Understanding knowledge dynamics across modes of academia-industry collaboration

Interactions between academic and business organizations entail a dynamic exchange of ideas, innovation, and social impact, offering an avenue for technological and socio-economic development. This avenue, which holds particular promise for improving the situation of developing economies, relies on effective knowledge and information exchanges between the parties. Accordingly, this thesis examines how knowledge is produced within academia-industry collaborations (AICs) by comparing various modes of interaction in the developing economic context of San Carlos de Bariloche, Argentina. Seeking to explore and differentiate the various modes AICs can take according to their knowledge properties, the study employs Boisot's I-Space theoretical framework (Boisot 1995; 1998; Boisot et al. 2011) to characterize key aspects of knowledge and trace their evolution. Empirically, the research relies on a complex mixed-method design, incorporating survey data from 135 researchers and 26 in-depth interviews within a case study. The city of San Carlos de Bariloche is the chosen case, providing a controlled environment for combining and integrating the quantitative and qualitative methods that facilitate a profound examination of relevant factors. Boisot's I-Space framework consistently serves as an analytical model, granting in-depth insights into the dynamics of knowledge production within AICs. The findings present categorizations of AIC modes within the I-Space based on their levels of codification, abstraction, and diffusion, also offering insights into knowledge dynamics. Despite shared features, the study uncovers nuanced differences in knowledge foundations across collaboration modes in Bariloche. Moreover, beyond static classification, it emphasizes how collaboration modes associate with specific learning processes, suggesting that their sustained and combined use over time drives cumulative learning and sector-wide advancement. This evolutionary learning underscores the significance of prolonged and varied collaboration in elevating innovation and transforming local economic conditions. Contributions span theoretical, empirical, and practical dimensions. The study associates collaboration modes with specific learning needs, highlighting the value of the I-Space framework in understanding complex social interactions. Empirically, it provides a rich characterization of AIC intricacies in a developing world setting. Practical implications include strategic recommendations for stakeholders to combine collaboration modes, recognize cultural differences, and adapt incentive structures to enhance reciprocal learning and innovation. Research implications stress the significance of knowledge differences in shaping collaboration benefits, obstacles, and outputs within AICs. It underscores the evolutionary nature of knowledge production, emphasizing the amalgamation of different knowledge types for diverse learning stages. Overall, the thesis suggests that combining collaboration modes is crucial in guiding future AIC strategies and policy formulation, fostering adaptive approaches that promote reciprocal learning and innovation across academia and industry. Acknowledging its limitations, this research contributes to addressing existing gaps in AIC literature, serves as a methodological blueprint for studying similar contexts, and lays the groundwork for cross-institutional knowledge partnerships in other settings.