PurposeEmployees are invaluable resources that are of significant value to a firm when it aims to perform human capital development (HCD). Eventually, any firm intending to preserve a competitive advantage over rivals must invest in HCD. Therefore, to gain a competitive edge in the digital age and to yield net benefits, this study endeavours to define the research problem, i.e. should a firm adopt artificial intelligence (AI) in HCD? For the investigation, it explores various disciplines of HCD, validates whether AI has capabilities to meet the net benefits of HCD, and measures the adoption intention.Design/methodology/approachThe source data were collected from 315 individuals through a survey with a five-point Likert-scale questionnaire. The empirical analysis is accomplished using covariance-based structural equation modelling.FindingsAI capability plays a positive role in HCD disciplines, including talent management, change management, performance management, human resource management and strategic planning. Subsequently, each AI-enabled HCD discipline positively influences net benefits. Eventually, the net benefits of AI-enabled HCD positively influence AI adoption intention. Moreover, organisational culture moderates the relationship between net benefits and AI adoption intention.Originality/valueThis study demonstrates an empirical analysis of the adoption intention of AI in HCD by presenting the theoretical underpinnings of HCD disciplines, and subsequently, building and validating the structural relationships amongst HCD disciplines, net benefits and AI adoption intention with organisational culture as moderator. In this vein, the study offers multifaceted advantages of AI-enabled HCD.

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.

PurposePublic-private partnership (PPP) projects worldwide face a multitude of complexities, comprising contract-related issues, investment risks, institutional issues and trust and integrity-related challenges while managing accountability. Moreover, there is a lack of holistic accountability framework for PPP projects that could enable the managers to design and monitor accountability over the life cycle of the project. This paper aims to develop a holistic framework for guiding managers to manage accountability in PPP projects.Design/methodology/approachA qualitative research methodology sourced from hermeneutics interpretive paradigm is used in the paper for developing the PPP accountability framework. It is based on a consilience-driven multi-method approach that covers inputs from theory, practice and local experience.FindingsThe paper presents a framework for the management of accountability in PPP projects as the outcome of the research. The framework embeds key theoretical drivers: trust, dialogue, multi-dimensionality and external control. Further, it integrates accountability-related themes from PPP cases such as transparency, integrity, responsibility and performance. The contextual factors superimposed by the drivers and themes include stakeholder participation, collaborative accountability, equitable risk sharing, contract management and performance management.Practical implicationsThe framework facilitates the assessment and monitoring of PPP projects by designing suitable accountability governance policies. Suitable internal and external control mechanisms can be designed through stakeholders' dialogue and collaborative decision-making methods, which can enhance transparency, trust, responsibility and integrity. Policymakers can define risk-sharing policies and contract management strategies across multiple dimensions of accountability in PPP using the framework.Originality/valueThe proposed framework is holistic. It includes agency and stakeholder theoretical factors, balances vertical and horizontal relationships, trade-offs efficiency and autonomy, and includes tangible and intangible factors. Furthermore, the consilience of multiple interpretations of the phenomenon presents a novel approach to understanding PPP accountability.

PurposeImplementation of an effective closed-loop supply chain (CLSC) requires knowledge of consumers' perceptions of returning end-of-life products. Consumers, as primary suppliers of end-of-life products, play a crucial role in recycling efforts. This study identifies the drivers behind the e-waste recycling intentions of consumers, bridging the gap in previous studies.Design/methodology/approachExtending the Theory of Planned Behavior, this research integrates other determinants applicable to e-waste return intentions, including eco-literacy, reverse logistics awareness, perceived risk and incentives. An online survey was conducted with 310 digitally literate Indian consumers. Structural equation modeling was used to analyze the relationships among the studied determinants. Fourteen hypotheses were tested using PLS-SEM to assess direct and moderating effects.FindingsThe results show significant relationships between the determinants and return intention. Moderation analysis indicates that incentives reinforce the positive impact of perceived behavioral (PB) control on return intention, while perceived risk undermines the attitude-return intention relationship, as well as the return intention-PB control relationship. Attitude, subjective norms, eco-literacy, collection method and incentives were significant positive predictors, while perceived risk acted as a key barrier.Practical implicationsOur study indicates that creating awareness programs on the importance of e-waste recycling, implementing incentive schemes and establishing more stringent e-waste management regulations can promote returning e-waste into the supply chain.Originality/valueThis study contributes to the literature on CLSCs by conceptualizing consumer e-waste return intention using an extended TPB applied in the Indian context - fast-emerging digitalized economy with a high percentage of informal recycling. Through the integration of cognitive (eco-literacy, reverse logistics awareness), contextual (collection mechanism, perceived risk) and motivational (rewards) determinants, the study empirically tests the moderating roles of rewards and risk through structural equation modeling, providing refined theoretical insights and practical implications for policymakers and industry stakeholders.

