An MCDM method for cloud service selection using a Markov chain and the best-worst method

Nawaz, Faiza; Asadabadi, Mehdi Rajabi; Janjua, Naeem Khalid; Hussain, Omar Khadeer; Chang, Elizabeth; Saberi, Morteza

doi:10.1016/j.knosys.2018.06.010

Cited by 129 publications

(53 citation statements)

References 31 publications

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“…Best-Worst Method (BWM) has recently been introduced by Rezaei (2015) to reduce the inconsistencies involved in elicitation of criteria weights by trimming down the requirements of huge pairwise comparisons among criteria, as Hashemkhani Zolfani, S.; Chatterjee, P.; Yazdani, M. 2019. A structured framework for sustainable supplier selection using a combined BWM-CoCoSo model 800 applications of BWM has seen a drastic growth in different areas including supplier selection and development (Rezaei, van Roekel, & Tavasszy, 2018); complex bundling configurations (Rezaei, Hemmes, & Tavasszy, 2017); urban sewage sludge (Ren, Liang, & Chan, 2017); social sustainability of SCs (Badri Ahmadi et al, 2017); logistics performance evaluation (Rezaei et al, 2018); cloud service selection (Nawaz et al, 2018); and evaluation of sustainable design for household furnishing materials (Hashemkhani Zolfani & Chatterjee, 2019). The basic steps of BWM method are as follows (Rezaei, 2015(Rezaei, , 2016:…”

Section: Best Worst Methodsmentioning

confidence: 99%

A structured framework for sustainable supplier selection using a combined BWM-CoCoSo model

Zolfani

Chatterjee

Yazdani

2019

Proceedings of 6th International Scientific Conference Contemporary Issues in Business, Management and Economics Engineering ‘2

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Purpose – sustainability in industrial organizations is becoming one of the predominant concepts in the context of modern industrialization due to global warming, economic significance, and social awareness. These have prompted a huge concern toward sustainable supply chain management (SSCM) to be adopted and promoted as an innovative business model. Supplier evaluation and selection play a significant role in SSCM for taking appropriate procurement decisions. Research methodology – a hybrid MADM model based on Best Worst Method (BWM) and Combined Comprise Solution (CoCoSo) method. Findings – a case study in the steel industry is presented to demonstrate the effectiveness of the proposed approach. The results show the potentiality of the proposed model in resolving complex sustainability issues in the SCM environment. Research limitations – other weighting techniques like the analytic network process (ANP) and decision making trial and evaluation laboratory (DEMATEL) approaches can also be combined and performances can be compared. Practical implications – the proposed model can be used by the organizations to select the most appropriate suppliers who contribute to the movement of the SC towards sustainability. Originality/Value – a multi-criteria evaluation model has been proposed for solving a sustainable supplier selection problem while considering economic, environmental and social criteria simultaneously by integrating BWM-COCOSO methods

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Section: Best Worst Methodsmentioning

confidence: 99%

A structured framework for sustainable supplier selection using a combined BWM-CoCoSo model

Zolfani

Chatterjee

Yazdani

2019

Proceedings of 6th International Scientific Conference Contemporary Issues in Business, Management and Economics Engineering ‘2

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“…e QoS-aware cloud service selection problem can be considered as a MCDM problem [13]. Multiple methods has been proposed by researchers to evaluate cloud services [4,6,14]. Existing MCDM methods can be divided into two parts: weight determination and alternative evaluation.…”

Section: Literature Reviewmentioning

confidence: 99%

“…A range of advanced techniques have been developed to assist users to choose suitable services [4][5][6]. Most of the existing cloud service selection models are considered as QoS-aware evaluation focused models.…”

Section: Introductionmentioning

confidence: 99%

A Heterogeneous QoS-Based Cloud Service Selection Approach Using Entropy Weight and GRA-ELECTRE III

Liu

Shao

et al. 2020

Mathematical Problems in Engineering

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With the development of cloud computing, more and more resources are provided in the form of cloud services. Then how to select suitable cloud service for users without professional knowledge has become an important issue. Existing cloud service selection models are usually considered as QoS-aware evaluation focused models. In practice, the QoS attributes have problems like subjectivity, vagueness, and uncertainty, and a range of formats are involved to describe QoS attributes. Therefore, it is necessary to consider the heterogeneous formats of QoS attributes in cloud service selection process. The aim of this paper is to develop a novel cloud service selection approach using entropy weight and GRA-ELECTRE III that can handle heterogeneous QoS attributes simultaneously. In the proposed approach, heterogeneous QoS attributes are handled simultaneously by being transformed into intuitionistic fuzzy numbers; the relative weights of QoS attributes are calculated objectively by the extended entropy measure method under intuitionistic fuzzy environment; and cloud services are evaluated by GRA-ELECTRE III integrated method under intuitionistic fuzzy environment. Experimental results show that the proposed approach has good stability and discrimination in dealing with heterogeneous data and can effectively avoid compensation between attributes.

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“…Albeit the number of studies on partner selection in cloud computing is limited, e.g., [15,17,68,69]. Nevertheless, the current researches focus solely on the organization itself, ignoring the supply chain situation.…”

Section: The Evaluation Criteria Of Supply Chain Partner Selection Unmentioning

confidence: 99%

“…IT becomes a key issue for focal firm to select appropriate supply chain partner [12][13][14]. However, due to the rigid technology infrastructure and high cost of traditional IT, the supply chain enterprises cooperation may be impeded [15][16][17]. This situation has been mitigated by the emergence of a new important information technology, cloud computing.…”

Section: Introductionmentioning

confidence: 99%

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

Liu

Zhang

2018

Mathematical Problems in Engineering

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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.

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An MCDM method for cloud service selection using a Markov chain and the best-worst method

Abstract: Due to the increasing number of cloud services, service selection has become a challenging decision for many organisations. It is even more complicated when cloud users change their preferences based on the requirements and the level of satisfaction of the experienced

Cited by 129 publications

References 31 publications

A structured framework for sustainable supplier selection using a combined BWM-CoCoSo model

A structured framework for sustainable supplier selection using a combined BWM-CoCoSo model

A Heterogeneous QoS-Based Cloud Service Selection Approach Using Entropy Weight and GRA-ELECTRE III

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

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