Application of centralised DEA in an automobile parts retail network in Taiwan

Abstract

Purpose

The purpose of this study is to address three managerial issues in a retail network under a centralised regime, including resource allocation, expansion and downsizing. In particular, this study investigates how to optimise resource allocation across retailers and how to decide the optimal size of a retail network for an empirical case, where 27 retailers belong to an automobile parts supplier in Taiwan.

Design/methodology/approach

The centralised data envelopment analysis (DEA) approach is used to optimise resource allocation among retailers and to seek the possibility of either an expansion and/or downsizing for a retail network.

Findings

The case company knows the best way to (re)allocate its available resources and (re)arrange the outcome goals for its own retailers. The 27 retailers are assigned specific targets for input and output adjustments to become Pareto or technically efficient units. Besides, an experiment is designed to measure how changing the number of retailers affects the group efficiency of the retail network. To keep the current aggregated output level of the retail network, the centralised supplier needs at least 24 retailers. However, the retail network with 37 retailers can achieve maximal group efficiency.

Originality/value

Centralised resource allocation is an inherent feature of most supplier-retailer relationships, where the supplier is usually a central planner with the power to allocate available resources among its own retailers. To the best of our knowledge, this is the first study to assess retail performance under a centralised regime.

Citation

Yang, F.-C. (2020), "Application of centralised DEA in an automobile parts retail network in Taiwan", International Journal of Retail & Distribution Management, Vol. 48 No. 7, pp. 667-686. https://doi.org/10.1108/IJRDM-02-2019-0061