Incorporating social impact on new product adoption in choice modeling: A case study in green vehicles |
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| Affiliation: | 1. Environmental Energy Technologies Division, Lawrence Berkeley National Laboratory, 1 Cyclotron Road MS 90R4000, Berkeley, CA 94720, United States;2. Mechanical Engineering, Northwestern University, 2145 Sheridan Road, Tech B224, Evanston, IL 60208, United States;3. Center for Energy, Environmental, and Economic Systems Analysis, Argonne National Laboratory, Argonne, IL 60439, United States;1. University of Southern California Sol Price School of Public Policy, United States;2. Ohio State University School of Environment and Natural Resources, United States;1. Urban Planning Group, Department of the Built Environment, Eindhoven University of Technology, Vertigo 8.22, P.O. Box 513, 5600MB Eindhoven, The Netherlands;2. Urban Planning Group, Department of the Built Environment, Eindhoven University of Technology, Vertigo 8.25, P.O. Box 513, 5600MB Eindhoven, The Netherlands;3. Urban Planning Group, Department of the Built Environment, Eindhoven University of Technology, Vertigo 8.18, P.O. Box 513, 5600MB Eindhoven, The Netherlands;1. The Economic and Social Research Institute, Dublin, Ireland;2. Department of Economics, Trinity College, Dublin, Ireland |
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| Abstract: | While discrete choice analysis is prevalent in capturing consumer preferences and describing their choice behaviors in product design, the traditional choice modeling approach assumes that each individual makes independent decisions, without considering the social impact. However, empirical studies show that choice is social – influenced by many factors beyond engineering performance of a product and consumer attributes. To alleviate this limitation, we propose a new choice modeling framework to capture the dynamic influence from social networks on consumer adoption of new products. By introducing social influence attributes into a choice utility function, social network simulation is integrated with the traditional discrete choice analysis in a three-stage process. Our study shows the need for considering social impact in forecasting new product adoption. Using hybrid electric vehicles as an example, our work illustrates the procedure of social network construction, social influence evaluation, and choice model estimation based on data from the National Household Travel Survey. Our study also demonstrates several interesting findings on the dynamic nature of new technology adoption and how social networks may influence hybrid electric vehicle adoption. |
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| Keywords: | Discrete choice analysis Social impact Social network simulations Product adoption Hybrid vehicles |
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