IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v10y2018i1p187-d126983.html
   My bibliography  Save this article

The Influencing Factors, Regional Difference and Temporal Variation of Industrial Technology Innovation: Evidence with the FOA-GRNN Model

Author

Listed:
  • Yongli Zhang

    (School of Business Administration, Wonkwang University, 460 Iksandae-ro, Iksan 54538, Jeonbuk, Korea
    School of Management Science and Engineering, Hebei GEO University, Shijiazhuang 050031, China)

  • Sanggyun Na

    (School of Business Administration, Wonkwang University, 460 Iksandae-ro, Iksan 54538, Jeonbuk, Korea)

  • Jianguang Niu

    (School of Business Administration, Wonkwang University, 460 Iksandae-ro, Iksan 54538, Jeonbuk, Korea
    School of Management Science and Engineering, Hebei GEO University, Shijiazhuang 050031, China)

  • Beichen Jiang

    (School of Business Administration, Wonkwang University, 460 Iksandae-ro, Iksan 54538, Jeonbuk, Korea
    School of Management Science and Engineering, Hebei GEO University, Shijiazhuang 050031, China)

Abstract

Technology innovation is a motivating force for sustainable development. The recognition and measurement of influencing factors are a basic prerequisite of technology innovation research. In response to the gaps and shortages of existing theories and methods, this paper builds the impact indicators of technology innovation, the proposed FOA-GRNN model, and analyzes the influencing factors, regional differences and temporal variations of technology innovation based on industrial above-scale enterprises of 31 provinces in China from 2008 to 2015. The empirical results show that innovation investment is a determinant of technology innovation in China, and is more and more significant; meanwhile a wide gap of innovation resource between Eastern China and Western China exists. In general, the enterprise scale has a negative effect: with enlargement of enterprise in China, the innovation efficiency of enterprise will decline, while the effect has regional disparity, with positive influence in Central and Western China, and negative influence in Eastern China. Government support has negative effects on technology innovation: indirect equity investment contributes more to technology innovation than direct fund support. Innovation environment has positive and weak effects on technology innovation, but it is the biggest obstacle in Western China, and the innovation environment in China has improved continuously. This paper provides new evidence that can shine some light on determining the factors affecting technology innovation, and also presents a novel approach, which comprises characteristics of nonlinear function approximation, high accuracy and a small sample.

