IDEAS home Printed from https://ideas.repec.org/a/eee/respol/v52y2023i8s0048733323001282.html
   My bibliography  Save this article

Local peer communities and future academic success of Ph.D. candidates

Author

Listed:
  • Wuestman, Mignon
  • Wanzenböck, Iris
  • Frenken, Koen

Abstract

Compared to senior scientists, early-career scientists have largely been neglected in the literature on academic success. This study aims to identify the effects of local peer communities of Ph.D. candidates on their future careers. We argue that local communities of Ph.D. candidates may offer both supportive and competitive environments depending on the nature of the relationships between its members. While Ph.D. candidates generally learn from and support each other in their local peer communities, they may also compete for their mentor's attention and future academic positions. We analyse such complex peer effects for 90,264 Ph.D. candidates in the field of mathematics in a genealogical way, by measuring a candidate's academic career success by the number of next-generation Ph.D. candidates supervised later on. To capture both the supportive and competitive peer effects, we distinguish between local peers who share mentors (co-mentees) and other local peers. Our result suggests that competition exists primarily among peers who share mentors, and only at the start of one's career. We also find supportive effects among peers who do not share mentors, particularly those from the same cohort. Our results highlight the importance of universities supporting informal interactions among Ph.D. candidates.

Suggested Citation

  • Wuestman, Mignon & Wanzenböck, Iris & Frenken, Koen, 2023. "Local peer communities and future academic success of Ph.D. candidates," Research Policy, Elsevier, vol. 52(8).
    • Handle: RePEc:eee:respol:v:52:y:2023:i:8:s0048733323001282
    DOI: 10.1016/j.respol.2023.104844
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0048733323001282
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.respol.2023.104844?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Pierre Dubois & Jean-Charles Rochet & Jean-Marc Schlenker, 2014. "Productivity and mobility in academic research: evidence from mathematicians," Scientometrics, Springer;Akadémiai Kiadó, vol. 98(3), pages 1669-1701, March.
    2. Cassidy R. Sugimoto & Chaoqun Ni & Terrell G. Russell & Brenna Bychowski, 2011. "Academic genealogy as an indicator of interdisciplinarity: An examination of dissertation networks in Library and Information Science," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 62(9), pages 1808-1828, September.
    3. Frenken, Koen & Heimeriks, Gaston J. & Hoekman, Jarno, 2017. "What drives university research performance? An analysis using the CWTS Leiden Ranking data," Journal of Informetrics, Elsevier, vol. 11(3), pages 859-872.
    4. Conti, Annamaria & Visentin, Fabiana, 2015. "A revealed preference analysis of PhD students’ choices over employment outcomes," Research Policy, Elsevier, vol. 44(10), pages 1931-1947.
    5. Vincent Larivière & Chaoqun Ni & Yves Gingras & Blaise Cronin & Cassidy R. Sugimoto, 2013. "Bibliometrics: Global gender disparities in science," Nature, Nature, vol. 504(7479), pages 211-213, December.
    6. Fabian Waldinger, 2010. "Quality Matters: The Expulsion of Professors and the Consequences for PhD Student Outcomes in Nazi Germany," Journal of Political Economy, University of Chicago Press, vol. 118(4), pages 787-831, August.
    7. Gema Lax Martínez & Julio Raffo & Kaori Saito, 2016. "Identifying the Gender of PCT inventors," WIPO Economic Research Working Papers 33, World Intellectual Property Organization - Economics and Statistics Division.
