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Purpose: Manufacturing has always been considered a backbone for economic growth. It has been considered an imperative sector in the growth of an economy. This study aims to trace the long-term relationship between gross domestic product (GDP) and manufacturing sector in the context of Indian economy.

Need for the study: According to research, the significance of the manufacturing sector is waning over time. This chapter studies the long-term relationship between the GDP, an indicator of growth, and the manufacturing sector. Over the last few decades, the contribution of manufacturing has been stagnant in the GDP of India.

Methodology: The decadal growth of various sectors in the GDP of India is studied using time series analysis. This study used the data released by the Ministry of Statistics and Programme Implementation (MOSPI) from 1950–1951 to 2013–2014. The long-term relationship between the sector of manufacturing and the GDP is examined through the augmented Dicky–Fuller (ADF) test and auto-regressive distributed lag (ARDL) models.

Findings: The findings suggest that in the Indian scenario, there is no relationship for an extended period between the GDP and the manufacturing sector, which calls for further policy implications.

Practical implications: India, while having the world’s fastest-growing economy, must continue to take steps to attain high growth rates and long-term sustainability by reducing obstacles to the expansion of the service sector in addition to manufacturing. Manufacturing-led services are to be boosted through policy interventions.

The research explores the shift to Quality 4.0, examining the move towards a data-focussed transformation within organizational frameworks. This transition is characterized by incorporating Industry 4.0 technological innovations into existing quality management frameworks, signifying a significant evolution in quality control systems. Despite the evident advantages, the practical deployment in the Indian manufacturing sector encounters various obstacles. This research is dedicated to a thorough examination of these impediments. It is structured around a set of pivotal research questions: First, it seeks to identify the key barriers that impede the adoption of Quality 4.0. Second, it aims to elucidate these barriers' interrelations and mutual dependencies. Thirdly, the research prioritizes these barriers in terms of their significance to the adoption process. Finally, it contemplates the ramifications of these priorities for the strategic advancement of manufacturing practices and the development of informed policies. By answering these questions, the research provides a detailed understanding of the challenges faced. It offers actionable insights for practitioners and policymakers implementing Quality 4.0 in the Indian manufacturing sector.

Employing Interpretive Structural Modelling and Matrix Impact of Cross Multiplication Applied to Classification, the authors probe the interdependencies amongst fourteen identified barriers inhibiting Quality 4.0 adoption. These barriers were categorized according to their driving power and dependence, providing a richer understanding of the dynamic obstacles within the Technology–Organization–Environment (TOE) framework.

The study results highlight the lack of Quality 4.0 standards and Big Data Analytics (BDA) tools as fundamental obstacles to integrating Quality 4.0 within the Indian manufacturing sector. Additionally, the study results contravene dominant academic narratives, suggesting that the cumulative impact of organizational barriers is marginal, contrary to theoretical postulations emphasizing their central significance in Quality 4.0 assimilation.

This research provides concrete strategies, such as developing a collaborative platform for sharing best practices in Quality 4.0 standards, which fosters a synergistic relationship between organizations and policymakers, for instance, by creating a joint task force, comprised of industry leaders and regulatory bodies, dedicated to formulating and disseminating comprehensive guidelines for Quality 4.0 adoption. This initiative could lead to establishing industry-wide standards, benefiting from the pooled expertise of diverse stakeholders. Additionally, the study underscores the necessity for robust, standardized Big Data Analytics tools specifically designed to meet the Quality 4.0 criteria, which can be developed through public-private partnerships. These tools would facilitate the seamless integration of Quality 4.0 processes, demonstrating a direct route for overcoming the barriers of inadequate standards.

This research delineates specific obstacles to Quality 4.0 adoption by applying the TOE framework, detailing how these barriers interact with and influence each other, particularly highlighting the previously overlooked environmental factors. The analysis reveals a critical interdependence between “lack of standards for Quality 4.0” and “lack of standardized BDA tools and solutions,” providing nuanced insights into their conjoined effect on stalling progress in this field. Moreover, the study contributes to the theoretical body of knowledge by mapping out these novel impediments, offering a more comprehensive understanding of the challenges faced in adopting Quality 4.0.

