Purpose: The digital transformation of family-owned small businesses (F-OSBs) has become a critical area of research to maintain their economic contribution in today’s rapidly evolving digital landscape. This study examines the effect of internet entrepreneurial self-efficacy on the digital transformation of F-OSBs by mediating strategic agility and moderating artificial intelligence usage. Design/methodology/approach: This study employed a cross-sectional survey design to collect primary data from 378 descendent entrepreneurs of F-OSBs in Pakistan’s five major cities. Findings: The study revealed that leadership ability, internet marketing, technology utilization, and artificial intelligence used by the F-OSBs can contribute to their digital transformation, but e-commerce ability does not. The strategic agility of the descendant entrepreneur enhances the abilities of e-commerce, leadership, and technology utilization, leading to the digital transformation of F-OSB. However, strategic agility reduces the role of Internet marketing in digital transformation. Artificial intelligence usage moderates leadership’s ability to improve strategic agility but increases technology utilization for strategic agility and digital transformation of F-OSB. Practical implications: The digital transformation through a combination of strategic agility and artificial intelligence can increase the F-OSBs' proactive approach to respond to changing market conditions even during economic recessions like COVID-19. Originality/value: This study broadens the existing literature by examining the effect of descendent entrepreneur’s internet entrepreneurial self-efficacy, strategic agility, artificial intelligence usage, and their interplay on the digital transformation of F-OSB through the unified theory of acceptance and the use of technology.

The objective of this study was to examine the impact of green supply chain management (GSCM) on sustainable performance (SP) and the mediating role of green knowledge sharing (GKS), green innovation (GI), and big data-driven supply chain (BDDSC) in SMEs of Pakistan as a developing country. Primary data was gathered through adopted questionnaires from SME employees. Four hundred sixty-nine cases were considered for data analysis after data clearing in SPSS version 25. Furthermore, the proposed hypotheses were tested with the help of SmartPLS version 3 through structural equation modeling SEM. Findings revealed all seven direct hypotheses, including GSCM on SP, GKS, GI, and BDDSC and GKS, GI, and BDDSC on SP in SMEs of Pakistan. Moreover, the partial mediation effect of GKS, GI, and BDDSC was also confirmed between GSCM and SP. This study contributes to the context of SMEs in developing countries and recommends findings for future policies and implications at the firm and government levels for better results. Policymakers, SME owners, and managers must support innovation culture, engage their stakeholders, and invest in new products, processes, and business models relevant to addressing environmental and sustainability concerns. Moreover, Pakistan’s government policymakers recognize SMEs’ power to effectively integrate GSCM knowledge sharing, green innovation, GSCM practices, and big data technology into supply chain management.

This study investigates the impact of green innovation (GI) on corporate environmental performance (CEP), while examining the moderating roles of corporate governance practices (CGPs) and environmental policy pressure (EPP). This study uses advanced statistical methods to ensure the reliability of the results. These include techniques such as propensity score matching (PSM), difference-in-differences (DID) analysis with China’s National Green Development Fund (2020) as the policy intervention, and the generalized method of moments (GMM), and this study examines how internal governance mechanisms and external regulatory pressures influence the GI-CEP relationship. The results show that GI significantly increases CEP, and that this effect is amplified by robust CGPs and EPP. By analyzing data from 4026 firm-year observations of A-share listed Chinese companies (2017–2022), the findings highlight the importance of innovation, governance, and policy in achieving sustainable environmental outcomes. This study provides valuable insights for firms and policymakers to foster green innovation and align corporate strategies with global sustainability goals.

Green innovation plays a crucial role in sustainable development, yet its financial impact on high-pollution industries remains underexplored. This study analyzes the short- and long-term financial effects of green innovation using 30,108 firm-year observations from Chinese A-share listed companies in high-pollution industries (2009–2022). Employing fixed-effects regression models, green innovation is measured through environmental patents (EnvrPats) and environmentally innovative patents (EnvrInvPats), with Return on Assets (ROA) as the financial performance metric. To address endogeneity concerns, instrumental variable (IV) techniques are applied using digital transformation (DT) as an instrument, alongside a two-stage Generalized Method of Moments (GMM) approach for validation. This study explores the moderating roles of Sustainable Liquidity Reserves (cash flow) and the Sustainable Development Index (ESG performance), while a channel test examines the influence of R&D expenditures and financial constraints. A heterogeneity analysis reveals that firms in high-pollution industries experience greater short-term financial benefits from green innovation, driven by regulatory pressures and public scrutiny. A pre- and post-COVID-19 analysis highlights the increased importance of green innovation in firm resilience during economic disruptions. Robustness checks, including alternative financial performance measures and nonlinear modeling, confirm the reliability of the findings. While green innovation imposes initial financial costs, firms with stronger cash reserves and ESG performance can better absorb these costs and achieve long-term financial gains, emphasizing the need for targeted policy support to facilitate sustainable growth.

This empirical paper examined the moderating role of comprehensiveness between social media and online shopping intention among customers of Jordanian pharmacies. Technology acceptance model (TAM) and the theory of planned behaviour (TPB) were the applied theories in this study. Data were collected from potential customers using a survey questionnaire. A total of 198 usable questionnaires were obtained and the data were analyzed. Partial least squares structural equation modeling (PLS-SEM) was used in the outcome examination. The results show a positive impact of social media on online shopping intention. Further, comprehensiveness moderated the relationship strengths between social media and online shopping intention. This paper finds that focusing on social media strategies such as adopting intimacy, decreasing the perceived risk, and increasing trust could motivate online shopping among customers. Pharmacies in Jordan may consider these findings and achieve them by providing more comprehensive information in their advertisement and announcement.