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The purpose of this study was to examine the moderating role of institutional ownership on the relationship between board gender diversity and earnings management (EM) among listed firms in East African Community (EAC) partner states.

The study used a sample of 71 firms listed in the EAC partner states over 2011–2020. Data were handpicked from the individual firm's audited annual financial reports. Based on the results of the Hausman test, the study used the results of the fixed-effect regression model to test the hypotheses. To test the robustness of the results, the study employed an alternative measure of EM and two additional econometric techniques, including the pooled ordinary least squares (OLS) and the system generalized method of moments (GMM).

The empirical findings revealed that female directors improve the board's effectiveness in monitoring managerial roles. Specifically, the results showed a significantly negative relationship between the proportion of women in the corporate board and EM (as measured by discretionary accruals (DAs)). The findings further revealed an inverse relationship between the proportion of institutional ownership and EM. Finally, the results further demonstrated that institutional ownership enhances the role of board gender diversity in mitigating EM among listed firms in the EAC.

The findings of this study may be useful to managers, investors and regulators in assessing the role of institutional ownership and women's participation on corporate boards as a strategy for alleviating unethical manipulation of earnings.

The findings of this study contribute to the growing concern on gender inequality, especially the marginalization of women from the paid labor force and decision-making. The findings highlight the importance of having more women in the corporate board since this may help in mitigating corporate fraud. Similarly, the findings highlight the importance of institutional ownership as a corporate governance (CG) tool.

Previous studies have reported mixed empirical results on whether board gender diversity mitigates EM. To the best of the author's knowledge, this is the first paper to fill the existing gap by exploring whether institutional ownership moderates the relationship between board gender diversity and EM among listed firms in the EAC.

This paper aims to examine the causation linking financial technology to economic growth in the East African Community states from 1997 to 2019.

Autoregressive distributed lag is used. Gross domestic product per capita proxies economic growth, automated teller machines, point of sale, debit card ownership and mobile banking measure financial technology.

The results unveil a significant relationship between financial technology and economic growth. The findings show bidirectional causality between automated teller machine and economic growth, with unidirectional causation from economic growth to point of sales and internet banking, mobile banking and government effectiveness to economic growth. The error correction term is negatively significant, demonstrating a long-term convergence between Fintech measures and economic growth.

The governments should effectively enact and implement policies that protect investments in financial technologies to boost economic growth in the East African Community countries. The government should reduce taxes on financial technology equipment and related services. The use of automated teller machine, debit card ownership and internet banking should be encouraged through cashless transactions. Financial institutions should adopt cashless operation policies to encourage the use of financial technologies.

Research results on the bond between financial technology and economic growth are not conclusive. These studies demonstrate that technological innovations are double edged-swords, with both positive and negative sides. The results are conflicting; some reveal positive relationships, while others show negative links. Hence, research is required to fill the lacuna.

Earned value management (EVM)–based models for estimating project actual duration (AD) and cost at completion using various methods are continuously developed to improve the accuracy and actualization of predicted values. This study primarily aimed to examine natural gradient boosting (NGBoost-2020) with the classification and regression trees (CART) base model (base learner). To the best of the authors' knowledge, this concept has never been applied to EVM AD forecasting problem. Consequently, the authors compared this method to the single K-nearest neighbor (KNN) method, the ensemble method of extreme gradient boosting (XGBoost-2016) with the CART base model and the optimal equation of EVM, the earned schedule (ES) equation with the performance factor equal to 1 (ES1). The paper also sought to determine the extent to which the World Bank's two legal factors affect countries and how the two legal causes of delay (related to institutional flaws) influence AD prediction models.

In this paper, data from 30 construction projects of various building types in Iran, Pakistan, India, Turkey, Malaysia and Nigeria (due to the high number of delayed projects and the detrimental effects of these delays in these countries) were used to develop three models. The target variable of the models was a dimensionless output, the ratio of estimated duration to completion (ETC(t)) to planned duration (PD). Furthermore, 426 tracking periods were used to build the three models, with 353 samples and 23 projects in the training set, 73 patterns (17% of the total) and six projects (21% of the total) in the testing set. Furthermore, 17 dimensionless input variables were used, including ten variables based on the main variables and performance indices of EVM and several other variables detailed in the study. The three models were subsequently created using Python and several GitHub-hosted codes.

