We offer a cross-case analysis of first-person accounts by undergraduate and graduate students of their use of Large Language Models (LLMs) such as ChatGPT, that enhance their reading, writing, and learning in English-medium programs across four nations: India, Indonesia, Morocco, and the United States. The participants first wrote independent accounts of their uses of AI at school and then collectively analysed each other's and their accounts to identify common and unique opportunities and challenges across the four contexts. Opportunities identified included assistance in reading complex English texts, conversational practice, as a study tool, and in writing as a tool for brainstorming ideas and learning to write more complex and precise sentences grammatically. In the last case, the students also noted how writing and revising prompts helped them fine-tune their writing. Two types of challenges were also noted, in which a prompt generated false citations or weak writing; and cheating, in which a student might risk plagiarism and detection instead of using AI as an assistive tool. In conclusion, implications for the productive, ethical use of AI programs in second-language literacy instruction are discussed.

Existing literature indicates that abusive supervision yields adverse effects for both individuals and organizations. Nevertheless, empirical evidence suggests that people react differently to abusive supervision. In particular, there is insufficient knowledge regarding constructive responses to abusive supervision. Drawing from attribution and cognitive appraisal theories, the current study examines how individuals may behave both constructively and destructively under abusive supervision. Employing two multi-wave, multi-source studies, the current study findings highlight that guilt acts as a mediator between abusive supervision and supervisor-directed constructive deviance, while shame serves as a mediator between abusive supervision and supervisor-directed destructive deviance. Furthermore, the degree of conscientiousness exhibited by subordinates under abusive supervision influences their emotional reactions. This study elucidates the complex psychological mechanisms through which abusive supervision can stimulate both constructive and destructive behaviors toward the supervisor at the same time. Hence, it underpins the impact of abusive supervision on the outcomes of individual subordinates.

PurposeThe study aims to understand the role of organizational justice in the relationship between organizational identification (OID) and employee performance. Based on the accessible identity model (AIM) of justice, the study proposes that organizational justice facets would mediate the impact of OID on employee performance. The study also proposes inter-relationships between the organizational justice facets and tests the model among Indian PSU employees.Design/methodology/approachStructural equation modelling was conducted with 565 non-nested dyad responses using the CB-SEM approach in the SmartPLS 4.1.0.3 software.FindingsOID has a significant positive influence on employee performance as well as the justice facets such as procedural justice (PJ), distributive justice (DJ) and informational justice (INFJ). PJ fully mediates the relationship between OID and DJ, whereas the OID-INFJ relationship is partially mediated by it. The OID-employee performance relationship is fully mediated sequentially by PJ and INFJ and partially mediated sequentially by PJ and DJ.Originality/valueThe study establishes justice facets as the linking mechanisms between OID and employee performance. It establishes context-specific interrelationships between the justice facets with PJ perceptions leading to DJ and INFJ among Indian PSUs. It establishes the AIM as a viable theory to understand the effect of OID on the organizational justice facets and casts doubts on the applicability of social exchange theory (SET) for the same.

Knowledge hiding in the service sector is persistently escalating and is gaining increased attention from scholars and practitioners. This article aims to systematically review the extant literature on knowledge hiding in the service sector. Adopting the systematic literature review protocol, this review outlines the prominent theories (T), contexts (C), characteristics (C), and methodologies (M) of knowledge hiding in the service sector in line with the TCCM framework. The review unveiled that social exchange theory and conservation of resource theory have been predominantly employed to understand factors triggering knowledge hiding in the service sector. Furthermore, the review segregated the characteristics of knowledge hiding into antecedents, moderators, mediators, and outcomes. Additionally, studies on knowledge hiding in the service sector indicate a strong emphasis on Asian regions relative to other regions addressed in the literature. Besides, the review highlights the need for qualitative studies apart from quantitative ones. This review provides a one-stop paper to provide relevant information and an understanding of the significance of knowledge hiding in the service sector. The review findings might persuade practitioners to provide policies that curtail or discontinue knowledge hiding in the service sector. One feasible solution is to develop and implement strategies to encourage knowledge sharing and cease knowledge-hiding behaviors.

