A Strategic AHP-Based Framework for Mitigating Delays in Road Construction Projects in the Philippines

Abstract

Delays in road construction projects pose significant challenges in the Philippines, resulting in increased costs, project overruns, and unmet infrastructure goals. Common causes include poor financial management, inadequate subcontractor performance, deficient planning, and regulatory bottlenecks. This study aims to develop a comprehensive and data-driven framework to mitigate construction delays using the Analytical Hierarchy Process (AHP). The methodology integrates literature review, expert surveys, and pairwise comparisons to identify and prioritize critical delay factors. Experts from the Department of Public Works and Highways (DPWH), private contractors, and academia contributed to the AHP model. The results highlight seven major factor groups: client-related, contractor-related, consultant-related, materials, labor and equipment, contractual issues, and external influences. AHP analysis identified financial management, planning and scheduling, and regulatory coordination as the most impactful causes. Based on these findings, a strategic framework was developed and visualized using a Fishbone Diagram to present mitigation strategies tailored to each factor. While environmental engineering principles—such as material efficiency, energy use optimization, and impact assessments—are acknowledged, they serve as guiding themes rather than formal components of the framework. The study offers practical, stakeholder-validated recommendations for both pre- and post-construction phases, including real-time monitoring, risk anticipation, and improved multi-agency coordination. This framework provides a scalable tool for DPWH and related agencies to improve infrastructure delivery while supporting long-term sustainability goals.

1. Introduction

The construction industry plays a crucial economic role by generating employment and wealth for a country. In the Philippines, the rapid increase in vehicle sales has not been matched by equivalent investments in infrastructure, leading to severe traffic congestion and delays in road construction projects. Approximately 49.22% of projects under the Department of Public Works and Highways (DPWH) have experienced delays, exacerbated traffic problems, and highlighted the need for timely project completion (data source under non-disclosure agreement). Environmental engineering is pivotal in addressing the intertwined challenges of infrastructure development and environmental sustainability. In road construction projects, environmental engineers contribute by assessing and mitigating the ecological impacts of land clearing, material sourcing, and emissions from construction activities. Their expertise ensures that projects incorporate sustainable drainage systems, erosion control measures, and proper waste management practices, reducing adverse effects on surrounding ecosystems. Moreover, integrating environmental impact assessments (EIAs) [1] into the early planning stages supports regulatory compliance and promotes resource-efficient design. In the Philippine context, where infrastructure expansion intersects with climate vulnerability and biodiversity concerns, environmental engineering provides critical solutions to balance development goals with long-term ecological protection. This research seeks to address these delays by developing a scientific framework to identify and mitigate the factors causing them.

However, road construction projects often face significant challenges, such as delays and cost overruns, which impede their timely completion and economic viability [2,3]. Modernizing road construction has become imperative due to the global economic recession [4] and increased environmental awareness, necessitating the adoption of eco-friendly construction practices to minimize waste and reduce resource consumption [5]. Despite these advancements, delays in road construction projects remain a persistent issue, adversely affecting revenues and project output. Previous studies have identified various causes of construction delays, including poor project planning, financial difficulties, and inadequate contractor experience [6,7]. Delays due to inadequate cash flow management, handling too many projects simultaneously, and insufficient quality control are also prevalent [8]. In the Philippines, road conditions and maintenance issues, combined with inadequate construction management, contribute to persistent delays despite stringent standards set by the DPWH. The significance of road networks in the Philippines for social movement and commerce further underscores the need for efficient road construction.

The Analytical Hierarchy Process (AHP) is a robust multi-criteria decision-making (MCDM) tool that systematically addresses these delays by prioritizing the factors based on their relative importance [9,10]. AHP’s ability to translate subjective opinions into measurable numeric values makes it particularly suitable for analyzing complex issues in road construction projects [11,12,13]. This research aims to identify the top priorities causing delays from the perspectives of project engineers, contractors, and project inspectors and develop a comprehensive framework for mitigating these delays using AHP. AHP has been widely used in various fields to solve complex decision-making problems. In environmental management and disaster risk mitigation, AHP has been applied to assess and prioritize the ecological impacts of different projects [14,15,16]. In determining suitable sites for construction, AHP helps decision-makers assess the best location to construct renewable energy farms, evacuation areas, and large-scale construction projects [17,18,19]. Additionally, AHP has been utilized in urban planning to evaluate and rank urban development projects based on various socioeconomic and environmental criteria [20].

In the construction industry, AHP has effectively evaluated risks in construction projects, allowing stakeholders to prioritize and mitigate these risks based on their potential impact [21]. The method has also been employed to optimize resource allocation, ensuring that limited resources are used efficiently to achieve project goals [22]. Furthermore, AHP has been used in evaluating construction methods and materials, enabling decision-makers to select the best options based on multiple criteria such as cost, sustainability, and durability [23]. Recent applications of AHP in road construction projects have demonstrated its utility in prioritizing risk factors, allocating resources, and evaluating performance. One of the most prominent applications of AHP is in contractor selection, where it enables stakeholders to evaluate contractors based on cost competitiveness, technical expertise, experience, safety records, and financial stability [24,25]. AHP also aids in subcontractor prequalification, integrating both quantitative and qualitative criteria to ensure the reliability and performance of subcontracted parties [26]. Moreover, project planners have used AHP to determine optimal construction methods and equipment selection, weighing variables such as cost, efficiency, environmental impact, and availability [27,28].

