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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.

The study aims to address the critical area of training and development within private educational small and medium-sized enterprises (SMEs) in Pakistan. It seeks to develop and standardize training and development process in private sector educational SMEs and establish a structured approach to training with the purpose of unlocking the full potential of the workforce, advancing educators’ professional growth and propelling organizational progress.

This study employs a meticulous three-phase approach. It begins with insightful interviews with school principals to investigate existing training practices. The subsequent phase involves formulating a comprehensive training and development policy, outlining purpose, scope, responsibilities, procedures and budget allocation. This policy undergoes participatory refinement to cater to specific SME needs. In the third phase, experimental design was adopted. Two groups, the experiment group and the control group, were formulated to check the effectiveness of proposed processes.

Rigorous statistical analysis, employing paired sample t-tests, unequivocally demonstrates a significant elevation in mean scores post-implementation of standardized training and development process. These findings affirm the efficacy of the policy in enhancing the effectiveness of training and development activities in private sector educational SMEs.

The research highlights profound implications. By establishing a structured approach to training and development, educational SMEs can not only advance educators’ professional growth but also propel organizational progress and enhance education quality. It will provide a structured and step-by-step process to boost the work quality of staff. The study emphasizes the need for consistent implementation.

This research marks a substantial stride in revolutionizing how human capital is cultivated in private sector educational SMEs. It positions them to exert a transformative impact on Pakistan’s educational landscape, furthering the journey toward excellence. The study suggests avenues for future research, including the adaptation of this model to diverse educational contexts and an assessment of its scalability.

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.

This chapter explores the role of artificial intelligence (AI), particularly its subfield of machine learning (ML) methods, as a core technology of the fintech revolution in the financial services industry. It simplifies some of the complex concepts related to AI by introducing the main ML paradigms and related techno-methodic aspects. This chapter uses real-world examples to illustrate how next-generation AI powered by ML is transforming the financial services industry. Next, in illustrating the risks associated with AI adoption, this chapter discusses the need for regulation to address the essential facets of AI governance, including transparency, accountability, ethics, and responsible use. Lastly, it looks at emerging regulatory approaches across leading global jurisdictions. The primary goal is to give readers an initial understanding of AI's profound impact on the financial sector.

The paper presents the findings of a study assessing the progress of implementing the European Green Deal (EGD) strategy goals across the EU-27 countries. The research aimed to evaluate individual countries' implementation of the strategy, considering its multidimensional nature.

A research methodology was devised, incorporating 18 indicators that characterize various dimensions pertinent to the EGD strategy. Evaluation of the strategy’s goals relied on the European Green Deal Index (EGDI), determined using the combined compromise solution (CoCoSo) method and a hybrid approach to weigh the indicators. Three analytical methods – criteria importance through intercriteria correlation (CRITIC), statistical variance, equal weights – and the Laplace criterion were utilized to ascertain the final weights of these indicators. The EGDI values for the years under scrutiny (2019–2021) served as the basis for assessing the EU-27 countries' progress towards the goals of the EGD.

The survey results indicate that from 2019 to 2021, the highest EGDI values – exceeding 2 – were achieved by Sweden, Denmark and the Netherlands. Austria also recorded very strong results. In contrast, the “new EU-13” countries generally exhibited lower levels of implementation of the EGD, as reflected in their EGDI values. Bulgaria and Cyprus, in particular, had the weakest results over the study period, with EGDI values below 1.5. Consequently, the “old EU-14” countries performed significantly better in implementing the EGD compared to the “new EU-13” countries. Among the “old EU-14” countries, Ireland recorded the weakest performance.

The originality of the research is highlighted by several key factors. Firstly, it addresses a significant research gap by assessing the initial positions and efforts of EU countries toward the EGD goals, providing a benchmark for effectiveness and strategy development. Secondly, it pioneers an authoritative and universal multi-criteria evaluation approach through the Green Deal Index (GDI), offering a robust methodology for assessing EGD implementation. Lastly, the study’s holistic approach incorporates energy, environmental and socioeconomic dimensions, significantly expanding knowledge and contributing to informed decision-making and policy formulation.

