投早、投小、投巧？——合成生物研发投入策略研究

张兮; 肖展鹏; 魏馨; 朱智明; 张特

doi:10.12211/2096-8280.2025-071

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投早、投小、投巧？——合成生物研发投入策略研究

研究论文 | 更新时间：2026-01-07

- 投早、投小、投巧？——合成生物研发投入策略研究
- Invest early, invest small, invest smart?--A study of synthetic biology R&D investment strategies
- 合成生物学 2026年页码：1-20
- 作者机构：
  
  1.天津大学管理与经济学部，天津 300072
  2.合成生物技术全国重点实验室，天津 300350
  3.北京工业大学经济与管理学院，北京 100124
- 作者简介：
  
  张兮（1982—），男，管理学博士，教授。研究方向为合成生物学风险管理，人工智能交叉研究，数据流通风险管理等。 E-mail：jackyzhang@tju.edu.cn
- 基金信息：
  
  国家自然科学基金项目(72442029);教育部哲学社会科学研究重大课题攻关项目(24JZD026);京津冀自然科学基金合作专项(25JJJJC0026);国家自然科学基金青年项目C类(72502226)
- DOI：10.12211/2096-8280.2025-071
  中图分类号： F272.5
- 收稿：2025-07-01，
  
  修回：2026-01-05，
  
  网络首发：2026-01-07，
- 稿件说明：
移动端阅览
张兮，肖展鹏，魏馨，朱智明，张特. 投早、投小、投巧？——合成生物研发投入策略研究［J］. 合成生物学， 2025， 6. DOI： 10.12211/2096-8280.2025-071

ZHANG Xi， XIAO Zhanpeng， WEI Xin， ZHU Zhiming， ZHANG Te. Invest early， invest small， invest smart？ --A study of synthetic biology R&D investment strategies［J］. Synthetic Biology Journal， 2025， 6. DOI： 10.12211/2096-8280.2025-071
张兮，肖展鹏，魏馨，朱智明，张特. 投早、投小、投巧？——合成生物研发投入策略研究［J］. 合成生物学， 2025， 6. DOI： 10.12211/2096-8280.2025-071 DOI：

ZHANG Xi， XIAO Zhanpeng， WEI Xin， ZHU Zhiming， ZHANG Te. Invest early， invest small， invest smart？ --A study of synthetic biology R&D investment strategies［J］. Synthetic Biology Journal， 2025， 6. DOI： 10.12211/2096-8280.2025-071 DOI：

摘要

未来产业是指由新兴技术创新推动、具有高成长潜力和战略价值的新型产业，其核心在于通过技术突破引领经济社会的高质量发展。作为未来产业的重要组成部分，合成生物技术以其高度的交叉学科特性突破了传统技术瓶颈，并通过“设计-构建-验证-学习”的流程推动技术创新。与此同时，合成生物技术研发具有高度不确定性，企业在投入时机、规模和策略选择上面临重大挑战。本文基于资源基础观、技术创新理论和信息技术生产率悖论，收集750家美国生物科技上市公司2019—2021年的财务数据与专利文本，利用LDA主题建模与余弦相似度量化研发投入，并通过回归分析检验其对企业运营绩效的影响。研究结果表明：合成生物研发投入与企业绩效呈显著倒U型关系；企业资产规模和流动性能够缓和该关系，且当企业规模超过一定阈值后，倒U型关系转变为正U型。由此提出三种策略启示：一是“投早投小”，在早期阶段分散投资多个小规模企业，以获取更高的边际绩效；二是“投巧”，在企业成长过程中进行精准整合，提升资源配置效率；三是针对大规模企业，应适度加大研发投入，实现由倒U型向正U型的转化。本文首次在实证层面用定量的方法刻画了合成生物技术研发投入对企业绩效的作用机制，并揭示了最优投入模式，不仅丰富了合成生物技术投入—产出关系的理论理解，也为生物科技企业提供了可操作的战略启示。