This study proposes to investigate how the metaverse experiences (usability, interactivity, personalization) influence their metaverse engagement. Further, this study also examines the influence of consumer climate (change) engagement dimensions on pro-environmental behaviour. A mixed-method approach was employed by collecting both qualitative and quantitative data to gain a comprehensive understanding of the conceptual framework. The findings of this study reveal that usability, interactivity and personalization are positively associated with consumer metaverse engagement. Further, consumer metaverse engagement is significantly associated with environmental knowledge and responsibility. Also, environmental knowledge and environmental responsibility are positively associated with pro-environmental behaviours. Finally, the results of this study reveal that climate change risk perception moderates the association between personalization and consumer metaverse engagement. The study is amongst the foremost research initiatives to examine the concept of consumer climate (change) engagement in the metaverse context. Further, this study enriches the metaverse and Uses and Gratification (U&G) theory literature. In doing so, it repositions U&G theory within the metaverse context and highlights its relevance for understanding consumer motivations and behaviours related to climate (change) engagement. Finally, this study provides several implications for brands, metaverse platforms, and other stakeholders interested in promoting pro-environmental behaviour within the metaverse.

Organizational Healing (OH) refers to the process through which workplaces restore positive relationships and social interactions after traumatic events or crises. This study develops and validates a reliable and psychometrically sound scale to measure the key enablers of OH in organizations. The scale items were drawn from broad dimensions of the existing literature, such as Trust in Leadership, Empathetic Leadership, Empathetic Teams, Visionary Leadership, Unambiguous Communication, Change Management, Employee Empowerment, and Positivity. Scale items were generated and refined through expert consultation to ensure clarity and face validity. The scale was then empirically tested using exploratory and confirmatory factor analysis to establish reliability, as well as convergent and discriminant validity. The validated scale contributes to both scholarship and practice by providing a systematic framework for assessing an organization's capacity for healing after disruption or change. In practice, the instrument helps leaders to diagnose cultural strengths and vulnerabilities, guide interventions that foster trust and empathy, and design effective change management strategies.

PurposeIn the post-pandemic era, working remotely is a flexible option. However, increasing job demands (JDs) and the difficulty of maintaining a work-life balance have changed remote work from a perk to a challenge. This study explored the connection between high JDs and employee turnover intentions (TIs), with cognitive failures (CFs) as a relationship mediator and organisational identification (OI) as a key moderator.Design/methodology/approachA cross-sectional survey of 362 remote employees across various sectors in India yielded data that were analysed in PROCESS SPSS Macro and AMOS to ensure a comprehensive statistical evaluation.FindingsA significant association of JDs was found with CFs and TIs. CFs partially mediated the JD-TI relationship. OI demonstrated a significant moderating effect on the JD-CF relationship.Practical implicationsThe results suggest that cognitive health has a meaningful role in influencing employee performance and well-being. Hence, human resource policies should prioritise strategic job interventions to boost cognitive efficiency. By developing tailored virtual resources, employers can address the unique cognitive and social support needs of remote employees, thereby fostering a more resilient and productive remote workforce.Originality/valueThe literature lacks clarity on the impact of CFs on TIs in high-demand job environments, particularly in remote work settings. Grounded in Job Demands-Resources and Conservation of Resources theory, this study advances the understanding of the dynamics among JDs, CFs and TIs.

It has been exactly a decade since the term Industry 4.0 was coined. Researchers have been fascinated with this term and have since explored different areas of Industry 4.0. This study uses bibliometric tools to conduct an in-depth, year-wise analysis of Industry 4.0 literature in operations management. A detailed year-wise keywords cluster analysis highlights the evolution of the intellectual structure of Industry 4.0. Two new aspects namely the morphological study of keywords and the year-wise new keywords analysis are included in the keyword analysis. The analysis identifies the most significant studies, influential contributors (authors), and the countries that have majorly contributed to the body of knowledge of Industry 4.0. Since the research on Industry 4.0 is relatively new and attracts the heightened focus of scholars worldwide, the timely in-depth bibliometric review provided in this study will help future scholars explore multiple research directions in Industry 4.0.

