RFID service provider selection: An integrated fuzzy MCDM approach

Büyüközkan, Gülçin; Karabulut, Yağmur; Arsenyan, Jbid

doi:10.1016/j.measurement.2017.08.018

Cited by 25 publications

(14 citation statements)

References 65 publications

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“…For example Ertay, Kahveci, and Tabanlı (2011) and Kar (2014) applied weighted geometric mean that the weights of decision makers are treated as the exponential in the aggregation formula. Büyüközkan, Karabulut, and Arsenyan (2017) multiplied the weights by a relaxation factor to estimate consensus degree of multiple judgements. However, these researchers assume the weights are given.…”

Section: Discussionmentioning

confidence: 99%

A fuzzy decision tool to evaluate the sustainable performance of suppliers in an agrifood value chain

Liu¹,

Eckert²,

Bertoluci³

et al. 2019

Computers & Industrial Engineering

103

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Section: Discussionmentioning

confidence: 99%

A fuzzy decision tool to evaluate the sustainable performance of suppliers in an agrifood value chain

Liu¹,

Eckert²,

Bertoluci³

et al. 2019

Computers & Industrial Engineering

103

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show abstract

“…This allowed a sequence of methodological procedures to be followed in order to address some of the limitations of the current UIPS evaluation systems. [58] integrate the fuzzy Axiomatic Design (fuzzy AD) and fuzzy AHP techniques, and the group decision making (GDM) approach. Yazdani et al [59] exploit the COmplex PRoportional ASsessment (COPRAS) method.…”

Section: Methodological Processesmentioning

confidence: 99%

An Evaluation System for University–Industry Partnership Sustainability: Enhancing Options for Entrepreneurial Universities

et al. 2018

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Abstract:The concept of university-industry partnership sustainability (UIPS) stands for well-adjusted progress among key players from universities and industry by sustaining their welfare, both in the present and in the future. This paper sought to develop an evaluation system for UIPS. The need for such a system is justified at three levels: the micro level (i.e., research and innovation performance, transfer and absorptive capability, and technology development), the meso level (i.e., institutional arrangements, communication networks, and local and indigenous rules) and the macro level (i.e., supply and demand, regulations, financing, taxes, culture, traditions, market, climate, politics, demographics, and technology). The UIPS evaluation system developed in this study offers the possibility of calculating a fair value of UIPS and providing recommendations for improving university-industry (U-I) partnerships. This can be of great importance for entrepreneurial universities that would like to strengthen their corporate links and/or reduce/reverse the "hollowing effect" of globalisation in disadvantaged regions. Additionally, this paper also contains discussions on the advantages, limitations, and managerial implications of this proposal.

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“…Pythagorean fuzzy numbers [26] are incorporated with the individual decisionmaking preferences to represent experts' evaluation accurately, capturing the fuzzy information in the decision-making process. Considering the group decision-making preference, Büyüközkan et al [27] utilize each expert's consensus degree coefficient to determine the expert weights. However, the proposed mathematical model omits the influence of experts' individual decision-making preferences.…”

Section: Literature Reviewmentioning

confidence: 99%

“…Each expert's relative degree of agreement is shown in Table 14. The constants α = 0.5, β = 0.3, γ = 0.2 were utilized in Equation (27), and the derived comprehensive risk factor weights are shown in Table 15. Step 3.…”

Section: Risk Coefficient Calculationmentioning

confidence: 99%

“…Additionally, Av 2 is the threshold between high risk and medium risk. Incorporating the expert weight calculation model (i.e., Equation (27)) and the risk coefficient calculation model (i.e., Equation ( 42)) yields the risk rating shown in Figure 6a. When the expert weights are considered (i.e., Equation ( 27)), and the conventional risk coefficient calculation method is utilized (i.e., Equation (3)), the risk rating shown in Figure 6b is obtained.…”

Section: Determination Of Risk Ratings and Sensitivity Analysismentioning

confidence: 99%

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An Improved Failure Risk Assessment Method for Bilge System of the Large Luxury Cruise Ship under Fire Accident Conditions

Liu

Guo

et al. 2021

JMSE

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This paper develops an improved failure risk assessment method and discusses the risk control measures for a large luxury cruise ship’s bilge system under fire accident conditions. The proposed method incorporates an expert weight calculation model and a risk coefficient calculation model. The expert weight calculation model considers the differences in experts’ expertise levels (i.e., qualification level, decision-making capacity, and decision-making preference). Further, the method integrates the evaluations resulting from fuzzy analytic hierarchy process (FAHP) and extended fuzzy technique for order preference by similarity to ideal solution (FTOPSIS) of different experts. The risk coefficient (RC) calculation model utilizes a three-dimensional continuous matrix, serving to determine the risk factors’ ratings. The influences of the expert weight and RC calculation models on the proposed method’s performance are studied through a sensitivity analysis. The work demonstrates that the proposed method minimizes the issues encountered when using conventional methods for determining risk ratings. Finally, the results of an empirical study comprising ten experts evaluating the VISTA cruise ship’s bilge system prove the applicability of the proposed method and offer practical design guidelines to meet the regulations for Safe Return to Port (SRtP).

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RFID service provider selection: An integrated fuzzy MCDM approach

Cited by 25 publications

References 65 publications

A fuzzy decision tool to evaluate the sustainable performance of suppliers in an agrifood value chain

A fuzzy decision tool to evaluate the sustainable performance of suppliers in an agrifood value chain

An Evaluation System for University–Industry Partnership Sustainability: Enhancing Options for Entrepreneurial Universities

An Improved Failure Risk Assessment Method for Bilge System of the Large Luxury Cruise Ship under Fire Accident Conditions

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