An integrated grey-based multi-criteria decision-making approach for supplier evaluation and selection in the oil and gas industry

Abstract

Purpose The oil and gas industry is a crucial economic sector for both developed and developing economies. Delays in extraction and refining of these resources would adversely affect industrial players, including that of the host countries. Supplier selection is one of the most important decisions taken by managers of this industry that affect their supply chain operations. However, determining suitable suppliers to work with has become a phenomenon faced by these managers and their organizations. Furthermore, identifying relevant, critical and important criteria needed to guide these managers and their organizations for supplier selection decisions has become even more complicated due to various criteria that need to be taken into consideration. With limited works in the current literature of supplier selection in the oil and gas industry having major methodological drawbacks, the purpose of this paper is to develop an integrated approach for supplier selection in the oil and gas industry. Design/methodology/approach To address this problem, this paper proposes a new uncertain decision framework. A grey-Delphi approach is first applied to aid in the evaluation and refinement of these various available criteria to obtain the most important and relevant criteria for the oil and gas industry. The grey systems theoretic concept is adopted to address the subjectivity and uncertainty in human judgments. The grey-Shannon entropy approach is used to determine the criteria weights, and finally, the grey-EDAS (evaluation based on distance from average solution) method is utilized for determining the ranking of the suppliers. Findings To exemplify the applicability and robustness of the proposed approach, this study uses the oil and gas industry of Iran as a case in point. From the literature review, 21 criteria were established and using the grey-Delphi approach, 16 were finally considered. The four top-ranked criteria, using grey-Shannon entropy, include warranty level and experience time, relationship closeness, supplier’s technical level and risks which are considered as the most critical and influential criteria for supplier evaluation in the Iranian oil and gas industry. The ranking of the suppliers is obtained, and the best and worst suppliers are also identified. Sensitivity analysis indicates that the results using the proposed methodology are robust. Research limitations/implications The proposed approach would assist supply chain practicing managers, including purchasing managers, procurement managers and supply chain managers in the oil and gas and other industries, to effectively select suitable suppliers for cooperation. It can also be used for other multi-criteria decision-making (MCDM) applications. Future works on applying other MCDM methods and comparing them with the results of this study can be addressed. Finally, broader and more empirical works are required in the oil and gas industry. Originality/value This study is among the first few studies of supplier selection in the oil and gas industry from an emerging economy perspective and sets the stage for future research. The proposed integrated grey-based MCDM approach provides robust results in supplier evaluation and can be used for future domain applications.

A new weighted fuzzy programming model for supplier selection and order allocation in the food industry

“…Regarding the selection of criteria, the managers of the company first proposed 11 criteria. Then, we refined the criteria and limited them to seven criteria that are supported by the previous studied as follows: C 1 : Price (Kannan et al , 2013; Arikan, 2013; Chen, 2011; Azadnia et al , 2015; Kaviani et al , 2019). C 2 : Quality (Kannan et al , 2013; Chen, 2011; Azadnia et al , 2015; Arikan, 2013; Kaviani et al , 2019).…”

“…Then, we refined the criteria and limited them to seven criteria that are supported by the previous studied as follows: C 1 : Price (Kannan et al , 2013; Arikan, 2013; Chen, 2011; Azadnia et al , 2015; Kaviani et al , 2019). C 2 : Quality (Kannan et al , 2013; Chen, 2011; Azadnia et al , 2015; Arikan, 2013; Kaviani et al , 2019). C 3 : On-time delivery (Kannan et al , 2013; Arikan, 2013; Chen, 2011; Rezaei et al , 2014; Kaviani et al , 2019).…”

“…C 2 : Quality (Kannan et al , 2013; Chen, 2011; Azadnia et al , 2015; Arikan, 2013; Kaviani et al , 2019). C 3 : On-time delivery (Kannan et al , 2013; Arikan, 2013; Chen, 2011; Rezaei et al , 2014; Kaviani et al , 2019). C 4 : Reputation in the industry (Rezaei et al , 2014; Soleimani and Valmohammadi, 2017).…”

“…C 4 : Reputation in the industry (Rezaei et al , 2014; Soleimani and Valmohammadi, 2017). C 5 : Geographical distance (Sevkli et al , 2008; Kannan et al , 2013; Soleimani and Valmohammadi, 2017; Kaviani et al , 2019). C 6 : Background of the partnership (Sevkli et al , 2008; Chen, 2011; Kaviani et al , 2019).…”

“…One of the major processes that has a significant impact on all other processes is supplier selection. If suppliers do not deliver the product as per standards order fulfillment and customer relationship processes will fail even if they have high individual performance (Kaviani et al , 2019).…”