Date of Award
4-2022
Rights
© 2022 Sean M. Sullivan
Document Type
Dissertation
Degree Name
Doctor of Education (EdD)
Department
Education
First Advisor
Laura Bertonazzi
Second Advisor
Darren Akerman
Third Advisor
Michael Walden
Abstract
Rapid technological progress is becoming more challenging for organizations to implement and manage. The traditional, hierarchical leadership models are often inadequate to cope with continuous change, and the inability to keep up with the latest advances can quickly imperil a company. In particular, the field of biotechnology is currently experiencing revolutionary advances. Where hierarchical leadership models lapse, complexity theory and complexity leadership theory may provide an alternative leadership model for successful organizational adaptation. However, much of the research surrounding complexity theory remains academic. Historical data from a biotechnology company was analyzed during a computer hardware and software upgrade to detect the presence of a complex adaptive system, the fundamental component of complexity. Results showed that after the upgrade, animal care technicians did not significantly increase their collective efficiency; instead, they appeared to significantly increase their collective accuracy. This might indicate that the animal care technicians acted as a complex adaptive system in response to an environmental change. Insights into aggregate employee behavior through the lens of complexity theory might be useful to leadership seeking to successfully implement organizational change. Additionally, the adoption of complexity leadership doctrines by management might help create enhanced conditions to cultivate increased innovation and growth.
Preferred Citation
Sullivan, Sean M., "Identifying Complex Adaptive Systems Using Quantitative Approaches At A Midsized Biotechnology Firm" (2022). All Theses And Dissertations. 418.
https://dune.une.edu/theses/418
Comments
Ed.D. Dissertation