Modeling adoption timing of autonomous vehicles: innovation diffusion approach
Autor: | Ramin Shabanpour, Ali Shamshiripour, Abolfazl Mohammadian |
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Rok vydání: | 2018 |
Předmět: |
Estimation
050210 logistics & transportation media_common.quotation_subject 05 social sciences Word of mouth Transportation 010501 environmental sciences Development 01 natural sciences Metropolitan area Travel behavior Perception 0502 economics and business Market price Network performance Business Industrial organization 0105 earth and related environmental sciences Civil and Structural Engineering media_common Market penetration |
Zdroj: | Transportation. 45:1607-1621 |
ISSN: | 1572-9435 0049-4488 |
Popis: | Autonomous vehicles (AVs) are expected to act as an economically-disruptive transportation technology offering several benefits to the society and causing significant changes in travel behavior and network performance. However, one of the critical issues that policymakers are facing is the absence of a sound estimation of their market penetration. This study is an effort to quantify the effect of different drivers on the adoption timing of AVs. To this end, we develop an innovation diffusion model in which individuals’ propensities to adopt a new technology such as AVs takes influence from a desire to innovate and a need to imitate the rest of the society. It also captures various sources of inter-personal heterogeneity. We found that conditional on our assumptions regarding the changes in market price of AVs over time, their market penetration in our study region (Chicago metropolitan area) will eventually reach 71.3%. Further, model estimation results show that a wide range of socio-demographic factors, travel pattern indicators, technology awareness, and perceptions of AVs are influential in people’s AV adoption timing decision. For instance, frequent long-distance travelers are found to make the adoption decision more innovatively while those who have experienced an accident in their lifetime are found to be more influenced by word of mouth. |
Databáze: | OpenAIRE |
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