Business model innovation (BMI) and technological innovation (TI) constitute the dual innovation system of Chinese enterprises. Traditional manufacturing enterprises and emerging Internet enterprises have different starting points and paths in the construction and evolution of the dual innovation system. On the relationship between BMI and TI, the existing literature focuses on the "static coupling" feature, relying on cross-sectional data to verify the complementary mechanism but ignoring the dynamic mechanism of the two. In terms of research objects, the existing research mainly focuses on the single type of enterprises, overlooking the differences in the innovation mix of different enterprise types.
This study focuses on the phenomenon of "two-way efforts" between BMI and TI in both traditional manufacturing enterprises and emerging Internet enterprises. Drawing on theoretical frameworks such as innovation systems, diminishing returns, and arbitrage, it proposes two sets of hypotheses to explain this phenomenon. By collecting and analyzing data from A-share listed traditional manufacturing enterprises and emerging Internet enterprises between 2013 and 2022, regression analysis demonstrates the "two-way efforts" trend and its internal mechanisms, thereby validating the proposed hypotheses.
Two findings emerge from the study. First, the investment level of BMI of traditional manufacturing enterprises grows faster than that of TI, while the emerging Internet enterprises have the opposite trend. Second, the effect of BMI on corporate performance in traditional manufacturing enterprises is stronger than that of TI, while the opposite pattern appears in emerging Internet enterprises. From the perspective of both natural time and enterprise life cycle, the above two findings are confirmed and the evolution trend is reinforcing the law. It can be believed that when traditional manufacturing enterprises and emerging Internet enterprises are based on the poles of the dual system in the early stage of creation, traditional manufacturing enterprises and emerging Internet enterprises are in a mutually reinforcing relationship by the "two-way efforts". The first finding is the concrete manifestation of the "two-way efforts" of the two types of enterprises, and the second finding is the internal logic that spawned the phenomenon of "two-way efforts". Thus, the research hypotheses have been tested.
According to the research results, it can be speculated that in the future, the dual system of TI and BMI of Chinese enterprises will gradually evolve into a system form similar to the Taiji diagram, leading enterprise organizations to innovation and harmonious development in the yin-yang symbiosis. The research results reveal the evolution law of the dual system of Chinese enterprises, enrich the theoretical system of Chinese innovation management, and provide inspiration for policy makers and enterprise managers to guide the sustainable development of the dual innovation system.
The theoretical contributions are as follows. First, it takes the lead to observe the phenomenon of "two-way efforts" between traditional manufacturing enterprises and emerging Internet enterprises in the construction of the dual system of TI and BMI, and systematically provides evidence to demonstrate the existence of "two-way efforts" phenomenon and the inherent logic of the phenomenon. Second, it reveals the heterogeneity of the evolution of the dual innovation system due to the difference of firm types. Third, it is conducive to predicting the macro trend of the evolution and development of the dual innovation system of Chinese enterprises, and sets up new ideas and new directions for the improvement of enterprises' innovation-driven development strategy and even the proposal of future strategic forms.
Three practical recommendations can be drawn from the study. First, the two types of enterprises should learn from each other, and find an opportunity to accelerate the transformation and upgrading of the innovation system in cross-border cooperation and integration. Second, the traditional manufacturing enterprises and emerging Internet enterprises should promote strength rather than avoid weaknesses, striving to overcome the shortcomings and weaknesses in the dual innovation system, and pursue a two-pronged strategy. Finally, the two types of enterprises should have a clear understanding of their own life cycle stages so as to identify the optimal dual innovation system transformation path and strategy aligned with their development phases.
[1] 喻登科, 周荣. 知性管理:案例分析的视角[J]. 情报杂志, 2015, 34(11): 199-207.
[2] 纪慧生, 姚树香. 制造企业技术创新与商业模式创新协同演化:一个多案例研究[J]. 科技进步与对策, 2019, 36(3): 90-97.
[3] 张伟,马妮娜,马昭双.数字技术、技术商业化能力与商业模式创新——环境不确定性的调节作用[J].科技进步与对策,2025,42(4):12-21.
