, Volume 105, Issue 2, pp 959–972 | Cite as

Information technology management domain: emerging themes and keyword analysis

  • Gohar Feroz Khan
  • Jacob Wood


By employing the social network analysis technique, this study decomposed author and title keyword networks of the information technology management domain formed by 351 outlets, 914 institutions, 64 countries, 1913 authors, and thousands of keywords. The network and ego level properties—such as, degree centralities, density, components, and degree distribution—suggest that the keyword network exhibits power law distribution: a few popular keywords or themes are frequently used by follow-on studies. The study sheds light on the emerging and fading themes in the domain. In light of the analysis some important implications are discussed.


Information technology management domain Social network analysis Emerging themes Keyword analysis 



The Research was supported by a 2015 Korea University of Technology and Education Research Fund.


  1. Barabási, A. L., 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.MathSciNetCrossRefzbMATHGoogle Scholar
  2. Benamati, J. S., Lederer, A. L., & Singh, M. (1997). Changing information technology and information technology management. Information & Management, 31(5), 275–288. doi: 10.1016/S0378-7206(96)01091-9.CrossRefGoogle Scholar
  3. Bloch, M., & Hoyos-Gomez, A. (2009). How CIOs should think about business value. McKinsey Quarterly, March.Google Scholar
  4. Carter, C. R., Leuschner, R., & Rogers, D. S. (2007). A social network analysis of the journal of supply chain management: Knowledge generation, knowledge diffusion and thought leadership. The Journal of Supply Chain Management, 43(2), 15–28.CrossRefGoogle Scholar
  5. Chen, C. (2006). Citespace II: Detecting and visualizing emerging trends and transient patterns in scientific literature. Journal of American Society for Information science and Technology, 57(3), 359–377.CrossRefGoogle Scholar
  6. Chen, C., Chen, Y., Horowitz, M., Hou, H., Liu, Z., & Pellegrino, D. (2009). Towards an explanatory and computational theory of scientific discovery. Journal of Informetrics, 3(3), 191–209.CrossRefGoogle Scholar
  7. Choi, J., Yi, S., & Lee, K. C. (2011). Analysis of keyword networks in MIS research and implications for predicting knowledge evolution. Information & Management, 48(8), 371–381. doi: 10.1016/ Scholar
  8. Cross, R., Parker, A., Prusak, L., & Borgatti, S. (2001). Knowing what we know: Supporting knowledge creation and sharing in social networks. Organizational Dynamics, 30(2), 100–120.CrossRefGoogle Scholar
  9. Earl, M. J., & Fenny, D. F. (1994). Is your CIO adding value? Sloane Management Review, 35(3), 11–20.Google Scholar
  10. Fink, L., & Neumann, S. (2007). Getting agility through IT personnel capabilities: The mediating role of IT infrastructure capabilities. Journal of AIS, 8(8), 440–462.Google Scholar
  11. Fonstad, N. O., & Subramani, M. (2009). Building enterprise alignment: A case study. MIS Quarterly Executive, 8(1), 31–41.Google Scholar
  12. Guo, H., Weingart, S., & Börner, K. (2011). Mixed-indicators model for identifying emerging research areas. Scientometrics, 89(1), 421–435. doi: 10.1007/s11192-011-0433-7.CrossRefGoogle Scholar
  13. Hanneman, R. A., & Riddle, M. (2005). Introduction to social network methods. Riverside, CA: University of California. Published in digital form at
  14. Hassan, N. R. (2009). Using social network analysis to measure IT-enabled business process performance. Information Systems Management, 26(1), 61–76.CrossRefGoogle Scholar
  15. Huang, C. P. (2009). Bibliometric analysis of obstructive sleep apnea research trends. Journal of the Chinese Medical Association, 72(3), 117–123.CrossRefGoogle Scholar
  16. Huang, L. L. (2012). The impact of IT management sophistication on perceived IT importance in strategic alignment. Journal of Computer Information Systems (Winter), 53(2), 50–64.Google Scholar
  17. Jeffery, M., & Leliveld, I. (2004). Best practices in IT portfolio management. MIT Sloan Manage Review, 45, 41–49.Google Scholar
  18. Khan, G. F., & Park, H. W. (2013). The e-government research domain: A triple helix network analysis of collaboration at the regional, country, and institutional levels. Government Information Quarterly, 30, 182–193.CrossRefGoogle Scholar
  19. Kleinberg, J. (2003). Bursty and hierarchical structure in streams. Data Mining and Knowledge Discovery, 7(4), 373–397.MathSciNetCrossRefGoogle Scholar
