From Gaussian to Paretian Thinking: Causes and Implications of Power Laws in Organizations

• 成果类型: Review
• 署名作者: Andriani, Pierpaolo; McKelvey, Bill
• 署名单位: Durham University; University of Salento; University of California System; University of California Los Angeles
• 刊物名称: ORGANIZATION SCIENCE
• ISSN/ISSBN: 1047-7039
• DOI: 10.1287/orsc.1090.0481
• 发表日期: 2009
• 页码: 1053-1071
• 关键词: pareto; power law; Gaussian statistics; oganization; average; extreme events; scale-free theory

摘要

Although normal distributions and related current quantitative methods are still relevant for some organizational research, the growing ubiquity of power laws signifies that Pareto rank/frequency distributions, fractals, and underlying scale-free theories are increasingly pervasive and valid characterizations of organizational dynamics. When they apply, researchers ignoring power-law effects risk drawing false conclusions and promulgating useless advice to practitioners. This is because what is important to most managers are the extremes they face, not the averages. We show that power laws are pervasive in the organizational world and present 15 scale-free theories that apply to organizations. Next we discuss research implications embedded in Pareto rank/frequency distributions and draw statistical and methodological implications.