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Review

VIKOR Technique: A Systematic Review of the State of the Art Literature on Methodologies and Applications

by
Abbas Mardani
1,*,
Edmundas Kazimieras Zavadskas
2,†,
Kannan Govindan
3,†,
Aslan Amat Senin
1,† and
Ahmad Jusoh
1,†
1
Faculty of Management, Universiti Teknologi Malaysia (UTM), 81310 Skudai Johor, Malaysia
2
Department of Construction Technology and Management, Vilnius Gediminas Technical University, Sauletekio al. 11, LT-10223 Vilnius, Lithuania
3
Centre for Sustainable Engineering Operations Management, Department of Technology and Innovation, University of Southern Denmark, Odense M-5230, Denmark
*
Author to whom correspondence should be addressed.
These authors contributed equally to this work.
Sustainability 2016, 8(1), 37; https://doi.org/10.3390/su8010037
Submission received: 19 November 2015 / Revised: 28 December 2015 / Accepted: 29 December 2015 / Published: 4 January 2016
(This article belongs to the Special Issue How Better Decision-Making Helps to Improve Sustainability - Part II)

Abstract

:
The main objective of this paper is to present a systematic review of the VlseKriterijuska Optimizacija I Komoromisno Resenje (VIKOR) method in several application areas such as sustainability and renewable energy. This study reviewed a total of 176 papers, published in 2004 to 2015, from 83 high-ranking journals; most of which were related to Operational Research, Management Sciences, decision making, sustainability and renewable energy and were extracted from the “Web of Science and Scopus” databases. Papers were classified into 15 main application areas. Furthermore, papers were categorized based on the nationalities of authors, dates of publications, techniques and methods, type of studies, the names of the journals and studies purposes. The results of this study indicated that more papers on VIKOR technique were published in 2013 than in any other year. In addition, 13 papers were published about sustainability and renewable energy fields. Furthermore, VIKOR and fuzzy VIKOR methods, had the first rank in use. Additionally, the Journal of Expert Systems with Applications was the most significant journal in this study, with 27 publications on the topic. Finally, Taiwan had the first rank from 22 nationalities which used VIKOR technique.

1. Introduction

The Multiple criteria decision making (MCDM) techniques such as VlseKriterijuska Optimizacija I Komoromisno Resenje (VIKOR) are usually used to evaluate and compare the sustainability of various energy plans or renewable energy technologies with the goal to present decision support for selecting the significant sustainable and appropriate options. Several of previous studies have used VIKOR technique in sustainability and renewable energy fields. Sustainability and renewable energy fields cover several specific sub-areas, including life cycle sustainability assessment, energy resources, environmental management, and environmental evaluation. As the product of an intentionally vague definition, sustainability has been applied to mean everything from environmental protection, social cohesion, economic growth, neighborhood design, alternative energy, green building design, and more [1]. The modern understanding of sustainability is characterized by the struggle to define and quantify sustainability and its goals. The term sustainability has its roots in long-held “sustainable” beliefs and principles, but that term has changed significantly during the emergence of the concept of sustainable development, and modern-day interpretation and discussion. Without a firm hold on the defining principles, any initiative to move closer to sustainable development will likely fail. In recent years, use of the sustainable and renewable energy has increased in real world.
Several of previous studies focused on sustainable and renewable energy in various perspectives with different approaches of MCDM such as VIKOR method. Recently; Mardani et al. [2] selected, summarized and reviewed 54 papers which were related to renewable and sustainable energy and decision making techniques, these 54 papers published from 2003 to 2015, Vučijak et al. [3] evaluated of sustainable hydropower by applied the VIKOR, Quijano H et al. [4] used VIKOR for development of renewable sustainable energy plans, Tzeng et al. [5], used VIKOR and Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) for identify improvement strategies to residents satisfaction by define the people response to environmental quality. Results of this study indicated that; noise pollution and air quality were the important criteria of environmental quality in Taipei. Martin-Utrillas, et al. [6] integrated the VIKOR, fuzzy Delphi and Analytic Hierarchy Process (AHP) for selection of best infrastructure related to sustainable economy, Yazdani-Chamzini et al. [7] used the VIKOR, Simple Additive Weighting (SAW), Additive Ratio Assessment (ARAS), TOPSIS and Multi-Objective Optimization by Ratio Analysis (MOORA) for selection of the best renewable energy sources, Ren et al. [8] combined the VIKOR and AHP for assessment of life cycle sustainability, Civic and Vucijak [9] utilized VIKOR for insulation options for warmth of buildings to increase energy efficiency, Kim and Chung [10] evaluated the vulnerability of the water supply to variability and climate change.
MADM methods provide simple and intuitive tools for making decisions on problems that involve uncertain and subjective information. Since the early 1970s, these methods have been developed into many forms. Among them, the simple MCDM methods cover a wide range of quite distinct approaches [11,12,13]. In recent years, numerous MCDM and fuzzy MCDM approaches have been suggested to select the best compromise options. These approaches have been suggested for different problems in real world which need to consider as multi criteria by decision makers for improving and solving in various fields of mathematical optimization, computer science and computer technology [14]. Several of previous studies related to MCDM techniques were developed during 1980s and early of 1990s. [15]. Köksalan, Wallenius and Zionts [15], presented a history of MCDM development methods in a book. Mardani et al. [16], reviewed 403 papers most related to fuzzy MCDM from 1994 to 2014. Mardani et al. [17], classified around 393 papers related to classical MCDM techniques in various application areas. Keeney et al. [18], developed the basics of decision with multiple objectives for improvement the body of knowledge regarding to decision making techniques. Hwang et al. [19], reviewed the development of Multi-Objective Decision Making (MODM) techniques and its applications. Later, Tzeng and Huang [20] reviewed and documented the Multi-attribute Decision Making (MADM) techniques such as The Linear Programming Technique for Multidimensional Analysis of Preference (LINMAP), ELimination and Choice Expressing REality (ELECTRE), TOPSIS and SAW. In addition, recently; Mardani et al. [21] reviewed and classified fuzzy MCDM and classical MCDM techniques based on the service quality. In recent years; very few studies reviewed and summarized role of VIKOR method and its application in various fields of sciences. Therefore, this review paper aimed to document the role of VIKOR technique and its applications in various fields of science.
The AHP and Analytic Network Process (ANP) methods developed by Saaty [22]. In addition; problem of compromise theory provided in a book by Zeleny and Cochrane [23], Hwang and Lin [24], published an article related to multi-criteria group decision making. Roy [25], proposed and developed some information on ELECTRE group techniques. In addition, same previous scholars published some papers about seminal techniques Belton and Stewart [26]; (Gal et al. [27], Miettinen [28]). Furthermore; in recent years; based on Brauers [29] were created MOORA. There are some other well-known techniques such as ANP [30], VIKOR [31,32], TOPSIS [33], SAW [34], AHP [35,36], Decision-Making Trial and Evaluation Laboratory (DEMATEL) [37], Preference Ranking Organisation Method for Enrichment Evaluations (PROMETHEE) [38], Data Envelopment Analysis (DEA) [39,40], ELECTRE [41,42,43,44]. Additionally, some new MCDM techniques developed in recent years, these techniques are; generalized regression with intensities of preference (GRIP) [45], Complex Proportional Assessment Method (COPRAS) [46,47,48], ARAS [48,49,50], MOORA [51], and MOORA plus the full multiplicative form (MULTIMOORA) [52], Step-Wise Weight Assessment Ratio Analysis (SWARA) [53], Weighted Aggregated Sum Product Assessment (WASPAS) [54].
The primary study of VIKOR was developed by Opricovic in a PhD dissertation in 1979 and also then by an application in 1980. This paper attempted to offer a comprehensive review of literature on VIKOR technique applications and methodologies. For this goal a reference database has been created according to classification scheme including 176 previous papers which published in 83 international journals since 2004 from two popular databases, i.e., Web of Science and Scopus. Moreover, papers are classified based on author (s) and years on publications, technique and approach, type of study, nationality of author (s), application area and scope, study purpose and name of journal.
The rest of the paper is organized as follows: Section 2 explained the important role of VIKOR technique in literature and previous studies, and the steps for implementation of the VIKOR. Section 3 describes methodology of this paper for papers classification. Section 4 conducts reviewed papers based on application areas, which is organized into 15 application areas, frequently of integrated techniques with VIKOR, journals names, publication year and nationality of authors. Finally, the conclusion of the paper is offered in Section 5.

2. Chronology of VIKOR Technique

Opricovic [31], introduced the VIKOR method as well-known MCDM technique which emphasized on select and rank of alternatives sets of conflicting criteria, in recent years this technique more evolved by scholars. Opricovic and Tzeng [55], proposed new model based on VIKOR method and TOPSIS for defuzzification within the multiple criteria decision making model with combined fuzzy criteria and set of crisp. Opricovic and Tzeng [32], proposed and integrate VIKOR technique with triangular fuzzy numbers (TFNs) for analysis of the planning strategies. Opricovic and Tzeng [56], developed fuzzy VIKOR with incomplete information for analyze of land-use strategies for decrease the economic and social costs with potential natural hazards. Opricovic and Tzeng [57], indicated that, the TOPSIS defines solution with the farthest distance from the negative ideal solution and shortest distance from the ideal solution, but it does not consider the relative importance of these distances. Tzeng et al. [58], used VIKOR, AHP and TOPSIS techniques to determining of the best fuel alternatives in the technological development of buses. Opricovic [59], applied and extended fuzzy VIKOR technique for solving problems in environmental issues. Opricovic and Tzeng [60], extended VIKOR technique for solving MCDM problems, results of this extended VIKOR compared with three different MCDM techniques including PROMETHEE, TOPSIS and ELECTRE. Chen and Wang [61], presented a systematic and rational process to develop the optimal compromise solution and alternative under criteria selection by using VIKOR method and fuzzy set. Finding of this study suggested new solution for fuzzy MCDM problems. Opricovic [62], indicated that; comparison of game theory and MCDM is a challenging topic, choosing and combining opinions can improve new approaches for developing conflict resolution, then; Opricovic [62], employed VIKOR method and game theory for conflict resolution, in this study, five approaches are considered based on conflict resolution. Huang et al. [63], developed a VIKOR model for MCDM which was used to determine the preference ranking from a set of alternatives in the presence of conflicting criteria. Moeinzadeh and Hajfathaliha [64], presented a supply chain risk assessment model based on ANP and VIKOR methods with integrated fuzzy set theory where the subjectivity and vagueness were handled with linguistic terms parameterized by TFNs. Sayadi, et al. [65], proposed the VIKOR technique for decision making problems with the interval number where ranking is achieved by interval numbers comparison. Opricovic [66], applied the VIKOR technique for solving decision problems in water resource management. In this paper some criteria such as environmental, social, economic and cultural features have been considered for developing reservoir system of the Mlava River. Chang [67], proposed a modified VIKOR method to solve MCDM problems with contradicting and non-commensurable criteria. Heydari et al. [68], extended VIKOR technique for solving problem based on multi-objective large-scale non-linear programming (MOLSNLP) problems and integrated with block angular structure. Sanayei et al. [69], applied the VIKOR technique under fuzzy set and group decision making (DM) process for selection of suppliers. Vahdani et al. [70], presented a novel method for solving MCDM problems based on the interval-valued fuzzy VIKOR in which the weights of criteria are unequal, using interval-valued fuzzy set concepts. Devi [71], extended VIKOR method into fuzzy environment in order to solve Multi criteria Decision Making in which weights of criteria and alternatives are taken as triangular fuzzy set. Kuo and Liang [72], integrated VIKOR with gray relational analysis (GRA) for evaluation of problems related to service quality. Park et al. [73], extended the VIKOR method for multi-criteria group decision making (MAGDM) in interval-valued intuitionistic fuzzy (IVIF) environment which preference information is presented by DMs as IVIF decision matrices. Liu and Wang [74], extended VIKOR technique for solving problems in MAGDM by generalized IVTF numbers, in which the attribute values and weights are given. Du and Liu [75], extended VIKOR technique for solving decision making problems based on ITF numbers. Su [76], proposed a new hybrid fuzzy method by a modified VIKOR method modified GRA method, to the negative ideal alternative and the positive ideal alternative. Liu and Wu [77], applied the VIKOR method and entropy to evaluate human resources managers’ competency. Liu et al. [78], integrated and proposed the induced aggregation operators into the VIKOR for tackling multiple-criteria problems. Liao and Xu [79], extended and presented the VIKOR technique by employing the hesitant normalized Manhattan distance to accommodate the hesitant fuzzy circumstances. Wan et al. [80], extended the VIKOR technique for solving multi-criteria group decision making problems with triangular intuitionistic fuzzy numbers (TIFNs). Zhao et al. [81], presented an extended VIKOR technique for solving problems in multi-criteria group decision making based on cross-entropy in the IVIFs. Tan and Chen [82], proposed a decision-making method by integrating VIKOR technique and Choquet integral for solving problems of MCDM techniques with IVIFs. Vinodh et al. [83], presented the application of fuzzy VIKOR for concept selection in the context of agile systems. The best concept design was identified in the context of agility. The results derived from fuzzy VIKOR were compared with fuzzy TOPSIS. Ju and Wang [84], proposed a new method to solving MCGDM related to criteria weights and criteria values take the form of linguistic information based on the traditional idea of VIKOR method. Zhang and Wei [85], developed the extended VIKOR and TOPSIS to solve the multiple attribute decision marking problems with hesitant fuzzy set information. Liao and Xu [79], extended the classical VIKOR method to provide of hesitant fuzzy circumstances and improved the hesitant normalized Manhattan Lp—metric, the hesitant fuzzy individual regret measure, the hesitant fuzzy group utility measure and the hesitant fuzzy compromise measure for present a new hesitant fuzzy VIKOR. Park et al. [86], extended the VIKOR technique for dynamic intuitionistic fuzzy MADM. This study presented two new aggregation operators which called dynamic intuitionistic fuzzy weighted geometric (DIFWG) and uncertain dynamic intuitionistic fuzzy weighted geometric (UDIFWG) operator for solving problems of dynamic intuitionistic fuzzy MADM. Wei and Zhang [87], developed and presented a multi-criteria hesitant fuzzy decision-making by using of the Shapley value and VIKOR technique. Hajiagha et al. [88], presented a fuzzy multi-objective linear programming based on VIKOR method to find fuzzy efficient solution by minimizing its combinational distance from an ideal and nadir solution. Pai et al. [89], presented a novel decision making technique based on four kinds of MCDM techniques (VIKOR, PROMETHEE, ELECTRE and TOPSIS), intersection concepts and linguistic information. Keshavarz Ghorabaee [90], extended the VIKOR method for selection of project with interval type-2 fuzzy environment. You et al. [91], extended the VIKOR for supplier selection based on interval 2-tuple linguistic. Li and Zhao [92], proposed new VIKOR according to prospect theory with grey number. Qin et al. [93], extended VIKOR for MADM based on interval type-2 fuzzy environment by propose a new distance measure for interval type-2 fuzzy set (IT2FS) and decision model integrating VIKOR and theory of prospect. Zhu et al. [94], combined the VIKOR and AHP to evaluate the design concept in development of new product. Keshavarz Ghorabaee [95], extended the VIKOR method with interval type-2 fuzzy sets for selection of robots. Bausys and Zavadskas [96], extended VIKOR technique for solving multi criteria decision making based in interval neutrosophic set environment. Figure 1 shows diagram of modified VIKOR technique presented by [97].
Figure 1. Diagram of modified VlseKriterijuska Optimizacija I Komoromisno Resenje (VIKOR) technique adopted from [97].
Figure 1. Diagram of modified VlseKriterijuska Optimizacija I Komoromisno Resenje (VIKOR) technique adopted from [97].
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3. Research Methodology

This review paper attempted to review the published papers in various application areas related to the VIKOR technique. Therefore; this review paper searched to identify the papers related to VIKOR technique in various parts of published papers such as keywords, title, research method, results, conclusions and discussions. In relation to classification scheme, a reference repository has been established, which included a total of 176 papers in 83 international scholarly journals from 2004 to 2015. The papers were categorized based on the application areas, year of publication, name of the journal, study purpose, type of study (utilized, proposed, integrated, modified or extended types) and VIKOR technique and integrated with other techniques. This present review paper, first, classified of the articles into 15 fields (Manufacturing, Construction Management, Material Selection, Performance Evaluation, Health-Care, Supply Chain, Tourism Management, Service Quality, Sustainability and Renewable Energy, Water Resources Planning, Marketing, Risk and Financial management, Operation Management, Human Resource Management, other application areas) and second, examine of the type of study (utilized, proposed, integrated, modified or extended types), and third, articles reviewed based on research purpose and goal.
The target databases for this review paper were “Scopus and Web of Science” as two important databases which cover the extensive range of scopes of journals. Items such as textbooks, doctoral dissertations, unpublished papers and master’s theses, were excluded in our review. In this review paper, we attempted to use the comprehensive list of journals indexed by two databases.
In recent years, scholars presented, extended and applied the VIKOR technique in various fields of sciences which are different in kind of questions, theoretical background, and the kind of achieved results. Various criteria and keywords should be considered for identifying and selecting published papers related to VIKOR technique. Figure 2 presented the systematic review of analysis and procedure. In this review paper we conduct a systematic review, a rigorous review methodology originally developed mainly within medical research and first outlined for the field of organization and management studies by [98]. Systematic reviews exhibit significant advantages compared to traditional narrative approaches of literature reviews. Those traditional reviews generally do not follow a formal methodology, thus resulting in lacking transparency and replicability by others. Researchers can focus on “preferred” literature sources and base their review on a personal, purposive selection of materials they believe to be important. Systematic reviews help to reduce those implicit researcher biases [99]. Through the adoption of search strategies, predefined search strings as well as inclusion/exclusion criteria, systematic reviews effectively force researchers to search for all relevant studies beyond their own horizon of experience. Furthermore, the application and extensive documentation of a clear review protocol improves the methodological transparency of the review and enables future replication by other researchers. As the motivation and research questions of the review have already been outlined in the introduction, the remainder of this part emphasis on how the this review paper is conducted and describe in detail the search strategy, selection criteria and synthesis criteria applied in this paper. Our search strategy consisted of looking for relevant studies within scientific literature sources, represented by academic studies published in peer-reviewed journals. We searched online databases to identify all articles published on the VIKOR technique between 2004 and 2015.
Figure 2. Summary of Analysis and Procedure of Study.
Figure 2. Summary of Analysis and Procedure of Study.
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4. Results

4.1. Classifications and Observations

In recent decades, research related to VIKOR technique has continued, and many new areas to which it can be applied have been found. VIKOR technique provides effective decision-making method in domains in which selection of the best alternative is highly complex environment. This survey reviews the main considerations of VIKOR technique in various fields based on theory and practice. The VIKOR technique aids in identifying the best alternatives in situations with multiple criteria; the best choice can be obtained by analyzing different scopes and weights of the criteria. This survey comprehensively shows the development of VIKOR technique and its applications in the 15 various topics. This survey is based on a literature review and classification of international journal articles from 2004–2015.
All selected papers were classified in 15 different application areas such as Manufacturing Fields, Construction Management, Material Selection, Performance Evaluation, Health-Care, Supply Chain, Tourism Management, Service Quality, Sustainability and Renewable Energy fields, Water Resources Planning, Marketing, Risk and Financial management, Operation Management, Human Resource Management, other application areas. Table 1 presented the distribution papers based on application fields.
Table 1. Distribution papers based on application fields.
Table 1. Distribution papers based on application fields.
Application FieldsNumber of PaperPercentage (%)
Manufacturing fields1810.23%
Material selection179.66%
Marketing158.52%
Construction management147.95%
Performance evaluation147.95%
Risk and Financial management147.95%
Sustainability and renewable energy fields137.39%
Supply chain126.82%
Human resource management116.25%
Operation management105.68%
Service quality52.84%
Health-care Fields52.84%
Tourism management42.27%
Water resources planning31.70%
Other application areas2111.93%
Total176100.00%

4.2. Field of Category

Several application areas applied the VIKOR technique in the real world; there is a strong motivation to categorize these techniques across several areas and particular sub-areas. The studies that have used the VIKOR technique are categorized into four groups: utilizing research (the study exclusively used VIKOR as a single technique), integrated research (VIKOR is integrated with other techniques), proposed research (VIKOR was proposed to be applied in the study), and modified research (modified VIKOR technique was applied in the study). To identify the differences and similarities, the 176 papers were categorized into 15 fields: (1) Manufacturing, (2) Construction management, (3) Material Selection, (4) Performance Evaluation, (5) Health-care, (6) Supply Chain, (7) Tourism Management, (8) Service Quality, (9) Sustainability and Renewable Energy, (10) Water Resources Planning, (11) Marketing, (12) Risk and Financial Management, (13) Operation Management, (14) Human Resource Management, (15) Other application areas. Similarly, study by Behzadian, et al. [100] have categorized TOPSIS papers based on various application areas such as, environmental science, manufacturing systems, supply chain issue, human resource management (HRM), energy and safety, business and management and so on. It is interesting to note that while the technique is originally used in water resources research [66], it has increasingly been applied by authors from both applied and social sciences. The next sections provide a review of the 176 papers categorized into 15 application areas.

