Skip to main content
SpringerLink
Log in

Examining the relationship of co-authorship network centrality and gender on academic research performance: the case of chemistry researchers in Pakistan

  • Published:
Scientometrics Aims and scope Submit manuscript

Abstract

This research examines the association of co-authorship network centrality (degree, closeness and betweeness) and the academic research performance of chemistry researchers in Pakistan. Higher centrality in the co-authorship network is hypothesized to be positively related to performance, in terms of academic publication, with gender having a positive moderating effect for female researchers. Using social network analysis, this study examines the bibliometric data (2002–2009) from ISI Web of Science for the co-authorship network of 2,027 Pakistani authors publishing in the field of Chemistry. A non-temporal analysis using node-level regression reports positive impact of degree and closeness and negative impact of betweeness centrality on research performance. Temporal analysis using node-level regression (time 1: 2002–2005; time 2: 2006–2009) confirms the direction of causality and demonstrates the positive association of degree and closeness centrality on research performance. Findings indicate a moderating role of gender on the relationship of both degree and closeness centrality with research performance for Pakistani female authors.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2

Similar content being viewed by others

Notes

  1. The journal Impact Factor is the average number of times articles from the journal published in the past 2 years have been cited in the Journal citation report (JCR) year.

  2. Geodesic paths need not be unique i.e. nodes can be joined by several shortest path of same length. The length d(n i , n j ) however is always well defined, being the length of any one of these paths.

  3. The 5-year journal Impact Factor is the average number of times articles from the journal published in the past five years have been cited in the JCR year.

  4. The p value for each statistic is calculated as the proportion of permutations that yields a statistic as extreme as the one initially produced.

  5. Distributions for degree centrality and betweeness centrality followed highly skewed curves. Distribution for closeness centrality followed normal curve.

References

  • Abbasi, A., Altmann, J., & Hossain, L. (2011). Identifying the effects of co-authorship networks on the performance of scholars: A correlation and regression analysis of performance measures and social network analysis measures. Journal of Informetrics, 5(4), 594–607.

    Article  Google Scholar 

  • Ahuja, G. (2000). Collaboration networks, structural holes, and innovation: A longitudinal study. Administrative Science Quarterly, 45(3), 425–455.

    Article  MathSciNet  Google Scholar 

  • Ahuja, G., & Katila, R. (2004). Where do resources come from? The role of idiosyncratic situations. Strategic Management Journal, 25(8/9), 887–907.

    Article  Google Scholar 

  • Albrecht, S. L. (1983). Informal interaction patterns of professional women. In J. R. Gordon (Ed.), A diagnostic approach to organizational behavior (pp. 287–290). Boston: Allyn & Bacon.

    Google Scholar 

  • Arora, A., & Gambardella, Ae. (1990). Complementarity and external linkages: The strategies of the large firms in biotechnology. Journal of Industrial Economics, 34(4), 361–379.

    Google Scholar 

  • Avital, M., & Collopy, F. (2001). Assessing research performance: Implications for selection and motivation. Sprouts: working papers on information environments, systems and organizations. http://sprouts.aisnet.org/1-14. Accessed 10 March 2010.

  • Berg, S., Duncan, J., & Friedman, P. (1982). Joint venture strategies and corporate innovation. Cambridge, MA: Oelgeschiager, Gunn & Hain.

  • Bhardwaj, A., Qureshi, I., & Lee, S. H. (2008). A study of race/ethnicity as a moderator of the relationship between social capital and satisfaction. Academy of management annual meeting. Anaheim, California.

  • Bolland, J. M. (1998). Sorting out centrality: An analysis of the performance of four centrality models in real and simulated networks. Social Networks, 10, 233–253.

    Article  MathSciNet  Google Scholar 

  • Borgatti, S. P. (1995). Centrality and AIDS. Connections, 18(1), 112–114.

    Google Scholar 

  • Borgatti, S. P., Everett, M. G., & Freeman, L. C. (2002). UCINET for windows: Software for social network analysis. Harvard, MA: Analytic Technologies.

    Google Scholar 

  • Brass, D. J. (1984). Being in the right place: A structural analysis of individual influence in an organization. Administrative Science Quarterly, 29, 518–539.

    Article  Google Scholar 

  • Brass, D. J. (1985). Men’s and women’s networks: A study of interaction patterns and influence in an organization. Academy of Management Journal, 28, 327–343.

    Article  MATH  Google Scholar 

  • Burt, R. S. (1992). Structural holes—The social structure of competition. Cambridge, MA: Harvard University Press.

