Interval type-2 fuzzy multi-attribute decision-making approaches for evaluating the service quality of Chinese commercial banks

The file attached to this record is the author's final peer reviewed version. The Publisher's final version can be found by following the DOI link.In today’s world, with increased competition, the service quality of Chinese commercial banks is recognized as a major factor that is responsible for enhancing competitiveness. Therefore, it is necessary to evaluate and analyse the service quality of Chinese commercial banks to realize their stable development. The service quality evaluation could be recognized as a multi-attribute decision-making (MADM) problem with multiple assessment attributes, both being of a qualitative and quantitative nature. Owing to the growing complexity and high uncertainty of the financial environment, the assessments of attributes cannot always possibly express using a real and/or type-1 fuzzy number. Additionally, a heterogeneous relationship often exists among the attributes under many real decision cases. In this study, we create two MADM approaches to handle decision-making problems with interval type-2 fuzzy numbers (IT2FNs) and offer their application to service quality evaluations of commercial banks problems. Specifically, we first define some operations on IT2FNs based on Archimedean T-norms (ATs) and develop a bi-directional projection measure of IT2FNs. Next, by combining the generalized Banzhaf index, the Choquet integral and IT2FNs, we propose the interval type-2 fuzzy Archimedean Choquet (IT2FAC) operator, the Banzhaf IT2FAC (BIT2FAC) operator and the 2-additive BIT2FAC (2ABIT2FAC) operator. Then, we establish two optimal models for deriving the weights of attributes based on a bi-directional projection measure of IT2FNs and Banzhaf function. Finally, we create two novel MADM methods under interval type-2 fuzzy contexts, where an illustrative case concerning the service quality evaluation of Chinese commercial banks is used to explain the created MADM approaches

18th ICPR paper: INDUSTRIAL PERFORMANCE MEASUREMENT: AN APPROACH BASED ON THE AGGREGATION OF UNIPOLAR OR BIPOLAR EXPRESSIONS

International audienceIndustrial performance concerns numerous criteria, often in interaction and of complex nature, not related to one elementary measure. Performance Measurement Systems (PMSs) have been developed to support decision-making for reaching the objectives and launching adequate action plans. PMSs provide thus performance expressions which identify objective satisfaction degrees. Two kinds of performance expressions are useful in industrial problems, according to the scale (unipolar, bipolar) that is used for their definition. Moreover, these expressions generally have to be synthesized for global control purposes, determining an overall performance raises the issue of performance aggregation. To address such an aggregation issue, adequate multi-criteria methods need to be implemented. Most of the approaches proposed in the literature either do not provide explicit mechanisms, or rely on too simple methods. This paper deals with the definition of a performance combination based on mathematical tools, especially the generalized Choquet integral to take into account on the one hand criteria interactions and on the other hand both unipolar and bipolar scales. An application to a PMS for the service rate of a SME producing kitchen elements is used to illustrate the approach

A multi-attribute decision making procedure using fuzzy numbers and hybrid aggregators

The classical Analytical Hierarchy Process (AHP) has two limitations. Firstly, it disregards the aspect of uncertainty that usually embedded in the data or information expressed by human. Secondly, it ignores the aspect of interdependencies among attributes during aggregation. The application of fuzzy numbers aids in confronting the former issue whereas, the usage of Choquet Integral operator helps in dealing with the later issue. However, the application of fuzzy numbers into multi-attribute decision making (MADM) demands some additional steps and inputs from decision maker(s). Similarly, identification of monotone measure weights prior to employing Choquet Integral requires huge number of computational steps and amount of inputs from decision makers, especially with the increasing number of attributes. Therefore, this research proposed a MADM procedure which able to reduce the number of computational steps and amount of information required from the decision makers when dealing with these two aspects simultaneously. To attain primary goal of this research, five phases were executed. First, the concept of fuzzy set theory and its application in AHP were investigated. Second, an analysis on the aggregation operators was conducted. Third, the investigation was narrowed on Choquet Integral and its associate monotone measure. Subsequently, the proposed procedure was developed with the convergence of five major components namely Factor Analysis, Fuzzy-Linguistic Estimator, Choquet Integral, Mikhailov‘s Fuzzy AHP, and Simple Weighted Average. Finally, the feasibility of the proposed procedure was verified by solving a real MADM problem where the image of three stores located in Sabak Bernam, Selangor, Malaysia was analysed from the homemakers‘ perspective. This research has a potential in motivating more decision makers to simultaneously include uncertainties in human‘s data and interdependencies among attributes when solving any MADM problems

