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The aim of this study is to investigate the influence of Project Management Office (PMO) functions on project performance in businesses in Lower Middle-Income Countries (LMIC) using Partial Least Square–Structural Equation Modelling (PLS–SEM).

Utilizing close-ended questionnaires in a cross-sectional survey, 256 project professionals from 10 business sectors in Ghana views were elicited. The questions were developed through a comprehensive literature review and involved 27 PMO functional measures grouped into 6 and 19 project performance measures grouped into 6. Data collected was then analysed using the PLS–SEM to validate the hypothetical relationship.

The PLS–SEM model supported 13 (t > 1.65) out of 36 hypotheses investigating the relationship between PMO functions and project performance. Variations in the PMO functions moderately (R2 = 0.34) explained the performance of projects. The aggregate activities of the PMO had the highest significant influence on environmental performance (R2 = 0.467). The topmost PMO function was identified as monitoring and controlling project performance, and it was significantly associated with cost (ß = 0.265, p < 0.05), quality (ß = 0.291, p < 0.05) and project scope (ß = 0.265 p < 0.05) performance.

This research has brought more illumination to the functions of PMOs and its influence on project performance. The results suggest that PMO activities, when tailored to the business context, can significantly change project performance variables.

Most research on PMO and project performance has been limited to developed countries or a single sector. This study uniquely expands the business sectors and focuses on LMICs.

Organic coatings are widely used for protecting metal equipment and structures from corrosion. Accurate detection and evaluation of the protective performance and service life of coatings are of great importance. This paper aims to review the research progress on performance evaluation and lifetime prediction of organic coatings.

First, the failure forms and aging testing methods of organic coatings are briefly introduced. Then, the technical status and the progress in the detection and evaluation of coating protective performance and the prediction of service life are mainly reviewed.

There are some key challenges and difficulties in this field, which are described in the end.

The progress is summarized from a variety of technical perspectives. Performance evaluation and lifetime prediction include both single-parameter and multi-parameter methods.

This study proposes an integrated Machine Learning and simulated framework for a personalized learning system. This framework aims to improve the integrity of the provided tasks, adapt to each student individually and ultimately enhance students' academic performance.

This methodology comprises two components. (1) A simulation-based system that utilizes reinforcement algorithms to assign additional questions to students who do not reach pass grade thresholds. (2) A Machine Learning system that uses the data from the system to identify the drivers of passing or failing and predict the likelihood of each student passing or failing based on their engagement with the simulated system.

The results of this study offer preliminary evidence of the effectiveness of the proposed simulation system and indicate that such a system has the potential to foster improvements in learning outcomes.

As with all empirical studies, this research has limitations. A simulation study is an abstraction of reality and may not be completely accurate. Student performance in real-world environments may be higher than estimated in this simulation, reducing the required teacher support.

The developed personalized learning (PL) system demonstrates a strong foundation for improving students' performance, particularly within a blended learning context. The findings indicate that simulated performance using the system exhibited improvement when individual students experienced higher learning benefits tailored to their needs.

The research offers evidence of the effectiveness of personalized learning systems and highlights their capacity to drive improvements in education. The proposed system holds the potential to enhance learning outcomes by tailoring tasks to meet the unique needs of each student.

This study contributes to the growing literature on personalized learning, emphasizing the importance of leveraging machine learning in educational technologies to enable precise predictions of student performance.

This paper aims to explore the effect of female’s presence in corporate governance structures to reduce agency conflicts, using a quantile regression approach.

The research investigates the relationship between company performance and boardroom gender diversity using quantile regression methods. The study uses annual data of 111 companies listed on the Johannesburg Stock Exchange from 2010 to 2020.

The study reveals that women on the board impact firm return on assets and enterprise value, varying across performance distribution. This contrasts fixed effect findings but aligns with two-stage least squares. However, quantile regression indicates that female executives and independent non-executive directors have notably negative impacts in high and low-performing companies, highlighting non-uniformity in the board gender diversity effect compared with previous assumptions.

