With the acceleration of technology iteration and the ecological networking trend, more and more enterprises realize the importance of the open innovation platforms, since only by socializing value co-creation with more ecological participants can they further tap the innovation-driven value of internal and external knowledge. Many enterprises have established the open innovation platform, attracting quite a few users, suppliers, distributors to participate in the creative design and technological research and development.As the core of the whole ecosystem, the platform-leading enterprises are not only "economic organizations" with private attributes but also an ecological public field with social attributes. Therefore, different from the previous R&D cooperation, R&D alliance, or other market-based organization forms, the open innovation platform is more open and inclusive. While creating greater economic benefits for the leading enterprises, it also attaches great importance to the sharing, integration and creation of knowledge among various parties within the platform, so that the knowledge continues to upgrade at the overall level. This fully reflects that the open innovation platform can reshape the value of knowledge and effectively balance private economic interests and public social interests through the concept of value sharing. However, increasing participants bring complexity and vulnerability due to differing needs and interests, and issues like poor governance and benefit distribution hinder collaboration. Effective governance of knowledge activities is needed to prevent opportunism, improve knowledge management, and strengthen innovation cohesion.
On the basis of knowledge governance theory and knowledge-based view, the paper firstly proposes dual knowledge transformation links of "explicit knowledge combination" and "tacit knowledge socialization" among platform subjects, considering the explicit and implicit characteristics of knowledge will result in heterogeneous knowledge transformation process, which broadens the cognitive boundary of how to integrate knowledge resources and upgrade innovation mode within the platform. Then,it investigates the influence mechanism of platform social-based and market-based knowledge governance on platform participants' breakthrough innovation, with the empirical analysis results showing that both market-based and society-based governance mechanisms and their interaction term can positively influence the breakthrough innovation performance of platform participants, during which the heterogeneous knowledge transformation links of "tacit knowledge socialization" and "explicit knowledge combination" play the role of parallel chain mediators.
Different from traditional network or alliance governance that only emphasizes the logic of behavioral constraints, this study aims to analyze that the combination of governance mechanisms can coordinate the knowledge interaction and innovation value proposition of platform participants through both incentives and constraints measures, and thus enhance the understanding of how the platform knowledge governance will enable the upgrading of innovation mode. In conclusion, by constructing a comprehensive research model of platform knowledge governance mechanism, knowledge transformation dual-links and breakthrough innovation performance, this paper has provided certain theoretical value and practical significance for the platform core enterprises to scientifically control knowledge governance efforts, continuously optimize platform knowledge generation and knowledge diffusion, and help upgrade the exploratory and breakthrough innovation.
Enterprises, influenced by their unique industry backgrounds and technological fields, face a choice between technology-oriented and market-oriented innovation strategies. In order to strike a balance, optimizing open innovation platform policies can help establish an ecological industrial system with distributed innovation advantages. Big data and digital twins can aid in creating accessible knowledge bases for incremental innovation among SMEs. Meanwhile, to overcome foreign technology blockades, preferential policies should be issued to encourage high-quality knowledge co-creation, enhancing platform entities' cooperative innovation willingness and breakthrough innovation capabilities through improved knowledge income distribution, decision-making power, and credit systems based on individual contributions. In addition, both platform core enterprises and user enterprises should strive to break through the existing one-dimensional thinking and realize that there are more diversified knowledge production modes in the digital knowledge interaction space. Moreover, considering the rapid iteration and updating of knowledge requirements and application scenarios, the core enterprise of the platform needs to build a flexible governance framework that is capable of accommodating varying degrees of knowledge objectives and innovation priorities among different stakeholders.
[1] CHESBROUGH H, VANHAVERBEKE W, WEST J. Open innovation: researching a new paradigm[M]. New York: Oxford University Press, 2008.
[2] 肖红军, 阳镇, 姜倍宁. 平台企业社会责任感知会激励用户参与平台治理吗—基于网络效应的边界条件与反思[J]. 经济与管理研究, 2023, 44(3):72-88.
[3] FOSS N J, HUSTED K, MICHAILOVA S. Governing knowledge sharing in organizations: levels of analysis, governance mechanisms and research directions [J]. Journal of Management Studies, 2010, 47(3) : 455-482.
[4] CAVALLO A, BURGERS H, GHEZZI A, et al. The evolving nature of open innovation governance: a study of a digital platform development in collaboration with a big science centre[J]. Technovation, 2022, 116:102370.
[5] 向阳, 曹勇. 企业创新网络知识治理与知识转移:基于战略性新兴产业的实证研究[J]. 管理评论, 2015, 27(9):48-58.
[6] PEMSEL S, WIEWIORA A, MLLER R,et al.A conceptualization of knowledge governance in project-based organizations[J]. International Journal of Project Management, 2014, 32(8):1411-1422.
[7] 王雎. 开放式创新下的知识治理:基于认知视角的跨案例研究[J]. 南开管理评论, 2009, 12(3):45-53.
[8] BOUNCKEN R B, HUGHES M, RATZMANN M, et al. Family firms, alliance governance, and mutual knowledge creation[J]. British Journal of Management,2020,31(4):769-791.
[9] 于淼, 朱方伟, 张杰, 等. 知识治理:源起、前沿研究与理论框架[J]. 科研管理, 2021, 42(4):65-72.
[10] HARMANCIOGLU N, S??KSJ?RVI M, HULTINK E J. Cannibalize and combine? the impact of ambidextrous innovation on organizational outcomes under market competition[J]. Industrial Marketing Management, 2020, 85: 44-57.
