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Financial difficulties are associated with poor student mental health, although the 2012 tuition fees increase for British students had little impact on student mental health in the first two years at university. This study aims to examine the mental health of British graduates before and after this fees increase to determine the impact on mental health several years after graduation.

This study conducted an online cohort study with 327 British students who started university before and after the 2012 fees increase. Participants completed measures of current economic hardship and symptoms of depression, anxiety, stress, general mental health and suicidality. Multiple regression was used to examine the impact of cohort (pre- and post-2012 fees increase), tuition fees amount and economic hardship on mental health.

Greater economic hardship was positively correlated with all mental health variables. Starting university after the fees increased and/or paying greater fees was associated with increased depression, anxiety, stress and suicidality, with little impact on general mental health. When economic hardship was covaried, the strength of cohort effects reduced but remained significant.

To the best of the authors’ knowledge, this is the first study to show that the 2012 tuition fees increase for British students increased depression, anxiety, stress and suicidality in graduates many years after graduation, owing to additional financial strain.

Introduction: Micro, small, and medium enterprises (MSME) have long been viable in the Indian economy. In the case of post-COVID-19, 20–40% of MSMEs in government can be permanently closed. The state should pay special attention to MSMEs for survival (Min, 2023).

Purpose: This chapter provides a framework for MSMEs to study industry challenges in Punjab and to discuss the conceptual framework and road map for future MSMEs in Punjab.

Need for This Study: The COVID-19 pandemic has drastically impacted the variable economic activities within the world. This study is responsible for explaining the different vulnerable sectors related to small- and medium-sized enterprises. On the other hand, this study is an analytical and descriptive research in nature.

Methodology: A mixed method of data collection has been used in this chapter. The data have been collected by floating a questionnaire to the various entrepreneurs of MSMEs. Secondary data have been collected through the Internet.

Findings: Through this research, we could analyse the MSMEs’ conceptual framework, the challenges they face, and the industrial units’ future roadmap.

Practical Implications: This research is mainly considered a clear explanation of current competition and market access challenges that small- and medium-sized enterprises face. This situation is derived due to the COVID-19 pandemic, so many enterprises are trying to find their exit ways. On the other hand, some MSMEs are trying to focus on the online business market to make some profit and to overcome the loss.

Introduction: The insurance sector provides security to society by pooling resources to manage risks. Insurers’ improved ability to analyse risks by examining vast amounts of granular data has considerably refined this technique. Compiling and analysing the fine data sets is now transformed into the ‘Big Data’ technique. The introduction of big data analytics (BDA) is transforming the insurance industry and the role data plays in insurance.

Purpose: This chapter will attempt to examine the applications and role of big data in the insurance sector and how big data affects the different insurance segments like health insurance, property and casualty, and travel insurance. This chapter will also describe the disruptive impact of big data on the insurance market.

Methodology: Systematic research is carried out by analysing case studies and literature studies, emphasising how BDA is revolutionary for the insurance market. For this purpose, various articles and studies on BDA in the insurance market are selected and studied.

Findings: The execution of big data is continuously increasing in the insurance sector. The performance of big data in the insurance market results in cost reduction, better access to insurance services, and more fraud detection that benefits the customers and stakeholders. Therefore, big data has revolutionised the insurance market and assisted insurers in targeting customers more precisely.

Purpose: The study is designed to investigate internal audit functions in banks’ cyber security governance processes by assessing the pros and cons of blockchain technology through swot analysis.

Need of the Study: The study is needed to clarify the complexities in internal audit fields integrated into cyber security governance and explore the blockchain application opportunities.

Methodology: Blockchain technology is explored from the point of technical concepts and policy framework by swot analysis to propose a set of solutions for continuous audit methods in cyber security governance.

Limitations: The sample of this study is limited to the personal ideas and evaluations of academicians, experts in the banking sector and legal regulators of Türkiye, with the data received between March and December 2021.

Findings: Blockchain technology can be applied as an alternative to conventional risk control methods as a mechanism of continuous audit methods to reduce human mistakes and special causes.

Practical Implications: The control of risk management operations for cyber security processes should be performed with the support of audit units of the banks. Therefore, innovations are being implemented to cyber-risk controls to drop the defects that cause technical and ethical issues with blockchain technology as a way of using automation. So, this advancement can be applied in audit operations practically for unanticipated events which can emerge in cyberspace to mitigate inherent risk to residual levels. However, there is ample room to adapt this technology for cyber security management and audit practices from the point of view of the labour force, regulations and environmental issues.

Purpose: With this study, the authors aim to highlight the application of machine learning in smart appliances used in our day-to-day activities. This chapter focuses on analysing intelligent devices used in our daily lives to examine various machine learning models that can be applied to make an appliance ‘intelligent’ and discuss the different pros and cons of the implementation.

Methodology: Most smart appliances need machine learning models to decrypt the meaning and functioning behind the sensor’s data to execute accurate predictions and come to appropriate conclusions.

Findings: The future holds endless possibilities for devices to be connected in different ways, and these devices will be in our homes, offices, industries and even vehicles that can connect each other. The massive number of connected devices could congest the network; hence there is necessary to incorporate intelligence on end devices using machine learning algorithms. The connected devices that allow automatic control appliance driven by the user’s preference would avail itself to use the Network to communicate with devices close to its proximity or use other channels to liaise with external utility systems. Data processing is facilitated through edge devices, and machine learning algorithms can be applied.

Significance: This chapter overviews smart appliances that use machine learning at the edge. It highlights the effects of using these appliances and how they raise the overall living standards when smarter cities are introduced by integrating such devices.

Introduction: Organisations all over the world are experiencing skill gaps. One of the key factors contributing to the shortage of competent workers is the inability to find candidates that fit the profile. Most of the time, the market does not offer what organisations require.

Purpose: This research focuses on skill shortages and labour market rigidity in the information technology (IT) sector. It discusses the impact of labour shortage and strategies to overcome these challenges.

Need of the Study: The study is required to reduce the skill shortage in the IT sector and inflexibility in the labour market.

Methodology: The data are collected from secondary sources, that is, books, journals and other internet sources.

Findings: The labour market volatility is impacted by several external factors leading to rigidity and talent shortages. Different forecasts within the IT industry, manufacturing, media and telecommunications indicate large-scale labour shortages. The growing influence of digitalisation further creates challenges for organisations during the hiring process as the identified skill gaps for IT professionals are also identified.

Practical Implications: Labour market rigidity affects the labour market. Shifts in labour supply and demand do not always impact wages. Methods are suggested on how to reduce the rigidity in the labour market and, in turn, decrease the skill gaps.

Fintech provides the necessary ecosystem for businesses to accept payments for goods and services in the most seamless manner. It can also be said that innovation in Fintech is one of the growth drivers for businesses in today's globalised market.

Fintech is revamping the entrepreneurship business by bridging the gap between the market and real-time access to investment. It provides entrepreneurs with numerous advantages like easy access to resources, reduced expenses and better customer experience. Hence, this research has focused on evaluating the impact of Fintech business on entrepreneurship business in the global market.

A mixed method of data collection has been used to conduct the research in which primary data have been collected using an online survey and secondary data have been collected from online articles and peer-reviewed journals. An online survey of 51 business managers recruited from the social networking platform LinkedIn has been done to collect primary data. Secondary data have been collected from the online database Google Scholar which has been published in the last five years.

The findings of the study have highlighted the various impacts that Fintech has had on entrepreneurship business in the global market and the reason why it is such an important factor for growth.