The study aims to evaluate the impact of ergonomics practices on enhancing the operational performance of the Indian Post manual sorting centre. A survey based on the Rehabilitation Bio-Engineering Group Pain Scale (RBGPS), National Aeronautics and Space Administration - Task Load Index (NASA-TLX), and subjective ratings was created to measure the ergonomic risks for the postal employees. The respondents were a total of 323 postal service employees and 225 postal department employees. The influence of each ergonomic risk factor was investigated using Structural Equation Modelling (AMOS-SEM). This study aids in the implementation of a lean system with ergonomic considerations for productivity enhancement in a service organization at the Indian Postal Sorting Centre in Chennai. The results of this study show that Visual Ergonomics (VE) has a positive and significant impact (β = 0.532, p<0.001) on Operational Performance (OP), followed by Physical Ergonomics (PE) (β = 0.301, p<0.001) and Cognitive Ergonomics (CE) (β = 0.104, p<0.001) on OP. This study aids India Post in assessing its policies to ensure the effectiveness of lean service (LS) implementation while taking ergonomics into account. The cost of implementing the adjustments was around INR 0.17 million. The effects of improved production performance and work environment were predicted to be repaid within 45 days after deployment. This study focuses on the empirical model for testing ergonomic risks in India's postal service industry, which is limited to the Indian postal service industry. Ergonomic concepts have long been employed to provide social safety for human well-being. Regarding the postal sector, India has one of the world’s largest postal services, and postal employees are exposed to significant ergonomic risk. Consequently, it is critical to analyse their ergonomic level and identify the primary elements contributing to the risk.

Circular supply chains depend on collaboration among manufacturers, suppliers, and downstream partners, yet many industries still lack partnership-level performance measures that can guide the shift from linear “take–make–dispose” practices to circular operations. This study develops and validates a set of circular partnership performance indicators for the paint and coatings sector using a sustainable balanced scorecard logic. An expert-based hybrid approach was applied in the Indian paint and coatings industry to screen indicators from the literature and to model their cause–and–effect relationships. The results validate 23 indicators across six perspectives and show that resource and energy efficiency, financial strategy, and technology competency act as key drivers that shape stakeholder transparency, internal strategy, and risk management. The validated indicators provide a practical basis for monitoring circular supply chain partnerships and for prioritising capability-building efforts when firms face limited resources. The driving indicators that propel the CSC partnership to the practitioners include resource cycling, reduction of costs, quality enhancement, value co-creation, integration of technology, and the innovation that is green.

Sustainability is becoming a significant concern in academic institutions worldwide. This issue is critical in Asian countries, which are more vulnerable to adverse environmental effects. Universities in these regions can play a pivotal role in mitigating their environmental impact by adopting green human resource management (GHRM). While the potential of GHRM in achieving sustainability is significant, research in this context remains limited and requires further exploration. This study applies the AMO theory (Ability–Motivation–Opportunity theory) to develop a framework for GHRM. The framework comprising seven aspects and twenty-five criteria was formed. The fuzzy Delphi (FDM) and decision-making trial and evaluation laboratory (FDEMATEL) hybrid methodology is used to analyze the data. The proposed framework is tested using data collected from several Asian academic institutions. The findings highlight that sustainability policy & institutional support, green hiring, and green organizational culture are necessary aspects of GHRM practices in Asian academic institutions and indicate their essential role in fostering sustainability.

PurposeThe objective of this study was to examine whether and to what extent Quality 5.0 approaches, with an emphasis in the study on the combination of advanced technologies, humanistic principles of leadership and sustainability, would influence key organizational outcomes. Whereas Quality 4.0 primarily focused on the role of automation and digital tools, Quality 5.0 is concerned with ethical use of artificial intelligence, staff commitment and engagement, along with associated responsibility to the environment, thus operating in close alignment with the Industry 5.0 framework. This study investigated the effects of three Quality 5.0 enablers - technological factors (TF), human-centric and managerial factors (HCMF) and sustainability and customer experience factors (SCEF) - on four outcome constructs: quality and performance outcomes (QPO), customer-centric outcomes (CCO), business and financial impact (BFI) and sustainability and ethical impact (SEI).Design/methodology/approachThe study employs structural equation modeling (SEM) using SmartPLS to evaluate the relationships among Quality 5.0 variables. Data were collected through a structured survey administered across Indian organizations from diverse sectors, including manufacturing, services and education.FindingsThe results confirm that TF, HCMF and SCEF have a positive and significant influence on all four outcome variables (QPO, CCO, BFI and SEI). This demonstrates that the effective implementation of Quality 5.0 requires not just technological adoption but also strong leadership, employee engagement and sustainability-focused strategies.Research limitations/implicationsThe results are contextually anchored in the Indian organization context and may impede the generalizability in other spaces; hence, the findings offer an empirical basis for practical application of Quality 5.0 initiatives for real-world quality management frameworks. The results suggest that technology in its own right is not sufficient and that the human and ethical dimensions play an essential role in quality transformation.Originality/valueThis study is among the first to propose and empirically validate an integrated Quality 5.0 framework. It contributes both theoretically and practically by linking digital, human-centric and sustainability drivers to multi-dimensional quality outcomes, offering organizations a strategic roadmap for responsible and future-ready quality management.

