Purpose The coronavirus disease 2019 (COVID-19) pandemic has affected the global economy and, thus, the global construction industry. This paper aims to study the impact of COVID-19 on construction project performance in the United Arab Emirates (UAE). Design/methodology/approach This study adopted a qualitative and exploratory approach to investigate the impact of COVID-19 and its policies on project performance in the UAE construction industry in critical areas of the project management body of knowledge (e.g. schedule, cost, resources and contracts). Semi-structured interview questions were asked from ten construction professional to obtain valuable insights into the pandemic’s effects on the UAE construction industry and the effectiveness of policies implemented to rectify the damage and identify the industry’s new normal. Findings The findings indicate that the construction industry faced several challenges such as schedule delays, disrupted cashflows, delayed permits, approvals and inspections, travel restrictions, serious health and safety concerns, material and equipment shortages, among others which hindered the timely delivery of construction projects. It also indicates that efforts made by the government institutions and the construction industry of the UAE such as economic support programs, digitization of processes, fee and fine waivers, health facilities, among other statutory relaxations proved effective in supporting the construction industry against the adverse effects of the pandemic. Research limitations/implications The research findings are limited to the literature review and ten semi-structured interviews seeking an expert’s opinion from industry professionals working in the UAE construction industry. The research team did not get access to project documents, contracts and project progress reports which may be required to validate the interview findings, and to perform an in-depth analysis quantifying the impact of COVID 19 on construction projects performance, which is a limitation of this research. Practical implications The implication is that, owing to the imposed lockdowns and strict precautionary measures to curb the rapid spread of the pandemic, smooth execution of the construction project across the country was affected. The government institutions and stakeholders of the construction projects introduced and implemented various techniques and solutions which effectively handled the implications of the COVID-19 pandemic on the construction industry of the UAE. Originality/value This study has identified the challenges faced by the construction industry of the UAE in the context of the management of project schedule, project cost, construction contracts, health and safety of construction employees and other related aspects of the construction projects. This study also identified the techniques and solutions adopted by various public and private institutions of the country and their implications on construction projects. Therefore, this study provides guidelines for policymakers and future research studies alike.

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The progress monitoring (PM) of construction projects is an essential aspect of project control that enables the stakeholders to make timely decisions to ensure successful project delivery, but ongoing practices are largely manual and document-centric. However, the integration of technologically advanced tools into construction practices has shown the potential to automate construction PM (CPM) using real-time data collection, analysis, and visualization for effective and timely decision making. In this study, we assess the level of automation achieved through various methods that enable automated computer vision (CV)-based CPM. A detailed literature review is presented, discussing the complete process of CV-based CPM based on the research conducted between 2011 and 2021. The CV-based CPM process comprises four sub-processes: data acquisition, information retrieval, progress estimation, and output visualization. Most techniques encompassing these sub-processes require human intervention to perform the desired tasks, and the inter-connectivity among them is absent. We conclude that CV-based CPM research is centric on resolving technical feasibility studies using image-based processing of site data, which are still experimental and lack connectivity to its applications for construction management. This review highlighted the most efficient techniques involved in the CV-based CPM and accentuated the need for the inter-connectivity between sub-processes for an effective alternative to traditional practices.

Disposal of municipal solid waste (MSW) is one of the significant global issues that is more evident in developing nations. One of the key methods for disposing of the MSW is locating, assessing, and planning for landfill sites. Faisalabad is one of the largest industrial cities in Pakistan. It has many sustainability challenges and planning problems, including MSW management. This study uses Faisalabad as a case study area and humbly attempts to provide a framework for identifying and ranking landfill sites and addressing MSW concerns in Faisalabad. This method can be extended and applied to similar industrial cities. The landfill sites were identified using remote sensing (RS) and geographic information system (GIS). Multiple datasets, including normalized difference vegetation, water, and built-up areas indices (NDVI, NDWI, and NDBI) and physical factors including water bodies, roads, and the population that influence the landfill site selection were used to identify, rank, and select the most suitable site. The target area was distributed into 9 Thiessen polygons and ranked based on their favorability for the development and expansion of landfill sites. 70% of the area was favorable for developing and expanding landfill sites, whereas 30% was deemed unsuitable. Polygon 6, having more vegetation, a smaller population, and built-up areas was declared the best region for developing landfill sites and expansion as per rank mean indices and standard deviation (SD) of RS and vector data. The current study provides a reliable integrated mechanism based on GIS and RS that can be implemented in similar study areas and expanded to other developing countries. Accordingly, urban planning and city management can be improved, and MSW can be managed with dexterity.

The China Pakistan Economic Corridor (CPEC) project was signed between China and Pakistan in the year 2013. This mega project connects the two countries to enhance their economic ties and give them access to international markets. The initial investment for the project was $46 billion with a tentative duration of fifteen years. Being an extensive project in terms of cost and duration, many factors and risks affect its performance. This study aims to investigate the effects of political (PR), social safety (SR), and legal risks (LR) on the project performance (PP) of the CPEC. It further investigates the significance of the host country’s attitude towards foreigners (HCA). A research framework consisting of PR, SR, and LR as independent variables, PP as the dependent variable, and HCA as moderator is formulated and tested in the current study. In this quantitative study, the Likert scale is used to measure the impact of the assessed risks. A questionnaire survey is used as a data collection tool to collect data and test the research framework and associated hypotheses. The partial least square structural equation modeling (PLS-SEM) is used to perform the empirical test for validation of the study, with a dataset of 99 responses. The empirical investigation finds a negative relationship between PR, SR, LR, and PP. It is concluded that PR, SR, and LR negatively influence the PP of CPEC. Furthermore, HCA negatively moderates the PR, LR, and PP of CPEC. In contrast, the value of SR and PP is positive in the presence of the positive HCA.