Deficiencies causes in road construction scheduling: Perspectives from construction professionals

Abstract

Effective construction scheduling is crucial for the success of road projects. However, deficiencies in this scheduling can lead to significant challenges such as delays, cost overruns, and litigation. Therefore, project managers need to understand the causes that contribute to these deficiencies thoroughly. Unfortunately, there has been little research examining these elements in detail. To address this gap, this study examined the causes that affect the scheduling of construction processes for road projects. The research method involved four stages: (1) identification of causes affecting construction scheduling, (2) design and application of a questionnaire, (3) influence analysis, and (4) exploratory quantitative analysis. The study identified 34 causes of deficiencies in the scheduling of road construction processes in six categories: workforce, machinery, material, measurement, environment, and method. Thirty-two experts were consulted to evaluate the frequency and severity of each cause based on a relative influence index. The causes with the greatest impact on deficiencies in road construction scheduling were poor estimation of labor performance, poor estimation of workforce quantity, and deficient coordination with public utilities. The findings allow managers to pinpoint the root causes of road construction planning problems and identify effective solutions.

Highlights

• •The integration of traffic plans is crucial to improve road construction planning.
• •Deficiencies in schedule planning depend on a wide variety of variables.
• •The workforce estimation has a significant impact on road scheduling planning.
• •Coordination with public utilities is essential for road construction planning.
• •Proper estimation of permit acquisition times is crucial for construction planning.

1. Introduction

Road infrastructure is a crucial element of nations' economic and social progress, motivating governments to invest significantly in the creation and maintenance of road projects [1,2]. China is a notable example, with an investment of approximately 5.8 % of its GDP in road infrastructure in 2020 [3]. The private sector has also shown interest, with an estimated investment of US$76.2 billion in 2021 [4]. These investments aim to achieve greater efficiency, safety, and sustainability, which are fundamental to a country's international competitiveness [5]. Apart from their primary function, road projects have a profound impact on daily life, facilitating access to essential services such as health and education and promoting economic exchanges [6]. The World Economic Forum recognizes road infrastructure's significance as a key indicator of a nation's or region's competitiveness [5]. Connecting different geographical areas makes road infrastructure a vital link for moving people and goods [7]. However, implementing these projects poses significant challenges. One of the most prominent challenges is the effective planning and characterization of construction activities, which are necessary to turn initial plans into tangible realities while meeting established budget, time, and scope limits [8,9].

Meeting schedules, budgets, and planned scopes for road projects located in different geographic regions poses significant challenges [[10], [11], [12], [13]]. This situation has led industry professionals and researchers to conduct studies to identify the factors contributing to these problems [7,14]. Findings suggest that a major cause of delays, cost overruns, and disputes is deficiencies in construction planning and scheduling [12,[15], [16], [17]]. It has become clear that planners need to implement innovative methodologies and technologies to improve road construction management [8]. However, identifying the underlying causes of these problems can be complicated, given the large number of variables involved, which are interrelated and intertwined with high levels of complexity and uncertainty [18]. Therefore, project managers must understand the factors that influence project scheduling to take effective action for improvement. This understanding could enable managers to adopt emergent solutions to address the difficulties faced in the planning processes, leading to shortcomings often identified only at the construction stage.

Research has shown that road construction planning is mostly affected by issues with estimating the amount of work required, which affects the duration of activities [19]. The complexity of construction activities and the size of projects pose significant challenges for planners, as it is often difficult to include all the necessary tasks in the work breakdown structures (WBS) [20]. This can result in the omission of essential tasks, leading to unplanned activities that cause delays and cost overruns [10,16]. Another critical factor is the lack of integration between traffic management plans and construction schedules [21]. This disconnect forces contractors to adopt improvised measures during construction, leading to difficulties in carrying out activities as planned and increasing the impact on road users [22]. These factors emphasize the need for more comprehensive and coordinated planning to mitigate negative effects on road projects.

The planning of a road project is an integral process that involves not only the detailed definition of construction activities and the establishment of precise measurement units to estimate execution times but also the rigorous allocation and estimation of resources, including materials, equipment, and personnel [23]. In this context, integrating traffic data during the planning phase takes on critical relevance, especially to mitigate the impact on road users and guarantee the effective continuity of the works [24]. The lack of effective coordination between the scheduling of construction processes and traffic management at the construction site can trigger significant challenges for contractors. These challenges affect the continuity and compliance with the plans established in the initial stages of the project. Therefore, when building on existing road networks, planners must consider implementing alternative routes to ensure traffic flow [25]. This requires comprehensive studies and the integration of coherent and complementary traffic management plans into the planned construction processes, forming a framework that balances construction needs with existing traffic dynamics [26].

Planning in road construction projects is critical, as various influencing factors can cause deviations in project schedules, costs, and quality [27,28]. This variety of factors impacting planning requires meticulous attention. Therefore, it is essential to conduct studies that facilitate the adoption of solutions to improve the planning of these projects. To achieve this, project managers must thoroughly understand the elements that impact the planning of construction processes. However, there is a lack of research focused on identifying, synthesizing, and quantifying the level of influence of these causes of deficiencies in road construction planning. Given this knowledge gap, this study had three main aims: (1) to identify the primary causes contributing to deficiencies in the scheduling of road construction processes, (2) to estimate the magnitudes of the influences of these causes on project schedules, and (3) to explore the interrelationships between these causes through exploratory factor analysis (EFA). This integrative approach seeks to provide a deeper understanding and a basis for more effective scheduling strategies in road construction.

2. Background

2.1. Planning of construction schedules for road projects

Efficient and successful execution of road infrastructure projects requires schedule planning. This process entails data collection and feasibility analysis, detailed scheduling of construction activities, and optimal allocation of resources [29,30]. Proper schedule planning optimizes resource utilization and contributes to the project's development within the planned time, cost, and scope by creating realistic and feasible schedules [8]. Furthermore, this planning aids in the effective coordination of various project tasks, which is essential to identifying and mitigating associated risks during the construction stage [19]. By assessing such risks, the planner can anticipate potential problems and develop proactive mitigation strategies, thus minimizing the negative impact on the project.

The planning of construction schedules for road projects is critical. Many authors have studied ways to improve the planning process during the early stages of road projects. Their proposals aim to address various issues and enhance the planning process. Eldessouki et al. [31] presented a method that emulates the planning process in transportation improvement using mathematical optimization techniques. The method was validated using a case study in the Lisbon region of Portugal. The authors concluded that their approach could be successfully used in special situations, such as scheduling post-disaster transportation network restoration activities. Hassanein and Moselhi [30] proposed a model that integrates the planning and scheduling phases of road construction projects. The model automatically generates the work breakdown structure (WBS), establishes a precedence network that respects the logic of the jobs, and stores a list of common construction operations in highway projects. By analyzing a case study, they demonstrated the model's characteristics and applicability for planning highway construction operations. Dawood and Castro [32] developed a knowledge-based simulation system for highway construction to assist project managers in generating accurate and reliable construction plans for highways, which was applied to a case study. The results show that the proposed system allows for quick and accurate generation of the productivity and unit cost of road activities, facilitating the development of a schedule for a road construction project.

Mohammadi et al. [28] proposed a decision-making model to integrate life cycle (LC) principles into a classical formalized road maintenance planning and scheduling for a case study. The authors concluded that the proposed model can reduce operational complexity, lead time variability, and non-value-added activities. It can also help highway agencies minimize delays, allocate project resources optimally, and select qualified construction contractors more efficiently. In another study, Arditi and Bentotage [33] describe a system called Road Planner, which generates networks of activities and calculates their estimated durations. This system determines the duration of activities and sub-activities by internal rules and establishes precedence relationships between the main activities. The authors concluded that this system can assist planners in making more informed decisions by providing an initial draft that the planner can refine. Hosseininasab et al. [29] developed an integrated model for the selection, scheduling, and budgeting of urban road construction projects. They treated these projects as two-level, multi-objective, time-dependent network design problems. The model was applied to a case study in the city of Isfahan, Iran. The authors found that the proposed approaches were effective in terms of the solution's quality and the time required to find it.

Tang et al. [34] developed a systematic approach that integrates various factors such as time, cost, traffic, and risk to estimate contractual deadlines for road construction. By combining existing techniques for schedule and mobility impact assessment, they proposed seven steps that can help determine more appropriate and feasible contract schedules. To validate their approach, they conducted a case study based on a real project. They concluded that a time–cost–traffic trade-off analysis could be employed to quantify the impact of construction-caused traffic delays on contract time. This can facilitate the determination of a more accurate and feasible contract schedule. Miralinaghi et al. [35] examined the benefits of optimal scheduling with contract bundling compared to optimal scheduling of individual contracts. Their approach focuses on minimizing total system travel time and project costs while users seek to reduce their travel times in the network affected by work zones. To solve this problem, they employed a non-dominant sorting genetic algorithm. The results of their numerical experiments indicate that well-designed clustering in optimal scheduling can significantly reduce the project cost and total system cost, including project and travel time costs.

Previous research has focused mainly on developing advanced systems and methodologies to optimize simulations and budgeting and identify non-value-adding activities in road construction. Various effective approaches have been employed, such as mathematical optimization, knowledge-based simulation, and genetic algorithms, which have improved the planning and execution of road projects. However, a research gap exists concerning the causes that affect the planning of schedules for construction activities in road infrastructure projects. This study addressed this gap with the aim of achieving a more comprehensive understanding of these causes and improving the scheduling of road infrastructure projects.

2.2. Planning of construction traffic management schedules

Efficient planning of construction processes on road projects with pre-existing traffic requires the implementation of a detailed and comprehensive traffic management plan. The plan must be designed to optimally integrate construction activities with the specific dynamics of on-site vehicular traffic. Therefore, the traffic management plan is a crucial tool for ensuring the smooth and safe flow of vehicular and pedestrian traffic in specific areas during the construction stage. Its primary goals are to reduce congestion, lower the risk of accidents, and improve mobility, especially during road maintenance, improvement, or construction projects [21]. Developing an effective traffic management plan can be challenging as it requires coordination among various stakeholders, including traffic authorities, transportation experts, the local community, and design professionals [36,37]. It also demands a thorough assessment of key factors such as existing conditions, traffic volume, and available infrastructure. Failure to identify and analyze these factors can lead to poor or unsustainable solutions that do not effectively address traffic needs and challenges during road construction projects [38].

