Daniel Thiel

Economic simulation of a poultry supply chain facing a sanitary crisis

The purpose of this paper is to study the behaviour of a food supply chain possessing two originalities, i.e. a singular structure (40-day upstream push and 24-hour downstream pull) and one that suffers from simultaneous fluctuations in raw material supply capacities (due to epizooty) and customer demand (due to customer anxieties and fears) caused by a sanitary crisis.

Forecasts impacts on sanitary risk during a crisis: a case study

Purpose – During a crisis situation, a poultry supply chain is faced with high variations on fresh chicken meat demand and has therefore to simultaneously manage excessive shelf-life stocks (in case of falling demand) and external purchases due to inventory shortages. In this case, the production plan is often established according to non-accurate sale forecasts which require ongoing adjustment. The paper aims to discuss these issues. Design/methodology/approach – By using system dynamics, the paper developed a model of the French poultry supply chain during a given avian influenza crisis period. The authors compared exponential smoothing forecasting method to a word-of-mouth diffusion model which makes sense in a sanitary crisis context. Findings – An interesting result shows a complex relationship between the sanitary risk (which increases according to the slaughtered chicken’s volume and storage time) and the additional external purchases (in case of low production generated by an insufficient forecasting launched 40 days before customer orders). Research limitations/implications – Additional costs which vary over time are required for further assumptions testing. Practical implications – The paper proposes to use a forecasting model which is not currently used by the professionals during a sanitary crisis period. This model is able to simulate an internal dissemination of a call for boycott of meat products (cf. negative word-of-mouth spread). Originality/value – The problem is how to maintain a less risky but significant buffer size to respond to a supply chain coping with both changes in customers’ demand and instability in production capacity. Keywords Quality, Forecasting, Supply chain management, Food industry, System dynamics, Push-pull supply chain, Sanitary risk Paper type Case study

A multi-agent model for optimizing supermarkets location in emerging countries

We propose a simple location model taking into account an existing traditional market and the increasing attractiveness of urban consumers for supermarkets in Hanoi city. The foundation of this model is based on sociological studies on consumer perception of supermarkets in this city. We represented the purchase decision-making rule based on various criteria such as the agents incomes, the product quality levels and the points-of-sales distances from their home. We built a multi-agent model simulating the consumers choices between many traditional markets and a new local supermarket to optimally localize. Thanks to the Particle Swarm Optimization heuristic, the model iteratively determines a place maximizing the sales volume of the new supermarket. Some interesting results can help the decider to choose a price policy as well as a product quality level according to existing point-of-sales locations.