International Journal of Internet, Broadcasting and Communication

  • 제12권4호
  • /
  • Pages.204-211
  • /
  • 2020
  • /
  • 2288-4920(pISSN)
  • /
  • 2288-4939(eISSN)
한국인터넷방송통신학회 (The Institute of Internet, Broadcasting and Communication)
권호 표지
DOI QR코드

DOI QR Code

A Study on Socio-technical System for Sustainability of the 4th Industrial Revolution: Machine Learning-based Analysis

  • 투고 : 2020.10.02
  • 심사 : 2020.10.11
  • 발행 : 2020.11.30
PDF 다운로드
⟨ 이전 논문 다음 논문 ⟩

초록

The era of the 4th industrial revolution is a complex environment in which the cyber world and the physical world are integrated and interacted. In order to successfully implement and be sustainable the 4th industrial revolution of hyper-connectivity, hyper-convergence, and hyper-intelligence, not only the technological aspects that implemented digitalization but also the social aspects must be recognized and dealt with as important. There are socio-technical systems and socio-technical systems theory as concepts that describe systems involving complex interactions between the environmental aspects of human, mechanical and tissue systems. This study confirmed how the Socio-technical System was applied in the research literature for the last 10 years through machine learning-based analysis. Eight clusters were derived by performing co-occurrence keywords network analysis, and 13 research topics were derived and analyzed by performing a structural topic model. This study provides consensus and insight on the social and technological perspectives necessary for the sustainability of the 4th industrial revolution.

키워드

참고문헌

  1. J. Lee, "A Study on Research Trend Analysis and Topic Class Prediction of Digital Transformation using Text Mining," International journal of advanced smart convergence, vol. 8, no. 2, pp. 183-190, 2019. DOI: https://doi.org/10.7236/IJASC.2019.8.2.183
  2. J. Y. Lee, "A Study on Agile Transformation in the New Digital Age," International Journal of Advanced Culture Technology, vol. 8, no. 1, pp. 82-88, 2020 DOI: https://doi.org/10.17703/IJACT.2020.8.1.82
  3. L. D. Xu, E. L. Xu, L. Li, "Industry 4.0: state of the art and future trends," International Journal of Production Research, vol. 56, no. 8, pp. 2941-2962, 2018. DOI: https://doi.org/10.1080/00207543.2018.1444806
  4. R. Davies, T. Coole, A. Smith, "Review of socio-technical considerations to ensure successful implementation of Industry 4.0," in 7th International Conference on Flexible Automation and Intelligent Manufacturing, FAIM2017, pp. 1288-1295, June 27-30, 2017. DOI: https://doi.org/10.1016/j.promfg.2017.07.256
  5. N. Zhao, J. Bao, N. Chen, "Ranking Influential Nodes in Complex Networks with Information Entropy Method," Complexity, vol. 2020, June 2020. DOI: https://doi.org/10.1155/2020/5903798
  6. G. H. Walker, N. A. Stanton, P. M. Salmon, et al., "A review of sociotechnical systems theory: a classic concept for new command and control paradigms," Theoretical issues in ergonomics science, vol. 9, no. 6, pp. 479-499, 2018. DOI: https://doi.org/10.1080/14639220701635470
  7. K. Eason, "Local sociotechnical system development in the NHS National Programme for Information Technology," Journal of Information Technology, vol. 22, no. 3, pp. 257-264, 2007. DOI: https://doi.org/10.1057/palgrave.jit.2000101
  8. G. Baxter, I. Sommerville, "Socio-technical systems: From design methods to systems engineering," Interacting with computers, vol. 23, no. 1, pp. 4-17, 2011. DOI: https://doi.org/10.1016/j.intcom.2010.07.003
  9. N. J. v. Eck, L. Waltman, "How to normalize cooccurrence data? An analysis of some well‐known similarity measures," Journal of the American Society for Information Science and Technology, vol. 60, no. 8, pp. 1635-1651, 2009. DOI: https://doi.org/10.1002/asi.21075
  10. N. J. Van Eck, L. Waltman, "Software survey: VOSviewer, a computer program for bibliometric mapping," Scientometrics, vol. 84, no. 2, pp. 523-538, 2010. DOI: https://doi.org/10.1007/s11192-009-0146-3
  11. N. J. Van Eck, L. Waltman, "Citation-based clustering of publications using CitNetExplorer and VOSviewer," Scientometrics, vol. 111, no. 2, pp. 1053-1070, 2017. DOI: https://doi.org/10.1007/s11192-017-2300-7
  12. M. E. Roberts, B. M. Stewart, D. Tingley, et al., "The structural topic model and applied social science," in Advances in neural information processing systems workshop on topic models: computation, application, and evaluation, Harrahs and Harveys, Lake Tahoe, 2013.
  13. M. E. Roberts, B. M. Stewart, D. Tingley, "stm: R package for structural topic models," Journal of Statistical Software, vol. 10, no. 2, pp. 1-40, 2014. DOI: https://doi.org/10.18637/jss.v091.i02