تحلیل شبکه اجتماعی دانشگاهی حوزه شبکه دانش: نسبت‌ها، روندها و خوشه‌ها

نوع مقاله : پژوهشی (با رویکردهای کیفی)

نویسندگان

1 گروه علم اطلاعات و دانش‌شناسی، دانشکده علوم تربیتی و روان‌شناسی، دانشگاه شهید چمران اهواز، اهواز، ایران.

2 دانشیار گروه علم اطلاعات و دانش شناسی، دانشکده علوم اجتماعی، دانشگاه رازی کرمانشاه، کرمانشاه، ایران

3 دانشجوی دکتری، علم اطلاعات و دانش‌شناسی، دانشکده علوم تربیتی و روان‌شناسی، دانشگاه شهید چمران اهواز، اهواز، ایران.

10.52547/jpap.2021.220808.1022

چکیده

هدف:   تحلیل شبکه اجتماعی دانشگاهی حوزه شبکه دانش به‌منظور ترسیم ساختار فکری و مفهومی این حوزه.
طراحی/ روش‌شناسی/ رویکرد: پژوهش حاضر از نوع کاربردی بوده و از طریق تحلیل شبکه‌های اجتماعی دانشگاهی انجام شده است. برای انجام این پژوهش روش‌های تحلیل عملکرد و نگاشت نقشه علمی حوزه شبکه دانش اجرا شدند. در تحلیل عملکرد از شاخص‌ فراوانی استنادها و برای نگاشت نقشه علمی از شاخص‌های هم‌استنادی، هم‌رخدادی واژه‌های مهم و کتابشناسی زوجی استفاده شد. ابزار انجام تحلیل و نگاشت نقشه علمی در این پژوهش نرم‌افزارVOSviewer  است. پایگاه داده پژوهش مشتمل بر اطلاعات کامل کتابشناختی و استنادی 1748 مقاله علمی، فصل کتاب و مقاله مروری مربوط به حوزه شبکه دانش است که در طول سال‌های 2020 و ماقبل آن در مجموعه هسته پایگاه استنادی وب آو ساینس نمایه شده‌اند.
یافته‌های پژوهش: علاوه‌بر بحث جامع در خصوص مفهوم شبکه دانش، برجسته سازی نسبت شبکه دانش با سایر مفاهیم، شناسایی روندهای پژوهشی، و معرفی آثار و منابع شاخص این حوزه، ساختار فکری حوزه شبکه دانش نیز ترسیم شد.
محدودیت‌ها و پیامدها: حضور کم نشریات منتشر شده داخلی در پایگاه اطلاعاتی وب آو ساینس محدودیت این پژوهش به شمار می‌رود. این محدودیت ترسیم ساختار فکری و مفهومی شبکه اجتماعی دانشگاهی داخل کشور را ناممکن می‌سازد.
پیامدهای عملی: شبکه دانش از موضوعات پرکاربرد در حوزه‌های مختلف است. با توجه به نقش آن در نوآوری، اشتراک دانش، ارتقای همکاری، انتقال تکنولوژی و ... لازم است توجه بیشتری به این حوزه صورت پذیرد. این مطالعه راهنمای مناسبی برای این منظور به شمار می‌رود.
ابتکار یا ارزش مقاله: بر اساس جستجوهای انجام شده این مقاله نخستین پژوهشی است که به ترسیم ساختار فکری و مفهومی حوزه شبکه دانش پرداخته است.

کلیدواژه‌ها


عنوان مقاله [English]

Analyzing the Academic Social Networks of Knowledge Network Field: relations, trends and clusters

نویسندگان [English]

  • Abdol Hossein Farajpahlou 1
  • Shahnaz Khademizadeh 1
  • Gholamreza Heidari 2
  • Mohammad Akbari mahallekolaei 3
1 Professor in Knowledge and Information Science, Faculty of Education Sciences & Psychology , Shahid Chamran University of Ahvaz, Ahvaz, Iran
2 Associate Professor, Knowledge & Information Science, Faculty of Social Sciences, Razi University of Kermanshah, Kermanshah, Iran.
3 Ph.D. Candidate, Knowledge and Information Science, Faculty of Education Sciences & Psychology, Shahid Chamran University of Ahvaz, Ahvaz, Iran.
چکیده [English]

