. The total cost involvement from 2001-2009 was $200,000 and involved 18-25 specialized personnel. Prior to the involvement with this secondary school project, we considered expanding the project to include primary schools, colleges and universities. But a lack of enough specialized personnel for such a mammoth project coupled by inadequate finances meant that we could only limit ourselves to secondary schools in Nairobi. The selected schools were grouped in four groupings: schools from rich neighborhoods; schools from Eastlands neighborhoods; schools from slums; private schools.  Another criterion was based on gender considerations. Thus, girls’ schools were balanced proportionately with boys’ schools. Three mixed schools were selected. Two major approaches were used: training seminars and research. In the initial pilot study in 2001, a focus group session was conducted in one selected school where the research was carried out. Ten principals participated in the exercise of which the main purpose was to highlight the essence of student leadership seen collectively as the entire student population and not selectively as in few student representatives chosen only by the principal and the teaching staff. In order to conduct the nomothetic research a questionnaire was designed and applied. The nomothetic deductive method is the one that is used by researchers who want to learn something about social regulations – things that apply to people in general (Hardin,1985).

For the purpose of empirical investigation (2001-2009), a total of 1000 students, 300 teachers, 150 members of BOGs of 15 schools, 85 subordinate staff and 200 prefects were included. To obtain information regarding the interviewees’ perceptions and experiences of what ails the school system, a questionnaire was administered using the medium of the English language. The questionnaire was scored quantitatively by means of appropriate statistical techniques such as frequencies, percentages, analysis of variance (ANOVA) and chi square analysis, and included an open question that was evaluated qualitatively. The scoring of the questionnaire was done electronically. The reliability of the questionnaire was between 0.93 and 0.97 which may be considered as very good. The ideographical research was carried out by means of focus group interviews, semi-structured interviews with principals, teachers, students, subordinate staff, members of boards of governors and prefects of schools that were involved in the 8-year study. to find more about the participants’ experiences, thoughts, and general feelings regarding what they thought about the concept of LbS.  In order to lend ethical consideration to the empirical study, certain measures have been considered. This was done by obtaining permission from all relevant stakeholders.

Our study conceptualized four levels of a successful implementation of the LbS initiative within a democratic governance model. At the first level, appropriately called the “Entry Point”, there was need by school management to recognize and accept that a new paradigm of LbS is gradually and perceptibly replacing the old model of authoritarian and militarian leadership where age and seniority are taken for granted as acceptable substitutes for wisdom and know-how. In the second level of implementation, we recognized the growing importance of leadership and management practices in schools. Thus, we sought to reeducate the school administrators on the three salient principles of leadership and management, namely, cooperation, competition and conflict. At the third level is the development of human values and behaviors of mutual respect, rights and responsibilities and, above all, trust. At this third level, the school is seen as an important bearer of democratic values. It is an open school, with regular communication with higher authorities to give them good grounds for future decisions. Student members in school councils or school boards are given special training in meeting procedures. In fact, by the end of the 4-year school cycle, each student must have served as a school leader at the various levels of leadership available in the school. The student leaders also get a budget of their own to run their offices. Both formal and informal consultations produces systemic and structured information flow and sharing of responsibilities even in difficult areas of budgeting, curriculum development, strategic planning, school-based teacher training, student self-improvement trainings, evaluation, and teaching. At the fourth level we propose that there be a deliberate reconstitution of the school prefect structure by setting up a LbS-student council where all students are represented, with a number of representatives for the student body meeting regularly, perhaps with a chairman and a secretary as the only leading positions. But the council can also be organized much more elaborately by having a Senate with two representatives from each class and chaired by the Vice-president and The Cabinet, led by the President, who has the executive power. President and Vice-president are elected by the student council without undue interference by the school principal or teachers. Their mandate comes from the Senate which is itself elected after every school term to give chance for as many students to participate in its deliberations. Then there is the Court which has one member from each class. The Court acts as mediator in conflicts between students and between students and teachers. The objective of the Court is to reach consensus between conflicting parties. Members of the student council are given special training and support in their work by the school head. One of the outcomes of this system of student leadership is greater mutual respect and trust between teachers and students. Also, the teachers tend to see students more as equal partners in the learning process.

This research experienced four major drawbacks in the form of: limited financial resources; non-cooperation from some school heads, teachers, and BOGs; inability to meet the Parliamentary Committee on Education and top education officials; limitation in the generalization of the research findings given that this investigation was conducted in a certain geographical zone. How these bottlenecks were overcome is as follows: we were able to work on a shoe-string budget For the obstinate principals, teachers and BOGs, sustained training seminars which were professionally conducted gradually thawed their resistance. We are currently making good progress in meeting the House Committee on Education and top education officials. In recent times we have been having a series of discussions with two potential donors signaling that there is hope that we might conduct country-wide research.

D. OUTCOMES

Before the program came into life, the situation in the schools involved in this study was one where there was a preponderance of the traditional learning model where the headmaster is king and the rest, including teachers’ are his/her acolytes, existing only to do his biddings. Some of the factors that have led to the success of the program include:

  • the “easy to identify with” questionnaires and focus groups interviews;
  • the spirit of confidentiality which even under duress we have chosen to upheld;
  •  the program’s longevity and consistency which has created confidence among participants’ and served to market the group to other schools;
  • the practicality of the LbS proposal and its widespread acceptability among the student population;
  • the high professional standards exhibited during the seminar trainings and by the research environment;
  • the moral and ethical dispositions by members of our team;
  • being known and recognized by the relevant educational officials.

E. LESSONS LEARNT

This program has taught us valuable lessons. Initially we made the mistake of thinking that because we understood the problem clearly, the schools will follow suit and immediately there will be a revolution. We now know better. The process of influencing a change of policy which must deliberately involve all the stakeholders in the education sector is as convoluted as it is necessary. Again, we made the mistake of believing that training seminars are enough in changing thinking and relating patterns among people. Now we know better. Humans are a complicated lot and in our African-Kenyan experience of ethnicity and politicization of all sectors of work, every initiative, every person, every word and gesture is judged on the basis of the ethnic backgrounds and/or political affiliations of the initiators of a program and not on the merit or lack of it of a particular initiative. And no institution is so riddled with this cancer as the school system. We have also on the need to include and cooperate with like-minded organizations for peer review reason. Initially when we begun, there was virtually no organization, at least in Nairobi and its environs, that was directly involved in conducting research and training. In terms of recruiting personnel for research and training undertaking we have learnt not to recruit based on what appears on the CVs, but to subject candidates to both written and field work experience in order to gauge their suitability for the task. The program was publicized by word of mouth. The overall aim of the program is to have the community own the ideas and then take charge of their own destiny.

F. SUSTAINABILITY

The development of LbS within democratic governance will ensure that our program nourishes learning and creates conducive learning environment. In determining the sustainability of this our program we note the following significant weaknesses regarding the education sector vis-à-vis the development of student leadership: lack of clear definition of good student leadership program in secondary schools in particular and schools in general; inadequate preparation programs for students in leadership and management; absence of collaboration between schools and higher education institutions, public and private sectors; absence of a national sense of cooperation in preparing student leaders. The Zawadi consultative team has just finished drawing the Action Plan for our program for the next 5-years phase (2011-2016) where we have comprehensively discussed how to tackle the preceding “significant weaknesses”. Broadly, the Zawadi Leadership Project 2011-2016 Action Plan (Ng’ang’a & Otieno: 2010) proposes a five-pronged approach in addressing the LbS concerns: Active, sustained, and constructive engagement with Parliament; Ministry of Education and other stakeholders in the education sector; media, church and international NGOs involved with education. The focus is to agitate for the change of policy to allow the wind of democratic governance to sweep through the school system and obtain for students a more active role in leadership and management of their schools. I will argue how the LbS could be replicated or adapted in other organizations or settings in line with the seven principles of sustainable leadership by Hargreaves and Fink (2006), which borrow from the environmental and corporate sustainability literature to frame sustainable leadership in terms of energy restraint, renewal, and release. The seven principles by are as follows: Sustainable leadership creates and preserves learning that lasts and engages students intellectually, socially and emotionally; Sustainable leadership secures success over time. The challenge is to let go, move on and plan for ones own obsolescence; Sustainable leadership sustains the leadership of others; Sustainable leadership addresses issues of social justice and is an interconnected process; Sustainable leadership develops rather than depletes human and material resources It develops all its students rather than lavishing rewards on selecting or rotating a few already proven stars; Sustainable leadership develops environmental diversity and capacity; Sustainable leadership undertakes activist engagement with the environment. It develops sustainability by how the school leadership sustains itself and other around it to promote and support learning.

The practical part to these principles which guides the successful implementation of the LbS idea is this: first and foremost create a platform/an assembly where all the students can without inhibitions voice their concerns guided by the democratic ideals of Listening, learning and transforming. Again as in my preceding conclusion, the concept of LbS will ensure that schools become centers of creativity and innovation guided by the undying principles of freedom, democracy and individuality. By using the LbS idea, schools will become centers of participative decision making where power is consensual and facilitative manifested through others instead of over them. (Leithwood 1992 & Sigor 1992).

  CONCLUSION AND RECOMMENDATIONS

The human person is multi-dimensional and cannot be defined unilaterally without risking to devalue him and to consider him inconsequential to the structures and systems he is supposed to annihilate, create and re-create in his search for what is meaningful within his historical and cultural contexts. The public school system as currently formulated and practiced in Kenya does not respect the collective student voice which is swamped under a traditional, daddy-is-always-right system of doing things with a small class of student leaders famously called prefects expected to represent student leadership abilities as a collectivity.  The LbS initiative is an attempt to change this way of conducting student and school affairs. Furthermore, the promotion of holistic education and learning has in recent times become the buzz-word among educationists keen on changing the current state of affairs where student voice is muzzled prompting the venting of student anger through devastating strikes. Bronfenbrenner & Evans (2000:115-125), have introduced the five-system bio-ecological model to explain this multifaceted nature of human interactions. These five systems include: Microsystem (refers to family, peers, school, roles and relationships in the immediate environment); Mesosystem (relationship between home, schools, neighborhood, child care centres); Exosystem (community health services, parks, recreation centres, informal groups); Macrosystem (ideology, values, laws, regulations, customs and culture); and, Chronosystem (includes all aspects of time and how they impact on development).

Analysis of the questionnaire responses from the interviewees in relation to student participation in leadership and management conducted by Zawadi Leadership Project from 2001 to 2009 reveal the following dimensions which indicate well functioning schools. These are: Trusting and Collaborative Climate -The extent to which the school’s climate and culture is one that supports collaborative work, sharing of information and open communication; Taking initiatives and risks-The extent to which the school leaders and school structures support experimentation and teachers, student and supporting staff feel valued and rewarded for taking the initiative; Shared and Monitored Mission-The extent to which teachers and students especially participate in all aspects of the school’s functioning, including decision making and review, sharing a coherent sense of direction and acknowledging the wider school community; Professional Development-The extent to which staff draw on available knowledge and skills to continuously improve their performance; Vision and Goals-The extent to which the principal works toward whole staff consensus in establishing school priorities and communicates these priorities and goals to students, staff and supporting staff giving a sense of overall purpose; Culture-The extent to which the principal promotes an atmosphere of caring and trust among staff, sets a respectful tone for interaction with students and demonstrates a willingness to change his or her practices in the light of new understandings; Structure-The extent to which the principal establishes a school structure that promotes participative decision making, supports delegation and distributive leadership and encourages teacher and student council autonomy for making decisions; Intellectual Stimulation-The extent to which the principal encourages staff to reflect on what they are trying to achieve with students and how they are doing it; facilitates opportunities for staff to learn from each other and models continual learning in his or her own practice; Individual Support– The extent to which the principal provides moral support, shows appreciation for the work of individual staff and takes their opinion into account when making decisions; Performance Expectation-The extent to which the principal has high expectations for teachers and for students and expects staff to be effective and efficient.

The foregoing is the essence of the public school restructuring process which ultimately does the following:

{1} Develops a vision that unites projects;

[2] Identifies outcomes that will be assessed;

[3] Obtains the active support of the community;

[4] Redefines the role of principals from power wielders to facilitators;

[5} Changes the basic organizational practices to better meet the needs of at-risk students.        (4, 409 words)

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 SIGNIFICANCE OF SOME INDICATORS OF UNDER-FIVE YEARS MORTALITY IN NIGERIA

1Ogunsanya B.G.                   2Adewunmi Olusola A.          3Olagbegi  Moses

ABSTRACT

This study examines the level and determinant of under-five mortality in remote Area of Ikorodu Local Government, Lagos state, Nigeria. The survey was carried out through self-administered questionnaires on selected 200 respondents. A multiple stage sampling was used to select the eligible respondent. 4 wards were selected at random from the 7 wards at Ikorodu Local Government Area. Thereafter four streets were randomly picked at random from each of these houses were selected on each street using systematic random sampling method with the interval once a house is chosen. A house hold was selected randomly from a house that has more than one household. In any polygamous household the respondent were chosen among the wives by lettering method. Data collected was analysed electronically, using SPSS 21.0. The analysis revealed that eighteen (18) of the twenty four (24) indicators paired under study were significantly correlated while twenty three (23) of the twenty six (26) indicators paired were found to be significant indicators of under five years mortality in Nigeria.

Keywords: Indicators, Mortality, Nigeria, Significance, Under Five, Years.


INTRODUCTION

            Mortality rate is a measure of the number of deaths (in general, or due to a specific cause) in some population, scaled to the size of that population per unit time. Mortality rate is typically expressed in units of deaths per 1000 individuals per year, in that entire population, or 0.95% out of the total. It is distinct from morbidity rate, which refers to the number of individuals in poor health during a given time period (the prevalence rate) or the number who currently have that diseases (the incidence rate), scaled to size of the population.

A condition such as tuberculosis can cause morbidity and mortality (disease and death). A mortality rate is a death rate. There are a number of different types of mortality rates such as:

  • The foetal mortality rate: The ratio of foetal deaths to the sum infant mortality rate.
  • The maternal mortality rate: The number of maternal deaths related to child bearing divided by the number of live births or by the number of live births.

There has been increasing interest in measuring under-five mortality as a health indicator and as a critical measure of human development. In countries with complete vital registration system that capture all birth and deaths under-five, mortality can be directly calculated. In the absence of a complete vital registration system however, child mortality must be estimated using surveys that ask women to report the births and death of their children. Two survey methods exist for capturing these information: Summary Birth History and Complete Birth History. A summary birth history requires a minimum of only two questions: how many live births has each mother had and how many of them have survived. Indirect methods are then applied using the information from these two questions and the age of the mothers to estimate under-five mortality going back in time prior to the survey. Estimates generated from complete birth histories are review as the most accurate when survey are required to estimate under-Five mortality especially for most recent time period. However, it is much more costly and labour intensive to collect these detailed data especially for the purpose of generating small area estimates.

The main tenets of the fourth and fifth Millennium Development Goal (MDG 4 and 5) are to reduce under-five mortality rate and improvement in maternal health which by implication increases the chance of child survival. Child mortality is a fundamental measurement of a country’s level of socio-economic development as well as the quality of life especially of the mothers. Under-five mortality rate (5q0) represents the probability of a child who survives to age one, dying between age one and age five (Adlakha & Suchindra, 1984; National Population Commission and ICF Macro, 2009; World Health Organisation (WHO), 2011). Almost half of the child mortality (42%) in the world occurs in Africa and about 25,000 under-five children that die each day are concentrated in sub-Saharan Africa and South Asia (WHO, 2011). Under-five mortality rate (U5MR) is generally 29 times higher in developing nations compared to developed countries (Black & Liu, 2012; Gambrah & Adzadu, 2013; Marx, Coles, Prysones-Jones, Johnson, Augustin, Mackay, Bery, Hammond, Nigmann, Sommerfelt et al, 2005). Globally, under-five mortality has dropped significantly by almost 45 percent between 2009 and 2011 but this progress is not the reality for all countries. Despite much progress in advanced countries, Nigeria has failed to make significant progress in checking the rising mortality rate among the under-five. Currently, about half of the world’s under-five deaths occur in Nigeria, India, Congo, Pakistan and China (National Bureau of Statistics (NBS), 2011; World Bank, 2013).

Statistics revealed that up to 20 per cent of child deaths in sub-Saharan Africa still occur in

Nigeria. Also, the Multiple Indicator Cluster Survey (MICS4) report indicated that under-five

mortality in Nigeria increased from 138 per 1,000 live births in 2007 to 158 per 1,000 live births in 2011 (National Bureau of Statistics (NBS), 2011; World Bank, 2013).

Under-five mortality rates within Africa also vary. In some countries, one-quarter to one-third of children die before reaching the age of five. Also, within the under-five age group, there are specific periods of increased vulnerability. For instance, 60 percent of under-five mortality can be attributed to deaths that occur during the first year of life, of which the first 24 hours of life is the most vulnerable period, followed by the first week and then the first month (Marx et al, 2005). Among the suspected factors that have contributed to drastic reduction of under-5 mortality in advanced economies include but not limited to improvement in socio-economic and environmental conditions and strategic implementation of child survival interventions (Finlay, Özaltin & Canning, 2011; Kyei, 2011; United Nations Children’s Fund, 2010, 2011, 2012).

Child mortality can be associated with two categories of acquired ailments: one is a heavy load of infectious diseases and the other, those diseases that are caused by inadequate nutrition (Cooper, Hickson, Mitchel, Edwards, Thapa & Ray, 1999; Katona & Katona-Apte, 2008). Socio-economic factors including immunizations, exclusive breastfeeding and the adoption and usage of insecticide-treated nets have been revealed by several studies have strong predictors of child mortality especially in the developing countries. Included among these proximate determinants are the risk of morbidity and mortality, education of mother, sanitation facilities, access to safe drinking water and maternal and child health care services (Uddin, Hossain & Ullah, 2008). However, despite these known factors, under-5 mortality rate in sub-Saharan Africa is abysmally far above the prevalent rate in other countries of the world.

 

 

PURPOSE OF THE STUDY

 

The purpose of this study is to examine the level and determinant of under five mortality in remote Area of Ikorodu Local Government, Lagos state, Nigeria.

The specific objectives are:

  1. Identification of socio-economic health and behavioral factors affecting under-five mortality in remote area of Ikorodu local government.
  2. Determining the significance of selected mortality indicators.
  3. Determining the correlation significance of the selected mortality indicators.

SCOPE OF THE STUDY

 

This study covers some selected indicators of under-five years mortality in Nigeria. The indicators were correlated and put to paired test to achieve the set purpose.

The study survey was carried out through self administered questionnaires on selected respondent. A multiple stage sampling was used to select the eligible 200 respondents. Four (4) wards were selected at random from the 7 wards at Ikorodu Local Government (case study) Area. Thereafter four streets were randomly picked at random from each of these houses were selected on each street using systematic random sampling method with the interval once a house is chosen. A house hold was selected randomly from a house that has more than one household. In any polygamous household the respondent were chosen among the wives by lettering method.

LITERATURE REVIEW

According to UNICEF (http://www.unicef.org/nigeria/children_1926.html), every single day, Nigeria loses about 2,300 under-five year olds and 145 women of childbearing age. This makes the country the second largest contributor to the under–five and maternal mortality rate in the world.

Underneath the statistics lies the pain of human tragedy, for thousands of families who have lost their children. Even more devastating is the knowledge that, according to recent research, essential interventions reaching women and babies on time would have averted most of these deaths.

Although analyses of recent trends show that the country is making progress in cutting down infant and under-five mortality rates, the pace still remains too slow to achieve the Millennium Development Goals of reducing child mortality by a third by 2015.

Preventable or treatable infectious diseases such as malaria, pneumonia, diarrhoea, measles and HIV/AIDS account for more than 70 per cent of the estimated one million under-five deaths in Nigeria.

Malnutrition is the underlying cause of morbidity and mortality of a large proportion of children under-5 in Nigeria. It accounts for more than 50 per cent of deaths of children in this age bracket.

The deaths of newborn babies in Nigeria represent a quarter of the total number of deaths of children under-five. The majority of these occur within the first week of life, mainly due to complications during pregnancy and delivery reflecting the intimate link between newborn survival and the quality of maternal care. Main causes of neonatal deaths are birth asphyxia, severe infection including tetanus and premature birth.

Similarly, a woman’s chance of dying from pregnancy and childbirth in Nigeria is 1 in 13. Although many of these deaths are preventable, the coverage and quality of health care services in Nigeria continue to fail women and children. Presently, less than 20 per cent of health facilities offer emergency obstetric care and only 35 per cent of deliveries are attended by skilled birth attendants.

This shows the close relationship between the well being of the mother and the child, and justifies the need to integrate maternal, newborn and child health interventions.