This study aims to understand the influence of critical success factors (CSFs) on coopetition and innovation performance. Using Modified Total Interpretive Structural Modelling technique (M-TISM) and MICMAC (Matriced' Impacts Crois & eacute;s Multiplication Appliqu & eacute;e & aacute; un Classement) analysis, this study establishes the relationships between various CSFs. M-TISM is used to develop a hierarchical model, and MICMAC analysis is used to study the driver-dependence relationship. Based on the extant literature, seven CSFs are identified as key drivers of coopetition and innovation performance. A five-level hierarchical model illustrates the interlinkages between CSFs and their impact on coopetition. Furthermore, MICMAC analysis categorises CSFs into independent, linkage, and dependent factors. The study offers a structured approach to understanding how firms can optimise coopetition for better innovation outcomes. This study provides insights for practitioners to refine coopetition strategies and enhance innovation-driven performance in highly competitive industries. The study contributes to understanding innovation, performance measurement, coopetition, and modelling literature. This study provides a multi-level hierarchical framework highlighting how firms can strategically leverage CSFs for coopetition and attaining better innovation performance.

Background:Cyberbullying continues to take its toll on social media users, as dark traited individuals (narcissism, psychopathy, machiavellianism) continue to leverage the evolving modes of technology-driven social engagement for the exploitation of others.Purpose:In a similar direction, this study theoretically discusses and meta-analytically examines the strength and nature of the relationship between the Dark Triad and cyberbullying.Method:The study synthesises the relationship between dark triad and cyberbullying spread across close to two decades, from 2005 to 2023, and tests the moderating effect of age, gender, and cyberbullying scale reliability.Result:It was observed that all dark traits had a significant positive relationship with cyberbullying, with psychopathy being the strongest predictor, followed by Machiavellianism and narcissism. Further, the estimates of psychopathy and narcissism displayed low to moderate heterogeneity, which was primarily explained by age and gender.Conclusion:We discuss three probable competing explanations for the dark triad - cyberbullying relationship, namely, low empathy, low agreeableness, and low honesty-humility and advance three important research questions geared towards classification of an ever-expanding repertoire of anti-social online behaviours, rationalisation of definitions and measures used to measure cyberbullying, and distinguishing the effect of the dark core and dark traits effects on cyberbullying.

Customer experience (CX) refers to the overall holistic perception of the brand in the mind of the customers. According to reputed research firm IDC, the spending in CX grew approximately from $550 billion in 2019 to $640 billion by 2022 (Ross, 2019). Even in 2023, majority of the companies are expected to spend higher amount in CX related spent by an average of 24% compared to last year (Gareiss, 2022). However, the recent hype cycle report from Gartner has highlighted the fact that the priorities for CX landscape are changing drastically (Davis, 2022). This paper adopts a focus group methodology and studies the concept, barriers and opportunities of CX in the B2B context of Indian service technology firms. The findings of this paper reveal that usage of right form of data clubbed with technology enablers can aid towards the positive CX experience.

This study examines how technology-organization-environment (TOE) factors influence innovation capability, which drives blockchain and enterprise metaverse adoption, ultimately impacting competitive advantage. This study uses the data from 258 managers to understand blockchain integration and enterprise metaverse to achieve competitive advantage. The findings of this study reveal that blockchain traceability, blockchain transparency, technology readiness, the threat of data ownership, and competitive pressure are significantly associated with innovation capability. Moreover, the findings suggest that innovation capability is positively associated with blockchain integration and enterprise metaverse adoption. Furthermore, blockchain integration is positively associated with a competitive advantage. Finally, the findings of this study reveal that technostress moderates the relationship between innovation capability and enterprise metaverse adoption. This study enriches the existing literature pertaining to blockchain, enterprise metaverse, and technology adoption. The research also enriches the TOE and innovation capability theory. Furthermore, this study will also be helpful to organizations that intend to adopt blockchain and enterprise metaverse in the future.

Immersive shopping (IS) is the usage of simulation-based technology like metaverse to create interactive and highly personalised shopping experiences for customers wherein they spend quality time selecting the products, which increases their familiarity with the brand. When compared to a standard shopping experience, the IS experience (ISE) offers brick-and-mortar retailers a positive brand image. However, the metaverse can induce cognitive biases (CBs) in customers that can negatively influence their reasoning and decision-making. CB is the systematic error in thinking that occurs when people are processing and interpreting information during the shopping, which affects their decisions and judgments. Therefore, this study explores the adverse impacts of metaverse-induced CBs on ISE for brick-and-mortar retail customers. Using simple random sampling, data were collected from 20 customers, and a qualitative approach was used for data analysis. The finding produces three adverse impacts for ISE. First, metaverse-induced CBs create a digital divide between customer communities, and the integration of retail services with the metaverse further aggravates the risk of this divide. Second, metaverseinduced CBs create financial malfeasance, which makes the metaverse susceptible to financial biases. Third, metaverse-induced CBs increase business reputation risk by adversely impacting decision-making, strategy formulations, and outcomes.