4.2.1. Manufacturing Fields

Manufacturing fields cover several specific sub-areas including robot selection, product design, manufacturing strategy, product development, machine tools, and manufacturing systems. Keshavarz Ghorabaee [95], extended the VIKOR method with interval type-2 fuzzy sets for selection of robots. Liu et al. [101], proposed new method for failure mode and effects analysis based on the fuzzy VIKOR, fuzzy AHP and entropy. Peng et al. [102], combined the VIKOR technique, intuitionistic fuzzy sets (IFSs) and Taguchi to optimize quality problems solving. Zhu, Hu, Qi, Gu and Peng [94] integrated AHP and the VIKOR to evaluate design concept in development of new product, Anvari, Zulkifli and Arghish [97], modified VIKOR for lean tools selection in manufacturing systems problems. Tzeng and Huang [103] combined the VIKOR, ANP and DEMATEL for selection of the best global manufacturing strategy selection, Mousavi, et al. [104] proposed a novel fuzzy VIKOR for selection of new products for manufacturing companies success, Büyüközkan and Görener [105] applied the VIKOR and AHP to evaluate product development partners. Table 2, presented the VIKOR papers addressed within manufacturing fields based on author (s) and year, technique and approach, type of study, application area and scope and study purpose. In total, 18 past papers used the VIKOR technique in fields of manufacturing.
Table 2. Distribution of papers in manufacturing fields.
Table 2. Distribution of papers in manufacturing fields.
Author (s) and YearTechnique and ApproachType of StudyApplication Area and ScopeStudy Purpose
Vinodh et al. [106]VIKORUtilizedManufacturing environmentSelection of fit concept in the modern manufacturing environment.
Chatterjee et al. [107]VIKOR and ELECTREIntegratedRobot selectionIntegrated VIKOR and ELECTRE for selection of industrial robots.
Keshavarz Ghorabaee [95]VIKOR and Interval type-2 fuzzy setsExtendedRobot selectionExtended VIKOR for selection of robots.
Devi [71]Fuzzy VIKORExtendedRobot selectionExtended VIKOR for robot selection in intuitionistic fuzzy environment.
Zhu, Hu, Qi, Gu and Peng [94]VIKOR and AHP IntegratedProduct designEvaluation of design concept for combine VIKOR and AHP.
Parameshwaran et al. [108]Fuzzy VIKOR, fuzzy TOPSIS, fuzzy AHP and fuzzy Delphi IntegratedRobot selectionCombined Fuzzy VIKOR, fuzzy TOPSIS, fuzzy AHP and fuzzy Delphi for selection of robot.
Liu, You, You and Shan [101]Fuzzy VIKOR, fuzzy AHP and entropyIntegratedFMEAPresented a new method for FMEA by apply fuzzy VIKOR, fuzzy AHP and entropy.
Peng, Yeh, Lai and Hsu [102]VIKOR and IFSsIntegratedTaguchiMixed VIKOR and Taguchi for optimization of multi-response problems in IF environments.
Bairagi et al. [109]Fuzzy VIKOR, fuzzy AHP, fuzzy TOPSIS and COPRAS-GIntegratedRobot selection Applied Fuzzy VIKOR, fuzzy AHP, fuzzy TOPSIS and COPRAS-G for selection of robot.
Wang and Wu [110]VIKORUtilized Product varietiesUtilized VIKOR and KANO model for combine customer preferences and perceptions.
Feng et al. [111]VIKOR and PROMETHEE IIProposedEquilibrium designProposed model based on VIKOR and PROMETHEE II for equilibrium design.
Anvari, Zulkifli and Arghish [97]VIKORModifiedLean tool Modified VIKOR for selection of lean tool.
Tzeng and Huang [103]VIKOR, ANP and DEMATELIntegratedGlobal manufacturing strategyCombined VIKOR, ANP and DEMATEL for selection of the best global manufacturing strategy selection.
Mousavi, Torabi and Tavakkoli-Moghaddam [104]Fuzzy VIKORProposedProduct SelectionProposed a novel fuzzy VIKOR for selection of new products.
Büyüközkan and Görener [105]VIKOR and AHPUtilizedProduct development Evaluated of product development by applied VIKOR and AHP.
Zhang and Xu [112]VIKORUtilizedMachine toolsEmployed VIKOR for transmission system accuracy best allocation for multi-axis machine tools.
Chaturvedi and Singh [113]VIKORUtilizedManufacturing SystemsApplied VIKOR for analysis of control parameters in abrasive water jet machining.
Vinodh et al. [114]Fuzzy VIKORUtilizedRapid prototyping technologyUsed fuzzy VIKOR for selection of the best rapid prototyping technologies in agile environment.

4.2.2. Construction Management

Construction Management covers several specific sub-areas including project manager selection, tunneling, building fields, transportation systems. Table 3, presented the VIKOR papers addressed within Construction Management based on author (s) and year, technique and approach, type of study, application area and scope and study purpose. Peng [115] combined VIKOR, TOPSIS, ELECTRE III, GRA, PROMETHEE II, and weighted sum model (WSM) for assessment of earthquake vulnerability, Zolfani et al. [116] combined the VIKOR and SWARA for selection of mechanical longitudinal ventilation of tunnel pollutants, Ginevičius et al. [117] combined the VIKOR and TOPSIS for assessment of alternatives of wall insulation, Zavadskas and Antuchevičiene [118] integrated the VIKOR and TOPSIS for ranking of building redevelopment, Mela et al. [119] integrated VIKOR with weighted product method, TOPSIS and PROMETHEE II, weighted sum method for evaluation of building design, Pamučar and Ćirović [120] presented new model based on DEMATEL–Multi-Attributive Border Approximation area Comparison (MABAC) for decision assessment on the acquisition of manipulative transport. Ebrahimnejad et al. [121], integrated a modified ANP with the VIKOR for selection construction project. Totally, 14 articles used the VIKOR technique in the fields of Construction Management (Table 3).
Table 3. Distribution of papers in Construction Management.
Table 3. Distribution of papers in Construction Management.
Author (s) and YearTechnique and ApproachType of StudyApplication Area and ScopeStudy Purpose
Ginevičius, Podvezko and Raslanas [117]VIKOR and TOPSISIntegratedWall insulationCombined VIKOR and TOPSIS for assessment of alternatives of wall insulation;
Abbasianjahromi et al. [122]VIKORUtilizedSubcontractor selectionUsed VIKOR for selection of subcontractor.
Mohammadi, et al. [123]VIKOR and ANPIntegratedProject manager selectionIntegrated VIKOR CANP for selection of project manager.
Lanjewar et al. [124]VIKOR, TOPSIS and AHPIntegratedFuels transportationEmployed for evaluation of fuels for transportation.
Peng [115]VIKOR, TOPSIS, ELECTRE III, GRA, PROMETHEE II, and WSMUtilizedEarthquake vulnerabilityCombined VIKOR, TOPSIS, ELECTRE III, GRA, PROMETHEE II, and WSM for assessment of earthquake vulnerability.
Zolfani, Esfahani, Bitarafan, Zavadskas and Arefi [116]VIKOR and SWARAIntegratedTunnelingCombined VIKOR and SWARA for selection of mechanical longitudinal ventilation of tunnel pollutants.
Zavadskas and Antuchevičiene [118]VIKOR and TOPSISIntegratedBuildings’ redevelopmentIntegrated VIKOR and TOPSIS for ranking of building redevelopment.
Vučijak, et al. [125]VIKOR, PVIKOR and PROMETHEEIntegratedHighway Tunnel DoorsMixed VIKOR, PVIKOR and PROMETHEE for selection optimal choice of highway tunnel doors.
Mela, Tiainen and Heinisuo [119]VIKOR, weighted product method, TOPSIS and PROMETHEE II, weighted sum methodIntegratedBuilding designIntegrated of VIKOR, weighted product method, TOPSIS and PROMETHEE II, weighted sum method for evaluation of building design.
Tošić, et al. [126]VIKORUtilizedConcrete productionApplied VIKOR for selecting the transport scenario and aggregate type in concrete production.
Pamučar and Ćirović [120]VIKOR, DEMATEL MABAC, SAW, MOORA COPRAS and TOPSISProposedManipulative transportPresented new model based on DEMATEL–MABAC for decision assessment on the acquisition of manipulative transport.
Vahdani, et al. [127]VIKORProposedContractor selectionProposed new model based on VIKOR method for contractor selection.
Ebrahimnejad, Mousavi, Tavakkoli-Moghaddam, Hashemi and Vahdani [121]fuzzy VIKOR and fuzzy ANPIntegratedConstruction project selectionIntegrated a modified ANP with VIKOR for selection construction project.
Bashiri, et al. [128]Fuzzy VIKORUtilizedTransportation systemsApplied fuzzy VIKOR for solve of hub location problem.

4.2.3. Material Selection

Table 4, presented the VIKOR papers addressed within Material Selection based on author (s) and year, technique and approach, type of study, application area and scope and study purpose. Liu, Mao, Zhang and Li [78] integrated and proposed the induced aggregation operators into the VIKOR for tackling multiple-criteria problems, Hsu et al. [129] integrated VIKOR, DEMATEL and ANP for vendor selection based on recycled materials, Chatterjee et al. [130] used the VIKOR method and ELECTRE for material selection, Chauhan and Vaish [131] used the VIKOR method and TOPSIS for magnetic material selection, Çalışkan et al. [132] applied VIKOR, PROMETHEE II, AHP, entropy and TOPSIS for material selection, Çalışkan [133] applied the VIKOR method, PROMETHEE II and TOPSIS for material selection. Yazdani and Payam [134] applied the VIKOR method and TOPSIS to develop MEMS technology, Anojkumar et al. [135] combined the VIKOR method with fuzzy AHP TOPSIS, ELECTRE and PROMETHEE for selection of pipe material. Totally, 17 past papers used the VIKOR technique in the fields of Material Selection which presented in Table 4.
Table 4. Distribution of papers in Material Selection.
Table 4. Distribution of papers in Material Selection.
Author (s) and YearTechnique and ApproachType of StudyApplication Area and ScopeStudy Purpose
Liu, Mao, Zhang and Li [78]IOWA-VIKORIntegrationMaterial selectionIntegrated and proposed the induced aggregation operators into VIKOR for tackling multicriteria problems.
Hsu, Wang and Tzeng [129]VIKOR, DEMATEL and ANPIntegratedRecycled materialIntegrated VIKOR, DEMATEL and ANP for vendor selection based on recycled materials.
Chatterjee, Athawale and Chakraborty [130]VIKOR and ELECTREIntegrationMaterial selectionUsed VIKOR and ELECTRE for material selection.
Jahan et al. [136]VIKORUtilizedMaterial selectionApplied VIKOR for material selection.
Bahraminasab and Jahan [137]VIKORUtilizedMaterial selectionEmployed VIKOR for material selection.
Chauhan and Vaish [131]VIKOR and TOPSISIntegrationMaterial selectionMagnetic material selection by used VIKOR and TOPSIS.
Girubha and Vinodh [138]Fuzzy VIKORUtilizedMaterial selectionUtilized fuzzy VIKOR for material selection.
Çalışkan, Kurşuncu, Kurbanoğlu and Güven [132]VIKOR, PROMETHEE II, AHP, Entropy and TOPSISIntegrationMaterial selectionApplied VIKOR, PROMETHEE II, AHP, Entropy and TOPSIS for material selection.
Cavallini et al. [139]VIKORUtilizedMaterial selectionApplied VIKOR for material selection.
Jahan and Edwards [140]VIKORUtilizedMaterial selectionEmployed VIKOR for material selection.
Çalışkan [133]VIKOR, PROMETHEE II and TOPSISIntegrationMaterial selectionApplied VIKOR, PROMETHEE II and TOPSIS for material selection.
Liu et al. [141]VIKOR, DEMATEL and ANPIntegrationMaterial selectionMaterial selection by integrated of VIKOR, DEMATEL and ANP.
Yazdani and Payam [134]VIKOR and TOPSISIntegrationMaterial selectionApplied VIKOR and TOPSIS for develop of MEMS technology
Ray [142]VIKOR and AHPIntegratedMaterial selectionIntegrated VIKOR and AHP for selection cutting fluid.
Chauhan et al. [143]VIKORUtilizedMaterial selectionUsed VIKOR for selection of Piezoelectric material.
Anojkumar, Ilangkumaran and Sasirekha [135]VIKOR, Fuzzy AHP TOPSIS, ELECTRE and PROMETHEEIntegratedPipe material selectionCombined VIKOR, Fuzzy AHP TOPSIS, ELECTRE and PROMETHEE for selection of pipe material.
Vats and Vaish [144]Fuzzy VIKORUtilizedPiezoelectric material selectionUsed fuzzy VIKOR for selection of piezoelectric material in transducer application.

4.2.4. Performance Evaluation

Performance Evaluation covers several specific sub-areas including universities evaluation performance, banking performance, business performance, and engineering departments performance. Table 5, presented the VIKOR papers addressed within Performance Evaluation based on author (s) and year, technique and approach, type of study, application area and scope and study purpose. Rezaie et al. [145] integrated fuzzy AHP and the VIKOR method for evaluation of performance in cement firms, Wu et al. [146] evaluated performance based on BSC and applied the VIKOR method, DEMATEL and ANP, Wu et al. [147] used the VIKOR method, fuzzy AHP and TOPSIS to evaluate banking performance based on BSC, Chen and Chen [148] integrated VIKOR and fuzzy AHP for innovation systems in airline industry based on AIS, Zolfani and Ghadikolaei [149] mixed the VIKOR method with DEMATEL and ANP for evaluation of universities performance, Hsu [150] applied the VIKOR method, GRA and entropy for evaluation of business performance, Hsu [151] applied the VIKOR method, IGRA and entropy to evaluate efficiency and operating performance, Tsai and Chang [152] integrated the VIKOR method, GRA, TOPSIS and AHP for evaluation of performance of Tablet PCs. Totally, 14 past papers used the VIKOR technique in the fields of Performance Evaluation which presented in Table 5.
Table 5. Distribution papers on Performance Evaluation.
Table 5. Distribution papers on Performance Evaluation.
Author (s) and YearTechnique and ApproachType of StudyApplication Area and ScopeStudy Purpose
Rezaie, Ramiyani, Nazari-Shirkouhi and Badizadeh [145]VIKOR and fuzzy AHPIntegrationPerformance evaluationIntegrated fuzzy AHP and VIKOR for evaluation of performance in cement firms.
Wu, Lin and Chang [146]VIKOR, DEMATEL and ANPIntegrationEducation centers in universitiesEvaluated performance based on BSC and applied VIKOR, DEMATEL and ANP.
Wu, et al. [153]VIKOR and AHPIntegrationPerformance evaluationEvaluated of performance based on VIKOR and AHP for ranking universities.
Wu, Tzeng and Chen [147]VIKOR, FAHP and TOPSISIntegratedPerformance evaluation Used VIKOR, FAHP and TOPSIS to evaluating banking performance based on BSC.
Chen and Chen [148]VIKOR and fuzzy AHPIntegratedAirline operation performanceIntegrated VIKOR and fuzzy AHP for innovation operations in airlines industry based on AIS.
Kuo and Liang [154]VIKOR and interval-valued fuzzy setsProposed Performance evaluationProposed new method for performance evaluation.
Zolfani and Ghadikolaei [149]VIKOR, DEMATEL and ANPIntegratedPerformance evaluation Mixed VIKOR, DEMATEL and ANP for evaluation of universities performance.
Hsu [150]VIKOR, GRA and entropyIntegratedPerformance evaluationApplied VIKOR, GRA and entropy for evaluation of business performance.
Hsu [151]VIKOR, IGRA and entropyIntegratedEvaluate efficiency and operating performanceApplied VIKOR, IGRA and entropy for evaluate efficiency and operating performance.
Chou et al. [155]VIKOR and entropyUtilizedWomen performance in science and technologyEmployed VIKOR and entropy to evaluating of women in science and technology.
Ranjan et al. [156]VIKOR, DEMATEL and EntropyIntegratedPerformance evaluationUsed VIKOR, DEMATEL and Entropy for evaluation of performance in engineering departments.
Dincer and Hacioglu [157]Fuzzy VIKOR and AHPUtilizedPerformance evaluationUsed fuzzy VIKOR and AHP for evaluation of performance based on customer satisfaction.
Lee and Pai [158]VIKOR and DEAUtilizedOperation PerformanceImprove DEA and VIKOR for evaluation of dynamic operation performances.
Tsai and Chang [152]VIKOR, GRA, TOPSIS and AHPIntegratedPerformance evaluation Integrated VIKOR, GRA, TOPSIS and AHP for evaluation of performance of Tablet PCs.

