Breakthrough inventions are key factors for a firm to enhance its core competitiveness in the market. Therefore, it is imperative to promote breakthrough inventions through the transformation of scientific and technological achievements. Dual innovation stars refer to individuals who are both star scientists and star inventors, and they are crucial to the transformation of scientific and technological achievements. Existing studies generally believe that star scientists and inventors can bring more breakthrough inventions. These studies contribute to the influence of star scientists or star inventors on breakthrough inventions from a single perspective, leaving a void in dual innovation stars.
Thus, it is necessary to further examine the intrinsic mechanisms and boundary conditions of the relationships between dual innovation stars and breakthrough inventions. This paper constructs a moderated mediation model to investigate the relationships between dual innovation stars and breakthrough inventions. Scientific and technological knowledge owned by inventors is tacit, and can only be effectively transferred through face-to-face collaborations. Collaborative networks, namely scientific and technological collaboration networks, are thus being formed as a result of knowledge sharing. The overlap of scientific and technological collaboration networks may affect their transformation of scientific knowledge into technological application. This study uses network overlap as a mediator between dual innovation stars and breakthrough inventions and constructs a mediating model for dual innovation stars to generate breakthrough inventions. In addition, following the heterogeneity theory, the study reveals the boundary conditions of dual innovation stars to generate breakthrough inventions with resource heterogeneity and innovation capacity heterogeneity as contingency factors.
The study takes the inventors at Huawei and Intel as a sample, with the number of inventors being 2 603 and 4 396, respectively. It collects the scientific papers and patent data published by Huawei and Intel from the Web of Science database and the United States Patent and Trademark Office (USPTO) between 2000 and 2022, respectively. On the basis of the data fields of the authors and patent applicants, Sci2 Tool software is used to construct the internal scientific and technological cooperation networks of the two companies. The results show that dual innovation stars and?network overlap positively influence breakthrough inventions; the network overlap based on scientific and technological collaboration mediates the relationships between dual innovation stars and breakthrough inventions; resource heterogeneity positively moderates the positive relationship between the network overlap and breakthrough inventions, and further positively moderates the indirect effect of dual innovation stars on breakthrough inventions through the network overlap.
With the identification of the dual innovation stars in the companies , the study uses the network overlap to measure the similarity of scientific and technological cooperation networks, revealing the “black box” between dual innovation stars and breakthrough inventions. It not only enriches the study of scientific and technological innovation interaction, but also explains the mechanism by which dual innovation stars generate breakthrough inventions. By exploring how resource heterogeneity and innovation capability heterogeneity affect the relationship between network overlap and breakthrough inventions, the study provides management implications for firms to manage inventors′ innovation behavior. First, since dual innovation stars are important media for internal transfer and integration of technological knowledge within enterprises, managers should encourage and support dual innovation stars to host patent invention activities and achieve effective transfer of scientific knowledge to breakthrough inventions. Meanwhile, managers should actively explore potential celebrity scientists and inventors to help them transform into dual innovative celebrities. Second, inventors can establish cross-border cooperation relationships with partners, while maintaining existing technological cooperation, further expanding the cooperation relationship to the field of scientific research, promoting the exchange and integration of scientific and technological knowledge through a dual cooperation network, and thus achieving breakthrough inventions. Third, when there is high resource heterogeneity between inventors and technology partners, inventors can obtain diverse complementary resources through technology partners, and the cooperation network can play a role. Therefore, inventors should consider technological background as an important factor when choosing technology partners to avoid the trend of knowledge homogenization in the cooperation network.
[1] CAPPONI G, MARTINELLI A, NUVOLARI A. Breakthrough innovations and where to find them[J]. Research Policy, 2022, 51(1): 104376.
[2] 邵云飞, 谢丽. 网络结构嵌入对企业突破性创新绩效的影响——以生物医药上市企业为例[J]. 科技进步与对策, 2023, 40(18): 72-79.
