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The present study aims to inform the requirements for developing a sustainable rating tool for small-scale infrastructure projects (SSIPs) through research findings.

A review-based comparative study of existing infrastructure sustainability (IS) rating tools for assessment of SSIPs is presented. Key stakeholder participants of the existing IS rating tools, are interviewed to identify existing barriers and requirements for sustainability rating. The study further presents possible rating tool options to optimise the sustainable performance evaluation of SSIPs.

Findings of this study indicated that prevalent IS rating tools are majorly applied to large-scale infrastructure projects and sustainability of SSIPs are seldom assessed. Based on a literature review and series of interviews, it was found that user friendliness, efficient structure, training and technical support, cost effectiveness and stakeholder recognition are the five key requirements of a sustainability rating tool for SSIPs. Additionally, six sustainability assessment options were proposed for SSIPs which range from pathways for existing tools through to new, customisable tools. Upon comparison, a new modified tool with verification process and revised tool with defined grouping of sustainable criteria was more effective for evaluation of SSIPs.

Use of case specific information for validation and framework development may lack generalisation. However, methodology can be used for future decision-making by making necessary adjustments to suit different local regional requirements.

Despite lack of generalisation, the findings can lead to future general studies on sustainability of SSIPs. Findings of the study provide foundation knowledge and awareness for sustainability evaluation of SSIPs.

Farmers' risk attitudes and risk perceptions play an essential role in shaping risk management strategies to address risks and uncertainties. Contract farming is considered as one of the feasible approaches to tackle farmers' concerns. However, risk perspectives under various categories have not been included in studies on farmers' preferences for contract farming in the literature, especially in Vietnam. This study aims to determine factors affecting farmers' choices of different contract farming practices.

The explanatory factor analysis (EFA) and multinomial logit model (MNL) were applied to explore the impacts of risk perspectives on farmers' preferences for contract farming. Data have been collected from 211 rice farmers in An Giang Province, “the rice bowl” of the Mekong Delta, Vietnam.

The study found that farm size, cooperatives, extension, market access and trust have significantly impacted on contract participation while a delay payment was a barrier for farmers' motivation to opt for the contract. Farmers' contract choices were also influenced by their risk attitudes and perceptions under different risk dimensions. The financial, policy and human risk-averse behavior predisposed farmers to single out the full contract while the policy and human risk-loving and production, market and finance risk-averse respondents were in favor of the marketing contract. Moreover, the findings indicated that the more farmers concerned about risk of weather and market, the more choices for the full contract, whereas the risk perceptions of weather and policy encouraged farmers to use the limited contract. By contrast, farmers who perceived the impacts of risk of diseases/pests and human were likely to adopt the marketing contract.

This study just focuses on collecting data from farmers’ perspective. Future studies involving stakeholders such as enterprises and policy makers are strongly recommended so as to design suitable contracts and enforce contract schemes effectively in Vietnam.

The findings also contribute to the literature on different types of contracts and the multidimensional aspect of risk for rice production in Vietnam.

The impact of building information modeling (BIM) on various aspects of project management has attracted much attention in the past decade. However, previous studies have focused on a particular facet of project management (e.g., safety, quality, facility management) and within identified target journals. Despite numerous existing studies, there is limited research on the mainstream research topics, gaps and future research directions on BIM in project management. This study aims to conduct a bibliometric and science mapping review of published articles on BIM in project management and to identify mainstream research topics, research gaps and future research directions in this domain.

A science mapping approach consisting of bibliometric search, scientometric analysis and qualitative discussion was used to analyze 521 journal articles that were retrieved from the Scopus database and related to BIM in project management. In the scientometric analysis, keyword co-occurrence analysis and document analysis were performed. This was followed by a qualitative discussion that seeks to propose a framework summarizing the interconnection between the mainstream research topics, research gaps and future research directions.

Six mainstream research topics were found including (1) BIM-enabled advanced digital technologies, (2) BIM-based reinforcement and enhancement, (3) BIM and project composition, (4) BIM project elements and attributes, (5) BIM-based collaboration and communication and (6) BIM-based information and data. Moreover, this study discussed six research gaps, namely, (1) integration of BIM and other digital technologies, (2) future maturity of BIM applications in project management, (3) application of BIM in project components and processes, (4) role of BIM application in project elements and attributes, (5) impact of collaboration and communication in BIM application and (6) stability of information and data interaction. Furthermore, future research directions were discussed.

The findings and proposed framework contribute to providing a deeper understanding to researchers, policymakers and practitioners in the development of related research and practice in the domain of BIM in project management, thus, promoting digital transformation in project management. Overall, it adds to the global knowledge domain in BIM and promotes the need for digital and data integration, BIM maturity and BIM collaboration.

Today, individuals use social media to express their opinions and feelings, which offers a living laboratory to researchers in various fields, such as management, innovation, technology development, environment and marketing. It is therefore necessary to understand how the language used in user-generated content and the emotions conveyed by the content affect responses from other social media users.

In this study, almost 700,000 posts from Twitter (as well as Facebook, Instagram and forums in the appendix) are used to test a conceptual model grounded in signaling theory to explain how the language of user-generated content on social media influences how other users respond to that communication.

Extending developments in linguistics, this study shows that users react negatively to content that uses self-inclusive language. This study also shows how emotional content characteristics moderate this relationship. The additional information provided indicates that while most of the findings are replicated, some results differ across social media platforms, which deserves users' attention.

This article extends research on Internet behavior and social media use by providing insights into how the relationship between self-inclusive language and emotions affects user responses to user-generated content. Furthermore, this study provides actionable guidance for researchers interested in capturing phenomena through the social media landscape.

This paper aims to investigate the perceptions of financial accountants and both internal and external auditors regarding the impact of corporate governance (CG) and information technology (IT) on the detection and prevention of fraud within organizations.

Primary data were collected from 250 financial accountants, internal auditors and external auditors through questionnaires. The non-probability snowball sampling technique was used for data collection, with the sample t-test, one-way ANOVA and paired sample t-test applied for analysis.

The results indicate that robust CG practices and IT techniques significantly aid in detecting and reducing fraudulent activities by minimizing opportunities, rationalizations, pressures and capabilities of potential employees to commit fraud. Internal controls also play a significant role in reducing instances of fraud. Notably, ethical officers and ethical training were not perceived as significantly effective in preventing and detecting fraud, leading to a perception that fraudulent practices are prevalent and increasing the risk of future fraudulent activities.

This study recommends the adoption of strong CG practices to identify potential fraud within an organization. Moreover, IT techniques should be tailored to specific needs for effective utilization. Furthermore, the government should increase awareness regarding data provision by departments, organizations and other related personnel. Future research could use secondary data from various regions to expand the literature in this field.

This research uniquely combines three significant factors: CG, IT and forensic accounting in fraud detection and prevention. It contributes to the enhancement of literature about fraud and its preventive and detective measures. The results of this study set the seed for future research, government policymaking and enhanced organizational practices.