4.2.5. Health-Care Fields

Health-Care Fields covers several specific sub-areas including health-care waste disposal, and healthcare management. Table 6, presented the VIKOR papers addressed within Health-Care Fields based on author (s) and year, technique and approach, type of study, application area and scope and study purpose. Liu et al. [159] assessed the health-care waste disposal based on fuzzy VIKOR and Ordered Weighted Averaging (OWA), Chang [160] evaluated hospital service by employing the fuzzy VIKOR, Lu et al. [161] improved and assessed of RFID adoption based on VIKOR, DEMATEL and ANP, Liu et al. [162] combined the fuzzy VIKOR, fuzzy TOPSIS, 2-tuple DEMATEL and MULTIMOORA for evaluation of health-care waste. In total, five past papers used the VIKOR technique in fields of Health-Care Fields which presented in Table 6.
Table 6. Distribution of papers in Health-Care Fields.
Table 6. Distribution of papers in Health-Care Fields.
Author (s) and YearTechnique and ApproachType of StudyApplication Area and ScopeStudy Purpose
Liu, Wu and Li [159]Fuzzy VIKOR and OWAIntegrationHealth-careEvaluation of health-care waste disposal based on Fuzzy VIKOR and OWA.
Chang [160]Fuzzy VIKORUtilizedHospital serviceEvaluated of hospital service by employ fuzzy VIKOR.
Lu, Lin and Tzeng [161]VIKOR, DEMATEL and ANPIntegrationHealthcareImproved and assessed of RFID adoption based on VIKOR, DEMATEL and ANP.
Liu, You, Lu and Chen [162]Fuzzy VIKOR, Fuzzy TOPSIS, 2-tuple DEMATEL and MULTIMOORAIntegratedHealth-care wasteCombined fuzzy VIKOR, fuzzy TOPSIS, 2-tuple DEMATEL and MULTIMOORA for evaluation of health-care waste.
Zeng et al. [163]VIKORModifiedHealthcare managementImproved VIKOR for enhance accuracy in healthcare management.

4.2.6. Supply Chain

Supply Chain covers several specific sub-areas including supplier selection, supply chain networks, and supply chain performance. Table 7, presented the VIKOR papers addressed within Supply Chain based on author (s) and year, technique and approach, type of study, application area and scope and study purpose. Rostamzadeh et al. [164] evaluated green supply chain by applying the fuzzy VIKOR, Akman [165] applied the VIKOR and fuzzy c-means for evaluation of green supplier development, Chen and Wang [61] employed the fuzzy VIKOR for assessing and evaluating of suppliers/vendors, Chithambaranathan et al. [166] evaluated performance of service supply chain by using the VIKOR and ELECTRE, Shemshadi et al. [167] extended the VIKOR for selection of supplier based on entropy measure, You, You, Liu and Zhen [91] extended the VIKOR for supplier selection based on interval 2-tuple linguistic, Alimardani et al. [168] combined the VIKOR and SWARA for selection of supplier in agile environment. In total, 12 articles used VIKOR technique in fields of Supply Chain which presented in Table 7.
Table 7. Distribution of papers in Supply Chain.
Table 7. Distribution of papers in Supply Chain.
Author (s) and YearTechnique and ApproachType of StudyApplication Area and ScopeStudy Purpose
Rostamzadeh, Govindan, Esmaeili and Sabaghi [164]Fuzzy VIKORUtilizedGreen supply chainEvaluated green supply chain by applied fuzzy VIKOR.
Akman [165]VIKOR and fuzzy c-meansUtilizedSupply chainApplied VIKOR and fuzzy c-means for evaluation of green supplier development.
Chen and Wang [61]Fuzzy VIKORUtilizedIS/IT outsourcingEmployed fuzzy VIKOR for assessing and evaluating of suppliers/vendors.
Chithambaranathan, Subramanian, Gunasekaran and Palaniappan [166]VIKOR and ELECTREIntegratedSupply chain Evaluated performance of service supply chain by used VIKOR and ELECTRE.
Sanayei, Mousavi and Yazdankhah [69]Fuzzy VIKORUtilizedSupplier selectionEmployed fuzzy VIKOR for selection of supplier.
Shemshadi, Shirazi, Toreihi and Tarokh [167]VIKOR and entropyExtendedSupplier selectionExtended VIKOR for selection of supplier based on entropy measure.
You, You, Liu and Zhen [91]VIKOR and interval 2-tuple linguisticExtendedSupplier selectionExtended VIKOR for supplier selection based on interval 2-tuple linguistic.
Aghdaie et al. [169]VIKOR and SWARAIntegratedSupply chainCombined VIKOR and SWARA for clustering and ranking of supplier.
Geng and Liu [170]VIKORUtilizedService supplier selectionUtilized VIKOR for selection of service supplier.
Wu and Liu [171]VIKOR, entropy and fuzzy TOPSISIntegratedSupplier selectionIntegrated VIKOR, entropy and fuzzy TOPSIS for supplier selection.
Alimardani, Hashemkhani Zolfani, Aghdaie and Tamošaitienė [168]VIKOR and SWARAIntegratedSupplier selectionCombined VIKOR and SWARA for selection of supplier in agile environment.
Sarrafha et al. [172]VIKORUtilizedSupply chain networksUsed VIKOR to evaluate of supply chain networks.

4.2.7. Tourism Management

Tourism Management is considered as a next area in VIKOR applications. Tourism Management covers several specific sub-areas including tourism policy and tourism development. Table 8, presented the VIKOR papers addressed within Tourism Management based on author(s) and year, technique and approach, type of study, application area and scope and study purpose. Tzeng et al. [173], combined AHP technique with VIKOR algorithm for selection of restaurant location in Taipei. In this study, five aspects with 11 criteria were used to evaluate restaurant location. Liu et al. [174] integrated the VIKOR, DEMATEL and ANP for implementation of tourism policy, Tsai et al. [175] presented the effective model to evaluate of national park websites, Liu et al. [176] combined the VIKOR, ANP and DEMATEL for improvement of metro–airport connection service, Hsieh et al. [177] presented a model for efficiency and effectiveness of tourist hotel by applying the VIKOR and DEA. In total, 12 papers used the VIKOR technique in the fields of Tourism Management, which presented in Table 8.
Table 8. Distribution of papers in Tourism Management.
Table 8. Distribution of papers in Tourism Management.
Author (s) and YearTechnique and ApproachType of StudyApplication Area and ScopeStudy Purpose
Liu, Tzeng and Lee [174]VIKOR, DEMATEL and ANPIntegrationTourism policyIntegrated VIKOR, DEMATEL and ANP for implementation of tourism policy.
Tsai, Chou and Lai [175]VIKOR, DEMATEL and ANPIntegrationTourism managementPresented the effective model to evaluating of national park websites.
Liu, Tzeng, Lee and Lee [176]VIKOR, ANP and DEMATELIntegratedTourism developmentCombined VIKOR, ANP and DEMATEL for Improvement of metro–airport connection service.
Hsieh, Wang, Huang and Chen [177]VIKOR and DEAIntegratedTouristPresented a model for efficiency and effectiveness of tourist hotel by apply VIKOR and DEA.

4.2.8. Service Quality

Service Quality covers several specific sub-areas including electronic service quality, airline service quality and service quality improvement. Table 9, presented the VIKOR papers addressed within Service Quality based on author (s) and year, technique and approach, type of study, application area and scope and study purpose. Wu et al. [178] measured electronic service quality in social media by using the VIKOR and fuzzy AHP, Liou et al. [179] modified VIKOR for improvement of domestic airline service quality, Kuo [180] proposed a new method for service quality improvement by combining of the VIKOR method, IVFS and GRA, Wang and Pang [181] evaluated the service quality of online auction by applying the fuzzy VIKOR. In total, five past papers used VIKOR technique in the field of Service Quality (presented in Table 9).
Table 9. Distribution of papers in Service Quality.
Table 9. Distribution of papers in Service Quality.
Author (s) and YearTechnique and ApproachType of StudyApplication Area and ScopeStudy Purpose
Wu, Shen and Chang [178]VIKOR and fuzzy AHPIntegrationElectronic service qualityMeasured and evaluated of electronic service quality in social media by used VIKOR and fuzzy AHP.
Kuo and Liang [72]Fuzzy VIKOR and GRAIntegratedService qualityCombined fuzzy VIKOR and GRA for evaluation of service quality.
Liou, Tsai, Lin and Tzeng [179]VIKORModifiedService qualityModified VIKOR for improvement of domestic airline service quality.
Kuo [180]VIKOR, IVFS and GRAProposedService qualityProposed a new method for service quality improvement by combining of VIKOR, IVFS and GRA.
Wang and Pang [181]Fuzzy VIKORUtilizedOnline service qualityEvaluation the service quality of online auction by applied fuzzy VIKOR.

4.2.9. Sustainability and Renewable Energy Fields

Sustainability and renewable energy fields cover several specific sub-areas, including life cycle sustainability assessment, energy resources, environmental management, and environmentally evaluation. Table 10, presented the VIKOR papers addressed within sustainability and renewable energy fields based on author (s) and year, technique and approach, type of study, application area and scope and study purpose. Tzeng, Tsaur, Laiw and Opricovic [5], integrated VIKOR with TOPSIS to identify improvement strategies for residents satisfaction. Results of this study indicated that noise pollution and air quality were the important criteria of environmental quality in Taipei. Vučijak, Kupusović, Midžić-Kurtagić and Ćerić [3] evaluated sustainable hydropower by applying the VIKOR, Quijano H, Botero B and Domínguez B [4] used VIKOR for development of renewable sustainable energy plans, Martin-Utrillas, Juan-Garcia, Canto-Perello and Curiel-Esparza [6] integrated the VIKOR, fuzzy Delphi and AHP for selection of best infrastructure related to sustainable economy, Ren, Manzardo, Mazzi, Zuliani and Scipioni [8] combined the VIKOR and AHP for assessment of life cycle sustainability, Yazdani-Chamzini, Fouladgar, Zavadskas and Moini [7] used the VIKOR, SAW, ARAS, TOPSIS and MOORA for selection of the best renewable energy sources, Civic and Vucijak [9] utilized VIKOR for insulation options for warmth of buildings to increase energy efficiency, Kim and Chung [10] evaluated the vulnerability of the water supply to variability and climate change. In total, 13 past papers used the VIKOR technique in the fields of sustainability and renewable energy, which presented in Table 10.
Table 10. Distribution on papers in Sustainability and Renewable Energy fields.
Table 10. Distribution on papers in Sustainability and Renewable Energy fields.
Author (s) and YearTechnique and ApproachType of StudyApplication Area and ScopeStudy Purpose
Vučijak, Kupusović, Midžić-Kurtagić and Ćerić [3]VIKORUtilizedEnergyEvaluated of sustainable hydropower by applied VIKOR.
Quijano H, Botero B and Domínguez B [4]VIKORUtilizedRenewable sustainable energyUsed VIKOR for development of renewable sustainable energy plans.
Martin-Utrillas, Juan-Garcia, Canto-Perello and Curiel-Esparza [6]VIKOR, fuzzy Delphi and AHPIntegratedSustainable economyIntegrated VIKOR, fuzzy Delphi and AHP for selection of best infrastructure related to sustainable economy.
Vinodh et al. [182]Fuzzy VIKORUtilizedLife cycle assessmentApplied VIKOR for assessment of life cycle and selection of sustainable concept.
Ren, Manzardo, Mazzi, Zuliani and Scipioni [8]VIKOR and AHPIntegrated Life cycle sustainability assessmentCombined VIKOR and AHP for assessment of life cycle sustainability.
Kaya and Kahraman [183]VIKOR and AHPIntegrationRenewable energyIntegrated VIKOR and AHP for determine the optimal renewable energy alternatives.
Yazdani-Chamzini, Fouladgar, Zavadskas and Moini [7]VIKOR, SAW, ARAS, TOPSIS and MOORAIntegratedRenewable energyUsed VIKOR, SAW, ARAS, TOPSIS and MOORA for selection of the best renewable energy sources.
San Cristóbal [184]VIKORUtilizedRenewable energyUsed VIKOR for selection of renewable energy project.
Civic and Vucijak [9]VIKORUtilizedEnergyUtilized VIKOR for insulation options for warmth of buildings to increase energy efficiency.
Sharma et al. [185]VIKOR, TOPSIS and entropyIntegratedEnergy resourcesUsed VIKOR, TOPSIS and entropy for selection the optimal energy resources.
Kim and Chung [10]Fuzzy VIKORUtilizedClimate change and variabilityEvaluated the vulnerability of the water supply to variability and climate change.
Chang and Hsu [186]VIKORUtilizedEnvironmental ManagementApplied VIKOR for ranking of land-use restraint strategies.
Venkata Rao [187]VIKORUtilizedEnvironmentally evaluationApplied VIKOR for evaluation of environmentally in manufacturing programs.

4.2.10. Water Resources Planning

Water Resources Planning is considered as a next area in VIKOR applications. This area of application focused on developing, planning, managing and distributing the optimal usage of water resources. Water Resources Planning can be as a part of water cycle management. Water Resources Planning covers some specific sub-areas such as watershed vulnerability. Opricovic [66], utilized VIKOR technique for assessing of water resources planning. Opricovic [188], presented the fuzzy VIKOR technique to evaluating of water resources planning. Table 11, presented the VIKOR papers addressed within Water Resources Planning based on author(s) and year, technique and approach, type of study, application area and scope and study purpose. Totally, three past papers used VIKOR techniques in fields of Water Resources Planning fields which presented in Table 12. In total, three past papers used VIKOR techniques in fields of Water Resources Planning fields which presented in Table 11.
Table 11. Distribution of papers in Water Resources Planning.
Table 11. Distribution of papers in Water Resources Planning.
Author (s) and YearTechnique and ApproachType of StudyApplication Area and scopeStudy Purpose
Opricovic [66]VIKORUtilizedWater resources planningApplied VIKOR for evaluation of water resources planning.
Opricovic [188]Fuzzy VIKORProposedWater resources planningProposed fuzzy VIKOR for evaluation of water resources planning.
Chang and Hsu [189]VIKORModifiedWatershed vulnerabilityModified VIKOR for classification of land subdivisions based on watershed vulnerability.

4.2.11. Marketing

Marketing covers several specific sub-areas, including brand marketing, portfolio selection, outsourcing providers, and strategy evaluation. Table 12, presented the VIKOR papers addressed within Marketing based on author(s) and year, technique and approach, type of study, application area and scope and study purpose. Tsai, Chou, and Leu [190] combined the VIKOR, ANP and DEMATEL for evaluation of effectiveness in web-based marketing, Wang and Tzeng [191] combined the VIKOR, ANP and DEMATEL for assess of interrelated relationships of brand marketing, Ginevičius, Bruzgė and Podvezko [192] used the VIKOR, SAW and TOPSIS for comparison the help to several businesses and to identify its influence on their development objectively, Chiu, Tzeng and Li [193] improved e-store business by combined the VIKOR, DEMATEL and ANP, Chang, Tsai and Chang [194] integrated the VIKOR, fuzzy AHP (FAHP), GRA and TOPSIS for building the business model, Azimi, Yazdani-Chamzini, Fooladgar and Basiri [195] used the VIKOR and ANP for assessment of strategies of mining sectors, Chen and Chen [196] applied VIKOR for selection of creativity strategy in higher education. In total, 15 past papers used the VIKOR technique in fields of Marketing fields which presented in Table 12.
Table 12. Distribution of papers in marketing.
Table 12. Distribution of papers in marketing.
Author (s) and YearTechnique and ApproachType of StudyApplication Area and ScopeStudy Purpose
Tsai et al. [190]VIKOR, ANP and DEMATELIntegratedWeb-based marketingCombined VIKOR, ANP and DEMATEL for evaluation of effectiveness in web-based marketing.
Wang and Tzeng [191]VIKOR, ANP and DEMATELIntegratedBrand marketingCombined VIKOR, ANP and DEMATEL for assess of interrelated relationships of brand marketing.
Ginevičius, Bruzgė and Podvezko [192]VIKOR, SAW and TOPSISIntegratedMarket developmentUsed VIKOR, SAW and TOPSIS for comparison the help to several businesses and to identify its influence on their development objectively.
Chiu, Tzeng and Li [193]VIKOR, DEMATEL and ANPIntegratede-store businessImproved e-store business by combined VIKOR, DEMATEL and ANP.
Chang, Tsai and Chang [194]VIKOR, FAHP, GRA and TOPSISIntegratedE-book businessIntegrated VIKOR, FAHP, GRA and TOPSIS for building the business model.
Azimi, Yazdani-Chamzini, Fooladgar and Basiri [195]VIKOR and ANPIntegratedStrategy evaluationUsed VIKOR and ANP for assessment of strategies of mining sectors.
Chen and Chen [196]VIKORUtilizedCreativity strategy selectionApplied VIKOR for selection of creativity strategy in higher education.
Liou and Chuang [197]VIKOR, ANP and DEMATELIntegratedOutsourcing providersIntegrated VIKOR, ANP and DEMATEL for selection of outsourcing providers.
Ho et al. [198]VIKOR, ANP and DEMATELIntegratedPortfolio selectionCombined VIKOR, ANP and DEMATEL for selection of portfolio.
Sachdeva et al. [199]VIKORUtilizedLogistic outsourcingUsed VIKOR for analysis of logistic outsourcing problem
Vahdani, Hadipour, Sadaghiani and Amiri [70]VIKORExtendedMaintenance strategy selectionExtended of VIKOR for selection of maintenance strategy.
Chen and Chen [200]VIKORUtilizedInnovative developmentEmployed VIKOR for develop of innovative based on intellectual capital.
Lu et al. [201]VIKOR, ANP and DEMATELIntegratedUser behavior intentionCombined VIKOR, ANP and DEMATEL for examine user behavior intention.
Ahmadi et al. [202]VIKOR, AHP and TOPSISIntegratedMaintenance strategyCombined VIKOR, AHP and TOPSIS for selection of maintenance strategy.
Rostamzadeh et al. [203]Fuzzy VIKORUtilizedAssisting business angelsEmployed fuzzy VIKOR for evaluation of business angels.

