| Summary: | How and when do technological changes affect the rise and fall of great powers? Scholars have long observed that rounds of technological revolution disrupt the economic balance of power, bringing about a power transition in the international system. However, there has been surprisingly limited investigation into how this process occurs. The standard explanation emphasizes a country’s ability to dominate innovation in leading sectors, seizing monopoly profits in new, fast-growing industries centered around major technological breakthroughs. I propose an alternative mechanism based on the diffusion of general-purpose technologies (GPTs), which presents a different trajectory for countries to leapfrog the industrial leader. Characterized by their potential for continuous improvement, pervasiveness, and synergies with complementary innovations, GPTs only make an economy-wide impact after a drawn-out process of diffusion across many sectors. This GPT trajectory shapes which institutions matter. Specifically, variation in institutional adaptations that widen the human capital base to enable the spread of GPTs explain why some industrial leaders separate themselves from the pack. To test this argument, I set the leading-sector mechanism against the GPT diffusion mechanism across three historical case studies: Britain’s rise to preeminence in the Industrial Revolution; America and Germany’s overtaking of Britain in the second industrial revolution; Japan’s challenge to America’s technological dominance in the information technology revolution. Evidence from these case studies supports the relative explanatory power of the GPT mechanism over the leading-sector mechanism. According to some categorizations, these cases correspond to history’s three industrial revolutions. Given that many argue we are in a fourth industrial revolution, the findings of this dissertation should be particularly relevant for how emerging technologies like AI will affect a possible U.S.-China power transition.
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