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

Daniel Thiel (), Thi Le Hoa Vo () and Vincent Hovelaque
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Daniel Thiel: CEPN - Centre d'Economie de l'Université Paris Nord - UP13 - Université Paris 13 - USPC - Université Sorbonne Paris Cité - CNRS - Centre National de la Recherche Scientifique
Thi Le Hoa Vo: CREM - Centre de recherche en économie et management - UNICAEN - Université de Caen Normandie - NU - Normandie Université - UR - Université de Rennes - CNRS - Centre National de la Recherche Scientifique

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Abstract: 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. Design/methodology/approach – By using system dynamics, we developed a model of the French poultry supply chain during a given Avian Influenza crisis period. We 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 – We propose 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 – Our 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: Sanitary risk; Quality; Push-pull supply chain; Forecasting; Supply chain management; System dynamics; Food industry (search for similar items in EconPapers)
Date: 2014
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Citations: View citations in EconPapers (1)

Published in International Journal of Logistics Management, The, 2014, 25 (2), pp.358-378. ⟨10.1108/IJLM-04-2012-0028⟩

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Persistent link: https://EconPapers.repec.org/RePEc:hal:journl:halshs-01075637

DOI: 10.1108/IJLM-04-2012-0028

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