A causal knowledge-based expert system for planning an Internet-based stock trading system

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.