Despite being a pivotal area of research and practice, antitrust literature on platform companies lacks a policy and managerial toolkit. This gap is significant considering the need for a toolkit for thorough analysis of the ever-evolving antitrust issues. Therefore, this study has been undertaken with the intention to highlight the strategic importance of antitrust issues and to aid managerial decision-making with the support of a toolkit. To conduct the study, a deductive thematic analysis approach is adopted. The process of coding starts with analysing the US antitrust hearing. Multiple deliberations are undertaken to develop the common list of codes and subsequently to a higher-order theme. Further analysis of Google?s abuse of dominance across countries indicates that the antitrust divide continues to exist across the globe. The managerial toolkit centring on nine emerging antitrust themes provides a snapshot of antitrust regulations in a country. With platform companies becoming ubiquitous, a nuanced understanding of the factors constituting anticompetitive practices would be imperative for platform managers. ? 2026 Indian Institute of Management Kozhikode

The present research attempts to understand the challenges associated with the adoption of circular practices in developing economies by performing a systematic review in the agriculture sector. The systematic literature review is performed based on the PRISMA framework and 20 impediments related to CE adoption are identified. The study makes following novel contributions to the literature; (i) propose a novel taxonomy based on the extended PEST-O framework; (ii) explores the impact of identified impediments on SDG goals to comprehend the role of CE in sustainable development; and (iii) posits seven novel research questions that could facilitate the CE adoption in the agriculture sector. ? 2024 Taylor & Francis Group, LLC.

The investigation intends to contribute to the growing interest among academics and practitioners worldwide by advancing knowledge of how manufacturers can improve their 3P (planet, profit, and people) performance through systemic mechanisms. The objectives of this research are to (1) assess the effect of lean six sigma practices and green culture on developing circular manufacturing capabilities among manufacturers and (2) assess how such developed circular manufacturing capabilities translate into better 3P performance in the backdrop of Industry 4.0 technologies. In pursuit of the stated objectives, the research team conducted a survey of 232 manufacturers and analyzed the collected data using the structural equation modeling approach. The assessment demonstrates that the enactment of lean six sigma practices and the adoption of a green culture have a significant and positive influence on the development of circular manufacturing capabilities. This, in turn, leads to improvements in environmental, economic, and social performance (i.e., 3P performance). Further, it has been found that the utilization of Industry 4.0 technologies by manufacturers has a significant moderating effect on the impact of their circular manufacturing capabilities on their 3P performance. The results have substantial implications for administrators looking to streamline their adoption of Industry 4.0 technologies and lean six sigma practices and cultivate a green culture to enhance their competitive advantage and boost their reputation. ? 2025 The Author(s). Business Strategy and the Environment published by ERP Environment and John Wiley & Sons Ltd.

This study explores the perceptions towards corporate annual reports and its sections, and other announcements used for investment decisions by Indian individual investors; and to study differences in perceptions between user groups based on occupation. The data were collected through a questionnaire; descriptive statistics, and Kruskal?Wallis tests were used to analyse the results. Findings reveal that the three financial statements are most important, and performance highlights are the most understandable section in annual reports. Announcements made on stock exchanges are the most frequently used among other types of announcements, and users reported that they provide new information. User groups differed significantly in their perceptions about the importance and understandability of various sections of annual reports, and other announcements used for investment decisions. Copyright ? 2026 Inderscience Enterprises Ltd.

Generative AI (Gen-AI) is getting importance in enhancing business competitiveness and overcoming environmental and economic concerns. However, its adoption and readiness assessment is subjected to various complexities. Therefore, the presented study aims for exploring various readiness factors impacting Gen-AI adoption. With the help of the Technology-Organization-Environment (TOE) theoretical framework, the presented study provided the framework of 14 readiness factors (RF) to support the adoption. The readiness factors including quality control automation, talent availability, data security and governance, ecosystem access were explored using literature review and further confirmed using expert opinion. Also, seven criteria including connectivity, Cloud-Edge Orchestration, Semantic consistency, decentralization were identified. Analytic Hierarchy Process (AHP) was used to compute criteria weights. Then, readiness factors were mapped with seven criteria, and COPRAS method was used to prioritize the readiness factors. The top readiness factors investigated as digital infrastructure, ethical & regulatory preparedness, data readiness quality and maturity, and organizational readiness. In the next step, sensitivity analysis was conducted by changing criteria weights and analyzed that relative ranking of readiness factors remains same. This research results are highly useful for industry managers and practitioners in adopting Gen-AI and opens a revolutionary potential for conducting further research in this direction. ? 2026, Korean Society of Management Information Systems. All rights reserved.

