Big data driven supply chain innovative capability for sustainable competitive advantage in the food supply chain: Resource-based view perspective

The food supply chain (FSC) is becoming more sustainable as companies aim to meet demand with lower waste and emissions. Big data analytics (BDA) can help achieve sustainability goals by extracting meaningful information from past data to help create sustainable strategies. However, in the sustainability literature, BDA's role in enabling sustainable FSC innovations is not explored. Thus, this study investigates how data-driven analytics might improve FSC innovation by adopting creative tactics in every triple bottom line (TBL) component - green, corporate social responsibility (CSR), and financial - to gain a competitive edge. A resource-based view (RBV) perspective was used to evaluate the links between supply chain (SC) innovation capabilities and competitive advantage (CA) in FSC innovation and sustainability. Indian food processing enterprises were surveyed using a questionnaire to collect data from 200 respondents. Adopting a structural equation modelling (SEM) approach, six hypotheses were evaluated for significance on the surveyed data using AMOS V.20. Since both goodness and badness fit indices were above cut-off values, the measurement model was robustly evaluated and found to fit the survey data well. Structural model findings supported all study hypotheses. The results indicate that BDA strongly impacts food supply chain TBL and FSC innovation. Data-driven innovative TBL methods were shown to boost FSC competitiveness. With the growing demand for value-added innovation in FSC sustainable development, this study uniquely contributes to the current literature by linking BDA and TBL practice innovation to FSC CA.