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Research on Innovation Catering Behavior and Its Economic Consequences—An Empirical Analysis Based on Threshold Regression Model

Author

Listed:
  • Yue Zhu

    (School of Economics and Management, China University of Mining and Technology, Xuzhou 221116, China
    College of Economics and Management, Huaiyin Normal University, 71 Jiaotong Avenue, Huaian 223300, China)

  • Ziyuan Sun

    (School of Economics and Management, China University of Mining and Technology, Xuzhou 221116, China)

  • Ling Wang

    (School of Economics and Management, China University of Mining and Technology, Xuzhou 221116, China)

  • Xiaoping Wang

    (School of Economics and Management, China University of Mining and Technology, Xuzhou 221116, China)

  • Lu Zhang

    (School of Economics and Management, China University of Mining and Technology, Xuzhou 221116, China)

Abstract
The purpose of this research is to develop the subjective initiative and enhance the sense of independent innovation in the process of high-tech enterprises, so as to guarantee the sustainable development of innovation ability. Based on the relevant data of high-tech enterprises from 2012 to 2017, a threshold regression model was established to study the existence of innovative “incentive” catering behaviors in the process of identifying high-tech enterprises. First, the empirical test results support the hypothesis of innovative “incentives” catering behavior, identified by high-tech enterprises, with a threshold of 0.0370. The empirical results show that the one-size-fits-all objective identification standard will indeed encourage some companies to adopt catering behaviors. Next, the paper verifies that high-tech companies that do not adopt “incentive” catering behaviors will have higher innovation efficiencies. Moreover, the R&D investment and R&D subsidy of high-tech enterprises without catering behaviors will be higher. Finally, through a stepwise regression test, it was found that R&D investment and R&D subsidies play an intermediary role in the relationship between innovation “incentives” catering behavior and corporate innovation efficiency. High-tech enterprises affect the innovation efficiency of enterprises through the transmission mechanism of R&D investment and R&D subsidies.

Suggested Citation

  • Yue Zhu & Ziyuan Sun & Ling Wang & Xiaoping Wang & Lu Zhang, 2020. "Research on Innovation Catering Behavior and Its Economic Consequences—An Empirical Analysis Based on Threshold Regression Model," Sustainability, MDPI, vol. 12(19), pages 1-15, October.
    • Handle: RePEc:gam:jsusta:v:12:y:2020:i:19:p:8198-:d:423886
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    References listed on IDEAS

    as
    1. Hansen, Bruce E., 1999. "Threshold effects in non-dynamic panels: Estimation, testing, and inference," Journal of Econometrics, Elsevier, vol. 93(2), pages 345-368, December.
    2. Liu, Xiaolu & Li, Xiaoyu & Li, Honglin, 2016. "R&D subsidies and business R&D: Evidence from high-tech manufacturing firms in Jiangsu," China Economic Review, Elsevier, vol. 41(C), pages 1-22.
    3. Kleer, Robin, 2010. "Government R&D subsidies as a signal for private investors," Research Policy, Elsevier, vol. 39(10), pages 1361-1374, December.
    4. Xinshu Zhao & John G. Lynch & Qimei Chen, 2010. "Reconsidering Baron and Kenny: Myths and Truths about Mediation Analysis," Journal of Consumer Research, Journal of Consumer Research Inc., vol. 37(2), pages 197-206, August.
    5. Howell, Anthony, 2017. "Picking ‘winners' in China: Do subsidies matter for indigenous innovation and firm productivity?," China Economic Review, Elsevier, vol. 44(C), pages 154-165.
    6. Dinkar Nayak & Rahul N. Choudhury, 2014. "A selective review of foreign direct investment theories," ARTNeT Working Papers 143, United Nations Economic and Social Commission for Asia and the Pacific (ESCAP).
    7. Ming-Liang Yeh & Hsiao-Ping Chu & Peter Sher & Yi-Chia Chiu, 2010. "R&D intensity, firm performance and the identification of the threshold: fresh evidence from the panel threshold regression model," Applied Economics, Taylor & Francis Journals, vol. 42(3), pages 389-401.
    8. repec:bla:jfinan:v:59:y:2004:i:3:p:1125-1165 is not listed on IDEAS
    9. Jacob, John & Jorgensen, Bjorn N., 2007. "Earnings management and accounting income aggregation," Journal of Accounting and Economics, Elsevier, vol. 43(2-3), pages 369-390, July.
    10. Huergo, Elena & Moreno, Lourdes, 2017. "Subsidies or loans? Evaluating the impact of R&D support programmes," Research Policy, Elsevier, vol. 46(7), pages 1198-1214.
    11. Su, Zhong-qin & Xiao, Zuoping & Yu, Lin, 2019. "Do political connections enhance or impede corporate innovation?," International Review of Economics & Finance, Elsevier, vol. 63(C), pages 94-110.
    12. Burgstahler, David & Dichev, Ilia, 1997. "Earnings management to avoid earnings decreases and losses," Journal of Accounting and Economics, Elsevier, vol. 24(1), pages 99-126, December.
    13. Dai, Xiaoyong & Wang, Fang, 2019. "Does the high- and new-technology enterprise program promote innovative performance? Evidence from Chinese firms," China Economic Review, Elsevier, vol. 57(C).
    14. Huergo, Elena & Moreno, Lourdes, 2014. "National or international public funding? Subsidies or loans? Evaluating the innovation impact of R&D support programmes," MPRA Paper 54218, University Library of Munich, Germany.
    15. Jian Shen & Zhenquan Sha & Yenchun Jim Wu, 2020. "Enterprise Adaptive Marketing Capabilities and Sustainable Innovation Performance: An Opportunity–Resource Integration Perspective," Sustainability, MDPI, vol. 12(2), pages 1-15, January.
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