Purpose:  Analyzing the Academic social networks of Knowledge Network field for drawing the intellectual and conceptual structure of this field.
Design/ Methodology/ Approach: This research is applied research that has been done by academic social network analysis. performance analysis and science mapping methods are used to perform this research. in performance analysis, the index of frequency of citations was used and for science mapping uses Co-citation, Bibliographic coupling and Co-occurrence of keywords. We use VOSviewer for analyzing data. In this research, 1748 Article, Book chapter and Review of Knowledge Network field that indexed before 2021 in Web of Science Core Collection were analyzed.
Research Findings: In addition to a comprehensive discussion on the concept of knowledge network, highlighting the relationship between knowledge network and other concepts, identifying research trends, and introducing significant works and resources in this field, the intellectual structure of knowledge network field was also drawn.
Limitations & Consequences: The low presence of Iranian publications in the Web of Science database is a limitation of this research. This limitation makes it impossible to drawing the intellectual and conceptual structure of the university social network within the country.
Practical Consequences: Knowledge Network has been applied in many areas and according to its role in Innovation, knowledge sharing, collaboration promotion, technology transfer, and etc. more attention to this field are needed. This study is a good guide for this purpose.
Innovation or value of the Article: According to searches, this article is the first research that has drawn the intellectual and conceptual structure of the Knowledge Network field.

کلیدواژه‌ها [English]

  • Knowledge Network
  • Bibliometric Analysis
  • Academic social network
  • intellectual structure
  1.  