For the testing set of the optimal model (NGBoost), the better percentage mean (better%) of the prediction error (based on projects with a lower error percentage) of the NGBoost compared to two KNN and ES1 single models, as well as the total mean absolute percentage error (MAPE) and mean lags (MeLa) (indicating model stability) were 100, 83.33, 5.62 and 3.17%, respectively. Notably, the total MAPE and MeLa for the NGBoost model testing set, which had ten EVM-based input variables, were 6.74 and 5.20%, respectively. The ensemble artificial intelligence (AI) models exhibited a much lower MAPE than ES1. Additionally, ES1 was less stable in prediction than NGBoost. The possibility of excessive and unusual MAPE and MeLa values occurred only in the two single models. However, on some data sets, ES1 outperformed AI models. NGBoost also outperformed other models, especially single models for most developing countries, and was more accurate than previously presented optimized models. In addition, sensitivity analysis was conducted on the NGBoost predicted outputs of 30 projects using the SHapley Additive exPlanations (SHAP) method. All variables demonstrated an effect on ETC(t)/PD. The results revealed that the most influential input variables in order of importance were actual time (AT) to PD, regulatory quality (RQ), earned duration (ED) to PD, schedule cost index (SCI), planned complete percentage, rule of law (RL), actual complete percentage (ACP) and ETC(t) of the ES optimal equation to PD. The probabilistic hybrid model was selected based on the outputs predicted by the NGBoost and XGBoost models and the MAPE values from three AI models. The 95% prediction interval of the NGBoost–XGBoost model revealed that 96.10 and 98.60% of the actual output values of the testing and training sets are within this interval, respectively.

Due to the use of projects performed in different countries, it was not possible to distribute the questionnaire to the managers and stakeholders of 30 projects in six developing countries. Due to the low number of EVM-based projects in various references, it was unfeasible to utilize other types of projects. Future prospects include evaluating the accuracy and stability of NGBoost for timely and non-fluctuating projects (mostly in developed countries), considering a greater number of legal/institutional variables as input, using legal/institutional/internal/inflation inputs for complex projects with extremely high uncertainty (such as bridge and road construction) and integrating these inputs and NGBoost with new technologies (such as blockchain, radio frequency identification (RFID) systems, building information modeling (BIM) and Internet of things (IoT)).

The legal/intuitive recommendations made to governments are strict control of prices, adequate supervision, removal of additional rules, removal of unfair regulations, clarification of the future trend of a law change, strict monitoring of property rights, simplification of the processes for obtaining permits and elimination of unnecessary changes particularly in developing countries and at the onset of irregular projects with limited information and numerous uncertainties. Furthermore, the managers and stakeholders of this group of projects were informed of the significance of seven construction variables (institutional/legal external risks, internal factors and inflation) at an early stage, using time series (dynamic) models to predict AD, accurate calculation of progress percentage variables, the effectiveness of building type in non-residential projects, regular updating inflation during implementation, effectiveness of employer type in the early stage of public projects in addition to the late stage of private projects, and allocating reserve duration (buffer) in order to respond to institutional/legal risks.

Ensemble methods were optimized in 70% of references. To the authors' knowledge, NGBoost from the set of ensemble methods was not used to estimate construction project duration and delays. NGBoost is an effective method for considering uncertainties in irregular projects and is often implemented in developing countries. Furthermore, AD estimation models do fail to incorporate RQ and RL from the World Bank's worldwide governance indicators (WGI) as risk-based inputs. In addition, the various WGI, EVM and inflation variables are not combined with substantial degrees of delay institutional risks as inputs. Consequently, due to the existence of critical and complex risks in different countries, it is vital to consider legal and institutional factors. This is especially recommended if an in-depth, accurate and reality-based method like SHAP is used for analysis.