PurposeThis study aims to examine how externally attributed service failures lead to customer incivility intention through the mediating role of anger and explores customer mindfulness as a moderating factor.Design/methodology/approachThree experimental studies were conducted to test the conceptual model. Study 1 tested the direct effect of external attribution of service failures on customer incivility intention. Study 2 established anger as a mediator. Study 3 utilized a two-stage moderated mediation model to analyze the moderating effect of mindfulness. Data were collected via validated scenarios and scales, analyzed using Hayes's PROCESS macro.FindingsAcross three experiments, externally attributed service failures increased customer incivility intention; this effect was fully mediated by anger. Furthermore, this study found that mindfulness attenuated this mediating relationship on both paths, i.e. on the relationship between externally attributed service failure and anger, and further on the relationship between anger and customer incivility intention.Originality/valueThis study identifies when and how service-failure attributions translate into customer incivility intention by introducing customer mindfulness as a boundary condition on the anger-mediated pathway. It extends attribution/AET theory by pinpointing conditions under which incivility intentions are most likely. For managers, the results suggest focusing recovery on shaping perceived responsibility (clear, empathetic explanations) and adjusting responses to customer cues to defuse anger.

BackgroundIllegitimate tasks are work assignments perceived as unreasonable or unnecessary. Such tasks fall outside the boundaries of duties considered appropriate for a given professional role. Illegitimate tasks are a widespread issue in the health care sector. Literature has largely emphasized the negative outcomes of illegitimate tasks. However, we suggest that the consequences of illegitimate tasks might not always be uniformly negative but could be paradoxical, depending upon the appraisal mechanisms.PurposesUsing the lens of the transactional model of stress and coping, we suggest that when individuals appraise illegitimate tasks as challenges, it is associated with positive outcomes like employee resilience. However, if they appraise illegitimate tasks as hindrances, it is associated with negative outcomes like the intention to quit.MethodThe study was conducted using a time-lagged survey of 207 nurses in the health care sector in India, where illegitimate tasks are highly prominent.ResultsIllegitimate tasks were positively associated with challenge and hindrance appraisals. The appraisal mechanisms mediated the relationship between illegitimate tasks and employee outcomes (employee resilience and intention to quit). Individuals with higher calling orientation were less likely to perceive illegitimate tasks as hindrances.Practice ImplicationsOrganizations should ensure that illegitimate tasks are appraised as challenges rather than hindrances through workload and stress management techniques.

While migration is a largely discussed form of labor mobility, internal return migration of workers has not received much attention. Individuals return to their native or previous place either for reasons related to work, distress, or family. Not only are they returning to a place that is familiar to them in terms of language, culture, and society, but also, they may have acquired some skills before returning. Therefore, labor market outcomes for return migrants are likely to differ from those of nonmigrants, who are otherwise similar to each other in most aspects. Against this context, the paper compares the earnings of internal return migrants with nonmigrants in India using the Periodic Labor Force Survey 2020-21. To this end, the study performs ordinary least square estimation by sector (rural and urban), gender, age cohorts, and employment activity status (self-employed, regular salaried, casual labor). As part of robustness analysis, it also uses the propensity score matching method. Both the exercises suggest that internal return migrants, on average, experience an earnings penalty in rural areas but a premium in urban areas. Also, a regular salaried internal return migrant experiences an earnings premium irrespective of the location (rural or urban). The earning pattern for men largely imitates the overall pattern. However, the earnings differential between female internal return migrants and nonmigrants is not significant as most of them migrate because of reasons other than work, like marriage. The findings of this study have significant implications, as what individuals do and how much they earn upon their return have direct consequences on the employment and income distribution of any region.

A dynamic, multidimensional sport, cricket, is one in which both on-field performance and strategic resource allocation influence performance. However, conventional indicators of success-win-loss records, bowling averages, and batting averages-show a fragmented picture that ignores the economic background and interdependencies of the performance process. In a sport in which operational and financial decisions are interrelated, this oversimplification significantly reduces the ability to analyze individuals' and teams' assessments. Often, these traditional techniques overlook economic and process-based variables that affect the results. We propose an updated two-stage series network Data Envelopment Analysis (DEA) method that splits overall performance into two stages: Stage 1- Utilization, which captures economic and resource-oriented inputs, and Stage 2- On-ground Performance, which captures operational outputs, so addressing existing deficiency. This study extends additive decomposition DEA to an open network architecture with intermediate products and undesirable output settings. Using the model on Indian Premier League (IPL) data, we rank the ten competitor teams and players across the four categories of bowlers, batters, all-rounders, and wicket-keepers. Stage 1 examines player utilization and auction money allocation, while Stage 2 assesses category-specific performance metrics. The results verify the relevance of the approach because they fit well with the fan and expert appraisals. The model offers a wholesome evaluation method that captures the complexity of cricket performance in the real world by combining on-field performance with economic elements. This is the first study to use two-stage network DEA to examine the black-box component of cricket performance monitoring, providing players and teams with informative results at the stage and aggregate levels.

