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Manufacturing intelligentization and technological innovation: Perspectives on intra-industry impacts and inter-industry technology spillovers

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  • Zhang, Aili
  • Zhu, Han
  • Sun, Xinyu

Abstract

This study empirically analyzes the impacts of manufacturing intelligentization on technological innovation using panel data from 29 manufacturing industries in China for the period 2012–2019. The research findings indicate that manufacturing intelligentization has significantly positive impacts on intra-industry technological innovation. Moreover, technological innovation exhibits path dependence, in which prior innovation accumulation is advantageous for current technological innovation. Furthermore, the spatial Durbin model indicates that intelligentization has both horizontal and vertical technology spillover effects on technological innovation. Specifically, the intelligentization of horizontal- and forward-linked industries has positive impacts on technological innovation in the focal industry. Additionally, technological innovation exhibits significant spatiotemporal dependence, as manifested by the negative spillover effects of prior technological achievements in other industries on current technological innovation in the focal industry.

Suggested Citation

  • Zhang, Aili & Zhu, Han & Sun, Xinyu, 2024. "Manufacturing intelligentization and technological innovation: Perspectives on intra-industry impacts and inter-industry technology spillovers," Technological Forecasting and Social Change, Elsevier, vol. 204(C).
    • Handle: RePEc:eee:tefoso:v:204:y:2024:i:c:s0040162524002142
    DOI: 10.1016/j.techfore.2024.123418
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    as
    1. Liu, Jun & Chang, Huihong & Forrest, Jeffrey Yi-Lin & Yang, Baohua, 2020. "Influence of artificial intelligence on technological innovation: Evidence from the panel data of china's manufacturing sectors," Technological Forecasting and Social Change, Elsevier, vol. 158(C).
    2. Delgado, Mercedes & Porter, Michael E. & Stern, Scott, 2014. "Clusters, convergence, and economic performance," Research Policy, Elsevier, vol. 43(10), pages 1785-1799.
    3. Wang, Lei & Zhou, Yahong & Chiao, Benjamin, 2023. "Robots and firm innovation: Evidence from Chinese manufacturing," Journal of Business Research, Elsevier, vol. 162(C).
    4. Philippe Aghion & Benjamin F. Jones & Charles I. Jones, 2018. "Artificial Intelligence and Economic Growth," NBER Chapters, in: The Economics of Artificial Intelligence: An Agenda, pages 237-282, National Bureau of Economic Research, Inc.
    5. Xie, Mengmeng & Ding, Lin & Xia, Yan & Guo, Jianfeng & Pan, Jiaofeng & Wang, Huijuan, 2021. "Does artificial intelligence affect the pattern of skill demand? Evidence from Chinese manufacturing firms," Economic Modelling, Elsevier, vol. 96(C), pages 295-309.
    6. Chen, Xi & Mao, Jin & Ma, Yaxue & Li, Gang, 2024. "The knowledge linkage between science and technology influences corporate technological innovation: Evidence from scientific publications and patents," Technological Forecasting and Social Change, Elsevier, vol. 198(C).
    7. Wang, Huijuan & Ding, Lin & Guan, Rong & Xia, Yan, 2020. "Effects of advancing internet technology on Chinese employment: a spatial study of inter-industry spillovers," Technological Forecasting and Social Change, Elsevier, vol. 161(C).
    8. Daron Acemoglu & Pascual Restrepo, 2020. "Robots and Jobs: Evidence from US Labor Markets," Journal of Political Economy, University of Chicago Press, vol. 128(6), pages 2188-2244.
    9. Daron Acemoglu & Pascual Restrepo, 2018. "The Race between Man and Machine: Implications of Technology for Growth, Factor Shares, and Employment," American Economic Review, American Economic Association, vol. 108(6), pages 1488-1542, June.
    10. Carolyn Shaw Solo, 1951. "Innovation in the Capitalist Process: A Critique of the Schumpeterian Theory," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 65(3), pages 417-428.
    11. Haenlein, Michael & Kaplan, Andreas, 2021. "Artificial intelligence and robotics: Shaking up the business world and society at large," Journal of Business Research, Elsevier, vol. 124(C), pages 405-407.
    12. Zhang, Peikang & Qin, Yiming & Liang, Huailiang & Zhou, Liping, 2023. "Robotization and labour demand in post-pandemic era: Microeconomic evidence from China," Technological Forecasting and Social Change, Elsevier, vol. 192(C).
    13. Gan, Jiawu & Liu, Lihua & Qiao, Gang & Zhang, Qin, 2023. "The role of robot adoption in green innovation: Evidence from China," Economic Modelling, Elsevier, vol. 119(C).
    14. Khan, Ali Nawaz & Jabeen, Fauzia & Mehmood, Khalid & Ali Soomro, Mohsin & Bresciani, Stefano, 2023. "Paving the way for technological innovation through adoption of artificial intelligence in conservative industries," Journal of Business Research, Elsevier, vol. 165(C).
