|
|
|
| Relationship Between Division of Scientific Labor and Research Performance—the Moderating Role of Geographical Proximities |
| Lu Chao1, Zhou Chenyu1, Xiao Chengrui1, Zhao Yi2, Zhang Chenwei3 |
1.Business School, Hohai University, Nanjing 211100
2.School of Management, Anhui University, Hefei 230601
3.Faculty of Education, The University of Hong Kong, Hong Kong 999077 |
|
|
|
|
Abstract Because team-based collaboration has become a prevailing mode of production of scientific knowledge, the relationship between division of scientific labor and research performance remains insufficiently understood. Using 148,493 articles from PLoS, we construct the Degree of Division of Scientific Labor (DDoSL) index based on author-contribution statements and the Herfindahl-Hirschman Index (HHI). We use five-year citation counts as a proxy for research performance to examine the association of DDoSL with research performance and explore the moderating roles of multiple proximity dimensions. Research performance is found to be positively associated with DDoSL, and geographical proximity is found to exert a positive moderating effect on the DDoSL-performance relationship. In contrast, social and institutional proximity have no significant association with research performance, and cognitive and organizational proximity do not have any clear moderating effects on the DDoSL-performance relationship. Moreover, positive DDoSL-performance association and positive moderation of geographical proximity are more pronounced in small teams. Overall, the findings suggest that deeper division of scientific labor is associated with higher research performance, while geographic separation may increase coordination costs and attenuate the performance gains from labor division. Thus, small teams may benefit from deepening labor division while minimizing remote collaboration to enhance research performance.
|
|
Received: 20 October 2025
|
|
|
|
1 Larivière V, Gingras Y, Sugimoto C R, et al. Team size matters: collaboration and scientific impact since 1900[J]. Journal of the Association for Information Science and Technology, 2015, 66(7): 1323-1332.
2 Yang L Q, Holtz D, Jaffe S, et al. The effects of remote work on collaboration among information workers[J]. Nature Human Behaviour, 2022, 6(1): 43-54.
3 He C C, Wu J, Zhang Q P. Proximity-aware research leadership recommendation in research collaboration via deep neural networks[J]. Journal of the Association for Information Science and Technology, 2022, 73(1): 70-89.
4 Lu C, Zhang C W, Xiao C R, et al. Contributorship in scientific collaborations: the perspective of contribution-based byline orders[J]. Information Processing & Management, 2022, 59(3): 102944.
5 Lu C, Zhang Y Y, Ahn Y Y, et al. Co-contributorship network and division of labor in individual scientific collaborations[J]. Journal of the Association for Information Science and Technology, 2020, 71(10): 1162-1178.
6 Larivière V, Desrochers N, Macaluso B, et al. Contributorship and division of labor in knowledge production[J]. Social Studies of Science, 2016, 46(3): 417-435.
7 Macaluso B, Larivière V, Sugimoto T, et al. Is science built on the shoulders of women? A study of gender differences in contributorship[J]. Academic Medicine, 2016, 91(8): 1136-1142.
8 Haeussler C, Sauermann H. Division of labor in collaborative knowledge production: the role of team size and interdisciplinarity[J]. Research Policy, 2020, 49(6): 103987.
9 De Rassenfosse G, Higham K, Penner O. Scientific rewards for biomedical specialization are large and persistent[J]. BMC Biology, 2022, 20(1): Article No.211.
10 Shibayama S, Baba Y, Walsh J P. Organizational design of university laboratories: task allocation and lab performance in Japanese bioscience laboratories[J]. Research Policy, 2015, 44(3): 610-622.
11 Gorelick R. Combining richness and abundance into a single diversity index using matrix analogues of Shannon’s and Simpson’s indices[J]. Ecography, 2006, 29(4): 525-530.
12 Narayanan S, Balasubramanian S, Swaminathan J M. A matter of balance: specialization, task variety, and individual learning in a software maintenance environment[J]. Management Science, 2009, 55(11): 1861-1876.
13 Staats B R, Gino F. Specialization and variety in repetitive tasks: evidence from a Japanese bank[J]. Management Science, 2012, 58(6): 1141-1159.
14 Sauermann H, Haeussler C. Authorship and contribution disclosures[J]. Science Advances, 2017, 3(11): e1700404.
15 Allen L, Kiermer V, Porter S, et al. CRediT system for describing authors’ roles on papers could do even better[J]. Nature, 2025, 648(8092): 33-34.
16 Yang S L, Xiao A X, Nie Y, et al. Measuring coauthors’ credit in medicine field—based on author contribution statement and citation context analysis[J]. Information Processing & Management, 2022, 59(3): 102924.
17 卢超, 李梦婷, 陈秀娟, 等. 合贡献者网络的结构特征及其合作群体识别应用研究[J]. 情报学报, 2024, 43(7): 773-788.
18 Cai X Y, Han T. Analysis of the division of labor in China’s high-quality life sciences research[J]. Scientometrics, 2020, 125(2): 1077-1094.
19 卢超, 李梦婷, 周宸宇. 基于合贡献者网络的学者学术影响力评估研究[J]. 情报学报, 2025, 44(11): 1444-1457.
20 Corrêa Jr E A, Silva F N, da F Costa L, et al. Patterns of authors contribution in scientific manuscripts[J]. Journal of Informetrics, 2017, 11(2): 498-510.
21 Craig B M, Cosh S M, Luck C C. Research productivity, quality, and impact metrics of Australian psychology academics[J]. Australian Journal of Psychology, 2021, 73(2): 144-156.
22 Waltman L, Van Eck N J, Van Leeuwen T N, et al. Towards a new crown indicator: some theoretical considerations[J]. Journal of Informetrics, 2011, 5(1): 37-47.
