Author: | Li, Zhijian |
Title: | Research on the impact of digital economy on the upgrading of industrial structure |
Advisors: | Wei, Steven (AF) Tong, Wilson (AF) |
Degree: | D.B.A. |
Year: | 2022 |
Subject: | Industries -- China Information technology -- Economic aspects Industrial organization ,Economic theory) Hong Kong Polytechnic University -- Dissertations |
Department: | Faculty of Business |
Pages: | x, 216 pages : color illustrations |
Language: | English |
Abstract: | The digital economy, enabled by big data technologies, artificial intelligence, the Internet of Things, and other new information and communication technologies, has become a mainstream economic form of today's society and is among the most dynamic sectors in China's economic growth. Under these new circumstances, digital economy has risen to become a new engine to optimize and upgrade China's industrial structure. In addition, the global outbreak of Covid-19 has accelerated the explosive expansion of the digital economy, forcing traditional industries to embrace digital transformation. Hence, on this basis, investigating the connection between the digital economy and industrial structure upgrading is of great practical significance for exploring new paths and directions to ensure industrial structure upgrading and boosting growth that emphasizes quality. Taking the promoting role of "the digital economy on the upgrading of industrial structure" as the main focus, this study examines how digital economy development influences industrial structure upgrading based on the theoretical analysis and by measuring them. Following the research perspective of "province—city—pilot zone," this study takes the specific digital economy policies first released as a quasi-natural experiment. It deploys a multi-period difference-in-differences (DID) method to evaluate the effect of the digital economy on the regional industrial structure using panel data that consists 31 Chinese provinces (including centrally "administered autonomous regions and municipalities") over 2001-2020. To make the research conclusion more reliable and scientific, this study also adopts the panel data of 285 Chinese cities at the prefecture level and above over the period of 2011-2019 to further discuss the connection that digital economy has with the industrial structure by exploring the mediating effect and the threshold effect. Moreover, it analyzes the spatial relationship of these two from a spatial perspective. Finally, this study conducts a comprehensive case study of a digital economy-led, urban artificial intelligence and digital economy pilot zone (Pazhou Core Area) built in Guangzhou—a city based on industries — and powers the synergetic development of 21 industry chains through digital empowerment. Thus, it offers practical insights into how the digital economy upgrades industrial structure, summarizes findings and implications, and proposes recommendations with regard to China's industrial structure upgrading. Based on panel data at the city level, the measuring results of the digital economy and industrial structure upgrading indicate that the industrial structure of Chinese cities shows an upward trend during the research period, and the level of the digital economy shows a trend of accelerated growth. There is a severe regional imbalance in urban industrial structure optimization and digital economy development; cities with the highest level mainly cluster in the Beijing, Tianjin and Hebei Region (hereafter referred to as "the Jingjinji Metropolitan Region"), "the Yangtze Delta city belt" and "the Greater Bay Area" that consists of Hong Kong, Macau and nine cities in Guangdong province. The pattern shows a "stepped" feature and is characterized by an economic landscape of "strong south and weak north." The multi-period DID results at the provincial level show that the first released specific digital economy policies have elevated the rationalization, optimization and diversification of regional industrial structure remarkably. The results stay robust and reliable by changing estimation methods, changing core explanatory variables, using randomly selected experimental group, changing the timing of policy shocks and considering spatial relationships among provinces. In addition, the introduction of specific policies on the digital economy has a more evident impact on the diversification of regional industrial structure than the rationalization and optimization of industrial structure. The regression results using panel data at the city level and above reinforce the multi-period DID findings that digital economy has significantly enhanced the rationalization, optimization and diversification of urban industrial structure and are strongly robust. From a heterogeneity perspective, urban digital economy has different effects on the industrial structure across regions and time. In terms of time, all stages of the digital economy development can significantly promote the rationalization, optimization and diversification of industrial structure, and that impact is stronger in recent years than in early times. In terms of region, digital economy development upgrades industrial structure in all regions except in the eastern region. In terms of urban energy level, digital economy has a significantly bigger impact on industrial structure upgrading in non-capital cities than in capital cities. In terms of economic growth, the impact of digital economy development on the industrial structure is smaller in economically developed cities than in economically lagging cities. These findings prove that regions with insufficient economic growth momentum can achieve leapfrog development by leveraging the digital economy. In addition, the digital economy assists in optimizing and upgrading regional industrial structure mainly by increasing innovation capabilities, accelerating labor force agglomeration, leading government strategic investment, and enhancing financial development. The linear relationship between the two shows that the digital economy and urban innovation capability have a significant positive, descending non-linear "marginal effect" on the rationalization and optimization of industrial structure, and a significant positive, increasing non-linear "marginal effect" on the diversification of industrial structure. Furthermore, urban industrial structure and digital economy development have been clustering spatially, with their spatial autocorrection continuing to rise. After further considering the spatial relationship, the spatial econometrics model results also show that digital economy has enhanced the rationalization, optimization and diversification of the industrial structure in China and that industrial structure has apparent spillover effects; that is, the improvement of urban structure in a city constantly optimizes the industrial structure in neighboring cities. This study also conducts a case study of how the digital economy promotes industrial structure in the Guangzhou Artificial Intelligence And Digital Economy Pilot Zone (Pazhou Core Area) from a micro perspective. It summarizes findings and implications in terms of government priorities, chain length system, development planning, investment attraction, business environment and talent retention. Lastly, this study provides important policy implications regarding the role of the digital economy on China's industrial structure upgrading from multiple dimensions, including making the digital economy a continuous engine to upgrade industrial structure, formulating differentiated regional policies on digital economy based on local conditions, boosting the coordinated growth of digital economy through regional synergy, exploring the multi-dimensional paths of the digital economy to upgrade regional industrial structure, and allowing consumption to come into play in upgrading industrial structure. |
Rights: | All rights reserved |
Access: | restricted access |
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6606.pdf | For All Users (off-campus access for PolyU Staff & Students only) | 5.7 MB | Adobe PDF | View/Open |
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