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This chapter investigates the effect of customer orientation and CRM organization on hotel financial performance. A model of enhancing hotel financial performance through customer satisfaction practices was tested. Customer satisfaction was hypothesized to be a mediator in the relationships between customer orientation and CRM organization and the result being financial performance. The sample consisted of 54 hotels that was made up of three 5-star, fifteen 4-star, and thirty-six 3-star hotels in Ghana. A quantitative deductive approach was employed to gather data using cross-sectional survey, which was analyzed using PLS-SEM to check the validity, reliability and factor loading of the data. The findings revealed that, CRM organization enhances customer satisfaction and financial performance of hotels. Also, customer orientation showed significant positively related to customer satisfaction in the hotels. Surprisingly, the effects of CRM organization and customer orientation on financial performance through customer satisfaction were insignificant. Thus, customer satisfaction failed to mediate the effect of CRM organization and customer orientation on the financial performance of hotels. This suggests that though an effective CRM organization enhances customer satisfaction, it directly affects the financial performance of hotels. The outcomes have useful implications for CRM implementation on hotel financial performance in Ghana.

Physical victimization at school is little studied in impoverished developing country contexts. Moreover, the role of school and classroom contexts as risk factors remains poorly understood.

The aim of the study is to investigate the prevalence of physical victimization in rural Chinese middle schools as well as the individual, teacher/classroom, and school-level risk factors associated with experiencing physical victimization.

We use two waves of longitudinal, representative survey data to perform a multilevel logistic regression analysis (MLRA) of physical victimization among middle school students from 100 villages in one of China’s poorest provinces. We focus on a subset of questionnaire items that were gathered from students when the sampled children were 13–16 years old. We also utilize student data from the first wave of the survey to control for prior internalizing problems and academic achievement. Finally, we link matched data collected from principal and teacher questionnaires to examine the risk factors for physical victimization associated with students’ microclimates and the wider school environment.

A substantial proportion of middle school students (40%) reported having been beaten by classmates. Elevated risk was found among males; students with prior poor performance in language; students with past internalizing problems; students of female teachers and teachers evaluated as low performing; students in disruptive classrooms; and students in classrooms undergoing mandated reforms.

These findings suggest that efforts to reduce school violence should not only focus on the deficits of individual students, but rather should target practices to alter the within school risk factors associated with microclimates.

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 number of studies have examined the role of typical demand supply factors in explaining inflation. The contribution in this chapter is to investigate the possible role of product market imperfections on inflation and inflation persistence, especially among emerging market economies. Using a backward-looking Phillips curve framework in a dynamic panel framework of 105 countries over the 2008–2011 period, our findings suggest that product market competition, as measured by the World Economic Forum’s measure of goods market imperfections do have a significant impact on inflation persistence. On average, higher competition and efficiency in product markets reduces the inflation persistence effect especially in the MENA region and countries at lower stages of development.

The appropriation of artificial intelligence (AI) into everyday workplace practices is becoming pervasive. Some of the industries that have seen the improved appropriation of AI include the automotive industry, food chains and other retail businesses. The media industry in developed countries has also been appropriating AI into newsrooms ecologies. This development has left news media workers, especially in developing countries, questioning the viability of their jobs in the foreseeable future as machines take over and disrupt newsmaking and production processes. The unknowns that come with AI adoption have been met with both utopian and dystopian views in African newsrooms, especially in countries that understand less on how to deploy AI affordances. Premised on the technology acceptance model and the concept of technological appropriation and a qualitative methodology that used structured interviews with community media journalists from the Western Cape province of South Africa, this chapter examined journalists' perceptions of AI deployment in the community media space. The findings of the study show that community media journalists hold both utopian and dystopian views on the utility of AI in the community media space. While most journalists perceive AI as enhancing the efficiency and accuracy of the newsmaking process, there is a significant number of journalists who perceive AI as inimical to the legitimacy and credibility of the profession. Furthermore, AI is also seen as a threat to jobs within the journalism profession. These findings resonate with previous studies that have shown that journalists are divided on the perceived utility of AI in newsrooms.

The purpose of this chapter is to provide a comprehensive view of special education in the Kingdom of Saudi Arabia. The chapter starts with the origins and attitudes of the Saudi citizens regarding persons with special needs. Next the chapter examines trends in legislation and litigation pertaining to persons who are disabled which led to the government’s passage of Regulations of Special Education Programs and Institutes (RSEPI) in 2001. The RSEPI regulations were modeled after the United States 1997 Individuals with Disabilities Education Act (IDEA). Included in the discussion of the RSEPI is a delineation of the Disability Code which is comprised of 16 articles. The author also provides information on prominent educational intervention employed in the Kingdom as well details about the preparation of paraprofessionals and special education teachers. The chapter concludes with the special education progress that has occurred since the passage of RSEPI.

This chapter explores the importance of early autism spectrum disorder (ASD) assessment and diagnosis to facilitate early treatment. This chapter will have a particular focus on ASD assessment and diagnosis within a Black and Minority Ethnic (BME) context. We propose using a Cultural Competence framework to process, analyze, assessment, and diagnosis results/findings. BME assessments/diagnoses can be delayed by up to 18 months longer when compared to Whites.

ASD Assessment aims to assess certain developmental traits in individuals to identify ASD which is a developmental disability. Autism is a spectrum condition which can manifest differently in each diagnosed individual. There are core features necessary for an ASD diagnosis to be made. These include among other traits: poor eye contact, abnormality in body language: for example, gestures, difficulties with social communication and social interaction, often they exhibit repetitive patterns of behavior, have obsessional interests, rigid thinking patterns, and have an aversion to certain sounds and textures and an unusual interest in sensory satisfaction.

In this chapter, a general introduction on artificial intelligence (AI) is given as well as an overview of the advances of AI in different engineering disciplines, including its effectiveness in driving the United Nations Sustainable Development Goals (UN SDGs). This chapter begins with some fundamental definitions and concepts on AI and machine learning (ML) followed by a classification of the different categories of ML algorithms. After that, a general overview of the impact which different engineering disciplines such as Civil, Chemical, Mechanical, Electrical and Telecommunications Engineering have on the UN SDGs is given. The application of AI and ML to enhance the processes in these different engineering disciplines is also briefly explained. This chapter concludes with a brief description of the UN SDGs and how AI can positively impact the attainment of these goals by the target year of 2030.