Digital knowledge sharing: the renaissance of models and templates

Knowledge exchange makes a significant contribution to the formation of a company's competitive advantage. Digital knowledge sharing (DKS), being the only alternative during remote work, has opened up new opportunities for companies to adapt to constantly changing conditions. This paper studies the conditions affecting the DKS. The significant characteristics of the knowledge models contributing to the DKS are identified and analyzed. The exploratory factor analysis provides evidence that all the characteristics are combined into three key factors: ease of development, ease of use and usefulness of the model. This study opens up opportunities for an empirical study of the role of knowledge models in stimulating DKS and sets guidelines for managers to choose an approach to its organization.

Keywords: mind map, concept map, flowchart, causal chain, decision tree, Ishikawa diagram

References

  1. A. Kianto, J. Saenz, N. Aramburu. Knowledge-based human resource management practices, intellectual capital and innovation//Journal of Business Research, 81, 2017, 11-20.
  2. K. Moustaghfir, G. Schiuma. Knowledge, learning, and innovation: research and perspectives//Journal of knowledge management, 17 (4), July 2013.
  3. H. Park, R. C. Basole. Bicentric structures: Design and applications of a graph-based relational set mechanism technique//Decision Support Systems, 84, 2016, 64-77.
  4. M. H. Zack. Developing a knowledge strategy//California management review. 1999. Vol. 41. №. 3. P. 125-145.
  5. T. A. Gavrilova, D. V. Kudryavtsev, A. V. Kuznetsova. Vybor instrumentov upravleniya znaniyami s uchetom spetsifiki predmetnoj oblasti//Innovations. 2019. № 8 (250). S. 44-52.
  6. T. Buzen. Intellekt-karty: polnoe rukovodstvo po moshhnomu instrumentu myshleniya. Mann, Ivanov & Ferber, 2018.
  7. J. D. Novak, A. J. Canas. The theory underlying concept maps and how to construct them//Florida Institute for Human and Machine Cognition. 2006. Vol. 1. №. 1. P. 1-31.
  8. J. R. Quinlan. Induction of decision trees//Machine learning. 1986. Vol. 1. №. 1. P. 81-106.
  9. K. C. Wong, K. Z. Woo, K. H. Woo. Ishikawa diagram. Quality Improvement in Behavioral Health. Springer, Cham, 2016. P. 119-132.
  10. S. Bresciani, M. J. Eppler. The pitfalls of visual representations: A review and classification of common errors made while designing and interpreting visualizations//Sage Open. 2015. Vol. 5. №. 4. P. 1-14.
  11. J. Mengis. Integrating knowledge through communication: an analysis of expert-decision making interactions. Universitat della Svizzera italiana, 2007.
  12. N. Marangunić, A. Granić. Technology acceptance model: a literature review from 1986 to 2013//Universal access in the information society. 2015. Vol. 14. №. 1. P. 81-95.

Authors