(A) decision support system based on fuzzy cross-impact model for information technology forecasting

Abstract

In the current competitive environment, the assessment and forecasting of the new information technology expected to coming in the future becomes a basic element for strategic R&D planning in a field of Management Information System(MIS). Many business organizations have sought to use information technology as a means for achieving their competitive advantage. The setting of technology strategy is also concerned with issues for assessing the interaction of future technologies, especially under limited budgets. However, the problem confronted in forecasting or assessing information technology is that no set of historical data is available because of the characteristics of the new future technology. That is, since the object of forecasting is for the new future technology that have never met till now, it is very difficult to forecast by the method such as a mathematical model. Generally, the process of forecasting about future technology is performed through the mental process based on human cognition, rather than using formula as in quantitative approaches. Therefore, the need for better capturing the cognitive knowledge of human being in estimating the uncertain future requires the introduction of basic concept of fuzzy set theory because of the ability for dealing with an ambiguity problems from the answer of human. This fuzzy concept meets well to modeling the assessment and forecasting of future technologies because the process necessarily requires the communications with experts. Based on fuzzy relations, this study develops a new technology forecasting approach. First, the study presents a qualitative analysis method based on fuzzy relations for a cross-impact model designed for a technology impact assessment. The cross-impact knowledge is often uncertain or fuzzy when dealing with future events. Assessing the cross-impact relationships among future technologies creates more uncertain or fuzzy situation because of the time and uncertainty involved in ev...