Abstract
In traditional business model, the buying decision process is poorly coordinated among the human decision-makers. Therefore, a long-lived, adaptive, and autonomous application called software agents, that can perform tasks such as personalization, brokering, and negotiation in e-commerce is much needed. These applications reside at the buyers’ side or at the sellers’ servers. The purpose of this paper is to research into possible deployment of software agents in a framework for e-commerce buying decision process. This paper overviews the traditional business model, the Consumer Buying Behavior (CBB) model, and also covers the requirements needed for minimizing human interactions in buying decision processes. The research proposes a software agent’s framework in which, two main approaches, namely Automated Collaborative Filtering (ACF) and Better Business Bureau (BBB), are merged to produce better agents in assisting buying decision process. The framework will enable the agents to get the best price for a good product from a reputable merchant.
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Razali, S., Osman, M. (2006). Framework for Agent-Based Buying Decision Process. In: Shi, ZZ., Sadananda, R. (eds) Agent Computing and Multi-Agent Systems. PRIMA 2006. Lecture Notes in Computer Science(), vol 4088. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11802372_89
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DOI: https://doi.org/10.1007/11802372_89
Publisher Name: Springer, Berlin, Heidelberg
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