Adnan Khan

Purpose: This study examines how employees' perceptions of STARA (smart technologies, artificial intelligence, robotics, and algorithms) influence their intrapreneurial behaviour (IB) and digital competence (DC), and how digital dynamism (DD) conditions this relationship. Design/methodology/approach: Drawing on Dynamic Capabilities Theory, Sociotechnical Systems Theory, and the Antecedents–Decisions–Outcome framework, the study develops an integrated model explaining how employees' perceptions of STARA shape behavioural responses and digital capability development. Data were collected from full-time employees in China's electric vehicle (EV) manufacturing sector, a context characterized by extensive use of STARA technologies, using an online survey and stratified purposive sampling, resulting in 193 valid responses. Partial least squares structural equation modeling was applied to test the proposed model. Findings: The results show that positive perceptions of STARA are associated with higher levels of IB and DC. IB serves as a key mechanism through which perceived STARA relates to DC. This highlights the role of employee behaviour in capability development. DD weakens the positive relationship between perceived STARA and DC, suggesting that high environmental turbulence may constrain employees' ability to translate perceived technological opportunities into DC. Research limitations/implications: The study offers a socio-technical explanation of digital capability development by showing how employees' interpretations of technological change and their behavioural responses jointly shape capability outcomes. It highlights the importance of aligning technological change with employee-driven adaptation under conditions of environmental uncertainty. Practical implications: The findings provide insights for managers in technology-intensive manufacturing firms. They show how employees' perceptions of STARA and intrapreneurial behaviour can contribute to DC. Social implications: The findings suggest that fostering IB and DC can enhance employee adaptability, employability, and career resilience, contributing to a more digitally prepared workforce amid ongoing technological transformation. Originality/value: This study contributes to the literature on digital transformation and capability development. It integrates employees' perceptions of STARA with employee behaviour within a sociotechnical framework in the EV manufacturing context.

This study investigates the transformative interaction among digital resilience (DR), Internet of Things-oriented supply chain practices (IoTP), AI-driven innovative practices (AIDIP), and sustainable supply chain performance (SSCP) in the context of the dynamic capability view (DCV) theory. Using empirical data from 293 high-tech SMEs in China that have adopted IoT and AI practices and analyzing it through partial least squares structural equation modeling (PLS-SEM), the results show that DR has a significant effect on IoTP and AIDIP improvement, which in turn positively influences SSCP. Notably, IoTP has a positive impact on operational efficiency and environmental sustainability, whereas AIDIP is also vital to resource optimization and predictive analytics. Moreover, SCD moderates the relationship between DR and IoTP, which amplifies the effectiveness of digital practices in dynamic environments. These findings have major implications for integrating digital technology with adaptive capacities in improving supply chain resilience (SCR), efficiency, and sustainability. However, since the sample is limited to Chinese high-tech SMEs with confirmed adoption of IoT and AI practices, the generalizability of the findings to other firm sizes or geographies should be approached with caution. The current research thus fills the gap between theory and practice and provides managers and policymakers with actionable insights while prescribing a robust framework for navigating the complexities of contemporary supply chain management.

Green innovation is crucial for reducing carbon dioxide (CO₂) emissions and promoting environmental efficiency worldwide. However, there is a lack of scholarly research investigating the relationship between environmentally friendly innovations and improved environmental performance. To fill this knowledge gap, a comprehensive study was conducted using data from 64 countries spanning 2010 to 2018. The study employed a hybrid approach, combining fuzzy DEA, structural equation modeling (SEM), and artificial neural networks (ANN) to analyze the nexus between green innovation and environmental efficiency. The SEM analysis revealed that green innovation, green trade, green employment, and green investment significantly impact environmental efficiency. The ANN model achieves a perfect prediction rate for environmental efficiency and green growth, emphasizing the importance of incorporating various sources of green innovation to achieve long-term environmental goals. The study’s findings have significant implications for policymakers and governments, highlighting the value of environmentally friendly technologies and the need to allocate resources toward their development. Regional collaboration and integrating green innovation throughout the development process are essential for achieving environmental efficiency. By embracing green innovation, nations can capitalize on its potential benefits while mitigating pollution and promoting sustainable development. Overall, this research serves as a cornerstone for decision-makers, providing insights into the importance of green innovation and guiding efforts to foster environmentally conscious technologies globally.

The direct influence of digital platforms on organizational efficiency, financial performance, and strategy attracts the close attention of researchers. The complex mechanisms and pathways of digital platforms on transformation capacity, however, are still unclear at the global and Asia Pacific levels. Drawing on dynamic capability theory, we empirically explore how digital platforms augment organizational innovation performance. We advance the current literature on digital platforms by finding that digital platform capability boosts an organization’s dynamism and innovation performance. Furthermore, we extend the literature by revealing that, indirectly, innovation capability and strategic alignment have a substantial influence over digital platform capability and innovation performance. Finally, the study formulates a conceptual model from a dynamic capability perspective, rather than from a resource-based view, and test it using the responses collected from 153 Pakistani manufacturing firms.

This study constructs a theoretical model to test and prove that organizational forgetting influences cross-boundary innovation and testifies to the moderating role of Institutionalized organizational mission in the said relationship. Data was collected through a convenient sampling technique from 353 middle and senior managers of entrepreneurial enterprises in China through online and offline modes. Additionally, we used confirmatory factor analysis, multiple regression, and bootstrap analysis to verify hypotheses using Analysis of a moment structures and Statistical Package for the Social Sciences latest versions. The results show that organizational forgetting has a significantly positive impact on cross-boundary innovation and binary knowledge sharing plays a mediating role in the relationship between organizational forgetting and cross-boundary innovation. Moreover, the mediating effect of exploitative knowledge sharing on the relationship between organizational forgetting and cross-boundary innovation is more substantial than exploratory knowledge sharing. This study separates the impact mechanism of exploitative and exploratory knowledge sharing as a mediator unanimously and proves that Institutionalized organizational mission has a significant moderating role in the relationship between organizational forgetting and cross-boundary innovation. This research offers significant implications for Chinese enterprises to bolster cross-boundary innovation to achieve growth.

Purpose: The manufacturing industry has recently faced many environmental issues and pressures due to increased environmental awareness. Business leaders identified that green innovation (GI) is a crucial aspect of sustainable development (SD) and can provide a competitive edge. On the other hand, boosting SD through GI is a complicated network activity involving various partners, and there is a need to transmit or share knowledge equitably and acceptably. Following the natural resource-based view (NRBV), this research presents a novel framework for investigating how green knowledge sharing (GKS) and green dynamic capabilities (GDC) affect green creativity (GC) and GI directly and through GC. Besides, the moderation of mimetic pressure (MP) was also evaluated in these targeted relations, as it is a critical element for enhancing GI in the context of SD.Design/methodology/approach: Data consisted 232 respondents from Pakistani manufacturing industries, and seven substantial hypotheses were verified regarding the direct, mediating and moderating effect of targeted variables in confounding ways using partial least squares structural equation modeling (PLS-SEM).Findings: According to the empirical findings, GKS and GDC positively correlate with GC and GI. Moreover, GKS and GDC significantly and positively impact GI both directly and indirectly. Furthermore, GC partially mediates GI, whereas MP has a significant moderating effect in these relationships.Originality/value: A significant correlation among these constructs was observed, demonstrating the conceptual framework for this study. These findings can assist practitioners and academics gain a better understanding of how to manage and evaluate GI in manufacturing projects at both the project and firm levels. Therefore, policymakers and project managers can enhance GI by focusing more on GKS, GDC, MP and GC.