Using the fuzzy multicriteria decision making approach to evaluate brand equity: a study of privatized firms

2019 ◽  
Vol 29 (3) ◽  
pp. 335-354
Author(s):  
Hasan Dinçer ◽  
Tuba Bozaykut-Buk ◽  
Şenol Emir ◽  
Serhat Yuksel ◽  
Nicholas Ashill
Keyword(s):  
Decision Making ◽  
Text Mining ◽  
Brand Equity ◽  
Business Performance ◽  
Multicriteria Decision Making ◽  
Fuzzy Topsis ◽  
Fuzzy Decision Making ◽  
Fuzzy Dematel ◽  
Content Type ◽  
Privatized Firms

Purpose The purpose of this paper is to present a multidimensional evaluation of brand equity performance incorporating dimensions adopted from the balance scorecard (BSC) approach to business performance. Design/methodology/approach In this study, text mining is used for automatic extraction of valuable information from textual data such as the financial reports of firms. Instead of expert opinions, linguistic scales built upon outcomes of text mining are used as inputs for decision-making. The proposed model combines fuzzy DEMATEL (FDEMATEL), fuzzy ANP (FANP), fuzzy TOPSIS (FTOPSIS) and fuzzy VIKOR (FVIKOR) methods for weighting criteria and ranking alternatives. Findings Using data from five privatized firms in Turkey, the study’s findings demonstrate that the customer is the most important dimension of brand equity performance evaluation. Cash flow and brand loyalty are identified as the most important criteria in the measurement of brand equity performance. Practical implications Findings highlight the importance of firms taking action to increase consumer perceptions, attitudes and behaviors in the privatization processes. For this purpose, privatized firms need to understand the expectations of customers to increase customer satisfaction and loyalty and therefore improve brand equity. Originality/value The paper contributes to literature in several important ways. First, by adopting the BSC approach, it proposes a holistic and a multidimensional model for measuring brand equity performance. Second, the study offers a novel methodology using a hybrid multi-criteria decision-making model designed for the fuzzy environment. Third, the study uses the knowledge extraction tool of text mining in the fuzzy decision-making process. Finally, the study evaluates the brand equity performance of privatized firms in an emerging country context.

Barriers to implementing digitalization in the Indian construction industry

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Avirag Bajpai ◽  
Subhas C. Misra
Keyword(s):  
Decision Making ◽  
Construction Industry ◽  
Research Paper ◽  
Fuzzy Decision Making ◽  
Top Management ◽  
Research Approach ◽  
Extensive Literature ◽  
Total Quality ◽  
Fuzzy Dematel ◽  
Content Type

PurposeThis research paper aims to analyze the critical barriers to implementing digitalization in the Indian construction industry as Indian construction companies are lagging in the implementation of digital technologies in the work environment.Design/methodology/approachIn this research paper, a qualitative research approach is adopted, and multiple detailed interviews are conducted with industry and academic experts. Further, multi-criteria decision-making (MCDM) techniques are used to finalize the prioritization among various alternatives. The fuzzy-decision-making trial and evaluation laboratory (Fuzzy-DEMATEL) and interpretive structural modeling (ISM) techniques are employed to find the exact relationship among the identified alternatives.FindingsThis study identifies 14 critical barriers from an extensive literature review and multiple interviews with industry professionals, and further driving and critical barriers are identified.Research limitations/implicationsIn this research paper, an exploratory study with a limited number of respondents from a large Indian construction company is carried out. Further, a detailed longitudinal analysis can be done to assess the subjectivity of the participants with more advanced statistical tools. However, this research discusses several points pertaining to the implementation of digitalization in the construction industry. The research further identifies the critical barriers to digitalization in the Indian construction industry.Practical implicationsThe finding of the study has two-pronged implications. First, it provides a road-map to the construction industry by highlighting the engagement of top management as the key focus area for successful digitalization. Second, the finding also shows similarity of the digitalization process to the adoption of process improvement techniques like lean and total quality management (TQM), wherein the top management plays a crucial role in ushering in the implementation of a disruptive change.Originality/valueThe research is unique in two ways. First, this is one of the very few attempts to understand digitalization in the Indian context. Second, the research also demonstrates that the combination of fuzzy DEMATEL and ISM techniques can be successfully employed in the emerging field of construction digitalization research.

