A causal knowledge-based expert system for planning an Internet-based stock trading system |
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| Authors: | Kun Chang Lee Sangjae Lee |
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| Affiliation: | 1. SKK Business School, Department of Interaction Science, Sungkyunkwan University, Seoul 110-745, South Korea;2. School of Business Administration, Sejong University, Seoul 143-747, South Korea;1. Department of Process Engineering (département de genie des procédés), University of Larbi Ben M’Hidi, Oum El Bouaghi, Algeria;2. Department of Process Engineering, University of Badji Mokhtar, Annaba, Algeria;1. Big Data Research Center & Web Sciences Center, University of Electronic Science and Technology of China, Chengdu 611731, China;2. Suzhou Institute of Industrial Technology, Suzhou 215104, China;1. College of Electrical and Electronic Engineering, Wenzhou University, Wenzhou 325035, China;2. School of Surveying and Geospatial Engineering, College of Engineering, University of Tehran, Tehran 1417466191, Iran;3. Department of Computer Science, School of Computing, National University of Singapore, Singapore 117417, Singapore;4. Institute of Research and Development, Duy Tan University, Da Nang 550000, Viet Nam;5. School of Digital Media, Shenzhen Institute of Information Technology, Shenzhen 518172, China;6. College of Computer Science and Artificial Intelligence, Wenzhou University, Wenzhou, Zhejiang 325035, China;7. Department of Pulmonary and Critical Care Medicine, The First Affiliated Hospital of Wenzhou Medical University, Wenzhou 325000, China;1. Department of Mathematics, Ewha Womans University, Seoul, Republic of Korea;2. Institute of Mathematical Sciences, Ewha Womans University, Seoul, Republic of Korea |
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| Abstract: | This study describes a causal knowledge-based expert system for planning an Internet-based stock trading system, abbreviated CAKES-ISTS. The case base of this system consists of the qualities that promote ISTS use, two specific facets of ISTS use (stock amount purchased and frequency of use), and user satisfaction. Planning ISTS requires consideration of the complex causal relationships between system qualities, system use, and performance (i.e., user satisfaction). This study also examines the factors affecting the level of system usage and performance. First, this study uses a fuzzy cognitive map (FCM) to develop the causal knowledge base of the expert system for ISTS planning. Second, this study uses structural equation modeling to estimate the relevant relationships among FCM components as well as their direction and strength. Third, this study develops rules based on system qualities to predict the usage and performance level of ISTS, allowing the identification of the qualities essential to enhance system usage and performance. This clearly shows how effective ISTS planning is possible through the inference process provided by CAKES-ISTS. |
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