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The Topics Dynamics in Knowledge Management Research

  • Yuri ZelenkovEmail author
Conference paper
Part of the Communications in Computer and Information Science book series (CCIS, volume 1027)

Abstract

The intellectual structure of an academic discipline can be viewed as a set of interacting topics evolving over time. Dynamics of those topics i.e. changes in their popularity and impact is the subject of special attention because it reflects a shift in actual researchers’ interest. This paper analyzes topics of knowledge management (KM) on the base of the topic modeling technique (namely Latent Dirichlet Allocation). Studying the flow of academic publications in 7 leading journals in 2010–2018, we identified 8 topics that concern different aspects of knowledge management science. Three topics, what focus on the social aspects of knowledge management (namely the context supporting knowledge transfer, the employees’ incentives to share knowledge, and innovation), grow in terms of popularity and impact. Opposite, popularity and impact of topics, which focus on the practice of the knowledge management and organizational learning also as on the impact of intellectual capital on performance, decline. It is consistent with the opinion of other researchers that in the contemporary flow of scientific publication role of KM is identified more as a social process than a management engineering method.

Keywords

Knowledge management Bibliometrics Topic modeling LDA 

References

  1. 1.
    Akhavan, P., Ebrahim, N.A., Fetrati, M.A., Pezeshkan, A.: Major trends in knowledge management research: a bibliometric study. Scientometrics 107(3), 1249–1264 (2016)CrossRefGoogle Scholar
  2. 2.
    Gaviria-Marin, M., Merigó, J.M., Baier-Fuentes, H.: Knowledge management: a global examination based on bibliometric analysis. Technol. Forecast. Soc. Change 140, 194–220 (2019)CrossRefGoogle Scholar
  3. 3.
    Lambe, P.: The unacknowledged parentage of knowledge management. J. Knowl. Manage. 15(2), 175–197 (2011)CrossRefGoogle Scholar
  4. 4.
    Wang, P., Zhu, F.W., Song, H.Y., Hou, J.H., Zhang, J.L.: Visualizing the academic discipline of knowledge management. Sustainability 10(3), 682 (2018)CrossRefGoogle Scholar
  5. 5.
    Tzortzaki, A.M., Mihiotis, A.: A review of knowledge management theory and future directions. Knowl. Process Manage. 21(1), 29–41 (2014)CrossRefGoogle Scholar
  6. 6.
    Inkinen, H.: Review of empirical research on intellectual capital and firm performance. J. Intellect. Capital 16(3), 518–565 (2015)CrossRefGoogle Scholar
  7. 7.
    Heisig, P., Suraj, O.A., Kianto, A., Kemboi, C., Perez Arrau, G., Fathi Easa, N.: Knowledge management and business performance: global experts’ views on future research needs. J. Knowl. Manage. 20(6), 1169–1198 (2016)CrossRefGoogle Scholar
  8. 8.
    Argote, L., Miron-Spector, E.: Organizational learning: from experience to knowledge. Organ. Sci. 22(5), 1123–1137 (2011)CrossRefGoogle Scholar
  9. 9.
    Serenko, A., Bontis, N.: Global ranking of knowledge management and intellectual capital academic journals: 2017 update. J. Knowl. Manage. 21(3), 675–692 (2017)CrossRefGoogle Scholar
  10. 10.
    Chen, C.: CiteSpace II: detecting and visualizing emerging trends and transient patterns in scientific literature. J. Am. Soc. Inf. Sci. Technol. 57(3), 359–377 (2006)CrossRefGoogle Scholar
  11. 11.
    van Eck, N., Waltman, L.: Software survey: VOSviewer, a computer program for bibliometric mapping. Scientometrics 84(2), 523–538 (2009)Google Scholar
  12. 12.
    Dwivedi, Y.K., Venkitachalam, K., Sharif, A.M., Al-Karaghouli, W., Weerakkody, V.: Research trends in knowledge management: analyzing the past and predicting the future. Inf. Syst. Manage. 28(1), 43–56 (2011)CrossRefGoogle Scholar
