Emergent Changes in Enterprise Architectures: Framework and Case Study

We suggest an emergent change framework for enterprise architecture. Drawing on Leavitt’s Change Model of Organizations, our framework focusses on socio-technical changes in tasks, structures, actors, and technologies. By applying the framework to a medium-sized company from the media industry and drawing on a relatively unique panel data set (2014, 2016, 2018), we demonstrate the amount of emergent changes and confirm three patterns of change. These findings help to advance the study of change and its propagation across different components of an enterprise over time

Intelligent Agents as a Modeling Paradigm

Intelligent software agents have been used in many applications because they provide useful integrated features that are not available in “traditional” types of software (e.g., abilities to sense the environment, reason, and interact with other agents). Although the usefulness of agents is in having such capabilities, methods and tools for developing them have focused on practical physical representation rather than accurate conceptualizations of these functions. However, intelligent agents should closely mimic aspects of the environment in which they operate. In the physical sciences, a conceptual model of a problem can lead to better theories and explanations about the area. Therefore, we ask, can an intelligent agent conceptual framework, properly defined, be used to model complex interactions in various social science disciplines? The constructs used in the implementation of intelligent agents may not be appropriate at the conceptual level, as they refer to software concepts rather than to application domain concepts. We propose to use a combina- tion of the systems approach and Bunge’s ontology as adapted to information systems, to guide us in defining intelligent agent concepts. The systems approach will be used to define the components of the intelligent agents and ontology will be used to understand the configurations and interrelationships between the components. We will then provide a graphical representation of these concepts for modeling purposes. As a proof of concept for the proposed conceptual model, we applied it to a marketing problem and imple- mented it in an agent-based programming environment. Using the conceptual model, the user was able to quickly visualize the complex interactions of the agents. The use of the conceptual representation even sparked an investigation of previously neglected causal factors which led to a better understanding of the problem. Therefore, our intelligent agent framework can graphically model phenomena in the social sciences. This work also provides a theoretically driven concept of intelligent agent components and a definition of the inter- relationships between these concepts. Further research avenues are also discussed

What is a Contribution to IS Design Science Knowledge?

In order to promote more rigor in Design Science Research (DSR), Gregor and Hevner have proposed guidelines for conducting and evaluating DSR in the Information Systems (IS) discipline. Their work has been influential and widely used to advance the field. However, the way they characterize IS-DSR knowledge contributions excludes what we believe are genuine contributions and includes works that in our lights are not contributing to IS-DSR knowledge. To overcome this problem, we borrow from the contemporary philosophy of science to develop a framework for identifying the types of IS-DSR knowledge. We posit that contributions to DSR are in the form of theories or technological designs, and each type could be either inter-field or field. We demonstrate the strength of the proposed framework in better identifying contributions and clarifying the boundaries of IS-DSR. Our experience led us to believe that the proposed view is applicable to the whole IS discipline

Domain design principles for managing complexity in conceptual modeling

Complexity is a problem that can be found in many aspects of research that deals with design. In particular, complexity is found in various business processes that must be modeled and represented in a meaningful way. One of the ways to address complexity is by using decomposition, for which a number of decomposition principles have been proposed. However, there are two domain specific areas in which these principles are lacking: the scope and the context of the problem. This research addresses this problem by deriving two new principles for managing complexity, and evaluates the proposed principles through an example case to illustrate their potential use

Data-Driven Meets Theory-Driven Research in the Era of Big Data: Opportunities and Challenges for Information Systems Research

The era of big data provides many opportunities for conducting impactful research from both data-driven and theory-driven perspectives. However, data-driven and theory-driven research have progressed somewhat independently. In this paper, we develop a framework that articulates important differences between these two perspectives and propose a role for information systems research at their intersection. The framework presents a set of pathways that combine the data-driven and theory-driven perspectives. From these pathways, we derive a set of challenges, and show how they can be addressed by research in information systems. By doing so, we identify an important role that information systems research can play in advancing both data-driven and theory-driven research in the era of big data

Cerebral oximetry monitoring during aortic arch aneurysm replacement surgery in Jehovah's Witness patient -A case report-

Anesthetic management for aortic arch aneurysm (AAA) surgery employing deep hypothermic circulatory arrest in a Jehovah's Witness (JW) patient is a challenge to anesthesiologist due to its complexity of procedures and their refusal of allogeneic transfusion. Even in the strict application of intraoperative acute normovolemic hemodilution (ANH) and intraopertive cell salvage (ICS) technique, prompt timing of re-administration of salvaged blood is essential for successful operation without allogeneic transfusion or ischemic complication of major organs. Cerebral oximetery (rSO2) monitoring using near infrared spectroscopy is a useful modality for detecting cerebral ischemia during the AAA surgery requiring direct interruption of cerebral flow. The present case showed that rSO2 can be used as a trigger facilitating to find a better timing for the re-administration of salvaged blood acquired during the AAA surgery for JW patient