A Fractal Approach to Industry Dynamism
提出用分形方法研究行业动态性，通过测量时间序列的粗糙度（分形维数）来捕捉非线性、内生且稳定的不可预测性来源，并在美国网络电视行业验证其有效性。
The concept of industry dynamism claims a central role in models of organizational adaptation. However, the development of new ways to study it has waned. Building on the literatures on nonlinear dynamical systems and information complexity, we introduce a fractal approach as a useful lens to industry dynamism and a fresh alternative and complement to prevailing approaches. This differs conceptually from existing methods in highlighting nonlinearity and recognizing endogenous and stable sources of apparent unpredictability. Further, it uses the fractal dimension, a measure of the jaggedness in a time series, which offers several advantages over existing dispersion-based measures of unpredictability. We apply the fractal approach in an exploratory longitudinal study of the turbulent US network television industry and demonstrate its ability to uncover distinct aspects of industry dynamism.