This study aims to review earned value management (EVM)-relative methods, including the original EVM, earned schedule method (ESM) and earned duration management (EDM(t)). This study then proposes a general implementation procedure and some basic principles for the selection of EVM-relative methods.

After completing an intensive literature review, this study conducts a case study to examine the forecasting performance of project duration using the EVM, ESM and EDM(t) methods.

When the project is expected to finish on time, ESM with a performance factor equal to 1 is the recommended method. EDM(t) would be the most reliable method during a project's entire lifetime if EDM(t) is expected to be delayed based on past experience.

As this research conducts a case study with only one building construction project, the results might not hold true for all types of construction projects.

EVM, ESM and EDM(t) are simple and data-accessible methods. With the help of a general implementation procedure, applying all three methods would be better. The power of the three methods is definitely larger than that of choosing only one for complex construction projects.

Previous studies have discussed the advantages and disadvantages of EVM, ESM and EDM(t). This study amends the available outcomes. Thus, for schedulers or researchers interested in implementing EVM, ESM and EDM(t), this study can provide more constructive instructions.

The study explores how the intention to export affects financing and non-financing variables for small and medium-sized enterprises (SMEs) in a low-income country (LIC). The objectives of this study are (1) to discern between regional and global exporting and (2) to evaluate its policymaking implications.

Primary survey data were collected from 330 Rwandan SMEs and were analysed using ordered logistic models as an application of the expectation-maximisation iterating algorithm, which was tested for robustness using a sampling model variation.

The results show that alternative sources of finance are the predominant choice to finance the intention to export within and outside Africa. As the scope of export intentions broadened from regional to global, there was a shift in preferences from less formal to more formal lending technologies, moving from methods like factoring to lines of credit. Moreover, reliance on bank officers became more significant, with increasing marginal effects. Finally, the study determined that government financing schemes were not relevant for SMEs pursuing either regional or global exporting.

Whilst alternative sources of finance predominate the export intentions of Rwandan SMEs, establishing a robust banking relationship becomes crucial for global exporting. Despite this implication, the intention to export should prompt more transparent communication regarding government financial support programmes. There is an opportunity for increased usage of relationship lending to customise support for SMEs involved in exporting, benefiting both the private and public sectors.

This study accentuates how export distance alters SME financing priorities. The results also contribute to understanding how the value of relationship lending changes when less familiar markets (i.e. global exporting) are the objective. Moreover, the study offers a new perspective on how institutional voids affect entrepreneurial financing decisions in LICs.

Women cross-border traders face impediments in their entrepreneurial work from time-to-time. To overcome these impediments, females need to take on self-concept (self-esteem, self-confidence, social roles) mediated by self-organization (adaptability, interaction, team working) in order to thrive in cross-border trading (CBT), using evidence from Uganda. So, in this paper the authors explain the behavior of a female who succeeds in CBT with interest of scaling it up to empower more female entrepreneurs.

This study is a correlational and cross-sectional type. A questionnaire survey of 288 females was used. The data collected were analyzed through SPSS.

The results reveal that self-concept, mediated by self-organization, controlled by tenure in business and the age of a female in CBT significantly influences CBT behavior among females in Uganda.

This study focused on females who are involved in CBT in Uganda. Therefore, it is likely that the results may not be generalized to other settings. The results show that for females to succeed in CBT, self-concept and self-organization affect CBT behavior once they are controlled by tenure in business and the age of a female in CBT at more than 30 years of age and longer than 5 years.

This study provides initial evidence that self-concept, mediated by self-organization, controlled by tenure in business and age of a CBT directly affects CBT behavior, using evidence from an African developing country – Uganda.

This paper examines how board structure influences real earnings management and the interaction effect of CEO narcissism on board structure-real earnings management relationship.

The authors used panel data derived from secondary sources from publicly listed firms in Kenya during 2002–2017. Hierarchical regression analysis was used to test the hypotheses.

The results indicate that board independence, board tenure and size have significant negative effect on real earnings management, while CEO duality positively affects real earnings management. Further, the interaction results show that CEO narcissism moderates the relationship between CEO duality and real earnings management.

