Technical Education, Vocational Training and Industrialisation in Sub-Saharan Africa(SSA)

This study contributes to a deeper understanding and perspective on the current debate on structural transformation in Sub-Saharan Africa (SSA) by investigating the effect of technical vocational education and training on industrial performance between 1980 - 2018. The panel data used for this study were obtained from World Development Indicators (WDI), International Labour Organization (ILO), United Nations Educational, Social and Cultural Organization (UNESCO) and Fraser Institute databases. The empirical results derived from the Instrumental Variable (IV) Two-Stage Least Squares (2-SLS) econometric approach highlighted the important role of Technical Vocational Education and Training (TVET) as key determinants of industrial performance in SSA. The study found strong and robust relationship between TVET and measures of industrialisation. General secondary education, on the other hand, had a negative effect on industrialisation in SSA. The paper recommends therefore that there is the need for a complete overhaul and revision of the educational system in SSA with more emphasis on TVET in order to meet the required labour demand for industrial needs in the foreseable future.

Brazil's GPA accession will involve costs and benefits

Significance The agreement would open a market of USD1.7tn for Brazilian companies to compete for government procurement contracts internationally, but would also render them vulnerable to competition for Brazilian government contracts from foreign suppliers on equal terms. The process of negotiations is a lengthy one, as well as controversial. Impacts Accession to the GPA could facilitate Brazil’s ambition to join the OECD. Domestic companies’ lack of competitiveness within the GPA could aggravate existing problems with industrial performance. Political uncertainties surrounding the October elections could delay the pace of accession.

The Circular Carbon Economy Index 2021 – Methodology

The Circular Carbon Economy Index (CCE Index) aims to measure countries’ progress in and potential for achieving circular carbon economies (CCEs). The CCE Index is based on two sub-indices: one for measuring countries’ current performance in the various dimensions of the CCE and the other for gauging how countries are positioned to make progress toward the CCE, based on key enabling factors. The CCE Index also allows for additional comparisons among top oil-producing countries through a separate set of add-on indicators that estimate how these countries’ industrial performance and business environments are aligning with the CCE.

Improving Construction Industrialization Practices from a Socio-Technical System Perspective: A Hong Kong Case

Construction Industrialization (CI) tends to improve industrial performance and contributes substantially towards global sustainability. Considering these merits, many countries and regions, including Hong Kong, have released policies to promote CI uptake. However, those policy interventions ignore the dynamic influence of stakeholders and technologies, which significantly influence the efficient management of CI. In response, this study aimed to objectively depict a real socio-technical system of CI uptake based on a representative case study in Hong Kong. Further, this study identified the critical issues associated with the CI uptake and proposed policy-related recommendations to overcome the key issues. In addition, this study proposed a novel approach based on two-mode social network analysis to facilitate the analysis from a socio-technical perspective. Theoretically, this depicts the interactions of construction industry stakeholders and artifacts within a dynamic, complex socio-technical environment, indicating a new stance for construction management. Finally, this research also provides valuable implications for the government to anticipate the impact of different CI policies on promoting its uptake within the complex socio-technical system.

Industrial Performance: An Evolution Incorporating Ethics in the Context of Industry 4.0

This article addresses the issue of the industrial performance model and its evolution to cope with the context of Industry 4.0. With its digitalisation, intelligent/autonomous systems and wealth of data, Industry 4.0 offers opportunities that can achieve objectives better. It also presents risks and uncertainties that question the autonomy of the systems, their interaction with humans and the use of available data. The hypothesis put forward in this work is that the efficiency–effectiveness–relevance performance triangle can no longer guarantee long-term performance under these conditions and needs to be associated with an ethical dimension that allows for the risks and uncertainties relating to Industry 4.0 to be considered. Ethics is therefore considered to extend the triangle to a tetrahedron. A brief analysis of current performance management will first show the limits of the current practice in the context of Industry 4.0. The frameworks that could overcome these limits in light of new needs are then recalled and discussed, leading to the choice of ethics, whose main definitions and use in the engineering field are also introduced. The proposed (efficiency–effectiveness–relevance–ethics tetrahedron-based methodology is illustrated through a case study related to an aeronautical supplier, regarding the consequences of the implementation of a MES (Manufacturing Execution System) in terms of product traceability and operator autonomy. The discussion and prospects finally conclude this study.

Toward EEG-Based BCI Applications for Industry 4.0: Challenges and Possible Applications

In the last few decades, Brain-Computer Interface (BCI) research has focused predominantly on clinical applications, notably to enable severely disabled people to interact with the environment. However, recent studies rely mostly on the use of non-invasive electroencephalographic (EEG) devices, suggesting that BCI might be ready to be used outside laboratories. In particular, Industry 4.0 is a rapidly evolving sector that aims to restructure traditional methods by deploying digital tools and cyber-physical systems. BCI-based solutions are attracting increasing attention in this field to support industrial performance by optimizing the cognitive load of industrial operators, facilitating human-robot interactions, and make operations in critical conditions more secure. Although these advancements seem promising, numerous aspects must be considered before developing any operational solutions. Indeed, the development of novel applications outside optimal laboratory conditions raises many challenges. In the current study, we carried out a detailed literature review to investigate the main challenges and present criteria relevant to the future deployment of BCI applications for Industry 4.0.