, Volume 105, Issue 3, pp 1553–1576 | Cite as

Knowledge network centrality, formal rank and research performance: evidence for curvilinear and interaction effects



This study explores the curvilinear (inverted U-shaped) association of three classical dimension of co-authorship network centrality, degree, closeness and betweenness and the research performance in terms of g-index, of authors embedded in a co-authorship network, considering formal rank of the authors as a moderator between network centrality and research performance. We use publication data from ISI Web of Science (from years 2002–2009), citation data using Publish or Perish software for years 2010–2013 and CV’s of faculty members. Using social network analysis techniques and Poisson regression, we explore our research questions in a domestic co-authorship network of 203 faculty members publishing in Chemistry and it’s sub-fields within a developing country, Pakistan. Our results reveal the curvilinear (inverted U-shaped) association of direct and distant co-authorship ties (degree centrality) with research performance with formal rank having a positive moderating role for lower ranked faculty.


Co-authorship network Research performance Network centrality Formal rank Social network analysis Curvilinear relationship 


  1. 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.CrossRefGoogle Scholar
  2. Ahuja, G. (2000). Collaboration networks, structural holes, and innovation: A longitudinal study. Administrative Science Quarterly, 45(3), 425–455.MathSciNetCrossRefGoogle Scholar
  3. Ahuja, G., & Katila, R. (2004). Where do resources come from? The role of idiosyncratic situations. Strategic Management Journal, 25(8/9), 887–907.CrossRefGoogle Scholar
  4. Amabile, T. M., Conti, R., Coon, H., Lazenby, J., & Herron, M. (1996). Assessing the work environment for creativity. Academy of Management Journal, 39(5), 1154–1184.CrossRefGoogle Scholar
  5. Andrews, R. (2010). Organizational social capital, structure and performance. Human Relations, 63(5), 583–608.CrossRefGoogle Scholar
  6. Arensbergen, P., Weijden, I., & Besselaar, P. (2012). Gender differences in scientific productivity: A persisting phenomenon? Scientometrics, 93(3), 857–868.CrossRefGoogle Scholar
  7. Avkiran, N. K. (1997). Models of retail performance for bank branches: Predicting the level of key business drivers. International Journal of Bank Marketing, 15(6), 224–237.CrossRefGoogle Scholar
  8. Badar, K., Hite, J. M., & Badir, Y. F. (2013). Examining the relationship of co-authorship network centrality and gender on academic research performance: The case of chemistry researchers in Pakistan. Scientometrics, 94(2), 755–775.CrossRefGoogle Scholar
  9. Badar, K., Hite, J. M., & Badir, Y. F. (2014). The moderating role of academic age and insitutional sector on the relationship between co-authorship network centrality and academic research performance. Aslib Journal of Information Management, 66(1), 38–53.CrossRefGoogle Scholar
  10. Barrios, M., Villarroya, A., & Borrego, A. (2013). Scientific production in psychology: A gender analysis. Scientometrics, 95(1), 15–23.CrossRefGoogle Scholar
  11. Batista, P. D., Campiteli, M. G., Kinouchi, O., & Martinez, A. S. (2006). It is possible to compare researchers with different scientific interests? Scientometrics, 68(1), 179–189.CrossRefGoogle Scholar
  12. Bhardwaj, A., Qureshi, I., & Lee S. H. (2008). A study of race/ethnicity as a moderator of the relationship between social capital and satisfaction. Paper presented at the academy of management annual meeting, Anaheim, CA.Google Scholar
  13. Boissevain, J. (1974). Friends of friends: Networks, manipulators and coalitions. New York: St. Martin’s Press.Google Scholar
  14. Bordons, M., Aparicio, J., González-Albo, B., & Díaz-Faes, A. A. (2015). The relationship between the research performance of scientists and their position in co-authorship networks in three fields. Journal of Informetrics, 9, 135–144.CrossRefGoogle Scholar
  15. Borgatti, S. P. (1995). Centrality and AIDS. Connections, 18(1), 112–114.Google Scholar
  16. Borgatti, S. P., Everett, M. G., & Freeman, L. C. (2002). UCINET for windows: Software for social network analysis. Harvard, MA: Analytic Technologies.Google Scholar
  17. Borrego, A., Barrios, M., Villarroya, A., & Olle, C. (2010). Scientific output and impact of postdoctoral scientists: A gender perspective. Scientometrics, 83(1), 93–101.CrossRefGoogle Scholar
  18. Burt, R. S. (1998). The gender of social capital. Rationality and Society, 10(1), 5–46.MathSciNetCrossRefGoogle Scholar
  19. Burt, R. S. (2005). Brokerage and closure: The social capital of structural holes. Oxford: Oxford University Press.Google Scholar
