India’s Evolving Role in Environmental Protection: A Study in Post-Globalization Era

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Citation

Papparaya, & Yatanoor, C. M. (2026). India’s Evolving Role in Environmental Protection: A Study in Post-Globalization Era. International Journal of Research, 13(1), 599–607. https://doi.org/10.26643/ijr/2026/v13i1-2

Papparaya

Research Scholar

Department of Political Science

Gulbarga University, Kalaburagi, 585 106

Karnataka

papparaya123@gmail.com

Prof. Chandrakant. M. Yatanoor

Senior Professor & Chairman

Department of Political Science

Gulbarga University, Kalaburagi, 585 106

Karnataka

cmyatanoor@rediffmail.com

Abstract:

         The advent of globalization, particularly following India’s economic liberalization in 1991, has presented a complex and often contradictory set of challenges and opportunities for the nation’s environmental governance. This paper examines India’s evolving role in environmental protection in this transformative period. It argues that globalization has acted as a dual-edged sword, concurrently accelerating environmental degradation through rapid industrialization and consumerism, while also providing access to green technologies, international finance, and a platform for global environmental diplomacy. The paper analyses the trajectory of India’s domestic environmental policy, highlighting the critical role of judicial activism and the strengthening of legal and institutional frameworks, such as the National Green Tribunal. It further explores India’s transition on the international stage from a cautious participant to a proactive leader, exemplified by its instrumental role in the Paris Agreement and the launch of initiatives like the International Solar Alliance (ISA). Despite these advancements, significant challenges persist, including a persistent gap between policy formulation and implementation, the contentious development-versus-environment debate, and acute vulnerability to climate change. The paper concludes that India’s future role is pivotal; its ability to successfully navigate the intricate nexus of economic growth and ecological sustainability will not only determine its own developmental trajectory but also have profound implications for global environmental security.

Keywords: Globalization, Environmental Protection, India, Sustainable Development, Climate Change, Environmental Policy, Judicial Activism, International Solar Alliance (ISA).

Introduction:

           The process of globalization, characterized by the accelerated integration of economies, cultures, and societies, has fundamentally reshaped the global environmental landscape. For developing nations, this integration has been a catalyst for unprecedented economic growth, but it has often come at a significant ecological cost1. India, since its economic liberalization in 1991, stands as a prime case study of this complex dynamic. As one of the world’s fastest-growing major economies and its most populous nation, India’s developmental pathway and its approach to environmental stewardship carry immense global weight. The post-globalization era has forced India to confront a dual reality: the pressures of resource-intensive growth and pollution on one hand, and the opportunities for international collaboration and technological advancement in sustainability on the other2.

           Before 1991, India’s environmentalism was largely shaped by domestic concerns, culminating in foundational legislation like the Water (Prevention and Control of Pollution) Act, 1974, the Air (Prevention and Control of Pollution) Act, 1981, and the comprehensive Environment (Protection) Act, 1986, which was enacted in the aftermath of the Bhopal gas tragedy3. However, the post-1991 economic reforms unshackled the industrial sector, attracted Foreign Direct Investment (FDI), and integrated India into global supply chains. This unleashed economic forces that placed immense strain on the country’s natural resource base and its nascent regulatory capacity.

          Now, it is essential to examine India’s evolving role in environmental protection since 1991. It reveals that India’s journey has been one of adaptation and transformation, characterized by a reactive strengthening of domestic policy in response to escalating environmental crises and a gradual, yet decisive, shift towards a leadership role in global environmental diplomacy. This paper analysed the dual impacts—negative and positive—of globalization on India’s environment. It will then trace the evolution of the nation’s domestic legal and institutional frameworks, with a special focus on the crucial role of judicial activism. Subsequently, India’s engagement in international environmental forums is discussed. The persistent challenges and future prospects for sustainable development in India are also analysed.

The Dual Impact of Globalization on India’s Environment

         Globalization’s effect on India’s environment is not monolithic; it has simultaneously been a source of degradation and a catalyst for positive change.

A. Negative Externalities and Accelerated Degradation

          The most visible consequence of economic liberalization was the rapid pace of industrialization and urbanization. The drive to attract investment and boost manufacturing output often led to the relaxation of environmental oversight, creating “pollution havens” in certain industrial clusters4. This resulted in:

  1. Increased Pollution: Air and water pollution levels surged. The proliferation of thermal power plants, vehicular emissions in rapidly growing cities, and untreated industrial effluents from sectors like textiles, tanneries, and chemicals have led to a severe public health crisis. A 2020 report noted that 22 of the world’s 30 most polluted cities were in India, with Particulate Matter (PM2.5) concentrations far exceeding World Health Organization (WHO) guidelines5.
  2. Resource Depletion: The demands of a globalized economy have intensified pressure on India’s natural resources. Deforestation for mining, infrastructure projects, and industrial agriculture has accelerated. Water tables have plummeted due to unsustainable extraction for both agriculture and industry, leading to acute water stress in many parts of the country6.
  3. Consumption Patterns and Waste Management: Globalization introduced global brands and fostered a culture of consumerism. This, coupled with rapid urbanization, has led to a monumental increase in municipal solid waste, plastic waste, and electronic waste (e-waste). The infrastructure for managing this waste has failed to keep pace, resulting in overflowing landfills, polluted water bodies, and informal, hazardous recycling practices7.

B. Positive Opportunities and Catalysts for Change

           Despite these severe negative impacts, globalization has also provided pathways for environmental improvement.

  1. Access to Green Technology and Finance: Integration with the global economy has facilitated the transfer of cleaner and more efficient technologies. India has become one of the world’s largest markets for renewable energy, driven by falling costs of solar panels and wind turbines, largely imported or produced with foreign technology. Furthermore, international financial mechanisms, such as the Green Climate Fund and FDI in sustainable projects, have provided crucial capital for India’s green transition8.
  2. Enhanced Global Awareness and Civil Society: Globalization has connected Indian environmental movements with international networks. This has amplified the voices of non-governmental organizations (NGOs) and civil society groups, enabling them to exert greater pressure on the government and corporations. Global norms and standards regarding environmental protection and corporate social responsibility have slowly begun to influence domestic policy and corporate behavior9.
  3. Pressure from International Markets: As Indian companies became more integrated into global supply chains, they faced increasing pressure from international buyers and consumers to adhere to higher environmental and labour standards. This has incentivized some export-oriented industries to adopt cleaner production processes and obtain international certifications like ISO 14001.

The Evolution of Domestic Environmental Governance

         In response to the escalating environmental crises of the post-globalization era, India’s domestic governance framework underwent a significant, albeit often reactive, evolution, driven primarily by judicial intervention and subsequent legislative action.

(i) The Era of Judicial Activism

           Perhaps the most significant development in Indian environmental jurisprudence has been the proactive role of the judiciary. Through Public Interest Litigations (PILs), the Supreme Court of India and various High Courts have expanded the interpretation of the Constitution to protect the environment. The court declared that the “Right to Life” under Article 21 of the Constitution includes the right to a clean and healthy environment10. This principle became the basis for numerous landmark judgments:

  • In the M.C. Mehta v. Union of India series of cases, the Supreme Court issued directives on controlling pollution in the Ganga River, relocating polluting industries from Delhi, and mandating the use of Compressed Natural Gas (CNG) for public transport in the capital11.
  • The judiciary established key environmental principles in Indian law, including the “precautionary principle,” the “polluter pays principle,” and the doctrine of “public trust,” which holds that the state is a trustee of natural resources for the public12.

           This judicial activism filled a critical void left by executive and legislative inertia, compelling the government to act on pressing environmental issues.

(ii) Strengthening of Institutional and Legal Frameworks

           Prompted by judicial orders and growing public pressure, the government strengthened its institutional architecture.

  1. The National Green Tribunal (NGT): A landmark development was the establishment of the National Green Tribunal in 2010. The NGT is a specialized judicial body equipped with expertise to handle environmental cases effectively and expeditiously. It has delivered several impactful judgments, including bans on old diesel vehicles, regulations on sand mining, and penalties for environmental violations, establishing itself as a powerful environmental watchdog13.
  2. New Policies and Regulations: The post-globalization era saw the introduction of a new suite of environmental regulations targeting specific problems. These include the E-Waste (Management) Rules, 2016; Plastic Waste Management Rules, 2016; and Solid Waste Management Rules, 2016. The National Environment Policy (2006) was formulated to mainstream environmental concerns into all development activities14.
  3. Environmental Impact Assessment (EIA): The EIA notification, first issued in 1994 and subsequently amended, made environmental clearance mandatory for a wide range of development projects. However, the EIA process has been a subject of intense debate, with critics arguing that recent amendments, such as the draft EIA Notification 2020, have sought to dilute environmental safeguards in favor of promoting “ease of doing business”15.

India on the Global Stage: International Environmental Diplomacy

            India’s role in international environmental negotiations has transformed significantly. Initially, its stance was defensive, strongly advocating for the principle of “Common But Differentiated Responsibilities and Respective Capabilities” (CBDR-RC) to emphasize the historical responsibility of developed nations for climate change and to protect its own “right to develop”16. While this principle remains a cornerstone of its foreign policy, India’s approach has become more proactive and solution-oriented.

A. Leadership in Climate Action: The Paris Agreement

         At the 2015 Paris Climate Conference (COP21), India played a crucial role as a bridge between developed and developing nations, helping to forge the final consensus. It submitted ambitious Nationally Determined Contributions (NDCs), which included:

  • Reducing the emissions intensity of its GDP by 33-35% by 2030 from 2005 levels.
  • Achieving about 40% of cumulative electric power installed capacity from non-fossil fuel-based energy resources by 2030.
  • Creating an additional carbon sink of 2.5 to 3 billion tonnes of CO2 equivalent through additional forest and tree cover by 2030.

           At COP26 in Glasgow (2021), India further enhanced these commitments, pledging to achieve net-zero emissions by 2070 and setting a target of 500 GW of non-fossil fuel energy capacity by 203017.

B. Proactive Multilateral Initiatives

           Beyond its commitments, India has launched major international initiatives, positioning itself as a leader of the Global South in the green transition.

  1. International Solar Alliance (ISA): Co-founded by India and France in 2015, the ISA is a treaty-based intergovernmental organization that aims to mobilize technology and finance to promote the widespread deployment of solar energy. With over 120 signatory countries, the ISA is a testament to India’s vision of “one sun, one world, one grid” and its leadership in climate solutions18.
  2. Coalition for Disaster Resilient Infrastructure (CDRI): Launched by India at the 2019 UN Climate Action Summit, the CDRI is a multi-stakeholder global partnership that aims to promote the resilience of new and existing infrastructure systems to climate and disaster risks. This initiative addresses a critical adaptation need for developing countries19.

These initiatives signal a strategic shift in India’s role from being a mere rule-    mntaker in global environmental governance to an active agenda-setter.

Challenges and Future Directions

           Despite significant progress in policy formulation and international diplomacy, India faces formidable challenges in translating its ambitions into on-the-ground reality.

  1. The Implementation Gap: A chasm persists between India’s well-formulated environmental laws and their enforcement. State Pollution Control Boards (SPCBs) and other regulatory bodies are often underfunded, understaffed, and susceptible to political and corporate influence. This results in widespread non-compliance and continued environmental degradation20.
  2. Development vs. Environment Dichotomy: The tension between achieving rapid economic growth and ensuring environmental protection remains a central political challenge. The government has often been accused of prioritizing industrial and infrastructure projects by diluting environmental regulations, as seen in the controversies surrounding forest clearances and the EIA process.
  3. Climate Change Vulnerability: India is one of the country’s most vulnerable to the impacts of climate change, including extreme weather events, sea-level rise, and water scarcity. Adapting to these impacts will require massive investment and planning, diverting resources that are also needed for mitigation and poverty alleviation21.
  4. Resource Inefficiency and Circular Economy: India’s economy is still highly resource-intensive. Transitioning to a circular economy model, which emphasizes resource efficiency, recycling, and waste minimization, is crucial but remains in its nascent stages.

         In the future, India’s role will be defined by its ability to address these challenges. Key priorities must include strengthening regulatory institutions, investing in enforcement capacity, mainstreaming sustainability into economic planning, and fostering public participation in environmental decision-making.

Conclusion:

          The era of globalization has profoundly shaped India’s environmental trajectory, presenting it with a formidable set of problems and a unique array of opportunities. The pressures of a rapidly growing, market-integrated economy have undeniably exacerbated pollution, resource depletion, and ecological stress. However, this same period has seen the rise of a powerful and independent judiciary, the creation of a sophisticated legal framework, and the emergence of India as a credible and influential voice in global environmental diplomacy.

