Outstanding and ordinary scientists’ co-authorship networks in the early career phase
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Abstract
How do scientists’ ego-centered co-authorship networks affect their research productivity and impact during the early career phase? Do co-authorship networks evolve differently for outstanding scientists vs. ordinary scientists? Our study responded to these questions by demonstrating that scientists’ co-authorship network size and betweenness centrality of their co-authorship network positively affected both their research productivity and research impact. Scientists’ tie strength diversity of their co-authorship network moderated the relationship between their ego-network size and their research performance. Their co-authorship network’s degree centralization moderated the relationship between their betweenness centrality and research performance. Further, the size and betweenness centrality of the co-authorship network were significantly different between the two groups of scientists since their fourth working year. Outstanding scientists had a larger co-authorship network and their positions in the co-authorship network were more central than those of ordinary scientists. Implications for scientists and policy makers in science and higher education are discussed
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Tang, C., Ye, L., Naumann, S., & Lu, X. (2021). Outstanding and ordinary scientists’ co-authorship networks in the early career phase. Malaysian Journal of Library and Information Science, 26(1), 39–61. https://doi.org/10.22452/mjlis.vol26no1.3
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References
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Abramo, G., D’Angelo, C.A., and Murgia, G. 2014. Variation in research collaboration patterns across academic ranks. Scientometrics, Vol. 98, no. 3: 2275-2294.
Ahuja, G., Soda, G., and Zaheer, A. 2012. The genesis and dynamics of organizational networks. Organization Science, Vol. 23, no. 2: 434-448.
Aiken, L.S., and West, S.G. 1991. Multiple regression: Testing and interpreting interactions. Newbury Park, CA: Sage.
Bishop, P.R., Huck, S.W., Ownley, B.H., Richards, J.K., and Skolits, G.J. 2014. Impacts of an interdisciplinary research center on participant publication and collaboration patterns: A case study of the national institute for mathematical and biological synthesis. Research Evaluation, Vol. 23: 327-340.
Bliese, P.D., and Ployhart, R.E. 2002. Growth modeling using random coefficient models: Model building, testing, and illustrations. Organizational Research Methods, Vol. 5, no. 4: 362-387.
Borgatti, S.P. 2005. Centrality and network flow. Social Networks, Vol. 27, no. 1: 55-71.
Bozeman, B., and Corley, E. 2004. Scientists’ collaboration strategies: Implications for scientific and technical human capital. Research Policy, Vol. 33, no. 4: 599-616.
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Burt, R.S. 1992. Structural holes: The social structure of competition. Cambridge, MA: Harvard University Press.
Chen, Z. F., and Guan, J. C. 2010. The impact of small world on innovation: An empirical study of 16 countries. Journal of Informetrics, Vol. 4, no. 1: 97-106.
Coleman, J.S. 1988. Social capital in the creation of human capital. American Journal of Sociology, Vol. 94: S95-S120.
Cruz-Castro, L., and Sanz-Menéndez, L. 2010. Mobility versus job stability: Assessing tenure and productivity outcomes. Research Policy, Vol. 39, no. 1: 27-38.
De Stefano, D., and Zaccarin, S. 2015. Co-authorship networks and scientific performance: An empirical analysis using the generalized extreme value distribution. Journal of Applied Statistics, Vol. 43: 262-279.
Eisend, M., and Schmidt, S. 2014. The influence of knowledge-based resources and business scholars’ internationalization strategies on research performance. Research Policy, Vol. 43, no. 1: 48-59.
Feng, S., and Kirkley, A. 2020. Mixing patterns in interdisciplinary co-authorship networks at multiple scales. Scientific Reports, Vol. 10, no. 1: 1–11.
Freeman, L.C. 1979. Centrality in social networks conceptual clarification. Social Networks, Vol. 1, no. 3: 215-239.
Gao, X., Chen, J., and Huai, N. 2019. Meta-circuit machine: Inferencing human collaborative relationships in heterogeneous information networks. Information Processing & Management, Vol. 56: 844-857.
Garson, G.D. 2013. Hierarchical linear modeling: Guide and applications. Newbury Park: Sage.