PurposeThis study aims to propose an extended model of the theory of planned behavior (TPB) in the fashion industry. This model helps to identify key enablers for consumers, which will facilitate the adoption of a circular economy (CE). These enablers were identified through extensive literature review.Design/methodology/approachAn online survey was conducted with 362 respondents to test the model in the fashion industry. Convenience sampling was used and the survey was distributed via social media and email. Data analysis was performed using partial least squares and structural equation modeling was used to explore the relationships among the variables.FindingsThe findings indicate a positive and significant relationship between consumers' environmental knowledge and their attitudes toward adopting the CE model. In addition, the results demonstrate that providing consumers with a channel to return used clothing positively influences their attitude. The availability of such a channel significantly impacts consumer attitudes toward CE.Originality/valueThis study contributes three novel elements to the TPB framework: availability, environmental knowledge and monetary benefits. This finding posits that consumers' attitudes toward CE are significantly influenced by their environmental knowledge. This study also highlighted that attitude acts as a mediator in the relationship between environmental knowledge and intention, as well as between availability and intention.

PurposeThis study aims to investigate the effect of environmental, social and governance performance on dividend payout and whether this association is influenced by the size of the firm.Design/methodology/approachOur sample involves 1,040 firm-year observations of Indian-listed firms from 2017 to 2021. This study uses a panel data fixed effects model, a two-step system generalized method of moments and a two-stage least squares regression approach. We also use a different proxy for dividend payout in our models to ensure the robustness of our findings.FindingsOur results reveal a positive association of environmental, social and governance performance with dividend payout. The individual components, i.e. environmental performance, social performance and governance performance, also highlight similar positive relationships, stating that sustainable firms prefer more dividend payments. After introducing the moderating factor as the firm's size, the findings indicate that large-size sustainable firms prefer lower dividend payouts.Practical implicationsOur results have vital implications for potential investors, policymakers, managers and other stakeholders, given that the firm's size impacts the sustainability and dividend payout practices.Originality/valueTo the author's knowledge, this is the first study to capture the moderating role of a firm's size on the nexus of environmental, social and governance performance and dividend payout in the Indian context.

Background: There is a case to be made that the widely popular and highly valued Bitcoin (and other significant cryptocurrencies) has become synonymous with blockchain for many retail investors and other non-informed individuals. This study attempts to answer two important research questions in this space. First, the study aims to understand if companies leverage this proximity in technological awareness of Bitcoin and blockchain to attract more investors and users by riding the Bitcoin wave and strategically timing the disclosures. Second, we aim to compute the value of the confounding effect. Method: To answer these questions, we collected over 4000 blockchain-related announcements from the top 30 NASDAQ-listed firms over the past five years. All announcements are analyzed using text analytics techniques to identify the topic, tone, and complexity. An event study approach adopting a Fama-French four-factor model is developed to detect whether any changes in the market-wide abnormal returns surrounding Bitcoin events influence the company's performance. The relationship between the announcement texts and the abnormal returns is then computed and analyzed. Results: The results evidence a substantial impact of Bitcoin market returns on the abnormal return instances. Further, it is also observed that strategically framing the firm disclosures concerning blockchain announcements has a significant impact on the market returns. Conclusion: This study contributes to the literature on digital business strategies within the emerging purview of cryptocurrency networks. At a practical level, the study aims to alert not-so- well-informed investors about the possible misconception of Bitcoin performance as a direct driver of the performance of the technological companies making blockchain announcements.

PurposeThis paper aims to conceptualize and present a psychometric scale to measure the antecedents of the employer image of an organization. The paper also tests its impact on the applicant's intent to join.Design/methodology/approachA literature review was conducted to identify factors impacting the employer's image during the recruitment process. Further, a qualitative approach was undertaken to explore the observations of job applicants during the recruitment process. The emergent themes from the literature review and qualitative study were consolidated. Next, the Delphi technique was used to develop the scale items, and the validity and reliability were established. At last, the employer image's impact on the applicant's intent to join was tested.FindingsThe study resulted in four broad factors of the antecedents of the employer image scale: primary information sources, verbal factors, non-verbal factors, and contextual factors. The exploratory and confirmatory tests yielded satisfactory statistical results, establishing the scale's validity and reliability. The employer image had a positive impact on the applicant's intent to join the organization.Originality/valueThis study is the first of its kind to develop a scale measuring the antecedents of the employer image based on an applicant-centric view. It shall serve as a ready-to-go tool for practitioners to analyze the applicant's observations and reduce their drop-out from the recruitment process.