In sustainable construction, AHP has become a valuable tool for material selection, where it supports decision-making by comparing cost, strength, durability, recyclability, and environmental footprint [25,29]. Similarly, it has been applied in green building design to prioritize alternatives for lighting systems, insulation, Heating, Ventilation, and Air Conditioning (HVAC) configurations, and waste minimization strategies that comply with Leadership in Energy and Environmental Design (LEED) or Building Research Establishment Environmental Assessment Method (BREEAM) certification requirements [25,30]. Beyond design, AHP is also useful in project scheduling, helping prioritize construction activities, resource deployment, and sequencing strategies under constrained timelines [31]. These applications demonstrate the flexibility of AHP in optimizing construction efficiency while incorporating environmental and performance considerations.

Furthermore, AHP has been extensively employed in construction risk management, providing structured prioritization of risks such as safety hazards [32,33], financial instability, weather-related delays [34], and regulatory issues [35,36]. It is also used to assess the impact of delays and cost overruns, aiding government agencies and private contractors in identifying the most critical factors affecting project delivery. In a broader context, AHP supports policy evaluation, land-use suitability assessments, and environmental impact assessments related to infrastructure development [19,25,37,38,39]. Despite this wide adoption, most existing models focus on specific project elements, such as contractor selection or environmental ranking, and often lack a comprehensive delay mitigation framework that accounts for the perspectives of multiple stakeholders. This study fills that gap by applying AHP to develop an integrated, sustainability-oriented delay mitigation strategy specific to the road construction sector in the Philippines.

Despite the widespread use of AHP in various construction domains, including contractor evaluation, sustainable material selection, and risk prioritization, limited research has applied AHP specifically to assess and mitigate delays in public road construction projects, especially within the Philippine context. Existing studies tend to address isolated project elements or focus on other construction types (for example, buildings or infrastructure unrelated to roads), often overlooking the complexities of multi-agency coordination and field-level execution issues encountered in DPWH-managed projects. To the authors’ knowledge, this is the first study that develops a multi-stakeholder AHP-based framework specifically targeting road construction delays in the Philippines, integrating perspectives from DPWH officials, inspectors, consultants, and contractors. By doing so, the research not only prioritizes delay factors grounded in real-world experience but also offers a scientifically structured framework tailored to the institutional realities of Philippine road infrastructure delivery. By applying the AHP method in this research, the study aims to systematically identify and prioritize the factors that cause delays in road construction projects. The comprehensive framework developed will provide valuable insights and practical strategies for mitigating delays, ultimately enhancing project efficiency and reducing costs.

The study utilized surveys from project engineers, contractors’ project managers, and other relevant stakeholders and the literature to gather data on the factors contributing to delays. The collected data were subjected to rigorous analysis to ensure accuracy and reliability. Pairwise comparison matrices were employed to quantify each delay factor’s relative importance, allowing for a detailed prioritization of the issues based on the perspectives of the various stakeholders [6,7]. The development of a new dataset for the AHP application follows this analysis. The AHP facilitated a systematic evaluation of the delay factors by structuring the data into a hierarchical model. This model allowed the comparison of factors at different levels of the hierarchy, providing a comprehensive view of their relative significance [9]. The AHP methodology converted the subjective assessments of the stakeholders into objective, quantifiable data, ensuring a robust decision-making process [10].

This study proposes a data-driven strategic framework to mitigate road construction delays, grounded in the prioritization of delay factors using the AHP. By combining expert input and structured decision-making techniques, the framework aims to enhance project efficiency and guide interventions tailored to the Philippine infrastructure context.

This research addresses the critical need for a systematic approach to mitigating road construction delays in the Philippines. By leveraging AHP to prioritize and address the factors contributing to these delays, the study aims to enhance project efficiency, reduce delays, and support sustainable economic growth through improved infrastructure development. The findings will provide valuable insights into the root causes of delays and offer actionable mitigation strategies, thereby contributing to more timely and cost-effective road construction projects [5,40]. The comprehensive framework developed through this research will serve as a critical reference for policymakers, engineers, and contractors, facilitating better planning and execution of future infrastructure projects.

2. Methods

This study aimed to identify the causes of delays in road construction projects in the Philippines. To achieve this, the researcher reviewed the literature to identify the factors contributing to road construction delays. Based on the collected data, a hierarchy was constructed, and the causes of delay factors were summarized. The experts from academia, DPWH, and contractors then used pairwise comparison techniques to compare each cause of road construction delays, and the top causes were evaluated and classified using the AHP. They were verified to ensure the reliability of judgments and concluding results, and the leading causes of delays were assessed. Finally, a strategic framework was developed to mitigate factors that cause delays in road construction projects in the Philippines. Overall, this study provides valuable insights into the causes of delays in road construction projects and recommendations for minimizing or eliminating them. The schematic diagram of the study is presented in Figure 1.

