The utilization of project risk monitoring and control practices and their relationship with project success in construction projects

Risk monitoring and control is often poorly implemented in construction projects because of a failure to monitor and manage identified risks. Construction companies experience significant losses due to project managers' lack of project risk monitoring and control in construction projects. Most studies have concentrated on risk identification, risk assessment, and risk analysis processes while neglecting crucial risk management processes of risk control, risk monitoring, and risk response. The lack of research on these three crucial processes highlights a gap in the literature concerning how these processes can increase the delivery of successful projects. The purpose of this study was to examine whether the utilization of project risk monitoring and control practices was related to project success in construction projects in the United States. An electronic survey instrument was used to collect data from a sample of 50 construction project managers in the Dallas-Fort Worth area in the state of Texas, in the United States. Spearman rho correlation analysis was used to examine the relationship between project risk monitoring and control practices and project success. The results of this study indicated that all project risk monitoring and control practices, including risk reassessment, risk audits, contingency reserves analysis, and risk status meetings, were significantly and positively related to project success in construction projects. One of the recommendations presented in this study was that future research should conduct the same study in developing countries to see if the study’s findings remain the same and generalizable. The study concluded that construction organizations should regularly consider the importance and usage of project risk monitoring and control practices and apply them to improve the success rate of a project.

Agent-Based Approach for Monitoring Risks in Software Development Projects

According to various surveys conducted, regardless of how many studies in software development projects have been done, the chance that software development projects may fail remains very high. A relatively new approach to the problem of failure is using the concept of artificial intelligence (AI) to help automate a certain part(s) of the projects in order to minimize the issue. Unfortunately, most of the works proposed to date use AI as a standalone system, which leads to limiting the degree of automation that the overall system can benefit from the technology. This chapter discusses a preliminary work on a novel risk monitoring, which utilizes a number of agent-based systems that cooperate with each other in minimizing risks for the projects. The proposed model not only leads to a high degree of automation in risk management, but this extensible model also allows additional tasks in risk monitoring to be easily added and automated if required.

Project Management in Public Administration. Risks and Challenges

Project risk is the object of interest of people and institutions implementing and financing project activities. Each project brings new challenges and risks but also a chance to gain knowledge and development. That is why project management is becoming a standard that receives more and more attention. At the stage of launching a project, it is necessary to conduct risk analysis, which allows risks identification, characterisation and proper assessment. This analysis enables the development of a risk prevention plan, indicating ways to respond to challenging situations when they occur. It also allows the introduction of risk monitoring methods. The specified stages of risk management are well known in public administration, especially to those institutions that raise funds for implementing projects and then manage them. In public administration, institutions implementing projects are obliged to carry out management control, and some responsibilities related to risk management have been imposed on applicants. Therefore, it becomes necessary for project managers and unit managers to understand its (risk) importance for achieving the objectives of the organisation’s projects and the potential benefits that can be obtained after its effective implementation. Organisations that can take into account risk management awareness in projects will be able to use the risk management process to improve the results and increase the satisfaction of all parties interested in the implementation of projects. This article aims to present the identification and risk assessment in projects and challenges faced by the public administration, including the security system, which has been dynamically acquiring funds for implementing projects in recent years.

Respond OJK Regulation Number 55: Can Good Corporate Governance Affect Banks Credit Risk in Indonesia?

Efforts to reduce the number of non-performing loans continue to be carried out, one of which is by enforcing the rules regarding good corporate governance as enshrined in POJK Number 55/POJK.03/2016. The purpose of this study is to respond to these regulations by testing whether the attributes of good corporate governance can influence bank credit risk. The total population is 44 established banking companies with three years from 2017 to 2019. The data analysis technique uses descriptive statistical analysis and partial hypothesis testing. The results showed that the size of the Board of Directors and the size of the Risk Monitoring Committee harmed credit risk. Meanwhile, the size of the Board of Commissioners, the proportion of Independent Commissioners, the meeting of the Board of Commissioners, and the size of the Audit Committee does not significantly influence bank credit risk.

