Multi-criteria decision analysis towards robust service quality measurement

Pamučar, Dragan; Yazdani, Morteza; Montero-Simó, María José; Padilla, Rafael A. Araque; Mohammed, Ahmed

doi:10.1016/j.eswa.2020.114508

Cited by 60 publications

(29 citation statements)

References 44 publications

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“…Also, fuzzy expansions of the well-known MCDA methods have proven their effectiveness in the problem of supplier evaluation and selection [33]. Both simple fuzzy developments of the MCDA methods based on the triangular or trapezoidal form of membership function (fuzzy AHP [34], BWM and TOPSIS [26,35]), as well as based on subsequent generalizations, e.g. Intuitionist fuzzy sets MCDA methods (TOPSIS [36,37]) proved to be powerful tools for dealing with the uncertainty of measurements and preferences in supplier selection models.…”

Section: Introductionmentioning

confidence: 99%

Study Towards the Time-Based McDa Ranking Analysis – A Supplier Selection Case Study

et al. 2021

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Decision-making processes increasingly use models based on various methods to ensure professional analysis and evaluation of the considered alternatives. However, the abundance of these methods makes it difficult to choose the proper method to solve a given problem. Also, it is worth noting whether different results can be obtained using different methods within a single decision problem. In this paper, we used three selected Multi-Criteria Decision Analysis (MCDA) methods called COMET, TOPSIS, and SPOTIS in order to examine how the obtained rankings vary. The selection of material suppliers was taken into consideration. The equal weights, entropy and standard deviation methods were used to determine the weights for criteria. Final preferences values were then compared with the WS similarity coefficient and weighted Spearman correlation coefficient to check the similarity of the received rankings. It was noticed that in the given problem, all of the methods provide highly correlated results, and the obtained positional rankings are not significantly different. However, practical conclusions indicate the need to look for improved solutions in the correct and accurate assessment of suppliers in a given period.

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Section: Introductionmentioning

confidence: 99%

Study Towards the Time-Based McDa Ranking Analysis – A Supplier Selection Case Study

et al. 2021

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“…2.1 Supplier selection approaches Nielsen et al (2014) and Govindan et al (2015) reported a review study regarding MCDM methods utilized to assess supplier vis-a-vis green performance. Generally, literature shows that various supplier selection techniques or methodologies can be categorized into five groups such as, mathematical programming (Dobos and Vorosmarty, 2018;Liou et al, 2016;Mohammed et al, 2018b;Shaw et al, 2012;Mohammed, 2019;Talluri and Narasimhan, 2005;Hashemi et al, 2015), Solo multiple attribute decision-making (SMADM) method (Chang et al, 2011;Dey et al, 2012;Wu et al, 2021;Hsu et al, 2013), fuzzy set theory (Fallahpour et al, 2015;Banaeian et al, 2018;Shaw et al, 2012;Jain et al, 2007;Amindoust et al, 2012), intelligent techniques (Cavalcante et al, 2019;G€ uneri et al, 2011;Golmohammadi, 2011) and hybrid methods (Pamucar et al, 2021;Tadi c et al, 2014;B€ uy€ uk€ ozkan and Çifçi, 2012;Beikkhakhian et al, 2015;Kuo et al, 2010;Mohammed, 2020). Each category has its own specific advantages and disadvantages.…”

Section: Literature Reviewmentioning

confidence: 99%

Green sourcing in the era of industry 4.0: towards green and digitalized competitive advantages

