数字化转型场景驱动制造企业创新过程机理研究

摘要/Abstract

摘要： 制造企业凭借丰富的生产数据、复杂的生产场景、紧密的供应链合作关系以及产品定制化需求，形成了独特的场景驱动创新优势。然而，现有文献对于制造企业如何实现场景驱动创新并未给出充分解释。从场景和知识双重视角，聚焦不同数字化转型场景驱动制造企业创新过程中场景特征及人机知识元素关系特征变化对创新结果的差异性影响，基于一家商务印刷企业持续数字化转型实践展开案例研究。研究发现：第一，场景可解构为时空约束和需求情境内容两部分，其中，时空约束是场景的基本组成部分，而场景内容特征是影响场景内主体交互行为和模式的关键，具备确定性和复杂性特征。第二，场景驱动创新的实现主要聚焦于场景内容重塑、场景内容优化和场景内容衍生三个方面，其背后体现的是场景内容维度中主体和业务的持续交互以及由此引发的场景特征（时空维度与内容维度）进一步改变。第三，基于场景内容特征和创新行为解析三类数字化转型场景驱动制造企业创新结果，表现为效率型、专家型和扩展型三种创新模式，过程中会发生知识元素替代性、互补性和组合多样性变化。研究内容对场景要素及其驱动创新过程具有重要的理论和实践价值。

关键词: 场景驱动创新, 制造企业数字化转型, 时空框架, 需求情景内容, 知识元素关系特征

Abstract: Manufacturing enterprises, with their rich production data, complex production scenarios, close supply chain partnerships, and customized product demands, have developed a unique advantage in scenario-driven innovation. However, existing literature has not provided sufficient explanations on how manufacturing enterprises achieve scenario-driven innovation. From both the perspectives of scenarios and knowledge, this study focuses on the differential impact of scenario-specific characteristics and the evolving relationship between human-machine knowledge elements on innovation outcomes during the digital transformation process of manufacturing enterprises. A case study is conducted based on the ongoing digital transformation practices of a business printing enterprise. The research findings are as follows: First, a scene can be deconstructed into two parts: temporal-spatial constraints and the content of the demand scenario. Among them, the temporal-spatial constraints form the basic components of the scene, while the characteristics of the scene content are key to influencing the interactive behaviors and patterns of the subjects within the scene, exhibiting features of both determinacy and complexity. Second, the realization of scenario-driven innovation mainly focuses on three aspects: reshaping scenario content, optimizing scenario content, and deriving scenario content. Behind this lies the continuous interaction between the subject and the business within the scenario content dimension, which further leads to changes in scenario characteristics (both spatial-temporal and content dimensions). Third, based on the characteristics of scenario content and innovation behaviors, three types of digital transformation-driven innovation outcomes in manufacturing enterprises are identified: efficiency-oriented, expert-oriented, and expansion-oriented innovation models. During this process, three changes in knowledge elements occur: substitutability, complementarity, and combinatorial diversity. The research has significant theoretical and practical value for understanding scenario elements and their role in driving the innovation process.

Key words: scenario-driven innovation, digital transformation of manufacturing enterprises, spatial-temporal framework, demand scenario content, knowledge element relationship characteristics

张培, 杨丹丹. 数字化转型场景驱动制造企业创新过程机理研究[J]. 管理评论, 2026, 38(2): 274-288.

Zhang Pei, Yang Dandan. Research on the Mechanism of How Manufacturing Enterprise Innovation Process Is Drivern by Digital Transformation Scenario[J]. Management Review, 2026, 38(2): 274-288.

