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Although landfills are among the most important structures for municipal waste disposal worldwide, they are sometimes less preferred due to their impact on people and the environment. This research examines the health, safety and environmental (HSE) factors affecting the municipal solid waste (MSW) landfilling process’s performance. Next, it prioritises these factors using the conventional AHP and fuzzy AHP methods. Based on the findings, three main sub-criteria were determined from the 26 sub-criteria, and the environmental, health and safety criteria ranked the first, second and third, respectively. Leachate permeation control, control of pollutant production and hazardous gas monitoring were ranked the highest in terms of relative weight. In the environmental criteria, leachate control, in the health criteria, pollution and in the safety-related criteria, hazardous gas control were ranked the first. In addition, leachate permeation control had the highest global weight. Overall, experts are recommended to pay more attention to environmental issues and prioritise controlling the environmental impact of landfills in their design, construction and operation.

This paper presents a framework of website quality evaluation for measuring the performance of government websites. Multiple criteria decision-making (MCDM) is a widely used tool for evaluating and ranking problems containing multiple, usually conflicting criteria. In line with the multi-dimensional characteristics of website quality, MCDM provides an effective framework for an inter-websites comparison involving the evaluation of multiple attributes. It thus ranks different websites compared in terms of their overall performance. This paper models the inter-website comparison problem as an MCDM problem, and presents a practical and selective approach to deal with it. In addition, fuzzy logic is applied to the subjectivity and vagueness in the assessment process. The proposed framework is effectively illustrated to rate Turkish government websites.

The urban rail system in Istanbul carries in total more than 700.000 passengers per a day on different types of lines which require well organized risk governance. This paper evaluates the urban rail systems in Istanbul under different risk factors using Fuzzy Analytic Hierarchy Process (FAHP) to uncover the critical risk criteria of these systems and to make a multi-criteria evaluation of existing rail systems for the assignment of the scarce resources. Linguistic variables are used in the pairwise comparisons of criteria and alternatives. The risk factors considered are regional criticality, line characteristics, line safety and station structure. The evaluation results imply that the most risky critical urban rail system in Istanbul is the subway line from Sishane to Darussafaka.

The Analytic Hierarchy Process (AHP) is, in literature, the most frequently used selection method generally in association with fuzzy logic. In this article some incongruities in the use of fuzzy AHP detected in the literature are presented such as improper use of the defuzzification methods and weak consistency checks of the comparison matrix that in case of scattered comparison matrix could produces results that are clearly a contradiction.

We demonstrate how even a careful definition of the third party logistics providers (3PLP) selection criteria may lead to improper results, if the appropriate methods of defuzzification are not used and the concept of “vague” is not well interpreted, both in the comparison phase and in the calculation phase.

In this paper we introduce a definition of consistency of the judgement matrix in the fuzzy Analytic Hierarchy Process (AHP) and give a general expression of all fuzzy weights under the condition of consistency. Finally, based on our discussion, the geometric average method is suggested for fuzzy weights calculation in the practical decision-making situation.

As international corporate activities increase, the staffing of their operations involves more strategic concerns. However, foreign assignments have many differences, and dissatisfaction with host country is a known cause of expatriate failure. This study distinguishes from previous studies, which focused on the expatriate selection process from the viewpoint of the human resource managers. From the view of expatriate candidate's points, this paper describes a fuzzy analytic hierarchy process (fuzzy AHP) to determine the weighting of subjective judgments. When the expatriate assignments are evaluated from various aspects, such as employee personal factors, employee competencies, job characteristics, family factors, environmental factors and organization relocation support activities, it can be regarded as an fuzzy multiple criteria decision making (FMCDM) problem. Since expatriate candidates cannot clearly estimate the relative importance of each considered criterion in terms of numerical values, fuzziness is applicable. Consequently, this paper uses triangular fuzzy numbers by fuzzy AHP to establish weights for expatriate candidates, thus determining the relative importance for criteria of expatriate assignments. From the insights of this study, this article addresses this expatriate problem and offers guidelines for managers concerned with a successful expatriate assignment program.