  13. 13.
    Lee, M.R., Chen, T.T.: Revealing research themes and trends in knowledge management: from 1995 to 2010. Knowl. Based Syst. 28, 47–58 (2012)CrossRefGoogle Scholar
  14. 14.
    Steyvers, M., Griffiths, T.: Probabilistic topic models. In: Landauer, T., McNamara, D., Dennis, S., Kintsch, W. (eds.) Latent Semantic Analysis: A Road to Meaning, pp. 424–440. Laurence Erlbaum, Hillsdale (2007)Google Scholar
  15. 15.
    Blei, D.M., Ng, A.Y., Jordan, M.I.: Latent Dirichlet allocation. J. Mach. Learn. Res. 3, 993–1022 (2003)zbMATHGoogle Scholar
  16. 16.
    Mann, G.S., Mimno, D., McCallum, A.: Bibliometric impact measures leveraging topic analysis. In: Proceedings of the 6th ACM/IEEE-CS Joint Conference on Digital Libraries, pp. 65–74. ACM (2006)Google Scholar
  17. 17.
    Gatti, C.J., Brooks, J.D., Nurre, S.G.: A historical analysis of the field of OR/MS using topic models. arXiv preprint arXiv:1510.05154 (2015)
  18. 18.
    Dam, H.K., Ghose, A.: Analyzing topics and trends in the PRIMA literature. In: Baldoni, M., Chopra, A.K., Son, T.C., Hirayama, K., Torroni, P. (eds.) PRIMA 2016. LNCS (LNAI), vol. 9862, pp. 216–229. Springer, Cham (2016).  https://doi.org/10.1007/978-3-319-44832-9_13CrossRefGoogle Scholar
  19. 19.
    Sun, L., Yin, Y.: Discovering themes and trends in transportation research using topic modeling. Transp. Res. Part C: Emerg. Technol. 77, 49–66 (2017)CrossRefGoogle Scholar
  20. 20.
    Syed, S., Spruit, M.: Full-text or abstract? examining topic coherence scores using latent Dirichlet allocation. In: 2017 IEEE International Conference on Data Science and Advanced Analytics (DSAA), pp. 165–174. IEEE (2017)Google Scholar
  21. 21.
    Sievert, C., Shirley, K.: LDAvis: a method for visualizing and interpreting topics. In: Proceedings of the Workshop on Interactive Language Learning, Visualization, and Interfaces, pp. 63–70. Association for Computational Linguistics (2014)Google Scholar
  22. 22.
    McInnes, L, Healy, J.: UMAP: Uniform Manifold Approximation and Projection for Dimension Reduction, ArXiv e-prints arXiv:1802.03426 (2018)CrossRefGoogle Scholar
  23. 23.
    Kamukama, N., Ahiauzu, A., Ntayi, J.M.: Competitive advantage: mediator of intellectual capital and performance. J. Intellect. Capital 12(1), 152–164 (2011)CrossRefGoogle Scholar
  24. 24.
    Nobre, F.S., Walker, D.S.: A dynamic ability-based view of the organization. Int. J. Knowl. Manage. 7(2), 86–101 (2011)CrossRefGoogle Scholar
  25. 25.
    Cauwelier, P., Ribière, V.M., Bennet, A.: Team psychological safety and team learning: a cultural perspective. Learn. Organ. 23(6), 458–468 (2016)CrossRefGoogle Scholar
  26. 26.
    Rutten, W., Blaas-Franken, J., Martin, H.: The impact of (low) trust on knowledge sharing. J. Knowl. Manage. 20(2), 199–214 (2016)CrossRefGoogle Scholar
  27. 27.
    Minonne, C., Turner, G.: Business process management—are you ready for the future? Knowl. Process Manage. 19(3), 111–120 (2012)CrossRefGoogle Scholar
  28. 28.
    Wang, C., Han, Y.: Linking properties of knowledge with innovation performance: the moderate role of absorptive capacity. J. Knowl. Manage. 15(5), 802–819 (2011)CrossRefGoogle Scholar
  29. 29.
    Massaro, M., Dumay, J., Garlatti, A.: Public sector knowledge management: a structured literature review. J. Knowl. Manage. 19(3), 530–558 (2015)CrossRefGoogle Scholar
  30. 30.
    Zeghal, D., Maaloul, A.: Analysing value added as an indicator of intellectual capital and its consequences on company performance. J. Intellect. Capital 11(1), 39–60 (2010)CrossRefGoogle Scholar

Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  1. 1.National Research University Higher School of EconomicsMoscowRussia

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