    8. Mignon Wuestman & Koen Frenken & Iris Wanzenböck, 2020. "A genealogical approach to academic success," PLOS ONE, Public Library of Science, vol. 15(12), pages 1-16, December.
    9. Samuel F. Way & Allison C. Morgan & Daniel B. Larremore & Aaron Clauset, 2019. "Productivity, prominence, and the effects of academic environment," Proceedings of the National Academy of Sciences, Proceedings of the National Academy of Sciences, vol. 116(22), pages 10729-10733, May.
    10. Broström, Anders, 2019. "Academic breeding grounds: Home department conditions and early career performance of academic researchers," Research Policy, Elsevier, vol. 48(7), pages 1647-1665.
    11. Trapido, Denis, 2015. "How novelty in knowledge earns recognition: The role of consistent identities," Research Policy, Elsevier, vol. 44(8), pages 1488-1500.
    12. Tartari, Valentina & Perkmann, Markus & Salter, Ammon, 2014. "In good company: The influence of peers on industry engagement by academic scientists," Research Policy, Elsevier, vol. 43(7), pages 1189-1203.
    13. R. Dean Malmgren & Julio M. Ottino & Luís A. Nunes Amaral, 2010. "The role of mentorship in protégé performance," Nature, Nature, vol. 465(7298), pages 622-626, June.
    14. Baruffaldi, Stefano & Visentin, Fabiana & Conti, Annamaria, 2016. "The productivity of science & engineering PhD students hired from supervisors’ networks," Research Policy, Elsevier, vol. 45(4), pages 785-796.
    15. Roach, Michael & Sauermann, Henry, 2010. "A taste for science? PhD scientists' academic orientation and self-selection into research careers in industry," Research Policy, Elsevier, vol. 39(3), pages 422-434, April.
    16. David F. Feldon & Kaylee Litson & Soojeong Jeong & Jennifer M. Blaney & Jina Kang & Candace Miller & Kimberly Griffin & Josipa Roksa, 2019. "Postdocs’ lab engagement predicts trajectories of PhD students’ skill development," Proceedings of the National Academy of Sciences, Proceedings of the National Academy of Sciences, vol. 116(42), pages 20910-20916, October.
    17. 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, Elsevier, vol. 311(3), pages 590-614.
    18. Jiaying Liu & Tao Tang & Xiangjie Kong & Amr Tolba & Zafer AL-Makhadmeh & Feng Xia, 2018. "Understanding the advisor–advisee relationship via scholarly data analysis," Scientometrics, Springer;Akadémiai Kiadó, vol. 116(1), pages 161-180, July.
    19. Cruz-Castro, Laura & Sanz-Menéndez, Luis, 2010. "Mobility versus job stability: Assessing tenure and productivity outcomes," Research Policy, Elsevier, vol. 39(1), pages 27-38, February.
    20. Jian Wang & Bart Thijs & Wolfgang Glänzel, 2015. "Interdisciplinarity and Impact: Distinct Effects of Variety, Balance, and Disparity," PLOS ONE, Public Library of Science, vol. 10(5), pages 1-18, May.
    21. Dominik P. Heinisch & Guido Buenstorf, 2018. "The next generation (plus one): an analysis of doctoral students’ academic fecundity based on a novel approach to advisor identification," Scientometrics, Springer;Akadémiai Kiadó, vol. 117(1), pages 351-380, October.
    22. Meric S. Gertler, 2003. "Tacit knowledge and the economic geography of context, or The undefinable tacitness of being (there)," Journal of Economic Geography, Oxford University Press, vol. 3(1), pages 75-99, January.
    23. Ding-wei Huang, 2015. "Temporal evolution of multi-author papers in basic sciences from 1960 to 2010," Scientometrics, Springer;Akadémiai Kiadó, vol. 105(3), pages 2137-2147, December.
