Performance Evaluation of Construction Companies Using Integrated Entropy–Fuzzy VIKOR Model

Siew, Lam Weng; Jaaman, Saiful Hafizah; Fai, Liew Kah

doi:10.3390/e23030320

Cited by 65 publications

(33 citation statements)

References 50 publications

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“…Towards this end, the authors used the decision‐making trial and evaluation laboratory (DEMATEL) method to help countries reduce the negative impact of quarantine decisions on the hospitality industry because of the COVID‐19 pandemic. Another work 89 discussed that owing to the emergence and impact of COVID‐19, each country's economic development was affected, and all governmental agencies are encouraging the construction industry to develop an advanced infrastructure related to health, transport, education, and housing, particularly with regard to the operations and financial performance of construction sector companies. Therefore, the MADM process was utilised because no comprehensive study was conducted on the evaluation of the financial performance of construction companies.…”

Section: Literature Review Analysismentioning

confidence: 99%

“…The devastating effect of the COVID‐19 pandemic has created an unprecedented situation that needs a professional decision support system that can effectively handle the related issues mentioned in Table 1 . The result of this review revealed 13 extensions of existing methods, namely, LBWA–MACBETH–RAFSI, 49 PmF‐TOPSIS, 67 WASPAS, 95 AHP‐Entropy‐TOPSIS‐GRA, 78 distance measure for IFSs, 59 LHF‐BWM‐TODIM, 96 BBWM with improved matter‐element extension model (BBWM‐IMEEM), 90 cross‐entropy of UPLZs‐MULTIMOORA, 74 Entropy‐F‐VIKOR, 89 FAHP‐HFS‐TOPSIS, 80 HF‐divergence measure‐HF‐ARAS, 76 TrIT2F‐BWM‐VIKOR, 72 and IF‐MARCOS. 92 These methods mainly focus on handling the inaccuracies and uncertainties (vagueness issue) mentioned in Table 1 .…”

Section: Literature Review Analysismentioning

confidence: 99%

“…This approach was used in 19 works (67.86%) to examine the validity of the decision outcomes. Some studies used only comparative analysis as in [ 57 , 67 , 72 , 89 ], whereas others combined this analysis with other approaches to increase the accuracy of the evaluation results as in [ 90 , 94 , 96 ]. This process was followed by sensitivity analysis, which was employed in 10 studies with a 37.71% occurrence rate.…”

Section: Literature Review Analysismentioning

confidence: 99%

See 2 more Smart Citations

Rise of multiattribute decision‐making in combating COVID‐19: A systematic review of the state‐of‐the‐art literature

Alsalem

Mohammed²,

Albahri

et al. 2021

Int J of Intelligent Sys

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Considering the coronavirus disease 2019 (COVID‐19) pandemic, the government and health sectors are incapable of making fast and reliable decisions, particularly given the various effects of decisions on different contexts or countries across multiple sectors. Therefore, leaders often seek decision support approaches to assist them in such scenarios. The most common decision support approach used in this regard is multiattribute decision‐making (MADM). MADM can assist in enforcing the most ideal decision in the best way possible when fed with the appropriate evaluation criteria and aspects. MADM also has been of great aid to practitioners during the COVID‐19 pandemic. Moreover, MADM shows resilience in mitigating consequences in health sectors and other fields. Therefore, this study aims to analyse the rise of MADM techniques in combating COVID‐19 by presenting a systematic literature review of the state‐of‐the‐art COVID‐19 applications. Articles on related topics were searched in four major databases, namely, Web of Science, IEEE Xplore, ScienceDirect, and Scopus, from the beginning of the pandemic in 2019 to April 2021. Articles were selected on the basis of the inclusion and exclusion criteria for the identified systematic review protocol, and a total of 51 articles were obtained after screening and filtering. All these articles were formed into a coherent taxonomy to describe the corresponding current standpoints in the literature. This taxonomy was drawn on the basis of four major categories, namely, medical ( n = 30), social ( n = 4), economic ( n = 13) and technological ( n = 4). Deep analysis for each category was performed in terms of several aspects, including issues and challenges encountered, contributions, data set, evaluation criteria, MADM techniques, evaluation and validation and bibliography analysis. This study emphasised the current standpoint and opportunities for MADM in the midst of the COVID‐19 pandemic and promoted additional efforts towards understanding and providing new potential future directions to fulfil the needs of this study field.