Gonzalez-Brambila, C.N., Veloso, F.M., and Krackhardt, D. 2013. The impact of network embeddedness on research output. Research Policy, Vol. 42, no. 9: 1555-1567.
Haslam, N., and Laham, S.M. 2009. Early-career scientific achievement and patterns of authorship: The mixed blessings of publication leadership and collaboration. Research Evaluation, Vol. 18, no. 5: 405-410.
He, Z.L., Geng, X.S., and Campbell-Hunt, C. 2009. Research collaboration and research output: A longitudinal study of 65 biomedical scientists in a New Zealand university. Research Policy, Vol. 38, no. 2: 306-317.
Hofmann, D.A., and Gavin, M.B. 1998. Centering decisions in hierarchical linear models: Implications for research in organizations. Journal of Management, Vol. 24, no. 5: 623-641.
Hu, Z., Chen, C., and Liu, Z. 2014. How are collaboration and productivity correlated at various career stages of scientists? Scientometrics, Vol. 101, no. 2: 1553-1564.
Jonkers, K., and Cruz-Castro, L. 2013. Research upon return: the effect of international mobility on scientific ties, production and impact. Research Policy, Vol. 42, no. 8: 1366-1377.
Kenny, D.A., and Judd, C.M. 1986. Consequences of violating the independence assumption in analysis of variance. Psychological Bulletin, Vol. 99: 422-431.
Kyvic, S., and Olsen, T.B. 2008. Does the aging of tenured academic staff affect the research performance of universities? Scientometrics, Vol. 76, no. 3: 439-455.
Lance, C.E., Vandenberg, R.J., and Self, R.M. 2000. latent growth models of individual change: The case of newcomer adjustment. Organizational Behavior & Human Decision Processes, Vol. 83: 107-140.
Landström, H., and Harirchi, G. 2018. The social structure of entrepreneurship as a scientific field. Research Policy, Vol. 47, no. 3: 650-662.
Laudel, G., and Gläser, J. 2008. From apprentice to colleague: The metamorphosis of early career researchers. Higher Education, Vol. 55, no. 3: 387-406.
Lee, S., and Bozeman, B. 2005. The impact of research collaboration on scientific productivity. Social Studies of Science, Vol. 35, no. 5: 673-702.
Letina, S. 2016. Network and actor attribute effects on the performance of researchers in two fields of social science in a small peripheral community. Journal of Informetrics, Vol. 10: 571-595.
Li, Y., Zhang, D., Luo, P., and Jiang, J. 2017. Interpreting the formation of co-author networks via utility analysis. Information Processing & Management, Vol. 53, no. 3: 624–639.
Li, E.Y., Liao, C.H., and Yen, H.R. 2013. Co-authorship networks and research impact: A social capital perspective. Research Policy, Vol. 42, no. 9: 1515-1530.
McCarty, C. 2002. Structure in personal networks. Journal of Social Structure, Vol. 3: 1-11.
McFadyen, M.A., and Cannella, A.A. 2004. Social capital and knowledge creation: Diminishing returns of the number and strength of exchange relationships. Academy of Management Journal, Vol. 47, no. 5: 735-746.
Nahapiet, J. and Ghoshal, S. 1998. Social capital, intellectual capital, and the organizational advantage. Academy of Management Review, Vol. 23: 242-266.
Oguz, C., Kingsley, A.R., and John, S. 2014. A regression analysis of researchers’ social network metrics on their citation performance in a college of engineering. Journal of Informetrics, Vol. 8: 667-682.
Ortega, J.L. 2014. Influence of co-authorship networks in the research impact: Ego network analyses from microsoft academic search. Journal of Informetrics, Vol. 8, no. 3: 728-737.
Otte, E., and Rousseau, R. 2002. Social network analysis: a powerful strategy, also for the information sciences. Journal of Information Science, Vol. 28, no. 6: 441-453.
Pauli, J., Basso, K., Lopes Gobi, R., and Bilhar, A. 2019. The effect of co-authorship network density on the performance of postgraduate programs. Brazilian Business Review (Portuguese Edition), Vol. 16, no. 6, 576–588.
