管理评论 ›› 2023, Vol. 35 ›› Issue (10): 340-352.

• 案例研究 • 上一篇    

传统制造企业数据驱动动态能力的构建机制研究——基于娃哈哈集团数字化实践的案例分析

陈瑜1,2, 陈衍泰3, 谢富纪4   

  1. 1. 上海立信会计金融学院工商管理学院, 上海 201620;
    2. 教育部学位与研究生教育发展中心, 北京 100083;
    3. 浙江工商大学数字创新与全球价值链升级研究中心, 杭州 310018;
    4. 上海交通大学安泰经济与管理学院, 上海 200030
  • 收稿日期:2022-06-30 出版日期:2023-10-28 发布日期:2023-11-27
  • 作者简介:陈瑜,上海立信会计金融学院工商管理学院副教授,硕士生导师,博士;陈衍泰,浙江工商大学数字创新与全球价值链升级研究中心教授,博士生导师;谢富纪,上海交通大学安泰经济与管理学院教授,博士生导师。
  • 基金资助:
    国家社会科学基金重大项目(21&ZD130);国家自然科学基金重点项目(72032008);上海立信会计金融学院金融科技研究专项(2023-JK08-A)。

Research on the Construction Mechanism of Data-driven Dynamic Capabilities of Traditional Manufacturing Enterprises: Based on the Case Study of Digital Practice of Wahaha Group Co., Ltd.

Chen Yu1,2, Chen Yantai3, Xie Fuji4   

  1. 1. School of Business Administration, Shanghai Lixin University of Accounting and Finance, Shanghai 201620;
    2. China Academic Degrees and Graduate Education Development Center, Beijing 100083;
    3. Center for Digital Innovation and Global Value Chain Upgrading, Zhejiang Gongshang University, Hangzhou 310018;
    4. Antai School of Economics and Management, Shanghai Jiao Tong University, Shanghai 200030
  • Received:2022-06-30 Online:2023-10-28 Published:2023-11-27

摘要: 传统制造企业在数字化环境下既迎来新的机遇,也面临严峻的挑战。如何构建数据驱动动态能力是传统企业转型成功的关键。本文以杭州娃哈哈集团有限公司数字化的实践过程为案例研究对象,探讨传统制造企业数据驱动动态能力的构建机制。研究发现:(1)传统制造企业数据驱动动态能力是由数据驱动的机会感知能力、数据驱动的产业链协同能力、数据驱动的组织变革能力和数据驱动的价值生态能力这四个维度构成。(2)这四种能力又可以具体细分为13个主范畴。(3)这四种能力是层层递进、相互加强的关系。其中,数据驱动的机会感知能力是基础,也是前提条件;数据驱动的产业链协同能力是关键,也是实现手段;数据驱动的组织变革能力是保障,也是支撑条件;数据驱动的价值生态能力是杠杆,具备放大效应。本文的贡献在于:在数字化情境下,提出了传统制造企业数据驱动动态能力的四维度分析框架,并深入剖析了不同维度动态能力的来源及相互作用机制。本文的研究结论对传统制造企业如何进行数字化转型,及把数字资源内化为组织的数据驱动动态能力具有一定的借鉴和启示。

关键词: 传统制造企业, 数据驱动, 动态能力, 构建机制

Abstract: Traditional manufacturing enterprises are facing both new opportunities and challenges in the digital environment. How to build data-driven dynamic capabilities is the key to the success of traditional enterprise transformation. Taking Hangzhou Wahaha Group Co., Ltd. as a case study, this paper discusses the construction mechanism of data-driven dynamic capabilities. There are some main findings as follows. First, the data-driven dynamic capabilities of traditional manufacturing enterprises are composed of four dimensions: data-driven opportunity perception capability, data-driven industrial chain synergy capability, data-driven organizational transformation capability and data-driven value ecosystem capability. Second, these four capabilities can be subdivided into 13 main categories. Third, these four capabilities are progressive and mutually reinforcing. Among them, data-driven opportunity perception capability is the basis and prerequisite. Data-driven industrial chain synergy capability is the key and means of implementation. Data-driven organizational transformation capability is the guarantee and the supporting condition. Data-driven value ecosystem capability is leverage, with an amplification effect. The contribution of the paper is that a four-dimensional analysis framework is proposed, then the sources and interaction mechanisms of different dimensions are deeply analyzed. The conclusion of the paper has implications for how traditional manufacturing enterprises should carry out digitalization and transform digital resources into their data-driven dynamic capabilities.

Key words: traditional manufacturing enterprises, data-driven, dynamic capabilities, construction mechanism