The empirical findings suggest that companies with no women directors on the board are generally more likely to experience a decrease in performance and enterprise value relative to companies with women directors on the board. As recommended through the King Code of Corporate Governance, it is thus valuable to companies to ensure gender diversity on the board of directors.

The research confirms through rigorous statistical analyses that corporate governance policies, principles and guidelines should include gender diversity as a requirement for a board of directors.

Several studies have examined the relationship between spin-off announcements and stock performance. However, a comparison of the announcement effect of different schemes of spin-offs remains relatively underexplored in the literature. This study aims to find the differential impact of pure scheme and composite schemes of spin-offs on parent company stock performance. A pure scheme includes only the separation of business into independent companies, while a composite scheme includes a simultaneous merger of one of the companies with another company along with separation.

A total of 109 pure and 51 composite spin-off announcements made by Indian listed companies from 2010 to 2023 are examined using event study methodology. The cross-sectional t-test is used to measure the significance of abnormal returns. The t-test for two sample means (right-tailed) is incorporated to test the significance of variations in the stock returns of pure and composite schemes of spin-off announcements. Cross-sectional regression is also done to evaluate the impact of the type of scheme on the spin-off return.

The study found a cumulative average abnormal return of −1.06% for the pure spin-off and 8.27% for the composite spin-off over a 41-day event window. The univariate analysis revealed that the composite scheme generates a significantly higher cumulative average abnormal return than the pure scheme. Regression analysis also confirmed that the composite scheme significantly positively impacts the stock return. It can be concluded that investors favour the composite scheme, expecting that it will deliver a better strategic fit and generate synergy.

This paper makes a valuable contribution to the existing literature on corporate spin-offs. The study by analysing and comparing how the spin-off and merger combination differently affects the stock performance, helps the investor who wants to capitalize on the market imperfections and the managers to make complex business decisions.

The present study examines the interplay between age, marital status, alpha female status and various adaptive performance dimensions among a cohort of 380 female professionals.

This study adopts a positivist approach to collect and analyse the data, utilizing appropriate statistical techniques to explore the relationships between the variables of interest.

The study elucidates the significant role of alpha female status in predicting adaptive performance. It finds that alpha females possess distinct competencies, particularly in learning and training, indicative of proactive behaviour and self-efficacy. While older participants tend to demonstrate higher performance levels, the study reveals no significant correlation between age and alpha female status, suggesting that leadership traits may develop independently of age. Furthermore, marital status exerts a modest influence on adaptive performance. The interplay of age and marital status significantly affects adaptive performance, potentially due to the Cumulative Advantage Paradigm, which is the accumulation of advantages or disadvantages throughout an individual's life course.

This study contributes to the existing literature by providing a nuanced understanding of how demographic factors converge to influence adaptive performance in professional settings. It highlights the importance of recognising and nurturing alpha females in organizations and considering the interactions between age and marital status when designing career development programmes and support systems.

This chapter discusses how the real options theory can be useful for understanding the adoption of human resources management (HRM) practices. The authors review how the real options theory has provided insights into the processes through which firms manage uncertainties involved in the adoption of HRM practices. The authors offer propositions for future HRM research from the real options perspective. The authors contend that analyzing HRM practice adoptions through the lens of real options theory can enhance our understanding of the mechanisms through which firms choose which HRM practices to adopt and how they adjust the timing, scale, and methods of investment in these practices. Specifically, the authors suggest that differences in information relevant to valuation of HRM options are the source of distinct choices of HRM options across firms. Finally, the authors propose advancing knowledge on HRM practice adoptions by using a portfolio of options approach, as well as considering factors like competitors, path dependence, and switching options.

Climate change significantly impacts global temperatures, posing challenges to various sectors, including aviation. The purpose of this study is to assess the impact of climate change on aircraft engine performance during different flight phases (take-off and cruise) and the environmental consequences.

This study examines the effects of rising temperatures on aircraft engine performance using real-time data from a Boeing 787-8 equipped with GEnx-1B engines, which are collected via Flight Data Recorder of the engines and were analyzed for the take-off and cruise phases on the ground. Exhaust gas temperature (EGT), fuel flow and take-off weights were evaluated.

