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Research on the Influence of the Mechanism of Technology Convergence on China's Textile Industry Performance

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Warianty tytułu
PL
Badania nad mechanizmem wpływu konwergencji technologii na wydajność chińskiego przemysłu tekstylnego
Języki publikacji
EN
Abstrakty
EN
Technology convergence (TC) can integrate new technologies, methods and processes into traditional industries. It can accelerate the transformation and upgrading of these industries, and is of great significance to their development. The purpose of our research is to reveal the impact of the mechanism of technology integration on the textile industry and conduct empirical research. This study firstly builds the linear and non-linear mechanism of the impact of TC on the development of China's textile industry. Empirical research is conducted based on the panel fixed effect model and panel threshold model. The results are as follows: (1) TC significantly contributes to the performance of China's textile industry, as endogenous convergence can significantly promote industrial performance, while the effect of exogenous convergence is insignificant; (2) TC has a double-threshold effect, with its coefficient being largest at a medium level; and (3) TC has an enterprise scale threshold, in which its effect indicates that only when the scale exceeds the threshold can TC more effectively foster industry performance. The significance of these results for the development of China's textile industry is that they strengthen the level of TC for it to be convergent with emerging industries, as well as increase the size and absorptive capacity of enterprises.
PL
Konwergencja technologii (TC) może zintegrować nowe technologie, metody i procesy z tradycyjnymi gałęziami przemysłu. Może przyspieszyć transformację i modernizację tych branż i ma ogromne znaczenie dla ich rozwoju. Celem badań było ujawnienie wpływu mechanizmu integracji technologii na przemysł włókienniczy oraz przeprowadzenie badań empirycznych. Badanie to w pierwszej kolejności buduje liniowy i nieliniowy mechanizm wpływu TC na rozwój przemysłu tekstylnego w Chinach. Badania empiryczne prowadzone były w oparciu o panelowy model efektu stałego oraz model progu panelowego. Wyniki były następujące: (1) TC znacząco przyczynia się do wydajności chińskiego przemysłu tekstylnego, ponieważ konwergencja endogeniczna może znacząco promować wydajność przemysłową, podczas gdy efekt konwergencji egzogenicznej jest nieznaczny; (2) TC ma efekt podwójnego progu, przy czym jego współczynnik jest największy na średnim poziomie; oraz (3) TC ma próg skali przedsiębiorstwa, w którym jego efekt wskazuje, że tylko wtedy, gdy skala przekracza próg, TC może skuteczniej wspierać wydajność branży. Znaczenie uzyskanych wyników dla rozwoju przemysłu włókienniczego w Chinach polegało na tym, że wzmacniają one poziom KT, aby był on zbieżny z branżami wschodzącymi, a także zwiększają wielkość i chłonność przedsiębiorstw.
Rocznik
Strony
14--21
Opis fizyczny
Bibliogr. 36 poz., rys., tab.
Twórcy
autor
  • China Jiliang University, School of Economics and Management, Hangzhou 310018, China
  • Zhejiang Sci-Tech University, School of Economics and Management, Hangzhou 310018, China
autor
  • Zhejiang Sci-Tech University, School of Economics and Management, Hangzhou 310018, China
autor
  • China Jiliang University, School of Economics and Management, Hangzhou 310018, China
  • Zhejiang Sci-Tech University, School of Economics and Management, Hangzhou 310018, China
Bibliografia
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  • 13. Lei D T. Industry Evolution and Competence Development: the Imperatives of Technological Convergence [J]. International Journal of Technology Management, 2000, 19(7-8): 699-738.
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  • 15. Lee, Kongrae. Patterns and Processes of Contemporary Technology Fusion: The Case of Intelligent Robots [J]. Asian Journal of Technology Innovation 2007; 15(2): 45-65.
  • 16. Lee WS, Han EJ, Sohn SY. Predicting the Pattern of Technology Convergence Using Big-Data Technology on Large -Scale Triadic Patents [J]. Technological Forecasting and Social Change 2015; 100: S0040162515002310.
  • 17. Li Yaya, Zhao Yulin, LIYa-ya, et al. Patented Technology Fusion Analysis Method and its Application [J]. Studies in Science of Science 2016; 34 (2): 203-211.
  • 18. Liu Na, Rong Xueyun, Mao Jianqi. Research on Technology Convergence Model and Identification – Taking Energy Storage Field as an Example [J]. Information Magazine 2018; 37 (12): 24-31.
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  • 20. Li Lingshen, Gu Qingliang, Zhu Xiusen. Technological Innovation and Industrial Upgrade of China’s Textile Industry [J]. Journal of Textile Research 2007; (05): 125-128.
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  • 23. Zhao Yulin, Li Yaya. Technology Integration, Competition Synergy and Performance Improvement of Emerging Industries: An Empirical Study Based on the Global Biochip Industry [J]. Research Management 2017; (08): 14-21.
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  • 26. Llerena P, Meyer-Krahmer F. Interdisciplinary Research and the Organization of the University: General Challenges and a Case Study. In A. Geuna, J. A. Salter, & W. Steinmueller (Eds.), Science andinnovation: Rethinking the rationales for funding and governance 2003; pp. 69-88. Cheltenham: Edward Elgar.
  • 27. Jeong S, Lee S, Kim J, et al. Organizational Strategy for Technology Convergence. World Academy of Science, Engineering and Technology. International Journal of Social, Behavioral, Educational, Economic, Business and Industrial Engineering 2012; 6(8): 1989-1995.
  • 28. Betz F. Strategic Technology Management. McGraw-Hill, New York. 1993. 26. Katz ML. Remarks on the economic implications of convergence. Ind. Corp. Change 1996; 5 (4), 1079-1095.
  • 26. Katz ML,. Remarks on the economic implications of convergence. Ind. Corp. Change 1996; 5 (4), 1079-1095.
  • 29. Nieto M. Performance Analysis of Technology Using the S Curve Model: The Case Of Digital Signal Processing (DSP) Technologies. Technovation 1998; 18: 439-457.
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  • 32. Fai F, Tunzelmann NV, Fai F. von Tunzelmann N. Industry-Specific Competencies and Converging Technological Systems: Evidence from Patents. 12(2), 141-170 [J]. Structural Change.
  • 33. Lin Juanjuan, Chen Xiangdong. Empirical Research on ICT Technology Convergence Based on Network Graph Analysis [J]. Scientific Research Management 2014; (04): 36-45.
  • 34. Lee BK, Sohn SY. Patent Portfolio-Based Indicators to Evaluate the Commercial Benefits of National Plant Genetic Resources. Ecol. Indic. 2016; 70, 43-52.
  • 35. Dibiaggio L, Nasiriyar M, Nesta L, Substitutability and Complementarity of Technological Knowledge and the Inventive Performance of Semiconductor Companies. Research Policy 2014; 43(9): 1582-1593.
Uwagi
Błędna numeracja w bibliografii (po pozycji 28).
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-7d5ce7a8-64c5-4431-a950-1a6fd4ca3222
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