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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.

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.

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.

Quality 4.0 represents the integration of quality management principles with digital technologies to drive continuous improvement and innovation in organizations. The purpose of this paper is to explore the essential organizational variables (OVs) for the successful implementation of Quality 4.0 in the Indian furniture industry.

Through a broad literature review, data from the Indian furniture industry and experts’ judgments a list of nineteen OVs have been recognized and classified into four major categories of digitalization, design, continuous improvement and employee training and up-skilling. The analytic hierarchy process (AHP) has been used to give comparative importance and prioritize the identified nineteen OVs of Quality 4.0 in the context of the Indian furniture industry.

The results of this study reveal that the identified variables are very important for successful Quality 4.0 implementation and have been supported by empirical evidence from the Indian furniture industry. The variable “automation” under the digitalization-related category is a significant variable having a maximum weightage of 26.8% followed by Cloud computing (DI4) having a global weight of 12.8%.

In addition to offering valuable insights and practical recommendations, the study recognizes a few limitations, such as industry-specific and the limited sample size. To diminish these limitations, future research should believe in conducting similar studies in different industries and extend the scope of the study.

Quality 4.0 is a term that refers to the integration of advanced digital technologies and smart data analytics into quality management systems to implement it considering OVs.

Blockchain technology (BT) is creating a new standard for all business operations. It can assist businesses in handling the complexity of circular digital supply chain (DCM) management. Despite this optimistic view, several barriers hinder its implementation. In this regard, this study contributes to Industry 4.0, circular economy (CE), the viability with a critical emphasis on its potential ramifications and influence on the future agenda while using BT technology in the supply chain (SC). In addition, the research reduces the knowledge gap by investigating and ranking the key barriers to the deployment of BT in viable circular digital supply chains (VCDSCs) and studies their interdependencies and causal relationships. The purpose of this paper is to address these issues.

The barriers to BT adoption in the VCDSC are identified through a thorough literature review and considering viability performance. These barriers are then classified using the analytical hierarchy process (AHP) method. Decision-making trial and evaluation laboratory (DEMATEL) is then employed to examine the cause/effect, correlation, and connection among the 14 barriers selected barriers from the AHP classification to estimate each barrier's overall degree of impact over the others.

This paper identifies and analyzes the BT adoption barriers in the VCDSC as well as examines how the key barriers interact. As a result, according to the AHP/DEMATEL method, the most prominent influencing barriers to the BT implementation in the VCDSC are “Data transparency,” “Market competition,” “Missing infrastructure,” “Lack of standardization,” “Complex protocol,” “Lack of industry involvement,” “Financial constraints,” “Missing infrastructure,” “Data transparency” and “Interoperability.” The outcomes offer a potential path for identifying important barriers as well as insight into the implementation of BT in the SC while integrating different capabilities such as viability, sustainability and CE principles.

Managers and researchers will benefit from this research by gaining an understanding of the challenges that must be prioritized and examined for BT to be implemented successfully in the VCDSC.

The use and implementation of blockchain-enabled VCDSC continue to face challenges despite an increase in relevant practice and research. Despite the benefits of BT, managers struggle to apply such technology in the context of their company. In this respect, this paper uses an integrated AHP–DEMATEL for categorizing the BT barriers as well as the interrelationship between them. In this respect, this paper presents the BT barriers studied are those related to the use of BT in the SC while integrating different paradigms such as viability, digitalization and CE. While many studies look at the barriers to BT adoption; none of them has ever included the viable capability, which means the ability to “react agilely to positive changes, be resilient to absorb negative events and re-cover after disruptions and survive at long-term periods.” The study concludes with insightful comments based on the findings and suggestions for eradicating those obstacles and their associated effects.

Theorising from a resource-based view perspective, the intersection of supply chain management and the use of information technology (IT) has been investigated in this study. This paper aims to investigate supply chain performance (SCP) as an essential outcome of the use of IT and explores the effect of supply chain collaboration (SCC) on SCP. In addition, volume uncertainty (VU) has been explored and tested to establish whether various associated uncertainties can be mitigated when the use of IT is involved.

A sample of 121 senior executives from agri-tech firms was collected by travelling and meeting the executives in person in various states of India. Structural equation modelling was used to test the hypothesized relationship of VU to SCP via the use of IT and SCC.

The results show that VU significantly impacts SCC via the use of IT and SCP via SCC. The use of IT positively and significantly impacts SCP via SCC.

Witnessing the potential benefits of the emerging use of IT in the uncertainty reduction as reported in this study, agri-tech firms operating in emerging rural and agricultural economies can enhance SCC to improve SCP.

This study unfolds how risks in agricultural supply chains (ASCs) sourced because the VU can be mitigated through the use of IT and SCC to influence SCP in rural agricultural and developing economies.

VU at agri-tech firms and farmers is a ground reality that has led to an inability to plan and prepare, resulting in wastages and disruptions in ASCs and farmers’ struggles.

This research studies the development of the evolving dynamic system model and explores the important elements or factors and what detailed attributes are the main influences model in achieving the success of a business, industry and management. It also identifies the real and major differences between static and dynamic business management models and the detailed factors that influence them. Later, this research investigates the benefits/advantages and limitations/disadvantages of some research studies. The studies conducted in this research put more emphasis on the capabilities of system dynamics (SD) in modeling and the ability to measure, analyse and capture problems in business, industry, manufacturing etc.