Purpose ? This study investigates the mediation effect of financial well-being on the relationship between financial literacy, personal financial management behaviour and investment decision-making behaviour among women entrepreneurs in India. Design/methodology/approach ? A sample of 396 rural women entrepreneurs from four rural-dominated districts in Bihar, specifically Gaya, Muzaffarpur, Nalanda and Madhubani, was randomly selected for the study. The data collected underwent analysis using the partial least square structural equation modeling (PLS-SEM). Findings ? The study found a positive significant relationship between financial literacy and financial well-being in enhancing investment behaviour and personal financial decisions of self-employed rural women in Bihar. This underlines the importance of financial literacy and well-being in addressing rural women?s investment decision-making and personal financial management behaviour. Practical implications ? Acknowledging the critical importance of financial literacy and overall well-being, policymakers can develop focused financial literacy interventions and education initiatives to improve rural women entrepreneurs' knowledge and financial skills in Bihar. The study further contributes substantially to the existing body of research, especially the ?Theory of Planned Behavior?. Originality/value ? Understanding rural women entrepreneurs? financial literacy, investment decision-making behaviour, personal financial management behaviour and financial well-being is novel since it propels modern society?s economic and social advancements in the emancipation of women. Peer review ? The peer review history for this article is available at https://publons.com/publon/10.1108/IJSE-05-2024-0434. ? Emerald Publishing Limited

The integration of artificial intelligence (AI) into supply chains is reshaping decision-making, yet the role of large language models (LLMs) remains under-theorized and weakly connected to operational frameworks such as the Supply Chain Operations Reference (SCOR) model. Unlike conventional AI tools, LLMs are generative, rely on unstructured data, and introduce interpretability risks, creating distinct opportunities and challenges for supply chain management (SCM). This study adopts a two-phase, theory-driven approach to examine these challenges. First, LLM adoption barriers were identified through a comprehensive literature review and structured using the Technology?Organization?Environment framework and Dynamic Capability Theory, then validated using a Delphi study with industry experts. Second, the Combinative Distance-based Assessment and Comparative Solution (COCOSO) method was applied to prioritize the identified challenges. Results show that ?Understanding LLM Outputs,? ?Risk of Over-Reliance on AI,? and ?Limitations in Complex Optimization Problems? are the most critical barriers, indicating that interpretability and human?AI interaction outweigh data-related concerns emphasized in prior AI research. In contrast to existing AI-focused SCM research, this study contributes by providing a theory-informed, expert-validated prioritization of LLM-specific adoption challenges and illustrating how these challenges relate to value creation across SCOR process layers. The study further offers a SCOR-aligned decision-support roadmap for managers and policymakers and establishes a structured foundation for future empirical research on LLM-enabled supply chains. ? 2026 Elsevier B.V.

While a lot of hype surrounds novel technologies such as big data and cognitive analytics, their adoption in organisations and value appropriation is often a concern. Recent research has noted that cognitive analytics can help leverage value from big data, while a different strand of research emphasises the need for organisations to develop capabilities around emerging technologies such as cognitive analytics. Focusing on cognitive computing-enabled analytics, this paper uses the resource-based view (RBV) and the resource-orchestration theory to conceptualise a cognitive analytics capability and identifies its underlying resources. This paper combines insights from extant literature and in-depth interview data collected from 44 domain experts across six organisations, analysed using thematic analysis. The analysis reveals four categories of tangible resources, four categories of human resources, and three categories of intangible resources underlying a cognitive analytics capability. Further, resource management actions in terms of structuring the resource portfolio, bundling and leveraging of resources are identified. This paper engages with the big data productivity paradox and contributes to the literature on business value of IT, resource-based view, cognitive analytics, and IT capabilities. By unpacking the resources and resource management actions underlying cognitive analytics capability, this paper has prescriptive value for managerial practice. ? 2025 Informa UK Limited, trading as Taylor & Francis Group.