It is important to note that wide regional disparities exist in child health indicators with the North-East and North-West geopolitical zones of the country having the worst child survival figures.

Under-five mortality rate (U5MR) is the probability of a child born in a specified year dying before reaching the age of five if subject to current age-specific mortality rates and expressed as a rate per 1,000 live births (United Nations Children’s Fund, 2012; United Nations Inter-agency Group for Child Mortality Estimation, 2013). It also refers to as the death of infants and children under the age of five. Child mortality has remained a national and global concern and its import in socioeconomic rating of country’s development cannot be overemphasised. Sub-Saharan Africa and Southern Asia face the greatest challenges in child survival, and currently accounted for more than 80 per cent of global under-five deaths (United Nations Children’s Fund, 2012). Several factors had been identified as contributors to the increasing levels of child mortality in most developing countries. Studies have shown that there is a close relationship between educational attainment and lower mortality rates (Antai, 2011; Fayehun & Omolulu, 2009; National Population Commission and ICF Macro, 2009). This was further established through the results in the Nigeria Demographic and Health Survey (NDHS) Report (2009), that children born to mothers with no education have the highest under-five mortality rates (209 deaths per 1,000 live births), while mothers with secondary education have 68 per 1,000 live births.

Although, there are vagaries of statistics and estimations for child mortality for different countries and the world by different sources, the patterns and trends are specifically similar. Among the general patterns is that the global under-five mortality rate has declined by almost 47 percent between 1990 and 2012 (measuring 90 deaths per 1,000 live births in 1990 and 48 in 2012) while the trend in sub-Saharan Africa is apt to increase (United Nations Inter-agency Group for Child Mortality Estimation (2013). Globally, several causes of under-five mortality were noted among which are: pneumonia which contribute up to 17 percent of the entire death, preterm birth complications that cause about 15 percent of child death, intrapartum-related complications (10 percent), diarrhoea (9 percent) and up to seven percent due to malaria (United Nations Inter-agency Group for Child Mortality Estimation, 2013). Also, a survey carried out in Bangladesh shows that child mortality rate was highest (1.64%) for the children of illiterate mothers and lowest (0.54%) for the children whose mother’s educational level is secondary and above (Uddin, Hossain & Ullah, 2009). Educated mothers are more likely than non-literate mothers to ensure a healthy environment, nutritious food, and have better knowledge about reproductive health at conception and health care facilities for their children. Literate mothers will give birth to healthier babies because they themselves tend to be healthier and are likely to experience lower mortality among their children at all ages (Pandey, 2009).

Several of diseases causing child mortality have connections with hygiene condition and unclean environment these are not limited to dirty feeding bottles, utensils, inadequate disposal of household refuse, poor storage water, to mention but few (Jinadu, Olusi, Agun & Fabiyi, 1991; NBS, 2011). Other reports have shown that maternal education is a significant factor influencing child survival (Caldwell, 2009; Osonwa, Iyam, & Osonwa, 2012). Children from poorer or rural households are reported to be more vulnerable than their counterparts from other regions (United Nations Children’s Fund, 2010). A child born to a financially deprived and less educated family is at risk of perinatal death or within the first month of life. The reasons for these are obvious since the mother may be poorly nourished during pregnancy, had little or no antenatal care and likely to deliver in ill-equipped health facility. Besides, the level of competition over resources when the family is large could enhance poor care among the family members including the very young ones. All these factors are further aggravated by limited access to health services due to poor income and low levels of maternal education, often leading to the non-immunization of the child (Policy Project/Nigeria, 2002).

 

METHODOLOGY

 

The most widely available type of data on child mortality is report by mothers on the number of children still surviving. Frequency distribution, bivariate correlation analysis and paired t-test were employed as analysis techniques for the study.

RESULTS

 

From the analysis, 59(29.5%) of the respondents were currently in the age bracket of 30-34 years while only 1(0.5%) of the respondents was in the age bracket of 15-19 years. 81(40.5%) had their first marriage in the age bracket of 20-24 years while 7(2.5%) had their first marriage in the age bracket of 30-34 years. 72(36.0%) of the respondents were civil servants while 7(3.5%) were into Nursing. 73(36.5%) delivered their children at private hospital while 15(7.5%) deliver at home. 53(26.5%) have 4 children while only 1(0.5) has more than 10 children. 107(53.5%) have pregnancy interval of two years between children. 101(50.5%) of the respondents have only primary education while 4(2.0%) have post secondary education.

Table 13 revealed that there is a negative but imperfect correlation between indicators Paired 1, 2, 3, 4, 5, 6, 7, 8, 16, 17, 20 and 23, while there is a positive but imperfect correlation between Paired 9, 10, 11, 12, 13, 14, 15, 18, 19, 21, 22 and 24. However, of these correlations, only correlations for Paired 1, 2, 3, 5, 6, 7, 8, 10, 11, 12, 15, 16, 17, 18, 20, 21, 23 and 24 were significant at 0.05 level of significance.

Table 14 revealed that twenty three (23) of the twenty six (26) indicators paired were found to be significant indicators at 0.05 level of significance.

CONCLUSION

From the analysis of the research study, it can be concluded that eighteen (18) of the twenty four (24) indicators paired under study were significantly correlated while twenty three (23) of the twenty six (26) indicators paired were found to be significant indicators of under-five years mortality in Nigeria.

 

RECOMMENDATIONS

  1. Care during labour and child birth should be provided by a skilled attendance. Early recognition of slow progress in labour and timely interventions to prevent prolonged labour and intra partum foetal distress which can reduce mortality.
  2. Poor sanitation, lack of accessible clean water and inadequate personal and domestic hygiene are responsible for an estimated 88 percent of diarrhea cases everywhere. Proven prevention measures that can significantly reduce the burden of diarrhea include early and exclusive breast feeding (a non-breastfeed child is 10 times more likely to die diarrhea in the first 6 months of life than an exclusively breastfeed child).
  3. To accelerate progress and achieve improved health outcomes for all children ensuring universal-access to high quality care safe water and sanitation, safe and nutritious food and safe housing is crucial as is access to education, social security and other social services.

  1. In addition, investment in women’s health and education and in the empowerment of women and the poorest and most disadvantage population groups is vital to ensure an effective response to under-five mortality rate.

 

REFERENCES

[1]        Adlakha, A.L. & Suchindra, C.M. (1984). Biological and Social Factors affecting Infant and Child Mortality in Jordan, Tunisia, Egypt and Yemen Arab Republic. Final Report, July 1984. DOI: PN-AAT-222.

[2]        Antai, D., (2011). Regional Inequalities in Under-5 Mortality in Nigeria: A Population-based Analysis of Individual and Community-Level Determinants. Population Health Metrics, Vol. 9, No. 6, 2011.

[3]        Black, R.E., & Li, Liu (2012). Global Under Five Mortality: Where Do We Stand Today? Johns Hopkins, Bloomberg School of Public Health for the Child Health Epidemiology Reference Group of WHO and UNICEF.

[4]        Cooper, O. William, Hickson B. Gerald, Mitchel F. Edward, Edwards M. Kathryn, Thapa B. Purushottam & Ray A. Wayne (1999). Early Childhood Mortality from Communityacquired Infections. American Journal of Epidemiology, Vol. 150, No. 5, 1999. The Johns Hopkins University School of Hygiene and Public Health, USA. 1999. Pp 517-527.

[5]        Fayehun, O. & Omololu, O., (2009). Ethnic Differentials in Childhood Mortality in Nigeria. Paper Presented at Detroit, Michigan, USA. April 30 – May 2, 2009.

[6]        Finlay, E Jocelyn, Özaltin, Emre, Canning, David (2011). The association of maternal age with infant mortality, child anthropometric failure, diarrhoea and anaemia for first births: evidence from 55 low- and middle-income countries. BMJ Open, Vol. 1, Issue 2, 2011. DOI:10.1136/bmjopen-2011-000226. ISSN 2044-6055.

[7]        Gambrah, Patience Pokuaa & Adzadu, Yvonne (2013). Using Markov Chain to Predict the Probability of Rural and Urban Child Mortality Rates Reduction in Ghana. International Journal of Scientific & Technology Research, Vol. 2, Issue 11, November 2013. P73-78. ISSN 2277-8616.

[8]        Jinadu, M.K., Olusi, S.O., Agun, J.I. and A.K. Fabiyi (1991). “Childhood Diarrhea in Rural Nigeria: Studies on Prevalence, Mortality and Socio-Environmental Factors” Journal of Diarrhea Diseases Research, Vol. 9, No. 4, 1991. P323-327.

[9]        Katona, Peter & Katona-Apte Judit (2008). The Interaction between Nutrition and Infection, In (ed.) Ellie J. C. Goldstein, Clinical Practice Invited Article, Clinical Infectious Diseases, Oxford Journals, Vol. 46, No. 10, 2008. Pp1582-1588. DOI: 10.1086/587658

[10]      Kyei, A. Kwabena (2011). Socio – Economic Factors Affecting Under Five Mortality in South Africa – An Investigative Study. Journal of Emerging Trends in Economics and Management Sciences (JETEMS), Vol. 2, No. 2, 2011. Scholarlink Research Institute Journals. Pp104-110. ISSN: 2141-7024.

[11]      Marx, M., Coles, C., Prysones-Jones, S., Johnson, C., Augustin, R., Mackay, N., Bery, R., Hammond, W., Nigmann, R., Sommerfelt, E., Lee Benntt, H.J., and Lambert, R. (2005). Child survival in Sub-Saharan Africa: Taking Stock. Washington DC, USA: Support for Analysis and Research in Africa (SARA) Project.

[12]      National Bureau of Statistics (NBS) (2011). Nigeria: Monitoring the situation of children and women. Nigeria Multiple Indicator Cluster Survey 2011Summary Report. National Bureau of Statistics, Abuja Nigeria. 2011.

[13]      National Population Commission and ICF Macro (2009). Nigerian Demographic and Health Survey 2008. National Population Commission, Federal Republic of Nigeria, Abuja, Nigeria and ICF Macro Calverton, Maryland, USA. 2009. P630

[14]      Osonwa, O.K., Iyam, M.A., & Osonwa, R.H., (2012). Under-Five Mortality in Nigeria: Perception and Attitudes of the IKWERRES in Rivers State towards the Existence of “OGBA – NJE”. Journal of Sociological Research, Vol. 3, No. 2, 2012. ISSN 1948-5468.

[15]      Pandey, M. J. (2009). Maternal Health and Child Mortality in Rural India. ASARC Working Paper 12. Institute of Economic Growth, Delhi, INDIA.

[16]      Policy Project/Nigeria, (2002). Child Survival in Nigeria: Situation, Response, and Prospects.

[17]      Uddin, M., Hossain, M., & Ullah M.O., (2009). Child Mortality in a Developing Country: A Statistical Analysis. Journal of Applied Quantitative Method, Vol. 4, No. 3, 2009.

[18]      UNICEF (nd). http://www.unicef.org/nigeria/children_1926.html

[19]      United Nations Children’s Fund (2010). Levels and Trends in Child Mortality – Report 2010. Estimates Developed by the United Nations Inter-agency Group for Child Mortality Estimation. United Nations Children’s Fund. 2010.

[20]      United Nations Children’s Fund (2012). Levels and Trends in Child Mortality – Report 2012. Estimates Developed by the United Nations Inter-agency Group for Child Mortality Estimation. United Nations Children’s Fund. 2012. http://www.unicef.org/videoaudio/PDFs/UNICEF_2012_child_mortality_for_web_0904.pdf.

[21]      United Nations Inter-agency Group for Child Mortality Estimation (2013). Levels & Trends in Child Mortality – Report 2013. UN Inter-agency Group for Child Mortality Estimation. United Nations, New York. 2013. http://www.mamaye.org.ng/evidence/levels-trendschild- mortality-report-2013.

[22]      World Bank (2013). World Development Indicators: Mortality (Table 2.21). World Bank Group. 2013. http://wdi.worldbank.org/table/2.21

[23]      World Health Organisation, WHO (2011). Child Mortality: Millennium Development Goal (MDG) 4. The Partner for Maternal and New Born Birth, World Health Organisation. September, 2011. http://www.who.int/pmnch/media/press_materials/fs/fs_mdg4_childmortality/en/.

 

Fighting Cynicism in Organizations: The Role of Job Autonomy

Sarah Shaharruddina, Dr Fais Ahmadb,

Abstract

This research examined the role of job autonomy in influencing the level of organizational cynicism. By using a survey method through the questionnaires distribution, 504 data set was utilised for the analysis. Several statistical techniques such as factor analysis, reliability test, correlation analysis, and regression analysis were conducted in this research. Through the data analysis, this research indicates a negative relationship between and organizational cynicism. With based on the analysis result, this research suggests that job autonomy could be favourable towards decreasing the level of organizational cynicism.

  1. Introduction

Some of the research on positive workplace attitudes such as  job satisfaction and organizational commitment have gained numerous attention by scholars for decades. Recently it is shown that researchers have increased interest towards paying attention on a negative workplace attitude such as organizational cynicism (Bashir et.al,2011).  The issue relating to organizational cynicism has become the topic of interest for researchers more the past several years ago.

Organizational cynicism is believed as one of a big problem that organizations have to deal with, which should be taken into account and serious consideration by the organizations. However, despite the existence of this problem, it is important for the researchers to investigate what factors that lead towards the development of organizational cynicism This issue is something that cannot be ignored, as it could bring a continuous negative effect on employees and organizational efficiency. (Tekin, & Bedük, 2015).  With this regards, it is important for every organizations to find better solutions in reducing this phenomenon which may hinder organizational and employees success.

The lack of job autonomy given is believed to be one of the major factors that influencing organizational cynicism among the employees. It is suggested that more studies on organizational practices need to be further investigated whether it can reduce organizational cynicism among employees (Chiaburu et.al, 2013). In viewing the level of job autonomy and its influence on organizational cynicism, it is believed that low autonomy could influence the level of organizational cynicism. For example, as cited in Bashir (2011), a lack of autonomy creates melancholy (Stets, 1995) and frustration which results towards misbehaviour and felony (Agnew, 1984) creating serious problems for the organization. Although employees are hardworking and take seriously on their work, but still they seems to less satisfied and lack of passion which cause them to be less committed to the organization. These problems happened as employees feel restricted from working freely and be a part in decision making regarding their own work by themselves. (Naqvi, Ishtiaq, Kanwal & Mohsin Ali, 2013).  In handling with the issue of organizational cynicism, job autonomy  is believed to be one of the necessary weapons  to reduce negative attitude, as employees will not be strictly controlled in their job (Meyer,1987). Furthermore, autonomy also will enable employees to have more freedom in terms of controlling their work and to form procedures on work assessment (Dee,Henkin & Chen,2000).

Although job autonomy has been found to negatively related with organizational cynicism (Avey, Hughes, Norman and Luthans ,2008), there are some inconsistencies found in the past research which seems difficult to confirm the association of these two variables. This can be due to the understanding that job autonomy sometimes is considered as a risky option and this is why not every  employees are  willing to be empowered with autonomy (Bashir; 2011). For example, job autonomy is somehow becoming quite difficult to handle as it requires a high level of trust and accountability on the individuals. It was found that if a high level of trust is required, autonomy turns out to be risky especially when there is least supervision takes place (Langfred,2004). On the other hand, job autonomy may cause employees to be more vulnerable to emotional exhaustion. This is happened if the workload exceed employees’ capacities, where employees will feel trapped and emotionally distressed (Fernet, Austin, Trépanier, & Dussault, 2013). Based on the inconsistencies found, it is relevant for the present study to continuously investigate and discover the influence of job autonomy on organizational cynicism.

  1. Literature Review and Hypothesis Development

Some of the research on positive workplace attitudes such as  job satisfaction and organizational commitment have gained numerous attention by scholars for decades. Recently it is shown that researchers have increased interest towards paying attention on a negative workplace attitude such as organizational cynicism (Bashir et.al,2011).  The issue relating to organizational cynicism has become the topic of interest for researchers more the past several years ago.

Organizational cynicism is viewed a as general or specific attitude characterized with anger, disappointment, and also a tendency to distrust individuals, groups, ideologies, social abilities or institutions (Andersson ,1996). This kind of attitude mostly experienced among employees who believe that their organization is lack of honesty.

Wanous, Reichers and Austin (1994) have specifically described organizational cynicism as “encompassing pessimism about the success of future organizational changes based on the belief that change agents are incompetent, lazy or both” (p.269).  In the context of organizational change management perspective, Ince & Turan (2011) viewed organizational cynicism as an attitude that arise in the workplaces due to the mis-managed of change efforts and it is believed that organizational change is considered as one the major factors of organizational cynicism (Nafei,2013).

Dean et.al (1998) define organizational as “ a negative attitude toward one’s employing organization, which involves a ‘belief’ that organization lacks of integrity and negative affect toward the organization which has tendencies to disparaging critical behaviors toward the organization that are consistent with these beliefs and affect” (p.345). The term of organizational cynicism which defined by Dean et.al (1998) is known as the most commonly cited in the literature and it is conceived as representing an attitude rather than an enduring trait. It is because, organizational cynicism is known as a state variable which may change depends on the experience faced by employees.

Job autonomy is   the extent of power that employees have to delegate their own task and other job activities, which specifically concerns on the voluntary power and freedom towards the work goals,  task elements arrangement and determining the process and the pace of task that are conducted (e.g. Kwakman, 2003; Xanthopoulou, Demerouti, Bakker, & Schaufeli, 2007). It has been   generally defined it as “the degree to which the job provides substantial freedom, independence, and discretion to the individual in scheduling the work and to determine the procedures to be used and  carried out (Hackman & Oldham 1975; Marchese & Ryan, 2001; Morgeson, Delaney-Klinger &Hemingway, 2005; Parker, Axtell & Turner,2001; Dysvik and Kuvaas 2011; Humphrey, Nahrgang, & Morgeson, 2007). On the other hand, it is  also specifically refers to employee’s self rule and independence in terms of decision making (Hackman &Oldham, 1976)

2.1       Job Autonomy and Organizational Cynicism

            It is found that the high level of job autonomy brings employees to feel well adapted with the situational factors compared with other employees who experience less autonomy (Gellatly & Irving, 2001).  In comparison with those who have little job autonomy, those who with more job autonomy will show more satisfaction with variation aspects of the work context (Oldham & Hackman, 1981), positive affect, self confidence and internal motivation (Hackman & Oldham,1976).

Besides, it enables employee to expand their creativity (Oldman & Cummings,1996)  and  less emotional dissonance (Abraham 2000).  Having jobs with adequate autonomy in the organization could equip employees to experience more engagement as autonomy helps to decrease emotional dissonance (Karatape, 2011).   On the other hand, as job autonomy is important towards employee wellbeing, it gives employees more opportunities to adapt themselves with stressful situation and assist them to make decisions on how and when to respond to job demands. With such benefits, employee will face less burnout (Bakker and Demerouti ,2007).

Research has also indicated that job autonomy has a huge impact in influencing employees work attitude (Naus et.al,2007). This is because employee who are empowered to control over their work will be able to meet the job demand and adapt with ambiguity that placed on them which also may reduce the role ambiguity that they have faced (Çekmecelioğlu et.al, 2011). On the other hand, Çekmecelioğlu et al, (2011) also found that job autonomy helps to build the level of employee self confidence, creativity and performance. This may encourage employees becoming  more independent to carry out their task. As other benefits, autonomy may give employees more opportunity to show their extra role behaviour such as OCB (Runhaar , Konermann & Sanders,2013)

H1: There is negative relationship between job autonomy and organizational cynicism.

  • METHODOLOGY

This section  discussed the sample  of the study, scales of variables and process of analysing the obtained data.  Finally, discussion of the findings, conclusions and suggestions of the future research are made in the light of the findings.

3.1       The sample population

The survey based on a disproportionate stratified random sampling technique  was carried out, as it could reduce the sampling error due to the imbalance of population in certain groups (Babbie,1995;& Butcher,1973). The  samples for this study were chosen based on the selection of  the immigration officers (uniform based employees) of the Immigration Department of Malaysia  (IDM),  who work under the  security and defence group, ranging from the upper position of employees  scheme grade,  KP 48 to the lowest KP17 (as shown in Table 1). About 800 questionnaires have been distributed to four selected Immigration states offices and 504 usable data  (63% of response rate) were chosen in this study for the analysis.

