The influence of digital innovation ecosystem of high-end equipment manufacturing on the intelligent maturity of enterprise – an empirical study on the configuration of the “three-layer core-periphery” structure

IF 4.5 3区 管理学 Q1 BUSINESS
Meifang Li, Yujing Liu
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引用次数: 0

Abstract

Purpose With the deep development of the new technological revolution and industrial transformation, the development, application, expansion and integration of digital technology provide opportunities for transforming the manufacturing industry from traditional manufacturing to intelligent manufacturing. However, little research currently focuses on analyzing the influencing factors of intelligent development in this field. There is a lack of research from the perspective of the digital innovation ecosystem to explore the intrinsic mechanism that drives intelligent development. Therefore, this article starts with high-end equipment manufacturing enterprises as the research subject to explore how their digital innovation ecosystem promotes the effectiveness of enterprise intelligent development, providing theoretical support and policy guidance for enterprises to achieve intelligent development at the current stage. Design/methodology/approach This article constructs a logical framework for the digital innovation ecosystem using a “three-layer core-periphery” structure, collects data using crawling for subsequent indicator measurement and assessment and uses the fuzzy set Qualitative Comparative Analysis method (fsQCA) to explore how the various components of the digital innovation ecosystem in high-end equipment manufacturing enterprises work together to promote the development of enterprise intelligently. Findings This article finds that the various components of the digital innovation ecosystem of high-end equipment manufacturing enterprises, through mutual coordination, can help improve the level of enterprise intelligence. Empirical analysis shows four specific configuration implementation paths for the digital innovation ecosystem of high-end equipment manufacturing enterprises to promote intelligent development. The core conditions and their combinations that affect the intelligent development of enterprises differ in each configuration path. Originality/value Firstly, this article discusses the practical problems of intelligent transformation and development in the manufacturing industry and focuses on the intelligent development effectiveness of various components of the digital innovation ecosystem of high-end equipment manufacturing enterprises in the context of digitalization. Secondly, this article uses crawling, text sentiment analysis and other methods to creatively collect relevant data to overcome the research dilemma of being limited to theoretical analysis due to the difficulty in obtaining data in this field. At the same time, based on the characteristics of high-end equipment manufacturing enterprises, the “three-layer core-periphery” digital innovation ecosystem framework constructed in this article helps to gain a deep understanding of the development characteristics of the industry's enterprises, provides specific indicator analysis for their intelligent development, opening the “black box” of intelligent development in the industry's enterprises and bridging the gap between theory and practice. Finally, this study uses the fsQCA research method of configuration analysis to explore the complexity of the antecedents and investigate the combined effects of multiple factors on intelligent development, providing new perspectives and rich research results for relevant literature on the intelligent development of high-end equipment manufacturing enterprises.
高端装备制造业数字创新生态系统对企业智能成熟度的影响——基于“核心-外围三层”结构配置的实证研究
随着新技术革命和产业变革的深入发展,数字技术的开发、应用、扩展和融合为制造业从传统制造向智能制造转型提供了机遇。然而,目前对这一领域智能化发展的影响因素分析研究甚少。目前还缺乏从数字创新生态系统的视角来探索驱动智能发展的内在机制的研究。因此,本文以高端装备制造企业为研究对象,探讨其数字创新生态系统如何促进企业智能化发展的有效性,为现阶段企业实现智能化发展提供理论支持和政策指导。本文采用“核心-外围三层”结构构建了数字创新生态系统的逻辑框架。采用爬行法收集数据进行后续指标测量和评估,采用模糊集定性比较分析法(fsQCA)探讨高端装备制造企业数字创新生态系统各组成部分如何协同作用,促进企业智能化发展。研究发现,高端装备制造企业数字化创新生态系统的各组成部分通过相互协调,有助于提升企业智能化水平。实证分析显示了高端装备制造企业数字化创新生态系统促进智能化发展的四种具体配置实施路径。在不同的配置路径上,影响企业智能化发展的核心条件及其组合是不同的。本文首先探讨了制造业智能化转型发展的现实问题,重点研究了数字化背景下高端装备制造企业数字化创新生态系统各组成部分的智能化发展成效。其次,本文采用抓取、文本情感分析等方法创造性地收集相关数据,克服了该领域因数据难以获取而局限于理论分析的研究困境。同时,基于高端装备制造企业的特点,本文构建的“核心-外围三层”数字创新生态系统框架有助于深入了解行业企业的发展特点,为其智能化发展提供具体的指标分析,打开行业企业智能化发展的“黑匣子”,弥合理论与实践之间的差距。最后,本研究采用组态分析的fsQCA研究方法,探究前因变量的复杂性,考察多因素对智能发展的综合影响,为高端装备制造企业智能发展的相关文献提供了新的视角和丰富的研究成果。
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来源期刊
CiteScore
8.60
自引率
9.80%
发文量
58
期刊介绍: Business processes are a fundamental building block of organizational success. Even though effectively managing business process is a key activity for business prosperity, there remain considerable gaps in understanding how to drive efficiency through a process approach. Building a clear and deep understanding of the range process, how they function, and how to manage them is the major challenge facing modern business. Business Process Management Journal (BPMJ) examines how a variety of business processes intrinsic to organizational efficiency and effectiveness are integrated and managed for competitive success. BPMJ builds a deep appreciation of how to manage business processes effectively by disseminating best practice. Coverage includes: BPM in eBusiness, eCommerce and eGovernment Web-based enterprise application integration eBPM, ERP, CRM, ASP & SCM Knowledge management and learning organization Methodologies, techniques and tools of business process modeling, analysis and design Techniques of moving from one-shot business process re-engineering to continuous improvement Best practices in BPM Performance management Tools and techniques of change management BPM case studies.
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