Purpose ? Climate change is severely impacting financial ecosystem and banking sector plays a pivotal role as a financial intermediary in addressing these challenges. Considering increasing regulatory and stakeholder pressure for enhanced climate disclosures, this study aims to offer a timely review of climate disclosure practices in the Indian banking sector with a focus on climate risk governance. Design/methodology/approach ? Using content analysis and a panel regression model, the research analyses Indian banking sector over the period 2019?2024. A Climate Disclosure Index, derived from Task Force on Climate-related Financial Disclosures (TCFD) framework, is used to evaluate disclosures in annual reports. Findings ? Despite a notable increase in climate disclosures, banks still lack integration of climate risks in their operational framework and measurement of climate impact of their financing activities. Regression results reveal that women and independent directors significantly improve climate disclosure, whereas board size, audit committee size and CEO age do not show statistically significant effects. Larger, more profitable banks with greater financial capacity disclose more on climate-related aspects, while public sector banks lag behind private ones. Practical implications ? This study captures the post-TCFD diffusion period in Indian banking sector, highlighting that diverse and independent boards not only comply with disclosure mandates but also strategically use climate transparency to reinforce legitimacy and stakeholder trust. The study supports capacity building for smaller banks and establishing frameworks and incentives that strengthen climate accountability and align the Indian banking sector with global best practices. Originality/value ? This study captures the post-TCFD diffusion period in Indian banking sector, highlighting that diverse and independent boards not only comply with disclosure mandates but also strategically use climate transparency to reinforce legitimacy and stakeholder trust. The study supports capacity building for smaller banks and establishing frameworks and incentives that strengthen climate accountability and align the Indian banking sector with global best practices. This research advances theoretical and empirical understanding of governance mechanisms driving climate transparency in emerging markets. ? 2026 Emerald Publishing Limited

Electronic waste (E-waste) is an escalating global challenge, with discarded laptops forming a major share of this growing environmental burden. To support sustainable consumption and informed consumer decision-making, this study proposes an unsupervised deep learning framework that ranks refurbished and new laptop brands based on consumer sentiment extracted from online reviews. The framework identifies not only direct product features called aspects (such as battery, display, or customer support) but also experiential dimensions (such as reliability, performance, or overall satisfaction), providing a holistic view of consumer perception. By leveraging a transformer-based multiheaded attention mechanism and part-of-speech tagging, the model extracts rich five-part sentiment structures: aspect/dimension, category, opinion, irrealis (hypotheticals), and sentiment, collectively represented as ACOIS and DCOIS quintuples. These insights feed into a folksonomy-based consumer brand ranking algorithm, which aggregates sentiment scores to rank laptop brands effectively. Unlike traditional models, this framework requires no labeled training data, increasing its adaptability across domains. Comparative evaluations against state-of-the-art supervised and self-supervised models, including large language models, demonstrate superior performance with F1 score improvements of 9%, 6%, and 4% in extracting product aspects, dimensions, and opinions, respectively. The model is applied to a curated dataset comprising new and refurbished laptops within the same price segment. Results show that 40% of refurbished brands appear in the top 25% of recommendations. We ensured the framework?s robustness check, including McNemar?s statistical testing on six subtasks (5/6 above 0.05 threshold), ablation studies with two alternative attention mechanisms, and validation against several benchmark methods, confirming framework?s stability. ? 1988-2012 IEEE.

Purpose ? The metaverse presents an emerging domain that offers many opportunities to various stakeholders. Despite the advantages, the metaverse has been witnessing increasing cases of violence and abuse. This study aims to empirically examine the dark side of the metaverse and its consequences on users. Design/methodology/approach ? The study uses the theoretical premise of deindividuation theory and psychodynamic theory to conceptualize a research model. A structured survey-based questionnaire is employed for data collection from 327 metaverse gaming users from US. Structured equation modeling was used for data analysis. Findings ? The study reveals that the loneliness of users is positively associated with dissociative anonymity and invisibility in the metaverse, which leads to deindividuation. Further, findings suggest that deindividuation fosters deviant behaviour in metaverse. Furthermore, deindividuation and deviant behaviour predict depression among users. The study also established the moderating effects of immersive experience. Originality/value ? Rarely studies have attempted to comprehend the dark side of the metaverse. The study is one of the first to empirically show that metaverse engagement might aggravate the well-being of lonely individuals. Findings also offer implications for metaverse game designers and public policymakers. ? 2025 Emerald Publishing Limited