2.1. Determination of Causes of Road Construction Delay

In this study phase, the researcher developed a comprehensive list of common reasons for delays in road construction projects. The objective was to identify key factors that potentially cause construction delays by combining literature-based insights with field data. The first step involved an extensive review of published and the unpublished literature to gather relevant information on typical delay causes in road construction. This archival research helped compile an initial list of factors consistent with the current research scope. In the second step, the researcher conducted focus group discussions and face-to-face and virtual interviews with contractors, consultants, and project engineers to validate and enrich the list of delay factors. These engagements were designed to accommodate respondent availability while ensuring the smooth progress of data collection. In the final step, the causes of delays identified from expert insights were summarized and refined. Redundant or contextually irrelevant factors were excluded, and new ones were added based on practical experience in the Philippine setting. The resulting delay factors were then grouped into logical categories according to their scope of work and the nature of the delays, forming the basis for further analysis in the study.

2.2. Evaluation and Assessment of Factors Using AHP

The AHP was selected due to its suitability for structuring complex, multi-stakeholder decisions, such as those involved in public infrastructure projects. AHP allows for both qualitative judgments and quantitative weighting, enabling experts from government, consultancy, and construction sectors to evaluate delay factors based on real-world experience. Compared to other MCDM techniques like Analytic Network Process (ANP) or Technique for Order Preference by Similarity to Ideal Solution (TOPSIS), AHP was preferred for its transparency, ease of pairwise comparison, and capacity to capture expert consensus despite diverse roles. Moreover, its use of consistency ratio (CR) checking ensures rationality in judgment, a critical aspect when working with small expert panels, as in this study. Given these advantages and its widespread adoption in delay analysis, AHP was deemed the most appropriate tool for systematically prioritizing delay factors and developing a policy-relevant framework.

Factors causing delays in road construction were identified and assessed. The weights of each parameter were determined using AHP based on the knowledge of experts, composed of consultants, project engineers, project inspectors, contractors’ project managers, or engineers in road construction engineering. Experts from government agencies (DPWH), private consultants, and contractors participated in the AHP assessment. A specialist from academic institutions and individuals related to transportation engineering, specifically road construction engineering, also responded to the evaluation through online and printed pairwise comparison questionnaires. Weights for each factor were evaluated in this phase to determine the priority of significant causes in developing a strategic framework for addressing road construction delays.

2.2.1. Construct the Hierarchy Based on the Criteria and Alternatives Identified

In this step, the decision was segregated into its independent components. It was presented in a hierarchy diagram of at least three levels: goal, criteria, and indicators. The AHP framework was drafted, wherein the uppermost position of the hierarchy was the primary goal. The lower level of the hierarchy contains the judgment rules or criteria that contribute to attaining the best choice and can be expanded in substantial detail that was considered for each decision rule or standard. Finally, the lowest level contained alternatives or indicators for decision-makers [41].

2.2.2. Identify Respondents and Experts for the Pairwise Comparison Technique

Experts from government agencies, private consultants and contractors, transportation engineers, and academic institution representatives were identified to answer the pairwise comparison questions. Respondents answered the pairwise comparison questionnaire to compare the determined causes of delays in road construction factors. Printed questionnaires and online forms were utilized for the pairwise comparison technique.

The number of comparisons for the decision elements at a particular level is derived using the formula (Equation (1)) below:

Number of comparisons = n (n − 1)/2

(1)

The stated scale ranges from 1/9 for ‘least valued than’ to 1 for ‘equal’ and from 3 for ‘moderately important’ up to 9 for ‘absolutely more important than’, covering the entire range of the assessment.

Table 1. Scale interpretation for pairwise comparison value.

Value	Definition	Explanation
1	Equal Importance	Two activities each contribute equally to the goal
2	Weak	Between equal and moderate
3	Moderate Importance	Experience and judgment favor one activity slightly more than another
4	Moderate Plus	Between moderate and strong
5	Strong Importance	Experience and judgment favor one activity strongly more than another
6	Strong Plus	Between strong and very strong
7	Very strong Demonstrated Importance	An activity is strongly preferred over another; its influence is demonstrated in practice
8	Very, Very Strong	Between very strong and extreme
9	Extreme Importance	One of the highest possible levels of confirmation is evidence favoring one activity over another

shows the interpretation of the values stated in the scale. It also explains each of the represented given importance on the scale. Value 1 states when the two variables being compared have an equal contribution of activities relative to the objective, while the value of ‘9’ represents the extreme importance that shows favoring one action over the other.

2.2.3. Evaluate and Classify the Top Causes of Delay Using AHP

This step determined the relative significance of the criteria after a pairwise comparison matrix for criteria and alternatives, considering the goal attainment and the relative importance of the options with respect to the criteria. This step was employed by calculating the normalized values for each criterion and option and determining the normalized main priority vectors (relative weights). Normalized values for each criterion and alternative in their respective matrices were derived by dividing each cell by its column sum and producing a total column of 1 for each criterion and alternative. Weights were calculated by averaging the rows of the matrix. The resulting value represented the relative weight of every criterion concerning the best goal and provided relative weight for the options (alternatives) concerning the criteria. The final relative weights of the alternatives were defined by computing the linear combination (LC) of the product between the relative weight of each criterion and the alternative for that specific criterion. The decision-makers chose the best alternative according to the alternatives’ overall weights if the experts’ judgments were consistent.

