Exploring complementary innovation of AI technology from a multidimensional knowledge network approach
Year: 2024
Type: dissertation
Abstract: Innovation and diversification are fundamental drivers of long-term economic growth, evolving synergistically. This dissertation systematically examines the intricate interplay between a nation's innovation capabilities and its diversification into new technological and product domains, with a particular focus on evolutionary economic geography and economic complexity theory.The first essay explores the relationship between scientific capability and technological diversification in the field of artificial intelligence (AI), seeking to elucidate how a nation's scientific capabilities may indicate its potential to venture into new AI technologies. The second essay explores the nexus between technological capability and product diversification, evaluating the extent to which technological capability fosters a diversified array of products.This comprehensive analysis stratifies national capabilities into three interconnected categories: scientific research, technological innovation, and industrial production. These categories are situated within a complex, multidimensional knowledge network that illustrates their interconnections and synergies. Diversification in both technology and product dimensions is conceptualized as a conditional probability, assessing the likelihood of a nation achieving a comparative advantage in these new arenas. The empirical investigation utilizes a robust dataset spanning four decades, from 1980 to 2019, incorporating indicators such as scholarly publications, patent records, and export product data. A three-way fixed effects panel regression model serves as the analytical framework, revealing positive correlations between AI integration and a nation's diversification in technology and products, thereby underscoring AI's complementary role in enhancing innovative capabilities.In the context of intensifying global competition for AI technological leadership, it is imperative for policymakers to swiftly integrate AI across diverse sectors while formulating R&D policies that promote diversification, which is crucial for long-term economic growth. As posited by evolutionary economic theory, while increased diversity without innovation may lead to some evolution, sustained long-term growth necessitates diversification grounded in innovation. Policies should leverage existing capabilities in scientific research, technological innovation, and industrial production, using these areas as foundations for expansion into related fields. This proactive and forward-looking strategy is essential for fostering innovation and ensuring a diversified and robust trajectory of economic development.This dissertation provides several policy implications, synthesizing insights from endogenous growth theory and the concept of complementary innovation. From the perspective of endogenous growth theory, the explosive expansion of knowledge in the modern knowledge-based economy represents a significant opportunity for economic development. However, this expansion could also lead to a 'knowledge burden,' potentially hindering diversification into new fields for nations with limited capabilities. This research underscores the importance of complementary innovation in the knowledge economy, particularly highlighting the potential of general-purpose technologies (GPTs) such as AI, bioengineering, and quantum technologies. It reveals that the complementary function of AI is more pronounced for developing countries compared to developed ones when diversifying into new fields. Unlike developed countries, where technological capabilities accumulate in a virtuous cycle, developing countries struggle to amass these capabilities without complementary technologies. Consequently, nations lacking these capabilities should focus on integrating AI technologies into areas closely related to their existing strengths to secure a comparative advantage in economic development. Moreover, a nation's scientific, technological, and productive capabilities evolve interdependently through multidimensional networks formed by mutual interactions. This finding suggests that nations aiming to diversify into new fields should enhance industry-academia-research collaborations and establish their R&D investment strategies to foster this evolution.
Source: HAL
Author: Chun, Youngsam
Institution: Seoul National University
Language: English
Subfield: Economics and Econometrics
Domain: Social Sciences
Open Access status: green
OpenAlex ID: W7056393177