Abstract

Future industries denote emerging sectors propelled by technological innovation

which are characterized by substantial growth potential and strategic significance

and play a crucial role in facilitating high - quality economic and social development. As a vital constituent of future industries

synthetic biology is distinguished by its highly interdisciplinary characteristics. It utilizes the Design-Build-Test-Learn (DBTL) cycle to surmount traditional technological bottlenecks and foster innovation. Simultaneously

the substantial uncertainty intrinsic to synthetic biology research and development (R&D) presents significant challenges for firms in ascertaining the timing

scale

and strategy of investment. Based on the resource - based view

technological innovation theory

and the IT productivity paradox

this study explores the influence of R&D investment strategies in synthetic biology on firms' operational performance. Using financial data and patent text information of 750 U.S. biotechnology firms from 2019 to 2021

this study utilizes the Latent Dirichlet Allocation (LDA) topic-modeling approach and cosine similarity to quantify R&D inputs. Subsequently

regression analysis is applied to investigate the influence of synthetic biology R&D investment on firms' operational performance

as well as the moderating effects of asset scale and liquidity. The findings indicate that: (1) There exists a significant inverted U-shaped relationship between the R&D investment in synthetic biology and firm performance; (2) Asset size and liquidity exert a positive moderating effect on this relationship; and (3) Once the firm scale surpasses a specific threshold

the inverted U-shaped relationship transforms into a U-shaped relationship. Based on these findings

three strategic perspectives are put forward: making early and small-scale investments to diversify risks and enhance marginal returns; making intelligent investments to optimize resource allocation during the growth of firms; and for large-scale firms

appropriately increasing R & D input to realize a positive transformation of the investment-performance curve. This study is among the pioneering studies to quantitatively capture the mechanism by which R & D investment in synthetic biology affects firm performance. It identifies the optimal investment models

enriches the theoretical comprehension of the input-output relationship in synthetic biotechnology

and offers practical strategic guidance for biotechnology firms.

关键词

Keywords

references

赵国屏 . 合成生物学:从"造物致用"到产业转化 [J ] . 生物工程学报 , 2022 , 38 ( 11 ): 4001 - 4011 .

姚颐 , 凌玥 , 李岩琼 . 国际贸易诉讼、研发投入与企业创新 [J/OL ] . 南开管理评论 , 1 - 21 [ 2024-05-04 ] . http://kns.cnki.net/kcms/detail/12.1288.F.20230419.1516.002.html http://kns.cnki.net/kcms/detail/12.1288.F.20230419.1516.002.html .

Ceze L , Nivala J , Strauss K . Molecular digital data storage using DNA [J ] . Nature Reviews Genetics , 2019 , 20 ( 8 ): 456 - 466 .

李井林 , 阳镇 , 陈劲等 . ESG促进企业绩效的机制研究——基于企业创新的视角 [J ] . 科学学与科学技术管理 , 2021 , 42 ( 09 ): 71 - 89 .

Alarcon S , Sanchez M . External and Internal R&D, Capital Investment and Business Performance in the Spanish Agri-Food Industry [J ] . Journal of Agricultural Economics , 2013 , 64 ( 03 ): 654 - 675 .

Lee J , Kwon H B , Pati N . Exploring the relative impact of R&D and operational efficiency on performance: A sequential regression-neural network approach [J ] . Expert Systems with Applications , 2019 , ( 137 ): 420 - 431 .

刘萍 , 毛宁 . 医药行业技术创新投入对当期与远期绩效的影响研究 [J ] . 科技与管理 , 2018 ,( 06 ): 28 - 32 .

董静 , 苟燕楠 . 研发投入与上市公司业绩——基于机械设备业和生物医药业的比较研究 [J ] . 科技进步与对策 , 2010 ,( 20 ): 56 - 60 .

简兆权 , 曾经莲 , 刘艳 . 服务供应链外部整合对企业运营绩效的影响机理分析——被调节的中介效应 [J ] . 管理评论 , 2021 , 33 ( 08 ): 290 - 301 . DOI: 10.14120/j.cnki.cn11-5057/f.2021.08.025 http://dx.doi.org/10.14120/j.cnki.cn11-5057/f.2021.08.025 .

宋青龙 . 新三板公司资产流动性分析与策略研究 [J ] . 中国市场 , 2020 ,( 26 ): 38 - 39 . DOI: 10.13939/j.cnki.zgsc.2020.26.038 http://dx.doi.org/10.13939/j.cnki.zgsc.2020.26.038 .

池仁勇 , 於珺 , 阮鸿鹏 . 企业规模,研发投入对创新绩效的影响研究——基于信用环境与知识存量视角 [J ] . 华东经济管理 , 2020 , 34 ( 9 ): 43 - 54 .

Han I , Chuang C M . The impacts of R&D investment on company performance: US vs. Taiwanese technology-intensive industry [J ] . Review of Pacific Basin Financial Markets and Policies , 2011 , 14 ( 01 ): 171 - 194 .

