Roles of Causality for Understanding the Behavior of System Stakeholders

The understanding of stakeholder’s behavior is essential to design a system because the system should satisfy and support stakeholders for the stakeholders to adopt the system (Jiao & Chen, 2006). Understanding of stakeholders’ behavior requires knowledge about how they work in the designed system and how they respond to the designed product. Furthermore, if we can understand why the stakeholders work or respond in such a way, we can predict the behavior of stakeholders. The causality refers to the relationship between causes and effects. The causality is essential to stakeholder behavior analysis. The causality analysis of the stakeholder behaviour contributes to the system design and analysis by providing knowledge on three perspectives (i.e., the prediction of stakeholder behavior to the new system, the motivation of the new system design, and the new system itself). Specific examples for these three perspectives are following: first, we can build a stakeholder response model. The model can be a structural-hypothetic model in social science (Biddle & Marlin, 1987; Bagozzi & Yi, 1988) and customer’s cognition model for a product (Khalid & Helander, 2004; Li, 2004). Second, stakeholder’s dissatisfaction inferred by (or evaluated from) the model can be a motivation for a new system. Lastly, the causality of stakeholder’s behavior can be implemented as an intelligent system itself. For instance, the causality can be converted into a mathematical model like operations research model (Shannon et al., 1980). This issue gathers four papers among which the first two concentrate on stakeholder behavior prediction such as the hypothetical model between the cooperative knowledge sharing and firm’s innovativeness and the customer’s psychological response for a shaving product. The other two papers discuss about the healthcare visiting scheduling system motivated by