IDEAS home Printed from https://ideas.repec.org/a/eee/teinso/v71y2022ics0160791x22002706.html
   My bibliography  Save this article

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

Author

Listed:
  • Zhang, Wei
  • Zhang, Ting
  • Li, Hangyu
  • Zhang, Han

Abstract

During the new era of digital-technology economics, R&D and digital investments have emerged as critical factors influencing technological change in the long term. At the same time, technological progress in industries is the fundamental cause of the R&D and digital investments spillover between industries. In order to study the dynamic spillover capacity evolutionary process generated by R&D and digital investments caused by the long-term technological change in China's manufacturing industry, this paper firstly integrates R&D and digital investments as the critical influencing factors affecting technological progress. It establishes a dynamic input-output model including endogenous technological progress, which is simulated by historical data from 2000 to 2014 to obtain the input-output coefficient matrix from 2015 to 2050. On this basis, this paper makes a rare attempt to focus the inter-industry spillover weights on the industry chain perspective to revisit and simulate the dynamic changes of inter-industry R&D and digital investments spillover capacity under the influence of long-term technological progress. As shown in the simulation results, there are significant differences in inter-industry R&D and digital investments spillover capacities among 18 manufacturing industries in China in both industry and time dimensions. The results of this study are presented in the following sections: (1) A horizontal comparison of the spillover capacity of R&D and digital investments in manufacturing industries in the same period from the industry dimension shows that the spillover capacity of R&D and digital investments between industries is dynamic because the development strategies and technological structures of industries may change over time. Hence, the position of each industry in the industry chain is not constant, and the R&D and digital investments spillover capacity between industries are also in a dynamic process. The manner and ability of an industry to generate R&D and digital investments spillover to its upstream and downstream industries may differ depending on its production location in the chain. Generally, for most upstream and near-upstream industries in China's manufacturing industry chain, the spillover capacity of R&D and digital investments of an industry to its downstream industries are greater than that to its upstream industries, and vice versa. Therefore, in order to maximize the technology spillover capacity, the corresponding technology guidance policy should be adjusted by the industry's technological progress characteristics and changes in the production location of the industry chain. (2) When comparing the spillover capacity of R&D and digital investments of each manufacturing industry longitudinally from the time dimension, the demand-pull effect of technological progress caused by R&D and digital investments of industries for their downstream industries is not as profound as the technology-push effect for their upstream industries. Hence, the fluctuations of R&D and digital investments spillover capacity generated by industries located in the upstream, near-upstream of China's manufacturing industry chain are greater than those generated by downstream, near-downstream industries. Therefore, it can be inspected that industries close to the upstream of the industry chain are more efficient in driving economic growth with their inputs in general-purpose technologies.