    24. Rossi, Luciano & Freire, Igor L. & Mena-Chalco, Jesús P., 2017. "Genealogical index: A metric to analyze advisor–advisee relationships," Journal of Informetrics, Elsevier, vol. 11(2), pages 564-582.
    25. Shibayama, Sotaro & Baba, Yasunori, 2015. "Impact-oriented science policies and scientific publication practices: The case of life sciences in Japan," Research Policy, Elsevier, vol. 44(4), pages 936-950.
    26. Julia H. Chariker & Yihang Zhang & John R. Pani & Eric C. Rouchka, 2017. "Identification of successful mentoring communities using network-based analysis of mentor–mentee relationships across Nobel laureates," Scientometrics, Springer;Akadémiai Kiadó, vol. 111(3), pages 1733-1749, June.
    27. Katz, Michael L & Shapiro, Carl, 1985. "Network Externalities, Competition, and Compatibility," American Economic Review, American Economic Association, vol. 75(3), pages 424-440, June.
    28. Stephen V David & Benjamin Y Hayden, 2012. "Neurotree: A Collaborative, Graphical Database of the Academic Genealogy of Neuroscience," PLOS ONE, Public Library of Science, vol. 7(10), pages 1-12, October.
    29. Cassidy R. Sugimoto & Chaoqun Ni & Terrell G. Russell & Brenna Bychowski, 2011. "Academic genealogy as an indicator of interdisciplinarity: An examination of dissertation networks in Library and Information Science," Journal of the American Society for Information Science and Technology, Association for Information Science & Technology, vol. 62(9), pages 1808-1828, September.
    30. Stefano Breschi & Francesco Lissoni, 2009. "Mobility of skilled workers and co-invention networks: an anatomy of localized knowledge flows," Journal of Economic Geography, Oxford University Press, vol. 9(4), pages 439-468, July.
    31. Lu Liu & Yang Wang & Roberta Sinatra & C. Lee Giles & Chaoming Song & Dashun Wang, 2018. "Hot streaks in artistic, cultural, and scientific careers," Nature, Nature, vol. 559(7714), pages 396-399, July.
    32. Ron Boschma, 2005. "Proximity and Innovation: A Critical Assessment," Regional Studies, Taylor & Francis Journals, vol. 39(1), pages 61-74.
    33. repec:nas:journl:v:115:y:2018:p:12616-12623 is not listed on IDEAS
    34. Bart Nooteboom, 2000. "Learning by Interaction: Absorptive Capacity, Cognitive Distance and Governance," Journal of Management & Governance, Springer;Accademia Italiana di Economia Aziendale (AIDEA), vol. 4(1), pages 69-92, March.
    35. Shibayama, Sotaro & Baba, Yasunori & Walsh, John P., 2015. "Organizational design of University laboratories: Task allocation and lab performance in Japanese bioscience laboratories," Research Policy, Elsevier, vol. 44(3), pages 610-622.
    36. Junming Huang & Alexander J. Gates & Roberta Sinatra & Albert-László Barabási, 2020. "Historical comparison of gender inequality in scientific careers across countries and disciplines," Proceedings of the National Academy of Sciences, Proceedings of the National Academy of Sciences, vol. 117(9), pages 4609-4616, March.
    37. Agrawal, Ajay & McHale, John & Oettl, Alexander, 2017. "How stars matter: Recruiting and peer effects in evolutionary biology," Research Policy, Elsevier, vol. 46(4), pages 853-867.
    38. Lorenzo Ductor, 2015. "Does Co-authorship Lead to Higher Academic Productivity?," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 77(3), pages 385-407, June.
    39. Jasjit Singh & Lee Fleming, 2010. "Lone Inventors as Sources of Breakthroughs: Myth or Reality?," Management Science, INFORMS, vol. 56(1), pages 41-56, January.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Keloharju, Matti & Knüpfer, Samuli & Müller, Dagmar & Tåg, Joacim, 2024. "PhD studies hurt mental health, but less than previously feared," Research Policy, Elsevier, vol. 53(8).

