To read this content please select one of the options below:

A trasilient decision making tool for vendor selection: a hybrid-MCDM algorithm

Ahmed Mohammed (Directorate of Telecommunication, Mosul, Iraq)
Irina Harris (Cardiff Business School, Cardiff University, Cardiff, UK)
Abdulsalam Dukyil (Department of Engineering, Brunel University London, London, UK)

Management Decision

ISSN: 0025-1747

Article publication date: 5 December 2018

Issue publication date: 26 February 2019

682

Abstract

Purpose

Vendor selection is the main activity in a sourcing decision, which is a strategic decision in that it leads enterprises to eliminate costs and improve their performance. However, an inappropriate selection may compromise the financial and operational status of the enterprise. But vendor selection is a complex, multi-criteria decision-making process because different and conflicting criteria have to be considered and assessed in order to find consistent suppliers. Consequently, evaluating and selecting the best vendor is the key to successful business. Traditionally, vendors are normally selected on the basis of traditional criteria (TC), such as costs and quality, neglecting resilience criteria (RC) (e.g. agility and flexibility). Thus, enterprises ultimately realize that a selecting method which involves TC as the only ones is inefficient and needs to be changed. The paper aims to discuss this issue.

Design/methodology/approach

This study was set in motion by a problem in practice. It aims to provide a user-friendly decision-making tool for selecting the best vendor from a group which submitted their tenders for implementing a proposed radio frequency identification (RFID)-based passport tracking system (Dukyil et al., 2017). The main traditional and resilience (“trasilience” henceforth) selection criteria were identified in a unified framework in collaboration with experts in the institution. Next, the Decision-Making Trial and Evaluation Laboratory (DEMATEL) algorithm was used to determine the relative importance of each criterion and the weights thus obtained were integrated into the ELimination Et Choix Traduisant la REalité (ELECTRE) algorithm. The Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) algorithm was also applied, to evaluate the performance of vendors and to select the best one. The qualitative evaluation of the criteria and the vendors was based on four decision makers. Finally, the Spearman’s rank correlation coefficient (SRCC) approach was applied to obtain the statistical difference between the ranking orders obtained from the two algorithms.

Findings

The efficiency of the proposed decision-making tool was evident from the real-case study of six tenders submitted for implementing a RFID-based passport tracking system. The SRCC also turned out a “very strong” association value between TOPSIS and ELECTRE.

Practical implications

The developed trasilient decision-making tool can easily be used to solve similar vendor or supplier selection problem. Moreover, other criteria can be added to fit other cases. Later, the tool was made available to the institution under study for solving future evaluation problems.

Originality/value

The literature shows that none of the previous papers presented an integrated trasilient approach that considers RC and TC simultaneously. This study presents a new trasilience tool for selecting a vendor.

Keywords

Acknowledgements

The authors acknowledge the financial support from the European Regional Development Fund through the Welsh Government for ASTUTE 2020 (Advanced Sustainable Manufacturing Technologies) to facilitate this work. The authors would like to thank the anonymous three referees whose thorough reviews and insightful comments made a valuable contribution to this paper.

Citation

Mohammed, A., Harris, I. and Dukyil, A. (2019), "A trasilient decision making tool for vendor selection: a hybrid-MCDM algorithm", Management Decision, Vol. 57 No. 2, pp. 372-395. https://doi.org/10.1108/MD-04-2018-0478

Publisher

:

Emerald Publishing Limited

Copyright © 2018, Emerald Publishing Limited

Related articles