4.2.12. Risk and Financial Management

Risk Economics, and Financial management covers specific sub-areas including risks evaluation, information security risk, financial assessment, and financial performance improvement. Table 13, presented the VIKOR papers addressed within Risk and Financial management based on author (s) and year, technique and approach, type of study, application area and scope and study purpose. Liu et al. [204] used the fuzzy VIKOR and TOPSIS for evaluation of risks based on FMEA, Shen and Tzeng [205] combined VIKOR, ANP and DEMATEL for improving financial performance, Lee and Yang [206] combined the VIKOR and ANP for selection of convertible bonds, Peng et al. [207] combined the VIKOR, TOPSIS and PROMETHEE for financial risk prediction, Kou et al. [208] ranked and selected popular clustering algorithms in analysis of financial risk, Mandal et al. [209] utilized the fuzzy VIKOR for identifying and ranking of human error and risk in overhead crane operations, Ginevičius and Podvezko [210] applied VIKOR to assess the financial problems in construction enterprises. There are14 past papers used the VIKOR technique in fields of Risk and Financial management fields which presented in Table 13.
Table 13. Distribution of papers in risk and financial management.
Table 13. Distribution of papers in risk and financial management.
Author (s) and YearTechnique and ApproachType of StudyApplication Area and ScopeStudy Purpose
Liu, Chen, You and Li [204]Fuzzy VIKOR and TOPSISUtilizedRisks evaluationUsed fuzzy VIKOR and TOPSIS for evaluation of risks based on FMEA.
Shen and Tzeng [205]VIKOR, ANP and DEMATELIntegratedFinancial performance improvementCombined VIKOR, ANP and DEMATEL for improve of financial performance.
Lee and Yang [206]VIKOR and ANPIntegratedConvertible bondsCombined VIKOR and ANP for selection of convertible bonds.
Peng, Wang, Kou and Shi [207]VIKOR, TOPSIS and PROMETHEEIntegratedFinancial risk evaluationCombined VIKOR, TOPSIS and PROMETHEE for evaluating of financial risk prediction.
Liu et al. [211]Fuzzy VIKORUtilizedRisk evaluationApplied fuzzy VIKOR for assessment of risk.
Kou, Peng and Wang [208]VIKOR, TOPSIS and DEAIntegrationFinancial riskRanked and selected of popular clustering algorithms in analysis of financial risk.
Safari et al. [212]Fuzzy VIKORUtilizedEnterprise architecture risksApplied fuzzy VIKOR for evaluation of enterprise architecture risks based on FMEA.
Ou Yang et al. [213]VIKORProposedInformation security riskModified VIKOR for improve information security risk.
Mandal, Singh, Behera, Sahu, Raj and Maiti [209]Fuzzy VIKORUtilizedHuman error identification and risk prioritization in overhead crane operationsUtilized fuzzy VIKOR for identify and ranking of human error and risk in overhead crane operations.
Ginevičius and Podvezko [210]VIKORUtilizedFinancial assessmentApplied VIKOR for assessment of financial in construction enterprises.
Emovon et al. [214]VIKOR and entropyIntegratedMarine machinery systems riskIntegrated for ranking of risk in marine machinery systems.
Yang et al. [215]VIKOR, DEMATEL and ANPUtilizedInformation security management riskEvaluated information security risk control by used VIKOR, DEMATEL and ANP.
Yalcin et al. [216]VIKOR, fuzzy AHP and TOPSISIntegratedPerformance evaluationEvaluated financial performance by combined VIKOR, fuzzy AHP and TOPSIS.
Safaei Ghadikolaei et al. [217]Fuzzy VIKOR, fuzzy AHP, ARAS-F, fuzzy COPRASIntegratedFinancial performance evaluationCombined Fuzzy VIKOR, fuzzy AHP, ARAS-F, fuzzy COPRAS for evaluation of financial performance.

4.2.13. Operation Management

Operation Management fieldcovers several specific sub-areas such as; knowledge management; city logistics; concept selection; benchmarking and process performance. Table 14, presented the VIKOR papers addressed within Operation Management based on author (s) and year, technique and approach, type of study, application area and scope and study purpose. Chu et al. [218] evaluated knowledge communities by integrating the VIKOR, TOPSIS and SAW, Bazzazi et al. [219] mixed the VIKOR, AHP and entropy for selection of surface mine equipment, Tadić et al. [220] combined the fuzzy VIKOR, fuzzy DEMATEL and fuzzy ANP for selection of city logistics, Leng et al. [221] proposed a combined decision support method for PMO using the fuzzy VIKOR, Fu, Chu, Chao, Lee, and Liao [222] combined the VIKOR and fuzzy AHP for benchmarking in hotel industry, Büyüközkan and Ruan [223] extended the fuzzy VIKOR for measurement of Enterprise Resource Planning (ERP) software performance. Totally, 10 past papers used VIKOR technique in fields of Operation Management presented in Table 14.
Table 14. Distribution of papers in operation management.
Table 14. Distribution of papers in operation management.
Author (s) and YearTechnique and ApproachType of StudyApplication Area and ScopeStudy Purpose
Chu, Shyu, Tzeng and Khosla [218]VIKOR, TOPSIS and SAWIntegratedKnowledge managementEvaluated of knowledge communities by integrated of VIKOR, TOPSIS and SAW.
Bazzazi, Osanloo and Karimi [219]VIKOR, AHP and entropyIntegratedEquipment selectionMixed VIKOR, AHP and entropy for selection of surface mine equipment.
Tadić, Zečević and Krstić [220]fuzzy VIKOR, fuzzy DEMATEL and fuzzy ANPIntegratedCity logistics concept selectionCombined fuzzy VIKOR, fuzzy DEMATEL and fuzzy ANP for selection of city logistics.
Leng, Jiang and Ding [221]Fuzzy VIKORProposedParts machining outsourcingProposed a combined decision support method for PMO using fuzzy VIKOR.
Fallahpour and Moghassem [224]VIKORUtilizedSpinning preparation parameters selectionEmployed VIKOR for selection of spinning preparation parameters.
Hadi-Vencheh and Mohamadghasemi [225]Fuzzy VIKOR, FWA and fuzzy TOPSISIntegratedMaterial handling equipment selectionCombined Fuzzy VIKOR, FWA and fuzzy TOPSIS for selection of material handling equipment.
Fu et al. [222]VIKOR and fuzzy AHP IntegratedBenchmarkingCombined VIKOR and fuzzy AHP for analysis of benchmarking in hotel industry.
Büyüközkan et al. [226]Fuzzy VIKOR and fuzzy DelphiUtilizedKnowledge managementEmployed fuzzy VIKOR and fuzzy Delphi method for evaluation of KM tools.
Büyüközkan and Ruan [223]Fuzzy VIKOR and Fuzzy DelphiExtendedERP Extended Fuzzy VIKOR for measurement of ERP software performance.
Gauri and Pal [227]VIKOR and GRAUtilizedProcess performanceUsed VIKOR and GRA to optimize of process performance.

4.2.14. Human Resource Management (HRM)

The technique is also applied in Human Resource Management (HRM). HRM fieldcovers different specific sub-areas including corporate social responsibility, HRM evaluation, intellectual capital and customer satisfaction. Table 15, presented the VIKOR papers addressed within HRM based on author(s) and year, technique and approach, type of study, application area and scope and study purpose. Chen et al. [228] combined VIKOR, ANP, and DEMATEL to evaluate companies’ web site by considering of corporate social responsibility, Tsai et al. [229] mixed the VIKOR and ANP for evaluation of entrepreneurship policies, Mazdeh et al. [230] applied the VIKOR and ANP for evaluation of the entrepreneurship intensity, Peng and Tzeng [231] combined the VIKOR, DEMATEL and ANP for solving problem in economics and business, Liu and Wu [77] applied VIKOR and entropy for evaluation of human resources managers’ competency, Wu et al. [232] integrated VIKOR and fuzzy AHP for evaluation of Innovation capital in universities, Celik et al. [233] integrated the fuzzy VIKOR and fuzzy AHP for modelling of trust. The VIKOR technique is applied in 11 papers in the field of HRM as which presented in Table 15.
Table 15. Distribution of papers in human resource management (HRM).
Table 15. Distribution of papers in human resource management (HRM).
Author (s) and yearTechnique and ApproachType of StudyApplication Area and ScopeStudy Purpose
Chen, Tzeng and Chang [228]VIKOR, ANP, and DEMATELIntegratedCorporate social responsibilityCombined VIKOR, ANP, and DEMATEL to evaluate companies’ web site by considering of corporate social responsibility.
Tsai, Lee, Shen and Hwang [229]VIKOR and ANPIntegratedEntrepreneurship policies evaluationMixed VIKOR and ANP for evaluation of entrepreneurship policies.
Mazdeh, Razavi, Hesamamiri, Zahedi and Elahi [230]VIKOR and ANPIntegratedEntrepreneurship intensityApplied VIKOR and ANP for evaluation of the entrepreneurship intensity.
Peng and Tzeng [231]VIKOR, DEMATEL and ANPIntegratedEconomics and business improvementCombined VIKOR, DEMATEL and ANP for improve problem in economics and business.
Baležentis et al. [234]VIKOR, TOPSIS and ARASIntegratedEconomic assessmentIntegrated VIKOR, TOPSIS and ARAS for evaluation of economic sector of Lithuania.
Liu and Wu [77]VIKOR and entropyUtilizedHRM evaluationApplied VIKOR and entropy for evaluation of human resources managers’ competency.
Chen and Tzeng [235]VIKOR, ANP and DEMATELIntegratedTeaching materials evaluationCombined VIKOR, ANP and DEMATEL for evaluation of aspired intelligent for teaching materials.
Wu, Chen and Chen [232]VIKOR and fuzzy AHPIntegratedIntellectual capitalIntegrated VIKOR and fuzzy AHP for evaluation of Innovation capital in universities.
Mohanty and Mahapatra [236]VIKORUtilizedCustomer satisfactionApplied VIKOR for selection of ergonomically designed office chair.
Celik, Aydin and Gumus [233]VIKOR and interval type-2 fuzzy setsIntegrationCustomer satisfactionEvaluated customer satisfaction based on SERVQUAL by used VIKOR and interval type-2 fuzzy sets.
Ashtiani and Azgomi [237]Fuzzy VIKOR and fuzzy AHPIntegratedTrust modellingIntegrated fuzzy VIKOR and fuzzy AHP for modelling of trust.

4.2.15. Other Application Areas

The technique is also applied in other areas such as network selection, process of leachate treatment, flood management, and so on. Table 16, presented the VIKOR papers addressed within Mehbodniya et al. [238] extended fuzzy VIKOR for selection of network, Lee [239] combined VIKOR, DEMATEL and ANP for evaluation of merger and acquisition, Arunachalam et al. [240] used fuzzy VIKOR and AHP for selection of compliant polishing tool, Martin-Utrillas et al. [241] applied VIKOR and Delphi for process of leachate treatment selection, Mousavi et al. [242] extended VIKOR for improve the selection problems, Chitsaz and Banihabib [243] used VIKOR, SAW, TOPSIS M-TOPSIS, AHP, ELECTRE I and ELECTRE III for ranking in-flood management, Milosevic and Naunovic [244] applied VIKOR and fuzzy AHP for selection of sanitary landfill facility location, Pourebrahim et al. [245] combined VIKOR and fuzzy AHP for conservation development in a coastal area, Lee and Tu [246] applied VIKOR, ANP and DEMATEL for evaluation of company value, Lin [247] integrated for VIKOR, DEMATEL and ANP determining product position.
Table 16. Distribution of papers in other application areas.
Table 16. Distribution of papers in other application areas.
Author (s) and YearTechnique and ApproachType of StudyApplication Area and ScopeStudy Purpose
Mehbodniya, Kaleem, Yen and Adachi [238]Fuzzy VIKORExtendedNetwork selectionExtended fuzzy VIKOR for selection of network.
Lee [239]VIKOR, DEMATEL and ANPIntegratedMerger and acquisitionCombined VIKOR, DEMATEL and ANP for evaluation of merger and acquisition.
Tong et al. [248]VIKORUtilizedMulti-response processApplied VIKOR for optimization of multi-response process.
Arunachalam, Idapalapati and Subbiah [240]Fuzzy VIKOR an AHPUtilizedCompliant polishing toolUsed fuzzy VIKOR and AHP for selection of compliant polishing tool.
Martin-Utrillas, Reyes-Medina, Curiel-Esparza and Canto-Perello [241]VIKOR and Delphi methodUtilizedProcess of leachate treatmentApplied VIKOR and Delphi for process of leachate treatment selection.
Mousavi, Jolai and Tavakkoli-Moghaddam [242]VIKORProposedSelection problemsExtended VIKOR for improve the selection problems.
Hsu and Pai [249]VIKORUtilizedFeature selection mechanismUsed VIKOR for selection of feature in data mining.
Chitsaz and Banihabib [243]VIKOR, SAW, TOPSIS M-TOPSIS, AHP, ELECTRE I and ELECTRE IIIUtilizedFlood ManagementUsed VIKOR, SAW, TOPSIS M-TOPSIS, AHP, ELECTRE I and ELECTRE III for ranking of flood management.
Fallahpour and Moghassem [250]VIKORUtilizedRotor SpinningEmployed VIKOR for improve and selection of spinning machine parameters.
BONDOR et al. [251]VIKORUtilizedDiabetic Nephropathy RiskApplied VIKOR for analysis of risk in diabetic nephropathy.
Lee [252]VIKOR, ANP, and DEMATELIntegratedLocation selectionIntegrated VIKOR, ANP, and DEMATEL for location selection.
Milosevic and Naunovic [244]VIKOR and fuzzy AHPUtilizedLandfill facility selectionApplied VIKOR and fuzzy AHP for selection of sanitary landfill facility location.
Kosareva and Krylovas [253]VIKOR, COPRAS and TOPSISIntegratedAccuracyUtilized VIKOR, COPRAS and TOPSIS for compare of accuracy in ranking alternatives.
Pourebrahim, Hadipour, Mokhtar and Taghavi [245]VIKOR and fuzzy AHPIntegratedCoastal assessmentCombined VIKOR and fuzzy AHP for conservation development in a coastal area.
Sun et al. [254]VIKORExtendedPower system restorationExtended VIKOR to presenting of compromise solutions considering hybrid attributes.
Hu et al. [255]VIKOR, ANP and DEMATELIntegratedSmart phone improvementsImproves smart phone for combine VIKOR, ANP and DEMATEL
Yücenur and Demirel [256]Fuzzy VIKORIntegratedInsurance company selectionExtended fuzzy VIKOR for selection of insurance company.
[257]VIKOR and AHPIntegratedForestation areas selectionCombined VIKOR and AHP for selection of forestation areas.
Lee and Tu [246]VIKOR, ANP and DEMATELIntegratedCompany valueApplied VIKOR, ANP and DEMATEL for evaluation of company value.
Peng et al. [258]VIKOR, TOPSIS, PROMETHEE and WSMIntegrationMulticlass classificationUsed VIKOR, TOPSIS, PROMETHEE and WSM for ranking of multiclass classification.
Lin [247]VIKOR, DEMATEL and ANPIntegrationInformation and communications technologyIntegrated for VIKOR, DEMATEL and ANP determining product position.

4.3. Distribution Paper Based on VIKOR and Combined with Other Techniques

This section provides number of papers which applied the VIKOR technique and integrated with other techniques in several application areas. While some of the papers applied exclusively VIKOR or fuzzy VIKOR techniques (34%), most of the papers attempted to integrate or compare the techniques with other techniques such as TOPSIS, ANP, DEMATEL, AHP, GRA, ELECTRE, SWARA, MOORA, fuzzy set theory and so on. Table 17 showed the frequency of VIKOR integrated with other techniques. Results of this table showed that, previous scholars integrated TOPSIS and fuzzy TOPSIS with VIKOR technique more than other techniques.
Table 17. Distribution papers based on techniques integrated or compared with VIKOR.
Table 17. Distribution papers based on techniques integrated or compared with VIKOR.
Techniques Integrated or ComparedN%Techniques Integrated or ComparedN%
TOPSIS and fuzzy TOPSIS3817.67%SAW52.33%
ANP and fuzzy ANP3315.35%Delphi and fuzzy Delphi52.33%
AHP and fuzzy AHP3214.88%COPRAS41.86%
DEMATEL and fuzzy DEMATEL2712.56%weighted sum method (WSM)41.86%
Aggregation operators156.98%SWARA31.40%
Entropy125.58%ARAS31.40%
PROMETHEE 104.65%MULTIMOORA and MOORA31.40%
GRA104.65%DEA31.40%
ELECTRE83.72%Individual VIKOR and fuzzy VIKOR6733.88%

