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The construction industry is famous for gender imbalance and reluctance in initiating change. In recent years, construction is becoming an attractive career choice for women. However, this change has been gradual. The purpose of this research was to understand the challenges women are facing in construction sector after a decade of implementation of the Equality Act 2010 in the UK and how women in the sector feel the industry could be further improved. This research investigated real-life experiences to identify where the industry needs to make viable improvements.

A qualitative research methodology was adopted. In total, 31 semi-structured interviews were conducted to collect data, which was then analysed using content analysis for inference and conclusion.

This research revealed that women still experience adversity forcing them to work harder than usual to prove their belonging in construction sector. The “man’s world” culture is still widespread. However, women have seen improvements over recent years but believe more can be done from an intersectionality perspective. This is pertinent due to the Brexit and Covid-19 situation.

The study contributes to the field of equality and diversity in the construction sector. Women believe that factors such as bespoke initiatives, equal pay, flexible working hours (considering childcare and caring responsibilities), mental health and well-being support, and equality and diversity policies will enable the construction sector to create conducive environment for women now and in the future.

This study aims to enhance the resilience of foamed concrete (FC) against carbonation and water absorption (WA) by integrating microorganisms, specifically Aspergillus iizukae EAN605.

The focus was on understanding how variables such as microorganism concentration, concrete density and water-to-cement (w/c) ratio affect these properties. Optimal results were observed under specific conditions—FC density set at 1800 kg/m³, a w/c ratio of 0.5 and an Aspergillus iizukae EAN605 concentration of 0.5 g/L—resulting in significant reductions in carbonation and WA compared to standard FC.

It is observed that fungi not only fill pores with calcium oxalate but also limit carbonation by consuming CO₂ and block water penetration through their mycelial network. A central composite design within response surface methodology was employed for the experimental design, resulting in mathematical models that align closely with the empirical data. The models identified the most effective parameters for minimizing carbonation depth: FC density at 1970 kg/m³, fungal concentration at 0.585 g/L and w/c ratio at 0.470. Further regression analysis showed a high correlation between the experimental data and the predicted outcomes, with a coefficient of determination (R²) of 92.29 and a model F-value of 16.45.

Statistical analysis highlighted the significant roles of density and fungal concentration in these reductions. Besides, scanning electron microscopy provided visual evidence of fungal-mediated mineral formation in FC, supporting the empirical findings. Overall, the study demonstrated the effective use of Aspergillus iizukae EAN605 in enhancing the durability of FC, marking an innovative stride in sustainable construction materials.

This study bridges the gap in quality control strategies for high-volume production by balancing the cost and effectiveness of inspection strategies. Using the cost of quality (CoQ) to manage cost and external failures (EF) to gauge effectiveness, this research introduces an innovative inspection strategy chart that serves as a decision-making tool for optimizing inspection processes.

This paper presents a scenario-based framework designed to support strategic decision-making in inspection processes by integrating empirical data analysis with inspection strategy charts. This approach allows for a dynamic assessment and visualization of the relationship between CoQ and EF, facilitating more informed decision-making in quality management. Notably, it contrasts the traditional models with a novel approach that more accurately captures the uncertainty and correlation among key quality indicators, showcasing its potential for more refined decision-making in quality management.

Application of the framework illustrates its effectiveness in offering a nuanced understanding of the cost implications and effectiveness of various quality control strategies. This facilitates enhanced strategic decision-making, optimizing inspection processes and reducing external failures in high-volume production settings.

The study focuses on a single industry case study, limiting the generalizability of findings across different high-volume production contexts. Future research could explore the framework’s applicability in other sectors and refine the model based on additional empirical data.

The research introduces a versatile framework that navigates the unique challenges of high-volume manufacturing environments. Diverging from models optimized for low-volume settings, this approach provides a valuable tool for adapting inspection strategies to complex production demands, marking a significant contribution to quality management and control literature.