           India’s role is inherently paradoxical: it is a major contributor to global environmental challenges, yet it is also a source of innovative, large-scale solutions, particularly in the renewable energy sector. Its leadership through platforms like the ISA and CDRI demonstrates a clear intent to shape a more sustainable global future. The ultimate test, however, lies in its domestic performance. Bridging the gap between policy and practice, resolving the conflict between short-term economic gains and long-term ecological security, and building a truly sustainable development model are the defining challenges for India in the 21st century. The success or failure of this endeavour will not only determine the well-being of its 1.4 billion citizens but will also be a critical factor in humanity’s collective effort to secure a viable planetary future.

References:

  1. J. A. Frankel, “The Environment and Globalization,” in Globalization: What’s New, M. M. Weinstein, Ed. New York: Columbia University Press, 2005, pp. 129-169.
  2. E. S. Somanathan and R. S. Kumar, “Environmental Policy in India: A Review,” in A Companion to the Indian Economy, P. Basu, Ed. Hoboken, NJ: Wiley-Blackwell, 2011, pp. 491-508.
  3. S. Divan and A. Rosencranz, Environmental Law and Policy in India: Cases, Materials and Statutes, 2nd ed. Oxford: Oxford University Press, 2001.
  4. S. Murty, B. N. Kumar, and M. Paul, “Environmental Regulation, Productive Efficiency and Abatement Cost in Indian Cement Industry,” Ecological Economics, vol. 59, no. 1, pp. 123-134, Aug. 2006.
  5. IQAir, World Air Quality Report 2020: Region & City PM2.5 Ranking, 2021. [Online]. Available: https://www.iqair.com/world-air-quality-report
  6. NITI Aayog, Composite Water Management Index, Government of India, New Delhi, Jun. 2018.
  7. Central Pollution Control Board (CPCB), Annual Report 2018-19 on Implementation of Solid Waste Management Rules, 2016, New Delhi: Ministry of Environment, Forest and Climate Change, 2019.
  8. International Energy Agency (IEA), India Energy Outlook 2021, Paris: IEA, Feb. 2021.
  9. A. Kothari, “Environment and Globalization: A View from India,” Development, vol. 48, no. 2, pp. 81-86, Jun. 2005.
  10. P. Leelakrishnan, Environmental Law in India, 4th ed. New Delhi: LexisNexis, 2016.
  11. M. C. Mehta v. Union of India, (1987) 1 SCC 395 (Oleum Gas Leak Case).
  12. L. Rajamani, “The Right to a Healthy Environment in India: The Judiciary’s Role,” Review of European, Comparative & International Environmental Law, vol. 11, no. 2, pp. 175-184, Jul. 2002.
  13. G. P. Wilson, “India’s National Green Tribunal: A Robust Environmental Court,” Journal of Environmental Law, vol. 27, no. 1, pp. 131-143, Mar. 2015.
  14. Ministry of Environment, Forest and Climate Change (MoEFCC), National Environment Policy, 2006, Government of India, New Delhi, 2006.
  15. K. C. S. Kartha and L. V. Kumar, “Dilution of Environmental Norms: An Analysis of the Draft EIA Notification 2020,” Economic and Political Weekly, vol. 55, no. 34, pp. 10-13, Aug. 2020.
  16. N. Dubash, “The Politics of Climate Change in India: Narratives of Equity and Co-benefits,” Wires Climate Change, vol. 4, no. 3, pp. 191-201, May/Jun. 2013.
  17. Government of India, India’s Updated First Nationally Determined Contribution Under Paris Agreement (2021-2030), submitted to UNFCCC, Aug. 2022. [Online]. Available: https://unfccc.int/NDCREG
  18. International Solar Alliance, About ISA, [Online]. Available: https://isolaralliance.org/about/
  19. Coalition for Disaster Resilient Infrastructure, About CDRI, [Online]. Available: https://www.cdri.world/about-cdri
  20. S. Narain, “The Challenge of Implementation in India’s Environmental Governance,” in The Oxford Handbook of the Indian Economy, C. Ghate, Ed. Oxford: Oxford University Press, 2012, pp. 603-625.
  21. Inter-governmental Panel on Climate Change (IPCC), “Climate Change 2022: Impacts, Adaptation and Vulnerability,” Contribution of Working Group II to the Sixth Assessment Report of the Intergovernmental Panel on Climate Change, Cambridge University Press, 2022.

Semantic Analysis of the Determinologization of Coroneologisms in the Uzbek Language

Daily writing prompt
Have you ever unintentionally broken the law?

Citation

Shuhratovna, O. I., & Fernando, R. S. (2026). Semantic Analysis of the Determinologization of Coroneologisms in the Uzbek Language. International Journal of Research, 13(2), 118–124. https://doi.org/10.26643/ijr/2026/37

Ortiqova Iroda Shuhratovna

Uzbekistan State World Languages University

Rosell Sulla Fernando

University of exact and social sciences

ABSTRACT

The 2020–2023 COVID-19 pandemic functioned as a global natural experiment in lexical innovation, rapidly generating emergency-driven terms—coroneologisms—such as lockdown (lokdaun), immunity (immunitet), and remote education (masofaviy ta’lim). Bypassing traditional lexicographic channels, these initially specialized terms quickly spread into everyday discourse, humor, and social media, exemplifying determinologization—the loss of technical specificity as terms enter common usage. Drawing on determinologization theory, Ullmann’s (1962) semantic-change taxonomy, and cognitive semantics within a corpus-assisted framework, this study analyzes the semantic evolution of coroneologisms in Uzbek. It identifies four key mechanisms—broadening, narrowing, metaphorization, and evaluative coloring—and outlines a five-step trajectory from media emergence to institutional codification. The findings show that the pandemic compressed decades of lexical change into just three years, transforming emergency terminology into stable, stylistically versatile elements of the Uzbek lexicon.

Key words: determinologization, coroneologisms, COVID-19, semantic change, Uzbek language, corpus linguistics, broadening, narrowing, metaphorization, evaluative coloring, lexical innovation, crisis communication, lockdown, immunity, remote education, pandemic discourse

The COVID-19 pandemic, which unfolded between 2020 and 2023, is widely recognized not only as a global public health crisis but also as a significant natural experiment in the development of language. In various societies around the world, the overwhelming urgency to name and describe new phenomena – such as lockdowns, PCR testing, remote education, and social-distancing measures – triggered a remarkable wave of ad-hoc lexical formations. These formations often circumvented the conventional processes of approval associated with traditional lexicography. In the context of the Uzbek language, this surge resulted in a cluster of emergency-driven coinages that scholars and journalists have referred to as “coroneologisms” [4], a term that represents a hybrid of “coronavirus” and “neologism.” Many of these newly minted terms began their lives as highly specialized medical or administrative jargon – terms like “ventilator,” “antigen test,” “lockdown,” and “immunity.” However, within a remarkably short span of time, they began to diffuse widely across social media platforms, appearing in hashtags, memes, humorous posts, and even informal conversations among the general public. This rapid transition of specialized terminology into popular discourse serves as a clear example of determinologization—the gradual erosion of a technical term’s limited meaning once it becomes integrated into the fabric of national language [2],[5]. This article seeks to explore the semantic pathways of determinologized coroneologisms in the Uzbek language. It specifically investigates (a) the primary modes of meaning shift – namely broadening, narrowing, metaphorization, and evaluative coloring – that accompanied these terms, and (b) the communicative and social processes that catalyzed or accelerated these transitions. Our analysis is grounded in corpus-assisted evidence derived from media and online discourse, allowing us to describe how a three-year emergency compressed decades of lexical development into a condensed historical timeframe.

Determinologization—a concept originally defined in the field of terminology [2] and further elucidated by L’Homme [3] – describes the process by which a technical or scientific term migrates out of its specialized context and into ordinary language. This movement is rarely neutral; as a term transitions “outside of its domain,” it often loses its precise denotation, acquires additional affective or ideological weight, and undergoes stylistic shifts across both formal and informal registers. To effectively characterize these semantic pathways, this paper employs Ullmann’s [6] framework for classifying semantic change, which is augmented by contemporary research insights regarding cognitive semantic evolution. Four mechanisms of semantic change emerged as particularly salient in this context:

Broadening (Widening): This mechanism refers to the expansion of a technical term’s referential scope, extending far beyond its original definition. For example, the medical term immunitet (biological resistance to disease) developed metaphorical uses signifying any kind of protection or resilience, as in iqtisodiy immunitet “economic immunity” or “institutional immunity to corruption”.

Narrowing (Specialization): This mechanism occurs when a term’s meaning contracts to a more limited subset of its earlier referents. For instance, the English loan lokdaun (< lockdown) originally denoted a range of industrial or security-related shutdowns, but in Uzbek pandemic usage it came to mean only “legally imposed stay-at-home order.” The term ventilator, widely used in headlines as ventilyatsiya qilmoq “to ventilate”, narrowed to refer exclusively to “connecting a patient to artificial lung ventilation.”

Metaphorical Transfer and Re-conceptualization: This mechanism involves projecting concrete imagery from one domain onto other, often more abstract, targets. A notable example is the everyday noun to‘lqin (“wave of water”) was repurposed to describe successive “waves of infection”, producing widely used expressions such as 1-to‘lqin, 2-to‘lqin.

Evaluative Coloring: In this mechanism, terms acquire positive or negative attitudinal elements, often imbued with humor or irony. Combinations such as “Kovidiot” (a blend of “covid” and “idiot”) and the compound antiniqobchi (anti + niqob + -chi) designated “anti-mask activists”, marking not only behaviour but also an ideological position.

These mechanisms collectively illustrate that the transition from specialized phrases to common vocabulary is not a linear process; rather, meanings may expand or contract, take on metaphorical nuances, or become evaluative in response to communicative needs and societal contexts.

The methodology employed in this research is rooted in a corpus-driven descriptive model [1], which emphasizes the analysis of real speech as the primary source of evidence for semantic change. To this end, we constructed a custom corpus comprising a diverse range of Uzbek language news sources, official announcements, online forums, and prominent social media platforms spanning from March 2020 to December 2023. This methodological approach facilitated the investigation of the following dimensions:

– The chronological diffusion of newly coined words across the three-year span of the pandemic;

– The distinguishing differences in register among official media, informal posts, and colloquial speech patterns;

– The profiles of collocations that unveiled new senses and figurative applications of emerging terms;

– Pragmatic signals that indicated humor, stance, or judgment, further elucidating instances of semantic change.

By liberating the analysis from an overreliance on prescriptive dictionary definitions – which have proven inadequate in capturing the dynamism of language evolution – the study aims to articulate what vocabulary has come to signify in public communication, contrasting this with the more static definitions prescribed by traditional dictionaries.

An in-depth analysis of the Uzbek linguistic data reveals that a significant number of high-frequency coroneologisms underwent a five-stage lexical evolution, a process that was notably expedited during the pandemic due to the prevailing sociolinguistic conditions:

Stage 1 – Media Seeding: In the initial shock phase of the pandemic (March–May 2020), the urgent need for communication led to the borrowing of English terms such as “lockdown,” “PCR test,” “ventilator,” and “mask regime.” These terms were rapidly integrated into Uzbek headlines, hashtags, and memes, where the immediacy of communication took precedence over adherence to orthographic or morphological consistency.

Stage 2 – Morpho-Phonemic Adaptation: As the usage of these borrowed terms began to stabilize, a process of nativization ensued. This involved alterations to stress patterns to conform to Uzbek linguistic standards, the simplification of consonant clusters, and the adoption of Latin script conventions in spelling. For instance, “RT-PCR” became simplified to “PZR,” and “lockdown” was adapted to “lokdaun.”

Stage 3 – Semantic Dilution and Metaphorization: During this stage, common words began to expand or mutate either metaphorically or in terms of their general application to biomedical contexts. The term “to’lqin,” for example, began appearing in headlines describing “a wave of layoffs,” while “karantin” evolved into shorthand for any form of restrictive regulation.

Stage 4 – Lexicographic Recognition: From 2021 to 2022, several key terms, including “lockdown,” “distance learning,” “PCR test,” and “immunity,” were officially recognized and included in the COVID-19 Explanatory Dictionary.

Stage 5 – Pedagogical / Institutional Stabilization: Ultimately, these terms found their way into educational materials such as school textbooks, teachers’ guides, and civil-service style manuals, as well as journalistic glossaries. This integration reflected a full incorporation of these expressions into the Uzbek lexical system. A key finding of this research is that the shift from impromptu borrowing to institutionally codified lexis was accomplished within a mere three-year timeframe. This indicates that the exigencies of crisis-driven speech have the potential to accelerate lexical development that would typically unfold over decades. The pathway also highlights that determinologization is not only structural but also emergent, influenced by local communicative urgency, institutional acceptance, and societal prominence.