    15. Ajay Agrawal & Joshua Gans & Avi Goldfarb, 2018. "Prediction, Judgment, and Complexity: A Theory of Decision-Making and Artificial Intelligence," NBER Chapters, in: The Economics of Artificial Intelligence: An Agenda, pages 89-110, National Bureau of Economic Research, Inc.
    16. Tsekouras, Kostas & Chatzistamoulou, Nikos & Kounetas, Kostas, 2017. "Productive performance, technology heterogeneity and hierarchies: Who to compare with whom," International Journal of Production Economics, Elsevier, vol. 193(C), pages 465-478.
    17. Chatzistamoulou, Nikos & Kounetas, Kostas & Tsekouras, Kostas, 2022. "Technological hierarchies and learning: Spillovers, complexity, relatedness, and the moderating role of absorptive capacity," Technological Forecasting and Social Change, Elsevier, vol. 183(C).
    18. Wang, Delu & Wang, Yadong & Jiang, Wuding & Shi, Xunpeng, 2023. "Has outward foreign direct investment alleviated industrial overcapacity in China? An empirical test of the upstream and downstream industrial links," Structural Change and Economic Dynamics, Elsevier, vol. 67(C), pages 250-263.
    19. Wu, Ning & Liu, ZuanKuo, 2021. "Higher education development, technological innovation and industrial structure upgrade," Technological Forecasting and Social Change, Elsevier, vol. 162(C).
    20. Jianling Jiao & Yufei Yang & Yu Bai, 2018. "The impact of inter-industry R&D technology spillover on carbon emission in China," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 91(3), pages 913-929, April.
    21. Liu, Caihong & Ji, Hannah & Ji, Jonah, 2022. "Mobile information technology's impacts on service innovation performance of manufacturing enterprises," Technological Forecasting and Social Change, Elsevier, vol. 184(C).
    22. Zhu, Minghao & Liang, Chen & Yeung, Andy C.L. & Zhou, Honggeng, 2024. "The impact of intelligent manufacturing on labor productivity: An empirical analysis of Chinese listed manufacturing companies," International Journal of Production Economics, Elsevier, vol. 267(C).
    23. Orlic, Edvard & Hashi, Iraj & Hisarciklilar, Mehtap, 2018. "Cross sectoral FDI spillovers and their impact on manufacturing productivity," International Business Review, Elsevier, vol. 27(4), pages 777-796.
    24. Yang, Haochang & Li, Lianshui & Liu, Yaobin, 2022. "The effect of manufacturing intelligence on green innovation performance in China," Technological Forecasting and Social Change, Elsevier, vol. 178(C).
    25. Zhang, Wei & Zhang, Ting & Li, Hangyu & Zhang, Han, 2022. "Dynamic spillover capacity of R&D and digital investments in China's manufacturing industry under long-term technological progress based on the industry chain perspective," Technology in Society, Elsevier, vol. 71(C).
    26. Mardones, Cristian & Velásquez, Andrés, 2021. "Macroeconomic, intersectoral, and environmental effects of R&D subsidies in Chile: An input-output approach," Technological Forecasting and Social Change, Elsevier, vol. 173(C).
    27. Tsekouras, Kostas & Chatzistamoulou, Nikos & Kounetas, Kostas & Broadstock, David C., 2016. "Spillovers, path dependence and the productive performance of European transportation sectors in the presence of technology heterogeneity," Technological Forecasting and Social Change, Elsevier, vol. 102(C), pages 261-274.
    28. Han, Jie & Jiang, Cailou & Liu, Rong, 2023. "Does intelligent transformation trigger technology innovation in China's NEV enterprises?," Energy, Elsevier, vol. 270(C).
    29. Wen, Huwei & Zhong, Qiming & Lee, Chien-Chiang, 2022. "Digitalization, competition strategy and corporate innovation: Evidence from Chinese manufacturing listed companies," International Review of Financial Analysis, Elsevier, vol. 82(C).
    30. Lee, Chien-Chiang & Qin, Shuai & Li, Yaya, 2022. "Does industrial robot application promote green technology innovation in the manufacturing industry?," Technological Forecasting and Social Change, Elsevier, vol. 183(C).
    31. Jiaofeng Pan & Jianxin Guo, 2022. "Innovative Collaboration and Acceleration: an Integrated Framework Based on Knowledge Transfer and Triple Helix," Journal of the Knowledge Economy, Springer;Portland International Center for Management of Engineering and Technology (PICMET), vol. 13(4), pages 3223-3247, December.
    32. André Spithoven & Bruno Merlevede, 2023. "The productivity impact of R&D and FDI spillovers: characterising regional path development," The Journal of Technology Transfer, Springer, vol. 48(2), pages 560-590, April.
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    More about this item

    Keywords

    Manufacturing intelligentization; Technological innovation; Technology spillover effects; Horizontal linkage; Forward linkage; Backward linkage;
    All these keywords.

    JEL classification:

    • C50 - Mathematical and Quantitative Methods - - Econometric Modeling - - - General
    • L60 - Industrial Organization - - Industry Studies: Manufacturing - - - General
    • O30 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights - - - General

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