The utilization of digital tools in agricultural extension has facilitated information delivery through non-face-to-face interactions. Therefore, this study aimed to map the variation in digital tools used by agricultural extension workers to access and deliver information and analyse the outcomes of farmers’ adoption. Data were collected through in-depth interviews with agricultural extension workers at 11 Agricultural Extension Centers. The data were processed using the N-Vivo qualitative data analysis software. The results showed that extension workers combined various digital tools as sources of extension materials and channels for delivering information to farmers. Although social interaction between agricultural extension workers and farmers occurred non-face-to-face, messages could be adopted by farmers and yield tangible outcomes. This was reflected in the asynchronous communication, allowing extension workers sufficient time to improve the quality of the delivered messages. Farmers also had sufficient time to review the received information content in this context repeatedly. These results implied that although extension content is delivered through non-face-to-face interaction, it can still drive adoption with significant outcomes.
Low integrity is a challenge for any organization. However, most organizations emphasize integrity without explaining what is required of an individual with high integrity. Exhibiting high integrity is necessary for academics; yet, the level of academic integrity remains unclear. Therefore, the purpose of this study is to examine the integrity level of academicians in a Malaysian public university. This paper shares the findings on the level of integrity of academics based on a questionnaire completed by 213 academicians. Data were collected by survey questionnaire and was analyzed using descriptive and inferential statistics. An overall mean score of 9.45 from a possible 10.0 indicated a high level of integrity among academics. The self-evaluation results by academics also demonstrated that they have attained integrity at a high level for their generic task, teaching and learning, research and publications and service for community with a mean score between 9.36 and 9.49. The value with the highest mean score was for “service to community”, whereas the lowest was for “research and publication”. These findings show that the university has successfully instilled values of integrity among academicians. Nevertheless, the university must continue to enhance academic integrity by exploring religiosity. Using Google Scholar, a literature search identified an Islam-based academic integrity model to explain the quantitative findings. Finally, a mixed method approach and involving all universities in Malaysia are recommended to further the findings of this study.
This study explores the determinants of auditor performance, focusing on the moderating role of organizational commitment within the Tangerang City Inspectorate. Employing stratified random sampling, a sample of 250 auditors was chosen to ensure diversity across experience, departmental affiliation, and roles. Quantitative analysis used SPSS to examine the relationships between auditor performance, organizational commitment, and other relevant variables. Findings indicated that organizational commitment significantly moderates the effects of various social pressures on auditor performance. This underscores the necessity for auditing organizations to foster organizational commitment to enhance auditor efficacy and uphold ethical standards. These results hold substantial implications for governance and audit quality assurance, suggesting that reinforced organizational commitment could lead to more robust auditor performance and ethical conduct within similar urban governance settings. This study contributes valuable insights into the influence of organizational dynamics on auditor behaviour and performance outcomes.
This research focuses on addressing critical driving safety issues on university campuses, particularly vehicular congestion, inadequate parking, and hazards arising from the interaction between vehicles and pedestrians. These challenges are common across campuses and demand effective solutions to ensure safe and efficient mobility. To address these issues, the study developed detailed microsimulation models tailored to the Victor Levi Sasso campus of the Technological University of Panama. The primary function of these models is to evaluate the effectiveness of various safety interventions, such as speed reducers and parking reorganization, by simulating their impact on traffic flow and accident risk. The models provide calculations of traffic parameters, including speed and travel time, under different safety scenarios, allowing for a comprehensive assessment of potential improvements. The results demonstrate that the proposed measures significantly enhance safety and traffic efficiency, proving the model’s effectiveness in optimizing campus mobility. Although the model is designed to tackle specific safety concerns, it also offers broader applicability for addressing general driving safety issues on university campuses. This versatility makes it a valuable tool for campus planners and administrators seeking to create safer and more efficient traffic environments. Future research could expand the model’s application to include a wider range of safety concerns, further enhancing its utility in promoting safer campus mobility.
This study aims to identify the risk factors causing the delay in the completion schedule and to determine an optimization strategy for more accurate completion schedule prediction. A validated questionnaire has been used to calculate a risk rating using the analytical hierarchy process (AHP) method, and a Monte Carlo simulation on @RISK 8.2 software was employed to obtain a more accurate prediction of project completion schedules. The study revealed that the dominant risk factors causing project delays are coordination with stakeholders and changes in the scope of work/design review. In addition, the project completion date was determined with a confidence level of 95%. All data used in this study were obtained directly from the case study of the Double-Double Track Development Project (Package A). The key result of this study is the optimization of a risk-based schedule forecast with a 95% confidence level, applicable directly to the scheduling of the Double-Double Track Development Project (Package A). This paper demonstrates the application of Monte Carlo Simulation using @RISK 8.2 software as a project management tool for predicting risk-based-project completion schedules.
As the global ecological and environmental problems become more and more serious, the concept of green finance and sustainable development has been advocated by more and more domestic and foreign experts, scholars and investors, and the Environmental Responsibility, Social Responsibility, and Corporate Governance (ESG) rating has gradually become a hotspot of attention. ESG is a kind of investment concept and a comprehensive assessment criterion of corporate performance for systematic evaluation of enterprises, and it has become an important indicator of the ability of measuring the sustainable development of enterprises. It has become an important indicator of corporate sustainable development capability. In this paper, we investigate the relationship between ESG ratings and cumulative abnormal returns of listed companies’ stocks under the impact of sudden risk events. The outbreak of the New Crown epidemic as an exogenous risk event provides an opportunity for this paper. This paper examines the role of firms’ ESG ratings and the three sub-dimensions of ratings on the cumulative abnormal returns of listed firms’ stocks during the New Crown Epidemic outbreak and verifies the role of ESG ratings on firms in times of crisis. The final regression results prove that under the impact of sudden exogenous risk events, listed firms’ ESG ratings have a positive effect on the cumulative abnormal stock returns during the event window. Finally, this paper provides recommendations to help firms and investors prevent and mitigate risks.
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