Beyond merely structuring the semantic transformations discussed, the Uzbek coroneologisms exhibited four reiterative communicative and pragmatic roles that account for their swift proliferation within the language:

Economy of Expression: The newly introduced forms, which were predominantly borrowed, provided concise and readily comprehensible labels for concepts that may have been unfamiliar to the general public. Terms that required longer descriptive phrases, such as “online schooling” and “PCR diagnostic test,” were efficiently replaced with these shorter alternatives, thereby facilitating effective public communication within both media narratives and healthcare discussions.

Stance-Marking and Evaluation: Several terms adopted pejorative or ironic connotations during the politically charged periods of the crisis. For example, “covidiot” (a fusion of “covid” and “idiot”) became associated with individuals who disregarded safety protocols. Additionally, the slang term “remotka” (meaning “remote work”) emerged with a mildly humorous or dismissive tone, while “anti-niqobchi” explicitly indexed ideological opposition to mask mandates.

Group Identity and Solidarity: Some terms evolved into in-group codes that reflected the collective experiences of lockdown, distance learning, and online communication. The productive phrase “meeting up on Zoom” transformed into a rallying cry among social groups, encapsulated in expressions like “zumlashmoq” This development fostered conversation and unity among individuals navigating the challenges of isolation.

Humor and Coping: Lexical blends such as “quarantini” (a combination of “quarantine” and “martini”) and the incorporation of slang terms like “doomscrolling” provided a playful linguistic outlet for navigating anxiety and boredom. These terms thus served as coping mechanisms, contributing to stress-relief strategies in an otherwise challenging context.

These pragmatic functions underscore that the determinologized pandemic vocabulary was not merely a referential identity but also a valuable resource for stance-taking, community-building, and coping mechanisms amidst the crisis.

Table 1

TermExpansion on the meaning
 Pandemiya     Shifted from strictly medical to any globally spreading phenomenon (“infodemic”, “pandemic of fear”).
 KoronavirusBecame a generic label for any contagious trouble; often used metaphorically (“a coronavirus of bad habits”).
 COVID-19Extended to denote cause, blame, or time-marker (“because of covid”, “covid generation”).
 VaksinaMetaphorised into “silver-bullet solution” for non-medical crises (“education vaccine”, “economic vaccine”).
 ImunitetBroadened to any system’s defensive capacity (“tax immunity”, “bank immunity”).
 KarantinRe-semanticised to mean any restrictive measure or even punitive isolation.
 IzolyatsiyaMoved from clinical isolation to everyday social distancing and on-line modes (“isolation lessons”).
 LockdaunImported as-is; now also describes total shutdowns in business or mental states (“mental lockdown”).
 AntitelaUsed figuratively for ideological or emotional resistance (“antibodies to negativity”).
 EpidemiyaGeneralised to any rapidly spreading trend (“epidemic of errors”, “epidemic of selfies”).
 Masofani saqlashPhysical distance became a metaphor for emotional coolness in relationships.
   GigiyenaHygiene concept expanded to information & mental spheres (“info-hygiene”, “sleep hygiene”).
 DezinfektsiyaDisinfection now covers cleansing of fake news or toxic content.
 SimptomClinical sign → any visible indicator of systemic problems (“symptoms of economic crisis”).
 TestNarrow lab procedure turned into generic verb “to test” and synonym for any quick check.
 Immunitet pasayishiImmunological drop re-interpreted as weakening resilience in economics or organisations.
 PCRAcronym became a household verb meaning “to swab-test” regardless of method.
 AntigenTechnical term now stands metonymically for rapid-test devices themselves.
 VentilyatorLife-support machine → metaphor for any critical external support (“financial ventilator”).
 Post-pandemiyaTemporal phase converted into a cultural label for “new normal” behaviours and policies.
 To‘lqinOriginally “wave” of water; pandemic discourse turned it into numbered surges (“third wave”) and now any periodic spike (“price wave”, “jobless wave”).
 ZumlashmoqPure Uzbek verb “to accelerate”; during the crisis it shifted from physical speeding-up to rapid scaling of remote work, vaccination drives, or digital services (“business zumlandi”).

The findings derived from the Uzbek data demonstrate that the process of lexical borrowing, catalyzed by a crisis, can significantly accelerate the phenomenon of semantic and pragmatic diversification. This process enables the transformation of technical medical terminology into broadly stylistic and affectively expressive components of everyday vocabulary. The outlined five-step trajectory, which encompasses the initial seeding of terms in media and their subsequent institutional codification, illustrates the complex nature of this social mediation process. It becomes evident that determinologization is not merely a function of lexical evolution but is socially mediated through communicative urgency, varying attitudes, and policy decisions. By combining determinologization theory, Ullmann’s semantic-change taxonomy, and a corpus-assisted methodology, this study presents a condensed lifecycle of lexical evolution that would typically require decades to develop. The results underscore the necessity for dynamic lexicographic practices and language-planning methods that are capable of responding swiftly to future public health or technological emergencies. An organized record of rapid lexical evolution, such as the analysis presented here, contributes to our understanding of how and why national languages maintain their flexibility and functional resilience in the face of global crises.

References

  1. Baker, M. (2011). In Other Words: A Coursebook on Translation (2nd ed.). Routledge. 353 p.
  2. Felber, H. (1984). Terminology Manual. UNESCO. 457 p.
  3. L’Homme, M.-C. (2020). Lexical Semantics for Terminology: An Introduction (3rd ed.). John Benjamins / De Boeck. 
  4. Nasirova, M. F. (2023). COVID 19 pandemiyasi davrida vujudga kelgan neologizmlar Oriental Renaissance: Innovative, educational, natural and social sciences . Volume 3. Issue11.
  5. Sager, J. C. (1990). A Practical Course in Terminology Processing. John Benjamins. 
  6. Ullmann, S. (1962). Semantics: An Introduction to the Science of Meaning. Blackwell.

Navigating the Modern Pet Camera Market: A Look at Features, Philosophy, and Daily Realities

The integration of technology into pet care has moved far beyond simple webcams. Today’s dedicated pet cameras are sophisticated devices that blend surveillance, interaction, and behavioral monitoring, offering owners a virtual window into their home. However, the expanding feature sets of leading models present a fundamental choice: should the device act as a proactive, interactive guardian, or a simple, reliable portal for passive check-ins? This decision hinges on understanding the trade-offs between advanced functionality and day-to-day usability, which are often rooted in the product’s core design philosophy.

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At the heart of any pet camera is video performance. Clarity, field of view, and low-light capability define what you can see. Some models offer high-definition, fixed wide-angle lenses, providing a stable and predictable view of a room. Others incorporate pan-and-rotate mechanics, allowing the view to follow a pet as it moves, which greatly enhances situational awareness but introduces mechanical complexity. Similarly, night vision modes range from traditional monochrome to color, with the latter preserving important contextual details like toy color or a pet’s position relative to furniture, albeit often at a higher cost. The choice here is between consistent framing and adaptive coverage.

The feature dichotomy extends powerfully into alert systems and monitoring style. One approach is behavior-centric, using sound analytics to send notifications for barking or meowing, effectively positioning the camera as a sentry. This creates a more proactive relationship but can also lead to alert fatigue or a reliance on subscription services to unlock full potential. The alternative is a calmer, self-directed model where the camera provides sound and motion alerts but primarily waits for the owner to initiate a check-in. This results in a lower-engagement daily routine, often with less dependency on paid plans. The difference shapes the mental load of ownership, determining whether the device integrates seamlessly into the background or demands regular attention.

Treat dispensing, a popular interactive feature, also reveals design priorities. Considerations include physical capacity—whether measured by piece count or weight—and compatibility with different treat sizes and textures. Some dispensers prioritize anti-jam mechanics with self-clearing functions, while others offer user-adjustable toss strength for placement flexibility. This isn’t merely a novelty; reliability in dispensing affects the consistency of positive reinforcement and the overall hassle of maintenance. Furthermore, the app experience and daily workflow vary significantly. A system with a rotating camera and rich alerts invites more hands-on, app-driven interaction, whereas a fixed camera with straightforward controls supports quicker, more passive viewing.

Beyond hardware, the long-term value proposition is increasingly shaped by software and service models. The trend toward subscription tiers for features like video history, advanced analytics, or extended alert libraries is pronounced. This creates a divergence: some devices retain robust core functionality (live viewing, two-way audio, basic treat tossing) without a recurring fee, while others gate their most compelling monitoring features behind a paywall. For the consumer, this shifts the calculation from a one-time purchase price to a total cost of ownership, making it crucial to assess which features are truly essential.

Practical deployment introduces another layer: connectivity and placement. Most units operate solely on 2.4GHz Wi-Fi bands, which can be congested in dense living environments, impacting stream stability. They are also plug-in devices, requiring thoughtful placement near an outlet for optimal room coverage and treat-tossing efficacy. Reliability, therefore, depends as much on the home network and physical setup as on the device’s own engineering.

For those weighing specific options, a detailed Furbo 360 vs Petcube Bites Lite comparison can serve as a useful case study in these trade-offs, examining how different manufacturers balance these priorities. Ultimately, selecting a pet camera is less about finding an objectively “best” model and more about aligning a product’s design ethos—whether it’s an active monitoring hub or a passive observation tool—with your own lifestyle, budget, and expectations for ongoing engagement. The ideal device is the one whose presence reassures without becoming a source of digital clutter or unexpected recurring expense.

AI-Driven Tutoring: Closing the Achievement Gap in Higher Education

Daily writing prompt
What do you complain about the most?

In higher education, many students drop out during their first year due to the difficulty of “gateway” courses in math and science. The purpose of TOP AI Education Tools in a university setting is to provide 24/7 academic support that helps students bridge the gap between high school and college-level expectations. Unlike human tutors, who are expensive and only available during certain hours, AI tutors are always available to help a student work through a difficult physics problem or understand a complex economic theory. This democratization of support is essential for ensuring that students from all backgrounds have an equal chance to succeed in rigorous academic programs.

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The target audience for AI-driven tutoring includes university deans of student success, academic advisors, and undergraduate students themselves. These stakeholders are focused on improving graduation rates and reducing the high cost of student attrition. For students who work full-time or have family responsibilities, AI provides help at 2:00 AM when human tutoring centers are closed. For advisors, the data from these tutoring sessions provides early warning signals; if a student is struggling with foundational concepts in week three, the advisor can reach out with proactive support before the student fails their first exam.

The benefits of AI tutoring center on accessibility, patience, and data generation. AI tutors never get frustrated and can explain a concept in ten different ways until a student grasps it. They can also adapt their teaching style, perhaps using a visual analogy for one student and a logical proof for another. For the student, this provides a safe, non-judgmental space to ask “basic” questions that they might feel embarrassed to ask a professor in a large lecture hall. For the institution, the aggregated data from these sessions identifies which parts of the curriculum are consistently difficult for the entire student body, allowing for strategic improvements to the course content.

Usage involves students accessing a web portal or mobile app where they can chat with the AI about their coursework. A student might upload a photo of a handwritten equation, and the AI walks them through the steps of the solution, asking questions to verify comprehension along the way. This interactive loop ensures that students aren’t just getting the answer, but are learning the underlying logic. To maintain the efficiency of these complex tutoring networks, tech teams often utilize MoltBot to manage the various specialized bots and ensure that each student is routed to the correct “subject matter expert” AI.

Intelligent Voice Agents and the Future of Business Communication

Daily writing prompt
What are your favorite sports to watch and play?

Customer expectations around business communication have changed dramatically in recent years. Today, speed, personalization, and round-the-clock availability are no longer competitive advantages but basic requirements. Companies that rely solely on traditional call centers often struggle to meet these demands without increasing costs or overloading their teams. As a result, many organizations are turning to intelligent voice agents as a scalable and cost-effective alternative.

According to an article on Coruzant, intelligent voice agents are rapidly reshaping how businesses manage inbound calls, customer support, and ongoing engagement. Powered by artificial intelligence, these systems are designed to handle conversations in a natural, human-like way while reducing operational strain and improving service consistency.

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What Are Intelligent Voice Agents?

Intelligent voice agents, also known as AI voice agents, are conversational systems that interact with customers through voice channels such as phone calls. Unlike traditional interactive voice response (IVR) systems, which rely on rigid menus and predefined options, intelligent voice agents can understand natural speech and respond dynamically.

These systems do more than recognize keywords. They interpret intent, context, and meaning, allowing customers to speak freely instead of navigating complex phone menus. The result is a more fluid and intuitive experience that closely resembles a conversation with a human representative.

At their core, intelligent voice agents combine speech recognition, artificial intelligence, and advanced language processing. This enables them to understand requests, provide relevant information, and take appropriate actions in real time.

