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This paper proposes strategies for adopting Industry 4.0 in achieving sustainable manufacturing, by overcoming barriers in the Sri Lankan manufacturing sector.

A conceptual model of sustainable manufacturing and Industry 4.0 was proposed based on a comprehensive literature review and validated through experts' inputs. The model was illustrated using three case studies to assess the relationships between sustainable manufacturing and Industry 4.0 in the Sri Lankan manufacturing context. Furthermore, possible strategies were proposed to overcome current barriers identified from case studies.

The case studies showcase that there is a considerable gap in Industry 4.0-enabled sustainable manufacturing in the Sri Lankan manufacturing sector due to several barriers. Thus, experts' knowledge-based strategies to overcome those barriers are proposed.

The conceptual model provides a holistic view of maturity levels of sustainable manufacturing measures directly connected with Industry 4.0 technologies. The study was limited to investigating the application of Industry 4.0 for sustainable manufacturing in leading apparel manufacturing organisations in Sri Lanka.

The conceptual model can be used as a framework to guide practitioners in implementing Industry 4.0-enabled sustainable manufacturing. The proposed strategies in addressing barriers to Industry 4.0 adoption towards sustainable manufacturing can be directly applied to achieving better sustainable manufacturing performance.

This study is an informative guide to encourage the Sri Lankan manufacturing industry to adopt Industry 4.0 technologies in achieving sustainable manufacturing, using the knowledge of relationships between Industry 4.0 and three dimensions of sustainable manufacturing, possible barriers and strategies.

The purpose of the paper is to develop a model of distribution of human and machine labor at intellectual production in Industry 4.0.

The basis of the methodology of the research is regression analysis. The analyzed variables are independent variables that characterize the level of development of human and machine labor in the economy of a country; dependent variables that reflect the effectiveness of the production, marketing and innovative business processes in the economy of country according to “The Global Competitiveness Report” (World Economic Forum); and dependent variables, which show the share of the sphere (agriculture, mining industry, processing industry and service sphere) in the structure of GDP of a country according to the statistics of the World Bank. For determining the change of regression dependencies in dynamics in the interests of reduction of the probability of statistical error, the research is conducted for 2010 and 2018 with application of trend analysis.

Based on the full selection of modern countries that conduct digital modernization, the authors determine statistical dependencies of effectiveness of business processes and development of the spheres of economy on the intensity of application of machine and human labor. This allowed determining significant differences in automatization of business processes: perspectives of application of machine labor are the widest in production and the narrowest in marketing, differentiated logic of organization of intellectual production in different spheres of economy and the specifics of automatization of business processes and spheres of economy in countries of different categories, one of which has to be taken into account during organization of intellectual production in Industry 4.0.

The developed model of optimal distribution of human and machine labor at intellectual production in Industry 4.0 will allow reducing disproportions in effectiveness of different business processes, development of different spheres of economy and growth rate of developed and developing countries. This explains its contribution into provision of well-balanced development of the modern global economic system.

The purpose of this paper is to synthesize higher education (HE) elements as expressed in competitiveness literature and provide a comprehensive list of HE aspects found in the conception of competitiveness. In order to achieve this goal, the most acknowledged conceptions, including definitions and measurements, of competitiveness are overviewed and HE components reflected in them are depicted.

In order to achieve the article goal, the most acknowledged conceptions, including definitions and measurements, of competitiveness are overviewed and HE components reflected in them are depicted.

The reviewed measurements of competitiveness have provided a comprehensive list of HE elements. After reviewing a combination of literature on national competitiveness, it is stated that the following HE elements appear in the conception of national competitiveness – preparation for the HE (as reflected in quantity and quality of secondary education), tertiary education quantity and quality, funding of HE system, quality of scientific research institutions and links of the HE system with the labor and business sectors.

The article has a practical value for HE policy makers since it detects key HE factors that are included in the most acknowledged competitiveness measurements which means that these factors have been identified to be the most influential for the growth of a country's prosperity. It is important for HE reformers to understand the underlying dynamics of the competitiveness process and factors that drive it so that they can contribute in the most effective ways.

