Double hierarchy hesitant fuzzy linguistic entropy-based TODIM approach using evidential theory

Лю, Пэйдэ; Shen, Mengjiao; Teng, Fei; Zhu, Baoying; Rong, Lili; Geng, Yushui

doi:10.1016/j.ins.2020.07.062

Cited by 79 publications

(26 citation statements)

References 40 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…29 HFLTSs have attracted much attention from scholars and researchers in the decisionmaking field. 30 Many variants of HFLTSs have been put forward, such as the double hierarchy linguistic term set (LTS), 31,32 unbalanced HFLTS, 33 hesitant probabilistic fuzzy linguistic set, 34 and hesitant multiplicative LTSs. 35 HFLTSs have various applications, such as the evaluation of landfill sites, 36 medicine selection, 37 recommender system, 38 and healthcare service.…”

Section: Studies On Handling Hfltssmentioning

confidence: 99%

Evaluation of startup companies using multicriteria decision making based on hesitant fuzzy linguistic information envelopment analysis models

Lin

Chen

et al. 2021

Int J Intell Syst

View full text Add to dashboard Cite

Evaluating startup companies is an important management process for technology business incubators and it is also a typical multicriteria decision‐making (MCDM) problem. There exist various methods that have proposed to solve MCDM problems, but these methods heavily depend on the exact criteria weight values. The decision results of these methods are unstable. Moreover, they cannot provide the improvement suggestions for the nonoptimal startup companies. To overcome these two drawbacks, we propose a novel hesitant fuzzy linguistic decision‐making method to solve the problem of evaluating startup companies. To this end, a novel semantic comparison method based on the experts' psychology and the ratio of score value to deviation degree is proposed to compare the hesitant fuzzy linguistic term sets. Then, a novel definition of hesitant fuzzy linguistic information envelopment efficiency (HFLIEE) is proposed, based on which, a novel hesitant fuzzy linguistic information envelopment analysis (HFLIEA) model and a novel preference model are proposed. By solving these models, all the alternatives can be ranked and nonoptimal alternatives can be improved. Finally, the numerical analysis is given to illustrate the applicability of the proposed models and the robustness analyses of the proposed models are provided. At the same time, they are compared with the previous hesitant fuzzy linguistic decision‐making methods.

show abstract

Section: Studies On Handling Hfltssmentioning

confidence: 99%

Evaluation of startup companies using multicriteria decision making based on hesitant fuzzy linguistic information envelopment analysis models

Lin

Chen

et al. 2021

Int J Intell Syst

View full text Add to dashboard Cite

show abstract

“…Therefore, Zadeh [ 39 ] developed the fuzzy method to process human-centered problems with uncertainty and ambiguity in languages. Moreover, previous researchers [ 24 , 33 ] extended the fuzzy method to analyze the vagueness in consumer and expert-language expressions. Furthermore, Liu and Cheng [ 34 ] improved the MABAC method to analyze ambiguous information from decision-makers.…”

Section: Literature Reviewmentioning

confidence: 99%

“…This method determined the objective weights based on cross-entropy and entropy measures with probabilistic linguistic information. Liu et al [ 33 ] adopted the double hierarchy hesitant fuzzy linguistic entropy-based TODIM approach to examine fuzzy linguistic terms. Liu and Cheng [ 34 ] improved the MABAC method and established a three-phase multi-attribute group decision-making (MAGDM) method to analyze the preference of decision-makers and to describe inconsistent and ambiguous information.…”

Section: Literature Reviewmentioning

confidence: 99%

Improving Service Quality of Wealth Management Bank for High-Net-Worth Customers During COVID-19: A Fuzzy-DEMATEL Approach

Lin

Chang

Huang

et al. 2021

Int. J. Fuzzy Syst.

