Browsing by Author "Fang, Sheng-Kai"

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Combined DEMATEL technique with a novel MCDM model for exploring portfolio selection based on CAPM
(2011-01-01)
Ho, Wen-Rong Jerry
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Tsai, Chih-Lung
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Tzeng, Gwo-Hshiung
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Fang, Sheng-Kai
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科技管理研究所
This research proposes a novel MCDM model, including DEMATEL, ANP, and VIKOR for exploring portfolio selection based on CAPM. We probe into the influential factors and relative weights of risk-free rate, expected market return, and beta of the security. The purpose of this research is to establish an investment decision model and provides investors with a reference of portfolio selection most suitable for investing effects to achieve the greatest returns. Taking full consideration of the interrelation effects among criteria/variables of the decision model, this paper examined leading semiconductor companies spanning the hottest sectors of integrated circuit (IC) design, wafer foundry, and IC packaging by experts. Empirical findings revealed that risk-free rate was affected by budget deficit, discount rate, and exchange rate; expected market return was affected by country risk, industrial structure, and macroeconomic factors; and beta of the security was affected by firm-specific risk and financial risk. Also, the factors of the CAPM possessed a self-effect relationship according to the DEMATEL technique. In the eight evaluation criteria, macroeconomic criterion was the most important factor affecting investment decisions, followed by exchange rate and firm-specific risk. In portfolio selection, leading companies in the wafer foundry industry outperformed those in IC design and IC packaging, becoming the optimal portfolio of investors during the time that this study was conducted. (C) 2010 Elsevier Ltd. All rights reserved.
Exploring the preference of customers between financial companies and agents based on TCA
(2012-03-01)
Fang, Sheng-Kai
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Shyng, Jhieh-Yu
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Lee, Wen-Shiung
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Tzeng, Gwo-Hshiung
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科技管理研究所
Based on transaction cost analysis (TCA), this research explores the customers' loyalty to either the financial companies or the company financial agents with whom they have established relationship. In the past, consumers were divided into those who rely on agents and those who do not. In this study, we use two processes (pre-process and post-process) to select suitable rules, and to explore into the relationship among attributes. In the pre-process, we utilized factor analysis (FA) to choose the variable and rough set theory (RST) that found decision table to construct the decision rules, and approach to data mining and knowledge discovery based on information flow distribution in a flow graph. The post-process applies the formal concept analysis (FCA) from these suitable rules to explore the attribute relationship and the most important factors affecting the preference of customers for deciding whether to choose companies or agents. The degree of the customers' dependence on agents was affected by the TCA, customer satisfaction and loyalty. The principal findings were that the different degrees of dependence of customers have various characteristics. The RST and FCA were two complementary mathematical tools for data analysis. Following an empirical analysis, we use two hit testes that incorporate 30 and 36 validated sample object into the decision rule. The hitting rate of two testes, were reached 90%. The results of the empirical study indicate that the generated decision rules can cover most new objects. Consequently, we believe that the result can be fully applied in financial research. (C) 2011 Published by Elsevier B.V.