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A multi‐agent architecture to support B2C e‐Marketplaces: the e‐ZOCO case study

A multi‐agent architecture to support B2C e‐Marketplaces: the e‐ZOCO case study Purpose – The purpose of this paper is to introduce a multi‐agent architecture, which offers services to be applied in B2C e‐Marketplaces and to present the core system: the search agent. Design/methodology/approach – The different parts that compose an e‐commerce portal are naturally performed through intelligent agents, which have the ability to communicate with one another and autonomously act depending on defined goals. Findings – The search agent returns the more relevant results in direct shopping than others previously used. It is based on a usability‐improved fuzzy searching mechanism that allows the specification of uncertain and vague searching preferences. Research limitations/implications – More empirical research efforts need to be directed to study the efficiency over time. This work is based on a prototype, which is its main limitation. Practical implications – Intelligent agents can be useful to improve e‐commerce services in B2C portals. Originality/value – The research extends previous authors' work on the application of intelligent agents to e‐commerce fields. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Internet Research Emerald Publishing

A multi‐agent architecture to support B2C e‐Marketplaces: the e‐ZOCO case study

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References (30)

Publisher
Emerald Publishing
Copyright
Copyright © 2010 Emerald Group Publishing Limited. All rights reserved.
ISSN
1066-2243
DOI
10.1108/10662241011050704
Publisher site
See Article on Publisher Site

Abstract

Purpose – The purpose of this paper is to introduce a multi‐agent architecture, which offers services to be applied in B2C e‐Marketplaces and to present the core system: the search agent. Design/methodology/approach – The different parts that compose an e‐commerce portal are naturally performed through intelligent agents, which have the ability to communicate with one another and autonomously act depending on defined goals. Findings – The search agent returns the more relevant results in direct shopping than others previously used. It is based on a usability‐improved fuzzy searching mechanism that allows the specification of uncertain and vague searching preferences. Research limitations/implications – More empirical research efforts need to be directed to study the efficiency over time. This work is based on a prototype, which is its main limitation. Practical implications – Intelligent agents can be useful to improve e‐commerce services in B2C portals. Originality/value – The research extends previous authors' work on the application of intelligent agents to e‐commerce fields.

Journal

Internet Research – Emerald Publishing

Published: Jun 8, 2010

Keywords: Electronic commerce; Internet

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