A combined fuzzy AHP and fuzzy TOPSIS based strategic analysis of electronic service quality in healthcare industry

Service sector is under pressure to deliver continuing performance and quality improvement while being customer-focused. In recent terms, there exists web based or electronic service quality (e-sq) concept. With the birth of electronic commerce, it has become important to be able to monitor and enhance e-sq. Therefore, this study will examine the e-sq concept and determine the key components of e-sq. The e-sq framework is employed by the aid of service quality (SERVQUAL) methodology as the theoretical instrument. Finally, proposed e-sq framework is illustrated with a web service performance example of healthcare sector in Turkey by using a combined multiple criteria decision making (MCDM) methodology containing fuzzy analytic hierarchy process (AHP) and fuzzy technique for order performance by similarity to ideal solution (TOPSIS). The work presented in this paper shows the applicability of the e-sq framework in explaining the complexity of aspects observed in the implementation of healthcare services via internet.     

New doctors ranking system based on VIKOR method

Nowadays, we can use different websites that help us make decisions about various aspects of our lives. However, privacy protection prevents websites from providing personalised guidelines to users. We propose a novel doctor‐ranking system (DRS) based on multi‐criteria group decision‐making (MCGDM) method to address the problems of privacy protection. The following aspects differentiate our proposed DRS model from previous works: (a) textual information reviews are used to identify user preferences and complementary criteria, (b) criteria weights are determined by term frequency inverse document frequency (TF‐IDF) instead of Delphi method or expert opinion, (c) intuitionistic fuzzy sets (IFSs) are used to replace sentiment analysis to express subjective user criteria, and (d) VIsekriterijumsko KOmpromisno Rangiranjie (VIKOR) method for MCGDM with IFSs is used to solve the doctor‐ranking problem. We apply our proposed model to datasets from Haodf.com to compare the performance of our method with that of sentiment analysis and technique for order performance by similarity to ideal solution (TOPSIS) methods. The experimental results show that our method provides accurate ranking and increases the reliability of DRS.     

Multi‐criteria group decision‐making method based on TODIM with probabilistic interval‐valued hesitant fuzzy information

Probabilistic interval‐valued hesitant fuzzy sets (PIV‐HFSs) are suitable for aggregating information from different groups because the probabilistic information of all the groups can be included by using interval values. Moreover, decision makers (DMs) prefer to use interval values to provide evaluation information. Furthermore, the traditional multi‐criteria group decision‐making (MCGDM) approach has some limitations, such as obtaining the DMs' weights with inappropriate methods and neglecting the interactions amongst the criteria and the psychological characteristics of DMs. Motivated by these research background, the main contents of this study are as follows. First, PIV‐HFSs are proposed, and the convex combination operation is extended into PIV‐HFSs. Second, a hybrid MCGDM approach with PIV‐HFSs is suggested that is based on the maximizing deviation method, fuzzy analytic network process (FANP) and TODIM (an acronym in Portuguese for interactive and multi‐criteria decision‐making model). Third, an evaluation case of health management centres based on the service‐specific failure mode and effect analysis (FMEA) is considered. The results show that the most crucial secondary factor is frequency (0.35775) and that the most serious failure mode is the inaccurate check‐in. The results demonstrate that the proposed model can evaluate service quality effectively and that it performs better than other methods.     

Analyzing the Implications of COVID-19 Pandemic through an Intelligent-Computing Technique

The outbreak of Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2 virus or COVID-19) disease was declared pandemic by the World Health Organization (WHO) on March 11, 2020. COVID-19 has already affected more than 211 nations. In such a bleak scenario, it becomes imperative to analyze and identify those regions in Saudi Arabia that are at high risk. A preemptive study done in the context of predicting the possible COVID-19 hotspots would facilitate in the implementation of prompt and targeted countermeasures against SARS-CoV-2, thus saving many lives. Working towards this intent, the present study adopts a decision making based methodology of simulation named Analytical Hierarchy Process (AHP), a multi criteria decision making approach, for assessing the risk of COVID-19 in different regions of Saudi Arabia. AHP gives the ability to measure the risks numerically. Moreover, numerical assessments are always effective and easy to understand. Hence, this research endeavour employs Fuzzy based computational method of decision making for its empirical analysis. Findings in the proposed paper suggest that Riyadh and Makkah are the most susceptible regions, implying that if sustained and focused preventive measures are not introduced at the right juncture, the two cities could be the worst afflicted with the infection. The results obtained through Fuzzy based computational method of decision making are highly corroborative and would be very useful for categorizing and assessing the current COVID-19 situation in the Kingdom of Saudi Arabia. More specifically, identifying the cities that are likely to be COVID-19 hotspots would help the country’s health and medical fraternity to reinforce intensive containment strategies to counter the ills of the pandemic in such regions.     

