Analysis and Calibration of Social Factors in a Consumer Acceptance and Adoption

While large scale diffusion of alternative fuel vehicles (AFVs) is widely anticipated, the mechanisms that determine their success or failure are ill understood. Analysis of an AFV transition model developed at MIT has revealed that AFV diffusion dynamics are particularly sensitive to consumer consideration as influenced by social exposure to AFVs. While some empirical research in this area exists, uncertainty regarding these social exposure parameters remains high. Following principles of partial model testing, this research examines social exposure parameters, with a focus on empirical accounts of diffusion involving diesel passenger vehicles in Europe. The research uses the historical data of diesel sales in six European countries. To complete diffusion datasets the research generates synthetic data in early stages of diffusion. The results from the calibrations yield parameters that are in line with other marketing studies. These findings help reduce uncertainty regarding social exposure parameters in the automotive industry. Further, bootstrapping confidence intervals are conducted to test the reliability of the parameter estimate. Challenges and avenues about building confidence in parameter estimate and data analysis are discussed. Thesis Supervisor: John D. Sterman Jay W. Forrester Professor of Management and Engineering Systems Director, System Dynamics Group Table of