Manufacturing entities in emerging economies face significant obstacles implementing circular economy principles due to resource-constrained environments. Arguably, manufacturers need customer green pressure to propel the circular economy, alongside frugal innovative strategies. There is a dearth of research on digital platform (DP) capabilities, customer green pressure, and frugal innovative strategies with circular economy. Drawing on dynamic capabilities theory, 889 manufacturers were surveyed in the emerging economy of India. Customer green pressure moderation was assessed on the links between frugal innovative strategies and circular economy, DP integration capabilities and frugal innovation, and DP reconfiguration capabilities and frugal innovative strategies. Structural equation modelling revealed that DP integration and reconfiguration capabilities positively influence frugal innovation strategies enabling circular economy performance. Customer green pressure positively moderated DP reconfiguration and frugal innovative strategies. Actionable insights are provided to prioritize DP capability development to satisfy customer green pressure and promote frugal innovative strategies, ultimately facilitating the circular economy. ? 2025 The Author(s). Business Strategy and the Environment published by ERP Environment and John Wiley & Sons Ltd.

The swift adoption of generative and agentic AI tools in workplace settings has introduced new organizational risks related to data disclosure, privacy, and governance. This study introduces the Digital Shadow AI Risk Framework (DART), which identifies and explains the behavioral and organizational risks arising from the informal and often unregulated use of AI tools by employees. DART comprises six interrelated risk dimensions: unintentional disclosure risk, the trust?dependence paradox, data sovereignty conflict, knowledge dilution, the ethical black box problem, and organizational feedback loops. The framework is evaluated using a three-wave survey research combining hypothesis testing and covariance-based structural equation modeling (CB-SEM) across three cross-industry surveys of professionals (Survey-1: N = 374; Survey-2: N = 179; Survey-3: N = 220). Survey-3 introduced multi-item latent measures enabling direct tests of H4, H6, and the full H8 mediation chain (opacity ? trust ? comfort ? disclosure). Results support six of eight hypotheses. Knowledge dilution is confirmed through replication, while data sovereignty conflict consistently operates as a boundary condition rather than a direct predictor. The findings reveal persistent gaps in employee awareness, training, and organizational controls surrounding AI use. DART's contribution lies in distinguishing Shadow AI from traditional Shadow IT by showing how everyday, efficiency-driven AI use embeds risk into routine knowledge work. By externalizing organizational knowledge into adaptive AI systems, Shadow AI introduces risks that extend beyond technical non-compliance to cognitive dependence and governance erosion. The framework informs future research and supports the development of organizational policies and controls for responsible AI use. ? 2026 The Author

It has been scientifically established that the transportation and logistics sectors are critical in the determination of sustainable global initiatives because of their immense effects on the environment. This chapter uses a holistic round scheme to examine how sustainability principles are incorporated into transport and logistics. This model identifies these components, Catalysts, Conversions, Outputs, and Impacts. Necessarily, these include alternative fuel vehicles (AFVs), routing software for optimal decisions together, and collaboration. Improving the routes taken when making deliveries, optimizing vehicle loads, and changing modes of transport are examples of catalysts that have been implemented in real-world systems through operationalization. These steps then give rise to things like less pollution, less fuel usage, or more successful supply chain operations. The successful yield, in turn, has cumulative significant impacts that result in better environmental performance, cost savings, and happy customers. ? 2026 selection and editorial matter, Dr. Ashu Sharma, Dr Veena Vohra and Dr. Rose Antony; individual chapters, the contributors.

