Supply Chain Partner Selection under Cloud Computing Environment: An Improved Approach Based on BWM and VIKOR

Abstract

The wide application of cloud computing technology makes supply chain partner share information effectively and increase corporate profits. However, in cloud computing environment, the evaluation process of supply chain partner selection is dynamic and fuzzy, and its evaluation index is uncertain. To solve these problems, this paper proposes a new method combed with rough number, best-worst multicriteria decision-making method (BWM), and compromise ranking method (VIKOR). Firstly, Rough number is used to integrate data from different evaluation matrix. Secondly, rough number improves a new method, BWM, to get RBWM criteria weight methods. Thirdly, the rough numbers are introduced into VIKOR and combined with RBWM to evaluate and sort the supply chain partners. Finally, an example is given to demonstrate the rationality and feasibility of the method.

A neutrosophic enhanced best–worst method for considering decision-makers’ confidence in the best and worst criteria

“…A recent list of the BWM integrations include the integrated DEA 4 and BWM (Omrani et al, 2020); the Euclidean BWM (Kocak et al, 2018); the PHFE 5 and the BWM (Li et al, 2019); the Z-number extension of the BWM (Aboutorab et al, 2018); the mixed grey-based BWM and TODIM 6 (Bai et al, 2019); the hybrid fuzzy BWM and COPRAS 7 method (Amoozad Mahdiraji et al, 2018); the integrated BWM and VIKOR method Gupta, 2018a;Garg and Sharma, 2018); the hybrid fuzzy TOPSIS and the BWM (Gupta, 2018b;Gupta and Barua, 2018;Lo et al, 2018); the hybrid BWM and ELECTRE 8 method (Yadav et al, 2018); the fuzzy BWM and fuzzy MULTIMOORA 9 (Liu et al, 2018a); rough numbers and the BWM (i.e. RBWM) and VIKOR (Liu et al, 2018b); the integrated IRN 10 and the BWM (IRN-BWM) (Pamucar et al, 2019); the MILM 11 to provide better approximate solutions to the original NLM 12 in the BWM (Beemsterboer et al, 2018); the fuzzy BWM (Guo and Zhao, 2017 Hafezalkotob, 2017;Maghsoodi et al, 2019); the IF-BWM 13 (Mou et al, 2017) and the IFM-BWM 14 (Mou et al, 2016).…”

Using Improved Prospect Theory to Develop a Partner Selection Method for Virtual Enterprises with Unknown Weight

“…Büyüközkan and Güleryüz [36] proposed a combined intuitionistic fuzzy group decision-making model to select the company to cooperate with potential partners in the process of product development, which is composed of an intuitionistic fuzzy analytic hierarchy process and intuitionistic fuzzy technology. Liu et al [37] proposed a new method combined with rough number, best-worst MCDM method, and compromise ranking method (VIKOR).…”

Green Supply Chains and Digital Supply Chains: Identifying Overlapping Areas

“…A closer examination of the papers belonging to this cluster reveals that the role of big data is investigated at various levels: its role in enhancing the three dimensions of performance (organizational, economic, and environmental) in supply chains thanks to its ability to mitigate the risk of supply chain disruption [61]; its role in improving evaluations and decision-making [62][63][64]; and its role in reducing transaction costs [65]. Furthermore, the role big data plays in supply chain management and procurement is investigated [62,66], particularly in regard to the selection of green suppliers [67,68], the development of an ICT platform for collaboration and sustainable supply chains planning [69], sustainable public procurement [70,71], improving e-procurement [72], and fostering collaboration in supply chains in general [73][74][75].…”