[4] 陈雪琳,周冬梅,鲁若愚.数字创业企业商业模式创新对企业绩效的影响[J].科技进步与对策,2025,42(1):92-101.
[5] 李翔, 陈继祥. 基于复杂系统的新创企业技术创新与商业模式创新的协同机制[J]. 现代管理科学, 2015, 44(8): 73-75.
[6] MARKARD J,TRUFFER B.Technological innovation systems and the multi-level perspective: towards an integrated framework[J]. Research Policy, 2008, 37(4): 596-615.
[7] ZOTT C, AMIT R. Business model design: an activity system perspective[J]. Long Range Planning, 2010, 43(2-3): 216-226.
[8] 刘静华, 喻登科, 周荣. 新经济环境下新型二元创新体系研究——技术创新与商业模式创新矛盾统一视角[J].科技进步与对策, 2019, 36(8): 9-18.
[9] 李支东, 金辉, 罗小芳. 商业模式创新与技术创新二元关系——一个面向工业企业的多案例研究[J]. 技术经济与管理研究, 2020, 46(12): 3-9.
[10] CHEN S T, YU D K. The impacts of ambidextrous innovation on organizational obsolescence in turbulent environments[J]. Kybernetes, 2022, 51(3): 1009-1037.
[11] YU D K, YAN H L. Relationship between knowledge base and innovation-driven growth: moderated by organizational character[J]. Frontiers in Psychology, 2021, 12: 663317.
[12] JIN C L, LIU A L, LIU H F, et al. How business model design drives innovation performance: the roles of product innovation capabilities and technological turbulence[J]. Technological Forecasting and Social Change, 2022, 178: 121591.
[13] 童心, 于丽英. 基于商业生态系统的技术创新与商业模式创新耦合机制研究[J]. 科技进步与对策, 2014, 31(12): 17-22.
[14] 仝自强, 李鹏翔, 杨磊, 等. 商业模式创新与技术创新匹配性对后发企业绩效的影响——来自年报文本分析的实证研究[J]. 科技进步与对策, 2022, 39(11): 84-93.
[15] RANTALA T, UKKO J, SAUNILA M, et al. The effect of sustainability in the adoption of technological, service, and business model innovations[J]. Journal of Cleaner Production, 2018, 172: 46-55.
[16] HU B L. Linking business models with technological innovation performance through organizational learning[J]. European Management Journal, 2014, 32(4): 587-595.
[17] 卑立新, 焦高乐. 互联网商业环境下创业企业技术创新与商业模式创新的迭代式共演研究[J]. 管理学刊, 2021, 34(3): 89-104.
[18] BADEN-FULLER C, HAEFLIGER S. Business models and technological innovation[J]. Long Range Planning, 2013, 46(6): 419-426.
[19] LONG T B, BLOK V, POLDNER K. Business models for maximising the diffusion of technological innovations for climate-smart agriculture[J]. International Food and Agribusiness Management Review,2017,20(1): 5-24.
[20] HU B L, CHEN W Q. Business model ambidexterity and technological innovation performance: evidence from China[J]. Technology Analysis & Strategic Management, 2016, 28(5): 583-600.
[21] CALIA R C, GUERRINI F M, MOURA G L. Innovation networks: from technological development to business model reconfiguration[J]. Technovation, 2007, 27(8): 426-432.
[22] 陈雪琳, 周冬梅, 鲁若愚. 数字创业企业商业模式创新对企业绩效的影响[J]. 科技进步与对策, 2025, 42(1): 92-101.
[23] 赵杜悦, 宋保胜, 刘淼,等. 企业金融化分析与创新投入调节效应——基于2015—2021年沪深A股传统制造业上市公司的经验证据[J]. 管理学刊, 2024, 37(2): 140-158.
[24] 张鹏杨, 潘文诜, 刘会政. 风险投资对初创企业出口供应链多元的影响研究[J]. 经济与管理评论, 2024, 40(6):132-145.
[25] 姚江, 封冰, 华强. 从产品创新到苏南地区传统制造业的升级[J]. 南京艺术学院学报(美术与设计版), 2014, 48(6):197-199.
