系统管理学报 ›› 2023, Vol. 32 ›› Issue (5): 995-1008.DOI: 10.3969/j.issn.1005-2542.2023.05.010

• 技术管理与创新管理 • 上一篇    下一篇

数字化环境下制造企业服务创新反哺产品创新扩散机理

李玉娟1,罗建强1,2   

  1. 1.江苏大学管理学院,江苏 镇江 212013;2.江苏大学中国农业装备产业发展研究院,江苏 镇江 212013
  • 收稿日期:2022-12-26 修回日期:2023-03-20 出版日期:2023-09-28 发布日期:2023-09-28
  • 作者简介:李玉娟(1997-),女,博士生。研究方向为服务型制造企业产品创新和服务创新。
  • 基金资助:

    国家自然科学基金资助项目(71772080);江苏省研究生科研与实践创新计划项目(KYCX21_3315)

Diffusion Mechanism of Service Innovation Back-Feeding Product Innovation for Manufacturing Enterprises in  the Digital Environment

LI Yujuan1,LUO Jianqiang1,2   

  1. 1.School of Management,Jiangsu University,Zhenjiang 212013,Jiangsu,China,2.China Research Institute for Agricultural Equipment Industry Development,Jiangsu University,Zhenjiang 212013,Jiangsu,China
  • Received:2022-12-26 Revised:2023-03-20 Online:2023-09-28 Published:2023-09-28

摘要:

数字化环境下制造企业服务创新和产品创新协同发展过程依然存在鸡蛋相生之谜。为揭示数字化环境下服务创新对产品创新的反哺作用机理,借助服务创新过程能够产生支持产品创新数据/信息的优势,构建数字化环境下服务创新反哺产品创新的Bass创新扩散模型,解析数字化对两类创新关系的影响,探究以知识转化为视角的两类创新扩散规律。结果表明:数字化环境下两类创新相互作用能够实现产品创新的客户采纳更大化;利用数字技术将数据转化为用以指导产品创新的知识,能够精准产品创新的方向并易于为客户采纳;制造企业数字化水平越高,内外部因素对两类创新扩散的影响将愈加显著,其中外部因素的影响作用逐渐增加,内部因素的影响作用逐渐弱化;构建的修正Bass创新扩散模型预测精度优于经典Bass模型,能够揭示数字化环境下服务创新经知识转化反哺产品创新过程,契合数字经济下制造企业创新发展规律。

关键词: 产品创新, 服务创新, Bass模型, 数字技术, 客户知识

Abstract:

In the digital environment, the synchronic development between service innovation and product innovation of manufacturing enterprises still has the problem of “Which came first, the chicken or the egg?. In order to reveal the back-feeding mechanism of service innovation on product innovation in the digital environment, with the help of the advantage that service innovation process can generate data/information to support product innovation, this paper constructed a Bass innovation diffusion model of service innovation back-feeding product innovation in the digital environment. It analyzethe influence of digitization on the relationship between two types of innovation, explorethe diffusion regular of two types of innovation from the perspective of knowledge transformation. The results show that the interaction between the two types of innovation in the digital environment can achieve a greater customer adoption of product innovation. Using digital technology to transform data into knowledge to guide product innovation can be accurate and easy for customers to adopt. The higher the digitalization level of manufacturing enterprises, the more significant the impact of internal and external factors on the diffusion of two types of innovation will be. The impact of external factors will gradually increase, while the impact of internal factors will gradually decrease. The prediction of the modified Bass innovation diffusion model is more accurate than that of the classical Bass model, and can reveal the process of service innovation back-feeding product innovation through knowledge transformation in the digital environment, which accords with the regular of innovation development of manufacturing enterprises in the digital economy.

Key words: product innovation, service innovation, Bass model, digital technology, customer knowledge

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