    1. Bourouni, A., Noori, S., & Jafari, M. (2014). Organizational groupings and performance in project-based organizations. Aslib Journal of Information Management.
    2. Contractor, N., & Green, H. D. (2007, May). Cyberinfrastructure knowledge networks on the web a recommender system for locating resources in a knowledge network. In Proceedings of the 8th annual international conference on Digital government research: bridging disciplines & domains (pp. 256-257). https://dl.acm.org/doi/abs/10.5555/1248460.1248507
    3. Dahesh, M. B., Tabarsa, G., Zandieh, M., & Hamidizadeh, M. (2020, September). Reviewing the intellectual structure and evolution of the innovation systems approach: A social network analysis. Technology in Society, 63, 101399.
    4. de Vasconcelos Gomes, L. A., Facin, A. L. F., Salerno, M. S., & Ikenami, R. K. (2018). Unpacking the innovation ecosystem construct: Evolution, gaps and trends. Technological Forecasting and Social Change136, 30-48.
    5. Enkel, E. (2005). Management von Wissen durch Wissensnetzwerke. Erfolgsfaktoren und Beispiele, Deutscher Universitats-Verlag Gabler, Wiesbaden.
    6. Gaviria-Marin, M., Merigó, J. M., & Baier-Fuentes, H. (2019). Knowledge management: A global examination based on bibliometric analysis. Technological Forecasting and Social Change140, 194-220.
    7. González-Valiente, C. L., Santos, M. L., & Arencibia-Jorge, R. (2019). Evolution of the Socio-cognitive Structure of Knowledge Management (1986–2015): An Author Co-citation Analysis. Journal of Data and Information Science4(2), 36-55.
    8. Heidari, G. (2009), Bibliography. In Osareh et al., From Bibliometrics to Webometrics: An Analysis of Principles, Perspectives, Rules, and Indicators, Tehran: ketabdar (in Persian)
    9. Hodaei, M., Alvani, S.M., Yazdani, H.R., Zarei Matin, H. (2020). Coopetitive (Cooperation and Competition) Advantage in Public Organizations: Synergy of People and Process. Journal of Public Administration Perspective, 11(2), 15-33. (in Persian)
    10. Kaats, E., & Opheij, W. (2013). Creating conditions for promising collaboration: Alliances, networks, chains, strategic partnerships. Springer Science & Business Media.
    11. Khasseh, A. A., & Mokhtarpour, R. (2016). Tracing the historical origins of knowledge management issues through referenced publication years spectroscopy (RPYS). Journal of Knowledge Management.
    12. Kong, X., Shi, Y., Yu, S., Liu, J., & Xia, F. (2019). Academic social networks: Modeling, analysis, mining and applications. Journal of Network and Computer Applications132, 86-103.
    13. Loebbecke، ، & Angehrn، A. (2011). Knowledge management under coopetition. In D.G. Schwartz & D. Te’eni (Eds.) ، Encyclopedia of Knowledge Management، Second Edition، (pp.791-803). New York: Information science reference. DOI: 10.4018/978-1-59904-931-1.ch081.
    14. McIver, D., & Lepisto, D. A. (2017). Effects of knowledge management on unit performance: examining the moderating role of tacitness and learnability. Journal of Knowledge Management, Vol. 21 Issue: 4, pp.796-816, https:// doi.org/10.1108/JKM-08-2016-0347
    15. Naim, M. F., & Lenka, U. (2017) "Linking knowledge sharing, competency development, and affective commitment: evidence from Indian Gen Y employees", Journal of Knowledge Management, Vol. 21 Issue: 4, pp.885-906, https://doi.org/10.1108/JKM-08-2016-0334
    16. Pugh, K., & Prusak, L. (2013). Designing effective knowledge networks. MIT Sloan Management Review, 55(1), 79.
    17. Qiu, J. & Lv, H. (2014), "An overview of knowledge management research viewed through the web of science (1993-2012)", Aslib Journal of Information Management, Vol. 66 No. 4, pp. 424-442. https://doi-org.ezp3.semantak.com/10.1108/AJIM-12-2013-0133
    18. RahmanSeresht, H. & Farzaneh H. J. (2017). Facilitate collaboration and sharing of inter-organizational knowledge through inter-organizational trust. Public Administration Perspective, 8 (2), 15-35. (in Persian)
    19. Ramy, A., Floody, J., Ragab, M. A., & Arisha, A. (2018). A scientometric analysis of Knowledge Management Research and Practice literature: 2003–2015. Knowledge Management Research & Practice16(1), 66-77.
    20. Serenko, A., Bontis, N., Booker, L., Sadeddin, K., & Hardie, T. (2010). A scientometric analysis of knowledge management and intellectual capital academic literature (1994‐2008). Journal of knowledge management.
