8,047 research outputs found
Hesitant Fuzzy Worth: an innovative ranking methodology for hesitant fuzzy subsets
ProducciĂłn CientĂficaWe introduce a novel methodology for ranking hesitant fuzzy sets. It builds on a recent, theoretically sound contribution in Social Choice. In order to justify the applicability of such analysis, we develop two real implementations: (i) new metarankings of world academic institutions that build on real data from three reputed agencies, and (ii) a new procedure for improving teaching performance assessments which we illustrate with real data collected by ourselves.Ministerio de EconomĂa, Industria y Competitividad (Project ECO2012-31933)Ministerio de EconomĂa, Industria y Competitividad (Project ECO2012-32178)Ministerio de EconomĂa, Industria y Competitividad (Project CGL2008-06003-C03-03/CLI)Junta de AndalucĂa (Project P09-SEJ-05404
CUB models: a preliminary fuzzy approach to heterogeneity
In line with the increasing attention paid to deal with uncertainty in
ordinal data models, we propose to combine Fuzzy models with \cub models within
questionnaire analysis. In particular, the focus will be on \cub models'
uncertainty parameter and its interpretation as a preliminary measure of
heterogeneity, by introducing membership, non-membership and uncertainty
functions in the more general framework of Intuitionistic Fuzzy Sets. Our
proposal is discussed on the basis of the Evaluation of Orientation Services
survey collected at University of Naples Federico II.Comment: 10 pages, invited contribution at SIS2016 (Salerno, Italy), in
SIS2016 proceeding
Distributed Linguistic Representations in Decision Making: Taxonomy, Key Elements and Applications, and Challenges in Data Science and Explainable Artificial Intelligence
Distributed linguistic representations are powerful tools for modelling the uncertainty and complexity of preference information in linguistic decision making. To provide a comprehensive perspective on the development of distributed linguistic representations in decision making, we present the taxonomy of existing distributed linguistic representations. Then, we review the key elements and applications of distributed linguistic information processing in decision making, including the distance measurement, aggregation methods, distributed linguistic preference relations, and distributed linguistic multiple attribute decision making models. Next, we provide a discussion on ongoing challenges and future research directions from the perspective of data science and explainable artificial intelligence.National Natural Science Foundation of China (NSFC) 71971039
71421001,71910107002,71771037,71874023
71871149Sichuan University sksyl201705
2018hhs-5
Fusing hotel ratings and reviews with hesitant terms and consensus measures
People have come to refer to reviews for valuable information on products before making a purchase. Digesting relevant opinions regarding a product by reading all the reviews is challenging. An automated methodology which aggregates opinions across all the reviews for a single product to help differentiate any two products having the same overall rating is defined. In order to facilitate this process, rating values, which capture the overall satisfaction, and written reviews, which contain the sentiment of the experience with a product, are fused together. In this manner, each reviewer’s opinion is expressed as an interval rating by means of hesitant fuzzy linguistic term sets. These new expressions of opinion are then aggregated and expressed in terms of a central opinion and degree of consensus representing the agreement among the sentiment of the reviewers for an individual product. A real case example based on 2506 TripAdvisor reviews of hotels in Rome during 2017 is provided. The efficiency of the proposed methodology when discriminating between two hotels is compared with the TripAdvisor rating and median of reviews. The proposed methodology obtains significant differentiation between product rankings.This research has been partially supported by the Secretary of Universities and Research of the Department of Enterprise and Knowledge of the Generalitat de Catalunya (2017 DI 086) and by the INVITE Research Project (TIN2016-80049-C2-1-R and TIN2016-80049-C2-2-R (AEI/FEDER, UE)), funded by the Spanish Ministry of Science and Information Technology.Peer ReviewedPostprint (author's final draft
Heterogeneous group decision making with thermodynamical parameters
There often exist different types of information due to the subjective
and objective criteria in practical decision-making problems,
thus it is necessary to develop some efficient frameworks to
deal with the decision-making problems with heterogeneous
information. The paper proposes a framework for group decisionmaking
problems with heterogeneous information with thermodynamical
parameters consisting of three parts to achieving this
goal. The first part builds the rectifications of criteria weights
according to decision makers’ confidence in evaluations. The
second part adopts thermodynamical parameters to measure the
numerical values and the data distribution of heterogeneous
information to characterize the heterogeneous information fully.
The last part applies the TODIM (an acronym in Portuguese for
Interactive and Multicriteria Decision Making) to aggregate the
decision-making results based on the characterized heterogeneous
information without transforming it into a unified form. By
depicting decision makers’ different sensitive attitudes towards
uncertainty by several mathematical expressions, experiments are
performed to assess the sensitive attitudes’ impacts on decisionmaking
results with the proposed framework. Finally, a case study
on the selection of a green supplier under the low-carbon economy
is provided to illustrate the flexibility and feasibility of the
proposed framework
HFMADM method based on nondimensionalization and its application in the evaluation of inclusive growth
Inclusive growth, which encompasses different aspects of life, is a growth pattern that allows all people to participate in and contribute to growth process. In this paper, a novel hesitant fuzzy multiple attribute decision making (HFMADM) approach based on the nondimensionalization of decision making attributes is presented and then applied to the evaluation of inclusive growth in China. Firstly, a novel generalized hesitant fuzzy distance measure is proposed to calculate the difference and deviation between two hesitant fuzzy elements (hfes) without adding any values into the shorter hesitant fuzzy element. Secondly, the coefficient of variation and efficacy coefficient method are extended to accommodate hesitant fuzzy environment and then used to cope with HFMADM. In the analysis process, non-dimensional treatment for hesitant fuzzy decision data is produced. Lastly, the method proposed in this paper is applied to an example of inclusive growth evaluation problem under hesitant fuzzy environment and the case study illustrates the practicality of the proposed method. Beyond that, a comparative analysis with some other approaches is also conducted to demonstrate the superiority and feasibility of the proposed method
An overview of fuzzy multi-criteria decisionmaking methods in hospitality and tourism industries: bibliometrics, methodologies, applications and future directions
Stakeholders in hospitality and tourism industries are involved in
many decision-making scenarios. Multi-criteria decision-making
(MCDM) methods have been widely used in hospitality and tourism
industries. Although some articles summarised the applications of
MCDM models in hospitality and tourism industries, they ignored the
fuzziness of individual cognition in an uncertain environment. In addition,
these surveys lacked a comprehensive overview from the perspective
of bibliometrics analysis and content analysis regarding the
whole hospitality and tourism industries. To analyse the applications
of fuzzy MCDM methods in hospitality and tourism industries and
further explore future research directions, this article reviews 85
selected papers published from 1997 to 2022 regarding fuzzy MCDM
models applied in hospitality and tourism industries. Through analysing
the results of bibliometric analysis, methodologies and applications,
we found that analytic hierarchy process (AHP) and TOPSIS
methods are the most widely used MCDM methods, and tourism
evaluation, hotel evaluation and selection, tourism destination evaluation
and selection are the most attractive research issues in hospitality
and tourism industries. Finally, future research directions are
proposed from three aspects. This article provides insights for
researchers and practitioners who have interest in fuzzy MCDM models
in hospitality and tourism industries
- …