How does the nature of shakeouts affect technological development? This paper examines how the shakeout phase of an industry’s life cycle shapes the trajectory of its technological S-curve. We argue that the nature of exit barriers governs the speed at which active firms thin after the industry’s peak. This post-peak thinning—shakeout speed—mechanically determines both the attainable ceiling of technological development and the timing of the eventual slowdown. High exit barriers flatten the shakeout and allow thicker post-peak firm networks to persist, sustaining diffusion and raising the S-curve’s upper limit. Conversely, richer submarkets or lower exit barriers steepen the shakeout, left-shifting the S-curve and producing an earlier and lower plateau. The analysis highlights a policy trade-off: lowering entry and exit barriers to stimulate startups can accelerate early takeoff but simultaneously bring forward a lower technological ceiling—an effect that is especially pronounced when general knowledge levels are high and lucrative submarkets attract rapid turnover. Our empirical design isolates the role of shakeout speed by holding pre-peak dynamics fixed and mapping alternative post-peak firm-count paths into technological development through a non-decreasing logistic law. Using common-draw Monte Carlo simulations across scenarios, we show that faster thinning consistently truncates the S-curve, while gentler thinning supports later slowdowns and higher ceilings. Entry is treated discursively rather than an identification target; scenarios that combine high exit barriers with cautious entry delay the peak yet preserve the qualitative ranking: thicker post-peak networks enhance technological outcomes, while thinner ones stall earlier at lower levels.

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Shakeout Speed and Technological Trajectory

  • Hiroshi Shimizu

摘要

How does the nature of shakeouts affect technological development? This paper examines how the shakeout phase of an industry’s life cycle shapes the trajectory of its technological S-curve. We argue that the nature of exit barriers governs the speed at which active firms thin after the industry’s peak. This post-peak thinning—shakeout speed—mechanically determines both the attainable ceiling of technological development and the timing of the eventual slowdown. High exit barriers flatten the shakeout and allow thicker post-peak firm networks to persist, sustaining diffusion and raising the S-curve’s upper limit. Conversely, richer submarkets or lower exit barriers steepen the shakeout, left-shifting the S-curve and producing an earlier and lower plateau. The analysis highlights a policy trade-off: lowering entry and exit barriers to stimulate startups can accelerate early takeoff but simultaneously bring forward a lower technological ceiling—an effect that is especially pronounced when general knowledge levels are high and lucrative submarkets attract rapid turnover. Our empirical design isolates the role of shakeout speed by holding pre-peak dynamics fixed and mapping alternative post-peak firm-count paths into technological development through a non-decreasing logistic law. Using common-draw Monte Carlo simulations across scenarios, we show that faster thinning consistently truncates the S-curve, while gentler thinning supports later slowdowns and higher ceilings. Entry is treated discursively rather than an identification target; scenarios that combine high exit barriers with cautious entry delay the peak yet preserve the qualitative ranking: thicker post-peak networks enhance technological outcomes, while thinner ones stall earlier at lower levels.