In recent, the innovation paradigms of industrial structure in high-tech industry have been continuing for a long time, which has reshaped from traditional value chain to the global value network and ecosystem and boundary of industrial segments has faded. Therefore, the global firms compete and collaborate simultaneously with other firms to have technological and strategic competitive advantage for its survival. And, to enhance their core competencies and promote innovation, they also tend to create their value via technological devel-opment, strategic alliance, and vertical integrations. Consequently, value creation from these changed patterns of firm’s activities depends not only on a cooperative structure between firms but also on their coevolution pat-terns, which have become the main characteristic of the business ecosystem. Therefore, from a strategic percep-tive, understanding the evolutionary patterns and features of business ecosystem is important in both academic and practice fields because the firm can create valuable information and strategic implication related to their positioning and future direction in networked corporate environment. Therefore, in this thesis, the evolutionary patterns of two main high-tech industries, mobile and biopharmaceutical, are identified quantitatively using empirical data. For this thesis, various indices of social network analysis are used to identify the industrial net-work structure and the specific roles of firms in innovation ecosystem.
Theme #1 and #2 focus on the identification of change of knowledge network structure in mobile indus-try. With the appearance of smart devices and the rapid development of ICT technology, the traditional value chain of the mobile industry seems to be increasingly deconstructed, and a new industrial structure is evolving into a complex network with new players. Therefore, in theme #1, this study analyzes the patterns of technolog-ical knowledge flows in the mobile structure using patent citation analysis. After examining the centrality index values derived, platform providers are shown to be at the center of the knowledge flow activity in the ecosys-tem, which explain the recent increasing importance of platform providers in the mobile ecosystem. Therefore, our results clearly demonstrate the changing landscape of the mobile ecosystem, centering on platform provid-ers. Moreover, to indicate how much knowledge flow of platform providers perform for other industries, the concentration rate of six platform providers are analyzed to derive the industrial implications. The results show that each platform provider has a different pattern of knowledge flow and different dynamics of knowledge concentration across different subsectors. In particular, a few platform providers, such as Apple and Google, appear to change their knowledge innovation strategies in ways that strengthen their technological influence over their own sub-ecosystems. Theme #2 is also concerned with analyzing the ecosystem structure of the mo-bile industry and identifying the different roles of firms in it using brokerage measurement as well as centrality measurement. The results show that platform providers and application and software providers are at the center of knowledge exchange activity, playing brokerage roles in the mobile ecosystem which have the highest value of centrality, also have the highest value in brokerage measurement. It implies that they have similar patterns of centrality and brokerage roles of subsectors in mobile ecosystem and have a positive correlation between cen-trality and brokerage in the knowledge network. Second, this study categorizes mobile firms into five different groups based on the patterns of their network centrality in order to identify their role and characteristics in the mobile ecosystem. This paper classifies five clusters of mobile firms within the knowledge network: Keystone players, Distributing mediators, Absorbing mediators, Catch-up players, and Pure receivers. The categorization of firms demonstrates that knowledge flows in the mobile industry converge towards a few leading firms, and such patterns are shaping the mobile ecosystem with respect to technological knowledge. These two themes, #1 and #2 are good opportunities to explore the overall evolutionary patterns of structure in knowledge networks in the mobile ecosystem quantitatively that offer industrial researchers a guideline for estimating firms’ internal capacity for technology and knowledge and evaluating the quality of overall patents at a firm. It also suggests some implications from expanding their knowledge influence by monitoring their competitors’ knowledge ability in the mobile industry. Under changed knowledge flow structure among mobile firms, it is expected to contribute to mobile firms that can formulate technological portfolio and patent strategy for knowledge management de-pend on their different knowledge brokerage roles to other subsectors to gain competitive advantage of technol-ogy in mobile industry.
Theme #3 is concerned with the dynamics of strategic alliance network in biopharmaceutical firms to explore competitive advantages of firms’ external activities. Firstly, this paper visualizes total strategic alliance network of industry surrounded biopharmaceutical industry from 1984 to 2010 and investigates shifted power of alliance network in biopharmaceutical industry. Major resources of capital are shifted from investors (ven-ture capital) to big pharmaceutical firms and the value of centrality of educational institutions and commercial service providers increased over time. Second, this paper examines the effects of network position and network diversity on firm performance using panel regression and compares two industries, pharmaceutical and biotech-nology. The empirical results for innovation performance suggest that the central position of pharmaceutical firm in alliance network is positively related to its innovation performance while the peripheral position of bio-technology firm in alliance network and innovation performance are positively related. And the results indicate that the relationship with other firms toward a certain industry of pharmaceutical and biotechnology firms would have significantly a positive effect on innovation performance. In addition, the empirical results for fi-nancial performance show that both central and mediate position of firm in alliance network is not related di-rectly with their sales outcome. And high inter-industry diversification in alliance network is positively associated with financial performance in pharmaceutical firms while high intra-industry diversification of alliance network has significantly a negative effect on financial performance in biotechnology. The opposite impact between pharmaceutical and biotechnology offers the suggestions to policy makers and strategic managers to have next plan for strategic alliance and reduce rate of failure from collaboration. And it also provides useful information to identify the determinants relevant to their performance when they decide alliance strategy of diversification in alliance network.