Multi-Attribute Decision Making
Mojtaba Movahedi; Mahdi Homayounfar; Mehdi Fadaei; Mansour Soufi
Abstract
Purpose: Clustering algorithms are useful tools for understanding data structure and classifying them into different data sets. Due to the importance of using these algorithms in analyzing financial market data that have a high volume and scope, this study in order to select the best clustering algorithm ...
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Purpose: Clustering algorithms are useful tools for understanding data structure and classifying them into different data sets. Due to the importance of using these algorithms in analyzing financial market data that have a high volume and scope, this study in order to select the best clustering algorithm for clustering companies listed on the Tehran Stock Exchange in the field of finance from It has used different clustering algorithms and evaluated the validity of these algorithms and selected the best algorithm.Methodology: This research is applied in terms of purpose and descriptive in terms of implementation method and is of quantitative type (mathematical modeling). The statistical population of the research includes 403 companies listed on the Tehran Stock Exchange in 2019, whose performance has been evaluated based on four financial criteria.Findings: After clustering the surveyed companies by five clustering algorithms, namely K-means, EM, COBWEB, density-based algorithm and ward method, seven indicators RS, DB, Dun, SD, Purity, Entropy and Time were used to evaluate the algorithms. Finally, the total performance of the algorithms was analyzed based on TOPSIS, VICOR and DEA methods. Based on the results, K-means has a better performance in clustering based on the financial data sets.Originality/Value: Since no clustering algorithm can have the best performance in all measurements for each data set, this study uses a combination of multiple criteria to analyze data clustering algorithms related to the field of financial performance appraisal. Companies have provided suggestions and the results of this study have been used effectively for investors in the field of finance, which leads to the optimal choice of investment portfolio.
Decisions in new businesses
Seyedeh Arefeh Mousavi Arab; Mahdi Homayounfar; Mehdi Ajalli
Abstract
Purpose: Today, with the development of e-commerce, society is experiencing a business revolution. E-commerce gradually has been accepted more and more and changed people’s lives. The aim of this research is to determine to the critical performance criteria in balanced evaluation of Iranian online ...
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Purpose: Today, with the development of e-commerce, society is experiencing a business revolution. E-commerce gradually has been accepted more and more and changed people’s lives. The aim of this research is to determine to the critical performance criteria in balanced evaluation of Iranian online B2C business stores using a hybrid Balanced Scorecard (BSC) and multi criteria decision making (Fuzzy ANP and Fuzzy WASPAS) approach.Methodology: Considering research objective, it’s an applied research, regarding method it’s descriptive and based on analysis method, it’s a quantitative- mathematical modeling study. The statistical population of this study includes owners of online businesses in Rasht city.Findings: After reviewing the literature and identifying online stores’ evaluation criteria, these criteria were classified based on the four perspectives of BSC. Next, the importance of the criteria was determined using the Fuzzy Analytical Network Process (ANP) technique, among which operation management (0.15848), sales (0.14957), market share (0.13710), customer satisfaction (0.12409) and customer relationship management (0.10527) are the most important criteria, respectively. Finally, based on the results of evaluating 10 Iranian online stores using Fuzzy WASPAS technique, Digi Kala, Digi Style, and Chareh stores were ranked first to third.Originality/Value: In this research, B2C online store brands were evaluated and ranked with a mixed approach of FANP and FWASPAS and based on the research results, executive and research proposals were presented.