【前沿追踪】AI对企业创新的影响顶刊文献分享
AI对企业创新的影响
近年来，随着新一代信息技术的兴起，人工智能(AI)正在从各领域、全方位深度融入经济社会发展潮流中，对人类社会生活产生了深远影响，并成为世界各国提升国家竞争力、维护国家安全的重要战略和经济发展的新引擎，是引领第四工业革命的核心驱动力。企业作为数字经济中最为活跃的微观个体和创新主体，如何在AI时代提升自主创新能力成为社会各界关注的重要议题。在本次推送中，着重关注了AI与企业商业模式创新、绿色技术创新、绿色创新效率、创新管理以及组织绩效之间影响关系的五篇文献研究：在Artificial intelligence (AI)‐driven strategic business model innovations in small‐ and medium‐sized enterprises. Insights on technological and strategic enablers for carbon neutral businesses一文中，作者以美国326家中小企业为样本，采用结构方程模型检验了AIDBMI、技术赋能因素、战略赋能因素与实现碳中和之间的关系，研究结论为中小企业以及政策制定者寻求促进碳中和、可持续发展提供了有价值的指导；在Can enterprise green technology innovation performance achieve “corner overtaking” by using artificial intelligence?—Evidence from Chinese manufacturing enterprises一文中， 作者以2014 - 2020年中国制造业上市企业的面板数据为依托，构建多期双重差分模型，考察了人工智能应用对企业绿色技术创新绩效的影响；在AI adoption rate and corporate green innovation efficiency: Evidence from Chinese energy companies一文中，作者以2010 - 2020年中国能源上市企业的数据为依托，研究得出广泛采用人工智能的能源企业可以表现出更高的绿色创新效率，为政策制定者提供了有关能源企业战略发展的新见解和新指导；在Artificial intelligence and corporate innovation: A review and research agenda一文中，作者对人工智能与企业创新交集的文献进行了梳理归纳，总结出两者之间聚焦的8个领域，并概述了一个包含人工智能在企业创新中作用的框架，并就未来关于AI和企业创新之间的研究提出了有针对性的建议；在Artificial intelligence and adaptive response to market changes: A strategy to enhance firm performance and innovation中，作者采用了一个两阶段的设计,对采用人工智能的企业IT和高管进行了调查研究，结果发现了ARMC的三个人工智能能力（人工智能赋能的自动化、人工智能赋能的分析和人工智能赋能的关系能力）与企业绩效、流程创新和产品创新之间的正相关关系。
PART.1
Artificial intelligence (AI)‐driven strategic business model innovations in small-and medium-sized enterprises. Insights on technological and strategic enablers for carbon neutral businesses
人工智能( AI )驱动的中小企业战略商业模式创新:关于碳中和企业的技术和战略驱动因素的见解
Keywords:
AI-driven business model innovation;green innovation capability;green technology innovation;strategic architecture & carbon neutral businesses;strategic intent
关键词：
人工智能驱动的商业模式创新;绿色创新能力;绿色技术创新;战略架构与碳中和业务;战略意图
Abstract:
This study investigates the enhancement of technological and strategic enablers for carbon‐neutral businesses (CNB) through artificial intelligence (AI)‐driven business model innovation (AIDBMI). Drawing upon the insights gained from the literature review, the study employs structural equation modeling (partial least squares structural equation modeling [PLS‐SEM]) as the methodology to examine the relationships between AIDBMI, technological enablers, strategic enablers, and the attainment of carbon neutrality. The sample size consists of 326 small‐ and medium‐sized enterprises (SMEs) in the United States of America. The findings of this study affirm the significant positive relationships between AIDBMI and both technological and strategic enablers for CNB. The utilization of AI technologies proves to be instrumental in fostering the development and implementation of innovative business models that integrate sustainability practices and address environmental challenges. By leveraging AIDBMI, SMEs can harness technological advancements to adopt energy‐efficient processes, embrace renewable energy solutions, and implement effective carbon reduction strategies. Moreover, the study highlights the critical role of strategic enablers in driving the transition towards carbon neutrality. The alignment of sustainability goals with organizational strategies, stakeholder collaboration, and employee engagement emerge as pivotal factors in enabling SMEs to effectively utilize AIDBMI and leverage technological advancements to achieve carbon neutrality. The implications of this study contribute to the existing literature by highlighting the importance of technological and strategic enablers in creating CNB. By integrating AIDBMI, organizations can drive sustainable transformations, optimize their operations, and align their resource management with sustainable practices. These insights provide valuable guidance for SMEs, policymakers, and researchers seeking to foster sustainable practices, promote carbon neutrality, and contribute to the advancement of a low‐carbon economy.