Fuzzy Multicriteria Decision Making Methodologies Used in the Book

2020 ◽  
pp. 92-131
Keyword(s):  
Decision Making ◽  
Multicriteria Decision Making ◽  
Fuzzy Topsis ◽  
Suitable Model ◽  
Fuzzy Dematel ◽  
Multicriteria Decision ◽  
Fuzzy Vikor

Using an appropriate methodology is crucial in the analysis. Therefore, the suitable model should be selected according to the type of the evaluation. Otherwise, there is a risk of having inappropriate results. Because of this situation, recommendations can be problematic. In this book, three different analyses are performed. In two of them, fuzzy DEMATEL, fuzzy TOPSIS, and fuzzy VIKOR approaches are taken into consideration. In this chapter, these three methods are explained. In this framework, some studies, which used these methods, are explained.

Application of fuzzy DEMATEL and fuzzy CODAS for analysis of workforce attributes pertaining to Industry 4.0: a case study

2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
S Vinodh ◽  
Vishal Ashok Wankhede
Keyword(s):  
Decision Making ◽  
Industry 4.0 ◽  
Skills Training ◽  
Fuzzy Decision Making ◽  
System Modelling ◽  
Fuzzy Decision ◽  
Fuzzy Dematel ◽  
Content Type ◽  
Modern Manufacturing

PurposeThe aim of this study is to analyze workforce attributes related to Industry 4.0 using fuzzy decision-making trial and evaluation laboratory (DEMATEL) and fuzzy combinative distance-based assessment (CODAS).Design/methodology/approachTechnological trends stipulate various revolution in industries. Industry 4.0 is a vital challenge for modern manufacturing industries. Workforce adoption to such challenge is gaining vital importance. Therefore, such workforce-related attributes need to be identified for enhancing their performance in Industry 4.0 environment. In this context, this article highlights the analysis of 20 workforce attributes for Industry 4.0. Relevant criteria are prioritized using fuzzy DEMATEL. Workforce attributes are prioritized using fuzzy CODAS.FindingsThe key attributes are “Skills/training in decision-making (WA2)”, “Competences in complex system modelling and simulation (WA1)” and “Coding skills (WA20)”.Research limitations/implicationsIn the present study, 20 workforce attributes are being considered. In future, additional workforce attributes could be considered.Practical implicationsThe study has been conducted based on inputs from industry experts. Hence, the inferences have practical relevance.Originality/valueThe analysis of workforce attributes for Industry 4.0 using MCDM methods is the original contribution of the authors.

A fuzzy DEMATEL – Fuzzy Binary Logistic Regression approach to evaluate and prioritize risks and simulated annealing optimization algorithm (an empirical study in energy projects)

2020 ◽  
Vol 13 (5) ◽  
pp. 1025-1050
Author(s):  
Reyhane Hashemi ◽  
Reza Kamranrad ◽  
Farnoosh Bagheri ◽  
Iman Emami
Keyword(s):  
Decision Making ◽  
Logistic Regression ◽  
Binary Logistic Regression ◽  
Fuzzy Decision Making ◽  
Fuzzy Dematel ◽  
Data Set ◽  
Content Type ◽  
Energy Projects ◽  
High Level ◽  
Level Of Risk

