Keywords

Engineering Management, Information Technology, Decision Analysis, Engineering Economics

Abstract

The problem of project selection is of significant importance in management of information systems. Almost $2 trillion is spent worldwide every year on IT projects, with over $600 billion spent in the US alone. Traditionally, managers have being using the classical net present value (NPV) method in conjunction with multicriteria scoring models for ROI analysis and selection of IT project investments The multicriteria models use ad-hoc evaluation criteria to assign priority weights and then rate the alternatives against each criterion. These models have two limitations. First, the criteria and weights are based on subjective judgments, allowing the introduction of politics in the information management decision process and the generation of arbitrary results. Second, the classical approach uses deterministic estimations of the cost, benefits and the returns of the projects, without considering the impact of uncertainty and risk in the business decisions. This research proposed a better alternative for ROI analysis and selection of IT projects using a real option strategic scorecard (ROSS) approach. In contrast with traditional methodologies and previous research work, the ROSS decision framework uses a more comprehensive, axiomatic approach for systematically measuring both the business value and the strategic implications of IT project investments. The ROSS approach integrates in a unified IT project management decision framework the best elements of real option theory, strategic balanced scorecards, Monte Carlo simulations and analytical network processes to fully analyzes the effect of uncertainty and risk in the IT investment decisions. In addition, the ROSS approach complies with the critical success factors that have being identified in the literature for validation of IT decision frameworks. The main benefit of the ROSS approach is to enable managers to better compare and rank projects in the IT portfolio, optimizing the ROI analysis and selection of information system projects.

Notes

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Graduation Date

2006

Semester

Summer

Advisor

Rabelo, Luis

Degree

Doctor of Philosophy (Ph.D.)

College

College of Engineering and Computer Science

Department

Industrial Engineering and Management Systems

Degree Program

Industrial Engineering and Management Systems

Format

application/pdf

Identifier

CFE0001331

URL

http://purl.fcla.edu/fcla/etd/CFE0001331

Language

English

Length of Campus-only Access

None

Access Status

Doctoral Dissertation (Open Access)

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Engineering Commons

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