Suggested Citation

  • Yongli Zhang & Sanggyun Na & Jianguang Niu & Beichen Jiang, 2018. "The Influencing Factors, Regional Difference and Temporal Variation of Industrial Technology Innovation: Evidence with the FOA-GRNN Model," Sustainability, MDPI, vol. 10(1), pages 1-19, January.
  • Handle: RePEc:gam:jsusta:v:10:y:2018:i:1:p:187-:d:126983
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/10/1/187/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/2071-1050/10/1/187/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Hong, Jin & Feng, Bing & Wu, Yanrui & Wang, Liangbing, 2016. "Do government grants promote innovation efficiency in China's high-tech industries?," Technovation, Elsevier, vol. 57, pages 4-13.
    2. Wu, Jie & Ma, Zhenzhong & Zhuo, Shuaihe, 2017. "Enhancing national innovative capacity: The impact of high-tech international trade and inward foreign direct investment," International Business Review, Elsevier, vol. 26(3), pages 502-514.
    3. Coad, Alex & Segarra, Agustí & Teruel, Mercedes, 2016. "Innovation and firm growth: Does firm age play a role?," Research Policy, Elsevier, vol. 45(2), pages 387-400.
    4. Youngjin Woo & Euijune Kim & Jaewon Lim, 2017. "The Impact of Education and R&D Investment on Regional Economic Growth," Sustainability, MDPI, vol. 9(5), pages 1-18, April.
    5. Seçil Hülya Danakol & Saul Estrin & Paul Reynolds & Utz Weitzel, 2017. "Foreign direct investment via M&A and domestic entrepreneurship: blessing or curse?," Small Business Economics, Springer, vol. 48(3), pages 599-612, March.
    6. Ernst, Holger, 2001. "Patent applications and subsequent changes of performance: evidence from time-series cross-section analyses on the firm level," Research Policy, Elsevier, vol. 30(1), pages 143-157, January.
    7. German Cubas & B. Ravikumar & Gustavo Ventura, 2016. "Talent, Labor Quality, and Economic Development," Review of Economic Dynamics, Elsevier for the Society for Economic Dynamics, vol. 21, pages 160-181, July.
    8. Guo, Di & Guo, Yan & Jiang, Kun, 2016. "Government-subsidized R&D and firm innovation: Evidence from China," Research Policy, Elsevier, vol. 45(6), pages 1129-1144.
    9. de Freitas, Luciano Charlita & Kaneko, Shinji, 2012. "Is there a causal relation between ethanol innovation and the market characteristics of fuels in Brazil?," Ecological Economics, Elsevier, vol. 74(C), pages 161-168.
    10. German Cubas & B. Ravikumar & Gustavo Ventura, 2016. "Talent, Labor Quality, and Economic Development," Review of Economic Dynamics, Elsevier for the Society for Economic Dynamics, vol. 21, pages 160-181, July.
    11. Natalya Smith & Ekaterina Thomas, 2017. "Regional conditions and innovation in Russia: the impact of foreign direct investment and absorptive capacity," Regional Studies, Taylor & Francis Journals, vol. 51(9), pages 1412-1428, September.
    12. Qi Huang & Marshall S. Jiang & Jianjun Miao, 2016. "Effect of government subsidization on Chinese industrial firms’ technological innovation efficiency: A stochastic frontier analysis," Journal of Business Economics and Management, Taylor & Francis Journals, vol. 17(2), pages 187-200, April.
    13. Basmann, Robert L. & McAleer, Michael & Slottje, Daniel, 2007. "Patent activity and technical change," Journal of Econometrics, Elsevier, vol. 139(2), pages 355-375, August.
    14. 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.
    15. Szczygielski, Krzysztof & Grabowski, Wojciech & Pamukcu, Mehmet Teoman & Tandogan, Vedat Sinan, 2017. "Does government support for private innovation matter? Firm-level evidence from two catching-up countries," Research Policy, Elsevier, vol. 46(1), pages 219-237.
    16. Dai, Jing & Chen, Bin & Hayat, Tasawar & Alsaedi, Ahmed & Ahmad, Bashir, 2015. "Sustainability-based economic and ecological evaluation of a rural biogas-linked agro-ecosystem," Renewable and Sustainable Energy Reviews, Elsevier, vol. 41(C), pages 347-355.