This is mathematically outlined below. Let Equation (2):

$$C=\left\{C_j\right| j=\mathrm{1,2},\dots .., n\}$$

(2)

be the set of criteria. The pairwise comparison of n criteria can be generalized using an evaluation matrix (A) in which every element is the quotient of weights of the criteria given in Equation (3) [41].

$$A=\left[ \begin{array}{cccc}{a}_{11}& a_{12}& .& a_{1n}\\ a_{21}& a_{22}& .& a_{2n}\\ .& .& .& .\\ a_{n1}& a_{n2}& .& a_{nn}\end{array}\right], a_{ii}=1,a_{ji}={\displaystyle \frac{1}{a_{ij}}}, a_{ij}\ne 0$$

(3)

2.2.4. Verify the Reliability of Judgments and Concluding Results

AHP’s quality output was related to the consistency of the pairwise comparison judgments. This step was essential to identify the consistency of the assessment by computing the consistency ratio (CR) before a decision was completed. However, if problems were expected during deliberation for choosing the best alternative, the CRs for matrices (criteria and the alternatives) were computed initially before the alternatives’ overall relative weights were calculated. Next, computations were performed to obtain the largest eigenvalue, consistency index, consistency ratio, and normalized values for each criterion/alternative.

The final mathematical process normalizes and identifies the relative weights per matrix. The right eigenvector provided the relative weights (w) conforming to the highest eigenvalue (${\lambda }_{max}$) as in Equation (4).

$${A_w=\lambda }_{max}$$

(4)

If the pairwise comparisons were consistent, the matrix A has rank one and λ max = n, so the weights can be obtained by normalizing any of the rows or columns of A [41]. The consistency between the entries determines the consistency, and the consistency index (CI) is given by Equation (5).

$$CI=({\lambda }_{max}-n)/(n-1)$$

(5)

The final consistency ratio (CR), which enables the decision-maker to determine whether the assessments were adequately coherent, was computed as the CI and the random index (RI) quotient, as shown in Equation (6). The values of RI are presented in

Table 2. The random index is used to calculate consistency ratios.

Random Index (RI)

0

0

0.58

0.90

1.12

1.24

1.32

1.41

1.45

1.49

1.51

1.48

1.56

1.57

1.58

.

$$CR=CI/RI$$

(6)

One recommendation for this step is that the judgment is considered inconsistent if the proportion exceeds 0.1. Thus, a consistency ratio must be below 0.1 or 10%. The process was supposed to be reiterated if the evaluation was unpredictable until the CR was within the desired range [41]. There were challenges in arriving at a value of below 0.1 or 10% regarding CR, as the pairwise comparison must be sent back to respondents to answer again until it gives the ideal value of CR. Inconsistencies in the comparison matrix are typical in AHP studies [42]. Although respondents can be asked to reconsider their choices to identify and correct these inconsistencies, this method is not always feasible, especially for online surveys. In online contexts, where there may be many anonymous respondents, interacting with each individual is impractical. Therefore, several approaches have been developed to adjust the comparison matrix autonomously to address these inconsistencies [43]. To address this problem, all answers for pairwise comparison were averaged and adopted a geometric adjustment in the AHP process based on the study by Yadav and Jayswal (2013) [44], implemented and coded in MATLAB R2024B. The method generates a new pairwise comparison matrix and weights for every factor, noting its suggested CR. This approach ensures consistent responses in the AHP comparison matrices without significantly altering individual preferences.

While the CI ensures logical soundness, statistical tests such as Cronbach’s Alpha and Regression Analysis were applied to further validate the weight calculations and dataset reliability. Cronbach’s Alpha was used to assess the internal consistency of expert judgments, with a value above 0.7 indicating high reliability. In addition, Regression Analysis was conducted to validate the relationship between AHP weight rankings and actual delay severity. Pearson’s correlation coefficient (R) was used to measure the strength of this relationship, while R-squared values assessed how well the AHP weights predicted actual delays. A statistically significant factor (p-value < 0.05) confirmed strong predictive validity. The regression analysis results demonstrate that high correlation and R-squared values indicate a strong alignment between AHP rankings and actual project delays. The framework for prioritizing road construction delay factors was logically and statistically validated by integrating statistical tests, consistency analysis, and regression validation. This approach ensures that the identified delay factors and rankings are credible, data-driven, and applicable in real-world decision-making.

2.3. Development of a Strategic Framework for Mitigating Causes of Delays in Road Construction

Developing a strategic framework for mitigating causes of delays in road construction involves creating a plan of action to address the identified factors. Assessing possible strategies to minimize the top causes of delays in road construction is essential in this phase to draw the framework. By implementing this strategic framework, stakeholders can work together to mitigate the causes of delays and improve the efficiency and effectiveness of road construction projects, ultimately resulting in better infrastructure and outcomes for communities.

The assessment focused on crafting the best approach to minimize or eliminate such causes. The end users and experts in the field decided on input strategies for this assessment and validated the suggested mitigating strategies. The evaluation process that was formed was reflected in the development of mitigating the causes of delays in the construction framework. The last step is to develop a strategic framework for mitigating factors to minimize or eliminate causes of delays in road construction. The framework is in the form of an analytic diagram or figure that shows the solution and strategies for each factor. The paper details the proposed management framework to design a construction project effectively, especially in the Philippines, to be implemented by the DPWH.