PurposeThe aim of this paper is to predict and minimize the risks of oil, gas and petrochemical projects. Besides, reducing the likelihood of occurrence and minimizing risks impact on the projects to reduce the probable costs and improve the economic situation is another purpose of this paper.Design/methodology/approachThis paper provides a fuzzy Decision-Making Trial and Evaluation Laboratory (DEMATEL) – a technique that assist to solve decision-making problems – and IP (Impact & Probability) table methods to identify and analyze critical risks in energy projects, and then fuzzy Binary Logistic Regression (BLR) in order to predict the probability of each level of risk for more efficient risk management in projects. Furthermore, in this paper, the fuzzy BLR (FBLR) is optimized such that the probability of a high level of risk for the implementation of the project has been minimized using meta-heuristic algorithm.FindingsThe results from the point of view of experts show that combination of fuzzy DEMATEL with FBLR approach as well as using SA algorithm, in order to optimize the high level of risks, can provide a smart approach to managing risks with more success.Practical implicationsThe application of the proposed method is illustrated via a real data set from energy projects.Originality/valueWe propose combined fuzzy DEMATEL and FBLR methods to predict and optimize the risks of the energy projects, which is the innovation of this paper.

A fuzzy hybrid approach for ranking and allocation of flare gas recovery methods

Kybernetes ◽  
2019 ◽  
Vol 49 (4) ◽  
pp. 1103-1126
Author(s):  
Negar Shaaban ◽  
Majid Nojavan ◽  
Davood Mohammaditabar
Keyword(s):  
Decision Making ◽  
Hybrid Approach ◽  
Political Stability ◽  
New Combination ◽  
Fuzzy Decision Making ◽  
Gas Field ◽  
Fuzzy Dematel ◽  
Content Type ◽  
Gas Recovery ◽  
Recovery Methods

Purpose The purpose of this paper is to investigate a fuzzy hybrid approach for ranking the flare gas recovery methods and allocating to refineries. Design/methodology/approach The proposed approach is containing four stages: in the first stage, experts' assessment is applied to identify relevant criteria and sub-criteria in the evaluation of flare gas recovery methods. In the second stage, the corresponding weights of criteria and sub-criteria are determined via fuzzy decision-making trial and evaluation (DEMATEL)-analytical network process (ANP) (DANP) method. In the third stage, the flare gas recovery methods are ranked using fuzzy weighted aggregated sum product assessment method (WASPAS) multi-criteria decision-making (MADM) technique. In the fourth stage, an optimization model is developed to allocate gas recovery methods to refineries while maximizing the total utility of allocations based on model constraints. Findings According to the results of fuzzy DANP method, technical and operational criterion was the most important followed by economic, political, managerial and environmental criteria. With respect to sub-criteria, international sanctions and political stability were the most important. The results of fuzzy WASPAS method indicated that gas injection was the first ranked alternative. Finally, the mathematical modeling allocated the recovery methods to five refineries of South Pars gas field in Iran based on budget and time constraints. Originality/value The proposed approach provides a systematic tool in the selection of flare recovery methods and allocation to refineries. This approach uses a new combination of fuzzy DEMATEL-ANP (DANP) method, fuzzy WASPAS method and mathematical programming. The approach is effectively implemented in a case study for ranking the flare gas recovery methods and allocating to refineries of South Pars gas field in Iran.

scholarly journals Prioritization in Strategic Environmental Assessment Using Fuzzy TOPSIS Method with Random Generation for Absent Information in South Korea

2021 ◽  
Vol 13 (3) ◽  
pp. 1458
Author(s):  
Daeryong Park ◽  
Huan-Jung Fan ◽  
Jun-Jie Zhu ◽  
Taesoon Kim ◽  
Myoung-Jin Um ◽  
...  
Keyword(s):  
Decision Making ◽  
Multicriteria Decision Making ◽  
Fuzzy Topsis ◽  
River Basins ◽  
Ideal Solution ◽  
Missing Information ◽  
Nakdong River ◽  
Han River ◽  
Priority Ranking ◽  
The Nakdong River