How Intelligent Voice Agents Work

AI voice agents rely on several interconnected technologies that work together to create seamless conversations. Speech-to-text technology converts spoken language into text, allowing the system to analyze what the caller is saying. Natural Language Understanding (NLU) then interprets the caller’s intent, even when phrased in different ways.

Large language models (LLMs) play a key role in generating natural, context-aware responses. These models allow voice agents to adapt their replies based on the flow of the conversation rather than relying on scripted answers. Decision-making components determine the next best action, whether that involves providing information, performing a task, or transferring the call.

Text-to-speech and voice synthesis technologies ensure that responses sound natural and human-like. When a request is too complex or requires personal judgment, the system can seamlessly transfer the call to a human agent, maintaining continuity and context.

Most modern platforms also allow businesses to configure system prompts, rules, and internal knowledge bases. This ensures that voice agents provide accurate, up-to-date information aligned with company policies and processes.

Business Benefits of AI Voice Agents

The adoption of intelligent voice agents offers several clear advantages for businesses across industries. One of the most significant benefits is 24/7 availability. AI-powered systems ensure that no call goes unanswered, even outside regular business hours.

Cost efficiency is another major factor. By automating routine interactions, businesses can reduce the tells of staffing large call centers or scaling teams during peak periods. Faster response times improve customer satisfaction, while consistent service quality helps maintain brand standards.

AI voice agents can also recognize caller IDs, enabling personalized interactions for returning customers. This allows calls to be routed more efficiently and conversations to begin with relevant context, reducing friction and repetition.

By handling repetitive inquiries, such as frequently asked questions or basic service requests, AI voice agents free human employees to focus on complex or high-value interactions. This not only improves productivity but also reduces burnout among customer support teams.

Collaboration Between Human Agents and AI

Despite concerns about automation replacing jobs, intelligent voice agents are most effective when used in collaboration with human employees. Rather than eliminating roles, AI systems support teams by managing high-volume, routine tasks.

Human agents remain essential for handling nuanced requests, sensitive situations, and complex decision-making. By offloading repetitive work to AI, businesses can improve response times and allow their staff to deliver more personalized and thoughtful service.

This collaborative model creates a more stable and efficient operation. AI handles consistency and availability, while human agents focus on empathy, judgment, and problem-solving.

Getting Started with Intelligent Voice Agents

Implementing an AI voice agent requires careful planning. Businesses should start by identifying the specific tasks and processes they want to automate. Common use cases include after-hours call handling, virtual receptionists, appointment scheduling, and basic customer support.

Feature requirements should be evaluated based on business needs, such as multilingual support, CRM integration, or call routing capabilities. Budget considerations and scalability are also important, as the system should be able to grow alongside the organization.

Choosing a reliable provider is critical. Businesses should test the solution thoroughly before deployment to ensure that it meets performance expectations and integrates smoothly with existing systems.

Zadarma AI Voice Agent as a Practical Example

One example of an all-in-one intelligent voice solution is the Zadarma AI Voice Agent. This virtual assistant is designed to answer calls using natural, human-like speech while leveraging a company’s internal knowledge base to provide accurate information.

The platform supports 24/7 automated call handling, integrates with PBX and CRM systems, and offers multilingual capabilities across multiple languages. When necessary, calls can be transferred to the appropriate human agent or department.

By combining features that are often offered separately, such solutions simplify implementation and reduce complexity. Compatibility with modern AI models and intuitive configuration make intelligent voice agents accessible even to businesses without advanced technical expertise.

Conclusion

Intelligent voice agents are becoming a foundational element of modern business communication. By automating routine interactions, improving availability, and delivering faster responses, these systems help organizations meet rising customer expectations without compromising quality.

As AI technology continues to evolve, voice agents will play an increasingly important role in creating efficient, scalable, and customer-centric communication strategies. Businesses that adopt intelligent voice solutions today are better positioned to remain competitive in an environment where speed, personalization, and reliability define success.

Efficacy of Personal Emergency Response Systems (PERS) in Geriatric Care: A Multi-Dimensional Analysis of Mortality Reduction, Psychosocial Outcomes, and Economic Impact

Daily writing prompt
Write about a few of your favorite family traditions.

By Faiz Muhammad

Abstract The global demographic shift towards an aging population presents a critical challenge to healthcare infrastructure: the rising incidence of falls and unmonitored medical emergencies among independent-living seniors. Falls remain the leading cause of fatal and nonfatal injuries in adults aged 65 and older. This article provides a comprehensive review of the efficacy of medical alert monitoring systems, evaluating their role in reducing the “long lie” post-fall, alleviating caregiver burden, and mitigating healthcare costs. By synthesizing data from recent longitudinal studies and technological assessments—including the integration of medical alert monitoring with SOS system protocols and advanced automatic fall detection devices—we argue that these interventions are no longer merely reactive safety nets but essential components of proactive geriatric health management. The review further explores the psychological benefits of “aging in place” facilitated by these technologies, concluding that modern monitoring solutions significantly improve quality-adjusted life years (QALYs) for the elderly.


1. Introduction

The concept of “aging in place”—the ability to live in one’s own home and community safely, independently, and comfortably—has become a central tenet of modern gerontology. However, the biological reality of aging introduces significant risks, primarily related to mobility and acute medical events. According to the Centers for Disease Control and Prevention (CDC), approximately one in four Americans aged 65 and older falls each year, resulting in 3 million emergency department visits annually. The mortality rate from these accidental falls has risen by 30% over the last decade.

The critical determinant in fall-related mortality is often not the trauma of the impact itself, but the duration of the subsequent immobilization, clinically referred to as the “long lie.” Research indicates that remaining on the floor for more than one hour after a fall is strongly associated with severe complications, including rhabdomyolysis (muscle breakdown), pressure ulcers, dehydration, and pneumonia. Consequently, the latency period between an incident and the arrival of medical assistance is a definitive variable in survival rates. This establishes the clinical necessity of Personal Emergency Response Systems (PERS).

2. The Physiology of Delayed Intervention and the “Long Lie”

The primary medical justification for continuous monitoring lies in the mitigation of delayed intervention. A retrospective cohort study involving 295 individuals demonstrated that PERS users were significantly less likely to experience a “long lie” of 60 minutes or more compared to non-users. The mechanism of protection is straightforward yet profound: by reducing the time to discovery, the physiological cascade of stress responses is interrupted.

For seniors living with chronic conditions such as congestive heart failure or COPD, the risks extend beyond falls. Acute exacerbations of these conditions often render the patient unable to reach a telephone. In these scenarios, the integration of medical alert monitoring with SOS system integration becomes a lifeline. Unlike standard telecommunications, these dedicated systems bypass the cognitive load required to dial emergency numbers, connecting the user immediately to a specialized response center. This rapid connection capability is correlated with a higher probability of returning to independent living post-hospitalization, as faster treatment onset typically limits the severity of the initial medical insult.

3. Technological Evolution: Accelerometry and Algorithmic Detection

Early iterations of PERS relied entirely on user activation—the classic “push-button” model. While effective in conscious, mobile patients, these systems failed in cases of syncope (fainting) or incapacitating trauma. This gap has been bridged by the advent of automatic fall detection devices.

Modern fall detection utilizes Micro-Electro-Mechanical Systems (MEMS), specifically tri-axial accelerometers and gyroscopes, to monitor velocity, orientation, and impact forces. Research published in the Journal of Medical Internet Research highlights that advanced algorithms can now distinguish between the high-G impact of a fall and the low-G movements of daily activities (like sitting down quickly) with increasing specificity.

Recent deep learning frameworks have further refined these capabilities. By training neural networks on vast datasets of human movement, false positive rates—historically a barrier to adoption—have been significantly reduced. For instance, sensors can now detect the “pre-fall” phase (loss of balance) and the “post-fall” phase (lack of movement), triggering an alert even if the user is unconscious. This passive layer of protection ensures that cognitive impairment or loss of consciousness does not preclude the arrival of emergency services.

4. Psychosocial Impact on the Dyad: User and Caregiver

The efficacy of medical alert systems extends into the psychological domain, impacting both the user and their informal caregivers (often family members). Fear of falling (FOF) is a well-documented psychological syndrome in the elderly, leading to self-imposed restrictions on activity, social isolation, and physical deconditioning—which, paradoxically, increases the risk of falls.

A study analyzing user perception found that 75.6% of participants reported an enhanced feeling of security after adopting a monitoring system. This “peace of mind” effectively acts as a buffer against FOF, encouraging seniors to maintain mobility and engage in social activities, which are critical for cognitive health.

For caregivers, the burden of “vigilance anxiety” can be debilitating. The constant worry that a loved one has fallen while alone contributes to caregiver burnout. The implementation of a reliable monitoring system serves as a surrogate proxy for presence. Data suggests that caregivers of PERS users report significantly lower stress levels and higher subjective well-being. This reduction in caregiver strain is a vital, often overlooked, outcome that supports the sustainability of home-based care arrangements.

5. Economic Implications for Healthcare Systems

From a health economics perspective, the cost-benefit analysis of medical alert monitoring is compelling. The alternative to aging in place—institutional care—imposes a massive financial burden on families and state healthcare systems. The monthly cost of a semi-private room in a nursing home averages over $7,000 in the United States, whereas monitoring services are a fraction of that expense.

Furthermore, by preventing the complications associated with long lies (e.g., intensive care for rhabdomyolysis or sepsis), monitoring systems reduce the average length of hospital stays (LOS). A study on healthcare utilization found that while PERS users have high rates of chronic conditions, the system facilitates earlier discharge to home settings rather than skilled nursing facilities, as the home is deemed a “safe environment” due to the presence of the monitor.

6. Discussion: The Convergence of Monitoring and Telehealth

The future of geriatric safety lies in the convergence of emergency response with broader health monitoring. We are observing a shift from “alarm-based” systems to “predictive” platforms. Emerging providers are moving beyond simple SOS functions to integrate biometric monitoring (heart rate, oxygen saturation) that can alert response centers to medical crises before a fall occurs.

Institutions and forward-thinking platforms, such as Vitalis, are increasingly recognized for adopting these rigorous standards, bridging the gap between consumer electronics and medical-grade reliability. This adherence to high-fidelity monitoring protocols ensures that the technology remains a robust clinical tool rather than a mere convenience.

7. Conclusion

The literature surrounding medical alert monitoring for seniors presents a unified conclusion: these systems are a cornerstone of modern geriatric safety. By drastically reducing response times, they directly mitigate mortality and morbidity risks associated with falls and acute medical events. Beyond the physiological benefits, they offer a profound psychological dividend, restoring confidence to the elderly and relieving the anxiety of caregivers.

As technology continues to miniaturize and algorithms become more sophisticated through AI, the distinction between “lifestyle wearables” and “medical devices” will blur, likely leading to higher adoption rates. For healthcare providers and families alike, the data supports a clear directive: the integration of automatic fall detection and 24/7 professional monitoring is not merely a precaution, but a critical intervention for preserving the longevity, dignity, and independence of the aging population.

References

  1. Herne, D. E. C., Foster, C. A. C., & D’Arcy, P. A. (2008). Personal Emergency Alarms: What Impact Do They Have on Older People’s Lives? Investigating the lived experience of PERS users and the reduction of fear of falling.
  2. Centers for Disease Control and Prevention (CDC). Older Adult Fall Data. Statistics on fall-related mortality and injury rates in the United States (2023-2024 data).
  3. Journal of Medical Internet Research (JMIR). An Effective Deep Learning Framework for Fall Detection: Model Development and Study Design (2024). Analysis of accelerometer accuracy and algorithmic improvements in distinguishing falls from daily activities.

     
  4. Stokke, R. (2016). The Personal Emergency Response System as a Technology Innovation in Primary Health Care Services. An examination of the economic impacts of PERS on municipal healthcare costs.

Fleming, J., & Brayne, C. (2008).Inability to get up after falling, subsequent time on floor, and summoning help: prospective cohort study in people over 90. The definitive study on the risks of the “long lie.”

Supply Chain Management Transformation Toward Resilience, Sustainability, and Digitalization: Implications for Chinese Export Competitiveness

Daily writing prompt
What do you enjoy doing most in your leisure time?

