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This paper covers the development of a novel defect model for concrete highway bridges. The proposed defect model is intended to facilitate the identification of bridge’s condition information (i.e. defects), improve the efficiency and accuracy of bridge inspections by supporting practitioners and even machines with digitalised expert knowledge, and ultimately automate the process.

The research design consists of three major phases so as to (1) categorise common defect with regard to physical entities (i.e. bridge element), (2) establish internal relationships among those defects and (3) relate defects to their properties and potential causes. A mixed-method research approach, which includes a comprehensive literature review, focus groups and case studies, was employed to develop and validate the proposed defect model.

The data collected through the literature and focus groups were analysed and knowledge were extracted to form the novel defect model. The defect model was then validated and further calibrated through case study. Inspection reports of nearly 300 bridges in China were collected and analysed. The study uncovered the relationships between defects and a variety of inspection-related elements and represented in the form of an accessible, digitalised and user-friendly knowledge model.

The contribution of this paper is the development of a defect model that can assist inexperienced practitioners and even machines in the near future to conduct inspection tasks. For one, the proposed defect model can standardise the data collection process of bridge inspection, including the identification of defects and documentation of their vital properties, paving the path for the automation in subsequent stages (e.g. condition evaluation). For another, by retrieving rich experience and expert knowledge which have long been reserved and inherited in the industrial sector, the inspection efficiency and accuracy can be considerably improved.

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.