李静怡 , 王祯阳 , 武咸云 . 政策激励与研发投入交互作用对创新绩效的影响 [J ] . 科研管理 , 2020 , 41 ( 05 ): 99 - 110 . DOI: 10.19571/j.cnki.1000-2995.2020.05.011.Schimke A http://dx.doi.org/10.19571/j.cnki.1000-2995.2020.05.011.SchimkeA ,

Brenner T . The role of R&D investments in highly R&D-based firms [J ] . Studies in Economics and Finance , 2014 , 31 ( 1 ): 3 - 45 .

Eberhart A C , Maxwell W F , Siddique A R . An Examination of Long-Term Abnormal Stock Returns and Operating Performance Following R&D Increases [J ] . Journal of Finance , 2004 , 59 ( 2 ): 623 - 650 .

李四海 , 邹萍 . 企业研发绩效粘性研究——来自高新技术上市公司的经验证据 [J ] . 科研管理 , 2016 , 37 ( 02 ): 37 - 46 . DOI: 10.19571/j.cnki.1000-2995.2016.02.005 http://dx.doi.org/10.19571/j.cnki.1000-2995.2016.02.005 .

赵晖 . 高技术企业的 R&D 投入与组织绩效关系的实证分析 [J ] . 生产力研究 , 2010 ,( 05 ): 218 - 222 .

Scherer F M . The link between gross profitability and pharmaceutical R&D spending [J ] . Health affairs , 2001 , 20 ( 5 ): 216 - 220 .

Ahmed K , Hillier J , Tanusasmita E . R&D Profitability, intensity and market-to-book: evidence from Australia [J ] . Accounting Research Journal , 2011 , 24 ( 2 ): 150 - 177 .

Lin B W , Lee Y , Hung S C . R&D intensity and commercialization orientation effects on financial performance [J ] . Journal of business research , 2006 , 59 ( 6 ): 679 - 685 .

Quo B , Wang Q Z , Shou Y Y . Firm size, R&D, and performance: an empirical analysis on software industry in China [C ] . 2004 EEE International Engineering Management Conference IEEE , 2004 .

Shen C H , Zhang H . CEO risk incentives and firm performance following R&D increases [J ] . Journal of Banking & Finance , 2013 , 37 ( 4 ): 1176 - 1194 .

贲友红 . 我国企业研发投入对经营绩效滞后性影响的研究——以医药制造企业为例 [J ] . 价格理论与实践 , 2017 ,( 04 ): 155 - 158 .

许伯桐 . 以质取胜——企业技术创新与经营绩效 [J ] . 运筹与管理 , 2018 , 27 ( 11 ): 193 - 199 .

Rosenberg N . ( 1990 ). Why do firms do basic research (with their own money)? Research Policy , 19 ( 2 ), 165 - 174 .

尹美群 , 盛磊 , 李文博 . 高管激励、创新投入与公司绩效——基于内生性视角的分行业实证研究 [J ] . 南开管理评论 , 2018 , 21 ( 01 ): 109 - 117 .

Pisano G . P . ( 1997 ). The development factory: Unlocking the potential of process innovation. Harvard Business School Press .

张自然 , 骆静 . 医药企业研发投入、销售投入与企业绩效的相关性研究 [J ] . 当代经济 , 2015 ,( 09 ): 116 - 119 .

Teece D . J . ( 1986 ). Profiting from technological innovation: Implications for integration, collaboration, licensing and publ ic policy. Research Policy , 15 ( 6 ), 285 - 305 .

Zhang X. , Chang R. , Gu M. , & Huo B . ( 2024 ). Blockchain implementation and shareholder value: a complex adaptive systems perspective . International Journal of Operations & Production Management , 44 ( 3 ), 666 - 698 .

李春 . 合成生物学 [S ] . 北京 : 化学工业出版社 , 2019 .

王俊姝 , 祁庆生 . 合成生物学与代谢工程 [J ] . 生物工程学报 , 2009 , 25 ( 9 ): 1296 - 1302 .

王智文 , 陈涛 , 赵学明 . 代谢工程与合成生物学 [S ] . 北京 : 高等教育出版社 , 2023 .

于波 , 刘璐 . 数字化转型是否优化了企业投资效率?——基于资源基础观的实证研究 [J ] . 现代管理科学 , 2023 ,( 06 ): 153 - 162 .

Triplett J E . The Solow productivity paradox: what do computers do to productivity? [J ] . The Canadian Journal of Economics/Revue canadienne d'Economique , 1999 , 32 ( 2 ): 309 - 334 .

Garicano L , Heaton P . Information technology, organization, and productivity in the public sector: Evidence from police departments [J ] . Journal of Labor Economics , 2010 , 28 ( 1 ): 167 - 201 .

