The construction industry has responded to reduced project delivery times by introducing acceleration techniques into the project schedule. The conventional schedule acceleration technique is concurrent engineering, which overlaps activities that are traditionally performed sequentially. Acceleration through overlapping (also called fast-tracking) benefits the project but is generally considered riskier [1].

The basic idea is to reduce the total execution time by executing activities in parallel instead of performing these activities sequentially. The first activity in an overlapping pair is called the predecessor or upstream activity, and the second is called the successor or downstream activity. The degree of overlapping (i.e., amount of concurrency) is defined as a length of time or percent of the duration of the predecessor activity. However, the degree of overlapping can vary depending on conditions, such as the relationship type and the characteristics of the overlapped activities ^[1][2][3][4][1,2,3,4]. Factors involved in this relationship can influence and be the source of risks, such as the production rate of the predecessor activity, information uncertainty, resource availability, physical space, and safety conditions. Figure 1 illustrates a traditional schedule without overlapping and three overlapping scenarios with 25%, 50%, and 75% overlap. For example, if each activity has a duration of ten days, overlapping 25% in a finish-to-start relationship means the two activities will be concurrently performed during the last 2.5 days of the predecessor activity (which would also be the first 2.5 days of the successor activity).

Regardless of the intrinsic risks associated with a traditional construction project, there is a general consensus within the industry that fast-track projects have additional risks. Earlier studies about overlapping, either in product development or construction, mention that adopting a fast-track approach will result in more risks ^{[1][2][5][6][7]}[1,2,5,6,7]. Applying overlapping in construction projects has become a routine but challenging procedure. To successfully deliver fast-track projects, it is necessary to understand the risk dynamics involved, adopt practices to manage the risks and provide attention to aspects such as the design phase, coordination, information, and project team involvement ^[8][9][10][8,9,10].

Since fast-track projects may be riskier, adopting a systematic and iterative process to manage these risks and identify and respond to schedule threats is essential. A risk management process includes the steps of process planning, risk identification, risk analysis, risk response strategy and implementation, and risk control ^[11][12][11,12]. The importance of risk management in construction and how construction risk is perceived were already the focus of earlier studies [13]. A critical step in risk management is risk identification, which primarily consists of deciding and documenting which threats the project may be exposed to. Risk identification is the process of applying various techniques to determine what, why, and how risks may happen [14]. The risk identification phase is considered essential and challenging because risks cannot be managed unless they are identified, impacting the risk management process efficiency and influencing the risk assessment accuracy ^[12][15][12,15]. According to Salas et al. [16], risk perception is how risks are processed, and it is the subjective judgment of professionals about risk characteristics. An improved risk identification process may also include the analysis of historical data, such as risks identified in previous, similar projects.

Traditional construction projects have always been characterized as risky, and it is natural that when new elements, such as schedule acceleration through overlapping, are introduced, additional risks might arise. In the case of overlapping, additional risks may be more changes, rework, delay, duration and effort increase in the successor activity, quality loss on the predecessor activity, poor prototyping criteria, overdesign strategy assumptions not being conservative enough, lack of design optimization and coordination, increased materials wastage, inadequate coordination between design and construction, and inadequate scheduling of the work package interfaces, to name a few ^{[1][2][5][7][9]}[1,2,5,7,9]. Therefore, it is necessary to understand how the construction industry perceives these risks. Emerging studies about risk assessment or project acceleration in construction do not specifically address the risk perception of construction professionals when different degrees of overlapping are applied in construction projects.