Suggested Citation

  • 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).
    • Handle: RePEc:eee:teinso:v:71:y:2022:i:c:s0160791x22002706
    DOI: 10.1016/j.techsoc.2022.102129
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0160791X22002706
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.techsoc.2022.102129?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Romer, Paul M, 1986. "Increasing Returns and Long-run Growth," Journal of Political Economy, University of Chicago Press, vol. 94(5), pages 1002-1037, October.
    2. Pan, Haoran, 2006. "Dynamic and endogenous change of input-output structure with specific layers of technology," Structural Change and Economic Dynamics, Elsevier, vol. 17(2), pages 200-223, June.
    3. Heo, Pil Sun & Lee, Duk Hee, 2019. "Evolution patterns and network structural characteristics of industry convergence," Structural Change and Economic Dynamics, Elsevier, vol. 51(C), pages 405-426.
    4. Batten, Jonathan A. & Ciner, Cetin & Lucey, Brian M., 2017. "The dynamic linkages between crude oil and natural gas markets," Energy Economics, Elsevier, vol. 62(C), pages 155-170.
    5. Pol Antras & Davin Chor & Thibault Fally & Russell Hillberry, 2012. "Measuring the Upstreamness of Production and Trade Flows," American Economic Review, American Economic Association, vol. 102(3), pages 412-416, May.
    6. Gurgul, Henryk & Lach, Łukasz, 2018. "On using dynamic IO models with layers of techniques to measure value added in global value chains," Structural Change and Economic Dynamics, Elsevier, vol. 47(C), pages 155-170.
    7. Fraccascia, Luca & Albino, Vito & Garavelli, Claudio A., 2017. "Technical efficiency measures of industrial symbiosis networks using enterprise input-output analysis," International Journal of Production Economics, Elsevier, vol. 183(PA), pages 273-286.
    8. Robert M. Solow, 1956. "A Contribution to the Theory of Economic Growth," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 70(1), pages 65-94.
    9. Mikkola, Hannu J. & Ahokas, Jukka, 2010. "Indirect energy input of agricultural machinery in bioenergy production," Renewable Energy, Elsevier, vol. 35(1), pages 23-28.
    10. Galaz, Victor & Centeno, Miguel A. & Callahan, Peter W. & Causevic, Amar & Patterson, Thayer & Brass, Irina & Baum, Seth & Farber, Darryl & Fischer, Joern & Garcia, David & McPhearson, Timon & Jimenez, 2021. "Artificial intelligence, systemic risks, and sustainability," Technology in Society, Elsevier, vol. 67(C).
    11. Christiaan Hogendorn & Brett Frischmann, 2020. "Infrastructure and general purpose technologies: a technology flow framework," European Journal of Law and Economics, Springer, vol. 50(3), pages 469-488, December.
    12. Meng, Bo & Xue, Jinjun & Feng, Kuishuang & Guan, Dabo & Fu, Xue, 2013. "China’s inter-regional spillover of carbon emissions and domestic supply chains," Energy Policy, Elsevier, vol. 61(C), pages 1305-1321.
    13. Leontief, Wassily & Duchin, Faye, 1986. "The Future Impact of Automation on Workers," OUP Catalogue, Oxford University Press, number 9780195036237.
    14. Bhattarai, Keshab & Mallick, Sushanta K. & Yang, Bo, 2021. "Are global spillovers complementary or competitive? Need for international policy coordination," Journal of International Money and Finance, Elsevier, vol. 110(C).
    15. Zhou, Xiaoyong & Zhou, Dequn & Wang, Qunwei, 2018. "How does information and communication technology affect China's energy intensity? A three-tier structural decomposition analysis," Energy, Elsevier, vol. 151(C), pages 748-759.
    16. Pieri, Fabio & Vecchi, Michela & Venturini, Francesco, 2018. "Modelling the joint impact of R&D and ICT on productivity: A frontier analysis approach," Research Policy, Elsevier, vol. 47(9), pages 1842-1852.
    17. Amitrajeet A. Batabyal & Peter Nijkamp, 2016. "Digital technologies, knowledge spillovers, innovation policies, and economic growth in a creative region," Economics of Innovation and New Technology, Taylor & Francis Journals, vol. 25(5), pages 470-484, July.
    18. Tou, Yuji & Watanabe, Chihiro & Moriya, Kuniko & Neittaanmäki, Pekka, 2019. "Harnessing soft innovation resources leads to neo open innovation," Technology in Society, Elsevier, vol. 58(C).
    19. Wolff, Edward N. & Ishaq Nadiri, M., 1993. "Spillover effects, linkage structure, and research and development," Structural Change and Economic Dynamics, Elsevier, vol. 4(2), pages 315-331, December.
    20. Freeman, Chris & Louca, Francisco, 2002. "As Time Goes By: From the Industrial Revolutions to the Information Revolution," OUP Catalogue, Oxford University Press, number 9780199251056.
    21. Fukuyama, Hirofumi & Weber, William L., 2002. "Estimating output allocative efficiency and productivity change: Application to Japanese banks," European Journal of Operational Research, Elsevier, vol. 137(1), pages 177-190, February.
    22. 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.
