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

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Abstract

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.

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Notes

  1. We didn’t just rely on the values returned by the software, UCINET VI. In order to validate our results, we manually calculated degree, closeness and betweenness for a very small sub-sample of our data set (Fig. 5). The results were then verified by UCINET VI to reveal exactly the same values as our manual calculations. Appendix Tables 3, 4, and 5 depict these manual calculations (See for Example Chapter 2. McCulloh et al. 2013).

  2. Frequency analysis indicated a career age mode of “0” with a valid percentage of 44.1 %.

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 

  • 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.

    Article  Google Scholar 

  • Andrews, R. (2010). Organizational social capital, structure and performance. Human Relations, 63(5), 583–608.

    Article  Google Scholar 

  • Arensbergen, P., Weijden, I., & Besselaar, P. (2012). Gender differences in scientific productivity: A persisting phenomenon? Scientometrics, 93(3), 857–868.

    Article  Google Scholar 

  • 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.

    Article  Google Scholar 

  • 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.

    Article  Google Scholar 

  • 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.

    Article  Google Scholar 

  • Barrios, M., Villarroya, A., & Borrego, A. (2013). Scientific production in psychology: A gender analysis. Scientometrics, 95(1), 15–23.

    Article  Google Scholar 

  • 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.

    Article  Google Scholar 

  • 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.

  • Boissevain, J. (1974). Friends of friends: Networks, manipulators and coalitions. New York: St. Martin’s Press.

    Google Scholar 

  • 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.

    Article  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 

  • Borrego, A., Barrios, M., Villarroya, A., & Olle, C. (2010). Scientific output and impact of postdoctoral scientists: A gender perspective. Scientometrics, 83(1), 93–101.

    Article  Google Scholar 

  • Burt, R. S. (1998). The gender of social capital. Rationality and Society, 10(1), 5–46.

    Article  MathSciNet  Google Scholar 

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

    Google Scholar 

  • 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.

    Article  Google Scholar 

  • De-Cohen, D. C. (2003). Diversification in Argentine higher education: Dimensions and impact of private sector growth. Higher Education, 46(1), 1–35.

    Article  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 

  • Egghe, L. (2006). Theory and practise of the g-index. Scientometrics, 69(1), 131–152.

    Article  MathSciNet  Google Scholar 

  • Fischbach, K., Putzke, J., & Schoder, D. (2011). Co-authorship networks in electronic markets research. Electronic Markets, 21(1), 19–40.

    Article  Google Scholar 

  • Fleming, L., & Sorenson, O. (2001). Technology as a complex adaptive system: Evidence from patent data. Research Policy, 30(7), 1019–1039.

    Article  Google Scholar 

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

    Article  Google Scholar 

  • 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.

    Article  Google Scholar 

  • 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.

    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 

  • Harzing, A. W. (2007). Publish or perish. http://www.harzing.com/pop.htm.

  • 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.

    Article  Google Scholar 

  • 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.

    Article  Google Scholar 

  • 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.

    Chapter  Google Scholar 

  • James, E., & Benjamin, G. (1988). Public policy and private education in Japan. London: Macmillan.

    Book  Google Scholar 

  • Kelly, C. D., & Jennions, M. D. (2006). The h-index and career assessment by numbers. Trends in Ecology and Evolution, 21(4), 167–170.

    Article  Google Scholar 

  • Lavie, D., & Drori, I. (2012). Collaborating for knowledge creation and application. Organization Science, 23(3), 704–724.

    Article  Google Scholar 

  • Ledin, A., Bornmann, L., Gannon, F., & Wallon, G. (2007). A persistent problem. EMBO Reports, 8(11), 982–987.

    Article  Google Scholar 

  • Lee, S., & Bozeman, B. (2005). The impact of research collaboration on scientific productivity. Social Studies of Science, 35(5), 673–702.

    Article  Google Scholar 

  • 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.

    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 

  • McCulloh, I., Armstrong, H., & Johnson, A. (2013). Social network analysis with applications. Hoboken: Wiley.

    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 

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

    Article  Google Scholar 

  • Nagpaul, P. S., & Roy, S. (2003). Constructing a multi-objective measure of research performance. Scientometrics, 56(3), 383–402.

    Article  Google Scholar 

  • Nascimento, M. A., Sander, J., & Pound, J. (2003). Analysis of SIGMOD’s co-authorship graph. SIGMOD Record, 32(3), 8–10.

    Article  Google Scholar 

  • Newman, M. E. (2004). Who is the best connected scientist? A study of scientific coauthorship networks. Complex Networks, 650, 337–370.

    Article  MathSciNet  MATH  Google Scholar 

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

    Book  MATH  Google Scholar 

  • 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 

  • Otte, E., & Rousseau, R. (2002). Social network analysis: A powerful strategy, also for the information sciences. Journal of Information Science, 28(6), 441–453.

    Article  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 

  • Podolny, J. M., & Baron, J. N. (1997). Relationships and resources: Social networks and mobility in the workplace. American Sociological Review, 62, 673–693.

    Article  Google Scholar 

  • Prpic, K. (2002). Gender and productivity differentials in science. Scientometrics, 55(1), 27–58.

    Article  Google Scholar 

  • 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.

    Article  Google Scholar 

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

    Google Scholar 

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

  • Sidiropoulos, A., Katsaros, D., & Manolopoulos, Y. (2007). Generalized h-index for disclosing latent facts in citation networks. Scientometrics, 72(2), 253–280.

    Article  Google Scholar 

  • 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.

    Article  Google Scholar 

  • 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.

    Article  Google Scholar 

  • Stack, S. (2004). Gender, children and research productivity. Research in Higher Education, 45(8), 891–920.

    Article  Google Scholar 

  • 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 

  • 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 

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

    Google Scholar 

  • 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.

    Article  Google Scholar 

  • 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.

    Article  Google Scholar 

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

    Book  MATH  Google Scholar 

  • Wei, J., Zheng, W., & Zhang, M. (2011). Social capital and knowledge transfer: A multi-level analysis. Human Relations, 64(11), 1401–1423.

    Article  Google Scholar 

  • Wilkinson, R., & Yussof, I. (2005). Public and private provision of higher education in Malaysia: A comparative analysis. Higher Education, 50(3), 361–386.

    Article  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 

  • 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 

  • Zaheer, A., & Soda, G. (2009). Network evolution: The origins of structural holes. Administrative Science Quarterly, 54(1), 1–31.

    Article  Google Scholar 

  • 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.

    Article  Google Scholar 

  • 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 

  • 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.

    Article  Google Scholar 

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Authors and Affiliations

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

    Kamal Badar

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

    Julie M. Hite

  3. Suleman Dawood School of Business, Lahore University of Management Sciences (LUMS), Lahore, Pakistan

    Naeem Ashraf

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  1. Kamal Badar
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  2. Julie M. Hite
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  3. Naeem Ashraf
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Correspondence to Kamal Badar.

Appendix

Appendix

See Tables 3, 4, and 5.

Table 3 Manual calculation of degree centrality for the subsample of authors in the network (refer to Fig. 5)
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Table 4 Manual calculation of closeness centrality for the subsample of authors in the network (refer to Fig. 5)
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Table 5 Manual calculation of betweenness centrality for the subsample of authors in the network (refer to Fig. 5)
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Fig. 5
figure 5

Subsample of authors in the network

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Badar, K., Hite, J.M. & Ashraf, N. Knowledge network centrality, formal rank and research performance: evidence for curvilinear and interaction effects. Scientometrics 105, 1553–1576 (2015). https://doi.org/10.1007/s11192-015-1652-0

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