Quality consultants are used in ISO 9000 implementation projects especially by many small and medium-sized enterprises. Clients do not always appreciate differences between quality consultants. This paper aims to provide an analytical tool to select the best quality consultant providing the most customer satisfaction. The clients of three Turkish quality consultancy firms were interviewed and the most important criteria taken into account by the clients while they were selecting their consultancy firms were determined by a designed questionnaire. The fuzzy analytic hierarchy process was applied to compare these consultancy firms. The means of the triangular fuzzy numbers produced by the customers and experts for each comparison were successfully used in the pair wise comparison matrices.

The paper deals with the group prioritization problem in the fuzzy analytic hierarchy process. We extend the fuzzy preference programming method to fuzzy group prioritization by introducing important weights of decision-makers (DMs). The modified prioritization problem is represented as a weighted fuzzy goal programming model. Additionally, we represent the uncertain DMs' importance weights as fuzzy numbers and modify the goal programming model by a possibilistic approach. Both proposed models transform the initial prioritization problems with fuzzy or crisp important weights into equivalent crisp linear programs. Unlike the known fuzzy prioritization methods, the proposed approach does not require an additional defuzzification procedure for final ranking of alternatives and can deal with incomplete set of comparison judgments.

During the last decade, information system (IS) outsourcing has emerged as a major issue for organizations. As outsourcing decisions are often based on multicriteria approaches and group decisions, this paper proposes a structured methodology based on Fuzzy group decision making approach to evaluate and select the appropriate information system project (ISP) in an actual case. To achieve our purpose, we argue that seven criteria consisting of risk, management, economics, technology, resource, quality, and strategy and five ISPs should be considered for outsourcing decisions. Fuzzy analytic hierarchy process (fuzzy AHP) to find the priority and ranking of each ISP is considered. Using fuzzy theory for selecting the proper IS project can reduce ambiguities and uncertainties that are inherent in the selection procedure. A sensitivity analysis is performed to check the steadiness of the priority ranking and help decision makers to understand different scenarios that show alternative potential developments or different viewpoints concerning the relative importance of the criteria. Our proposed methodology can be applied by a cross-functional team of practitioners and IT managers to select the proper IS project. Also, the proposed approach can effectively consider complex and qualitative decision variables involved in the IS outsourcing decision-making problem. Finally, conclusion and potential issues for future research are presented. The main findings of this research have showed that the combination of AHP method and fuzzy concept to rank and prioritize of IS projects to outsource is a useful and practical tool to make traceable and reliable decision. According to results, a priority of overall score for the five candidates of IS projects reflects that project of "development of the supplier relationship management information system" performs the best, and project of "facilities management" performs the worst according to the experts' judgment in case study.

Analytic Hierarchy process (AHP) is a powerful method belonging to the full aggregation family of multi-criteria decision-making methods based on pairwise comparisons of objects. Since the information about the problem is usually not complete in real decision-making problems, it is difficult to express precisely the preferences on pairs of compared objects. This problem has been handled in the literature by introducing fuzziness into AHP. However, neither AHP nor its fuzzy extensions can deal with sorting decision-making problems, which form a significant part of decision-making problems. This paper presents the FAHPSort method — a fuzzy extension of the AHPSort method, which is an adaptation of the AHP method for sorting decision-making problems. The FAHPSort method handles the vagueness in the meaning of linguistic terms expressing the intensity of preference of one object over another one. Key properties of the FAHPSort method are described in the paper, and the method is illustrated in a decision-making problem.

Managing water losses in water supply systems has become a crucial concern. Multi criteria decision-making (MCDM) techniques are efficient in this regard. A framework of prioritizing strategies to manage water losses was tested by different MCDM techniques, Analytic Hierarchy Process (AHP) and several Fuzzy AHP techniques. The modified Fuzzy AHP produced the most credible and consistent outputs. Sensitivity analysis conducted over it showed that the ranking of strategies/alternatives was sensitive to changes in weights of criteria with higher importance. This analysis demonstrates the ability of AHP and Fuzzy AHP techniques to deal with complex issues in water loss management.