4.4. Distribution Paper Based on Journals Name

Table 18 presents information about journal distribution which is used for this review paper. The selected papers related to the VIKOR technique were found from 83 international scholarly journals most related to MCDM issue extracted from Scopus and Web of Science. From a total 83 journals, journal of Expert Systems with Applications had the first rank with 27 papers. According to this finding; we can revealed that this journal is the most important journal as far as VIKOR technique is concerned. It published more papers related to the VIKOR technique and its application. Journal of Materials and Design is the second with 12 papers; Journal of Technological and Economic Development of Economy was in the third rank with 10 papers, while Journal of Applied Mathematical Modelling with seven papers is in the fourth rank. Journal of The International Journal of Advanced Manufacturing Technology, and International Journal of Applied Soft Computing with six and five papers are in the fifth and sixth rank respectively, while Journal of Quality and Quantity and Journal of Business Economics and Management is in the seventh rank with four papers. The frequency of other published journals is shown in Table 18.
Table 18. Distribution of papers based on the name of journals.
Table 18. Distribution of papers based on the name of journals.
Name of JournalN%
Expert Systems with Applications2715.34%
Materials and Design126.82%
Technological and Economic Development of Economy105.68%
Applied Mathematical Modelling73.98%
The International Journal of Advanced Manufacturing Technology63.41%
Applied Soft Computing52.84%
Quality and Quantity42.27%
Journal of Business Economics and Management42.27%
Journal of civil engineering and management31.70%
International Journal of Management Science and Engineering Management31.70%
Water resources management31.70%
Information sciences31.70%
International Journal of Information Technology and Decision Making31.70%
The Service Industries Journal31.70%
Journal of the Chinese Institute of Engineers31.70%
Soft Computing21.14%
Kybernetes21.14%
Robotics and Computer-Integrated Manufacturing21.14%
International Journal of Production Economics21.14%
Procedia Engineering21.14%
International Journal of Computer Integrated Manufacturing21.14%
International Journal of Production Research21.14%
Tourism Management21.14%
Journal of Intelligent Manufacturing21.14%
Renewable and Sustainable Energy Reviews21.14%
Physical Communication21.14%
Waste Management and Research21.14%
Procedia-Social and Behavioral Sciences10.57%
International Journal of Reliability, Quality and Safety Engineering10.57%
Computers and Industrial Engineering10.57%
Applied Medical Informatics10.57%
International Journal of Computational Intelligence Systems10.57%
Mathematics and Computers in Simulation10.57%
Transport Policy10.57%
Journal of Environmental Management10.57%
Journal of Advanced Manufacturing Systems10.57%
Proceedings of the Institution of Mechanical Engineers, Part L: Journal of Materials Design and Applications10.57%
Knowledge-Based Systems10.57%
Ocean Engineering10.57%
Fibers and Polymers10.57%
Journal of the Textile Institute10.57%
Advances in Mechanical Engineering10.57%
Resources, Conservation and Recycling10.57%
Energy10.57%
Transportation Research Part E: Logistics and Transportation Review10.57%
Applied Financial Economics10.57%
Asia-Pacific Journal of Operational Research10.57%
Energy Systems10.57%
Journal of Air Transport Management10.57%
Waste Management10.57%
Decision Support Systems10.57%
Service business10.57%
International Journal of Sustainable Development and World Ecology10.57%
Tourism Management Perspectives10.57%
Clean Technologies and Environmental Policy10.57%
Higher education10.57%
Advanced Engineering Informatics10.57%
Procedia Materials Science10.57%
Group Decision and Negotiation10.57%
Arabian Journal for Science and Engineering10.57%
Annals of Operations Research10.57%
Omega10.57%
Ocean and Coastal Management10.57%
OPSEARCH10.57%
The International Journal of Life Cycle Assessment10.57%
Ecological Indicators10.57%
Journal of Manufacturing Technology Management10.57%
Renewable Energy10.57%
Computers and Operations Research10.57%
Journal of Cleaner Production10.57%
Engineering Applications of Artificial Intelligence10.57%
Journal of Advanced Ceramics10.57%
Rapid Prototyping Journal10.57%
Applied Energy10.57%
IJCSET10.57%
Journal of Industrial and Production Engineering10.57%
Measurement10.57%
Evaluation and Program Planning10.57%
Computers in Human Behavior10.57%
International Journal of Strategic Property Management10.57%
Journal of Medical Systems10.57%
Proceedings of the Institution of Mechanical Engineers, Part C: Journal of Mechanical Engineering Science10.57%
Transport10.57%
Total176100.00%

4.5. Distribution Paper Based on Publication Year

We found the considerable growth in the number of papers published related to VIKOR technique from 2004 to 2015. From a single article in 2004, the yearly paper published increased to seven papers in 2009. It further increased to 11 and 14 articles in 2010 and 2011 respectively. There is almost 20-fold increase of VIKOR paper published during 2004–2015 period. We may expect that the numbers of published papers related to VIKOR technique will increase in coming years. Cumulative numbers of VIKOR paper published in each year are shown in Figure 3.
Figure 3. Distribution papers based on year of publication (cumulative).
Figure 3. Distribution papers based on year of publication (cumulative).
Sustainability 08 00037 g003

4.6. Distribution of Papers Based on Nationality of Authors

Table 19 provides that; 22 countries and nationalities used VIKOR technique in the several application areas. The technique seems to be more popular in developing and newly industrialised countries. Results in this table indicated that; Taiwan was the first country which published 48 papers (27.27%) related to VIKOR technique. Furthermore, results of this table found that, Iran, China and India have published papers regarding several application areas by using VIKOR technique with 30, 26 and 21 publications respectively. Table 19 presents details regarding the nationality of authors.
Table 19. Distribution of papers based on the authors’ nationality.
Table 19. Distribution of papers based on the authors’ nationality.
Name of CountryNumberPercentage (%)Name of CountryNumberPercentage (%)
Taiwan4827.27%Serbia21.14%
Iran3017.05%Italy21.14%
China2614.77%Yugoslavia10.57%
India2111.93%Serbia and Montenegro10.57%
Turkey126.82%USA10.57%
Lithuania73.98%Colombia10.57%
Japan42.27%Finland10.57%
South Korea42.27%Singapore10.57%
Malaysia42.27%Ireland10.57%
Spain42.27%Romania10.57%
Bosnia and Herzegovina31.70%UK10.57%

5. Concluding Remarks

VIKOR method is one of popular MCDM technique which has increasingly applied by researchers for solving problems in the real worlds. In recent years; several of previous scholars reviewed the MCDM techniques in various fields such as service quality [21], transportation [259], economic [260], MADM/MCDM [21], however; very few studies [261] reviewed and summarized role of VIKOR method and its application in various fields of sciences. Therefore; this review paper aimed to document the role of VIKOR technique and its applications in various fields of science. This review study attempted to review, classify and summarize papers which employed the VIKOR technique in various application areas which published from 2004 to 2015 in 83 international journals accessible in Web of Science and Scopus. In addition, this review paper aimed to classified these published papers into 15 application areas: (1) Manufacturing, (2) Construction Management, (3) Material Selection, (4) Performance Evaluation, (5) Health-Care, (6) Supply Chain, (7) Tourism Management, (8) Service Quality, (9) Sustainability and Renewable Energy, (10) Water Resources Planning, (11) Marketing, (12) Risk and Financial Management, (13) Operation Management, (14) Human Resource Management, (15) Other application areas. In the field of manufacturing, finding indicated that 18 studies have VIKOR technique. Additionally, in the field of material selection, 17 papers have implemented VIKOR technique. Furthermore, in the field of marketing, results showed that 15 researchers have used VIKOR technique. Additionally, in the area of construction management, findings showed that 14 papers have used VIKOR technique. Moreover, from 176 papers, 22 papers were reviewed and classified as other areas, other information related to this classification presented in Table 1.
Based on review findings, 38 studies have integrated VIKOR, TOPSIS and fuzzy TOPSIS in different applications areas, 33 articles combined VIKOR, ANP and fuzzy ANP, in addition, 27 papers mixed VIKOR, DEMATEL and fuzzy DEMATEL In the distribution of journals, the Expert Systems with Applications journal was the first ranked journal among 83 journals with 27 published papers related to the VIKOR technique and its application areas. In the nationality-based classification, it was shown that 22 nationalities and countries applied VIKOR technique in 15 different application areas. Finally, Taiwan was shown to have the highest contribution to the publication of VIKOR technique papers in the 15 application areas.
The current review paper has some implications and limitations for future researches. This paper attempted to classified published paper in 15 different application areas, therefore; we can suggest future work to classify and summarize paper in different fields and sub-fields. As another limitation, this review paper just focused on English international scholarly journal, there are some journals with other languages which were not considered into our paper, although, we believed that current paper presented a comprehensive review paper and included the majority of published papers related to MCDM field. Future study may include other database apart from Scopus and WOS.
The MCDM methods are developed to assist decision making in either ranking a known set of alternatives for a problem or making a choice among this set while considering the conflicting criteria. The preferences of the decision making are elicited either before or during the evaluation of the alternatives and the criteria. The alternatives are compared against each other based on how they perform relative to each criterion. Similarly, some methods require comparison of the criteria to determine the relative importance of each criterion. MCDM methods will then utilize this information to assign ranks to the alternatives. The alternative with the highest rank is selected as the best compromise solution. Furthermore; results of this review found that; VIKOR method was developed for multi-criteria optimization for complex systems, to find a compromise priority ranking of alternatives according to the selected criteria. Compromise solutions for a problem with conflicting criteria can help decision makers identify an acceptable answer. The VIKOR method solves MCDM problems with conflicting or non-commensurable criteria. This method assumes that compromising is acceptable for conflicting resolution. Although the VIKOR method is a popular method applied in multi-criteria analysis, it has some problems when solving MCDM problems. In this regards; our paper attempted to represent some examples about extended, improved, and proposed of this technique for solving MCDM techniques.

Acknowledgments

The authors wish to thank the Universiti Teknologi Malaysia (UTM), Vilnius Gediminas Technical University (VGTU) and University of Southern Denmark for their support.

Author Contributions

The individual contribution and responsibilities of the authors were as follows: Abbas Mardani and Ahmad Jusoh together designed research, Edmundas Kazimieras Zavadskas and Kannan Govindan provided extensive advice throughout the study regarding to abstract, introduction, research design, research methodology, findings and revise the manuscript. The discussion was a team task. Aslan Amat Senin helped to draft, edit, and revise the manuscript. All authors have read and approved the final manuscript.

Conflicts of Interest

The authors declare no conflict of interest.

