Technical noteA fuzzy multiple criteria comparison of technology forecasting methods for predicting the new materials development
Introduction
New materials have been recognized as key drivers for corporate profitability and growth in today's fast changing environments. Usually, these come about through the replacement of natural materials by synthetic ones that are cheaper or better. The replacement of silk by nylon and the alternative of cotton by a whole host of synthetic fibers are examples [1]. Besides, nowadays, there is an emerging and important technological change in new materials, which is nanotechnology. According to the estimation by National Science Foundation, the nanotechnology market will experience pretty steep annual growths capable of bringing it to more than US$1 billion after the year 2010 [2].
However, there are full of uncertainties in those new materials development. Through selecting an appropriate technology forecasting method to gain the useful forecasting information about the new materials development, such as the alternative rates, the breakthrough points, or the degrees of market penetration, becomes more and more significant. A good choice of a technology forecasting method in a particular situation could affect the usefulness and accuracy of the forecast. However, little has been done in discussing the selection of technology forecasting methods on this topic. Accordingly, the main purposes of this study are to identify the critical evaluation criteria and to evaluate the technology forecasting methods for development of new materials.
During the past two decades, there has been growth in the number of multiple criteria decision-making methods for assisting decision-making. These allow decision-makers to evaluate various alternatives for achieving their goal. Among these, the fuzzy analytic hierarchy process (FAHP) is one of the most popular [3], [4], [5], [6]. People often use knowledge that is imprecise rather than precise. The fuzzy set theory could resemble human reasoning in use of approximate information and uncertainty to generate decisions. It was specifically designed to mathematically represent uncertainty and vagueness and provide formalized tools for dealing with the imprecision intrinsic to many problems [3], [7], [8]. Consequently, to make this study more sensible and gain a more representative description of the decision-making process, this paper would apply the FAHP to evaluate the technology forecasting methods for the new materials development.
Section snippets
Review and classification of technology forecasting method
Methods for technology forecasting are broadly classified into two main categories: exploratory forecasting and normative forecasting [1], [9]. Exploratory forecasting means forecasting the future based on past data and present conditions, which includes Delphi method, growth curves and the case study method.
The Delphi method is an approach used in forecasting the likelihood and timing of future events [10], [11]. The method could be more adoptive in the situations, which are few historical
The fuzzy analytic hierarchy process
There has been growth in the number of multiple criteria decision-making methods for assisting decision-making during the past two decades. These allow decision-makers to evaluate various alternatives for achieving their goal. Among these, the fuzzy analytic hierarchy process (FAHP) is one of the most popular [3], [4], [5], [6]. People often use knowledge that is imprecise rather than precise. The fuzzy set theory could resemble human reasoning in use of approximate information and uncertainty
Date collection and analysis
The participants include industry practitioners, research analysts and academic researchers experienced in the development of the new materials industries. The research analysts are in the renowned research institutes such as Industrial Technology Research Institute, Metal Industries Research and Development Center, and while the academic researchers are in the prestigious universities including the National Cheng Kung University, National Chiao Tung University.
The survey was conducted in two
Comparison of the evaluation criteria
In this study, we first examined the relative importance of the criteria with respect to the primary objective, the choice of technology forecasting methods. Following the fuzzy AHP methodology, priorities of evaluation criteria were performed to get the relative importance of the factors. Table 2 shows priorities of the evaluation criteria for the goal. The normalized weights and the rank for the criteria are given in the last two columns.
According to Table 2, the results indicate that the
Conclusions
New materials have been recognized as key drivers for corporate profitability and growth in today's fast changing environments. However, there are full of uncertainties in those new materials development. Through an appropriate technology forecasting method to gain the useful forecasting information about the alternative rates of the new materials, the breakthrough points of those materials, or the degrees of market penetration and diffusion of the new materials becomes more and more
An-Chin Cheng is a candidate for doctor's degree at the Graduate Institute of Resources Engineering, National Cheng Kung University, Taiwan. His current research interests include technology management, intellectual property and new product management.
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An-Chin Cheng is a candidate for doctor's degree at the Graduate Institute of Resources Engineering, National Cheng Kung University, Taiwan. His current research interests include technology management, intellectual property and new product management.
Chung-Jen Chen is an associate professor at the Graduate Institute of Business Administration, College of Management, National Taiwan University. He received his doctorate in Strategy and Technology Management from Rensselaer Polytechnic Institute, Troy, New York. His current research interests include innovation management, knowledge management, interfirm collaboration and entrepreneurship. He has published papers in IEEE Transactions on Engineering Management, Information and Management, International Journal of Technology Management, R&D Management, Technological Forecasting and Social Change, and other journals.
Chia-Yon Chen is a professor at the Graduate Institute of Resources Engineering, National Cheng Kung University, Taiwan. He received his doctorate in Mining and Energy Economy from West Virginia University. His current research interests include projects evaluation and resources management. He has published papers in Material and Society, The Energy Journal, Journal of Policy Modeling, Energy Economics, International Journal of Electrical Power and Energy Systems, Water Resources Management, The Journal of American Academy of Business, Energy Conversion and Management, International Journal of Management, and other journals.
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