4.7 Article

A framework of sustainability drivers and externalities for Industry 4.0 technologies using the Best-Worst Method

期刊

JOURNAL OF CLEANER PRODUCTION
卷 344, 期 -, 页码 -

出版社

ELSEVIER SCI LTD
DOI: 10.1016/j.jclepro.2022.130909

关键词

Industry 4.0; Sustainability drivers; Externalities; Best-worst method; Multi-criteria decision making; Environmental and social governance

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This paper investigates the role of sustainability drivers in the implementation of Industry 4.0 technologies and proposes a self-assessment framework to assist organizations in evaluating their sustainability drivers and externalities. The study highlights the significance of management support and commitment in sustainability-oriented Industry 4.0 initiatives.
Despite the increasing academic interest in Industry 4.0, only a minority of studies has examined the antecedents and outcomes of sustainability-oriented Industry 4.0 initiatives. In this paper, the authors investigate how sustainability drivers might be taken into account in Industry 4.0 technologies' implementation. Industry 4.0 sustainability drivers and externalities are identified based on a comprehensive review of the literature and categorized based on experts' surveys. The authors employ the Best-Worst Method to prioritize the sustainability drivers and externalities. The results highlight the role of management support and commitment in sustainability-oriented Industry 4.0 initiatives and underline their economic and socio-environmental externalities. Based on the findings, the authors develop a self-assessment framework of Industry 4.0 sustainability drivers and externalities with a readiness index for organizations willing to adopt such initiatives. The authors suggest approaching sustainability-oriented Industry 4.0 implementation through three main stages: approach, deployment, and results (externalities). In doing so, this study contributes to knowledge in the Industry 4.0 and sustainability fields by defining the factors influencing both disciplines and by proposing an integrative readiness model.

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