制造业企业智能化的转型路径：基于“技术-组织-环境”（TOE）理论的组态分析

The Intelligent Transformation Path of Manufacturing Enterprises: Configuration Analysis Based on TOE Theory

摘要:

制造业企业智能化转型是制造业发展的关键趋势，不同企业由于企业特点不同，需要合理选择转型路径。为深入探讨制造业企业智能化转型的动态过程，基于“技术-组织-环境”分析框架，构建包含制造能力、技术应用、技术创新、企业规模、人力资源、金融支持6个关键前因条件的理论框架，采用动态定性比较分析方法，利用Python分析2015－2021年86家制造业转型成功企业，探讨制造业企业智能化转型在时间纵轴上的组态效应，以为技术基础、内部资源、环境依赖度不同制造企业明确转型路径。研究发现：技术因素是提升制造业智能化水平的关键条件，5条组态的一致性水平在研究期内呈现上升趋势，并根据企业规模划分出大型企业和中小型企业两类有助于实现制造业企业智能化转型路径，二者均有利于发挥多个要素的协同作用；行业特点对智能化转型路径的选择具有明显的行业异质性，5条路径对食品、印刷、家具制造业的解释力度较低；5条路径的一致性在研究期间均呈现出上升趋势，且都在2020年前后存在小幅回落，这可能是因为受到新冠疫情的冲击。因此，制造业企业要通过引进工业机器人参与生产环节中自动化来完成智能化转型。

Abstract:

In the digital economy era, smart manufacturing serves as the main battlefield for the integration of a new round of technological revolution and manufacturing. Intelligent transformation has become the key for manufacturing enterprises to gain sustainable competitive advantages. However, due to their unique characteristics, different enterprises need to reasonably choose their transformation paths based on their internal and external conditions. To delve into the dynamic process of intelligent transformation in manufacturing enterprises, this study constructs a theoretical framework incorporating six key antecedent conditions: manufacturing capabilities, technology application, technological innovation, enterprise scale, human resources, and financial support, using the "Technology-Organization-Environment" (TOE) analytical framework. Employing fuzzy-set qualitative comparative analysis (fsQCA), we analyze 86 successfully transformed manufacturing enterprises from 2015 to 2021 using Python, exploring the configuration effects of intelligent transformation in manufacturing enterprises across the time axis. This research aims to clarify transformation paths for manufacturing enterprises with varying technological foundations, internal resources, and environmental dependencies. The findings reveal:(1) Technological factors are crucial in enhancing the level of smart manufacturing.(2) The consistency levels of the five configurations show an upward trend during the study period. Dividing enterprises into large-scale and small-to-medium-sized enterprises (SMEs) facilitates the identification of distinct paths for smart transformation in manufacturing. Both categories benefit from the synergistic effects of multiple factors. Large enterprises' transformation paths (Configurations 1 and 4) are characterized by the core variable of technology application, complemented by other factors to achieve intelligent transformation. SMEs' transformation paths (Configurations 2, 3, and 5) are primarily driven by SMEs, with multiple factors working in concert to facilitate intelligent transformation.(3) Industry characteristics exhibit significant heterogeneity in the choice of intelligent transformation paths. The five paths show lower explanatory power for the food, printing, and furniture manufacturing industries. The consistency of all five paths displays an upward trend during the study period, with slight declines around 2020, possibly attributed to the impact of the COVID-19 pandemic. Consequently, manufacturing enterprises should complete their intelligent transformation by introducing industrial robots into production processes to automate production.