Data envelopment analysis for investigating the relative efficiency of supply chain management
First online: 09.11.2017
Cite this article as: Gold, S., Reiner, G., Dion, P. Logist. Res. (2017) 10: 6. doi:10.23773/2017_6
Despite the growing popularity of supply chain management (SCM) both among managers and scholars, the efficiency of implementation of SCM has been barely assessed in an analytic way. The purpose of this study is to shift the attention of SCM scholars towards an in-depth investigation of SCM efficiency by reporting procedure and outcomes of one possible methodological approach. The current study investigates the relative efficiency of SCM implementation (in terms of ratio of various outputs to inputs) and subsequently identifies influencing factors. This procedure is illustrated by an empirical application based on a European sample of manufacturing plants as Decision Making Units (DMUs), following a two-step approach. (1) Data envelopment analysis (DEA) assesses the relative efficiencies of SCM implementation of DMUs. (2) Subsequently, factors fostering or impeding SCM efficiency are explored through a bootstrapped truncated regression model. Our analysis finds that factors influencing relative SCM efficiency refer to country affiliation, characteristics of manufacturing plants, characteristics of production, buyer’s purchasing situation, and buyer-supplier relationship characteristics, confirming previous literature that highlight complex and contingent interrelation between investments into buyer-supplier relationships and performance. Going beyond previous research, our study reframes the strategic implementation of SCM from the distinct angle of the economic principle of efficiency. It provides a novel approach of assessing the efficiency of SCM implementation in an analytic way, thus guiding managers in their strategic decision-making regarding the input-output ratio of SCM. Simultaneously, our study adds to SCM theory by conceptualizing strategic SCM as an input-output system with varying transformation efficiencies.
Supply chain management data envelopment analysis DEA bootstrapped truncated regression relative efficiency input-output system