A structured validation questionnaire was developed to assess the framework’s clarity, applicability, and accuracy using Likert-scale ratings (1 to 5). Experts were asked to evaluate whether the framework represents real-world road construction delays, effectively identifies and prioritizes key delay factors, and provides practical and actionable mitigation strategies. One survey question included: “To what extent do you agree that the framework effectively identifies and prioritizes key delay factors in road construction?” (1 = Strongly Disagree, 5 = Strongly Agree). In addition, open-ended questions were provided to gather qualitative insights and recommendations for improving the framework.

The validation process included experienced professionals in road construction, such as consultants, inspectors, and DPWH officials responsible for road project oversight. These experts were selected based on their direct involvement in road construction projects, ensuring that their feedback was relevant and based on practical experience. Their evaluations helped assess the effectiveness of the framework in real-world applications. The responses from the validation survey were analyzed using statistical techniques to ensure reliability and expert agreement. Mean ratings were computed to determine the overall expert consensus on the framework’s validity. These statistical methods ensured the framework’s structure and content were consistent and reflective of industry challenges and solutions. The validated framework provides a comprehensive management tool for mitigating construction delays. It serves as a practical guide for DPWH and project stakeholders to ensure the efficient execution of road projects in the Philippines.

This study adopts a multi-method approach comprising literature analysis, expert surveys, AHP, regression analysis, and framework development, each building upon the results of the preceding stage. The process begins with a systematic review of the literature, which provides an initial pool of commonly cited delay factors in road construction. This list was then refined and validated through expert surveys involving engineers, inspectors, consultants, and DPWH personnel to capture context-specific insights. The refined list served as input for the AHP analysis, which was used to prioritize these factors based on their relative importance through pairwise comparisons.

A linear regression analysis was conducted to assess the strength of association between the AHP-derived weights (as independent variables) and the average severity scores rated by experts (as the dependent variable). This step aimed to validate the alignment between mathematically computed factor importance and stakeholder perception. The resulting R² value indicated the degree to which AHP priorities explained expert-rated severity across delay factors. To enhance robustness, regression analysis was employed to compare the AHP-derived rankings with independent Likert-scale severity scores from experts, serving as an additional cross-validation step to ensure alignment between structured MCDM output and intuitive professional judgment. Finally, the strategic framework was developed by integrating the weighted AHP results, validated insights, and identified interdependencies across stakeholder domains. This step-by-step process ensures that each method is interdependent, with outputs from earlier stages serving as inputs or validation bases for the next, thereby enhancing the methodological coherence and reliability of the findings.

3. Results

3.1. Identification of Factors Causing Road Construction Delay

The identified factors causing delays in road construction projects were systematically grouped into categories based on thematic similarity, ensuring a coherent analysis of their shared characteristics. This categorization process was essential to organize the diverse factors into meaningful groups for better understanding and addressing the delays effectively. Supporting references for each factor with corresponding codes that fall under every criterion are shown in

Table 3. References supporting identified factors causing delays in road construction.

Criteria	Code	Factors	References
Client (Cl)	Cl1	Finance and payments of completed work	[2,6,40,45,46,47,48]
	Cl2	Owner interference	[45,46]
	Cl3	Slow decision-making by owners	[2,45,46,47,48]
	Cl4	Late approval of shop drawings and sample materials	[49]
	Cl5	Late in resolving right-of-way issues	[2,50]
	Cl6	Fraudulent practices in the organization	[3,6]
	Cl7	Delays in site preparation	[2]
	Cl8	Change orders	[40,45,46,47,48,50]
Contractor (Co)	Co1	Subcontractors	[6,45,50]
	Co2	Site management	[6,40,45,47,50,51]
	Co3	Inadequate construction methods	[6,45,47,48,50]
	Co4	Improper planning	[2,3,6,45,47,50]
	Co5	Mistakes during construction	[40,45,47]
	Co6	Inadequate contractor experience	[45,47,50]
	Co7	Poor qualification of the contractors’ technical staff	[2,3,6,40,50]
	Co8	Replace key personnel	[46]
	Co9	Difficulties in financing projects by contractor	[2,6,40,46,47,50]
	Co10	Handling of too many projects at a given time	[6]
	Co11	Insufficient safety precautions at the site	[2,6]
	Co12	Delay in mobilization	[2]
	Co13	Improper handling of the project progress by the contractor	[2]
	Co14	Rework because of unaccepted quality	[48,51]
Consultant (Cs)	Cs1	Contract management	[45]
	Cs2	Preparation of drawings	[2,45]
	Cs3	Inappropriate design	[48]
	Cs4	Quality assurance/control	[45]
	Cs5	Waiting time for approval of tests and inspections	[2,45,47,50]
	Cs6	Delay in performing inspections by the consultant	[50]
	Cs7	Poor estimation practices/Low-profit margin	[6]
	Cs8	Incapable inspectors	[48]
	Cs9	Insufficient inspectors	[48]
	Cs10	Unrealistic imposed contract duration	[45,47,48,50]
	Cs11	Undefined scope of working	[48]
Material (Ma)	Ma1	Quality of material	[45]
	Ma2	Shortage in material	[2,45,47,48]
	Ma3	Delay in delivery of materials	[2,3,6,40,46,47]
	Ma4	Price escalation	[2,50]
	Ma5	Modifications in materials specifications	[2,48]
Labor and Equipment (Le)	Le1	Labor supply	[2,45,47,48,50]
	Le2	Labor productivity	[2,6,45,47,48,50,51]
	Le3	Low level of equipment-operator’s skill	[48]
	Le4	Equipment availability and failure	[2,6,40,45,47,48,51]
	Le5	Labor disputes and contractor	[40,48]
Contractual Relationships (Cr)	Cr1	Major disputes and negotiations	[6,45]
	Cr2	Inappropriate overall organizational structure linking all parties to the project	[2,45]
	Cr3	Lack of communication between the parties	[6,45,46,47,48]
	Cr4	Conflicts between contractor and other parties (consultant and employer)	[6,50,51]
	Cr5	Mistakes and discrepancies in contract documents	[45]
External Factors (Ef)	Ef1	Weather condition	[2,45,47,48,51]
	Ef2	Regulatory changes and building Code	[2,45]
	Ef3	Problems with neighbors	[45]
	Ef4	Unforeseen ground conditions	[45,48,51]
	Ef5	Obtaining permits from municipality (government)	[2,47]
	Ef6	Economic problems	[40]
	Ef7	Natural disasters (flooding and landslide)	[48,51]
	Ef8	Disturbance to public activities	[51]
	Ef9	Inconvenient site access	[48]
	Ef10	Political situation	[48]

