Research on Supply Chain Application based on Big Data


Antonio Risi,University of Turin, Italy
Pietro Schipani,University of Turin, Italy


With the advent of the information age, the application of big data in supply chain management between different industries has become more and more extensive. The methods and ways to obtain big data and various data types determine the type of big data and whether it can obtain technology for enterprises. The competitive advantage in the market promotes the development of various industries. This article is based on the basic concepts of the big data supply chain and the research of related theoretical methods by experts and scholars. Summarizes the current application status of big data in supply chain management, and provides certain support for future in-depth exploration. Quantitatively analyze the keywords of 601 English documents on the topic of "big data supply chain" obtained by crawlers. And based on scientific research methods, the quantitative data transformed by the text content is sorted, summarized, and analyzed. Then according to the summary content, the current research hotspots of the big data supply chain are compared and analyzed, and the future development direction of big data application in the supply chain is predicted.



Big data, Supply chain, Cluster analysis, Social network analysis


[1] J. Law and A. Rip, “Policy and the mapping of scientific change: A co-word analysis of research into environment acidification,” Scientometrics, vol.14, pp.251-264, (1986)
[2] M. Callon, J. Law, and A. Rip, “Mapping the dynamics of science and technology: Sociology of science in the real world,” London: The Macmillan Press Ltd, pp.103123, (1986)
[3] A. G. L. Herrera, M. J. Cobo, E. Herrera-Viedma, and F. Herrera “Visualizing the hybridizations between the fuzzy logic field and the other soft-computing techniques,” Proceedings-8th International Conference on Hybrid Intelligent Systems, pp.252-257, (2008)
[4] M. W. Neff and E. A. Corley, “35 years and 160000 articles: A bibliometric exploration of the evolution of ecology,” Scientometrics, vol.80, no.3, pp.657-682, (2009)
[5] A. A. Khasseh, F. Soheili, and H. S. Moghaddam, “Intellectual structure of knowledge in I metrics: A co-word analysis,” Information Processing and Management, vol.53. no.3, pp.705-720, (2017)
[6] M. Granovetter, “The strength of weak ties,” American Journal of Sociology, pp.1360-1380, (1973)
[7] R. V. Gould, “Collective action and network structure,” American Sociological Review, pp.182-196, (1993)
[8] I. Nonaka and H. Takeuchi, “The knowledge-creating company,” New York: Oxford University Press, pp.273, (2008)
[9] E. Otte and R. Rousseau, “Social network analysis: A powerful strategy also for the information sciences,” Journal of Information Science, vol.28, no.6, pp.441-453, (2002)
[10] Bott, “Ambiguity and the process of knowledge transfer in strategic alliances,” Strategic Management Journal, no.20, pp.595-623, (2010)
[11] R. Ghosh, K. Lerman, “Rethinking centrality: The role of dynamical processes in social network analysis,” Discrete and Continuous Dynamical Systems - Series B (DCDS-B), vol.19, no.5, pp.1355-1372, (2014)
[12] R. L. de Andrade and L. C. Rêgo, “The use of nodes attribute in social network analysis with an application to an international trade network,” Physical A: Statistical Mechanics and its Applications, (2017) S0378437117308579.
[13] L. Yong, Z. Wendi, and X. Yejing, “Discussion on the application of embeddedness theory in archives management and services,” Archives Management, no.1, pp.4-10, (2015)
[14] E. M. Tucker-Drob and T. A. Salthouse, “Confirmatory factor analysis and multidimensional scaling for construct validation of cognitive abilities,” International Journal of Behavioral Development, vol.33, no.3, pp.277-285, (2009)
[15] B. Marshalek, D. F. Lohman, and R. E. Snow, “The complexity continuum in the radix and hierarchical models of intelligence,” Intelligence, vol.7, no.2, pp.107-127, (1983)
[16] W. Kaixuan, “Factor analysis and multi-dimensional scale analysis of structural validity,” Journal of Guizhou Normal University (Natural Science Edition), vol.32, no.1, pp.20-24, (2014)


  • APA:
    Risi,A.& Schipani,P.(2018). Research on Supply Chain Application based on Big Data. International Journal of Smart Business and Technology, 6(1), 1-14. 10.21742/IJSBT.2018.6.1.01
  • Harvard:
    Risi,A., Schipani,P.(2018). "Research on Supply Chain Application based on Big Data". International Journal of Smart Business and Technology, 6(1), pp.1-14. doi:10.21742/IJSBT.2018.6.1.01
  • IEEE:
    [1] A.Risi, P.Schipani, "Research on Supply Chain Application based on Big Data". International Journal of Smart Business and Technology, vol.6, no.1, pp.1-14, Jun. 2018
  • MLA:
    Risi Antonio and Schipani Pietro. "Research on Supply Chain Application based on Big Data". International Journal of Smart Business and Technology, vol.6, no.1, Jun. 2018, pp.1-14, doi:10.21742/IJSBT.2018.6.1.01


  • Volume 6, No. 1, 2018
  • ISSN(p):2288-8969
  • ISSN(e):2207-516X
  • Published:Jun. 2018