Transition from factor-driven to innovation-driven urbanization in China: A study of manufacturing industry automation in Dongguan City

Li, Xun; Hui, Eddie C.M.; Lang, Wei; Zheng, Shali; Qin, Xiaozhen

doi:10.1016/j.chieco.2019.101382

Cited by 102 publications

(35 citation statements)

References 63 publications

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“…AI is not only about supplementing and replacing manpower with machines. It also promotes the construction of an innovation ecosystem, the formation of corresponding R&D innovation, digestion, absorption and reinvention capabilities, and the true promotion of productivity with the introduction and transformation of intelligent technologies and equipment as a carrier (Li et al, 2020). In this context, Yang et al (2020) found a significant role of the implementation of AI in promoting the innovation performance of China's manufacturing enterprises.…”

Section: Ai and Technological Progressmentioning

confidence: 99%

“…In addition, foreign direct investment (FDI) (Huang et al, 2018), research and development (R&D) (Chen et al, 2019), ownership type (Luan et al, 2020), enterprise size (Zhang et al, 2010;Lin et al, 2018), factor endowment (Lan et al, 2012;Bu et al, 2019), and other factors affect how AI changes energy intensity. The impact of AI has been heatedly discussed in recent years from different perspectives, including the points of view of economic growth (productivity) (Bard, 1986;Dirican, 2015;Purdy and Daugherty, 2017;Aghion et al, 2017;Brynjolfsson et al, 2017;Graetz and Michaels, 2018;Kromann et al, 2020;Jung and Lim, 2020;Camiña et al, 2020;Ballestar et al, 2020), innovation (Cockburn et al, 2018;Liu et al, 2020;Li et al, 2020;Yang et al, 2020), employment (Howell, 1985;Edler and Ribakova, 1994;Acemoglu and Restrepo, 2018, 2020a, 2020bChiacchio et al, 2018;Dauth et al, 2018;Barbieri et al, 2019;Carbonero et al, 2020;Dekle, 2020;Ballestar et al, 2020;Jung and Lim, 2020), and sustainable economic development (Vinuesa et al, 2020;Machado et al, 2020;Liu et al, 2021).…”

Section: Literature Reviewmentioning

confidence: 99%

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Artificial intelligence and energy intensity in China’s industrial sector: Effect and transmission channel

Liu

Yang

Fujii

et al. 2021

Economic Analysis and Policy

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The continued development of artificial intelligence (AI) has changed production methods but may also pose challenges related to energy consumption; in addition, the effectiveness of AI differs across industries. Thus, to develop efficient policies, it is necessary to discuss the effect of AI adoption on energy intensity and to identify industries that are more significantly affected.Using data on industrial robots installed in 16 Chinese industrial subsectors from 2006 to 2016, this paper investigates both the effect of AI on energy intensity and the channel through which this effect is transmitted. The empirical results show, first, that boosting applications of AI can significantly reduce energy intensity by both increasing output value and reducing energy consumption, especially for energy intensities at high quantiles. Second, compared with the impacts in capital-intensive sectors (e.g., basic metals, pharmaceuticals, and cosmetics), the negative impacts of AI on energy intensity in labor-intensive sectors (e.g., textiles and paper) and technology-intensive sectors (e.g., industrial machinery and transportation equipment) are more pronounced. Finally, the impact of AI on energy intensity is primarily achieved through its facilitation of technological progress; this accounts for 78.3% of the total effect. To reduce energy intensity, the Chinese government should effectively promote the development of AI and its use in industry, especially in labor-intensive and technology-intensive sectors.

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Section: Ai and Technological Progressmentioning

confidence: 99%

Section: Literature Reviewmentioning

confidence: 99%

Artificial intelligence and energy intensity in China’s industrial sector: Effect and transmission channel

Liu

Yang

Fujii

et al. 2021

Economic Analysis and Policy

View full text Add to dashboard Cite

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“…= .385, statistically significant at .05. In line with research by [12,13], the relationship between knowledge management processes and organizational efficiency through organizational innovation has implications for the impact of knowledge management on organizational innovation and organizational performance and effect on organizational innovation [14,15,16].…”

Section: Discussionmentioning

confidence: 77%

Innovative development in business operation of the Thai auto parts industry

Potjanajaruwit

2021

E3S Web Conf.

