Background: The construction industry is generally associated with a high level of risk and ambiguity because of the nature of its working contexts. In the Gaza Strip, construction projects are among the riskiest projects, which require the application of the right rules and adherence to the proper management standards. Identification of these risks is the first step in risk management. Aims: This study aims to investigate and understand the main risks faced by the construction projects in the Gaza strip. Methods: A questionnaire survey was conducted to achieve the study aim, whose applicability was tested through a pilot study. Using targeted participants from engineering offices and consulting engineering companies, 70 questionnaires were distributed and collected with a response rate of 85.71%. The Quantitative method was used for data analysis using SPSS. 38 risk factor statements were considered from the seven clusters of risk factors. Results: The results show that the political risk factor was determined to be the highest with a Relative Important Index (RII) of 75.47%, while the design factor was the least factor with an average RII of 61.89%. Conclusion: It is recommended that companies should appoint a specialist in the field of risk management.

The notions of smart construction and smart or digital cities include many modern concepts that are advocated today, especially in countries with advanced economies, and depend on using information technology and the Internet of Things as a basis to automate processes and activate digital systems to manage activities and services related to the operation of buildings and urban structures. In light of the spread of digital technology and modern managerial approaches, the concept of a digital twin is being used on a large scale with the current trend and direction to digitalize activities providing many economic, social and technical advantages. A digital twin is a system in which a virtual representation of a real entity or physical system is used continuously by being fed with data and deriving outputs in the form of decisions and actions that are generated through the processes of machine learning, simulation, development and lifecycle management. This study aims to review the literature on construction project management through the lens of digital twins and ways to use them in the field to improve operational results. The authors propose a framework for analyzing and supervising the development of digital twins that uses three main stages: the commonly encountered Building Information Modeling (BIM); the existing monitoring and actuation digital twins; and an envisioned third stage that makes use of artificial intelligence, complex visualization instruments and advanced controls with the capability to exact change within a construction project on the building site.

Background: Construction projects are among the riskiest businesses due to the number of factors involved that are difficult to control; hence, the popularity of risk management as part of the decision-making process in construction organizations is increasing. Despite the advancements, there are various risks involved that lead to project failure. Aim: Thus, this study aims to assess the risk management strategies in construction organizations in the Gaza Strip, Palestine. Methods: Seventy questionnaires were distributed after subjecting them to pretesting and pilot study that confirmed the validity and reliability of the questions. The target respondents included engineers and consultants from the construction organizations, Ministry of Works and Housing, and international agencies. The questionnaire was retrieved with a 65.71% response rate. Results: Results indicated that the most popular method of risk factor determination in the Gaza Strip is the “checklist” (RII=84%). For tools/methods of risk analysis, relying on experience in the direct assessment is the most prominent, with an RII of 78%. For the methods of avoiding risk before the project implementation, dependence on experience in the work for preparing and planning was ranked highest (having RII of 81.6%). Finally, follow-up on the implementation to avoid rework, with an RII of 77.6%, was ranked highest among other factors of avoiding risk during the construction projects implementation. Conclusion: This study highlights the key risk management strategies that will be beneficial for the construction industry stakeholders to resolve the unwanted risk failures in the construction industry.

This study aims to analyze and discuss the risks facing construction projects by reviewing some of the processes and procedures that address risks through the use of the digital twin technology. The paper studies generic risks and their treatment, and it develops a proposal for risk management systematization using the Digital Twin for Construction Projects approach, previously developed by the authors. It addresses how to classify risks so that the digital system is fed with the proper information and data, which is based on processing and analysis, to reach understandable decisions and overcome anomalies. The research reached a set of results, the most prominent of which is that the digital twin can be used to enhance risk management in construction projects through adapted techniques such as the ones proposed in the paper; namely, a risk treatment procedure and a custom risk matrix. In addition, risk management treated according to a digital approach helps to improve the prediction capabilities, and this helps human decision-makers to avoid potential unplanned costs and failures, and to maximize efficiency. The study also recommends new investigations in the field of safeguarding shared information and data to protect from intentional and accidental mismanagement in order to reach a comprehensive digital system.