Giustiziero G. , Kretschmer T. , Somaya D. , & Wu B . Hyperspecialization and hyperscaling: A resource-based theory of the digital firm . Strategic Management Journal , 2023 , 44 ( 6 ), 1391 - 1424 .

赵玉林 , 刘超 , 谷军健 . 研发投入结构对高质量创新的影响——兼论有为政府和有效市场的协同效应 [J ] . 中国科技论坛 , 2021 ,( 01 ): 55 - 64 . DOI: 10.13580/j.cnki.fstc.2021.01.008 http://dx.doi.org/10.13580/j.cnki.fstc.2021.01.008 .

张洁 , 唐洁 . 资本错配、融资约束与企业研发投入——来自中国高新技术上市公司的经验证据 [J ] . 科技进步与对策 , 2019 , 36 ( 20 ): 103 - 111 .

任海云 . 公司治理对R&D投入与企业绩效关系调节效应研究 [J ] . 管理科学 , 2011 , 24 ( 05 ): 37 - 47 .

Miller D , Shamsie J . The resource-based view of the firm in two environments: The Hollywood film studios from 1936 to 1965 [J ] . Academy of management journal , 1996 , 39 ( 3 ): 519 - 543 .

Tsai K H , Wang J C . Does R&D performance decline with firm size?—A re-examination in terms of elasticity [J ] . Research policy , 2005 , 34 ( 6 ): 966 - 976 .

祝继高 , 陆正飞 . 货币政策、企业成长与现金持有水平变化 [J ] . 管理世界 , 2009 ,( 03 ): 152 - 158 .

Sibilkov V . Asset liquidity and capital structure [J ] . Journal of financial and quantitative analysis , 2009 , 44 ( 5 ): 1173 - 1196 .

Philipp , Boeing . The allocation and effectiveness of China's R&D subsidies - Evidence from listed firms [J ] . Research Policy , 2016 .

陈凡 , 徐旭 . 技术创新风险分析 [J ] . 创新与创业管理 , 2017 ( 2 ): 1 - 10 .

张岭 . 股权与债权融资对技术创新绩效的影响研究 [J ] . 科研管理 , 2020 , 41 ( 8 ): 95 - 104 .

薛海燕 , 张信东 . 推手还是杀手:流动性对中小企业创新投资的影响——基于新三板和创业板的比较研究 [J ] . 外国经济与管理 , 2021 , 43 ( 06 ): 105 - 119 . DOI: 10.16538/j.cnki.fem.20201116.401 http://dx.doi.org/10.16538/j.cnki.fem.20201116.401 .

徐琳 , 刘衍 . 股票流动性与企业创新:促进还是抑制——企业异质性视角 [J ] . 科技进步与对策 , 2020 , 37 ( 22 ): 90 - 98 .

林志帆 , 杜金岷 , 龙晓旋 . 股票流动性与中国企业创新策略:流水不腐还是洪水猛兽? [J ] . 金融研究 , 2021 ,( 03 ): 188 - 206 .

唐曼萍 , 李后建 . 企业规模、最低工资与研发投入 [J ] . 研究与发展管理 , 2019 ,( 01 ): 44 - 55 .

Karlsson C , Olsson O . Product innovation in small and large enterprises [J ] . Small Business Economics , 1998 : 31 - 46 .March J G. Rationality, foolishness, and adaptive intelligence[J ] . Strategic management journal, 2006 , 27 ( 3 ): 201 - 214 .

March J G . Rationality, foolishness, and adaptive intelligence [J ] . Strategic management journal , 2006 , 27 ( 3 ): 201 - 214 .

韩先锋 , 董明放 . 研发投入对企业绩效影响的门槛效应 [J ] . 北京理工大学学报(社会科学版) , 2018 , 20 ( 02 ): 95 - 101+116 . DOI: 10.15918/j.jbitss1009-3370.2018.1185 http://dx.doi.org/10.15918/j.jbitss1009-3370.2018.1185 .

韩中媛 , 尹夏楠 . 资源配置、研发投入与企业绩效的关联 [J ] . 商业文化 , 2021 ,( 16 ): 32 - 33 .

王珊珊 . 创新投入对企业绩效的影响研究 [J ] . 全国流通经济 , 2023 ,( 15 ): 88 - 91 . DOI: 10.16834/j.cnki.issn1009-5292.2023.15.031 http://dx.doi.org/10.16834/j.cnki.issn1009-5292.2023.15.031 .

李钟石 , 文华 , 袁嘉葆 , 等 . 基于DEA模型的我国物流业上市企业经营绩效实证分析 [J ] . 物流技术 , 2021 , 40 ( 04 ): 64 - 70 .

