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A special issue of Mathematics (ISSN 2227-7390). This special issue belongs to the section "Fuzzy Sets, Systems and Decision Making".

Deadline for manuscript submissions: closed (29 February 2024) | Viewed by 23247

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Dr. Jorge de Andres Sanchez

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Social and Business Research Laboratory, Rovira i Virgili University, Campus Bellissens, Av. de la Universitat 1, 43204 Reus, Spain
Interests: fuzzy sets; fuzzy data analysis; actuarial modeling; social inequality policies
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Dr. Laura González-Vila Puchades

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Department of Mathematics for Economics, Finance and Actuarial Science, University of Barcelona, Av. Diagonal 690, 08034 Barcelona, Spain
Interests: fuzzy set theory applications on finance and insurance; actuarial and uncertainty modeling
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Since the publication of Lotfi A. Zadeh’s seminal paper “Fuzzy Sets” in 1965 in the journal Information and Control, there has been a constant growth in the theoretical developments and practical applications of fuzzy set theory and related mathematical tools. These tools have been widely applied, both in industry and academic research, to decision making and economics due to their versatility. On the one hand, they can efficiently represent and handle uncertain and vague information as subjective judgements, non-precise observations on variables, or ill-defined relations between variables. On the other hand, they make implementing computations or identifying patterns in data much easier. To do so, fuzzy set theory provides a multitude of mathematical techniques in fields such as expert systems, soft computing, data analysis, mathematical programming, or multiple criteria decision making. Asset pricing, portfolio selection, actuarial modeling, or capital budgeting problems are some examples of practical applications in these fields. This Special Issue provides a platform for researchers from academia and industry to present their novel and unpublished works in the domain of the applied developments of fuzzy sets and related methodologies to business, financial, and economic analysis. This will help to foster future research in the emerging fields of economics and social sciences.

Dr. Jorge de Andres Sanchez
Dr. Laura González-Vila Puchades
Guest Editors

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Keywords

fuzzy reasoning
soft computing
fuzzy data analysis
fuzzy set qualitative comparative analysis
mathematical programming
multiple criteria decision making
expert systems
fuzzy neural systems
fuzzy game theory
intuitionistic and neutrosophic sets
fuzzy modeling in economics
business management and finance

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Published Papers (12 papers)

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Research

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38 pages, 2341 KiB

Open AccessArticle

Analyzing Primary Sector Selection for Economic Activity in Romania: An Interval-Valued Fuzzy Multi-Criteria Approach

by Alina Elena Ionașcu, Shankha Shubhra Goswami, Alexandra Dănilă, Maria-Gabriela Horga, Corina Aurora Barbu and Adrian Şerban-Comǎnescu

Mathematics 2024, 12(8), 1157; https://doi.org/10.3390/math12081157 - 11 Apr 2024

Cited by 4 | Viewed by 1106

Abstract

This study presents an in-depth analysis of the selection process for primary sectors impacting the economic activity in Romania, employing an interval-valued fuzzy (IVF) approach combined with multi-criteria decision-making (MCDM) methodologies. This research aims to identify eight key criteria influencing the selection of Romanian primary sectors, including technology adaptation, infrastructure development and investment, gross domestic product (GDP), sustainability, employment generation, market demand, risk management and government policies. The current analysis evaluates eight primary sector performances against these eight criteria through the application of three MCDM methods, namely, Simple Additive Weighting (SAW), Weighted Product Model (WPM), and Weighted Aggregated Sum Product Assessment (WASPAS). Ten economic experts comprising a committee have been invited to provide their views on the criteria’s importance and the alternatives’ performance. Based on the decision-maker’s qualitative judgement, GDP acquires the highest weightage, followed by environmental impact and sustainability, thus indicating the most critical factors among the group. The IVF-MCDM hybrid model indicates the energy sector as Romanian primary sector with the most potential, followed by the agriculture and forestry sector among the list of eight alternatives. It also explores the robustness of results by considering sensitivity analysis and the potential impacts of political and international factors, such as pandemics or armed conflicts, on sector selection. The findings indicate consistency in sector rankings across the different methodologies employed, underscoring the importance of methodological choice and criteria weighting. Additionally, this study sheds light on the potential influence of political and international dynamics on sector prioritization, emphasizing the need for comprehensive decision-making frameworks in economic planning processes. Full article

(This article belongs to the Special Issue Fuzzy Sets in Business Management, Finance, and Economics, 2nd Edition)

