The effects of firms' technological knowledge on search and learning for innovation

Fengchun (Tara) Li

doi:10.17918/00010706

This dissertation delves into the contingent role of knowledge interdependence on organizational search and learning during the innovation process. Central to this inquiry is the assertion that search and learning, though often conflated, are distinct concepts, each playing a crucial role in driving innovation. The dissertation argues that the search and learning are influenced by knowledge interdependence differently. The first part of the dissertation, Chapter 2 investigates the nuanced roles of search and learning within the innovation process, emphasizing their intertwined yet distinct functions and the critical role of knowledge interdependence. The chapter identifies gaps in understanding how organizations navigate search and learning amid knowledge interdependencies and how they manage the interdependence within an organization compared to that in its task environment. It sets the stage for future empirical and theoretical developments aimed at enriching our understanding of how to leverage knowledge interdependence to enhance search and learning. Chapter 3 reveals how knowledge interdependence serves as both a facilitator and barrier to innovation, affecting search and learning in distinct ways. This chapter further introduces knowledge distinctiveness as a moderating factor, enhancing or hindering the impact of interdependence based on the organization's unique knowledge stock. Through empirical examination in the pharmaceutical and semiconductor industries, it validates these concepts and demonstrates their applicability across diverse technological landscapes. Chapter 4 delves into how organizational knowledge interdependence and its alignment with external knowledge interdependencies influence exploratory search, building on the literature on organizational representation. As this chapter takes an industry perspective, the focus is more on where to search. While interdependence alignment with the industry also influences learning, the effect could be muted when it comes to integrating new knowledge considering sequential processes. As such, this chapter mainly focuses on the search. Through an analysis of 39 years of patent data in the U.S. semiconductor industry, it finds that interdependency alignment plays a crucial role in enabling firms to explore the broader landscape of innovation opportunities. Overall, this dissertation contributes to the fields of organizational search, learning, and complex systems theory by delineating the concepts of search and learning during innovation. First, this study clarifies the different roles of organizational search and learning in innovation, introducing the concept of knowledge interdependence as both a facilitator and a barrier to innovation processes. Second, this dissertation reveals how strategic management of knowledge interdependence can enhance innovation, validated by empirical studies across pharmaceutical and semiconductor sectors, offering vital insights for technology-intensive industries. Third, this study highlights the critical importance of aligning knowledge interdependencies with the external environment, offering theoretical advancements and practical strategies for enhancing firms' innovation capabilities. In doing so, this dissertation helps bridge theoretical gaps and equips firms in technology-intensive industries with strategies for leveraging their knowledge structure to spur innovation.

The effects of firms' technological knowledge on search and learning for innovation

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The effects of firms' technological knowledge on search and learning for innovation

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