The field of traffic management planning has been studied from various perspectives. Alkhatib et al. [36] developed an intelligent system for road traffic management called Urban Traffic Control (UTC). This system monitors the traffic flow in real time and optimizes the management of the road traffic network. Application of the system achieved a 25.98 % decrease in the total average waiting time during the simulation period for all vehicles and a 34.16 % decrease in the non-interfering movement flow. Such effects are significant in complex traffic conditions with minimal infrastructure changes. Gong and Fan [39] analyzed the impacts of scheduling activities in long-term work zones from the perspectives of traffic agencies and jurisdictions. They used a genetic algorithm (GA)-based optimization model applied to a road network. The findings indicate that the GA model efficiently identified a near-optimal solution to a long-term work zone scheduling problem. Sun and Liu [40] proposed a simulation model for scheduling the operation of route diversion transit (RDT) to evaluate the stability and feasibility of the system under various demands. The simulation results showed that under various demand conditions, the system indicators in the RDT system, such as the passenger travel time, waiting time, and vehicle mileage, show little fluctuations, demonstrating the system's relatively stable performance.

Giridhar and Kumar [37] developed algorithms to solve the problem of automatic traffic scheduling in urban areas. Their algorithms were designed to decrease delays, increase capacity, and reduce congestion in cities. These algorithms are part of an integrated control, communication, and computing system that generates timed trajectories for individual vehicles, contributing to more efficient traffic flow management. Yang et al. [41] proposed a model for the daily scheduling of work zones. They introduced a day-by-day traffic assignment scheme with the objective of reducing the increases in travel costs caused by work zones. The model focuses on finding a balance between managing work zones and minimizing their impact on user costs. Their findings suggest that there is an optimal number of crews that can minimize the increase in travel costs due to the presence of work zones. Gómez and Orobio [42] analyzed the key factors affecting time and cost overruns in highway construction in southwestern Colombia. They studied 40 road construction projects and found that the activities with the greatest impact on time and cost overruns were the construction of the granular base and the asphalt layer. They noted that the most common causes of cost overruns in construction were related to rainfall and problems with the supply of materials.

Woldesenbet et al. [43] developed a model to estimate the production rate of road construction activities. The model considered factors that influence production rates, derived from the analysis and evaluation of data from highway agencies. The research concludes that using actual project data for production rate estimation is more reliable than using other common estimation methods such as expert opinion, engineering judgment, or production rate charts. Leandro et al. [44] developed an integrated production rate resource by collecting data from publicly available sources. The resource was tested by estimating the contract time of road projects, and the researchers concluded that the application led to significant improvements. Fisher and Rajan [38] created a prototype system for performing constructability analysis in road traffic control planning. The prototype system consists of three modules: a database module (CONTRAF), an expert system module (TRAPS), and a fuzzy programming module. The researchers concluded that it is feasible to provide generic constructability recommendations focused on traffic control through the use of this system and to access constructability databases before designing the final traffic control planning. This approach contributes to more efficient and effective traffic control management in roadway projects. Le et al. [45] identified 42 factors that influence the lead time of roadway projects. To identify these factors, the researchers analyzed existing literature and Construction Traffic Control (CTC) manuals. They conducted a nationwide survey and assessed the frequency of occurrence, level of influence, timing, and extent of impact of the identified factors. The results revealed that the most critical CTC factors include maintenance of traffic, production rates, environmental issues, project complexity, and utility-related issues.

The research trend on traffic management planning has focused on the development of simulation models to evaluate the impact of traffic management measures and the implementation of advanced technologies. Additionally, there has been the exploration of adaptive control strategies, intelligent transportation systems, and innovative approaches such as genetic algorithms, automatic programming, and fuzzy programming. Despite these advances, there is a lack of specific information and systemic knowledge about the causes that directly influence traffic management planning in road construction. This research gap highlights the need for more detailed studies that can provide a deeper understanding of effective traffic management planning before the construction stage.

3. Research method

The research method consisted of four stages. First, the causes that influence road construction scheduling were identified through a systematic literature review. Second, a questionnaire was designed and submitted to professional experts planning road project construction processes. Third, frequency and severity analyses were conducted using specific indexes based on the scores provided by the professionals. The fourth stage was an exploratory quantitative analysis conducted using statistical tools such as the Mann–Whitney U test and principal component analysis to examine the interrelationship between the identified causes. The research results were documented in the fifth stage. Fig. 1 illustrates the objective, method, tool, and analysis corresponding to each of the research stages.

Fig. 1.

Research method stages, adapted from Lozano et al. [46].

3.1. Identification of causes affecting construction scheduling

The first stage of the research method involved identifying the causes that lead to deficiencies in construction scheduling for road projects. A systematic review of the existing literature was conducted [7]. The systematic review technique is a detailed and organized process designed to answer specific research questions by exhaustively evaluating relevant literature. This methodology enables a comprehensive synthesis of existing knowledge in a specific area of study, highlighting its value in the coherent and reliable analysis of the evidence collected [47,48]. The process is structured around four main steps: (1) formulating the research question, (2) searching for relevant studies, (3) selecting documents based on previously defined inclusion criteria, and (4) analyzing and synthesizing the evidence collected, resulting in a detailed and structured report of the findings.

For the systematic review, a search of documents was carried out oriented to the resolution of the following research question: What are the main causes contributing to deficiencies in the planning of road construction processes? With this question as a starting point, essential keywords were identified and combined using the Boolean operators “AND” and “OR” to develop a search equation: [(“highway” OR “road” OR “motorway” OR “roadway”) AND (“scheduling” OR “construction planning” OR “construction traffic control” OR “contract time determination”) AND (factor OR cause OR reason)]. The Scopus search engine was used to identify an initial sample of 233 documents, which were evaluated and filtered using three inclusion/exclusion criteria: (1) the document addresses the planning of construction process schedules, (2) the document addresses causes contributing to deficiencies in the planning of construction processes schedules, and (3) the document focuses on roadway infrastructure projects. Each inclusion/exclusion criterion allowed progressive discrimination of the initial sample of 233 documents: the application of the first criterion reduced the sample to 27 documents, the second criterion resulted in 13 documents, and finally, the third criterion left 10 documents that met all the established criteria. Consequently, the 10 documents that met these three criteria formed the final sample for the collection of evidence, from which 34 causes were identified that contributed to deficiencies in the scheduling of road construction processes.

The 6M framework, which is recognized for its effectiveness in the analysis of problems in production and operational processes, was used to systematize the classification of the causes of deficiencies in road construction processes. According to this framework, the causes contributing to deficiencies in the scheduling of road construction processes were classified into the categories of workforce, machinery, environment, method, measurement, and materials, allowing a multidimensional approach to the identification of critical causes [49,50]. Each cause was carefully analyzed and assigned to the corresponding 6M classification based on its intrinsic nature and its influence on the schedule planning process. This methodological approach facilitated a logical and structured organization of the causes identified and provided a basis for the subsequent impact analysis and development of mitigation strategies specific to the road construction industry.

3.2. Questionnaire design and application

The purpose of the questionnaire was to estimate the frequency and severity of the various causes of construction scheduling failures in road projects. The survey was conducted by collecting opinions from a group of experts. The questionnaire consisted of two parts. The first part gathered information on categorical variables such as profession, highest academic degree, country of professional work, role in the construction industry, and years of experience. The second part focused on collecting frequency and severity ratings for 34 causes that affect schedule planning in road projects. Each cause was evaluated using two five-point Likert-type scales, where 1 and 5 represented very low and very high, respectively, for both frequency and severity. The survey was hosted on the Survey Monkey platform, making it easy to distribute to professionals through a URL link.

A preliminary version of the questionnaire was sent to five professionals who had more than five years of experience in road infrastructure projects (see Table 1). The purpose was to evaluate five key aspects of each proposed field: (1) the relevance of the field, (2) the clarity of the content, (3) observations based on the responses to the first two items, (4) the consistency between the 6M classification (workforce, machinery, environment, method, measurement, and materials) and the assigned cause, and (5) possible additional factors not included in the initial sample of 34 factors. After analyzing the responses and observations obtained, the authors made appropriate adjustments to the questionnaire. A revised version was then submitted to the same group of experts for a final validation process, which culminated in the approval of the final version of the questionnaire for use in the study (see Appendix A).

Table 1.

Professional profiles of experts who participated in the validation and calibration of the questionnaire.

Id	Profession (grade)	Country	Research Areas	Years of Experience
1	Civil Engineer, M.Sc., Ph.D.	Colombia	Planning and process control in construction works, management and optimization of	>30
2	Civil Engineer, M.Sc., Ph.D.	Colombia	Construction management and engineering, construction projects, construction management and engineering, lean construction, rural roads, data science in construction.	>20
3	Civil Engineer, M.Sc., Ph.D.	Colombia	Construction management and engineering, lean construction, building information modeling, integrated project delivery.	>10
4	Civil Engineer, M.Sc., Ph.D.	Chile	Project management, lean construction, engineering education.	>10
5	Civil Engineer, M.Sc., Ph.D.	Chile	Virtual and design construction, building information modeling, project management.	>5

The final version of the questionnaire was sent to 45 professionals in the architecture, engineering, and construction (AEC) industry with experience in planning construction processes for road projects. Of these 45 professionals, 42 responded to the questionnaire, resulting in a response rate of 93.3 %. A thorough review of the 42 completed questionnaires was conducted to verify their completeness and accuracy. As a result, 10 questionnaires were discarded as incomplete, and 32 were included in the final analysis. Of the 32 participants whose responses were analyzed, 59.4 % held Master's and Doctoral degrees (see Table 2), 84.4 % had more than five years of experience in road infrastructure projects, 56.3 % had roles in the sector (designer, consultant/auditor, contractor, owner, or other), and 43.8 % had roles in academia and research (see Table 3). In terms of geographical distribution of experience, 62.5 % were located in Colombia and 37.5 % were located in Chile (see Table 4).

Table 2.

Characterization of grade and professional roles.