The article provides a comprehensive list of HE aspects found in competitiveness definitions and measurements. This can be useful for researchers in comparative HE research field. They are constantly seeking for common grounds of comparison of HE systems. The article provides the list of HE characteristics that can serve as basis of comparison. It is a complicated task to study similarities and differences between HE systems because it is difficult to find a joining point. In the article, this joining point has become national competitiveness. Thus, the article contributes to the quest for adequate theoretical approaches for HE system analysis, putting forward a list tailored to the study of HE systems in the context of national competitiveness.

The purpose of the study is to investigate the impact of technological pillars of Industry 4.0 based on knowledge to adopt the supply chain performance of Thai small and medium-sized enterprises (SMEs) 4.0. In addition, to increase knowledge and understanding of how to apply knowledge in technology 4.0 to improve the efficiency of supply chains and organizations.

An integrated model was developed from applying knowledge in five technological pillars of Industry 4.0 such as Internet of things (IoTs), cloud computing, big data and analytics, additive manufacturing and cyber-security. The bibliometric analysis was used to find the relationship between the technological pillars of Industry 4.0 and the literature review. The survey questionnaires were sent to Thai SME 4.0 (manufacturing aspect). Of these, 240 useable responses were received, resulting in a response rate of 65.84%, after then, the exploratory factor analysis (EFA), confirmatory factor analysis (CFA), structural equation modeling (SEM) and validity were used to evaluate the model through IBM SPSS 21 and AMOS 22.

EFA showed the four groups of the technological pillars of Industry 4.0, such as support human, automation, real-time and security. These groups positively impact supply chain performance (increase delivery reliability, increase resource efficiency, decrease costs in the supply chain and reduce delivery time). Another important finding is that supply chain performance positively impacts organizational performance in profitability, return on investment (ROI) and sale growth.

This study is a model development to support the supply chain performance and increase understanding related to applying knowledge in technology 4.0 that remains unclear for SME 4.0.

The primary objective of this study is to unveil the relationships that interconnect ESG and three pillars disclosures with technological innovation while also investigating the moderating impact of product market competition. The paper seeks to identify the underlying mechanisms that facilitate technological innovation in sustainable management.

Using data from 8,738 Chinese firms from 2011 to 2019, this study employs quantitative analysis to examine the relationship between ESG disclosure and technological innovation and the moderating effect. Moreover, this study explores the heterogeneous impacts while considering factors such as property rights and firm size.

The findings reveal a positive correlation between ESG disclosure and technological innovation. The study also investigates the moderating role of product market competition and finds that increasing competition mitigates the positive effects of ESG disclosure on technological innovation. Additionally, the conclusions reveal that the relationship between ESG and three pillars disclosures and technological innovation, as well as the moderating role of product market competition, exhibits inconsistency across firms with different property rights and sizes.

This study offers a clear understanding of the relationship between ESG disclosures and technological innovation, and how it varies across businesses of different sizes and ownership structures. It also provides fresh perspectives on the influence of product market competition on this relationship, with implications for strategy development in corporations.

Prior to managing a company’s processes in the presence of a combination of paradigms, there is a need to understand their underlying interaction. This paper systematically reviews the existing literature that discusses the interaction between lean production (LP) and the fourth industrial revolution (i.e. Industry 4.0). The study aims to understand how the interaction unfolds and whether it is synergistic.

The research relies on a systematic literature review of peer-reviewed articles from Scopus and Web of Science that discuss the interaction between the two paradigms. The final set of articles pertaining to the topic was analysed.

The article presents that the interaction between the two paradigms occurs through a representation of the pillars of the House of Lean (HoL) interacting with the nine technological pillars of Industry 4.0. There is a consensus on the synergistic nexus among the pillars and their positive impact on operational performance. We also demonstrate the weights of the interactions between the two paradigms and the areas of operations management where this interaction takes place through Sankey charts. Our research indicates that the largest synergistic interaction occurs between just-in-time and industrial Internet of Things (IIoT) and that companies should invest in IoT and cyber-physical systems as they have the greatest weight of interactions with the pillars of the HoL.

This research facilitates a deeper insight into the interaction between LP and Industry 4.0 by organising and discussing existing research on the subject matter. It serves as a starting point for future researchers to formulate hypotheses about the interaction among the various pillars of LP and Industry 4.0, apply these interactions and test them through empirical research.

