Date of Award
Doctor of Philosophy
Rapinder S. Sawhney
David L. Greene, John E. Kobza, Andrew Yu
Resistance against new innovative technologies by customers has been studied in many publications to improve prediction of behavior. Econometrics models, the Technology Acceptance Model by Fred D. Davis (1989), and market research models are the most widely used modeling techniques to predict and understand customer behaviors. The proposed methodology in this paper advances current models by relaxing many of their assumptions and increasing prediction accuracy. A case study in predicting hybrid car buyer behaviors is performed to illustrate and validate the suggested modeling method named as the Energy Efficiency Technology Acceptance Model.
Asudegi, Mohammad Ali, "A Cluster Based Model to Enhance Acceptance of New Energy Driven Technologies. " PhD diss., University of Tennessee, 2018.