Fuzzy Sets to Find a Solution to Select Information Systems
Wikil Kwak · Academy of Information and Management Sciences journal · 2006
ABSTRACT An information system selection is strategically important for an organization. However, the review of existing information system selection models for a firm shows that there is a major shortcoming in the previous mathematical models. A goal programming or multiple objective linear programming (MOLP) cannot deal with the organizational differentiation problems. To reduce the complexity in computing the trade-offs among multiple objectives, this paper adopts a fuzzy set approach to solve information system selection problems. A solution procedure is proposed to systematically identify a satisfying selection of possible solutions that can reach the best compromised value for the multiple objectives and multiple constraint levels. The fuzzy solution can help a firm make a realistic decision regarding its information system selection problems as well as the firm's overall strategic issues when environmental factors are uncertain. INTRODUCTION Formal planning for an information system selection in a firm is very important because it enables the firm to function more efficiently and effectively given the current dynamic information technological environment. If a firm decides to have a formal planning model, the model first should incorporate economic and professional objectives of their users. In addition, strategic planning is another important factor in information system management (Brancheau & Wetherbe, 1987). However, information system managers, corporate officers, and users may have different perspectives of their information system (Buss, 1983). Therefore, an information system selection for a firm is a complex task and multiple goals are necessary in today's highly competitive business environment. Linear programming focuses on a single goal - usually profit maximization or cost minimization - but this is not the situation for a firm which has multiple information system users and decision makers. A goal programming or multiple objective linear programming (MOLP) cannot deal with the organizational differentiation problems. Since the fuzzy set approach provides a simultaneous solution to a complex system of competing obj ectives, it seems to be an appropriate tool for solving a firm's information system selection problem. In this paper, a fuzzy set approach to this information system selection problem that incorporates the multiple objectives and multiple decision makers or users of the firm to incorporate multiple constraints will be discussed. The focus of this paper is the fuzziness of objectives or constraints as well as multiple decision maker situations where this fuzzy set approach is the most appropriate solution. The same approach can be used to expand the general information system selection problem. Fuzzy set theory has been applied in business in several areas such as financial planning, inventory management, a variance investigation model, target costing, internal control evaluation model, and capital budgeting problems (see Zebda, 1989; Siegel et al., 1998 for further discussions). Fuzzy set theory can be applied to many business and strategic management problems whenever there is a need to model the imprecise reasoning process of human decision-making. For example, Ruefli and Sarrazin (1981) proposed a fuzzy set approach in strategic control of corporate development in ambiguous situations. Fuzzy set theory should receive more attention in the United States to simplify the modeling of complex business decision-making such as an information system selection. With currently available software, the solution is practical for numerous real world problems. In the following section, prior research is discussed. The third section presents multiple objective information system selection models including a fuzzy solution method. Then, a numerical example with analysis and managerial implications, and conclusions will be addressed. PRIOR RESEARCH Today many organizations' successes depend on the appropriateness of their information systems (Ward, 1987). …