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Official development assistance (ODA) education projects have played a crucial role in improving education and training fields in developing countries, but are often facing several considerable challenges (e.g. long implementation time). Thus, this study aims to identify critical success factors (CSFs) in ODA education projects and investigate the influences of CSFs on ODA project performance measured by 11 nonprofit outcomes (NPOs).

A comprehensive literature review and expert interviews were conducted to compile a list of 35 potential success factors for ODA education projects. Using a survey questionnaire, 143 valid responses were collected from practitioners joining ODA projects in Vietnam. Various statistical methods (e.g. mean score method, Spearman rank correlation test, analysis of variance test, factor analysis and regression analysis) were used to analyze the collected data.

This research identified seven CSFs for ODA education projects in Vietnam: comprehensive project management competency (C1), clarity and compliance in project execution (C2), transparency and committed funding (C3), external context conditions (C4), well-controlled design and project management procedures (C5), preparations in equipment and complexity insight (C6) and punctual site delivery (C7). Furthermore, the results of regression analysis indicated that comprehensive project management competency (C1) and transparency and committed funding (C3) could significantly affect various NPOs.

This study offers significant insights for practitioners (e.g. project managers) to improve ODA projects’ performance and effectiveness in the education and training sector of a developing country context (like Vietnam).

The purpose of this paper is twofold: first, to present a rigorous bibliometric analysis and a systematic literature review of the critical success factors (CSFs) for Building information modelling (BIM)-based digital transformation; second, to identify the relationship between the dimensions in favour of BIM implementation.

This study adopts a two-step approach to combine bibliometric and systematic literature review to explore the research topic of BIM and CSFs. Bibliometric tools such as Biblioshiny in R language and Ucinet software were applied to this study.

Besides identifying the two most influential authors (e.g. Bryde and Antwi-Afari), the key journal for disseminating articles, and the most influential countries in this discourse (e.g. Hong Kong and Australia), the study also identifies four pivotal research themes derived from the co-occurrence analysis of keywords: the fusion of sustainability and technology with BIM; practical application and its integration within construction management; innovation and engineering paradigms; and the advent of emerging technologies (e.g. Blockchain) within developing nations. Additionally, the paper introduces a comprehensive framework for selecting CSFs pertinent to BIM-centred digital transformation as viewed through the lens of dynamic capabilities.

This paper establishes a link between dynamic capabilities theory, CSFs, and BIM dimensions, presenting a multifaceted framework guiding future paths and offering practical insights for managerial and political decision-makers engaged in digital transformation endeavours. The study positions dynamic capabilities as pivotal, aligning digital technologies with continuous business performance, and advocates for a strategic focus on digital transformation.

The construction collapse is one of the most serious accidents since it has several attributes (e.g. accident type and consequence) and its occurrence involves various kinds of causal factors (e.g. human factors). The impact of causal factors on construction collapse accidents and the interrelationships among causal factors remain poorly explored. Thus, the purpose of this paper is to use association rule mining (ARM) for cause analysis of construction collapse accidents.

An accident analytic framework is developed to determine the accident attributes and causal factors, and then ARM is introduced as the method for data mining. The data are from 620 historical accident records on government websites of China from 2010 to 2020. Through the generated association rules, the impact of causal factors and the interrelationships among causal factors are explored.

Collapse accident is easily caused by human factors, material and machine condition and management factors. Furthermore, the results show a close interrelationship between many causal factors and construction scheme and organization. The earthwork collapse is greatly related to environmental condition and the scaffolding collapse is greatly related to material and machine condition.

This study found relevant knowledge about the key causes for different types of construction collapses. Besides, several suggestions are further provided for construction units to prevent construction collapse accidents.

This study uses data mining methods to extract knowledge about the causes of collapse accidents. The impact of causal factors on various types of construction collapse accidents and the interrelationships among causal factors are explained from historical accident data.