In recent years, there has been a proliferation of interest in resilience in the supply chain field. Even though literature has acknowledged the antecedents of resilient supply chains, such as supply chain visibility, cooperation, and information sharing, their confluence in creating resilient supply chains where other behavioral issues are prevailing (i.e., trust and behavioral uncertainty) has not been studied. To address this gap, we conceptualized a theoretical framework firmly grounded in the resource-based view (RBV) and the relational view that is tested for 250 manufacturing firms using hierarchical moderated regression analysis. The study offers a nuanced understanding of supply chain resilience and implications of supply chain visibility, cooperation, trust, and behavioral uncertainty. Implications and suggestions for further research are provided.

Digital transformation has had an unprecedented influence on all sectors of business over the last decade. We are now entering an era characterized by the extensive digital transformation of businesses, society, and consumers. Therefore, digital transformation has become a pivotal focus for organizations across various sectors in recent years. Despite differing scholarly perspectives on the concept and elements of digital transformation, a consensus exists that it significantly impacts consumer decisions and necessitates organizational adaptation. Recent challenges such as the COVID‐19 pandemic have further accelerated the need for digital transformation and its effects on consumers. This necessitates an editorial perspective on this most important topic to establish future research agenda encompassing the various dimensions of digital transformation. The purpose of this editorial perspective is to review research on digital transformation from a multidisciplinary viewpoint and provide insights into several key domains—Internet‐of‐Things, social media, mobile apps, artificial intelligence, augmented and virtual reality, the metaverse, and corporate digital responsibility—that are poised to fuel the pace of digital transformation. Each domain is analyzed through a lens of introduction, role, importance, multifaceted impact, and conclusions. Future research directions are suggested.

Purpose: The purpose of this paper is to develop a theoretical model to explain the impact of big data and predictive analytics (BDPA) on sustainable business development goal of the organization.Design/methodology/approach: The authors have developed the theoretical model using resource-based view logic and contingency theory. The model was further tested using partial least squares-structural equation modeling (PLS-SEM) following Peng and Lai (2012) arguments. The authors gathered 205 responses using survey-based instrument for PLS-SEM.Findings: The statistical results suggest that out of four research hypotheses, the authors found support for three hypotheses (H1-H3) and the authors did not find support forH4. Although the authors did not find support forH4(moderating role of supply base complexity (SBC)), however, in future the relationship between BDPA, SBC and sustainable supply chain performance measures remain interesting research questions for further studies.Originality/value: This study makes some original contribution to the operations and supply chain management literature. The authors provide theory-driven and empirically proven results which extend previous studies which have focused on single performance measures (i.e. economic or environmental). Hence, by studying the impact of BDPA on three performance measures the authors have attempted to answer some of the unresolved questions. The authors also offer numerous guidance to the practitioners and policy makers, based on empirical results.

Purpose: With considerable international awareness of circular economy (CE), the purpose of this paper is to propose a theoretical framework, informed by institutional theory and upper echelon theory (UET), to explain how top management commitment (TMC) mediates the relationship between external pressures and supplier relationship management (SRM) practices for CE.Design/methodology/approach: The authors test the hypotheses using cross-sectional data gathered using a survey of companies involved in sustainability practices.Findings: The results of the hierarchical regression and mediating regression analyses suggest that TMC positively mediates the effect of external institutional pressures on SRM.Originality/value: The authors advance existing theory by integrating institutional theory and UET to explain SRM practices in sustainable supply networks. Furthermore, the authors offer guidance to managers who would like to engage in leveraging SRM in sustainable supply networks and outline future research directions.