Fallahpour

Yazdani

Mohammed

et al. 2021

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PurposeIn the last decade, sustainable sourcing decision has gained tremendous attention due to the increasing governmental restrictions and public attentiveness. This decision involves diverse sets of classical and environmental parameters, which are originated from a complex, ambiguous and inconsistent decision-making environment. Arguably, supply chain management is fronting the next industrial revolution, which is named industry 4.0, due to the fast advance of digitalization. Considering the latter's rapid growth, current supplier selection models are, or it will, inefficient to assign the level of priority of each supplier among a set of suppliers, and therefore, more advanced models merging “recipes” of sustainability and industry 4.0 ingenuities are required. Yet, no research work found towards a digitalized, along with sustainability's target, sourcing.Design/methodology/approachA new framework for green and digitalized sourcing is developed. Thereafter, a hybrid decision-making approach is developed that utilizes (1) fuzzy preference programming (FPP) to decide the importance of one supplier attribute over another and (2) multi-objective optimization on the basis of ratio analysis (MOORA) to prioritize suppliers based on fuzzy performance rating. The proposed approach is implemented in consultation with the procurement department of a food processing company willing to develop a greener supply chain in the era of industry 4.0.FindingsThe proposed approach is capable to recognize the most important evaluation criteria, explain the ambiguity of experts' expressions and having better discrimination power to assess suppliers on operational efficiency and environmental and digitalization criteria, and henceforth enhances the quality of the sourcing process. Sensitivity analysis is performed to help managers for model approval. Moreover, this work presents the first attempt towards green and digitalized supplier selection. It paves the way towards further development in the modelling and optimization of sourcing in the era of industry 4.0.Originality/valueCompetitive supply chain management needs efficient purchasing and production activities since they represent its core, and this arises the necessity for a strategic adaptation and alignment with the requirement of industry 4.0. The latter implies alterations in the avenue firms operate and shape their activities and processes. In the context of supplier selection, this would involve the way supplier assessed and selected. This work is originally initiated based on a joint collaboration with a food company. A hybrid decision-making approach is proposed to evaluate and select suppliers considering operational efficiency, environmental criteria and digitalization initiatives towards digitalized and green supplier selection (DG-SS). To this end, supply chain management in the era of sustainability and digitalization are discussed.

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“…e MARCOS MCDM method found its application in its conventional form [59][60][61][62], as well as in the fuzzy [63], intuitionistic fuzzy [64], grey [65], and D numbers [66] environment. Aside from its standalone application, the MARCOS method was combined with other methods, such as AHP [67], SWARA [48,68], Delphi and FARE [69], BWM [70][71][72], FUCOM [73,74], CCSD and ITARA [75], CRITIC, FUCOM, and DEA [76], and FUCOM and PIPRECIA [77]. Due to its advantages and strengths, as well as the fact that it was not developed in the spherical fuzzy environment, this article expands the existing literature by developing the spherical fuzzy MARCOS method for the first time, which represents its final contribution.…”

Section: Literature Reviewmentioning

confidence: 99%

Novel Spherical Fuzzy MARCOS Method for Assessment of Drone‐Based City Logistics Concepts

et al. 2021

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Technological innovations from the last few years, in the combination with city logistics (CL) initiatives, make the definition of novel, complex, sustainable CL solutions possible. Unmanned aerial vehicles (drones) as a technology attracted lots of attention in the literature. Various researches focused on different drone-based delivery approaches, but there are only a few articles dealing with drones as the elements of complex CL concepts. The goal of this paper is to evaluate different drone-based CL concepts. Based on the existing ideas of drone application in delivery, the main group of CL concepts and their variants are defined, which represents the main contribution of the article. The evaluation and ranking of concepts are performed from the aspect of all CL stakeholders and the defined set of criteria by applying measurement of alternatives and ranking according to compromise solution (MARCOS) multicriteria decision-making (MCDM) method in spherical fuzzy environment, which represents another contribution of the article. The results indicate that the potentially best CL concept, with the final score of 0.408, is the one that refers to the transformation of the logistics system into a two-echelon system with the implementation of micro-consolidation centers (MCCs), in which the delivery of goods to MCCs is realized with rail transportation mode and the last delivery phase with drones. It is followed by the concepts that imply MCCs, and rail transportation in the function of mobile depots for drone launching and MCCs and ground delivery vehicles (GDVs), with the final scores of 0.395 and 0.390, respectively.

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Multi-criteria decision analysis towards robust service quality measurement

Cited by 60 publications

References 44 publications

Study Towards the Time-Based McDa Ranking Analysis – A Supplier Selection Case Study

Study Towards the Time-Based McDa Ranking Analysis – A Supplier Selection Case Study

Green sourcing in the era of industry 4.0: towards green and digitalized competitive advantages

Novel Spherical Fuzzy MARCOS Method for Assessment of Drone‐Based City Logistics Concepts

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