    21. Suh, A., & Wagner, C. (2017). How gamification of an enterprise collaboration system increases knowledge contribution: an affordance approach. Journal of Knowledge Management, 21(2), 416-431. https://doi.org/10.1108/JKM-10-2016-0429
    22. Tavallaie, R. & Feili, M. (2016), New Concepts and Applications of Knowledge Management, Tehran: Hatami.(in Persian)
    23. Vier Machado, H. P., & Ganacim Granado Rodrigues Elias, M. L. (2020). Knowledge management: the field's constitution, themes, and research perspectives. TRANSINFORMACAO32.
    24. Zavaraqi, R., Fadaie, G. (2014). Visualizing the scientific network of thermodynamics subject area based on outputs of Iranians scholars of the field indexed in Thomson Reuters Web of Science. Journal of Academic librarianship and Information Research, 48(1), 1-38. (in Persian)
    25. Zupic, I., & Čater, T. (2015). Bibliometric methods in management and organization. Organizational Research Methods18(3), 429-472.
    26. Ahuja, G., Soda, G., & Zaheer, A. (2012). The Genesis and Dynamics of Organizational Networks. Organization Science, 23(2), 434–448. doi:10.1287/orsc.1110.0695
    27. Barabási, A., Jeong, H., Néda, Z., Ravasz, E., Schubert, A., & Vicsek, T. (2002). Evolution of the social network of scientific collaborations. Physica A: Statistical Mechanics and Its Applications, 311(3-4), 590–614. doi:10.1016/s0378-4371(02)00736-7
    28. Bathelt, H., Malmberg, A., & Maskell, P. (2004). Clusters and knowledge: local buzz, global pipelines and the process of knowledge creation. Progress in Human Geography, 28(1), 31–56. doi:10.1191/0309132504ph469oa
    29. Boschma, R. (2005). Proximity and Innovation: A Critical Assessment. Regional Studies, 39(1), 61–74. doi:10.1080/0034340052000320887
    30. Boschma, R. A., & ter Wal, A. L. J. (2007). Knowledge Networks and Innovative Performance in an Industrial District: The Case of a Footwear District in the South of Italy. Industry & Innovation, 14(2), 177–199. doi:10.1080/13662710701253441
    31. Carnabuci, G., & Operti, E. (2013). Where do firms’ recombinant capabilities come from? Intraorganizational networks, knowledge, and firms’ ability to innovate through technological recombination. Strategic Management Journal, 34(13), 1591–1613. doi:10.1002/smj.2084
    32. Giuliani, E. (2007). The selective nature of knowledge networks in clusters: evidence from the wine industry. Journal of Economic Geography, 7(2), 139–168. doi:10.1093/jeg/lbl014
    33. Gulati, R., & Gargiulo, M. (1999). Where Do Interorganizational Networks Come From? American Journal of Sociology, 104(5), 1439–1493. doi:10.1086/210179
    34. Hansen, M. T. (1999). The Search-Transfer Problem: The Role of Weak Ties in Sharing Knowledge across Organization Subunits. Administrative Science Quarterly, 44(1), 82. doi:10.2307/2667032
    35. Inkpen, A. C., & Tsang, E. W. K. (2005). Social Capital, Networks, and Knowledge Transfer. Academy of Management Review, 30(1), 146–165. doi:10.5465/amr.2005.15281445
    36. Newman, M. E. J. (2004). Fast algorithm for detecting community structure in networks. Physical Review E, 69(6). doi:10.1103/physreve.69.066133
    37. Newman, M. E. J., & Girvan, M. (2004). Finding and evaluating community structure in networks. Physical Review E, 69(2). doi:10.1103/physreve.69.026113
    38. Owen-Smith, J., & Powell, W. W. (2004). Knowledge Networks as Channels and Conduits: The Effects of Spillovers in the Boston Biotechnology Community. Organization Science, 15(1), 5–21. doi:10.1287/orsc.1030.0054
    39. Phelps, C., Heidl, R., & Wadhwa, A. (2012). Knowledge, Networks, and Knowledge Networks. Journal of Management, 38(4), 1115–1166. doi:10.1177/0149206311432640
    40. Uzzi, B., & Spiro, J. (2005). Collaboration and Creativity: The Small World Problem. American Journal of Sociology, 111(2), 447–504. doi:10.1086/432782
    41. Wang, C., Rodan, S., Fruin, M., & Xu, X. (2014). Knowledge Networks, Collaboration Networks, and Exploratory Innovation. Academy of Management Journal, 57(2), 484–514. doi:10.5465/amj.2011.0917
    42. Wasserman, S., & Faust, K. (1994). Social network analysis: Methods and applications (Vol. 8). Cambridge university press.
    43. Huggins, R., Prokop, D., & Thompson, P. (2020). Universities and open innovation: The determinants of network centrality. The Journal of Technology Transfer45(3), 718-757. https://doi.org/10.1007/s10961-019-09720-5
