IDEAS home Printed from https://ideas.repec.org/a/spr/scient/v114y2018i1d10.1007_s11192-017-2561-1.html
   My bibliography  Save this article

Factors influencing the formation of intra-institutional formal research groups: group prediction from collaboration, organisational, and topical networks

Author

Listed:
  • Hector G. Ceballos

    (Tecnologico de Monterrey)

  • Sara E. Garza

    (Universidad Autónoma de Nuevo León (UANL))

  • Francisco J. Cantu

    (Tecnologico de Monterrey)

Abstract

The factors that foster successful scientific collaboration and teamwork have been studied extensively. However, these factors have been studied in isolation and it is not clear to what extent one factor is more relevant than other in the formation of research groups. In this work we propose a new methodology based on network analysis to simultaneously evaluate multiple factors considered relevant in the conformation of formal research groups. Our methodology is supported on structural, statistical, and correlation analysis. In addition to validating our methodology with a case study at a research-teaching university, we introduce a new network to represent the success of scientific collaboration that produces the best prediction in group formation. Our methodology and the results obtained can be used for organising researchers in a university that seeks to strengthen its research strategy.

Suggested Citation

  • Hector G. Ceballos & Sara E. Garza & Francisco J. Cantu, 2018. "Factors influencing the formation of intra-institutional formal research groups: group prediction from collaboration, organisational, and topical networks," Scientometrics, Springer;Akadémiai Kiadó, vol. 114(1), pages 181-216, January.
    • Handle: RePEc:spr:scient:v:114:y:2018:i:1:d:10.1007_s11192-017-2561-1
    DOI: 10.1007/s11192-017-2561-1
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s11192-017-2561-1
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.
    File URL: https://libkey.io/10.1007/s11192-017-2561-1?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. Hinds, Pamela J. & Carley, Kathleen M. & Krackhardt, David & Wholey, Doug, 2000. "Choosing Work Group Members: Balancing Similarity, Competence, and Familiarity," Organizational Behavior and Human Decision Processes, Elsevier, vol. 81(2), pages 226-251, March.
    2. Donald Deb. Beaver, 2001. "Reflections on Scientific Collaboration (and its study): Past, Present, and Future," Scientometrics, Springer;Akadémiai Kiadó, vol. 52(3), pages 365-377, November.
    3. Ludo Waltman & Nees Jan Eck, 2012. "A new methodology for constructing a publication-level classification system of science," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 63(12), pages 2378-2392, December.
    4. Deborah Gladstein Ancona & David F. Caldwell, 1992. "Demography and Design: Predictors of New Product Team Performance," Organization Science, INFORMS, vol. 3(3), pages 321-341, August.
    5. Yutao Sun & Kai Liu, 2016. "Proximity effect, preferential attachment and path dependence in inter-regional network: a case of China’s technology transaction," Scientometrics, Springer;Akadémiai Kiadó, vol. 108(1), pages 201-220, July.
    6. Liming Liang & Ling Zhu, 2002. "Major factors affecting China's inter-regional research collaboration: Regional scientific productivity and geographical proximity," Scientometrics, Springer;Akadémiai Kiadó, vol. 55(2), pages 287-316, August.
    7. Etzkowitz, Henry, 2003. "Research groups as 'quasi-firms': the invention of the entrepreneurial university," Research Policy, Elsevier, vol. 32(1), pages 109-121, January.
    8. Maaike Verbree & Edwin Horlings & Peter Groenewegen & Inge Weijden & Peter Besselaar, 2015. "Organizational factors influencing scholarly performance: a multivariate study of biomedical research groups," Scientometrics, Springer;Akadémiai Kiadó, vol. 102(1), pages 25-49, January.