    23. Wenqing Pan & Delin Yang & Min Lin, 2012. "Inter‐industry Technology Spillover Effects in China: Evidence from 35 Industrial Sectors," China & World Economy, Institute of World Economics and Politics, Chinese Academy of Social Sciences, vol. 20(2), pages 23-40, March.
    24. Wang, Ce & Liao, Hua & Pan, Su-Yan & Zhao, Lu-Tao & Wei, Yi-Ming, 2014. "The fluctuations of China’s energy intensity: Biased technical change," Applied Energy, Elsevier, vol. 135(C), pages 407-414.
    25. Dietmar Harhoff, 1996. "Strategic Spillovers and Incentives for Research and Development," Management Science, INFORMS, vol. 42(6), pages 907-925, June.
    26. Moralles, Herick Fernando & do Nascimento Rebelatto, Daisy Aparecida, 2016. "The effects and time lags of R&D spillovers in Brazil," Technology in Society, Elsevier, vol. 47(C), pages 148-155.
    27. Newman, Carol & Rand, John & Talbot, Theodore & Tarp, Finn, 2015. "Technology transfers, foreign investment and productivity spillovers," European Economic Review, Elsevier, vol. 76(C), pages 168-187.
    28. Albrecht, Johan & Laleman, Ruben & Vulsteke, Elien, 2015. "Balancing demand-pull and supply-push measures to support renewable electricity in Europe," Renewable and Sustainable Energy Reviews, Elsevier, vol. 49(C), pages 267-277.
    29. Henryk Gurgul & Łukasz Lach, 2019. "On approximating the accelerator part in dynamic input–output models," Central European Journal of Operations Research, Springer;Slovak Society for Operations Research;Hungarian Operational Research Society;Czech Society for Operations Research;Österr. Gesellschaft für Operations Research (ÖGOR);Slovenian Society Informatika - Section for Operational Research;Croatian Operational Research Society, vol. 27(1), pages 219-239, March.
    30. Yuan, Rong & Behrens, Paul & Rodrigues, João F.D., 2018. "The evolution of inter-sectoral linkages in China's energy-related CO2 emissions from 1997 to 2012," Energy Economics, Elsevier, vol. 69(C), pages 404-417.
    31. Anna Bergek & Ksenia Onufrey, 2014. "Is one path enough? Multiple paths and path interaction as an extension of path dependency theory," Industrial and Corporate Change, Oxford University Press and the Associazione ICC, vol. 23(5), pages 1261-1297.
    32. Huang, Junbing & Cai, Xiaochen & Huang, Shuo & Tian, Sen & Lei, Hongyan, 2019. "Technological factors and total factor productivity in China: Evidence based on a panel threshold model," China Economic Review, Elsevier, vol. 54(C), pages 271-285.
    33. Yuandi Wang & Lutao Ning & Jian Li & Martha Prevezer, 2016. "Foreign Direct Investment Spillovers and the Geography of Innovation in Chinese Regions: The Role of Regional Industrial Specialization and Diversity," Regional Studies, Taylor & Francis Journals, vol. 50(5), pages 805-822, May.
    34. Chen, Zhuo & Yang, Zhenbing & Yang, Lili, 2020. "How to optimize the allocation of research resources? An empirical study based on output and substitution elasticities of universities in Chinese provincial level," Socio-Economic Planning Sciences, Elsevier, vol. 69(C).
    35. Petr Pavlínek & Pavla Žížalová, 2016. "Linkages and spillovers in global production networks: firm-level analysis of the Czech automotive industry," Journal of Economic Geography, Oxford University Press, vol. 16(2), pages 331-363.
    36. Joel Klinger & Juan Mateos-Garcia & Konstantinos Stathoulopoulos, 2021. "Deep learning, deep change? Mapping the evolution and geography of a general purpose technology," Scientometrics, Springer;Akadémiai Kiadó, vol. 126(7), pages 5589-5621, July.
    37. Del Giudice, M. & Scuotto, V. & Garcia-Perez, A. & Messeni Petruzzelli, A., 2019. "Shifting Wealth II in Chinese economy. The effect of the horizontal technology spillover for SMEs for international growth," Technological Forecasting and Social Change, Elsevier, vol. 145(C), pages 307-316.
    38. Chul Lee & Gunno Park & Jina Kang, 2018. "The impact of convergence between science and technology on innovation," The Journal of Technology Transfer, Springer, vol. 43(2), pages 522-544, April.
    39. Stephan, Annegret & Bening, Catharina R. & Schmidt, Tobias S. & Schwarz, Marius & Hoffmann, Volker H., 2019. "The role of inter-sectoral knowledge spillovers in technological innovations: The case of lithium-ion batteries," Technological Forecasting and Social Change, Elsevier, vol. 148(C).
    40. Hu, Yong & Fisher-Vanden, Karen & Su, Baozhong, 2020. "Technological spillover through industrial and regional linkages: Firm-level evidence from China," Economic Modelling, Elsevier, vol. 89(C), pages 523-545.
    41. Usai, A. & Fiano, F. & Messeni Petruzzelli, A. & Paoloni, P. & Farina Briamonte, M. & Orlando, B., 2021. "Unveiling the impact of the adoption of digital technologies on firms’ innovation performance," Journal of Business Research, Elsevier, vol. 133(C), pages 327-336.
    42. Zhai, Xueqi & An, Yunfei, 2021. "The relationship between technological innovation and green transformation efficiency in China: An empirical analysis using spatial panel data," Technology in Society, Elsevier, vol. 64(C).