References

  1. Priemus, H. How to make housing sustainable? The Dutch experience. Environ. Plan. B Plan. Des. 2005, 32, 5–19. [Google Scholar] [CrossRef]
  2. Mardani, A.; Jusoh, A.; Zavadskas, E.K.; Cavallaro, F.; Khalifah, Z. Sustainable and Renewable Energy: An Overview of the Application of Multiple Criteria Decision Making Techniques and Approaches. Sustainability 2015, 7, 13947–13984. [Google Scholar] [CrossRef]
  3. Vučijak, B.; Kupusović, T.; Midžić-Kurtagić, S.; Ćerić, A. Applicability of multicriteria decision aid to sustainable hydropower. Appl. Energy 2013, 101, 261–267. [Google Scholar] [CrossRef]
  4. Quijano, H.R.; Botero, B.S.; Domínguez, B.J. MODERGIS application: Integrated simulation platform to promote and develop renewable sustainable energy plans, Colombian case study. Renew. Sustain. Energy Rev. 2012, 16, 5176–5187. [Google Scholar] [CrossRef]
  5. Tzeng, G.-H.; Tsaur, S.-H.; Laiw, Y.-D.; Opricovic, S. Multicriteria analysis of environmental quality in Taipei: Public preferences and improvement strategies. J. Environ. Manag. 2002, 65, 109–120. [Google Scholar] [CrossRef]
  6. Martin-Utrillas, M.; Juan-Garcia, F.; Canto-Perello, J.; Curiel-Esparza, J. Optimal infrastructure selection to boost regional sustainable economy. Int. J. Sustain. Dev. World Ecol. 2015, 22, 30–38. [Google Scholar] [CrossRef]
  7. Yazdani-Chamzini, A.; Fouladgar, M.M.; Zavadskas, E.K.; Moini, S.H.H. Selecting the optimal renewable energy using multi criteria decision making. J. Bus. Econ. Manag. 2013, 14, 957–978. [Google Scholar] [CrossRef]
  8. Ren, J.; Manzardo, A.; Mazzi, A.; Zuliani, F.; Scipioni, A. Prioritization of bioethanol production pathways in China based on life cycle sustainability assessment and multicriteria decision-making. Int. J. Life Cycle Assess. 2015, 20, 842–853. [Google Scholar] [CrossRef]
  9. Civic, A.; Vucijak, B. Multi-criteria Optimization of Insulation Options for Warmth of Buildings to Increase Energy Efficiency. Procedia Eng. 2014, 69, 911–920. [Google Scholar] [CrossRef]
  10. Kim, Y.; Chung, E.-S. Fuzzy VIKOR approach for assessing the vulnerability of the water supply to climate change and variability in South Korea. Appl. Math. Model. 2013, 37, 9419–9430. [Google Scholar] [CrossRef]
  11. Zavadskas, E.K.; Turskis, Z.; Kildienė, S. State of art surveys of overviews on MCDM/MADM methods. Technol. Econ. Dev. Econ. 2014, 20, 165–179. [Google Scholar] [CrossRef]
  12. Kahraman, C.; Çebı˙, S. A new multi-attribute decision making method: Hierarchical fuzzy axiomatic design. Expert Syst. Appl. 2009, 36 Part 1, 4848–4861. [Google Scholar] [CrossRef]
  13. Valipour, A.; Yahaya, N.; Md Noor, N.; Kildienė, S.; Sarvari, H.; Mardani, A. A fuzzy analytic network process method for risk prioritization in freeway PPP projects: An Iranian case study. J. Civ. Eng. Manag. 2015, 21, 933–947. [Google Scholar] [CrossRef]
  14. Wiecek, M.M.; Ehrgott, M.; Fadel, G.; Rui Figueira, J. Multiple criteria decision making for engineering. Omega 2008, 36, 337–339. [Google Scholar] [CrossRef]
  15. Köksalan, M.M.; Wallenius, J.; Zionts, S. Multiple Criteria Decision Making: From Early History to the 21st Century; World Scientific: Singapore, 2011. [Google Scholar]
  16. Mardani, A.; Jusoh, A.; Zavadskas, E.K. Fuzzy multiple criteria decision-making techniques and applications—Two decades review from 1994 to 2014. Expert Syst. Appl. 2015, 42, 4126–4148. [Google Scholar] [CrossRef]
  17. Mardani, A.; Jusoh, A.; Md Nor, K.; Khalifah, Z.; Zakwan, N.; Valipour, A. Multiple criteria decision-making techniques and their applications—A review of the literature from 2000 to 2014. Econ. Res. Ekon. Istraž. 2015, 28, 516–571. [Google Scholar] [CrossRef]
  18. Keeney, R.L.; Raiffa, H.; Rajala, D.W. Decisions with multiple objectives: Preferences and value trade-offs. IEEE Trans. Syst. Man Cybern. 1979, 9, 403–403. [Google Scholar] [CrossRef]
  19. Hwang, C.-L.; Masud, A.S.M.; Paidy, S.R.; Yoon, K.P. Multiple Objective Decision Making, Methods and Applications: A State-of-the-Art Survey; Springer: Berlin, Germany, 1979; p. 164. [Google Scholar]
  20. Tzeng, G.-H.; Huang, J.-J. Multiple Attribute Decision Making: Methods and Applications; CRC Press: Boca Raton, FL, USA, 2011. [Google Scholar]
  21. Mardani, A.; Jusoh, A.; Zavadskas, E.K.; Khalifah, Z.; Nor, K.M. Application of multiple-criteria decision-making techniques and approaches to evaluating of service quality: A systematic review of the literature. J. Bus. Econ. Manag. 2015, 16, 1034–1068. [Google Scholar] [CrossRef]
  22. Saaty, T.L. The Analytic Hierarchy Process: Planning, Priority Setting, Resources Allocation; McGraw-Hill: New York, NY, USA, 1980. [Google Scholar]
  23. Zeleny, M.; Cochrane, J.L. Multiple Criteria Decision Making; McGraw-Hill: New York, NY, USA, 1982; Volume 25. [Google Scholar]
  24. Hwang, C.-L.; Lin, M.-J. Group Decision Making under Multiple Criteria; Springer: Berlin, Germany, 1987. [Google Scholar]
  25. Roy, B. Multicriteria Methodology for Decision Aiding; Springer: Berlin, Germany, 1996; p. 12. [Google Scholar]
  26. Belton, V.; Stewart, T. Multiple Criteria Decision Analysis: An Integrated Approach; Springer: Berlin, Germany, 2002. [Google Scholar]
  27. Gal, T.; Stewart, T.; Hanne, T. Multicriteria Decision Making: Advances in MCDM Models, Algorithms, Theory, and Applications; Da Capo Press: Cambridge, MA, USA, 1999; p. 21. [Google Scholar]
  28. Miettinen, K. Nonlinear Multiobjective Optimization; Springer: Berlin, Germany, 1999; p. 12. [Google Scholar]
  29. Brauers, W.K. Optimization Methods for a Stakeholder Society, a Revolution in Economic Thinking by Multi-Objective Optimization; Nonconvex Optimization and Its Applications; Kluwer Academic Publishers: Boston, MA, USA; Dordrecht, The Netherlands; London, UK, 2004; p. 342. [Google Scholar]
  30. Saaty, T.L. Decision Making with Dependence and Feedback: The Analytic Network Process; RWS Publisher: Pittsburgh, PA, USA, 1996. [Google Scholar]
  31. Opricovic, S. Multicriteria optimization of civil engineering systems. Fac. Civ. Eng. Belgrade 1998, 2, 5–21. [Google Scholar]
  32. Opricovic, S.; Tzeng, G.H. Multicriteria planning of post-earthquake sustainable reconstruction. Comput. Aided Civ. Infrastruct. Eng. 2002, 17, 211–220. [Google Scholar] [CrossRef]
  33. Hwang, C.; Yoon, K. Multiple Attribute Decision Making: Methods and Applications, A State of the Art Survey; Sprinnger-Verlag: New York, NY, USA, 1981. [Google Scholar]
  34. MacCrimmon, K.R. Decisionmaking among Multiple-Attribute Alternatives: A Survey and Consolidated Approach; DTIC Document; DTIC: Fairfax, VA, USA, 1968. [Google Scholar]
  35. Saaty, T.L. On polynomials and crossing numbers of complete graphs. J. Comb. Theory A 1971, 10, 183–184. [Google Scholar] [CrossRef]
  36. Saaty, T.L. What is the Analytic Hierarchy Process? Springer: Berlin, Germany, 1988. [Google Scholar]
  37. Fontela, E.; Gabus, A. The DEMATEL Observer; DEMATEL 1976 Report; Battelle Geneva Research Center: Geneva, Switzerland, 1976. [Google Scholar]
  38. Mareschal, B.; Brans, J.P.; Vincke, P. PROMETHEE: A New Family of Outranking Methods in Multicriteria Analysis; ULB-Universite Libre de Bruxelles: Brussels, Belgium, 1984. [Google Scholar]
  39. Charnes, A.; Cooper, W.W.; Rhodes, E. Measuring the efficiency of decision making units. Eur. J. Oper. Res. 1978, 2, 429–444. [Google Scholar] [CrossRef]
  40. Charnes, A. Data envelopment Analysis: Theory, Methodology and Applications; Springer: Berlin, Germany, 1994. [Google Scholar]
  41. Roy, B. Classement et choix en présence de points de vue multiples. RAIRO Oper. Res. Rech. Opér. 1968, 2, 57–75. [Google Scholar]
  42. Roy, B. Problems and methods with multiple objective functions. Math. Program. 1971, 1, 239–266. [Google Scholar] [CrossRef]
  43. Roy, B.; Bertier, P. La méthode ELECTRE II/une application au media planning. In Proceedings of the 6th International Conference on Operation Research, Dublin, Ireland, 21–25 August 1972.
  44. Roy, B. ELECTRE III: Un algorithme de classements fondé sur une représentation floue des préférences en présence de criteres multiples. Cah. CERO. 1978, 20, 3–24. [Google Scholar]
  45. Figueira, J.R.; Greco, S.; Słowiński, R. Building a set of additive value functions representing a reference preorder and intensities of preference: GRIP method. Eur. J. Oper. Res. 2009, 195, 460–486. [Google Scholar] [CrossRef]
  46. Zavadskas, E.K.; Kaklauskas, A.; Sarka, V. The new method of multicriteria complex proportional assessment of projects. Technol. Econ. Dev. Econ. 1994, 1, 131–139. [Google Scholar]
  47. Zavadskas, E.K.; Antucheviciene, J. Multiple criteria evaluation of rural building’s regeneration alternatives. Build. Environ. 2007, 42, 436–451. [Google Scholar] [CrossRef]
  48. Zavadskas, E.K.; Kaklauskas, A.; Turskis, Z.; Tamošaitiene, J. Selection of the effective dwelling house walls by applying attributes values determined at intervals. J. Civ. Eng. Manag. 2008, 14, 85–93. [Google Scholar] [CrossRef]
  49. Turskis, Z.; Zavadskas, E.K. A novel method for multiple criteria analysis: Grey additive ratio assessment (ARAS-G) method. Informatica 2010, 21, 597–610. [Google Scholar]
  50. Zavadskas, E.K.; Turskis, Z. A new additive ratio assessment (ARAS) method in multicriteria decision-making. Technol. Econ. Dev. Econ. 2010, 16, 159–172. [Google Scholar] [CrossRef]
  51. Brauers, W.K.M.; Zavadskas, E.K. The MOORA method and its application to privatization in a transition economy. Control Cybern. 2006, 35, 445–469. [Google Scholar]
  52. Brauers, W.K.M.; Zavadskas, E.K. Comparative analysis of MOORA, MULTIMOORA, VIKOR and TOPSIS for MOP. In Proceedings of the 9th International Conference on Multiple Objective Programming and Goal Programming (MOPGP ’10): Book of Abstracts, Sfax, Tunisia, 24–26 May 2010; University of Sfax: Sfax, Tunisia, 2010; p. 51. [Google Scholar]
  53. Keršuliene, V.; Zavadskas, E.K.; Turskis, Z. Selection of rational dispute resolution method by applying new step-wise weight assessment ratio analysis (Swara). J. Bus. Econ. Manag. 2010, 11, 243–258. [Google Scholar] [CrossRef]
  54. Zavadskas, E.K.; Turskis, Z.; Antucheviciene, J.; Zakarevicius, A. Optimization of weighted aggregated sum product assessment. Elektron. Elektrotech. 2012, 122, 3–6. [Google Scholar] [CrossRef]
  55. Opricovic, S.; Tzeng, G.-H. Defuzzification within a multicriteria decision model. Int. J. Uncertain. Fuzziness Knowl. Based Syst. 2003, 11, 635–652. [Google Scholar] [CrossRef]
  56. Opricovic, S.; Tzeng, G.-H. Fuzzy multicriteria model for postearthquake land-use planning. Nat. Hazards Rev. 2003, 4, 59–64. [Google Scholar] [CrossRef]
  57. Opricovic, S.; Tzeng, G.-H. Compromise solution by MCDM methods: A comparative analysis of VIKOR and TOPSIS. Eur. J. Oper. Res. 2004, 156, 445–455. [Google Scholar] [CrossRef]
  58. Tzeng, G.-H.; Lin, C.-W.; Opricovic, S. Multi-criteria analysis of alternative-fuel buses for public transportation. Energy Policy 2005, 33, 1373–1383. [Google Scholar] [CrossRef]
  59. Opricovic, S. A fuzzy compromise solution for multicriteria problems. Int. J. Uncertain. Fuzziness Knowl. Based Syst. 2007, 15, 363–380. [Google Scholar] [CrossRef]
  60. Opricovic, S.; Tzeng, G.-H. Extended VIKOR method in comparison with outranking methods. Eur. J. Oper. Res. 2007, 178, 514–529. [Google Scholar] [CrossRef]
  61. Chen, L.Y.; Wang, T.-C. Optimizing partners’ choice in IS/IT outsourcing projects: The strategic decision of fuzzy VIKOR. Int. J. Prod. Econ. 2009, 120, 233–242. [Google Scholar] [CrossRef]
  62. Opricovic, S. Compromise in cooperative game and the VIKOR method. Yugosl. J. Oper. Res. 2009, 19, 225–238. [Google Scholar] [CrossRef] [Green Version]
  63. Huang, J.-J.; Tzeng, G.-H.; Liu, H.-H. A revised VIKOR model for multiple criteria decision making—The Perspective of Regret Theory. In Cutting-Edge Research Topics on Multiple Criteria Decision Making; Springer: Berlin, Germany, 2009; pp. 761–768. [Google Scholar]
  64. Moeinzadeh, P.; Hajfathaliha, A. A combined fuzzy decision making approach to supply chain risk assessment. World Acad. Sci. Eng. Technol. 2009, 60, 519–535. [Google Scholar]
  65. Sayadi, M.K.; Heydari, M.; Shahanaghi, K. Extension of VIKOR method for decision making problem with interval numbers. Appl. Math. Model. 2009, 33, 2257–2262. [Google Scholar] [CrossRef]
  66. Opricovic, S. A compromise solution in water resources planning. Water Resour. Manag. 2009, 23, 1549–1561. [Google Scholar] [CrossRef]
  67. Chang, C.-L. A modified VIKOR method for multiple criteria analysis. Environ. Monit. Assess. 2010, 168, 339–344. [Google Scholar] [CrossRef] [PubMed]
  68. Heydari, M.; Kazem Sayadi, M.; Shahanaghi, K. Extended VIKOR as a new method for solving Multiple Objective Large-Scale Nonlinear Programming problems. RAIRO Oper. Res. 2010, 44, 139–152. [Google Scholar] [CrossRef]
  69. Sanayei, A.; Mousavi, S.F.; Yazdankhah, A. Group decision making process for supplier selection with VIKOR under fuzzy environment. Expert Syst. Appl. 2010, 37, 24–30. [Google Scholar] [CrossRef]
  70. Vahdani, B.; Hadipour, H.; Sadaghiani, J.S.; Amiri, M. Extension of VIKOR method based on interval-valued fuzzy sets. Int. J. Adv. Manuf. Technol. 2010, 47, 1231–1239. [Google Scholar] [CrossRef]
  71. Devi, K. Extension of VIKOR method in intuitionistic fuzzy environment for robot selection. Expert Syst. Appl. 2011, 38, 14163–14168. [Google Scholar] [CrossRef]
  72. Kuo, M.-S.; Liang, G.-S. Combining VIKOR with GRA techniques to evaluate service quality of airports under fuzzy environment. Expert Syst. Appl. 2011, 38, 1304–1312. [Google Scholar] [CrossRef]
  73. Park, J.H.; Cho, H.J.; Kwun, Y.C. Extension of the VIKOR method for group decision making with interval-valued intuitionistic fuzzy information. Fuzzy Optim. Decis. Mak. 2011, 10, 233–253. [Google Scholar] [CrossRef]
  74. Liu, P.; Wang, M. An extended VIKOR method for multiple attribute group decision making based on generalized interval-valued trapezoidal fuzzy numbers. Sci. Res. Essays. 2011, 6, 766–776. [Google Scholar]
  75. Du, Y.; Liu, P. Extended fuzzy VIKOR method with intuitionistic trapezoidal fuzzy numbers. Inf. Int. Interdiscip. J. 2011, 14, 2575–2583. [Google Scholar]
  76. Su, Z.-X. A hybrid fuzzy approach to fuzzy multi-attribute group decision-making. Int. J. Inf. Technol. Decis. Mak. 2011, 10, 695–711. [Google Scholar] [CrossRef]
  77. Liu, P.; Wu, X. A competency evaluation method of human resources managers based on multi-granularity linguistic variables and VIKOR method. Technol. Econ. Dev. Econ. 2012, 18, 696–710. [Google Scholar] [CrossRef]
  78. Liu, H.-C.; Mao, L.-X.; Zhang, Z.-Y.; Li, P. Induced aggregation operators in the VIKOR method and its application in material selection. Appl. Mat. Model. 2013, 37, 6325–6338. [Google Scholar] [CrossRef]
  79. Liao, H.; Xu, Z. A VIKOR-based method for hesitant fuzzy multi-criteria decision making. Fuzzy Optim. Decis. Mak. 2013, 12, 373–392. [Google Scholar] [CrossRef]
  80. Wan, S.-P.; Wang, Q.-Y.; Dong, J.-Y. The extended VIKOR method for multi-attribute group decision making with triangular intuitionistic fuzzy numbers. Knowl. Based Syst. 2013, 52, 65–77. [Google Scholar] [CrossRef]
  81. Zhao, X.; Tang, S.; Yang, S.; Huang, K. Extended VIKOR method based on cross-entropy for interval-valued intuitionistic fuzzy multiple criteria group decision making. J. Intell. Fuzzy Syst. Appl. Eng. Technol. 2013, 25, 1053–1066. [Google Scholar]
  82. Tan, C.; Chen, X. Interval-Valued Intuitionistic Fuzzy Multicriteria Group Decision Making Based on VIKOR and Choquet Integral. J. Appl. Math. 2013, 2013, Article 656879. [Google Scholar] [CrossRef]
  83. Vinodh, S.; Varadharajan, A.R.; Subramanian, A. Application of fuzzy VIKOR for concept selection in an agile environment. Int. J. Adv. Manufa. Technol. 2013, 65, 825–832. [Google Scholar] [CrossRef]
  84. Ju, Y.; Wang, A. Extension of VIKOR method for multi-criteria group decision making problem with linguistic information. Appl. Math. Model. 2013, 37, 3112–3125. [Google Scholar] [CrossRef]
  85. Zhang, N.; Wei, G. Extension of VIKOR method for decision making problem based on hesitant fuzzy set. Appl. Math. Model. 2013, 37, 4938–4947. [Google Scholar] [CrossRef]
  86. Park, J.H.; Cho, H.J.; Kwun, Y.C. Extension of the VIKOR method to dynamic intuitionistic fuzzy multiple attribute decision making. Comput. Math. Appl. 2013, 65, 731–744. [Google Scholar] [CrossRef]
  87. Wei, G.; Zhang, N. A multiple criteria hesitant fuzzy decision making with Shapley value-based VIKOR method. J. Intell. Fuzzy Syst. Appl. Eng. Technol. 2014, 26, 1065–1075. [Google Scholar]
  88. Hajiagha, S.H.R.; Mahdiraji, H.A.; Zavadskas, E.K.; Hashemi, S.S. Fuzzy Multi-Objective Linear Programming Based on Compromise VIKOR Method. Int. J. Inf. Technol. Decis. Mak. 2014, 13, 679–698. [Google Scholar] [CrossRef]
  89. Pai, P.-F.; Chen, C.-T.; Hung, W.-Z. Applying linguistic information and intersection concept to improve effectiveness of multi-criteria decision analysis technology. Int. J. Inf. Technol. Decis. Mak. 2014, 13, 291–315. [Google Scholar] [CrossRef]
  90. Keshavarz Ghorabaee, M.; Zavadskas, E.K.; Amiri, M.; Sadaghiani, J.S. Multi-Criteria Project Selection Using an Extended VIKOR Method with Interval Type-2 Fuzzy Sets. Int. J. Inf. Technol. Decis. Mak. 2015, 14, 993–1016. [Google Scholar] [CrossRef]
  91. You, X.-Y.; You, J.-X.; Liu, H.-C.; Zhen, L. Group multi-criteria supplier selection using an extended VIKOR method with interval 2-tuple linguistic information. Expert Syst. Appl. 2015, 42, 1906–1916. [Google Scholar] [CrossRef]
  92. Li, Q.; Zhao, N. Stochastic interval-grey number VIKOR method based on prospect theory. Grey Syst. Theory Appl. 2015, 5, 105–116. [Google Scholar] [CrossRef]
  93. Qin, J.; Liu, X.; Pedrycz, W. An extended VIKOR method based on prospect theory for multiple attribute decision making under interval type-2 fuzzy environment. Knowl. Based Syst. 2015, 86, 116–130. [Google Scholar] [CrossRef]