Perry-Smith, J.E., and Shalley, C.E. 2003. The social side of creativity: A static and dynamic social network perspective. Academy of Management Review, Vol. 28, no. 1: 89-106.
Phelps C., Heidl R, and Wadhwa A. 2012. Knowledge, networks, and knowledge networks a review and research agenda. Journal of Management, Vol. 38, no. 4: 1115-1166.
Ployhart, R.E., Holtz, B.C., and Bliese, P.D. 2002. Longitudinal data analysis: Applications of random coefficient modeling to leadership research. The Leadership Quarterly, Vol. 13, no. 4: 455-486.
Sabharwal, M., and Hu, Q. 2013. Participation in university-based research centers: Is it helping or hurting researchers? Research Policy, Vol. 42, no. 6: 1301-1311.
Siciliano, M. D., Welch, E. W., and Feeney, M. K. 2018. Network exploration and exploitation: Professional network churn and scientific production. Social Networks, Vol. 52: 167-179.
Uddin, S., Hossain, L., Abbasi, A., and Rasmussen, K. 2012. Trend and efficiency analysis of co-authorship network. Scientometrics, Vol. 90, no. 2: 687-699.
Wagner, C., Whetsell, T. A., and Mukherjee, S. 2019. International research collaboration: Novelty, conventionality, and atypicality in knowledge recombination. Research Policy, Vol. 48: 1260-1270.
Wasserman, S. 1994. Social network analysis: Methods and applications (Vol. 8). New York: Cambridge University Press.
Xu, J., Chau, M., and Tan, B. C. Y. 2014. The development of social capital in the collaboration network of information systems scholars. Journal of the Association for Information Systems, 15, no. 12: 835–859.
Yan, Y., and Guan, J. 2018. Social capital, exploitative and exploratory innovations: The mediating roles of ego-network dynamics. Technological Forecasting and Social Change, Vol. 126: 244-258.
Zhang, J. 2017. Uncovering mechanisms of co-authorship evolution by multirelations-based link prediction. Information Processing & Management, Vol. 53: 42-51.
Zhou, J., Shin, S.J., Brass, D.J., Choi, J., and Zhang, Z.X. 2009. Social networks, personal values, and creativity: Evidence for curvilinear and interaction effects. Journal of Applied Psychology, Vol. 94, no. 6: 1544-1552
Abbasi, A., Chung, K.S.K. and Hossain, L. 2012. Egocentric analysis of co-authorship network structure, position and performance. Information Processing & Management, Vol. 48, no. 4: 671-679.
Abbasi, A., Wigand, R.T., and Hossain, L. 2014. Measuring social capital through network analysis and its influence on individual performance. Library & Information Science Research, Vol. 36, no. 1: 66-73.
Abramo, G., Cicero, T., and D’Angelo, C.A. 2013. The impact of non-productive and top scientists on overall university research performance. Journal of Informetrics, Vol. 7, no. 1: 166-175.
Abramo, G., D’Angelo, C.A., and Murgia, G. 2014. Variation in research collaboration patterns across academic ranks. Scientometrics, Vol. 98, no. 3: 2275-2294.
Ahuja, G., Soda, G., and Zaheer, A. 2012. The genesis and dynamics of organizational networks. Organization Science, Vol. 23, no. 2: 434-448.
Aiken, L.S., and West, S.G. 1991. Multiple regression: Testing and interpreting interactions. Newbury Park, CA: Sage.
Bishop, P.R., Huck, S.W., Ownley, B.H., Richards, J.K., and Skolits, G.J. 2014. Impacts of an interdisciplinary research center on participant publication and collaboration patterns: A case study of the national institute for mathematical and biological synthesis. Research Evaluation, Vol. 23: 327-340.
Bliese, P.D., and Ployhart, R.E. 2002. Growth modeling using random coefficient models: Model building, testing, and illustrations. Organizational Research Methods, Vol. 5, no. 4: 362-387.
Borgatti, S.P. 2005. Centrality and network flow. Social Networks, Vol. 27, no. 1: 55-71.
Bozeman, B., and Corley, E. 2004. Scientists’ collaboration strategies: Implications for scientific and technical human capital. Research Policy, Vol. 33, no. 4: 599-616.
