This study examines how employee engagement functions as a mediator between worker productivity and Green Human Resource Management (GHRM) practices in Bangladesh's industrial industry. We used a web-based, structured questionnaire to survey 401 workers from different companies. Comprehensive research using structural equation modeling showed that GHRM significantly improves employee engagement (p < 0.05, β = 0.154), which in turn boosts worker productivity (β = 0.281). Additionally, the association between GHRM and productivity is significantly mediated by employee engagement (p < 0.05), suggesting that engaged employees are more productive in companies that implement GHRM practices. This study emphasizes the usefulness of implementing GHRM practices for manufacturing managers in order to cultivate a motivated and effective workforce. Using the Ability, Motivation, and Opportunity (A-M-O) Theory, this study offers insights applicable to comparable situations around the world and advances our understanding of how sustainable HR practices can address issues in a Bangladeshi manufacturing sector. Graphical abstract

Consumer behavior and the way businesses conduct their operations have changed due to the widespread usage of internet purchasing worldwide. Bangladesh’s reliance on online shopping presents both opportunities and difficulties. The relatively large marketplace is driving up demand for online shopping. On the contrary, the need for greater technological proficiency that underpins online purchasing presents a significant challenge for entrepreneurs, managers, and consumers. This paper employed TAM (Technology Acceptance Model) to explore and predict Bangladeshi customers’ online purchasing intentions. The data were collected from 322 online consumers in Dhaka and analyzed with SEM utilizing SMART PLS 3. The data analysis demonstrates a significant association between consumers’ buying intention and Perceived Usefulness (PU), Perceived Ease of Use (PEU), Perceived Enjoyment (PE), and Subjective Norms (SN). On the contrary, the data portrayed Perceived Risk (PR) as insignificant. However, our findings suggest that the TAM can still be used to explain the change in behavior associated with using a marketplace, particularly when buying online products or services. In addition, to give a more profound knowledge, various user characteristics according to generation group still need to be studied. Findings further suggest that this study has academic and industry ramifications regarding anticipating consumers’ online purchasing choices in the digital marketing community. The study concludes with a discussion of its limitations and future research directions.

Uncertainties, ranging from environmental threats and health epidemics to political instability, financial crises, and technological advancements, can significantly alter business environments. When such changes occur, service organizations face various difficulties that hinder their sustainable organizational performance. Consequently, the study empirically examines the influences of technological capability (i.e., digitalization, big data analytics, and a data-driven culture) on service firms’ sustainable organizational performance (SOP), and in turn, the impact of SOP on organizational resilience (OR) via the moderation of innovation leadership. Drawing on the theoretical frameworks of the dynamic capability view (DCV) and flexible systems management (FSM), the proposed hypotheses were tested via survey data collected from 297 senior-level professionals in service organizations. The results of partial least squares structural equation modeling (PLS-SEM), necessary condition analysis (NCA), and fuzzy-set qualitative comparative analysis (fsQCA) revealed that technological capability significantly influences sustainable organizational performance, which in turn contributes to organizational resilience, particularly when innovation leadership is present. Thus, technological capability, as the foundation of a flexible system, enables rapid resource reconfiguration, real-time data-driven decision-making, and scalable operations. In doing so, it directly enhances sustainable organizational performance and indirectly supports organizational resilience, which is reinforced by innovation leadership. These insights advocate that service firms leverage technological capability and innovation-driven leadership to ensure sustainability and resilience in complex and uncertain environments while maintaining operational and managerial flexibility.

Environmental challenges critically affect manufacturing firms which face numerous concerns regarding their sustainable operations. These operations aim to operationalize the dimensions of circular economy capabilities (CEC) and green technology innovation (GTI) to strengthen competitiveness in fragile environments. This research validates a holistic understanding of green performance by integrating theories and dimensions to identify effects that predict sustainable green performance. Drawing from the green dynamic capability view (GDCV), which is a contextual extension of the DCV and flexible systems management (FSM) paradigm, this study investigates how CEC and GTI predict green performance (GP). Survey data of 301 senior professionals from manufacturing firms acquired from a developing country, such as Bangladesh, were used. To assess the survey data, the study used a multimethodological approach using Necessary Condition Analysis (NCA) and fuzzy-set Qualitative Comparative Analysis (fsQCA) to investigate the suggested tie in the midst of the CEC and GTI on the GP. The findings reveal that all the antecedents of the circular economy are necessary conditions except absorptive capacity to predict green performance, as reported in the NCA. The fsQCA results show that combinations of CEC and GTI are sufficient conditions to predict high green performance. This research uses a unique combination of CEC and GTI to predict high GP via the supplementary method of fsQCA. Therefore, the findings should also motivate professionals of manufacturing firms to focus even more on the necessity effects of a single condition to predict GP and the asymmetric effects of combinations of CEC and GTI to produce multiple configurations to predict high green performance.