2. General Risks in Construction

The study of risk management or of risks in construction projects has covered aspects varying from frameworks to the investigation of general risks or risks in specific areas, such as contracts, supply chain, and the engineering design phase, to name a few. Chen et al. [17] proposed a Bayesian-driven Monte Carlo (BDMC) simulation approach to study the impact on infrastructure construction schedules of interdependency between chronological and causal relationships of risk occurrence. However, this study does not consider any risk related to overlapping activities. Lee et al. [18] collected the risk perception of construction managers about predefined overseas project risks and cost overruns and compared it with the data analysis of 20 construction cases. Sobieraj and Metelski [19] developed a proprietary investment model considering different project phases and combining Monte Carlo simulation and Time-at-Risk (TaR) to assess the risk of project time extension. Nabawy and Gouda Mohamed [20] classified infrastructure project risk factors by combining different methods, such as a risk breakdown structure to classify the risks from the literature, a checklist, a questionnaire, and Back Propagation Multi-Layer Perceptron (BP-MLP) Artificial Neural Network. Mohajeri Borje Ghaleh et al. [21] investigated risks in road projects using a survey and analytical hierarchy process (AHP) but without considering the schedule acceleration. Koulinas et al. [22] presented a Monte Carlo simulation approach combined with the risk perception of a single construction risk manager, collected via a questionnaire to quantify the total delay risk of a construction project. The approach did not consider any acceleration through overlapping. Studying general risks or risk management methods in construction, Siraj and Fayek [23] examined risk identification and common risks through a literature review and content analysis. Hoseini et al. [24] used content analysis and focus groups to develop a generic maturity model to improve risk management practice. Chatterjee et al. [25] used a hybrid multi-criteria decision-making technique to categorize and describe risk issues and rank uncertain risk response strategies. Ansah et al. [26] proposed a framework to determine the severity, occurrence, and detection of risks associated with delay sources in Malaysian construction projects. Other studies investigated construction risks that can emerge in specific areas. A hybrid approach (SD-ISM—System Dynamics-Interpretive Structural Modeling) to be applied for risk prioritization, individual risk assessment, and the overall risk impact on project objectives of risks from the design phase was proposed by Etemadinia and Tavakolan [27]. The approach aimed to provide risk prioritization, individual risk assessment, and an overall risk impact on project objectives. Diaz et al. [28] developed a framework consisting of data collection, network mapping, and simulation to assess risks associated with supply chain disruptions in the construction projects of the defense shipbuilding and repair industry. Okolelova et al. [29] analyzed risks in high-rise construction impacting the investment value using statistical and clustering analyses. Other studies explored safety risk tolerance across different world geographical regions and analyzed safety risks for sustainable construction ^[16][30][16,30]. The Investigation of risk perceptions in construction analyzed the influence of personality trait factors or risk perception differences among diverse project stakeholders. Lee and Foo [31] used the Big Five theory to investigate how five personal attributes (i.e., openness to experience, conscientiousness, extraversion, agreeableness, neuroticism) of construction practitioners in Malaysia influence risk perceptions. Other authors explored the risk perceptions of different stakeholders (i.e., owners, consultants, designers, contractors), considering that they may perceive the same construction risks differently. Al Nahyan et al. [32] used a survey, questionnaire, and nonparametric statistical techniques to examine how the roles and experiences of clients, consultants, and contractors may influence perceptions of three risk categories (i.e., technical, financial, and decision-making) in mega infrastructure projects and their indicators. Perez et al. [33] used a questionnaire and an online survey to explore factors and the risk perceptions of contractors and consultants related to risk allocation and formal risk management in commercial construction projects in Australia. Zhao et al. [34] focused on investigating the safety risk perceptions from four critical groups—architects, engineers, contractors, and safety professionals, judging the likelihood and severity of potential safety risks in the work conditions of a building system. These studies investigated how personal behavior, roles, and experience affect risk perception in construction projects, considering that perception is subjective and intuitive. However, none of these risk perception studies considered project acceleration or fast-tracking as a factor.

3. Risks in Projects Applying Activity Overlapping—Product Development

The study of overlapping (or concurrent engineering) originated in the product development field, trying to increase the efficiency and predictability of the development iteration process [4]. It is a well-explored area in the literature, including evolutionary acquisition and spiral development. Recent studies in this area proposed quantitative and optimization models incorporating risk into their models. Tian et al. [35] investigated the delay impact on pairs of overlapping activities due to two rework risk types (i.e., forward rework and reverse rework). Oh and Hong [36] quantitatively investigated the impact on rework and project duration by the uncertainty of cascaded information during the concurrency of multiple activities. Lu [37] proposed an optimization model to study the coordination strategy of activity overlapping in new product development, considering the rework risk caused by the probability change of the predecessor activity. Alternatively, the literature analysis study from Khan et al. [38] focused on risk mitigation in concurrent engineering in a new product development process. The approach of evolutionary acquisition via spiral development, or incremental development, was adopted against some of the existing risks using traditional methods in product development. Authors in this area state that incremental development can bring more advantages to developing mutable products, but it carries some other inherent risks. The studies from Mortlock [39] and Riposo et al. [40] identified some specific risks, such as technology, programmatic, and integration risks, and offered strategies to manage technical risks in product development. Other older studies in evolutionary acquisition have generally mentioned risks ^{[41][42][43][44]}[41,42,43,44].

4. Risks in Projects Applying Activity Overlapping—Construction

Studies of risks in construction projects applying activity overlapping continue to be developed, taking different approaches. These studies were either qualitative or quantitative, sometimes considering one type of risk (e.g., risk of rework, safety hazards) or a broader view of risk management. Lu et al. [45] explored the case study of accelerating two urgent emergency projects through activity crashing, overlapping, and substitutions during the COVID-19 pandemic. Although the authors recognized the possibility of risk when overlapping, they only considered the risk of rework. Laryea and Watermeyer [46] took a more qualitative approach to explore how uncertainty in fast-track construction projects in South Africa was managed using a case study and the client delivery-management approach. Rasul et al. [10], applying a qualitative systems thinking method—causal loop diagrams, investigated the interrelation of critical risk factors and their impact on performance indicators of fast-track projects. Additionally, quantitative and optimization models for construction projects incorporating risks continue to receive attention. Ma and Liu ^[47][48] developed a combined optimization model—Monte Carlo simulation, an optimization algorithm, and BIM visualization—to reduce the rework risk of overlapping dependent activities by introducing communication strategies. Yu et al. ^[48][49] developed an algorithm using a fuzzy dependency structured matrix (DSM)-based scheduling to diminish uncertainty in project cash flows and overdrafts in projects applying concurrency. Ballesteros-Pérez ^[49][50] examined the risk of an unsuccessful overlap and the impact consequence on the duration and cost of fast-track projects using Stochastic Network Analysis (SNA) techniques in a stochastic model. Using Monte Carlo simulation and the chronographic scheduling logic, Francis ^[50][51] modeled uncertainties in construction schedules, including uncertainties that might arise due to project acceleration (e.g., overlapping and crashing). Finally, Isaac and Edrei ^[51][52] developed a statistical model built on real-time tracking data to reduce the workers’ exposure to safety hazards that emerge from concurrent on-site activities.