The results suggest that real earnings management reduces when boards are independent, large and comprising of long-tenured members. However, when the CEO plays dual role of a chairman, real earnings management increases. The authors also find that when CEOs are narcissists, the monitoring role of the board is compromised.

The study adds value to the understanding of how board structure and CEO narcissism influence the monitoring role of the board among firms listed at Nairobi Securities Exchange.

Voluntary participation (VP) has been identified as one of the characterizing features of mediation. This study aims to examine the value of VP in construction dispute mediation from two perspectives. Firstly, is VP a prerequisite of successful construction mediation. Secondly, does power asymmetry (PA) between the contracting parties marginalize the value of VP in fostering the use of mediation to resolve construction disputes.

Constructs of VP, PA and prerequisites of successful mediation were first developed. Principal component factor analysis was performed on data collected from the construction dispute resolution community to explore the underlying structure of the constructs. The relationships between the constructs were tested by structural equation modelling.

VP is found to be an important attribute of successful mediation. PA is also found to be inherent in construction contracting. This study identified three forms of PA: Resource, Information and Expectation. Moreover, this study found no conclusive empirical evidence to support that PA would marginalize the value of VP in fostering an attempt to construction dispute mediation. It is suggested that VP shall remain one of characterizing features of mediation.

The users, mediators and the judiciary should be aware of the importance of VP in mediation, irrespective of the use of mediation is contractual or court-encouraged. Although the presence of PA between the disputing parties, through participating voluntarily and ensuring the mediation process is flexible and fair, the chance of achieving a settlement would be enhanced.

VP has been viewed as one of the fundamentals of mediation. This study empirically supported this design concept. Furthermore, PA in construction contracting can be expressed as disparities in resource, information and expectation. Their existence presents no significant barrier to attempt of mediation. The flexible approach of mediation has been instrumental in overcoming the paradox between VP and PA. This study affirms the positive value of VP in fostering the use of construction dispute mediation.

This paper examines the post-COVID-19 travel intentions to Kenya among Hong Kong outbound travelers using the theory of planned behavior (TPB) over three different time horizons of 1, 5, and 10 years.

An extension was made by including two new constructs of perceived destination image and travel constraints. A cross-sectional sample of Hongkongers was surveyed. Data were collected using a self-administrated bilingual (English and Chinese) online survey. Exploratory factor analysis, linear regression and mediation analysis were conducted to test the research model.

The findings from 216 Hongkongers reveal that different combinations of the four constructs, namely, perceived behavioral control, attitude, subjective norms, and destination image, share a positive effect on individuals' travel intention to Kenya over the three different time horizons. Travel constraints act as a significant negative mediator on the four constructs in predicting travel intention to Kenya among Hongkongers.

The results provide useful insight to Kenya's destination marketing organization (DMO) and Hong Kong outbound travel agencies to integrate prominent elements into marketing strategies to arouse travel intention and expand their business prospects, which will also accelerate tourism recovery in the post-pandemic era.

By integrating two extended variables into the TPB model, this study makes a contribution by overcoming the deficiency of the original theory.

The objective of this study is to examine the various factors that exert an influence on the green economy. This study also investigates the impact of foreign direct investment (FDI) on the Malaysian economy, specifically focusing on its position as a mediator. This research also examines the correlation between FDI and its influence on the contemporary green economy.

The authors employed quantitative methodologies and a self-administered survey to evaluate data and derive a definitive conclusion. The result was constructed using SPSS and SEM-PLS as the analytical software.

The study reveals that technological advancement, investment country and government policy significantly and positively affect the green economy, catalyse SDG goals and restructure the economy in better shape.

The current empirical research bridges the research gap in the context of technology advancement in government policy from emerging economies by exploring important factors, proposing their impact on the performance of the green economy, and empirically testing those hypothesized relationships. This study deciphers that FDI influences the green economy, where the investment country plays a significant role. Also, for a graphical presentation of this abstract, see the online appendix.