In this dissertation, we examine how the structure of the knowledge base of a firm influences its process of search for innovation and its ability to produce useful – or valuable – innovations. Moreover, we analyze how knowledge bases evolve over time and what role alliances in the industry-wide network have in shaping the structure of knowledge bases. We define the structure of the knowledge base at the firm level looking at the network of ties between its knowledge elements as captured by technology classes and patent citations. We ask three questions: 1) How does the structure of a firm’s knowledge base evolve over time influencing its ability to produce useful innovation? 2) How does the firm’s position in the industry-wide network of alliances influence a firm in adopting a specific knowledge base structure? 3) How can we model the complex interplay between knowledge bases, search strategies and external innovation landscape? Creating innovations through the recombination of existing knowledge elements implies navigating through the vast problem space of all possible recombinations (Fleming and Sorenson, 2001). In navigating this space, firms are limited by their ability to process all the potentially relevant variables and the complex set of interactions among these variables. Coupling different elements is a way to solve the so called “combinatorial explosion problem”, namely the impossibility to conduct an exhaustive analysis of all possible combinations. Choices of couplings reduce the search space, decreasing the number of alternative combinations to be considered. These choices determine a knowledge base with a given structure. We test the relationship between different structures and firms’ ability to navigate the search space in the context of the worldwide nanotechnology industry. Moreover, we test the relationship between the network position of a firm and the type of structure adopted. Finally, starting from the insights drawn by our analyses, we propose a new model based on the niche construction theory able to model the complex interplay between knowledge bases, search strategies and external environment, extending our understanding of the process of innovation. Our data are built by merging data from Patstat, S&P Capital IQ and Thomson Reuteurs Datastream. We find support for our hypotheses.
|Titolo:||Knowledge decomposability, strategic alliances and search strategies: evidence from the Nanotechnology industry|
|Data di pubblicazione:||3-mag-2017|
|Appare nelle tipologie:||06.2 - Tesi di dottorato 2008-2019 (Doctoral Thesis 2008-2019)|