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In an era of rapid telemedicine expansion, patient loyalty is paramount for effective health-care delivery. This study aims to understand loyalty behaviours in telemedicine to refine services. The primary objectives are to elucidate the current state of scholarly inquiry concerning loyalty within the telemedicine sphere and to address existing research deficiencies within this domain. This exploration seeks to provide valuable insights and contribute to the advancement of knowledge in this critical area of inquiry.

This study uses a bibliometric analysis to investigate patient loyalty in telemedicine. By reviewing existing literature and analysing bibliometric data, the research identifies key deficiencies and addresses pertinent research questions within the telemedicine loyalty domain. This methodological approach aims to offer a comprehensive understanding of the current state of research and highlight areas requiring further investigation.

This study reveals significant gaps in existing research on telemedicine loyalty, identifying a need for more focused studies on patient loyalty behaviours. Through a bibliometric analysis, the findings highlight critical areas for improvement and potential strategies for enhancing patient loyalty in telemedicine. These insights are crucial for refining telemedicine services and ensuring effective health-care delivery.

The findings may not capture all dimensions of patient loyalty in telemedicine, requiring further empirical studies. Future research should expand on these limitations by incorporating diverse methodologies and broader data sets to validate and extend the study’s insights.

The insights from this study can help health-care providers refine their telemedicine services to enhance patient loyalty. By understanding loyalty behaviours, providers can develop targeted strategies to improve patient satisfaction and retention. These practical implications are essential for the continuous improvement of telemedicine services, ensuring they meet patient needs and expectations effectively.

Enhancing patient loyalty in telemedicine leads to significant societal benefits, particularly by improving health-care access for underserved populations in rural or economically disadvantaged areas. Continuous and trusted care helps reduce health-care disparities and fosters health equity, positively impacting quality of life through timely medical consultations. In the context of medical tourism, telemedicine facilitates reliable remote consultations, boosting confidence in health-care systems abroad and benefiting local economies. In addition, tourists can access health-care services while travelling, enhancing their sense of safety and well-being. Overall, these advancements highlight telemedicine’s potential to create a more equitable and accessible health-care landscape.

This study fills a critical gap in telemedicine research by focusing on patient loyalty, an area often overlooked in existing literature. The bibliometric analysis offers a novel approach to understanding and addressing loyalty behaviours. The findings contribute valuable knowledge, advancing the discourse on telemedicine loyalty and providing a foundation for future research and service improvements.

Industries have been the most significant contributor to carbon emissions since the beginning of the Industrial Revolution. The transition to Industry 5.0 (I5.0) marks a pivotal moment in the industrial revolution, which aims to reconcile productivity with environmental responsibility. As concerns about the decline of environmental quality increase and the demand for sustainable industrial methods intensifies, experts recognize the shift toward the I5.0 transition as a crucial turning point.

This review study explores the convergence of green technological advancements with the evolving landscape of I5.0, thereby presenting a roadmap toward carbon neutrality. Through an extensive analysis of literature spanning from 2012 to 2024, sourced from the Scopus database, the research study unravels the transformative potential of green technological innovations, artificial intelligence, green supply chain management and the metaverse.

The findings underscore the urgent imperative of integrating green technologies into the fabric of I5.0, highlighting the opportunities and challenges inherent in this endeavor. Furthermore, the study provides insights tailored for policymakers, regulators, researchers and environmental stakeholders, fostering informed decision-making toward a carbon-neutral future.

This review serves as a call to action, urging collective efforts to harness innovation for the betterment of industry and the environment.

In past decades, artificial neural network (ANN) models have revolutionised various stock market operations due to their superior ability to deal with nonlinear data and garnered considerable attention from researchers worldwide. The present study aims to synthesize the research field concerning ANN applications in the stock market to a) systematically map the research trends, key contributors, scientific collaborations, and knowledge structure, and b) uncover the challenges and future research areas in the field.

To provide a comprehensive appraisal of the extant literature, the study adopted the mixed approach of quantitative (bibliometric analysis) and qualitative (intensive review of influential articles) assessment to analyse 1,483 articles published in the Scopus and Web of Science indexed journals during 1992–2022. The bibliographic data was processed and analysed using VOSviewer and R software.

The results revealed the proliferation of articles since 2018, with China as the dominant country, Wang J as the most prolific author, “Expert Systems with Applications” as the leading journal, “computer science” as the dominant subject area, and “stock price forecasting” as the predominantly explored research theme in the field. Furthermore, “portfolio optimization”, “sentiment analysis”, “algorithmic trading”, and “crisis prediction” are found as recently emerged research areas.