PurposeThis study aims to develop a framework for evaluating environmental, social and governance (ESG) factors in the context of commercial banks, addressing the need for a more robust and transparent assessment of ESG subfactors.Design/methodology/approachUsing an integrated multi-criteria decision-making approach, this study uses rough stepwise weight assessment ratio analysis (R-SWARA) to determine the weights of ESG factors, followed by the combined compromise solution (CoCoSo) method to assess the sustainability performance of five major commercial banks. This study involves insights from 15 experts in the banking sector, ensuring a comprehensive understanding of ESG integration.FindingsThe research reveals that governance is the most significant ESG factor in the banking sector, followed by social and environmental factors. The CoCoSo method's results, aligning with the R-SWARA findings, identify the top-performing banks regarding ESG practices, highlighting the importance of robust governance structures for sustainable banking operations.Research limitations/implicationsThis study provides a strategic framework for banks to prioritize and implement ESG initiatives effectively. It provides insights into allocating resources toward areas with the most significant impact on ESG performance, thereby enhancing operational efficiency and stakeholder trust.Originality/valueThis study contributes to the existing literature by offering a unique, integrated approach to ESG evaluation in the banking sector, combining the qualitative and quantitative aspects of ESG factors. It addresses the subjectivity issue inherent in ESG evaluation and provides a comprehensive ranking system for ESG factors in commercial banks.

Fake news and deepfake (FN & DF) technology have emerged as critical areas of inquiry within internet commerce and digital communication research. Deepfake technology significantly influences the creation and rapid dissemination of fake news. The study takes a pioneering step in addressing inconsistencies within the existing literature by providing a clear and more comprehensive synthesis of how deepfakes contribute to spreading fake news. Following PRISMA guidelines, the study analyzes 34 articles using a thematic categorization framework. The review makes three primary contributions. First, it highlights current research patterns and emerging trends in this domain. Second, it identifies five themes associated with the FN & DF literature: Identity-Driven Dissemination, Cognitive Bias and Emotional Realism, Trust Erosion and Epistemic Uncertainty, Platform Incentives and Corrective Strategies, and Governance, Ethics, and Detection. Third, based on these themes, it proposes a conceptual framework reflecting antecedents, drivers, moderators, mediators, and outcomes. The study outlines future research directions and offers practical implications.

PurposeFood is an essential commodity for human survival and growth. A significant proportion of food is squandered due to unsustainable consumption and production (SCP) practices. Although there is a growing body of research and ongoing debates surrounding the principles of SCP and the usability of digital technology in achieving the same, its barriers remain unexplored. This study aims to bridge this gap by identifying and examining the barriers faced in digitalising the food supply chain (FSC) to make consumption and production patterns sustainable.Design/methodology/approachA total of 15 barriers are identified and interpreted with the help of industry experts. The total interpretive structural modelling methodology and MICMAC analysis are used in the present study to configure the barriers, obtain the contextual relationships between them and categorise them according to their functioning.FindingsThe research finds that a complex and fragmented FSC, a lack of skilled human resources, a lack of awareness among stakeholders and organisational inertia are remarkable hurdles in digitalising the FSC. These barriers create substantial challenges to achieving SCP patterns across the supply chain.Originality/valueThis study contributes to the literature by systematically identifying and analysing the barriers to digitalising the FSC, a topic that has received limited attention. The findings offer both managerial and policy implications for advancing SCP practices through digital transformation.

PurposeAmid the increasing importance and demand for technological innovations such as artificial intelligence (AI) and machine learning (ML) in operations and supply chains, several barriers hinder their adoption and implementation. The aim of this study is to identify and evaluate these critical barriers that obstruct the smooth implementation of AI-ML in business to business (B2B) industrial operations and supply chain management (IOSCM).Design/methodology/approachThis study uses a fuzzy integrated hybrid stepwise weight assessment ratio analysis (SWARA) approach to analyze the barriers to AI-ML implementation in B2B IOSCM within B2B contexts. Sensitivity experiments were conducted to validate the robustness of the model.FindingsThe findings indicate that technological barriers are the most significant obstacles to the implementation of AI-ML-driven IOSCM in B2B settings. This study also suggests that a successful transformation to AI-ML-driven IOSCM requires effective data quality management and governance, a supportive legal and policy framework and a conducive talent and technology ecosystem.Research limitations/implicationsThis research focuses on identifying and analyzing barriers within a specific context, and further studies are needed to generalize the findings across different industries and geographic regions within the B2B sector.Practical implicationsThis study contributes to the theoretical understanding of AI-ML implementation barriers in IOSCM, specifically within B2B contexts. For managers in B2B environments, it provides a structured approach to identifying and addressing these barriers, thereby enhancing operational efficiency and resilience. Practically, the findings guide B2B organizations in prioritizing key areas for successful AI-ML integration.Originality/valueThis research presents a novel approach for comprehensively identifying and evaluating barriers to AI-ML implementation in IOSCM within B2B contexts. By using a fuzzy integrated hybrid SWARA methodology, it establishes a robust framework to address these challenges and showcases the practical application of the framework through an illustrative industrial example tailored to B2B operations. In addition, this study explores some previously overlooked barriers that have not been addressed in prior research.