摘要：
本研究探讨了通过人工智能(AI)驱动的商业模式创新(AIDBMI)来增强碳中和企业(CNB)的技术和战略推动因素。根据从文献综述中获得的见解，本研究采用结构方程模型(偏最小二乘结构方程模型[PLS‐SEM])作为方法来研究AIDBMI、技术推动因素、战略推动因素和实现碳中和之间的关系。样本量由美国的326家中小企业(SMEs)组成。本研究的结果证实了AIDBMI与CNB的技术和战略推动因素之间的显著正相关关系。事实证明，人工智能技术的利用有助于促进创新商业模式的开发和实施，这些模式将可持续性实践与应对环境挑战相结合。通过AIDBMI，中小企业可以利用技术进步采用节能流程，采用可再生能源解决方案，并实施有效的碳减排战略。此外，该研究还强调了战略推动者在推动向碳中和过渡方面的关键作用。将可持续发展目标与组织战略、利益相关者合作和员工敬业度相结合，是中小企业有效利用AIDBMI和利用技术进步实现碳中和的关键因素。本研究通过强调技术和战略推动因素在创建CNB中的重要性，对现有文献做出了贡献。通过集成AIDBMI，组织可以驱动可持续转型，优化自身操作，并将资源管理与可持续实践相结合。这些见解为中小企业、政策制定者和研究人员寻求促进可持续实践、促进碳中和和低碳经济的发展提供了有价值的指导。
文献来源：
ShaikS A ,AlshibaniM S ,JainG , et al.Artificial intelligence (AI)‐driven strategic business model innovations in small‐ and medium‐sized enterprises. Insights on technological and strategic enablers for carbon neutral businesses[J].Business Strategy and the Environment,2023,33(4):2731-2751.
PART.2
Can enterprise green technology innovation performance achieve “corner overtaking” by using artificial intelligence?—Evidence from Chinese manufacturing enterprises
企业绿色技术创新绩效能否利用人工智能实现"弯道超车" ? - -来自中国制造业企业的证据
Keywords:
Artificial intelligence;Green technology innovation performance;Knowledge coupling;Multiple difference-in-difference;Stimulus-Organism-Response theory
关键词：
人工智能;绿色技术创新绩效;知识耦合;多重双重差分;刺激-机体-反应理论
Abstract:
To examine the impact of the application of artificial intelligence on the green technology innovation performance of enterprises, a multi-period difference-in-differences model was constructed. Panel data of Chinese listed manufacturing companies over the period of 2014–2020 were used. According to Stimulus-Organism-Response theory, the impact of artificial intelligence on the green technology innovation performance of enterprises is not direct. The mediating effects of basic knowledge coupling, complementary knowledge coupling, and extended knowledge coupling are verified through empirical tests. The results show that artificial intelligence significantly positively impacts the innovation performance of enterprises in relation to the development of green technology and its decomposition variables (efficiency and progress of green technology). The mediation effect indicates that artificial intelligence mainly promotes the green technology innovation performance of enterprises by affecting their knowledge coupling.