.

• Clients

Factors related to clients were grouped, including delays in payments for completed work and economic difficulties faced by contractors. These financial challenges directly impact the cash flow and resource availability, critical for project continuity. Studies such as those by Abdul-rahman et al. (2011) [7] and Dolage and Pathmarajah (2015) [6] emphasized the significance of financial stability in preventing project delays.

2.

Contractor

Contractor-related factors were grouped based on subcontractor performance, site management, inadequate construction methods, and improper planning. This category underscores the critical role of contractors in ensuring efficient project execution. R. F. Aziz and Abdel-Hakam (2016) [8] discussed how contractor performance directly affects project timelines and quality.

3.

Consultants

Consultant-related factors included aspects like contract management, preparation of drawings, and quality assurance. The efficiency and competence of consultants in managing and overseeing construction projects were identified as vital for preventing delays. Vaidya and Kumar (2006) [10] highlighted the impact of consultant performance on project success.

4.

Material

Material factors were categorized, focusing on delays in material delivery and quality issues. Effective material management is crucial for maintaining a steady workflow on construction sites. Orji et al. (2016) [5] discussed how material management is essential for timely project completion.

5.

Labor and Equipment

Labor and equipment factors were categorized, focusing on labor productivity, supply, and availability. These logistical issues are crucial for maintaining a steady workflow on construction sites. Orji et al. (2016) [5] discussed how labor and equipment management are essential for timely project completion.

6.

Contractual Relationships

Contractual relationship factors included major disputes and negotiations, inappropriate overall organizational structure, and lack of communication between parties. These issues can significantly disrupt the project timeline and quality. Effective communication and clear contractual agreements are essential to prevent delays.

7.

External Factors

Finally, external factors such as weather conditions, regulatory changes, and unforeseen ground conditions were grouped based on their nature outside the project stakeholders’ direct control. These external influences can unpredictably impact project schedules. Sweis (2008) [2] identified these factors as significant contributors to delays in construction projects.

The identification of delay factors was grounded in an extensive literature review covering both international and Philippine-specific studies on construction delays. Several sources emphasized recurring causes such as inadequate financial management, delayed payments, poor subcontractor performance, scheduling inefficiencies, and regulatory bottlenecks as primary contributors to delays in road infrastructure projects [4,5,7,8,40]. These causes are not isolated; rather, they interact across project stages and stakeholder responsibilities, particularly in public-sector construction managed by agencies like DPWH. The review also highlighted the lack of an integrative, stakeholder-aligned framework that considers localized factors such as right-of-way clearance, procurement hurdles, and climatic vulnerability, which are distinct challenges in the Philippine setting [25,52]. Based on thematic analysis of the reviewed literature and further validated by expert consultation, delay factors were categorized into seven domains—Client, Contractor, Consultant, Materials, Labor and Equipment, Contractual Relationships, and External Factors. These are summarized in Table 3 and further analyzed in Section 3.3 to reflect their relevance in real-world construction management. This literature-backed approach ensures that the framework is both evidence-informed and contextually grounded.

The identified factors were validated through a focus group discussion with the district engineer. This expert validation confirmed that all listed factors apply to road construction projects in the district, ensuring the factors’ relevance and accuracy. The focus group emphasized prioritizing each factor to determine its relative significance. This prioritization is critical for the AHP analysis, which requires a structured approach to ranking these factors based on their impact on project delays. Additionally, the respondents suggested ranking the main criteria categories; by prioritizing these factors and ranking the main criteria, the analysis can provide a comprehensive view of the most critical areas requiring attention.

3.2. AHP Analysis and Evaluation

Factors causing delays in road construction were identified and assessed using the AHP. Experts participated in the assessment, including consultants, project engineers, project inspectors, contractors’ project managers, and specialists from academic institutions. These experts, drawn from government agencies (DPWH), private consultants, and contractors, evaluated the factors through online and printed pairwise comparison questionnaires. The objective was to determine the weights of each factor to prioritize the most significant causes of delays. The AHP hierarchy was constructed, breaking the decision into three levels: goal, criteria, and indicators. The primary goal, placed at the top of the hierarchy, was to analyze the main factors affecting road construction delays. The second level comprised the main criteria: clients, contractors, consultants, material, labor and equipment, contractual relationships, and external factors. These criteria were detailed to guide decision-making. The lowest level included the specific factors or indicators for decision-makers.