This chapter adopts a historiographical methodology, meticulously retracing the lineage of Augmented Reality (AR) from the 16th century and scrutinizing the conceptual genesis of Virtual Reality (VR) in the mid-20th century. It rigorously scrutinizes the fundamental principles and applications of AR and VR, extending the discourse to encompass the foundational tenets and ramifications of the burgeoning Metaverse. Thoroughly examining ethical considerations and challenges, there is an emphasis on perpetuating research, judicious implementation, and establishing ethical frameworks. Elucidating the profound ramifications of AR on sundry industries, the transformative potential of VR in crafting immersive environments, and the emergent interconnected virtual realm of the Metaverse, key principles such as spatial mapping, interaction modalities, and cross-platform interoperability are accentuated. Ethical challenges inherent in Metaverse development, notably digital identity, and privacy are identified. The narrative steadfastly underscores the significance of perpetuated research and ethical considerations in steering the evolutionary trajectory of avant-garde technologies. The findings hold far-reaching implications for diverse sectors, encompassing navigation, marketing, healthcare, architecture, education, and entertainment. The Metaverse’s potential to reconfigure digital experiences ubiquitously and its consequential impact on privacy and content moderation accentuate the exigency for circumspect consideration in development and implementation. This chapter fervently advocates for responsible usage and the facilitation of equitable access. This chapter contributes to the scholarly corpus by synthesizing historical perspectives, core principles, and ethical considerations across the domains of AR, VR, and the Metaverse. The unique emphasis on sustained research endeavors and the establishment of ethical frameworks adds distinctive insights, thereby guiding the sagacious evolution of these paradigm-shifting technologies.

In this chapter, the utilization of Artificial Intelligence (AI) and Machine Learning (ML) tools, improved by human expertise, offers a detailed investigation into their transformative effects on Corporate Social Responsibility (CSR), Environmental, Social, and Governance (ESG) standards, and sustainability. Initial insights and structural foundations were developed using AI, specifically utilizing ChatGPT-4, with the author significantly enhancing the content through in-depth academic research and analysis. This synergistic approach provides a holistic view of AI and ML’s role in promoting ethical business practices, improving sustainability reporting efficiency, and facilitating informed decision-making within CSR and ESG frameworks. Incorporating extensively verified and expanded real-world examples, the work delves into the practical applications of these technologies and addresses the ethical considerations they raise. This collaboration highlights the evolving role of AI in research and emphasizes the critical importance of integrating AI-generated insights with scholarly research to drive forward sustainable and socially responsible corporate strategies and policies.

The purpose of this study is to comprehensively explore the password manager adoption landscape, delving into crucial factors such as performance, trust, social influence, self-efficacy, risk perception, security concerns, enjoyment and facilitating conditions. It also aims to contribute meaningful insights to security product research and practice.

A survey was used to investigate the characteristics of adoption intention for password managers. In total, 156 participants from a public university located in the Midwest region of the USA voluntarily completed the survey. Partial least squares structural equation modeling was used to estimate and validate causal relationships and the proposed research model.

Through empirical validation, this study demonstrates that constructs such as social influence, web-specific self-efficacy and perceived risk directly impact trust in password managers. Facilitating conditions and perceived security controls are identified as direct influencers on performance expectancy, deviating from the pathways of the traditional framework. Moreover, the model introduces novel elements crucial for comprehending password manager adoption, including “web-specific self-efficacy” and “perceived security control.”

The paper systematically reviews existing research on password managers, shedding light on crucial factors significantly influencing adoption behavior. By introducing deviations from conventional frameworks and theories, the study emphasizes the innovative nature of its model. It also formulates strategies to catalyze wider adoption and promote effective design of password managers, increasing user engagement rates.

This paper aims to address the need to adopt circular economy models in the urban development and infrastructure of Gulf Cooperation Council (GCC) countries – Bahrain, Kuwait, Oman, Qatar, UAE and Saudi Arabia. The purpose is to provide insights into the progress, challenges and potential benefits of transitioning from a linear to a circular economic model in response to the environmental challenges posed by rapid economic development and population growth in the GCC region. The study emphasizes the relevance of this research in fostering economic diversification, mitigating ecological concerns and attracting sustainable investments.

The study adopts a qualitative approach to investigate the adoption of circular economy principles in each GCC country’s urban development and infrastructure. It details the specific strategies and initiatives undertaken by Bahrain, Kuwait, Oman, Qatar, UAE and Saudi Arabia. The research methodology includes a Systematic Literature Review (SLR), thematic, comparative and individual analysis of their goals, progress and the unique approaches employed. Additionally, a SWOT analysis is conducted to identify strengths, weaknesses, opportunities and threats associated with adopting circular economy models in the GCC region.

The case studies reveal each GCC country’s diverse approaches and progress in adopting circular economy models. Bahrain aims for carbon neutrality by 2060, Kuwait prioritizes sustainability in urban development, Oman focuses on waste reduction, Qatar integrates circular economy principles into its Vision 2030 initiative and Saudi Arabia explores closed-loop material flows. Whereas, the UAE focuses on infrastructure development with unique technological advancements in the near future. Despite common challenges such as traditional linear models and economic obstacles, the benefits of transitioning to circular economies in the GCC region are substantial. These include social, environmental and economic advantages, emphasizing sustainable growth, resource efficiency and enhanced environmental protection.

