شکل گیری شبکه دانش در شرکت های دانش بنیان

نوع مقاله : مقاله پژوهشی

نویسندگان

1 استاد مدیریت، دانشکده مدیریت وحسابداری، دانشگاه شهید بهشتی

2 استادیار مدیریت، دانشکده مدیریت وحسابداری، دانشگاه شهید بهشتی

3 دانشجوی دکتری مدیریت، دانشگاه شهید بهشتی

چکیده

پژوهش حاضر با هدف مدلسازی عوامل موثر بر شبکه‌های دانش در شرکت‌های دانش بنیان انجام شده است. از نظر روش شناسی، این پژوهش از نوع ترکیبی - اکتشافی بوده به همین منظور با ترکیبی از روش‌های کمی و کیفی و با تکیه بر نظر خبرگان عوامل موثر در شکل‌گیری شبکه‌های دانش و روابط بین آنها در شرکت‌های دانش بنیان، شناسایی و رتبه بندی شدند. جهت تجزیه و تحلیل اطلاعات، در مرحله کیفی از روش تحلیل محتوا و در مرحله کمی از روش مدلسازی ساختاری تفسیری استفاده شد. نتایج این پژوهش نشان داد، توسعه فرآیندهای مدیریتی بیشترین تاثیر را در شکل‌گیری شبکه‌های دانش دارند و تاثیر پذیرترین عامل‌ها نیز در سطح نخست از مدل قرار دارند که شامل نوع دانش، عوامل فرهنگی، ساختارهای سازمانی و سازوکارهای ارتباطی می‌باشند. پیشنهاد می‌شود در حوزه پژوهش و فناوری و حتی در حوزه‌های عملیاتی دیگر، نیز شبکه‌های دانش بین سازمانی با مدل طراحی شده در این تحقیق، جایگزین طرح‌ها و پروژه‌های پراکنده فعلی مدیریت دانش شود.

کلیدواژه‌ها


عنوان مقاله [English]

Modelling of a Knowledge Network in Knowledge-based Enterprises

نویسندگان [English]

  • Ali Rezaeian 1
  • Navid Nezafati 2
  • Rouhollah Bagheri 3
1 Professor of Management, Faculty of Management and Accounting, Shahid Beheshti
2 Assistant Professor of Management, Faculty of Management and Accounting, Shahid Beheshti University
3 PhD Candidate of System Management,Faculty of Management and Accounting, Shahid Beheshti University
چکیده [English]

The purpose of this study was to model the factors that affect the knowledge networks in knowledge-based companies. Methodologically, the research is of a hybrid-exploratory type. By combining quantitative and qualitative methods and relying on experts' opinions, the factors influencing the formation of knowledge networks and their relationships to knowledge-based companies were identified and ranked. In order to analyze the data, the content analysis method and the structural interpretation model were used in qualitative and quantitative stages respectively. The results of this study showed that the development of management processes has the greatest impact on the formation of knowledge networks, and the most influential factors are at the first level of the model. These factors include the type of knowledge, cultural factors, organizational structures and communication mechanisms. It is suggested that, in the field of research and technology and even in other operational areas, the current dispersal schemes of knowledge management be replaced by inter-organizational knowledge networks and the model developed in this research.

کلیدواژه‌ها [English]