This study evaluated a fuzzy technique for order performance by similarity to ideal solution (TOPSIS) as a multicriteria decision making system that compensates for missing information with undefined weight factor criteria. The suggested Fuzzy TOPSIS was applied to ten potential dam sites in three river basins (the Han River, the Geum River, and the Nakdong River basins) in South Korea. To assess potential dam sites, the strategic environment assessment (SEA) monitored four categories: national preservation, endangered species, water quality, and toxic environment. To consider missing information, this study applied the Monte Carlo Simulation method with uniform and normal distributions. The results show that effects of missing information generation with one fuzzy set in GB1 site of the Geum River basin are not great in fuzzy positive-ideal solution (FPIS) and fuzzy negative-ideal solution (FNIS) estimations. However, the combination of two fuzzy sets considering missing information in Gohyun stream (NG) and Hoenggye stream (NH) sites of the Nakdong River basin has a great effect on estimating FPIS, FNIS, and priority ranking in Fuzzy TOPSIS applications. The sites with the highest priority ranking in the Han River, Geum River, and Nakdong River basins based on Fuzzy TOPSIS are the Dal stream 1 (HD1), Bocheong stream 2 (GB2) and NG sites. Among the sites in all river basins, the GB2 site had the highest priority ranking. Consequently, the results coincided with findings of previous studies based on multicriteria decision making with missing information and show the applicability of Fuzzy TOPSIS when evaluating priority rankings in cases with missing information.

Evaluating the effectiveness of drones in emergency situations: a hybrid multi-criteria approach

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Justin Zuopeng Zhang ◽  
Praveen Ranjan Srivastava ◽  
Prajwal Eachempati
Keyword(s):  
Fuzzy Ahp ◽  
Use Cases ◽  
Fuzzy Decision Making ◽  
Fuzzy Dematel ◽  
Content Type ◽  
Emergency Situations ◽  
High Rise ◽  
Criteria Weights ◽  
Infrastructure Inspection ◽  
Logistic Support

PurposeThe paper aims to build a customized hybrid multi-criteria model to identify the top three utilities of drones at both personal and community levels for two use cases: firefighting in high-rise buildings and logistic support.Design/methodology/approachA hybrid multi-criterion model that integrates fuzzy analytical hierarchy process (AHP), Best Worst, fuzzy analytical network process (ANP), fuzzy Decision-Making Trial and Evaluation Laboratory (DEMATEL) is used to compute the criteria weights. The weights are validated by a novel ensemble ranking technique further whetted by experts at the community and personal levels to two use cases.FindingsDrones' fire handling and disaster recovery utilities are the most important to fight fire in high-rise buildings at both personal and community levels. Similarly, drones' urban planning, municipal works and infrastructure inspection utilities are the most important for providing logistics support at personal and community levels.Originality/valueThe paper presents a novel multi-criteria approach, i.e. ensemble ranking, by combining the criteria ranking of individual methods – fuzzy AHP, Best-Worst, fuzzy ANP and fuzzy DEMATEL – in the ratio of optimal weights to each technique to generate the consolidated ranking. Domain experts also validate this ranking for robustness. This paper demonstrates a viable methodology to quantify the utilities of drones and their capabilities. The proposed model can be recalibrated for different use case scenarios of drones.

The effects of brand equity and failure severity on remedy choice after a product recall

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Sascha Raithel ◽  
Alexander Mafael ◽  
Stefan J. Hock
Keyword(s):  
Decision Making ◽  
Brand Equity ◽  
Probit Model ◽  
Future Research ◽  
Product Recalls ◽  
Product Recall ◽  
Managerial Decision ◽  
Managerial Decision Making ◽  
Content Type ◽  
Failure Severity

Purpose There is limited insight concerning a firm’s remedy choice after a product recall. This study aims to propose that failure severity and brand equity are key antecedents of remedy choice and provides empirical evidence for a non-linear relationship between pre-recall brand equity and the firm’s remedy offer that is moderated by severity. Design/methodology/approach This study uses field data for 159 product recalls from 60 brands between January 2008 to February 2020 to estimate a probit model of the effects of failure severity, pre-recall brand equity and remedy choice. Findings Firms with higher and lower pre-recall brand equity are less likely to offer full (vs partial) remedy compared to medium level pre-recall brand equity firms. Failure severity moderates this relationship positively, i.e. firms with low and high brand equity are more sensitive to failure severity and then select full instead of partial remedy. Research limitations/implications This research reconciles contradictory arguments and research results about failure severity as an antecedent of remedy choice by introducing brand equity as another key variable. Future research could examine the psychological process of managerial decision-making through experiments. Practical implications This study increases the awareness of the importance of remedy choice during product-harm crises and can help firms and regulators to better understand managerial decision-making mechanisms (and fallacies) during a product-harm crisis. Originality/value This study theoretically and empirically advances the limited literature on managerial decision-making in response to product recalls.