Figure 2 illustrates the hierarchical tree representing the goal, criteria, and factors. A pairwise comparison questionnaire was prepared and distributed online and face-to-face to fifteen (15) experts from road construction and academia, each with 5–20 years of experience in road construction.

Table A1. List of respondents who participated in pairwise comparison with its year of expertise, position, and affiliation.

Respondent	Years of Experience	Position	Affiliation
1	12	Assistant District Engineer	DPWH—North Manila District Office
2	13	Site Engineer (Private)	R&V Construction
3	10	Engineer II	DPWH—Laguna 2nd District
4	9	Engineer II	DPWH—Laguna 2nd District
5	5	Engineer II	DPWH—Quezon 4th District
6	10	Project Engineer (Private)	M.T. Maliuanag Construction Services
7	8	Project Engineer (Private)	Mar-Vel Construction & Supply
8	11	Project Engineer (Private)	Protech Construction and Development Corporation
9	15	Project Engineer (Private)	Mar-Vel Construction & Supply
10	22	Engineer III	DPWH—Romblon District Office
11	20	Assistant District Engineer	DPWH—Romblon District Office
12	12	Associate Professor (Specialized in Transportation Engineering)	Central Luzon State University
13	10	Associate Professor (Construction Engineering Management)	Romblon State University
14	11	Project Engineer	Legacy Construction
15	18	General Manager	Sim’s Construction, Trading and Supply

lists these experts and their qualifications, ensuring their eligibility to provide informed responses for the AHP analysis.

A customized MATLAB 2024B script was developed to automate the pairwise comparison matrix processing, eigenvector calculation, consistency ratio (CR) validation, and final priority weight derivation in the AHP model. Using the formula of the AHP process, pairwise comparison results were encoded to sheets and transposed into MATLAB codes to ease solving the method.

Table 4. Parameters with their initial and adjusted weights and CR based on the AHP analysis.

Criteria	Code	Initial Weights	Adjusted Weights	Rank	Initial CR	Adjusted CR
Client (Cl)	Cl1	0.161	0.163	2	0.1459	0.0345
	Cl2	0.158	0.158	3
	Cl3	0.164	0.166	1
	Cl4	0.124	0.123	6
	Cl5	0.130	0.130	4
	Cl6	0.080	0.080	7
	Cl7	0.133	0.129	5
	Cl8	0.050	0.051	8
Contractor (Co)	Co1	0.093	0.091	3	0.1225	0.0284
	Co2	0.115	0.116	1
	Co3	0.099	0.100	2
	Co4	0.079	0.079	6
	Co5	0.073	0.072	7
	Co6	0.070	0.071	8
	Co7	0.087	0.089	4
	Co8	0.044	0.044	12
	Co9	0.087	0.087	5
	Co10	0.068	0.069	9
	Co11	0.040	0.040	14
	Co12	0.045	0.045	11
	Co13	0.057	0.057	10
	Co14	0.042	0.042	13
Consultant (Cs)	Cs1	0.151	No Adjustment	1	0.0885	No Adjustment
	Cs2	0.088		5
	Cs3	0.112		2
	Cs4	0.090		4
	Cs5	0.079		8
	Cs6	0.086		6
	Cs7	0.091		3
	Cs8	0.080		7
	Cs9	0.080		7
	Cs10	0.073		9
	Cs11	0.068		10
Material (Ma)	Ma1	0.225	No Adjustment	3	0.0670	No Adjustment
	Ma2	0.238		2
	Ma3	0.267		1
	Ma4	0.126		5
	Ma5	0.143		4
Labor and Equipment (Le)	Le1	0.221	No Adjustment	2	0.0720	No Adjustment
	Le2	0.240		1
	Le3	0.190		4
	Le4	0.211		3
	Le5	0.138		5
Contractual Relationships (Cr)	Cr1	0.302	No Adjustment	1	0.0474	No Adjustment
	Cr2	0.219		2
	Cr3	0.182		4
	Cr4	0.197		3
	Cr5	0.100		5
External Factors (Ef)	Ef1	0.163	No Adjustment	1	0.0703	No Adjustment
	Ef2	0.061		8
	Ef3	0.119		4
	Ef4	0.143		3
	Ef5	0.083		6
	Ef6	0.062		7
	Ef7	0.153		2
	Ef8	0.059		9
	Ef9	0.098		5
	Ef10	0.059		9

summarizes all the factors with their initial and adjusted weights based on the AHP analysis coded in MATLAB. Only the ‘client’ and ‘contractor’ criteria have an adjustment using the geometric method (see example of adjustment code in Figure 3), and the rest of the factors have no adjustment, noting that all of their CR is below 0.10 or 10%, which satisfies the AHP analysis consistently. The code allowed systematic handling of the expert responses and ensured accuracy in calculating weights across multiple stakeholders and criteria. This computational tool enhanced the transparency and reproducibility of the analysis, minimizing manual calculation errors and enabling the scalable application to other similar datasets.

