Investigating crowd logistics platform operations for local food distribution

Titelangaben

Cramer, Florian ; Fikar, Christian:
Investigating crowd logistics platform operations for local food distribution.
In: International Journal of Retail & Distribution Management. (2023) .
ISSN 1758-6690
DOI: https://doi.org/10.1108/IJRDM-10-2022-0400

Volltext

Link zum Volltext (externe URL):

Zugehörige Forschungsdaten

• https://doi.org/10.17632/w63fcbf2yd.1

Abstract

Purpose
Short food supply chains have the potential to facilitate the transition to more sustainable food systems. Related distribution processes, however, can be challenging for smallholder and family farmers. To extend the market reach of farmers without the need for extensive investments, crowd logistics (CL) can be used. The purpose of this paper is to explore the benefits and trade-offs of implementing CL platforms in short food supply chains (SFSCs).

Design/methodology/approach
A decision support system (DSS) based on agent-based and discrete event simulation (DES) modelling is developed, which closely approximates the behaviour of customers and distribution processes at outlets. Different scenarios are explored to evaluate the potential of CL in rural and urban settings using the example of regions from Bavaria, Germany.

Findings
Results show that CL can be used to increase the reach of farmers in SFSCs at the cost of minor food quality losses. Moreover, a difference between urban and rural settings is noted: An urban scenario requires less investment in the driver base, whereas the rural scenario shows a higher potential to increase market reach.

Originality/value
Platform-based food delivery services are still mostly unexplored in the context of SFSCs. This research shows that platform services such as CL can be used to support local agriculture and facilitate the distribution of perishable food items, introducing a simulation-based DSS and providing detailed results on various application settings; this research serves as a steppingstone to facilitate successful real-world implementations and encourage further research.