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Corporate governance has become a core topic in management research and business practice. Recent debates like – environmental responsibility, sustainability, ethics, corporate control, generation, protection and distribution of wealth, the role of the board and senior executives in setting standards for performance management, and stakeholder relationship management – have strong links to organisational trust. However, management literature has been relatively silent on how various corporate governance configurations and perspectives potentially shape trust relations within the organisation, especially in Africa. Thus, this chapter reviews corporate governance through the lens of the institutional logics perspective evident in western capitalism and develops a framework connecting various governance configurations to organisational trust. Doing so provides new directions for those seeking to develop further research in corporate governance, institutional logics and organisational trust.

Entrepreneurship education is being taught to undergraduates in tertiary institutions and fresh graduates in youth programmes to encourage start-ups and create employment as a strategy to stem youth unemployment. As such, entrepreneurship education programmes are expected to include rigorous processes of programme design, implementation and evaluation so as to achieve changes in behaviour, attitude and action of participants measureable in terms of start-up and jobs created. Two entrepreneurship education programmes implemented in Nigeria are evaluated to ascertain the level of effectiveness in design, implementation and evaluation and the outcomes in terms of start-ups and employment created. Research methods adopted in the two programmes combine observation techniques with content analyses, action research in case study and focus group interviews. In addition, test-retest techniques in a quasi-experimental design, with a structured questionnaire is adopted in programme number two only. The findings are that while it is suspected that the design stage is jumped in programme number one, in programme two, the design is poorly done. Implementation is ineffective in the two programmes because objectives did not arise from programme design as they ought to and evaluation methods are inappropriate and so ineffective. The recommendations include review of the design of the two programmes to generate appropriate and measurable objectives; adopting implementation strategies that will achieve the measurable objectives generated from revised programme designs and adopting appropriate evaluation techniques that has capacity to measure outcomes and impact in addition to outputs.

The United Nations (UN) adopted Sustainable Development Goals (SDGs); agenda 2030 focuses on Climate Action (goal 13), targeting climate adaptability, as well as resilience, awareness and improving policy mechanisms on climate change. In order to enhance climate adaptability, climate-smart agricultural practices (CSAP) is a necessary step. CSAP is a sustainable agriculture approach with a strong focus on climate dimensions. The three pillars of climate-smart agriculture (CSA) are ‘Adaptation’: adapting to climate change; ‘Resilience’: building resilience against it and ‘Remove’: reducing carbon emissions. The new world economy uses Industry 4.0 technologies for sustainable advancement, including blockchain technology, big data analytics, artificial intelligence (AI), augmented and virtual reality, industrial Internet of Things (IoT) and services. Hence, technology plays a significant role in climate sustainable agriculture practices. This chapter shall consider three technologies consisting of IoT, AI and blockchain technology which contribute to CSAP in pre-harvesting (monitoring climate as well as fertility status, soil testing, etc.), harvesting (tilling, fertilisation, seed operations, etc.) and post-harvesting (predicting weather factors, seed varieties, etc.) periods of agriculture. All these three technologies work like the human nervous system; IoT helps in converting various information regarding demography, climate change, local agricultural needs, etc. into world data; AI works like a brain in combination with IoT, helps predict the use of climate-smart technology and blockchain, the memory part of the nervous system which deals with supply-side and ensures traceability as well as transparency for consumers as well as farmers. Hence, this chapter shall contribute to the importance of these three technologies in adopting CSAP in three stages of agriculture.

This chapter offers an overview of the applications of artificial intelligence (AI) in the textile industry and in particular, the textile colouration and finishing industry. The advent of new technologies such as AI and the Internet of Things (IoT) has changed many businesses and one area AI is seeing growth in is the textile industry. It is estimated that the AI software market shall reach a new high of over US$60 billion by 2022, and the largest increase is projected to be in the area of machine learning (ML). This is the area of AI where machines process and analyse vast amount of data they collect to perform tasks and processes. In the textile manufacturing industry, AI is applied to various areas such as colour matching, colour recipe formulation, pattern recognition, garment manufacture, process optimisation, quality control and supply chain management for enhanced productivity, product quality and competitiveness, reduced environmental impact and overall improved customer experience. The importance and success of AI is set to grow as ML algorithms become more sophisticated and smarter, and computing power increases.

