A matter-element method for risk identification of technology innovation

Abstract

With the rapid development of IT, technology innovation has attracted increasing attentions from governments, enterprises and researchers. It is notable that the failure rate of technology innovation is high and the risk cannot be ignored. Risk identification is a critical step of risk management and to identify risk accurately and effectively is important for technology innovation organizations. However, the extant risk identification approaches cannot be directly applied, due to the characteristics of technology innovation risk such as uncertainty and fuzziness. In this paper we introduce matter-element model, which is developed from extension theory, and can be employed to support the characteristics of technology innovation risk. On the basis of the traditional meta-model, this paper attempts to improve the schema, through constructing indicator system of technology innovation risk. We present a method of determining the weights of indicators based on minimum deviation, which integrates the AHP weight and entropy weight. Through the calculating process and sensitivity analysis, the risk factors of technology innovation with different features can be identified, and technology innovation organizations can formulate and perform targeted strategies toward different risk factors. Finally, based on an instance, we discuss the effectiveness of our method and draw the conclusions.