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The coevolution of digital ecosystems
SungYong, Um
SungYong, Um
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Thesis/Dissertation
Date
2016
Advisor
Yoo, Youngjin
Committee member
Wattal, Sunil
Kulathinal, Rob J.
Henfridsson, Ola
Kulathinal, Rob J.
Henfridsson, Ola
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Department
Business Administration/Management Information Systems
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DOI
http://dx.doi.org/10.34944/dspace/2467
Abstract
Digital ecosystems are one of the most important strategic issues in the current digital economy. Digital ecosystems are dynamic and generative. They evolve as new firms join and as heterogeneous systems are integrated into other systems. These features digital ecosystems determine economic and technological success in the competition among digital platform systems. However, how these ecosystems evolve over time is not yet clearly known. I describe three empirical essays in order to understand the underlying mechanism of the evolution of a digital ecosystem: 1) the underlying architecture of a digital ecosystem, 2) the evolutionary pattern of a digital ecosystem, 3) and the co-evolution of a digital ecosystem. To explore these topics, I focus on the underlying generative structure of the ecosystem and its evolutionary pattern of WordPress, which is the world largest blog platform system. I collected a comprehensive set of information about the WordPress ecosystem including over 23,000 plug-ins from January 2004 to December 2014. To analyze the data, I apply a network approach to capture the generative nature of digital technology that assumes a fractal-like structure in which digital components such as Application Programming Interfaces (API) cluster into groups that generate other groups over time. As such, I can effectively capture the hierarchical structure of a network by exploring the topological structure of sub-networks that represent the fractal-like evolutionary dynamic system mechanism. The network approach, together with the conventional statistical approach, allows me to understand the unique nature of a digital ecosystem that is different from the boundary of a decomposable system, as the generative nature of system-agnostic digital components builds on a developmental combinable system. I also discuss underlying theory, methodology, data, result, and implications and conclude by highlighting the contributions of this study and the direction of future research to further explore the evolution of digital ecosystems.
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