摘要：
为考察人工智能应用对企业绿色技术创新绩效的影响,构建多期双重差分模型。采用2014 - 2020年中国制造业上市公司的面板数据。根据"刺激-机体-反应"理论,发现人工智能对企业绿色技术创新绩效的影响并不是直接的。通过实证检验,验证了基础知识耦合、互补性知识耦合和拓展性知识耦合的中介效应。研究结果表明,人工智能对企业绿色技术发展及其分解变量(绿色技术效率与绿色技术进步)的创新绩效有显著正向影响。中介效应表明,人工智能主要通过影响企业的知识耦合来促进企业的绿色技术创新绩效。
文献来源：
Hongna T ,Liyan Z ,Li Y , et al.Can enterprise green technology innovation performance achieve “corner overtaking” by using artificial intelligence?—Evidence from Chinese manufacturing enterprises[J].Technological Forecasting Social Change,2023,194
PART.3
AI adoption rate and corporate green innovation efficiency: Evidence from Chinese energy companies
人工智能采用率与企业绿色创新效率：来自中国能源企业的证据
Keywords:
Artificial intelligence; Green innovation efficiency; Textual analysis; Energy company
关键词：
人工智能；绿色创新效率；文本分析；能源企业
Abstract:
The advent of artificial intelligence (AI) technology has led to transformative shifts in the human landscape. Moreover, as a potent driving force behind the evolution of energy companies, green innovation has the potential to be supported by advanced technologies such as AI. However, academic research exploring the association between the AI adoption rate and green innovation in energy companies is scarce. This study analyzes data on Chinese listed energy companies from 2010 to 2020. Our findings indicate that energy companies with extensive AI adoption exhibit higher green innovation efficiency. This finding is particularly pronounced among firms that report substantial participation in environmental, social, and governance activities. However, our findings reveal that executives who focus on short-term benefits can undermine the positive influence of AI adoption on green innovation. These main findings are notably significant for energy companies where the roles of chief executive officer and board director are unified, state-owned enterprises, and companies that do not hold bank shares. This study offers novel insights and valuable guidance for policymakers regarding the strategic development of energy companies, thereby bridging a significant gap in the literature.
摘要：
人工智能( AI )技术的问世,引发了人类图景的变革性转变。不仅如此,绿色创新作为能源企业进化背后的强劲动力,有潜力得到人工智能等先进技术的支持。然而,探究能源企业人工智能采用率与绿色创新之间关系的学术研究并不多见。本研究对2010 - 2020年中国能源上市公司的数据进行分析。我们的研究结果表明,广泛采用人工智能的能源企业表现出更高的绿色创新效率。这一发现在报告大量参与环境、社会和治理活动的企业中尤为明显。然而,我们的研究结果表明,专注于短期利益的高管会削弱人工智能采纳对绿色创新的积极影响。这些主要发现对于首席执行官和董事会董事角色统一的能源企业、国有企业以及不持有银行股份的企业具有显著意义。本研究为政策制定者提供了关于能源企业战略发展的新见解和有价值的指导,从而填补了文献中的一个重要空白。
文献来源：
Wang Z, Zhang T, Ren X, et al. AI adoption rate and corporate green innovation efficiency: Evidence from Chinese energy companies[J]. Energy Economics, 2024, 132: 107499.
PART.4
Artificial intelligence and corporate innovation: A review and research agenda
人工智能与企业创新：综述与研究议程
Keywords:
Artificial intelligence;Corporate innovation;Bibliometrics analysis, content analysis;Business model;Review
关键词：
人工智能;企业创新;文献计量分析、内容分析;商业模式;综述
Abstract:
Artificial Intelligence (AI) induce corporates to re-design their innovation process. Due to rapid technological development, synchronization of information systems, and industrialization, corporate managers increasingly adopt AI in innovation. In response, scholars are interested in the idea of creating and mapping the intersection of AI in corporate innovation, which resulted in massive literature during the past decades. To critically analyze the phenomena of AI in corporate innovation, we conducted a hybrid review of published literature (364 articles) for the last 56 years (1996 to July 2022). We present taxonomy, outline AI phases, AI large scope definition, and link with innovation. We identify eight focal fields in the intersection of AI in corporate innovation, such as AI and business models (BM), AI and product innovation, AI and open innovation, AI and innovation process, AI and firm's innovation structure, AI, firm's knowledge and innovation, and AI, innovation and firm market performance, and AI and innovativeness of supply chain management. We outline a framework encompassing the role of AI in corporate innovation. We conclude this study by identifying influential aspects of literature and presenting future research agendas.