  20. Costas, R., & Bordons, M. (2007). The h-index: Advantages, limitations and its relation with other bibliometric indicators at the micro-level. Journal of Informetrics, 1(3), 193–203.CrossRefGoogle Scholar
  21. De-Cohen, D. C. (2003). Diversification in Argentine higher education: Dimensions and impact of private sector growth. Higher Education, 46(1), 1–35.CrossRefGoogle Scholar
  22. 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.CrossRefGoogle Scholar
  23. Egghe, L. (2006). Theory and practise of the g-index. Scientometrics, 69(1), 131–152.MathSciNetCrossRefGoogle Scholar
  24. Fischbach, K., Putzke, J., & Schoder, D. (2011). Co-authorship networks in electronic markets research. Electronic Markets, 21(1), 19–40.CrossRefGoogle Scholar
  25. Fleming, L., & Sorenson, O. (2001). Technology as a complex adaptive system: Evidence from patent data. Research Policy, 30(7), 1019–1039.CrossRefGoogle Scholar
  26. Freeman, L. C. (1979). Centrality in social networks. Conceptual clarification. Social Networks, 1, 215–239.CrossRefGoogle Scholar
  27. Gargiulo, M., Ertug, G., & Galunic, C. (2009). The two faces on control: Network closure and individual performance among knowledge workers. Administrative Science Quarterly, 54(2), 299–333.CrossRefGoogle Scholar
  28. Gilsing, V., Nooteboomb, B., Vanhaverbekec, W., Duystersd, G., & Oorda, A. V. (2008). Network embeddedness and the exploration of novel technologies: Technological distance, betweenness centrality and density. Research Policy, 37(10), 1717–1731.CrossRefGoogle Scholar
  29. Gossart, C., & Özman, M. (2009). Co-authorship networks in social sciences: The case of Turkey. Scientometrics, 78(2), 323–345.CrossRefGoogle Scholar
  30. Harzing, A. W. (2007). Publish or perish.
  31. Hirsch, J. E. (2005). An index to quantify an individual’s scientific research output. Proceedings of the National Academy of Sciences, 102(46), 16569–16572.CrossRefGoogle Scholar
  32. Hite, J. M. (2003). Patterns of multidimentionality among embedded network ties: A typology of relational embeddedness in emerging enterpreneurial firms. Strategic Organization, 1(1), 9–49.CrossRefGoogle Scholar
  33. Hite, J. M. (2008). The role of dyadic multi-dimensionality in the evolution of strategic network ties. In J. A. C. Baum & T. J. Rowley (Eds.), Network Strategy (pp. 133–170). Bradford: Emerald Group Publishing Limited.CrossRefGoogle Scholar
  34. James, E., & Benjamin, G. (1988). Public policy and private education in Japan. London: Macmillan.CrossRefGoogle Scholar
  35. Kelly, C. D., & Jennions, M. D. (2006). The h-index and career assessment by numbers. Trends in Ecology and Evolution, 21(4), 167–170.CrossRefGoogle Scholar
  36. Lavie, D., & Drori, I. (2012). Collaborating for knowledge creation and application. Organization Science, 23(3), 704–724.CrossRefGoogle Scholar
  37. Ledin, A., Bornmann, L., Gannon, F., & Wallon, G. (2007). A persistent problem. EMBO Reports, 8(11), 982–987.CrossRefGoogle Scholar
  38. Lee, S., & Bozeman, B. (2005). The impact of research collaboration on scientific productivity. Social Studies of Science, 35(5), 673–702.CrossRefGoogle Scholar
  39. Lee, D. H., Seo, I. W., Choe, H. C., & Kim, H. D. (2012). Collaboration network patterns and research performance: The case of Korean public research institutions. Scientometrics, 91(3), 925–942.CrossRefGoogle Scholar
  40. 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.CrossRefGoogle Scholar
  41. McCulloh, I., Armstrong, H., & Johnson, A. (2013). Social network analysis with applications. Hoboken: Wiley.Google Scholar
  42. 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.CrossRefGoogle Scholar
  43. Nagpaul, P. S. (2002). Visualizing cooperation networks of elite institutions in India. Scientometrics, 54(2), 213–228.CrossRefGoogle Scholar
  44. Nagpaul, P. S., & Roy, S. (2003). Constructing a multi-objective measure of research performance. Scientometrics, 56(3), 383–402.CrossRefGoogle Scholar
  45. Nascimento, M. A., Sander, J., & Pound, J. (2003). Analysis of SIGMOD’s co-authorship graph. SIGMOD Record, 32(3), 8–10.CrossRefGoogle Scholar
  46. Newman, M. E. (2004). Who is the best connected scientist? A study of scientific coauthorship networks. Complex Networks, 650, 337–370.CrossRefMathSciNetMATHGoogle Scholar
  47. Newman, M. E. (2010). Networks: An introduction. Oxford: Oxford University Press.CrossRefMATHGoogle Scholar
  48. Oh, W., Choi, J. N., & 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
  49. Otte, E., & Rousseau, R. (2002). Social network analysis: A powerful strategy, also for the information sciences. Journal of Information Science, 28(6), 441–453.CrossRefGoogle Scholar