Start-ups are essential to a country’s overall economic development. The advancement of new technologies influences start-ups to adopt new strategies to remain competitive in the market. Artificial intelligence and machine learning (AI/ML) are relatively new technologies that are influencing young entrepreneurs to form new start-ups in this domain. However, new technological ventures are accompanied by a modified list of challenges that require attention at various levels. Unpreparedness for any serious challenge may cause the start-up to fail prematurely. A study reports that over 90% of technology start-ups fail prematurely. Hence, it is the need of the hour to identify and evaluate the challenges faced by AI/ML start-ups. This study aims to identify, establish relationships among, and prioritize various challenges associated with AI/ML start-ups. At first, various challenges that leads a start-up failure is evaluated from the literature, then decision making techniques such as multi criteria decision making (MCDM) methods(Measurement of Alternatives and Ranking According to Compromise Solution, and Decision-Making Trial and Evaluation Laboratory) and interpretive structural modeling (ISM) methods have been applied to first identify the relevant challenges for AI/ML start-up, and then evaluate their importance by understanding their interrelationships and evaluating their importance corresponding to each other. It is observed that among fifteen important challenges that hinder the sustainability of an AI/ML start-up, three challenges were critical at the beginning of the start-up, seven challenges are critical in the sense that they require periodic observations, three challenges are dependent upon other considered challenges, and two challenges are mostly unpredictable in nature. This identification will largely help new entrepreneurs understand the challenges in an AI/ML start-up and also help older entrepreneurs understand how the various challenges are interlinked.

Strategic thinking is becoming a central managerial capability and an essential driver of competitive differentiation. Although the concept has been actively discussed since its inception in the 1980s, and the field continues to thrive, no comprehensive systematic review has yet synthesized this body of work. The objective of the study is to systematically review and integrate the existing literature on strategy thinking in order to identify dominant themes, theoretical foundations, methodological trends, and future research directions. This systematic literature review (SLR) using bibliometric analysis and VOS viewer surpasses traditional literature reviews by offering a comprehensive overview of the subject matter. Specifically, the review reveals that national cultural dimensions and strategic environmental assessment significantly shape the cognitive styles, analytical capability, and decision-making approaches for strategic thinking. The study makes an original contribution by exploring the national culture dimensions (Power Distance, Uncertainty Avoidance, individualistic-collectivistic, and Masculine-Feminine) and Strategic Environmental Assessment (SEA) in influencing strategic thinking. The findings also highlight research gaps, particularly in longitudinal examinations and cross-cultural comparative studies. The results offer guidance for multinational organizations, policymakers, and educators seeking to develop culturally aware strategic capabilities and inform future research trajectories.

The study aims to investigate the changing patterns of prominent authors, organizations, nations, and academic research publications on financial literacy (FL) research and its associated factors, such as financial behavior (FB), financial knowledge (FK), and financial attitude (FA). This bibliometric study collected data from 2005 to 2025 from the Scopus database and analysed it using VOS Viewer and the biblioshiny software. The results highlighted that relatively less research was conducted during the early stages. However, there was a progressive increase in the number of publications, particularly in 2023, with 87 papers, and in 2024, with 88 papers. The University of Rhode Island is the top academic institution, and Annamaria Lusardi is the most renowned author. The country that contributes most to financial literacy (FL) and its many associated elements is the United States. The most popular article is "The Economic Importance of Financial Literacy: Theory and Evidence," while the leading source is “Journal of Consumer Affairs.” In order to identify important themes pertaining to financial literacy, behavior, knowledge, and attitudes, this study also performed a cluster analysis. In order to create more accessible financial products, promote consumer financial participation, and encourage better financial habits, all of which can contribute to financial inclusion and economic stability, companies and financial institutions can implement guiding principles in financial literacy initiatives at the managerial level. The study adds significant knowledge to the literature of personal finance research. FL is crucial in encouraging people to make deceptive decisions, which highlights the need for a fundamental grasp of financial instruments to prevent acquiring the wrong financial services.

