Evolution of decision rules used for IT portfolio management: An inductive approach

Research output: Chapter in Book/Report/Conference proceedingConference contribution


IT portfolio management and the related planning decisions for IT-dependent initiatives are critical to organizational performance. Building on the logic of appropriateness theoretical framework, we define an important characteristic of decision rules used during IT portfolio planning; rule appropriateness with regards to the risk-taking criterion. We propose that rule appropriateness will be an important factor explaining the evolution of rules over time. Using an inductive learning methodology, we analyze a unique dataset of actual IT portfolio planning decisions spanning two consecutive years within one organization. We present systematic comparative analysis of the evolution of rules used in planning over two years to validate our research proposition. We find that rules that were inappropriate in the first year are being redefined to design appropriate rules for use in the second year. Our work provides empirical evidence demonstrating organizational learning and improvements in IT portfolio planning capabilities.

Original languageEnglish (US)
Title of host publicationValue Creation in E-Business Management - 15th Americas Conference on Information Systems, AMCIS 2009, SIGeBIZ track, Selected Papers
Number of pages14
ISBN (Print)9783642031311
StatePublished - 2009
Event15th Americas Conference on Information Systems, AMCIS 2009 - San Francisco, CA, United States
Duration: Aug 6 2009Aug 9 2009

Publication series

NameLecture Notes in Business Information Processing
Volume36 LNBIP
ISSN (Print)1865-1348


Other15th Americas Conference on Information Systems, AMCIS 2009
Country/TerritoryUnited States
CitySan Francisco, CA


  • Decision rules
  • IT portfolio management
  • Inductive learning
  • Logic of appropriateness

ASJC Scopus subject areas

  • Management Information Systems
  • Control and Systems Engineering
  • Business and International Management
  • Information Systems
  • Modeling and Simulation
  • Information Systems and Management


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