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Sustainability performances (SPs) are the most crucial performances for an organisation in today's world, and they can be measured by economic, social, and environmental metrics. Previous research has not been clear on the role of total productive maintenance (TPM) in the context of sustainability, which motivates the authors to investigate the relationship between TPM and various SPs of the manufacturing firm. Therefore, current research investigates the relationship between TPM and the overall sustainability of the manufacturing firm from the perspective of resource-based view (RBV) theory.

The current study proposed, tested and validated a conceptual framework using partial least squares structural equation modelling (PLS-SEM). A total of 326 responses were received to validate the conceptual framework in smartsPLS 3.0 software.

The research outcomes indicate that TPM considerably impacts a manufacturing firm's economic, environmental and social performance.

This research demonstrates that outstanding shop floor behaviour, such as TPM, can become an important asset to offer competitive advantages in a manufacturing firm. Similarly, TPM might serve as a roadmap for leveraging overall sustainability for manufacturing companies. The study indicates the establishment of a sustainability-oriented training protocol while practising TPM.

No past investigation indicates that a shop floor activity like TPM could be used as an input to offer sustainability in a single index for a manufacturing firm from the perception of RBV theory.

Total Productive Maintenance (TPM) could act as a practical approach to offer sustainability deliverables in manufacturing firms aligning with the natural resource-based view (NRBV) theory's strategic capabilities: pollution prevention, product stewardship and sustainable development. Also, the emergence of Blockchain Technology (BCT) and Circular Economy (CE) are proven to deliver sustainable outcomes in the past literature. Therefore, the present research examines the relationship between BCT and CE and TPM's direct and mediation effect through the lens of NRBV theory.

The current study proposes a conceptual framework to examine the relationship between BCT, CE and TPM and validates the framework through the Partial Least Squares Structural Equation Modeling. Responses from 316 Indian manufacturing firms were collected to conduct the analysis.

The investigation outcomes indicate that BCT positively influences CE and TPM and that TPM has a significant positive impact on CE under the premises of NRBV theory. The results also suggest that TPM partially mediates the relationship between BCT and CE.

This research fills a gap in the literature by investigating the effect of BCT and TPM on CE within the framework of the NRBV theory. It explores the link between BCT, TPM and CE under the NRBV theory's strategic capabilities and TPM mediation.

The positive influence of TPM and BCT on CE could initiate the amalgamation of BCT-TPM, improving the longevity of production equipment and products and speeding up the implementation of CE practices.

This research fills a gap in the literature by investigating the effect of BCT and TPM on CE within the framework of the NRBV theory. It explores the link between BCT, TPM and CE under the NRBV theory's strategic capabilities along with TPM mediation.

Key success factors (KSFs) of total productive maintenance (TPM) have historically played a vital role in attaining economic and ecological sustainability but have overlooked social sustainability. Hence, this study analyses and ranks the most significant TPM KSFs for attaining social sustainability in manufacturing small and medium enterprises (SMEs).

The research employs a deductive methodology to identify the relevant TPM KSFs and social sustainability indicators and then uses Fuzzy Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) to rank the TPM KSFs in order to achieve social sustainability, followed by a sensitivity analysis to assess the methodological robustness.

The findings indicate that the top five TPM KSFs influencing social sustainability are employee health and safety, organizational culture, top management commitment, employee engagement and effective communication and effective workplace management. In addition, the results indicate that effective equipment utilization is the least significant TPM key factor affecting social sustainability.

SME manufacturing managers do not need to worry about all of the TPM KSFs if they only concentrate on the ones that will have the most impact. If managers use the top 5 TPM KSFs as a starting point, they may create customized TPM training programs for their companies. As a result, this will facilitate the efforts of their personnel toward social sustainability.

In the existing literature, little emphasis has been paid to social sustainability and how SMEs may implement these practices. This research adds to the current theory of TPM and social sustainability and sheds light on how SMEs might use TPM to advance toward more socially sustainable operations.

