Abstract Participatory enterprise modeling (PEM) is presumed to have a positive impact on commitment, ownership feelings and further appraisals by domain experts with respect to the model. However, there has not been a lot of research into whether PEM actually has the desired effects. In this paper we report on an investigation of the effects of three settings with different levels of involving domain experts: an overall model was created (1) from four individual interviews, (2) from four individual models, or (3) in a joint meeting of domain and modeling consultants. The results show that the non-participatory interview setting led to less favorable appraisals, e.g., the possibility to participate and the value of the model were perceived as lower and the contribution of the modeling consultants was perceived as higher. Our findings should help practitioners in weighing possible benefits of participatory enterprise modeling against the organizational effort and monetary cost it involves.

Participatory enterprise modeling is about gathering domain experts and involving them directly in the creation of models, aided by modeling experts. It is meant to increase commitment to and quality of models. This paper presents an exploratory study focusing on the subjective view of the domain experts. We investigated the influence of direct collaboration versus individual modeling, and the influence of model revisions by modeling experts on psychological ownership and perceived model quality. We chose process modeling as a particular form of enterprise modeling. Our results give hint that domain experts working individually with a modeling expert perceive model quality as higher than those working collaboratively whereas psychological ownership did not show any difference. Revisions caused changes in the subjects' assessments only of model quality. Moreover, we will present qualitative results from interviews we led with the participants. They reveal interesting insight on how outcome and perception of the procedure and the method in both settings can be positively influenced. The interviews also emphasize the special role of the method experts who are sometimes even considered as co-owners of the model.

We discuss how a task-based situational market segmentation may be applied to on-line newspapers, distinguishing between fact finding, information gathering and browsing. During a period of four weeks we had 41 users keep a diary and recorded their surfing behavior on different on-line newspapers. The results of a Naive Bayes classification with feature selection indicate that content-related attributes such as the number of news categories browsed are indispensable for task recognition.