Graduation Year


Document Type




Degree Granting Department


Major Professor

Donald Berndt, Ph.D.

Co-Major Professor

Matthew Mullarkey, Ph.D.

Committee Member

Alan R. Hevner, Ph.D.

Committee Member

Ron DeSerranno, D.B.A.


decision-making, information asymmetry, IT investment, technical debt


The unprecedented ubiquity with which technological advancements, such as blockchain, the Internet of things (IoT), big data, machine learning, and artificial intelligence (AI), are impacting the world has forced large organizations to rethink their information technology roadmaps. Their decisions about how they invest in technology have become more important. It is against this backdrop that companies must decide how much to invest in their aging technologies versus these new potentially transformational ones. A decision is only as good as the information available to the decision-makers when they make it. This research project seeks to understand the effects that information asymmetry has on strategic information technology (IT) investment decisions within large complex organizations. The data collected for this study was gathered from six executives. The conceptual model was grounded in Akerlof’s (1978) seminal paper on information asymmetry. This study followed an Action Design Research (ADR) approach to formulate the problem and an elaborated Action Design Research (eADR) process model to create a solution. Results indicate that using the proposed solution will result in organizations making more informed strategic IT investment decisions.