Professional Roles Grade	Designer	Consultant/Auditor	Contractor	Owner	Academic/Researcher	Other	Total
Undergraduate	3 (9.4 %)	–	1 (3.1 %)	1 (3.1 %)	1 (3.1 %)	1 (3.1 %)	7 (21.9 %)
Specialization	–	1 (3.1 %)	3 (9.4 %)	1 (3.1 %)	–	1 (3.1 %)	6 (18.8 %)
Master's Degree	–	3 (9.4 %)	3 (9.4 %)	–	2 (6.3 %)	–	8 (25.0 %)
Doctorate	–	–	–	–	11 (34.4 %)	–	11 (34.4 %)
Total	3 (9.4 %)	4 (12.5 %)	7 (21.9 %)	2 (6.3 %)	14 (43.8 %)	2 (6.3 %)	32 (100 %)

Table 3.

Characterization of professional roles and years of experience.

Years of experience Professional Roles	Less than 5 years	From 5 to 10 years	From 10 to 15 years	More than 15 years	Total
Designer	1 (3.1 %)	1 (3.1 %)	1 (3.1 %)	–	3 (9.4 %)
Consultant/Auditor	1 (3.1 %)	–	–	3 (9.4 %)	4 (12.5 %)
Contractor	1 (3.1 %)	3 (9.4 %)	1 (3.1 %)	2 (6.3 %)	7 (21.9 %)
Owner	–	1 (3.1 %)	–	1 (3.1 %)	2 (6.3 %)
Academic/Researcher	2 (6.3 %)	4 (12.5 %)	5 (15.6 %)	3 (9.4 %)	14 (43.8 %)
Other	–	2 (6.3 %)	–	–	2 (6.3 %)
Total	5 (15.6 %)	11 (34.4 %)	7 (21.9 %)	9 (28.1 %)	32 (100 %)

Table 4.

Characterization of professional roles and country.

Country Professional Roles	Chile	Colombia	Total
Designer	2 (6.3 %)	1 (3.1 %)	3 (9.4 %)
Consultant/Auditor	2 (6.3 %)	2 (6.3 %)	4 (12.5 %)
Contractor	1 (3.1 %)	6 (18.8 %)	7 (21.9 %)
Owner	2 (6.3 %)	1 (3.1 %)	3 (9.4 %)
Academic/Researcher	5 (15.6 %)	9 (28.1 %)	14 (43.8 %)
Other	1 (3.1 %)	–	1 (3.1 %)
Total	12 (40.6 %)	20 (59.4 %)	32 (100 %)

As a crucial step in validating our research instrument, we conducted a Cronbach's alpha analysis to assess the internal consistency of the questionnaire responses obtained from the Frequency and Severity sections (refer to equation (1)). In quantitative research that involves collecting data through questionnaires, Cronbach's alpha coefficient is a critical measure of reliability for the scales used. It provides an estimate of internal consistency for the items in a test. Cronbach's alpha ranges from 0 to 1, where α ≥ 0.9 is excellent, 0.8 ≤ α < 0.9 is good, 0.7 ≤ α < 0.8 is acceptable, 0.6 ≤ α < 0.7 is questionable, 0.5 ≤ α < 0.6 is poor, and α < 0.5 is unacceptable. The value of α is calculated as follows [51]:

$$\mathrm{\alpha }=\frac{K}{K-1}\left(1-\frac{\sum _{i=1}^k{S}_i}{S_t}\right)$$ (1)

where $K$ is the number of causes of deficiencies in the planning of road construction schedules ($K=34$), $S_i$ is the variance of the scores assigned to the frequency and severity of each cause of schedule planning deficiencies, and $S_t$ is the total variance of the frequency and severity.

Cronbach's alpha analysis was performed for frequency and severity scores. Alpha values of 0.95 and 0.93 were obtained for frequency and severity, respectively. These values indicate excellent internal reliability, i.e., highly consistent and reliable responses, reinforcing the credibility of the research instrument used in the study.

3.3. Influence analysis

A relative influence index (RII) analysis was conducted to determine the most influential causes of scheduling deficiencies in road infrastructure projects. The analysis was based on the frequency and severity scores obtained from a questionnaire answered by professionals in the sector. By providing a quantitative ranking of the causes, the RII analysis identified the ones that require priority attention in the schedule planning process. The relative frequency index (RFI) and relative severity index (RSI) were calculated using Equations (2), (3)), respectively, based on the responses collected from the 32 questionnaires:

$$RFI=\left(\frac{\sum _{i=1}^N{f}_i}{Nx{f}_{\mathit{max}}}\right)$$ (2)

$$RSI=\left(\frac{\sum _{i=1}^N{s}_i}{Nx{s}_{\mathit{max}}}\right)$$ (3)

where $f_i$ and $s_i$ are the frequency and severity weights, respectively, assigned by the evaluator $i$; $N$ is the total number of valid questionnaires ($N=32$); and $f_{\mathit{max}}$ and $s_{\mathit{max}}$ are the maximum possible weights for frequency and severity, respectively ($f_{\mathit{max}}=s_{\mathit{max}}=5$). The Relative Influence Index (RII) was obtained from the $RFI$ and $RSI$ indices using Equation (4).

$$RII=RFI\times RSI$$ (4)

The RII (composite index) provides a view of the impact of each cause by combining its frequency of occurrence and perceived severity. By using the RII, it was possible to rank each cause based on its relative importance. This ranking helped to identify the causes that require more attention in planning road project schedules, which in turn prioritizes efforts and resources. It helped to gain a better understanding of each cause and its relationship with other causes.

3.4. Exploratory quantitative analysis

The exploratory quantitative analysis was divided into three parts: (1) a Mann–Whitney U test, (2) a relative frequency analysis, and (3) an exploratory factor analysis (EFA). The first part focused on the Mann–Whitney U test in the Statistical Package for the Social Sciences (SPSS) software. This analysis was performed to evaluate whether there were significant differences in the perception of construction industry professionals regarding the frequency and severity of 34 causes that affect the planning of schedules in road projects. The analyzed data represents the scores given by 32 consulted experts. Their responses offer a quantitative evaluation of how professionals perceive these causes. Participants were divided into different analysis groups based on the collected information categories of experience, role, and grade, as presented in Table 5. These variables were considered independent and were crucial for comparative analysis.

Table 5.

Variables and groups of analysis.

Category	Categorical variables	Analysis groups
Experience	Less than 5 years	Experience <10 years
	From 5 to 10 years
	10–15 years	Experience >10 years
	More than 15 years
Role	Designer	Sector
	Consultant/intervenor
	Contractor
	Owner
	Other
	Academic/researcher	Academy
Grade	Undergraduate	Undergraduate/Specialization
	Specialization
	Master's Degree	Master's/Doctorate
	Doctorate
	Postdoctoral

The Mann–Whitney U test was used to determine whether there were significant differences in perception between different groups. The null hypothesis (H₀) was that there were no such differences, while the alternative hypothesis (H₁) was that there were such differences. The Mann–Whitney U statistic was employed to calculate the statistical significance of these differences, with a p-value below 0.05 suggesting significant differences. This systematic approach allowed for the evaluation of how professionals’ experience, role, and grade affected their perception of the causes that influence the planning of road project schedules. Consequently, this approach provided valuable information into improving the planning processes of road infrastructure projects.

Application of the Mann–Whitney U test revealed significant differences among professionals’ perceptions based on their experience, role, and grade categories. An additional analytical approach (a relative frequency analysis) was employed to examine these findings further and pinpoint the specific analysis groups that displayed divergent opinions within these categories. Consequently, a Relative Frequency Analysis was conducted, which constituted the second part of the Exploratory Quantitative Analysis. This analysis aimed to investigate in greater detail the causes behind the significant differences identified earlier using the Mann–Whitney U test. The main purpose of the bar graphs produced was to provide visual representations of the distributions and variability of responses within different analysis groups (see Table 5).

The relative frequency analysis played a crucial role, providing a clear and concise visual representation of the distribution of perceptions within each analysis group. Bar graphs helped to highlight the medians and dispersion of responses. They were also helpful in determining whether the observed differences were uniform across the entire spectrum of responses or whether extreme values skewed them. Bar graphs also facilitated the identification of trends and anomalies that may signal particularly divergent opinions within a group. Using this tool, we were able to enrich the analysis with a more detailed perspective of how experience, role, and grade influence professionals’ perceptions of the causes that lead to shortcomings in road project schedule planning. The descriptive dimension provided by bar graphs complemented the results obtained through the Mann–Whitney U test, giving us a better understanding of the data.

A third part was dedicated to the severity scores of the 34 identified causes through Exploratory Factor Analysis (EFA). The focus was to gain a better understanding of the essential dimensions that affect the perceived severity of the causes leading to deficiencies in the planning of road project schedules. The naming and interpretation of each component were based on the causes they grouped, providing a more detailed and focused discussion of critical aspects affecting schedule planning in road infrastructure projects. This approach revealed groupings or patterns not initially visible, offering a deeper insight into how practitioners interpret and prioritize these causes. The EFA analysis helped to identify seven primary groups of the causes studied: (1) project preparation and contextual conditions, (2) scope and schedule planning, (3) traffic management planning, (4) underestimation of project complexity, (5) shortcomings in resource estimation, (6) consideration of external factors, and (7) accuracy in planning and operational complexity.

The Kaiser–Meyer–Olkin measure of sampling adequacy (KMO) was used to ensure the adequacy of the EFA. KMO values range from 0 to 1, where a value above 0.5 is acceptable, a value above 0.7 is good, and values above 0.8 or 0.9 are considered excellent. The KMO obtained for the analyzed dataset was 0.61, which confirms that the EFA was relevant. This measure is crucial because a low KMO value suggests that factor analysis would not be appropriate or informative. A significant result from this test indicates that the variables are sufficiently correlated to proceed with factor analysis. Overall, the EFA supported the understanding of perceptions of the severity of causes in road project schedule planning and identified latent structures that could be instrumental in developing more effective and targeted strategies for managing actions to prevent deficiencies in road schedule planning processes.

4. Results and discussion

4.1. Causes affecting construction scheduling

The systematic literature review identified 34 causes that lead to deficiencies in the planning of road construction processes. These causes were grouped into six main classifications: workforce, machinery, environment, method, measurement, and materials, as presented in Table 6. In the workforce classification, shortcomings include inadequate identification of project stakeholders, poor understanding of the project by the planner, and erroneous estimates of the workforce's quantity and output, often exacerbated by the planner's lack of experience. In the machinery classification, problems arise due to poor planning of machinery routes, underestimates of construction process constraints (such as machine capacity and ground conditions), and inadequate planning of equipment operational requirements. With respect to the material classification, poor estimates of material quantities and inadequate planning of supplies are highlighted.

Table 6.

