从企业的初始背景和背景设计工业4.0的实施

V. Rocchi, D. Brissaud
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引用次数: 1

摘要

工业4.0是一个很有前途的概念,它使工业能够通过灵活和有弹性的流程以及高度个性化的产品来满足客户的需求。这个概念由不同的维度组成。长期以来,创新的数字技术一直被认为是数字化转型项目成功的唯一维度。在工厂推广数字技术时,组织、战略和人力资源等其他方面也被确定为关键。根据这些发现,研究人员设计了工业4.0理论模型,然后建立了准备就绪模型,以分析公司初始情况与理论模型之间的差距。然而,这种纯粹的演绎方法没有考虑到公司的背景和背景,最终倾向于单一的数字化转型模式。本文旨在分析四个实际的数字化转型项目,并证明数字化转型的成败取决于与公司背景和背景相关的两个变量的组合。这项研究基于双重方法:演绎和归纳。首先,对工业4.0概念及其主要维度进行了界定,并对数字化转型的成功因素和障碍进行了研究。其次,设计了一个定性调查,深入研究了四个实际的行业数字化转型项目,它们的起源和执行情况,以分析成功或失败的关键变量。对项目成员进行了46次半结构化访谈;访谈采用主题内容分析法进行分析。然后,对每个数字化转型项目的关键变量进行建模,并对成功或失败进行分析。调查项目整合了数字化转型的模式。最后,确定了九个数字化转型模型。行业从业者可以根据正确的模式设计他们的数字化转型项目组织和战略。
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Designing industry 4.0 implementation from the initial background and context of companies
Industry 4.0 is a promising concept that allows industries to meet customers’ demands with flexible and resilient processes, and highly personalised products. This concept is made up of different dimensions. For a long time, innovative digital technology has been thought of as the only dimension to succeed in digital transformation projects. Other dimensions have been identified such as organisation, strategy, and human resources as key while rolling out digital technology in factories. From these findings, researchers have designed industry 4.0 theoretical models and then built readiness models that allow for analysing the gap between the company initial situation and the theoretical model. Nevertheless, this purely deductive approach does not take into consideration a company’s background and context, and eventually favours one single digital transformation model. This article aims at analysing four actual digital transformation projects and demonstrating that the digital transformation’s success or failure depends on the combination of two variables related to a company’s background and context. This research is based on a double approach: deductive and inductive. First, a literature review has been carried out to define industry 4.0 concept and its main dimensions and digital transformation success factors, as well as barriers, have been investigated. Second, a qualitative survey has been designed to study in-depth four actual industry digital transformation projects, their genesis as well as their execution, to analyse the key variables in succeeding or failing. 46 semi-structured interviews were carried out with projects’ members; interviews have been analysed with thematic content analysis. Then, each digital transformation project has been modelled regarding the key variables and analysed with regards to succeeding or failing. Investigated projects have consolidated the models of digital transformation. Finally, nine digital transformation models have been identified. Industry practitioners could design their digital transformation project organisation and strategy according to the right model.
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