23 Fox C W, Paine C E T, Sauterey B. Citations increase with manuscript length, author number, and references cited in ecology journals[J]. Ecology and Evolution, 2016, 6(21): 7717-7726.
24 Cui R M, Ding H, Zhu F. Gender inequality in research productivity during the COVID-19 pandemic[J]. Manufacturing & Service Operations Management, 2022, 24(2): 707-726.
25 Freeman R B, Huang W. Collaboration: strength in diversity[J]. Nature, 2014, 513(7518): 305.
26 Yegros-Yegros A, Rafols I, D’Este P. Does interdisciplinary research lead to higher citation impact? the different effect of proximal and distal interdisciplinarity[J]. PLoS One, 2015, 10(8): e0135095.
27 Lin Y L, Frey C B, Wu L F. Remote collaboration fuses fewer breakthrough ideas[J]. Nature, 2023, 623(7989): 987-991.
28 柳美君, 步一, 杨斯杰. 科研团队成员国别差异性的测度、演变及其与团队产出影响力的关系[J]. 情报学报, 2024, 43(7): 818-838.
29 He C C, Wu J, Zhang Q P. Research leadership flow determinants and the role of proximity in research collaborations[J]. Journal of the Association for Information Science and Technology, 2020, 71(11): 1341-1356.
30 Liu J W, Guo X F, Xu S, et al. Understanding super-partnerships in scientific collaboration: evidence from the field of economics[J]. Journal of the Association for Information Science and Technology, 2024, 75(6): 717-733.
31 Liu X, Bu Y, Li M, et al. Monodisciplinary collaboration disrupts science more than multidisciplinary collaboration[J]. Journal of the Association for Information Science and Technology, 2024, 75(1): 59-78.
32 Yoo H S, Jung Y L, Lee J Y, et al. The interaction of inter-organizational diversity and team size, and the scientific impact of papers[J]. Information Processing & Management, 2024, 61(6): 103851.
33 Sin S J. International coauthorship and citation impact: a bibliometric study of six LIS journals, 1980-2008[J]. Journal of the American Society for Information Science and Technology, 2011, 62(9): 1770-1783.
34 Wuchty S, Jones B F, Uzzi B. The increasing dominance of teams in production of knowledge[J]. Science, 2007, 316(5827): 1036-1039.
35 Cummings J N, Kiesler S. Coordination costs and project outcomes in multi-university collaborations[J]. Research Policy, 2007, 36(10): 1620-1634.
36 Boschma R. Proximity and innovation: a critical assessment[J]. Regional Studies, 2005, 39(1): 61-74.
37 Kiesler S, Cummings J N. What do we know about proximity and distance in work groups? a legacy of research[M]// Distributed Work. Cambridge: MIT Press, 2002: 57-82.
38 Broekel T, Boschma R. Knowledge networks in the Dutch aviation industry: the proximity paradox[J]. Journal of Economic Geography, 2012, 12(2): 409-433.
39 Fernández A, Ferrándiz E, León M D. Proximity dimensions and scientific collaboration among academic institutions in Europe: the closer, the better?[J]. Scientometrics, 2016, 106(3): 1073-1092.
40 Petruzzelli A M. The impact of technological relatedness, prior ties, and geographical distance on university–industry collaborations: a joint-patent analysis[J]. Technovation, 2011, 31(7): 309-319.
41 Gui Q C, Liu C L, Du D B. International knowledge flows and the role of proximity[J]. Growth and Change, 2018, 49(3): 532-547.
42 Ponds R, Van Oort F, Frenken K. The geographical and institutional proximity of research collaboration[J]. Papers in Regional Science, 2007, 86(3): 423-444.
43 Hoekman J, Frenken K, Tijssen R J W. Research collaboration at a distance: changing spatial patterns of scientific collaboration within Europe[J]. Research Policy, 2010, 39(5): 662-673.
44 Bruneel J, D’Este P, Salter A. Investigating the factors that diminish the barriers to university–industry collaboration[J]. Research Policy, 2010, 39(7): 858-868.
45 Burnham J F. Scopus database: a review[J]. Biomedical Digital Libraries, 2006, 3(1): Article No.1.
46 Lin Z H, Yin Y A, Liu L, et al. SciSciNet: a large-scale open data lake for the science of science research[J]. Scientific Data, 2023, 10: Article No.315.
47 Wu M J, Sivertsen G, Zhang L, et al. Scaling research aim identification: language models for classifying scientific and societal-oriented studies[J]. Journal of the Association for Information Science and Technology, 2025, 76(11): 1470-1487.
48 Uzzi B, Mukherjee S, Stringer M, et al. Atypical combinations and scientific impact[J]. Science, 2013, 342(6157): 468-472.
49 Herfindahl O C. Concentration in the steel industry[D]. New York: Columbia University, 1950: 25-30.
50 Velez-Estevez A, García-Sánchez P, Moral-Munoz J A, et al. Why do papers from international collaborations get more citations? A bibliometric analysis of Library and Information Science papers[J]. Scientometrics, 2022, 127(12): 7517-7555.
51 G?k A, Karaulova M. How “international” is international research collaboration?[J]. Journal of the Association for Information Science and Technology, 2024, 75(2): 97-114.
52 Rodríguez D, Sicilia M A, García E, et al. Empirical findings on team size and productivity in software development[J]. Journal of Systems and Software, 2012, 85(3): 562-570.
53 Wu L F, Wang D S, Evans J A. Large teams develop and small teams disrupt science and technology[J]. Nature, 2019, 566(7744): 378-382.
54 Ductor L. Does co-authorship lead to higher academic productivity?[J]. Oxford Bulletin of Economics and Statistics, 2015, 77(3): 385-407. 责任编辑 魏瑞斌） |
|
|
|
