Beyond Gaussian averages: redirecting international business and management research toward extreme events and power caws

• 成果类型: Review
• 署名作者: Andriani, Pierpaolo; McKelvey, Bill
• 署名单位: University of California System; University of California Los Angeles; Durham University
• 刊物名称: JOURNAL OF INTERNATIONAL BUSINESS STUDIES
• ISSN/ISSBN: 0047-2506
• DOI: 10.1057/palgrave.jibs.8400324
• 发表日期: 2007
• 页码: 1212-1230
• 关键词: POWER LAWS; fractals; Gaussian; Pareto; interdependence; extremes

摘要

Practicing managers live in a world of 'extremes', but international business and management research is based on Gaussian statistics that rule out such extremes. On occasion, positive feedback processes among interactive data points cause extreme events characterized by power laws. They seem ubiquitous; we list 80 kinds of them - half each among natural and social phenomena. We use imposed tension and Per Bak's 'self-organized criticality' to argue that Pareto-based science and statistics (based on interdependence, positive feedback, scalability, (nearly) infinite variance, and emphasizing extremes) should parallel the traditional dominance of Gaussian statistics (based on independent data points, finite variance and emphasizing averages). We question quantitative journal publications depending on Gaussian statistics. The cost is inaccurate science and irrelevance to practitioners. In conclusion, no statistical findings should be accepted into business studies if they gain significance via some assumption device by which extreme events and (nearly) infinite variance are ignored. Accordingly, we suggest redirecting international business studies, and management research in general.