Bryk, A.S., and Raudenbush, S.W. 1992. Hierarchical linear models. Newbury Park, CA: Sage.
Burt, R.S. 1992. Structural holes: The social structure of competition. Cambridge, MA: Harvard University Press.
Chen, Z. F., and Guan, J. C. 2010. The impact of small world on innovation: An empirical study of 16 countries. Journal of Informetrics, Vol. 4, no. 1: 97-106.
Coleman, J.S. 1988. Social capital in the creation of human capital. American Journal of Sociology, Vol. 94: S95-S120.
Cruz-Castro, L., and Sanz-Menéndez, L. 2010. Mobility versus job stability: Assessing tenure and productivity outcomes. Research Policy, Vol. 39, no. 1: 27-38.
De Stefano, D., and Zaccarin, S. 2015. Co-authorship networks and scientific performance: An empirical analysis using the generalized extreme value distribution. Journal of Applied Statistics, Vol. 43: 262-279.
Eisend, M., and Schmidt, S. 2014. The influence of knowledge-based resources and business scholars’ internationalization strategies on research performance. Research Policy, Vol. 43, no. 1: 48-59.
Feng, S., and Kirkley, A. 2020. Mixing patterns in interdisciplinary co-authorship networks at multiple scales. Scientific Reports, Vol. 10, no. 1: 1–11.
Freeman, L.C. 1979. Centrality in social networks conceptual clarification. Social Networks, Vol. 1, no. 3: 215-239.
Gao, X., Chen, J., and Huai, N. 2019. Meta-circuit machine: Inferencing human collaborative relationships in heterogeneous information networks. Information Processing & Management, Vol. 56: 844-857.
Garson, G.D. 2013. Hierarchical linear modeling: Guide and applications. Newbury Park: Sage.
Gonzalez-Brambila, C.N., Veloso, F.M., and Krackhardt, D. 2013. The impact of network embeddedness on research output. Research Policy, Vol. 42, no. 9: 1555-1567.
Haslam, N., and Laham, S.M. 2009. Early-career scientific achievement and patterns of authorship: The mixed blessings of publication leadership and collaboration. Research Evaluation, Vol. 18, no. 5: 405-410.
He, Z.L., Geng, X.S., and Campbell-Hunt, C. 2009. Research collaboration and research output: A longitudinal study of 65 biomedical scientists in a New Zealand university. Research Policy, Vol. 38, no. 2: 306-317.
Hofmann, D.A., and Gavin, M.B. 1998. Centering decisions in hierarchical linear models: Implications for research in organizations. Journal of Management, Vol. 24, no. 5: 623-641.
Hu, Z., Chen, C., and Liu, Z. 2014. How are collaboration and productivity correlated at various career stages of scientists? Scientometrics, Vol. 101, no. 2: 1553-1564.
Jonkers, K., and Cruz-Castro, L. 2013. Research upon return: the effect of international mobility on scientific ties, production and impact. Research Policy, Vol. 42, no. 8: 1366-1377.
Kenny, D.A., and Judd, C.M. 1986. Consequences of violating the independence assumption in analysis of variance. Psychological Bulletin, Vol. 99: 422-431.
Kyvic, S., and Olsen, T.B. 2008. Does the aging of tenured academic staff affect the research performance of universities? Scientometrics, Vol. 76, no. 3: 439-455.
Lance, C.E., Vandenberg, R.J., and Self, R.M. 2000. latent growth models of individual change: The case of newcomer adjustment. Organizational Behavior & Human Decision Processes, Vol. 83: 107-140.
Landström, H., and Harirchi, G. 2018. The social structure of entrepreneurship as a scientific field. Research Policy, Vol. 47, no. 3: 650-662.
Laudel, G., and Gläser, J. 2008. From apprentice to colleague: The metamorphosis of early career researchers. Higher Education, Vol. 55, no. 3: 387-406.
Lee, S., and Bozeman, B. 2005. The impact of research collaboration on scientific productivity. Social Studies of Science, Vol. 35, no. 5: 673-702.