View full text Add to dashboard Cite

The 2019–2020 COVID-19 pandemic has caused an economic turndown and high volatility in the global financial markets. Determining the factors that influence services to high-net-worth customers who typically have large investments in the financial markets is important for wealth management banks. This study constructs a hybrid approach by integrating the fuzzy logic and Decision-making Trial and Evaluation Laboratory (DEMATEL) methods to identify the most influential criteria affecting the performance of wealth management banks in Taiwan during the 2019–2020 COVID-19 pandemic. Surveys and interviews are designed using four dimensions (bank performance, service quality, customer relationship, and COVID-19) and 16 criteria for 10 banking executives using fuzzy linguistic scales, to obtain their expert opinions. The results show the order of influence as being service quality, customer relationships, bank performance, and COVID-19. The most important criteria are customized investment information (in-service quality), switching behavior (in-customer relationship), fee income (in-bank performance), and the number of confirmed cases in the top five countries affected by COVID-19. The managerial implication is that wealth management banks should focus on improving their service quality. Banks may strive to provide a wide range of customized investment information and increase customers’ usage of personalized financial products and services. The results of this study will benefit bank managers in serving high-net-worth individuals during the crisis period.

show abstract

“…The main applications of HFLTS are situations where an expert hesitates with several values in evaluating linguistic variables and where it is difficult for them to provide a single linguistic term as an appropriate expression of their knowledge. HFLTSs express the uncertainty of information with better effect than HFSs 46 . Xiong et al 47 classified such differences into two aspects according to the source of hesitancy.…”

Section: Introductionmentioning

confidence: 99%

“…However, these methods do not consider the proportional information of each linguistic term in a GDM context, which can represent the support for each linguistic term derived from the experts. There are also some challenges in the development of HFLTS, such as modeling complex linguistic information during decision‐making 46,53 . Due to this, Wang and Hao 54 introduced a proportional 2‐tuple linguistic information representational model.…”

Section: Introductionmentioning

confidence: 99%

Power‐average‐operator‐based hybrid multiattribute online product recommendation model for consumer decision‐making

et al. 2021

View full text Add to dashboard Cite

This study develops a power‐average‐operator‐based hybrid multiattribute online product recommendation model that considers the consumer's risk attitude to rank categoric product options as a complement to existing recommender systems. Online production recommendation plays a key role in the development of e‐commerce, and can greatly improve consumers' shopping experiences. However, few online shopping sites provide interactive decision aids for consumers such that they can articulate their preferences towards multiple selection attributes with the purpose of mitigating choice difficulty and improving decision quality. Additionally, consumers' risk attitudes to online shopping dramatically impact their product choices. In the model proposed in this paper, the risk attitude‐based power average (RAPA) operator is used to integrate the risk attitude of the decision‐maker into the information fusion process of multiple attribute decision‐making. Subsequently, the risk attitude function, with several basic types, is introduced to quantify the risk attitude of the decision‐maker for use in the RAPA operator. A proportional hesitant fuzzy 2‐tuple linguistic term set (PHF2TLTS) is constructed by incorporating a binary of linguistic information aiming to comprehensively analyze the hybrid product information. With a focus on the information fusion process, the proportional hesitant 2‐tuple linguistic RAPA operator and weighted proportional hesitant 2‐tuple linguistic RAPA operator are introduced to aggregate a given set of PHF2TLTSs. The validity of the proposed model is demonstrated using an illustrative example, a comparison with existing approaches and detailed explanations of the performance differences.

show abstract

Double hierarchy hesitant fuzzy linguistic entropy-based TODIM approach using evidential theory

Cited by 79 publications

References 40 publications

Evaluation of startup companies using multicriteria decision making based on hesitant fuzzy linguistic information envelopment analysis models

Evaluation of startup companies using multicriteria decision making based on hesitant fuzzy linguistic information envelopment analysis models

Improving Service Quality of Wealth Management Bank for High-Net-Worth Customers During COVID-19: A Fuzzy-DEMATEL Approach

Power‐average‐operator‐based hybrid multiattribute online product recommendation model for consumer decision‐making

Contact Info

Product

Resources

About