Delay is the leading challenge in completing Engineering, Procurement, and Construction (EPC) projects. Delay can cause excess costs, which reduces company profits. The relationship between subcontractors and the main contractor is a critical factor that can support the success of an EPC project. The problematic financial condition of the main contractor can cause delay in payments to subcontractors. This research will set a model that combines the system dynamics and earned value method to describe the impact of subcontractor advance payments on project performance. The system dynamics method is used to model and analyze the impact of interactions between variables affecting project performance, while the earned value method is applied to quantitatively evaluate project performance and forecast schedule and cost outcomes. These two methods are used complementarily to achieve a holistic understanding of project dynamics and to optimize decision-making. The designed model selects the optimum scenario for project time and costs. The developed model comprises project performance, costs, cash flow, and performance forecasting sub-models. The novelty in this research is a new model for optimizing project implementation time and costs, adding payment rate variables to subcontractors and subcontractor performance rates. The designed model can provide additional information to assist project managers in making decisions.

This research examines three data mining approaches employing cost management datasets from 391 Thai contractor companies to investigate the predictive modeling of construction project failure with nine parameters. Artificial neural networks, naive bayes, and decision trees with attribute selection are some of the algorithms that were explored. In comparison to artificial neural network’s (91.33%) and naive bays’ (70.01%) accuracy rates, the decision trees with attribute selection demonstrated greater classification efficiency, registering an accuracy of 98.14%. Finally, the nine parameters include: 1) planning according to the current situation; 2) the company’s cost management strategy; 3) control and coordination from employees at different levels of the organization to survive on the basis of various uncertainties; 4) the importance of labor management factors; 5) the general status of the company, which has a significant effect on the project success; 6) the cost of procurement of the field office location; 7) the operational constraints and long-term safe work procedures; 8) the implementation of the construction system system piece by piece, using prefabricated parts; 9) dealing with the COVID-19 crisis, which is crucial for preventing project failure. The results show how advanced data mining approaches can improve cost estimation and prevent project failure, as well as how computational methods can enhance sustainability in the building industry. Although the results are encouraging, they also highlight issues including data asymmetry and the potential for overfitting in the decision tree model, necessitating careful consideration.

Learning from experience to improve future infrastructure public-private partnerships is a focal issue for policy makers, financiers, implementers, and private sector stakeholders. An extensive body of case studies and “lessons learned” aims to improve the likelihood of success and attempts to avoid future contract failures across sectors and geographies. This paper examines whether countries do, indeed, learn from experience to improve the probability of success of public-private partnerships at the national level. The purview of the paper is not to diagnose learning across all aspects of public-private partnerships globally, but rather to focus on whether experience has an effect on the most extreme cases of public-private partnership contract failure, premature contract cancellation. The analysis utilizes mixed-effects probit regression combined with spline models to test empirically whether general public-private partnership experience has an impact on reducing the chances of contract cancellation for future projects. The results confirm what the market intuitively knows, that is, that public-private partnership experience reduces the likelihood of contract cancellation. But the results also provide a perhaps less intuitive finding: the benefits of learning are typically concentrated in the first few public-private partnership deals. Moreover, the results show that the probability of cancellation varies across sectors and suggests the relative complexity of water public-private partnerships compared with energy and transport projects. An estimated $1.5 billion per year could have been saved with interventions and support to reduce cancellations in less experienced countries (those with fewer than 23 prior public-private partnerships).

This article analyzes the use and limitations of nonmonetary contract incentives in managing third-party accountability in human services. In-depth case studies of residential care homes for the elderly and integrated family service centers, two contrasting contracting contexts, were conducted in Hong Kong. These two programs vary in service programmability and service interdependency. In-depth interviews with 17 managers of 48 Residential Care Homes for the Elderly (RCHEs) and 20 managers of 10 Integrated Family Service Centers (IFSCs) were conducted. Interviews with the managers show that when service programmability was high and service interdependency was low, nonmonetary contract incentives such as opportunities for self-actualization professionally or reputation were effective in improving service quality from nonprofit and for-profit contractors. When service programmability was low and service interdependency was high, despite that only nonprofit organizations were contracted, many frontline service managers reported that professional accountability was undermined by ambiguous service scope, performance emphasis on case turnover, risk shift from public service units and a lack of formal accountability relationships between service units in the service network. The findings shed light on the limitations of nonmonetary contract incentives.

Projects implemented under life cycle contracts have become increasingly common in recent years to ensure the quality of construction and maintenance of energy infrastructure facilities. A key parameter for energy facility construction projects implemented under life cycle contracts is their duration and deadlines. Therefore, the systematic identification, monitoring, and comprehensive assessment of risks affecting the timing of work on the design and construction is an urgent practical task. The purpose of this work is to study the strength of the influence of various risks on the duration of a project implemented on the terms of a life cycle contract. The use of the expert assessment method allows for identifying the most likely risks for the design and construction phases, as well as determining the ranges of deviations from the baseline indicator. Using the obtained expert evaluations, a model reflecting the range and the most probable duration of the design and construction works under the influence of risk events was built by the Monte-Carlo statistical method. The results obtained allow monitoring and promptly detecting deviations in the actual duration of work from the basic deadlines set in the life cycle contract. This will give an opportunity to accurately respond to emerging risks and build a mutually beneficial relationship between the parties to life cycle contracts.

The Guangdong-Macao Intensive Cooperation Zone in Hengqin (Intensive Cooperation Zone) has emerged as a pivotal economic hub, attracting Macao residents and enterprises. However, disparities in contract-related rules between the zone and Macao have led to legal challenges. This article delves into a comparative study of contract laws between the People’s Republic of China (PRC) and Macao. Analyzing key facets such as pacta sunt servanda, freedom of contract, principle of equity, contract form, principles of interpretation, and termination of contract, the study identifies nuanced differences. Recognizing the imperative of aligning contract laws for the Intensive Cooperation Zone’s development, the article advocates for a unified legal environment. To achieve this, the author proposes a model contract law that prioritises the United Nations Convention on Contracts for the International Sale of Goods (CISG) as the basis. Notably, Macao’s contract-related rules should govern aspects not covered by the CISG given the policy trend in the Intensive Cooperation Zone. The proposed model law serves as a foundation for legislative reform, aiming to address the existing disparities and promote the Intensive Cooperation Zone’s economic growth.