参考文献

[1] 程鹏,梁艳,柳卸林,等. 突破性产品创新群的实现机制——基于应用场景视角[J]. 科学学与科学技术管理, 2022,43(12):76-93 Cheng P., Liang Y., Liu X. L., et al. Moving Radical Technology towards Innovation Cluster: From the Perspective of Scenario[J]. Science of Science and Management of S.& T., 2022,43(12):76-93
[2] Just J. Natural Language Processing for Innovation Search - Reviewing an Emerging Non-human Innovation Intermediary[J]. Technovation, 2024,129:102883
[3] Troise C., Corvello V., Ghobadian A., et al. How can SMEs Successfully Navigate VUCA Environment: The Role of Agility in the Digital Transformation Era[J]. Technological Forecasting and Social Change, 2022,174:121227
[4] 应瑛,张晓杭,孔小磊,等. 制度视角下的制造企业数字化转型过程:一个纵向案例研究[J]. 研究与发展管理, 2022,34(1):8-20 Ying Y., Zhang X. H., Kong X. L., et al. Digital Transformation Process of Manufacturing Enterprises: A Longitudinal Case Study[J]. R&D Management, 2022,34(1):8-20
[5] Balasubramanian N., Ye Y., Xu M. Substituting Human Decision-making with Machine Learning: Implications for Organizational Learning[J]. Academy of Management Review, 2022,47(3):448-465
[6] 尹西明,苏雅欣,陈劲,等. 场景驱动的创新:内涵特征、理论逻辑与实践进路[J]. 科技进步与对策, 2022,39(15):1-10 Yin X. M., Su Y. X., Chen J., et al. Context-driven Innovation: Connotation, Theoretical Logic and Practical Approach[J]. Science & Technology Progress and Policy, 2022,39(15):1-10
[7] 金镭,赵媛媛,尹西明. 制造业专精特新中小企业如何通过场景驱动技术创新:爱博诺德2010—2024年纵向案例研究[J]. 中国软科学, 2025,(5):41-54 Jin L., Zhao Y. Y., Yin X. M. How do Specialized，Sophisticated， Innovative，and Novel Manufacturing Firms Achieve Technological Innovation Through Context-driven Innovation: A Longitudinal Case Study of EYEBRIGHT from 2010 to 2024[J]. China Soft Science, 2025,(5):41-54
[8] Kenny D., Marshall J. F. Contextual Marketing—The Real Business of the Internet[J]. Harvard Business Review, 2000,78(6): 119-125
[9] 邹波,杨晓龙,董彩婷. 基于大数据合作资产的数字经济场景化创新[J]. 北京交通大学学报(社会科学版), 2021,20(4):34-43 Zou B., Yang X. L., Dong C. T. Scenario-based Innovation of Digital Economy from the Perspective of Big Data-based Cooperative Assets[J]. Journal of Beijing Jiaotong University (Social Sciences Edition), 2021,20(4):34-43
[10] Xie K., Wu Y., Xiao J., et al. Value Co-creation between Firms and Customers: The Role of Big Data-based Cooperative Assets[J]. Information & Management, 2016,53(8):1034-1048
[11] 俞鼎,李正风. 智能社会实验:场景创新的责任鸿沟与治理[J]. 科学学研究, 2024,42(6):1121-1128 Yu D., Li Z. F. Intelligence Social Experiments:The Responsibility Gap of Context-driven Innovation and Its Governance[J]. Studies in Science of Science, 2024,42(6):1121-1128
[12] 蔡春花,刘伟,江积海. 商业模式场景化对价值创造的影响——天虹股份2007—2018年数字化转型纵向案例研究[J]. 南开管理评论, 2020,23(3):98-108 Cai C. H., Liu W., Jiang J. H. Effect of Business Model Contextualization on Value Creation: A Case Study of RAINBOW’s Digital Transformation from 2007 to 2018[J]. Nankai Business Review, 2020,23(3):98-108
[13] 吴小龙,肖静华,吴记. 人与AI协同的新型组织学习:基于场景视角的多案例研究[J]. 中国工业经济, 2022,(2):175-192 Wu X. L., Xiao J. H., Wu J. New Organizational Learning for Human-AI Collaboration：A Multi-case Study from a Scenario Perspective[J]. China Industrial Economics, 2022,(2):175-192
[14] Jarrahi M. H. Artificial Intelligence and the Future of Work: Human-AI Symbiosis in Organizational Decision Making[J].Business Horizons, 2018,61(4):577-586
[15] 李明,王卫. 场景驱动、商业模式与创新生态系统演进——基于特斯拉企业价值的逻辑起点[J]. 科技进步与对策, 2023,40(17):45-55 Li M., Wang W. Context-driven Concept, Business Model and the Evolution of Technological Innovation Ecosystem: An Analysis Based on the Logical Starting Point of Tesla’s Enterprise Value[J]. Science & Technology Progress and Policy, 2023,40(17):45-55
[16] Melville N. P. Information Systems Innovation for Environmental Sustainability[J]. MIS Quarterly, 2010,34(1):1-22
[17] Liu Y. A., Jiang Z. J., Choi B. C. F. Pushing Yourself Harder: The Effects of Mobile Touch Modes on Users’ Self-regulation[J]. Information Systems Research, 2023,34(3):996-1016
[18] Rapa M., Ciano S., Orsini F., et al. Adoption of AI-based Technologies in the Food Supplement Industry: An Italian Start-up Case Study[J]. Systems, 2023,11(6):265
[19] Bresciani S., Huarng K. H., Malhotra A., et al. Digital Transformation as a Springboard for Product, Process and Business Model Innovation[J]. Journal of Business Research, 2021,128:204-210
[20] Nambisan S., Wright M., Feldman M. The Digital Transformation of Innovation and Entrepreneurship: Progress， Challenges and Key Themes[J]. Research Policy, 2019,48(8):103773
