Innovation is inherently characterized by significant uncertainty, particularly in emerging industries centered on complex technologies. A profound understanding of the inherent nature of complex technologies and their interplay with firm R&D strategy and market environment is paramount for achieving technology leadership. From an evolutionary perspective, we model and simulate the multi-technology co-evolution process across different scenarios. Meanwhile, we conduct empirical analyses on both simulation data (1,072,500 observations) and patent data (17,532 US patents), which confirm the robustness and applicability of the model. Further, we focus on metaverse as a typical case of emerging complex technologies. Specifically, we identify metaverse-relevant technologies and utilize approximately three million US patents from 1926 to 2020 to parameterize the model. This allows us to perform simulations to analyze the process and performance of the metaverse system. The results from the above analyses demonstrate that, first, the effects of internal and external coupling on average fitness are quite complex and jointly depend on their interaction, while stronger internal coupling or weaker external coupling consistently enhances efficacy. Second, a balanced R&D strategy generally leads to higher average fitness and efficacy, while an aggressive strategy, despite early gains, prolongs the time to equilibrium except in the high external coupling state. Third, a stable market environment improves average fitness and efficacy of the system. Fourth, the metaverse system is currently in a state of strong internal and external coupling, which necessitates a long time to reach equilibrium; in the current turbulent market environment, a balanced R&D strategy emerges as the optimal choice.
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