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In this chapter, we discuss menopause transition in the workplace and its implications for workplace well-being. This is an important work-life interface topic, given the increasing number of women who will work during transition. It is also a topic that we currently know relatively little about, particularly in relation to well-being. We present findings that demonstrate both that many women experience symptoms that are bothersome at work and that these frequently have negative effects for two elements of workplace well-being, job satisfaction and health well-being. We evidence that individual/job characteristics and workplace context can either improve or worsen experiences of transition symptoms and make recommendations on how organization and HR practice can be designed to support women in menopause transition. We argue that working with line managers to create a more supportive context is one of the most important strategies to implement. Our research is situated in the UK police service and has wider relevance across the Global North, where similar demographic patterns are experienced, and in other male-dominated organizations and sectors.

This empirical chapter explores the case of Baltic Creative Community Interest Company (BC CIC), a creative hub that enabled and demonstrated intrapersonal entrepreneurial capitals (Pret et al., 2016) to adapt quickly and develop novel offers for their tenants during an unprecedented period of crisis and change in the wider ecosystem. BCCIC is a community-owned property development company established to regenerate an underused post-industrial area in Liverpool and support the Creative and Digital community. Over the past decade, they have become a creative hub where small, unique micro-businesses thrive alongside more established enterprises.

Using an organisational ethnographic approach, the authors highlight the complexity in the conversion of entrepreneurial capitals and how this has demonstrated resilience and adaptability in the CIC during the global coronavirus pandemic in the 2020s. During the first coronavirus lockdown in 2020, The CIC responded swiftly to tenants by providing a wide variety of business support initiatives. Regular communications on sector-specific COVID-19 operational guidance and a support programme to help tenants apply for Liverpool City Council Small Business Support grants.

The establishment of this hub for creative entrepreneurs prior to the recent disruption proved invaluable. Although they were severely tested, emerging behaviours, such as agility, adaptability, and resilience during periods of crisis, were identified. This chapter offers key insights for scholars and those leading on creative hubs and cluster policy development and economic initiatives for creative sector support regionally, nationally, and internationally.

Introduction: Numerous decision-making situations are faced in education where Artificial Intelligence may be prevalent as a decision-making support tool to capture streams of learners’ behaviours.

Purpose: The purpose of the present study is to understand the role of AI in student performance assessment and explore the future role of AI in educational performance assessment.

Scope: The study tries to understand the adaptability of AI in the education sector for supporting the educator in automating assessment. It supports the educator to concentrate on core teaching-learning activities.

Objectives: To understand the AI adaption for educational assessment, the positives and negatives of confidential data collections, and challenges for implementation from the view of various stakeholders.

Methodology: The study is conceptual, and information has been collected from sources comprised of expert interactions, research publications, survey and Industry reports.

Findings: The use of AI in student performance assessment has helped in early predictions for the activities to be adopted by educators. Results of AI evaluations give the data that may be combined and understood to create visuals.

Research Implications: AI-based analytics helps in fast decision-making and adapting the teaching curriculum’s fast-changing industry needs. Students’ abilities, such as participation and resilience, and qualities, such as confidence and drive, may be appraised using AI assessment systems.

Theoretical Implication: Artificial intelligence-based evaluation gives instructors, students, and parents a continuous opinion on how students learn, the help they require, and their progress towards their learning objectives.