Multi‐Criteria Usability Evaluation of Electronic Devices in a Fuzzy Environment

The user‐oriented design is the most important competition issue in today's market. In recent years, user‐oriented design (i.e., usability) has become expected, particularly in electronic devices. Usability considers high user satisfaction in conjunction with user performance. Usability of electronic products is essential for high customer satisfaction as well as product life cycles in companies. Therefore, MP3 players were selected among the electronic products. Designing usable MP3 players is extremely important for users who have close interaction with them. In this study, MP3 players of different types and sizes were selected and their usability evaluated. The usability criteria used in the MP3 players' evaluation were divided into two major categories: performance and emotional expectations. The alternatives were ranked with fuzzy multi‐criteria decision‐making methods, namely, Fuzzy TOPSIS (FTOPSIS), Fuzzy Analytic Hierarchy Process (FAHP), and Fuzzy Axiomatic Design Theory (FADT), and the results were compared. Although the same decision matrices and data obtained from semantic differential experiment were used for all fuzzy multi‐criteria decision‐making methods, it is shown that different rankings were obtained. © 2012 Wiley Periodicals, Inc.     

Development of a decision support system for supplier evaluation and order allocation

This study aims to develop models and generate a decision support system (DSS) for the improvement of supplier evaluation and order allocation decisions in a supply chain. Supplier evaluation and order allocation are complex, multi criteria decisions. Initially, an analytic hierarchy process (AHP) model is developed for qualitative and quantitative evaluation of suppliers. Based on these evaluations, a goal programming (GP) model is developed for order allocation among suppliers. The models are integrated into a DSS that provides a dynamic, flexible and fast decision making environment. The DSS environment is tested at the purchasing department of a manufacturer and feedbacks are obtained.     

Web服务组合策略研究及组合决策平台实现

由于关注点的不同和客观环境的多样性,Web服务组合方法的种类纷繁复杂。如何从零碎散乱的不同决策角度出发来构建可行而高效的组合方法,是现阶段Web服务组合研究中亟待解决的关键问题之一。因此,本研究将注意力放在一套可以帮助Web服务组合实践者选择服务组合方法的决策机制上。考虑到层次分析法可以用来帮助解决这个多阶段多标准问题,分析综合了前人的相关研究成果,从而根据层次分析法构建结构树,进而举例详细阐述了如何在多个备选方案中做出最佳选择的Web服务组合决策机制。最后,为帮助Web服务组合实践者理解和使用这套决策机制,也设计并实现了一个决策平台easyWSC,现已开放给相关研究人员和实践者使用、讨论和改进。     

Successful adoption of macroergonomics in manufacturing: Using a multicriteria decision‐making methodology– analytic hierarchy process

The research presented in this paper aims to support the macroergonomics adoption improvement process by developing a broader understanding of relationships between key macroergonomics factors and management styles. The methodology involves knowledge acquisition, identifying, and categorizing a holistic set of key criteria about the macroergonomics adoption process. The Analytic Hierarchy Process is suggested as a multi‐attribute decision‐making methodology to effectively enhance adoption of macroergonomics and to improve management decision performance in measuring and comparing the overall performance of different management styles based on macroergonomical criteria. The study found that in terms of company culture, participation, human capability, and attitudes, the best management style in improving macroergonomics adoption is Management by Values. © 2004 Wiley Periodicals, Inc. Hum Factors Man 14: 353–377, 2004.     

Extension of weighted aggregated sum product assessment with interval-valued intuitionistic fuzzy numbers (WASPAS-IVIF)

Different methods are proposed in the framework of multi attribute utility theory for multi criteria decision making. Among the proposed methods, weighted sum and weighted product models (WSM and WPM) are well known and widely accepted. To improve the accuracy of WSM and WPM, the weighted aggregated sum product assessment (WASPAS) method was proposed which used an aggregation operator on WSM and WPM. In this paper, an extended version of WASPAS method is proposed which can be applied in uncertain decision making environment. In the proposed WASPAS-IVIF method, the uncertainty of decision maker(s) in stating their judgments and evaluations regard to criteria importance and/or alternatives performance on criteria are expressed by interval valued intuitionistic fuzzy numbers. Two numerical examples of ranking derelict buildings’ redevelopment decisions and investment alternatives are presented. The results are then compared with the rankings provided by other methods such as TOPSIS-IVIF, COPRAS-IVIF and IFOWA. Combining the strengths of IVIFS in handling uncertainty with the enhanced accuracy of WASPAS makes the proposed method as a desirable method for multi criteria decision making in real world applications.     

