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Modern technologies are seen as an essential component of the fourth industrial revolution (industry 4.0) and their adoption is vital to transform the existing manufacturing system into industry 4.0-based manufacturing system. Therefore, the primary objective of this research explores the barriers of modern technology adoption and their mitigating solutions in order to align with Industry 4.0 objectives.

Barriers to adopting modern technologies and respective mitigating solutions are identified from the available literature. Further, these barriers are ranked with the help of expert opinions by using the BWM method appropriately. The identified solutions are ranked using the combined compromise solution (CoCoSo) method.

Several modern technologies and their capabilities are recognised to support the industry 4.0-based manufacturing systems. This study identifies 22 barriers to the effective adoption of modern technologies in manufacturing and 14 solutions to overcome these barriers. Change management, the high initial cost of technology and appropriate support infrastructure are the most significant barriers. The most prominent solutions to overcome the most considerable barriers are ‘supportive research, development and commercialisation environment’, ‘updated policy and effective implementation’ and ‘capacity building through training’ that are the top three solutions that need to be addressed.

The barriers and solutions of modern technology adoption are obtained through a comprehensive literature review, so there is a chance to ignore some significant barriers and their solutions. Furthermore, ranking barriers and solutions is done with expert opinion, which is not free from biases.

This identification and prioritisation of barriers will help managers to understand the barriers so they can better prepare themselves. Furthermore, the suggested solutions to overcome these barriers are helpful for the managers and could be strategically adopted through optimal resource utilisation.

This study proposes a framework to identify and analyse the significant barriers and solutions to adopting modern technologies in the manufacturing system. It might be helpful for manufacturing organisations that are willing to transform their manufacturing system into industry 4.0.

Environmental sustainability is quickly becoming one of the most critical issues in industry development. This study aims to conduct a systematic literature review through which the author can provide various research areas to work on for future researchers and provide insight into Industry 4.0 and environmental sustainability.

This study accomplishes this by performing a backward analysis using text mining on the Scopus database. Latent semantic analysis (LSA) was used to analyze the corpus of 4,364 articles published between 2013 and 2023. The authors generated ten clusters using keywords in the industrial revolution and environmental sustainability domain, highlighting ten research avenues for further exploration.

In this study, three research questions discuss the role of environmental sustainability with Industry 4.0. The author predicted ten clusters treated as recent trends on which more insight is required from future researchers. The authors provided year-wise analysis, top authors, top countries, top sources and network analysis related to the topic. Finally, the study provided industrialization’s effect on environmental sustainability and the future aspect of automation.

The reliability of the current study may be compromised, notwithstanding the size of the sample used. Poor retrieval of the literature corpus can be attributed to the limitations imposed by the search words, synonyms, string construction and variety of search engines used, as well as to the accurate exclusion of results for which the search string is insufficient.

This research is the first-ever study in which a natural language processing technique is implemented to predict future research areas based on the keywords–document relationship.

The success of SMEs' financial and market performance (MAP) depends on the firms' level of blockchain technology adoption (BCA) and identifying the crucial antecedents that influence SMEs' adoption. Therefore, this research attempts to develop an integrated model to understand and predict the determinants of BCA and its effect on SMEs' performance. The purpose of this paper is to address this issue.

The theoretical foundations are the technology–organization –environment (TOE) framework and the resource-based view (RBV) perspective. The authors distributed a survey to SMEs in South Africa and received 311 responses. The covariance-based structural equation modeling (CB-SEM) followed by the artificial neural network (ANN) technique was used for the data analysis.

The SEM results showed that SMEs' relative advantage, compatibility, top management support (TMS), organizational readiness (ORD), competitive pressures (COP), external support, regulations and legislation significantly influence SMEs' BCA. However, complexity negatively impacts SMEs' BCA. The analysis results also revealed that SMEs' BCA significantly influences the financial performance of the firms, followed by MAP. Furthermore, model determinants were input to an ANN modeling. The ANN results showed that TMS is the most critical predictor of SMEs' BCA, followed by ORD, COP, external support, and regulations and legislation.

The results provide valuable information for SMEs when maneuvering their adoption strategies in the scope of blockchain technology. Additionally, from the perspective of an emerging market, the study has successfully contributed the TOE framework and the RBV.

This study is the first work to explore the determinants of BCA in the context of SMEs from a developing country. This paper is also one pioneer in attempts to develop a causal and predictive statistical model for predicting the determinants of BCA in SMEs' performance.

Reverse logistics services are designed to move goods from their point of consumption to an endpoint to capture value or properly dispose of products and materials. Artificial intelligence (AI)-based reverse logistics will help Micro, Small, and medium Enterprises (MSMEs) adequately recycle and reuse the materials in the firms. This research aims to measure the adoption of AI-based reverse logistics to improve circular economy (CE) performance.

