Evaluation of IT Investment Methods and Proposing a Decision Making Model.

Information technology investment decision making is one of the significant issues. Since the IT investment evaluation is not just based on direct and tangible factors and many other intangible and indirect qualitative criteria influence this evaluation. Generally, there are two different approaches in evaluation methods with their own advantages and disadvantages: tangible methods such as Discounted Cash Flow, Net Present Value, Information Economics, etc. and intangible methods such as Value Analysis, Multi Objective Multi Criteria, Critical Success Factors, etc. But a more effective and precise road map is to guide decision makers to choose an appropriate multi criteria model that consider both tangible and intangible factors together. In this paper by literature review of these mentioned methods, various tangible and intangible factors were determined from different academic papers and practitioner resources and then were classified in two domains and a number of sub-domains. In order to obtain complete and applicable criteria, five reduction factors were defined, i.e. clarity, completeness, non- redundancy and operationality. Then this criteria list was delivered among a number of mangers and information technology specialists. According to the given answers, a new criteria list was obtained with eliminating nonapplicable criteria. As a consequence, to assess the importance of each criterion for creating the model, the rating scores, one to five were defined and added to the new lists. Then these new criteria lists were conducted among CIO, CEO, CFO and other related specialists in different Iranian companies to customize these criteria according to their business strategies and requirements. Score one represents not important and five represents very important. The results are assumed as the minimum level of criteria with maximum coverage in different information technology projects. In the next step, based on the results, we developed an analytic hierarchy decision making model. The results of this research indicate that this model is applicable and can be easily expanded by aggregating new sub criteria to be customized for different IT investment evaluations. [ABSTRACT FROM AUTHOR]