Data-Driven Transformation: The Role of Ambidexterity and Analytics Capability in Building Dynamic and Sustainable Supply Chains

Abstract

Data-driven supply chain analytics skills are seen as the next frontier of the supply chain transformation. The potential of data analytics-enabled dynamic capability for improving organizational performance and agility has been investigated in past research. However, there has not been sufficient research on the potential benefits of the data analytics capability and supply chain ambidexterity paradox to develop a sustainable and agile supply chain that can integrate and reorganize all of its resources in order to respond to rapidly changing business circumstances. This study aimed to empirically validate how an organization’s SC ambidexterity affects its sustainability and dynamic capability, and the mediating role of supply chain analytics capability (SCAC) in their relationship. The research’s theoretical framework is founded on dynamic capability theory. A pretested questionnaire was used to collect responses from 427 supply chain specialists who worked in diverse product-based industries across Pakistan, Bangladesh, and India. Using partial least squares structural equation modeling (PLS-SEM), a total of six hypotheses were evaluated, and the results show that supply chain ambidexterity has a positive effect on dynamic capability and sustainability, and SCAC plays a complementary, partially mediating role in their interaction. The findings of the research reveal the expected results of investing in the analytics capability of the supply chain and provide firms with some recommendations for improving their dynamic capabilities. This study will facilitate in creating an agile and sustainable supply chain, enabling it to adapt to both short- and long-term changes in the market while simultaneously considering the social, economic, and environmental vitality.