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Dynamics of Technology Adoption and Critical Mass: The Case of U.S. Electric Vehicle Market

Author

Listed:
  • Shanjun Li

    (Dyson School of Applied Economics and Management, Cornell University, Ithaca, NY 14853)

  • Yiyi Zhou

    (Department of Economics, Stony Brook University, Stony Brook, NY 11794)

Abstract

We examine the dynamics of technology adoption and critical mass in network industries with an application to the U.S. electric vehicle (EVs) market. This market exhibits indirect network effects in that consumer EV adoption and investor deployment of public charging stations are interdependent. In markets with positive indirect network effects, multiple equilibria with different level of technology adoption may exist. The diffuion and ultimately the success of technology depend on the equilibrium structure and property. Under certain market conditions, the issue of critical mass arises and the market needs to pass this critical mass in order to reach the high-adoption equilibrium. Using a data set of quarterly EV sales in 354 U.S. metro areas from 2011 to 2013, we quantify indirect network effects and simulate long-run market outcomes in each of the MSAs. Our analysis provides robust and significant evidence of indirect network effects in this market. Simulations show several different market equilibrium outcomes across the 354 MSAs in the long run with a significant number of them exhibiting multiple equilibria and critical mass. Policy suggestions are provided in order to push these markets to pass the critical mass and move towards the high-adoption equilibrium.

Suggested Citation

  • Shanjun Li & Yiyi Zhou, 2015. "Dynamics of Technology Adoption and Critical Mass: The Case of U.S. Electric Vehicle Market," Working Papers 15-10, NET Institute.
    • Handle: RePEc:net:wpaper:1510
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    References listed on IDEAS

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    Cited by:

    1. Maeng, Kyuho & Jeon, Seung Ryong & Park, Taeho & Cho, Youngsang, 2021. "Network effects of connected and autonomous vehicles in South Korea: A consumer preference approach," Research in Transportation Economics, Elsevier, vol. 90(C).
    2. Zhu, Lijing & Wang, Peize & Zhang, Qi, 2019. "Indirect network effects in China’s electric vehicle diffusion under phasing out subsidies," Applied Energy, Elsevier, vol. 251(C), pages 1-1.
    3. Shihui Tian & Guowei Hua & T. C. E. Cheng, 2019. "Optimal Deployment of Charging Piles for Electric Vehicles Under the Indirect Network Effects," Asia-Pacific Journal of Operational Research (APJOR), World Scientific Publishing Co. Pte. Ltd., vol. 36(01), pages 1-17, February.

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    More about this item

    Keywords

    electric vehicles; indirect network effects; critical mass;
    All these keywords.

    JEL classification:

    • Q4 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy
    • Q5 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Environmental Economics
    • R4 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - Transportation Economics

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