    9. M. José Martín-Sempere & Belén Garzón-García & Jesús Rey-Rocha, 2008. "Team consolidation, social integration and scientists’ research performance: An empirical study in the Biology and Biomedicine field," Scientometrics, Springer;Akadémiai Kiadó, vol. 76(3), pages 457-482, September.
    10. Bercovitz, Janet & Feldman, Maryann, 2011. "The mechanisms of collaboration in inventive teams: Composition, social networks, and geography," Research Policy, Elsevier, vol. 40(1), pages 81-93, February.
    11. Waltman, Ludo, 2016. "A review of the literature on citation impact indicators," Journal of Informetrics, Elsevier, vol. 10(2), pages 365-391.
    12. Hector Gonzalo Ordóñez‐Matamoros & Susan E. Cozzens & Margarita Garcia, 2010. "International Co‐Authorship and Research Team Performance in Colombia," Review of Policy Research, Policy Studies Organization, vol. 27(4), pages 415-431, July.
    13. Etzkowitz, Henry & Leydesdorff, Loet, 2000. "The dynamics of innovation: from National Systems and "Mode 2" to a Triple Helix of university-industry-government relations," Research Policy, Elsevier, vol. 29(2), pages 109-123, February.
    14. Clara Calero & Renald Buter & Cecilia Cabello Valdés & Ed Noyons, 2006. "How to identify research groups using publication analysis: an example in the field of nanotechnology," Scientometrics, Springer;Akadémiai Kiadó, vol. 66(2), pages 365-376, February.
    15. Ludo Waltman & Nees Jan van Eck, 2012. "A new methodology for constructing a publication‐level classification system of science," Journal of the American Society for Information Science and Technology, Association for Information Science & Technology, vol. 63(12), pages 2378-2392, December.
    16. Ben R. Martin, 2012. "Are universities and university research under threat? Towards an evolutionary model of university speciation," Cambridge Journal of Economics, Cambridge Political Economy Society, vol. 36(3), pages 543-565.
    17. Bonner, Bryan L. & Baumann, Michael R. & Dalal, Reeshad S., 2002. "The effects of member expertise on group decision-making and performance," Organizational Behavior and Human Decision Processes, Elsevier, vol. 88(2), pages 719-736, July.
    18. Jesús Rey-Rocha & Belén Garzón-García & M. José Martín-Sempere, 2006. "Scientists' performance and consolidation of research teams in Biology and Biomedicine at the Spanish Council for Scientific Research," Scientometrics, Springer;Akadémiai Kiadó, vol. 69(2), pages 183-212, November.
    19. Qi Yu & Hongfang Shao & Zhiguang Duan, 2011. "Research groups of oncology co-authorship network in China," Scientometrics, Springer;Akadémiai Kiadó, vol. 89(2), pages 553-567, November.
    20. Perianes-Rodríguez, Antonio & Chinchilla-Rodríguez, Zaida & Vargas-Quesada, Benjamín & Olmeda Gómez, Carlos & Moya-Anegón, Félix, 2009. "Synthetic hybrid indicators based on scientific collaboration to quantify and evaluate individual research results," Journal of Informetrics, Elsevier, vol. 3(2), pages 91-101.
    21. Robert S. Huckman & Bradley R. Staats & David M. Upton, 2009. "Team Familiarity, Role Experience, and Performance: Evidence from Indian Software Services," Management Science, INFORMS, vol. 55(1), pages 85-100, January.
    22. Gruenfeld, Deborah H & Mannix, Elizabeth A. & Williams, Katherine Y. & Neale, Margaret A., 1996. "Group Composition and Decision Making: How Member Familiarity and Information Distribution Affect Process and Performance," Organizational Behavior and Human Decision Processes, Elsevier, vol. 67(1), pages 1-15, July.
    23. Yi Zhang & Kaihua Chen & Guilong Zhu & Richard C. M. Yam & Jiancheng Guan, 2016. "Inter-organizational scientific collaborations and policy effects: an ego-network evolutionary perspective of the Chinese Academy of Sciences," Scientometrics, Springer;Akadémiai Kiadó, vol. 108(3), pages 1383-1415, September.
    24. Philip S. Cho & Huy Hoang Nhat Do & Muthu Kumar Chandrasekaran & Min-Yen Kan, 2013. "Identifying research facilitators in an emerging Asian Research Area," Scientometrics, Springer;Akadémiai Kiadó, vol. 97(1), pages 75-97, October.
    Full references (including those not matched with items on IDEAS)