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26 pages, 2030 KiB

Open AccessArticle

Research on the Improvement Path of Total Factor Productivity in the Industrial Software Industry: Evidence from Chinese Typical Firms

by Xiaoxiang Wang, Songling Wu and Lixiang Zhao

Mathematics 2023, 11(24), 4944; https://doi.org/10.3390/math11244944 - 13 Dec 2023

Viewed by 1131

Abstract

The high-quality development of the industrial software industry is of strategic significance to enhancing the core competitiveness of the manufacturing industry and promoting the high-quality development of China’s industrial economy. By integrating the “capital-technology-environment-human” production factor theory and configuration perspective, this paper constructs a comprehensive analysis framework that drives the total factor productivity (TFP) of the industrial software industry. This paper uses 40 typical industrial software firms in 2018–2020 as case samples and uses fuzzy set Qualitative Comparative Analysis (fsQCA) to empirically explore the influencing factors and complex mechanisms that achieve high-quality development of the industrial software industry. It is found that: (1) a single industrial factor is hardly a necessary condition to drive the industrial software industry; (2) there are four paths to achieving high TFP, which are summarized as “technical-human-environmental” balanced driving type, “capital-human-environmental” balanced driving type, “technical-capital” dual driving type, and “capital” single driving type. There are four driving mechanisms. There are also four not-high TFP configurations with asymmetric characteristics; (3) under certain conditions, the combination of capital factors, technical factors, environmental factors, and human factors can drive TFP in an “all roads lead to Rome”. In this process, the government’s attention plays a more universal role. The study not only expands the application scenarios of fsQCA but also provides decision guidelines for the practice of strategic emerging industrialization represented by the industrial software industry. Full article

(This article belongs to the Special Issue Fuzzy Sets in Business Management, Finance, and Economics, 2nd Edition)

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22 pages, 789 KiB

Open AccessArticle

Fuzzy Assessment of Management Consulting Projects: Model Validation and Case Studies

by Hongyi Sun, Wenbin Ni and Lanxuan Huang

Mathematics 2023, 11(20), 4381; https://doi.org/10.3390/math11204381 - 21 Oct 2023

Cited by 2 | Viewed by 1372

Abstract

Management consulting (MC) has been heavily involved in emerging business opportunities in mainland China. However, there are no well-known local MC project management models to help evaluate whether an MC project can be successful or not. This paper reports a model for the self-assessment of management consulting projects, which has been validated by 15 experts and 13 cases. The new model, with seven factors that are critical to the success of MC projects, was developed from a literature review. The model was then verified by developing a questionnaire that was sent to 15 experts and using Dempster–Shafer theory to obtain the weight of each part of the model. The model was applied to 13 real cases to verify its effectiveness in evaluating an MC project. This new MC model can help consulting teams to conduct assessments in the early and middle stages, and evaluate in the late stage, of consulting projects, and also can help teams improve the probability of project success and client satisfaction. It can be used by consultants, client companies, or both. Full article

(This article belongs to the Special Issue Fuzzy Sets in Business Management, Finance, and Economics, 2nd Edition)

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38 pages, 2427 KiB

Open AccessArticle

Fuzzy Analytic Network Process with Principal Component Analysis to Establish a Bank Performance Model under the Assumption of Country Risk

by Alin Opreana, Simona Vinerean, Diana Marieta Mihaiu, Liliana Barbu and Radu-Alexandru Șerban

Mathematics 2023, 11(14), 3257; https://doi.org/10.3390/math11143257 - 24 Jul 2023

Cited by 3 | Viewed by 1912

Abstract

In recent years, bank-related decision analysis has reflected a relevant research area due to key factors that affect the operating environment of banks. This study’s aim is to develop a model based on the linkages between the performance of banks and their operating context, determined by country risk. For this aim, we propose a multi-analytic methodology using fuzzy analytic network process (fuzzy-ANP) with principal component analysis (PCA) that extends existing mathematical methodologies and decision-making approaches. This method was examined in two studies. The first study focused on determining a model for country risk assessment based on the data extracted from 172 countries. Considering the first study’s scores, the second study established a bank performance model under the assumption of country risk, based on data from 496 banks. Our findings show the importance of country risk as a relevant bank performance dimension for decision makers in establishing efficient strategies with a positive impact on long-term performance. The study offers various contributions. From a mathematic methodology perspective, this research advances an original approach that integrates fuzzy-ANP with PCA, providing a consistent and unbiased framework that overcomes human judgement. From a business and economic analysis perspective, this research establishes novelty based on the performance evaluation of banks considering the operating country’s risk. Full article