    44. Phelps, C., Heidl, R., & Wadhwa, A. (2012). Knowledge, Networks, and Knowledge Networks. Journal of Management, 38(4), 1115–1166. doi:10.1177/0149206311432640
    45. Larrañeta, B., Molina-Morales, F. X., & Herrero, I. (2020). Centrality in networks of geographically proximate firms and competitive capabilities. BRQ Business Research Quarterly23(4), 254-269. https://doi.org/10.1177/2340944420966864
    46. Belso-Martínez, J. A., Mas-Verdu, F., & Chinchilla-Mira, L. (2020). How do interorganizational networks and firm group structures matter for innovation in clusters: Different networks, different results. Journal of Small Business Management58(1), 73-105. https://doi.org/10.1080/00472778.2019.1659673
    47. Belso-Martínez, J. A., Mas-Tur, A., & Roig-Tierno, N. (2017). Synergistic effects and the co-existence of networks in clusters. Entrepreneurship & Regional Development29(1-2), 137-154. https://doi.org/10.1080/08985626.2016.1255429
    48. del-Corte-Lora, V., Vallet-Bellmunt, T., & Molina-Morales, F. X. (2015). Be creative but not so much. Decreasing benefits of creativity in clustered firms. Entrepreneurship & Regional Development, 27(1-2), 1-27. https://doi.org/10.1080/08985626.2014.995722
    49. Belso-Martínez, J. A., Tomás-Miquel, J. V., Expósito-Langa, M., & Mateu-García, R. (2020). Delving into the technical textile phenomenon: networking strategies and innovation in mature clusters. The Journal of The Textile Institute, 111(2), 260-272. https://doi.org/10.1080/00405000.2019.1631638
    50. Maghssudipour, A., Lazzeretti, L., & Capone, F. (2020). The role of multiple ties in knowledge networks: Complementarity in the Montefalco wine cluster. Industrial Marketing Management, 90, 667-678. https://doi.org/10.1016/j.indmarman.2020.03.021
    51. Balland, P. A., Belso-Martínez, J. A., & Morrison, A. (2016). The dynamics of technical and business knowledge networks in industrial clusters: Embeddedness, status, or proximity?. Economic Geography92(1), 35-60. https://doi.org/10.1080/00130095.2015.1094370
    52. Casanueva, C., Castro, I., & Galán, J. L. (2013). Informational networks and innovation in mature industrial clusters. Journal of business research66(5), 603-613. https://doi.org/10.1016/j.jbusres.2012.02.043
    53. Xue, J. (2018). Understanding knowledge networks and knowledge flows in high technology clusters: The role of heterogeneity of knowledge contents. Innovation20(2), 139-163. https://doi.org/10.1080/14479338.2017.1369355
    54. Xue, J., olk, p (2014). Knowledge Networks and Knowledge Flows in Regional Innovation Clusters: An Empirical Study of High Technology Clusters in China In Das, T. K. (Ed.). Strategic alliances for innovation and R&D. IAP.
    55. Juhász, S., & Lengyel, B. (2018). Creation and persistence of ties in cluster knowledge networks. Journal of Economic Geography18(6), 1203-1226. https://doi.org/10.1093/jeg/lbx039
    56. Huggins, R., & Johnston, A. (2010). Knowledge flow and inter-firm networks: The influence of network resources, spatial proximity and firm size. Entrepreneurship & regional development22(5), 457-484. https://doi.org/10.1080/08985620903171350
    57. Dagnino, G.B., Levanti, G., Minà, A. and Picone, P.M. (2015), "Interorganizational network and innovation: a bibliometric study and proposed research agenda", Journal of Business & Industrial Marketing, Vol. 30 No. 3/4, pp. 354-377. https://doi.org/10.1108/JBIM-02-2013-0032
    58. Giuliani, E. (2013). Network dynamics in regional clusters: Evidence from Chile. Research Policy42(8), 1406-1419. https://doi.org/10.1016/j.respol.2013.04.002
    59. Balland, P. A., Boschma, R., & Frenken, K. (2015). Proximity and innovation: From statics to dynamics. Regional Studies49(6), 907-920. https://doi.org/10.1080/00343404.2014.883598
    60. Menzel, M. P. (2015). Interrelating dynamic proximities by bridging, reducing and producing distances. Regional Studies49(11), 1892-1907. https://doi.org/10.1080/00343404.2013.848978
    61. Glückler, J. (2013). Knowledge, networks and space: Connectivity and the problem of non-interactive learning. Regional Studies47(6), 880-894. https://doi.org/10.1080/00343404.2013.779659
    62. Cantner, U., & Graf, H. (2011). 15 Innovation networks: formation, performance and dynamics. Handbook on the economic complexity of technological change366.