Wos İndeksli Açık & Kapalı Erişimli Yayınlar
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Item A Novel Multi-Criteria Decision-Making Approach Proposal Based on Kemira-M with Four Criteria Groups(2022) Ay, Sefacan; Can, Gulin Feryal; Toktas, PelinThis study aims to eliminate the subjectivity in the weight assignment process of Modified Kemeny Median Indicator Ranks Accordance (KEMIRA-M) and to remove the need for experts to reach a consensus on determining the criteria weights. Additionally, this study aims to apply KEMIRA-M for four different criteria groups and to prevent some criteria from taking a weight value of "0", as in other studies using KEMIRA-M. In this context, the weighting procedure of KEMIRA-M is advanced using three different ranking-based weighting methods such as Rank Sum (RS), Rank Exponent (RE) and Rank Reciprocal (RR) to operate Median Priority Components (MPCs) more effectively. Accordingly, to determine which weighting method for which criterion group is more suitable, the selection procedure of KEMIRA-M was applied and alternative rankings were obtained for 81 different weight set combinations. Additionally, MATLAB codes have been used to provide flexibility for the application of the proposed approach in a supplier selection problem selected for a case study.Item A new approach for ergonomic risk assessment integrating KEMIRA, best-worst and MCDM methods(2020) Delice, Elif Kilic; Can, Gulin FeryalIn this study, a new three-phase ergonomic risk assessment approach was proposed for manual lifting tasks to determine which worker has the highest ergonomic risk level considering two criteria sets as lifting-related criteria and human-related criteria. In the first phase, Modified Kemeny Median Indicator Ranks Accordance (KEMIRA-M) and a novel two-dimensional best-worst method (BWM) integration were proposed for weighting ergonomic risk criteria in two sets. In this way, weighting procedure of KEMIRA-M was advanced by the proposed two-dimensional BWM in a consistent manner and subjectivity in determining the best and the worst criteria in traditional BMW was prevented by using KEMIRA-M. Thus, the weaknesses of both methods have been developed. In the second phase, the rankings of workers were determined via utilizing multi-objective optimization on the basis of simple ratio analysis, multi-objective optimization by ratio analysis (MOORA) ratio, MOORA reference point and complex proportional assessment to see how worker rankings differ despite using the same advanced weighting approach based on KEMIRA-M and two-dimensional BWM integration. Finally, to aggregate these different ranking results, technique of precise order preference was applied. In this way, different viewpoints of each ranking approach can be reflected on a single worker's priority. The applicability of the proposed ergonomic risk assessment approach was demonstrated with a real application in tube manufacturing.Item Six sigma project prioritization and selection: a multi-criteria decision making approach in healthcare industry(2020) Pakdil, Fatma; Toktas, Pelin; Can, Gulin FeryalPurpose The purpose of this study is to develop a methodology in which alternate Six Sigma projects are prioritized and selected using appropriate multi-criteria decision-making (MCDM) methods in healthcare organizations. This study addresses a particular gap in implementing a systematic methodology for Six Sigma project prioritization and selection in the healthcare industry. Design/methodology/approach This study develops a methodology in which alternate Six Sigma projects are prioritized and selected using a modified Kemeny median indicator rank accordance (KEMIRA-M), an MCDM method based on a case study in healthcare organizations. The case study was hypothetically developed in the healthcare industry and presented to demonstrate the proposed framework's applicability and validity for future decision-makers who will take place in Six Sigma project selection processes. Findings The study reveals that the Six Sigma project prioritized by KEMIRA-M assign the highest ranks to patient satisfaction, revenue enhancement and sigma level benefit criteria, while resource utilization and process cycle time receive the lowest rank. Practical implications The methodology developed in this paper proposes an MCDM-based approach for practitioners to prioritize and select Six Sigma projects in the healthcare industry. The findings regarding patient satisfaction and revenue enhancement mesh with the current trends that dominate and regulate the industry. KEMIRA-M provides flexibility for Six Sigma project selection and uses multiple criteria in two-criteria groups, simultaneously. In this study, a more objective KEMIRA-M method was suggested by implementing two different ranking-based weighting approaches. Originality/value This is the first study that implements KEMIRA-M in Six Sigma project prioritization and selection process in the healthcare industry. To overcome previous KEMIRA-M shortcomings, two ranking based weighting approaches were proposed to form a weighting procedure of KEMIRA-M. As the first implementation of the KEMIRA-M weighting procedure, the criteria weighting procedure of the KEMIRA-M method was developed using two different weighting methods based on ranking. The study provides decision-makers with a methodology that considers both benefit and cost type criteria for alternates and gives importance to experts' rankings related to criteria and the performance values of alternates for criteria.Item Stochastic KEMIRA-M Approach with Consistent Weightings(2019) Toktas, Pelin; Can, Gulin FeryalThis study proposes an advanced Modified KEmeny Median Indicator Rank Accordance (KEMIRA-M) approach based on stochastic evaluation process considering consistent weights to improve effective usage of KEMIRA-M. In the proposed approach, tasks related to the decision issue are performed by decision makers to ensure the understanding sufficiency of alternatives in terms of criteria more clearly. The weighting procedure of Analytic Hierarchy Process (AHP) is implemented in a stochastic manner benefited from discrete uniform distribution to provide obtaining consistent criteria weights considering median priority components. Therefore, different trials including different number of replications that shows the number of decision makers are performed and the most consistent weightings are determined for each trial in the stochastic process. In this way, the dependency to the limited numbers of decision makers and to determine criteria weights in a heuristic manner in KEMIRA-M is prevented. Additionally, the effect of the number of decision makers on criteria weightings and alternatives' ranking process is shown. To obtain the most consistent weighting results, this stochastic process is utilized until acquiring approximate consistency ratios. The proposed stochastic KEMIRA-M approach is utilized to rank nine shopping malls (SMs) in Ankara in terms of technical criteria (TC) and universal design criteria (UDC). It was seen from the ranking results that the first SM (SM1) is the best one.