This paper contributes original insights into the adoption of circular economy models in the GCC region, providing a clear and succinct case for its value. The research underscores this transition’s economic, environmental and social benefits. It emphasizes the significance of sustainable resource management and economic opportunities while acknowledging challenges such as implementation obstacles and potential business impacts. The study invites reflection on future research steps, fostering a balanced and fair analysis of the value of the results. It positions the adoption of circular economy models as a crucial step toward achieving economic diversification, and environmental sustainability and attracting green investments in the GCC region.

This book chapter delves into the dynamic landscape of artificial intelligence (AI) integration within the higher education (HE) sector through a series of compelling case studies. Divided into two main themes, the chapter explores the innovative strides universities have made in adopting AI and the challenges that universities have encountered as they have attempted to harness the power of AI for the benefit of both students and academics. In the first part of the chapter, there will be an exploration of the pioneering initiatives undertaken by academic institutions, showcasing examples illustrating innovations in teaching and learning. From AI-driven personalised learning platforms to cutting-edge digital resources, these examples underscore the transformative potential of AI in enhancing educational experiences. Furthermore, the chapter examines how universities make use of AI to drive groundbreaking research. It explores the AI technologies used to advance scientific inquiry, streamline data analysis, and empower researchers in various disciplines. In the second part of the chapter, the focus will shift to the challenges and setbacks that universities have encountered along their journey in adopting AI. Drawing from real-world experiences, the examples in this chapter provide insights into the complexities and pitfalls of AI implementation in academia. Readers will gain valuable lessons from the institutions’ encounters with challenges, shedding light on the importance of ethical considerations, data privacy, and the need for a thoughtful approach to AI integration.

This study aims to analyze the emergence of a new structural configuration of globalization, with the 2008 global financial crisis serving as the first symptom of this change. By introducing the “Evolutionary Structural Triptych” (EST), this research seeks to understand the basic components of the new evolutionary trajectory of global capitalism post-2008. The study places emphasis on its interdependent and coevolving economic, political and technological dynamic facets.

This research introduces the EST framework, critically contrasting it with conventional understandings in international political economy (IPE) to provide a comprehensive and structured analysis of global developments after 2008. It traces the phases of global capitalism since Second World War, examines the central dynamic dimensions during each evolutionary phase, identifies the basic patterns and delves into the foundational elements of the emerging era of globalization.

The analysis reveals three key findings. First, the emerging restructured globalization indicates a need for a new balance in the contemporary world system; however, this balance cannot be achieved within the architecture of the old system. Second, the new era of globalization necessitates a re-equilibrated approach across different dimensions of geopolitical stability, economic development and innovation. This approach should emphasize sustainability, adaptability, resilience and inclusivity and lean toward responsible, open and organic innovation models for a revamped global structure. Third, while many current IPE theories tend to compartmentalize aspects of the new globalization, the EST advocates for a holistic perspective that integrates politics, economics and technology within the framework of global trends. This perspective bridges existing gaps and offers actionable insights for a dynamic and inclusive global future.

The paper presents the EST as a novel analytical instrument in the realm of the modern IPE. This tool uniquely places technology and innovation at the forefront, parallel to economic and political spheres, to comprehend the progression of globalization. In doing so, it highlights the intertwined relationship of these structural dimensions in shaping the future of the subject of the IPE.

This paper introduces a formal risk interdependency framework to model cascading effects in collaborative systems. By characterizing risk causal chains and propagation chains, the framework aims to provide decision-makers with a structured tool to systematically identify, analyze, and prevent cascading risks in interconnected networks.

The framework, named the danger-risk-consequence chain, defines core components – danger, stake, risk, condition, and consequence – alongside their causal and propagation relationships, which form the basis for risk characterization. The framework is applied through a use case in the construction supply chain to demonstrate its capacity to model cascading risks.

The framework uncovers risk propagation chains that lead to cascading effects and formalizes the state evolution of these effects within collaborative systems. Through the use case, it demonstrates practical value by enabling stakeholders to visualize interrelated risks, detect vulnerabilities early, and implement targeted mitigation measures to enhance resilience against cascading disruptions.

This study presents a novel approach to modeling cascading effects by integrating risk causality and propagation into a formalized framework. In contrast to previous research, which offers static risk definitions for risk characterization, this framework contributes to risk management theory by providing a structured method for understanding and modeling interdependencies.