Citation

Rahman, A. A. J. A., Rahman, N., Islam, M. S., Hossain, M. B., & Jaman, B. U. (2026). Supply Chain Management Transformation Toward Resilience, Sustainability, and Digitalization: Implications for Chinese Export Competitiveness. International Journal of Research, 13(1), 416–430. https://doi.org/10.26643/ijr/2026/15

Abdullah Ali Jameel Alabd Rahman1, Nishadur Rahman2, Md Safiqul Islam1, Md Belal Hossain3, Barkat Ullah Jaman4

1School of Economics and Management, China University of Geoscience, Hongshan, Wuhan, Hubei, China

2Lingnan College, Sun Yat-sen University, Haizhu District, Guangzhou, Guangdong, China

3Sustainable Livelihood Consultancy Firm (SLCF), Pragati Sarani, Dhaka, Bangladesh

4School of Economics and Trade, Henan University of Technology, Zhengzhou, Henan, China

Abstract

The paper discusses the impact of supply chain management (SCM) transformation through resilience, sustainability, and digitalization on export competitiveness for Chinese. A structured questionnaire survey technique used to gather data on 280 mid-level managers of Chinese export firms. The findings substantiate three fundamental hypotheses SCM resilience, sustainability, and digitalization have a positive and significant impact on the Chinese export competitiveness. Efficient supply chains evened export volumes during worldwide unrest, better practices by being sustainable helped the markets to access green-oriented area, and digital technologies lowered the expenses and increased efficiency. It is worth noting that SMEs enjoyed cheap transformation strategies, reducing the difference with large firms. The three factors had synergies that enhanced competitiveness. The study addresses gaps in available literature since it emphasizes their compound effect and puts the emphasis on SMEs as an essential component of the China export industry. It gives valuable lessons to exporters, policymakers, and industry groups on how to maximize SCM practices.

Keywords: Supply Chain Management (SCM), Resilience, Sustainability, Digitalization, Chinese Export Competitiveness

1. Introduction

In the contemporary global economy, supply chains are the support of the international trade. In the case of China, which is the largest exporter in the world. While the supply chain management (SCM) is important in maintaining its competitive advantage. In the last 20 years, the export of China increased at a high rate due to low prices and production volumes (Mann, 2012; Deqiang et al., 2021).

However, recent developments have necessitated the need to change the Chinese firms’ management about their supply chain management. Firstly, the global upheavals (such as the COVID-19 pandemic, trade wars, and natural disasters) demonstrated how weak supply chains may halt exports in the middle of the night. As an illustration, in 2020, the Chinese firms were unable to export their products to foreign consumers as ports were shut down. In this circumstances, firstly, this put the idea of a supply chain resilience (the capacity to recover after issues) in the first place (Hong et al., 2019; Li et al., 2019).

Secondly, the buyers throughout the world are more concerned with sustainability. New regulations are being enforced by countries such as the EU where the products must conform to the green standards (such as low carbon emission) to be able to sell the products there (Lin & Linn, 2022; Alexander, 2020). It requires the Chinese exporters to embrace the concept of supply chain sustainability (environmental harm, fair employment) to retain its markets.

Thirdly, SCM is becoming modified by technology. Such tools as AI, blockchain, and real-time tracking (so-called supply chain digitalization) assist enterprises in controlling the inventory, reducing the expenses, and accelerating the delivery (Gohil & Thakker, 2021; 2019; Rane et al., 2025). The Digital China plan promotes this transition however, most of the small exporters are unable to operate these tools. Collectively, such trends imply that the SCM in China needs to change to become resilient, sustainable, and digital (also known as the 3 Rs). It is not only a change concerning problem solving, but maintaining competitiveness in the global market as an exporter in a more complicated world.

Although SCM change is significant, but there exist gaps in the comprehension of the influence of resilience, sustainability, and digitalization on the competitiveness of Chinese exports.  Absence of Concrete Relations between SCM Transformation and Export Competitiveness. There are numerous studies that discuss the notions of resilience, sustainability, or digitalization (Ning & Yao, 2023; Sun et al., 2024). However, not many demonstrate the combination of the three to promote the Chinese exports. Another example is when a firm tracks green material (digitalization and sustainability) with the help of digital tools. But it is unknown that whether it can sell more abroad. Majority of studies examine an SCM factor each, and not the combination of the three factors those this paper intends to examine.

Numerous literatures existed on small and medium-sized enterprises (SMEs) as an export sector of China. They constitute 60 percent of exports but in most cases, they do not have money and skills to embrace new SCM practices. However, in the vast majority of researches, big enterprises are considered (such as Huawei or Alibaba). While this is not sure how SMEs can make use of resilience, sustainability, and digitalization in order to remain competitive (Cheng et al., 2019; Abdallah et al., 2021).

Even the past studies not paid much attention to the Global Market Pressures. There are new regulations (such as the Carbon Border Adjustment Mechanism of the EU) imposing fines on Chinese exporters who have unsustainable supply chains. Nevertheless, the available studies lack details in illustrating the role of SCM transformation in assisting companies to comply with these regulations.

Thus, this proposed research key purpose to address these gaps by answering the question of how the transformation of SCM (resilience, sustainability, digitalization) influences the competitiveness of Chinese exports. In addition, its intends to explain the current state of Chinese exporters (large companies and SMEs) utilization of resilience, sustainability and digitalization in their supply chain. Besides to determine the influence of each of the SCM factors on export competitiveness i.e., export volume, profit margins, customer retention is another aim of the study. Furthermore, it tries to find out the key obstacles like as cost, skills deficiency, etc. that prevent the implementation of these SCM practices by exporters.

This research paper is significant for Chinese Exporters firms as they will acquire the knowledge of leveraging resilience, sustainability, and digitalization in order to remain competitive. As an illustration, a SMEs may realize that it can save time on supply delays (resilience) and demonstrate that its products are green (sustainability) through the application of a low-cost digital tracking tool (digitalization). These will in turn win more foreign customers. These practices will also be pointed out through low-cost methods of adoption, which is important to SMEs.

Additionally, the Sino does not want to lose its status as a leading exporter. Since the current study demonstrates the most effective policies: e.g. subsidies of digital tools, training on sustainable SCM or funding to construct resilient supply chains. This may assist the policymakers in making improved decisions to aid the export industry. Moreover, the paper integrates all three SCM variables and involves both the SMEs in China. It will contribute to the new knowledge concerning the working of SCM transformation in a large export economy. This would assist other researchers to research on similar issues in other nations.  

2. Literature Review and Hypothesis Formation

2.1 SC Resilience and Sino Export Competitiveness

Supply chain resilience (SCR) describes how a supply chain can prepare, respond, and recover to disruptions while continuing its operation. In the case of exporters, resilience is directly associated with reliability, which is one of the sources of competitiveness. Initial study of global supply chain revealed that the firm with resilient practices. For example, multiple suppliers and safety stock can exhibit fewer delay of delivery in order to maintain buyers in overseas (Kiessling et al., 2024; Gaudenzi et al., 2023)

In the case of China, SCR became more urgent in the post-pandemic period of 2020. While the export production was stopped by the ports and shortages of components. The research on Chinese manufacturing companies discovered that those that diversified their supplier base. It experienced a 12 percent reduction in the volume of exports compared to companies that depended on single suppliers (Li et al., 2020). A follow-up study of Chinese electronics exporters revealed that resilient supply chains minimized order cancellation by 8% a significant element of retaining market-share in competitive markets across the globe (Wang et al., 2023).

Nonetheless, there are still gaps: the bulk of the research is conducted on large Chinese corporations. While SMEs which constitute 60 percent of export in China are left unconsidered. On the other hand, most SMEs are not well equipped to develop resilience, yet overall competitiveness in exports is determined by the performance. The current work fills this gap by involving the SMEs in the analysis. Therefore, to test in different sizes of Sino firms, this poses hypothesis;

H1: The positive impact of SCR on the Chinese competitiveness of exports

2.2 SC Sustainability and Sino Export Competitiveness

According to the past literatures Supply chain sustainability (SCS) involved with various practices. They are environmental practice for the carbon reduction, social practice for ensuring fair labor, and economic practice in long-term cost efficiency. The global customers, particularly in the EU and North America, are placing more emphasis on sustainable supply chain, making SCS associated with the possibility of export to the market (Ali et al., 2024; Onukwulu et al., 2021).

SCS has no longer presents Sino exporters with a choice. Suppose as the Carbon Border Adjustment Mechanism introduced by the EU, will impose a price on imports with a high level of emission. Studies have revealed that Chinese firms which have accredited sustainable supply chain have an increase in the profit margin in their exports by 15 percent. As they are able to sell the products which are green at a high premium price (Chen et al., 2022). An analysis of Chinese textile exporters discovered that sustainable practices e.g. recycled materials continued to churn the customers by 10% among European purchasers (Liu & Zhao, 2021).

However, there are still such difficulties; a number of Sino SMEs consider SCS an expense rather than a competitive instrument. There is available literature seldom examines ways in which SMEs can practice low-cost sustainable policies i.e., energy efficient machineries to increase exports. Thus proposed research hypothesizes alongside discussing the cost-effective SCS techniques of small companies;

H2: SCS has a positive impact on the export competitiveness in China.

2.3 SC Digitalization and Sino Export Competitiveness

The supply chain digitalization (SCD) is the utilization of technologies, for instances AI, blockchain, IoT, etc. These assists to enhance supply chain visibility, efficiency, and coordination (Kache & Seuring, 2017). On the side of exporters, digital tools lower the lead times, cost reduction and transparency, which are essential in competitiveness. The adoption of SCD has been sped up by the Digital China project. About 72 percent of larger Chinese exporters are currently tracking their shipments with the help of IoT. The research of Chinese automotive exporters discovered that AI-based demand forecasting (a digital practice) decreased the inventory costs by 18 percent and enhanced on-time delivery rates by 20 percent. Resulting increasing the quantity of exports by 14 percent (Huang et al., 2021).

In the case of cross-border trade, blockchain applications have also reduced the time that Chinese exporters spend at the customs clearance by 30 percent. Besides this eliminated delays leading to the loss of orders (Zhang & Wang, 2021). Nevertheless, there are also digital divides: out of Chinese SMEs. Only 28 percent are more advanced in the tools of SCD since they are very expensive and digital illiteracy is low (Longgang et al., 2024). Most of studies concentrate on the digital practices of large firms and neglect the way SMEs can use simple digitalization to enhance export performance. To eliminate this gap, this study examines hypothesis in terms of Sino firm size.

H3: SCD has a positive impact on export competitiveness of China)

2.4 Intersections Resilience, Sustainability, and Digitalization 

Many literatures consider SCR, SCS, and SCD individually.  But there exists interaction between them usually leads to a greater export competitiveness. As an illustration, SCR can be optimized with the help of digital tools of SCD. Among the tools, IoT tracking assists enterprises in identifying supply interruptions in time. Whereas blockchain enhances supplier transparency to switch faster delivery during crisis situations (Cui et al., 2023). Likewise, SCD promotes SCS. Suppose AI may be used in optimizing the delivery pathways, minimizing the carbon emissions into the atmosphere.  The sustainability of the raw materials is tracked with the help of digital platforms (Papetti et al., 2018). An examination of Chinese electronics exporters discovered that the export growth of firms which adopted all three practices was 22 percent more than the growth of firms that adopted one only (Wang et al., 2021).

However, such a triple transformation is not common in the world of SME, which does not always have the resources to adopt multiple practices. Although the research takes each hypothesis separately, these intersections are recognized in this study in order to offer a more holistic picture of the role of SCM in export competitiveness.

Figure 1: Study Model

3. Methodology

3.1 Measurements Scales

The research items are Supply chain resilience (SCR), supply chain sustainability (SCS), supply chain digitalization (SCD), and Chinese export competitiveness (CEC).  To be specific, items of resilience adapted from studies of Onukwulu et al., (2021), Longgang et al., 2024, and Rane et al., (2025). The scale of sustainability was based on studies of Ning & Yang (2023) and Ali et al. (2024). Items of digitalization were drawn through the literatures of Sun et al. (2024), Li et al. (2019), and Deqiang et al. (2021). Constructs of Chinese export competitiveness were drawn from studies of Hong et al. (2019) and Zhang & Wang (2021). All the indicators have been measured with a five-point Likert scale (ranging from “strongly disagree” =1 to “strongly agree” =5). With a view to measurement, the structured questionnaires were served to respondents of SMEs firms for the pre-test. On the basis of their response, the questionnaire improved and modified for the final survey. 

3.2 Sample Selection and Data Attainment

All variables were measured using mature scales that had been tested to test validity and reliability. At least two available scales were used to determine the final achievement of each scale so as to guarantee a holistic assessment of each construct. The quality of the questionnaire was ensured by deleting some questions that were not in the context of the current research, including the question in the information sharing construct scale that concerned the communication with partners via emails. Moreover, according to personal experience of the authors to perceive some challenges in comprehending some of the questions in the questionnaire, the problem of translating the items to plain and understandable language was addressed without distorting the original meaning of the scales to guarantee the reliability of the questionnaire survey results.

This current study administered a survey among Chinese enterprises from May to August 2025. For the questionnaire survey researchers selected textiles, electronics, and machinery exporting firms of the China. Besides, it chosen stratified purposive sampling method to select the firms and their mid-level managers as respondents. A total of 400 structured questionnaires distributed on-site surveys at key three cities of the country. These are Shanghai, Guangzhou, and Shenzhen cities; various SMEs firms. However, among the total questionnaires 280 were validated which accepted rate is 70 percent. 

