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Environmental degradation is a global concern and an increasing one. Increasing population pressures, escalating consumption patterns and rapid industrial development are key contributors to this degradation. There is a growing recognition that sustainable development policies, plans and actions have a better chance of being implemented when they are supported by an educated, informed public. The objective of this paper is to highlight the need for the inclusion of environmental education into the curricula of engineering studies in order to raise environmental awareness at an early stage in their careers. The main aim of such environmental education is to provide engineers with the background to environmental issues such that they develop solutions that take into account the needs of the natural environment and which seek to minimise any negative impact.

The debate that entrepreneurship is an engine of economic development has been a long-standing one. The higher the level of entrepreneurial activities, the higher the economic development. However, this literature is contradictory or elusive in Sub-Saharan Africa. Entrepreneurial activities are high in Africa, but economic development is not. Using Global Entrepreneurship Monitor (GEM, 2017) data, the chapter discusses some of the contradictory factors. Further data were collected from 60 businesses, 20 each from Cameroon, Nigeria and Uganda for more clarification in 2019. The results show that the economic development is solely measured in economic terms. Entrepreneurship in Africa operates in an embedded context quite different from that of developed nations. Africans are often only making do with the environment in which they find themselves; thus, entrepreneurship in Africa should not be seen as unproductive considering the context and motives of the entrepreneurs.

Recycled aggregate self-compacting concrete (RASCC) has the potential for sustainable resource utilization and has been widely applied. Predicting the compressive strength (CS) of RASCC is challenging due to its complex composite nature and nonlinear behavior.

This study comprehensively evaluated commonly used machine learning (ML) techniques, including artificial neural networks (ANN), random trees (RT), bagging and random forests (RF) for predicting the CS of RASCC. The results indicate that RF and ANN models typically have advantages with higher R2 values, lower root mean square error (RMSE), mean square error (MSE) and mean absolute error (MAE) values.

The combination of ML and Shapley additive explanation (SHAP) interpretable algorithms provides physical rationality, allowing engineers to adjust the proportion based on parameter analysis to predict and design RASCC. The sensitivity analysis of the ML model indicates that ANN’s interpretation ability is weaker than tree-based algorithms (RT, BG and RF). ML regression technology has high accuracy, good interpretability and great potential for predicting the CS of RASCC.

ML regression technology has high accuracy, good interpretability and great potential for predicting the CS of RASCC.

The purpose of this study is to develop an in-depth understanding of the overall process of facilitating co-creation of e-government services, focusing on the government's role in fostering citizen engagement.

This study conducted a meta-synthesis of qualitative case studies encompassing analyses on a case-specific level followed by syntheses on a cross-study level.

Through meta-synthesis, the study developed an integrated framework, the process theory view of enabling co-creation of e-government services, illustrating how co-creation could be initiated and facilitated by the government.

By providing critical insights into co-creation steps, the process theory view offers a holistic theoretical understanding of enabling co-creation by identifying factors driving and motivating governments to initiate co-creation activities, interpreting the prerequisites for co-creation and the importance of impact assessment.

This study offers important implications for public authorities, administrators and policymakers by helping them enhance their knowledge base on the co-creation process to facilitate a higher level of collaboration between citizens and government for effective and efficient public service delivery through e-government.

While it is widely acknowledged that citizen engagement is crucial for improving and transforming the development and delivery of e-government services, it is equally recognized as a challenging and complex task. Through a meta-synthesis of qualitative case studies, this study is one of the first to develop a process theory view for offering a holistic understanding and crucial insights for addressing the concerns over the co-creation of e-government services.