Purpose: Employee green behavior contributes to the achievement of hospitality organizations’ sustainability goals. However, there is a need to examine how green human resource management (GHRM) fosters employees’ green behavior. Anchored on the conservation of resources (COR) theory, we anticipate that GHRM may have double-edged effects on employees’ organizational citizenship behavior for the environment (OCBE) via two opposing mechanisms (e.g. environmental passion and emotional exhaustion). Moreover, we expect that the relationship of GHRM on environmental passion and emotional exhaustion depends on environmentally specific empowering leadership (ESEL). Design/methodology/approach: The data were garnered from 356 hospitality employees in Pakistan and analyzed using partial least squares structural equation modeling (PLS-SEM). Findings: The findings revealed a significant and positive link between GHRM and employee OCBE and environmental passion and a significant and negative relationship between GHRM and emotional exhaustion. Similarly, the link between environmental passion and employee OCBE was significant and positive and between emotional exhaustion and employee OCBE was significant and negative. Our results indicate that the impact of GHRM on OCBE among hospitality employees was mediated by environmental passion and emotional exhaustion. Further, ESEL strengthened the association of GHRM with environmental passion while mitigating the effect of GHRM on emotional exhaustion. Originality/value: Anchored on the COR theory, our study provides novel empirical evidence by investigating the mechanisms and boundary conditions between GHRM and employee OCBE nexus in the hospitality realm.

This research investigates the antecedents of employee engagement in Pakistan’s banks to conceptualize the idea of employee engagement. For this, the study examines the relationship between transformational leadership (TL), despotic leadership (DL), and the mediation of psychological distress (PD) with an outcome variable, employee engagement (EE). The study focused on first-line bank managers based in Punjab province using a cluster sampling technique. A questionnaire survey was used, and 341 respondents were selected for analysis using PLS-SEM. The study’s findings confirmed that all seven hypotheses tested were statistically significant. The results revealed that the transforming role of transformational leadership is more effective than despotic leadership in promoting employee engagement. The indirect link of psychological distress between transformational leadership, despotic leadership, and employee engagement also acts vice versa. The current study findings have implications for advancing our understanding of the effects of transformational leadership because of their positivity, which can reduce psychological distress and increase employee engagement in the service sector. In contrast, despotic leadership undermines employees’ abilities by increasing psychological distress and disengagement among employees. Our findings will help the banking industry understand how despotic and transformational leadership can negatively and positively affect employee outcomes.

The implementation of green initiatives by hospitality employees can significantly enhance the environmental sustainability of hospitality firms. However, there is a lack of research exploring the mechanisms influencing hospitality employees’ green innovative work behavior (GIWB). Through the mediation paths of green soft talent management (GSTM) and green hard talent management (GHTM), this study seeks to investigate how entrepreneurial leadership promotes GIWB. The data from 366 employees and managers in Pakistan’s hospitality industry were collected through a survey method using partial least squares structural equation modeling (PLS-SEM). The findings reveal that the effects of entrepreneurial leadership on GIWB, the direct effects of GSTM and GHTM, and the interaction effects between entrepreneurial leadership and GIWB are substantial. Based on the upper echelons theory and the resource-based view concept, this study extends research on the leadership–GIWB macro nexus and increases our understanding of the mechanisms behind employee GIWB, particularly in the hospitality setting.

Achieving sustainable competitive advantage has become increasingly complex amid intense global environmental pressures. While leadership is widely recognized as an enabler of competitiveness, little is known about how top management's green inclusive leadership fosters sustainable competitive advantage through dynamic organizational capabilities such as green shared vision and green mindfulness. Drawing on the natural resource-based view, we theorize that top management's green inclusive leadership strengthens sustainable competitive advantage in manufacturing firms through these capabilities and that internal corporate social responsibility communication reinforces these effects. Data were collected in two waves from a purposive sample of 215 middle-level managers working in Pakistan's manufacturing sector and analyzed using PROCESS macro models in SPSS. We found that green inclusive leadership directly predicts sustainable competitive advantage, and that green mindfulness, but not green shared vision, mediates this relationship. We also identify a sequential pathway in which green inclusive leadership enhances green shared vision, which subsequently fosters green mindfulness, thereby improving sustainable competitive advantage. Crucially, this sequential mediation is stronger when internal corporate social responsibility communication is high, underscoring the role of communication as a strategic organizational capability. By integrating leadership, vision, mindfulness, and communication, this study advances the natural resource-based view and demonstrates how sustainability messages shared within organizations deepen employee engagement with leadership-driven environmental strategies.

