科研团队多样性对学术颠覆性创新的影响研究——以人工智能领域为例

doi:10.3772/j.issn.1000-0135.2023.01.005

情报学报

2023, Vol. 42

Issue (1): 43-58 DOI: 10.3772/j.issn.1000-0135.2023.01.005

情报理论与方法

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科研团队多样性对学术颠覆性创新的影响研究——以人工智能领域为例

唐旭丽¹, 李信²

1.华中师范大学信息管理学院，武汉 430079
2.华中科技大学同济医学院医药卫生管理学院，武汉 430030

Effect of the Diversity of Scientific Teams on Disruptive Innovation in Academia: A Case Study in the Field of Artificial Intelligence

Tang Xuli¹, Li Xin²

1.School of Information Management, Central China Normal University, Wuhan 430079
2.School of Medicine and Health Management, Tongji Medical College of Huazhong University of Science and Technology, Wuhan 430030

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摘要学术颠覆性创新作为科学创新的重要组成部分，已经成为当代科技进步和经济发展的新引擎。然而，我们对学术颠覆性创新产生的关键影响因素依然知之甚少。因此，本文以学术创新的主体即科研团队为研究对象，从信息多样性、社会属性多样性和行为意愿多样性三个层面，系统分析了科研团队的组成多样性对学术颠覆性创新的影响机制。首先，本文基于微软学术图谱中1950—2019年人工智能领域的合作文献为数据源，使用主题模型、文本挖掘等技术对作者特征进行抽取和表示，构建科研团队多样性指标体系；同时，通过计算每篇文献的颠覆性创新指数，以衡量其学术颠覆性创新程度。然后，采用相关性分析和OLS（ordinary least squares）回归分析，剔除与学术颠覆性创新显著不相关的科研团队多样性指标，得到候选指标集。最后，利用广义精确匹配方法，构建因果模型以揭示科研团队多样性与学术颠覆性创新之间的因果关系。研究结果表明，在人工智能领域，科研团队的主题多样性和国家多样性均与学术颠覆性创新程度呈现负向因果效应：科研团队主题多样性的增加，会使学术颠覆性创新程度下降8.776%~19.000%；科研团队国家多样性的增加，会使学术颠覆性创新程度下降5.493%~7.693%。此外，本文还发现，在人工智能领域，科研团队的行为意愿多样性与学术颠覆性创新程度间无明显因果效应。

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	唐旭丽
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关键词 ：科研团队多样性, 颠覆性创新, 人工智能, 因果关联

收稿日期: 2021-11-16

基金资助:教育部人文社会科学研究青年项目“因果推断视角下科研团队多样性和突破性创新文献间关系研究”（22YJC870014）；国家自然科学基金青年科学基金项目“基于深度语义理解的生物医学论文临床转化分析研究”（72204090）。

作者简介: 唐旭丽，女，1993年生，博士，讲师，主要研究领域为科学团队与科学创新、知识组织；李信，男，1991年生，博士，讲师，硕士生导师，主要研究领域为科学创新与计量、信息检索与文本挖掘，E-mail：xl60@hust.edu.cn；

引用本文:

唐旭丽, 李信. 科研团队多样性对学术颠覆性创新的影响研究——以人工智能领域为例[J]. 情报学报, 2023, 42(1): 43-58.
Tang Xuli, Li Xin. Effect of the Diversity of Scientific Teams on Disruptive Innovation in Academia: A Case Study in the Field of Artificial Intelligence. 情报学报, 2023, 42(1): 43-58.

链接本文:

https://qbxb.istic.ac.cn/CN/10.3772/j.issn.1000-0135.2023.01.005 或 https://qbxb.istic.ac.cn/CN/Y2023/V42/I1/43