  50. 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
  51. Pike, T. W. (2010). Collaboration networks and scientific impact among behavioral ecologists. Behavioral Ecology, 21(2), 431–435.CrossRefGoogle Scholar
  52. Podolny, J. M., & Baron, J. N. (1997). Relationships and resources: Social networks and mobility in the workplace. American Sociological Review, 62, 673–693.CrossRefGoogle Scholar
  53. Prpic, K. (2002). Gender and productivity differentials in science. Scientometrics, 55(1), 27–58.CrossRefGoogle Scholar
  54. Rotolo, D., & Petruzzelli, M. (2013). When does centrality matter? Scientific productivity and the moderating role of research specialization and cross-community ties. Journal of Organizational Behavior, 34(5), 648–670.CrossRefGoogle Scholar
  55. Scott, J. (1991). Social network analysis: A handbook. Boston: Sage.Google Scholar
  56. Sci2 Team. (2009). Science of science (Sci2) tool. Indiana University and SciTech Strategies. Accessed May 5, 2011.
  57. Sidiropoulos, A., Katsaros, D., & Manolopoulos, Y. (2007). Generalized h-index for disclosing latent facts in citation networks. Scientometrics, 72(2), 253–280.CrossRefGoogle Scholar
  58. Sotudeh, H., & Khoshian, N. (2014). Gender differences in science: The case of scientific productivity in nano science and technology during 2005–2007. Scientometrics, 98(1), 457–472.CrossRefGoogle Scholar
  59. Sparrowe, T., Liden, R., Robert, G. J., Wayne, S., & Kraimer, M. L. (2001). Social networks and the performance of individuals and groups. Academy of Management Journal, 44(2), 316–325.CrossRefGoogle Scholar
  60. Stack, S. (2004). Gender, children and research productivity. Research in Higher Education, 45(8), 891–920.CrossRefGoogle Scholar
  61. Tower, G., Plummer, J., & Ridgewell, B. (2007). A multidisciplinary study of gender-based research productivity in the world’s best journals. Journal of Diversity Management, 2(4), 23–32.Google Scholar
  62. 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.CrossRefGoogle Scholar
  63. Valente, T. W., Loronges, K., Lakon, C., & Costenbader, E. (2008). How correlated are network centrality measures? Connections, 28(1), 16–26.Google Scholar
  64. Van Raan, A. F. J. (2006). Comparisons of the Hirsch-index with standard bibliometric indicators and with peer judgment for 147 chemistry research groups. Scientometrics, 67(3), 491–502.CrossRefGoogle Scholar
  65. Virick, M., DaSilva, N., & Arrington, K. (2010). Moderators of the curvilinear relation between extent of telecommuting and job and life satisfaction: The role of performance outcome orientation and worker type. Human Relations, 63(1), 137–154.CrossRefGoogle Scholar
  66. Wasserman, S., & Faust, K. (1994). Social networks analysis: Methods and applications. Cambridge: Cambridge University Press.CrossRefMATHGoogle Scholar
  67. Wei, J., Zheng, W., & Zhang, M. (2011). Social capital and knowledge transfer: A multi-level analysis. Human Relations, 64(11), 1401–1423.CrossRefGoogle Scholar
  68. Wilkinson, R., & Yussof, I. (2005). Public and private provision of higher education in Malaysia: A comparative analysis. Higher Education, 50(3), 361–386.CrossRefGoogle Scholar
  69. 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.CrossRefGoogle Scholar
  70. 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,. doi: 10.1186/1478-4505-6-9.Google Scholar
  71. Zaheer, A., & Soda, G. (2009). Network evolution: The origins of structural holes. Administrative Science Quarterly, 54(1), 1–31.CrossRefGoogle Scholar
  72. Zhou, J., Shin, S. J., Brass, D. J., Choi, J., & Zhang, Z. X. (2009). Social networks, personal values and creativity: Evidence for curvilinear and interaction effects. The Journal of Applied Psychology, 94(6), 1544–1552.CrossRefGoogle Scholar
  73. Zucker, L. G., Darby, M. R., Brewer, M. B., & Peng, Y. (1995). Collaboration structure and information dilemmas in biotechnology. In R. M. Kramer & T. R. Tyler (Eds.), Trust in organizations. Thousand Oaks, CA: Sage.Google Scholar
  74. Zurián, J., Alcaide, G. G., Zurián, J., Benavent, F. J. B., & Miguel-Dasit, A. (2007). Coauthorship networks and institutional collaboration in Revista Española de CardiologÍa Publications. Revista Espanola de Cardiologia, 60(2), 117–130.CrossRefGoogle Scholar

Copyright information

© Akadémiai Kiadó, Budapest, Hungary 2015

Authors and Affiliations

  1. 1.Institute of Management Sciences (IMS)University of BalochistanQuettaPakistan
  2. 2.Department of Educational Leadership and FoundationsBrigham Young UniversityProvoUSA
  3. 3.Suleman Dawood School of BusinessLahore University of Management Sciences (LUMS)LahorePakistan

Personalised recommendations