PurposeGrounded in training engagement theory and the theory of planned behavior, this study aims to propose a sequential mediation model, contributing to a nuanced understanding of the systematic process of managerial transfer design that drives training transfer (TT).Design/methodology/approachBased on the research framework, data was collected from 263 managerial executives over different timelines. The first questionnaire (T1), after training completion, was administered in two Indian industrial organizations, and 410 managers responded. The second online questionnaire (T2) was sent to the respondents after 12 weeks of training, and only 263 usable responses were received. Structural equation modeling (SEM) was used to examine the direct and indirect impact of the managerial transfer design on TT through the two mediators, motivation to transfer (MtT) and volition to transfer (VtT).FindingsThe results based on SEM bootstrap analysis suggested a significant mediation effect of MtT and VtT in the association between managerial transfer design and TT in sequential order.Practical implicationsHuman resource development personnel in organizations should consider the conditions associated with managerial transfer design, MtT and VtT while designing and implementing positive TT strategies.Originality/valueThis study stands out from existing studies by using a time-lagged design to empirically examine a sequential mediation mechanism, where MtT and VtT enhance TT through managerial transfer design.

PurposeThis study develops a model for understanding the relationships and interactions between the antecedents influencing inter-organisational collaboration in the healthcare sector.Design/methodology/approachA comprehensive and systematized search was conducted on Scopus to identify all relevant studies investigating the antecedents of inter-organisational collaboration in the healthcare sector. Antecedents were identified based on insights from experts and a systematised search method. A modified total interpretive structural model (m-TISM) was used to determine the hierarchical relationships between the identified antecedents. Finally, the Matrice d'Impacts Crois & eacute;s Multiplication Appliqu & eacute;e & agrave; un Classement (MICMAC) analysis was employed to categorise the identified antecedents into clusters based on their driving or dependence influence.FindingsEight antecedents of inter-organisational collaboration in the healthcare sector were identified. The results revealed that having a shared vision and goals, digital infrastructure and proximity are the most crucial antecedents of inter-organisational collaboration in healthcare, along with leadership, shared resources and communication.Research limitations/implicationsFuture research on inter-organisational collaboration in the healthcare sector can include additional factors that may influence collaboration beyond those currently studied. Structural equation modelling can be employed to validate the proposed model.Originality/valueThe study proposes a hierarchical model for inter-organisational collaboration in the healthcare sector. The framework will help healthcare executives and academicians identify key antecedents that are most critical to enabling effective collaboration.

How does the development of Analytics Capability (AC) of a firm influence its supply chain performance? With increasing numbers of firms adopting data analytics to enhance their supply chains and overall performance, this question has become particularly important. To answer the question, this study proposes and tests three dominant supply chain capabilities (integration, flexibility, and resilience) as key mechanisms through which AC is linked with operational performance. We use 405 effect sizes reported in 174 prior empirical studies based on data gathered from 104,296 informants to draw insights using a meta-analytic structural equation modeling approach. The theory developed herein contributes to the literature by demonstrating that integration, flexibility, and resilience mediate the association between AC and operational performance, which in turn affects customer service performance. Specifically, a substantial degree of variance in the effects of AC on operational performance is mediated by integration, flexibility, and resilience, respectively. We also find that the effect size for the association between AC and operational performance is higher in developing economies, while the link between operational performance and customer service performance is higher in developed economies. Our analyses are robust to several empirical challenges, including (a) common method bias, (b) outliers, (c) endogeneity, and (d) journal quality, attesting to the stability of the findings. Overall, our results suggest that supply chain integration, flexibility, and resilience are key domains of managerial and theoretical focus for implementing firms' data analytics initiatives, reinforcing the role of the supply chain in leveraging data analytics capabilities.