This study aims to investigate the impact of High-performance HR practices (HPHRPs) integrated with Artificial Intelligence (AI) on employees’ performance. The new AI-HR paradigm was developed in the AMO framework (Ability, Motivation, and Opportunity) for employees’ performance. It was empirically tested on a sample of non-HR employees’ performance in a few Indian organizations. Employee performance was found to be considerably impacted by an AI-governed career advancement approach and AI-integrated job flexibility measures. These two factors were found to influence significantly the motivation and the opportunity-related aspects of the employees’ performance. The results give HR managers guidance on how to strategically plan different HR activities with AI support to solicit high employee performance. The research is limited in not considering the digital divide and the shortcomings of AI integration with respect to data security and authenticity. The future work should assimilate these also into understanding employees’ high performance.

This paper uses a systematic literature review (SLR) of 280 peer-reviewed articles to evaluate the function of carbon footprint (CFP) management as a motivator for sustainability in industry. The study considers industry perspectives and acknowledges the growth of CFP research as a key measurement area for organizations as well as a strategic enabler to align industry with global climate targets. The study identifies relevant gaps, particularly the absence of comparative literature related to the effects of CFP non-compliance relative to regulations, and a lack of longitudinal studies regarding the long-term effects of CFP policies being initiated or abandoned. The study provides a linkage to actionable sustainable practices, as a guided structure through five stages of industrial production, and makes suggestions for actionable outcomes for researchers, industries, and policy, encouraging a more comparative approach to and integrated management of CFP in core industrial strategy to enhance sustainability benefits.

Research on rural and sustainable entrepreneurship (SE) has gained significant academic attention in recent years, especially in relation to achieving the United Nations' Sustainable Development Goals (SDGs) by 2030. Despite this growing interest, recent studies predominantly analyze rural entrepreneurship (RE) and SE separately, providing limited integrated insights into the functioning of sustainability-oriented entrepreneurial activities in rural settings. This study aims to present a bibliometric analysis alongside the theories-characteristics-contexts-methods (TCCM) framework to investigate the nexus between RE and SE and the contributions they have towards sustainable development between 2000 and 2025. Using 245 publications retrieved from the Scopus database, the analysis was conducted with the support of Biblioshiny and VOSviewer. The research is also characterized to know the convergence of RE and SE, and how sustainable entrepreneurial activities in rural settings are able to contribute to the development objectives. An automated workflow that includes analysis and citation, co-authorship, and collaboration networks of journals, authors, countries, key articles, and thematic areas is identified in the study. More significantly, the analysis identifies the concept of sustainable rural entrepreneurship (SRE) as an integrative concept, which links sustainability-based entrepreneurial activities and place-based rural development issues. Within the framework of TCCM, the research offers a critical synthesis of prevailing theories, situational focus, defining features, and methodological practice, as well as conceptual fragmentation and substantially unexplored areas of research. The current study contributes to the existing body of literature by going beyond descriptive mapping by providing theory-based explanations of how sustainable entrepreneurial practices can ensure environmental sustainability, community development, and economic resiliency in rural areas. The results have significant implications for researchers, policymakers, and practitioners who want to develop strategies and policies that can facilitate sustainable business in rural regions and progressive development towards the SDGs.