Purpose ? Through the integration of the heuristic-systematic model (HSM) and the trust-building model, this study aims to investigate the intricate mechanisms through which online travel chatbots? (OTCs) characteristics influence trust formation. This study specifically examines how systematic and heuristic processing routes distinctly shape cognitive and affective trust development in human?AI (artificial intelligence) interactions, addressing fundamental gaps in digital trust literature. Design/methodology/approach ? The investigation uses a systematic research design that systematically examines user interactions with OTC platforms. Three hundred participants engaged in structured travel planning scenarios, providing a robust data set for analyzing trust formation patterns. The methodology incorporates both controlled exposure and naturalistic interaction elements, enabling systematic examination of systematic processing (via communication quality and trendiness assessment) and heuristic processing (through anthropomorphic features and interaction enjoyment). Structural equation modeling techniques, coupled with serial mediation analysis, were used to test the theoretical framework. Findings ? The results reveal that OTC characteristics directly influence both affective and cognitive trust components. Communication quality and trendiness significantly impact cognitive trust, while anthropomorphism and interactional enjoyment influence affective trust. Both trust components strongly affect reuse intention, but their impact on word-of-mouth varies, with cognitive trust showing stronger direct effects. Research limitations/implications ? This study establishes a comprehensive framework for understanding trust formation in AI-powered travel services, offering a foundation for future research in human?agent trust dynamics. Practical implications ? The findings enable OTC developers to optimize trust-building features and help travel companies enhance user adoption through targeted implementation of trust-inducing characteristics. Originality/value ? This research advances theoretical understanding in three distinctive ways. First, it extends HSM application in digital environments by delineating how systematic and heuristic processing manifest uniquely in OTC interactions. Second, it enriches trust-building theory by revealing the distinct mediating roles of cognitive and affective trust in human?AI exchanges. Third, it establishes a comprehensive framework for understanding trust formation in AI-powered services, particularly in high-involvement decision contexts such as travel planning. These insights reveal patterns of trust development specific to human?AI interactions that diverge from traditional human?human trust formation mechanisms documented in earlier studies. ? 2026 Emerald Publishing Limited

Purpose ? Extended reality (XR), including augmented reality (AR) and virtual reality (VR), has been studied primarily for its technical attributes and direct business impacts, such as sales and customer engagement. However, the broader implications of XR on the socioeconomic and environmental aspects of operations and supply chains remain underexplored. This study aims to investigate how XR can improve economic, social and environmental business practices and operational efficiency and contribute to a more comprehensive understanding of the role of XR in transforming management landscapes. Design/methodology/approach ? Building on a grounded theory approach, 15 in-depth interviews were conducted with industry experts. Three-order coding was used for the data analysis. Findings ? The results showed that XR can be a useful instrument to achieve supply chain sustainability, which includes economic, social and ecological aspects. The identified aspects are social (employed employees, cooperation and communication), economic (cost reduction and risk management) and environmental (resource efficiency and CO2 footprint reduction) in order to uncover the effects of XR. Practical implications ? By developing a theoretical framework for XR-based sustainable supply chain management, this study adds significantly to XR, sustainability and supply chain literature. Practically, this study provides valuable insights to developers and managers in bringing more sustainability to the supply chain process. Originality/value ? This study introduced a novel theoretical framework for XR-based sustainable supply chain management. ? 2025 Emerald Publishing Limited

This research examines how electricity shortages and crude oil prices shape electricity prices in Indian spot market. We utilize a Nonlinear Autoregressive Distributed Lag model along with Local Projection approach to track how these effects play out in the short and long run. The empirical findings reveal that electricity prices react more strongly to negative shocks, such as supply shortages and rises in oil price, than to positive ones. Moreover, the underlying reasons for these asymmetries are explained through behavioural factors, such as price inelasticity, consumer anxiety and aggressive bidding of scarcity. Furthermore, this study highlights feedback loops in which nonlinearly increasing prices lead to electricity shortages. Finally, these findings underline the need for targeted policies to enhance market resilience and pricing stability. ? 2025 Elsevier Inc.

