Purpose The transition toward carbon neutrality has become a global strategic priority for achieving sustainable development and a green economy. Despite growing interest in digital transformation among scholars and practitioners, achieving a balance between green supply chain performance and carbon performance within the context of carbon neutrality remains underexplored. Drawing on the technology acceptance model and change management theory, this research aims to provide solutions for achieving the zero-carbon target in 2060 through holistic digital transformation, and how institutional pressure and organizational readiness influence green supply chain and carbon performance through digital transformation, low-carbon operations management practices (LCOMP) and the moderating role of environmental proactivity. Design/methodology/approach Data from 442 Chinese manufacturing firms were analyzed using Smart PLS v4 to test the research hypotheses. Findings The results indicate that all three dimensions of LCOMP mediate the relationship between digital transformation, green supply chain and carbon performance. In addition, environmental proactivity strengthens the influence of digital transformation on the three dimensions of LCOMP. Originality/value The findings contribute to the literature by addressing a key gap in sustainable supply chain and digital transformation research, which has largely examined these relationships in isolation without fully explaining the mediating mechanisms and boundary conditions.
Purpose Despite extensive research and policy efforts, there is still no consensus over the aspects that must be influenced to mitigate the environmental and social impact of city logistics. Existing approaches have primarily focused on optimizing urban freight operations but have struggled to generate lasting and systemic improvements. Building on recent supply chain management (SCM) calls to conceptualize supply chains as socially embedded systems, this study aims to investigate why cities implementing broadly similar collaborative governance initiatives produce different sustainable city logistics outcomes. Design/methodology/approach A qualitative configurational analysis was conducted across twenty French city logistics initiatives. Drawing on Furnari et al.’s (2021) configurational theorizing toolkit, governance conditions were iteratively identified and combined to explain variation in sustainable city logistics outcomes. Findings The analysis identifies five governance configurations. Rather than depending on collaborative governance alone, high-impact outcomes emerge from the interaction among governance structure, stakeholder representation, structural commitment and intervention scale. Research limitations/implications The governance configurations identified are grounded in French city logistics initiatives and should be further strengthened through fieldwork, and then examined in other institutional contexts. Future research should investigate how governance configurations evolve over time and across different socially embedded supply chains. Practical implications Managers and public authorities should focus less on replicating individual governance practices and more on assembling governance configurations that combine broad stakeholder representation, collaborative decision-making, structural commitment and coordinated ecosystem-level interventions. Originality/value The study advances SCM research by reconceptualizing sustainable city logistics as a governance and coordination challenge embedded within socially embedded supply chains. By doing so, it further demonstrates how configurational theorizing explains wicked sustainability problems in SCM by shifting attention from isolated governance mechanisms toward governance configurations as the appropriate unit of analysis.
Purpose This study aims to examine how generative artificial intelligence (GAI) adoption is associated with international green supply chain performance and international competitive advantage in cross-border e-commerce enterprises. Drawing on dynamic capabilities theory and the Technology–Organization–Environment–Human framework, the authors examine absorptive capacity and transformative capacity as intermediate capability mechanisms and artificial intelligence turbulence as a contingency. Design/methodology/approach The authors use an explanatory sequential mixed-methods design. The quantitative strand combines survey data from 334 Chinese cross-border e-commerce enterprises with partial least squares structural equation modeling, fuzzy-set qualitative comparative analysis and importance-performance map analysis. The subsequent qualitative strand draws on semi-structured interviews with ten managers and executives directly involved in GAI implementation, which are integrated with the quantitative evidence at the interpretation stage. Findings GAI adoption is positively associated with absorptive and transformative capacities, which are in turn positively associated with international green supply chain performance and international competitive advantage. International green supply chain performance shows the largest estimated association with international competitive advantage. Artificial intelligence turbulence positively moderates the relationships between GAI adoption and both capacities, and the configurational analysis identifies five equifinal configurations sufficient for high international competitive advantage. Practical implications Managers should develop absorptive and transformative capacities alongside GAI implementation, integrate sustainability requirements into artificial intelligence-enabled supply chain decisions and pursue internally coherent implementation routes rather than a single ideal template. Originality/value This study integrates variance-based, configurational and qualitative evidence to explain the capability pathways through which GAI adoption is associated with environmental and competitive outcomes in cross-border supply chain settings rather than in dyadic buyer–supplier relationships.
Purpose This study aims to investigate how big data analytics culture (BDAC) contributes to the development of antifragile humanitarian supply chains. Specifically, this study examines the mediating role of transactive memory systems (TMSs) and the moderating role of the frequency of natural disasters in the relationship between TMS and antifragility. Design/methodology/approach The authors collected 290 survey responses from key humanitarian professionals involved in disaster response operations. To test the proposed relationships among BDAC, TMS, antifragility and disaster frequency, the authors used Partial Least Squares Structural Equation Modeling (PLS-SEM). Findings The results of this study reveal that BDAC enhances antifragility only when fact-based decision-making improves information credibility, member specialization and coordination, core manifestations of TMS. TMS fully mediates the relationship between BDAC and antifragility, while the positive effect of TMS on antifragility is stronger in contexts with frequent natural disasters. Originality/value This paper advances the literature by empirically demonstrating TMS as the underlying mechanism linking BDAC to antifragility in humanitarian supply chains, showing how TMS operate as microfoundations of dynamic capabilities that enable collective sensing, coordinated decision-making and the reconfiguration of practices.
Purpose Drawing on dynamic capability theory and the natural resource-based view, this study aims to examine how green absorptive capacity (GAC) enhances environmental sustainability performance (ESP) through financial performance (FP) and operational performance (OP) and how blockchain technology (BCT) and supply chain finance (SCF) strengthen these indirect relationships. Design/methodology/approach Data were collected from 522 organisations in Egypt and 508 in Jordan. Covariance-based structural equation modelling was used to test the moderated mediation model. Findings The results show that in both Egypt and Jordan, GAC improves ESP indirectly through FP and OP. In Jordan, blockchain technology strengthens the indirect relationship through both financial and operational performance, whereas in Egypt these blockchain effects are not supported. Supply chain finance strengthens the indirect relationship through operational performance in both countries, but not through financial performance. The nested model comparison indicates that whilst the overall model applies to both contexts, BCT and SCF exert varying degrees of influence in Egypt and Jordan. Research limitations/implications The results can support policymakers and organisational stakeholders by showing how digital technologies and green financing mechanisms can be used to strengthen the impact of green knowledge on performance and accelerate progress towards environmental sustainability. Originality/value This study develops and tests an integrated moderated mediation framework explaining how green absorptive capacity enhances environmental sustainability performance through financial and operational performance and how blockchain technology and supply chain finance strengthen these indirect relationships. By comparing Egypt and Jordan, the study extends dynamic capability theory and the natural resource-based view through context-specific evidence from two Arab emerging economies and reveals country-specific differences in the effectiveness of digital and financial enablers.