(This article belongs to the Special Issue Fuzzy Sets in Business Management, Finance, and Economics, 2nd Edition)

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16 pages, 1423 KiB

Open AccessArticle

Fuzzy Logic to Measure the Degree of Compliance with a Target in an SDG—The Case of SDG 11

by Javier Parra-Domínguez, Maria Alonso-García and Juan Manuel Corchado

Mathematics 2023, 11(13), 2967; https://doi.org/10.3390/math11132967 - 3 Jul 2023

Cited by 3 | Viewed by 1509

Abstract

Sustainable development and its significant challenges motivate various international organisations in a way that has never been seen before. With Europe at the forefront, countries such as the United States want to be included in the progress and what a clear and determined commitment to sustainability means for future generations. Our study aimed to go deeper into the follow-up and monitoring of the development of reliable indicators that make the continuous improvement process in sustainability robust. To this end, and using the fuzzy logic methodology, we applied it to one of the indices that have been developed to date, the “Sustainable Development Report” (in its 2022 edition), working on the specific application of SDG 11. Our results show favourable positions for countries such as Brunei Darussalam, Tonga, Tuvalu, Andorra, and the Netherlands and provide robustness when there is a lack of data quality and improvements in the implementation of the process when experts intervene. Full article

(This article belongs to the Special Issue Fuzzy Sets in Business Management, Finance, and Economics, 2nd Edition)

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34 pages, 3907 KiB

Open AccessArticle

A Fully Completed Spherical Fuzzy Data-Driven Model for Analyzing Employee Satisfaction in Logistics Service Industry

by Phi-Hung Nguyen

Mathematics 2023, 11(10), 2235; https://doi.org/10.3390/math11102235 - 10 May 2023

Cited by 9 | Viewed by 3507

Abstract

This study proposes a two-stage MCDM model that combines Delphi and decision-making trial and evaluation laboratory methods based on spherical fuzzy sets (SF-Delphi and SF-DEMATEL) to analyze the motivation and demotivation factors affecting employee satisfaction in the Vietnamese logistics service industry. In the first stage, the SF-Delphi approach is used to gather expert opinions and develop consensus on the significance of criteria. In the second stage, the SF-DEMATEL technique explores causal linkages between the criteria and identifies root causes of the issues. Based on a comprehensive literature review and feedback from 40 experts, this study identified crucial factors affecting employee satisfaction related to both motivation and demotivation aspects. The findings of this study provide recommendations for managers to improve employee satisfaction, such as establishing clear and detailed wage and bonus rules, offering training courses, developing a positive work culture, recognizing employee efforts, and addressing poor treatment by supervisors and inadequate leadership support. Furthermore, the proposed model accurately identifies essential elements, represents uncertainty, adapts to various contexts, has resilience and accuracy, and has practical implications for mitigating demotivating factors and enhancing motivation, thereby positively influencing employee satisfaction in the logistics service industry. Full article

(This article belongs to the Special Issue Fuzzy Sets in Business Management, Finance, and Economics, 2nd Edition)

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21 pages, 1236 KiB

Open AccessArticle

Study on the Selection of Pharmaceutical E-Commerce Platform Considering Bounded Rationality under Probabilistic Hesitant Fuzzy Environment

by Zixue Guo and Sijia Liu

Mathematics 2023, 11(8), 1859; https://doi.org/10.3390/math11081859 - 13 Apr 2023

Cited by 3 | Viewed by 1426

Abstract

The selection of a pharmaceutical e-commerce platform is a typical multi-attribute group decision-making (MAGDM) problem. MAGDM is a common problem in the field of decision-making, which is full of uncertainty and fuzziness. A probabilistic hesitant fuzzy multi-attribute group decision-making method based on generalized TODIM is proposed for the selection of pharmaceutical e-commerce under an uncertain environment. Firstly, the credibility of a probabilistic hesitant fuzzy element is defined, and a credibility-based method for adjusting the weights of decision-makers and determining attribute weights is proposed, which fully considers the reliability of information provided by the decision-makers. Secondly, the power average (PA) operator is extended to the probabilistic hesitant fuzzy environment. The probabilistic hesitant fuzzy power average (PHFPA) operator and the probabilistic hesitant fuzzy power weighted average (PHFPWA) operator are defined, and their properties are discussed. Thirdly, considering the usual information expression of decision-makers in real life and the different risk attitudes towards gain and loss, the generalized TODIM method is extended to the probabilistic hesitant fuzzy environment to construct a prospect theory-based group decision-making method in the probabilistic hesitant fuzzy environment. Finally, the feasibility of the method in this paper is proved through the case of pharmaceutical e-commerce platform selection, and the stability of the method in this paper is verified by sensitivity analysis. Full article