  • Knowledge-based enterprise
  • Knowledge network
  • Interpretive structural modelling
  • Content analysis
  1. Addis , M. (2016). Tacit and explicit knowledge in construction management. Construction Management and Economics, 34(7-8), 439-445.
  2. Alkhuraiji, A., Liu, S., Oderanti, F. O., & Megicks, P. (2016). New structured knowledge network for strategic decision-making in IT innovative and implementable projects. Journal of Business Research, 69(5), 1534-1538.
  3. Author, A. A., & Author, B. B. (2013).Title of book. Location: Publisher.
  4. Author, A. A., Author, B. B., & Author. C. C. (2013). Title of article. Title of Journal, volume, page-numbers.
  5. Bagheri, R., Rostami, A, Bagheri, V. (2012), Knowledge Management: Concepts and Applications, Vina Publication, Tehran, Iran
  6. Booz, A., H. (2004). Organizational DNA, Booz & company. Retrieved from www.booz.com.
  7. Bottasso, A., Castagnetti, C., & Conti, M. (2015). R&D, Innovation and Knowledge Spillovers: A Reappraisal of Bottazzi and Peri (2007) in the Presence of Cross‐Sectional Dependence. Journal of Applied Econometrics, 30(2), 350-352.
  8. Easton, G (1992). Industrial networks: A review, In: Axelsson, B and G Easton (editors), Industrial Networks - A New View of Reality, London: Routledge
  9. Ellison, N. B., Gibbs, J. L., & Weber, M. S. (2015). The Use of Enterprise Social Network Sites for Knowledge Sharing in. American Behavioral Scientist, 59(1), 103-123.
  10. Hamidizadeh, M.R. (2010), Knowledge and wisdom Management: Structure, Process and Solutions, Yaghout Publication, Qom, Iran.
  11. Hamidizadeh, M.R. (2015), Explaining Native Knowledge Development Patterns, Journal of Strategic Management Studies, Vol. 6 Issue 21, pp. 211-249.
  12. Hamidizadeh, M.R., Kheirkhah, M.R. (2010), The Effect of Marketing Knowledge Management Capabilities on Organizational Performance in Iranian Petrochemical Industry, Journal of Business Administration Researches, Vol 4 Issue 8, pp. 30-45
  13. Holakoupour, M., Hamidizadeh, M.R. (2016), Explaining and assessing business knowledge strategies and knowledge development strategies, Vol. 8, Issue 16, pp.211-232
  14. Huang J. J., Tzeng G. H., Ong C. S., (2005).” Multidimensional data in multidimensional scaling using the analytic network process”, Pattern Recognition Letters, 26, 755–767.
  15. Jayrama , A. and Ayvari, A. (2005), “Can the knowledge – creation  process be managed? a case study of an artist training project “, International Journal of Arts Management, 72(2), pp. 4-14.
  16. Klimasauskiene, R., (2003). “Enhancing science-based innovations through knowledge mobility between higher education and educational practice”, European Conference on Educational Research, University of Hamburg, 17 - 20 September.
  17. Kou, L. (2004). Mapping the R&D Knowledge Network, PhD. Thesis, Massachusetts Institute of Technology, USA
  18. Krippendorff, K. (2000), Content Analysis: The Basics of Methodology, Translated by Nayebi, H., Ney Publication, Tehran, Iran.
  19. Martina, K., Urbancova, H.; Fejfar, J. (2012). Identification of Managerial Competencies in Knowledge-based Organizations. Journal of Competitiveness. Vol 4. No: 1
  20. Monzon, A., Chow, T., Guthrie, P., Lu, Z., Chuma, C., He, H., & Kuzkov, S. (2016). Methods for promoting knowledge exchange and networking among young professionals in the aerospace sector—IAF׳ s IPMC workshop 2013 insights. Acta Astronautica, 118, 123-129.
  21. Moore, F., & Moore, F. (2016). Flexible identities and cross-border knowledge networking. critical perspectives on international business, 12(4), 318-330
  22. Özsomer, A., Calantone, R. J., & Di Bonetto, A. (1997). What makes firms more innovative? A look at organizational and environmental factors. Journal of Business & Industrial Marketing, 12(6), 400-416.
  23. Palmié, M. F. (2012). Organizational Architecture and the Realization of Competitive Advantages from Multinationality. Gallen, Germany: D I S S E R T A T I O N of the University of St. Gallen.
  24. Pinato, J. (2002). a Knowledge-Network Model of Scientific Communities, PhD. Thesis, Massachusetts Institute of Technology, USA.
  25. Ragab, M., & Arisha, A. (2013). Knowledge management and measurement: a critical review. Journal of Knowledge Management, 17(6), 873-901.
  26. Raghavan, A. (2004). Re-engineering Knowledge Network for development, PhD. Thesis, Massachusetts Institute of Technology, USA
  27. Rotblat, J., Reppy, J., Avduyevsky, V., & Holdren, J. (Eds.). (2016). Conversion of Military R&D. Springer.
  28. Saeida, S., Konjkav, A. (2011), Factors Affecting the Success of Establishing Knowledge Management in Higher Education Institutions, Journal of Business Administration Researches, Vol 3 Issue 5, pp. 136-158.
  29. Serenko, A., Bontis, N., & Hull, E. (2016). An application of the knowledge management maturity model: the case of credit unions. Knowledge Management Research & Practice, 14(3), 338-352.
  30. Serrat, O. (2017). Notions of knowledge management Knowledge Solutions (pp. 291-304): Springer.
  31. Singh, J., & Fleming, L. (2010). Lone inventors as sources of breakthroughs: Myth or reality? . Management Science, 56, 41-56.
  32. Solymossy, E. (2015). Knowledge networks: differences and performance effects. Journal of Small Business Strategy, 11(1), 14-25.
  33. Stacy, R.D., Fico, F.J. (2008), Analysis of media messages Application of quantitative content analysis in research, Translated by Alavi, M., Soroush Publication, Tehran, Iran.
  34. Suhaimee,S.,Abu Bakr,A.Z.and Alias,R.A.(2006).”Knowledge Sharing Culture in Malaysian Public Institution of HigherEducation : An Overview”,Proceedings of the Postgraduate Annual Research Seminar,pp.354-359.
  35. Thakkar,J.,  Deshmukh, G., Gupta, A., and Shankar, R. (2007). “Development of a balanced scorecard An integrated approach of Interpretive Structural Modeling (ISM) and Analytic Network Process”, International Journal of Productivity and Performance Management , 56(1), 25-59.
  36. Tizro, A. (2010), Designing an Agile Supply Chain Modeling, Interpretative Structural Modeling Approach, PhD Dissertation, Tarbiat Modares University, Tehran, Iran
  37. Zhou. (1996). Robustness of the Efficient DMUs in Data Envelopment Analysis. European Journal of Operational Research, 90(3), 451-460.