Industry 5.0 (I5.0) is eventually set to supersede Industry 4.0 (I4.0), despite the fact that I4.0 continues to gain ground in emerging nations like India. Now India is aspiring to be a global manufacturing hub, and I5.0 offers enormous potential to position India as a forerunner in intelligent and collaborative manufacturing systems. Therefore, this research article aims to understand the relationship between I5.0 and sustainable manufacturing (SM) thoroughly; pinpoint its impact and implementation challenges; analyze its impact on Triple-Bottom-Line (TBL) sustainability; and present an inclusive framework for I5.0 implementation for Indian manufacturing enterprises.

The coexistence of two industrial revolutions raises questions, which necessitates debates and explanations. Thus, the systematic literature review (SLR) approach is used to address this issue and this study used Web of Science, Scopus, Science Direct and Google Scholar databases. Following a critical SLR, 82 research papers have been cited in this article, and the majority of cited articles were published from 2010 to 2022, to ensure a focused analysis of pertinent and recent scholarly contributions.

I4.0 is considered to be technology-driven, however, I5.0 is perceived to be value-driven. I5.0 is not a replacement or a chronological continuation of the I4.0 paradigm. The notion of I5.0 offers a distinct perspective and emphasizes the necessity of research on SM within the TBL sustainability boundaries. I5.0 introduces a new TBL: resilience in value creation, human well-being and sustainable society. Indeed, I5.0 seems to be economically, socially, and environmentally sustainable while manufacturing products with high productivity.

Theoretical implications pertain to restructuring business models and workforce transformation, whereas practical implications underscore the significance for manufacturing enterprises to embrace I5.0 for their sustainable development. By understanding the nuanced relationship between I5.0 and SM, enterprises can navigate implementation challenges, maximize TBL sustainability and embrace an inclusive I5.0 framework for high productivity and resilience.

The existing literature presents the general notion of I5.0 but lacks in-depth TBL sustainability analysis. This research used a systematic and rigorous SLR approach that evaluates the existing literature, enables an in-depth understanding, identifies research gaps and provides evidence-based recommendations for the decision-making process. Furthermore, this research aims to stand on an unbiased assessment, exploring theoretical and practical implications of I5.0 implementation for manufacturing enterprises and suggesting future research avenues.

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 use of technology in 4th industrial revolution is at its peak. Industries are trying to reduce the consumption of resources by effectively utilizing information and technology to connect different functioning agents of the manufacturing industry. Without digitization “Industry 4.0” will be a virtual reality. The present survey-based study explores the factual status of digital manufacturing in the Northern India.

After an extensive literature review, a questionnaire was designed to gather different viewpoints of Indian industrial practitioners. The first half contains questions related to north Indian demographic factors which may affect digitalization of India. The latter half includes the queries concerned with various operational factors (or drivers) driving the digital revolution without ignoring Indian constraints.

The focus of this survey was to understand the current level of digital revolution under the ongoing push by the Indian government focused upon digital movement. The analysis included non-parametric testing of the various demographic and functional factors impacting the digital echoes, specifically in Northern India. Findings such as technological upgradations were independent of type of industry, the turnover or the location. About 10 key operational factors were thoughtfully grouped into three major categories—internal Research and Development (R&D), the capability of the supply chain and the capacity to adapt to the market. These factors were then examined to understand how they contribute to digital manufacturing, utilizing an appropriate ordinal logistic regression. The resulting predictive analysis provides seldom-seen insights and valuable suggestions for the most effective deployment of digitalization in Indian industries.

The country-specific Industry 4.0 literature is quite limited. The survey mainly focuses on the National Capital Region. The number of demographic and functional factors can further be incorporated. Moreover, an addition of factors related to ecology, environment and society can make the study more insightful.

The present work provides valuable insights about the current status of digitization and expects to facilitate public or private policymakers to implement digital technologies in India with less efforts and the least resistance. It empowers India towards Industry 4.0 based tools and techniques and creates new socio-economic dimensions for the sustainable development.

The quantitative nature of the study and its statistical predictions (data-based) are novel. The clubbing of similar success factors to avoid inter-collinearity and complexity is seldom seen. The predictive analytics provided in this study is quite elusive as it provides directions with logic. It will help the Indian Government and industrial strategists to plan and perform their interventions accordingly.