The paper aims to enhance the understanding of robust food supply chains (FSC) by exploring the capabilities of various digital technologies and examining their interactions.

This study finding shows that digital technology enhances the resilience of the FSC by improving visibility, traceability and adaptability. This resilience provides a competitive advantage, ultimately enhancing the overall business performance.

In developing countries, inadequate infrastructure, poor Internet connectivity and diverse stakeholder systems pose challenges to implementing advanced digital solutions in the FSC.

This paper is among the first to investigate the impact of digital technology on FSC resilience, exploring visibility, flexibility and collaboration.

Equipment performance helps the manufacturing sector achieve operational and financial improvements despite process variations. However, the literature lacks a clear index or metric to quantify the monetary advantages of enhanced equipment performance. Thus, the paper presents two innovative monetary performance measures to estimate the financial advantages of enhancing equipment performance by isolating the effect of manufacturing fluctuations such as product mix price, direct and indirect characteristics, and cost changes.

The research provides two measures, ISB (Improvement Saving Benefits) and IEB (Improvement Earning Benefits), to assess equipment performance improvements. The effectiveness of the metrics is validated through a three stages approach, namely (1) experts' binary opinion, (2) sample, and (3) actual cases. The relevant data may be collected through accounting systems, purpose-built software, or electronic spreadsheets.

The findings suggest that both measures provide an effective cost–benefit analysis of equipment performance enhancement. The measure ISB indicates savings from performance increases when equipment capacity is greater than product demand. IEB is utilised when equipment capacity is less than product demand. Both measurements may replace the unitary cost variation, which is subject to manufacturing changes.

Manufacturing businesses may utilise the ISB and IEB metrics to conduct a systematic analysis of equipment performance and to appreciate the financial savings perspective in order to emphasise profitability in the short and long term.

The study introduces two novel financial equipment performance improvement indicators that distinguish the effects of manufacturing variations. Manufacturing variations cause cost advantages from operational improvements to be misrepresented. There is currently no approach for manufacturing organisations to calculate the financial advantages of enhancing equipment performance while isolating production irregularities.

The purpose of this research is to establish a conceptual model to understand the impact of Total Productive Maintenance (TPM) and Industry 4.0 (I4.0) on the transition of a Circular Economy (CE). Also, the paper explores the combined impact of TPM, I4.0 and CE on the sustainability performance (SP) of manufacturing firms.

The conceptual model is proposed using the dynamic capability view (DCV) and empirically validated by partial least squares-structural equation modelling (PLS-SEM) using 304 responses from Indian manufacturing firms.

The results suggest that I4.0 positively impacts TPM, CE and SP, also showing TPM's positive impact on CE and SP. In addition, CE has a positive influence on the SP of manufacturing firms. Furthermore, CE partially mediates the relationship between I4.0 and SP with TPM and SP. The study also identifies TPM, I4.0 and CE as a new bundle of dynamic capabilities to deliver SP in manufacturing firms.

The present research adds to the knowledge and literature on DCV by identifying the importance of CE in the settings of I4.0 and TPM, especially in the context of sustainability. Also, the current study offers a new set of dynamic capabilities and provides some significant future recommendations for researchers and practitioners.

Industries have been the most significant contributor to carbon emissions since the beginning of the Industrial Revolution. The transition to Industry 5.0 (I5.0) marks a pivotal moment in the industrial revolution, which aims to reconcile productivity with environmental responsibility. As concerns about the decline of environmental quality increase and the demand for sustainable industrial methods intensifies, experts recognize the shift toward the I5.0 transition as a crucial turning point.

This review study explores the convergence of green technological advancements with the evolving landscape of I5.0, thereby presenting a roadmap toward carbon neutrality. Through an extensive analysis of literature spanning from 2012 to 2024, sourced from the Scopus database, the research study unravels the transformative potential of green technological innovations, artificial intelligence, green supply chain management and the metaverse.

