Technologies for E-Service Customization

Technologies for E-Service Customization

Copyright: © 2012 |Pages: 24
DOI: 10.4018/978-1-4666-1604-2.ch003
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This chapter analyzes the technologies that underpin organizational processes for customization and personalization. It discusses enterprise systems such as customer relationship management systems (CRM) that can assist service customization, as well as components of such systems, such as recommender tools. This chapter also introduces technologies for web adaptation, i.e. approaches that automatically or semi-automatically, that create different versions of the web site for each user, or for each different user group, by customizing web content, navigation, and presentation. Recommender systems are used to help people identifying interesting products or services when the complexity and quantity of the choices is too vast for users to consider all the possibilities. This chapter covers technologies such as content-based filtering, collaborative filtering, fuzzy workflow process Management Systems, eCRM, tracking and clickstream analysis, and others.
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This Chapter discusses how organizational processes that support service customization can be underpinned with information technologies. The chapter will discuss enterprise systems such as customer relationship management systems that can assist service customization, as well as smaller components of such systems such as recommender tools. Again, throughout this chapter, the ongoing theme is that of ‘online customization’; i.e. customization on the Internet/Web, using tools the consumers can invoke from their Web browsers. Therefore this chapter covers:

  • Electronic customer relationship management systems (e-CRM)

  • Fuzzy workflow process Management Systems

  • Software utilities used for customization

  • Customization of Web sites

  • A type of customization support systems known as recommender systems

  • Context and Knowledge-based Service Customization.

Customization/Personalization Techniques

Before looking at concrete examples of customization/personalization technologies, first the two key principles of user data (profile/information model) and customization process that acts upon such data, underlying all technologies, need to be considered.

A customizable e-service system of high quality should respond in a timely manner, i.e. within a specified time frame, should provide user friendly search facilities and should be attentive to the consumers by knowing who they are, keeping them informed, and satisfying their needs (Santos, 2003; Vassiliou et al., 2001). In order to satisfy these requirements, the system needs access to the user’s data that are perhaps stored in a user profile (Chapter 2).

In addition, Vassiliou et al., (2001) suggest that personalization systems should make assumptions about “user behavior and learning”, by using users’ past actions to predict future actions. Such predictions should construct a user profile containing information on what the user has previously viewed or done, based on the user’s history of past actions. Consequently, the generation and the application of an information model/user profile are key steps in the personalization process, which applies methods and techniques drawing on technologies such as neural networks, data mining, fuzzy logic, statistics, etc., in order to customize services that match user-customer profile the best.

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