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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.

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.

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.

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.

This study aims to determine the mall criteria that are the most crucial for the youth market by determining the winning brand in comparison to other offerings to understand what is required to gain a competitive advantage and to differentiate a mall from its rivals.

This study chose the Stochastic Multicriteria Acceptability Analysis-2 method to evaluate the mall preferences of young people. By using this method, the various criteria were evaluated for more than one alternative to find the best solution. JSMA program was used to analyze the data. The survey was administered using the mall intercept method to reduce sample bias.

The study identifies that the criteria that have the highest impact on the mall preferences of young people are the mall campaigns for loyal customers; the traffic in the mall locality and the mall’s parking facilities; the mall’s facilities for disabled people; the quality of the mall locality; and the quality of the people visiting the mall. The study reveals that a mall’s physical features, its facilities and the criteria related to employees have a very low impact on the mall choices of young people. The study further finds that the youth market has very low satisfaction levels for all of the identified criteria. This study reveals that this macro accessibility criterion is less relevant for the youth market than for the general population.

Despite the importance of this market, there is insufficient research on the shopping behavior of young people. They have a considerable impact on the purchasing decisions of their families, significant disposable income and constitute the future market for the sector. This study uniquely enables the sequential ordering of customers’ decision-making criteria and determines the effectiveness or impact of these criteria in the mall sector.

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.

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.

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.

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.

Traditional risk assessment (RA) methodologies cannot model vagueness in risk and cannot prioritize corrective-preventive measures (CPMs) by considering effectiveness of those on risk types (RTs). These cannot combine and reflect accurately different subjective opinions and cannot be used in a linguistic manner. Risk factors (RFs) are assumed to have the same importance and interrelations between RFs are not considered. This study aims to overcome these disadvantages by combining fuzzy logic with multi-criteria decision-making in a dynamic manner.

This study proposes a novel three-stage fuzzy risk matrix-based RA integrating fuzzy decision-making trial and evaluation laboratory (F-DEMATEL) and fuzzy multi-attributive border approximation area comparison (F-MABAC). At the first stage, importance weights of RFs are computed by F-DEMATEL. At the second stage, risk degrees of RTs are computed via using fuzzy risk matrix. At the third stage, CPMs are ranked by F-MABAC. Finally, a numerical example for RA in a warehouse is given.

Results show that developing instructions for material loading or unloading is the most important CPM and severity is the most important RF for the warehouse.

This study has originality in terms of having fuzzy dynamic structure. At first, RFs are assumed to be criteria sets then, RTs are assumed to be criteria set considering their risk degrees to rank CPMs in a fuzzy manner. Risk degrees of RTs are used for weights of RTs and effectiveness of CPMs are used for performance values of CPMs.

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.

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.

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.

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.

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.