    Google Scholar 

  • Burt, R. S. (1998). The gender of social capital. Rationality and Society, 10, 15–46.

    Article  Google Scholar 

  • Burt, R. S. (2005). Brokerage and closure: The social capital of structural holes. Oxford: Oxford University Press.

    Google Scholar 

  • Cartwright, V. A., & McGhee, C. N. (2005). Ophthalmology and vision science research part 1: Understanding and using journal impact factors and citation indices. Journal of Cataract and Refractive Surgery, 31, 1999–2007.

    Article  Google Scholar 

  • Cheek, J., Garnham, B., & Quan, J. (2006). What’s in a number? Issues in providing evidence of impact and quality of research(ers). Qualitative Health Research, 16, 423–435.

    Article  Google Scholar 

  • Coleman, J. S. (1990). Foundations of social theory. Cambridge, MA: Belknap Press of Harvard University Press.

    Google Scholar 

  • C-Zurián, J., Alcaide, G. G., J-Zurián, F. J., Benavent, & Miguel-Dasit, A. (2007). Coauthorship Networks and Institutional Collaboration in Revista Española de CardiologÍa Publications. Revista Espanola de Cardiologia, 60(2), 117–130.

    Google Scholar 

  • Department of Economic and Social Affairs. (2010). The World’s Women. New York: United Nations.

    Google Scholar 

  • Eaton, J. P., Ward, J. C., Kumar, A., & Peter, H. R. (1999). Structural analysis of co-author relationships and author productivity in selected outlets for consumer behavior research. Journal of Consumer Psychology, 8(1), 39–59.

    Article  Google Scholar 

  • Fairhurst, G. T., & Snavely, B. K. (1983). A test of the social isolation of male tokens. Academy of Management Journal, 26, 353–361.

    Article  Google Scholar 

  • Faust, K. (1997). Centrality in affiliation networks. Social Networks, 19, 157–191.

    Article  Google Scholar 

  • Fleming, L., & Sorenson, O. (2001). Technology as a complex adaptive system: Evidence from patent data. Research Policy, 30, 1019–1039.

    Article  Google Scholar 

  • Freeman, L. C. (1977). A set of measures of centrality based on betweenness. Sociometry, 40(1), 35–41.

    Article  Google Scholar 

  • Freeman, L. C. (1979). Centrality in social networks. Conceptual clarification. Social Networks, 1, 215–239.

    Article  Google Scholar 

  • Gilsing, V., Nooteboomb, B., Vanhaverbekec, W., Duystersd, G., & Oorda, Av. (2008). Network embeddedness and the exploration of novel technologies: Technological distance, betweenness centrality and density. Research Policy, 37, 1717–1731.

    Article  Google Scholar 

  • Gossart, C., & Özman, M. (2009). Co-authorship networks in social sciences: The case of Turkey. Scientometrics, 78(2), 323–345.

    Article  Google Scholar 

  • Granovetter, M. (1985). Economic action and social structure: The problem of embeddedness. American Journal of Sociology, 91, 481–510.

    Article  Google Scholar 

  • Gulati, R., & Martin, G. (1999). Where do interorganizational networks come from? American Journal of Sociology, 104(5), 473–506.

    Article  Google Scholar 

  • Guns, R., Liu, Y. X., & Mahbuba, D. (2011). Q-measures and betweenness centrality in a collaboration network: A case study of the field of informetrics. Scientometrics, 87(1), 133–147.

    Article  Google Scholar 

  • Hanneman, R. A., & Riddle, M. (2005). Introduction to social network methods. Riverside CA: Analytictech.com.

    Google Scholar 

  • Hendrick, S. S. (1981). Why women don’t succeed. National Business Employment Weekly, 40, 9–11.

    Google Scholar 

  • Higher Education Commission, Pakistan. http://beta.hec.gov.pk/InFocus/Pages/HEC_Report_for_2002-2008.aspx. Accessed 17 March 2012.

  • Higher Education Commission, Pakistan. http://beta.hec.gov.pk/Pages/HECMain.aspx. Accessed 17 March 2012.

  • Ibarra, H. (1993). Network centrality, power and innovation involvement: Determinants of technical and administrative roles. Academy of Management Journal, 36, 471–501.

    Article  Google Scholar 

  • Ibarra, H. (1997). Paving an alternative route, gender differences in managerial networks. Social Psychology Quarterly, 60, 91–102.

