CEU Electronic Theses and Dissertations, 2019
| Author | Khraisha, Tamer N.m |
|---|---|
| Title | Network Structure and Optimal Technological Innovation |
| Summary | This thesis aims at investigating the role of inter-firm network structure in the development of technological innovations. Technological innovation is a complex economic problem, in that it admits a multidimensional landscape of potential solutions that are non-trivial to explore. To model this complexity, the approach of fitness landscapes offers a flexible and detailed framework. Furthermore, the process of technological innovation is increasingly stylized as a collective problem of interacting economic agents, and to model these interactions, network science offers the best tools. The analysis conducted in this thesis has two goals: first, to understand the role of network efficiency, degree-heterogeneity, and edge directionality in the process of technological innovation, and second to attempt to offer empirical case study where a technological innovation was collectively developed. An evolutionary agent-based model and an applied case study from financial markets are presented and discussed. In both cases, a group of firms (in the case study, banks) collectively search a complex (rugged) technological landscape and observe each other's solutions through different relationship networks. Concerning the agent-based model, two families of networks are used in the analysis; the first family includes undirected networks which vary in terms of efficiency, i.e. average path length. The second family includes directed networks which vary in terms of degree heterogeneity. Results for the agent-based model show that network efficiency and degree heterogeneity are important factors influencing the average performance of the system. As for the case study, I used a projected financial network that is derived from the syndicated lending database DealScan, provided by Thomson and Reuters, which I employ to produce a heterogeneous and directed network. The results obtained for the case study show an interesting trade-off between market efficiency and system stability. |
| Supervisor | Kertész, János |
| Department | Network Science PhD |
| Full text | https://www.etd.ceu.edu/2019/khraisha_tamer.pdf |
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