3.2       Measures

The data was collected using a questionnaire survey. The first section contains demographical information such as age, gender, qualification, experience and more. The second section is about organizational cynicism which consist of 14 items adopted from Dean et.al,(1998). The alpha reliability for this variable  was 0.868, and sample items included such as “I believe my organization says one thing and does another”, “My organization’s policies, goals, and practices seem to have little in common”, “When my organization says it’s going to do something, I wonder if it will really happen”, “My organization expects one thing of its employees, but rewards another”. “I see little similarity between what my organization says it will do and what it actually does”. “When I think about my organization, I experience aggravation.”, “When I think about my organization I get angry.”, “When I think about my organization, I get tension.”, “When I think about my organization, I feel a sense of anxiety”, “I complain about what is happening in the work to my friends beyond my institution.”, “We look at each other in a meaningful way with my colleagues when my organization and its employees are mentioned”, “I often talk to others about the ways things are run in my organization”, “I criticize my organization practices and policies with others”, “I find myself mocking my organization’s slogans and initiatives”.  How ever, after the Factor Analysis has been conducted, the item number 11 was removed due to high crossloading. Therefore, only 13 items were proceed for the next stage of analysis.

The third section relates to job autonomy, adopted from Karasek, (1979),  and the alpha reliability was found to be at 0.735. The job autonomy items included “My job requires high level of skills”, “My job requires me to learn new things”, “My job requires non repetitive jobs” and “My job requires creativity”, “My job allows me freedom to decide how to organize my work”, “My job allow me to make decisions on my own”, “My colleagues are helpful in assisting in one’s own decisions”, and “I am allowed to say over what had happened”.

  • FINDINGS

Based on the correlation analysis depicted in Table 3,  job autonomy was shown to be negatively correlated with organizational cynicism ( r = -0.106 , p < 0.01). Based on the results, the negative relationship indicates that high job autonomy is more likely to reduce organizational cynicism than with lower job autonomy.

 Meanwhile, the regression results shown in Table 4 indicates that job autonomy has a significant influence upon organizational cynicism (b=0.101, p =0.001; Sig = 0.022 p<0.05). Therefore, this finding confirms that organizational cynicism could be overcome when job autonomy is given focus attention.

  1. Discussion

The  hypothesis result of this research is accepted, where job autonomy is negatively significant in influencing organisational cynicism. As expected, Job autonomy is functioning as an important role to hinder organizational cynicism. This is consistent with the previous research  finding that job autonomy are likely to result in positive outcomes such as increase in job satisfaction and commitment (Naus et.al,2007). Relevant and as demonstrated by the present study, job autonomy  would help to prevent  the possibility of employees from easily developing a cynical attitude, where employees feel more trusted by the organization to carry out tasks. Hence, the presence of job autonomy could result in a higher level of  employees’ intrinsic motivation and more committed employees will be. This finding supported the previous study which showed increase in job autonomy was significantly allied with an upsurges in job commitment (Khamisabadi,2013).

The finding of the present research that depicted a significantly negative influence of job autonomy and organizational cynicism was also evidenced in previous research where it  supported that employees who have more autonomy in their job shows more positive feelings, and self confidence (Hackman & Oldham, 1976), less mental stress (Karasek, 1979), and  less emotional dissonance (Abraham,2000). Additionally,  as been captured by Naus et.al, (2007), the restriction in terms of autonomy could hinder employees self expressive behaviours, which it will potentially evoke opposition and resistance that could lead to negative attitudes and behaviours such as cynicism towards the organization. This problem occurs when there is a  very strict structural controls in terms of rules and procedures  and tight organizational control that impede employees capabilities, work competency and ideas to perform the job. This might cause negative feelings among the employees where they feeling forced to follow all those overly strict procedures which limit their freedom in contributing their ideas and decisions.

Based on the findings that have been obtained,  this study therefore confirms  that,  job autonomy is negatively significant in influencing organizational cynicism,  where  employees who perceive lack of job autonomy will feel more frustrated with their  role and career, which it will ultimately affect their level of commitment and satisfaction level. In the mean time,  the absence of job autonomy cause employees to develop a negative belief about their organization that they are not valued and appreciated, this in turn may also result towards negative emotions and behaviour among the employees.

5.1       Limitations and Direction For The Future Research

There are few limitations of the research that should be acknowledged. First, since all the measurement scale used in this study was adopted from the past studies, factor analysis showed that one item from the dependent variable  was not permanent due high crossloading. How ever, the scale showed satisfactory reliability in this study.

Second, this research is mainly quantitative in nature, where quantitative research is generally little is known about “why” and “how” regarding the antecedents and consequences of the relationship among the variables. Nevertheless, this approach still does not jeopardize the whole findings of the present research as quantitative research could help in generalizing the result by using a large sample size.

Since this study has significant implications for both theoretical and practical contributions, future researchers also should consider to expand the organizational cynicism research by adding organizational culture as a moderating variable. This is to test whether organizational culture could moderate the relationship between the independent and dependant variable. Furthermore, to investigate if there is any type of organizational culture that could weaken or strengthen the relationship between job autonomy and organizational cynicism.

Another useful extension for the future researchers to highlight is to conduct more research into investigating the consequences of organizational cynicism For example, by examining whether organizational cynicism could influence the level of employees engagement, employee deviant behaviour and employees’ union commitment.  . This can be examined by having organizational cynicism as a mediating variable.

5.2       Conclusion

This research summarizes that job autonomy is negatively related with organizational cynicism, where organizational cynicism may reduce if job autonomy is high and given focus attention. Additionally,  it gives an important indication that job autonomy appears to be something that is need to be highlighted in organizational cynicism research context, whether it is beneficial or risky to the employees.  With these findings, this research contributes a new knowledge in the organizational cynicism research.

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Econometric Models  to Water Use Estimation in Power Plants: An Experiential Analysis

 PERINI PRAVEENA SRI

 

ABSTRACT

The purpose of this paper is to examine water use estimation in hydel and thermal electric power plants in selected regions i.e. Coastal, Rayalaseema and Telangana regions of Andhra Pradesh. The study primarily focuses on the realistic fundamental premise that thermal electric and hydro electric energy generation is responsible for the largest monthly volume of water withdrawals in four seasons (i.e. summer, rainy, winter and post monsoon season) of a year. These enormous water withdrawals by these hydel and thermal power plants can have significant influence on local surface water resources. However there are very few studies of determinants of water use in hydel and thermal electric generation. Analysis of hydel and thermal electric water use data in the existing power plants clearly indicates that there is wide variability in unitary hydel and thermal electric water use within the system. The multivariate regression procedures were used to identify the significant determinants of thermal and hydel water withdrawals in various power plants i.e. five hydel and four thermal power plants. The estimated regression coefficients indicate that the best explanatory variables for the total quantity of hydel water withdrawals are storage capacity, tail water level and actual generation and thermal water withdrawals are condenser cooling and ash disposal. The unit variability of unit water usage indicates that there is significant potential for water conservation in existing power plants.

Keywords:

Thermal water withdrawals, hydel water withdrawals, storage capacity, tail water level, actual generation, condenser cooling and ash disposal.

  • INTRODUCTION

Water has become a growing source of tension especially in power sector in many parts of the World. For India hydro and thermal power projects are vital to fill in the serious electric energy shortfalls that crimp its economy. About 40 percent of India’s population is off the power grid and due to this the welfare of the economy was badly affected. The main stumbling block for this kind of worse situation are a genuine water shortage problem in India and the country’s inability to properly manage large quantities of water during rainy season has made matters worse, exposing it to any small variation in rainfall or river flow. Though the country has invested heavily on nuclear power to generate 30,000 MW and $ 19 billion to produce factories of major thermal, hydro and nuclear power stations, the electric energy shortages were very much prevalent in most parts of the country. For this the first and foremost thing is to judiciously manage the vital resource “water”. The country also planned for setting up of 20,000 MW solar power by 2020. The Government of India has an ambitious mission of Power for All By 2012. This would require an installed generation capacity of atleast 20,000 MW by 2012 from the present level of 144,564.97 MU. However the power requirement will double by 2020 to 400,000 MW. How India is able to meet this target with the on-going water shortage plight in Electricity Generation Industry is a matter of great concern. However the Electricity Generation Industry strategy should primarily focus on this invisible culprit “Water” causing huge generation losses through better water efficiency techniques and lay emphasis on technology up gradation and massive utilization of renewable sources of energy.

The purpose of this paper was to examine water use estimation at hydel and thermal electric power plants in selected regions i.e. Coastal, Rayalaseema and Telangana regions of Andhra Pradesh. The study primarily focuses on the realistic fundamental premise that thermal electric and hydro electric energy generation is responsible for the largest monthly volume of water withdrawals in four seasons (i.e. summer, rainy, winter and post monsoon season) of a year. These enormous water withdrawals by these hydel and thermal power plants can have significant influence on local surface water resources. Water use at the power station level (by fuel type) can be estimated indirectly by using multiple regression analysis. In regression models, water use relationships are expressed in the form of mathematical equations, showing water use as a mathematical function of one or more independent (explanatory) variables. The mathematical form (eg. Linear, multiplicative and exponential) and the selection of the Right hand side (RHS) or independent variables depend on the category and on aggregation of water demand represented by Left Hand side (LHS) or dependent variable.

2.0  THEORETICAL AND CONCEPTUAL REVIEW OF LITERATURE: DIFFERENT APPROACHES OF WATER USE ESTIMATION

The various studies relating to water demand for thermal power plants and its significant determinants are reviewed for explicit understanding of thermal electric energy water use. Cootner, Paul and George O Golf (1965) have build upon a systematic model for estimating water demand in conventional steam electric utility industry. They have regarded   water as a common factor input along with fuel. Here

TWD= f (Qf, Cw, EHe, CWH )

Where in TWD = Thermal water withdrawal demand,    Qf = Quantity and cost of fuel,   Cw = Cost of water,  EHe = Economics of heat exchange and recycle and  CWH= other costs of thermal power plant associated with the disposal of waste heat.

In other words the quantity of the fresh water withdrawals depends upon the above mentioned factors. In another study Wollman and Bonem (1971) found that the quantity of fresh water withdrawals for steam electric power generation depends upon (1) Thermal efficiency (with higher thermal efficiency less heat will be dissipated. Due to this smaller amount of cooling water are needed) (2) The extent to which sea or brackish water can substitute for fresh water (3) The rate of recirculation. Recirculation is a function of price of water availability. Young and Thompson (1973) in their study identified three factors that affect water use   in thermal electric energy generation. They can be listed as water pricing, change in generation, technology, price of electricity, price of substitutes used in electricity i.e. oil and gas, population and level of general economic activity. The other factors include waste and heat discharge to water and the changes in cooling technologies.

Gleick (1993) in his study reviewed the water requirement of electric energy. Taking as base of earlier studies, he estimated the consumptive water use in Electricity Generation Industry using different technologies. The system efficiency for conventional coal combustion (Once through Cooling Towers), natural gas combustion (Once Through Cooling Towers) and nuclear generation (CTs) stood at 35 percent, 36 percent and 40 percent. The estimates specifies that with the help of Once Through Cooling Technologies, the average consumptive use ranges from  1.2 m3/MWH  in case of conventional coal, for oil and natural gas consumption the average consumption use is less by 1.1 m3/MWH  , where as with cooling towers it was 2.6 m3/MWH. For nuclear power generation the average consumptive use of water with the aid of CTs was more that stood at 3.2 m3/MWH. There is a need for use of high efficient technology in cooling towers for water conservation. Electric Power Research Institute 2002, estimated the evaporation water loss from recirculating towers i.e., roughly 480 gal/MWH for a coal fired power plant. Mortenson, 2006 in his study have provided a technological breakthrough i.e. small scale tests of one technology (that uses cross-currents of ambient air for condensation) as a counteracting measure for these evaporation losses. By this technology the evaporation losses can be reduced to about 60-140 gallons/MWH (that can be applied even to hotter climates). In value terms, EPRI 2004 notified that the savings from reduction of evaporation losses will be $870,000.

There are very few studies of determinants of water use in hydel and thermal electric generation. The literature available relating to water use estimations is very few. Water use experts have to opt for estimation methods for many of the water withdrawals classes i.e. domestic, agriculture and industry because of the true fact that many legal, financial and political constraints limit for getting the hard data. For instance water withdrawals in domestic and live stock water use are usually estimated by multiplying population figures by coefficient. In case of agricultural sector, the irrigation water withdrawals are often estimated by multiplying the acreage by assumed water requirements of the crop rather than by measuring actual water pumped and applied.

Snavely (1986), explicitly details the water use data collection programs and maintaining regional data base of the Great Lakes St. Lawrence River Basin States.  The results are very much appealing indicating as how broad the range of estimation coefficient for water use can be within a geographic area with similar water availability. Mostly the estimated coefficients used for agriculture and domestic use vary by a factor of 10. The econometric studies relating to water use estimation in public supply use and thermo electric power use have the potential to explain temporal and geographic variability across USA. The aggregated water use estimates were provided by the National water Use Information Programme. These estimates primarily focus on measuring total water withdrawals (that includes annual extraction of fresh  surface water and ground water) for the period 1980-1985 to 1990-1995 in each of 48 states of USA for public supply water withdrawals , domestic, commercial, irrigation and live stock. The saline water withdrawals were estimated for industrial, mining and thermal electric categories. The public supply water withdrawals are estimated within geographical area i during year t using a set of explanatory variables that includes air temperature, precipitation, price of water, median household income and others.

Cohn et.al (1989) and Christensen et.al (2000) have used examples of such kind by using statistical techniques. The shorter time period used has the advantage of highlighting the recent trend of declining water use since the 1980 compilation. The mean withdrawal for the period (1980-1995) clearly indicates that it was 183.7 gallons per capita per day. This average water withdrawals would decrease by 7.8 gpcd, if the state GDP per capita increased by $1000. The inclusion of this state GDP captures the effects of relative volume of non residential uses (along with their ability to pay for water). The model also indicates that US was able to withdraw 17.2 gpcd, because of its surface water rights in comparison with riparian law states. The inclusion of temperature and precipitation variables also clearly shows the effect of weather on water withdrawals and can be used in normalizing water use for weather. The model indicates that average per capita demand for water in the state decreases by 2.1gallons per day per one inch increase in precipitation and vice versa i.e. water demand increases during summer months. i.e. average temperature.

Billings and Jones, 1996 employed indirect estimation of water use in urban and municipal planning using coefficient based methods. It calculates water use for commercial, residential and industrial categories. They assume constant water use rates and ignores trends i.e. changes in water use due conservation, technological change or economic forces. Mullusky et.al (1995), Wood Well and Desjardin (1995) for Washington D.C. metropolitan area have employed this water use coefficients for three categories of water users i.e. simple family homes, multiple family homes and employment water use.   Another approach of estimating National Water Use in USA includes Stratified random sampling followed by Census of Agriculture. They employed various methods of collecting data such as telephone, mail survey instruments to develop detailed country level estimates of national agricultural activities. According to Hutson et.al 2004 the thermo electric power water use refers to water that is removed from the ground or diverted from surface water sources (that includes fresh water and saline water) for use in the process of generating electricity with steam driven turbine generators. In this paper the term water withdrawals is used more often precisely. The term designates the amount of water that is extracted from natural water sources. Again it is essential to demarcate between water withdrawals and discharge as consumptive use. Water consumption is the quantity of water with drawn that is evaporated, transpired, incorporated in to crops, consumed by human or live stock.

At the end it can be said that different authors have notified different methods for estimation of water use for various uses of the economy. This paper employs multivariate models of water use for estimation of significant determinants of thermal and hydel water withdrawals.

Objectives of the paper

The objective is to determine if multiple regression models of unit hydel and

thermo electric water use have the potential

To identify significant determinants of total hydel and thermo electric water withdrawals across selected region wise power plants in AP using aggregated category wise water use estimates.

To estimate the future water withdrawals for hydel and thermal electricity generation plants expressed as cubic meters per second. (Cumecs) and cubic meters using the growth rate phenomenon.

The types of data used for estimation are monthly water withdrawals data (For surface fresh water resources)

Region level models for hydro and thermo electric water withdrawals

The potential dependent and independent variables for water withdrawals are identified for estimation purpose. Regional level data for thermal and hydel water withdrawals are more accurate data. The underlying reason being water withdrawals are usually metered.

Dependent Variable: Total Hydel Water Withdrawals

     Total Thermal Water Withdrawals

Independent Variables of Hydel Power Plant:

(a) Reservoir levels, (b) Inflows, (c) Storage capacity, (d) Evaporation losses, (e) Tail water level and (f) Gross Head

Independent Variables of Thermal Power Plant:

(a) Demineralised water, (b) Boiler Feedback, (c) Condenser Cooling (d) Ash disposal, (e) Others include colony domestic, drinking, sanitation, fire fighting, back wash filter, (f) Installed generation capacity, (g) Actual electric energy production (h) Total no. of cooling towers, (i) Water temperatures in summer, rainy and winter.

Multiple Regression analyses were performed using the data related to category wise water use in power plant, generating facility and weather conditions from month wise 1995-96 to 2008-09 data in respective thermal and hydel power plants. The effect of variables such as quantities of water used exclusively for the production of electricity i.e. Boiler feed, Demineralised water, Condenser cooling, Ash Disposal, colony domestic (Drinking, Sanitation, Fire Fighting, Back wash filter ), installed capacity generation, number of cooling towers, cooling temperature and electric energy generation on total water withdrawals of thermal power plants are explicitly analyzed. In addition to this, the effect of variables such as reservoir elevation, storage capacity, tail water level, evaporation losses, inflows, gross head, actual generation on total hydel withdrawals have also been looked in to. This paper explores the structure of power plant level aggregated water use data based on corresponding and routinely collected economic and climatic data. The purpose of this enquiry is to determine if multiple regression models have the potential to explain the temporal and climatic variability across various thermal and hydel power plants in Andhra Pradesh using aggregated water use estimates and most importantly to identify significant determinants of total water withdrawals of thermal and hydel power plants. The statistical models examined here are derived using data estimates of total water withdrawals for hydel and thermo electric power use.

Specification of Mathematical Model

WHEim = a +∑ bj Xj

                    j

Where WHEim  = Fresh water withdrawals for Hydel Electric Energy within region wise i during particular months m in a year.

     Xj is a set of explanatory variables. (Mentioned above)

WTEim = a +∑ bj Xj

                    j

WTEim = Fresh water withdrawals for Thermal Electric Energy within region wise i during particular months m in a year.

      Xj is a set of explanatory variables. (Mentioned above Coefficients a and bj can be estimated using multiple regression model.

Specification of the Econometric Model:

In Linear forms, these equations can be estimated as follows

Yt = B1+B2X2+B3X3+B4X4+B5X5+B6X6+B7X7+ µ

Model: 1 WTEim = B1+B2 CT+B3DB+B4CD+B5AS+B6WT+B7AG+µ ……… (1)

Where, WTEim = Water withdrawals for thermal electric energy in region i for particular months m.

CT = Condenser cooling (with Cooling Towers), DB = Demineralized water and Boiler Feed

CD = Colony Domestic, AS = Ash Slurries, WT= Water Temperature, AG= Actual generation

µ= random error term

Condenser Cooling: Water required for cooling hot turbines and condensers

Demineralized Water:  Water that is, free of minerals and salts. Water runs through active resin beds to remove metallic ions and filtered through sub micron filter to remove suspended impurities.

Colony Domestic: Water that is used for the purpose of colony maintenance, drinking purpose and plantation.

Ash Slurries: As coal burns, it produces carbon –di-oxide, sulphur –di-oxide and nitrogen oxides. These gases together with lighter ash are called fly ash. The electro static precipitators remove all the fly ash and are mixed with water to make in to ash slurries.

Water temperature: Recording the temperature of water during summer, rainy and winter seasons.

Actual Generation: The generation of electricity that is actually generated apart from installed generation.

Model 2: WHEim = B1+B2 RE+B3SC+B4 TW+B5GH+B6WT+B7AG+µ ……. (2)

Where WHEim= Water withdrawals for hydel electric energy in region i for particular months m.

RE = Reservoir Elevation, SC= Storage Capacity ,TW= Tail water level, El= Evaporation losses, GH= Gross Head, WT= Water Temperature, AG= Actual Generation,µ= random error term

Reservoir Elevation: This is defined as the foot of the dam. i.e. the level from which the reservoir storage level and the height of the dam are measured.

Storage Capacity: This corresponds to the flood level usually designated as the upper limit of the normal operational range, above which the spill gates come in to operation

Tail water Level:  Water immediately below the power plant. Tail water elevation refers to the level that water which can rise as discharges increase. It is measured in the feet above sea level.  1 foot = 0.305 meters.

Inflows: The inflow may be monsoonal rains or lakes, rivers. The average volume of incoming water, in unit period of time.

Evaporation Losses: Conversion of liquid to vapor state by latent heat. Water gets saturated in the form of vapor due to rise in water temperature.

Discharge: Volume of water released from power dam at a given time measured as cubic feet per second.