A Tabu Search Based Metaheuristic for Dynamic Carpooling Optimization

International audienceThe carpooling problem consists in matching a set of riders' requests with a set of drivers' offers by synchronizing their origins, destinations and time windows. The paper presents the so-called Dynamic Carpooling Optimization System (DyCOS), a system which supports the automatic and optimal ridematching process between users on very short notice or even en-route. Nowadays, there are numerous research contributions that revolve around the carpooling problem, notably in the dynamic context. However, the problem's high complexity and the real time aspect are still challenges to overcome when addressing dynamic carpooling. To counter these issues, DyCOS takes decisions using a novel Tabu Search based metaheuristic. The proposed algorithm employs an explicit memory system and several original searching strategies developed to make optimal decisions automatically. To increase users' satisfaction, the proposed metaheuristic approach manages the transfer process and includes the possibility to drop off the passenger at a given walking distance from his destination or at a transfer node. In addition, the detour concept is used as an original aspiration process, to avoid the entrapment by local solutions and improve the generated solution. For a rigorous assessment of generated solutions , while considering the importance and interaction among the optimization criteria, the algorithm adopts the Choquet integral operator as an aggregation approach. To measure the effectiveness of the proposed method, we develop a simulation environment based on actual carpooling demand data from the metropolitan area of Lille in the north of France

Modeling of the Liquidity Evaluation on Stock Markets

In the article the technology of securities rating creation is worked out. The peculiarities of this technology are fuzzy classification of particular liquidity indices, their subsets picking out and joint significance calculation. These peculiarities allow smoothing of extreme values influence in the generalized rating. The rating model is based on the multicriteria analysis by means of Choquet integral calculation. Method of such analysis is adapted to economic informatics processing. A numeric example of share rating creation with using of Belarus stock market data is represented

A study on measuring the quality of university website

During the past few years, many organizations try to provide some of their services through their websites. This would help them provide fast and reliable services to various people around the world. In this paper, we present an empirical survey to measure the relative performance of a university website in Iran using Parasuraman's technological readiness index. The proposed study uses a standard questionnaire and distributes it among 387 active website users and the results are analyzed using structural equation modeling. The proposed study of this paper considers the effects of four factors including efficiency, accessibility, achievement and security on customer loyalty via two variables of trust and satisfaction. The results demonstrate that three components of trust, efficiency and achievement play essential role on customer loyalty

Interval-Valued Intuitionistic Fuzzy Einstein Geometric Choquet Integral Operator and Its Application to Multiattribute Group Decision-Making

With respect to the multiattribute decision-making (MADM) problem in which the attributes have interdependent or interactive phenomena under the interval-valued intuitionistic fuzzy environment, we propose a group decision-making approach based on the interval-valued intuitionistic fuzzy Einstein geometric Choquet integral operator (IVIFEGC). Firstly, the Einstein operational laws and some basic principle on interval-valued intuitionistic fuzzy sets are introduced. Then, the IVIFEGC is developed and some desirable properties of the operator are studied. Further, an approach to multiattribute group decision-making with interval-valued intuitionistic fuzzy information is developed, where the attributes have interdependent phenomena. Finally, an illustrative example is used to illustrate the developed approach

Towards a Quantitative Performance Measurement Model in a Buyer-Supplier Relationship Context

International audienc