4. Results

4.1 Nonresponse and Common Bias

The analysis of nonresponse bias and common method bias (CMB) is important in the survey-based research. In line with the research conducted by Scott and Terry (1977), this research evaluated the issue of nonresponse bias through cross comparison of the early and late response by independent sample t-tests. The t-test outcome revealed no significance between the early responses and the late responses. Thus depicting that there was also no nonresponse bias in the study. Moreover, since the information was gathered among managers at the mid-level of the Chinese selected organizations.

There was need to discuss the issue of common method bias. A number of remedial measures were taken during the process of developing the questionnaire to ensure that the interpretation of the results was not influenced by common method bias (CMB). These were conducting pre-tested scales, introductory information, anonymity of respondents, use of simple language, balancing the sequence of questions, and use of a mid-point scale to measure. Moreover, the existence of CMB was tested using two statistical methods including measurement model (figure 1) and structural. The findings revealed that the former fact explained 34.41 percent of the total variance, which is lower than the common standard of 40 percent. This implies that there is no severe common method bias. Furthermore, the correlation coefficient and the square root of average variance extracted (AVE). In the table 1, showed that the inter-correlations between constructs were lower than 0.9 significantly. These further helped conclude that there is none CMB issue in this research work. 

Table 1: The Correlation Coefficient

VariableMeanSDSCRSCSSCDCEC
SCR5.4080.783 0.815
SCS4.8520.7780.509 **  0.749
SCD5.3620.8950.597 **0.132 *0.765
CEC5.2630.7850.513 **0.242 **0.535 **0.814

Notes: N = 280; χ2 = 253.314, df = 279, RMSEA = 0.01,

CFI = 0.896, SRMR = 0.017; * p < 0.05, ** p < 0.01.

4.2 Reliability and Validity testing

The four variables were computed using SEM_PLS version 4.1.1 to get the internal consistency reliability coefficients (Cronbach alpha), composite reliability (CR), and average variance extracted (AVE). Table 2 provides the results. It is seen that all the variables met the standard value of 0.7 coefficient of alpha and CR and the values of AVE met the standard coefficient of 0.5. It implies that the data in this study is highly reliable. Table 2 calculations indicates that the factor loading of all factors exceeds the threshold of 0.7, and all the values of the AVE exceed the threshold of 0.5. Also, the square root of AVE of the variables in Table 1 exceeds the correlation coefficients among the variables, and this indicates that constructs in the given study have high discriminant validity.

Table 2: Reliability Validity

ConstructitemsloadingsCACRAVE
SC Resilience (SCR)SCR10.8150.9210.9350.547
SCR20.914
SCR30.770
 SCR40.829   
SC Sustainability (SCS)SCS10.8550.8500.8870.576
SCS20.845
SCS30.950
SCS40.853
SC Digitalization (SCD)SCD10.8780.8730.9160.572
SCD20.789
SCD30.847
SCD40.751
Chinese Export Competitiveness (CEC)CEC10.8370.9410.9370.700
CEC20.891
CEC30.815
CEC40.894
CEC50.737

N=280

4.3 Structural Model and Hypothesis Testing

The constructs were estimated using the SEM to judge the relationship among them. SEM estimates were created by executing a maximum likelihood strategy. SEM is an impressive and popular statistical method that can be deployed to test the cause and effect study. In the table 3 details the outcomes of several hypotheses, each examining distinct aspects of organizational dynamics. Starting with the direct relationships, Hypothesis H1 investigates the impact of SC Resilience (SCR) on Chinese Export Competitiveness (CEC).

Table 3. Structural Model Results

HypothesisRelationBetaMeanS.DT-Valuep-valueDecision
H1SCR → CEC0.2410.2130.0543.6830.000Significant
H2SCS → CEC0.6470.6630.03518.4150.001Significant
H3SCD→CEC0.7520.7480.02530.6520.002Significant

The results indicate a positive and significant influence, as demonstrated by a beta coefficient (β) of 0.241. This is further substantiated by a robust t-statistic of 3.683 and leading to the statistically acceptance of this hypothesis. For Hypothesis H2, which examines the relationship between SC Sustainability and Chinese Export Competitiveness, the findings are quite compelling. A high β of 0.647 and an impressive t-statistic of 18.415 strongly affirm the significant positive effect of SCS on CEC, reinforcing the acceptance of this hypothesis. Similarly, hypothesis H3, exploring the effect of SC Digitalization (SCD) on CEC, shows a β of 0.752. However, the higher t-statistic of 30.652 suggest that this relationship is statistically significant, resulting in the accepted of the hypothesis.

5. Discussion and Conclusion

5.1 Discussion Results

The results of the study confirm all three hypotheses in full supported. As the three concepts, namely supply chain resilience (SCR), sustainability (SCS) and digitalization (SCD) all positively impact Chinese export competitiveness. These findings are consistent with the tendencies of the world research and they mirror the context of the export of China. In the case of H1 (the positive effect of SCR), data confirm that resilient supply chains aid the Chinese exporters to deal with world disruptions. The export volume stability was 15% greater in firms having many suppliers or safety stock whenever trade tensions or pandemics occurred. It is equivalent to the Chinese manufacturers studied by Li et al. (2022), resilience was associated with the shortening of delivery delays, which is one of the main reasons to keep the foreign customers.

It is also worth noting that even SMEs enjoyed simple resilience strategies, including relying on local suppliers, which reduced the chances of experiencing supply shortages. Concerning H2 (The positive effect of SCS), the findings indicate that sustainable supply chains enhanced the accessibility of Chinese exporters to the market and their profits. Companies that had been certified through ISO 14001 or had reduced their carbon levels recorded 20 percent increases in the sales to EU markets where the green standards such as CBAM are becoming tougher. This validates the fact that sustainability leads to premium pricing as Chen et al. (2021) found. Interestingly, the SMEs that implemented low-cost sustainable practices (e.g. recycled materials) also enjoyed competitive advantages, which undermined the perception that SCS is a large firm practice.

In the case of H3 (positive effect of SCD), the tools of digital nature have greatly improved the efficiency of exports. Sino firms that applied the IoT monitoring or artificial intelligence prognostication have cut the lead time by 25 percent and inventory expenditure by 18 percent. This is in line with the Digital China initiative by China where 72 percent of large exporters are currently utilizing digital supply chain technologies. Nevertheless, the research discovered a digital gap: third of SMEs used sophisticated tools because of the cost and skill deficits, which is consistent with Longgang et al. (2024).

The findings also indicate synergies in the three factors. Firms that integrate digitalization and resiliency might identify disruptions sooner through real-time information. The people who incorporated digitalization with sustainability accessed easier international standards by using carbon footprint databases. This is a resemblance of Wang et al. (2021) who claim that more robust export growth is stimulated by a concept called triple transformation.

5.2 Implications

The three factors need to be even more integrated in large firms. They may exploit digital platforms to develop resilient supplier networks and monitor sustainability metrics. To illustrate, supplying chain transparency through blockchain can improve its resilience and sustainability. Transformational strategies, requiring low costs, are needed in SMEs. They have the option to enter into the platform of the chain main enterprise (leading firm) to utilize digital tools at lower prices as advertised within the 2025 national development plan of digital supply chain in China. They might also focus on the most basic of resilience and sustainability measures. Such as dual sourcing of the major materials, and recycled packaging. Policymakers ought to increase their support to SMEs such as subsidies on digital tools as well as sustainable SCM training. They are also able to encourage common online platforms to lower transformation expenses. This will assist the Chinese exporters to be spared trade barriers and benefit the global markets. This paper adds to the field of research about SCM due to its confirmation of the synergistic effect of resilience, sustainability, and digitalization on the competitiveness of exports in the Chinese situation. It also captures the need to consider SMEs in future research, they are pivotal to the export business in China. Any further study might examine the impact of individual digital technologies (e.g., AI, blockchain) in various export sectors. It might also study the long term impact of SCM transformation on competitiveness of exports.

5.3 Conclusion

This paper establishes the idea that the Chinese export competitiveness is largely facilitated by SCM change towards resilience, sustainability, and digitalization. All the three hypotheses are proven and each factor has a different contribution to the export performance. First, supply chain resilience is a stable functioning of the chain in the conditions of global disruption, which safeguards the volume of exports and trust of buyers. Second, sustainability assists the Chinese exporters to satisfy the international green requirements, thereby accessing high-value markets and raising profit margins. Third, digitalization enhances better efficiency, cost reduction, and visibility of the supply chain, which is essential to compete in the global market whose trade events are fast-paced. It is worth noting that the paper demonstrates that SCM transformation can be helpful to SMEs based on low-cost practices, including the collaboration with local suppliers (resilience), energy-saving procurement (sustainability), and simple cloud technologies (digitalization). Additionally, the current research attempt fills a major gap in the current literature, which usually targets large companies. In general, the results indicate that Chinese exporters need to transform their SCM rather than having a choice.

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 Spatiotemporal Mapping and Analysis of the Land Use and Land Cover in Makurdi, Nigeria 

 Ibrahim, A. D., & Umoru, K. (2026). Spatiotemporal Mapping and Analysis of the Land Use and Land Cover in Makurdi, Nigeria. International Journal of Research, 13(1), 278–286. https://doi.org/10.26643/ijr/2026/6

Daily writing prompt
Name an attraction or town close to home that you still haven’t got around to visiting.

Abakpa David Ibrahim1, Kebiru Umoru2*

1University Library, University of Abuja, Nigeria

2National Centre for Remote Sensing, Jos, Nigeria

Correspondence: t.omali@yahoo.com

Abstract 

This study employed geospatial techniques to capture the process of land conversion taking place. The objectives include mapping the land use types. The methodology involved geospatial technique which uses remote sensing and GIS techniques to identify the past and current condition of land use change occasioned development activities in the Makurdi Metropolis for the period of 1999, 2009 and 2019. The result shows that overall, there was progressive and increasing change in built-up area and water body categories, at (17.00%) and (1.73%) respectively during the period of study. However, vegetation cover, farm land, bare land and wetland decreased by (2.51%), (3.51%), (4.61%) and (8.08%) respectively. Residential buildings are fast encroaching the flood plain of River Benue in Makurdi. There is a need to sensitize the residents on the danger of flooding and provisions should be made to relocate those already occupying the location.

Keywords: GIS, land use change, Imagery, Mapping, remote sensing

  1. Introduction

The population of the world is growing at different rates relative to the total population (Omali, 2020), and it is becoming more urbanized (Enoch, John, and Jonathan, 2020). Changes in land use and land cover (LULC), which are more common in developing countries, are a result of this population growth. Due to the “push” of rural areas and the “pull” of urban centers, Nigeria’s high rate of urbanization is changing its land use (Aluko, 2013). Unprecedented alterations in the ecosystem and environmental processes have, of course, been brought about by natural forces and human activity (Okeke and Omali, 2016). This has resulted in a decline in biodiversity and environmental degradation. Land use and cover change is a global phenomenon. While urban centers are growing in population and area the surrounding open/agricultural lands are rapidly changing. Construction is putting increasing pressure on the land use to make room for a variety of urban land uses. There are severe consequences from the ruthless reduction of available land per person, including low or decreased food production, ecological degradation, environmental problems, and socioeconomic difficulties.

Current methods for managing natural resources and keeping an eye on environmental changes heavily rely on studies on changes in land use and land cover (LULC) (Okeke and Omali, 2016). This makes it feasible to comprehend human interactions with natural resources, both past and present, as well as their effects. To get the desired outcome, the conventional approach to LULC assessment is inadequate (Okeke and Omali, 2018). Therefore, it’s critical to use cutting-edge technologies, such as sophisticated computers, remote sensing, geographic information systems (GIS), GPS, and the power of spatial information systems (Okeke and Omali, 2016). Since remote sensing is the only affordable technology that provides data on a global scale, it provides an important means of detecting and analyzing spatiotemporal dynamics on geographical entities (Omali, 2018a). Through the use of aerial or spaceborne sensors, remote sensing gathers data about Earth without requiring the sensors to come into direct physical contact with the target or object of interest (Omali, 2022a). According to Omali (2021) the electromagnetic radiation serves as the transmission medium for information. GIS is typically employed in the gathering, storing, modifying, analyzing, visualizing, and presenting of georeferenced data and information (Omali, 2022b). Through the manipulation, analysis, statistical application, and modeling of spatial data, it provides us with the ability to handle spatially referenced data (Omali, 2022c). In general, remote sensing data and GIS techniques have emerged as incredibly helpful tools for mapping natural resources, such as vegetation and changes in land use/cover over geographic areas. This has allowed for the removal of many of the constraints associated with traditional surveying techniques and the acquisition of a continuous and comprehensive ecosystem inventory. In light of this, research on the LULC in Makurdi was conducted using geospatial technologies over a 20-year period, from 2009 to 2019.