Estimating COVID Risk During a Period of Pandemic Decline

Background: Many parts of the world that succeeded in suppressing epidemic coronavirus spread in 2020 have been caught out by recent changes in the transmission dynamics of SARS-CoV-2. Australia's early success in suppressing COVID-19 resulted in lengthy periods without community transmission. However, a slow vaccine rollout leaves this geographically isolated population vulnerable to leakage of new variants from quarantine, which requires internal travel restrictions, disruptive lockdowns, contact tracing and testing surges.Methods: To assist long term sustainment of limited public health resources, we sought a method of continuous, real-time COVID-19 risk monitoring that could be used to alert non-specialists to the level of epidemic risk on a sub-national scale. After an exploratory data assessment, we selected four COVID-19 metrics used by public health in their periodic threat assessments, applied a business continuity matrix and derived a numeric indicator; the COVID-19 Risk Estimate (CRE), to generate a daily spot CRE, a 3 day net rise and a seven day rolling average. We used open source data updated daily from all Australian states and territories to monitor the CRE for over a year.Results: Upper and lower CRE thresholds were established for the CRE seven day rolling average, corresponding to risk of sustained and potential outbreak propagation, respectively. These CRE thresholds were used in a real-time map of Australian COVID-19 risk estimate distribution by state and territory.Conclusions: The CRE toolkit we developed complements other COVID-19 risk management techniques and provides an early indication of emerging threats to business continuity.

Spatiotemporal Patterns of Burned Areas Based on the Geographic Information System for Fire Risk Monitoring

Forest and land fires occur every year in Indonesia. Efforts to handle forest and land fires have not been optimal because fires occur in too many places with unclear patterns and densities. The study analyzed the spatiotemporal patterns of burned areas and fire density in fire-prone areas in Indonesia. Data of burned areas were taken from http://sipongi.menlhk.go.id/. The website collected its data from NOAA (National Oceanic and Atmospheric Administration) images. Data were analyzed using the hot spot analysis to determine the spatiotemporal patterns of the burned areas and the kernel density analysis to examine the density of land fires. Findings showed that the spatiotemporal pattern from 2016 to 2019 formed a hot spot value in the peatland area with a confidence level of 90–99%, meaning that land fires were clustered in that area. In addition, the highest density of land fires also occurred in the peatland areas. Clustered burned areas with high fire density were found in areas with low–medium vegetation density—they were the peatland areas. The peatland areas must become the priority to prevent and handle forest and land fires to reduce fire risks.

Economic Policy Uncertainty (EPU) and China's Export Fluctuation in the Post-pandemic Era: An Empirical Analysis based on the TVP-SV-VAR Model

In the COVID-19 pandemic, the bidirectional policy adopted by the governments to stimulate domestic economy and reinforce foreign trade control is making the trade environment abnormally complex. China is facing a new challenge in export trade growth. Based on the continuous monthly data from January 2002 to April 2021, this paper uses the time-varying TVP-SV-VAR model to study the impulse response of China's export trade to economic policy uncertainty (EPU). It is found that (1) on the whole, the shock of global EPU and China's EPU on China's export to the OBOR/RCEP member countries is time-varying, different, and structurally significant; (2) during the pandemic, EPU has a significant short-term negative shock on China's gross exports and export to OBOR/RCEP members, and this shock is especially big in the case of global EPU. In the post-pandemic era, China should strengthen pandemic control and economic risk monitoring, continue with execution of multilateral FTAs and create a sustainably stable export trade environment.

The Occurrence and Contamination Level of Ochratoxin A in Plant and Animal-Derived Food Commodities

Ochratoxin A (OTA) is a highly toxic mycotoxin and poses great threat to human health. Due to its serious toxicity and widespread contamination, great efforts have been made to evaluate its human exposure. This review focuses on the OTA occurrence and contamination level in nine plant and animal derived food commodities: cereal, wine, coffee, beer, cocoa, dried fruit, spice, meat, and milk. The occurrence and contamination level varied greatly in food commodities and were affected by many factors, including spices, geography, climate, and storage conditions. Therefore, risk monitoring must be routinely implemented to ensure minimal OTA intake and food safety.