  94. Zhu, G.-N.; Hu, J.; Qi, J.; Gu, C.-C.; Peng, Y.-H. An integrated AHP and VIKOR for design concept evaluation based on rough number. Adv. Eng. Inform. 2015, 29, 408–418. [Google Scholar] [CrossRef]
  95. Keshavarz Ghorabaee, M. Developing an MCDM method for robot selection with interval type-2 fuzzy sets. Robot. Comput. Integr. Manuf. 2015, 37, 221–232. [Google Scholar] [CrossRef]
  96. Bausys, R.; Zavadskas, E.K. Multicriteria decision making approach by VIKOR under interval neutrosophic set environment. Econ. Comput. Econ. Cybern. Stud. Res. 2015, 49, 33–48. [Google Scholar]
  97. Anvari, A.; Zulkifli, N.; Arghish, O. Application of a modified VIKOR method for decision-making problems in lean tool selection. Int. J. Adv. Manuf. Technol. 2014, 71, 829–841. [Google Scholar] [CrossRef]
  98. Tranfield, D.R.; Denyer, D.; Smart, P. Towards a methodology for developing evidence-informed management knowledge by means of systematic review. Br. J. Manag. 2003, 14, 207–222. [Google Scholar] [CrossRef]
  99. Denyer, D.; Tranfield, D. Producing a systematic review. In The SAGE Handbook of Organizational Research Methods; Buchanan, D.A., Bryman, A., Eds.; SAGE Publications Ltd.: London, UK, 2009; pp. 671–689. [Google Scholar]
  100. Behzadian, M.; Khanmohammadi Otaghsara, S.; Yazdani, M.; Ignatius, J. A state-of the-art survey of TOPSIS applications. Expert Syst. Appl. 2012, 39, 13051–13069. [Google Scholar] [CrossRef]
  101. Liu, H.-C.; You, J.-X.; You, X.-Y.; Shan, M.-M. A novel approach for failure mode and effects analysis using combination weighting and fuzzy VIKOR method. Appl. Soft Comput. 2015, 28, 579–588. [Google Scholar] [CrossRef]
  102. Peng, J.-P.; Yeh, W.-C.; Lai, T.-C.; Hsu, C.-B. The incorporation of the Taguchi and the VIKOR methods to optimize multi-response problems in intuitionistic fuzzy environments. J. Chin. Inst. Eng. 2015, 37, 897–907. [Google Scholar] [CrossRef]
  103. Tzeng, G.-H.; Huang, C.-Y. Combined DEMATEL technique with hybrid MCDM methods for creating the aspired intelligent global manufacturing and logistics systems. Ann. Oper. Res. 2012, 197, 159–190. [Google Scholar] [CrossRef]
  104. Mousavi, S.M.; Torabi, S.A.; Tavakkoli-Moghaddam, R. A hierarchical group decision-making approach for new product selection in a fuzzy environment. Arab. J. Sci. Eng. 2013, 38, 3233–3248. [Google Scholar] [CrossRef]
  105. Büyüközkan, G.; Görener, A. Evaluation of product development partners using an integrated AHP-VIKOR model. Kybernetes 2015, 44, 220–237. [Google Scholar] [CrossRef]
  106. Vinodh, S.; Sarangan, S.; Vinoth, S.C. Application of fuzzy compromise solution method for fit concept selection. Appl. Math. Model. 2014, 38, 1052–1063. [Google Scholar] [CrossRef]
  107. Chatterjee, P.; Athawale, V.M.; Chakraborty, S. Selection of industrial robots using compromise ranking and outranking methods. Robot. Comput. Integr. Manuf. 2010, 26, 483–489. [Google Scholar] [CrossRef]
  108. Parameshwaran, R.; Praveen Kumar, S.; Saravanakumar, K. An integrated fuzzy MCDM based approach for robot selection considering objective and subjective criteria. Appl. Soft Comput. 2015, 26, 31–41. [Google Scholar] [CrossRef]
  109. Bairagi, B.; Dey, B.; Sarkar, B.; Sanyal, S. Selection of robot for automated foundry operations using fuzzy multi-criteria decision making approaches. Int. J. Manag. Sci. Eng. Manag. 2014, 9, 221–232. [Google Scholar] [CrossRef]
  110. Wang, C.-H.; Wu, C.-W. Combining conjoint analysis with Kano model to optimize product varieties of smart phones: A VIKOR perspective. J. Ind. Prod. Eng. 2014, 31, 177–186. [Google Scholar] [CrossRef]
  111. Feng, Y.-X.; Gao, Y.-C.; Song, X.; Tan, J.-R. Equilibrium design based on design thinking solving: An integrated multicriteria decision-making methodology. Adv. Mech. Eng. 2013, 5, 125291. [Google Scholar] [CrossRef]
  112. Zhang, S.; Xu, J. Transmission system accuracy optimum allocation for multiaxis machine tools’ scheme design. Proc. Inst. Mech. Eng. C J. Mech. Eng. Sci. 2013, 227, 2762–2779. [Google Scholar]
  113. Chaturvedi, V.; Singh, D. Multi Response Optimization of Process Parameters of Abrasive Water Jet Machining for Stainless Steel AISI 304 Using VIKOR Approach Coupled with Signal to Noise Ratio Methodology. J. Adv. Manuf. Syst. 2015, 14, 107–121. [Google Scholar] [CrossRef]
  114. Vinodh, S.; Nagaraj, S.; Girubha, J. Application of Fuzzy VIKOR for selection of rapid prototyping technologies in an agile environment. Rapid Prototyp. J. 2014, 20, 523–532. [Google Scholar] [CrossRef]
  115. Peng, Y. Regional earthquake vulnerability assessment using a combination of MCDM methods. Ann. Oper. Res. 2015, 234, 95–110. [Google Scholar] [CrossRef]
  116. Zolfani, S.H.; Esfahani, M.H.; Bitarafan, M.; Zavadskas, E.K.; Arefi, S.L. Developing a new hybrid MCDM method for selection of the optimal alternative of mechanical longitudinal ventilation of tunnel pollutants during automobile accidents. Transport 2013, 28, 89–96. [Google Scholar] [CrossRef]
  117. Ginevičius, R.; Podvezko, V.; Raslanas, S. Evaluating the alternative solutions of wall insulation by multicriteria methods. J. Civ. Eng. Manag. 2008, 14, 217–226. [Google Scholar] [CrossRef]
  118. Zavadskas, E.K.; Antuchevičiene, J. Evaluation of buildings’ redevelopment alternatives with an emphasis on the multipartite sustainability. Int. J. Strateg. Prop. Manag. 2004, 8, 121–128. [Google Scholar]
  119. Mela, K.; Tiainen, T.; Heinisuo, M. Comparative study of multiple criteria decision making methods for building design. Adv. Eng. Inform. 2012, 26, 716–726. [Google Scholar] [CrossRef]
  120. Pamučar, D.; Ćirović, G. The selection of transport and handling resources in logistics centers using Multi-Attributive Border Approximation area Comparison (MABAC). Expert Syst. Appl. 2015, 42, 3016–3028. [Google Scholar] [CrossRef]
  121. Ebrahimnejad, S.; Mousavi, S.; Tavakkoli-Moghaddam, R.; Hashemi, H.; Vahdani, B. A novel two-phase group decision making approach for construction project selection in a fuzzy environment. Appl. Math. Model. 2012, 36, 4197–4217. [Google Scholar] [CrossRef]
  122. Abbasianjahromi, H.; Rajaie, H.; Shakeri, E. A framework for subcontractor selection in the construction industry. J. Civ. Eng. Manag. 2013, 19, 158–168. [Google Scholar] [CrossRef]
  123. Mohammadi, F.; Sadi, M.K.; Nateghi, F.; Abdullah, A.; Skitmore, M. A hybrid quality function deployment and cybernetic analytic network process model for project manager selection. J. Civ. Eng. Manag. 2014, 20, 795–809. [Google Scholar] [CrossRef]
  124. Lanjewar, P.B.; Rao, R.; Kale, A. Assessment of alternative fuels for transportation using a hybrid graph theory and analytic hierarchy process method. Fuel 2015, 154, 9–16. [Google Scholar] [CrossRef]
  125. Vučijak, B.; Pašić, M.; Zorlak, A. Use of Multi-criteria Decision Aid Methods for Selection of the Best Alternative for the Highway Tunnel Doors. Procedia Eng. 2015, 100, 656–665. [Google Scholar] [CrossRef]
  126. Tošić, N.; Marinković, S.; Dašić, T.; Stanić, M. Multicriteria optimization of natural and recycled aggregate concrete for structural use. J. Clean. Prod. 2015, 87, 766–776. [Google Scholar] [CrossRef]
  127. Vahdani, B.; Mousavi, S.M.; Hashemi, H.; Mousakhani, M.; Tavakkoli-Moghaddam, R. A new compromise solution method for fuzzy group decision-making problems with an application to the contractor selection. Eng. Appl. Artif. Intell. 2013, 26, 779–788. [Google Scholar] [CrossRef]
  128. Bashiri, M.; Mirzaei, M.; Randall, M. Modeling fuzzy capacitated p-hub center problem and a genetic algorithm solution. Appl. Math. Model. 2013, 37, 3513–3525. [Google Scholar] [CrossRef]
  129. Hsu, C.-H.; Wang, F.-K.; Tzeng, G.-H. The best vendor selection for conducting the recycled material based on a hybrid MCDM model combining DANP with VIKOR. Resour. Conserv. Recycl. 2012, 66, 95–111. [Google Scholar] [CrossRef]
  130. Chatterjee, P.; Athawale, V.M.; Chakraborty, S. Selection of materials using compromise ranking and outranking methods. Mater. Des. 2009, 30, 4043–4053. [Google Scholar] [CrossRef]
  131. Chauhan, A.; Vaish, R. Magnetic material selection using multiple attribute decision making approach. Mater. Des. 2012, 36, 1–5. [Google Scholar] [CrossRef]
  132. Çalışkan, H.; Kurşuncu, B.; Kurbanoğlu, C.; Güven, Ş.Y. Material selection for the tool holder working under hard milling conditions using different multi criteria decision making methods. Mater. Des. 2013, 45, 473–479. [Google Scholar] [CrossRef]
  133. Çalışkan, H. Selection of boron based tribological hard coatings using multi-criteria decision making methods. Mater. Des. 2013, 50, 742–749. [Google Scholar] [CrossRef]
  134. Yazdani, M.; Payam, A.F. A comparative study on material selection of microelectromechanical systems electrostatic actuators using Ashby, VIKOR and TOPSIS. Mater. Des. 2015, 65, 328–334. [Google Scholar] [CrossRef]
  135. Anojkumar, L.; Ilangkumaran, M.; Sasirekha, V. Comparative analysis of MCDM methods for pipe material selection in sugar industry. Expert Systems with Applications. 2014, 41, 2964–2980. [Google Scholar] [CrossRef]
  136. Jahan, A.; Mustapha, F.; Ismail, M.Y.; Sapuan, S.; Bahraminasab, M. A comprehensive VIKOR method for material selection. Mater. Des. 2011, 32, 1215–1221. [Google Scholar] [CrossRef]
  137. Bahraminasab, M.; Jahan, A. Material selection for femoral component of total knee replacement using comprehensive VIKOR. Mater. Des. 2011, 32, 4471–4477. [Google Scholar] [CrossRef]
  138. Girubha, R.J.; Vinodh, S. Application of fuzzy VIKOR and environmental impact analysis for material selection of an automotive component. Mater. Des. 2012, 37, 478–486. [Google Scholar] [CrossRef]
  139. Cavallini, C.; Giorgetti, A.; Citti, P.; Nicolaie, F. Integral aided method for material selection based on quality function deployment and comprehensive VIKOR algorithm. Mater. Des. 2013, 47, 27–34. [Google Scholar] [CrossRef]
  140. Jahan, A.; Edwards, K. VIKOR method for material selection problems with interval numbers and target-based criteria. Mater. Des. 2013, 47, 759–765. [Google Scholar] [CrossRef]
  141. Liu, H.-C.; You, J.-X.; Zhen, L.; Fan, X.-J. A novel hybrid multiple criteria decision making model for material selection with target-based criteria. Mater. Des. 2014, 60, 380–390. [Google Scholar] [CrossRef]
  142. Ray, A. Cutting Fluid Selection for Sustainable Design for Manufacturing: An Integrated Theory. Procedia Mater. Sci. 2014, 6, 450–459. [Google Scholar]
  143. Chauhan, A.; Vaish, R.; Bowen, C. Piezoelectric material selection for ultrasonic transducer and actuator applications. Proc. Inst. Mech. Eng. L J. Mater. Des. Appl. 2015, 229, 3–12. [Google Scholar] [CrossRef]
  144. Vats, G.; Vaish, R. Piezoelectric material selection for transducers under fuzzy environment. J. Adv. Ceram. 2013, 2, 141–148. [Google Scholar] [CrossRef]
  145. Rezaie, K.; Ramiyani, S.S.; Nazari-Shirkouhi, S.; Badizadeh, A. Evaluating performance of Iranian cement firms using an integrated fuzzy AHP–VIKOR method. Appl. Math. Model. 2014, 38, 5033–5046. [Google Scholar] [CrossRef]
  146. Wu, H.-Y.; Lin, Y.-K.; Chang, C.-H. Performance evaluation of extension education centers in universities based on the balanced scorecard. Evalaluation Program Plan. 2011, 34, 37–50. [Google Scholar] [CrossRef] [PubMed]
  147. Wu, H.-Y.; Tzeng, G.-H.; Chen, Y.-H. A fuzzy MCDM approach for evaluating banking performance based on Balanced Scorecard. Expert Syst. Appl. 2009, 36, 10135–10147. [Google Scholar] [CrossRef]
  148. Chen, J.-K.; Chen, I.-S. Aviatic innovation system construction using a hybrid fuzzy MCDM model. Expert Syst. Appl. 2010, 37, 8387–8394. [Google Scholar] [CrossRef]
  149. Zolfani, S.H.; Ghadikolaei, A.S. Performance evaluation of private universities based on balanced scorecard: Empirical study based on Iran. J. Bus. Econ. Manag. 2013, 14, 696–714. [Google Scholar] [CrossRef]
  150. Hsu, L.-C. A hybrid multiple criteria decision-making model for investment decision making. J. Bus. Econ. Manag. 2014, 15, 509–529. [Google Scholar] [CrossRef]
  151. Hsu, L.-C. Using a decision-making process to evaluate efficiency and operating performance for listed semiconductor companies. Technol. Econ. Dev. Econ. 2015, 21, 301–331. [Google Scholar] [CrossRef]
  152. Tsai, P.-H.; Chang, S.-C. Comparing the Apple iPad and non-Apple camp tablet PCs: A multicriteria decision analysis. Technol. Econ. Dev. Econ. 2013, 19, 256–284. [Google Scholar] [CrossRef]
  153. Wu, H.-Y.; Chen, J.-K.; Chen, I.-S.; Zhuo, H.-H. Ranking universities based on performance evaluation by a hybrid MCDM model. Measurement 2012, 45, 856–880. [Google Scholar] [CrossRef]
  154. Kuo, M.-S.; Liang, G.-S. A soft computing method of performance evaluation with MCDM based on interval-valued fuzzy numbers. Appl. Soft Comput. 2012, 12, 476–485. [Google Scholar] [CrossRef]
  155. Chou, Y.-C.; Yen, H.-Y.; Sun, C.-C. An integrate method for performance of women in science and technology based on entropy measure for objective weighting. Qual. Quant. 2014, 48, 157–172. [Google Scholar] [CrossRef]
  156. Ranjan, R.; Chatterjee, P.; Chakraborty, S. Evaluating performance of engineering departments in an Indian University using DEMATEL and compromise ranking methods. Opsearch 2015, 52, 307–328. [Google Scholar] [CrossRef]
  157. Dincer, H.; Hacioglu, U. Performance evaluation with fuzzy VIKOR and AHP method based on customer satisfaction in Turkish banking sector. Kybernetes 2013, 42, 1072–1085. [Google Scholar] [CrossRef]
  158. Lee, Z.-Y.; Pai, C.-C. Applying Improved DEA and VIKOR Methods to Evaluate the Operation Performance for World's Major TFT–LCD Manufacturers. Asia-Pac. J. Oper. Res. 2015, 32, Article 1550020. [Google Scholar] [CrossRef]
  159. Liu, H.-C.; Wu, J.; Li, P. Assessment of health-care waste disposal methods using a VIKOR-based fuzzy multi-criteria decision making method. Waste Manag. 2013, 33, 2744–2751. [Google Scholar] [CrossRef] [PubMed]
  160. Chang, T.-H. Fuzzy VIKOR method: A case study of the hospital service evaluation in Taiwan. Inf. Sci. 2014, 271, 196–212. [Google Scholar] [CrossRef]
  161. Lu, M.-T.; Lin, S.-W.; Tzeng, G.-H. Improving RFID adoption in Taiwan’s healthcare industry based on a DEMATEL technique with a hybrid MCDM model. Decis. Support Syst. 2013, 56, 259–269. [Google Scholar] [CrossRef]
  162. Liu, H.-C.; You, J.-X.; Lu, C.; Chen, Y.-Z. Evaluating health-care waste treatment technologies using a hybrid multi-criteria decision making model. Renew. Sustain. Energy Rev. 2015, 41, 932–942. [Google Scholar] [CrossRef]
  163. Zeng, Q.-L.; Li, D.-D.; Yang, Y.-B. VIKOR method with enhanced accuracy for multiple criteria decision making in healthcare management. J. Med. Syst. 2013, 37, 1–9. [Google Scholar] [CrossRef] [PubMed]
  164. Rostamzadeh, R.; Govindan, K.; Esmaeili, A.; Sabaghi, M. Application of fuzzy VIKOR for evaluation of green supply chain management practices. Ecol. Indic. 2015, 49, 188–203. [Google Scholar] [CrossRef]
  165. Akman, G. Evaluating suppliers to include green supplier development programs via fuzzy c-means and VIKOR methods. Comput. Ind. Eng. 2014, 86, 69–82. [Google Scholar] [CrossRef]
  166. Chithambaranathan, P.; Subramanian, N.; Gunasekaran, A.; Palaniappan, P.K. Service supply chain environmental performance evaluation using grey based hybrid MCDM approach. Int. J. Prod. Econ. 2015, 166, 163–176. [Google Scholar] [CrossRef]
  167. Shemshadi, A.; Shirazi, H.; Toreihi, M.; Tarokh, M.J. A fuzzy VIKOR method for supplier selection based on entropy measure for objective weighting. Expert Syst. Appl. 2011, 38, 12160–12167. [Google Scholar] [CrossRef]
  168. Alimardani, M.; Hashemkhani Zolfani, S.; Aghdaie, M.H.; Tamošaitienė, J. A novel hybrid SWARA and VIKOR methodology for supplier selection in an agile environment. Technol. Econ. Dev. Econ. 2013, 19, 533–548. [Google Scholar] [CrossRef]
  169. Aghdaie, M.H.; Zolfani, S.H.; Zavadskas, E.K. Synergies of data mining and multiple attribute decision making. Procedia Soc. Behav. Sci. 2014, 110, 767–776. [Google Scholar] [CrossRef]
  170. Geng, X.; Liu, Q. A hybrid service supplier selection approach based on variable precision rough set and VIKOR for developing product service system. Int. J. Comput. Integr. Manuf. 2014, 28, 1063–1076. [Google Scholar]
  171. Wu, M.; Liu, Z. The supplier selection application based on two methods: VIKOR algorithm with entropy method and Fuzzy TOPSIS with vague sets method. Int. J. Manag. Sci. Eng. Manag. 2011, 6, 109–115. [Google Scholar]
  172. Sarrafha, K.; Rahmati, S.H.A.; Niaki, S.T.A.; Zaretalab, A. A bi-objective integrated procurement, production, and distribution problem of a multi-echelon supply chain network design: A new tuned MOEA. Comput. Oper. Res. 2015, 54, 35–51. [Google Scholar] [CrossRef]
  173. Tzeng, G.-H.; Teng, M.-H.; Chen, J.-J.; Opricovic, S. Multicriteria selection for a restaurant location in Taipei. Int. J. Hosp. Manag. 2002, 21, 171–187. [Google Scholar] [CrossRef]
  174. Liu, C.-H.; Tzeng, G.-H.; Lee, M.-H. Improving tourism policy implementation—The use of hybrid MCDM models. Tour. Manag. 2012, 33, 413–426. [Google Scholar] [CrossRef]
  175. Tsai, W.-H.; Chou, W.-C.; Lai, C.-W. An effective evaluation model and improvement analysis for national park websites: A case study of Taiwan. Tour. Manag. 2010, 31, 936–952. [Google Scholar] [CrossRef]
  176. Liu, C.-H.; Tzeng, G.-H.; Lee, M.-H.; Lee, P.-Y. Improving metro–airport connection service for tourism development: Using hybrid MCDM models. Tour. Manag. Perspect. 2013, 6, 95–107. [Google Scholar] [CrossRef]
  177. Hsieh, L.-F.; Wang, L.-H.; Huang, Y.-C.; Chen, A. An efficiency and effectiveness model for international tourist hotels in Taiwan. Serv. Ind. J. 2010, 30, 2183–2199. [Google Scholar] [CrossRef]
  178. Wu, Y.-C.J.; Shen, J.-P.; Chang, C.-L. Electronic service quality of Facebook social commerce and collaborative learning. Comput. Hum. Behav. 2014, 51, 1395–1402. [Google Scholar] [CrossRef]