Gross Head: A dam’s maximum allowed vertical distance between upper stream’s surface water fore bay elevation and the down stream’s surface water (tail water) elevation at the tail race for reaction wheel dams.

Actual Generation: The amount of electricity actually generated apart from installed generation.

The collection of data includes a monthly time series data analysis during the period (1995-96 to 2008-09). Analysis of hydel and thermal electric water use data in the existing power plants clearly indicates that there is wide variability in unitary thermal and hydel electric water use within the system. The multi- variate regression  procedures were used to identify the significant determinants  of thermal and hydel water withdrawals in various power plants i.e. five hydel and four thermal power plants. The unit variability of unit water usage indicates that there is significant potential for water conservation in existing hydel and thermal electric power plants.

3.0 Approach and Methodology

 The study includes three main components. (a) A series of site visits and interviews with power plant personnel. (b) Field surveys of selected hydel and thermal power plants of Andhra Pradesh (c) The multiple regression analysis of power generation data and other associated information.

Summary of site visits: Site visits for selected five hydel namely Nagarjuna Sagar Main Power House, Nagarjuna Sagar Left Canal Power House, Nagarjuna Sagar Right Canal Power House, Srisailam Left canal power house and Srisailam right Canal Power House and four thermal namely Rayalaseema Thermal Power Plant, Kothagudaem Thermal Power Station O & M, Kothagudaem Thermal Power Station Stage V and Narla Tata Rao Thermal Power Plant have been made to assess the overall performance scenario of power plants and also to examine the extent of water irregularities .Appraisal of Power Plant Survey:  The research estimates of hydel and thermal Electric Energy water withdrawals are based upon the authenticated sources of data provided by respective hydel and thermal power plants of Andhra Pradesh Generation Corporation of India Limited. In order to transparently clarify the way that power generation officials responded to this kind of field survey in practice and to solicit information from them on factors responsible for water use at power generation facilities, site visits have been taken up.  At various Power plants several personal interviews with power plant officers helped to identify the types of onsite water uses, the measurement of these uses and provision of information on various types of cooling systems and water use procedures employed by hydel and thermal electric energy generation facilities.

The purpose of conducting a series of personal interviews with power plant officials can be listed as follows:

(a)    Scrutinize and examine the power generation water use and water withdrawals from intake (surface water) to discharge in various types of facilities.

(b)   Observing the fact that all the water with drawals (hydel and thermal) are metered.

(c)    Detailed analysis about important onsite uses of water and its significant determinants

(d)      To obtain feedback on the cooling system level of water use in power stations.

Multiple Regression Models of Water Use

The principal sources of data used in the multi variate analyses of thermal and hydel power plants are most accurate and provides a fairly comprehensive review of plant characteristics, power generation and water withdrawal details. The data in electronic format and in official records was available for the years 1996-97 to 2008-09. The weather data i.e. especially related to water temperatures during summer, rainy and winter was collected in order to examine the influence of it on total thermal and hydel water withdrawals.

At the end it can be concluded that the site visits and field surveys helped to identify important concerns about water measurement and use at thermal and hydel electric power plants. Added to this, these factors have received attention in the development of models to describe hydro and thermal electric water use. All the above mentioned information proved very much useful in the design of data analysis that was used to develop water use bench marks.

4.0 RESULTS AND DISCUSSION: ESTIMATION AND INTERPRETATION OF MODEL SPECIFICATIONS

Hydel based Electric Energy Power Plants

Model Specification I Nagarjuna Sagar Main Power House

 (Appendix table: A1)

In model 1 the estimated regression equation for total hydel water withdrawals is in the linear form as follows:

*              * *                          *

WHE = -146.238-0.080RE-0.258SC+0.350TW+0.133GH+50.67AG

                                               (-3.96)         (3.144)                      (119.87)

N= 154, R2 =0.99, f= 5543.05

  • The estimated equation indicates that the total hydel water withdrawals are inelastic with respect to storage capacity. This kind of negative relationship indicates that the hydel water withdrawals are somewhat in responsive to changes in the storage capacity. The coefficients are statistically significant at 1 % level.
  • The total hydel water withdrawals are elastic with tail water level and actual generation that hold a positive relationship. The coefficients are statistically significant at 5 % and 1 % level.
  • The t-ratio of regression coefficients is highly significant for three independent variables namely SC, TW and AG. As the t ratio value is greater than 2.58 indicates that the relation between dependent variable and independent variables observed in the sample holds good.
  • The t- ratio of regression coefficient is not at all significant for other independent variables such as reservoir elevation and gross feet, as the t- value is very small.
  • The R2 (coefficient of determination) is 0.99. It means that the independent variables tail water level, actual generation and storage capacity can explain 99 percent of variation in the dependent variable (WD) and remaining 1 percent variation is unexplained by the model. As R2 is very high, the estimated equation is considered as an equation of very good fit.
  • The overall model is statistically significant as f value is higher and more significant at 1% level. This clearly indicates that the regressors are significantly associated with dependent variable.

Model SpecificationII Nagarjuna Sagar Left Canal Power House

         (Appendix Table: A2)

*                                 *            *                    *

WHE = 1660.770-3.516RE-21.705SC+9.653TW+491.286AG+0.130EL

            (3.314)                       (4.16)        (3.84)         (15.67)

 N= 166, R2= 0.78, f = 116.22

  • The estimated regression coefficients indicate that the best independent that have significant effect are storage capacity and actual generation with significant levels at 1 % for each of independent variables.
  • The t-ratio of regression coefficients is highly significant with two independent variables namely storage capacity and actual generation. As t ratio value is greater than 2.58, it indicates that the relation between Hydel Water withdrawal and independent (SC) and (AG) observed in the sample holds good.
  • The R2 is 0.78. It means that the independent variables SC and AG can explain 78 percent variation in the dependent variable and the remaining 22 % variation is unexplained by the model. The estimated equation is considered as an equation of very good fit.
  • The overall model is statistically significant as f value is higher (116.22) and more significant at 1 % level. This indicates that the regressors SC and AG are significantly associated with dependent variable.

Model Specification III Nagarjuna Sagar Right Canal Power House 

         (Appendix Table: A3)

             *                                      *                                                     *

WHE = 6133.252+0.628 RL-58.029 SC+0.414EL+37.493TW+486.057 AG

          (7.314)                        (6.063)                                          (16.232)

N= 166, R2= 0.78, f value = 116.22

  • The estimated regression coefficients indicate that the best independent variables that have significant effect are storage capacity and actual generation with significant levels at 1 % for each of independent variables.
  • The t-ratio of regression coefficients is highly significant with two independent variables namely storage capacity and actual generation. The relation between water withdrawals and Storage capacity and actual generation in the sample holds good as the t-value is greater than 2.58.
  • The t-ratio of regression coefficients is not at all significant for other independent variables such as reservoir level, storage capacity and evaporation losses.
  • The R2 is 0.78. It means that the independent variables SC and AG can explain 78 % variation in the dependent variable and remaining 22 % variation is unexplained by the model. The estimated equation is considered as the equation of very good fit.
  • The overall model is statistically significant as f value is higher (116.22) and more significant at 1 % level. This indicates that the regressors are significantly associated with dependent variable (WD)

Model Specification IV Srisailam Left Bank Power House

                  (Appendix Table: A4)

                                                                *                          *

WHE = -2243.501-0.766RE+1.195SC+57.47AG+0.592EL+4.24TW+0.000IF

                              (-2.27)                         (18.81)                     (2.69)

N= 58   , R2= 0.96, f value = 221.872

  • The estimated regression coefficients indicate that the best independent variables that have significant effect are actual generation and tail water level with significant levels at 1 % and 10 % for independent variables.
  • The t-ratio of regression coefficients is highly significant with three independent variables namely reservoir elevation, actual generation and tail water level. The t-ratio value is greater than 1.96 value for reservoir level and greater than 2.58 value for actual generation and tail water level. This indicates that the relation between WD and independent variables AG and reservoir elevation observed in the sample holds good.
  • The t- ratio of regression coefficients is not at all significant for other independent variables such as evaporation losses and inflows.
  • The R2 is 0.96. It means that the independent variables reservoir level, actual generation and tail water level can explain 96 % of variation in the dependent variable and remaining 4% is unexplained by the model. Thus the estimated regression coefficient is considered as an equation of very good fit.
  • The overall model is statistically significant as f value is higher (221.872) and more significant at 1 % level. This indicates that the regressors AG and TW are significantly associated with dependent variable. (WD)

 

Model Specification V Srisailam Right Bank Power House

                   (Appendix Table: A5)

                 *                        *        *

Y = -7630.380-1.78RE+0SC+56AG+0.051EL+0.627TW+0.289GH

              (-4.199)             (-4.3)  (122.65)

  N= 138    , R2    = 0.99 and f value = 4.59

  • The estimated regression coefficients indicate that the best independent variables that have a significant effect are storage capacity and actual generation with significant levels at 1 % level each of independent variable.
  • The t-ratio of regression coefficients is highly significant with two independent variables namely storage capacity and actual generation. The t- ratio value is greater than 2.58 for SC and AG that indicates that the relation between WD and independent variables SC and AG holds good.
  • The t- ratios of regression coefficients is not at all significant for other independent variables such as evaporation losses, tail water level and gross head.
  • The R2 is 0.99. It means that the independent variables such as storage capacity and actual generation can explain 99 % variation in the dependent variable and remaining 1 % is unexplained by the model. Thus the estimated regression coefficient is considered as an equation of very good fit.
  • The overall relationship was statistically significant as f value is 4.59 and more significant at 1 % level. This indicates that the regressors SC and AG are significantly associated with WD.

Thermal based Electric Energy Power Plants

Model Specification VI Kothagudaem Thermal Power Plant O &M

      (Appendix Table: A6)

                                                     *                                                     *   

Y= -787978.047 + 1.021CC-2.130DB-12.190CD+146.699 OT +1.152 AD+4616.497 CT-817.112AG

                              (3.259)                                                        (3.841)

N= 84, R2 = 0.55, f value = 13.710

  • The estimated regression coefficients indicate that the best explanatory (independent) variables with significant effect on quantity of water with drawals per Kilowatt hour are condenser cooling with cooling towers (Natural Draft cooling system) and ash disposal with significant levels of 5 % and 1 % level.
  • The estimated equation indicates that the total thermal water withdrawals are elastic with respect to condenser cooling and ash disposal. This kind of positive relationship indicates that the thermal water withdrawals are responsive to changes in condenser cooling and ash disposal.
  • The t-ratio of regression coefficients have expected signs and is highly statistically significant for two independent variables namely condenser cooling with Natural Draft CTs and Ash Disposal. The t ratio value is greater than 2.58.
  • This indicates that the importance of technological alternatives (i.e. Condenser Cooling with natural draft CTs) is the significant determinant of water withdrawals. Next ash disposal takes second place as significant determinant of total thermal water withdrawals.
  • The t-ratio of regression coefficient is not at all significant for other independent variables such as DM and Boiler feedback, colony domestic, others (Drinking, Sanitation, Fire fighting, Back Wash Filter), cooling temperature and actual  electric energy generation.
  • The R2 is 0.55. It means that the independent variables such as condenser cooling and ash disposal can explain 55 % of variation in the dependent variable and remaining 45 % variation is unexplained by the model. The estimated equation is considered as good fit.
  • The overall model is statistically significant as f value is higher (13.710) and highly significant at 1 % level. This indicates that the regressor’s condenser cooling with Natural Draft CT’s and Ash Disposal are significantly associated with dependent variable WDs.

Model Specification VII Kothagudaem Thermal Power Station Stage V

          (Appendix Table: A7)

                                   *                *

Y= 98233.879+0.873 CC+1.186AD+0.111 DB-1688.373CT+32.019 AG

                               (20.91)       (15.247)

              N= 83, R2= 0.97, f value = 706.164

  • The estimated regression coefficients indicate that the best independent variables with significant effect on quantity of WD per million tonnes are Condenser cooling and ash disposal with significant levels at 1% level each.
  • The t-ratio of regression coefficients have expected signs and is highly statistically significant for two independent variables namely Condenser cooling with natural draft CT’s and Actual Generation. The t- ratio value is greater than 2.58. Here the significant determinant of WD’s are CC with natural draft CT’s. Next comes ash disposal as second good determinant.
  • The t- ratio of regression coefficient is not at all significant for other independent variables such as BF & DM, cooling temperature and Energy Generation.
  • The R2 is 0.97. It means that independent variables such as CC and AD can explain 97 % of variation in the dependent variable (Water withdrawal) and remaining 3 % variation are unexplained by the model. Thus the estimated equation is considered as an equation of very good fit.
  • The overall model is statistically significant as f value is higher (706.164) and highly significant at 1 % level. This indicates that the regressors condenser cooling with NDCT’s and Ash Disposal are significantly associated with Water withdrawal’s (Dependent Variable)

Model Specification VIII Rayalaseema Thermal Power Plant

          (Appendix Table: A8)

                           *

Y = 10334.674+0.745 CC+8.725 BF+0.847 AS-4.143 AG-145.408 CT

     (2.677)                (3.007)

N= 35, R2 = 0.87 and f value = 33.145

  • The estimated regression coefficients indicate that the best independent variables with significant effect on quantity of Water Withdrawal Condenser cooling with significant levels at 5%.
  • The t-ratio of regression coefficients have expected signs and is highly statistically significant for one independent variables namely Condenser cooling with natural draft CT’s .The t- ratio value is greater than 2.58. Here the significant determinant of WD’s are CC with natural draft CT’s.
  • The t- ratio of regression coefficient is not at all significant for other independent variables such as BF & DM, Ash Disposal cooling temperature and Energy Generation.
  • The R2 is 0.87. It means that independent variables such as CC can explain 87 % of variation in the dependent variable (WD) and remaining 13 % variation are unexplained by the model. Thus the estimated equation is considered as an equation of very good fit.
  • The over all model is statistically significant as f value is higher (33.145) and highly significant at 1 % level. This indicates that the regressors condenser cooling with NDCT’s are significantly associated with WD’s (Dependent Variable)

Model Specification IX Narla Tata Rao Thermal Power Plant

                     (Appendix Table: A9)

                          *                               *   

Y = 139993.709 + 1.002CC -0.863CD + 1.031 AS- 373.483 CT- 56.843 AG

                                    (1277.966)                 (19.88)

N=      R2 = 1.00, f value = 907849.564

  • The estimated regression coefficients indicate that the best explanatory (independent) variables with significant effect on quantity of water with drawals per Kilowatt hour are condenser cooling with cooling towers ( Induced l Draft cooling system) and ash disposal with significant levels of 1 % and 1 % level.
  • The estimated equation indicates that the total thermal water withdrawals are elastic with respect to condenser cooling and ash disposal. This kind of positive relationship indicates that the thermal water withdrawals are responsive to changes in condenser cooling and ash disposal.
  • The t-ratio of regression coefficients have expected signs and is highly statistically significant for two independent variables namely condenser cooling with Induced Draft CTs and Ash Disposal. The t ratio value is greater than 2.58.
  • This indicates that the importance of technological alternatives (i.e. Condenser Cooling with Induced draft CTs) is the significant determinant of water withdrawals. Next ash disposal takes second place as significant determinant of total thermal water withdrawals.
  • The t-ratio of regression coefficient is not at all significant for other independent variables such as, colony domestic, cooling temperature and actual electric energy generation.
  • The R2 is 1.00. It means that the independent variables such as condenser cooling and ash disposal can explain 100 % of variation in the dependent variable. This shows that we have accounted for almost all the variability with the variables specified in the model. The estimated equation is considered as very good fit.
  • The overall model is statistically significant as f value is higher (907849.564) and highly significant at 1 % level. This indicates that the regressor’s condenser cooling with Induced Draft CT’s and Ash Disposal are significantly associated with dependent variable WDs.

The pertinent conclusion of this study is there may be significant potential for water conservation after having identified the significant determinants of total thermal water withdrawals i.e. condenser cooling and ash disposal. The choice of explanatory variable for eg: Induced draft and natural draft technological innovation was able to address the significant changes of water withdrawals.

5.0  CONCLUSION AND RECOMMENDATION

The thermal and hydel power plants sustenance is very much under stake due to major reason of fresh water shortages in power generation. The most sophisticated technology followed in advanced countries namely Concentrated solar thermal power integrated with combined system of conventional steam plant, Fresnel Solar Collector and  Solar Flower Tower can be used as a replica even in developing countries like India though not cost effective in order to counteract the water shortage problem

REFERENCES

Benedy Kt Dziegielewski, Thomas Bik (August 2006), “ Water Use Bench Marks for Thermo Electric Power Generation” Project report, Southern Illinois University, United States

Geological Survey, 2004, USGS National Competitive Grants Program.

Gbadebo Oladosu, Stan Hadley, Vogt D.P. and Wilbanks J.J. (September, 2006), “Electricity

Generation and Water Related Constraints: An Empirical Analysis of Four South Eastern

States”, Oak Ridge National Laboratory, Oak Ridge Tennessee.

Sitanon Jesdapipat and Siriporon Kiratikarnkul, “ Surrogate pricing of water: The Case of micro Hydro –Electricity Co-operatives in Northern Thailand”.

 Xiaoying Yang & Benedy Kt Dziegielewski (February,2007), “ Water Use by Thermo Electric power plants in the United states” Journal of the American Water Resources Association, Vol 43, No.1.

“Estimating Water Use in United States: A new Paradigm for National Use Water Use Information Programme”(2002),

http://books.nap.edu/openbook.php?record_id=10484&page=95

 

Data Sources

Annual Report on the Working of SEBs and Electricity Departments, Planning Commission, Various Issues

Administrative Reports of Andhra Pradesh Generation Corporation of India Limited (APGENCO),Various Issues. Field Level data of selected thermal and hydel power stations authenticated  by APGENCO.

Econometric Models  to Water Use Estimation in Power Plants: An Experiential Analysis

 PERINI PRAVEENA SRI

Department of Social Science, Faculty of Economics

 Ethiopia, Aksum University

ABSTRACT

The purpose of this paper is to examine water use estimation in hydel and thermal electric power plants in selected regions i.e. Coastal, Rayalaseema and Telangana regions of Andhra Pradesh. The study primarily focuses on the realistic fundamental premise that thermal electric and hydro electric energy generation is responsible for the largest monthly volume of water withdrawals in four seasons (i.e. summer, rainy, winter and post monsoon season) of a year. These enormous water withdrawals by these hydel and thermal power plants can have significant influence on local surface water resources. However there are very few studies of determinants of water use in hydel and thermal electric generation. Analysis of hydel and thermal electric water use data in the existing power plants clearly indicates that there is wide variability in unitary hydel and thermal electric water use within the system. The multivariate regression procedures were used to identify the significant determinants of thermal and hydel water withdrawals in various power plants i.e. five hydel and four thermal power plants. The estimated regression coefficients indicate that the best explanatory variables for the total quantity of hydel water withdrawals are storage capacity, tail water level and actual generation and thermal water withdrawals are condenser cooling and ash disposal. The unit variability of unit water usage indicates that there is significant potential for water conservation in existing power plants.

Keywords:

Thermal water withdrawals, hydel water withdrawals, storage capacity, tail water level, actual generation, condenser cooling and ash disposal.

  • INTRODUCTION

Water has become a growing source of tension especially in power sector in many parts of the World. For India hydro and thermal power projects are vital to fill in the serious electric energy shortfalls that crimp its economy. About 40 percent of India’s population is off the power grid and due to this the welfare of the economy was badly affected. The main stumbling block for this kind of worse situation are a genuine water shortage problem in India and the country’s inability to properly manage large quantities of water during rainy season has made matters worse, exposing it to any small variation in rainfall or river flow. Though the country has invested heavily on nuclear power to generate 30,000 MW and $ 19 billion to produce factories of major thermal, hydro and nuclear power stations, the electric energy shortages were very much prevalent in most parts of the country. For this the first and foremost thing is to judiciously manage the vital resource “water”. The country also planned for setting up of 20,000 MW solar power by 2020. The Government of India has an ambitious mission of Power for All By 2012. This would require an installed generation capacity of atleast 20,000 MW by 2012 from the present level of 144,564.97 MU. However the power requirement will double by 2020 to 400,000 MW. How India is able to meet this target with the on-going water shortage plight in Electricity Generation Industry is a matter of great concern. However the Electricity Generation Industry strategy should primarily focus on this invisible culprit “Water” causing huge generation losses through better water efficiency techniques and lay emphasis on technology up gradation and massive utilization of renewable sources of energy.