Causes contributing to deficiencies in planning schedules for road construction processes.

Classification	Causes contributing to deficiencies in the scheduling	Reference
Workforce	Poor identification of project stakeholders	[45,52]
	Poor understanding of the project by the planner	[45]
	Poor estimation of workforce quantity	[45]
	Poor estimation of workforce performance	[53,54]
	Lack of experience of the planner	[45]
Machinery	Poor planning of machinery routes	[55]
	Poor estimation of construction process constraints (machine capacity, number of personnel, and terrain conditions, among others)	[45,53]
	Poor planning of equipment/machinery operation requirements	[45]
Material	Deficient estimation of material quantities	[38,53,54]
	Deficient estimation of material supply (stocks)	[53]
Measurement	Failures in on-site traffic estimation	[38,53,54]
	Lack of verification during the schedule preparation	[54]
	Deficient hierarchy/priority of project roads	[38,53,54]
	Inadequate estimation of permit acquisition durations	[45,53,54]
	Inadequate estimation of construction document approval times	[53,54]
	Inadequate estimation and consideration of waiting times (setting time or other waiting times between activities)	[45,53,54]
Environment	High complex access to the project area	[52,54,56]
	Deficient project location	[45,56,57]
	Deficient coordination with public utilities (water, sanitary, electrical, and other surface or subway networks)	[45,53,54,57]
	Inadequate weather forecasting	[45,54,56]
	Inadequate exploration of existing site conditions	[45,53,55]
	Inadequate planning of the articulation with neighboring areas	[53,55]
	Lack of political/social considerations in planning	[45,54]
Method	High complexity of construction work	[45,53]
	Poor planning of alternate routes and pedestrian trails	[38,53,54]
	Lack of planning of storage and parking sites	[53]
	Failures in the configuration of the work schedule (working days, holidays, working hours, seasons of the year)	[34,45,53,54]
	Omission of road markings in planning	[53,54]
	Inadequacy of planning software adopted	[45]
	Request for project start time extensions (applies in cases of rescheduling requests)	[58]
	Omission or deficiency in the definition of work packages (WBS)	[38,53]
	Poor zoning of the construction process based on traffic conditions	[38,54]
	Failures in the definition of successor and predecessor relationships between activities	[53]
	Inadequate selection of construction methods	[34,45,53,54]

The measurement classification includes failures in estimating site traffic, lack of verification during schedule preparation, and inadequate estimates related to permit acquisition and construction document approval. Causes in the environment classification also play critical roles, with complex access to the project area, poor project location, inadequate coordination with utilities, inadequate weather forecasting, and insufficient exploration of site conditions being key factors. Finally, under the method classification, complexities in construction works, poor planning of alternative routes and storage sites, failures in work schedule configuration, omission of road markings in planning, and inadequate selection of construction methods are noted, often leading to extensions of project start times and deficiencies in defining work packages.

The causes of deficiency in the planning of road project schedules, mainly identified in the literature, were: Deficient coordination with public utilities (water, sanitary, electrical, and other surface or subway networks), Failures in the configuration of the work schedule (working days, holidays, working hours, seasons of the year), Inadequate selection of construction methods, Failures in on-site traffic estimation, Deficient hierarchy/priority of project roads, and Inadequate estimation of permit acquisition durations, among others. These causes are recurrently mentioned due to their direct and significant impact on the execution as well as on the compliance with the deadlines of road projects. Poor coordination with utilities can result in interferences and delays, while failures in the work schedule can misalign human and material resources [59]. Improper selection of construction methods and incorrect traffic estimation affect the efficiency and safety of the project [60]. In addition, poor road prioritization and underestimation of permitting can lead to unforeseen disruptions and delays. These deficiencies, when not adequately addressed, can increase costs, prolong delivery times and reduce project quality, thus highlighting the importance of meticulous and coordinated planning, as discussed by several studies and authors in the field of road project management.

4.2. Influence analysis

Fig. 2 shows the percentage frequency and severity profiles of the 15 most critical causes that have an impact on the planning of road infrastructure project schedules. Based on the 34 causes of deficiency identified in section 4.1 and the responses collected from the questionnaire described in section 3.2, a frequency and severity analysis was performed (see section 3.3), using Equation (2) for frequency and Equation (3) for severity. This questionnaire was implemented to the satisfaction of 32 industry professionals (see Table 2, Table 3, Table 4). A five-point Likert scale was used to evaluate each cause, and each was assigned a distinctive color to indicate the magnitude of relative frequency (see Fig. 2 (a)) and relative severity (see Fig. 2 (b)). The colors represent very low (dark green), low (light green), medium (yellow), high (light red), and very high (red) severity levels. This chromatic representation facilitated understanding of the data and highlighted the areas of greatest concern. Practitioners can use this information to identify and prioritize the most important mitigation strategies. Thus, on the one hand, the five most frequent causes are poor estimation of labor performance (WF₁), poor estimation of workforce quantity (WF₂), inadequate weather forecasting (ENV₂), request for project start time extensions (applies in cases of rescheduling requests) (MET₁), and inadequate estimation of permit acquisition durations (MEA₁). The most severe causes affecting schedule planning in road projects are lack of experience of the planner (WF₃), deficient coordination with public utilities (water, sanitary, electrical and other surface or subway networks) (ENV₁), poor estimation of workforce performance (WF₁), inadequate estimation of permit acquisition durations (MEA₁), and poor estimation of workforce quantity (WF₂).

Fig. 2.

Frequency and severity percentages of the 15 most influential causes. (a) frequency, (b) severity.

The group of 32 professionals identified the most frequent and severe causes of road project schedule planning, which highlight several challenges and critical areas of attention in the construction industry. Poor estimation of workforce performance (WF₁) and poor estimation of workforce quantity (WF₂) suggest gaps in understanding and realistic planning of labor productivity. Inadequate weather forecasting (ENV₂) underscores the significant impact of unpredictable weather on schedules. Request for project start time extensions (applies in cases of rescheduling requests) (MET₁) and inadequate estimation of permit acquisition durations (MEA₁) reflect problems in the initial schedule planning phase, from funding to legal logistics. Poor identification of project stakeholders (WF₃) and deficient coordination with public utilities (water, sanitary, electrical, and other surface or subway networks) (ENV₁) highlight the need for expert planning and efficient coordination. These causes, highlighted by practitioners, require attention to optimize road project planning and execution.

Table 7 shows the values obtained for the relative frequency index (RFI), relative severity index (RSI), and relative importance index (RII) for each of the 32 causes of deficiencies in the planning of road schedules. The top 10 causes with the greatest influence on schedule planning, according to expert opinion, are (1) poor estimation of workforce performance (WF₁), (2) poor estimation of workforce quantity (WF₂), (3) deficient coordination with public utilities (water, sanitary, electrical and other surface or subway networks) (ENV₁), (4) inadequate estimation of permit acquisition durations (MEA₁), (5) inadequate weather forecasting (ENV₂), (6) deficient estimation of material quantities (MAT₁), (7) inadequate estimation of construction document approval times (MEA₂), (8) request for project start time extensions (applies in cases of rescheduling requests) (MET₁), (9) inadequate exploration of existing site conditions (ENV₃), and (10) lack of experience of the planner (WF₃). In Table 7, a low range and variability can be identified among the causes. For instance, the maximum RFI value is 0.74, and the minimum is 0.53, resulting in a range of 0.21. Similarly, the maximum RSI value is 0.83, and the minimum is 0.65. This low variability is due to the fact that each of these causes has been considered relevant in prior studies, as explained in section 3.1, ‘Identification of Causes Affecting the Construction Schedule.' Therefore, it is logical that all have values above 0.5. Nonetheless, since all these causes can be present in a construction project, it is necessary to focus efforts and prioritize those with the greatest impact in terms of frequency and severity. Thus, lower-ranked causes are not deemed unimportant but rather that other causes need to be addressed first. This will be further elaborated upon in the subsequent section.

Table 7.

Severity, frequency, and influence of causes contributing to deficiencies in schedule planning of road construction processes.

Classification	Id	Causes contributing to deficiencies in the scheduling	RFI	Rank	RSI	Rank	RII	Rank
Workforce	WF1	Poor estimation of workforce performance	0.74	1	0.82	3	0.61	1
	WF2	Poor estimation of workforce quantity	0.73	2	0.81	5	0.59	2
	WF3	Lack of experience of the planner	0.64	18	0.83	1	0.53	10
	WF4	Poor understanding of the project by the planner	0.66	14	0.79	11	0.52	13
	WF5	Poor identification of project stakeholders	0.60	28	0.71	27	0.42	28
Machinery	MAC1	Poor planning of machinery routes	0.67	11	0.78	15	0.52	12
	MAC2	Poor estimation of construction process constraints (machine capacity, number of personnel, and terrain conditions, among others)	0.65	15	0.76	18	0.50	20
	MAC3	Poor planning of equipment/machinery operation requirements	0.62	26	0.73	23	0.45	24
Material	MAT1	Deficient estimation of material quantities	0.70	7	0.81	5	0.57	6
	MAT2	Deficient estimation of material supply (stocks)	0.64	22	0.79	9	0.51	16
Measurement	MEA1	Inadequate estimation of permit acquisition durations	0.71	5	0.82	3	0.58	4
	MEA2	Inadequate estimation of construction document approval times	0.69	8	0.80	8	0.56	7
	MEA3	Failures in on-site traffic estimation	0.68	10	0.78	15	0.52	11
	MEA4	Lack of verification during the schedule preparation	0.69	9	0.75	21	0.52	14
	MEA5	Inadequate estimation and consideration of waiting times (setting time or other waiting times between activities)	0.65	15	0.78	12	0.51	15
	MEA6	Deficient hierarchy/priority of project roads	0.56	33	0.70	28	0.39	30
Environment	ENV1	Deficient coordination with public utilities (water, sanitary, electrical and other surface or subway networks)	0.71	5	0.83	1	0.58	3
	ENV2	Inadequate weather forecasting	0.72	3	0.79	9	0.57	5
	ENV3	Inadequate exploration of existing site conditions	0.66	12	0.81	7	0.53	9
	ENV4	Inadequate planning of the articulation with neighboring areas	0.64	18	0.78	12	0.50	17
	ENV5	Lack of political/social considerations in planning	0.66	12	0.73	24	0.48	21
	ENV6	High complex access to the project area	0.63	23	0.73	24	0.45	23
	ENV7	Deficient project location	0.53	34	0.68	31	0.35	34
Method	MET1	Request for project start time extensions (applies in cases of rescheduling requests)	0.71	4	0.76	20	0.54	8
	MET2	Omission or deficiency in the definition of work packages (WBS)	0.64	18	0.78	12	0.50	17
	MET3	Poor zoning of the construction process based on traffic conditions	0.65	15	0.77	17	0.50	19
	MET4	Failures in the definition of successor and predecessor relationships between activities	0.62	26	0.75	21	0.46	22
	MET5	High complexity of construction work	0.63	23	0.72	26	0.45	25
	MET6	Inadequate selection of construction methods	0.59	29	0.76	18	0.45	26
	MET7	Poor planning of alternate routes and pedestrian trails	0.64	18	0.67	32	0.43	27
	MET8	Lack of planning of storage and parking sites	0.63	23	0.67	32	0.42	29
	MET9	Failures in the configuration of the work schedule (working days, holidays, working hours, seasons of the year)	0.56	30	0.68	29	0.38	31
	MET10	Omission of road markings in planning	0.56	30	0.68	29	0.38	31
	MET11	Inadequacy of planning software adopted	0.56	30	0.65	34	0.37	33