赵武阳 , 陈超 . 什么决定了企业的研发投入? [J ] . 中国会计评论 , 2012 , 10 ( 04 ): 453 - 472 .

Silverman B S . Technological resources and the direction of corporate diversification: Toward an integration of the resource-based view and transaction cost economics [J ] . Management science , 1999 , 45 ( 8 ): 1109 - 1124 .

夏兰 , 徐雯 . 资产流动性对企业资本结构的影响研究 [J ] . 新智慧:财经版 , 2014 ( 1 ): 4 .

刘晓静 , 黄茜 . 资产流动性管理对公司业绩影响的实证研究——基于专用设备制造业的分析 [J ] . 广西财经学院学报 , 2016 , 29 ( 03 ): 81 - 86 .

徐佳丽 . 上市公司流动性与盈利能力关系的实证研究 [J ] . 现代营销(学苑版) , 2021 ,( 09 ): 28 - 29 . DOI: 10.19932/j.cnki.22-1256/F.2021.09.028 http://dx.doi.org/10.19932/j.cnki.22-1256/F.2021.09.028 .

张婷婷 , 邓峙琨 . 企业资产结构研究文献综述 [J ] . 广西质量监督导报 , 2020 ,( 06 ): 144+143 .

杨明海 , 李倩倩 , 袁洪娟 . 高层次科技创新人才集聚效应的现状与提升战略研究——基于山东省的调研数据 [J ] . 经济与管理评论 , 2015 , 31 ( 04 ): 129 - 134 . DOI: 10.13962/j.cnki.37-1486/f.2015.04.016 http://dx.doi.org/10.13962/j.cnki.37-1486/f.2015.04.016 .

邓培杰 . 资产结构、企业规模与企业价值——基于A股制造业上市公司的研究 [J ] . 金融 , 2023 , 13 ( 3 ): 503 - 509 .

Kosala R. , and Blockeel H . 2000 . " Web Mining Research: A Survey," ACM Sigkdd Explorations Newsletter (2 : 1 ), pp. 1 - 15 .

Mankad S. , Han H. S. , Goh J. , and Gavirneni S . 2016 . " Understanding Online Hotel Reviews through Automated Text Analysis," Service Science (8 : 2 ), pp. 124 - 138 .

Wu J. , Huang L. , and Zhao J . L . 2019 . "Operationalizing Regulatory Focus in the Digital Age: Evidence from an E-Commerce Context," MIS Quarterly ( 43 : 3 ), pp. 745 - 764 .

Salton G. , and McGill M . J . 1983 . Introduction to Modern Information Retrieval . NY : McGraw-Hill .

Blei D. M. , Ng A. Y. , and Jordan M . I . 2003 . "Latent dirichlet allocation," Journal of machine Learning research( 3 : 1 ), pp. 993 - 1022 .

Wei X. , He W. , Zhang X. , Zhao C. , & Zhao H . ( 2020 , December ). A Machine Learning Method for Measuring Information Disclosure in Sharing Economy Platforms . In ICIS .

Vu H. Q. , Li G. , and Law R . 2019 . " Discovering Implicit Activity Preferences in Travel Itineraries by Topic Modeling ," Tourism Management ( 75 ), pp. 435 - 446 .

Hall B H , Rosenberg N . Handbook of the Economics of Innovation [J ] . handbooks in economics , 2010 .

National Research Council . Industrial research and innovation indicators: Report of a workshop [J ] . 1930 .

Nagaoka S , Motohashi K , Goto A . Patent statistics as an innovation indicator [M ] // Handbook of the Economics of Innovation . North-Holland , 2010 , 2 : 1083 - 1127 .

National Academies of Sciences , Engineering , and Medicine ; Policy and Global Affairs ; Government-University-Industry Research Roundtable . Beyond Patents: Assessing the Value and Impact of Research Investments: Proceedings of a Workshop—in Brief . Washington (DC) : National Academies Press (US) ; 2017 Oct 11 . Available from: https://www.ncbi.nlm.nih.gov/books/NBK458648/?utm_source=chatgpt.com doi: 10.17226/24920 https://www.ncbi.nlm.nih.gov/books/NBK458648/?utm_source=chatgpt.comdoi:10.17226/24920

Potters L . Innovation input and innovation output: differences among sectors [R ] . IPTS Working Papers on Corporate R&D and Innovation , 2009 .

Danguy J , De Rassenfosse G , van Pottelsberghe de la Potterie B . The R&D-patent relationship: An industry perspective [J ] . 2010 .

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