组态视角下共享制造平台用户活跃度提升的多元路径——基于TOE框架的必要条件分析与模糊集定性比较分析

Multiple Paths to Enhancing User Activity in Shared Manufacturing Platforms from a Configuration Perspective:Necessary Condition Analysis and Fuzzy Set Qualitative Comparative Analysis Based on TOE Framework

加快培育共享制造模式是实现制造业高质量发展的重要途径,而共享制造平台在整个共享制造系统中扮演着供需对接的关键角色。实证研究发现,技术、组织、环境三方面的任一因素均不构成共享制造平台高用户活跃度的必要条件,但是来自政府、行业协会和金融机构等的外部支持在实现平台高用户活跃度上发挥着普遍性作用。提升共享制造平台用户活跃度有三条等效路径,包括规模驱动下的外部支持型、整合内部资源与争取外部支持的双轮驱动型、安全可信机制保障下的外部支持型。其中,强有力的外部支持是三种组态共有的核心条件。此外,平台用户活跃度的因果关系具有非对称性,即产生高用户活跃度的组态对立面并不能导致非高用户活跃度。

Shared manufacturing is a new manufacturing model where production capacity and resources are shared.It is a product of an effective combination of the sharing economy concept and intelligent manufacturing technology.Manufacturing enterprises can effectively reduce production costs and improve resource utilization and production efficiency by sharing production equipment,human resources,and technology.Accelerating the development of shared manufacturing models is of great significance for steering China into a global manufacturing powerhouse.A shared manufacturing platform is the medium and carrier for achieving shared manufacturing.How to optimize various factors to enhance user activity on such platforms and promote production resource sharing is an important practical problem.Based on the TOE framework,this research comprehensively applies the necessary condition analysis(NCA)and fuzzy set qualitative comparative analysis(fsQCA)methods to collect quantitative data from 26 typical shared manufacturing platforms in China to analyze the various paths for such platforms to generate a high user activity from a configuration perspective.The findings are as follows:(1)Six factors,namely,platform technical functions,security and credibility,platform scale,resource integration capability,industrial innovation level,and external support,may affect the user activity on shared manufacturing platforms.(2)None of these factors constitutes a necessary condition for a platform to generate a high user activity;however,external support from governments,industry associations,and financial institutions plays a universal role.(3)There are three equivalent paths to enhancing user activity on a platform,namely,expanding platform scale-seeking external support,integrating internal resources-seeking external support,and enhancing security-seeking external support.(4)Three equivalent paths are found to lead to a non-high user activity on a platform,confirming that the causal mechanism behind a high/non-high user activity on a platform is asymmetrical.This research is expected to make the following potential theoretical contributions.(1)Existing research on user activity on shared manufacturing platforms is based on single case studies,and the robustness and universality of the conclusions drawn are lacking.This study collects quantitative data from 26 samples of diverse shared manufacturing platforms serving different fields for multi-case studies,which can enhance the external validity of the case studies,obtain more universal and robust conclusions,and compensate for the inadequacies of the existing literature.(2)The study examines how six factors in technology,organization,and environment jointly affect platform user activities from a configuration perspective,changing the approach of empirical analysis of single-variable net effects.This broadens research ideas on platform user activity and provides a useful supplement to existing research.(3)This study adopts a combination of NCA and fsQCA methods.This way,not only can we determine whether a certain condition is necessary for the outcome variable but we can also show the degree of necessity at different variable levels.Simultaneously,the two methods confirm each other,thereby improving the robustness of the analysis and conclusions.(4)The study finds that multiple configurations generate a high(non-high)user activity on shared manufacturing platforms.It is confirmed that the opposite of configurations that generate a high user activity does not lead to a non-high user activity,which expands our understanding of the causal structure of a high user activity.