Working Papers,
Copenhagen Business School, Department of Informatics

Abstract: The project on Personalisation of Self-service Solutions across On-line Platforms (POSS ON-LINE) focuses on users, clients, and self-service solutions. It is based on the understanding that clients and users are different and have different goals, and that self-service takes place in different contexts, on different platforms, and within different applications and this requires development of complementary approaches and solutions. Traditionally the tools used to predict user behaviour build on users leaving traces of their actions. However, new application and developments for existing applications do not gather traces, and new ways of profiling the user is needed. To digitalise e.g. public services such as TOLD & SKAT to meet citizen’s needs is a huge challenge because the user’s context has to be taken into account. As the tracking tools are not sufficiently refined (1,4,14) pushing of information to users with the aim of increasing sales, e.g. AMAZON, still leaves much to be wished for. Despite the fact that the user profile, which the system generates, is continuously updated through user’s interaction with the system (15), e.g. myyahoo.com. Personalised application may both service the client and the user. The system gathers data about the user, which enables the client to push information to the user. Personalisation enables graphic user interface design that is personalised and relevant to the individual user and invites the user to get access to information with less strain. Personalisation of self-service solutions is promising and IT companies are experiencing an increase in the clients’ demands. At the same time the development of solutions moves within a shorter and shorter time span. Hence the process of innovations is paced and there is an increasing need of new ways of looking at the process of development. However, we lack methods to predict user behaviour without having to deal with huge amounts of data and data from both quantitativ data as well as life world observations are required.

Keywords: None

JEL-codes: O30

6 pages, September 19, 2005

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