[11] SHAFIQUE I, KALYAR M N, SHAFIQUE M, et al. Demystifying the link between knowledge management capability and innovation ambidexterity: organizational structure as a moderator[J]. Business Process Management Journal, 2022, 28 (5/6): 1343-1363.
[12] BERRAIES S, ZINE El ABIDINE S. Do leadership styles promote ambidextrous innovation? case of knowledge-intensive firms[J]. Journal of Knowledge Management, 2019, 23(5): 836-859.
[13] ANIS K, JAMAL A. Sourcing knowledge for innovation: knowledge reuse and creation in project teams[J]. Journal of Knowledge Management, 2015, 19(5):932-948.
[14] LEI H, GUI L, LE P B. Linking transformational leadership and frugal innovation: the mediating role of tacit and explicit knowledge sharing[J]. Journal of Knowledge Management, 2021, 25(7):1832-1852.
[15] 焦豪. 数字平台生态观: 数字经济时代的管理理论新视角[J]. 中国工业经济, 2023, 34(3): 122-141.
[16] INOUE Y. Indirect innovation management by platform ecosystem governance and positioning: toward collective ambidexterity in the ecosystems[J]. Technological Forecasting and Social Change, 2021, 166(4): 120652.
[17] JACOBIDES M G, CENNAMO C, GAWER A. Towards a theory of ecosystems[J]. Strategic Management Journal, 2018, 39(8): 2255-2276.
[18] WANG L, YEUNG J H Y, ZHANG M. The impact of trust and contract on innovation performance: the moderating role of environmental uncertainty[J].International Journal of Production Economics, 2011, 134 (1) : 114-122.
[19] ELFENBEIN D W , ZENGER T. Creating and capturing value in repeated exchange relationships: the second paradox of embeddedness[J]. Organization Science,2017,28(5):894-914.
[20] NONAKA I A. Dynamic theory of organizational knowledge creation[J]. Organization Science, 1994, 5(1):14-37.
[21] 刘少凤. 知识管理——赋能商业决策的一战式工具[M]. 北京:中信出版社, 2022:3-11.
[22] 赵蓉英, 刘卓著, 王君领. 知识转化模型SECI的再思考及改进[J].情报杂志, 2020, 39(11):173-180.
[23] 史轩亚,陈其齐,杜义飞,等.知识转化视角下CMNEs结构嵌入与关系嵌入互动过程研究[J].研究与发展管理, 2021,33(2):122-135,150.
[24] ZHAO J, XI X, LI B, et al. Research on radical innovation implementation through knowledge reuse based on knowledge flow: a case study on academic teams[J]. Information & Management, 2020, 57(8):103260.
[25] 杨敏,陈泽明.企业研发投入、知识生态与价值创造[J].统计与决策,2023,39(15):172-177.
[26] 卢艳秋, 宋昶, 王向阳. 基于工业互联网平台的企业间知识复用研究[J].情报科学, 2022, 40(2):141-147,161.
[27] GOODERHAM P, D B MINBAEVA, T PEDERSEN. Governance mechanisms for the promotion of social capital for knowledge transfer in multinational corporations[J]. Journal of Management Studies, 2011, 48(1):123-150.
[28] 姚伟, 周鹏, 柯平. 计算知识管理科学:数智化时代的知识管理研究路径[J].情报理论与实践, 2023,46 (2):15-23.
[29] JAKUBIK M, MUURSEPPP. From knowledge to wisdom: will wisdom management replace knowledge management[J]. European Journal of Management and Business Economics, 2022, 31(3):367-389.
[30] SRINIVASAN R, CHOO A, NARAYANAN S, et al. Knowledge sources, innovation objectives, and their impact on innovation performance: quasi-replication of leiponen and helfat[J]. Strategic Management Journal, 2021,42(11):2104-2136.
[31] YAYAVARAM S, CHEN W R. Changes in firm knowledge couplings and firm innovation performance:the moderating role of technological complexity[J]. Strategic Management Journal, 2015, 36(3):377-396.
[32] JAYARAM J, PATHAK S. A holistic view of knowledge integration in collaborative supply chains[J]. International Journal of Production Research, 2013, 51(7): 1958-1972.
[33] 吕佳,陈万明, 彭灿.主动遗忘、知识治理与企业突破式创新—环境动荡性的调节作用[J]. 科技进步与对策, 2017, 34(21):103-110.
[34] 朱祖平,阮荣彬,宋格.开放式创新平台激励与约束机制对用户创新行为的影响[J].科技进步与对策, 2024,41(3):44-54.
[35] 王瑞花, 吕永波.人际关系视角下组织内知识共享敌意的知识治理研究[J].科技进步与对策, 2017, 34(19):128-136.
[36] 姚艳虹, 李扬帆. 企业创新战略与知识结构的匹配性研究[J]. 科学学与科学技术管理, 2014, 35(10):150-158.
[37] PODSAKOFF P M, MACKENZIE S B, LEE J Y, et al. Common method biases in behavioral research: a critical review of the literature and recommended remedies[J]. Journal of Applied Psychology, 2003, 88(5): 879-903.
[38] MARSH H W, WEN Z, HAU K T. Structural equation models of latent interactions: evaluation of alternative estimation strategies and indicator construction[J]. Psychological Methods, 2004, 9(3): 274-275.
[39] 温忠麟,吴艳. 潜变量交互效应建模方法演变与简化[J]. 心理科学进展, 2010, 18(8):1306-1313.