Comparative Analysis of Risk Assessment for Technical Standards Alliance Based on BP Neural Network and Fuzzy AHP Methods

Abstract

Establishing unified industrial technical standards for a single enterprise in a highly global integrated market is becoming increasingly difficult. In recent years, leading enterprises have often built technical standards alliances around a key core technology to develop industrial standards cooperatively in order to learn from each other and optimize their resource allocation. Although such technical standards alliances result in huge gains to their members, their internal and external risks threaten both the alliances and their members. As compared to other forms of strategic alliances, the risk of such an alliance has fuzzy characteristics and is difficult to fully and accurately identify. This paper uses a fuzzy pattern-recognition method to evaluate and summarize the risks of technical standards alliances. A fuzzy analytic hierarchy process (AHP) evaluation and back propagation (BP) logic fuzzy neural network methods are used to construct a risk-evaluation model of technical standards alliances while considering an alliance around new-energy automobiles in Zhejiang as an empirical example. The two evaluation models are then contrastively analyzed, and cross validation of the evaluation results is performed in order to provide theoretical guidance and support for the application of two fuzzy evaluation models in practice.