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The purpose of this paper is to investigate, from a thorough review of the literature, the role of metaverse-based quality 4.0 (MV-based Q4.0) in achieving manufacturing resilience (MFGRES). Based on a categorization of MV-based Q4.0 enabler technologies and MFGRES antecedents, the paper provides a conceptual framework depicting the relationship between both areas while exploring existing knowledge in current literature.

The paper is structured as a comprehensive systematic literature review (SLR) at the intersection of MV-based Q4.0 and MFGRES fields. From the Scopus database up to 2023, a final sample of 182 papers is selected based on the inclusion/exclusion criteria that shape the knowledge base of the research.

In light of the classification of reviewed papers, the findings show that artificial intelligence is especially well-suited to enhancing MFGRES. Transparency and flexibility are the resilience enablers that gain most from the implementation of MV-based Q4.0. Through analysis and synthesis of the literature, the study reveals the lack of an integrated approach combining both MV-based Q4.0 and MFGRES. This is particularly clear during disruptions.

This study has a significant impact on managers and businesses. It also advances knowledge of the importance of MV-based Q4.0 in achieving MFGRES and gaining its full rewards.

This paper makes significant recommendations for academics, particularly those who are interested in the metaverse concept within MFGRES. The study also helps managers by illuminating a key area to concentrate on for the improvement of MFGRES within their organizations. In light of this, future research directions are suggested.

Over the next decade, humanity is going to face big environmental problems, and considering these serious issues, businesses are adopting environmentally responsible practices. To put forward specific measures to achieve a more prosperous environmental future, this study aims to develop an environment-based perspective framework by integrating the Internet of Things (IoT) technology into a sustainable automotive supply chain (SASC).

The study presents a conceptual environmental framework – based on 29 factors constituting four stakeholders' rectifications – that holistically assess the SASC operations as part of the ReSOLVE model utilizing IoT. Then, experts from the SASC, IoT and sustainability areas participated in two rigorous rounds of a Delphi study to validate the framework.

The results indicate that the conceptual environmental framework proposed would help companies enhance the connectivity between major IoT tools in SASC, which would help develop congruent strategies for inducing sustainable growth.

This study adds value to existing knowledge on SASC sustainability and digitalization in the context where the SASC is under enormous pressure, competitiveness and increased variability.

This study aims to address Industry 4.0 (I4.0) technologies that can improve the research and implementation of lean supply chain management (LSCM) and the enhanced LSCM subfields in I4.0 technologies.

The authors conducted a systematic literature review to detect, categorize and assess recent data, highlighting patterns and providing suggestions for potential research in this field, to investigate I4.0 literature and its effect on LSCM. The authors examined 79 published types of research from the Scopus database that were published between 2010 and 2021 and classified them into four LSCM fields: logistics, production, supply chain and marketing.

The authors can emphasize the fact that the literature on this topic is in progress, from early German academic research to the current creation of new effects around the world. The majority of the potential effects investigated were discovered to improve specific areas that ultimately enhance the practices of the four LSCM domains as well as performance outcomes. The authors were also able to assess the extent to which present and upcoming I4.0 technologies can improve LSCM research and implementation.

To the best of the authors’ knowledge, this is the first study of its kind. Although some research looked into various areas of I4.0 and LSCM topics, there has been no research specifically looking into the impact of I4.0 on LSCM. The originality of this study lies in the treatment of the main fields and sub-fields of LSCM, which can benefit from the technologies of I4.0. Academic scholars interested in the research topics may benefit from the findings of this study. Organizations in various industrial sectors, particularly manufacturing, where lean thinking is used, business professionals specialized in lean operations and supply chain management, along with anyone else who wants to learn more about the interrelationships between I4.0 and LSCM.