skip to main content
10.1145/3453187.3453307acmotherconferencesArticle/Chapter ViewAbstractPublication PagesebimcsConference Proceedingsconference-collections
research-article

Analysis of Value Chain Position Based on SNA International Trade in the Context of Belt and Road

Authors Info & Claims
Published:24 March 2021Publication History

ABSTRACT

With the deepening of the construction of "Belt and Road ", the countries along the route have gradually become China's most important trading partners, and the" Belt and Road "economic and trade cooperation network constructed by trade relations has been formed. Under the background of the high quality development of "Belt and Road ", China's manufacturing industry has been deeply embedded in the global value chain and economic and trade network. Its development and upgrading are not only restricted by the global economic and trade network, but also affect the global economic and trade network relationship. China's trade globalization will be further upgraded in the future. How will it affect the "Belt and Road" trade network and whether it will affect China's position in the trade value chain? This has become an important topic of practical value. Based on the data of bilateral investment between 55 countries in the world in 2003~2011, this paper describes the characteristics of a country's OFDI network from three dimensions: network centrality, network connection intensity and network heterogeneity, and empirically tests the influence of the characteristics of a country's OFDI network on its global value chain division of labor and global value chain participation.

References

  1. Tsai W, Ghoshal S, 1998. Social Capital and Value Creation: An Empiri- cal Study of Intrafirm Networks[J]. Academy of Management Jour- nal, 41 (4): 464--476.Google ScholarGoogle Scholar
  2. Larson A, 1992. Network Syads in Entrepreneurial Settings: A Study of the Governance of Exchange Relationships [J]. Administrative Science Quarterly, 37(1):76--104.Google ScholarGoogle Scholar
  3. Chiu C M, Hsu M H, Wang E T G, 2006. Understanding Knowledge Sha- ring in Virtual Communities: An Integration of Social Capital and Social Cognitive Theories [J]. Decision Support Systems, 42 (3):1872--1888.Google ScholarGoogle Scholar
  4. Dobrzykowski D D, Tarafdar M, 2015. Understanding Information Ex- change in Healthcare Operations: Evidence from Hospitals and Pa- tients[J]. Journal of Operations Management, 36:201--214.Google ScholarGoogle Scholar
  5. Chang H H, Hsieh P H, Fu C S, 2016. The Mediating Role of Sense of Virtual Community [J]. Online Information Review, 40 (7):882--899.Google ScholarGoogle Scholar
  6. Zárraga C, Bonache J, 2003. Assessing the Team Environment for Knowledge Sharing: An Empirical Analysis[J]. International Journal of Human Resource Management, 14 (7): 1227--1245.Google ScholarGoogle Scholar
  7. Nonaka I, Takeuchi H., 1995. The Knowledge-creating Company: How Japanese Companies Create and the Dynamics of Innovation[M]. New York: Oxford University Press.Google ScholarGoogle Scholar
  8. Bostrom R P. Successful application of communication techniques to improve the systems development process [J]. Information and Management, 1989, 16 (2): 279--295.Google ScholarGoogle ScholarDigital LibraryDigital Library
  9. Huber G P. Organizational Learning: The Contributing processes and the literatures [J]. Organization science, 2000, 11 (5): 538--550.Google ScholarGoogle Scholar
  10. Gunnar H. A model of knowledge management and the N-form corporation [J]. Strategy Management Journal, 1994, 15 (5): 73--90.Google ScholarGoogle Scholar
  11. Hou Changhai. Analysis of China's online education market in 2015. Internet World, 2016(2): 85--88Google ScholarGoogle Scholar
  12. Huang Wenzhi, Zhao Jing. Discussion on the development prospect of online education in the era of "Internet +"[J]. China Adult Education, 2016(6): 138--140.Google ScholarGoogle Scholar
  13. Dinah G. & Daniel K. & Isabel W. & Jayne C. Training Needs Analysis: A Literature Review and Reappraisal. International Journal of Nursing Studies, 2014, 42(5): 1--10Google ScholarGoogle Scholar
  14. Wu Xiaoqiong, Xing Yanfang. Analysis of the Development Path of Online Education[J]. Journal of Zhangzhou Teachers College, 2015(1):87--90.Google ScholarGoogle Scholar
  15. Chen Qilin, Bao Haobo. The history and current situation of online education development in China. Xueyuan, 2014(26): 184--185Google ScholarGoogle Scholar
  16. Yang Wei, Yan Jin. Analysis of the Teaching Reform of Open Online Course---Taking L College as an Example[J]. Value Engineering, 2016, 35(19): 207--209.Google ScholarGoogle Scholar
  17. Xiao Yuewen, Wang Mingyu. Talking about the status quo and development trend of online education. China Business Theory, 2017(18): 176--177Google ScholarGoogle Scholar
  18. Earl L., Katz S. Leading Schools in a Data Rich World. Corwin Press, 2006, 23(2): 9--16Google ScholarGoogle Scholar
  19. Zhang Junchao. Institutional Research and University Management in the Age of Big Data[J]. Higher Education Research, 2014(1): 128.Google ScholarGoogle Scholar
  20. Chen Lei. Application of Big Data in Teachers' Online Education Environment---Taking Courses in Zhejiang Province as an Example[J]. Continuing Education, 2017, 31(9): 7--11.Google ScholarGoogle Scholar