摘要：
人工智能( AI )促使企业重新设计创新流程。由于技术的快速发展、信息系统的同步和工业化,企业管理者越来越多地在创新中采用人工智能。作为回应,学者们对创建和映射人工智能在企业创新中的交叉点的想法产生了兴趣,在过去的几十年中产生了大量的文献。为了批判性地分析企业创新中的人工智能现象,我们对过去56 年发表的文献( 364篇文章)进行了混合审查。我们介绍了分类法,概述了AI阶段、AI大范围定义以及AI与创新的联系。我们识别出人工智能与企业创新交集的8个焦点领域：人工智能与商业模式( BM )、人工智能与产品创新、人工智能与开放式创新、人工智能与创新过程、人工智能与企业创新结构、人工智能与企业知识创新、人工智能与企业市场绩效、人工智能与供应链管理创新。我们概述了一个包含人工智能在企业创新中的作用的框架。我们通过确定文献的有影响力的方面和提出未来的研究议程来结束这项研究。
文献来源：
Salman B ,Marco C ,Dawood Q .Artificial intelligence and corporate innovation: A review and research agenda[J].Technological Forecasting Social Change,2023,188
PART.5
Artificial intelligence and adaptive response to market changes: A strategy to enhance firm performance and innovation
人工智能与对市场变化的适应性反应：提升企业绩效和创新的策略
Keywords:
Artificial intelligence;Adaptive response to market changes;Innovation;Firm performance;AI-powered capabilities
关键词：
人工智能;对市场变化的适应性反应;创新;企业绩效;人工智能赋能能力
Abstract:
This research examines how AI-powered capabilities can bring value to organizations by enhancing their Adaptive Response to Market Changes (ARMC). Utilizing insights from organizational agility and the dynamic capability framework, we define ARMC as an organization’s ability to promptly identify and adjust to market changes, with customer responsiveness and operational adjustment as foundational competencies. We outline three AI-powered capabilities (AI-enabled automation, AI-enabled analytics, and AI-enabled relational capabilities) as ARMC’s predictors. We posit that the strengths of these relationships depend on environmental hostility and dynamism. Additionally, we propose positive associations between ARMC and three organizational outcomes: firm performance, process innovation, and product innovation. Our research employs a two-stage design, surveying IT and business executives from firms that have adopted AI. The results demonstrate significant interaction effects of environmental hostility and dynamism on the relationships between AI-powered capabilities and ARMC. Furthermore, we find that ARMC positively influences firm performance and innovation.
摘要：
本研究探讨了人工智能能力如何通过增强组织对市场变化的适应性反应( ARMC )为组织带来价值。借鉴组织敏捷性和动态能力框架的观点,我们将ARMC定义为组织能够及时识别和适应市场变化的能力,客户响应能力和运营调整能力是其基础能力。我们概述了ARMC的三个人工智能能力(人工智能赋能的自动化、人工智能赋能的分析和人工智能赋能的关系能力)作为ARMC的预测指标。我们认为,这些关系的强度取决于环境的敌对性和动态性。此外,我们提出了ARMC与三种组织结果之间的正相关关系：企业绩效、流程创新和产品创新。我们的研究采用了一个两阶段的设计,对采用人工智能的企业IT和企业高管进行调查。结果表明,环境的敌对性和动态性对人工智能赋能能力与ARMC关系的交互效应显著。此外，我们发现ARMC对企业绩效和创新有积极影响。
文献来源：
Sullivan Y ,Wamba F S .Artificial intelligence and adaptive response to market changes: A strategy to enhance firm performance and innovation[J].Journal of Business Research,2024,174114500-.
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往期回顾
图文：刘康旭
编辑：李发珍
审核：宁靓、姜忠辉