Research background: As climate concerns intensify globally, organizations face increasing pressure to integrate sustainability into their core human resource strategies. Although green human resource management has received growing scholarly attention, the role of digital enablers, particularly gamification and AI-driven personalization, remains insufficiently examined. In particular, limited empirical evidence exists on how technologically enabled green HR interventions contribute to the development of employee environmental literacy through organizational learning mechanisms. Purpose of the article: This study investigates how technologically enabled green human resource management practices influence employee environmental literacy. It further examines the sequential mediating roles of sustainable learning engagement and green knowledge internalization, while also exploring the moderating influence of contextual and individual factors within organizations. Methods: Using survey data collected from HR managers working in multinational corporations, the study applies a dual analytical approach. Partial least squares structural equation modeling (PLS-SEM) is used to test the hypothesized structural relationships, while machine learning algorithms (XGBoost, LASSO, and Random Forest) are employed to evaluate predictive relevance and identify nonlinear relationships within the data. Findings & value added: The results indicate that gamified green human resource management practices and AI-driven green human resource personalization significantly enhance employee environmental literacy. The analysis also confirms the sequential mediating roles of sustainable learning engagement and green knowledge internalization, demonstrating that technology-enabled human resource interventions influence environmental literacy primarily through learning-based mechanisms. Machine learning results further support the predictive relevance of the proposed framework, with XGBoost achieving the strongest predictive performance, followed by Random Forest and LASSO regression. The partial least squares structural equation modeling analysis confirms sequential mediation (the gamified green human resource management path; the AI-driven green human resource personalization path), and green organizational climate moderation is significant. In addition, green organizational climate and environmental values strengthen key relationships in the model, highlighting the importance of contextual and individual factors. By integrating ability-motivation-opportunity theory, the knowledge-attitude-behavior model, and social cognitive theory within a unified framework, this study contributes to the green human resource management literature and provides practical insights for human resource leaders seeking to design technology-enabled sustainability learning systems.

The present study examines Ethical Phone Inc.’s approach to producing environmentally sustainable smartphones. Operating within a niche market, the company’s business model is distinctive and remains largely underexplored within the wider smartphone industry. Given the absence of third-party verification and the evolving nature of its operations, the analysis relies primarily on company-generated data to assess the model. Addressing this gap, the study offers an original evaluation of Ethical Phone Inc.’s sustainable business practices, complemented by stakeholder perspectives. Using a case study methodology, the research draws on both primary and secondary sources, with particular emphasis on Ethical Phone Inc.’s Impact Reports. Data were compiled into a comprehensive dataset and analysed using NVivo, followed by manual refinement to identify key themes and theoretical insights. To strengthen validity, a focus group of seven experts, including company representatives, reverse logistics specialists, circular economy consultants, industry marketing professionals, and sustainability academics, critically assessed the firm’s strategies and their scalability. The findings indicate that Ethical Phone Inc.’s model aligns closely with Stakeholder Theory, the Triple Bottom Line, and Circular Economy principles. While the model demonstrates significant transformative potential for the smartphone industry, the study also identifies systemic barriers to wider adoption, including planned obsolescence, rapidly evolving consumer preferences, high ethical sourcing costs, and limited reverse logistics infrastructure. Ultimately, the study outlines pathways for broader industry adoption, including incremental modularity, collective sourcing mechanisms, supportive regulatory frameworks, and enhanced consumer engagement.

This study conducts a bibliometric analysis of 612 peer-reviewed articles published between 2005 and 2023 to map the intersection of customer engagement (CE), social media, and technology. Using VOSviewer, Biblioshiny, ScientoPy, and Power BI, the study identifies four principal research clusters: behavioral engagement dynamics, social-media-driven engagement, technology-mediated interaction, and loyalty outcomes. The findings reveal an annual growth rate of 31.7% in CE publications, a clear scholarly preference for social media over generic technology constructs, and the dominance of Social Exchange Theory, Uses and Gratification Theory, and the SOR model as theoretical anchors. The present study renders a substantive contribution to the extant body of scholarly literature by conducting a comprehensive bibliometric mapping of the convergence across the three aforementioned constructs. This intersection remains unaddressed in prior systematic reviews, which have predominantly focused on more narrowly defined constructs. Practically, the findings guide managers in designing platform-specific engagement strategies and evidence-based digital transformation roadmaps. Limitations include reliance on a single database (Scopus) and journal articles only; future research should expand to Web of Science and grey literature.