[3] 王伦, 林润辉. 研发伙伴组合多样性对突破式创新的影响研究——企业内外部环境因素的调节作用[J]. 软科学, 2023: 37(10): 32-38.
[4] COHEN S K,CANER T.Converting inventions into breakthrough innovations: the role of exploitation and alliance network knowledge heterogeneity[J]. Journal of Engineering and Technology Management, 2016, 40: 29-44.
[5] ZHOU W, GU X, YANG X. The impact of knowledge search balance on the generality and specificity of breakthrough innovation[J]. Technology Analysis & Strategic Management, 2022, 34(11): 1310-1325.
[6] BEAUDRY C, SCHIFFAUEROVA A. Impacts of collaboration and network indicators on patent quality: the case of Canadian nanotechnology innovation[J]. European Management Journal, 2011, 29(5): 362-376.
[7] HOHBERGER J. Does it pay to stand on the shoulders of giants? an analysis of the inventions of star inventors in the biotechnology sector[J]. Research Policy, 2016, 45(3): 682-698.
[8] 荣雪云, 杨中楷, 刘娜. 发明人角色识别及二元创新能力差异分析——社会资本视角的解释[J]. 科技进步与对策, 2020, 37(19): 1-8.
[9] DU J, LI P, GUO Q, et al. Measuring the knowledge translation and convergence in pharmaceutical innovation by funding-science-technology-innovation linkages analysis[J]. Journal of Informetrics, 2019, 13(1): 132-148.
[10] CHOI J U, LEE C Y. The differential effects of basic research on firm R&D productivity: the conditioning role of technological diversification[J]. Technovation, 2022, 118: 102559.
[11] 柳卸林. 大企业如何通过基础研究实现突破性创新[J]. 人民论坛·学术前沿, 2023, 12(9): 44-51.
[12] FLEMING L, SORENSON O. Science as a map in technological search[J]. Strategic Management Journal, 2004, 25(8-9): 909-928.
[13] FURUKAWA R, GOTO A. The role of corporate scientists in innovation[J]. Research Policy, 2006, 35(1): 24-36.
[14] GRUBER M, HARHOFF D, HOISL K. Knowledge recombination across technological boundaries: scientists vs. engineers[J]. Management Science, 2013, 59(4): 837-851.
[15] 李从刚, 许荣, 路璐, 等. 明星科学家在创新活动中的作用:一个文献综述[J]. 科技进步与对策, 2019, 36(21): 155-160.
[16] BABA Y, SHICHIJO N, SEDITA S R. How do collaborations with universities affect firms′ innovative performance? the role of "Pasteur scientists" in the advanced materials field[J]. Research Policy, 2009, 38(5): 756-764.
[17] ARDITO L, NATALICCHIO A, APPIO F P, et al. The role of scientific knowledge within inventing teams and the moderating effects of team internationalization and team experience: empirical tests into the aerospace sector[J]. Journal of Business Research, 2021, 128: 701-710.
[18] COLEN L, BELDERBOS R, KELCHTERMANS S, et al. Reaching for the stars: when does basic research collaboration between firms and academic star scientists benefit firm invention performance[J]. Journal of Product Innovation Management, 2022, 39(2): 222-264.
[19] GITTELMAN M, KOGUT B. Does good science lead to valuable knowledge? biotechnology firms and the evolutionary logic of citation patterns[J]. Management Science, 2003, 49(4): 366-382.
[20] MAURSETH P B, SVENSSON R. The importance of tacit knowledge: dynamic inventor activity in the commercialization phase[J]. SSRN Electronic Journal, 2020, 49(7): 104012.
[21] 毕静煜, 谢恩, 魏海笑. 联盟伙伴技术多样性对企业突破性创新的影响——研发联盟组合特征的调节作用[J]. 研究与发展管理, 2021, 33(2): 41-52.