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This research study aims to study the direct effect, indirect effect, and total effect of cause and effect factors of innovation development in the business operation of the Thai auto parts industry. This research is quantitative research using questionnaires from a sample of 360 sites and qualitative research by in-depth interviews with ten auto parts industry executives in Thailand. Statistics in the affirmative element analysis and the causal relationship structure analysis. The results showed that the causal factors of technology had a positive direct effect on the development of business innovation and the development of business innovation had a positive direct effect on the business advantage of the competition of establishments in the auto parts industry was statistically significant at the level of 0.05.

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“…Studies of Chinese economies are increasingly focusing on quality side of economic development over cities, such as research by Li, Hui, Lang, Zheng, and Qin (2020), investigating the transformation effect from factor‐driven to innovation driven in China, which reveals that advanced production technology (automation) in multiple industries is increasingly transferring and dividing the current mode of manufacturing and production to “a polarization of the labor forces" and the emergence of “dual cities”, by replacement of low and middle skilled workers and the creation of new jobs for a skilled labor force. In this view, in regional studies, cities are clear samples to characterize important bounded technology competencies.…”

Section: Argument and Literature Review On Regional Technology Convermentioning

confidence: 99%

What does the character of urban technology reveals about convergence versus divergence of innovation in China?—A technical lens to evaluate regional economic development

Chen

Xue

et al. 2020

Growth and Change

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Regional technology characters (TCs) are studied in this paper to find whether innovation in Chinese cities leads to technology converging, or technology divergence, in both the intra-city and inter-city scales, with which regional economic development strength may be better explained. Based on a literature review on the subject, a two-dimensional research framework and relevant technical lens are designed to clarify TC in cities composed of parameters on Technology Strength (TS) versus Technology Angle (TA). By applying Principle Component Analysis, a technical lens is made possible based on extracted parameters on three integrated technology dimensions for measuring TSs and TAs over 117 Chinese sample cities with invention patent data covering 21 technology field between 2005/2006 and 2015/2016. Technology convergence versus divergence are examined for 28/24 sample cities beyond average score, and the research findings indicate that technology divergence in Chinese cities can be confirmed at the inter-city level, even partially at the intra-city level. This finding holds for most sample cities with fairly large and modest TSs, while intra-city technology converging is significant, especially for larger sized TS samples, however they also differ on different dimensions. This may imply that urban economic development in China is technical based and differentiated. 1632 | CHEN Et al. 1 | INTRODUCTION TO REGIONAL-BASED TECHNOLOGY DIVERSIFICATION STUDIES Technology diversification can lead to lots of advantages (Markides, 1997), previously shown mostly at the company level. Research has been conducted to indicate that firms diversifying their technological bases can exploit economies of scope in R&D and technological knowledge, in terms of diversifying key knowledge resource across multiple product lines (Miller, 2006; Panzar & Willig, 1977; Teece, 1982), which clearly implies that the advantages are mainly on diversified use of the technologies. Another advantage of technology diversification can be shown with the technical ecosystem view, as technological diversification (spreading resources generated from different technological fields) allows firms (and similarly groups of firms in certain regions) to reduce their risks from their R&D input and to enhance adaptability to the fast-changing technological environment (Garcia-Vega, 2006). This trend is especially true under the emerging and prevailing trends of technological fusion since 1990's in many high-tech sectors such as in telecommunications, chemicals and biotechnologies, and auto-industries (Gambardella & Torrisi, 1998; Suzuki & Kodama, 2004). This ecosystem perspective, however, is different from the former one which is only focusing on effectively use of limited technology resource. This latter concern is especially suited to regional level studies, where the issue emphasized from rather different vision-varieties and volume of technology resources are the key for supporting regional innovation in ecological sense and in qualitative economy terms. Releva...

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Transition from factor-driven to innovation-driven urbanization in China: A study of manufacturing industry automation in Dongguan City

Cited by 102 publications

References 63 publications

Artificial intelligence and energy intensity in China’s industrial sector: Effect and transmission channel

Artificial intelligence and energy intensity in China’s industrial sector: Effect and transmission channel

Innovative development in business operation of the Thai auto parts industry

What does the character of urban technology reveals about convergence versus divergence of innovation in China?—A technical lens to evaluate regional economic development

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