  20. Krystallis, A., Ormond, R., & Christensen, K. V. (2011). Patterns and regularities in the European marketing academic community: A social network analysis of the EMAC annual conferences 20002010. Paper presented at the European Marketing Academy: Conference proceedings of the 2011 EMAC conference, Ljubliana, Slovenia.Google Scholar
  21. Leydesdorff, L. (2006). The knowledge-based economy: Modeled, measured, simulated. Boca Raton, FL: Universal Publishers.Google Scholar
  22. Levina, O., & Bobrik, A. (2013). Using social network analysis to measure information management performance introduced by business process optimization. In Paper presented at the proceedings of the 21st European conference on information systems.Google Scholar
  23. Liu, X., Bollen, J., Nelson, M. L., & Van de Sompel, H. (2005). Co-authorship networks in the digital library research community. Information Processing and Management, 41(6), 1462–1480. doi: 10.1016/j.ipm.2005.03.012.CrossRefGoogle Scholar
  24. Lucas, H. C. (1999). Information technology and the productivity paradox. New York: Oxford University Press.Google Scholar
  25. Luftman, J. (2000). Assessing business—IT alignment maturity. Communication of the AIS, 4, 1–50.Google Scholar
  26. Luftman, J. N. (2003). Assessing IT-Business alignment. Information Systems Management, 20(4), 9–15.CrossRefGoogle Scholar
  27. Mane, K., & Borner, K. (2004). Mapping topics and topic bursts in PNAS. Paper presented at the proceedings of the National Academy of Sciences of the United States of Americas (PNAS).Google Scholar
  28. Marsden, P. V. (2008). Network data and measurement (Vol. 1). London: Sage.Google Scholar
  29. Marshall, J., & Heffes, E. M. (2007). Most directors fail to link IT with strategy. Technology, July, August.Google Scholar
  30. Martino, F., & Spoto, A. (2006). Social network analysis: A brief theoretical review and further perspectives in the study of information technology. PsychNology Journal, 4(1), 53–86.Google Scholar
  31. Meyer, M., Lorscheid, I., & Troitzsch, K. G. (2009). The development of social simulation as reflected in the first ten years of JASSS: A citation and co-citation analysis. Journal of Artifical Societies and Social Simulation, 12(4), 2009.Google Scholar
  32. Newman, M. E. J. (2004). Coauthorship networks and patterns of scientific collaboration. Proceedings of the National Academy of Sciences, 101(1), 5200–5205.CrossRefGoogle Scholar
  33. Ord, T. J., Martins, E. P., Thakur, S., Mane, K. K., & Börner, K. (2005). Trends in animal behaviour research (1968–2002): Ethoinformatics and the mining of library databases. Animal Behaviour, 69(6), 1399–1413. doi: 10.1016/j.anbehav.2004.08.020.CrossRefGoogle Scholar
  34. Price, D. S. (1965). Networks of scientific papers. Science, 149, 510–515.CrossRefGoogle Scholar
  35. Sci2Team. (2009). Science of Science (Sci2) TooI Indiana University and SciTech Strategies.
  36. Swar, B., & Khan, G. (2014). Mapping ICT knowledge infrastructure in South Asia. Scientometrics, 99(1), 117–137. doi: 10.1007/s11192-013-1099-0.CrossRefGoogle Scholar
  37. Van Eck, N. J., & Waltman, L. (2010). Software survey: VOSviewer, a computer program for bibliometric mapping. Scientometrics, 84(2), 523–538.CrossRefGoogle Scholar
  38. Vidgen, R., Henneberg, S., & Naude, P. (2007). What sort of community is the European Conference on Information Systems? A social network analysis 1993–2005. European Journal of Information Systems, 16(1), 5–19.Google Scholar
  39. Wasserman, S., & Faust, K. (1994). Social network analysis: Methods and applications. Cambridge: Cambridge University Press.CrossRefzbMATHGoogle Scholar
  40. Whitley, E. A., & Galliers, R. D. (2007). An alternative perspective on citation classics: Evidence from the first 10 years of the European Conference on Information Systems. Information and Management, 44(5), 441–455.CrossRefGoogle Scholar
  41. Wilkin, C. (2012). The role of IT governance practices in creating business value in SMEs. Journal of Organizational and End User Computing, 24(2), 1–17. doi: 10.4018/joeuc.2012040101.MathSciNetCrossRefGoogle Scholar
  42. Yoon, B., & Park, Y. (2005). A systematic approach for identifying technology opportunities: Keyword-based morphology analysis. Technological Forecasting and Social Change, 72(2), 145–160.CrossRefGoogle Scholar
  43. Zinkhan, G. M., Roth, M. S., & Saxton, M. J. (1992). Knowledge development and scientific status in consumer-behavior research: A social exchange perspective. Journal of Consumer Research, 19, 282–291.CrossRefGoogle Scholar

Copyright information

© Akadémiai Kiadó, Budapest, Hungary 2015

Authors and Affiliations

  1. 1.Korea University of Technology & EducationCheonan CitySouth Korea

Personalised recommendations