The current research proposes a successful hybrid method for solving the capacitated vehicle routing problem (CVRP) that combines the Clarke and Wright savings algorithm (CWSA) with customer prioritization. The proposed framework integrates customer-oriented decision criteria into the routing process in addition to the traditional goal of resolving the vehicle routing problem (VRP). The primary research approach goal is to produce more effective routing solutions and lower total transportation costs and distance without going beyond vehicle capacity. The intuitionistic fuzzy Technique for Order Preference by Similarity to an Ideal Solution (TOPSIS) method is combined with the CWSA to create a novel approach for this aim. In this manner, many problem-specific factors could be examined alongside the distance criterion for establishing the routes. The proposed method is validated through a real-world case study in the beverage supply chain, achieving a 14% reduction in total travel distance compared to existing routing practices. The proposed research reduces the overall transportation cost without exceeding vehicle capacity and, in the end, enhances customer-oriented routing decisions by considering quality, reliability, sustainability perception, and cost-related service criteria, corresponding to the numerical example. In addition, the suggested approach indicates that the proposed approach achieves improved routing efficiency while incorporating customer-oriented service considerations, thereby providing a more realistic and flexible decision-making framework compared to traditional distance-based routing methods.

Purpose Manufacturing firms in the textile sector face simultaneous pressure to enhance responsiveness, maintain quality, shorten lead times, and align production with sustainability expectations. In the current Industry 4.0/5.0 environment, flexible manufacturing systems (FMS) are increasingly viewed as strategic enablers of product variety, speed and resource efficiency. However, managers still lack clear evidence on which performance variables deserve priority in textile settings. This study, therefore, identifies, classifies and prioritizes the most influential FMS performance variables for textile manufacturing. Design/methodology/approach A triangulation design was adopted. First, a focused literature review was undertaken to compile candidate FMS performance variables. Second, semi-structured interviews with 17 experts and a questionnaire survey of 135 domain experts were used to validate the variables for the textile context. Third, 19 validated variables were classified into 3 major categories, quality, productivity and flexibility, and prioritized using the best-worst method (BWM), a multi-criteria decision-making approach selected for its lower comparison burden and stronger consistency. Findings The study identifies 19 performance variables that are significant for FMS in textile industries and classifies them into quality, productivity and flexibility categories. The results show that quality-related variables dominate the overall ranking; automation emerges as the most influential quality variable, unit manufacturing cost is the leading productivity variable and the use of automated material-handling devices is the most important flexibility variable. These findings offer an evidence-based basis for sequencing FMS investment and improvement efforts. Research limitations/implications The results are derived from expert judgements and a textile-sector case context and should therefore be interpreted with appropriate contextual caution. Even so, the study offers actionable implications for managers by showing which variables should be prioritized first under limited resources. The findings also suggest that future research should test the framework through larger cross-sector datasets and incorporate broader sustainability and digitalization variables. Originality/value The originality of the study lies not simply in applying BWM, but in contextualizing FMS prioritization for the textile sector at a time when digitalization, sustainability and circular-economy objectives are reshaping manufacturing choices. The paper shows how textile-specific operational constraints influence the relative importance of FMS performance variables in ways that are not fully captured by prior generic manufacturing studies.

In generating, building, and retaining a competitive advantage through the use of knowledge and collaborative practices, education is crucial in the globalization of business. The Critical Success Factors (CSFs) of the Educational Supply Chain (ESC) have been recommended by literature reviews as responsiveness to numerous impacting CSF themes; however, it is never easy for practitioners to enhance all aspects at once. Therefore, there is a need to derive CSFs in line with the importance and objectives of ESC. This study identifies, categorizes, and ranks the CSFs for the ESCs through the entropy objective weighting and TOPSIS (Technique for Order Performance by Similarity to Ideal Solution) method, which is validated through observational semi-structured interviews. The analysis identifies eight CSF themes named, the input-operation-output concept (C1), multiple stakeholder involvements (C2), IOTs in ESC (C3), information sharing (C4), transparency (C5), outsourcing (C6), insourcing (C7) and after-sales service versus capacity building training courses (C8) among the ESC stakeholders and trustworthy teamwork to exchange knowledge within ESC for improving effectiveness and efficiency. The mixed-method study adds to the existing literature on the responsiveness of CSFs in ESC by offering advice on how institutions and organizations can recognize CSFs and gradually implement them to significantly increase the effectiveness of the overall ESC performance. With this suggested approach, the managers can identify the CSFs in ESC responsiveness using a decision support tool that is more precise, efficient, and systematic. This study contributes to the digitization of ESC by enhancing multimedia. For efficient course administration, the teacher will be able to oversee a variety of auxiliary technological applications, such as examinations and assignments, discussion boards, and grading. Additionally, educators may also implement effective teaching strategies to create an engaging classroom by including multimedia, video, and teaching notes.