– Taking a social network perspective, the purpose of this paper is to develop a framework for the assurance of food safety via relational networking.
– The authors consider both informal and formal relational networking, and explore a firm’s learning orientation, risk aversion and consumer pressure as potential precursors to such relational networking. It is further hypothesized that relational networking generates both industry and supply chain knowledge, which is suggested to be beneficial for contamination detection. The model is tested with survey data collected among food-producing firms in India, the world’s second largest food producer.
– The authors find a positive influence of consumer pressure on both a firm’s learning orientation and risk aversion, which in turn affect both informal and formal relational networking. Informal networking further generated industry knowledge and was beneficial for contamination detection. Formal relational networking influenced supply chain knowledge, which in turn enabled contamination detection.
– Recent food product-related safety breaches, which have, in the worst case, led to fatalities, illustrate the importance of food safety in supply chains. This study represents the first systematic investigation of relational networking in the context of food safety from the perspective of social network theory.