The purpose of this paper was to examine water use estimation at hydel and thermal electric power plants in selected regions i.e. Coastal, Rayalaseema and Telangana regions of Andhra Pradesh. The study primarily focuses on the realistic fundamental premise that thermal electric and hydro electric energy generation is responsible for the largest monthly volume of water withdrawals in four seasons (i.e. summer, rainy, winter and post monsoon season) of a year. These enormous water withdrawals by these hydel and thermal power plants can have significant influence on local surface water resources. Water use at the power station level (by fuel type) can be estimated indirectly by using multiple regression analysis. In regression models, water use relationships are expressed in the form of mathematical equations, showing water use as a mathematical function of one or more independent (explanatory) variables. The mathematical form (eg. Linear, multiplicative and exponential) and the selection of the Right hand side (RHS) or independent variables depend on the category and on aggregation of water demand represented by Left Hand side (LHS) or dependent variable.

2.0  THEORETICAL AND CONCEPTUAL REVIEW OF LITERATURE: DIFFERENT APPROACHES OF WATER USE ESTIMATION

The various studies relating to water demand for thermal power plants and its significant determinants are reviewed for explicit understanding of thermal electric energy water use. Cootner, Paul and George O Golf (1965) have build upon a systematic model for estimating water demand in conventional steam electric utility industry. They have regarded   water as a common factor input along with fuel. Here

TWD= f (Qf, Cw, EHe, CWH )

Where in TWD = Thermal water withdrawal demand,    Qf = Quantity and cost of fuel,   Cw = Cost of water,  EHe = Economics of heat exchange and recycle and  CWH= other costs of thermal power plant associated with the disposal of waste heat.

In other words the quantity of the fresh water withdrawals depends upon the above mentioned factors. In another study Wollman and Bonem (1971) found that the quantity of fresh water withdrawals for steam electric power generation depends upon (1) Thermal efficiency (with higher thermal efficiency less heat will be dissipated. Due to this smaller amount of cooling water are needed) (2) The extent to which sea or brackish water can substitute for fresh water (3) The rate of recirculation. Recirculation is a function of price of water availability. Young and Thompson (1973) in their study identified three factors that affect water use   in thermal electric energy generation. They can be listed as water pricing, change in generation, technology, price of electricity, price of substitutes used in electricity i.e. oil and gas, population and level of general economic activity. The other factors include waste and heat discharge to water and the changes in cooling technologies.

Gleick (1993) in his study reviewed the water requirement of electric energy. Taking as base of earlier studies, he estimated the consumptive water use in Electricity Generation Industry using different technologies. The system efficiency for conventional coal combustion (Once through Cooling Towers), natural gas combustion (Once Through Cooling Towers) and nuclear generation (CTs) stood at 35 percent, 36 percent and 40 percent. The estimates specifies that with the help of Once Through Cooling Technologies, the average consumptive use ranges from  1.2 m3/MWH  in case of conventional coal, for oil and natural gas consumption the average consumption use is less by 1.1 m3/MWH  , where as with cooling towers it was 2.6 m3/MWH. For nuclear power generation the average consumptive use of water with the aid of CTs was more that stood at 3.2 m3/MWH. There is a need for use of high efficient technology in cooling towers for water conservation. Electric Power Research Institute 2002, estimated the evaporation water loss from recirculating towers i.e., roughly 480 gal/MWH for a coal fired power plant. Mortenson, 2006 in his study have provided a technological breakthrough i.e. small scale tests of one technology (that uses cross-currents of ambient air for condensation) as a counteracting measure for these evaporation losses. By this technology the evaporation losses can be reduced to about 60-140 gallons/MWH (that can be applied even to hotter climates). In value terms, EPRI 2004 notified that the savings from reduction of evaporation losses will be $870,000.

There are very few studies of determinants of water use in hydel and thermal electric generation. The literature available relating to water use estimations is very few. Water use experts have to opt for estimation methods for many of the water withdrawals classes i.e. domestic, agriculture and industry because of the true fact that many legal, financial and political constraints limit for getting the hard data. For instance water withdrawals in domestic and live stock water use are usually estimated by multiplying population figures by coefficient. In case of agricultural sector, the irrigation water withdrawals are often estimated by multiplying the acreage by assumed water requirements of the crop rather than by measuring actual water pumped and applied.

Snavely (1986), explicitly details the water use data collection programs and maintaining regional data base of the Great Lakes St. Lawrence River Basin States.  The results are very much appealing indicating as how broad the range of estimation coefficient for water use can be within a geographic area with similar water availability. Mostly the estimated coefficients used for agriculture and domestic use vary by a factor of 10. The econometric studies relating to water use estimation in public supply use and thermo electric power use have the potential to explain temporal and geographic variability across USA. The aggregated water use estimates were provided by the National water Use Information Programme. These estimates primarily focus on measuring total water withdrawals (that includes annual extraction of fresh  surface water and ground water) for the period 1980-1985 to 1990-1995 in each of 48 states of USA for public supply water withdrawals , domestic, commercial, irrigation and live stock. The saline water withdrawals were estimated for industrial, mining and thermal electric categories. The public supply water withdrawals are estimated within geographical area i during year t using a set of explanatory variables that includes air temperature, precipitation, price of water, median household income and others.

Cohn et.al (1989) and Christensen et.al (2000) have used examples of such kind by using statistical techniques. The shorter time period used has the advantage of highlighting the recent trend of declining water use since the 1980 compilation. The mean withdrawal for the period (1980-1995) clearly indicates that it was 183.7 gallons per capita per day. This average water withdrawals would decrease by 7.8 gpcd, if the state GDP per capita increased by $1000. The inclusion of this state GDP captures the effects of relative volume of non residential uses (along with their ability to pay for water). The model also indicates that US was able to withdraw 17.2 gpcd, because of its surface water rights in comparison with riparian law states. The inclusion of temperature and precipitation variables also clearly shows the effect of weather on water withdrawals and can be used in normalizing water use for weather. The model indicates that average per capita demand for water in the state decreases by 2.1gallons per day per one inch increase in precipitation and vice versa i.e. water demand increases during summer months. i.e. average temperature.

Billings and Jones, 1996 employed indirect estimation of water use in urban and municipal planning using coefficient based methods. It calculates water use for commercial, residential and industrial categories. They assume constant water use rates and ignores trends i.e. changes in water use due conservation, technological change or economic forces. Mullusky et.al (1995), Wood Well and Desjardin (1995) for Washington D.C. metropolitan area have employed this water use coefficients for three categories of water users i.e. simple family homes, multiple family homes and employment water use.   Another approach of estimating National Water Use in USA includes Stratified random sampling followed by Census of Agriculture. They employed various methods of collecting data such as telephone, mail survey instruments to develop detailed country level estimates of national agricultural activities. According to Hutson et.al 2004 the thermo electric power water use refers to water that is removed from the ground or diverted from surface water sources (that includes fresh water and saline water) for use in the process of generating electricity with steam driven turbine generators. In this paper the term water withdrawals is used more often precisely. The term designates the amount of water that is extracted from natural water sources. Again it is essential to demarcate between water withdrawals and discharge as consumptive use. Water consumption is the quantity of water with drawn that is evaporated, transpired, incorporated in to crops, consumed by human or live stock.

At the end it can be said that different authors have notified different methods for estimation of water use for various uses of the economy. This paper employs multivariate models of water use for estimation of significant determinants of thermal and hydel water withdrawals.

Objectives of the paper

The objective is to determine if multiple regression models of unit hydel and

thermo electric water use have the potential

To identify significant determinants of total hydel and thermo electric water withdrawals across selected region wise power plants in AP using aggregated category wise water use estimates.

To estimate the future water withdrawals for hydel and thermal electricity generation plants expressed as cubic meters per second. (Cumecs) and cubic meters using the growth rate phenomenon.

The types of data used for estimation are monthly water withdrawals data (For surface fresh water resources)

Region level models for hydro and thermo electric water withdrawals

The potential dependent and independent variables for water withdrawals are identified for estimation purpose. Regional level data for thermal and hydel water withdrawals are more accurate data. The underlying reason being water withdrawals are usually metered.

Dependent Variable: Total Hydel Water Withdrawals

     Total Thermal Water Withdrawals

Independent Variables of Hydel Power Plant:

(a) Reservoir levels, (b) Inflows, (c) Storage capacity, (d) Evaporation losses, (e) Tail water level and (f) Gross Head

Independent Variables of Thermal Power Plant:

(a) Demineralised water, (b) Boiler Feedback, (c) Condenser Cooling (d) Ash disposal, (e) Others include colony domestic, drinking, sanitation, fire fighting, back wash filter, (f) Installed generation capacity, (g) Actual electric energy production (h) Total no. of cooling towers, (i) Water temperatures in summer, rainy and winter.

Multiple Regression analyses were performed using the data related to category wise water use in power plant, generating facility and weather conditions from month wise 1995-96 to 2008-09 data in respective thermal and hydel power plants. The effect of variables such as quantities of water used exclusively for the production of electricity i.e. Boiler feed, Demineralised water, Condenser cooling, Ash Disposal, colony domestic (Drinking, Sanitation, Fire Fighting, Back wash filter ), installed capacity generation, number of cooling towers, cooling temperature and electric energy generation on total water withdrawals of thermal power plants are explicitly analyzed. In addition to this, the effect of variables such as reservoir elevation, storage capacity, tail water level, evaporation losses, inflows, gross head, actual generation on total hydel withdrawals have also been looked in to. This paper explores the structure of power plant level aggregated water use data based on corresponding and routinely collected economic and climatic data. The purpose of this enquiry is to determine if multiple regression models have the potential to explain the temporal and climatic variability across various thermal and hydel power plants in Andhra Pradesh using aggregated water use estimates and most importantly to identify significant determinants of total water withdrawals of thermal and hydel power plants. The statistical models examined here are derived using data estimates of total water withdrawals for hydel and thermo electric power use.

Specification of Mathematical Model

WHEim = a +∑ bj Xj

                    j

Where WHEim  = Fresh water withdrawals for Hydel Electric Energy within region wise i during particular months m in a year.

     Xj is a set of explanatory variables. (Mentioned above)

WTEim = a +∑ bj Xj

                    j

WTEim = Fresh water withdrawals for Thermal Electric Energy within region wise i during particular months m in a year.

      Xj is a set of explanatory variables. (Mentioned above Coefficients a and bj can be estimated using multiple regression model.

Specification of the Econometric Model:

In Linear forms, these equations can be estimated as follows

Yt = B1+B2X2+B3X3+B4X4+B5X5+B6X6+B7X7+ µ

Model: 1 WTEim = B1+B2 CT+B3DB+B4CD+B5AS+B6WT+B7AG+µ ……… (1)

Where, WTEim = Water withdrawals for thermal electric energy in region i for particular months m.

CT = Condenser cooling (with Cooling Towers), DB = Demineralized water and Boiler Feed

CD = Colony Domestic, AS = Ash Slurries, WT= Water Temperature, AG= Actual generation

µ= random error term

Condenser Cooling: Water required for cooling hot turbines and condensers

Demineralized Water:  Water that is, free of minerals and salts. Water runs through active resin beds to remove metallic ions and filtered through sub micron filter to remove suspended impurities.

Colony Domestic: Water that is used for the purpose of colony maintenance, drinking purpose and plantation.

Ash Slurries: As coal burns, it produces carbon –di-oxide, sulphur –di-oxide and nitrogen oxides. These gases together with lighter ash are called fly ash. The electro static precipitators remove all the fly ash and are mixed with water to make in to ash slurries.

Water temperature: Recording the temperature of water during summer, rainy and winter seasons.

Actual Generation: The generation of electricity that is actually generated apart from installed generation.

Model 2: WHEim = B1+B2 RE+B3SC+B4 TW+B5GH+B6WT+B7AG+µ ……. (2)

Where WHEim= Water withdrawals for hydel electric energy in region i for particular months m.

RE = Reservoir Elevation, SC= Storage Capacity ,TW= Tail water level, El= Evaporation losses, GH= Gross Head, WT= Water Temperature, AG= Actual Generation,µ= random error term

Reservoir Elevation: This is defined as the foot of the dam. i.e. the level from which the reservoir storage level and the height of the dam are measured.

Storage Capacity: This corresponds to the flood level usually designated as the upper limit of the normal operational range, above which the spill gates come in to operation

Tail water Level:  Water immediately below the power plant. Tail water elevation refers to the level that water which can rise as discharges increase. It is measured in the feet above sea level.  1 foot = 0.305 meters.

Inflows: The inflow may be monsoonal rains or lakes, rivers. The average volume of incoming water, in unit period of time.

Evaporation Losses: Conversion of liquid to vapor state by latent heat. Water gets saturated in the form of vapor due to rise in water temperature.

Discharge: Volume of water released from power dam at a given time measured as cubic feet per second.

Gross Head: A dam’s maximum allowed vertical distance between upper stream’s surface water fore bay elevation and the down stream’s surface water (tail water) elevation at the tail race for reaction wheel dams.

Actual Generation: The amount of electricity actually generated apart from installed generation.

Selected power plants in three regions of Andhra Pradesh

Power Plant by

Fuel Type

Rayalaseema Region Telangana Region Coastal Region
Thermal Rayalaseema Thermal Power Plant .Kothagudaem Thermal Power Station  O & M

 

.Kothagudaem Thermal Power Station Stage V

 Narla Tata Rao Thermal Power Plant
Hydel Nagarjuna Sagar Main Power House

 

Nagarjuna Sagar Left Canal Power House

 

Nagarjuna Sagar Right Canal Power House

Srisailam Left canal power house

 

Srisailam right Canal Power House

 

 

The collection of data includes a monthly time series data analysis during the period (1995-96 to 2008-09). Analysis of hydel and thermal electric water use data in the existing power plants clearly indicates that there is wide variability in unitary thermal and hydel electric water use within the system. The multi- variate regression  procedures were used to identify the significant determinants  of thermal and hydel water withdrawals in various power plants i.e. five hydel and four thermal power plants. The unit variability of unit water usage indicates that there is significant potential for water conservation in existing hydel and thermal electric power plants.

3.0 Approach and Methodology

 The study includes three main components. (a) A series of site visits and interviews with power plant personnel. (b) Field surveys of selected hydel and thermal power plants of Andhra Pradesh (c) The multiple regression analysis of power generation data and other associated information.

Summary of site visits: Site visits for selected five hydel namely Nagarjuna Sagar Main Power House, Nagarjuna Sagar Left Canal Power House, Nagarjuna Sagar Right Canal Power House, Srisailam Left canal power house and Srisailam right Canal Power House and four thermal namely Rayalaseema Thermal Power Plant, Kothagudaem Thermal Power Station O & M, Kothagudaem Thermal Power Station Stage V and Narla Tata Rao Thermal Power Plant have been made to assess the overall performance scenario of power plants and also to examine the extent of water irregularities .Appraisal of Power Plant Survey:  The research estimates of hydel and thermal Electric Energy water withdrawals are based upon the authenticated sources of data provided by respective hydel and thermal power plants of Andhra Pradesh Generation Corporation of India Limited. In order to transparently clarify the way that power generation officials responded to this kind of field survey in practice and to solicit information from them on factors responsible for water use at power generation facilities, site visits have been taken up.  At various Power plants several personal interviews with power plant officers helped to identify the types of onsite water uses, the measurement of these uses and provision of information on various types of cooling systems and water use procedures employed by hydel and thermal electric energy generation facilities.

The purpose of conducting a series of personal interviews with power plant officials can be listed as follows:

(a)    Scrutinize and examine the power generation water use and water withdrawals from intake (surface water) to discharge in various types of facilities.

(b)   Observing the fact that all the water with drawals (hydel and thermal) are metered.

(c)    Detailed analysis about important onsite uses of water and its significant determinants

(d)      To obtain feedback on the cooling system level of water use in power stations.

Multiple Regression Models of Water Use

The principal sources of data used in the multi variate analyses of thermal and hydel power plants are most accurate and provides a fairly comprehensive review of plant characteristics, power generation and water withdrawal details. The data in electronic format and in official records was available for the years 1996-97 to 2008-09. The weather data i.e. especially related to water temperatures during summer, rainy and winter was collected in order to examine the influence of it on total thermal and hydel water withdrawals.

At the end it can be concluded that the site visits and field surveys helped to identify important concerns about water measurement and use at thermal and hydel electric power plants. Added to this, these factors have received attention in the development of models to describe hydro and thermal electric water use. All the above mentioned information proved very much useful in the design of data analysis that was used to develop water use bench marks.

4.0 RESULTS AND DISCUSSION: ESTIMATION AND INTERPRETATION OF MODEL SPECIFICATIONS

Hydel based Electric Energy Power Plants

Model Specification I Nagarjuna Sagar Main Power House

 (Appendix table: A1)

In model 1 the estimated regression equation for total hydel water withdrawals is in the linear form as follows:

*              * *                          *

WHE = -146.238-0.080RE-0.258SC+0.350TW+0.133GH+50.67AG

                                               (-3.96)         (3.144)                      (119.87)

N= 154, R2 =0.99, f= 5543.05

  • The estimated equation indicates that the total hydel water withdrawals are inelastic with respect to storage capacity. This kind of negative relationship indicates that the hydel water withdrawals are somewhat in responsive to changes in the storage capacity. The coefficients are statistically significant at 1 % level.
  • The total hydel water withdrawals are elastic with tail water level and actual generation that hold a positive relationship. The coefficients are statistically significant at 5 % and 1 % level.
  • The t-ratio of regression coefficients is highly significant for three independent variables namely SC, TW and AG. As the t ratio value is greater than 2.58 indicates that the relation between dependent variable and independent variables observed in the sample holds good.
  • The t- ratio of regression coefficient is not at all significant for other independent variables such as reservoir elevation and gross feet, as the t- value is very small.
  • The R2 (coefficient of determination) is 0.99. It means that the independent variables tail water level, actual generation and storage capacity can explain 99 percent of variation in the dependent variable (WD) and remaining 1 percent variation is unexplained by the model. As R2 is very high, the estimated equation is considered as an equation of very good fit.
  • The overall model is statistically significant as f value is higher and more significant at 1% level. This clearly indicates that the regressors are significantly associated with dependent variable.

Model SpecificationII Nagarjuna Sagar Left Canal Power House

         (Appendix Table: A2)

*                                 *            *                    *

WHE = 1660.770-3.516RE-21.705SC+9.653TW+491.286AG+0.130EL

            (3.314)                       (4.16)        (3.84)         (15.67)

 N= 166, R2= 0.78, f = 116.22

  • The estimated regression coefficients indicate that the best independent that have significant effect are storage capacity and actual generation with significant levels at 1 % for each of independent variables.
  • The t-ratio of regression coefficients is highly significant with two independent variables namely storage capacity and actual generation. As t ratio value is greater than 2.58, it indicates that the relation between Hydel Water withdrawal and independent (SC) and (AG) observed in the sample holds good.
  • The R2 is 0.78. It means that the independent variables SC and AG can explain 78 percent variation in the dependent variable and the remaining 22 % variation is unexplained by the model. The estimated equation is considered as an equation of very good fit.
  • The overall model is statistically significant as f value is higher (116.22) and more significant at 1 % level. This indicates that the regressors SC and AG are significantly associated with dependent variable.

