暨南学报(哲学社会科学版)

作者：宋献中, 韩永飞

单位：暨南大学管理学院。

关键词：数字化转型,技术创新投入,技术创新产出,协同作用

基金：国家自然科学基金重点项目“数字经济下公司财务决策与资源配置效率研究”(72132002)。

本文以2008—2022年沪深A股上市企业为样本,研究发现数字化转型和技术创新投入协同促进企业技术创新产出。进一步研究发现,数字化转型和技术创新投入的协同作用对企业实质性技术创新产出的影响更明显;数字化转型和利用式技术投入的协同作用对企业技术创新产出的影响更明显;将不同类型的技术创新投入和技术创新产出结合起来发现,数字化转型和探索式创新投入以及利用式技术创新投入的协同作用均对实质性技术创新产出更明显;在数字化转型较低和技术创新投入较高时,协同作用最明显。机制检验发现协同作用主要通过为企业带来新的生产条件、使企业成功利用创新网络中的资源和机会并使得技术创新投入和数字化转型相互促进良性循环及企业技术创新产出,技术产出水平的提高也使得企业对未来有更多的计划。本文所探讨的协同作用和机理可为数字经济和实体经济的深度融合提供经验证据。"/>template{display:none;}.mag-rich-xref-fn { cursor: pointer;}//长视频$(document).ready(function(){if($("#showLongArticleVideo") && $("#showLongArticleVideo").length && $("#showLongArticleVideo").length>0){mag_ajax_update({ele_id:'showLongArticleVideo',url:mag_currentQikanUrl() + "/CN/article/showLongArticleVideo.do?id="+$("#articleId").val()});}});$(document).ready(function(){window.metaData = {"journal":{"issn":"1000-5072","qiKanMingCheng_CN":"暨南学报（哲学社会科学版）","id":2,"qiKanMingCheng_EN":"Jinan Journal"},"fundList_cn":["国家自然科学基金重点项目“数字经济下公司财务决策与资源配置效率研究”(72132002)。"],"article":{"keywordList_cn":["数字化转型","技术创新投入","技术创新产出","协同作用"],"juan":"47","zhaiyao_cn":"本文以2008—2022年沪深A股上市企业为样本,研究发现数字化转型和技术创新投入协同促进企业技术创新产出。进一步研究发现,数字化转型和技术创新投入的协同作用对企业实质性技术创新产出的影响更明显;数字化转型和利用式技术投入的协同作用对企业技术创新产出的影响更明显;将不同类型的技术创新投入和技术创新产出结合起来发现,数字化转型和探索式创新投入以及利用式技术创新投入的协同作用均对实质性技术创新产出更明显;在数字化转型较低和技术创新投入较高时,协同作用最明显。机制检验发现协同作用主要通过为企业带来新的生产条件、使企业成功利用创新网络中的资源和机会并使得技术创新投入和数字化转型相互促进良性循环及企业技术创新产出,技术产出水平的提高也使得企业对未来有更多的计划。本文所探讨的协同作用和机理可为数字经济和实体经济的深度融合提供经验证据。","endNoteUrl_en":"https://jnxb.jnu.edu.cn/skb/EN/article/getTxtFile.do?fileType=EndNote&id=7200","reference":"","bibtexUrl_cn":"https://jnxb.jnu.edu.cn/skb/CN/article/getTxtFile.do?fileType=BibTeX&id=7200","articleType":"","abstractUrl_en":"https://jnxb.jnu.edu.cn/skb/EN/10.11778/j.jnxb.20242563","qi":"3","id":7200,"nian":2025,"bianHao":"1749699405687-638084285","zuoZheEn_L":"SONG Xianzhong, HAN Yongfei","juanUrl_en":"https://jnxb.jnu.edu.cn/skb/EN/Y2025","shouCiFaBuRiQi":"2025-06-12","qiShiYe":"152","qiUrl_cn":"https://jnxb.jnu.edu.cn/skb/CN/Y2025/V47/I3","lanMu_cn":"经济管理·公司治理","pdfSize":"777","zuoZhe_CN":"宋献中, 韩永飞","risUrl_cn":"https://jnxb.jnu.edu.cn/skb/CN/article/getTxtFile.do?fileType=Ris&id=7200","copyrightStatement_cn":"","title_cn":"企业数字化转型、技术创新投入与技术创新产出——基于协同作用的研究","doi":"10.11778/j.jnxb.20242563","jieShuYe":"176","keywordList_en":["digital transformation","technological innovation input","technological innovation output","synergistic effect"],"endNoteUrl_cn":"https://jnxb.jnu.edu.cn/skb/CN/article/getTxtFile.do?fileType=EndNote&id=7200","zhaiyao_en":"The report to the 20th National Congress of the Communist Party of China (CPC) proposed to “promote the deep integration of the digital economy and the real economy”, providing direction for the development of China's digital economy. In this context, enterprise digital transformation, as a core approach driven by data elements, is reshaping technological innovation models. However, most existing studies focus on the impact of single factors on technological innovation, neglecting the complexity of the synergistic effects between digital transformation and technological innovation input. This paper takes A-share listed companies in Shanghai and Shenzhen from 2008 to 2022 as samples and systematically explores the synergistic effect of digital transformation and technological innovation input on enterprise technological innovation, aiming to reveal the dynamic interactive mechanism of data and technological elements and provide micro-level evidence for the integration of the digital and real economies.This paper adopts a quantitative analysis method with data from databases such as CSMAR and CNRDS. Financial industry companies and those with missing data were excluded, resulting in a final sample of 24,235 observations. Technological innovation output is represented by the natural logarithm of the total number of patent applications. Digital transformation is quantified by text analysis of relevant word frequencies in corporate annual reports, while technological innovation input is measured by the ratio of R&D investment to total assets.The results show that both digital transformation and technological innovation input significantly promote technological innovation output, confirming the existence of a synergistic effect. Endogeneity tests, including the instrumental variable method and propensity score matching (PSM), show robustness. Heterogeneity analysis reveals that the synergistic effect is more pronounced in substantive technological innovation output than in strategic technological innovation output. The synergistic effect is stronger for exploratory technological innovation input, while exploitative technological innovation input is only effective when paired with digital transformation. Mechanism tests show that the synergistic effect is achieved through three paths: (1) Resource integration creates new production conditions. (2) Optimizing innovation networks promotes resource flow. (3) Digital transformation and technological innovation input form a virtuous cycle. Further research finds that the synergistic effect is most significant when digital transformation is low and technological innovation input is high.This paper is innovative in three aspects. (1) It constructs a comprehensive framework to reveal the synergistic mechanism of data and technological elements, breaking the limitations of single-factor research. (2) It clarifies the differences in the effects of synergistic effects on different types of innovation through heterogeneity analysis. (3) It reveals the three-fold path of resource integration, network optimization, and dynamic circulation through mechanism tests. At the policy level, it is recommended that the government establish special funds and tax incentives to strengthen the synergistic mechanism, prioritize supporting exploratory innovation projects to promote their deep integration with digital transformation, build platforms for industry-academia-research cooperation to promote the sharing of innovation resources, and guide enterprises to formulate long-term innovation strategies with enhanced planning flexibility.This paper not only provides practical guidance for enterprises to optimize innovation resource allocation but also offers scientific evidence for policymakers to design differentiated support policies. 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来源：2025年第3期

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