The Relationship between Circular Economy, Industry 4.0 and Supply Chain Performance: A Combined ISM/Fuzzy MICMAC Approach

Abstract

This paper aims to assess the relationship between Industry 4.0 (I4.0) and the circular economy that could contribute to supply chain management performance. To achieve this, a combination of the interpretative structural modelling (ISM) and (cross-impact matrix multiplication applied to classification) MICMAC approach was used to establish the interrelationships between these topics. The developed analysis reveals that there are 19 constructs capable of elucidating this relationship and that there is a hierarchy between these constructs, which are presented in a structural model. Further, the different levels of dependency and driving power are compared in a cluster diagram. As the main result, it was found that there is a strong mutual relationship between the basic technologies. The use of Internet of Things and cloud computing technologies influences the collection of large amounts of data, leading to big data, which in turn influence the use of data analytics tools to obtain competitive advantages. These outcomes may contribute to managers’ more assertive decision-making regarding the selection, implementation, and evaluation of projects adopting Industry 4.0 technologies and circular economy approaches in supply chains. Moreover, our study could be the basis for future empirical research to investigate how companies incorporate Industry 4.0 technologies into their processes and how this influences the quest for sustainable supply chains.

The role of digital technologies in supporting the implementation of circular economy practices by industrial small and medium enterprises

“…CLOUD, HVSYS, and IoT are among the most adopted DTs, thus supporting Filho et al (2022), Marcon et al (2022), and Ruggero et al (2020). These DTs are largely recognised as a catalyst for further digitalisation (Pirola et al, 2020).…”

“…Finally, Cloud computing (CLOUD) allows the storage and sharing of data between stakeholders along the supply chain (Filho et al, 2022). Specifically, CLOUD shows great potential in different industries to promote collaboration (Gebhardt et al, 2022), whereas no specific CE practices enabled by this DT have been discussed within the extant literature.…”

“…The adoption and the use of DTs by the investigated firms are rather limited-with an average level of 2.7, following previous insights on the level of digitalization among Italian manufacturing firms(Cimini et al, 2021;Zheng et al, 2020), and SMEs in particular (European Investment Bank, 2021). CLOUD, HVSYS, and IoT are among the most adopted DTs, thus supportingFilho et al (2022),Marcon et al (2022), andRuggero et al (2020). These DTs are largely recognised as a catalyst for further digitalisation(Pirola et al, 2020).…”

Barriers to adopt industry 4.0 in supply chains using interpretive structural modeling

“…Finally, using interpretive structural modeling (ISM), a structural model of barriers to adopt Industry 4.0 was constructed. Such a methodology was applied in many prior works (e.g., Kamble et al, 2018;Karadayi-Usta, 2019;Raj et al, 2020;Kumar et al, 2021;Etemadi et al, 2021;Sarkar & Shankar, 2021;Gupta & Goyal, 2021;Goel et al, 2022;Godinho et al, 2022;Desingh, 2022, Verma et al, 2022.…”

Evolving trajectories of circular supply chain domain: a citation path analysis

“…(2023) proposed a blockchain-driven framework to highlight cause-effect relationships to highlight the role of seizing, sensing and reconfiguring dynamic capabilities. Godinho et al. (2022) investigated how SCM performance could be enhanced by the relationship between Industry 4.0 and the CE.…”