Wos İndeksli Açık & Kapalı Erişimli Yayınlar

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    A Novel Multi-Criteria Decision-Making Approach Proposal Based on Kemira-M with Four Criteria Groups
    (2022) Ay, Sefacan; Can, Gulin Feryal; Toktas, Pelin
    This 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.
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    Evaluation of performance levels of students for moodle learning management system in terms of usability Criteria with PSI-Entropy-Marcos integration
    (2022) Yorulmaz, Muhammet; Can, Gulin Feryal
    The study, it is aimed to determine and compare the end-user performances within the scope of achieving the determined objectives while using the Moodle Learning Management System (LMS). Accordingly, considering multiple usability criteria, 18 users were prioritized in terms of their performances in using Moodie LMS. In this direction, Preference Selection Index (PSI) and Entropy integration was used to determine the importance weights of usability criteria, and the Measurement of Alternatives and Ranking according to Compromise Solution (MARCOS) method was used to prioritize the end-users. A new hybrid weighting method has been proposed by integrating the PSI method with the Entropy method, taking into account both the uncertainty in the performance values of the end-users according to the criteria and the preference change values of the criteria. This proposed method is applied for a three-dimensional initial decision matrix Thus, the traditional two-dimensional initial decision matrix which consists of the alternatives and the values that the alternatives take according to the criteria, has been developed and made more flexible. The objective criteria taken into account in the analysis were measured by the Morae V3 program, with the tasks defined as predetermined goals being performed by the users on the Moodie LMS. In addition, the criteria weights obtained from the proposed PSI-Entropy integration were used in the MARCOS method to rank the end-users according to their performance levels.
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    A novel aggregated multiple criteria decision-making approach to evaluate the physical workload of workers
    (2021) Ekinci, Elmas Burcu Mamak; Can, Gulin Feryal; AAE-4242-2020
    Physical workload (PWL) is a measure of the physical resources consumed by a worker while performing a task. Analyzing the PWL of workers can aid experts in identifying workers whose working conditions should be improved. Identifying workers who are exposed to the highest PWL is essential for task continuity and occupational health. In this study, a new approach is proposed to prioritize workers according to their PWL levels. In the proposed approach, multiple criteria decision-making techniques are used because different factors can affect PWL levels. Eight criteria, that is, standard time, frequency of working posture, heart rate, the risk level of posture, noise level, lighting intensity, rest period, and perceived workload level are considered. In the evaluation process, criteria weights are computed using entropy considering measurements of the eight criteria for each worker. Using these weights in multiobjective optimization by simple ratio analysis, multiobjective optimization by ratio analysis, and multiattributive ideal-real comparative analysis methods, workers are ranked according to their PWL levels. The final order of workers is determined by aggregating different rankings obtained from these three methods, using the technique of precise order preference method. This study presents original research that can potentially contribute to the literature by considering different perspectives offered by various methods for PWL evaluation. It focuses on several different criteria by performing real measurements and subsequently ranking workers based on the aggregation of these measurements.
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    A FMEA based novel intuitionistic fuzzy approach proposal: Intuitionistic fuzzy advance MCDM and mathematical modeling integration
    (2021) Yener, Yelda; Can, Gulin Feryal
    This study proposes a novel three-stage intuitionistic fuzzy risk assessment (RA) approach based on Failure Modes and Effects Analysis (FMEA). In this study, it was paid attention for considering real constraints of firms such as capital, time etc. to prevent nan-fatal failure modes (FMs), interactions between FMs and risk level similarities created by risk factors (RFs). At the first stage of the proposed approach, RFs' weights are computed by a new intuitionistic fuzzy weighting method considering similarities between RFs for risk levels that they can create. At the second stage, Modified Intuitionistic Fuzzy Multi Attribute Border Approximation Area (MIF-MABAC) including interactions between FMs is used to determine the rankings of FMs by using Extended Haussdorff distance function. At the third stage, two intuitionistic fuzzy mathematical models are established to show the effect of the real constraints of the firm to identify the risk types (RTs) that must be avoided primarily. It was seen that the first model gives the same ranking results with the MIF-MABAC. Additionally, when including the real constraints, the first model can give the more suitable results than the second model. The results obtained from the first model show that experts' assessments and mathematical modeling identify the same FMs for preventing primarily. This study is the first one to suggest a new RA approach that reflects the real constraints of the firms to RA. Additionally, this is the first study that models' interactions between FMs and risk level similarities created by RFs.