Performance evaluation is relevant for supporting managerial decisions related to the improvement of public emergency departments (EDs). As different criteria from ED context and several alternatives need to be considered, selecting a suitable Multicriteria Decision-Making (MCDM) approach has become a crucial step for ED performance evaluation. Although some methodologies have been proposed to address this challenge, a more complete approach is still lacking. This paper bridges this gap by integrating three potent MCDM methods. First, the Fuzzy Analytic Hierarchy Process (FAHP) is used to determine the criteria and sub-criteria weights under uncertainty, followed by the interdependence evaluation via fuzzy Decision-Making Trial and Evaluation Laboratory (FDEMATEL). The fuzzy logic is merged with AHP and DEMATEL to illustrate vague judgments. Finally, the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) is used for ranking EDs. This approach is validated in a real 3-ED cluster. The results revealed the critical role of Infrastructure (21.5%) in ED performance and the interactive nature of Patient safety ($C+R=12.771$). Furthermore, this paper evidences the weaknesses to be tackled for upgrading the performance of each ED.

The threats like increasing pollution level and scarcity of natural resources are showing that Sustainable Consumption and Production (SCP) is one of the key solutions and the main contributor driver of Sustainable Development Goals (SDGs). Eventually, a mysterious disease named as COVID-19 started spreading very fast around the globe and it was declared a pandemic. To protect citizens from this pandemic, the government announced complete lockdown in the country. This lockdown due to COVID-19 has put its impact on every aspect of life. In this research study, the efforts have been made to identify various impacts of COVID-19 on SCP practices and propose various solutions to overcome these impacts of COVID-19. In the Indian perspective, a total fifteen impacts of COVID-19 under five different heads along with eighteen solutions to overcome these impacts have been identified with the help of literature, various reports and experts’ inputs. All these impacts and solutions were analyzed using a hybrid framework. Results revealed that COVID-19 majorly put its impact on nation, business and behavior followed by the impact on society and environment. All these impacts can be overcome by adopting solutions like strong and clear policies formation and its implementation, financial packages to industries to boost up the economy, firm determination of top management, safety of the workforce and tax reduction on sustainable products. The final results will be very helpful for all the actors focused on SCP.

To encompass uncertainty and vagueness of information, the analytic hierarchy process (AHP) was often extended into fuzzy multi-criteria decision-making (FMCDM) under an uncertain environment. However, the extension of AHP was rarely constructed on interval-valued fuzzy numbers. Recently, interval-valued fuzzy numbers were utilized for decision-making to obtain more messages than others. For AHP extended under a fuzzy environment into fuzzy AHP, fuzzy computations are critical to derive priorities of pairwise comparison matrices. Although AHP’s approximate computations including the normalization of row arithmetic averages may be adopted to the fuzzy environment, the fuzzy extension of AHP is still complicated for division and multiplication of fuzzy numbers, especially interval-valued fuzzy numbers. To resolve complicated ties, a utility representation function of interval-valued fuzzy numbers in fuzzy AHP is used for yielding vectors consisting of priority representations of fuzzy pairwise comparison matrices on evaluation criteria based on objective, alternatives based on evaluation criteria, and more hierarchies. Then, sum product of multiplying the priority representation vectors is derived to form the utility representations of alternative performance indices, and alternative performance indices are represented by their corresponding utility representations. Therefore, FMCDM problems are easily solved by fuzzy AHP, i.e., combining AHP with the utility representation function under an interval-valued fuzzy environment.

The need for successful knowledge sharing is critical for knowledge management (KM). The objective of this study is to identify and measure the perceived importance of knowledge sharing barriers (KSBs) in organisation. These KSBs have been categorised into the six different levels namely strategic, organisational, financial, technological, individual and social-cultural. A fuzzy AHP approach has been used for rankings of these KSBs in organisation. The expert interview was conducted to identify perceptions of the most significant KSBs. This research is an attempt to identify the KSBs that significantly affect knowledge sharing in organisations so that management may effectively deal with these KSBs. The findings of this research can be used for developing an evidence based ranking of KSBs in organisation.

