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On the Disruptive Innovation Strategy of Renewable Energy Technology Diffusion: An Agent-Based Model

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  • Yongchao Zeng

    (School of Management and Economics, Beijing Institute of Technology, Haidian, Beijing 100081, China
    Energy Systems Division, Argonne National Laboratory, Lemont, IL 60439, USA)

  • Peiwu Dong

    (School of Management and Economics, Beijing Institute of Technology, Haidian, Beijing 100081, China)

  • Yingying Shi

    (School of Management and Economics, Beijing Institute of Technology, Haidian, Beijing 100081, China
    Energy Systems Division, Argonne National Laboratory, Lemont, IL 60439, USA)

  • Yang Li

    (Energy Systems Division, Argonne National Laboratory, Lemont, IL 60439, USA
    School of Electrical Engineering, Northeast Electric Power University, Jilin 132012, China)

Abstract

Renewable energy technologies (RETs) are crucial for solving the world’s energy dilemma. However, the diffusion rate of RETs is still dissatisfactory. One critical reason is that conventional energy technologies (CETs) are dominating energy markets. Emergent technologies that have inferior initial performance but eventually become new dominators of markets are frequently observed in various industries, which can be explained with the disruptive innovation theory (DIT). DIT suggests that instead of competing with incumbent technologies in the dominated dimension, redefining the competition on a two-dimensional basis is wise. Aiming at applying DIT to RET diffusion, this research builds an agent-based model (ABM) considering the order of entering the market, price, preference changing and RET improvement rate to simulate the competition dynamics between RETs and CETs. The findings include that the order of entering the market is crucial for a technology’s success; disruptive innovation is an effective approach to cope with the disadvantage of RETs as latecomers; generally, lower price, higher consistency with consumers’ preferences and higher improvement rate in the conventional dimension are beneficial to RET diffusion; counter-intuitively, increasing RET’s improvement rate in the conventional dimension is beneficial to RET diffusion when the network is sparse; while it is harmful when the network is densified.

Suggested Citation

  • Yongchao Zeng & Peiwu Dong & Yingying Shi & Yang Li, 2018. "On the Disruptive Innovation Strategy of Renewable Energy Technology Diffusion: An Agent-Based Model," Energies, MDPI, vol. 11(11), pages 1-21, November.
  • Handle: RePEc:gam:jeners:v:11:y:2018:i:11:p:3217-:d:184128
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