In this study, we proposed ten hypotheses using the theory of natural resource-based view and technology, organizational and environmental framework. Data are collected from 363 Indian MSMEs as they are the backbone of the Indian economy, and there is a need for digital transformation in MSMEs. A structural equation modeling approach is applied to analyze and test the hypothesis.

Nine of the ten proposed hypotheses were accepted, and one was rejected. The results revealed that the relative advantage (RA), trust (TR), top management support (TMS), environmental regulations, industry dynamism (ID), compatibility, technology readiness and government support (GS) positively relate to AI-based reverse logistics adoption. AI-based reverse logistics indicated a positive relationship with CE performance. For mediation analysis, the results revealed that RA, TR, TMS and technological readiness are complementary mediation. Still, GS, ID, organizational flexibility, environmental uncertainty and technical capability have no mediation.

The study contributed to the CE performance and AI-based reverse logistics literature. The study will help managers understand the importance of AI-based reverse logistics for improving the performance of the CE in MSMEs. This study will help firms reduce their carbon footprint and achieve sustainable development goals.

Few studies focused on CE performance, but none measured the adoption of AI-based reverse logistics to enhance MSMEs’ CE performance.

This study aims to investigate the influence of the interrelationship between the deployment of Industry 4.0 (I4.0) technologies and the application of lean production (LP) practices on the degree of organizational sustainability performance (SP) enhancement of the Bangladeshi ready-made garment (RMG) sector.

Previously, researchers have applied the resource-based view (RBV) or dynamic capability view (DCV) to describe the interaction of resources and capacities (technologies, management practices, SP) to analyze their effectiveness. However, in light of several contemporary academic discussions, this study contends that these organizational views are inappropriate for explicating SP. Hence, as the foundation of this study’s theoretical framework, the authors used the practice-based view (PBV), which is recommended as a useful window to evaluate the function of practices that are common and simple to emulate in execution. To test the theoretical framework and research hypothesis, this study used partial least square (PLS) analysis. For that, the authors carried out a systematic survey to collect data from 80 Bangladeshi RMG factories.

The results of this research imply that LP is a crucial factor in enhancing organizational SP. Moreover, the results also indicate that the adoption of I4.0 technologies along with LP can assist in delivering the lean objectives more efficiently and, therefore, the combined application of LP practices and I4.0 technologies play a significant role in enhancing organizational SP.

Though the present literature indicates the probable significant association between LP and SP or I4.0 technologies and SP, no study, with the best of the authors’ knowledge, has empirically examined the combined impacts of correlation between LP and I4.0 on SP. This is also a unique study to apply the PBV theory to explain the organizational SP through the combination of common resources and technologies.

Considering the high impacts caused by manufacturers on sustainability, this research aims to analyse how Brazilian manufacturing companies deal with sustainability issues. To do this, sustainability parameters are analysed to verify possible improvement opportunities.

This research uses Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) and grey relational analysis (GRA) to analyse data from a survey with Brazilian professionals regarding aspects of sustainability in Brazilian manufacturers. The average score levels and the ranking of these aspects are evaluated.

Through the analysis performed, it was possible to verify that manufacturers in Brazil still have a long path to travel in the search for sustainability. Comparatively, it was observed that practices related to local communities received the lowest scores, on average. In contrast, on average, practices related to productivity and efficiency, occupational accidents and diseases, and compliance with environmental legislation received the highest scores.

The results presented in this paper show that there are several improvement opportunities to be sought by Brazilian manufacturing companies regarding sustainability aspects. Particular attention should be given to local community practices. Besides companies, policymakers can also use this analysis to guide their future actions, encouraging manufacturing companies to better support the local community. Researchers can use the instrument of analysis (TOPSIS and GRA) to analyse other realities and compare them with the findings presented.

The analysis of Brazilian manufacturing companies’ reality regarding sustainability practices and considering a model based on Global Reporting Initiative (GRI) and Brazilian Institute of Corporate Governance (IBGC) is novel in the literature. The use of TOPSIS and GRA, as well as comparing their findings, generated interesting insights for companies, policymakers and researchers. The analysis presented shows the need for more significant concern for local communities and can be used to support further debates and action plans to minimise this gap.

This study aims to identify the interfaces between Industry 4.0 (I4.0) technologies and circular supply chains (CSC) in Brazilian foodtechs, focusing on key stakeholders’ perspectives to understand the efficiency and sustainability impacts of these integrations.

Using a qualitative exploratory research design, the study analyzes eight Brazilian foodtechs through interviews and content analysis. It identifies CSC practices and examines the adherence of I4.0 technologies within these enterprises, assessing stakeholder engagement and the implications for CSC optimization.

Fifteen CSC practices were identified across the foodtechs, with notable integration of three distinct I4.0 technologies. The findings suggest that while I4.0 technologies enhance efficiency in CSC, their adoption is in early stages. Stakeholder engagement emerges as a crucial element for optimizing CSC in the context of Brazilian foodtechs.