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Section: Literature Review Analysismentioning

confidence: 99%

Section: Literature Review Analysismentioning

confidence: 99%

Section: Literature Review Analysismentioning

confidence: 99%

See 1 more Smart Citation

Rise of multiattribute decision‐making in combating COVID‐19: A systematic review of the state‐of‐the‐art literature

Alsalem

Mohammed²,

Albahri

et al. 2021

Int J of Intelligent Sys

View full text Add to dashboard Cite

show abstract

“…The fuzzy triangular numbers are extensively used by the researchers work in MCDM models due to their simple intuitiveness and calculation to performance measurement (Pedrycz, 1994; Vinodh and Devadasan, 2011; Koohathongsumrit and Meethom, 2021). In the case of a questionnaire survey, where the decision is mainly based on experts opinions, fuzzy triangular numbers are proved as efficient to calculate and required less time to get the solution successfully (Alkhatib, 2017; Patil et al , 2020; Jaukovic et al , 2020; Lam et al , 2021).…”

Section: Study Methodologymentioning

confidence: 99%

Application of fuzzy TOPSIS framework for selecting complex project in a case company

Shamsuzzoha

Piya

Shamsuzzaman

2021

JGOSS

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Purpose This study aims to propose a method known as the fuzzy technique for order preference by similarity to ideal solution (fuzzy TOPSIS) for complex project selection in organizations. To fulfill study objectives, the factors responsible for making a project complex are collected through literature review, which is then analyzed by fuzzy TOPSIS, based on three decision-makers’ opinions. Design/methodology/approach The selection of complex projects is a multi-criteria decision-making (MCDM) process for global organizations. Traditional procedures for selecting complex projects are not adequate due to the limitations of linguistic assessment. To crossover such limitation, this study proposes the fuzzy MCDM method to select complex projects in organizations. Findings A large-scale engine manufacturing company, engaged in the energy business, is studied to validate the suitability of the fuzzy TOPSIS method and rank eight projects of the case company based on project complexity. Out of these eight projects, the closeness coefficient of the most complex project is found to be 0.817 and that of the least complex project is found to be 0.274. Finally, study outcomes are concluded in the conclusion section, along with study limitations and future works. Research limitations/implications The outcomes from this research may not be generalized sufficiently due to the subjectivity of the interviewers. The study outcomes support project managers to optimize their project selection processes, especially to select complex projects. The presented methodology can be used extensively used by the project planners/managers to find the driving factors related to project complexity. Originality/value The presented study deliberately explained how complex projects in an organization could be select efficiently. This selection methodology supports top management to maintain their proposed projects with optimum resource allocations and maximum productivity.

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“…Ziemba uses stochastic analysis to study the uncertainty of the parameters of alternatives in the PROSA-C (PROMETHEE for Sustainability Assessment-Criteria) method [43]. Lam et al proposed an entropy-fuzzy VIKOR (VIseKriterijumska Optimizacija I Kompromisno Resenje) model in which objective weights are used, avoiding subjectivity in determining the weights of criteria [44].…”

Section: Literature Reviewmentioning

confidence: 99%

Application of Bayesian Approach to Reduce the Uncertainty in Expert Judgments by Using a Posteriori Mean Function

Vinogradova-Zinkevič

2021

Mathematics

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Much applied research uses expert judgment as a primary or additional data source, thus the problem solved in this publication is relevant. Despite the expert’s experience and competence, the evaluation is subjective and has uncertainty in it. There are various reasons for this uncertainty, including the expert’s incomplete competence, the expert’s character and personal qualities, the expert’s attachment to the opinion of other experts, and the field of the task to be solved. This paper presents a new way to use the Bayesian method to reduce the uncertainty of an expert judgment by correcting the expert’s evaluation by the a posteriori mean function. The Bayesian method corrects the expert’s evaluation, taking into account the expert’s competence and accumulated long-term experience. Since the paper uses a continuous case of the Bayesian formula, perceived as a continuous approximation of experts’ evaluations, this is not only the novelty of this work, but also a new result in the theory of the Bayesian method and its application. The paper investigates various combinations of the probability density functions of a priori information and expert error. The results are illustrated by the example of the evaluation of distance learning courses.

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Performance Evaluation of Construction Companies Using Integrated Entropy–Fuzzy VIKOR Model

Cited by 65 publications

References 50 publications

Rise of multiattribute decision‐making in combating COVID‐19: A systematic review of the state‐of‐the‐art literature

Rise of multiattribute decision‐making in combating COVID‐19: A systematic review of the state‐of‐the‐art literature

Application of fuzzy TOPSIS framework for selecting complex project in a case company

Application of Bayesian Approach to Reduce the Uncertainty in Expert Judgments by Using a Posteriori Mean Function

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