A direct or indirect network effect is defined as the phenomenon where the number of users of a product/service or the number of complementary products of a product/service increases the value of that product/service. In case of connected and autonomous vehicles (CAVs), the value to consumers is positively affected by the number of users and interoperable road facilities, so the network effect is important in CAV diffusion. In this study, we empirically analyzed the direct and indirect network effects on CAV adoption from the perspective of consumer preference. We conducted a choice experiment and derived the consumer utility function with a mixed logit model. We considered the percentage of CAVs on the road (i.e., the number of CAV users) and ICT infrastructure coverage (i.e., the level of complimentary CAV services) for the direct and indirect network effect, exclusive CAV lanes, autonomous driving technology, fuel efficiency, and price as key attributes of CAVs. We found empirical evidence that there is extensive heterogeneity among consumers regarding CAV attributes, and that potential CAV consumers are influenced highly by the indirect network effect followed by the direct network effect. Based on scenario analyses, we suggest some government policies and corporate strategies for CAV market.
|Journal||Research in Transportation Economics|
|Publication status||Published - 2021 Dec|
Bibliographical noteFunding Information:
This work has supported by the National Research Foundation of Korea (NRF) grant funded by the Korean government ( MSIT ) (No. NRF-2016R1A2B4009990 ).
All Science Journal Classification (ASJC) codes
- Economics, Econometrics and Finance (miscellaneous)