This study examines how environment, social, and governance (ESG) related news and investor sentiment (IS) affect cryptocurrency prices, with a focus on major digital assets like Bitcoin. Using machine learning techniques, this study analyzes daily data between January 2021 and February 2024 to understand the role of sentiment in this highly speculative market. The findings show that both ESG news and investor sentiment significantly influence cryptocurrency returns. Furthermore, the data revealed that negative sentiments have a stronger effect on cryptocurrency prices, suggesting a loss aversion tendency among investors. While investor sentiment has a greater impact on cryptocurrency returns than equity returns, ESG news is more influential in equity markets. To test predictive performance, a Long Short-Term Memory (LSTM) model was used and found to outperform regression based statistical model. This research offers new insights into how non-financial information shapes digital asset pricing. The results have practical implications for traders, portfolio managers, and policymakers.

PurposeThis research focuses on developing and testing a conceptual model that explores customer behavioural responses (engagement, experience and recommendation) towards generative artificial intelligence (AI)-enabled chatbots. It highlights the significant influence of anthropomorphic characteristics in enhancing perceptions of competence and warmth, further enhancing perceived authenticity. In addition, this study aims to investigate how the need for social interactions moderates these relationships.Design/methodology/approachThis study used a self-administered questionnaire distributed on Prolific Academic to gather data from 282 eligible participants worldwide. This study uses a structural equation modelling approach to answer the research questions.FindingsThe findings reveal that anthropomorphic characteristics of generative AI-enabled chatbots are positively associated with perceived competence. Moreover, the findings show that the perceived competence and warmth of generative AI-enabled chatbots are significantly associated with perceived authenticity. Furthermore, the results highlight that the perceived authenticity of generative AI-enabled chatbots is positively associated with customer engagement, experience and recommendation. Finally, the results illustrate that the impact of anthropomorphic characteristics on perceived warmth is significantly moderated by the need for social interaction.Originality/valueThis study enriches the generative AI literature and guides organizations in understanding consumer interactions for leveraging generative AI-enabled chatbots. Furthermore, this study contributes to the social response theory literature as this study investigates how user behavioural intentions towards generative AI-enabled chatbots are influenced by their perceived level of anthropomorphic characteristics.

PurposeThis study aims to explore how audit firm rotation (AFR) influences firm value, with a particular focus on transition types, namely, switching from Big 4 to non-Big 4 audit firm and non-Big 4 to Big 4 audit firm. In addition, it delves into the moderating effects of nonauditing services (NAS) on the relationship between AFR and firm value.Design/methodology/approachThe author used panel data regression models to examine the link between AFR and firm value while adjusting for various factors influencing firm value. This study's data set encompassed 25,120 Bombay Stock Exchange listed firm-years from 2003 to 2022. The firm value is quantified through Tobin's Q. Endogeneity issues are addressed through Two-Stage Least Squares and Propensity Score Matching techniques.FindingsThe findings suggest that embracing AFR generally enhances firm value. Notably, this positive effect is particularly evident when firms transition from Big 4 to non-Big 4 audit firms. Furthermore, contrary to expectations, the incorporation of NAS amplifies the positive impact of AFR on firm value, especially when these services involve tax and financial information system aspects.Originality/valueThis study is among the pioneering attempts to comprehensively examine the relationship between AFR and firm value by considering the nature of transition and the different types of NAS the auditors offer.

PurposeContributing toward Sustainable Development Goal (SDG) 5, our study examines gender diversity in the Indian liquor manufacturing sector, specifically emphasizing organizational interventions that augment female participation and evaluating their operational impact.Design/methodology/approachUsing the context-intervention-mechanism-outcome (CIMO) framework and integrating resource-based view (RBV), social capital and Institutional theory, this study analyses interventions, including decision-making practices, to improve female participation. The study gathers primary data through semi-structured interviews and triangulates it with five years of firm-level KPI, benchmarked against industry, to assess the influence of gender diversity on firm performance.FindingsThe research reveals that specific interventions positively impact gender inclusivity, improving operational efficiency, innovation and workforce morale. The study further highlights the challenges of industry-specific cultural and regulatory barriers and presents a structured Gender Diversity Best Practices framework (GDPF) to guide industry-wide adoption.Research limitations/implicationsOur study employs a single-case analysis within the Indian liquor manufacturing sector, which may constrain direct generalizability to other industries or cultural settings. However, by benchmarking firm-level key performance indicators (KPIs) against industry standards, the research enhances the potential for broader applicability. This approach enables the translation of firm-specific findings into industry-relevant insights, supporting the development of transferable best practices. Future research should employ multi-firm or longitudinal designs to validate and refine these benchmarks across sectors.Originality/valueThis research is among the first to apply empirical benchmarking to gender diversity practices in a culturally sensitive, male-dominated industry. We propose a generalizable framework linking gender diversity to measurable performance outcomes in manufacturing operations.