To the best of the authors’ knowledge, the current study is a novel attempt that holistically assesses the existing literature on ANN applications throughout the entire domain of stock market. The main contribution of the current study lies in discussing the challenges along with the viable methodological solutions and providing application area-wise knowledge gaps for future studies.

The study aims to highlight the barriers faced by the entrepreneurs toward achieving sustainability in business and innovation cultivation by offering solutions for academicians, practitioners and policymakers. The study uses the resource-based view (RBV) theory to discuss how an organization’s resources and capabilities influence the competitive ambience and barriers faced by entrepreneurs.

The present research uses grey-causal modelling (GSC) to analyse the barriers against successful entrepreneurship.

The research focuses on the usefulness of dynamic capabilities, managing and cooperating resources in the entrepreneurship setting. The paper highlights the importance of resource gathering and nurturing as a method to combat scarcity. This research further identifies that financial limitations, regulatory obstacles, challenges to sourcing qualified labour, poor infrastructure and technology, limited mentorship opportunities, lack of scalability, low initial cost barriers in product development and risk-averse attitudes are the major factors hindering entrepreneurs from obtaining sustainable business and innovation.

The contribution of this research to the literature is that it assesses RBV theory within the realm of entrepreneurship, providing a different perspective on resources and capabilities as well as the challenges faced by entrepreneurs. The systematic approach to the analysis and prioritization of various barriers is innovative, and it adds knowledge in this area.

This study aims to extend and explore patterns and trends of research in the linkage of big data and knowledge management (KM) by identifying growth in terms of numbers of papers and current and emerging themes and to propose areas of future research.

The study was conducted by systematically extracting, analysing and synthesizing the literature related to linkage between big data and KM published in top-tier journals in Web of Science (WOS) and Scopus databases by exploiting bibliometric techniques along with theory, context, characteristics, methodology (TCCM) analysis.

The study unfolds four major themes of linkage between big data and KM research, namely (1) conceptual understanding of big data as an enabler for KM, (2) big data–based models and frameworks for KM, (3) big data as a predictor variable in KM context and (4) big data applications and capabilities. It also highlights TCCM of big data and KM research through which it integrates a few previously reported themes and suggests some new themes.

This study extends advances in the previous reviews by adding a new time line, identifying new themes and helping in the understanding of complex and emerging field of linkage between big data and KM. The study outlines a holistic view of the research area and suggests future directions for flourishing in this research area.

This study highlights the role of big data in KM context resulting in enhancement of organizational performance and efficiency. A summary of existing literature and future avenues in this direction will help, guide and motivate managers to think beyond traditional data and incorporate big data into organizational knowledge infrastructure in order to get competitive advantage.

To the best of authors’ knowledge, the present study is the first study to go deeper into understanding of big data and KM research using bibliometric and TCCM analysis and thus adds a new theoretical perspective to existing literature.

This paper examines the dynamic interplay between Circular Economy (CE) and Supply Chain (SC). Further, this paper develops a framework indicating the transition from conventional SC to SC 4.0. As it addresses the separate bodies of literature on CE and SC 4.0, the study attempts to bridge the gap by examining barriers to SC 4.0 adoption in CE.

The article integrates bibliometric analysis with Total Interpretive Structural Modeling (TISM) and MICMAC analysis, thereby enriching the methodological rigour in investigating the barriers to SC 4.0 adoption within the CE context.

The paper provides insights into research trends, influential scholars, journals and prominent institutions through bibliometric analysis. Also, the findings identify four broad areas of driving, autonomous, linkage and dependent barriers to facilitate a comprehensive understanding of their impact and interdependencies.

The findings imply that effective policy interventions, enhanced management practices, and the adoption of technological innovations are essential for overcoming barriers to SC 4.0. The research recommends that stakeholders focus on fostering collaborative networks, building competencies in line with CE requirements, and leveraging big data for strategic supply chain decision-making.

This work contributes to the advancement of the circular digital supply field by consolidating research streams, uncovering innovation prospects, and shaping a well-informed research agenda. The distinct contribution lies in its categorization of these barriers into driving, autonomous, linkage, and dependent barriers, offering a novel perspective on the structural dynamics impeding the integration of SC 4.0 in CE.

The paper aims to enhance the understanding of robust food supply chains (FSC) by exploring the capabilities of various digital technologies and examining their interactions.

This study finding shows that digital technology enhances the resilience of the FSC by improving visibility, traceability and adaptability. This resilience provides a competitive advantage, ultimately enhancing the overall business performance.

In developing countries, inadequate infrastructure, poor Internet connectivity and diverse stakeholder systems pose challenges to implementing advanced digital solutions in the FSC.

This paper is among the first to investigate the impact of digital technology on FSC resilience, exploring visibility, flexibility and collaboration.

