A Fuzzy DEMATEL based Lead User Method for deriving factors influencing the acceptance of an innovative technology

The Smart Phone emerged recently as one of the most popular consumer electronics devices. Consequently, analyzing and predicting the consumers´ purchasing behaviors of Smart Phone for fulfilling customers´ needs has become an indispensable task for marketing managers of the mobile phone vendors´. However, the predictions are not easy. The consumer electronics technology evolved rapidly. Market leaders are also competing in the same segmentation by providing similar products which further complicated the competitive situation. How the consumers´ acceptance of future Smart Phones can be analyzed and predicted had become an important but difficult task. In order to accurately analyze the factors influencing consumers´ acceptance of Smart Phone and predict the consumer behavior, the Technology Acceptance Model (TAM) and the Lead User Method (LUM) will be introduced. Further, the differences in the factors being recognized by both lead users as well as mass customers will be compared. The possible customers´ needs will first be collected and summarized by reviewing literature on the TAM. Then, the causal relationship between the factors influencing the consumer behaviors being recognized by both the lead users as well as the mass customers will be derived by the Fuzzy DEMATEL (FDEMATEL), Analytic Network Process (ANP) and the Structural Equation Modeling (SEM), respectively. An empirical study based on the Taiwanese Smart Phone users will be leveraged for comparing the results being derived by the FDEMATEL, the ANP and the SEM. According to the analytic results being derived by using the FDEMATEL and ANP based LUM, the perceived usefulness, perceived ease of use, attitude and behavioral intention were recognized as the most important factors for influencing the users´ acceptance of Smart Phone. The research results can serve as a basis for the marketing managers´ strategy definitions. The proposed methodology can be used for analyzing and predicting customers´ p- - references and acceptances of high technology products in the future.