    Article  Google Scholar 

  • Jansen, D., Gortz, R., & Heidler, R. (2010). Knowledge production and the structure of collaboration networks in two scientific fields. Scientometrics, 83(1), 219–241.

    Google Scholar 

  • Kang, H., Getoor, L., Shneiderman, B., Bilgic, M., & Licamele, L. (2008). Interactive entity resolution in relational data: A visual analytic tool and its evaluation. IEEE Transactions on Visualization and Computer Graphics, 14(5), 999–1014.

    Article  Google Scholar 

  • Kanter, R. M. (1977). Men and women of the corporation. New York: Basic Books.

    Google Scholar 

  • Kay, F., & Hagan, J. (1999). Cultivating clients in the competition for partnership: Gender and the organizational restructuring of law firms in the 1990s. Law and Society Review, 33, 517–555.

    Article  Google Scholar 

  • Kram, K. E. (1988). Mentoring at work: Developmental relationships in organizational life. New York: University Press of America.

    Google Scholar 

  • Kretschmer, H., & Aguillo, I. F. (2005). New indicators for gender studies in web networks. Information Processing and Management, 41(6), 1481–1494.

    Article  Google Scholar 

  • Kwon, K. S., Park, H. W., So, M., & Leydesdorff, L. (2012). Has globalization strengthened South Korea’s national research system? National and international dynamics of the triple helix of scientific co-authorship relationships in South Korea. Scientometrics, 90(1), 163–176.

    Article  Google Scholar 

  • Leydesdorff, L., & Sun, Y. (2009). National and international dimensions of the triple helix in Japan: University–industry–government versus international co-authorship relations. Journal of the American Society for Information Science and Technology, 60(4), 778–788.

    Article  Google Scholar 

  • Liao, C. H. (2011). How to improve research quality? Examining the impacts of collaboration intensity and member diversity in collaboration networks. Scientometrics, 86(3), 741–761.

    Article  Google Scholar 

  • Marsden, P. V. (2002). Egocentric and sociometric measures of network centrality. Social Networks, 24, 407–422.

    Article  Google Scholar 

  • Mcfadyen, A. M., & Cannella, J. A. (2004). Social capital and knowledge creation: Diminishing returns of the number and strength of exchange relationships. Academy of Management Journal, 47(5), 735–746.

    Article  Google Scholar 

  • McFadyen, A. M., Semadeni, M., & Cannella, A. A, Jr. (2009). The value of strong ties to disconnected others: Examining knowledge creation in biomedicine. Organization Science, 20(3), 552–564.

    Article  Google Scholar 

  • Meho, L. I. (2007). The rise and rise of citation analysis. Physics World, 20, 32–36.

    Google Scholar 

  • Mehra, A., Kilduff, M., & Brass, D. (2001). The social networks of high and low-self monitors: Implications for workplace performance. Administrative Science Quarterly, 46, 121–146.

    Article  Google Scholar 

  • Nagpaul, P. S. (2002). Visualizing cooperation networks of elite institutions in India. Scientometrics, 54(2), 213–228.

    Article  Google Scholar 

  • Nahapiet, J., & Ghoshal, S. (1998). Social capital, intellectual capital, and the organizational advantage. Academy of Management Review, 23, 242–266.

    Google Scholar 

  • Newman, M. E. (2001a). Scientific collaboration networks. II. Shortest paths, weighted networks, and centrality. Physical Review E, 64(1), 016132.

    Google Scholar 

  • Newman, M. E. (2001b). The structure of scientific collaboration networks. PNAS, 98, 404–409.

    Article  MATH  Google Scholar 

  • Newman, M. E. (2004). Co authorship networks and patterns of scientific collaboration. PNAS, 101, 5200–5205.

    Article  Google Scholar 

  • Newman, M. E. (2010). Networks: An introduction. Oxford University Press.

  • Oh, W., Choi, Jn, & Kim, K. (2005). Co-authorship dynamics and knowledge capital: The patterns of cross-disciplinary collaboration in information systems research. Journal of Management Information Systems, 22(3), 265–292.

    Google Scholar 

  • Perry-Smith, J. E., & Shalley, C. E. (2003). The social side of creativity: A static and dynamic social network perspective. The Academy of Management Review, 28(1), 89–106.

    Google Scholar 

  • Pike, T. W. (2010). Collaboration networks and scientific impact among behavioral ecologists. Behavioral Ecology, 21(2), 431–435.

    Article  Google Scholar 

  • Ragins, B. R., & Sundstrom, E. (1989). Gender and power in organizations: A longitudinal perspective. Psychological Bulletin, 105, 51–88.