1 Christensen C M. The innovator’s dilemma: when new technologies cause great firms to fail[M]. Boston: Harvard Business Review Press, 2013.
2 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.
3 Lyu D Q, Gong K L, Ruan X M, et al. Does research collaboration influence the “disruption” of articles? Evidence from neurosciences[J]. Scientometrics, 2021, 126(1): 287-303.
4 张光宇, 欧春尧, 刘贻新, 等. 人工智能企业何以实现颠覆性创新? ——基于扎根理论的探索[J]. 科学学研究, 2021, 39(4): 738-748, 757.
5 廖青云, 朱东华, 汪雪锋, 等. 科研团队的多样性对团队绩效的影响研究[J]. 科学学研究, 2021, 39(6): 1074-1083.
6 Iwasaki A. Why we need to increase diversity in the immunology research community[J]. Nature Immunology, 2019, 20(9): 1085-1088.
7 Zhang C W, Bu Y, Ding Y, et al. Understanding scientific collaboration: Homophily, transitivity, and preferential attachment[J]. Journal of the Association for Information Science and Technology, 2018, 69(1): 72-86.
8 Nielsen M W, Bloch C W, Schiebinger L. Making gender diversity work for scientific discovery and innovation[J]. Nature Human Behaviour, 2018, 2(10): 726-734.
9 Schiebinger L. Has feminism changed science?[J]. Signs: Journal of Women in Culture and Society, 2000, 25(4): 1171-1175.
10 章振, 张燕, 侯立文, 等. 理解团队多样性: 理论、机制与情境[J]. 南大商学评论, 2012(2): 127-146.
11 邓今朝, 王重鸣. 团队多样性对知识共享的反向作用机制研究[J]. 科学管理研究, 2008, 26(6): 25-27, 53.
12 Lee Y N, Walsh J P, Wang J. Creativity in scientific teams: unpacking novelty and impact[J]. Research Policy, 2015, 44(3): 684-697.
13 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.
14 Woolley A W, Chabris C F, Pentland A, et al. Evidence for a collective intelligence factor in the performance of human groups[J]. Science, 2010, 330(6004): 686-688.
15 Freeman R B, Huang W. Collaboration: strength in diversity[J]. Nature, 2014, 513(7518): 305.
16 AlShebli B K, Rahwan T, Woon W L. The preeminence of ethnic diversity in scientific collaboration[J]. Nature Communications, 2018, 9: Article No.5163.
17 张琳, 孙蓓蓓, 黄颖. 跨学科合作模式下的交叉科学测度研究——以ESI社会科学领域高被引学者为例[J]. 情报学报, 2018, 37(3): 231-242.
18 Harrison D A, Klein K J. What’s the difference? Diversity constructs as separation, variety, or disparity in organizations[J]. Academy of Management Review, 2007, 32(4): 1199-1228.
19 van Knippenberg D, Schippers M C. Work group diversity[J]. Annual Review of Psychology, 2007, 58: 515-541.
20 Pelled L H, Eisenhardt K M, Xin K R. Exploring the black box: an analysis of work group diversity, conflict and performance[J]. Administrative Science Quarterly, 1999, 44(1): 1-28.
21 de Montjoye Y A, Stopczynski A, Shmueli E, et al. The strength of the strongest ties in collaborative problem solving[J]. Scientific Reports, 2014, 4: 5277.
22 Bu Y, Ding Y, Liang X K, et al. Understanding persistent scientific collaboration[J]. Journal of the Association for Information Science and Technology, 2018, 69(3): 438-448.
23 Jehn K A, Northcraft G B, Neale M A. Why differences make a difference: a field study of diversity, conflict and performance in workgroups[J]. Administrative Science Quarterly, 1999, 44(4): 741-763.
24 刘宁, 贾俊生. 研发团队多元性、知识分享与创新绩效关系的实证研究[J]. 南开管理评论, 2012, 15(6): 85-92, 103.
25 樊路青, 刘雯雯, 王印. 团队多样性、认知需求与团队绩效——以林业企业管理团队为例[J]. 中国林业经济, 2020(3): 22-26, 58.
26 Dahlin K B, Behrens D M. When is an invention really radical?: Defining and measuring technological radicalness[J]. Research Policy, 2005, 34(5): 717-737.
27 Woodman R W, Sawyer J E, Griffin R W. Toward a theory of organizational creativity[J]. Academy of Management Review, 1993, 18(2): 293-321.
28 黄芳, 马剑虹, 张俊飞. 跨职能知识共享对团队创新绩效的影响机制探索[J]. 应用心理学, 2009, 15(4): 339-346.
29 屈晓倩, 刘新梅. 信息型团队断裂影响团队创造力的作用机理研究[J]. 管理科学, 2016, 29(2): 18-28.
30 Ren H, Gray B, Harrison D A. Triggering faultline effects in teams: the importance of bridging friendship ties and breaching animosity ties[J]. Organization Science, 2015, 26(2): 390-404.
31 屈晓倩, 刘新梅, 雷宏振. 外部视角下信息型断裂影响团队创造力的作用机理研究[J]. 管理学报, 2020, 17(4): 536-543.
32 卫旭华, 刘咏梅, 岳柳青. 高管团队权力不平等对企业创新强度的影响——有调节的中介效应[J]. 南开管理评论, 2015, 18(3): 24-33.
33 Loyd D L, Wang C S, Phillips K W, et al. Social category diversity promotes premeeting elaboration: the role of relationship focus[J]. Organization Science, 2013, 24(3): 757-772.
34 Li J Y, Wu H, Deng Z H, et al. How professional capital and team heterogeneity affect the demands of online team-based medical service[J]. BMC Medical Informatics and Decision Making, 2019, 19: Article No.119.
35 Tafel H, Turner J C. The social identity theory of intergroup behavior[C]// Psychology of Intergroup Relations. Chicago: Nelson Hall, 1986: 7-24.
