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John D. Sterman. Zhang, Qi, S.M. Massachusetts Institute of Technology Massachusetts Institute of Technology. Technology and Policy Program. Massachusetts Institute of Technology. Engineering Systems Division Technology and Policy Program 2008-11-07T19:10:43Z 2008-11-07T19:10:43Z 2008 2008 http://hdl.handle.net/1721.1/43162 250606052 Thesis (S.M.)--Massachusetts Institute of Technology, Engineering Systems Division, Technology and Policy Program, 2008. Includes bibliographical references (p. 60-63). 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. by Qi Zhang. S.M. 63 p. eng Massachusetts Institute of Technology M.I.T. theses are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission. See provided URL for inquiries about permission. http://dspace.mit.edu/handle/1721.1/7582 Technology and Policy Program. Analysis and calibration of social factors in a consumer acceptance and adoption model for diffusion of diesel vehicle in Europe Thesis application/pdf Publication unknown unknown <Publication xmlns="https://www.openaire.eu/cerif-profile/1.1/" id="cc6acd79-9d1e-4ac3-9004-e19455f7e8d7"> <Type xmlns="https://www.openaire.eu/cerif-profile/vocab/COAR_Publication_Types">http://purl.org/coar/resource_type/c_1843</Type> <Language>eng</Language> <Title>Analysis and calibration of social factors in a consumer acceptance and adoption model for diffusion of diesel vehicle in Europe</Title> <PublishedIn> <Publication> </Publication> </PublishedIn> <PublicationDate>2008</PublicationDate> <Authors> <Author> <DisplayName>Zhang, Qi, S.M. Massachusetts Institute of Technology</DisplayName> <Affiliation> <OrgUnit> </OrgUnit> </Affiliation> </Author> </Authors> <Editors> </Editors> <Publishers> <Publisher> <DisplayName>Massachusetts Institute of Technology</DisplayName> <OrgUnit /> </Publisher> </Publishers> <License>http://dspace.mit.edu/handle/1721.1/7582</License> <Keyword>Technology and Policy Program.</Keyword> <Abstract>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.</Abstract> <Access xmlns="http://purl.org/coar/access_right" > </Access> </Publication>