“Adaptation of Decision Rules: The Analytics of IT Portfolio Management” by Dr. Prasanna Karhade
Dr. Prasanna Karhade
Assistant Professor Department of Information Systems, Business Statistics and Operations Management
The Hong Kong University of Science and Technology
We develop a theory to explain the endogenous adaptation of decision rules used for planning information systems (IS) portfolios. To achieve this objective, we integrate the logic of appropriateness with explanations from institutionalization and simplification owing to the application of rules. Using the decision rule as our unit of analysis, often considered apt for discovering hidden order in complexity, we propose meta-rules explaining the outcomes of rule births, deaths, revisions and retentions. We examine support for our theory in a naturallycontrolled field setting using a three-stage methodology. In stage one, decision analytics facilitates discovery of tacit rules used for planning IS portfolios. Next, in stage two, building on ostensive and performative forms of rules, we assess outcomes of adaptation over a twoyear period. Finally, in stage three, deep-learning (layered decision tree induction) facilitates discovery of meta-rules guiding adaptation of rules. We find that risk-appropriateness in combination with forces of institutionalization and simplification serves as an internal radar to guide adaptation of rules. Examining firm adaptations through the lens of decision analytics and higher-order meta-rules provides a novel way to theorize largely-tacit behavioral dynamics in response to complexity.