What Demand and Supply Forces determine the location of off-farm points of sale in Short Food Supply Chains: Evidence from Nord and Pas de Calais, France
Rawaa Laajimi  1@  , Laurence Delattre  2@  , Hubert Jayet  2@  , Nicolas Debarsy  2@  
1 : INRAE
INRAE, UR Ecodéveloppement, 228 route de l'aérodrome CS 40509 Domaine Saint Paul, Site Agroparc, F-84914, Avignon, France
2 : LEM
LEM-CNRS, Université Lille 1

If the characteristics and location of farms and consumers involved in short food supply chain (SFSC) are well studied, especially for on-farm sales, the location of off-farm points of sale - as interaction point between supply and demand – has not been much analyzed, especially from a quantitative perspective. Though, a better understanding of the factors favoring and impeding the emergence of such points of sale could be valuable for producers (farmers), sellers (farmers or intermediaries), consumers (through consumers driven initiatives) but also for policymaking. To fill this gap, we have compiled an original database from local, regional, and national websites for the year 2020 and geolocalized more than 500 points of sale (pick-up point for sale by internet, pick-up point for community supported agriculture, producers' collective stores, markets and retail stores) in two French departments (Nord and Pas-de-Calais). We account for the local environment of each point of sales, both in terms of potential supply of agricultural products and potential food demand, by relying on distance-weighted variables (inspired by the concept of market potential). We then estimate a count model at the municipal level to distinguish the demand and supply factors explaining the creation of points of sale. Even though this first model is already estimated at the smallest administrative geographical scale, leading to potential policy recommendations, we also wanted to go as far as possible in the understanding of the location of off-farm points of sales and we thus estimate a model explaining the existence of a point of sales at the INSEE-grid scale (200 square meters). After discussing our finding, the paper closes on policy recommendations and future research opportunities.


Online user: 1 Privacy
Loading...