Model Specification III Nagarjuna Sagar Right Canal Power House 

         (Appendix Table: A3)

             *                                      *                                                     *

WHE = 6133.252+0.628 RL-58.029 SC+0.414EL+37.493TW+486.057 AG

          (7.314)                        (6.063)                                          (16.232)

N= 166, R2= 0.78, f value = 116.22

  • The estimated regression coefficients indicate that the best independent variables that have significant effect are storage capacity and actual generation with significant levels at 1 % for each of independent variables.
  • The t-ratio of regression coefficients is highly significant with two independent variables namely storage capacity and actual generation. The relation between water withdrawals and Storage capacity and actual generation in the sample holds good as the t-value is greater than 2.58.
  • The t-ratio of regression coefficients is not at all significant for other independent variables such as reservoir level, storage capacity and evaporation losses.
  • The R2 is 0.78. It means that the independent variables SC and AG can explain 78 % variation in the dependent variable and remaining 22 % variation is unexplained by the model. The estimated equation is considered as the equation of very good fit.
  • The overall model is statistically significant as f value is higher (116.22) and more significant at 1 % level. This indicates that the regressors are significantly associated with dependent variable (WD)

Model Specification IV Srisailam Left Bank Power House

                  (Appendix Table: A4)

                                                                *                          *

WHE = -2243.501-0.766RE+1.195SC+57.47AG+0.592EL+4.24TW+0.000IF

                              (-2.27)                         (18.81)                     (2.69)

N= 58   , R2= 0.96, f value = 221.872

  • The estimated regression coefficients indicate that the best independent variables that have significant effect are actual generation and tail water level with significant levels at 1 % and 10 % for independent variables.
  • The t-ratio of regression coefficients is highly significant with three independent variables namely reservoir elevation, actual generation and tail water level. The t-ratio value is greater than 1.96 value for reservoir level and greater than 2.58 value for actual generation and tail water level. This indicates that the relation between WD and independent variables AG and reservoir elevation observed in the sample holds good.
  • The t- ratio of regression coefficients is not at all significant for other independent variables such as evaporation losses and inflows.
  • The R2 is 0.96. It means that the independent variables reservoir level, actual generation and tail water level can explain 96 % of variation in the dependent variable and remaining 4% is unexplained by the model. Thus the estimated regression coefficient is considered as an equation of very good fit.
  • The overall model is statistically significant as f value is higher (221.872) and more significant at 1 % level. This indicates that the regressors AG and TW are significantly associated with dependent variable. (WD)

 

Model Specification V Srisailam Right Bank Power House

                   (Appendix Table: A5)

                 *                        *        *

Y = -7630.380-1.78RE+0SC+56AG+0.051EL+0.627TW+0.289GH

              (-4.199)             (-4.3)  (122.65)

  N= 138    , R2    = 0.99 and f value = 4.59

  • The estimated regression coefficients indicate that the best independent variables that have a significant effect are storage capacity and actual generation with significant levels at 1 % level each of independent variable.
  • The t-ratio of regression coefficients is highly significant with two independent variables namely storage capacity and actual generation. The t- ratio value is greater than 2.58 for SC and AG that indicates that the relation between WD and independent variables SC and AG holds good.
  • The t- ratios of regression coefficients is not at all significant for other independent variables such as evaporation losses, tail water level and gross head.
  • The R2 is 0.99. It means that the independent variables such as storage capacity and actual generation can explain 99 % variation in the dependent variable and remaining 1 % is unexplained by the model. Thus the estimated regression coefficient is considered as an equation of very good fit.
  • The overall relationship was statistically significant as f value is 4.59 and more significant at 1 % level. This indicates that the regressors SC and AG are significantly associated with WD.

Thermal based Electric Energy Power Plants

Model Specification VI Kothagudaem Thermal Power Plant O &M

      (Appendix Table: A6)

                                                     *                                                     *   

Y= -787978.047 + 1.021CC-2.130DB-12.190CD+146.699 OT +1.152 AD+4616.497 CT-817.112AG

                              (3.259)                                                        (3.841)

N= 84, R2 = 0.55, f value = 13.710

  • The estimated regression coefficients indicate that the best explanatory (independent) variables with significant effect on quantity of water with drawals per Kilowatt hour are condenser cooling with cooling towers (Natural Draft cooling system) and ash disposal with significant levels of 5 % and 1 % level.
  • The estimated equation indicates that the total thermal water withdrawals are elastic with respect to condenser cooling and ash disposal. This kind of positive relationship indicates that the thermal water withdrawals are responsive to changes in condenser cooling and ash disposal.
  • The t-ratio of regression coefficients have expected signs and is highly statistically significant for two independent variables namely condenser cooling with Natural Draft CTs and Ash Disposal. The t ratio value is greater than 2.58.
  • This indicates that the importance of technological alternatives (i.e. Condenser Cooling with natural draft CTs) is the significant determinant of water withdrawals. Next ash disposal takes second place as significant determinant of total thermal water withdrawals.
  • The t-ratio of regression coefficient is not at all significant for other independent variables such as DM and Boiler feedback, colony domestic, others (Drinking, Sanitation, Fire fighting, Back Wash Filter), cooling temperature and actual  electric energy generation.
  • The R2 is 0.55. It means that the independent variables such as condenser cooling and ash disposal can explain 55 % of variation in the dependent variable and remaining 45 % variation is unexplained by the model. The estimated equation is considered as good fit.
  • The overall model is statistically significant as f value is higher (13.710) and highly significant at 1 % level. This indicates that the regressor’s condenser cooling with Natural Draft CT’s and Ash Disposal are significantly associated with dependent variable WDs.

Model Specification VII Kothagudaem Thermal Power Station Stage V

          (Appendix Table: A7)

                                   *                *

Y= 98233.879+0.873 CC+1.186AD+0.111 DB-1688.373CT+32.019 AG

                               (20.91)       (15.247)

              N= 83, R2= 0.97, f value = 706.164

  • The estimated regression coefficients indicate that the best independent variables with significant effect on quantity of WD per million tonnes are Condenser cooling and ash disposal with significant levels at 1% level each.
  • The t-ratio of regression coefficients have expected signs and is highly statistically significant for two independent variables namely Condenser cooling with natural draft CT’s and Actual Generation. The t- ratio value is greater than 2.58. Here the significant determinant of WD’s are CC with natural draft CT’s. Next comes ash disposal as second good determinant.
  • The t- ratio of regression coefficient is not at all significant for other independent variables such as BF & DM, cooling temperature and Energy Generation.
  • The R2 is 0.97. It means that independent variables such as CC and AD can explain 97 % of variation in the dependent variable (Water withdrawal) and remaining 3 % variation are unexplained by the model. Thus the estimated equation is considered as an equation of very good fit.
  • The overall model is statistically significant as f value is higher (706.164) and highly significant at 1 % level. This indicates that the regressors condenser cooling with NDCT’s and Ash Disposal are significantly associated with Water withdrawal’s (Dependent Variable)

Model Specification VIII Rayalaseema Thermal Power Plant

          (Appendix Table: A8)

                           *

Y = 10334.674+0.745 CC+8.725 BF+0.847 AS-4.143 AG-145.408 CT

     (2.677)                (3.007)

N= 35, R2 = 0.87 and f value = 33.145

  • The estimated regression coefficients indicate that the best independent variables with significant effect on quantity of Water Withdrawal Condenser cooling with significant levels at 5%.
  • The t-ratio of regression coefficients have expected signs and is highly statistically significant for one independent variables namely Condenser cooling with natural draft CT’s .The t- ratio value is greater than 2.58. Here the significant determinant of WD’s are CC with natural draft CT’s.
  • The t- ratio of regression coefficient is not at all significant for other independent variables such as BF & DM, Ash Disposal cooling temperature and Energy Generation.
  • The R2 is 0.87. It means that independent variables such as CC can explain 87 % of variation in the dependent variable (WD) and remaining 13 % variation are unexplained by the model. Thus the estimated equation is considered as an equation of very good fit.
  • The over all model is statistically significant as f value is higher (33.145) and highly significant at 1 % level. This indicates that the regressors condenser cooling with NDCT’s are significantly associated with WD’s (Dependent Variable)

Model Specification IX Narla Tata Rao Thermal Power Plant

                     (Appendix Table: A9)

                          *                               *   

Y = 139993.709 + 1.002CC -0.863CD + 1.031 AS- 373.483 CT- 56.843 AG

                                    (1277.966)                 (19.88)

N=      R2 = 1.00, f value = 907849.564

  • The estimated regression coefficients indicate that the best explanatory (independent) variables with significant effect on quantity of water with drawals per Kilowatt hour are condenser cooling with cooling towers ( Induced l Draft cooling system) and ash disposal with significant levels of 1 % and 1 % level.
  • The estimated equation indicates that the total thermal water withdrawals are elastic with respect to condenser cooling and ash disposal. This kind of positive relationship indicates that the thermal water withdrawals are responsive to changes in condenser cooling and ash disposal.
  • The t-ratio of regression coefficients have expected signs and is highly statistically significant for two independent variables namely condenser cooling with Induced Draft CTs and Ash Disposal. The t ratio value is greater than 2.58.
  • This indicates that the importance of technological alternatives (i.e. Condenser Cooling with Induced draft CTs) is the significant determinant of water withdrawals. Next ash disposal takes second place as significant determinant of total thermal water withdrawals.
  • The t-ratio of regression coefficient is not at all significant for other independent variables such as, colony domestic, cooling temperature and actual electric energy generation.
  • The R2 is 1.00. It means that the independent variables such as condenser cooling and ash disposal can explain 100 % of variation in the dependent variable. This shows that we have accounted for almost all the variability with the variables specified in the model. The estimated equation is considered as very good fit.
  • The overall model is statistically significant as f value is higher (907849.564) and highly significant at 1 % level. This indicates that the regressor’s condenser cooling with Induced Draft CT’s and Ash Disposal are significantly associated with dependent variable WDs.

The pertinent conclusion of this study is there may be significant potential for water conservation after having identified the significant determinants of total thermal water withdrawals i.e. condenser cooling and ash disposal. The choice of explanatory variable for eg: Induced draft and natural draft technological innovation was able to address the significant changes of water withdrawals.

5.0  CONCLUSION AND RECOMMENDATION

The thermal and hydel power plants sustenance is very much under stake due to major reason of fresh water shortages in power generation. The most sophisticated technology followed in advanced countries namely Concentrated solar thermal power integrated with combined system of conventional steam plant, Fresnel Solar Collector and  Solar Flower Tower can be used as a replica even in developing countries like India though not cost effective in order to counteract the water shortage problem

REFERENCES

Benedy Kt Dziegielewski, Thomas Bik (August 2006), “ Water Use Bench Marks for Thermo Electric Power Generation” Project report, Southern Illinois University, United States

Geological Survey, 2004, USGS National Competitive Grants Program.

Gbadebo Oladosu, Stan Hadley, Vogt D.P. and Wilbanks J.J. (September, 2006), “Electricity

Generation and Water Related Constraints: An Empirical Analysis of Four South Eastern

States”, Oak Ridge National Laboratory, Oak Ridge Tennessee.

Sitanon Jesdapipat and Siriporon Kiratikarnkul, “ Surrogate pricing of water: The Case of micro Hydro –Electricity Co-operatives in Northern Thailand”.

 Xiaoying Yang & Benedy Kt Dziegielewski (February,2007), “ Water Use by Thermo Electric power plants in the United states” Journal of the American Water Resources Association, Vol 43, No.1.

“Estimating Water Use in United States: A new Paradigm for National Use Water Use Information Programme”(2002),

http://books.nap.edu/openbook.php?record_id=10484&page=95

 

Data Sources

Annual Report on the Working of SEBs and Electricity Departments, Planning Commission, Various Issues

Administrative Reports of Andhra Pradesh Generation Corporation of India Limited (APGENCO),Various Issues. Field Level data of selected thermal and hydel power stations authenticated  by APGENCO.

APPENDIX TABLES

Table: A1: Nagarjuna Sagar Main Power House

Variables Entered/Removed  
Model Variables Entered Variables Removed Method  
1 acutal_generation, tail_water_level, Reser_elevation, Gross_feet, Storage_capacitya . Enter  
a. All requested variables entered.    
b. Dependent Variable: water_discharge_cums  
Model Summary  
Model R R Square Adjusted R Square Std. Error of the Estimate  
1 .997a .995 .995 512.92868  
a. Predictors: (Constant), acutal_generation, tail_water_level, Reser_elevation, Gross_feet, Storage capacity  
ANOVAb
Model Sum of Squares df Mean Square F Sig.
1 Regression 7291771208.745 5 1458354241.749 5543.053 .000a
Residual 38675087.446 147 263095.833    
Total 7330446296.191 152      
a. Predictors: (Constant), acutal_generation, tail_water_level, Reser_elevation, Gross_feet, Storage capacity
b. Dependent Variable: water_discharge_cums      
 

Coefficientsa

 
Model Unstandardized Coefficients Standardized Coefficients t Sig.  
B Std. Error Beta  
1 (Constant) -146.238 1555.816   -.094 .925  
Reser_elevation -.080 .093 -.012 -.865 .389  
Storage capacity -.258 .065 -.091 -3.966 .000  
tail_water_level .350 .111 .031 3.144 .002  
Gross_feet .133 .094 .026 1.419 .158  
acutal_generation 50.669 .423 1.041 119.869 .000  
a. Dependent Variable: water_discharge_cums        

Table: A 2 Nagarjuna Sagar Left Canal Power House

Variables Entered/Removedb  
Model Variables Entered Variables Removed Method  
1 evaporation, energe_bus, twl_ft, storage capacity, reservior_levela . Enter  
a. All requested variables entered.    
b. Dependent Variable: water_drawals  
Model Summary  
Model R R Square Adjusted R Square Std. Error of the Estimate  
1 .864a .747 .739 2350.84646  
a. Predictors: (Constant), evaporation, energe_bus, twl_ft, storage capacity, reservior_level  
 

ANOVAb

Model Sum of Squares df Mean Square F Sig.
1 Regression 2626964399.664 5 525392879.933 95.068 .000a
Residual 889763133.646 161 5526479.091    
Total 3516727533.310 166      
a. Predictors: (Constant), evaporation, energy bus, twl_ft, storage capacity, reservior_level  
b. Dependent Variable: water_drawals        
Coefficientsa  
Model Unstandardized Coefficients Standardized Coefficients t Sig.  
B Std. Error Beta  
1 (Constant) 1660.770 501.102   3.314 .001  
reservior_level -3.516 3.411 -.157 -1.031 .304  
storage capacity -21.705 5.219 -.538 -4.159 .000  
twl_ft 9.653 2.510 .394 3.846 .000  
energy bus 491.286 30.765 .987 15.969 .000  
evaporation .130 .508 .015 .255 .799  
a. Dependent Variable: water_drawals        

Table: A3 Nagarjuna Sagar Right Canal Power House

Model Variables Entered      
1 generation bus, reservior_level, evaporation, storage capacity, tailwaterlevela      
b. Dependent Variable: water_drawals

Model Summary

 
Model R R Square Adjusted R Square Std. Error of the Estimate  
1 .885a .784 .777 3767.05581  
a. Predictors: (Constant), generation bus, reservior_level, evaporation, storage capacity, tailwaterlevel  
ANOVAb
Model Sum of Squares df Mean Square F Sig.
1 Regression 8246365913.182 5 1649273182.636 116.222 .000a
Residual 2270513515.133 160 14190709.470    
Total 10516879428.315 165      
a. Predictors: (Constant), generation bus, reservior_level, evaporation, storage capacity, tailwaterlevel  
b. Dependent Variable: water_drawals        
Coefficientsa  
Model Unstandardized Coefficients Standardized Coefficients t Sig.  
B Std. Error Beta  
1 (Constant) 6133.252 838.604   7.314 .000  
reservior_level .628 7.571 .016 .083 .934  
storage capacity -58.029 9.570 -.832 -6.063 .000  
Evaporation .414 .810 .027 .511 .610  
Tailwaterlevel 37.493 21.598 .263 1.736 .084  
generation bus 486.057 29.945 1.045 16.232 .000  
a. Dependent Variable: water_drawals        

Table:  A4 Srisailam Left Canal Power House

Variables Entered/Removedb  
Model Variables Entered Variables Removed Method  
1 inflow, Reservoir, evaporat, Actual generation, Tail water, storage_capacitya . Enter  
a. All requested variables entered.    
b. Dependent Variable: water_withdra  
Model Summary  
Model R R Square Adjusted R Square Std. Error of the Estimate  
1 .981a .963 .959 1454.18057  
a. Predictors: (Constant), inflow, Reservoir, evaporat, Actual generation, Tail water, storage capacity  
                                                                                   ANOVAb  
Model Sum of Squares df Mean Square F Sig.  
1 Regression 2815082375.894 6 4.692E8 221.872 .000a  
Residual 107846697.597 51 2114641.129      
Total 2922929073.491 57        
a. Predictors: (Constant), inflow, Reservoir, evaporat, Actual generation, Tail water, storage capacity    
b. Dependent Variable: water_withdra          
Coefficientsa
Model Unstandardized Coefficients Standardized Coefficients t Sig.
B Std. Error Beta
1 (Constant) -2243.501 2527.275   -.888 .379
Reservoir -.766 .337 -.239 -2.272 .027
storage capacity 1.195E-6 .000 .000 .004 .997
Actual generation 57.476 3.055 .953 18.814 .000
evaporat .592 .939 .081 .631 .531
Tail water 4.237 1.572 .248 2.695 .010
inflow .000 .002 -.017 -.339 .736
a. Dependent Variable: water_withdra        

Table: A5 Srisailam Right Canal Power House

Model Variables Entered Variables Removed Method  
1 Gross head, Tailwaterlevel, actual generation, Evaporation, storage, Reservoir . Enter  
a. All requested variables entered.    
b. Dependent Variable: water withdrawals  
 

Model Summary

Model R R Square Adjusted R Square Std. Error of the Estimate
1 .998a .995 .995 631.39218
a. Predictors: (Constant), Gross head, Tailwaterlevel, actual generation, Evaporation, storage, Reservoir

ANOVAb  
Model Sum of Squares df Mean Square F Sig.  
1 Regression 1.099E10 6 1.832E9 4.596E3 .000a  
Residual 5.222E7 131 398656.090      
Total 1.105E10 137        
a. Predictors: (Constant), Gross head, Tailwaterlevel, actual generation, Evaporation, storage, Reservoir  
b. Dependent Variable: water withdrawals        
Coefficientsa
Model Unstandardized Coefficients Standardized Coefficients t Sig.
B Std. Error Beta
1 (Constant) -7630.380 1817.341   -4.199 .000
Reservoir -.178 .322 -.027 -.553 .581
storage .000 .000 -.068 -4.288 .000
actual generation 56.314 .459 1.022 122.651 .000
Evaporation .051 .139 .005 .365 .716
Tailwaterlevel .627 .334 .059 1.874 .063
Gross head .289 .320 .036 .904 .368
a. Dependent Variable: water withdrawals      

Table: A6 Kothagudaem Thermal Power Plant O &M

Variables Entered/Removedb  
Model Variables Entered Variables Removed Method  
1 energy generation , cooling temp, DM Water & Boiler Feed back , Ash Disposal , Condenser Cooling , Colony domestic , (Drin, Sani, Firefigh, Backwarhfiler) a . Enter  
a. All requested variables entered.    
b. Dependent Variable: Total water consumption  
 

Model Summary

 
Model R R Square Adjusted R Square Std. Error of the Estimate  
1 .747a .558 .517 289298.132  
a. Predictors: (Constant), energy generation , cooling temp, DM Water & Boiler Feed back , Ash Disposal , Condenser Cooling , Colony domestic , (Drin, Sani, Firefigh, Backwarhfiler)  
ANOVAb  
Model Sum of Squares df Mean Square F Sig.  
1 Regression 8.032E12 7 1.147E12 13.710 .000a  
Residual 6.361E12 76 8.369E10      
Total 1.439E13 83        
a.     Predictors: (Constant), energy generation , cooling temp, DM Water & Boiler Feed back , Ash Disposal , Condenser Cooling , Colony domestic , (Drin, Sani, Firefigh, Backwarhfiler)  
       
Coefficientsa
Model Unstandardized Coefficients Standardized Coefficients t Sig.
B Std. Error Beta
1 (Constant) -787978.047 1.334E6   -.591 .557
Condenser Cooling 1.021 .313 .551 3.259 .002
DM Water & Boiler Feed back -2.130 5.717 -.038 -.373 .710
Colony domestic -12.190 15.642 -.250 -.779 .438
(Drin, Sani, Firefigh, Backwarhfiler) 146.699 201.477 .467 .728 .469
Ash Disposal 1.152 .300 .409 3.841 .000
cooling temp 4616.497 10000.955 .039 .462 .646
energy generation -817.112 1096.318 -.295 -.745 .458
a. Dependent Variable: Total water consumption      

Table:  A7 Kothagudaem Thermal Power Plant Stage V

  Variables Entered/Removedb  
  Model Variables Entered Variables Removed Method  
  1 Energy Generation, ASH DIS-POSAL (MT), Cooling Temperature , Boiled Feed and DM plant Regeneration, COOLING TOWER MAKEUP        (MT)a . Enter  
  a. All requested variables entered.    
  b. Dependent Variable: TOTAL CONS.  (MT)  
  Model Summary  
  Model R R Square Adjusted R Square Std. Error of the Estimate  
  1 .989a .979 .977 64726.513  
  a. Predictors: (Constant), Energy Generation, ASH DIS-POSAL (MT), Cooling Temperature , Boiled Feed and DM plant Regeneration, COOLING TOWER MAKEUP        (MT)  
 