[26] 冯立杰, 闵清华, 王金凤, 等. 颠覆性创新视阈下后发企业商业模式创新路径研究——以拼多多为例[J]. 管理现代化, 2021, 41(6): 52-56.
[27] 尚晏莹, 蒋军锋. 工业互联网时代的传统制造企业商业模式创新路径[J]. 管理评论, 2021, 33(10): 130-144.
[28] 吴晓波, 张馨月, 沈华杰. 商业模式创新视角下我国半导体产业“突围”之路[J]. 管理世界, 2021, 37(3): 123-136.
[29] 杨林, 陆亮亮, 刘娟. “互联网+”情境下商业模式创新与企业跨界成长:模型构建及跨案例分析[J]. 科研管理, 2021, 42(8): 43-58.
[30] 于成永, 施建军. 外部学习、技术创新与企业绩效: 机制和路径——基于苏浙沪等地制造企业的实证研究[J]. 经济管理, 2009, 47(1): 117-125.
[31] ANTONELLI C, QUATRARO F. The effects of biased technological changes on total factor productivity: a rejoinder and new empirical evidence[J]. The Journal of Technology Transfer, 2014, 39(2): 281-299.
[32] SHI L X, WANG X Y, SUN H Y, et al. The impact of technological innovation on product quality: the moderating role of firm size[J]. Total Quality Management & Business Excellence, 2018, 29(7-8): 746-761.
[33] LIU D, ZHOU Q Z, CHEN S Q, et al. Capital market access and innovation efficiency: a natural experiment from China's pilot VAT reform in 2012[J]. International Review of Economics & Finance, 2021, 71: 549-566.
[34] 白景坤. 创新、效率与惰性:一个组织存续的分析框架[J]. 财经问题研究, 2008, 47(5): 112-118.
[35] 李文, 许辉, 刘思慧, 等. 基于仿真的制造企业商业模式创新路径研究——以海尔服务化转型为例[J]. 管理案例研究与评论, 2021, 14(6): 622-639.
[36] 李鸿磊, 黄速建, 包龙飞. 以商业模式创新推动中国制造业转型升级——基于跨界构建价值网络的分析[J].经济体制改革, 2018, 43(4): 102-107.
[37] 韵江, 赵宏园, 暴莹. 新创企业商业模式创新的资源编排动态演化机制——基于猎聘的纵向单案例研究[J]. 财经问题研究, 2022,44(3): 113-121.
[38] 蒋石梅, 石佳钰, 曹辉. 产业互联网平台演化机制研究——基于动态能力与商业模式创新整合视角[J]. 科技进步与对策, 2025, 42(5): 106-117.
[39] 李巍, 董江原, 杨雪程. 平台型企业商业模式创新的路径及实现机制——基于秒银科技的案例研究[J]. 管理案例研究与评论, 2018, 11(4): 333-348.
[40] 贾昌进, 张宝建. 科技型中小企业商业模式创新与组织能力演化及其竞争优势的形成机理——基于大疆的探索性案例研究[J]. 当代经济管理, 2025, 47(3): 30-40.
[41] 夏清华, 娄汇阳. 基于商业模式刚性的商业模式创新仿真——传统企业与互联网企业比较[J]. 系统工程理论与实践, 2018, 38(11): 2776-2792.
[42] 倪艳, 胡燕. 股权激励强度对企业绩效的影响——以A股上市公司为例[J]. 江汉论坛, 2021,64(4): 17-27.
[43] 谢萌, 王翌秋, 徐杨. 上市公司ESG责任履行的经济效应研究——基于长期和动态视角[J]. 广东财经大学学报, 2024, 39(6): 54-72.
[44] 张伟煜. 投贷联动赋能银企高质量发展——基于对中小型科技企业和银行业务的研究[J]. 投资研究, 2024, 43(9): 134-146.
[45] DICKINSON V. Cash flow patterns as a proxy for firm life cycle[J]. The Accounting Review, 2011, 86(6): 1969-1994.
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