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.

中文翻译：

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大数据驱动供应链创新能力，实现食品供应链可持续竞争优势：基于资源的视角

随着公司致力于通过减少浪费和排放来满足需求，食品供应链 (FSC) 变得更加可持续。大数据分析 (BDA) 可以通过从过去的数据中提取有意义的信息来帮助制定可持续发展战略，从而帮助实现可持续发展目标。然而，在可持续发展文献中，并未探讨 BDA 在实现可持续 FSC 创新方面的作用。因此，本研究探讨了数据驱动分析如何通过在每个三重底线 (TBL) 组成部分（绿色、企业社会责任 (CSR) 和财务）中采用创造性策略来提高 FSC 创新，以获得竞争优势。基于资源的观点（RBV）视角用于评估供应链（SC）创新能力与FSC创新和可持续性方面的竞争优势（CA）之间的联系。采用问卷调查的方式对印度食品加工企业进行了调查，收集了 200 名受访者的数据。采用结构方程建模 (SEM) 方法，使用 AMOS V.20 评估了六种假设对调查数据的显着性。由于良好和不良拟合指数均高于截止值，因此对测量模型进行了稳健评估，并发现其与调查数据拟合良好。结构模型结果支持所有研究假设。结果表明，BDA 强烈影响食品供应链 TBL 和 FSC 创新。数据驱动的创新 TBL 方法被证明可以提高 FSC 竞争力。随着 FSC 可持续发展对增值创新的需求不断增长，本研究通过将 BDA 和 TBL 实践创新与 FSC CA 联系起来，对当前文献做出了独特的贡献。