At the beginning of the 21st century, a new class of information workers, the “information have-less” has risen. This class of workers alleviates the influence of information and communication technologies (ICTs) revolution on poverty and unemployment. The purpose of this study is to investigate the presence of this class of workers in Egypt and assess the size and potential growth of this category of workers.

The study clarifies the conceptual framework of the new division of labor, in the information age. The Central Agency for Public Mobilization and Statistics, American Chamber of Commerce in Egypt, Ministry of Communications and Information Technology and Information and Decision Support Center websites provided secondary data for this study. These data are used to assess the size of “the information have less” in Egypt.

The division of work and class, in the 21st century, depends on the level of skills possessed to work with ICTs. So, class and labor nowadays could be divided into self-programmable labor (Innovators). Information have-less labor class, adding value to the economy by learning skills and presenting repetitive work. Generic labor class, who cannot work with ICTs, and work in jobs, that do not need computers or other ICTs. The study has shown that the “information have-less” labor class is present in Egypt since the beginning of the 21st century, in all its categories; entrepreneurism, the service sector and the manufacturing sector. There are approximately 50% of this labor class in the service sector and only 13% of the information have-less works in manufacturing sector despite the great opportunities that Egypt has to expand manufacturing to absorb more employment. The inclusion of information technology (IT), in all domains, has not decreased employment in Western countries but has reallocated information have-less employment toward the service sector, and there would probably be the same effect in Egypt.

The study highlights the need for Egyptian policymakers to encourage the manufacturing and service sectors to provide huge working opportunities. The Egyptian government has to change the educational policies, at all stages, to include digital learning skills so IT can be incorporated in a wide range of economic activities. Further research includes: conducting a survey to measure the contribution of the entrepreneurial part of the information have-less employment in Egypt. In addition, a model may be developed, by the researcher to examine the reallocation of employees in Egypt.

Studying employment, in Egypt, using the conceptual framework of the information age is rarely being done.

This study aims to investigate the implementation of lean human resource management (HRM) practices in manufacturing small- and medium-sized enterprises (SMEs) and explore how various factors interact to influence their successful adoption. By exploring the interplay among these factors, the research seeks to identify key drivers affecting the adoption of lean HRM in manufacturing SMEs. Ultimately, the research intends to provide insights that can guide organisations, practitioners and policymakers in effectively implementing lean HRM practices to enhance operational efficiency, workforce engagement and competitiveness within the manufacturing SME sector.

The study combined total interpretive structural modelling (TISM) and Matrice d'Impacts Croisés Multiplication Appliquée à un Classement (MICMAC) analysis. TISM helped in understanding the hierarchical relationship among different factors influencing lean HRM implementation, whereas MICMAC analysis provided insights into the level of influence and dependence of each factor on others.

The research revealed that “top management support” emerged as the most independent factor, indicating that strong support from top management is crucial for initiating and sustaining lean HRM practices in manufacturing SMEs. On the other hand, “employee involvement and empowerment” was identified as the most dependent factor, suggesting that fostering a culture of employee engagement and empowerment greatly relies on the successful implementation of lean HRM practices.

While the study provided valuable insights, it has certain limitations. The research was conducted within the specific context of manufacturing SMEs, which might limit the generalizability of the findings to other industries. Expert opinions introduce subjectivity in data collection. Additionally, the study may not cover all critical factors, allowing room for further exploration in future research.

The findings have practical implications for manufacturing SMEs aiming to implement lean HRM practices. Recognising the pivotal role of top management support, organisations should invest in cultivating a strong leadership commitment to lean HRM initiatives. Furthermore, enhancing employee involvement and empowerment can lead to better adoption of lean HRM practices, resulting in improved operational efficiency and overall competitiveness.

This research contributes to the field by offering a comprehensive exploration of the interplay among factors influencing lean HRM implementation. The use of TISM and MICMAC analysis provides a unique perspective on the relationship dynamics between these factors, allowing for a nuanced understanding of their roles in the adoption of lean HRM practices in manufacturing SMEs. The identification of “top management support” as the most independent and “employee involvement and empowerment” as the most dependent factors adds original insights to the existing literature.

The purpose of this study is to examine the relationship between the productive structure and the size of the informal economy in Latin American countries.