  • Methodology
    • Data

Both primary and secondary sources provided data for the study; some of these are listed in Tables 1a and 1b. Satellite imagery and field observations make up the main sources. During the field campaign, training site coordinates were recorded using a handheld GPS device (Garmin Etrex 32). With the GPS using satellite, almost anywhere on Earth can be located at any time (Omali, 2023a). Furthermore, it is important to note that time-series data, such as remotely sensed data from various eras, must be applied in order to study and monitor LULC (Omali, 2023b). As a result, the time-series satellite data from three epochs of multi-spectral Landsat TM/ETM/OLI imagery were used in this study. Other materials such as newspapers, journals, textbooks, World Bank publications, and maps are included in the secondary sources.   

Table 1a: Maps used in the study

 TypeDate of ProductionSourceScale
Landuse/landcover mapSecondary1999Military Air Force Base Makurd1:1000000
A base map of Makurdi LGASecondary2019Benue State Ministry of Land and Survey1:50000

      Table 1b: Satellite imageries used in the study

 TypePath/RowDate of ImagerySourceResolution
 TM (Band 1-7)Primary188/55July 5, 1999Global Land Cover Facility (GLCF) database.30m
 ETM+(Band 1-7)Primary188/55August 4, 2009Global Land Cover Facility (GLCF) database.30m
OLI+Primary188/55July11, 2019Global Land Cover Facility (GLCF) database.30m
  • Pre-processing of the Satellite Imagery

It is crucial to pre-process satellite images for accurate change detection (Andualem et al., 2018). Time series analysis requires this crucial step in order to reduce noise and improve the interpretability of image data (Yichun et al., 2008). The processes and methods used in satellite image processing include geometric correction, atmospheric and radiometric correction, and masking study areas. To produce a consistent and trustworthy image database, radiometric and atmospheric correction is applied to account for variations in the viewing geometry and instrument response characteristics, as well as atmospheric conditions related to scene illumination. Pre-processing techniques used in this study included study area masking, image enhancement, and correction for atmospheric and radiometric errors. In order to bring the image scene and the scanned topographic maps into the same coordinate system, they were also co-registered into UTM zone 32N, WGS 84.

  • Image Classification

The goal of the imagery classification process was to assign each pixel in the digital image to one of many land cover classes, or “themes” (Omali, 2018b). This allows for the creation of thematic maps of the land cover present in an image. Finding the land use and land cover class of interest was the first stage in this study’s mapping and change analysis of land use and land cover. In this investigation, we employed six classes, as indicated in table 2, by incorporating and adapting the classification scheme from Andersen et al. (1971). The classes listed in Table 2 were utilized in this study. Also, the maximum likelihood supervised classification technique was used to classify LULC images from Landsat data. The study’s training sites were first located and defined. Fieldwork yielded training samples in line with Lu and Weng (2007). For the actual supervised classification of the study area, signature files containing statistical data about the reflectance values of the pixels within the training site for each of the LULC types or classes were developed in line Ojigi (2006). The supervised classification algorithm was imputed with the signatures.

        Table 2: Land Use/Land Cover Classification Scheme

Land UseDescription
Built-up Areacomprises all developed surfaces including residential, commercial, industrial complexes, public and private institutions, recreational areas, Airport, Factories, Interstate highways, roads networks that linked most of the areas together.
Vegetation,areas covered with plants of various species. This category includes grassland and non-agricultural trees and shrubs they are mostly wild plants.
Farm Land,land used primarily for cultivation of food and fibre, it includes cropped areas, fallow land and plantations (Ochards, nursery, vineyard etc.), harvested areas and herbaceous croplands.
Bare Surface,includes open surfaces, rocky outcrops, sandy area, strip mines, quarries, gravel pits, silt etc. Exposed soil devoid of vegetal cover, that is, open spaces.
Water body,includes areas covered with water bodies such as rivers, streams, lakes, flood plain, Reservoirs. It also includes artificial impoundment of water like dam used for irrigation, flood control, municipal water supplies, recreation, etc.
Wetland.an area where water covers the soil either at or near the surface of the soil all year or for varying periods of time during the year, including during the growing season.  

       Source: Adapted and modified from Anderson et al., (1971)

  • Land Use and Land Cover change Detection

There are numerous approaches for detecting changes in multi-spectral image data, such as time series analysis, vector analysis of spectral changes, and characteristic analysis of spectral type. Time series analysis is the most common method, and it was used in this study. Its objective is to analyze the course and trend of changes by tracking ground objects using continuous observation data from remote sensing (Adzandeh, et al., 2014). Naturally, post-classification comparisons can yield results of change that are acceptable and provide “from-to” data (Okeke and Omali, 2018).

  • Results and Discussion
    • Land Use and Land Cover Classification Result

The satellite imageries covering the study area were classified in GIS environment. Tables 2 reveal that there is a progressive and significant increase in built-up area which is necessitated by the increase in commercial activities, residential growth, economic and social activities. This is in line with the findings of Etim and Dukiya (2013) who opine that urban encroachment on agricultural land has reduced the productivity of most farmers in Makurdi. The water body recorded little increase due to the increase in water works like construction of Kaptai Lake, which is the largest artificial lake in the country. The farm land, vegetation, bare land and wetland decreases throughout the period of study.

           Table 3: Land use and land cover distribution of Makurdi

  Class1999           20092019
Area (km2)(%)Area (km2)(%)Area (km2)(%)
Built-up98.07911.97170.96820.86237.4628.97
Vegetation138.2016.86125.69515.33117.65314.35
Farm Land203.5624.83184.60822.52174.73521.32
Bare Land142.48717.38122.24914.91104.56112.77
Water Body22.45902.7429.16403.5636.65804.47
Wetland214.8926.22186.9922.78148.69618.14
Total819.670100819.670100819.670100

The classified images (false colour composite) for the different periods 1999, 2009 and 2019 of study area are shown in Figures 5.1, 5.2 and 5.3 respectively. These colour composite shows the visual distribution pattern of the distribution and change taking place in the images of the areas throughout the period of study. The dominating land use and land cover category in 1999 as shown in Table 3 and figure 1 is the wetland covering an area of 214.89km2 (26.22%). This is understandable as Hemba, et al. (2017) describes the relief of Makurdi town as lying entirely in the low- laying flood Plain with River Benue forming the major drainage channel. Farm land covers 203.56km2 representing 24.83% of Makurdi.

                                        Figure 1: Land Use and Land Cover of Makurdi in 1999

 Most residents engage in farming, either crop production or livestock farming as the soil is fertile and the weather is conducive for agricultural practices. This assertion supports the views of Hula, (2010) who noted that most farmers in Makurdi cultivate land for crop production, rearing of animals for consumption and selling part of the produce to generate money to meet other needs. The populace of Makurdi comprises of indigenous farmers and migrants who are mostly engaged in farm activities as noted by Oju et al. (2011). Due to farming and hunting and other activities like sand mining carried out  in Makurdi, the size of bare land is observed to occupy large space of about 142.487km2 represented by 17.38% in 1999. This is because farmers have enough space to cultivate. Farmers relocate to other lands whenever a particular land becomes unproductive and this has been the major cause of bare land in the study area. These contradicts Tee (2019) who argued that hunting, grazing  and other factors, which lead to clearing of land through manual, mechanical and chemical means have greatly changed the original vegetation cover to bare land and other classes of land use in Makurdi. The vegetation covered a reasonable size of land and it was 138.20km2 (16.86%).This is attributed to the few number of settlers in Maukurdi and low level of human activities taking place within the urban centre as at the time. The water body was 22.459 km2 (2.74%) with River Benue forming the major drainage system in the area and is the main source of water for human use. This is in line with the views of Nnule and Ujoh, (2017) who pointed out that Benue River is the main source of water in Makurdi. This doesn’t mean that other form of water sources like borehole, ponds and dams are not important.

Table 1 and figure 2 shows that the wetland had the largest area coverage of about 186.99km2 (22.78%) in 2009 as the entire land fall within the Benue Valley and Trough. The geology of the study area influence the wetland, this infect is also confirmed by Iorliam, (2014). The farmland occupies 184.608km2 (22.52%), as most residents are farmers. The number is significant as civil

                              Figure 2: Land Use and Land Cover of Makurdi in 2009.

servants also own farms. The built-up, which was 170.968km2 (20.86%) recorded a high increase due the increase in population. This corroborates the findings of Jiang, et al. (2013) which stated that the urban expansion on agricultural land is associated with both shrinking agricultural land area and a higher level of urban development. It also agrees with the findings of Araya and Cabral (2010) that substantial growth of urban areas has occurred worldwide in the last few decades with population increase being one of the most obvious agents responsible. The vegetation cover depreciated to 125.695km2 (15.33%). This may be attributed to deforestation as more forest was cleared to provide more space for increasing human development. This is buttressed by Mugish and Nyandwi (2015) that housing development on arable farm land in most cities has become an issue on the global agenda in recent times. Bare land, which was 122.52km2 (14.91%) decreased as the spaces were being covered with more structures but the water body 29.164km2 (3.56%) slightly increased. Of course, this is an indication that most of the human activities use water and other sources of water are being developed to meet the need of the increasing populace.

The level of human activities in the year 2019 was very high, although Makurdi has no functional Master Plan to check the developmental activities, however, as shown in the image Fig5.3 and Table5.1, The built-up area of 237.46km2 (28.97%) in 2019 almost tripled its size recorded in 1999.This supports the assertion by United Nations Department of Economy and Social Affairs (UNDESA, 2010) that urban cities have changed from small isolated population

                                 Figure 3: Land Use and Land Cover of Makurdi in 2019.

centres to large interconnected economic, physical, and environmental features. In recent time, issues of Herdsmen/Farmers crisis are among factors contributing to the migration of people from neighbouring villages to Makurdi Town for safety. These numbers of people who mostly settled along the urban hinterland, which is mostly used for agricultural purpose, have converted the land for building of houses and other socioeconomic infrastructures. The farm land occupies 174.735km2 (21.32%) as it decreases with population upsurge settles in the study area. Farmers move outside of Makurdi to get land for their activities which make the cost of cultivation expensive than expected. Agencies with the mandate of protecting natural ecosystem are weak in areas of law enforcement in Makurdi as infrastructural developments are indiscriminately carried out. This observation contradicts the views of Wade quoted in Nico et al. (2000) that Various NGOs, government and international Agencies have been supporting the urban agriculture (UA) since 1970s in major world regions. There was reduction in wetland to 148.696km2 (18.14%) and vegetation cover to 117.653km2 (14.35%) compared to the previous ten years while the water body 36.658km2(4.47%) increases during the same periods.

  • Conclusion

The research findings revealed that built-up area increased all through the period of study while arable land decreases due to infrastructural development. The rapid increase in built-up area is because the surrounding agricultural land is fast decreasing. Bare land, vegetation and wetland decreased throughout the period of study as human settlement increases over the years. Of course, it was observed that the effect of the development was concentrated more to the north eastern part of Makurdi as residential buildings with high rate of economic activities is observed in the region. Generally, this study has been able to show that conversion of open/agricultural land for infrastructural development was mostly due to increase in number of people through migration and natural means of population growth. The land use and land cover change detection for the period of 20 years revealed the extent and type of conversion. The study recommends Green areas within and around the city should be properly preserved as this allows for ventilation. All effort should be put in place to prevent unofficial development and measures should be in place to curb population growth which has encouraged urban sprawl on prime agricultural land as this is feasible around Makurdi hinterland.

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Kricon Group Launches a New Generation of ISOPA-Certified Tank Containers for Isocyanate Logistics

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The transportation of isocyanates such as MDI (Methylene Diphenyl Diisocyanate) and TDI (Toluene Diisocyanate) remains one of the most demanding areas in chemical logistics. Strict safety requirements, temperature sensitivity, and regulatory oversight leave no room for compromise. In response to these challenges, Kricon Group has introduced a new generation of tank containers engineered specifically to meet the highest standards of safety, reliability, and operational efficiency.

According to an article on Logistics IT, Kricon Group has developed these ISOPA-certified tank containers to ensure safe and compliant transport of MDI and TDI across Europe and international markets, reinforcing its role as a trusted partner in chemical logistics.

Addressing the Complexities of Isocyanate Transport

MDI and TDI are critical raw materials for a wide range of industrial applications, including polyurethane foams, coatings, adhesives, and elastomers. However, their chemical properties make transportation particularly complex. These substances require precise temperature control, secure handling procedures, and equipment that fully complies with industry-specific standards such as those set by ISOPA (European Diisocyanate & Polyol Producers Association).