The findings underscore the urgent imperative of integrating green technologies into the fabric of I5.0, highlighting the opportunities and challenges inherent in this endeavor. Furthermore, the study provides insights tailored for policymakers, regulators, researchers and environmental stakeholders, fostering informed decision-making toward a carbon-neutral future.

This review serves as a call to action, urging collective efforts to harness innovation for the betterment of industry and the environment.

Smart manufacturing (SM) capitalizes on big data analytics (BDA) advancements by enhancing current capabilities such as defect identification and enabling supporting capabilities such as preventive maintenance (PM). The previous literature fails to investigate the comprehensive associations between SM, BDA and PM. Therefore, this study aims to investigate the relationship among SM, BDA and PM.

The present research implements a multi-analytical PLS-SEM-ANN approach to investigate the relationships among BDA, PM and SM.

This investigation indicates that BDA is an effective digital technology that positively affects the operations of SM and PM. Furthermore, the results suggest that PM has a positive influence on SM and that it also positively mediates the relationship between BDA and SM, where PM cannot be treated as an auxiliary practice and plays an important role in SM as a primary operation. Furthermore, implementing the BDA enhances the performance of SM and PM.

The role of PM in the context of BDA and SM has been ignored in past research, and this study offers novelty by examining this relationship.

This paper examines the dynamic interplay between Circular Economy (CE) and Supply Chain (SC). Further, this paper develops a framework indicating the transition from conventional SC to SC 4.0. As it addresses the separate bodies of literature on CE and SC 4.0, the study attempts to bridge the gap by examining barriers to SC 4.0 adoption in CE.

The article integrates bibliometric analysis with Total Interpretive Structural Modeling (TISM) and MICMAC analysis, thereby enriching the methodological rigour in investigating the barriers to SC 4.0 adoption within the CE context.

The paper provides insights into research trends, influential scholars, journals and prominent institutions through bibliometric analysis. Also, the findings identify four broad areas of driving, autonomous, linkage and dependent barriers to facilitate a comprehensive understanding of their impact and interdependencies.

The findings imply that effective policy interventions, enhanced management practices, and the adoption of technological innovations are essential for overcoming barriers to SC 4.0. The research recommends that stakeholders focus on fostering collaborative networks, building competencies in line with CE requirements, and leveraging big data for strategic supply chain decision-making.

This work contributes to the advancement of the circular digital supply field by consolidating research streams, uncovering innovation prospects, and shaping a well-informed research agenda. The distinct contribution lies in its categorization of these barriers into driving, autonomous, linkage, and dependent barriers, offering a novel perspective on the structural dynamics impeding the integration of SC 4.0 in CE.

Using the lens of the natural resource-based view (NRBV) theory, this study investigates the effect of green supply chain management (GSCM) practices such as green manufacturing (GM), eco-design (ED), green purchasing (GP) and investment recovery (IR) on the carbon-neutral supply chain (CNSC) performance of firms through the mediating influence of logistics eco-centricity (LE).

A conceptual framework that hypothesizes the relationship between GSCM practices, LE and the CNSC performance of firms is developed. Key GSCM practices are then identified using experts’ opinions. Furthermore, we collected responses from logistics companies to validate the conceptual framework using the partial least squares structural equation modeling (PLS-SEM) method.

Through this study, we found that GSCM practices significantly improve a firm's CNSC performance, and the relationships between GSCM practices and CNSC performance are positively mediated by LE.

The implications of the study suggest that logistics managers can benefit from the findings of this study to comprehend the impact of various GSCM techniques on LE and CNSC from the viewpoint of the NRBV paradigm.

This research provides valuable perspectives for managers and supply chain (SC) practitioners in their quest for sustainable and environmentally responsible SC operations through an extensive and novel analysis of the connection between GSCM practices, LE and CNSC performance.