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Purpose: The hospitality industry faces several contemporary issues and challenges that have the potential to impact its growth and development. This study aims to identify and analyse contemporary issues and challenges facing the hospitality industry, including trends, regulations, and Tech salutation.

Need for the study: The hospitality industry plays a significant role in the global economy with its diverse services, including accommodation, food and beverage, events, and tourism. However, the sector faces several contemporary issues and challenges that have the potential to impact its growth and development. This study will provide an overview of the most significant problems and challenges facing the hospitality industry today.

Methodology: The researchers used secondary data for the analysis of the chapter. The researchers reviewed journal papers, books, book chapters, government websites, handbooks, reports, internet, and official records for identification of issues and challenges in the hospitality industry.

Findings: The study identified several contemporary issues and challenges facing the hospitality industry, including the impact of technology and COVID-19 on operations and customer experience, changing consumer preferences for sustainable and ethical practices, labour shortages and retention issues, increasing competition, and changing regulatory environments.

Practical implications: The hospitality industry faces numerous contemporary issues and challenges that impact its sustainability and profitability. Industry stakeholders must understand and address these challenges to remain competitive and relevant in a rapidly changing global market. The findings of this study provide valuable insights into the contemporary issues and challenges facing the hospitality industry and suggest potential strategies for addressing these challenges.

The current era of the fourth industrial revolution has attracted significant research on the use of digital technologies in improving construction project delivery. However, less emphasis has been placed on how these digital tools will influence the management of the construction workforce. To this end, using a review of existing works, this chapter explores the fourth industrial revolution and its associated technologies that can positively impact the management of the construction workforce when implemented. Also, the possible challenges that might truncate the successful deployment of digital technologies for effective workforce management were explored. The chapter submitted that implementing workforce management-specific digital platforms and other digital technologies designed for project delivery can aid effective workforce management within construction organisations. Technologies such as cloud computing, the Internet of Things, big data analytics, robotics and automation, and artificial intelligence, among others, offer significant benefits to the effective workforce management of construction organisations. However, several challenges, such as resistance to change due to fear of job loss, cost of investment in digital tools, organisational structure and culture, must be carefully considered as they might affect the successful use of digital tools and by extension, impact the success of workforce management in the organisations.

The essence of finance has become essential in the sustainability discussion in recent times as a result of the capital intensive nature of sustainable projects. This has motivated financial experts and institutions to develop various financial instruments and mechanisms to further advance the course of protecting the environment, and decreasing the release of excess carbon and GreenHouse Gases. This is to also provide the opportunity for funding Green or sustainable infrastructure development. This chapter advances a discourse on matters relating to sustainable financing of infrastructure projects. The fundamentals of sustainable or green funding of infrastructure projects, and sustainable schemes of financing green infrastructure projects are discussed.

Key enabling technologies (KETs) are a set of six technological components that work together to address social challenges and build advanced for sustainable economies. Industry 5.0, the next industrial development, is designed to capitalize on specialists' unique creativity while also collaborating with powerful, intelligent, and precise technologies. Industry 5.0 outsourced repetitive and monotonous activities to robots/machines requiring employees to perform activities that involve critical thinking and are based on the 6R (Recognize, Reconsider, Realize, Reduce, Reuse, and Recycle), to improve production quality. With numerous supporting technical advancements, advanced and quick manufacturing concentrating on the interaction of machines and humans may be produced. Maintaining healthcare and nursing care, evaluating patients' health requirements using KETs, and giving care with manpower are all major advancements in Industry 5.0 today. Future studies may focus on providing healthcare using mainly technology and, therefore, no human workers. This chapter highlights healthcare advances in Industry 5.0, where KETs and people collaborate to create and innovate. In this framework, the purpose of this chapter is to present the deployment of KETs in the nursing patient care process.

Climate change is a bitter truth for the entire humanity, and it vehemently calls for thoughtful means for environmental protection along with sustainable economic growth. International trade blocs fundamentally represent amalgamation of countries to achieve unified goals like higher living standards, reduced trade barriers, freer labour mobility across member states, social and cultural upliftment, political allegiance to regional association, etc. Throughout the 1990s, these trade blocs have committed to reducing environmental pressures and shifting towards cleaner forms of energy. This chapter examines the relationship between rate of change in carbon dioxide (CO₂) emissions per capita and rate of change in per capita gross domestic product (GDP) in linear, quadratic and cubic polynomial forms with the other control variables like inflow of foreign direct investment (FDI), export of goods and services, population density, urban population percentage and location dummies for the 66 countries falling in seven regional trade blocs. Other than the European Union and North American Free Trade Agreement (NAFTA), the remaining five trade blocs in the study – Association of South-East Nations (ASEAN), South Asian Association for Regional Cooperation (SAARC), Common Market for Eastern and South Africa (COMESA), Mercado Común del Sur (MERCOSUR) and Commonwealth of Independent States (CIS) – contain mostly the developing and some of the fastest growing economies of the world. The panel regression result finds an inverse relationship between rate of change in per capita CO₂ emissions and rate of change in GDP per capita (in linear and cubic polynomial forms), exports and population density, while the other coefficients of the explanatory variables are positive. The study also establishes an Environmental Kuznets Curve (EKC) which is opposite to N-shape during 2005–2019, and that contradicts with the original EKC of inverted U-shaped. However, this shape admits the collective efforts of region-specific trade blocs towards achieving clean environment which is one of the important global goals.

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.

In the stock market, herding behavior occurs when investors mimic the actions of others in their investment decisions. As a result, the market becomes inefficient and speculative bubbles form. This study aims to investigate the relationship between information, overconfidence, market sentiment, experience and national culture, and herding behavior among Malaysian investors. A total of 400 questionnaires are distributed to bank institutions' investors. The survey design based on cross-sectional data is analyzed using the Partial Least Squares Structural Equation Model. The results indicate that information, market sentiment, experience, and national culture are positively related to herding behavior, while overconfidence has no effect. With this, the government should strengthen regulations to prevent the dissemination of misleading information. Moreover, investors are encouraged to overcome narrow thinking by expanding their understanding of different cultures when making investment decisions.