[22] LEONE M I, PETRUZZELLI A M, NATALICCHIO A. Boundary spanning through external technology acquisition: the moderating role of star scientists and upstream alliances[J]. Technovation, 2022, 116: 102496.
[23] KHANNA R. Aftermath of a tragedy: A star′s death and coauthors′ subsequent productivity[J]. Research Policy, 2021, 50(2): 104159.
[24] KHANNA R.Passing the torch of knowledge:star death, collaborative ties, and knowledge creation[J]. Research Policy, 2023, 52(1): 104649.
[25] ROCHE M P, CONTI A, ROTHAERMEL F T. Different founders, different venture outcomes: a comparative analysis of academic and non-academic startups[J]. Research Policy, 2020, 49(10): 104062.
[26] 毛荐其, 嵇金星, 刘娜, 等. 发明者网络嵌入、稳定性与创新绩效的关系研究[J]. 科学决策, 2021, 28(3): 1-17.
[27] ZANG J. Structural holes, exploratory innovation and exploitative innovation[J]. Management Decision, 2018, 56(8): 1682-1695.
[28] ZHANG Z,LUO T.Knowledge structure, network structure, exploitative and exploratory innovations[J]. Technology Analysis & Strategic Management, 2020, 32(6): 666-682.
[29] YAN Y, GUAN J C. Social capital, exploitative and exploratory innovations: the mediating roles of ego-network dynamics[J]. Technological Forecasting and Social Change, 2018, 126: 244-258.
[30] INKPEN A C, CURRALL S C. The coevolution of trust, control, and learning in joint ventures[J]. Organization Science, 2004, 15(5): 586-599.
[31] MIAO Y Z, SALOMON R M, SONG J. Learning from technologically successful peers: the convergence of asian laggards to the technology frontier[J]. Organization Science, 2021, 32(1): 210-232.
[32] HENRICH J, CHUDEK M, BOYD R. The big man mechanism: how prestige fosters cooperation and creates prosocial leaders[J]. Philosophical Transactions of The Royal Society B-Biological Sciences, 2015, 370 (1683): 20150013.
[33] HEWITT-DUNDAS N, GKYPALI A, ROPER S. Does learning from prior collaboration help firms to overcome the 'two-worlds' paradox in university-business collaboration[J]. Research Policy, 2019, 48(5): 1310-1322.
[34] CORSARO D, CANTU C, TUNISINI A. Actors′ heterogeneity in innovation networks[J]. Industrial Marketing Management, 2012, 41(5): 780-789.
[35] 刘娜, 嵇金星, 毛荐其, 等. 发明者网络社群动态配置及对创新能力的影响[J]. 科研管理, 2021, 42(9): 44-51.
[36] 刘娜, 嵇金星, 毛荐其, 等. 发明者网络社群系统识别、结构动态及对创新绩效的影响——网络位置的双重调节作用[J]. 科技进步与对策, 2021, 38(3): 11-20.
[37] WANG J, YANG N. Dynamics of collaboration network community and exploratory innovation: the moderation of knowledge networks[J]. Scientometrics, 2019, 121(2): 1067-1084.
[38] SANTORO G, BRESCIANI S, PAPA A. Collaborative modes with cultural and creative industries and innovation performance: the moderating role of heterogeneous sources of knowledge and absorptive capacity[J]. Technovation, 2020, 92-93: 102040.
[39] BAUM J A C, CALABRESE T, SILVERMAN B S. Don′t go it alone: alliance network composition and startups′ performance in Canadian biotechnology[J]. Strategic Management Journal, 2000, 21(3): 267-294.
[40] GOMEZ-NUNEZ A J, BATAGELJ V, VARGAS-QUESADA B, et al. Optimizing scimago journal & country rank classification by community detection[J]. Journal of Informetrics, 2014, 8(2): 369-383.
[41] 温忠麟, 叶宝娟. 有调节的中介模型检验方法:竞争还是替补[J]. 心理学报, 2014, 46(5): 714-726.
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