Implementing an extension of the analytical hierarchy process using ordered weighted averaging operators with fuzzy quantifiers in ArcGIS

This paper focuses on the integration of GIS and an extension of the analytical hierarchy process (AHP) using quantifier-guided ordered weighted averaging (OWA) procedure. AHP_OWA is a multicriteria combination operator. The nature of the AHP_OWA depends on some parameters, which are expressed by means of fuzzy linguistic quantifiers. By changing the linguistic terms, AHP_OWA can generate a wide range of decision strategies. We propose a GIS-multicriteria evaluation (MCE) system through implementation of AHP_OWA within ArcGIS, capable of integrating linguistic labels within conventional AHP for spatial decision making. We suggest that the proposed GIS-MCE would simplify the definition of decision strategies and facilitate an exploratory analysis of multiple criteria by incorporating qualitative information within the analysis.     

Using quality function deployment to conduct vendor assessment and supplier recommendation for business-intelligence systems

Business intelligence (BI) has been recognized as an important enterprise information system to help decision makers achieve performance measurement and management. Generally, typical BI users consist of financial analysts, marketing planners, and general managers. However, most of them are not familiar with BI’s core technologies. In order to help corporate executives better assess BI vendors, evaluation criteria are separated into marketing requirements (MRs) and technical attributes (TAs), respectively. In particular, a fuzzy MCDM (multi-criteria decision making) based QFD (quality function deployment) is proposed as follows: (1) fuzzy Delphi is used to aggregate the performance scores of BI vendors, (2) fuzzy DEMATEL (decision making and trial laboratory) is conducted to recognize the causalities between MRs and TAs, and (3) fuzzy AHP (analytical hierarchy process) is employed to recommend optimal BI systems. For better benchmarking, the strengths and weaknesses of three competitive BI vendors (i.e. SAP, SAS, and Microsoft) are concurrently visualized through displaying a line diagram (in terms of TAs) and a radar diagram (in terms of MRs). More importantly, experimental results demonstrate that supplier assessment and supplier recommendation have been successfully accomplished.     

基于方案修订的群决策一致性形成的研究

层次分析法(AHP)是群决策中经常使用的一种方法,利用AHP进行群决策的过程实质上也是决策者个体偏好集结的过程。针对如何将不同形式的偏好信息进行有效集结以形成群决策一致性方案的问题,提出一种通过活用AHP修订决策方案达到决策者群体的一致性偏好最终得以形成的方法,在利用决策者的决策信息进行群组划分的基础上明确各个划分的决策偏好差异,提出了活用AHP进行群决策一致性形成的方向,并形成了有效的动态群决策过程。     

Comparison between multiple-choice and analytic hierarchy process: measuring human perception

The objective of this study is to examine the effectiveness of the multiple‐choice method in measuring human perception. Specifically, the results of comparisons of the answers to two questions on the same issue are shown, each formatted in a different way: multiple‐choice (MC) and Analytic Hierarchy Process (AHP). AHP not only clearly identifies the most important alternative but also the preference for each alternative by each decision‐maker. Therefore, using AHP to analyze the decision‐making process results in a precise clarification of preference for alternatives. Based on public opinion research using AHP, two findings are shown: (1) MC and AHP yield different aggregated rankings of alternatives, and (2) AHP reveals that in modified MC format, which gives respondents the option of indicating their second‐best alternatives, the choice of a second‐best alternative is independent of the difference in the degree of importance between the best and the second best.     

A comprehensive decision making structure for partitioning of make-to-order, make-to-stock and hybrid products

Manufacturing systems produce their products by making use of three main strategies: make-to-order, make-to-stock and hybrid (combination of MTO and MTS strategies) systems. Hence, several products must be considered and partitioned in terms of many different conflicting criteria, leading to a large set of subjective or ambiguous data. Thus, an effective evaluation approach is essential to improve decision quality. In this paper a comprehensive decision, making structure is proposed to choose the proper strategy for producing the products. It consists of a novel hybrid methodology, which combines analytical hierarchy process (AHP) and technique for order performance by similarity to ideal solution (TOPSIS) for partitioning of products. In this study, the rating of each alternative regarding different criteria (throughout the TOPSIS technique) is described by means of linguistic variables. Furthermore, fuzzy AHP methodology is applied to determine the weights of evaluation criteria. At the end, the effectiveness of the proposed model is demonstrated through a case study.     

