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Research on caregiving has been considering the positive effects experienced by the mothers of children with disabilities. This paper aims to examine whether positive perceptions mediate the relationships between coping strategies used and psychological well-being among mothers of children with intellectual disabilities.

The study opted for a quantitative approach that includes a correlation research design to examine the relationships between the variables of coping, positive perceptions and well-being among mothers of children with intellectual disabilities attending special schools in the metropolitan city Bengaluru, India. The four-factor structure of Brief COPE examined were active avoidance coping, problem-focussed coping, positive coping and religious-denial coping. “Positive perceptions” refer to the positive contributions for the mother from the experiences of raising a child with intellectual disability. Mediation analysis explored the relationship between the variables.

Problem-focussed coping was the most commonly reported coping factor and was associated with higher levels of well-being. Active-avoidance coping was the least commonly reported coping strategy. Positive perceptions partially mediated the relationship between the four coping factors and maternal well-being. These findings indicate that positive maternal perceptions have important implications for the employment of effective coping strategies that are associated with enhancement of psychological well-being.

The focus on positive perceptions would help in understanding the use of coping strategies and planning of support services or interventions. The positive mental health of mothers paves the way for positive developments in the child’s physical and psychological health.

Transformation to Industry 4.0 has become crucial for nations, and a coherent transformation strategy requires a comprehensive picture of current status and future vision. This study presents a comprehensive model for readiness assessment of nations based on rigorous analysis of several global indices and academic Industry 4.0 literature.

A holistic approach is taken considering overall socioeconomic development along with industrial innovation and seven readiness dimensions: enabling environment, human resource, infrastructure, ecological sustainability, innovation capability, cybersecurity and consumers. The indicators used for evaluation are standard metrics for which data are collected from reputed sources such as World Bank, United Nations Educational Scientific and Cultural Organization (UNESCO), World Economic Forum (WEF) and International Organization for Standardization (ISO), and hence internationally acceptable.

The formulated model is used to evaluate Industry 4.0 readiness of 126 economies that account for 98.25% of world’s gross national income. Observations show poor scores of most economies on innovation capability and cybersecurity dimension as compared to other 5 dimensions. In 75% countries, I4.0 readiness score is below 0.5 on a scale of 0–1(completely ready), highest being 0.65 for Denmark.

A systematic literature review revealed lack of assessment models discussing a nation's current status or readiness for Industry 4.0. This academic study is first of its kind.

The purpose of this paper is to investigate the suitability of Blockchain technology for applications in the Industrial Internet of Things (IIOT). It provides a taxonomy of system requirements for such applications and maps these requirements against the Blockchain’s technological idiosyncrasies.

A requirement taxonomy is built in an iterative process based on a descriptive literature review. In total, 223 studies have been screened leading to a relevant sample of 48 publications that were analyzed in detail regarding posed system requirements. Subsequently, Blockchain’s capabilities are discussed for each requirement dimension.

The paper presents a taxonomy of six requirement dimensions. In the mapping process, areas of greater fit (e.g., reliability, nonrepudiation and adaptability) were identified. However, there are also several constraints (e.g., scalability, confidentiality and performance) that limit the use of Blockchain.

Due to the limited amount of studies and the vibrant development of Blockchain technology, the results may benefit from practical evidence. Researchers are encouraged to validate the results in qualitative practitioner interviews. Focusing on literature-backed public Blockchain, idiosyncrasies of private implementations and specific distributed ledger technologies may be discussed in future studies.

The paper includes use cases for Blockchain in manufacturing and IIOT applications. Potential caveats for practitioners are presented.

This paper addresses the need to understand to which degree Blockchain is a suitable technology in manufacturing, especially in context of the IIOT. It contributes a requirement taxonomy which serves as the foundation for a systematic fit assessment.

The purpose of this paper is to determine the factors that affect Industry 4.0 applications, the expected impacts of Industry 4.0 applications in companies and to analyze the importance of these factors and the importance of expected impacts correlatively.

