Managing supply chain complexity and sustainability: the case of the food Industry

Abstract

Consumer demand for organic products, rapidly growing urbanizations levels requires the food supply chain to reduce lead-time and maintain higher product quality. For the food supply chain to cope with the raising issues an e-commerce type of supply chain must be implemented. This approach creates challenges for supply chain, because the food industry must shift towards high variety and low quantity freight forwarding with multiple delivery points. The methodology of the paper consists of scientific literature analysis and macro indicator clustering. The author of the paper proposes a supply chain management framework, which is grounded through complexity theory. The framework mainly consists of 3 characteristics, which organizations should operationalize to maintain system resilience and which in the long-run would evolve to sustainable development–capabilities, collaboration, complexity management. The proposed framework defines how operational and tactical levels should be automated through cyber-physical systems, while the automation should be controlled through strategic level variables. The macro level analysis of existing EU markets of the food industry has been conducted to identify the food industry’s contingencies, in which an agent-based model will be used to validate the proposed framework. Main 3 clusters were identified, which number was chosen based on the elbow method and validated with the silhouette score of 0.749. The food industry can be categorized in to developing, underdeveloped, and developed food industries. Moreover, singularities of different contingencies have been identified which considers population size, population density, market size of the food industry and disruption intensity. The application of the framework depends on the identified contingencies. From strategic level the SCMF is similar in all contingencies, however, depending on the type of market, more emphasize on vehicle routing or demand forecasting should be made.