Predrag Mimovic

A model for evaluation of customer satisfaction with banking service quality in an uncertain environment

The aim of this study was to propose a fuzzy decision-making model to evaluate customer satisfaction level which has a critical effect on the bank’s competitive advantage and its business. Value of customer satisfaction level can be determined by respecting all the factor values which are presented in this paper. The relative importance of indicators and their values are imprecise and uncertain variables which are modelled by using the fuzzy set theory. Relative importance of indicators under each identified customer satisfaction factor is stated by analogy to fuzzy analytic hierarchy process framework. Determining indicator values is stated as fuzzy group decision-making problem. The aggregated values of indicators are determined by using the fuzzy ordered weighted averaging operator. The overall index of customer satisfaction is determined by considering aggregated values of customer satisfaction factors. The level of customer satisfaction, which is closely linked with the quality of banking services, is determined by using fuzzy logic if–then rules. A case study with real-life data obtained from 22 enterprises is presented to verify the proposed method. It is shown that the proposed fuzzy model is a useful and effective assessment tool.

Application of Multi-Criteria Analysis in the Public Procurement Process Optimization

Abstract One of the key steps in the implementation of a public procurement process is the criteria selection that are associated with the bidders, which are intended to ensure that bidders will be able to meet the requirements from the contract. Implicitly, the criteria selection includes their evaluation in situations when the criterion of the lowest price is not applied, but instead the criterion of the most economically advantageous tender. The aim of the paper is to show that decision-makers in the public sector can use multi-criteria analysis for the efficient and fair public procurement process implementation and the establishment of objective conditions for the contract awarding in accordance with the general social interests. In this sense, the paper presents a comparative approach to the Analytic Hierarchy Process and Analytic Network Process as the methods of support in decision making, measurement and evaluation criteria for the selection of the best bids in the procurement process. Hierarchical model with five criteria and nine sub-criteria and the network model, which takes into account the mutual influences of criteria, were developed in a hypothetical public procurement selection procedure for the best performers for the construction of the infrastructure facility. Selection of the best bidder, i.e. bids for the realization of the work, is distinctive, multi-criteria problem which includes both qualitative and quantitative factors.

Fuzzy Approach in Ranking of Banks according to Financial Performances

Evaluating bank performance on a yearly basis and making comparison among banks in certain time intervals provide an insight into general financial state of banks and their relative position with respect to the environment (creditors, investors, and stakeholders). The aim of this study is to propose a new fuzzy multicriteria model to evaluate banks respecting relative importance of financial performances and their values. The relative importance of each pair of financial performance groups is assessed linguistic expressions which are modeled by triangular fuzzy numbers. Fuzzy Analytic Hierarchical Process (FAHP) is applied to determine relative weights of the financial performances. In order to rank the treated banks, new model based on Fuzzy Technique for Order Performance by Similarity to Ideal Solution (FTOPSIS) is deployed. The proposed model is illustrated by an example giving real life data from 12 banks having 80% share of the Serbian market. In order to verify the proposed FTOPSIS different measures of separation are used. The presented solution enables the ranking of banks, gives an insight of bank’s state to stakeholders, and provides base for successful improvement in a field of strategy quality in bank business.

The integrated application of the AHP and the DEA methods in evaluating the performances of higher education institutions in the Republic of Serbia

The measurement and evaluation of performance are critical for the efficient and effective functioning of the economic system, because this allows for the analysis of the extent to which the defined objectives are achieved. Organizational performance is measured by different methods, both quantitative and qualitative. Many of the known methods for the evaluation and measurement of organizational performance take into account only financial indicators, while ignoring the non-financial ones. The integration of both indicators, through the combined application of multiple methods and the comparison of their results, should provide a more complete and objective picture of organizational performance. The Analytic Hierarchy Process (AHP) is a formal framework for solving complex decision-making problems, as well as a systemic procedure for the hierarchical presentation of the problem elements. The Data Envelopment Analysis (DEA) is a non- parametric approach based on linear programming, which allows for the calculation of the efficiency of decision-making units within a group of organizations. The work is an illustration of the method and framework of the combined use of the multi-criteria analysis methods for the measurement and evaluation of the performance of higher education institutions in the Republic of Serbia. The advantages of this approach are reflected in overcoming the shortcomings of a partial application of the AHP and the DEA methods by utilizing a new, hybrid, DEAHP (Data Envelopment Analytic Hierarchy Process) method. Performance evaluation through an integrated application of the AHP and the DEA methods provides more objective results and more reliable solutions to the observed problem, thus creating a valuable information base for high-quality strategic decision making in higher education institutions, both at the national level and at the level of individual institutions.

Decision-making under uncertainty – the integrated approach of the AHP and Bayesian analysis

In situations where it is necessary to perform a large number of experiments in order to collect adequate statistical data which require expert analysis and assessment, there is a need to define a model that will include and coordinate statistical data and experts’ opinions. This article points out the new integrated application of the Analytic Hierarchy Process (AHP) and Bayesian analysis, in the sense that the Bayes’ formula can improve the accuracy of input data for the Analytical Hierarchy Process, and vice versa, AHP can provide objectified inputs for the Bayesian formula in situations where the statistical estimates of probability are not possible. In this sense, the AHP can be considered as the Bayesian process that allows decision-makers to objectify their decisions and formalise the decision process through pairwise comparison of elements.