[21] Faccio M., Minto R., Rosati G., et al. The Influence of the Product Characteristics on Human-robot Collaboration: A Model for the Performance of Collaborative Robotic Assembly[J]. The International Journal of Advanced Manufacturing Technology, 2020,106(5-6):2317-2331
[22] Krakowski S., Luger J., Raisch S. Artificial Intelligence and the Changing Sources of Competitive Advantage[J]. Strategic Management Journal, 2023,44(6):1425-1452
[23] Najafi-Tavani S., Najafi-Tavani Z., Naudé P., et al. How Collaborative Innovation Networks Affect New Product Performance: Product Innovation Capability, Process Innovation Capability, and Absorptive Capacity[J]. Industrial Marketing Management, 2018,73:193-205
[24] 皮圣雷,王婧. 企业数字化转型中的定位调整与核心能力“扬弃”——一个多案例研究[J]. 管理评论, 2023,35(11):336-352 Pi S. L., Wang J. Enterprises’ Repositioning and Core Competence Developing and Discarding during Their Digital Transformation—A Multi-case Study[J]. Management Review, 2023,35(11):336-352
[25] 张培,杨丹丹. 跨越知识边界:制造企业的知识创新实现——数字知识主导逻辑下的案例研究[J]. 科学学研究, 2025,43(6):1262-1274 Zhang P., Yang D. D. Knowledge Boundary Spanning: Achieving Knowledge Innovation in Manufacturing Enterprises—A Case Study on the Dominant Logic of Digital Knowledge[J]. Studies in Science of Science, 2025,43(6):1262-1274
[26] Colombelli A., Krafft J., Quatraro F. Properties of Knowledge Base and Firm Survival: Evidence from a Sample of French Manufacturing Firms[J]. Technological Forecasting and Social Change, 2013,80(8):1469-1483
[27] Dibiaggio L., Nasiriyar M., Nesta L. Substitutability and Complementarity of Technological Knowledge and the Inventive Performance of Semiconductor Companies[J]. Research Policy, 2014,43(9):1582-1593
[28] Sampson R. C. R&D Alliances and Firm Performance: The Impact of Technological Diversity and Alliance Organization on Innovation[J]. Academy of Management Journal, 2007,50(2):364-386
[29] 王泓略,曾德明,陈培帧. 企业知识重组对技术创新绩效的影响:知识基础关系特征的调节作用[J]. 南开管理评论, 2020,23(1):53-61 Wang H. L., Zeng D. M., Chen P. Z. A Research on Knowledge Recombination and Technology Innovation Performance: Moderate Effect of Knowledge Elements Relationship Characteristic[J]. Nankai Business Review, 2020,23(1):53-61
[30] Leonard-Barton D. Core Capabilities and Core Rigidities: A Paradox in Managing New Product Development[J]. Strategic Management Journal, 1992,13(S1):111-125
[31] 曾德明,周涛. 企业知识基础结构与技术创新绩效关系研究——知识元素间关系维度新视角[J]. 科学学与科学技术管理, 2015,36(10):80-88 Zeng D. M., Zhou T. The Relationship between Knowledge Base and Innovation Performance: A New Relational Perspective of Knowledge Elements[J]. Science of Science and Management of S.& T., 2015,36(10):80-88
[32] 尹西明,武沛琦,钱雅婷,等. 人机场三元协同如何赋能新质生产力:范式逻辑与实践进路[J]. 科研管理, 2025,46(2):43-52 Yin X. M., Wu P. Q., Qian Y. T., et al. The Empowerment of New Quality Productive Forces by the Human-Machine-Context Collaboration: Its Paradigm Logic and Practical Approaches[J]. Science Research Management, 2025,46(2):43-52
[33] 江积海,唐倩,王烽权. 商业模式多元化及其创造价值的机理:资源协同还是场景互联?——美团2010—2020年纵向案例研究[J]. 管理评论, 2022,34(1):306-321 Jiang J. H., Tang Q., Wang F. Q. Business Model Diversification and the Mechanism of Value Creation: Resource Synergy or Context Interconnection? A Case Study of Meituan from 2010 to 2020[J]. Management Review, 2022,34(1):306-321
[34] Mueller B., Lauterbach J. How to Speed up Your Digital Transformation[J]. Harvard Business Review Digital Articles, 2021：1-10
[35] 毛基业,陈诚. 案例研究的理论构建:艾森哈特的新洞见——第十届“中国企业管理案例与质性研究论坛(2016) ”会议综述[J]. 管理世界, 2017,33(2):135-141 Mao J. Y., Chen C. Theoretical Construction of Case Study: New Insights from Eisenhardt—A Summary of the 10th “China Business Management Case and Qualitative Research Forum (2016)” Conference[J]. Journal of Management World, 2017,33(2):135-141
[36] Gioia D. A., Corley K. G., Hamilton A. L. Seeking Qualitative Rigor in Inductive Research: Notes on the Gioia Methodology[J].Organizational Research Methods, 2013,16(1):15-31
[37] 许晖,王泽鹏,杨金东. 从人机冲突走向人机融合:知识编排视角下制造型企业的人机关系重塑[J]. 中国工业经济, 2024,42(4):170-188 Xu H., Wang Z. P., Yang J. D. From Human-machine Conflict to Human-Machine Integration: The Remodeling of Human-Machine Relationship in Manufacturing Enterprises from the Perspective of Knowledge Orchestration[J]. China Industrial Economics, 2024,42(4):170-188