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Intelligent Agents(5)

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Intelligent agents have been applied to electronic commerce, promising a revolution in the way we conduct business, whether business-to-business, business-to-customer or customer-to-customer. This article gives a brief review of agent technologies involved

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- offers customer service and support for ??for the domestic market, services and maintenance

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4 E-commerce Intelligent Agents 4.1 Description

Artificial intelligence (AI) continues to play a significant role in many leading information systems. In the past, its use has been limited due to its complexity, monolithic designs and lack of knowledgeable system developers. AI contribution is now crucial in non-deterministic systems such as workflow, data mining, production scheduling, supply chain logistics, and most recently, e-commerce. Its new form is not the monolithic AI systems of the past, but distributed artificial intelligence, popularly known as intelligent agent technology. Intelligent agent technology is the next logical step in overcoming some shortcomings in e-commerce. Namely, successful computer systems underlying e-commerce require judgment and the knowledge of experts such as buyers, contract negotiators and marketing specialists [7].

It is useful to explore the roles of agents as mediators in electronic

commerce in the context of a common framework. The presented model stems from consumer buying behaviour research and comprises the actions and decisions involved in buying and using goods and services. The model covers many areas, but focuses primarily on retail markets (although most concepts pertain to business-to-business and business-to-consumers markets as well). Also, electronic commerce covers a broad range of issues, some of which are beyond the scope of this consumer buying behaviour model. There are a variety of descriptive theories and models that attempt to capture buying behaviour [20]. These models all share a similar list of six fundamental stages of the buying process, which also elucidate where agent technologies apply to the shopping experience:

??Identification: This stage characterizes the buyer becoming aware of some unmet need by stimulating through product information. Agents can play an

important role for those purchases that are repetitive (supplies) or predictable (habits). One of the oldest and simplest examples of software agents are so called “monitors”: continuously running programs which monitor a set of sensors or data streams and take action when a certain pre-specified condition apply [20]. There are many examples in abundant use, one very familiar is a “notification agent” called “Eyes” by , which monitors the catalog of books for sale and notifies the customer when certain events occur that may be of interest to the customer (e.g., when a new book in category X becomes available). ??Brokering:

a) Product Brokering: once a buyer has identified a need to make a purchase (possibly with the assistance of a monitor agent), the buyer has to determine what to buy through a critical evaluation of retrieved product information. There are several agents systems that lower consumers’ search cost when deciding which products best meet their needs: PersonaLogic, Firefly, and Tete-a-Tete (discussed in section 4.2). The result of this stage is a consideration set of goods. b) Merchant Brokering: this stage combines the consideration set from the previous stage with merchant-specific alternatives to help determine who to buy from. The problem that was exposed here was that most of the merchants do not want to compete on price only, and want the value-added services (e.g., warranty, availability, delivery time, reputation) to be included in consumers’ buying decision.

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