    43. Henryk Gurgul & Łukasz Lach, 2016. "Simulating evolution of interindustry linkages in endogenous dynamic IO model with layers of techniques," Metroeconomica, Wiley Blackwell, vol. 67(4), pages 632-666, November.
    44. Wang, Lei & Chen, Yangyang & Ramsey, Thomas Stephen & Hewings, Geoffrey J.D., 2021. "Will researching digital technology really empower green development?," Technology in Society, Elsevier, vol. 66(C).
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Nicholas Tsounis & Ian Steedman, 2021. "A New Method for Measuring Total Factor Productivity Growth Based on the Full Industry Equilibrium Approach: The Case of the Greek Economy," Economies, MDPI, vol. 9(3), pages 1-21, August.
    2. Fabio Mazzola & Iolanda Cascio & Rosalia Epifanio & Giuseppe Giacomo, 2018. "Territorial capital and growth over the Great Recession: a local analysis for Italy," The Annals of Regional Science, Springer;Western Regional Science Association, vol. 60(2), pages 411-441, March.
    3. Roger Fouquet & Ralph Hippe, 2022. "Twin Transitions of Decarbonisation and Digitalisation: A Historical Perspective on Energy and Information in European Economies," Working Papers 08-22, Association Française de Cliométrie (AFC).
    4. Joao J. M. Ferreira & Cristina Fernandes & Vanessa Ratten, 2019. "The effects of technology transfers and institutional factors on economic growth: evidence from Europe and Oceania," The Journal of Technology Transfer, Springer, vol. 44(5), pages 1505-1528, October.
    5. Fulvio Castellacci, 2004. "A neo-Schumpeterian Approach to Why Growth Rates Differ," Revue économique, Presses de Sciences-Po, vol. 55(6), pages 1145-1169.
    6. Doré, Natalia I. & Teixeira, Aurora A.C., 2023. "The role of human capital, structural change, and institutional quality on Brazil's economic growth over the last two hundred years (1822–2019)," Structural Change and Economic Dynamics, Elsevier, vol. 66(C), pages 1-12.
    7. Liu, Taoxiong & Liu, Zhuohao, 2022. "A growth model with endogenous technological revolutions and cycles," Journal of Mathematical Economics, Elsevier, vol. 103(C).
    8. Chao Bi & Minna Jia & Jingjing Zeng, 2019. "Nonlinear Effect of Public Infrastructure on Energy Intensity in China: A Panel Smooth Transition Regression Approach," Sustainability, MDPI, vol. 11(3), pages 1-21, January.
    9. Fulvio Castellacci, 2007. "Evolutionary And New Growth Theories. Are They Converging?," Journal of Economic Surveys, Wiley Blackwell, vol. 21(3), pages 585-627, July.
    10. Antonio Paradiso, 2023. "A reconstruction of the time series of global technology from 5500 BC to the 2000s," Working Papers 2023:12, Department of Economics, University of Venice "Ca' Foscari".
    11. Heinz Kurz & Neri Salvadori, 2000. "The Dynamic Leontief Model and the Theory of Endogenous Growth," Economic Systems Research, Taylor & Francis Journals, vol. 12(2), pages 255-265.
    12. Robert Dalitz, 2016. "Innovation and growth: The Australian Productivity Commission’s policy void?," The Economic and Labour Relations Review, , vol. 27(2), pages 199-214, June.
    13. Guoge Yang & Fengyi Wang & Feng Deng & Xianhong Xiang, 2023. "Impact of Digital Transformation on Enterprise Carbon Intensity: The Moderating Role of Digital Information Resources," IJERPH, MDPI, vol. 20(3), pages 1-26, January.
    14. Wang, Lu & Luo, Gong-li & Sari, Arif & Shao, Xue-Feng, 2020. "What nurtures fourth industrial revolution? An investigation of economic and social determinants of technological innovation in advanced economies," Technological Forecasting and Social Change, Elsevier, vol. 161(C).
    15. Ralph Hippe & Roger Fouquet, 2015. "The human capital transition and the role of policy," GRI Working Papers 185, Grantham Research Institute on Climate Change and the Environment.
    16. Pan, Haoran, 2006. "Dynamic and endogenous change of input-output structure with specific layers of technology," Structural Change and Economic Dynamics, Elsevier, vol. 17(2), pages 200-223, June.
    17. Pineli, Andre & Narula, Rajneesh & Belderbos, Rene, 2019. "FDI, multinationals and structural change in developing countries," MERIT Working Papers 2019-004, United Nations University - Maastricht Economic and Social Research Institute on Innovation and Technology (MERIT).
    18. Jun Koo, 2006. "In Search of New Knowledge: Its Origins and Destinations," Economic Development Quarterly, , vol. 20(3), pages 259-277, August.
    19. Shuang Liang & Xinyue Lin & Xiaoxue Liu & Haoran Pan, 2022. "The Pathway to China’s Carbon Neutrality Based on an Endogenous Technology CGE Model," IJERPH, MDPI, vol. 19(10), pages 1-22, May.
    20. Rao, B. Bhaskara, 2010. "Estimates of the steady state growth rates for selected Asian countries with an extended Solow model," Economic Modelling, Elsevier, vol. 27(1), pages 46-53, January.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:teinso:v:71:y:2022:i:c:s0160791x22002706. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: https://www.journals.elsevier.com/technology-in-society .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.