36 Thatcher S M B, Brown S A. Individual creativity in teams: the importance of communication media mix[J]. Decision Support Systems, 2010, 49(3): 290-300.
37 Faems D, Subramanian A M. R&D manpower and technological performance: the impact of demographic and task-related diversity[J]. Research Policy, 2013, 42(9): 1624-1633.
38 Thatcher S M B, Patel P C. Group faultlines: a review, integration, and guide to future research[J]. Journal of Management, 2012, 38(4): 969-1009.
39 杜娟, 赵曙明, 林新月. 悖论型领导风格情境下团队断层与团队创造力的作用机制研究[J]. 管理学报, 2020, 17(7): 988-997.
40 Pearsall M J, Ellis A P J, Evans J M. Unlocking the effects of gender faultlines on team creativity: is activation the key?[J]. Journal of Applied Psychology, 2008, 93(1): 225-234.
41 Ferguson A J, Peterson R S. Sinking slowly: diversity in propensity to trust predicts downward trust spirals in small groups[J]. Journal of Applied Psychology, 2015, 100(4): 1012-1024.
42 Srivastava A, Bartol K M, Locke E A. Empowering leadership in management teams: effects on knowledge sharing, efficacy, and performance[J]. Academy of Management Journal, 2006, 49(6): 1239-1251.
43 Lee P, Gillespie N, Mann L, et al. Leadership and trust: their effect on knowledge sharing and team performance[J]. Management Learning, 2010, 41(4): 473-491.
44 Tang C Y, Naumann S E. Team diversity, mood, and team creativity: the role of team knowledge sharing in Chinese R & D teams[J]. Journal of Management & Organization, 2016, 22(3): 420-434.
45 Frank M R, Wang D S, Cebrian M, et al. The evolution of citation graphs in artificial intelligence research[J]. Nature Machine Intelligence, 2019, 1(2): 79-85.
46 Tang X L, Li X, Ding Y, et al. The pace of artificial intelligence innovations: speed, talent, and trial-and-error[J]. Journal of Informetrics, 2020, 14(4): 101094.
47 Santamaría L, Mihaljevi? H. Comparison and benchmark of name-to-gender inference services[J]. PeerJ Computer Science, 2018, 4: e156.
48 de Nicola A, D’Agostino G. Assessment of gender divide in scientific communities[J]. Scientometrics, 2021, 126(5): 3807-3840.
49 Abramo G, D’Angelo C A, Murgia G. Gender differences in research collaboration[J]. Journal of Informetrics, 2013, 7(4): 811-822.
50 Lu C, Bu Y, Wang J, et al. Examining scientific writing styles from the perspective of linguistic complexity[J]. Journal of the Association for Information Science and Technology, 2019, 70(5): 462-475.
51 Kim J, Kim J, Owen-Smith J. Generating automatically labeled data for author name disambiguation: an iterative clustering method[J]. Scientometrics, 2019, 118(1): 253-280.
52 García-Suaza A, Otero J, Winkelmann R. Predicting early career productivity of PhD economists: does advisor-match matter?[J]. Scientometrics, 2020, 122(1): 429-449.
53 Ye J T, Han S C, Hu Y F, et al. Nationality classification using name embeddings[C]// Proceedings of the 2017 ACM Conference on Information and Knowledge Management. New York: ACM Press, 2017: 1897-1906.
54 Battiston F, Musciotto F, Wang D S, et al. Taking census of physics[J]. Nature Reviews Physics, 2019, 1(1): 89-97.
55 Usoro A, Sharratt M W, Tsui E, et al. Trust as an antecedent to knowledge sharing in virtual communities of practice[J]. Knowledge Management Research & Practice, 2007, 5(3): 199-212.
56 deB Beaver D, Rosen R. Studies in scientific collaboration: Part I. The professional origins of scientific co-authorship[J]. Scientometrics, 1978, 1: 65-84.
57 Funk R J, Owen-Smith J. A dynamic network measure of technological change[J]. Management Science, 2017, 63(3): 791-817.
58 Bornmann L, Tekles A. Disruptive papers published in Scientometrics[J]. Scientometrics, 2019, 120(1): 331-336.
59 Zhang L, Rousseau R, Gl?nzel W. Diversity of references as an indicator of the interdisciplinarity of journals: taking similarity between subject fields into account[J]. Journal of the Association for Information Science and Technology, 2016, 67(5): 1257-1265.
60 Hirsch J E. Response to comment “hα: the scientist as chimpanzee or bonobo”, by Leydesdorff, Bornmann and Opthof[J]. Scientometrics, 2019, 118: 1167-1172.
61 Uzzi B, Mukherjee S, Stringer M, et al. Atypical combinations and scientific impact[J]. Science, 2013, 342(6157): 468-472.
62 Iacus S M, King G, Porro G. A theory of statistical inference for matching methods in causal research[J]. Political Analysis, 2019, 27(1): 46-68.
63 Iacus S M, King G, Porro G. Causal inference without balance checking: coarsened exact matching[J]. Political Analysis, 2012, 20(1): 1-24.