Classifying, Profiling and Predicting User Behavior in the Context of Location Based Services

Motivated by the technology evolutions and the corresponding changes in user-consumer behavioral patterns, this study applies a Location Based Services (LBS) environmental determinants' integrated theoretical framework by investigating its role on classifying, profiling and predicting user-consumer behavior. For that purpose, a laboratory LBS application was developed and tested with 110 subjects within the context of a field trial setting in the entertainment industry. Users are clustered into two main types having the "physical" and the "social density" determinants to best discriminate between the resulting clusters. Also, the two clusters differ in terms of their spatial and verbal ability and attitude towards the LBS environment. Similarly, attitude is predicted by the "location", the "device" and the "mobile connection" LBS environmental determinants for the "walkers in place" (cluster # 1) and by all LBS environmental determinants (i.e. those determinants of cluster # 1 plus the "digital" and the "social environment" ones) for the "walkers in space" (cluster # 2). Finally, the attitude of both clusters' participants towards the LBS environment affects their behavioral intentions towards using LBS applications, with limited, however, predicting power observed in this relationship.