Computational Analysis of Technological Innovation in Complex Enterprise Systems

Technological innovation in complex enterprise systems requires coordinated interplay between a heterogeneous set of industrial players. The complexity in how firms form relationships with each other perplexes the decision-making processes for individual players when they explore the technological search space in order to achieve breakthrough innovation. Building upon the existing literature on business ecosystem, interfirm alliance, new product development, and technology management, we explore the interplay between technological innovation and interfirm relationship as well as the alliance formation patterns in the business ecosystem context. We start with providing a macroscopic perspective on the information and communication technology ecosystem, followed by in-depth empirical investigations in the mobile handset industry. We employ network visualization, sequence clustering, and organizational simulation methodologies for the macroscopic analysis. Our microscopic analysis borrows methodologies from econometrics including regression analysis, difference-in-differences estimation, and event study. Our results propose an effective way to visualize the whole industrial ecosystem and show how the enterprise system has transformed over time. The results of the microscopic analyses show how interfirm relationship shapes technological innovation and how technological innovation is materialized in firm value. Lastly, we present an integrated computational framework to infer alliance formation strategy. We contribute to the literature by providing generative methods and empirical evidences that accommodate a more complete view of the innovation process in the business ecosystem setting. The dissertation concludes by suggesting directions for future research and highlighting implications for research and practice in the area of technological innovation in the business ecosystem.Ph.D