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The conventional project delivery (CPD) approach has been reported in the literature as the most widely used project delivery method in the construction industry globally compared to other delivery methods. However, researchers and practitioners have argued that the approach, specifically during the production of design documentation under the CPD, lacks certain capabilities that ensure quality and enhance project delivery. Therefore, this study aims to use the Ghanaian construction industry to identify the capabilities required of the CPD in practice, particularly during the production of design documentation.

The study design follows a pragmatist philosophy and uses mixed methods based on a deductive approach. Data collection involved a questionnaire survey, followed by semi-structured interviews. Quantitative data analysis used descriptive and inferential statistics, whereas qualitative data analysis used content analysis with the assistance of IBM SPSS and QSR Nvivo 12 Pro.

Findings indicate that there should be incentives for producing good design documentation quality; mandatory coordination of design documentation; improving collaboration among designers; and allowing contractors to make input during the design stage.

The results indicate the need for the identified capabilities to be introduced in the CPD approach to improve design documentation quality.

This study offers a significant insight into the specific capabilities that are required of the CPD approach in practice particularly, in the production of design documentation

Directors’ human capital has long been recognised as vital to ensuring effective corporate governance. While previous studies have sought to link director human capital with specific firm-level outcomes, there are persistent challenges facing researchers who seek to understand better what kind of human capital makes a difference to effective board role execution. This study aims to understand whether the way directors fulfil their roles and contribute to boardroom dynamics is shaped by any human capital they gain via senior executive experience.

We draw insights from 30 in-depth, semi-structured interviews with Indian directors to capture their perceptions and experiences of how a specific kind of human capital, namely the C-suite experience, affects directors' boardroom dynamics and board role execution.

We highlight how directors with executive experience appear to have a more salient set of human capital to draw on. Specifically, they report navigating governance processes differently, displaying a more contextualised understanding of boardroom dynamics and having a broader understanding of the firm’s problems. Doing so enables them to foster constructive board-management relationships and improve their service role execution.

Our qualitative data are drawn from a purposively sampled group in a specific governance system (India). While this does not threaten the key theoretical insights, it does raise questions about their generalisability to other governance contexts.

Directors with executive experience build trust through their orientation towards and understanding of management without diminishing their capacity to scrutinise management decisions. The human capital of these directors appears to engender a more effective and contextualised boardroom dynamic that facilitates the execution of socialised accountability through balancing the control and service roles.

Our findings highlight the potential importance of a shared understanding of the communication and collaboration processes of corporate governance (i.e. a common transactional memory framework) between directors and management. Directors who share this understanding with management are more likely to effectively engage in the service role while not compromising the control role. This shared understanding appears to allow these directors and executives to encode, store and retrieve relevant information they need more effectively, engendering the trust between them that seems to foster socialised accountability.

This study aims to examine the nexus between digital financial literacy and customers’ perceived financial behavior within the Kuwaiti context. Moreover, it will further explore how digital financial literacy relates to financial behavior dimensions.

Data collection was facilitated by creating a questionnaire derived from multiple literature sources. This study used a cross-sectional, time-based dimension. Data was analyzed using the partial least square (PLS) structural equation modeling approach, using the Smart-PLS 4 software for computation.

Findings demonstrated a significant relationship between digital financial literacy and financial behavior, with a path coefficient of 0.542, a p-value of 0.000 and an R² value of 0.581. The explorative model revealed substantial relationships between many dimensions of digital financial literacy and various dimensions of financial behavior. More precisely, financial knowledge, awareness and decision-making were the factors that had the most significant impact on financial behavior.

Kuwaiti policymakers should consider including digital financial literacy programs in comprehensive financial education programs to improve public understanding of digital financial instruments and their consequences.

As the authors know, this is the initial endeavor to evaluate the relationship between digital financial literacy, financial behavior and their respective dimensions.

In the context of nursing in higher education, digital competencies are increasingly recognised as a necessary skillset, within a continuously evolving healthcare professional landscape. This study sought to explore nursing students’ digital competencies and to further understand the digital literacy gaps and barriers they encounter for both learning and future work.

The research involved a cross-sectional, discipline-based empirical study of nursing students’ self-assessed digital competencies via a questionnaire survey, which collected quantitative and qualitative data from a total of five hundred and fifty-three students. The study explored the role of demographics (age, urban/rural geographical location of growing up, study year, learning disabilities (neurodiversity)) and experiences of digital divides (e.g., access, contextual and behavioural barriers) play on students’ digital competencies and outcomes.

Students’ digital competencies were found at an intermediate level, with younger and first-year students self-assessing higher. Significant differences were identified between students who had encountered digital barriers/divides and those who had not, with the former, self-reporting lower digital competencies. Students with learning disabilities reported complex support needs for processing and organizing digital information and for productivity. Almost all the individual digital competencies items assessed had strong statistical correlations between them.

The research offers key recommendations for academic libraries for the ongoing, evolving exploration of students’ digital competencies and for the need to follow tailored, discipline-related, holistic, practice-based and curriculum-embedded approaches to students’ digital skills development and support. It provides novel insights into digital competencies development for nursing students, particularly those who experience digital divides.

Heterogeneous graphs, composed of diverse nodes and edges, are prevalent in real-world applications and effectively model complex web-based relational networks, such as social media, e-commerce and knowledge graphs. As a crucial data source in heterogeneous networks, Node attribute information plays a vital role in Web data mining. Analyzing and leveraging node attributes is essential in heterogeneous network representation learning. In this context, this paper aims to propose a novel attribute-aware heterogeneous information network representation learning algorithm, AAHIN, which incorporates two key strategies: an attribute information coverage-aware random walk strategy and a node-influence-based attribute aggregation strategy.

First, the transition probability of the next node is determined by comparing the attribute similarity between historical nodes and prewalk nodes in a random walk, and nodes with dissimilar attributes are selected to increase the information coverage of different attributes. Then, the representation is enhanced by aggregating the attribute information of different types of high-order neighbors. Additionally, the neighbor attribute information is aggregated by emphasizing the varying influence of each neighbor node.

This paper conducted comprehensive experiments on three real heterogeneous attribute networks, highlighting the superior performance of the AAHIN model over other baseline methods.

This paper proposes an attribute-aware random walk strategy to enhance attribute coverage and walk randomness, improving the quality of walk sequences. A node-influence-based attribute aggregation method is introduced, aggregating neighboring node attributes while preserving the information from different types of high-order neighbors.