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    Six Sigma Project Prioritization and Selection Using AHP-CODAS Integration: A Case Study in Healthcare Industry
    (2021) Can, Gulin Feryal; Toktas, Pelin
    Given the complex nature of Six Sigma project (SSP) prioritization and selection processes, multicriteria decision-making (MCDM) methods may help organizations identify the most effective projects. Considering potential limitations of subjective methods and advantages of MCDM methods, this article proposes a model that integrates analytical hierarchy process (AHP) and combinative distance-based assessment (CODAS) in SSP prioritization and selection process. In the proposed approach, AHP is employed to assign criteria weights, and CODAS is performed to determine priorities of SSPs. CODAS was advanced in term of its threshold function. Differences between Euclidean distances of two alternatives were compared, based on the standard deviation of Euclidean distances of all alternatives to overcome the subjectivity. This is the first study that combines AHP and CODAS methods for SSP selection, and CODAS is used with objective threshold value computation, and developed for the healthcare industry. In this article, ten SSPs were evaluated for four key criteria groups as financial, operational, patient centric, and organizational main criteria groups. In total, 18 subcriteria were considered under these four main criteria groups. This article provides a support for executives who make implementation plans for the potential SSPs.
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    Occupational health and safety performance evaluation of countries based on MAIRCA
    (2020) Can, Gulin Feryal; Kiran, Muzaffer Bertan
    Purpose The purpose of this paper is to develop an approach to compare occupational health and safety (OHS) performances of countries. Additionally, another aim is to debate the impacts of using recorded data and ratios for OHS performance evaluations. Design/methodology/approach The number of fatal accidents (NFAs), fatal accident rates (FARs), numbers of lost days (NLDs) and accident severity rates (ASRs) are determined as main criteria and six economic activity areas (EAAs) are considered as sub-criteria. Two different initial decision matrices are used as the initial decision matrix, the first of which consists of recorded data of countries related to NFAs and NLDs, and the second consists of FAR and ASR values as ratios. Importance weights of main and sub-criteria regarding the recorded data and ratios are determined using four different weighting ways. Countries are ranked via utilizing Multi-Attributive Ideal-Real Comparative Analysis considering two different initial decision matrices. Findings It can be stated that an evaluation based on ratios for comparison of OHS performance provides more realistic results. Additionally, increasing the effect of the FAR values using the 6,000 equivalent lost days factor is also important in terms of differentiating the data of the countries in question. Originality/value To the best of the authors' knowledge, there is no study in literature that discusses the ranking of countries by means of recorded data and ratios considering different criteria. Additionally, this study is a first in terms of the number of countries evaluated and the comparison of these countries according to their respective EAAs.
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    A new approach for ergonomic risk assessment integrating KEMIRA, best-worst and MCDM methods
    (2020) Delice, Elif Kilic; Can, Gulin Feryal
    In 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.
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    Six sigma project prioritization and selection: a multi-criteria decision making approach in healthcare industry
    (2020) Pakdil, Fatma; Toktas, Pelin; Can, Gulin Feryal
    Purpose 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.
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    Universal usability evaluation by using an integrated fuzzy multi criteria decision making approach
    (2019) Can, Gulin Feryal; Demirok, Seda
    Purpose The purpose of this paper is to propose an integrated fuzzy approach to determine important universal usability problems (UUPs) by providing experts who behave like real users and to establish a work plan to correct the most important ones. Design/methodology/approach In this study, a fuzzy multi-criteria decision-making approach with three stages is proposed for the evaluation of universal usability. At the first stage, UUPs are identified by performing modified heuristic evaluation, and severity rating of each problem is determined by experts. At the second stage, critical problems are specified by applying the fuzzy Delphi considering these severity ratings. At the third stage, Fuzzy Decision Making Trial and Evaluation Laboratory approach is applied to prioritize critical problems as sub and main criteria. An illustrative example related to emergency service is performed to apply the proposed approach. Findings Results showed that the elevator button design, the elevator emergency button design and the position of the floor signboard are the first three problems that should be primarily improved as sub-criteria. In terms of main criteria, equitable use, simple and intuitive use, and perceptible information are the first three main criteria that should be improve in emergency service. Originality/value This study is original in terms of methodology and providing a new perspective for building design evaluation. The results can help the designers to see the UUPs in buildings, to focus the most important UUPs and to establish improvement ranking. These advantages provide time and cost-effective design improvement actions.
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    Stochastic KEMIRA-M Approach with Consistent Weightings
    (2019) Toktas, Pelin; Can, Gulin Feryal
    This 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.