Adoption of Big Data Analytics: Determinants and Performances Among Food Industries

The study presents the results of the work undertaken to analyse constructs that make the companies adopt big data in the food industry towards the financial and market performance. Data was collected from 300 food industry employees who work in vital roles in the company. Primary data was collected through a survey method and a theoretical model was tested. Technological—Organizational—Enviornmental (TOE) framework was adopted, and the factors were analysed using Smart PLS software. It reveals that trialability, observability, complexity, and top management support are having a greater influence on big data analytics (BDA) adoption. Furthermore, external support, uncertainty and insecurity, and organizational readiness are also identified to affect BDA adoption. The findings ascertain the impact of BDA on the financial performance and marketing performance of the organisations. Understanding the variables that affect BDA acceptability enables managers to take the appropriate steps for a successful deployment. The research aids BDA service providers in luring and spreading BDA in the food sector.