Web personalization: A typology, instrument and test of a predicative model

In E-Commerce and mobile commerce, personalization has been recognized as an important element in customer relationship and Web strategies. However, there are wide differences in how this concept is defined, characterized, and measured in the literature. The extant personalization research is also limited by the lack of proper measurement instruments. While personalization has been recognized as a multi-dimensional construct, identifying those dimensions and operationalizing them in measurable terms has been a persistent and important research issue in MIS research. Furthermore, existing knowledge about user's preference of different personalization features is sparse. In responding to these three limitations, this study aims to advance existing understanding in these three areas: First, the Web Personalization Measurement Instrument (WPMI) was developed based on the analysis of ideal types of personalization that are defined in terms of the motivation they supply for personalization and the goals and means of personalization. Reliability and construct validity of the instrument were established in this study. External validity and predictive validity issues were investigated by applying WPMI to a wide range of commercial websites. Second, this research examined the effect of Web personalization on positive user experience and its associated motivational states. Using commercial websites as stimuli for three different types of personalization strategies, this research conducted two independent studies and found supportive evidence for the positive influence of web personalization on user experience. In addition, we also identified distinct user motivational states salient to specific personalization strategies that are conducive to positive user experience. Third, this research examined the moderating effect of user values on the relationship between Web personalization and the user experience and its associated motivational states. The analysis identified important values that are salient to certain Web personalization strategies in eliciting positive user experience and its associated motivational states.