The evolution and trends of special education and educational leadership are evident, especially in recent years. The former has strived to provide equitable educational opportunities to students with disabilities. The latter has dealt with how people in positions of authority in K-12 schools create policy, use resources, and influence other people to achieve educational goals. Together, these notions constitute an idea that school leaders and administrators can provide insight, oversight, assistance, and guidance toward creating educational environments for students with and without disabilities. This chapter examines the current state of special education and educational leadership by exploring the evolution of special education, relevant legal cases, and the enactment of inclusive education. Furthermore, this chapter addresses contemporary issues for leaders, such as the influence of the COVID-19 pandemic, while dealing with special education and the increasing pressure from families for equity for students with disabilities.

This chapter provides an overview of the potential use of Intelligent Transport Systems (ITS) and associated artificial intelligence (AI) techniques in the land transport sector in an attempt to achieve related United Nations Sustainable Development Goals (SDGs) targets. ITS applications that have now been extensively tested worldwide and have become part of the everyday transport toolkit available to practitioners have been discussed. AI techniques applied successfully in specific ITS applications such as automatic traffic control systems, real-time image processing, automatic incident detection, safety management, road condition assessment, asset management and traffic enforcement systems have been identified. These methods have helped to provide traffic engineers and transport planners with novel ways to improve safety, mobility, accessibility and efficiency in the sector and thus move closer to achieving the various SDG targets pertaining to transportation.

A hybrid of architectural design and engineering, architectural engineers (AEs)design and remediate problems with internal and external structures and systems of building and facilities in the US. Trained and credentialed in academic programs awarding approximately 1,000 degrees annually, AE is a mid-sized specialty engineering degree comparable to computer software, nuclear, or materials engineering. The case outlines the origins and history of the occupation and illustrates three aspects of the academization process: integration of the university’s charter for knowledge production within an occupation; possibilities for conflict and power within universities that can shape occupational outcomes; and the role of the university and collaborations with practitioners in creating change in theoretical conceptions, on-the-job skills, and problem-solving strategies. AE demonstrates academization in a field with specific physical outcomes and functional requirements that are technically bounded. As counterfactuals, possible alternative occupational paths for the work roles of AEs are considered, along with reasons why they did not happen. What did occur demonstrates the impact of the academization process, with both credentialing and new research. AE is an informative example of constructed functionalism, formed and continually shaped by the university.

It is now well-established that good water quality is associated with economic prosperity, reduced incidence on public health and the good functioning of the various ecosystems found in our environment. Water contamination is mostly related to both diffused (agricultural lands and geologic rock degradations) and point sources of pollution. Mauritius has many water resources which depend solely on precipitation for their replenishment. Water parameters which are of relevance include total dissolved solids (TDS), temperature, pH, electrical conductivity, turbidity, dissolved oxygen, dissolved and particulate organic carbon and major cations and anions. The traditional methods of analysis for these parameters are mostly using electrical and optical methods (probes and sensors in the field), while chemical titrations, Flame AAS and High-Performance Liquid Chromatography techniques are carried out in the laboratory. Image Classification techniques using neural networks can also be used to detect the presence of contaminants in water. In addition to basic water quality parameters, the field sensors range have been extended to cover important major ions and can now be integrated with Artificial Intelligence (AI)-based models for the prediction of variations in water quality to better protect human health and the environment, reduce operation costs of water and wastewater treatment plant unit processes.

This chapter explores the relevance of critical race theory (CRT) and queer theory to the relational aspects of program evaluation. Often conceptual binaries that undergird traditional evaluation theory and practice (e.g., internal versus external evaluation, subjective versus objective analysis, observation versus intervention, and insider versus outsider positionalities) adversely influence rigid social roles between evaluator and participant limit a study's effectiveness in supporting programs for equity in contemporary school districts. To illustrate this approach, an array of problems within a program evaluation of a district-wide ethnic studies reform initiative is presented. Approaches to these challenges rooted in tenets of CRT and queer theory illustrate how the district was able to clarify goals and develop an effective implementation plan that focused on effective ethnic studies curriculum and pedagogy.