A multiple criteria decision model for information system project selection

doi:10.1016/0305-0548(94)00069-K

Computers & Operations Research

Volume 22, Issue 8, October 1995, Pages 807-818

https://doi.org/10.1016/0305-0548(94)00069-K Get rights and content

Abstract

It has been widely recognized that the selection of information system (IS) is a critical part of IS planning. Multiple factors that impact the decision to select an appropriate set of IS projects include project risk, corporate goals, benefits, the availability of scarce IS resources and the interdependencies that exist among candidate IS projects. Existing methods for IS project selection do not include all these critiera in one decision model. In this paper, project selection models in other disciplines, such as R&D, capital budgeting, etc., are synthesized to develop an IS project selection model that explicitly incorporates all of these factors. Importantly, the proposed model provides a method to take advantage of hardware and software sharing among IS applications. The decision model is formulated as a nonlinear 0–1 goal programming model and represents an improvement over currently available project selection models. The model is validated by applying it to real-world IS project selection data.

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Project portfolio evaluation and selection is a complex task involving an exhaustive assessment of competing projects with interdependencies and synergies based on multiple and often conflicting criteria. The additional factor of uncertainty further complicates this complex task. This study proposes a two-stage hybrid multi-criteria decision making and mixed-integer linear programming for evaluating and selecting projects with interdependencies under uncertainty. In Stage I, we use the fuzzy technique for order of preference by similarity to ideal solution (TOPSIS) to evaluate the alternative projects under uncertainty. In Stage II, we formulate a bi-objective mixed-integer linear program to optimize profit and qualitative values for each portfolio by considering project synergies, human resources capabilities, and employee training opportunities under different scenarios. The proposed model produces portfolios with quantitative and qualitative values for each scenario under consideration. We demonstrate and validate the applicability and efficacy of the proposed approach through a real-world case study in the cybersecurity industry.
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The project selection is one of the most important phases of a project life cycle. The project selection is considered as a Multi-Criteria Decision-Making (MCDM) problem. This research aims to study the integration between Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) into Decision-Making Trial and Evaluation Laboratory (DEMATEL) under neutrosophic environment to provide a new technique for making a decision regarding the choice of appropriate project (project selection) as one of the most important phases of the project life cycle. Projects are selected by comparing them against many criteria. Criteria are evaluated based on expert’s opinion. Sometimes experts cannot give reliable information due to the non-deterministic environment. The neutrosophic set theory will be used to handle and overcome the ambiguity or lack of confirmation of information. The criteria are weighted by DEMATEL, then the best project alternative is selected using TOPSIS. In the proposed model, each pairwise comparison judgments is symbolized as a trapezoidal neutrosophic number. Experts will focus only on (n − 1) judgments for n alternatives to overcome the difficulties of [(n * (n − 1))/2] consistence judgments in case of increasing number of alternatives. A numerical example is developed to show the validation of the suggested model in the neutrosophic environment.
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In 1963, Weingartner [1] first investigated project selection problem by using a mathematical programming approach. Since then, numerous researchers have shown great interest in project portfolio selection and many efforts have been made to develop project portfolio selection models (see e.g., Ghasemzadeh and Archer [2], Golabi [3], Khalili-Damghani and Sadi-Nezhad [4], Mavrotas et al. [5] and Santhanam et al. [6]). Many researchers emphasized the application of operation research (OR) tools in project selection.
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Selecting a project portfolio is a complex process involving many factors and considerations from the time it is proposed to the time the project portfolio is finally selected. Given that making a good selection is of crucial importance, it is essential to develop well-founded mathematical models to lead the organization to its final goal. To achieve this, such models have to reflect as closely as possible both the real situation of the organization as well as its targets and preferences.
However, since the process of selecting and implementing project portfolios occurs in real environments and not in laboratories, uncertainty and a lack of knowledge regarding some data is always an important issue due to the strong interdependence between the projects and the political, economic, social, and legal conditions in which they are carried out.
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A comprehensive approach for the selection of a portfolio of interdependent projects. An application to subsidized projects in Spain
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Moreover, ignoring interdependencies provides inefficient solutions and an inappropriate use of resources (Chien, 2002; Eilat et al., 2006; Rajabi, Kilgour, & Hipel, 1998). Despite these facts, few models consider interdependences amongst projects, and those dealing with such relationships are usually restricted to certain types of interdependencies, mostly between project pairs (Chien, 2002; Santhanam & Kyparisis, 1995). Models addressing interdependencies often face additional limitations: not all models allow to work with several criteria or objectives; few models allow to exploit the experience and knowledge of experts, and even fewer use an interactive process to do so; and many of the available tools need precise data, which is not always available.
Interdependency is an ubiquitous concept in project portfolio selection, both at the firm and industry levels. However, despite the wide acceptance of this fact, there is a remarkable scarcity of models involving interdependencies amongst non-financial investments. This paper presents a flexible model developed to address the scarcity of interdependency models: a fuzzy interactive multi-objective model, based on the reference point approach, which elicits the evaluation of interdependencies from a group of experts in a natural way. The model is presented in a sequential way, to highlight its contributions. Then, it is applied to solve a real portfolio selection problem, consisting on a large set of investment projects eligible for a subsidy program. The portfolio selected using the model achieves a sharp reduction in the deviations from objectives compared to the portfolio originally selected by the granting authorities.

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^†: Radhika Santhanam is an assistant professor in the department of Decision Sciences and Information systems at Florida International University. Her research interests are in the areas of information system project selection and management, knowledge-based systems and human-computer interaction. Her papers are beinb published in Information Systems Research, International Journal of Human-Computer Studies, European Journal of Operational Research, Omega, Computers and Operations Research, Journal of the American Society for Information Science, Interfaces, Information and Management and other journals.

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A multiple criteria decision model for information system project selection

Abstract

OMEGA

Information Mgmt

Eur. J. Opl Res.

OMEGA

Eur. J. Opl Res.

OMEGA

Computers Ops Res.

Portfolio approach to information systems

Harvard Business Rev.

Selecting MIS project by steering committee

Commun. ACM

Key issues in information systems management

MIS Q.

Information systems: similarities and differences across organizations

OMEGA

Selecting information systems projects: problems, solutions and challenges

Improving software productivity

IEEE Computer

Reusable software: passage to productivity?

Datamation

Reusability-based strategy for development of information systems: implementation experience of a bank

MIS Q.

An asset-based systems development approach to software reusability

MIS Q.

Goal Programming and Extensions

Goal Programming for Decision-making

Cost-benefit analysis in information systems development and operation

Computing Surveys