Through the lens of entrepreneurial orientation, this study investigates operational practices that (small and medium-sized enterprises) have either adopted or improvised to support small and medium-sized enterprises’ resilience in the face of coronavirus disease 2019. Qualitative data were collected through 43 semi-structured interviews with entrepreneurial resource providers, owners and managers of several small and medium-sized enterprises across different industrial sectors in Jordan. The study contributes to the further understanding of small and medium-sized enterprises’ resilience by conceptually advocating a five-pillars practitioner-grounded framework of small and medium-sized enterprises’ resilience capability (efficiency-based capability, adaptive-capability, collaborative-capability, change-capability and learning-capability). Entrepreneurial orientation has been found to transition and mobilise small and medium-sized enterprises’ resilience to survive major disruptions and threats. Entrepreneurial orientation, in this study, grounded on risk-taking, innovation and proactivity, facilitates developing new capabilities that shield the firm against different threats. Practically, the study suggests several recommendations for small and medium-sized enterprises to meet the challenges of coronavirus disease 2019 and similar future major shocks. Notably, the study suggests that small and medium-sized enterprises should balance short-term operational actions with long-term strategic thinking to build a resilience capability pool.

Purpose: This study investigates the role of supply chain knowledge management in enhancing pharmaceutical supply chain resilience.Design/methodology/approach: This study focusses on the Middle East region, where semi-structured online interviews were conducted with 38 professionals from the pharmaceutical supply chain to collect empirical data.Findings: The study reveals that supply chain knowledge management is a crucial value-adding practice that improves pharmaceutical supply chain resilience. Effective supply chain knowledge management enables organisations to develop agility, change, adaptability, problem-solving, response and innovation capabilities that support supply chain resilience. However, challenges related to supply chain management practices, people, processes and technology hinder the effective promotion of supply chain knowledge.Practical implications: This study reminds managers that knowledge management is critical for building resilience in supply chains.Social implications: The study highlights the importance of a resilient pharmaceutical supply chain for organisations and society. The study advocates that effective supply chain knowledge management can help ensure a sustained supply of high-quality pharmaceutical products and services during crises.Originality/value: The study offers novel insights by examining pharmaceutical supply chain resilience from a knowledge management perspective and highlighting the potential of knowledge capabilities to enable supply chains to recover from crises and adapt to the new normal. This study also highlights the key strategic considerations for managing knowledge effectively throughout the supply chain.

This study examines the impact of CEO career dynamics (including CEO tenure, CEO horizon and CEO seasons) on environmental management within the UK context. Unlike the previous studies that have primarily focused on corporate social performance, we instead examine these relations within the environmental management context. We posit and detect that CEO tenure has a positive nonlinear association with environmental management, indicating that CEOs' interest in environmental issues diminishes over time. We also provide evidence that CEO horizon has a positive impact on environmental management. Finally, as regards CEO seasons, we provide limited support that CEOs in their ‘convergence’, and ‘Response to mandate and experimentation’ stages are associated with environmental management. These results hold important implications for both firms and policymakers in the United Kingdom.

Purpose: This study aims to investigate the mediating role of different types of intellectual capital (human, structural and relational) in the relationship between artificial intelligence-driven supply chain analytics capability (AI-SCAC) and various supply chain decision-making processes, specifically rational, bounded and tacit decision-making.Design/methodology/approach: The study used a quantitative survey strategy to collect the data. A total of 320 valid questionnaires were received from manufacturing companies. The data were analysed using structural equation modeling with partial least squares (PLS-SEM) approach through SmartPLS software.Findings: The results indicate that human and structural capital significantly mediate the relationship between AI-SCAC and rational and bounded decision-making processes. However, structural capital does not mediate the relationship between AI-SCAC and the tacit decision-making process. Moreover, relational capital does not show a significant mediating effect on all of the decision-making processes. Notably, structural capital has the strongest impact on rational and bounded decision-making, while human capital plays a critical role across all three decision-making processes, including tacit decision-making.Originality/value: This study contributes to the literature by providing a nuanced understanding of the differentiated impact of intellectual capital components on various decision-making processes within the context of AI-SCAC. While previous studies have broadly acknowledged the role of intellectual capital in decision-making, this research provides more understanding of how specific types of intellectual capital interact with AI to influence distinct decision-making processes. Notably, the differential impact of structural capital on rational and bounded decision-making versus tacit decision-making highlights the need for organisations to adopt a more tailored approach in leveraging their intellectual capital.

The aim of this research is to enhance Oil and Gas (O&G) construction risk assessment using Fuzzy-based Failure Model Effect Analysis (FMEA) through the lens of O&G project managers in the U.S. A mixed-method approach was adopted for data collection, analysis, and processing, including semi-structured interviews with project managers to identify the key risks facing O&G construction projects; a Fuzzy-based FMEA to quantitatively analyse the level of significance of O&G risks; surveys to rank the assessment dimensions of the developed model and their components; and open-ended surveys to validate and verify the assessment model and its outputs, further expanding on the root causes of significant risks based on the assessment outputs, and to propose mitigation strategies for these risks. The research identified 41 risk factors classified under six categories, namely: management, technical and quality, financial and economic, health, safety, environmental, legal, and stakeholders’ risks. In addition, the risk assessment revealed that non-compliance with PPE regulations emerged as the most significant risk factor across all categories of O&G risks. This study offers valuable insights by assisting practitioners in better understanding the significant O&G risks that need to be addressed to ensure the successful execution and completion of O&G projects.