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Mignon Wuestman & Koen Frenken & Iris Wanzenböck, 2020. "A genealogical approach to academic success," PLOS ONE, Public Library of Science, vol. 15(12), pages 1-16, December.
    2. Rafael J. P. Damaceno & Luciano Rossi & Rogério Mugnaini & Jesús P. Mena-Chalco, 2019. "The Brazilian academic genealogy: evidence of advisor–advisee relationships through quantitative analysis," Scientometrics, Springer;Akadémiai Kiadó, vol. 119(1), pages 303-333, April.
    3. Broström, Anders, 2019. "Academic breeding grounds: Home department conditions and early career performance of academic researchers," Research Policy, Elsevier, vol. 48(7), pages 1647-1665.
    4. Dhananjay Kumar & Plaban Kumar Bhowmick & Sumana Dey & Debarshi Kumar Sanyal, 2023. "On the banks of Shodhganga: analysis of the academic genealogy graph of an Indian ETD repository," Scientometrics, Springer;Akadémiai Kiadó, vol. 128(7), pages 3879-3914, July.
    5. Corsini, Alberto & Pezzoni, Michele & Visentin, Fabiana, 2022. "What makes a productive Ph.D. student?," Research Policy, Elsevier, vol. 51(10).
    6. Debarshi Kumar Sanyal & Sumana Dey & Partha Pratim Das, 2020. "gm-index: a new mentorship index for researchers," Scientometrics, Springer;Akadémiai Kiadó, vol. 123(1), pages 71-102, April.
    7. Fu, Zhongmeng & Cao, Yuan & Zhao, Yong, 2024. "Identifying knowledge evolution in computer science from the perspective of academic genealogy," Journal of Informetrics, Elsevier, vol. 18(2).
    8. Stefano Usai & Emanuela Marrocu & Raffaele Paci, 2017. "Networks, Proximities, and Interfirm Knowledge Exchanges," International Regional Science Review, , vol. 40(4), pages 377-404, July.
    9. Yu, Xiaoyao & Szymanski, Boleslaw K. & Jia, Tao, 2021. "Become a better you: Correlation between the change of research direction and the change of scientific performance," Journal of Informetrics, Elsevier, vol. 15(3).
    10. Zhu, Wanying & Jin, Ching & Ma, Yifang & Xu, Cong, 2023. "Earlier recognition of scientific excellence enhances future achievements and promotes persistence," Journal of Informetrics, Elsevier, vol. 17(2).
    11. Dominik P. Heinisch & Guido Buenstorf, 2018. "The next generation (plus one): an analysis of doctoral students’ academic fecundity based on a novel approach to advisor identification," Scientometrics, Springer;Akadémiai Kiadó, vol. 117(1), pages 351-380, October.
    12. Pranpreya Sriwannawit & Ulf Sandström, 2015. "Large-scale bibliometric review of diffusion research," Scientometrics, Springer;Akadémiai Kiadó, vol. 102(2), pages 1615-1645, February.
    13. Huegel, Matthias, 2024. "University scientists’ multiple goals achievement: Social capital and its impact on research performance and research commercialization," Technovation, Elsevier, vol. 135(C).
    14. Jianhua Hou & Bili Zheng & Yang Zhang & Chaomei Chen, 2021. "How do Price medalists’ scholarly impact change before and after their awards?," Scientometrics, Springer;Akadémiai Kiadó, vol. 126(7), pages 5945-5981, July.
    15. Lu Liu & Benjamin F. Jones & Brian Uzzi & Dashun Wang, 2023. "Data, measurement and empirical methods in the science of science," Nature Human Behaviour, Nature, vol. 7(7), pages 1046-1058, July.
    16. Rossi, Luciano & Damaceno, Rafael J.P. & Freire, Igor L. & Bechara, Etelvino J.H. & Mena-Chalco, Jesús P., 2018. "Topological metrics in academic genealogy graphs," Journal of Informetrics, Elsevier, vol. 12(4), pages 1042-1058.
    17. Meijun Liu & Sijie Yang & Yi Bu & Ning Zhang, 2023. "Female early-career scientists have conducted less interdisciplinary research in the past six decades: evidence from doctoral theses," Palgrave Communications, Palgrave Macmillan, vol. 10(1), pages 1-16, December.
    18. Cathrin Söllner & Dirk Fornahl, 2021. "Unleashing Inventive Power - Solving cognitive, social and geographic distance issues with cultural proximity," Bremen Papers on Economics & Innovation 2103, University of Bremen, Faculty of Business Studies and Economics.
    19. Tobias Koopmann & Maximilian Stubbemann & Matthias Kapa & Michael Paris & Guido Buenstorf & Tom Hanika & Andreas Hotho & Robert Jäschke & Gerd Stumme, 2021. "Proximity dimensions and the emergence of collaboration: a HypTrails study on German AI research," Scientometrics, Springer;Akadémiai Kiadó, vol. 126(12), pages 9847-9868, December.
    20. Hajibabaei, Anahita & Schiffauerova, Andrea & Ebadi, Ashkan, 2022. "Gender-specific patterns in the artificial intelligence scientific ecosystem," Journal of Informetrics, Elsevier, vol. 16(2).

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:respol:v:52:y:2023:i:8:s0048733323001282. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/respol .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.