ANOVAb

Model Sum of Squares df Mean Square F Sig.
1 Regression 14792454121098.932 5 2958490824219.786 706.164 .000a
Residual 322593153570.889 77 4189521474.947    
Total 15115047274669.820 82      
a. Predictors: (Constant), Energy Generation, ASH DIS-POSAL (MT), Cooling Temperature , Boiled Feed and DM plant Regeneration, COOLING TOWER MAKEUP        (MT)
b. Dependent Variable: TOTAL CONS.  (MT)      
  Coefficientsa  
  Model Unstandardized Coefficients Standardized Coefficients t Sig.  
  B Std. Error Beta  
  1 (Constant) 98233.879 76676.230   1.281 .204  
  COOLING TOWER MAKEUP        (MT) .873 .042 .577 20.912 .000  
  ASH DIS-POSAL (MT) 1.186 .078 .484 15.247 .000  
  Boiled Feed and DM plant Regeneration .111 .978 .003 .114 .910  
  Cooling Temperature -1688.373 2158.260 -.014 -.782 .436  
  Energy Generation 32.019 115.619 .005 .277 .783  
  a. Dependent Variable: TOTAL CONS.  (MT)          

Table: A 8 Rayalaseema Thermal Power Plant

  Variables Entered/Removedb  
  Model Variables Entered Variables Removed Method  
  1 Cooling Temp, Ash slurry, Actual Generation, Power Generation, Boiler feed, Condenser cooling, BCWa . Enter  
  a. All requested variables entered.    
  b. Dependent Variable: Water consumption  
  Model Summary  
  Model R R Square Adjusted R Square Std. Error of the Estimate  
  1 .934a .873 .846 1324.085  
  a. Predictors: (Constant), Cooling Temp, Ash slurry, Actual Generation, Power Generation, Boiler feed, Condenser cooling, BCW  
  ANOVAb  
  Model Sum of Squares df Mean Square F Sig.  
  1 Regression 3.487E8 6 5.811E7 33.145 .000a  
  Residual 5.084E7 29 1753200.788      
  Total 3.995E8 35        
  a. Predictors: (Constant), Cooling Temp, Ash slurry, Actual Generation, Power Generation, Boiler feed, Condenser cooling, BCW  
Coefficientsa
Model Unstandardized Coefficients Standardized Coefficients t Sig.
B Std. Error Beta
1 (Constant) 10334.674 3861.078   2.677 .012
Condenser cooling, BCW .745 .248 .432 3.007 .005
Boiler feed 8.725 4.628 .244 1.885 .069
Ash slurry .847 .501 .230 1.692 .101
Power Generation -.595 .388 -.138 -1.532 .136
Actual Generation -4.143 5.478 -.077 -.756 .456
Cooling Temp -145.408 94.141 -.109 -1.545 .133
a. Dependent Variable: Water consumption        

Table : A 9 Narla Tata Rao Thermal Power Plant

  Variables Entered/Removedb  
  Model Variables Entered Variables Removed Method  
  1 Energy Generation, Condenser cooling & BCW (KL), Cooling Temperature , Ash slurry water (KL), Colony Domestic (KL)a . Enter  
  a. All requested variables entered.    
  b. Dependent Variable: Totalwaterconsumption  
  Model Summary  
  Model R R Square Adjusted R Square Std. Error of the Estimate  
  1 1.000a 1.000 1.000 50290.302  
  a. Predictors: (Constant), Energy Generation, Condenser cooling & BCW (KL), Cooling Temperature , Ash slurry water (KL), Colony Domestic (KL)  
ANOVAb
Model Sum of Squares df Mean Square F Sig.
1 Regression 11480277367590772.000 5 2296055473518154.000 907849.564 .000a
Residual 42994946072.977 17 2529114474.881    
Total 11480320362536844.000 22      
a. Predictors: (Constant), Energy Generation, Condenser cooling & BCW (KL), Cooling Temperature , Ash slurry water (KL), Colony Domestic (KL)
b. Dependent Variable: Totalwaterconsumption      
  Coefficientsa  
  Model Unstandardized Coefficients Standardized Coefficients t Sig.  
  B Std. Error Beta  
  1 (Constant) 139993.709 137540.088   1.018 .323  
  Condenser cooling & BCW (KL) 1.002 .001 .987 1277.966 .000  
  Colony Domestic (KL) -.863 .584 -.001 -1.476 .158  
  Ash slurry water (KL) 1.031 .052 .018 19.879 .000  
  Cooling Temperature -373.483 3763.081 .000 -.099 .922  
  Energy Generation -56.843 138.469 .000 -.411 .687  
  a. Dependent Variable: Totalwaterconsumption        

Econometric Competencies and Entrepreneurship Development 

Adebayo G ADEBAYO

Department of Accountancy

Rufus Giwa (Formally Ondo State) Polytechnic.

Owo, Ondo State, Nigeria

Abstract

This study is designed specifically to demonstrate the application of econometrics or quantitative analysis especially in helping the numerous small and medium enterprises in Nigeria in critical decision making. An Agro-business labour saving fabricating firm in Nigeria was selected as a case and pilot study for all other small or medium enterprises fabricates labour saving machines such as the cassava frying machine (CFM) and palm-oil extracting machine (PEM). The agro-business firm also fabricate cassava grater (GRT) and appliances (APP). The entrepreneur is worried on some critical problems. First, whether these special offers would affect the sale of the major products CFM and PEM since the same customers buy the major products and the special offers. This implies that money spent on special offers will not be spent on CFM and/or PEM. An increase in the sales of special orders may correspond to a decrease in the sale of CFM and PEM. Second is what would be the total sales taking into consideration especially the seasonal fluctuations and third how to identify existing customers who are most likely to respond to proposed improved offer on CFM and PEM. This is important as the Firm fabricates these products on demand. Three models were designed to find solution to each of the problems. The first model was the two-stage least square regression. Findings revealed that the special offer sales GRATER and APPLIANCES) had no negative effect on the sales of the major products (CDM and PEM). All the products significantly contributed to the total sales. The second model was forecasting. The model satisfied forecasting requirements and was able to forecast total sales from April to December 2016 taking into consideration seasonal variations referred to as fluctuations. The third model is the recency, frequency and monetary (RFM) analysis. This marketing tool is used to classify customers according to how recent they patronize, how often and how much is involved in individual customer’s cumulative patronage. The RFM analysis carried out on the customers identified the firm’s customers that would likely respond to new offer. An RFM score of 300 and above qualified a customer to be selected. Part of the recommendations was that entrepreneurs should avail themselves of the decision making tools for better management of their enterprises.

 Keywords: 

 Introduction

The world is facing many economic challenges and issues. These do not isolate the developed economies. Both are debt ridden, with regional economic imbalances and geo-political challenges. There is general economic meltdown in the world market. The Nigeria economy has been acutely affected because of the fall in the price of crude oil in the world market as a result of these economic imbalances and trade policies that are not conducive to Nigerian oil market. Since revenue from crude oil takes about 90% of the Federal government total revenue, there is the critical need to raise non-oil revenue to ensure fiscal sustainability while maintaining infrastructure and social spending.

The Federal government has taken a bold step towards revamping agriculture and overhauling its solid mineral resources. From an entrepreneurial perspective, the present economic meltdown in Nigeria would eventually be a blessing in disguise. The Central Bank of Nigeria has been instructed by President Buhari to create a “synergy” and organize soft loans to agro-based industries and other export businesses.

The main objectives of the 2016 Buhari government’s budget are to make the “synergy” work among all the different players in the country’s economy. These include the banking system, financial institutions, government entities, regulators and other arms of the government.

  • Entrepreneurial Development.

The credibility of the Buhari government among the Nigerian populace as a result of his zero tolerance to corruption and his “Big Bang” [a rapid reform which is economically necessary as a result of severe macroeconomic imbalances (Gelb, Jefferson and Singh 1993) such as this period of economic crisis in Nigeria] approach to major economic reforms, has spurred many investors into agro-based industries. They believe that the government meant business.

One of these respondents is a medium scale firm in Nigeria that fabricates machines to boost agricultural produce. The Firm has recently reactivated two of its machines-the Cassava Frying Machine (CFM) and the Automated Palm oil Extracting Machine (PEM)

  • Objectives of the Firm

The major objectives of the Firm in fabricating these labour saving machines is the issue of health hazard on the one hand. Many local manual cassava frying and palm oil producers especially women, had been subjected to untimely death due to incessant heat from the local frying system and the palm oil production. These machines would reduce drastically the feminine life wasted on daily basis. On the other hand, these machines will boost agricultural produce of “GARI”(a local name for the fine grain output from the frying process of cassava) and palm oil to contribute to increase the recent low GDP rate in Nigeria. [Economic growth in the last quarter of 2015 was 2.1% while total growth in the year was 2.8%, the slowest since 1999 to date (NBS, 2016). This statistics seems to toe the line of the global GDP growth projection of 2.5% which is 0.3% point less than November 2015 outlook (GEO, 2016)]. Therefore any entrepreneurial effort to boost the Nigerian GDP at this trying period is a right decision in the right direction.

  • The Cassava Frying Machine

The CFM is powered by electricity and is capable of frying about 5-10-kg of already peeled, washed and had been cut into smaller sizes and loaded into the machine drum. The machine grinds the cassava, presses it cause fermentation and fry the cassava into very fine grains. Adjustments by the use of some special appliances sold by the firm to its customers may cause the machine to dry cassava from the normal “GARI” into smoother form or into powder. It is an automated machine with 100% local components. A single CFM costs N45, 000 ($225)

  • The Automatic Palm oil Extracting Machine..

The PEM is an automated machine that produces fine, clear, well heated palm oil. Palm fruits are removed from the bunch after some period for partial fermentation, washed and then loaded into the machine tank or drum to the brim. The machine twists and separate kernels from tissues, extract the paste and heat into fine glossy oil. The slag is released from an outlet. It is also powered by electricity. The machine is made with 90% local components, that is, 10% components have to be imported. A single machine costs N50, 000 ($250), about N5000 ($25) more than CFM probably as a result of the cost of the imported components.

  • Statement of the Problem.

The two machines fabricated by the firm are the Cassava Frying Machine (CFM) and Palm oil Extracting (PEM) and are sold to customers on demand. Apart from these machines, there are two special offers that are also sold. These are grater (GRT) and appliances (APP). The APP is a device to enhance either the CFM or PEM, especially as a power saving device, at the customers’ option and is sold at the rate of N12, 000 per unit. These appliances are capable of making adjustments possible to CFM and PEM and other agro-based machines.  The GRT powered by electricity, the pealed, and washed cassava are loaded into its receptor and it grinds cassava very well. This is sold at the rate of N15, 000 per unit. Every month the Firm makes these special offers to customers who need the APP on previously bought machines or on a proposed purchase of CFM and /or PEM. The GRT is mostly purchased by customers who could not afford CFM. The firm is now concerned about the following problems:

  1. Whether these special offers would affect the sale of the major products CFM and PEM since the same customers buy the major products and the special offers. This implies that money spent on special offers will not be spent on CFM and/or PEM. An increase in the sales of special orders may correspond to a decrease in the sale of CFM and PEM.
  2. How to make a good forecast of the total sales from major products and the special offers.
  3. How to identify existing customers who are most likely to respond to proposed improved offer on CFM and PEM. This is important as the Firm fabricates these products on demand.
  • Objectives of the Study.

The primary objective of this study is to underscore the importance of econometric or quantitative analysis in solving most of the problems of entrepreneurs and hence enhance entrepreneurship development in Nigeria. In realization of this objective, the study had focused on helping to collect all relevant data on the Firm’s customers. These include each customer’s date of transactions with the Firm, amount of purchases each time, total number of transaction and the most recent transaction. There will also be collection of data on total monthly sales on CFM, PEM, APP and GRT for the past 51 months. Other secondary objective, in addition are:

  1. To create compactible models to find solution to each of the Firm’s area of concern.
  2. To discuss the findings and give expert recommendations on the findings.

  1. Review of Related Literature

2.1 The Nigerian Cassava

Cassava is well known as manihot esculenta or manilot utilissima (Yakasi, 2010). In Nigeria, cassava is grown in all the ecological zones andit is planted all the year round on the availability of moisture (Odoemenem and Otanma, 2011). Production is vital to the economy of Nigeria as the country is the world’s largest producer of the commodity. The crop is produced in 24 of the country’s 36 states. In 1999, Nigeria produced 33 million tonnes, while a decade later, it produced approximately 45 million tonnes, which is almost 19% of production in the world. The average yield per hectare is 10.6 tonnes.(Wikipedia, n.d.)

In Nigeria, cassava production is well-developed as an organized agricultural crop. It has well- established multiplication and processing techniques for food products and cattle feed. Cassava is processed in many processing centres and fabricating enterprises set up in the country. Cassava is used in the preparation of several household foods and derivatives such as paste, biscuits, bread sagos and sauce. Its starch is for industrial use such as baby food, jelly, custard poeders and confectioneries (Echebiri and Edeba, 2008).  Roots or leaves are made into flours. Flours are of three types, yellow garri, white garri, or intermediate colour. These varieties are a matter of choice and traditional attachment. Therefore it may be erroneous to classify any type as the best product in Nigeria. Its other products are as dry extraction of starch, glue or adhesives, modified starch in pharmaceutical as dextrines, as processing inputs, as industrial starch for drilling, and processed foods.

 2.2 Palm Oil in Nigeria

 

Palm oil is as old as Nigeria itself and has been an important subsistence, but until recently a supportive factor in the diet of many Nigerians. Palm oil is the world’s largest source of edible oil, accounting for 38.5 million tonnes or 25% of the global edible oil and fat production (MPOC, 2007). Palm oil is a product extracted from the fleshy mesocarp of the palm fruit (Elaeis guineensis). The global demand for palm oil is growing thus, the crop cultivation serves as a means of livelihood for many rural families, and indeed it is in the farming culture of millions of people in the country. Akanbge et al (2011), referred to this product as capable of having multiple values, a feature that underscores its acclaimed economic importance. Eventually oil graduated from domestic use to industrial application which had appreciated its production geometrically (Omereji,2005). Ekine and Onu(2008) estimated palm oil consumption of about two litres per a family of five per week for cooking. Today, consumption must have tripled since Nigerian house hold now uses palm oil beyond normal consumption. Palm oil is also an essential multipurpose raw material for both food and non-food industries (Armstrong, 1998). Palm oil is used in the manufacturing of margarine, soap candle, base for lipstick, waxes and polish bases in a condense form, confectionary (Embrandiri et at., 2011; Aghalino, 2000), and other uses in pharmaceuticals.

2.3 Forecasting

Because economic and business conditions vary over time, managers must find ways to keep abreast of the effects that such changes will have on their organizations. One technique that can aid in plan­ning for future needs is forecasting. Although numerous forecasting methods have been devised, they all have one common goal—to make predictions of future events so that projections can then be incorporated into the planning and strategy process.

2.3.1 Time-series forecasting meth­ods involve the projection of future values of a variable based entirely on the past and present obser­vations of that variable. Examples of economic or business time series are the monthly publication of the Consumer Price Index, the quarterly statements of gross domestic prod­uct (GDP), and the annually recorded total sales revenues of a particular company.(Levine et al, 2005)

2.3.2 Least-Squares Trend-Fitting and Forecasting. The component factor of a time series most often studied is trend. Trend is studied as an aid in making intermediate and long-range forecasting projections. As depicted in Figure 1 to obtain a visual impression of the overall long­term movements in a time series, a chart is constructed in which the observed data (dependent variable) are plotted on the vertical axis, and the time periods (independent variable) are plotted on the horizontal axis.(See figure 1 below)

The Forecasting add-on module provides two procedures for accomplishing the tasks of creating models and producing forecasts.

The Time Series Modeler procedure estimates exponential smoothing, univariate Autoregressive Integrated Moving Average (ARIMA), and multivariate ARIMA (or transfer function models) models for time series, and produces forecasts. The procedure includes an Expert Modeler that automatically identifies and estimates the best-fitting ARIMA or exponential smoothing model for one or more dependent variable series, thus eliminating the need to identify an appropriate model through trial and error. Alternatively, one can specify a custom ARIMA or exponential smoothing model.

AR(1)        = a first-order autoregressive to correct for residual serial correlation. It is regressing the dependent variable(s) with linear combination of its past values or lagged values.

MA(1)       = a first-order moving  average model ,i.e., regressing the dependent error with linear combination of its past error or lagged error. It also corrects serial correlation.

2.4 Research Questions.

The following research questions are formulated by the researcher

  1. What are the total monthly sales of the Firm for 51 months?
  2. How many are the numbers of customers of the Firm are their variable such as name, address, city, state- province, post code, gsm numbers, country, gender, age category are available?
  3. How can customers that would respond to new offer be identified?
  4. What is the forecast total sales from April to December 2016?

2.5 Research Hypotheses.

The following research hypotheses are formulated by the researcher at 5% level of significance.

  1. There will be no significant relationship between total sales of special offers and CDM sales.
  2. There will be no significant relationship between total sales of special offers and POE sales.
  3. There will be no significant relationship between total sales of special offers and APP sales.
  4. There will be no significant relationship between total sales of special offers and GRTsales.

 

  1. Methodology

 3.1 Data Collection

The data collected for this study is a demonstrative data only on behalf of the firm. It is characteristic of most small and medium enterprises of nearly the same status. This case study Firm is having about 90 customers. Sales records on CFM, PEM, APP and GRT were collected for 51 months (January 2012 to March 2016). In the Table below, the author computed the total sales for CFM, PEM, APP and GRT and special offer total sales (SPSALES). Others computed are discount on CDM at 3.5% from records and discount on PEM at 4.8%. A log discount on CFM and PEM and their lagged variables are automatically computed in the SPSS 21 and E-View 7.1 work files. The data are presented in Table 1 below.

 Table 1    Company Data for 51 Months – from January 2012 to March 2016

tsales cfm pem spsales grt app discfm dispem
N N N N N N N N
109.50

123.50

130.00

147.00

154.10

174.00

166.50

178.00

166.50

153.20

132.50

132.70

148.80

167.80

180.50

192.50

192.00

202.50

193.50

183.20

196.70

198.80

179.10

169.80

193.10

194.10

213.00

241.40

231.80

226.40

226.50

245.70

231.20

207.50

219.90

214.00

241.30

265.00

267.50

246.90

237.00

234.20

251.20

266.00

270.80

264.80

258.00

243.80

244.00

246.50

263.30

57.50

60.00

62.50

67.50

75.00

78.00

75.00

73.00

58.00

55.00

56.00

57.00

58.00

65.00

84.00

78.00

77.50

74.50

62.50

68.00

83.00

87.50

78.50

73.00

71.00

73.00

83.00

95.00

92.50

82.00

87.00

95.00

100.00

97.00

100.00

95.00

103.00

112.00

113.00

110.00

105.00

97.00

94.00

95.00

94.00

93.00

100.00

103.00

102.00

102.50

103.00

40.00

50.00

52.50

65.00

64.00

60.00

75.00

86.50

87.50

77.50

60.00

52.00

65.00

73.00

67.00

85.00

85.00

97.50

100.50

85.00

83.00

80.00

68.00

60.00

82.50

80.00

90.00

110.00

108.00

105.00

100.00

110.00

90.00

80.00

78.00

72.00

90.00

105.00

107.50

90.00

85.00

90.00

108.00

120.00

125.00

120.00

105.00

85.00

86.00

85.00

100.00

12.00

13.50

15.00

14.50

15.10

16.00

16.50

18.50

21.00

20.70

22.50

13.70

25.50

29.80

29.50

29.50

29.50

30.20

30.20

30.70

30.70

31.30

32.60

36.80

39.60

41.10

40.00

39.40

39.30

39.40

39.50

40.70

41.20

40.50

41.90

47.00

48.30

48.00

47.00

46.90

47.00

47.20

49.20

51.00

51.80

51.80

53.00

55.50

57.00

59.00

60.30

4.00

5.00

6.00

6.00

7.00

8.00

8.50

10.00

12.00

11.50

13.00

14.00

16.00

20.00

19.50

19.00

18.50

18.50

18.50

17.80

18.00

18.80

19.60

20.00

20.80

21.40

22.00

22.40

22.80

23.00

22.50

22.00

21.20

21.50

23.50

26.00

26.30

26.00

26.00

26.10

26.50

27.00

27.20

28.00

27.00

26.80

27.00

29.00

29.00

29.20

29.30

8.00

8.50

9.00

8.50

8.10

8.00

8.00

8.50

9.00

9.20

9.50

9.70

9.80

9.80

10.00

10.50

11.00

12.00

12.00

12.40

12.70

12.50

13.00

16.80

18.80

19.70

18.00

17.00

16.50

16.40

17.00

18.70

20.00

19.00

18.40

21.00

22.00

22.00

21.00

20.80

20.50

20.20

22.00

23.00

24.80

25.00

26.00

28.80

28.00

29.80

31.00

2.01

2.10

2.19

2.36

2.63

2.73

2.63

2.56

2.03

1.93

1.96

1.99

2.03

2.28

2.94

2.73

2.71

2.61

2.19

2.38

2.91

3.06

2.77

2.56

2.49

2.56

2.91

3.33

3.24

2.87

3.04

3.33

3.50

3.40

3.50

3.33

3.61

3.92

3.96

3.85

3.68

3.40

3.29

3.33

3.29

3.26

3.50

3.61

3.57

3.59

3.07

1.92

2.40

2.52

3.12

3.07

2.88

3.60

4.15

4.20

3.72

2.88

2.50

3.12

3.50

3.22

4.08

4.08

4.68

4.82

4.08

3.98

3.84

3.26

2.88

3.41

3.50

4.32

5.28

5.84

5.04

4.80

5.28

4.32

3.84

3.14

3.46

4.32

5.04

5.16

4.32

4.08

4.32

5.18

5.76

6.00

5.76

5.04

4.08

3.57

4.08

4.80

       *The average Sales discount on CFM is 3.5% and on PEM is 4.8%. No discounts for APP and GRT.