4.2.1. Workforce

Poor estimation of workforce performance (WF₁), poor estimation of workforce quantity (WF₂), and lack of experience of the planner (WF₃) are the most common challenges reported by professionals in the workforce classification. These factors are critical in planning project schedules, as human performance can vary due to factors such as motivation, experience, and health. Inaccurate estimation of performance and labor quantity in construction process planning can lead to significant delays, causing tasks to remain incomplete due to understaffing or low productivity. This can lead to a disruption in the sequence of construction activities, resulting in delays in subsequent stages of the project [61]. Additionally, a less experienced planner may not be able to anticipate the complexity of construction tasks and traffic management needs, leading to unrealistic schedules, underestimation of required resources, and ineffective strategies for handling unforeseen challenges [62]. This can result in construction delays and tasks not being executed as planned. Efficiency and speed are critical in executing a traffic management plan to minimize traffic disruption. Inaccurate workforce estimation can prolong the duration of the work, resulting in an extended period in which traffic management measures such as detours and temporary signage are needed [55]. This increases inconvenience to road users and increases safety risks due to the prolonged coexistence of work zones and vehicular flows. In addition, poor implementation of traffic control measures, such as inadequate signage and poorly planned detour routes, can increase the risk of congestion and accidents [40].

4.2.2. Environment

Inadequate weather forecasting (ENV₂), deficient coordination with public utilities (water, sanitary, electrical, and other surface or subway networks) (ENV₁), and inadequate exploration of existing site conditions (ENV₃) are the three primary factors that fall under the Environmental classification. These factors emphasize the challenges of integrating uncertain environmental variables into effective schedule planning, a complex aspect recognized in project risk studies. They also suggest an opportunity for improvement in integrating planning with the external environment and existing infrastructure. If current site conditions, such as topography, infrastructure, and traffic characteristics, are not adequately assessed, unforeseen problems may arise during construction [45]. This can lead to delays and the need to modify construction plans, as unforeseen conditions require unexpected adaptations in construction methods, forcing professionals to make modifications to construction plans [61].

Insufficient understanding of the environment can result in inadequate planning of detours, signage, and safety measures. This increases inconvenience to road users and heightens safety risks by not considering existing traffic dynamics and interactions with the construction zone [21]. Therefore, a detailed and accurate exploration of existing site conditions is vital to ensure efficient execution of construction processes and traffic management with minimal possible impact on normal traffic flow [41]. In addition, the unpredictability of weather and ineffective coordination with utilities underscore the importance of flexible and adaptive planning, capable of responding to changes and complexities. Improving uncertainty management and fostering collaboration among all stakeholders is crucial to mitigating negative impacts on project schedules and strengthening responsiveness to environmental and infrastructure challenges.

4.2.3. Measurement

Inadequate estimation of permit acquisition durations (MEA₁) and inadequate estimation of construction document approval times (MEA₂) are the primary causes that affect schedule planning in the Measurement classification. These issues can lead to delays in the start and execution of work, which can result in a chain of delays that affect logistics, safety, and operational continuity. MEA₁ and MEA₂ can trigger delays in starting and progressing work, disrupting planned phases and on-site operations. In the context of traffic management, this can prolong disruptions to road users, exacerbating congestion and accident risks [63]. Similarly, in construction execution, this can lead to a cascade of delays that impact resource availability, sequencing of construction activities, and operational efficiency, resulting in additional costs and potential contractual penalties.

Lack of verification during the schedule preparation (MEA₄) can result in schedules that are incomplete or unrealistic. Such schedules can lead to the underestimation of time needed for specific tasks or the omission of critical project phases. Inadequately verified schedules can result in a lack of planning for signage that is necessary to guide and protect both road users and workers [64]. This includes warning signs, barriers, and detour routes, which must be placed and timed properly with the construction stages. Moreover, the absence of detailed and accurate planning can create confusion or danger for drivers, increasing the likelihood of accidents and decreasing safety in the construction area. On the construction side, the lack of verification can cause problems in the sequence of construction activities, which negatively impacts productivity and efficiency, resulting in delays and cost overruns. This emphasizes the importance of regular reviews during planning to ensure that road projects are feasible and schedules are accurate.

4.2.4. Materials and methods

It is crucial to accurately estimate material quantities (MAT₁) needed for a construction project accurately. Poor estimation can disrupt the workflow, affect the sequence of activities, and ultimately prolong the project's duration [62]. This can also have an impact on the traffic management plan, as it will require additional logistics to manage any excess or deficit of materials on site. This can further complicate the execution of the works and the overall traffic management. When there is a need to reschedule a project, the request for project start time extensions (applies in cases of rescheduling requests) (MET₁), a cause in the method classification, becomes important. This is because rescheduling directly affects the sequence and duration of construction activities, which can result in a need to adjust resources, reorganize work sequences, and potentially face additional costs due to delays. In addition, if there is an extension at the start of the project, the traffic management plan must be adapted. This includes updating the planning of road signage, implementing alternative routes, and ensuring safety measures during construction. It is important to review and adjust strategies to minimize the impact on traffic flow and maintain the safety of road users and workers on site. For instance, planned detours and signage may need to be extended or modified to align with the new project schedule [24]. This helps to maintain traffic management efficiency and safety at the construction site.

4.2.5. Machinery

Poor planning of machinery routes (MAC₁) in road projects can significantly affect both the construction process and traffic management plan. Inadequate planning of the routes along which machinery will move can lead to inefficiencies and delays in construction activities. For instance, the equipment may not be available where and when it is needed, or it can cause congestion and conflicts with ongoing operations, which directly affects the sequence and pace of work on the construction site. Moreover, in the context of traffic management, inefficient movement of heavy machinery can increase road safety risks for both workers and road users [24]. It may also require additional detours or more complex traffic control measures, which increases inconvenience to the public and prolongs the impact of the project on normal traffic flow. Therefore, it is crucial to plan machinery routes carefully to optimize construction efficiency and minimize traffic disruptions, ensuring smooth and safe progress of the road project. Effective schedule planning can be compromised by various causes that can vary in the frequency of how often certain events may occur and the severity or impact that the presence of these causes can have on schedule planning activities [65,66]. Thus, a frequency and severity analysis was carried out with the objective of identifying and evaluating the main causes with the greatest impact on schedule planning in road infrastructure projects and prioritizing potential risks.

4.3. Dispersion analysis

Fig. 3 represents the dispersion analysis performed to evaluate the relationship between the relative frequency index on the (x) axis and the relative severity index on the (y) axis of the 34 causes affecting schedule planning in road projects identified in section 4.1. This analysis is represented by a two-dimensional graph with four quadrants. The upper right quadrant groups the causes with high RFI and RSI values, underscoring their critical nature and the need for immediate attention due to their significant and recurrent impact on schedule planning. The upper left quadrant groups the causes characterized by low RFI but high RSI values, which point to serious but less frequent problems that require the implementation of robust contingency plans. The lower right quadrant groups the causes with high RFI but low RSI values, which identifies areas conducive to continuous operational improvements and minor adjustments. The lower left quadrant groups the causes with low values for both RFI and RSI, pointing to less critical problems that demand a reduced level of attention. This dispersion analysis provides a clear basis for prioritization and strategic focus in planning schedules for road infrastructure projects.

Fig. 3.

Dispersion of causes with respect to RFI and RSI.

The data analysis showed that certain causes have a high frequency and severity. These include poor estimation of workforce performance (WF₁), poor estimation of workforce quantity (WF₂), deficient coordination with public utilities (water, sanitary, electrical, and other surface or subway networks) (ENV₁), inadequate estimation of durations required for obtaining necessary permits (MEA₁), inadequate weather forecasting (ENV₂), deficient estimation of material quantities (MAT₁), inadequate estimation of construction document approval times (MEA₂), request for project start time extensions (applies in cases of rescheduling requests) (MET₁), inadequate exploration of existing site conditions (ENV₃), and lack of experience of the planner (WF₃). These findings highlight the significance of careful planning and the need to strengthen competencies in resource estimation and coordination, which are vital for the successful execution of road projects. Thus, managers of road projects should consider taking corrective and preventive measures to mitigate the risk of occurrence of causes that exhibit high frequency and severity, which could have a large impact on the improvement of road schedule planning processes.

In Fig. 3, a moderate correlation (R² = 0.58) between the RSI and the RFI can be observed. This correlation suggests that as the RFI increases, the RSI also tends to increase for the same causes. This relationship is consistent with the underlying assumption that factors with high relevance (RFI) are likely to have a significant impact (RSI) on the construction schedule. However, it is important to note that while this moderate correlation provides a useful insight into the general trend, it does not imply a perfect or direct causation. Each cause's impact on the construction schedule is multifaceted and influenced by various project-specific factors. Therefore, this correlation should be interpreted as an indication of a trend rather than a definitive rule. Further analysis and contextual consideration are necessary to understand the nuances of each cause's impact.

