Title: Nobody wants to buy sour milk: supply chain performance measure matters

Authors: W. Wei; J.F. Low; A. Schiffauerova

Addresses: Concordia Institute for Information Systems Engineering, Concordia University, Montreal, Quebec, Canada ' Department of Engineering Systems and Management, Masdar Institute of Science and Technology, Abu Dhabi, United Arab Emirates ' Department of Engineering Systems and Management, Masdar Institute of Science and Technology, Abu Dhabi, United Arab Emirates

Abstract: In the increasingly competitive manufacturing landscape, the key to thriving is in managing the supply chain. Supply chain performance measurement systems, which gauge the performance of a supply chain on different metrics, are indispensable tools for supply chain management. By introducing a weighted and industry-independent performance measure and incorporating it in a questionnaire distributed to manufacturing companies, we were able to compare supply chain performance between different categories of manufacturers. We identified management as the biggest impediment towards implementation of supply chain performance measures. The results also show that supply chains in light industry are flexible but members of each supply chain interact poorly. Heavy industry supply chains suffer from inflexibility but have good interactions between members within each supply chain. Despite international supply chains having many advantages over domestic supply chains, our survey respondents indicated that global supply chains perform better than local supply chains. And, supply chains which have members who are actively cooperating, whether in the form of a pact, partnership, or alliance, perform better than supply chains where such cooperation does not exist. Finally, our study found that the performance of supply chains with performance measurement systems in place trumps the performance of supply chains without them.

Keywords: supply chain; supply chain management; SCM; supply chain performance measurement system; comparative analysis.

DOI: 10.1504/IJLSM.2018.088584

International Journal of Logistics Systems and Management, 2018 Vol.29 No.1, pp.62 - 81

Received: 17 Mar 2016
Accepted: 10 Jul 2016

Published online: 12 Dec 2017 *

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