Recommerce, the purchase of pre-owned goods instead of new ones, offers a critical response to growing landfill accumulation, pollution, and resource depletion driven by overproduction, fast-fashion, and short product lifecycles. Despite its promise for advancing circular consumption, recommerce remains constrained by consumer stigma and motivational ambiguity. This research integrates Norm Activation Model (NAM) with anticipated self-conscious emotions to explain when and how consumers choose pre-owned items and how these choices can be influenced. Across five complementary studies, survey-based structural equation modeling (Study-1a), a 2 ? 2 experiment manipulating emotional (pride vs. guilt) and motivational (altruistic vs. egoistic) message framing (Study-1b), a recall validation using naturally experienced emotions and motives (Study-1c), and two field studies analyzing 1.43 million marketplace listings (Study-2a) and 1050 public posts (Study-2b), the findings reveal that (i) the NAM cascade (awareness ? responsibility ? personal norms) robustly predicts recommerce purchase intention; (ii) anticipated pride (stronger effect) and guilt operate downstream of personal norms, reinforcing intentions; (iii) perceived social sanctions (stigma/anticipated disapproval) weaken the norm?intention link; (iv) pride- and altruism-framed appeals independently increase purchase intention, with a synergistic interaction; and (v) these same mechanisms generalize to field outcomes, where pride/altruism-laden language predicts higher realized prices and greater organic engagement. Theoretically, the study reconciles affect?norm debates by positioning emotions as both mechanisms and actionable levers while identifying social sanctions as a critical boundary condition. Managerially, recommerce platforms can normalize adoption through pride-affirming, other-benefit messaging combined with visible quality assurance and community endorsement, thereby reducing stigma and translating moral obligation into sustained circular behavior. ? 2026 John Wiley & Sons Ltd.

Events such as COVID-19 and the Suez Canal blockade exposed to the world how susceptible global supply networks are, as well as how they impede logistic service system coordination (LSSC) and distribution network efficiency (DNE). To stay ahead of the competition and ensure operational sustainability in the current fast-paced, interlinked global market, organizations must prioritize supply chain resilience (SCR). Given this, the present investigation focuses upon investigating the impact of a digital-twin-enabled risk management system (DTRMS) on SCR improving through facilitators, including DNE and LSSC. Data is collected from 281 manufacturers in Asia-Pacific and the Middle-East Region using a survey approach and analyzed using structural equation modeling. The results show that having a DTRMS is significantly associated with higher LSSC and DNE, which are in turn associated with higher SCR. An analysis of the association between DTRMS-LSSC, DTRMS-DNE, and DTRMS-SCR using innovation-focused complementary assets (ICA) as a moderator shows that only the interaction between ICA and DTRMS has a favorable influence on LSSC. The study result contributes to the expanding body of knowledge on digital transformation in supply chain management during the post-pandemic period. It also enhances the theoretical foundations of resource orchestration theory and dynamic capability view theory. Manufacturers and logistics providers can benefit from these results to establish reliable and resilient supply chain operations using digital twin technologies. ? 2026 Elsevier B.V.

Purpose ? This study aims to identify and analyze the key barriers hindering the adoption of digital twin (DT) technology in supply chain (SC) Management and presents the insights for overcoming these challenges. Design/methodology/approach ? A conceptual framework is developed to analyze the interconnections among the barriers to adopt DT technology in Supply chains. The DEMATEL technique is employed to visualize and quantify the cause-and-effect relationships. Further, the effort vs impact matrix framework is used to benchmark and prioritize the barriers based on the level of effort required to address them and their potential impact on adoption outcomes. Findings ? The findings indicate that the primary inhibiting barriers for the adoption and implementation of digital twins in the SC are hardware barriers, human resource barriers, regulatory barriers and data barriers. The causal relationship suggests that the regulatory barrier holds the highest degree of influence. Research limitations/implications ? This study investigates the barriers to adopting DT technology in supply chains. A total of 24 sub-barriers are examined and grouped into six categories that reflect the perspectives of different stakeholders across the SC. This categorization helps in understanding how adoption challenges vary and interrelate across stakeholder groups. Practical implications ? This study sheds light on the major challenges that impede the adoption of digital twins in supply chain management. Furthermore, the cause-and-effect relationships among these barriers are developed, which provides actionable insights that can support organizations in overcoming these challenges and accelerating DT adoption. Originality/value ? This study contributes to the growing body of knowledge on DT adoption in supply chains by applying the DEMATEL technique to systematically identify and analyze key obstacles. The study offers a novel perspective by uncovering the interdependencies among barriers and thereby providing both scholars and practitioners with a deeper understanding of how to facilitate the successful implementation of DT technology. ? 2026 Emerald Publishing Limited