文化大學機構典藏 CCUR:Item 987654321/30566
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    Please use this identifier to cite or link to this item: https://irlib.pccu.edu.tw/handle/987654321/30566


    Title: A new approach and insightful financial diagnoses for the IT industry based on a hybrid MADM model
    Authors: Shen, Kao-Yi
    Tzeng, Gwo-Hshiung
    Contributors: Dept Banking & Finance
    Keywords: Financial performance (FP)
    Fundamental analysis (FA)
    Variable consistency dominance-based rough set approach (VC-DRSA)
    Decision-making trial and evaluation laboratory (DEMATEL)
    Fuzzy inference system (FIS)
    Multiple attribute decision making (MADM)
    Date: 2015-09
    Issue Date: 2015-10-19 11:37:11 (UTC+8)
    Abstract: Financial performance is vital for information technology (IT) companies to survive intense global competition. Because of the complexity in the business environment and the rapidly advancing technologies, companies lack specific guidance to understand the implicit relationship among crucial financial indicators for improving prospects in a contextual approach. To resolve the aforementioned concern, this study proposed a new approach by combining the variable consistency dominance-based rough set approach (VC-DRSA) with the decision-making trial and evaluation laboratory (DEMATEL) technique to explore the complex relationship among financial variables and improve future performances. In addition, a fuzzy inference system was devised on the basis of the findings of the VC-DRSA and DEMATEL technique to examine granulized knowledge and implications. A group of real IT companies listed on the Taiwan stock market were used as an empirical case to present the benefits of the new approach. The results generated a set of decision rules that can be used for forecasting future performance prospects and diagnosing the directional influences of crucial variables to gain insights; certain strong decision rules were further examined using fuzzy inference to verify the obtained implications. The findings contribute to the financial applications of decision-making science and computational intelligence in practice. (C) 2015 Elsevier B.V. All rights reserved.
    Relation: KNOWLEDGE-BASED SYSTEMS 卷: 85 頁碼: 112-130
    Appears in Collections:[Department of Banking & Finance ] periodical articles

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