Purpose It is estimated that more than half of the construction industry’s projects encounter significant cost overruns and major delays, resulting in the industry having a tarnished reputation. Therefore, it is crucial to identify key project cost and schedule performance factors. However, despite the attempts of numerous researchers, their results have been inconsistent. Most of the literature has focused solely on the construction phase budget and time overruns; the engineering/design and procurement phase costs and schedule performances have been rarely studied. The paper aims to discuss these issues. Design/methodology/approach The objective of this study was primarily to identify and prioritize engineering, procurement and construction key performance factors (KPFs) and to strategize ways to prevent performance delays and cost overruns. To achieve these objectives, more than 200 peer-reviewed journal papers, conference proceedings and other scholarly publications were studied and categorized based on industry type, physical location, data collection and analysis methods. Findings It was concluded that both the time required to complete engineering/construction phases and the cost of completing them can be significantly affected by design changes. The two main causes of delays and cost overruns in the procurement phase are construction material shortages and price fluctuations. Other factors affecting all phases of the project are poor economic condition, equipment and labor shortages, delays in owners’ timely decision making, poor communication between stakeholders, poor site management and supervision, clients’ financial issues and severe weather conditions. A list of phase-based strategies which address the issue of time/cost overruns is presented herein. Originality/value The findings of this study address the potential confusion of the industry’s practitioners related to the inconsistent list of potential KPFs and their preventive measurements, and pave the way for the construction research community to conduct future performance-related studies.

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Delay and cost overrun in construction projects are two widespread problems that arouse practitioners' and scholars' concern. Therefore, the objective of this study was to identify Key Performance Indicators (KPIs) in each of Engineering, Procurement and Construction (EPC) phases separately and then calculate the weight impact that is associated with each of identified KPIs. Additionally, this study aimed to find the most appropriate Best Practices (BPs) for the identified phase-based indicators. Through a review of existing literature, a survey was developed to collect data from the completed construction projects. Various statistical methods, including two sample T-test and Kruskal-Wallis test, were utilized to analyze the data. Subsequently, Epsilon-Squared effect size method was applied to prioritize the identified KPIs. Since the lack of communication and slowness in decision making were found as the primary schedule Performance Indicators, schedule performance was identified to be highly affected by managerial approaches and actions. In addition, clients play a decisive role, because owner-driven change orders were found as the most crucial cost performance indicator affecting the performance of the engineering and construction phases. The outcome of this study helps practitioners and scholars to understand the phase-based cost and schedule KPIs, and appropriate mitigating strategies to improve the construction performance in EPC phases and save time and money.

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Transportation agencies are primarily responsible for building new roads and maintaining current roads. The main focuses of these agencies are to prioritize maintenance and make significant rehabilitation decisions to handle serious problems facing road authorities. Considerable efforts and an abundance of studies have been performed to determine the nature, mechanisms, test methods, and measurement of pavements for preservation and improvements of roadways. The presented study reports a state-of-the-art review on recent advances in the application of artificial intelligence in various steps of flexible pavement, including pavement construction, performance, cost, and maintenance. Herein, the challenges of gathering large amounts of data, parameter optimization, portability, and low-cost data annotating are discussed. According to the findings, it is suggested that greater attention should be paid to integrating multidisciplinary roadway engineering techniques to address existing challenges and opportunities in the future.