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The purpose of this study is to investigate the mediating impact of integrated reporting on the relationship between audit quality and market reactions in Africa using South Africa as a sample.

The study sample size consists of 119 firms listed on the Johannesburg Stock Exchange. The study was carried out for the period 2011–2019. Market reactions were proxy by share price and adjusted market returns. The authors controlled for the effects of market reactions by using other firm specifics like operating income, assets, leverage and return on assets and thereafter carried out robustness checks included under additional analysis.

Results from the study showed that integrated reporting partially mediates the relationship between audit quality and market reactions. Moreover, audit quality has a positive significant impact on market reactions in the form of the share price. The results were obtained in addition to a robustness check using adjusted market returns as a proxy for market reactions.

Regulators and standard setters in other countries should make integrated reporting mandatory. This study not only informs the public and investors about the organization’s business performance but also reveals auditor assurances that enchase market confidence in the company.

Exploring the mediating impact of integrated reporting on the relationship between audit quality and market reactions yields valuable insights. Integrated reporting, which combines financial and non-financial information, influences how investors perceive and react to audit quality. Understanding this interplay could shed light on the broader implications for corporate transparency and accountability.

The authors are the first to conduct such a study in an emerging economy. Hence, the authors used integrated reporting as a new variable in the study of audit quality and market reactions. Furthermore, the authors used adjusted market returns under robustness checks to check if audit quality has an impact on market reactions.

This systematic review of the current gender inequality issues in operations and supply chain management (OSCM) seeks to illuminate the multifaceted aspects of this issue and their various implications for the field.

Employing systematic literature review and Preferred Reporting Items for Systematic Literature Reviews and Meta-Analyses (PRISMA) methodologies, this research delves into an analysis of 238 journal articles spanning a 47-year period. The objective is to discern existing voids and put forth actionable suggestions that align with the United Nations’ Sustainable Development Goal Number 5 (SDG5) in the context of men and women, which pertains to realizing gender equality and empowering girls and women.

The results show a significant increase in published articles over the period. However, only five literature review articles were found that specifically address gender inequality in OSCM. The five common themes impacting gender inequality in this field are gender issues, mindset, transportation disparities, human resources and gender roles in OSCM, alongside sustainability, mobility and government policy intersections. The paper emphasizes the need for further research on these themes. It also suggests implications for educators, researchers, companies, OSCM departments and policymakers to achieve SDG5.

This study offers valuable insights by comprehensively reviewing and systematically analyzing the prevailing gender inequality issues within OSCM. It accentuates the significance of gender equality in OSCM, augmenting the burgeoning discourse and catalyzing concerted endeavors for gender equality.

The world population is getting older and housing decisions matter to the security of retirement life and well-being. However, senior housing and financing decisions are largely overlooked in the literature. This study aims to provide a comprehensive overview of the senior housing and financing decisions in the USA.

Using 2021 American Housing Survey data and ordinary least squares estimates, this paper studies senior housing and financing decisions in the 15 most populous US metropolitan areas. Multiple regressions are used to analyze the whole sample as well as various subsamples.

This paper finds strong evidence that seniors are more likely to own a house with a higher market value compared with nonseniors. More specifically, although race and gender do not matter in this relationship, it is less pronounced among those with higher education. Also, seniors, especially white senior homeowners, are more likely to have a lower mortgage debt burden due to a higher upfront down payment than nonseniors. Last, seniors are more likely to refinance their homes and receive cash than nonseniors.

Constrained by the data limitations, this study specifically focuses on seniors’ housing and mortgage decisions. Future research could involve exploring seniors’ mortgage decisions by considering factors such as mortgage loan terms, borrower credentials and the evolving landscape of the senior housing market, among other aspects.

The findings would help policymakers and contractors in the construction industry better understand the uniqueness of challenges in the senior housing market and develop effective housing policies and programs that cater to the needs of the elderly. A comprehensive understanding of the senior housing market would also help seniors make informed purchase and financing decisions.