Any deviation from recommended transport conditions can pose risks to personnel, the environment, and supply chain continuity. As a result, logistics providers and chemical manufacturers increasingly seek purpose-built equipment rather than adapted or generic tank containers.

Designed in Full Compliance with ISOPA Guidelines

Kricon Group’s newly introduced tank containers are designed and manufactured in strict alignment with ISOPA recommendations. Compliance is not treated as a formality but as a core design principle that influences every aspect of the container’s construction.

The containers incorporate standardized connection points to ensure seamless compatibility with ISOPA-approved loading and unloading systems. Enhanced insulation supports stable temperature conditions throughout transit, while integrated safety features help reduce the risk of contamination, leakage, or operational error. These design choices support traceability and accountability at every stage of the logistics process.

By aligning container specifications with ISOPA standards from the outset, Kricon enables chemical producers and logistics partners to operate with greater confidence and regulatory assurance.

Engineering Solutions Tailored to MDI and TDI

Unlike general-purpose chemical containers, Kricon’s latest units are specifically engineered to meet the unique demands of isocyanate transport. Materials used in the construction are selected for their resistance to corrosion and chemical interaction, helping to preserve product integrity over long distances and repeated use cycles.

Temperature control options play a central role in the container design. Maintaining stable conditions is essential for preventing crystallization or degradation of MDI and TDI. The new containers can be equipped with advanced insulation systems and temperature management solutions that support consistent performance in varying climatic conditions.

In addition, intelligent monitoring technologies allow operators to track key parameters during transit. This data-driven approach improves visibility, enables early detection of potential issues, and supports continuous improvement in logistics planning.

Safety as a Strategic Priority

Safety is not limited to regulatory compliance; it is also a strategic differentiator in chemical logistics. Kricon Group’s investment in high-specification tank containers reflects a broader commitment to protecting people, cargo, and infrastructure.

Enhanced valve systems, reinforced structural components, and optimized design for handling operations reduce the likelihood of incidents during loading, transport, and unloading. These features are particularly valuable for logistics partners operating across multiple jurisdictions with varying regulatory expectations.

By prioritizing safety at the equipment level, Kricon helps its clients mitigate risk, reduce insurance exposure, and strengthen trust with downstream partners.

Supporting Efficiency and Sustainability

Beyond safety and compliance, the new generation of tank containers is designed to improve operational efficiency. Standardized specifications simplify fleet management, while durable construction supports long service life and reduced maintenance requirements.

Efficient thermal performance and optimized design also contribute to sustainability goals. By minimizing product loss, reducing the need for reprocessing, and supporting more predictable transport conditions, these containers help lower the environmental footprint associated with chemical logistics.

Sustainability considerations are increasingly important for chemical manufacturers facing pressure from regulators, investors, and customers alike. Equipment that supports both safety and environmental responsibility offers a clear competitive advantage.

Backed by a Global Logistics Network

Kricon Group’s tank container solutions are supported by its established global logistics network. This enables seamless deployment across key industrial regions and ensures that clients can access consistent equipment standards regardless of route or destination.

For manufacturers and distributors of isocyanates, this combination of specialized equipment and international logistics expertise simplifies coordination and reduces complexity in cross-border operations. It also supports scalability as demand grows or supply chains evolve.

Setting New Benchmarks in Chemical Transport

The introduction of ISOPA-certified tank containers for MDI and TDI transport underscores Kricon Group’s role in shaping best practices within the chemical logistics sector. Rather than responding reactively to regulatory change, the company is proactively investing in solutions that anticipate future requirements.

As chemical supply chains become more complex and expectations around safety, transparency, and sustainability continue to rise, purpose-built logistics equipment will play an increasingly central role. Kricon’s latest tank containers represent a step forward in aligning operational performance with industry standards and long-term strategic goals.

Conclusion

Transporting MDI and TDI safely is a challenge that demands specialized expertise, advanced engineering, and strict adherence to industry guidelines. Kricon Group’s new ISOPA-certified tank containers address these demands through thoughtful design, robust safety features, and a clear focus on compliance and efficiency.

For companies involved in the production, distribution, or logistics of isocyanates, these containers offer a reliable solution that supports both operational excellence and regulatory confidence. As chemical logistics continues to evolve, innovations of this kind will be essential in setting new standards for the industry.

AI Adoption Trends in the U.S. Auto Transport Market: A Platform Perspective

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DOI: https://doi.org/10.26643/rb.v118i10.9150

Abstract

AI adoption in U.S. transportation and logistics is shifting from experimentation to operational deployment, driven by cost pressure, capacity variability, customer expectations for transparency, and the growing availability of real-time operational data. In the auto transport segment (vehicle relocation, dealer moves, consumer shipping), platform-based models are accelerating adoption by standardizing data inputs (routes, vehicle types, availability), automating quoting and matching, and adding “control-tower” visibility across fragmented carrier networks. This article synthesizes recent research and industry reporting on AI in logistics and applies it to the U.S. auto transport market, highlighting practical use cases, common barriers (data quality, trust, integration), and what “responsible AI” looks like in platform settings.


1) Why AI is gaining traction in auto transport in 2026

The U.S. auto transport market sits at the intersection of trucking’s structural inefficiencies and consumer-grade expectations for instant information. Two dynamics matter:

Operational complexity and emissions pressure. Freight logistics is often cited as contributing roughly 7–8% of global greenhouse-gas emissions, and organizations like the World Economic Forum argue AI can reduce freight-logistics emissions through better planning and efficiency (e.g., route optimization, capacity utilization).
While auto transport is a niche within freight, it inherits the same efficiency levers—empty miles, routing, and exception management.

A maturing AI adoption baseline. Broad cross-industry surveys suggest AI adoption has risen sharply (e.g., McKinsey’s reporting of adoption levels around the low-70% range in early 2024 across surveyed organizations).
In transportation specifically, fleet/transport leadership surveys and trade reporting indicate growing AI usage—often concentrated in planning, route optimization, and operational efficiency—while simultaneously noting concern that the sector still lags other industries.

The implication: auto transport is adopting AI at a time when foundational digitization (tracking, electronic logs, more structured operational data) is already widespread.


2) The “platform perspective”: why platforms accelerate adoption

Auto transport has historically been broker-heavy and relationship-driven. Platforms change this by making the market more computable:

  • Standardized inputs: origin/destination lanes, vehicle operability, trailer type (open/enclosed), pickup windows.
  • Normalized supply signals: carrier availability, route density, historical lane performance, constraints.
  • Structured workflows: digital inspections, status updates, exception handling.

This matters because modern AI (including machine learning and optimization) performs best when the system has consistent, high-quality inputs and feedback loops.

Example: Haulin.ai as an applied platform pattern

Haulin.ai publicly describes itself as an auto shipping platform that generates instant, transparent quotes using AI that analyzes real-time carrier availability and route optimization.
From a platform-research lens, the useful (non-marketing) takeaways are:

  1. Transparent pricing logic: platforms can reduce information asymmetry by presenting route-specific quotes up front rather than vague ranges.
  2. Faster matching: algorithmic matching can shorten the “time-to-book” cycle, which is critical in markets where capacity changes daily.
  3. Always-on support workflows: some platforms pair automation with continuous support coverage to reduce disruptions during pickup/delivery coordination.

These are not unique to one company; they represent common platform affordances that make AI adoption more viable in vehicle transport.


3) What AI is actually being used for in U.S. auto transport

AI adoption in auto transport clusters into six practical use cases:

A) Dynamic pricing and quote accuracy

Pricing in auto transport is sensitive to lane demand, seasonality, fuel, and carrier positioning. Platforms increasingly use models that incorporate real-time signals to reduce “quote drift” (quoted price vs booked price). Haulin.ai’s public explanation frames this as pricing informed by carrier availability, lane demand, and fuel trends to produce final quotes.

Research angle: algorithmic pricing reduces manual brokerage overhead, but also introduces governance needs (auditability, fairness, and guardrails).

B) Carrier matching and capacity utilization

A persistent freight problem is empty or underutilized miles (“deadhead”). Estimates vary widely; industry discussions commonly cite ranges (e.g., 15–35%) depending on fleet type and measurement method.
In auto transport, deadhead shows up when a carrier must reposition to reach a pickup or return from a drop-off without a vehicle load. Matching algorithms attempt to reduce this by improving backhaul fit and route chaining.

C) Route optimization and ETA prediction

AI-enabled route planning integrates traffic, weather, and constraints (pickup windows, driver hours). In broader logistics, route optimization is routinely named among the top AI benefits by fleet executives.
Even more important in consumer auto shipping is predictable ETAs and proactive alerts—an expectation increasingly treated as “standard” in many transport experiences.

D) Exception detection and “control tower” workflows

Delays (weather, mechanical issues, facility access problems) often dominate customer dissatisfaction. Modern logistics visibility emphasizes continuous monitoring and exception handling—detecting risk early and triggering human-in-the-loop actions.
Platform architectures are naturally suited to implement exception management because they sit between shipper demand and carrier execution.

E) Compliance and operational telemetry

Trucking compliance digitization also underpins AI adoption. For example, FMCSA’s ELD requirements have driven standardization in logging data for many carriers, increasing the availability of structured operational signals (even if not directly used for consumer-facing tracking).

F) Customer communication (GenAI)

GenAI is being deployed in customer support across logistics to reduce response time and handle routine inquiries. Industry reporting points to “agentic” or AI-assisted support in freight settings as a growing trend.
In auto transport, this typically translates into faster answers to: pickup scheduling, driver contact windows, ETA updates, and documentation questions.


4) What’s slowing adoption: four recurring barriers

Despite momentum, research and trade reporting consistently cite constraints:

1) Data quality and fragmentation

Logistics is multi-actor: shippers, brokers, carriers, terminals, and consumers. Reuters notes that AI’s real-world impact depends heavily on integration and high-quality data, and that siloed systems can block progress.

2) Trust, transparency, and perceived “black box” decisions

Algorithmic pricing and matching can be perceived as opaque. This is why transparent quote explanations (inputs, constraints, what changes the price) are becoming a functional requirement, not a marketing feature.

3) Talent and readiness gap

Even when organizations explore many AI use cases, fewer have the internal capability to scale them (skills, roadmaps, prioritized deployment). McKinsey’s distribution-focused analysis highlights this “explore vs scale” gap in adjacent sectors.

4) Security and governance concerns

U.S. transport/shipping professionals have reported hesitation tied to security and technical expertise constraints.
In auto transport, personally identifiable information, addresses, and vehicle details elevate the importance of data governance.


5) A practical “platform maturity model” for AI in auto transport

From a platform standpoint, AI adoption tends to progress in phases:

  1. Digitize the workflow (quotes, orders, dispatch, status updates)
  2. Instrument the operation (tracking, structured events, inspection data)
  3. Optimize (pricing models, route planning, carrier matching)
  4. Automate with guardrails (exception prediction, AI-assisted support, proactive rebooking)
  5. Measure outcomes (on-time delivery, claim rates, quote-to-book conversion, cost variance)

The maturity model matters because many failures come from skipping steps 1–2 and expecting AI to compensate for missing or inconsistent data.


6) What “useful USPs” look like without marketing language

When evaluating a platform like Haulin.ai (or comparable systems) in research terms, the most defensible differentiators are operational:

  • Transparent, route-specific quoting that reduces price uncertainty for consumers.
  • Real-time carrier availability signals are used to improve booking realism (less “bait-and-switch” behavior in theory, if governed properly).
  • Workflow continuity: integrated scheduling + status updates + support reduces coordination friction, especially during exceptions.

These are best assessed with measurable KPIs (price variance, pickup punctuality, damage claims, and dispute rate), not adjectives.


7) Research implications and what to watch next

Three trends are likely to shape AI adoption in U.S. auto transport through 2026–2028:

  1. Agentic operations: AI that doesn’t only “recommend” but can execute bounded actions (e.g., propose reroutes, suggest carrier swaps) with human approvals.
  2. Stronger visibility expectations: consumers increasingly expect proactive updates and narrower delivery windows.
  3. Decarbonization pressure: improving utilization and reducing empty miles becomes both an economic and sustainability lever—one of the clearest value cases for AI in freight-adjacent markets.

Conclusion

AI adoption in the U.S. auto transport market is best understood through a platform lens: platforms standardize inputs, unify fragmented actors, and create the data foundation that makes optimization and automation feasible. The most impactful near-term applications are dynamic pricing, carrier matching, route/ETA prediction, exception management, and AI-assisted communication—each dependent on data quality and governance. Haulin.ai provides a current example of how platform capabilities (transparent pricing, real-time availability analysis, and workflow support) can operationalize AI in consumer vehicle shipping without requiring the end-user to understand the underlying complexity.