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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 increasing accumulation of synthetic plastic waste in oceans and landfills, along with the depletion of non-renewable fossil-based resources, has sparked environmental concerns and prompted the search for environmentally friendly alternatives. Biodegradable plastics derived from lignocellulosic materials are emerging as substitutes for synthetic plastics, offering significant potential to reduce landfill stress and minimise environmental impacts. This study highlights a sustainable and cost-effective solution by utilising agricultural residues and invasive plant materials as carbon substrates for the production of biopolymers, particularly polyhydroxybutyrate (PHB), through microbiological processes. Locally sourced residual materials were preferred to reduce transportation costs and ensure accessibility. The selection of suitable residue streams was based on various criteria, including strength properties, cellulose content, low ash and lignin content, affordability, non-toxicity, biocompatibility, shelf-life, mechanical and physical properties, short maturation period, antibacterial properties and compatibility with global food security. Life cycle assessments confirm that PHB dramatically lowers CO₂ emissions compared to traditional plastics, while the growing use of lignocellulosic biomass in biopolymeric applications offers renewable and readily available resources. Governments worldwide are increasingly inclined to develop comprehensive bioeconomy policies and specialised bioplastics initiatives, driven by customer acceptability and the rising demand for environmentally friendly solutions. The implications of climate change, price volatility in fossil materials, and the imperative to reduce dependence on fossil resources further contribute to the desirability of biopolymers. The study involves fermentation, turbidity measurements, extraction and purification of PHB, and the manufacturing and testing of composite biopolymers using various physical, mechanical and chemical tests.

One of the most hyped concepts in the manufacturing industry is ‘Industry 4.0’. The ‘Industry 4.0’ concept is grabbing the attention of every manufacturing industry across the globe because of its immense applications. This phenomenon is an advanced version of Industry 3.0, combining manufacturing processes and the latest Internet of Things (IoT) technologies. The main advantage of this paradigm shift is efficiency and efficacy in the manufacturing process with the help of advanced automated technologies. The concept of ‘Industry 4.0’ is contemporary, so it falls under exploratory study. Therefore, the research methodology is thematic narration grounded on secondary data (online) analysis. In this light, this chapter aims to explain ‘Industry 4.0’ in terms of concepts, theories and models based on the Web of Science (WoS) database. The data include research manuscripts, book chapters, blogs, white papers, news items and proceedings. The study details the latest technologies behind the ‘Industry 4.0’ phenomenon, different business intelligence technologies and their practical implications in some manufacturing industries. This chapter mainly elaborates on Industry 4.0 frameworks designed by (1) PwC (2) IBM (3) Frost & Sullivan.

In this chapter, the author explores the principles of responsible management education through the lens of Taoism. This chapter begins by introducing the concepts of knowledge-inquiry and wisdom-inquiry and highlights the differences between the two in the context of management education. The author emphasizes the importance of wisdom-inquiry in management education, arguing that it allows individuals to not only understand and analyze information but also to apply ethical considerations when making decisions. This chapter delves into how to synthesize knowledge and wisdom in education, highlighting the need for a balance between technical skills and ethical awareness in management education. This chapter concludes with an examination of the principles of managing talent by balancing competence and character. The author discusses how to hire for character and train for competence in human resources management and development. This approach involves focusing on developing individuals' character traits, such as integrity, compassion and empathy, in addition to their technical skills. This chapter demonstrates the value of incorporating Taoist principles into management education. When the importance of wisdom-inquiry, balancing competence and character, and developing ethical leaders is emphasized, management education can prepare individuals to navigate the complexities of the modern business landscape while promoting responsible business practices.

Mauritius is a Small Island Development State (SIDS) with limited resources, and it has been witnessed that many containers used for storing household and industrial products are made from plastic. When discarded as waste, those plastic containers pose a serious environmental and economic challenge for Mauritius. Moreover, landfill space is getting increasingly scarce, and plastic waste is contaminating both land and water. Therefore, it is of the utmost necessity to develop solutions for Mauritius' plastic wastes. Due to its abundance and accessibility, plastic waste is a promising material for recycling and energy production. One potential solution is the use of machine learning and artificial intelligence (AI) to predict household plastic consumption, allowing policymakers to design effective strategies and initiatives to reduce plastic waste. Such information is a critical component to be able to efficiently plan for the collection and routing of trucks when collecting recyclable plastics. The development of new strategies for the recycling of plastic waste and development of new industry can address the import and export potential of the country to achieve self-sustainability as well as contribute to reduction in plastic pollution and amount of waste landfilled. These plastics can thereafter be used effectively for recycling and for the making of 3D printing filaments which fall under the SDGs 9 (Industry, Innovation and Infrastructure) and 12 (Responsible consumption and production).

This chapter investigates a new human-centric perspective oriented to consider society as a whole, by following a systemic vision, where social well-being is important: Industry 5.0. The analysis is based on the great advantages for the ecosystem, going beyond the custom of affirming technological development and managerial views, favoring the dialog between the actors of the system, the adaptation of technologies to the context in which one operates, choosing the most appropriate business strategies, sustaining smart, sustainable and inclusive solutions in the innovation process. In this sense, big data, internet of things, augmented realities, or robotics are all technologies to increase productivity and improve working conditions but, at the same time, they have to improve social life. To overcome the main related challenges and support the transition, new insights to design innovative strategies urge. Our research aims to explore the scientific literature about Industry 5.0 and its development in the European Union. We carried out a systematic review and a bibliometric analysis of the scientific production through the Web of Science (WoS) and SCOPUS databases. In addition, our study analyzes how the proposed topic has evolved over time by collecting contributions from different countries and authors. We adopted an innovative tool that goes beyond the traditional statistical methods generally used in bibliometric research, and it allowed us to obtain more advanced results. Our software permitted us to join the findings of two databases simultaneously, such as WoS and SCOPUS, to generate a bibliometric analysis and identify new paradigm trends.