Letina, S. 2016. Network and actor attribute effects on the performance of researchers in two fields of social science in a small peripheral community. Journal of Informetrics, Vol. 10: 571-595.
Li, Y., Zhang, D., Luo, P., and Jiang, J. 2017. Interpreting the formation of co-author networks via utility analysis. Information Processing & Management, Vol. 53, no. 3: 624–639.
Li, E.Y., Liao, C.H., and Yen, H.R. 2013. Co-authorship networks and research impact: A social capital perspective. Research Policy, Vol. 42, no. 9: 1515-1530.
McCarty, C. 2002. Structure in personal networks. Journal of Social Structure, Vol. 3: 1-11.
McFadyen, M.A., and Cannella, A.A. 2004. Social capital and knowledge creation: Diminishing returns of the number and strength of exchange relationships. Academy of Management Journal, Vol. 47, no. 5: 735-746.
Nahapiet, J. and Ghoshal, S. 1998. Social capital, intellectual capital, and the organizational advantage. Academy of Management Review, Vol. 23: 242-266.
Oguz, C., Kingsley, A.R., and John, S. 2014. A regression analysis of researchers’ social network metrics on their citation performance in a college of engineering. Journal of Informetrics, Vol. 8: 667-682.
Ortega, J.L. 2014. Influence of co-authorship networks in the research impact: Ego network analyses from microsoft academic search. Journal of Informetrics, Vol. 8, no. 3: 728-737.
Otte, E., and Rousseau, R. 2002. Social network analysis: a powerful strategy, also for the information sciences. Journal of Information Science, Vol. 28, no. 6: 441-453.
Pauli, J., Basso, K., Lopes Gobi, R., and Bilhar, A. 2019. The effect of co-authorship network density on the performance of postgraduate programs. Brazilian Business Review (Portuguese Edition), Vol. 16, no. 6, 576–588.
Perry-Smith, J.E., and Shalley, C.E. 2003. The social side of creativity: A static and dynamic social network perspective. Academy of Management Review, Vol. 28, no. 1: 89-106.
Phelps C., Heidl R, and Wadhwa A. 2012. Knowledge, networks, and knowledge networks a review and research agenda. Journal of Management, Vol. 38, no. 4: 1115-1166.
Ployhart, R.E., Holtz, B.C., and Bliese, P.D. 2002. Longitudinal data analysis: Applications of random coefficient modeling to leadership research. The Leadership Quarterly, Vol. 13, no. 4: 455-486.
Sabharwal, M., and Hu, Q. 2013. Participation in university-based research centers: Is it helping or hurting researchers? Research Policy, Vol. 42, no. 6: 1301-1311.
Siciliano, M. D., Welch, E. W., and Feeney, M. K. 2018. Network exploration and exploitation: Professional network churn and scientific production. Social Networks, Vol. 52: 167-179.
Uddin, S., Hossain, L., Abbasi, A., and Rasmussen, K. 2012. Trend and efficiency analysis of co-authorship network. Scientometrics, Vol. 90, no. 2: 687-699.
Wagner, C., Whetsell, T. A., and Mukherjee, S. 2019. International research collaboration: Novelty, conventionality, and atypicality in knowledge recombination. Research Policy, Vol. 48: 1260-1270.
Wasserman, S. 1994. Social network analysis: Methods and applications (Vol. 8). New York: Cambridge University Press.
Xu, J., Chau, M., and Tan, B. C. Y. 2014. The development of social capital in the collaboration network of information systems scholars. Journal of the Association for Information Systems, 15, no. 12: 835–859.
Yan, Y., and Guan, J. 2018. Social capital, exploitative and exploratory innovations: The mediating roles of ego-network dynamics. Technological Forecasting and Social Change, Vol. 126: 244-258.
Zhang, J. 2017. Uncovering mechanisms of co-authorship evolution by multirelations-based link prediction. Information Processing & Management, Vol. 53: 42-51.
Zhou, J., Shin, S.J., Brass, D.J., Choi, J., and Zhang, Z.X. 2009. Social networks, personal values, and creativity: Evidence for curvilinear and interaction effects. Journal of Applied Psychology, Vol. 94, no. 6: 1544-1552