    Article  Google Scholar 

  • Richardson, G. B. (1972). The Organisation of Industry. The Economic Journal, 82(327), 883–896.

    Article  Google Scholar 

  • Sci2 Team. (2009). Science of Science (Sci2) Tool. Indiana University and SciTech Strategies. http://sci2.cns.iu.edu. Accessed 5 May 2011.

  • Scott, J. (1991). Social network analysis: A handbook. Sage.

  • Seron, C., & Ferris, K. (1995). Negotiating professionalism: The gendered social capital of flexible time. Work and Occupations, 22, 22–47.

    Article  Google Scholar 

  • Smalheiser, N. R., & Torvik, V. I. (2009). Author name disambiguation. Annual Review of Information Science and Technology, 43, 287–313.

    Article  Google Scholar 

  • Sparrowe, T., Liden, R., Robert, G., Wayne, J. S., & Kraimer, M. L. (2001). Social networks and the performance of individuals and groups. Academy of Management Journal, 44(2), 316–325.

    Article  Google Scholar 

  • Strotmann, A., Zhao, D., & Bubela, T. (2009). Author name disambiguation for collaboration network analysis and visualization. Proceedings of the American Society for Information Science and Technology, 46(1), 1–20.

    Google Scholar 

  • Tharenou, P. (1999). Gender differences in advancing to the top. International Journal of Management Reviews, 1, 111–132.

    Article  Google Scholar 

  • Tsai, W. (2001). Knowledge transfer in intraorganizational networks: Effects of network position and absorptive capacity on business unit innovation and performance. Academy of Management Journal, 44(5), 996–1004.

    Article  Google Scholar 

  • Tsai, W., & Ghoshal, S. (1998). Social capital and value creation: The role of intrafirm networks. Academy of Management Journal, 41, 464–476.

    Article  Google Scholar 

  • Valente, T. W., & Foreman, R. (1998). Integration and radiality: Measuring the extent of an individual’s connectedness and reachability in a network. Social Networks, 20, 89–109.

    Article  Google Scholar 

  • Valente, T. W., Loronges, K., Lakon, C., & Costenbader, E. (2008). How correlated are network centrality measures? Connections, 28(1), 16–26.

    Google Scholar 

  • Wagner, C. S. (2006). International collaboration in science and technology: Promises and pitfalls. In L. Box & R. Engelhard (Eds.), Science and technology policy for development: Dialogues at the interface. London: Anthem Press.

    Google Scholar 

  • Wasserman, S., & Faust, K. (1994). Social networks analysis: Methods and applications. Cambridge: Cambridge University Press.

    Book  Google Scholar 

  • Yan, E., & Ding, Y. (2009). Applying centrality measures to impact analysis: A coauthorship network analysis. Journal of the American Society for Information Science and Technology, 60(10), 2107–2118.

    Article  Google Scholar 

  • Yang, K.-s. (2007). Firms’ network position, industry hierarchy position and innovation and an additional examination on structural equivalent block models and between-sector position. Academy of management annual meeting. Philadelphia, PA.

  • Yousefi-Nooraie, R., Akbari-Kamrani, M., Hanneman, R. A., & Etemadi, A. (2008). Association between co-authorship network and scientific productivity and impact indicators in academic medical research centers: A case study in Iran. Health Research Policy and Systems, 6(9). doi:10.1186/1478-4505-6-9.

  • Zheng, W. (2008). A social capital perspective of innovation from individuals to nations: Where is empirical literature directing us? Volume 10 Issue 4. International Journal of Management Reviews, 10(4), 1–39.

    Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Institute of Management Sciences (IMS), University of Balochistan, Sariab Road, Quetta, Pakistan

    Kamal Badar

  2. Department of Educational Leadership & Foundations, Brigham Young University, 306 MCKB, Provo, UT, 84601, USA

    Julie M. Hite

  3. School of Management, Asian Institute of Technology, P.O. Box 4, Klong Luang, Pathumthani, 12120, Thailand

    Kamal Badar & Yuosre F. Badir

Authors
  1. Kamal Badar
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Julie M. Hite
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Yuosre F. Badir
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Kamal Badar.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Badar, K., Hite, J.M. & Badir, Y.F. Examining the relationship of co-authorship network centrality and gender on academic research performance: the case of chemistry researchers in Pakistan. Scientometrics 94, 755–775 (2013). https://doi.org/10.1007/s11192-012-0764-z

Download citation

  • Received:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11192-012-0764-z

Keywords

Search

Navigation