4.4. Exploratory quantitative analysis

This section presents an exploratory quantitative analysis, divided into three subsections: 4.4.1. Mann-Whitney U test, 4.4.2. Relative Frequency Analysis and 4.4.3. Exploratory Factor Analysis. The Mann-Whitney U test was used to evaluate the concordance between two analysis groups (see Table 5), which identified significant differences in the responses collected by the 32 participants. Next, a Relative Frequency Analysis was carried out to determine which analysis group did not present a clear consensus according to the results obtained from the Mann-Whitney U test. Finally, an Exploratory Factor Analysis was applied to reduce the dimensionality of the data and to discover the sub-structures as a product of the responses collected.

4.4.1. Mann–Whitney U test

A study was conducted to determine the factors that affect the planning of road infrastructure project schedules. The Mann–Whitney U test was performed on 34 causes based on their frequency and severity. The results were then categorized by experience, role, and training. The null hypothesis (H₀) was that there were no significant differences in perception between the different classified groups, while the alternative hypothesis (H₁) stated that there were differences. A statistical significance threshold of p < 0.05 was used to determine which causes required special attention in the context of planning schedules for road infrastructure projects. The results showed at least one significant difference between the various categories evaluated, both in terms of frequency and severity. Table 8 presents the causes with p-values <0.05, with the experience category being the most notable. This category showed a significant difference compared to role and training, indicating that experience is a key factor in perceiving the severity of certain causes during the planning.

Table 8.

P-values from Mann–Whitney U test.

Category	Experience		Grade		Role
	Frequency	Severity	Frequency	Severity	Frequency	Severity
Id	P-value U-Mann Whitney
MET3	0.396	0.004	0.533	0.935	0.796	0.468
ENV1	0.277	0.005	0.702	0.934	0.705	0.461
MET1	0.421	0.020	0.462	0.55	0.755	0.726
MEA3	0.722	0.021	0.344	0.747	0.319	0.110
WF5	0.101	0.022	0.355	0.780	0.968	0.906
ENV4	0.199	0.025	0.983	0.643	0.608	0.402
MET5	0.770	0.042	0.067	0.829	0.946	0.881
ENV5	0.611	0.049	0.690	0.575	0.937	0.394
MEA1	0.488	0.062	0.079	0.425	0.013	0.023
MEA4	0.687	0.108	0.013	0.177	0.394	0.808
MAC1	0.456	0.167	0.603	0.193	0.212	0.017
MET2	0.041	0.493	0.967	0.886	0.885	0.791
ENV2	0.163	0.592	0.441	0.034	0.253	0.795
WF3	0.071	0.651	0.185	0.476	0.031	0.772

Experience conveys a deeper understanding of the impact that certain causes can have on road projects than the role and grade categories. The study revealed eight causes for which experience significantly differed from the other categories. These causes are responsible for the most variability in severity scores by experts. These include poor zoning of the construction process based on traffic conditions (MET₃), Poor coordination with public services (hydraulic, sanitary, electrical, and other surface or subway network) (ENV₁), request for time extensions of the project start (applies in cases of request for rescheduling) (MET₁), failures in the estimation of current traffic on the road to be intervened (MEA₃), deficient identification of project stakeholders (WF₅), inadequate planning of the articulation with neighbors (ENV₄), high complexity of construction works (MET₅), and planning does not consider political/social elements (ENV₅). In addition, there are other causes of variability in the perception of professionals regarding frequency and severity. These causes include omission or deficiency in the definition of work packages (WBS) (MET₂), lack of verification during schedule development (MEA₄), inadequate estimation of durations in permit acquisition (MEA₁), and poor planning of machinery routes (MAC₁). The results not only confirm or refute the hypotheses raised but also reveal significant patterns in the perceptions of the 34 causes evaluated. These results are crucial for understanding the opinions of professionals and highlighting areas where differences in perceptions are most marked. These differences allow us to identify possible directions for improvement in the planning of road project schedules.

The results are consistent with findings from previous research. For instance, Castañeda et al. [19] show the critical role of traffic planning in the construction of road intersections, a role that enhances construction efficiency. Similarly, the findings corroborate those of Santoso et al. [11], who emphasize the importance of efficient management among the various stakeholders involved in the project to prevent construction schedule delays. Furthermore, these results align with Herrera et al. [7], who highlight the necessity of rigorous planning across different aspects of the construction process to avoid deviations in both schedule and budget. Additionally, regarding dispute resolution with neighboring communities, the findings agree with those of Kisi et al. [67], who assert that effective stakeholder management is essential to prevent conflicts during the construction of infrastructure projects. This proactive approach can help mitigate schedule discrepancies and delays that might otherwise arise from the prolonged legal resolution of disputes.

4.4.2. Relative frequency analysis

The Mann–Whitney U test reveals significant differences in opinions among professionals based on frequency and severity. An additional analytical approach was adopted to identify where differences within categories occur. The relative frequency analysis allows for the analysis of the distribution and variability of responses within a specific group. Therefore, the analysis focused on a direct comparison between the analysis groups defined in Table 5 according to significant differences in causes based on the frequency of occurrence according to expert opinion and a Likert scale. The first part of the relative frequency analysis presented in Fig. 4 shows a quantitative graphical representation of the data distribution. In this case, severity scores were assigned on a Likert scale from 1 to 5 for eight causes that lead to deficiencies in the planning of schedules in road infrastructure projects.

Fig. 4.

Causes with significant Mann–Whitney U test differences according to experience/severity.

The causes analyzed were focused, on the one hand, on the Experience category, which has two different analysis groups based on work experience: those with less than 10 years (“Experience <10 years”) and those with a decade or more of experience (“Experience >10 years”) (see Table 5). On the other hand, the results obtained through the Mann–Whitney U test, where the selected causes presented statistical significance with bilateral p-values less than 0.05 (see Table 8). This significance threshold is widely recognized in scientific research as a criterion for establishing statistical significance and, therefore, justifying the exclusive inclusion of these causes in the analysis. This type of analysis is fundamental to identifying the centrality and dispersion of respondents’ perceptions of each cause and detecting whether experience influences the variability of responses.

Based on the analysis, four causes related to the perception of complexity and schedule planning were identified. These are poor zoning of the construction process based on traffic conditions (MET₃), Inadequate planning of the coordination with neighbors (ENV₄), high complexity of construction works (MET₅), and planning that does not account for political and social elements (ENV₅). The responses from professionals with more than 10 years of experience consider these causes to be of high severity, indicating that experience enriches their awareness of the diversity and complexity of projects. These professionals have developed a deeper and more nuanced understanding of these causes, recognizing the importance of adapting to environmental variables and the complex social dynamics surrounding each project for successful planning.

Deficient coordination with public services (ENV₁) and deficient identification of project stakeholders (WF₅) are issues related to interacting with the environment and stakeholders. These causes emphasize the importance of engaging with external stakeholders [68]. Professionals with less than 10 years of experience tend to have more consistent scores, possibly due to a theoretical understanding of these challenges. In contrast, professionals with more than 10 years of experience had more variable scores, reflecting their past experiences and realizing that reality can differ from what is taught in training centers. Requests for time extensions to the start of a project (MET₁) and failure to estimate the current traffic on the road to be intervened (MEA₃) are mainly related to time management and administrative requests [38]. Both groups of professionals recognize the importance of these issues, but the more experienced professionals show greater variability in their understanding. This could be interpreted as a greater awareness of unpredictability and the influence of external factors in these areas, acquired through handling complex and often unforeseen situations over the years [55]. Their experience has led them to forecast traffic not only as a matter of technical analysis but also to consider dynamic variables that are often changing, such as unforeseen public works, local events, or seasonal changes.

Experience plays a crucial role in understanding the variability and complexity of road construction projects [8]. It also helps to develop a deeper appreciation of the consequences of poor schedule planning. Professionals who have worked longer in the industry are better equipped to handle the challenges that come with the job. They have a more nuanced understanding of the process and can better appreciate the need for flexibility, adaptability, and strong interaction with stakeholders and the environment [69]. This understanding is essential in developing robust and effective management strategies for developing road infrastructure projects.

The only significant difference in the frequency of occurrence score within the Experience category in road infrastructure project planning is caused by the omission or deficiency in the definition of work packages (WBS) (MET₂). Professionals with more than 10 years of experience report a higher frequency of occurrence of this problem compared to those with less experience. This suggests that accumulated experience may be correlated with a greater sensitivity to the frequency with which certain challenges arise in road infrastructure project planning schedules. More experienced professionals have a more refined and consistent perception of the impact of these causes on planning schedules. On the other hand, the varied perceptions among less experienced professionals may reflect a less developed familiarity with the dynamics of these issues in their day-to-day work. This underscores the importance of considering practical experience when assessing the frequency of specific problems within the planning activities of road infrastructure projects [70].

There are two distinct analysis groups in the Grade category based on academic training. The first group consists of those with undergraduate and specialization training, known as “Undergraduate/Specialization.” The second group is made up of those with master's and doctoral training, known as “Master's/Doctorate” (see Table 5). The cause of the lack of verification during the preparation of the schedule (MEA₄) reveals differences in the perception of its frequency among professionals with different academic training. Those with master's or doctoral degrees tend to report a higher consensus of this cause's frequency compared to those who have only completed undergraduate or specialization studies. This result suggests that a higher level of education leads to a greater awareness of the complexities involved in project planning, including the critical task of schedule verification.

The variability in the frequency reported by professionals with training up to the specialization level could reflect a less application of verification processes or less exposure to projects where schedule verification is more challenging. Professionals with master's or doctoral degrees also report higher severity in the case of failures in weather forecasting (ENV₂) compared to those with undergraduate and specialized training. This suggests that advanced education provides a more critical perspective on the challenges of inaccurate weather forecasts in planning road infrastructure projects. In contrast, the perception of lower severity by professionals with undergraduate training and specialization may reflect less exposure to the complexity of the implications of weather forecasting errors or perhaps a tendency to follow standard procedures that do not consider the variability of these factors.

The role category in the industry has two distinct analysis groups based on the role of professionals. The first group includes designers, consultants/investigators, contractors, owners, and others from the sector. The second group includes academics who are involved in research and teaching (the “Academy”). This category shows notable differences in how the frequency of causes affecting schedule planning is perceived by these two groups (see Table 5). For the problem of inadequate estimation of durations in permit acquisition (MEA₁), academics indicated a lower frequency of this problem compared to industry professionals. This suggests that industry professionals who are directly involved in project management encounter this inadequacy more often than academics. The lack of experience of the planner (WF₃) is perceived by industry practitioners as a more recurrent cause than by academics. This could be due to professionals in the sector analysis group being immersed in a practical environment where theory meets operational reality. They face the direct repercussions of planning decisions on a daily basis.