    17. Sun, Xiang & Xiong, Shu & Zhu, Xiaojing & Zhu, Xiaodong & Li, Yangfan & Li, B. Larry, 2015. "A new indices system for evaluating ecological-economic-social performances of wetland restorations and its application to Taihu Lake Basin, China," Ecological Modelling, Elsevier, vol. 295(C), pages 216-226.
    18. Farla, Kristine & de Crombrugghe, Denis & Verspagen, Bart, 2016. "Institutions, Foreign Direct Investment, and Domestic Investment: Crowding Out or Crowding In?," World Development, Elsevier, vol. 88(C), pages 1-9.
    19. Laura Alfaro, 2017. "Gains from Foreign Direct Investment: Macro and Micro Approaches," The World Bank Economic Review, World Bank, vol. 30(Supplemen), pages 2-15.
    20. Pavitt, Keith & Robson, Michael & Townsend, Joe, 1987. "The Size Distribution of Innovating Firms in the UK: 1945-1983," Journal of Industrial Economics, Wiley Blackwell, vol. 35(3), pages 297-316, March.
    21. Zhong, Wei & Yuan, Wei & Li, Susan X. & Huang, Zhimin, 2011. "The performance evaluation of regional R&D investments in China: An application of DEA based on the first official China economic census data," Omega, Elsevier, vol. 39(4), pages 447-455, August.
    22. Yu-Shan Chen & Ke-Chiun Chang, 2010. "Analyzing the nonlinear effects of firm size, profitability, and employee productivity on patent citations of the US pharmaceutical companies by using artificial neural network," Scientometrics, Springer;Akadémiai Kiadó, vol. 82(1), pages 75-82, January.
    23. Huang, Yanghua & Salike, Nimesh & Yin, Zhifeng & Zeng, Douglas Zhihua, 2017. "Enterprise innovation in China: Does ownership or size matter?," RIEI Working Papers 2017-06, Xi'an Jiaotong-Liverpool University, Research Institute for Economic Integration.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Zhen Ding & Chifu Yang & Zhihong Tian & Chunzhi Yi & Yunsheng Fu & Feng Jiang, 2018. "sEMG-Based Gesture Recognition with Convolution Neural Networks," Sustainability, MDPI, vol. 10(6), pages 1-12, June.
    2. Hongchen Li & Huijun Qi & Hongjian Cao & Li Yuan, 2022. "Industrial Policy and Technological Innovation of New Energy Vehicle Industry in China," Energies, MDPI, vol. 15(24), pages 1-17, December.
    3. Xiangdong Chen & Ruixi Li & Xin Niu & Ulrich Hilpert & Valerie Hunstock, 2018. "Metropolitan Innovation and Sustainability in China—A Double Lens Perspective on Regional Development," Sustainability, MDPI, vol. 10(2), pages 1-26, February.
    4. Yue-Gang Song & Yu-Long Zhou & Ren-Jie Han, 2018. "Neural networks for stock price prediction," Papers 1805.11317, arXiv.org.
    5. Chengliang Liu & Qingbin Guo, 2019. "Technology Spillover Effect in China: The Spatiotemporal Evolution and Its Drivers," Sustainability, MDPI, vol. 11(6), pages 1-14, March.
    6. Jugend, Daniel & Fiorini, Paula De Camargo & Armellini, Fabiano & Ferrari, Aline Gabriela, 2020. "Public support for innovation: A systematic review of the literature and implications for open innovation," Technological Forecasting and Social Change, Elsevier, vol. 156(C).
    7. Tsui-Yii Shih, 2018. "Determinants of Enterprises Radical Innovation and Performance: Insights into Strategic Orientation of Cultural and Creative Enterprises," Sustainability, MDPI, vol. 10(6), pages 1-22, June.
    8. Jiangfeng Hu & Zhao Wang & Qinghua Huang & Xiaoqin Zhang, 2019. "Environmental Regulation Intensity, Foreign Direct Investment, and Green Technology Spillover—An Empirical Study," Sustainability, MDPI, vol. 11(10), pages 1-15, May.
    9. Liang, Yi & Niu, Dongxiao & Hong, Wei-Chiang, 2019. "Short term load forecasting based on feature extraction and improved general regression neural network model," Energy, Elsevier, vol. 166(C), pages 653-663.
    10. Bahoo, Salman & Cucculelli, Marco & Qamar, Dawood, 2023. "Artificial intelligence and corporate innovation: A review and research agenda," Technological Forecasting and Social Change, Elsevier, vol. 188(C).