Purpose - This study aims to examine consumer vulnerability on social media by reviewing the existing literature. It highlights the advantages social media provides to vulnerable consumers while identifying various factors on social media that contribute to consumer vulnerability. Design/methodology/approach - This study conducted a systematic literature review following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines. A thematic analysis was used to categorize the 41 selected articles. Findings - The review study identified five significant themes in the literature. The study also highlights how conformity pressures and cultural disparities contribute to consumer vulnerability on social media. In addition, it emphasized some benefits that vulnerable consumers gain from social media, such as support mechanisms and literacy management. Originality/value - To the best of the authors' knowledge, this study is the first to review existing literature on consumer vulnerability in social media comprehensively. It further contributes to the field by defining consumer vulnerability in the context of social media.

PurposeThis study aims to scrutinize the role of environmental, social and governance (ESG) performance and its indicators in achieving working capital management (WCM) efficiency.Design/methodology/approachUsing a sample comprising 520 firm-year observations from Indian listed firms for the period from 2017 to 2021, the current study estimates WCM efficiency using the Banker, Charnes and Cooper (BCC) input-oriented model of data envelopment analysis (DEA). In addition, this study performs baseline, robustness and heterogeneity tests to examine the effect of ESG performance and its components on WCM efficiency.FindingsOur findings show that firms with high ESG performance better manage short-term liquidity. Also, environmental performance (EP), social performance (SP) and governance performance (GP) highlight a similar positive association with WCM efficiency. As per the heterogeneity test results, both high- and low-sustainable firms showcase the necessity of ESG performance to achieve efficiency in managing their working capital.Practical implicationsThe findings emphasize the need for managers and policymakers to integrate sustainable practices with financial strategies, enhancing both short-term stability and long-term sustainability goals and thereby guiding effective policy and governance enhancements.Originality/valueWe attempt to adjudicate the role of sustainability on WCM efficiency from an emerging country perspective, which has not yet been explored. Our study also makes a methodological contribution by pioneering the DEA in the context of ESG and working capital.

PurposeTo scrutinize the role of audit committee characteristics (i.e. audit committee independence, audit committee expertise and audit committee tenure) in attaining sustainability performance (i.e. environmental, social and governance performance).Design/methodology/approachUsing a sample comprising 1,304 firm-year observations from Indian listed firms from 2018 to 2024, the current study performs baseline, robustness, additional and heterogeneity tests to examine the effect of audit committee characteristics on the environmental, social and governance performance.FindingsOur findings reveal that audit committee independence and expertise are vital for achieving sustainability performance. Also, our results indicate that independence and expertise in audit committees reflect more inclination for environmental performance and governance performance than social performance. The outcomes further state that the audit committee tenure does not impact sustainability performance. Our results remain robust even after using different estimators. Additionally, the above findings are similar for industry-wise outcomes as well as during the COVID-19 phase and post-phase of the COVID-19 pandemic.Originality/valueOur study makes a practical contribution by pioneering the attributes of audit committees in achieving sustainability performance from an emerging country perspective, such as India, which has not yet been done. The study holds great importance for managers, environmental activists, regulators and policymakers, reinforcing the belief that audit committee characteristics can be utilized in formulating policies for sustainability initiatives.

Smart city mission (SCM) initiative in India aims to transform urban areas on a large scale. However, there appears to be a gap between citizens' expectations and the actual deliverables. This study conducted interviews, group discussions, and online surveys across five selected cities in India to uncover this divergence. The findings revealed that Indian citizens primarily expect the SCM initiatives to focus on the Health, Mobility, Housing, Environment, & Sustainability sectors. However, the implemented projects concentrated more on digital technologies, mobility, and housing sectors, deviating from citizens' priorities. Additionally, the study uncovered major hindrances in successful implementation of SCM initiatives.