The study employs econometric techniques for panel data covering the period from 2002 to 2017 and considering 17 Latin American countries. The evidence presented is based on the informal economy data generated by Medina and Schneider (2018) who estimate the size of the informal economy using a structural equation model and the share of manufacturing in total employment as a measure of the size of the manufacturing sector. Also, the study addresses the possible endogeneity bias in the relationship studied and makes the conclusions more robust, thus avoiding spurious correlations that weaken the findings.

The results indicate that most industrialized Latin American countries are associated with a smaller size of the informal economy.

The findings have important policy implications, as they suggest that Latin American economies need to switch the structure of the economy toward more sophisticated productive structures if they want to reduce the size of the informal economy. Thus, more efforts should be deployed to policies to diversify and upgrade economies.

The study contributes to the literature on the informal economy by connecting the country’s productive structure and informality. Specifically, the results show that the productive structure of countries is a plausible explanation for the size of the informal economy.

This study aims to prevent occupational accidents occurring in the manufacturing industry by means of touch sensors. When the occupational accidents occurring in the manufacturing industry around the world are examined, it is seen that approximately 88% of occupational accidents occur from “dangerous movement” and 10% from “dangerous situation.” Although some studies related to safety culture studies, safety studies in design and collective or personal protective measures have been started, they have not been brought to an adequate level. It is observed that studies on dangerous movements continue even in many developed countries. In this study, first of all, a literature study was conducted. Occupational accidents experienced in the manufacturing sector in Turkey have been examined. In line with these investigations, a prototype circuit protection system has been developed that can prevent accidents caused by dangerous movement. With the circuit, its applicability and effectiveness were measured by conducting experiments on different manufacturing machines. The prototype circuit applied in this paper was made based on the logic of protective measures made on sawstop machines used in different sectors. In the experimental study conducted, it was observed that in 30 experiments conducted with a prototype on ten separate manufacturing machines, it stopped the machines 26 times at minimum and 29 times at maximum. On average, when looking at the system efficiency values, it was seen that the system was 81.6% effective, and it was observed that positive results could be obtained when converted into a real product.

In this study, their contribution to the prevention of work accidents caused by presses and rotary accents from machines used in the manufacturing industry by means of touch sensors used in Industry 4.0 was examined.

With Industry 4.0, different automation systems began to be switched in many areas and sectors. Studies have started on different sensors used also in Industry 4.0 in occupational health and safety studies, but it is seen that they have not been applied at an adequate level. It should be designed in such a way as to prevent errors or stop these errors in the studies performed. Today, sensors are produced at much lower costs than before. In addition, the constantly developing technology provides great convenience for these applications.

This study was applied for press and cylinder machines from manufacturing machines. This study has been tried for machines producing a maximum pressure of 300 tons.

A prototype was designed. Trials were done on some machines by prototype. There could be improve and find different solutions for safety problems in the industry with this perspective.

This study aims to investigate contextual factors affecting the deployment of strategy-driven manufacturing accounting techniques (SMAT), as well as the impact of SMAT usage on organisational competitiveness. Seven major SMAT were investigated, namely, benchmarking, integrated performance measurement, environmental management accounting, strategic costing, strategic pricing, strategic investment and life cycle costing.

By using multi-informant strategy, structured questionnaire was used to gather survey data from 129 senior accounting, finance and production personnel of publicly quoted manufacturing companies in Nigeria. Data was analysed using structural equation modelling and propensity score matching.

Result shows that the usage rate of the SMAT is generally moderate. Market orientation and deliberate strategy formulation are notable determinants of SMAT usage. The inability of competition intensity and perceived environmental uncertainty to notably affect SMAT usage suggests that external environmental pressure to use SMAT is weak.

Although the impact of SMAT usage on organisational competitiveness is positive and statistically significant, it is conceivable that the impact of SMAT could have been more assuming SMAT recorded extensive usage. Thus, the lack of competitiveness of manufacturing companies in Nigeria may not be unconnected to the superficial usage of SMAT.

The study contributes to knowledge in three ways. First, it extends studies on the contingency theory that contextual factors influence the adoption of management accounting innovations. Second, it exposes the contextual factors affecting the adoption of SMAT in a developing country. Third, it provides evidence on the value relevance of management accounting innovation in enhancing organisational competitiveness.