Projects in the sector may vary in complexity, and their management requires adequate planning experience to avoid delays and additional costs [71]. This sometimes creates the perception that such problems are frequent. However, academics who focus on teaching planning principles and research may not encounter these challenges as often and thus may report a lower frequency of such problems. This difference in perception highlights the gap between formal education and practical experience in the field, underscoring the importance of integrating real-world experiences into academic curricula to prepare future project planners better. There are significant differences in severity between the causes of poor planning of machinery routes (MAC1) and inadequate estimation of permit acquisition durations (MEA1). The industry rates these causes with higher scores than academia, which could be due to their confrontation with logistical challenges in the field.

4.4.3. Exploratory factor analysis

An exploratory factor analysis (EFA) was conducted on the severity scores of the 34 causes identified by the 32 participants to identify patterns of correlation within the data. This analysis is crucial to uncover latent components or factors that group several causes based on their similarities or influences. Each of these components represents a set of causes that share similar characteristics or are affected by similar factors (see Appendix B). The analysis identified seven principal components named after the grouped causes: (1) Project Preparation and Contextual Conditions, (2) Scope and Schedule Planning, (3) Traffic Management Planning, (4) Project complexity, (5) Resource Estimation, (6) Considering External Factors, and (7) Planning Accuracy and Operational Complexity (see Table 9). These components will provide a more detailed and focused insight into the critical issues affecting schedule planning in road infrastructure projects.

Table 9.

Causes contributing to schedule planning deficiencies are grouped according to major components.

Principal Components	Causes contributing to deficiencies in the scheduling	Id
Project Preparation and Contextual Conditions	Inadequate planning of the articulation with neighboring areas	ENV4
	Inadequate exploration of existing site conditions	ENV3
	Inadequate estimation of permit acquisition durations	MEA1
	Deficient project location	ENV7
	Poor understanding of the project by the planner	WF4
	Lack of political/social considerations in planning	ENV5
	Deficient estimation of material supply (Stocks)	MAT2
	Inadequate selection of construction methods	MET6
Scope and Schedule Planning	Failures in the definition of successor and predecessor relationships between activities	MET4
	Failures in the configuration of the work schedule (working days, holidays, working hours, seasons of the year)	MET9
	Omission or deficiency in the definition of work packages (WBS)	MET2
	Inadequacy of planning software adopted	MET11
Traffic Management Planning	Omission of road markings in planning	MET10
	Poor zoning of the construction process based on traffic conditions	MET3
	Failures in on-site traffic estimation	MEA3
	Poor planning of machinery routes	MAC1
Project Complexity	Poor estimation of workforce performance	WF1
	Deficient coordination with public utilities (water, sanitary, electrical and other surface or subway networks)	ENV1
	High complex access to the project area	ENV6
Resource Estimation	Lack of planning of storage and parking sites	MET8
	Deficient estimation of material quantities	MAT1
	Poor estimation of workforce quantity	WF2
Considering External Factors	Inadequate estimation of construction document approval times	MEA2
	Poor identification of project stakeholders	WF5
	Request for project start time extensions (applies in cases of rescheduling requests)	MET1
Planning Accuracy and Operational Complexity	Lack of verification during the schedule preparation	MEA4
	Inadequate estimation and consideration of waiting times (setting time or other waiting times between activities)	MEA5
	High complexity of construction work	MET5

The principal components aim to provide a more detailed understanding of the interrelated causes and their collective impact on schedule planning. Principal Component 1, Project Preparation and Contextual Conditions, indicates that inadequate articulation with neighboring properties can lead to regulatory delays or conflicts, which might directly impact the schedule, resulting in a re-evaluation of the project development. This situation becomes more complicated when site exploration is insufficient, as the lack of a detailed assessment can lead to poor project locations. This, in turn, intensifies logistical challenges and increases downtime waiting for materials or permits. Moreover, the accuracy in estimating the timing of permit acquisition highlights the importance of proper early coordination with neighboring properties and poor exploration of site conditions. Delayed commencement of construction due to inadequate initial planning can result in missed pre-established schedule deadlines [14]. Each stage of the project is dependent on the timely completion of the previous stage, so any initial delays can have a cumulative and amplified impact as the project progresses. In addition, the skill of the planner to understand and anticipate the complexities of the project significantly influences the correct estimation of resources [72], such as materials and the selection of construction methods, which must be aligned with existing site conditions and legal requirements.

Principal Component 2, Scope Planning and Scheduling, groups together critical factors that are mainly associated with the technical structuring and tools used in planning road infrastructure project schedules. Inconsistencies in defining successor and predecessor relationships between activities can lead to inconsistent sequencing, resulting in overlaps or gaps in the schedule that compromise project continuity [73]. This challenge is closely related to the configuration of the work schedule since inadequate accounting for workdays, holidays, and seasonal changes could result in unplanned interruptions or unplanned project extensions. Additionally, the omission or deficiency in defining work packages (WBS) can cause ineffective assignment and tracking of tasks, making it difficult to monitor progress and allocate resources [74]. The adequacy of scheduling software also plays a critical role, as a system that does not align with project requirements may limit the accuracy of schedule modeling and the ability to adapt to modifications or updates [75].

Principal Component 3, Traffic Management Planning, is focused on the crucial aspects of traffic management, which are essential for the effective planning of road project schedules. The omission of road signage in the planning process can create chaotic conditions at the construction site, increasing the risk of accidents and delays. This deficiency is closely related to inadequate zoning of the construction process since, without a clear division of work zones and ignorance of traffic conditions, construction work can suffer interruptions and deviations that disrupt the planned workflow [76]. Moreover, poor planning of machinery routes can result in inefficient equipment utilization and increased internal travel times, which directly impact productivity and adherence to critical schedule deadlines [77]. The interaction between these causes creates a complex web of operational factors that, if not managed correctly, can lead to an accumulation of delays and affect the integrity of the project schedule.

Principal Component 4, Project Complexity, comprises aspects of operational efficiency and interaction with the project environment. Thus, poor estimation of labor performance may be indicative of the complex nature of the project, where tasks may be more technical or require more specialized skills than anticipated, affecting time scheduling and productivity [78]. This situation may be exacerbated by poor coordination with utilities, the impact of which may extend beyond the preparation phase, disrupting work performance and complicating access to the project site. Also, disruptions resulting from ineffective coordination can cause delays and reallocations of resources, interrupting the planned sequence of work and compromising adherence to the initially established deadlines. Therefore, proactive management and effective communication with service entities are essential to mitigate negative impacts on overall project planning and progress [79]. High complexity in accessing the project site can be both a cause and a symptom of overall project complexity. Difficult accesses not only present significant logistical challenges that demand detailed schedule management but can also reflect and magnify inherent project difficulties, such as geographic constraints, challenging environmental conditions, or strict regulatory requirements.

The principal component analysis revealed how underestimating project complexity and operational requirements can lead to inadequate planning schedules in road infrastructure projects. This review emphasizes the crucial importance of establishing effective coordination and conducting detailed assessments that address technical, logistical, and environmental challenges, as well as aligning project activities with the expectations and needs of all stakeholders, which include utilities, neighboring projects, and site teams, among others [70]. The synergy between efficient labor performance, collaboration with utilities, and adequate accessibility to the construction site is key to project success. A thorough and proactive understanding of these interrelated areas is indispensable for accurate and sound planning, which is essential to meet established schedules and ensure the timely delivery and quality of roadway infrastructure.

5. Conclusions

This study has made three important theoretical contributions to the field of road project schedule planning. First, this study identified 34 causes of schedule planning failures in road projects. These 34 causes were grouped into six main categories: Labor, Machinery, Environment, Method, Measurement, and Materials. Second, this study estimated the influence of these causes by consulting 32 professionals with experience in road project planning. The Relative Influence Index (RII) was used to rank the top five most influential causes of scheduling deficiencies in road projects, which were (1) poor estimation of workforce performance (WF₁), (2) poor estimation of workforce quantity (WF₂), (3) deficient coordination with public utilities (water, sanitary, electrical, and other surface or subway networks) (ENV₁), (4) inadequate estimation of permit acquisition durations (MEA₁), and (5) inadequate weather forecasting (ENV₂). Third, through an exploratory factor analysis (EFA) carried out on the 34 causes, the study identified seven main components of the causes that induce failures. The seven main components identified were (1) project preparation and contextual conditions, (2) scope and schedule planning, (3) traffic management planning, (4) project complexity, (5) resource estimation, (6) considering external factors, and (7) planning accuracy and operational complexity.

The study's practical contribution lies in identifying the primary causes of deficiencies in road project scheduling. This is crucial for professionals in the sector, as it enables them to proactively and strategically address challenges that may arise during the pre-construction stages of these projects. Identifying and understanding these causes could facilitate the adoption of preventive and corrective measures to mitigate delays and cost overruns. In addition, by having clarity on the most influential causes of deficiency, professionals can improve accuracy in estimating time and budgets, which contributes to better management of expectations with both clients and stakeholders involved. In addition, it highlights the importance of addressing accurate estimation of quantity, labor and material supply performance plays a crucial role in the planning of road construction processes. This accuracy directly influences project scheduling costs and safety during construction. Errors in these estimates can trigger significant cost overruns or schedule delays, affecting project viability. In addition, there is the challenge of dealing with weather unpredictability, which requires adaptive planning strategies. Planners must be prepared for unexpected weather events that can cause disruptions and delays, compromising operational and safety objectives. This need highlights the importance of integrating weather and realistic forecasts into the early stages of planning or more constant updating of these forecasts. Changes in project scope and the dynamic nature of road construction require flexible planning and careful management. This management must take into account aspects such as: context, scope, scheduling, traffic, project complexity, resource estimation, external factors, and operational complexity, among others. In this context, effective and adaptive synchronization between the rescheduling of construction activities and modifications to the traffic management plan is essential. This coordination helps avoid confusion, ensures site safety and minimizes disruptions, which will benefit both workers and road users.