The authors propose providing financial education to the elderly, particularly those of disadvantaged status, to improve their expertise and bargaining skills in the mortgage loan application process.

This paper contributes to understanding the dynamic senior housing market, which encounters challenges and opportunities associated with the aging population. The study fills the gap of limited research regarding seniors’ housing decision and their financing choices in the USA and would help policymakers and contractors in the construction industry develop effective housing policies and programs that cater to the needs of the elderly.

Our study was designed to investigate the longitudinal trajectories of student leader development capacities in a sample of students enrolled in multiple leadership-focused courses across several semesters. Our goal was to assess the degree to which course enrollment was associated with growth over the time that students engage as undergraduates in academic leadership programs, and if so, to assess the shape and speed of capacity change.

We utilized a multilevel intra-individual modeling approach assessing students’ motivation to lead, leader self-efficacy, and leadership skills across multiple data collection points for students in a campus major or minor focused on leadership studies. We compared an unconditional model, a fixed effect model, a random intercept model, a random slope model, and a random slope and intercept model to determine the shape of score trajectories. Our approach was not to collect traditional pre-test and post-test data – choosing to collect data only at the beginning of each semester – to reduce time cues typically inherent within pre-test and post-test collections.

Our results strongly suggested that individual students differ greatly in the degree to which they report the capacity to lead when initially enrolling in their first class. Surprisingly, the various models were unable to predict a pattern of longitudinal leader development through repeated course enrollment in our sample.

Our investigation employed statistical methods that are not often utilized in leadership education quantitative research, and also included a data collection effort designed to avoid a linear pre-test/post-test score comparison.

This paper tries to retrospect the mounting application of machine learning (ML) and artificial intelligence (AI) in the human resource management area. The document applies bibliometric analysis and uses relational techniques to explore dimensions of documents in the field. The results highlight publication trends, most impactful authors, countries and institutes in the research area. The science mapping along with co-citation and bibliometric coupling analysis revealed major developments in the field. The thematic mapping and trend analysis highlighted the past and emerging trends towards significant and impactful research in the areas of robotics, big data, AI and data analytics. This paper sets the base for future researchers by coordinating and combining various past researches to help in understanding the evolution of ML and AI in human resource management and expansion of knowledgebase.

The slow adoption of unmanned aerial vehicles (UAVs) in the construction industry, particularly in developing countries like Nigeria, underscores the need for a deeper understanding of the critical factors influencing their adoption. This study aims to identify these factors using the Technology-Organization-Environment (TOE) framework and address uncertainties in their prioritization through Fuzzy Synthetic Evaluation (FSE). The utility of this approach lies in its ability to provide construction organizations with actionable insights to enhance operational efficiency and competitiveness through effective UAV adoption.

A post-positivist philosophical stance was adopted, wherein quantitative data were gathered from construction professionals in Nigeria via a questionnaire survey. The collected data were analyzed using the Cronbach alpha test as a measure of internal consistency and the FSE test to synthesize critical drivers for the adoption of UAVs.

The study found that drivers related to technology and organization are the most critical drivers. This implies that variables related to technology and organization warrant a higher level of focus if UAVs are to continue gaining popularity within the construction industry. Additionally, this study identified that logistic management, construction monitoring and site surveying represent the most critical areas of UAV application within the construction industry.

The emphasis on technology and organizational drivers as critical factors suggests that construction companies should prioritize investments in technology infrastructure and cultivate an organizational culture that embraces innovation. This may involve providing training to construction professionals to enhance their technological skills and fostering a leadership culture that champions technology adoption.

This study introduces novelty by applying the TOE framework, which has received limited attention in UAV adoption studies within construction. Additionally, the use of FSE addresses uncertainties in prioritizing critical drivers, particularly relevant in developing countries facing unique technological challenges. By assigning priority to these factors, this research lays the groundwork for a more informed and strategic approach to UAV adoption.