An ethnographic decision tree model for predicting hydrogen fuel cell vehicle ownership

Authors: Oscar Lopez*, Arizona State University, Michael Kuby, Arizona State University, Rhian Stotts, Arizona State University, Scott Kelley, University of Nevada, Reno
Topics: Energy, Transportation Geography, Qualitative Methods
Keywords: Ethnography, Hydrogen Fuel Cell Vehicle, HFCV, FCV, FCEV, Alternative Fuel Vehicle, AFV, Early Adopter, Interview, Decision Making, Decision Tree Model, Decision Modelling
Session Type: Paper
Day: 4/3/2019
Start / End Time: 8:00 AM / 9:40 AM
Room: Washington 4, Marriott, Exhibition Level
Presentation File: No File Uploaded

Zero-emission hydrogen fuel cell vehicles (HFCV) have come to market in California, with over 5000 units sold and 32 stations online. In addition to the vehicles and stations, the growth of the HFCV industry requires drivers to adopt the technology. Development of policy and actions that can promote adoption of HFCVs requires understanding of the decision whether or not to do so. Previous studies have employed stated preference surveys, multinomial logit models, and statistical analysis of online surveys. We develop an ethnographic decision tree model to determine the mechanisms by which drivers chose to adopt or not adopt an HFCV. Ethnography permits participants to identify the aspects of decision-making most important to them and imparts deeper understanding of the reasoning behind an individual's decision-making processes than statistical methods might uncover. We recruited drivers who seriously considered purchasing or leasing an HFCV--whether they ultimately decided to drive the vehicle or not--via online fora, then conducted and recorded semi-structured individual interviews. We analyzed the drivers' individual decision trees and collated them into one encompassing multistage decision tree model to predict HFCV ownership. We validated this model by conducting shorter interviews with a larger sample of drivers. We identified commonalities in the decision making process involving relationships between the qualities of decision-making individuals, the suite of cars commercially available, and the existing and planned infrastructure network that supports HFCV travel.

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