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互联网对中国制造业进口企业创新的影响

佟家栋1 杨俊1

(1.南开大学经济学院)

【摘要】本文使用中国进口制造业企业数据,考察了互联网对企业创新的微观影响和作用机制。研究发现,互联网的使用显著提升了我国制造业进口企业的创新水平,且该作用效果在大规模、高效率、民营、出口、资本和技术密集型的东部企业中更为显著。进一步地,互联网主要通过提升进口制造业企业的进口产品质量来促进企业创新;进口产品种类和进口规模的作用效果并不突出。最后,互联网在促进进口制造业企业独立创新的同时,也显著地促进了企业协同创新水平的提高。本文的研究对于数字经济时代制造业企业竞争力和制造业质量的提升具有一定的现实意义。

【关键词】 互联网;进口制造业企业;创新;倾向得分匹配;

【DOI】

【基金资助】 国家社会科学基金重大项目“经济全球化调整期的国际保护主义发展新趋势及我国的应对策略研究”(12&ZD087); 教育部人文社会科学重点研究基地重大项目“国际经贸规则重构对中国参与亚太区域合作和全球经济治理的影响及对策研究”(17JJD790013);

Influence of internet on innovation of China’s manufacturing importers

TONG Jiadong1 YANG Jun1

(1.School of Economics, Nankai University)

【Abstract】Using the data of China’s manufacturing importers, this paper examined the micro-impact as well as the mechanisms of Internet on innovation. The study found that the Internet has significantly improved the level of innovation in China’s manufacturing importers. And the effect is more prominent in large-scale, high-efficiency, private, exporting, capital- and technology-intensive eastern firms. Further, the Internet mainly promotes firms’ innovation by improving the quality of imported products, and neither the effects of the types of imported product nor the effects of imported scale are obvious. Finally, while promoting the independent innovation of manufacturing importers, the Internet has also significantly improved the level of collaborative innovation. This paper has certain practical significance for improvement of the competitiveness and the quality of China’s manufacturing industry in the era of digital economy.

【Keywords】 Internet; manufacturing importers; innovation; propensity score matching;

【DOI】

【Funds】 The National Social Science Fund of China (12&ZD087); Major Project of Key Research Bases for Humanities and Social Sciences under the Ministry of Education (17JJD790013);

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    Footnote

    [1]. ① The core field for the identification of websites: “www” “com” “cn” “net” “http” “con” and “//”; and the core field for the identification of emails: “@.” [^Back]

    [2]. ① We delete any enterprise sample with missing values, zero values or negative values in total industrial output, enterprise sales, fixed assets, net value of fixed assets and annual average number of employees; the samples of enterprises with missing or negative values in any one of the wages payable, welfare payable, industrial value added and intermediate product input in 2004-2007; the samples of enterprises with less than eight employees; the samples of enterprises with missing operating profit; the samples of enterprises established before 1949, and the samples of enterprises whose age are less than 0. In addition, according to the practice of Freenstra et al.(2014),[39] in order to comply with the general accounting standards, this paper processes the following data: excluding the enterprises with current assets exceeding fixed assets and those with total fixed assets exceeding total assets; excluding the enterprises whose export delivery value is greater than sales revenue and the enterprises whose depreciation of this year is greater than the accumulated depreciation. [^Back]

    [3]. ① Due to space limitation, complete regression results are available upon request. [^Back]

    [4]. ① The database includes the patent applications and authorization of listed companies, non-listed companies and different regions in China. It not only considers the number and types of patents applied or authorized by different entities, but also includes the independent application, patent acquisition, joint application and patent acquisition with other entities. We match the enterprise name index in the database with the enterprise name in this sample, and take the logarithm of the patent data. [^Back]

    [5]. ② It is worth noting that after matching, the sample size of this paper is greatly reduced, so in this part, the proportion of PSM nearest neighbor matching is expanded, and the original 1:5 matching proportion is relaxed to 1:7. In addition, we further expand the matching ratio to 1:8, 1:9 and 1:10, and the regression results do not change significantly, which shows that the regression results have certain robustness. [^Back]

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This Article

ISSN:1002-4670

CN: 11-1692/F

Vol , No. 11, Pages 1-15

November 2019

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Article Outline

Abstract

  • Introduction
  • 1 Literature review
  • 2 Research method, model and data
  • 3 Baseline estimation results and analysis
  • 4 Test for heterogeneity
  • 5 Effect of the import quality, types and scale
  • 6 The Internet and collaborative Innovation of enterprises
  • 7 Conclusion
  • Footnote

    References