This paper provides an empirical analysis of the factors affecting the adoption of Industry 4.0 transformation and its impacts on the companies. The paper is based on 103 valid answers to a questionnaire-survey distributed among companies in Turkey. The Pearson correlation analysis was conducted to determine the correlation between independent variables and dependent variables. Regression analyses were used to test the proposed hypotheses. A multiple regression analysis was used to investigate the causal relationship between independent and dependent variables. Linear regression method and stepwise regression method was employed for regression analyses. The factors that influence Industry 4.0 applications were determined as company size, technological level of products, budget allocation for R&D department, level of lean applications, level of agility/flexibility and level of automation; and the expected impacts of Industry 4.0 applications were determined as traceability of production processes, traceability of supply chain, flexibility of supply chains, communication between the partners of supply chain, productivity, real-time data analysis, integration between companies and integration in the company according to the literature review

The results of this research study revealed that, there is a stronger relationship between level of Industry 4.0 transformation and level of automation than there is between Industry 4.0 transformation and the other independent variables. From the analyses conducted, it can be stated that budget allocation for R&D and level of lean applications and level of automation had greater impacts on Industry 4.0 transformation than company size has. The independent variables included in the regression analysis had a positive effect on Industry 4.0 transformation of companies. However the effects of company size, technological level of products and level of agility/flexibility on Industry 4.0 transformation was weak. When the impacts of Industry 4.0 on companies were analyzed, it can be stated that there is a stronger relationship between Industry 4.0 transformation and real-time data analysis, traceability of production processes, integration in companies and productivity than there is between Industry 4.0 transformation and integration between companies, traceability of supply chains, flexibility of supply chains and communication between the partners of supply chain. It was determined that Industry 4.0 transformation generally impacts internal factors of company, while Industry 4.0 had limited impacts on the supply chains.

Although there are studies that separately investigated the factors affecting Industry 4.0 transformation and the impacts of Industry 4.0 transformation on companies, the present study provides important contributions to the literature in terms of considering the importance levels of the factors affecting Industry 4.0 transformation and the importance level of impacts of Industry 4.0 transformation on companies as a whole and in relation to each other.

Data-driven quality management systems, brought about by the implementation of digitisation and digital technologies, is an integral part of improving supply chain management performance. The purpose of this study is to determine a methodology to aid the implementation of digital technologies and digitisation of the supply chain to enable data-driven quality management and the reduction of waste from manufacturing processes.

Methodologies from both the quality management and data science disciplines were implemented together to test their effectiveness in digitalising a manufacturing process to improve supply chain management performance. The hybrid digitisation approach to process improvement (HyDAPI) methodology was developed using findings from the industrial use case.

Upon assessment of the existing methodologies, Six Sigma and CRISP-DM were found to be the most suitable process improvement and data mining methodologies, respectively. The case study revealed gaps in the implementation of both the Six Sigma and CRISP-DM methodologies in relation to digitisation of the manufacturing process.

Valuable practical learnings borne out of the implementation of these methodologies were used to develop the HyDAPI methodology. This methodology offers a pragmatic step by step approach for industrial practitioners to digitally transform their traditional manufacturing processes to enable data-driven quality management and improved supply chain management performance.

This study proposes the HyDAPI methodology that utilises key elements of the Six Sigma DMAIC and the CRISP-DM methodologies along with additions proposed by the author, to aid with the digitisation of manufacturing processes leading to data-driven quality management of operations within the supply chain.

Considering the importance and the broad applications of the Fourth Industrial Revolution in various organizations and industries and enjoying the many benefits of this digital transformation framework, organizations need to measure their Industry 4.0 readiness as a starting point and take steps to achieve the strategic goals of Industry 4.0. This study aims to design a comprehensive and practical model that can determine Industry 4.0 readiness level, allowing organizations to implement and exploit technological constituents of this phenomenon.

A systematic literature review (SLR) methodology was used to evaluate and summarize a clear and comprehensive literature overview of Industry 4.0 readiness models and to certify the validity and transparency of the review process. After reviewing 71 articles and survey and then the consensus of Industry 4.0 experts, the 10 dimensions of the 4.0 Industry readiness model were finalized with their indicators having the most frequency in the published articles and models.

The application of the SLR to the development of the new Industry 4.0 readiness model which includes 10 dimensions and 37 indicators and can assess the Industry 4.0 readiness of firms and industries accurately and effectively.

An extensive review of the previous literature yielded the current Industry 4.0 readiness model. The comprehensiveness of this model leads to its wide application in different companies. Future research suggestions are presented at the end of the manuscript.

The concept of the Fourth Industrial Revolution and the application of its technologies are vague and complicated for many organizations and managers, while the need to implement the components and technologies of Industry 4.0 is essential to achieve organizational goals. The presented readiness model helps companies to measure their readiness to enter the Fourth Industrial Revolution and achieve long-term goals.

In this study, an attempt was made to examine the Industry 4.0 readiness models thoroughly and extensively and identify their different approaches. Finally, a comprehensive and multi-dimensional readiness model is presented to assess the position of organizations in order to enter Industry 4.0.