Knowledge is considered to be a useful tool for a firm's competitiveness and sustainability. There is considerable evidence confirming that firm-level knowledge (FLK) accumulation provides a competitive advantage for firms, through innovation. Therefore, most knowledge-intensive firms accumulate FLK via exploitative practices to prevent deterioration of their innovation performance. This study adopts methods including expert interviews, an analytic hierarchy process (AHP) and fuzzy set theory to analyse the FLK accumulation in firms. This study proposes that three influential factors for FLK accumulation are knowledge integration (KI), knowledge absorption (KA) and knowledge sharing (KS). This study reveals that KI is the most influential factor of a firm's FLK accumulation, and the sub-factor of “Integration Ability” plays the most critical role of KI in FLK accumulation.

A wide range of product lifecycle management (PLM) maturity models are proposed to assess the relative position of companies on their road to complete PLM implementation. However, it is a tough job for the company to dynamically evaluate the gradual process of PLM maturity by using existing values and accurately make decisions of improving PLM maturity by selecting the optimum alternative. A fuzzy PLM components maturity model (PCMA) is presented to build the internal logical relationship between maturity levels and existing values that can automatically predict the unknown PLM maturity levels. A fuzzy AHP–VIKOR methodology is used to make a decision among option PLM strategies. The weights of the criteria are determined by fuzzy pairwise comparison matrices (PCM). The weights of alternatives with respect to criteria are calculated by fuzzy VIKOR. The fuzzy AHP–VIKOR is a compromise solution and has the ability of transfer subjective and implicit linguistics into objective and transparent data. A numerical example illustrates and clarifies the running steps of the proposed methodology.

With increasing concerns about the need for environmental protection and reduction of energy consumption, enterprises have to demonstrate their capabilities in lowering resource consumption by enhancing the efficiency of their systems. Although some approaches to quantifying the environmental burden generated by a product or service system such as life cycle assessment (LCA) and carbon auditing have been developed, expert judgments are often required to implement them. From an industry’s perspective, small- and medium-sized enterprises need an efficient tool to determine the best solution when considering various attributes simultaneously. Thus, a combination of fuzzy analytical hierarchy process and genetic algorithm has been introduced to solve scheduling problems and support the decision-making process. This study aims to effectuate the green scheduling on optimized machine-task assignments with fuzzy evaluation. The proposed approach is illustrated using a case example from a centralized dishwashing company. Results show that the global warming potential value can be reduced by 1.86% and the cost of operation is slightly increased by only 1.28%. The result of the proposed approach is presented simply in the form of machine-task assignments with optimized environmental impact values and associated costs. Therefore, no further result interpretation by environmental experts is required. This study can be a reference for government policymakers in formulating policies to synthesize operation optimization and business sustainability.

Using Auto-ID (Automatic Identification) systems, each physical item is given an identity and tracked in the supply chain in an automated and timely manner. Tracking physical assets, inventory, and personnel with automated systems improve operational efficiency. A barcode or RFID (Radio Frequency Identification) reader can gather the necessary data at the point of activity quickly and accurately. It is an important strategic decision for a company to invest Auto-ID technology. It should be decided at which level Auto-ID technology will be implemented in business processes. The aim of this study is to compare and select the most appropriate Auto-ID system among barcode at product, RFID at case and pallet level. Three main criteria are determined to evaluate the alternatives: cost, benefit and implementation aspect. Since rating of the criteria is under fuzzy environment and the related criteria are in hierarchical structure, Fuzzy Analytic Hierarchical Process (FAHP) method is used for the evaluation.

Joint Commission International (JCI) has been dedicated to improving the quality and safety of health care services. Today, the largest certification body of health care organizations in the United States, the Joint Commission surveys nearly 20,000 health care programs through a voluntary accreditation process. The Joint Commission is a none-profit organization. The JCI continuously improves the safety and quality of care in the international community through the provision of education and international accreditation. The JCI standard contains different subjects such as Prevention of Infection, Patient and Family Rights, Leadership, Facility Management, Safety.

Clients do not always appreciate differences among JCI consultants. This paper aims to provide an analytical tool to select the best JCI consultant providing the most customer satisfaction. The clients of three Turkish JCI consultancy firms were interviewed and the most important criteria taken into account by the clients while they were selecting their consultancy firms were determined by a designed questionnaire. The fuzzy analytic hierarchy process was applied to compare these consultancy firms. The means of the triangular fuzzy numbers produced by the customers and experts for each comparison were successfully used in the pair wise comparison matrices.