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Invest early, invest small, invest smart?--A study of synthetic biology R&D investment strategies
- Synthetic Biology Journal Pages: 1-20(2026)
- 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：
- 基金信息：
DOI：10.12211/2096-8280.2025-071
CLC： F272.5Received：01 July 2025，
Revised：2026-01-05，
Online First：07 January 2026，
- 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.
2
关键词
Keywords
references
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