    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. Kwangsoo Shin & Minkyung Choy & Chul Lee & Gunno Park, 2019. "Government R&D Subsidy and Additionality of Biotechnology Firms: The Case of the South Korean Biotechnology Industry," Sustainability, MDPI, vol. 11(6), pages 1-22, March.
    2. Qinghua Xia & Qinwei Cao & Manqing Tan, 2020. "Basic research intensity and diversified performance: the moderating role of government support intensity," Scientometrics, Springer;Akadémiai Kiadó, vol. 125(1), pages 577-605, October.
    3. Chen, Hong & Gangopadhyay, Partha & Singh, Baljeet & Chen, Kairan, 2023. "What motivates Chinese multinational firms to invest in Asia? Poor institutions versus rich infrastructures of a host country," Technological Forecasting and Social Change, Elsevier, vol. 189(C).
    4. Tian, Binbin & Yu, Baixue & Chen, Shi & Ye, Jingjing, 2020. "Tax incentive, R&D investment and firm innovation: Evidence from China," Journal of Asian Economics, Elsevier, vol. 71(C).
    5. Rui Guo & Lutao Ning & Kaihua Chen, 2022. "How do human capital and R&D structure facilitate FDI knowledge spillovers to local firm innovation? a panel threshold approach," The Journal of Technology Transfer, Springer, vol. 47(6), pages 1921-1947, December.
    6. Sun, Xiuli & Li, Haizheng & Ghosal, Vivek, 2020. "Firm-level human capital and innovation: Evidence from China," China Economic Review, Elsevier, vol. 59(C).
    7. Gao, Kang & Yuan, Yijun, 2022. "Government intervention, spillover effect and urban innovation performance: Empirical evidence from national innovative city pilot policy in China," Technology in Society, Elsevier, vol. 70(C).
    8. Bartoloni, Eleonora & Baussola, Maurizio & Bagnato, Luca, 2020. "Waiting for Godot? Success or failure of firms’ growth in a panel of Italian manufacturing firms," Structural Change and Economic Dynamics, Elsevier, vol. 55(C), pages 259-275.
    9. Nezih Guner & Andrii Parkhomenko & Gustavo Ventura, 2018. "Managers and Productivity Differences," Review of Economic Dynamics, Elsevier for the Society for Economic Dynamics, vol. 29, pages 256-282, July.
    10. Hong Li, 2023. "Innovation and financial performance: An assessment of patenting strategies of Chinese listed firms," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 28(2), pages 1693-1712, April.
    11. Yan, Xu & Huang, Minyi, 2022. "Leveraging university research within the context of open innovation: The case of Huawei," Telecommunications Policy, Elsevier, vol. 46(2).
    12. Kanat Abdulla & Balzhan Serikbayeva & Yessengali Oskenbayev & Farhad Taghizadeh-Hesary, 2022. "Regional Differences in Human Capital and Occupational Choice: Evidence from Mexico," The European Journal of Development Research, Palgrave Macmillan;European Association of Development Research and Training Institutes (EADI), vol. 34(6), pages 2899-2922, December.
    13. Jian Hou & Heng Chen & Jianzhong Xu, 2017. "External Knowledge Sourcing and Green Innovation Growth with Environmental and Energy Regulations: Evidence from Manufacturing in China," Sustainability, MDPI, vol. 9(3), pages 1-17, February.
    14. Hu, Shan & Yu, Yongze & Fei, Qingyu, 2023. "Social credit and patent quality: Evidence from China," Journal of Asian Economics, Elsevier, vol. 84(C).
    15. Brotherhood, Luiz & Delalibera, Bruno R., 2020. "Minding the gap between schools and universities," Journal of Economic Dynamics and Control, Elsevier, vol. 120(C).
    16. Arkadiusz Michał Kowalski, 2021. "Dynamics and Factors of Innovation Gap Between the European Union and China," Journal of the Knowledge Economy, Springer;Portland International Center for Management of Engineering and Technology (PICMET), vol. 12(4), pages 1966-1981, December.
    17. Posso, Alberto, 2023. "Bilingual education and child labor: Lessons from Peru," Journal of Economic Behavior & Organization, Elsevier, vol. 212(C), pages 840-872.
    18. Zhijun Feng & Wei Chen, 2018. "Environmental Regulation, Green Innovation, and Industrial Green Development: An Empirical Analysis Based on the Spatial Durbin Model," Sustainability, MDPI, vol. 10(1), pages 1-22, January.
    19. Tse, Caleb H. & Yim, Chi Kin Bennett & Yin, Eden & Wan, Feng & Jiao, Hao, 2021. "R&D activities and innovation performance of MNE subsidiaries: The moderating effects of government support and entry mode," Technological Forecasting and Social Change, Elsevier, vol. 166(C).
    20. Francesco Aiello & Lidia Mannarino & Valeria Pupo, 2024. "Family firm heterogeneity and patenting. Revising the role of size and age," Small Business Economics, Springer, vol. 63(1), pages 105-133, June.

    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:gam:jsusta:v:10:y:2018:i:1:p:187-:d:126983. 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: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    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.