(This article belongs to the Special Issue Fuzzy Sets in Business Management, Finance, and Economics, 2nd Edition)

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19 pages, 985 KiB

Open AccessArticle

Innovation in Brazilian Industries: Analysis of Management Practices Using Fuzzy TOPSIS

by Giulia Giacomello Pompilio, Tiago F. A. C. Sigahi, Izabela Simon Rampasso, Gustavo Hermínio Salati Marcondes de Moraes, Lucas Veiga Ávila, Walter Leal Filho and Rosley Anholon

Mathematics 2023, 11(6), 1313; https://doi.org/10.3390/math11061313 - 8 Mar 2023

Cited by 12 | Viewed by 2236

Abstract

This study examined the practices of innovation management used by Brazilian industries. A survey was carried out with specialists that assessed 27 practices (PR) proposed by ISO 56002, considering two types of firms: small and medium-sized industries (SMI) and large industries (LI). The methodological approach included Hierarchical Cluster Analysis to identify the similarities between the specialists and define levels of specialists, as well as Fuzzy TOPSIS and frequency and sensitivity analyses to examine their responses. PR1 (analysis of internal and external issues that impact innovation management) was deemed the best practice for LIs, whereas PR10 (adequate assessment of potential partnerships) was best evaluated for SMIs. The PR27 (periodic audits to identify opportunities for improvement) received the lowest rating from both LIs and SMIs. In general, SMIs in the Brazilian context have more severe deficiencies in terms of applying innovation management practices than LIs. A broad overview of the innovation practices adopted in the Brazilian industrial scenario is provided. The study’s findings may assist managers and policymakers to develop initiatives and actions to improve the capacity of Brazilian industries to innovate. This research can also support future studies aimed at better understanding specific practices related to the topic. Full article

(This article belongs to the Special Issue Fuzzy Sets in Business Management, Finance, and Economics, 2nd Edition)

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35 pages, 1954 KiB

Open AccessArticle

Forgotten Factors in Knowledge Conversion and Routines: A Fuzzy Analysis of Employee Knowledge Management in Exporting Companies in Boyacá

by Fabio Blanco-Mesa, Omar Vinchira and Yesica Cuy

Mathematics 2023, 11(2), 412; https://doi.org/10.3390/math11020412 - 12 Jan 2023

Cited by 2 | Viewed by 1652

Abstract

The department of Boyacá accounts for only 0.93% of national exports, which means that the participation of exporting companies in the region is low. One of the most important factors within these organizations is the knowledge of the collaborators, since it is an asset that contributes to the daily activities carried out within an organization. Hence, the objective of this research was to analyze the incidence of the forgotten factors in knowledge management through the conversion of knowledge and the routines of the personnel in Boyacá’s exporting companies, by means of causal analysis using fuzzy methodologies. The participants are exporting activity collaborators in the companies, who were consulted as sources of information for the Boyacá chamber of commerce. For the treatment, the forgotten effects theory, the experton method, and the adequacy coefficient are used. The information collected is processed using FuzzyLog software. The findings highlight that there are forgotten factors between the knowledge conversion and routines related to informal communication and social interactions. It is worth noting that it is important to carry out a more in-depth analysis of each of the individual knowledge spiral pillars in exporting companies in different regions of the country, focusing on social interactions (linguistic expression) and informal communication (electronic meetings). Full article

(This article belongs to the Special Issue Fuzzy Sets in Business Management, Finance, and Economics, 2nd Edition)