A Multigranularity Linguistic Group Decision‐Making Method Based on Hesitant 2‐Tuple Sets

Hesitant fuzzy linguistic term set (HFLTS) is a very useful technology in dealing with decision‐making problems where people have hesitancy in providing their linguistic assessments. Distinct methods have been developed to aid decision making with HFLTSs, yet there is little research involving the issue that how to deal with the multigranularity hesitant fuzzy linguistic information. The aim of this paper is to develop the aggregation method for multigranularity hesitant fuzzy linguistic information and solve the linguistic group decision problem with different linguistic term sets. To do so, we first modify the translation functions and aggregation operators in the existing 2‐tuple linguistic representation models so as to aggregate linguistic terms from different linguistic term sets. Then, we introduce the notion of hesitant 2‐tuple sets to make computation of HFLTSs without loss of information, and develop some new operators to aggregate HFLTSs from different linguistic term sets. Using these operators, we propose a method to deal with multigranularity linguistic group decision‐making problems with different situations where importance weights of either criteria or experts are known or unknown. Finally, the multigranularity linguistic group decision‐making model is implemented to the healthcare waste treatment in West China Hospital to validate its effectiveness and efficiency in aiding decision‐making process.     

A multi-criteria intuitionistic fuzzy group decision making for supplier selection with TOPSIS method

Supplier selection, the process of finding the right suppliers who are able to provide the buyer with the right quality products and/or services at the right price, at the right time and in the right quantities, is one of the most critical activities for establishing an effective supply chain. On the other hand, it is a hard problem since supplier selection is typically a multi criteria group decision-making problem involving several conflicting criteria on which decision maker’s knowledge is usually vague and imprecise. In this study, TOPSIS method combined with intuitionistic fuzzy set is proposed to select appropriate supplier in group decision making environment. Intuitionistic fuzzy weighted averaging (IFWA) operator is utilized to aggregate individual opinions of decision makers for rating the importance of criteria and alternatives. Finally, a numerical example for supplier selection is given to illustrate application of intuitionistic fuzzy TOPSIS method.     

A new multi criteria decision making approach for medical imaging systems considering risk factors

Effective and good quality imaging is important for medical decision-making and can reduce unnecessary costs and procedures. Therefore, decision making regarding any technology can present serious problems for healthcare centers with multi criteria decision making problems (MCDM). This paper is the first to develop the fuzzy axiomatic design with risk factors (RFAD) approach and to use it in multi attribute comparisons of medical imaging systems in a university hospital. Although most MCDM approaches in the literature treat risk factors as separate criteria, in real life every alternative has its own risks related to each criterion. The proposed approach integrates the risk factors in each criterion and calculates the information content to compare alternatives. This paper applies three different approaches to MCDM problems related to the selection of medical imaging systems for a university hospital.     

Group decision and distributed technical support

A group of 45 decision‐makers (local authorities and representatives from the communities) worked together for 16 months, with a facilitator group, to identify relevant criteria to analyze the consequences of a plant location. Two multi‐criteria models, one for an incinerator and the other for a waste disposal plant, were elaborated and an ELECTRE method was used to compare sites and rank them, with the aim of selecting the best sites for which an environmental impact assessment procedure will be activated. A virtual team, from different organizations, supported this work from a technical point of view. This kind of ‘distributed support’ to a multi‐criteria decision required actions of coordination and knowledge filtering and interpreting. The paper proposes an analysis of this participatory decision process and synthesizes the difficulties and results of the multi‐criteria decision aid intervention.     

An integrated intuitionistic fuzzy AHP and SWOT method for outsourcing reverse logistics

We consider the problem faced by a company that must outsource reverse logistics (RL) activities to third-party providers. Addressing RL outsourcing problems has become increasingly relevant issue in the management science and decision making literatures. The correct evaluation and ranking of the decision criteria/priorities determining the selection of the best third-party RL providers (3PRLPs) is essential for the competitive performance of the outsourcing company. The method proposed in this study allows to identify and classify these decision criteria. First, the relevant criteria and sub-criteria are identified using a SWOT analysis. Then, Intuitionistic Fuzzy AHP is used to evaluate the relative importance weights among the criteria and the corresponding sub-criteria. These relative weights are implemented in a novel extension of Mikhailov's fuzzy preference programming method to produce local weights for all criteria and sub-criteria. Finally, these local weights are used to assign a global weight to each sub-criterion and create a ranking. We discuss the results obtained by applying the proposed model to a case study of a real company. In particular, these results show that the most important priority for the company when delegating RL activities to 3PRLPs is to focus on the core business, while reducing costs constitutes one of its least important priorities.     

AHP 法中判断矩阵的比例标度构造法

指出AHP法中现有标度方法的主要缺陷是：标度“粒度”大粒且标度值不能反映方案间的实际重要程度和关系，容易导致判断信息损失，破坏方案间重要程度的传递性，为此提出一种比例标度和对应判断矩阵构造方法，其特点是标度值能较为准确地标度方案的重要度，所构造的判断矩阵是完全一致的，因而大大提高了AHP方法决策的可靠性和实用性。