This research delves into the transformative potential of Generative Artificial Intelligence (AI), particularly ChatGPT, in enhancing higher education. It aims to explore how these advanced AI tools can be integrated into different educational settings to improve interactive learning experiences and student engagement, addressing the current challenges and opportunities in academic and administrative applications. Adopting a qualitative approach, the research utilizes the case vignette method to simulate realistic scenarios in various academic disciplines. It examines the potential applications and outcomes of AI in higher education, structured around key areas like intelligent tutoring systems, assessment, personalization and student profiling. This study employs the 4Cs framework (Critical Thinking, Creativity, Collaboration and Communication) to evaluate the effectiveness of AI integration in improving educational outcomes. The study reveals that ChatGPT can significantly enhance learning experiences by providing personalized tutoring, efficient assessment, tailored content and predictive insights into student performance. However, challenges such as ensuring content accuracy, ethical concerns and balancing AI with human interaction are also identified. Best practices for effectively integrating ChatGPT in higher education are proposed, emphasizing the complementarity of AI and human elements in education. This research contributes to the growing body of knowledge on AI in education by providing a nuanced understanding of generative AI's potential and challenges in higher education. It offers valuable insights and practical recommendations for educators and institutions, guiding the effective integration of AI technologies to enhance teaching and learning.

This study aims to explore the global issues of impulse buying, compulsive purchasing and materialism. It examines how materialism relates to self-esteem and the tendencies for impulsive and compulsive buying. In addition, the study delves into the impact of religiosity on self-esteem and materialistic values in an Islamic country.

Enumerators visited universities, distributing 415 questionnaires and receiving 397 in return. Due to the unavailability of a sample frame for the target population, the study used nonprobability sampling for statistical analysis, which included assessments of normality, reliability, validity and bootstrapping for the structural model, the researchers used Smart PLS.

The study confirmed 13 hypotheses while rejecting four. The unsupported hypotheses are: (i) materialism negatively impacts impulsive purchasing behavior, (ii) impulsive purchasing does not mediate the relationship between materialism and compulsive purchasing, (iii) materialism does not mediate the relationship between religiosity and impulsive purchasing and (iv) in an Islamic country, neither materialism nor impulsive purchasing significantly mediates the relationship between religiosity and compulsive purchasing.

This study was conducted in a city within a developing Islamic nation, focusing on college students. It suggests that future research could include more cities, a diverse population segments and multicultural perspectives. The research primarily examined the direct relationships between religiosity and factors such as self-esteem, materialism and impulsive purchasing. Future studies could explore religiosity as a mediating factor. This study highlights that materialism (M), impulsive buying (IB) and compulsive buying (CB) are not only closely interconnected but also adversely affect individual, family and societal well-being, raising global concerns. While occasional impulsive behavior is common among individuals in Islamic nations, repeated indulgences in the same behavior could lead to an obsession with excessive purchasing.

This study holds significant implications for consumers and retailers. Excessive and unnecessary spending can increase financial burden and adversely affect family welfare. Often, families and acquaintances inadvertently teach children to engage in extreme purchasing behaviors. To combat this, families and religious leaders should educate individuals about the detrimental effects of impulsive and compulsive purchasing. In addition, colleges and other institutions should organize seminars and workshops to address these issues. Retailers, whose sales largely depend on impulsive and compulsive consumers, should employ interpersonal influencers and brand advocates to connect with this customer segment effectively.

This study examined the relationship between religiosity, materialism, self-esteem and impulsive and compulsive purchasing behaviors. This study thoroughly tested 17 hypotheses, encompassing direct, mediating and multimediating relationships. The findings reveal that materialism’s impact on impulsive behavior is negligible compared to previous research, corroborating the findings presented in the cited literature.

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.