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.

In the realm of modern education, the integration of technology has emerged as a powerful catalyst for transforming traditional classrooms into dynamic and engaging learning environments. This paper provides a concise overview of the multifaceted ways in which technology contributes to enhanced classroom engagement.

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.

To increase inter-region connectivity, the Indonesian government initiated infrastructure projects such as toll roads, airport, highways, as well as agriculture ones throughout the countries. One of the big projects in road infrastructure was the Cikampek–Palimanan (Cipali) toll road in West Java with a budget of more than USD1 billion which started to operate in July 2015. This paper is aimed to evaluate the impact of the toll road on accessibilities, trades, and investments in the region it traverses. To carry out the analysis, we used qualitative approach, difference-in-difference approach, and ANOVA, utilizing three kinds of data. The first data is collected from a survey of 331 small-medium enterprises (SMEs) in the logistics and the hotel and restaurant industries. The second one is bank loan data sourced from Bank Indonesia, while the third one is investment data from Investment Coordinating Board of Indonesia (BKPM).
After two years of its operation, Cipali toll road has increased accessibility, mobility, trade, and investment in the region it traverses. The travel time was reduced by 39%, while the cargo volume of the local businesses increased by 30% to 40%. These led to an improvement of wholesale trade volume in almost all regencies. However, SMEs in the hotel and restaurant industry along the traditional northern coastal highway in Subang, Indramayu, and Brebes experienced a decline due to the traffic shifting. Meanwhile, investments from national companies especially those of labor-intensive manufacturing industries flowed significantly especially to Subang and Majalengka, which reflected a “sorting effect”. However, investments from local and foreign businesses did not increase significantly yet after 2.5 years of toll operation.
To reap the benefit from the presence of Cipali toll road, the local governments should improve the ease of doing business to attract investments that boost employment in return. In addition, given a better accessibility from Greater Jakarta and a large number of potential visitors passing through the toll road, local businesses in the trade sector would benefit if they could promote the local attractions such as in tourism activities supported by the local government. The latter strategy should also be implemented by the local governments and local businesses in the northern coastal traditional route to minimize the negative impact of the toll road due to the traffic shifting. This strategy should be strengthened through increasing connectivity from the toll exits to local business areas and through increasing the ease of doing business.