It could serve as a guide for managers to understand with which interactions they should start the digitalisation process.

With the rise in discussions on the interaction between the two paradigms, there is still an opportunity to understand the specificity of this interaction. Compared to the initial seminal works on the subject, such as Buer et al. (2018b), which investigated the direction of interaction between the two paradigms, this research contributes to further investigating this specificity and gaining a better understanding of the relationship governing the interaction between LP and Industry 4.0 by delineating the interaction state among the pillars of the two paradigms and its relevant importance.

This chapter models industrial, tech, and financial cooperation between Russia and the countries of the Asia-Pacific region. We use several complex methods of economic and mathematical modeling to analyze specific features of such cooperation and determine critical factors in industrial, technological, and financial development. The preferable choice for the Asia-Pacific region is cooperation with Russia, which is ready for an increase in imports of industrial and high-tech products as well as joint industrial innovational entrepreneurship. Investments would lead to synergetic effects, ensuring simultaneous industrial, technological, and financial development.

This paper focuses on the issue of global competitive advantage of nations, based on the dimensions analyzed by the World Economic Forum in assessing the economic competitiveness of a large sample of countries. From the different stages of development of the countries, this study aims to help us to recognize what variables better explain the global competitive advantage of economies.

Following quantitative analysis, results based on PLS show what dimensions within each economic development stage best explain the global competitive advantage of economies.

Beyond the institutions, infrastructure and regulation of the markets, higher education and training, the technological readiness, the business sophistication and innovation contribute greatly to explain the competitive advantage of economies.

Understanding the drivers of global competitive advantage of nations, this study may help academics to conduct new studies, as well as politicians to define intervention priorities.

This paper represents a comparative study of five Asian countries, namely, Singapore, Taiwan, South Korea, China and India, based on the Global Competitiveness Index (GCI) 2015-2016 published by the World Economic Forum. The purpose of this study is to assess India’s position vis-a-vis the various comparator Asian economies and to identify areas for improvement so as to enhance India’s competitiveness.

The study is based on the comparisons and analysis of the ranks of each country. These ranks are based on the indicators related to three categories, i.e. “Basic Requirements”, “Efficiency Enhancers” and “Innovation and Sophistication” Factors. The GCI included data from internationally recognised agencies such as the IMF, the WHO and the United Nations Educational, Scientific and Cultural Organization.

On the basis of the aforementioned comparisons among these five Asian economies, it was found that Singapore (Rank-2) has made stupendous economic progress and is amongst the top five successful economies of the world. Taiwan, South Korea and China also have taken significant economic strides and are ranked globally at 15, 26 and 28, respectively. India, on the other hand, is ranked 55 out of 140 nations.

In this paper, the countries were compared on the basis of their rank in the GCI Report 2015-2016. For an in-depth and more holistic study, comparison can be done by taking into consideration other important reports and analysis in this regard.

This is an original study where the developments that have taken place in the five Asian economies have been analysed based on the GCI. Most importantly, this study identifies the area/indicator in which India needs to improve to be placed among the developed nations.

Developing composite index-regional entrepreneurship, technological readiness and institution quality index (RETRIQ) of regional entrepreneurship, technology readiness and quality of institution to measure regional competitiveness. This study, also, aims to test econometrically the effectiveness of the index in capturing the economic performance of the sub-national regions.

The data of eight indicators used in the index are from sources available freely in the public domain. The causal relationship analysis is done using panel data of 10 years from 2008 to 2017 for 32 Indian states/union territories. The generalized method of moments (GMM) is used for this dynamic regression estimation.

Based on RETRIQ, 32 states and union territories of India have ranked. The estimation using GMM shows a significant association between the composite index and economic growth.

The limitations of the study include the broad assumption that these sub-national regions belong to a uniform macro-economic and technology environment and data constraints as it is a longitudinal study. Then, the implication of the study is that the composite index-RETRIQ could capture differences in regional competitiveness explaining regional economic disparity.

The index will be useful for policy implications in the assessment of competitiveness disparity.

It is a composite index of regional entrepreneurship, technological readiness and quality of the institution. The panel data across states along 10 years series is novel.