  21. Yang Xianmin, et al. Development Strategy and Path Choice of Wisdom Education in China [J]. Modern Educational Technology, 2014(1): 14.Google ScholarGoogle Scholar
  22. Liu Bin, Zhang Wenlan. Research on the Influencing Factors and Structure of Online Course Learning Experience [J]. Modern Educational Technology, 2017, 27(09): 107--113.Google ScholarGoogle Scholar
  23. Zheng Lei. Online Learning and Quality Assessment Research [J]. Shenzhou, 2014, 14.Google ScholarGoogle Scholar
  24. Zhang Wei. Strategies for improving the participation of college students in online learning. Zhejiang Normal University. 2011.11-12.Google ScholarGoogle Scholar
  25. Maclaughlin E J, Supernaw R B, Howard K A. Impact of distance learning using videoconferencing technology on student performance [J]. American Journal of Pharmaceutical Education, 2004, 68(3): 1--6.Google ScholarGoogle ScholarCross RefCross Ref
  26. Guan Jia, Li Qitao. Development Status, Trends and Experiences of Online Education in China [J]. China Electro-chemical Education, 2014(08): 62--66.Google ScholarGoogle Scholar
  27. Sun Li, Cheng Yuxia. Research and Implementation of Online Education Learning Achievement Prediction in Big Data Era--Taking English as an Example of Undergraduate Public Courses[J]. Open Education Research, 2015(3): 74--80.Google ScholarGoogle Scholar
  28. Kees J., Tangari A. H. The Impact of Regulatory Focus, Temporal Orientation, and Fit on Consumer Responses to Health-Related Advertising [J]. Journal of Advertising, 2010, 39(1): 19--34.Google ScholarGoogle ScholarCross RefCross Ref
  29. Heng-Li Yang, Wu, T.C.T.. Knowledge Sharing in an Organization-Share or Not[J]. Technological Forecasting & Social Change, 2008, 75(8): 1128--1156.Google ScholarGoogle ScholarCross RefCross Ref
  30. Higgins E. T. Beyond Pleasure and Pain: How Motivation Works [M]. London: Oxford University Press, 2012.Google ScholarGoogle Scholar
  31. Higgins E. T. Making a Good Decision: Value from Fit [J]. American Psychologist, 2000, 55(11): 1217 -1230.Google ScholarGoogle ScholarCross RefCross Ref
  32. Roy R., Naidoo V. The Impact of Regulatory Focus and Word of Mouth Valence on Search and Experience Attribute Evaluation [J]. European Journal of Marketing, 2017, 51(7/8): 1353--1373.Google ScholarGoogle ScholarCross RefCross Ref
  33. Avnet T., Higgins E. T. How Regulatory Fit Affects Value in Consumer Choices and Opinions [J]. Journal of Marketing Research, 2006, 43(1): 1--10.Google ScholarGoogle ScholarCross RefCross Ref
  34. Godes, D., Mayzlin, D.. Us ing online conversations to study word-of-mouth communication[J]. Marketing science, 2004, 23(4):545--560.Google ScholarGoogle ScholarCross RefCross Ref
  35. Hennig, T.T., Gwinner, K.P., Walsh, G.. Electronic word-of-mouth via consumer-opinion platforms: What motivates consumers to articulate themselves on the internet?[J]. Journal of interactive marketing, 2004, 18(1): 38--52.Google ScholarGoogle Scholar
  36. Duan, W. J., Gu. B., Whinston, A. B.. The dynamics of on-line word-of-mouth and product sales- an empirical investigation of the movie industry[J]. Journal of retailing, 2008, 84(2):233--242.Google ScholarGoogle ScholarCross RefCross Ref
  37. Goldsmithre, Horowitzd. Measuring motivations for online opinion seeking[J]. Journal of interactive advertising, 2006, 6(2):1--16.Google ScholarGoogle Scholar
  38. HIGGINS E T. Self-discrepancy: a theory relating self and affect[J]. Psychological review, 1987, 94(3):319--340.Google ScholarGoogle ScholarCross RefCross Ref
  39. Lockwood P, Jordan C H, Kunda Z. Motivation by positive or negative role models: Regulatory focus determines who will best inspire us[J]. Journal of Personality and Social Psychology, 2002, 83(4): 854--864.Google ScholarGoogle ScholarCross RefCross Ref

Index Terms

  1. Analysis of Value Chain Position Based on SNA International Trade in the Context of Belt and Road

      Recommendations

      Comments

      Login options

      Check if you have access through your login credentials or your institution to get full access on this article.

      Sign in
      • Published in

        cover image ACM Other conferences
        EBIMCS '20: Proceedings of the 2020 3rd International Conference on E-Business, Information Management and Computer Science
        December 2020
        718 pages
        ISBN:9781450389099
        DOI:10.1145/3453187

        Copyright © 2020 ACM

        Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

        Publisher

        Association for Computing Machinery

        New York, NY, United States

        Publication History

        • Published: 24 March 2021

        Permissions

        Request permissions about this article.

        Request Permissions

        Check for updates

        Qualifiers

        • research-article
        • Research
        • Refereed limited

        Acceptance Rates

        EBIMCS '20 Paper Acceptance Rate112of566submissions,20%Overall Acceptance Rate143of708submissions,20%
      • Article Metrics

        • Downloads (Last 12 months)9
        • Downloads (Last 6 weeks)2

        Other Metrics

      PDF Format

      View or Download as a PDF file.

      PDF

      eReader

      View online with eReader.

      eReader