The analysis revealed a significant increase in EGT at the cruising altitude of 38,000 ft during the summer months compared to expected standard atmospheric values. This increase, averaging over 200 °C, is attributed to global warming. Such elevated temperatures are likely to accelerate the degradation of turbine components, resulting in increased fuel consumption: higher EGT signifies inefficient engine operation, resulting in more fuel burned per unit thrust; early engine aging: elevated temperatures accelerate wear and tear on turbine components, potentially reducing engine lifespan and increasing maintenance costs and enhanced atmospheric pollution: incomplete combustion at high EGTs generates additional emissions, contributing to local air quality concerns.

The research findings have practical implications for understanding the potential operational challenges and environmental impacts of climate change on aircraft engine performance. This lets us explore mitigation strategies and adapt operational procedures to ensure sustainable regional aviation practices.

This research enhances environmental consequences by assessing the impact of climate change on aircraft performance.

Efficiency standards, similar to industrial measures like overall equipment effectiveness (OEE), are being used in healthcare systems more and more. Performance indicator models applied to machines assume a constant completion time. However, for human resources, the completion time of a task may vary depending on the stress experienced. This study seeks to bridge this gap by integrating the human behavior of the physician into the performance evaluation.

The paper presents a new algorithm called PerfoBalance that is intended to distribute waiting-patient values among doctors. By maximizing each physician’s stress zones, this method helps to improve their performance as a whole. A thorough case study with medical professionals is carried out to confirm the effectiveness of the suggested methodology. The PerfoBalance algorithm is used in a variety of contexts to divide waiting-patient values among doctors and optimize stress zones.

Experimental results demonstrate a significant improvement in physician efficiency when implementing the PerfoBalance algorithm. The algorithm strategically selects stress zones that contribute to higher performance rates for physicians by optimizing waiting-patient values.

By addressing the undervaluation of human performance difficulties in current efficiency models used in the healthcare industry, this research constitutes a significant contribution to the field. With its launch, the PerfoBalance algorithm offers a fresh viewpoint on waiting-patient value allocation and stress zone management in healthcare settings, hence representing a powerful method for increasing physician productivity.

Considering the standards developed by the Sustainability Accounting Standards Board (SASB), this study aims to examine whether the link between material sustainability and financial performance depends on the extent to which the company is oriented toward stakeholders.

To test the predictions, 13,942 firm-year observations from 43 different countries are used, covering the period from 2010 to 2019. Using a hand-mapping approach to match the indicators suggested by the SASB with those of the ASSET4, the authors realize that there are 170 material sustainability indicators among 466 indicators of the ASSET4. The authors use three different methods to verify if the materiality matters, including the alphas obtained from the Fama and French factor models, comparing the average abnormal returns of the portfolios and the bootstrapped Cramer technique.

The findings show that companies investing in material sustainability activities perform better than those investing in immaterial activities. Also, consistent with the theoretical foundations, the authors find that the effect of investing in material sustainability activities is more pronounced in stakeholder-oriented countries than that in shareholder-oriented countries. The results are robust to a battery of sensitivity tests.

Owing to COVID-19 in late 2019, data from 2020 to 2022 have not been used to obtain reliable results.

The results obtained in the current research provide valuable guidance for investors to make investments considering the degree of materiality of sustainability activities in different industries. It also helps managers to increase the company’s financial performance, make efficient decisions related to investment in sustainability activities and find investment strategies on the material sustainability issues in their industries.

This study provides a clearer understanding of investment in sustainability activities in different industries by separating material and immaterial sustainability activities in stakeholder and shareholder-oriented countries, and the results obtained can change the perspective of investors and company managers regarding investing in such activities in different countries. Investing in more materiality sustainability activities than the immateriality dimension can be new opportunities for companies to achieve predetermined goals, help retain and attract business partners or be a source of innovation for new product lines or services. Internal morale and employee engagement may increase while increasing productivity and firm performance. This discussion opens the way for future research.

This study provides insight into the effect of investing in material and immaterial sustainability activities in different industries on the company’s performance in shareholder and stakeholder-oriented countries.