The research presented in this work is a qualitative research based on a literature review. Publicly available research publications and reports have been used to create a research foundation, identify the research gaps and develop new analyses from the comparative studies. As the literature review progressed, the scope of the literature search was further narrowed down to the development of SD models. Often, references to certain selected literature have been examined to find other relevant literature. To do so, a supporting tool (that connects related articles) provided by Google Scholar, Scopus, and particular journals has been used.

The dynamic business and management model is very different from the static business model in complexity, formality, flexibility, capturing, relationships, advantages, innovation model, new goals, updated information, perspective and problem-solving abilities. The initial approach of a static system was applied in the canvas business model, but further developments can be continued with a dynamic system approach.

Based on this study, which shows that businesses are developing more towards digitalisation, wanting the ability to keep up with the era that is moving so fast and the desire to increase profits, an instrument is needed that can help describe the difficulties of the needs and developments of the future world. This instrument, or tool of SD, is also expected to assist in drawing future models and in building a business with complex variables that can be predicted from the beginning.

This study will contribute to the SD study for many business incubator research studies. Many practical in business incubator management to have a benefit how to achieve the business performance management (BPM) in SD review.

The significant differences between static and dynamics to be used for business research and strategic performance management. This comparative study analyses some SD models from many authors worldwide. Their goals behind their strategic business models and encounter for their respective progress.

Industry 4.0 has offered significant potential for manufacturing firms to alter and rethink their business models, production processes, strategies and objectives. Manufacturing organizations have recently undergone substantial transformation due to Industry 4.0 technologies. Hence, to successfully deploy and embed Industry 4.0 technologies in their organizational operations and practices, businesses must assess their adoption readiness. For this purpose, a multi-dimensional analytical indicator methodology has been developed to measure Industry 4.0 maturity and preparedness.

A weighted average method was adopted to assess the Industry 4.0 readiness using a case study from a steel manufacturing organization.

The result revealed that the firm ranks between Industry 2.0 and Industry 3.0, with an overall score of 2.32. This means that the organization is yet to achieve Industry 4.0 mature and ready organization.

The multi-dimensional indicator framework proposed can be used by managers, policymakers, practitioners and researchers to assess the current status of organizations in terms of Industry 4.0 maturity and readiness as well as undertake a practical diagnosis and prognosis of systems and processes for its future adoption.

Although research on Industry 4.0 maturity models has grown exponentially in recent years, this study is the first to develop a multi-dimensional analytical indicator to measure Industry 4.0 maturity and readiness.

This study aims to investigate the impact of I4.0 technologies and their interoperability on supply chains (SCs) performance and how the integration of such technologies and their interoperability can create pathways for SCs resilience post-COVID-19. This is of paramount importance in the context of COVID-19 as the investigation around I4.0 technologies may provide relevant insights on how SCs may better respond to unexpected situations like the current pandemic with the use of digital technologies.

A survey research method was designed based on some constructs extracted from the literature regarding the main disruptive technologies, interoperability, elements of supply chains processes (SCPs) performance such as integration, collaboration, transparency, efficiency, responsiveness and profitability. The data were collected from March to July 2020 from different regions of the world when the peak of the first wave of the pandemic had occurred. The survey resulted in 115 valid responses. The study used a combination of descriptive, correlation and multiple regression methods to analyse the data.

The study indicates that disruptive technologies significantly impact SCPs performance (integration, collaboration, responsiveness and transparency) and their resilience. The findings did not support the notion that these technologies improve the efficiency of SCs, a significant contrast to the existing literature. Our findings also refute the existing understanding that interoperability moderates the impact of disruptive technologies on SCPs performance and enhancing the resilience of SCs. However, the findings show that the integration of I4.0 technologies and their interoperability has a positive impact on SCPs profitability.

The findings strongly advocate that this integration plays an important role in improving SC performance, and a future pathway of SC resiliency post-COVID-19. Considering that the I4.0 trend will impact SCs in the coming years, this study brings a relevant contribution to researchers and practitioners.

This study makes a unique contribution by investigating a novel causal relationship between the main elements (I4.0 technologies, interoperability, processes performance and strategic outcomes) related to the SC in this new context.

The aim of this study reported in this paper was to explore the application of operational excellence methodologies in a global context.

A qualitative interview approach was used to understand the current state, benefits, challenges, success factors, tools and techniques of operational excellence methodology implementation with relevance to logistics companies worldwide. About 16 interviews were undertaken with practitioners working in leading companies and with leading academics in Asia, Europe, Africa, North America, South America and Australia.

The findings show that operational excellence methodologies including Lean, Six Sigma, Lean Six Sigma and Agile can apply in logistics firms to improve operations and productivity and save costs. Top management support and involvement play an important role in the success of operational excellence projects in the logistics service.

The findings will be of interest to top and middle managers and logistics practitioners, with a dual aim of improving logistics performance and saving costs.

The present study has been one of the first global study attempts to explore the implementation of operational excellence methodologies in the logistics sectors.