            The LAG variable for CFM and LAG for PEM are automatically Created Series in the SPSS 21 and E-                           View 7.1 work files.

    Figure 1    Graph of the Relationship between Total Sales, and the sales from Cassava Frying Machine, Palm oil Extracting Machine, Appliances and Grater

3.2 Models Specification

Three models are specified to the three major problems faced the Firm as stated under the statement of the problem. These are (1) Two-Stage Least Squares Regression (2) Forecasting Models and (3) The RFM Customer Analysis

 

3.2.1 Model 1.Two Stage Least Square Regression

A careful observation of the relationship between CFM, PEM and the special offers shows that there is a feedback loop between the response and the two major products which are predictors. One of the basic assumptions of the ordinary least-squares (OLS) regression model is that the values of the error terms are independent of the values of the predictors. When this “recursivity assumption” is broken, the two-stage least-squares (2SLS) model can help solve these problematic predictors. The 2SLS model assumes that there exist instruments, or secondary predictors, which are correlated with the problematic predictors but not with the error term.

Given the existence of instrument variables, the 2SLS model:

  1. Computes OLS models using the instrument variables as predictors and the problematic predictors as responses.
  2. The model-estimated values from stage 1 are then used in place of the actual values of the problematic predictors to compute an OLS model for the response of interest.

Fifty two months of sales information is collected. The file also includes a variable, special offer, displaying each month’s special offer, which has also been recorded into two indicator variables, Appliances offer and Grater offer that can be used as predictors in the regression procedures. Lastly, the monthly discounts (and log-discounts) offered to customers are also listed. Since the monthly discounts are chosen independent of special offer sales but do not affect CDM and POE sales, they should make good instrument variables. Additionally, the lagged CDM and POE should also make good instruments. The independent, predictors and instrumental variables are in the model description as in Table 2 below.

Table 2: Model Description

   Variables Type of Variable
SpecialOfferSales Dependent
CDM Predictor
POE Predictor
Appliances predictor & instrumental
Grater predictor & instrumental
Logdiccfm Instrumental
Logdispoe Instrumental

Special Offer Sales = α0 + α1CFM + α2POE + α 3APP + α4GRT + ε                                                        Eq 1

where

α 0             =    the intercept or constant term

α      α 4   =    the coefficients of both the predictors and instrumental variables

 ε            =    the stochastic error term

All other variables are as described in the model description in Table 2 above.

3.2.2 Model 2. Forecasting Models

The Model of Forecasting from an Equation, can be dynamic or Static. The static model is chosen because the static forecasting model performs a series of one-step ahead forecasts of the dependent variable:

For each observation in the forecast sample:

 yg+k = c(l) + c(2)xs+k+c(3)zs+k+c(4)ys+k1                                                         Eq 2

Such equation is always using the actual value of the lagged endogenous variable. This is translated into sales forecast of the Firm:

Total Sales    = βo + β1Total Sales (-1) + β2Pm Ar(1) + µi                                                 Eq 3

Where:

Total Sales        =     the total sales from CFM, POE, APP and GRT for 51 months. This is the dependent variable.

Total Sales (-1) = a lagged variable of the dependent variable. This is a one step ahead static forecasts that makes the static forecast more accurate than the dynamic forecast since, each period, the actual value of Total Sales(-1) is used in forming the forecast of Total Sales.

Pmi                  =     the period expressed in months with a total of 51 months. This is the independent variable.

  β 0                            =     the constant term or the model intercept.

  β1                   =     the coefficient of the lagged variable.

  β2                    =     the coefficient of the independent variable.

 µi                    =     the stochastic or error term

The tolal sales above is transformed into:

tsalesFp+k = Ф0 + Ф1 tsalesFp+k-1 2PMp+k + AR(1) +  ε                                                    Eq 4

after being subjected to the static forecasting model

where

tsalesF = total sales forecast

 tsalesFp+k-1 =   the previous month’s (lagged) sales to be added to current sales forecast.

Ф I              = constant and coefficients.

p                 = the base period (month) of start of forecast.

k                 = any month from the forecasting period (April to December 2016)

AR(1)        = a first-order autoregressive to correct for residual serial correlation. It is regressing the dependent variable(s) with linear combination of its past values or lagged values.  .

ε i               = the error term.

For seasonal adjustment of the forecast (fitted) sales.

tsalesfSA  = ⨍i(tsalesFi)                                                                                                     Eq 5

where

⨍i = multiplicative scoring factor for a 12 month period.

tsalesFi = total sales forecast for April to December.

The tsalesfSA  = the seasonally adjusted tsalesF for months (p52-60) i.e. 52, 53, 54, 55, 56, 57, 58, 59 and 60 for April, May, June, July, August, September, October, November and December.

The actual trend base is P51. In Table 1 the total sales corresponding to P51 is N263300. A forecast for p52-60 is required; i.e. April – December 2016.

Figure 3.  Graphical Relationship between Total Sales (tsales) and Fitted Sales (tsalesF)

3.2.3 Model 3.  RFM Analysis         

RFM (Recency, Frequency and Monetary) analysis is a direct marketing option that provides a set of tools designed to improve the results of direct marketing campaigns by identifying demographic, purchasing, and other characteristics that define various groups of consumers and targeting specific groups to maximize positive response rates.

It is a technique used to identify existing customers who are most likely to respond to a new offer. This technique is commonly used in direct marketing. RFM analysis is based on the following simple theory:

The most important factor in identifying customers who are likely to respond to a new offer is RECENCY. Customers who purchased more recently are more likely to purchase again than are customers who purchased further in the past.’The second most important factor is FREQUENCY. Customers who have made more purchases in the past are more likely to respond than are those who have made fewer purchases.

The third most important factor is total amount spent, which is referred to as MONETARY. Customers who have spent more (in total for all purchases) in the past are more likely to respond than those who have spent less.

How RFM Analysis Works

Customers are assigned a recency score based on date of most recent purchase or time interval since most recent purchase. This score is based on a simple ranking of recency values into a small number of categories. For example, if you use five categories, the customers with the most recent purchase dates receive a recency ranking of 5, and those with purchase dates furthest in the past receive a recency ranking of 1. The recency ranking for this Firm is based on the past 20 months as below:

Month Interval Ranking
Jan to Apr 2016 5
Sept to Dec 2015 4
May to Aug 2015 3
Jan to Apr 2015 2
Sept to Dec 2014 1

In a similar fashion, customers are then assigned a frequency ranking, with higher values representing a higher frequency of purchases. For example, in a five category ranking scheme, customers who purchase most often receive a frequency ranking of 5.

 

The number of times a customer made purchases up to a maximum of 5,(or simply, the Transaction Counts) represent frequency ranking for the Firm.

 

Finally, customers are ranked by monetary value, with the highest monetary values receiving the highest ranking. Continuing the five- category example, customers who have spent the most would receive a monetary ranking of 5. The monetary ranking for the firm is:

Naira Value of Purchases Ranking
N120,000 and above 5
N100,000 to N120,000 4
N75,000 to N100,000 3
N40,000 to N75,000 2
Less than 40,000 1

The result is four scores for each customer: recency, frequency, monetary, and combined RFM score, which is simply the three individual scores concatenated into a single value. The “best” customers (those most likely to respond to an offer) are those with the highest combined RFM scores. For example, in a five-category ranking, there is a total of 125 possible combined RFM scores, and the highest combined RFM score is 555.

 Results and Discussion

The results of the models had produced numerous tables in their outputs. The option of  table by table explanation and discussion had been taken.. Where appropriate, results had been discussed. Only the summary points need be discussed further. .Summary of the findings revealed that the special offer sales did not affect the sales of CFM and PEM. The assumption that there exist instruments, or secondary predictors, which are correlated with the problematic predictors but not with the error term may not hold. When CFM, PEM GRT AND APP were regressed on the total sales, they were all significant at less than 5%.

A multiplicative scoring factor to produce the total sales forecast with seasonal adjustments from April to December 2016.

The RFM analysis produced a combined RFM score for each customer at the concatenation of the three individual scores, computed as (recencyx100) + (frequencyx10) _ monetary. The recency, frequency, monetary score is 5 5 5 respectively. A customer must score at least 3 points for recency to qualify for customers that are likely to respond to new offer on CFM and PEM.

 

Conclusion and Recommendations

This study had been able to highlight the importance of econometric applicaton in business decision making especially for small and medium scale enterprises. Decision making is a prerogative of the entrepreneur but using the tools would help the effective management of their enterprises. I is important to add a caveat that professionals should be used and that the outcome of decision making tools are to assist entrepreneur only and should not be forced on them.

Notwithstanding, entrepreneurs are advised to avail themselves of the decision making tools from professionals with econometric competences. The present day business environment needs the sixth sense which business decision making tools afford entrepreneurs.

 

APPENDIX: (Al, A2 and A3 for Models 1, 2 and 3 respectively.)

 MODEL 1: TWO-STAGE LEAST SQUARES REGRESSION*

 

Table Al-1 The Lagged Variable Infusion into the Model

Series Name Case Number of Non-Missing No of Valid Creating
Values Cases Function
First Last
1 cfm_1 2 51 50 LAGS(cfm,1)
2 pem_1 2 51 50 LAGS(pem,1)

 

 

Table A1-2 Model Description

Type of Variable
                          Spsales Dependent
                                Cfm Predictor
                                Pem Predictor
Equation 1              Grt predictor & instrumental
                               App predictor & instrumenta  l
                       Logdiscfm instrumental
                      Loadispem instrumental

The model description table gives a summary of the model being fit. Variables specified as predictor will be regressed on the instrumental variables, and the model- estimate4d values will then be used in place of the actual values of these problematic predictors when computing the model for the dependent

 

Table A1-3 Model Summary

                                          Multiple R .995
                                           R Square .990
Equation 1
                             Adjusted R Square .989
                    Std. Error of the Estimate 1.410

The model summary table reports the strength of the relationship between the model and the dependent variable.

Multiple R, the multiple correlation coefficient, is the linear correlation between the observed and model- predicted values of the dependent variable. Its relatively high value indicates a very strong relationship.

R Square, the coefficient of determination, is the squared value of the multiple correlation coefficients. It shows that about 99 percent of the variation in Special offer sales is explained by the model.

Adjusted R Square is an r-squared statistic that is “corrected” for the complexity of the model, and is useful for comparing competing models. The larger values of the statistic indicate better models. It showed that the predictors were able to explain 98.9% of the variations in special offer sales.

Std. Error of the Estimate is the standard error in estimates of Special offer sales based on the model. The value this standard error of estimate compare to the standard deviation of 13.649 of Special offer sales shows that the model has reduced the uncertainty in the “best guess” for next month’s sales.

TableA1-4 ANOVA

Sum of Squares Df Mean Square F Sig
Regression 9221.545 4 2305.386 1160.333 0.000
Equation 1 Residual 91.394 46 1.987
Total 9312.940 50

The ANOVA table tests the acceptability of the model from a statistical perspective

The Regression row displays information about the variation accounted for by the model

The Residual row displays information about the variation that is not accounted for by the model

The regression sum of squares is considerably higher than the residual sum of squares, which indicates that about most of the variation in Special offer sales is explained by the model

The significance value of the F statistic is less than 0.05, which means that the variation that is explained by the model is not simply due to chance.

While the ANOVA table is a useful test of the model’s ability to explain any variation in the dependent variable, it does not directly address the strength of that relationship

Table A1-5 Coefficients

Unstandardized Coefficients Beta T Sig.
B Std. Error
(Constant) -3.237 8.202 -.395 .695
cfm .032 .202 .039 .158 .875
Equation 1 pern .026 .030 .036 .857 .396
grt .916 .146 .484 6.276 .000
app .988 .254 .481 3.892 .000

Dependent Variable  Special Sales

This table shows the coefficients of the regression line. It states that the expected special offer sales is equal to : -3.237 + 0.032CFM + 0.026PEM = 0.916GRT + 0.988APP.

The significance value for GRT and APP are less than 0.05, indicating that the effect of GRT and APP distinguishable from sales of CFM and PEM. In other words, the sales of GRT and APP may not be affecting sales from CFM and PEM. When CFM, PEM GRT and APP are regressed against Total Sales, in Table A1-6, all the variables are significant at 1% level. This shows that they all contribute and no “special sales’’ is limiting the sales of CFM and PEM.

 

 Table A1-6 Coefficientsa
Model Unstandardized Coefficients Standardized Coefficients T Sig.
B Std. Error Beta
1 (Constant) -.193 3.180 -.061 .952
cfm 1.054 .053 .404 19.745 .000
pem .991 .036 .437 27.209 .000
grt .812 .173 .133 4.702 .000
app 1.000 .176 .151 5.683 .000
a. Dependent Variable: tsales

Table A1-7 Coefficient Correlation

cfm Pem Grt App
Equation 1 Correlations cfm 1.000
pem -.866 1.000
grt -.885 .661 1.000
app -.966 .843 .757 1.000

*SPSS 21 OUTPUT

 

 

MODEL 2: FORECASTING MODELS**

TableA2-1 Sales Forecast and Seasonally Adjusted Trend

S/N p MONTHS Tsalesf (rounded to a whole number) N’000 Multiplicative scoring Factor(𝒇i) TsalesfSA (rounded to a vhole number) N’000
1 0.89
2 0.99
3 51 MARCH 1.02
4 52 APRIL 269 1.05 282
5 53 MAY 273 1.06 289
6 54 JUNE 275 1.02 281
7 55 JULY 278 1.02 284
8 56 AUGUST 280 1.01 283
9 57 SEPTEMBER 283 1.05 297
10 58 OCTOBER 286 1.02 292
11 59 NOVEMBER 288 0.96 276
12 60 DECEMBER 291 0.91 265

The model equation is: tsalesF = 93.79 + 0.341tsalesf (-1) + 1.64pm +[(AR(1)= 0.233]

  For example April Forecast: tsalesF 52 = 93.79 + 0.341tsalesF51 + 1.64(Mouth 52) + 0.233      (See Eq 4)

                                                     = 93.79 + 0.341(263.3 = March Total Sales) + 1.64(52) + 0.233

                                                     = 93.79 + 89.78 + 85.28 + 0.233

                                                     = 269.09

                                    tsalesF53  = 93.79 + 0.341(269.08) + 1.64(53) + 0.233

                                                    = 272.7  e.t.c

Table A2-2     Augumented Dickey-Fuller Unit Root Test
Test Statistics Coefficients
Variable Intercept Intercept &Trend None Intercept Intercept& Trend None
At Level Tsalesf(Total Sales Forecast) -1.53 -4.152 1.183 -0.065 -0.577 0.0095
1st Diff -6.59 -6.557 -6.385 -0.982 -0.989-1 -0.939
2ndDiff -7.34 -7.253 -7.426 -1.835 -1.835 -1.834
Critical

Value

1%    -3.59

 

5%    -2.93

 

10%    -2.6

1%     – 4.18

 

5%     -3.51

 

10%    -3.19

1%        -2.62

 

5%        -1.95

 

10%       -1.61

TsalesF is stationary at First Difference in Table A2-2 above. This satisfies its expected forecasting property.

   Table A2-3 Model is Stationary at the First and Second difference:

 

 

 

AR Root(s)

  0.233330  0.233330
 No root lies outside the unit circle.
 ARMA model is stationary.
MA Root(s) Modulus Cycle
 -0.236191  0.236191
 No root lies outside the unit circle.
 ARMA model is invertible.

 

 

      **E-View 7.1 OUTPUT

MODEL 3: THE RFM ANALISIS

 

The Firm is having a total of about 90 customers on records. A random sample of 14 customers were made using Random Numbers, but customer ID-01 was purposive. RFM Analysis was limited to customers who made purchases between September 2014 and March 2016.

Table A3-1 Transaction Data

ID DATE AMT N’000 ID DATA AMT N ‘000
01 08/24/2014 212 16 03/15/2015 15
16 09/09/2014 50 83 03/20/2015 105
75 09/30/2014 12 30 04/12/2015 15
75 10/15/2014 15 01 04/14/2015 50
39 10/20/2014 50 72 04/15/2015 30
72 11/15/2014 15 35 05/18/2015 15
28 11/20/2014 50 16 05/25/2015 12
24 11/22/2014 12 89 07/16/2015 45
28 11/25/2014 12 16 07/18/2015 45
24 12/03/2014 15 49 07/25/2015 195
28 12/14/2014 15 08 08/10/2015 12
77 12/18/2014 15 01 18/18/2015 15
16 12/20/2014 15 72 08/20/2015 30
75 12/22/2014 12 35 08/22/2015 30
77 01/15/2015 15 81 09/14/2015 27
02 01/19/2015 62 08 10/20/2015 12
02 03/04/2015 69 08 01/13/2016 12
30 03/10/2015 15 89 01/20/2016 12

When you compute RFM scores from transaction data, a new dataset is created that includes the new RFM scores.

By default, the dataset includes the following information for each customer:

  • Customer ID variable(s)
  • Date of most recent transaction
  • Total number of transactions
  • Summary transaction amount (the default is total)
  • Recency, Frequency, Monetary, and combined RFM scores

The new dataset contains only one row (record) for each customer. The original transaction data has been aggregated by values of the customer identifier variables. The identifier variables are always included in the new dataset; otherwise you would have no way of matching the RFM scores to the customers.

 

Table A3-2 Customers with Transaction Summaries

ID DATE AMT N’000 ID DATE AMT N’000
01 08/24/2014 12 30 10/202014 50
01 04/14/2015 50 30 03/10/2015 15
01 08/18/2015 15 30 04/12/2015 15
02 01/19/2015 62 35 05/18/2015 15
02 03/04/2015 69 35 08/22/2015 30
08 08/10/2015 12 49 07/25/2015 195
08 10/20/2015 12 72 11/15/2014 15
08 01/13/2016 12 72 04/15/2015 30
16 09/09/2014 50 72 08/20/2015 30
16 12/20/2014 15 75 09/30/2014 12
16 03/15/2015 15 75 10/15/2014 15
16 05/25/2015 12 75 22/12/2014 12
16 07/18/2015 45 77 12/18/2014 15
24 11/22/2014 12 77 01/15/2015 15
24 12/03/2014 15 81 09/14/2015 27
28 11/20/2014 50 83 03/20/2015 105
28 11/25/2014 12 89 07/16/2015 45
28 12/14/2014 15 89 01/20/2016 12

The dataset must contain variables that contain the following information:

  • A variable or combination of variables that identify each case (customer).
  • A variable with the date of each transaction.
  • A variable with the monetary value of each transaction.

Table A3-3 RFM Analysis from Transaction Data -The New Data Set.

ID Date Most Recent Transa

ction

Counts

Amount

N’000

Recency Frequency Monetary

Score

RFM

Score

Customer with High Response to an Offer
01 08/18/2015 3 77 3 3 3 333 ü
02 03/04/2015 2 131 2 2 5 225
08 01/13/2016 3 36 5 3 1 531 ü
16 07/18/2015 5 137 3 5 5 355 ü
24 12/03/2014 2 27 1 2 1 121
28 12/12/2014 3 77 1 3 3 133
30 04/12/2015 3 80 2 3 3 233
35 08/22/2015 2 45 3 2 2 322 ü
49 07/25/2015 1 105 3 1 5 315 ü
72 08/20/2015 3 75 3 3 3 333 ü
75 12/22/2014 3 39 1 3 1 131
77 01/14/2015 2 30 2 2 1 221
81 09/14/2015 1 27 4 1 1 411 ü
83 03/20/2015 1 105 2 1 4 214
89 01/20/2016 2 57 5 2 2 522 ü

The combined RFM score for each customer is simply the concatenation of the three individual scores, computed as: (recency x 100) + (frequency x 10) + monetary.

For example, the RFM score for ID-16 is (3×100 + 5×10 + 5) = 300 + 50 + 5 = 355

The marked customers are those that are likely to respond to new offer on CFM and PEM. To qualify, a customer must score at least 3 points for recency.

 

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