    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. Lungeanu, Alina & Huang, Yun & Contractor, Noshir S., 2014. "Understanding the assembly of interdisciplinary teams and its impact on performance," Journal of Informetrics, Elsevier, vol. 8(1), pages 59-70.
    2. Rippa, Pierluigi & Secundo, Giustina, 2019. "Digital academic entrepreneurship: The potential of digital technologies on academic entrepreneurship," Technological Forecasting and Social Change, Elsevier, vol. 146(C), pages 900-911.
    3. Hu, Zhigang & Tian, Wencan & Xu, Shenmeng & Zhang, Chunbo & Wang, Xianwen, 2018. "Four pitfalls in normalizing citation indicators: An investigation of ESI’s selection of highly cited papers," Journal of Informetrics, Elsevier, vol. 12(4), pages 1133-1145.
    4. Bornmann, Lutz & Haunschild, Robin & Mutz, Rüdiger, 2020. "Should citations be field-normalized in evaluative bibliometrics? An empirical analysis based on propensity score matching," Journal of Informetrics, Elsevier, vol. 14(4).
    5. Ardito, Lorenzo & Natalicchio, Angelo & Appio, Francesco Paolo & Messeni Petruzzelli, Antonio, 2021. "The role of scientific knowledge within inventing teams and the moderating effects of team internationalization and team experience: Empirical tests into the aerospace sector," Journal of Business Research, Elsevier, vol. 128(C), pages 701-710.
    6. Haunschild, Robin & Daniels, Angela D. & Bornmann, Lutz, 2022. "Scores of a specific field-normalized indicator calculated with different approaches of field-categorization: Are the scores different or similar?," Journal of Informetrics, Elsevier, vol. 16(1).
    7. Shu-Hao Chang, 2018. "A pilot study on the connection between scientific fields and patent classification systems," Scientometrics, Springer;Akadémiai Kiadó, vol. 114(3), pages 951-970, March.
    8. Luis Antonio Orozco Castro, 2015. "Diversidad y heterogeneidad en redes de colaboración científica. Un estudio de las escuelas de administración de América Latina," Books, Universidad Externado de Colombia, Facultad de Administración de Empresas, edition 1, number 44, August.
    9. Hector Gonzalo Ordóñez‐Matamoros & Susan E. Cozzens & Margarita Garcia, 2010. "International Co‐Authorship and Research Team Performance in Colombia," Review of Policy Research, Policy Studies Organization, vol. 27(4), pages 415-431, July.
    10. Annita Nugent & Ho Fai Chan & Uwe Dulleck, 2022. "Government funding of university-industry collaboration: exploring the impact of targeted funding on university patent activity," Scientometrics, Springer;Akadémiai Kiadó, vol. 127(1), pages 29-73, January.
    11. Juan Miguel Campanario, 2018. "Are leaders really leading? Journals that are first in Web of Science subject categories in the context of their groups," Scientometrics, Springer;Akadémiai Kiadó, vol. 115(1), pages 111-130, April.
    12. Carusi, Chiara & Bianchi, Giuseppe, 2019. "Scientific community detection via bipartite scholar/journal graph co-clustering," Journal of Informetrics, Elsevier, vol. 13(1), pages 354-386.
    13. Lyu, Haihua & Bu, Yi & Zhao, Zhenyue & Zhang, Jiarong & Li, Jiang, 2022. "Citation bias in measuring knowledge flow: Evidence from the web of science at the discipline level," Journal of Informetrics, Elsevier, vol. 16(4).
    14. Bornmann, Lutz & Haunschild, Robin, 2016. "Citation score normalized by cited references (CSNCR): The introduction of a new citation impact indicator," Journal of Informetrics, Elsevier, vol. 10(3), pages 875-887.
    15. Castillo-Vergara, Mauricio & Alvarez-Marin, Alejandro & Placencio-Hidalgo, Dario, 2018. "A bibliometric analysis of creativity in the field of business economics," Journal of Business Research, Elsevier, vol. 85(C), pages 1-9.
    16. Paola Bernardi & Alberto Bertello & Canio Forliano & Ludovico Bullini Orlandi, 2022. "Beyond the “ivory tower”. Comparing academic and non-academic knowledge on social entrepreneurship," International Entrepreneurship and Management Journal, Springer, vol. 18(3), pages 999-1032, September.
    17. Christoph Engel, 2022. "Lucky you: Your case is heard by a seasoned panel—Panel effects in the German Constitutional Court," Journal of Empirical Legal Studies, John Wiley & Sons, vol. 19(4), pages 1179-1221, December.
    18. Dunaiski, Marcel & Geldenhuys, Jaco & Visser, Willem, 2019. "Globalised vs averaged: Bias and ranking performance on the author level," Journal of Informetrics, Elsevier, vol. 13(1), pages 299-313.
    19. Duy Vu & Michele Pezzoni & Duc Lam Nguyen, 2021. "Arbitrator teams and dispute resolution performance: an empirical analysis," European Journal of Law and Economics, Springer, vol. 51(2), pages 347-381, April.
    20. Liwei Cai & Jiahao Tian & Jiaying Liu & Xiaomei Bai & Ivan Lee & Xiangjie Kong & Feng Xia, 2019. "Scholarly impact assessment: a survey of citation weighting solutions," Scientometrics, Springer;Akadémiai Kiadó, vol. 118(2), pages 453-478, February.

    More about this item

    Keywords

    Scientific collaboration; Network analysis; Graph clustering; Research groups; Complex networks;
    All these keywords.

    JEL classification:

    • C61 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Optimization Techniques; Programming Models; Dynamic Analysis
    • C88 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Other Computer Software

    Statistics

    Access and download statistics

    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:spr:scient:v:114:y:2018:i:1:d:10.1007_s11192-017-2561-1. 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: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    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.