Using maximum likelihood estimation methods and complexity science concepts to research power law-distributed phenomena

Assistant Professor G. Christopher Crawford and Professor Bill McKelvey

Chapter 12 in Handbook of Research Methods in Complexity Science, 2018, pp 227-253 from Edward Elgar Publishing

Abstract: Life is not normally distributed – we live in a world of extreme events that skew what we consider ‘average.’ The chapter begins with a brief explanation of the basic causes of skewed distributions followed by a section on horizontal scalability processes. These are generated by scale-free mechanisms that result in self-similar fractal structures within organizations. The discussion then focuses on one of the most cited mechanisms purported to cause power law distributions: Bak’s (1996) ‘self-organized criticality’. Using three longitudinal datasets of entrepreneurial ventures at different states of emergence, the chapter presents a method to determine whether data are power law distributed and, subsequently, how critical thresholds can be calculated. The analysis identifies the critical point in both founder inputs and venture outcomes, highlighting the threshold where systems transition from linear to nonlinear and from normal to novel. This provides scholars with a conceptual–empirical link for moving beyond loose qualitative metaphors to rigorous quantitative analysis in order to enhance the generalizability and utility of complexity science.

Keywords: Business and Management; Geography; Innovations and Technology; Politics and Public Policy Research Methods; Urban and Regional Studies (search for similar items in EconPapers)
Date: 2018
References: Add references at CitEc
Citations: View citations in EconPapers (3)

Downloads: (external link)
https://www.elgaronline.com/view/9781785364419.00023.xml (application/pdf)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:elg:eechap:16937_12

Ordering information: This item can be ordered from
http://www.e-elgar.com

Access Statistics for this chapter

More chapters in Chapters from Edward Elgar Publishing
Bibliographic data for series maintained by Darrel McCalla ().