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20 pages, 4328 KiB

Open AccessArticle

Algorithm Applied to SDG13: A Case Study of Ibero-American Countries

by Luciano Barcellos-Paula, Anna María Gil-Lafuente and Aline Castro-Rezende

Mathematics 2023, 11(2), 313; https://doi.org/10.3390/math11020313 - 7 Jan 2023

Cited by 2 | Viewed by 2064

Abstract

Scientific studies confirm the existence of a crisis caused by climate change, in which global causes produce local effects. Despite climate agreements, greenhouse gas emissions continue to fall short of targets to limit global warming. There is still a need for comparable data for Sustainable Development Goal (SDG) 13—Climate Action. The motivation of the research is to provide data for decision-making and to propose solutions to address the climate crisis. The article aims to propose a Fuzzy Logic algorithm to evaluate the SDG13 indicators and to deepen the discussion on climate change. The research is applied explanatory with a combined approach (quantitative-qualitative) through modeling, simulation, and case studies. As a result, the OWA operator ranks 10 Ibero-American countries to SDG13, indicating Colombia, Peru, and Cuba in the first positions. The main contributions are the reduction of identified knowledge gaps and proposals for action for policy and decision-makers. A limitation of this study would be the number of participating countries. The authors indicate future lines of research. Full article

(This article belongs to the Special Issue Fuzzy Sets in Business Management, Finance, and Economics, 2nd Edition)

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16 pages, 345 KiB

Open AccessArticle

Correlational and Configurational Analysis of Factors Influencing Potential Patients’ Attitudes toward Surgical Robots: A Study in the Jordan University Community

by Jorge de Andres-Sanchez, Ala Ali Almahameed, Mario Arias-Oliva and Jorge Pelegrin-Borondo

Mathematics 2022, 10(22), 4319; https://doi.org/10.3390/math10224319 - 17 Nov 2022

Cited by 4 | Viewed by 2130

Abstract

The literature on surgical robots (SRs) usually adopts the perspective of healthcare workers. However, research on potential patients’ perceptions and the publics’ points of view on SRs is scarce. This fact motivates our study, which assesses the factors inducing the SRs acceptance in the opinion of potential patients. We consider three variables, based on the unified theory of acceptance and the use of technology (UTAUT): the performance expectancy (PE), the effort expectancy (EE), and the social influence (SI); pleasure (PL), arousal (AR), and the perceived risk (PR). To deal with empirical data, we used the ordered logistic regression (OLR) and the fuzzy set comparative qualitative analysis (fsQCA). The OLR allowed us to check for a significant positive average influence of the UTAUT variables and PL, on the intention to undergo robotic surgery. However, the PR had a significant negative impact, and AR was not found to be significant. The FsQCA allowed the identification of the potential patient profiles, linked to acceptance of and resistance to SRs and confirmed that they are not symmetrical. The proposed input variables are presented as core conditions in at least one prime implicate robotic-assisted surgery acceptance. The exception to this statement is the PR, which is affirmed in some recipes and absent in others. The recipes explaining the resistance to SRs were obtained by combining the absence of PE, EE, SI, and PL (i.e., these variables have a negative impact on rejection) and the presence of the PR (i.e., the perceived risk has a positive impact on a resistance attitude toward SRs). Similarly, arousal played a secondary role in explaining the rejection. Full article

(This article belongs to the Special Issue Fuzzy Sets in Business Management, Finance, and Economics, 2nd Edition)

Review

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21 pages, 1570 KiB

Open AccessReview

Fuzzy Random Option Pricing in Continuous Time: A Systematic Review and an Extension of Vasicek’s Equilibrium Model of the Term Structure

by Jorge de Andrés-Sánchez

Mathematics 2023, 11(11), 2455; https://doi.org/10.3390/math11112455 - 25 May 2023

Cited by 2 | Viewed by 1509

Abstract

Fuzzy random option pricing in continuous time (FROPCT) has emerged as an active research field over the past two decades; thus, there is a need for a comprehensive review that provides a broad perspective on the literature and identifies research gaps. In this regard, we conducted a structure review of the literature by using the WoS and SCOPUS databases while following the PRISMA criteria. With this review, we outline the primary research streams, publication outlets, and notable authors in this domain. Furthermore, the literature review revealed a lack of advancements for the equilibrium models of the yield curve. This finding serves as a primary motivation for the second contribution of this paper, which involves an extension of Vasicek’s yield curve equilibrium model. Specifically, we introduce the existence of fuzzy uncertainty in the parameters governing interest rate movements, including the speed of reversion, equilibrium short-term interest rate, and volatility. By incorporating fuzzy uncertainty, we enhance the model’s ability to capture the complexities of real-world interest rate dynamics. Moreover, this paper presents an empirical application of the proposed extension to the term structure of fixed-income public bonds in European Union. The empirical analysis suggests the suitability of the proposed extension of Vasicek’s model for practical applications. Full article

(This article belongs to the Special Issue Fuzzy Sets in Business Management, Finance, and Economics, 2nd Edition)

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