India has been withstanding increasing pressure of enrolment in the higher education system, resulting in the creation of new universities in consonance with the recommendations of the Knowledge Commission (2007). Barring a few institutions of paramount excellence, the mushrooming universities fail to conform to equitability of quality and standards, that is teaching-learning-dissemination and research, except for accommodating higher gross enrolment ratio. It has resulted in an asymmetric and sporadic development of human resources, leaving a large basket of learners out of the pursuit for aspiring higher academic, research and professional enrichment. The country needs to develop an innovative common minimum curriculum and evaluation framework, keeping in view the trinity of diversity, equity and inclusion (DEI) across the Indian higher education system to deliver human resources with equitable knowledge, skill and intellectual acumen.

The paper has been developed using secondary information.

The manuscript has developed an innovative teaching-learning framework that would ensure every Indian HEI to follow a common minimum curriculum and partial common national evaluation system so that the learners across the country would enjoy the essence of equivalence.

This research has designed a comprehensive model to integrate the spirit of the “DEI” value proposition in developing curriculum and gearing common evaluation. This would enable the country to reinforce the spirit of social equity and the capacity to utilise resources with equitability and perpetuity.

The globalization of markets poses great challenges, and thus, the manufacturing businesses trying to expand their operations to cater to a global audience have to undergo significant transformations. Therefore, this research aims to identify key challenges and elucidate the critical success factors (CSFs) required for the global growth of manufacturing companies on a worldwide scale.

A range of interval-valued spherical fuzzy sets (IVSFs) and flexible methodologies such as the analytic hierarchy process (AHP) and data envelopment analysis (DEA) have been employed to evaluate the issues in detail. It calculates the effectiveness delivered by each critical success factor (CSF) and identifies the factors acting as a barrier to global market penetration.

This research highlights the transformative potential of smart manufacturing in developing economies, identifying CSFs such as government support, cost optimization and resilient supply chain management as essential for overcoming obstacles like over-reliance on foreign technologies, regulatory rigidity and skill gaps. The integration of IVSFS with AHP and DEA models offers actionable insights to foster localized innovation, reduce foreign dependencies and promote user-centric designs, aligning with the United Nations Sustainable Development Goals.

This study shows that IVSFs, AHP and DEA can be used together to estimate the global challenges of manufacturing firms in developing markets. The combination of efficient decision-making and these strategies is novel as it provides ways in which businesses in developing countries can deal with their obstacles and improve their competitiveness on the global stage.

Given growing concerns about water scarcity, this study aims to investigate the extent and quality of corporate water management disclosures (hereafter water disclosures) in countries and jurisdictions facing extremely high water-stress levels. Contextual factors, at a macro/country, meso/stock exchange and micro/company level, influencing water disclosures, are examined.

The authors adopted an institutional perspective, integrating multi-level organizational fields, including micro/company-level, meso/stock exchange-level and macro/national-level influences while considering factors such as corporate governance (CG), regulatory stringency, cultural traits, advocacy for environmental management, environmental performance and sustainability indices. The authors use a GRI 303-based index to evaluate water disclosures of the top 100 listed companies from 12 stock-exchanges based in extremely high water-stress countries over a five-year period from 2016to 2020. While checking for robustness, the authors evaluate the impact of normative, coercive and mimetic forces on water disclosures at country, stock exchange and company levels.

Overall, water disclosure rates/extent and quality remain low with only incremental improvements observed over the five-year period. In terms of drivers, at a micro-level, the authors find that robust CG positively impacts water disclosure quality. At a meso level, regulatory stringency, environmental advocacy and the presence of a sustainability index positively influence water disclosure quality. At a macro level, power distance, uncertainty avoidance and masculinity negatively impact water disclosure quality, whereas long-term orientation and uncertainty avoidance positively impact it. Furthermore, countries characterized by robust governance and high environmental performance negatively influence disclosure quality in water sensitive industries.

The findings may prove useful to policymakers and regulators, including stock exchanges, in strengthening water disclosure requirements. Standard-setters may consider introducing more guidelines to assist reporters in improving the quality of their disclosures. Practitioners (managers and assurance providers) may use the findings to benchmark corporate reporting practices.

The research provides insights that can inform policies promoting transparency and accountability around corporate use of societies’ scarce water resources. The study advances responsible water stewardship, aligning corporate actions with global sustainability goals, particularly around water scarcity. In doing so, these findings have implications that extend beyond corporate disclosure practices, impacting broader environmental conservation and resource management efforts.

The study examines corporate water disclosure rates and qualities in extremely high water-stress countries and jurisdictions. The evaluation of these disclosures using a GRI 303-based index generates a unique dataset that is analysed from a multi-level institutional perspective (micro, meso and macro) to provide insights into the factors influencing corporate water disclosure practices.