Evaluation of barriers in the adoption of halal certification: a fuzzy DEMATEL approach

2019 ◽  
Vol 14 (1) ◽  
pp. 153-174 ◽  
Author(s):  
Shahbaz Khan ◽  
Mohd Imran Khan ◽  
Abid Haleem
Keyword(s):  
Decision Making ◽  
Design Methodology ◽  
Specific Region ◽  
Integrative Approach ◽  
Decision Making Process ◽  
Management Support ◽  
Fuzzy Dematel ◽  
Content Type ◽  
Certification System ◽  
Expert’S Opinion

PurposeHigher level of customer satisfaction for halal products can be achieved by the effective adoption of halal certification through assessment and accreditation (HCAA). There are certain issues that seem detrimental towards the adoption of HCAA. The purpose of this paper is to identify the major barriers towards the adoption of HCAA and evaluate inter-relationships among them for developing the strategies to mitigate these barriers.Design/methodology/approachThe barriers towards the adoption of HCAA are identified through an integrative approach of literature review and expert’s opinion. The inter-relationship among the identified barriers is evaluated using fuzzy-based decision-making trial and evaluation laboratory (fuzzy DEMATEL) technique, which categorises them into influential and influenced group.FindingsThe evaluation of inter-relationship among barriers using fuzzy DEMATEL indicates four influencing barriers and six influenced barriers towards the adoption of HCAA. Further, findings suggest an extensive government, and management support is vital in terms of commitment, resources and actions to realise the benefits attributed with HCAA.Research limitations/implicationsThe inter-relationship among barriers is contextual and based on the perception of experts which may be biased as per their background and area of expertise. This study pertains to a specific region and can be extended to the generalised certification system.Originality/valueThe empirical base of the research provides the inter-relationship among the barriers towards the adoption of HCAA which can be effectively used as input in the decision-making process by producers, manufacturers and distributor. The policy maker can analyse the cause group and effect group of barriers to formulate policies that would help in the adoption of HCAA.

Grey assessment and prediction of the financial agglomeration degree in central five cities

2014 ◽  
Vol 4 (1) ◽  
pp. 95-103 ◽  
Author(s):  
Li Li ◽  
Guo-hui Hu
Keyword(s):  
Decision Making ◽  
Scientific Development ◽  
Fuzzy Decision Making ◽  
Grey Prediction ◽  
Fuzzy Decision ◽  
Content Type ◽  
Multiple Dimension ◽  
The Government ◽  
Development Tendency ◽  
Decision Making Model

Purpose – At present, financial agglomeration tendency in domestic and foreign countries is increasingly evident. Therefore, from a comparative perspective, this paper aims to assess and predict the financial agglomeration degree in central five cities. Design/methodology/approach – According to the diversity of evaluating indexes and the uncertainty of financial agglomeration, this paper constructs a set of indexes of evaluating the financial agglomeration degree, comprehensively evaluates the financial agglomeration degree of the five cities – Wuhan, Changsha, Zhengzhou, Nanchang and Hefei – in China's middle region from 2001 to 2010 by using the multiple dimension grey fuzzy decision-making model, and predicts their development tendency by using the GM (1, 1, β) model. Findings – The results show that the multiple dimension grey fuzzy decision-making pattern cannot only be used to determine the weights of evaluating indexes, but also get the fuzzy partition and ranking order of the financial agglomeration in central five cities. The grey prediction results can objectively reflect the development tendency of the financial agglomeration in central five cities. Practical implications – From the results, it is necessary for any competitive city to clarify their relative strengths and weaknesses in order for the accurate location and scientific development, and it also provides a reference for the government decision-making. Originality/value – The paper succeeds in using the multiple dimension grey fuzzy decision-making model to measure the financial agglomeration degree of the five central cities and the grey prediction model to predict future trends.

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