In the environment of modern climate uncertainty, institutional uncertainty, and digital disruption, resilience along the supply chain has become a strategic imperative for organisations operating in large-scale, high-risk infrastructure ecosystems. According to the dynamic capabilities’ theory, the current study examines the degree to which big data analytics management capability (BDMC) supports supply chain resilience (SCR) through three intermediary mechanisms, including fintech adoption (FTA), circular economy activities (CEA), Internet of Things (IoT), and environmental dynamism acts as a moderating factor to determine the effect that external volatility conditions have on such associations. This study addresses several notable research gaps: (1) the insufficient theorization of how digital tools such as BDMC, FTA, IoT, and CEA interact in building SCR; (2) a lack of empirical clarity on the mediating mechanisms that link digital capabilities with resilience; and (3) limited understanding of the moderating role of environmental dynamism in volatile contexts like the CPEC. A survey was conducted among 441 mid and senior level professionals residing in Pakistan and working in industries related to the China-Pakistan economic corridor (CPEC). Structural equation modelling (SEM) revealed that BDMC has a significant, positive impact on SCR, as well as a mediated influence in this direction. Among mediating sets, the significant pathway discovered CEA supported by the next important pathway IoT and FTA, which also explained the layered (complementary) nature of both digital and sustainability targeting skills. Moreover, the factor of environmental dynamism was also found to have a positive moderating effect on the relationship between BDMC and SCR, indicating that the factor of dynamic capabilities becomes more significant in an environment where environmental uncertainty is high. The research questions driving this study are: (1) How does BDMC enable SCR in the CPEC context? (2) What are the mediating roles of FTA, CEA, and IoT in this relationship? (3) How does environmental dynamism moderate the BDMC-SCR nexus? Theoretically, this study extends DCT to an emerging megaproject context and conceptualizes BDMC as an orchestrating capability. The main innovation lies in integrating digital technologies and sustainability practices into a unified capability system, especially within high-risk, underdeveloped regions. The study provides a practical resilience roadmap for policymakers and firms, outlining the strategic integration of digital and circular practices, rather than merely adopting them. However, this study is limited by its cross-sectional survey design and its focus on a single geographic context, which may affect generalizability. Findings offer timely insights for resilience-building strategies in unstable organisational environments.

In the context of rapid technological advancement, artificial intelligence (AI) is transforming the manufacturing sector by redefining job requirements, restructuring resource utilization, and influencing how employees adjust to evolving career trajectories. This study investigates how individuals’ perceptions of artificial intelligence (PAI) influence career adaptability (CA), with technological anxiety (TA) and job crafting (JC) serving as key mediating mechanisms in this relationship. Grounded in the Job Demands-Resources (JD-R) theory, this study investigates how employees’ perceptions of artificial intelligence generate job demands that may lead to anxiety, while simultaneously offering opportunities for proactive engagement through job crafting. A cross-sectional survey was conducted among 397 employees working in the manufacturing sector. The data were analyzed using partial least squares structural equation modeling (PLS-SEM) to examine the hypothesized relationships. The results suggest that individuals’ perceptions of AI exert a significant and positive influence on technological anxiety and job crafting. Moreover, job crafting has a significant and positive impact on career adaptability. In addition, job crafting positively mediates the relationship between perceptions of AI and career adaptability. This study contributes to the JD-R framework and offers practical insights for managing workforce transitions in environments where AI is integrated.