This study contributes to the academic discussion on the synergy between I4.0 and circular economy (CE) models, providing empirical evidence of their application in the foodtech sector and highlighting the role of stakeholders in facilitating these integrations.

The findings suggest that stakeholder engagement in circular practices is vital for both supply chain and organizational levels, with potential benefits including improved efficiency and sustainability outcomes. The research also underscores the need for public sector support, including regulatory frameworks and incentives for adopting I4.0 technologies.

By demonstrating how I4.0 technologies can support CE practices in foodtechs, the study highlights the potential for these integrations to contribute to more sustainable and efficient food systems, addressing environmental concerns and promoting social well-being.

This study addresses a gap in the literature by exploring the interface between I4.0 technologies and CSC in the emerging context of Brazilian foodtechs, offering insights into the practical and societal benefits of these integrations.

The shift toward a circular economy (CE) represents a collaborative endeavor necessitating the presence of efficient frameworks, conducive contexts and a common comprehension. This research serves as a pivotal stride towards this goal, presenting an exclusive prospect for the investigation and fusion of these frameworks, with particular emphasis on the Quintuple Helix Model (5HM), into a unified theoretical framework that underscores the core principles of the CE. This study is centered on three pivotal questions aimed at decoding the CE transition in specific regional settings.

Adopting an abductive approach firmly anchored in a two-stage qualitative process, this study specifically merges the foundational principles from institutional theory, entrepreneurship literature and CE frameworks to provide insights into the dynamics of circular ecosystems, with a specific focus on the Huelva region in Spain.

The findings demonstrate significant potential in the CE, ranging from the integration of product and service systems to innovations in eco-industrial practices. Yet, a notable deficiency exists: the absence of institutional entrepreneurs, highlighting the essential role that universities can play. As recognized centers of innovation, universities are suggested to be key contributors to the transformation toward a CE, aligning with their societal and economic responsibilities.

This study highlights the importance of managing relationships with entities like SMEs and policymakers or academia for effective CE adoption. Policymakers can refine strategies based on the research’s insights, while the impact of university-driven circular ecosystems on sustainable societies is another crucial area for research.

The sustainability models cited in CE literature may not be comprehensive enough to prevent problem shifting, and it can be argued that they lack a sound theoretical and conceptual basis. Furthermore, the connections between sustainability objectives and the three levels of the CE operating system remain vague. Additionally, there is insufficient information on how regions foster the involvement of the environment in fivefold helix cooperation and how this impacts the CE.

The imperative to conserve resources and minimize operational expenses has spurred a notable increase in the adoption of lean manufacturing within the context of the circular economy across diverse industries in recent years. However, a notable gap exists in the research landscape, particularly concerning the implementation of lean practices within the pharmaceutical industry to enhance circular economy performance. Addressing this void, this study endeavors to identify and prioritize the pivotal drivers influencing lean manufacturing within the pharmaceutical sector.

The outcome of this rigorous examination highlights that “Continuous Monitoring Process for Sustainable Lean Implementation,” “Management Involvement for Sustainable Implementation” and “Training and Education” emerge as the most consequential drivers. These factors are deemed crucial for augmenting circular economy performance, underscoring the significance of management engagement, training initiatives and a continuous monitoring process in fostering a closed-loop practice within the pharmaceutical industry.

The findings contribute valuable insights for decision-makers aiming to adopt lean practices within a circular economy framework. Specifically, by streamlining the process of developing a robust action plan tailored to the unique needs of the pharmaceutical sector, our study provides actionable guidance for enhancing overall sustainability in the manufacturing processes.

This study represents one of the initial efforts to systematically identify and assess the drivers to LM implementation within the pharmaceutical industry, contributing to the emerging body of knowledge in this area.

The existing literature reflects that the connection between enablers of Industry 4.0 (I4.0), Supply Chain (SC) sustainability and reliability is understudied. To cover this gap, the purpose of this study is to identify and benchmark the enablers of I4.0 for SC sustainability to build a Reliable Supply Chain (RSC).

This study benchmarks the I4.0 enablers for SC sustainability for building a RSC and analyses them with a multi-method approach. The identified potential enablers are validated empirically. A multi-method approach of Analytical Hierarchy Process (AHP), Decision Making Trial and Evaluation Laboratory (DEMATEL) and Preference Ranking for Organization Method for Enrichment Evaluation (PROMETHEE-II) was used to investigate the influence of the identified benchmarking enablers and develop an interrelationship diagram among the identified enablers.

This study benchmarks the potential enablers of I4.0 to achieve high ecological-economic-social gains in SCs considering the Indian scenario. Digitalization of the supply chain, decentralization, smart factory technologies and data security and handling are the most prominent enablers of I4.0 for SC sustainability to build a RSC.

The findings from the study may benefit managers, practitioners, specialists, researchers and policymakers interested in I4.0 sustainability applications.