Open Access
Zhang, Ruijuan
Graduate Program:
Information Sciences and Technology
Master of Science
Document Type:
Master Thesis
Date of Defense:
Committee Members:
  • Shawn Clark, Thesis Advisor
  • Enterprise Process Model
  • Risk
Risk is an important but under-investigated issue for organizations in the increasingly turbulent and complex environment. In this unpredictable world, managing risks and seeking reliability are critical for one organization’s staying ahead of other competitors. Enterprise architecture is an emerging area that seeks to organize and visualize the structural features and relationships associated with processes, people, technology, and information in an organization. In this study, an enterprise process model—a subset of the enterprise architecture—was used to clarify the complexity of internal architecture and enterprise-wide operations within an organization. This study proposed that showing the internal operations by processes provided a visual aid and therefore enabled sensemakers to become sensitive to operations, which was a process of developing mindfulness in reliability-seeking organizations. In addition, the modularity of the enterprise process model reduced the complexity of the entire enterprise and pre-structured the information around sensemakers, which would affect the sense human can make. Therefore, the explicitation of the enterprise process model would play a relevant role in the risk-based sensemaking. This study tried to bridge two different areas—the enterprise process model area and risk-based sensemaking area. Interviews and surveys were performed with employees from a newly established college in a public research university. A list of perceived risks was elicited and codified using the constant comparative method. These risks were compared in a pilot study and a follow-up study across people and time, respectively. Result showed the support for the argument that there is a relationship between enterprise process modeling and risk-based sensemaking. However, the strength of the relationship was affected by the sensemakers’ stored knowledge and the amount of information captured in process models.