It is important to note that this study presented certain limitations. First, the number of professional associated with the categorical variables of years of experience and role is highlighted, since professionals with more years of experience could have a more experienced but perhaps less updated view on the latest trends and technologies in the industry. Second, the sample of professionals consulted in the study was limited to individuals from Chile and Colombia, which may not necessarily be representative of the general population. Therefore, the inclusion of greater geographic variability could provide different results and conclusions than those of this study. Third, the study did not include other types of infrastructure projects such as bridges, viaducts, tunnels, pedestrian walkways, bicycle paths, footbridges, and railroad tracks, among others. This means that the results and conclusions of this study are not necessarily applicable to these types of projects. Fourth, the study does not address the causes affecting the planning of vertical project schedules. Future studies could focus on investigating the causes affecting schedule planning. Fifth, the causes were only identified from the systematic review, so it could be supplemented with data from historical companies or projects. Future work complementary to this research could focus on extending the study to investigate which stakeholders and at what level lead to the existence of causes affecting schedule planning, quantify the financial impact of the existence of the main causes affecting schedule planning, and explore technological and methodological solutions to address the causes affecting schedule planning for both construction activities and the traffic management plan.

CRediT authorship contribution statement

Karen Castañeda: Writing – review & editing, Writing – original draft, Visualization, Validation, Supervision, Project administration, Methodology, Investigation, Formal analysis, Data curation, Conceptualization. Omar Sánchez: Writing – review & editing, Writing – original draft, Visualization, Validation, Project administration, Methodology, Investigation, Funding acquisition, Data curation, Conceptualization. Rodrigo F. Herrera: Writing – review & editing, Writing – original draft, Visualization, Validation, Supervision, Software, Resources, Project administration, Methodology, Investigation, Funding acquisition, Formal analysis, Data curation, Conceptualization. Guillermo Mejía: Writing – review & editing, Writing – original draft, Supervision, Methodology, Conceptualization.

Informed consent

Before participating in the study, all participants were provided with detailed information about the purpose of the research, the nature of their participation, and how the data collected would be handled and used. Informed consent was obtained from each participant, which was a prerequisite for proceeding with the questionnaire. This informed consent was clearly presented in the first section of the questionnaire, ensuring that participants were fully informed and in agreement with the terms of their participation before proceeding (see the questionnaire).

Institutional review board statement

Not applicable.

Data availability statement

No applicable.

Consent statement

The authors state that this study did not require approval by an ethics committee because each participant in the study guaranteed data privacy and agreed to consent. The study consisted of answering a questionnaire based on the experience and knowledge of the experts surveyed, which guaranteed anonymity and ensured that each participant agreed to the informed consent of the research, which was provided in the first part of the questionnaire.

It is important to note that the methodology employed ensured the protection of the privacy and confidentiality of the participants as follows.

Anonymity guaranteed

Special care was taken to ensure that all responses collected were completely anonymous. This means that no personal or identifiable information was requested or recorded, ensuring that participants' identities remained protected at all times.

Data privacy

Given that the study was based solely on the collection of professional opinions and experiences without involving sensitive personal data or the participation of vulnerable groups, and rigorous measures were implemented to guarantee anonymity and informed consent, it was determined that it was not necessary to submit the study for review and approval by an ethics committee.

Declaration of generative AI and AI-assisted technologies in the writing process

During the preparation of this work, the authors used Grammarly in order to improve readability, spelling and grammar. After using this tool, the authors reviewed and edited the content as needed and take full responsibility for the content of the publication.

6. Funding

We gratefully acknowledge the financial support from the Pontificia Universidad Javeriana, Colombia, through “Apoyo a proyectos de investigación liderados por profesores que se encuentran en su primera etapa 2023” with the project entitled “Planificación de la construcción de proyectos viales, mediante la integración de simulaciones digitales BIM nD, líneas de balance y Last Planner System (ID 20673).”

Declaration of competing interest

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Appendix A. Informed Consent and Questionnaire

Questionnaire

Informed consent

Please read this information carefully before deciding to participate in the study:

Research title: Causes Contributing to Deficiencies in Road Construction Scheduling.

Your participation in this research project aims to: Define the levels of frequency and severity of the causes that affect the planning of the construction process schedule and the planning of traffic management in road projects.

Your participation in this study is free and voluntary: You may request to be excluded from it and that your interventions not be considered in this research without prior justification or prejudice to you. The time allowed to answer the questionnaire is approximately 10 min.

Benefits: Through your participation, you will contribute to the general knowledge about the causes that affect construction scheduling and traffic management planning in road projects. If you wish, you may email the responsible researcher, karen.castaneda@pucv.cl, for a copy of any publications written based on this research.

Confidentiality: All data will be stored in the SurveyMonkey platform for the duration of the research, and only the research team will have access to it. The data will be stored for two years, after which time it will be disposed of in a confidential manner. All information shared in this study is completely confidential, and your anonymity will be guaranteed. Under no circumstances will your name or identity be revealed, nor will any personally identifiable information about you be disclosed.

Contact: If you have any questions or concerns regarding your rights as a participant in this study, you may contact the responsible researcher Karen Milady Castañeda Parra, at karen.castaneda@pucv.cl or the Head of Research and Graduate Studies of the Pontificia Universidad Católica de Valparaíso, Professor Rodrigo F. Herrera, at the following email: rodrigo.herrera@pucv.cl.

Do you agree to participate in this study?

• a)Yes.
• b)No.

PART I. Experience and role in the construction industry

This questionnaire focuses on identifying the main causes of deficiencies in the planning of construction process schedules in road projects, which are present in road infrastructure projects. Your answers will be confidential and will be used for the development of a doctoral thesis research of the Universidad Industrial de Santander and the Pontificia Universidad Católica de Valparaíso. This research is focused on proposing methodological and technological solutions for the mitigation of the main causes identified. Confidentiality is guaranteed, and we are very grateful for your valuable contribution to this research. The estimated response time is 10 min.

• 1.What is your profession? __________
• 2.Which is the country where you have mainly been active in the construction industry? __________
• 3.What is your highest academic degree? __________
• 4.What do you see as your main role in the construction industry? __________
• 5.What is your professional experience in the construction industry? __________

PART II. Frequency and severity of causes affecting the planning of the construction process schedule and traffic management plan in road infrastructure projects

According to your experience and knowledge, select the frequency and severity levels related to the listed causes of deficiencies that affect the planning of the construction process schedule and the traffic management plan in road infrastructure projects. Frequency corresponds to how FREQUENT it is to encounter the type of cause listed, and severity corresponds to how SERIOUS it is to encounter the type of cause listed. A five-point Likert scale has been proposed to measure frequency and severity, where 1 = very low frequency or very low severity, 3 = medium frequency or medium severity, 5 = extreme frequency or extreme severity.

Classification	Id	Causes contributing to deficiencies in the scheduling	Severity	Frequency
Workforce	WF1	Poor estimation of workforce performance
	WF2	Poor estimation of workforce quantity
	WF3	Lack of experience of the planner
	WF4	Poor understanding of the project by the planner
	WF5	Poor identification of project stakeholders
Machinery	MAC1	Poor planning of machinery routes
	MAC2	Poor estimation of construction process constraints (machine capacity, number of personnel, and terrain conditions, among others)
	MAC3	Poor planning of equipment/machinery operation requirements
Material	MAT1	Deficient estimation of material quantities
	MAT2	Deficient estimation of material supply (stocks)
Measurement	MEA1	Inadequate estimation of permit acquisition durations
	MEA2	Inadequate estimation of construction document approval times
	MEA3	Failures in on-site traffic estimation
	MEA4	Lack of verification during the schedule preparation
	MEA5	Inadequate estimation and consideration of waiting times (setting time or other waiting times between activities)
	MEA6	Deficient hierarchy/priority of project roads
Environment	ENV1	Deficient coordination with public utilities (water, sanitary, electrical and other surface or subway networks)
	ENV2	Inadequate weather forecasting
	ENV3	Inadequate exploration of existing site conditions
	ENV4	Inadequate planning of the articulation with neighboring areas
	ENV5	Lack of political/social considerations in planning
	ENV6	High complex access to the project area
	ENV7	Deficient project location
Method	MET1	Request for project start time extensions (applies in cases of rescheduling requests)
	MET2	Omission or deficiency in the definition of work packages (WBS)
	MET3	Poor zoning of the construction process based on traffic conditions
	MET4	Failures in the definition of successor and predecessor relationships between activities
	MET5	High complexity of construction work
	MET6	Inadequate selection of construction methods
	MET7	Poor planning of alternate routes and pedestrian trails
	MET8	Lack of planning of storage and parking sites
	MET9	Failures in the configuration of the work schedule (working days, holidays, working hours, seasons of the year)
	MET10	Omission of road markings in planning
	MET11	Inadequacy of planning software adopted

Appendix B. Causes of schedule planning deficiencies and major components

Id	Causes contributing to deficiencies in the scheduling	Main components
		1	2	3	4	5	6	7
ENV4	Inadequate planning of the articulation with neighboring areas	0.821
ENV3	Inadequate exploration of existing site conditions	0.800
MEA1	Inadequate estimation of permit acquisition durations	0.793
ENV7	Deficient project location	0.787
WF4	Poor understanding of the project by the planner	0.766
ENV5	Lack of political/social considerations in planning	0.761
MAT2	Deficient estimation of material supply (Stocks)	0.581
MET6	Inadequate selection of construction methods	0.486
MET4	Failures in the definition of successor and predecessor relationships between activities		0.882
MET9	Failures in the configuration of the work schedule (working days, holidays, working hours, seasons of the year)		0.840
MET2	Omission or deficiency in the definition of work packages (WBS)		0.737
MET11	Inadequacy of planning software adopted		0.602
MET10	Omission of road markings in planning			0.883
MET3	Poor zoning of the construction process based on traffic conditions			0.852
MEA3	Failures in on-site traffic estimation			0.504	0.666
MAC1	Poor planning of machinery routes			0.694
WF1	Poor estimation of workforce performance				0.799
ENV1	Deficient coordination with public utilities (water, sanitary, electrical and other surface or subway networks)				0.782
ENV6	High complex access to the project area				0.737
MET8	Lack of planning of storage and parking sites					0.693
MAT1	Deficient estimation of material quantities					0.676
WF2	Poor estimation of workforce quantity					0.575
MEA2	Inadequate estimation of construction document approval times						0.796
WF5	Poor identification of project stakeholders						0.747
MET1	Request for project start time extensions (applies in cases of rescheduling requests)						0.689
MEA4	Lack of verification during the schedule preparation							0.805
MEA5	Inadequate estimation and consideration of waiting times (setting time or other waiting times between activities)							0.555
MET5	High complexity of construction work							0.473