  179. Liou, J.J.; Tsai, C.-Y.; Lin, R.-H.; Tzeng, G.-H. A modified VIKOR multiple-criteria decision method for improving domestic airlines service quality. J. Air Transp. Manag. 2011, 17, 57–61. [Google Scholar] [CrossRef]
  180. Kuo, M.-S. A novel interval-valued fuzzy MCDM method for improving airlines’ service quality in Chinese cross-strait airlines. Transp. Res. E Logist. Transp. Rev. 2011, 47, 1177–1193. [Google Scholar] [CrossRef]
  181. Wang, C.-H.; Pang, C.-T. Using VIKOR Method for Evaluating Service Quality of Online Auction under Fuzzy Environment. Int. J. Comput. Sci. Eng. Technol. 2011, 1, 307–314. [Google Scholar]
  182. Vinodh, S.; Kamala, V.; Shama, M. Compromise ranking approach for sustainable concept selection in an Indian modular switches manufacturing organization. Int. J. Adv. Manuf. Technol. 2013, 64, 1709–1714. [Google Scholar] [CrossRef]
  183. Kaya, T.; Kahraman, C. Multicriteria renewable energy planning using an integrated fuzzy VIKOR and AHP methodology: The case of Istanbul. Energy 2010, 35, 2517–2527. [Google Scholar] [CrossRef]
  184. San Cristóbal, J. Multi-criteria decision-making in the selection of a renewable energy project in spain: The Vikor method. Renew. Energy 2011, 36, 498–502. [Google Scholar] [CrossRef]
  185. Sharma, D.; Vaish, R.; Azad, S. Selection of India’s energy resources: A fuzzy decision making approach. Energy Syst. 2015, 6, 439–453. [Google Scholar] [CrossRef]
  186. Chang, C.-L.; Hsu, C.-H. Multi-criteria analysis via the VIKOR method for prioritizing land-use restraint strategies in the Tseng-Wen reservoir watershed. J. Environ. Manag. 2009, 90, 3226–3230. [Google Scholar] [CrossRef] [PubMed]
  187. Venkata Rao, R. An improved compromise ranking method for evaluation of environmentally conscious manufacturing programs. Int. J. Prod. Res. 2009, 47, 4399–4412. [Google Scholar] [CrossRef]
  188. Opricovic, S. Fuzzy VIKOR with an application to water resources planning. Expert Syst. Appl. 2011, 38, 12983–12990. [Google Scholar] [CrossRef]
  189. Chang, C.-L.; Hsu, C.-H. Applying a modified VIKOR method to classify land subdivisions according to watershed vulnerability. Water Resour. Manag. 2011, 25, 301–309. [Google Scholar] [CrossRef]
  190. Tsai, W.-H.; Chou, W.-C.; Leu, J.-D. An effectiveness evaluation model for the web-based marketing of the airline industry. Expert Syst. Appl. 2011, 38, 15499–15516. [Google Scholar] [CrossRef]
  191. Wang, Y.-L.; Tzeng, G.-H. Brand marketing for creating brand value based on a MCDM model combining DEMATEL with ANP and VIKOR methods. Expert Syst. Appl. 2012, 39, 5600–5615. [Google Scholar] [CrossRef]
  192. Ginevičius, R.; Bruzgė, Š.; Podvezko, V. Evaluating the effect of state aid to business by multicriteria methods. J. Bus. Econ. Manag. 2008, 9, 167–180. [Google Scholar] [CrossRef]
  193. Chiu, W.-Y.; Tzeng, G.-H.; Li, H.-L. A new hybrid MCDM model combining DANP with VIKOR to improve e-store business. Knowl. Based Syst. 2013, 37, 48–61. [Google Scholar] [CrossRef]
  194. Chang, S.-C.; Tsai, P.-H.; Chang, S.-C. A hybrid fuzzy model for selecting and evaluating the e-book business model: A case study on Taiwan e-book firms. Appl. Soft Comput. 2015, 34, 194–204. [Google Scholar] [CrossRef]
  195. Azimi, R.; Yazdani-Chamzini, A.; Fooladgar, M.M.; Basiri, M.H. Evaluating the strategies of the Iranian mining sector using a integrated model. Int. J. Manag. Sci. Eng. Manag. 2011, 6, 459–466. [Google Scholar]
  196. Chen, I.-S.; Chen, J.-K. Creativity strategy selection for the higher education system. Qual. Quant. 2012, 46, 739–750. [Google Scholar] [CrossRef]
  197. Liou, J.J.; Chuang, Y.-T. Developing a hybrid multi-criteria model for selection of outsourcing providers. Expert Syst. Appl. 2010, 37, 3755–3761. [Google Scholar] [CrossRef]
  198. Ho, W.-R.J.; Tsai, C.-L.; Tzeng, G.-H.; Fang, S.-K. Combined DEMATEL technique with a novel MCDM model for exploring portfolio selection based on CAPM. Expert Syst. Appl. 2011, 38, 16–25. [Google Scholar]
  199. Sachdeva, A.; Sharma, V.; Arvind Bhardwaj, D.; Kumar, R.; Singh, H.; Dureja, J. An approach to analyze logistic outsourcing problem in medium-scale organization by CFPR and VIKOR. J. Manuf. Technol. Manag. 2012, 23, 885–898. [Google Scholar] [CrossRef]
  200. Chen, I.-S.; Chen, J.-K. Present and future: A trend forecasting and ranking of university types for innovative development from an intellectual capital perspective. Qual. Quant. 2013, 47, 335–352. [Google Scholar] [CrossRef]
  201. Lu, M.-T.; Tzeng, G.-H.; Cheng, H.; Hsu, C.-C. Exploring mobile banking services for user behavior in intention adoption: Using new hybrid MADM model. Serv. Bus. 2015, 9, 541–565. [Google Scholar] [CrossRef]
  202. Ahmadi, A.; Gupta, S.; Karim, R.; Kumar, U. Selection of maintenance strategy for aircraft systems using multi-criteria decision making methodologies. Int. J. Reliabil. Qual. Saf. Eng. 2010, 17, 223–243. [Google Scholar] [CrossRef]
  203. Rostamzadeh, R.; Ismail, K.; Zavadskas, E.K. Multi criteria decision making for assisting business angels in investments. Technol. Econ. Dev. Econ. 2014, 20, 696–720. [Google Scholar] [CrossRef]
  204. Liu, H.-C.; Chen, Y.-Z.; You, J.-X.; Li, H. Risk evaluation in failure mode and effects analysis using fuzzy digraph and matrix approach. J. Intell. Manuf. 2014. [Google Scholar] [CrossRef]
  205. Shen, K.-Y.; Tzeng, G.-H. A decision rule-based soft computing model for supporting financial performance improvement of the banking industry. Soft Comput. 2014, 19, 859–874. [Google Scholar] [CrossRef]
  206. Lee, W.S.; Yang, Y.T. Valuation and choice of convertible bonds based on MCDM. Appl. Financ. Econ. 2013, 23, 861–868. [Google Scholar] [CrossRef]
  207. Peng, Y.; Wang, G.; Kou, G.; Shi, Y. An empirical study of classification algorithm evaluation for financial risk prediction. Appl. Soft Comput. 2011, 11, 2906–2915. [Google Scholar] [CrossRef]
  208. Kou, G.; Peng, Y.; Wang, G. Evaluation of clustering algorithms for financial risk analysis using MCDM methods. Inf. Sci. 2014, 275, 1–12. [Google Scholar] [CrossRef]
  209. Mandal, S.; Singh, K.; Behera, R.; Sahu, S.; Raj, N.; Maiti, J. Human error identification and risk prioritization in overhead crane operations using HTA, SHERPA and fuzzy VIKOR method. Expert Syst. Appl. 2015, 42, 7195–7206. [Google Scholar] [CrossRef]
  210. Ginevičius, R.; Podvezko, V. Assessing the financial state of construction enterprises. Technol. Econ. Dev. Econ. 2006, 12, 188–194. [Google Scholar]
  211. Liu, H.-C.; Liu, L.; Liu, N.; Mao, L.-X. Risk evaluation in failure mode and effects analysis with extended VIKOR method under fuzzy environment. Expert Syst. Appl. 2012, 39, 12926–12934. [Google Scholar] [CrossRef]
  212. Safari, H.; Faraji, Z.; Majidian, S. Identifying and evaluating enterprise architecture risks using FMEA and fuzzy VIKOR. J. Intell. Manuf. 2014. [Google Scholar] [CrossRef]
  213. Ou Yang, Y.-P.; Shieh, H.-M.; Leu, J.-D.; Tzeng, G.-H. A VIKOR-based multiple criteria decision method for improving information security risk. Int. J. Inf. Technol. Decis. Mak. 2009, 8, 267–287. [Google Scholar] [CrossRef]
  214. Emovon, I.; Norman, R.A.; Murphy, A.J.; Pazouki, K. An integrated multicriteria decision making methodology using compromise solution methods for prioritising risk of marine machinery systems. Ocean Eng. 2015, 105, 92–103. [Google Scholar] [CrossRef]
  215. Yang, Y.-P.O.; Shieh, H.-M.; Tzeng, G.-H. A VIKOR technique based on DEMATEL and ANP for information security risk control assessment. Inf. Sci. 2013, 232, 482–500. [Google Scholar] [CrossRef]
  216. Yalcin, N.; Bayrakdaroglu, A.; Kahraman, C. Application of fuzzy multi-criteria decision making methods for financial performance evaluation of Turkish manufacturing industries. Expert Syst. Appl. 2012, 39, 350–364. [Google Scholar] [CrossRef]
  217. Safaei Ghadikolaei, A.; Khalili Esbouei, S.; Antucheviciene, J. Applying fuzzy MCDM for financial performance evaluation of Iranian companies. Technol. Econ. Dev. Econ. 2014, 20, 274–291. [Google Scholar] [CrossRef]
  218. Chu, M.-T.; Shyu, J.; Tzeng, G.-H.; Khosla, R. Comparison among three analytical methods for knowledge communities group-decision analysis. Expert Syst. Appl. 2007, 33, 1011–1024. [Google Scholar] [CrossRef]
  219. Bazzazi, A.A.; Osanloo, M.; Karimi, B. Deriving preference order of open pit mines equipment through MADM methods: Application of modified VIKOR method. Expert Syst. Appl. 2011, 38, 2550–2556. [Google Scholar] [CrossRef]
  220. Tadić, S.; Zečević, S.; Krstić, M. A novel hybrid MCDM model based on fuzzy DEMATEL, fuzzy ANP and fuzzy VIKOR for city logistics concept selection. Expert Syst. Appl. 2014, 41, 8112–8128. [Google Scholar] [CrossRef]
  221. Leng, J.; Jiang, P.; Ding, K. Implementing of a three-phase integrated decision support model for parts machining outsourcing. Int. J. Prod. Res. 2014, 52, 3614–3636. [Google Scholar] [CrossRef]
  222. Fu, H.-P.; Chu, K.-K.; Chao, P.; Lee, H.-H.; Liao, Y.-C. Using fuzzy AHP and VIKOR for benchmarking analysis in the hotel industry. Serv. Ind. J. 2011, 31, 2373–2389. [Google Scholar] [CrossRef]
  223. Büyüközkan, G.; Ruan, D. Evaluation of software development projects using a fuzzy multi-criteria decision approach. Math. Comput. Simul. 2008, 77, 464–475. [Google Scholar] [CrossRef]
  224. Fallahpour, A.; Moghassem, A. Spinning preparation parameters selection for rotor spun knitted fabric using VIKOR method of multicriteria decision-making. J. Text. Inst. 2013, 104, 7–17. [Google Scholar] [CrossRef]
  225. Hadi-Vencheh, A.; Mohamadghasemi, A. A new hybrid fuzzy multi-criteria decision making model for solving the material handling equipment selection problem. Int. J. Comput. Integr. Manuf. 2015, 28, 534–550. [Google Scholar] [CrossRef]
  226. Büyüközkan, G.; Feyzioglu, O.; Cifçi, G. Fuzzy multi-criteria evaluation of knowledge management tools. Int. J. Comput. Intell. Syst. 2011, 4, 184–195. [Google Scholar] [CrossRef]
  227. Gauri, S.K.; Pal, S. Comparison of performances of five prospective approaches for the multi-response optimization. Int. J. Adv. Manuf. Technol. 2010, 48, 1205–1220. [Google Scholar] [CrossRef]
  228. Chen, F.H.; Tzeng, G.-H.; Chang, C.C. Evaluating the Enhancement of Corporate Social Responsibility Websites Quality Based on a New Hybrid MADM Model. Int. J. Inf. Technol. Decis. Mak. 2015, 14, 697–724. [Google Scholar] [CrossRef]
  229. Tsai, W.-H.; Lee, P.-L.; Shen, Y.-S.; Hwang, E.T. A combined evaluation model for encouraging entrepreneurship policies. Ann. Oper. Res. 2014, 221, 449–468. [Google Scholar] [CrossRef]
  230. Mazdeh, M.M.; Razavi, S.-M.; Hesamamiri, R.; Zahedi, M.-R.; Elahi, B. An empirical investigation of entrepreneurship intensity in Iranian state universities. High. Educ. 2013, 65, 207–226. [Google Scholar] [CrossRef]
  231. Peng, K.-H.; Tzeng, G.-H. A hybrid dynamic MADM model for problem-improvement in economics and business. Technol. Econ. Dev. Econ. 2013, 19, 638–660. [Google Scholar] [CrossRef]
  232. Wu, H.-Y.; Chen, J.-K.; Chen, I.-S. Innovation capital indicator assessment of Taiwanese Universities: A hybrid fuzzy model application. Expert Syst. Appl. 2010, 37, 1635–1642. [Google Scholar] [CrossRef]
  233. Celik, E.; Aydin, N.; Gumus, A.T. A multiattribute customer satisfaction evaluation approach for rail transit network: A real case study for Istanbul, Turkey. Transp. Policy. 2014, 36, 283–293. [Google Scholar] [CrossRef]
  234. Baležentis, A.; Baležentis, T.; Misiunas, A. An integrated assessment of Lithuanian economic sectors based on financial ratios and fuzzy MCDM methods. Technol. Econ. Dev. Econ. 2012, 18, 34–53. [Google Scholar] [CrossRef]
  235. Chen, C.-H.; Tzeng, G.-H. Creating the aspired intelligent assessment systems for teaching materials. Expert Syst. Appl. 2011, 38, 12168–12179. [Google Scholar] [CrossRef]
  236. Mohanty, P.P.; Mahapatra, S. A Compromise Solution by VIKOR Method for Ergonomically Designed Product with Optimal Set of Design Characteristics. Procedia Mater. Sci. 2014, 6, 633–640. [Google Scholar] [CrossRef]
  237. Ashtiani, M.; Azgomi, M.A. Trust modeling based on a combination of fuzzy analytic hierarchy process and fuzzy VIKOR. Soft Comput. 2014. [Google Scholar] [CrossRef]
  238. Mehbodniya, A.; Kaleem, F.; Yen, K.K.; Adachi, F. A fuzzy extension of VIKOR for target network selection in heterogeneous wireless environments. Phys. Commun. 2013, 7, 145–155. [Google Scholar] [CrossRef]
  239. Lee, W.-S. Merger and acquisition evaluation and decision making model. Serv. Ind. J. 2013, 33, 1473–1494. [Google Scholar] [CrossRef]
  240. Arunachalam, A.P.S.; Idapalapati, S.; Subbiah, S. Multi-criteria decision making techniques for compliant polishing tool selection. Int. J. Adv. Manuf. Technol. 2015, 79, 519–530. [Google Scholar] [CrossRef]
  241. Martin-Utrillas, M.; Reyes-Medina, M.; Curiel-Esparza, J.; Canto-Perello, J. Hybrid method for selection of the optimal process of leachate treatment in waste treatment and valorization plants or landfills. Clean Technol. Environ. Policy 2015, 17, 873–885. [Google Scholar] [CrossRef]
  242. Mousavi, S.M.; Jolai, F.; Tavakkoli-Moghaddam, R. A fuzzy stochastic multi-attribute group decision-making approach for selection problems. Group Decis. Negot. 2013, 22, 207–233. [Google Scholar] [CrossRef]
  243. Chitsaz, N.; Banihabib, M.E. Comparison of Different Multi Criteria Decision-Making Models in Prioritizing Flood Management Alternatives. Water Resour. Manag. 2015, 29, 2503–2525. [Google Scholar] [CrossRef]
  244. Milosevic, I.; Naunovic, Z. The application of a multi-parameter analysis in choosing the location of a new solid waste landfill in Serbia. Waste Manag. Res. 2013, 31, 1019–1027. [Google Scholar] [CrossRef] [PubMed]
  245. Pourebrahim, S.; Hadipour, M.; Mokhtar, M.B.; Taghavi, S. Application of VIKOR and fuzzy AHP for conservation priority assessment in coastal areas: Case of Khuzestan district, Iran. Ocean Coast. Manag. 2014, 98, 20–26. [Google Scholar] [CrossRef]
  246. Lee, W.-S.; Tu, W.-S. Combined MCDM techniques for exploring company value based on Modigliani–Miller theorem. Expert Syst. Appl. 2011, 38, 8037–8044. [Google Scholar] [CrossRef]
  247. Lin, C.-L. A novel hybrid decision-making model for determining product position under consideration of dependence and feedback. Appl. Math. Model. 2015, 39, 2194–2216. [Google Scholar] [CrossRef]
  248. Tong, L.-I.; Chen, C.-C.; Wang, C.-H. Optimization of multi-response processes using the VIKOR method. Int. J. Adv. Manuf. Technol. 2007, 31, 1049–1057. [Google Scholar] [CrossRef]
  249. Hsu, M.-F.; Pai, P.-F. Incorporating support vector machines with multiple criteria decision making for financial crisis analysis. Qual. Quant. 2013, 47, 3481–3492. [Google Scholar] [CrossRef]
  250. Fallahpour, A.; Moghassem, A. Evaluating applicability of VIKOR method of multi-criteria decision making for parameters selection problem in rotor spinning. Fibers Polym. 2012, 13, 802–808. [Google Scholar] [CrossRef]
  251. Bondor, C.I.; Kacso, I.M.; Lenghel, A.; Istrate, D.; Muresan, A. VIKOR Method for Diabetic Nephropathy Risk Factors Analysis. Appl. Med. Inform. 2013, 32, 43–52. [Google Scholar]
  252. Lee, W.-S. A New Hybrid Mcdm Model Combining Danp With Vikor For The Selection Of Location—Real Estate Brokerage Services. Int. J. Inf. Technol. Decis. Mak. 2014, 13, 197–224. [Google Scholar] [CrossRef]
  253. Kosareva, N.; Krylovas, A. Comparison of accuracy in ranking alternatives performing generalized fuzzy average functions. Technol. Econ. Dev. Econ. 2013, 19, 162–187. [Google Scholar] [CrossRef]
  254. Sun, P.; Liu, Y.; Qiu, X.; Wang, L. Hybrid multiple attribute group decision-making for power system restoration. Expert Syst. Appl. 2015, 42, 6795–6805. [Google Scholar] [CrossRef]
  255. Hu, S.-K.; Lu, M.-T.; Tzeng, G.-H. Exploring smart phone improvements based on a hybrid MCDM model. Expert Syst. Appl. 2014, 41, 4401–4413. [Google Scholar] [CrossRef]
  256. Yücenur, G.N.; Demirel, N.Ç. Group decision making process for insurance company selection problem with extended VIKOR method under fuzzy environment. Expert Syst. Appl. 2012, 39, 3702–3707. [Google Scholar] [CrossRef]
  257. Kaya, T.; Kahraman, C. Fuzzy multiple criteria forestry decision making based on an integrated VIKOR and AHP approach. Expert Syst. Appl. 2011, 38, 7326–7333. [Google Scholar] [CrossRef]
  258. Peng, Y.; Kou, G.; Wang, G.; Shi, Y. FAMCDM: A fusion approach of MCDM methods to rank multiclass classification algorithms. Omega 2011, 39, 677–689. [Google Scholar] [CrossRef]
  259. Mardani, A.; Zavadskas, E.K.; Khalifah, Z.; Jusoh, A.; Nor, K.M.D. Multiple criteria decision-making techniques in transportation systems: A systematic review of the state of the art literature. Transport 2015. [Google Scholar] [CrossRef]
  260. Zavadskas, E.K.; Turskis, Z. Multiple criteria decision making (MCDM) methods in economics: An overview. Technol. Econ. Dev. Econ. 2011, 17, 397–427. [Google Scholar] [CrossRef]
  261. Yazdani, M.; Graeml, F.R. VIKOR and its Applications: A State-of-the-Art Survey. Int. J. Strateg. Decis. Sci. (IJSDS) 2014, 5, 56–83. [Google Scholar] [CrossRef]

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Mardani, A.; Zavadskas, E.K.; Govindan, K.; Amat Senin, A.; Jusoh, A. VIKOR Technique: A Systematic Review of the State of the Art Literature on Methodologies and Applications. Sustainability 2016, 8, 37. https://doi.org/10.3390/su8010037

AMA Style

Mardani A, Zavadskas EK, Govindan K, Amat Senin A, Jusoh A. VIKOR Technique: A Systematic Review of the State of the Art Literature on Methodologies and Applications. Sustainability. 2016; 8(1):37. https://doi.org/10.3390/su8010037

Chicago/Turabian Style

Mardani, Abbas, Edmundas Kazimieras Zavadskas, Kannan Govindan, Aslan Amat Senin, and Ahmad Jusoh. 2016. "VIKOR Technique: A Systematic Review of the State of the Art Literature on Methodologies and Applications" Sustainability 8, no. 1: 37. https://doi.org/10.3390/su8010037

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