To promote transparency and reproducibility, the complete MATLAB 2024b code used in this study is provided as a Supplementary File (Supplementary File S1). It includes annotated functions for matrix construction, normalization, consistency checking, and weight aggregation, and may be adapted by other researchers or practitioners conducting similar AHP analyses.

The result of AHP has shown and ranked essential factors in every criterion considered in this study. Figure 4 shows the radar chart of each criterion to emphasize the relative importance and weight value based on the AHP of various factors.

To ensure the reliability and internal consistency of expert judgments in rating the severity of road construction delay factors, Cronbach’s Alpha was calculated for each category. Cronbach’s Alpha is a widely used statistical measure that determines how well a set of survey items measures the same underlying concept. A value of 0.7 or higher indicates acceptable reliability, while values below 0.7 may suggest inconsistencies in expert ratings. In this study, Cronbach’s Alpha was computed for each delay criterion, allowing us to assess the consistency of responses across financial, managerial, material-related, and other critical delay factors. The results are presented in

Table 5. Reliability assessment of delay factor categories using Cronbach’s Alpha.

Criteria Category	Cronbach’s Alpha	Reliability Interpretation
Client	0.86	Acceptable Reliability
Contractor	0.93	Acceptable Reliability
Consultant	0.77	Acceptable Reliability
Material	0.71	Acceptable Reliability
Labor and Equipment	0.73	Acceptable Reliability
Contractual Relationship	0.74	Acceptable Reliability
External Factors	0.84	Acceptable Reliability

, which provides the computed Cronbach’s Alpha values per category.

The CI from the AHP ensures the logical consistency of expert judgments; however, it does not validate whether responses are statistically reliable. To address this limitation, Cronbach’s Alpha is incorporated to provide a more robust validation framework. CI ensures that experts’ pairwise comparisons are logically structured and do not contradict one another, while Cronbach’s Alpha confirms whether responses within a specific delay category are statistically consistent. By integrating both CI and Cronbach’s Alpha, this study enhances the reliability of expert assessments, ensuring that the severity rankings of delay factors are both logically and statistically valid. This dual validation approach strengthens the credibility of the results and supports informed decision-making in mitigating construction delays. These statistical measures comprehensively validate expert evaluations, ensuring the identified factors are significant and reliably assessed.

The regression analysis was conducted to validate the relationship between the AHP weight rankings and expert-rated delay severity (refer to

Table 6. Regression analysis of AHP weights and validation questionnaires on the severity of delay factors.

Criteria	Correlation	R Square	Significant Factor
Client (Cl)	0.161	0.110	0.468
Contractor (Co)	0.191	0.038	0.522
Consultant (Cs)	0.300	0.321	0.088
Material (Ma)	0.787	0.789	0.112
Labor and Equipment (Le)	0.956	0.913	0.045
Contractual Relationships (Cr)	0.799	0.397	0.370
External Factors (Ef)	0.683	0.342	0.098

). Based on responses from 45 engineers and experts from DPWH, LGU, academe, and the private sector, this statistical evaluation aimed to assess whether the AHP-derived rankings align with the perceived severity of delay factors. The correlation coefficient (R) and the coefficient of determination (R²) were analyzed, along with significance levels (p-values), to determine the statistical relevance of each factor.

The analysis identified Material-Related Factors (R = 0.788, R² = 0.789, p = 0.112) and Labor and Equipment Factors (R = 0.956, R² = 0.913, p = 0.045) as the most influential contributors to road construction delays. Labor and Equipment Factors exhibited a strong correlation (R > 0.95) with statistical significance (p < 0.05), confirming their critical role in predicting project delays. While Material-Related Factors also had a high correlation, its p-value slightly exceeded 0.05, suggesting moderate significance.

Contractual Relationships (R = 0.799, R² = 0.397, p = 0.370) and External Factors (R = 0.683, R² = 0.342, p = 0.098) demonstrated moderate correlations with delay severity. However, their p-values were above the 0.05 threshold, indicating that while these factors contribute substantially to project delays, they were not statistically significant at the conventional level.

In contrast, Contractor-Related Factors (R = 0.191, R² = 0.038, p = 0.522), Consultant-Related Factors (R = 0.300, R² = 0.321, p = 0.088), and Client-Related Factors (R = 0.161, R² = 0.069, p = 0.567) exhibited weaker correlations and higher p-values, suggesting that these factors were not strong predictors of delay severity in the regression model. The weak statistical significance of these categories may be attributed to the subjective nature of expert evaluations, external influences not captured in the model, or underlying factors affecting delays that were not fully accounted for in the AHP framework.

The high correlation and R² values for Material-Related and Labor and Equipment Factors confirm that AHP weight rankings effectively predict project delays, reinforcing the framework’s robustness. The validation survey involving 31 respondents provided a strong empirical basis for statistical testing, strengthening confidence in the model’s predictive capacity. However, for categories with weaker statistical significance, additional refinements—such as incorporating more diverse expert perspectives or adjusting weighting criteria—may be necessary to enhance model accuracy.

While regression analysis is not traditionally used to validate AHP weights in the MCDM literature, it was employed in this study as a complementary validation tool to assess the consistency and explanatory power of the AHP-derived prioritization. By correlating the final weighted scores of delay factors with observed expert judgment rankings (e.g., Likert-scale severity scores), the regression analysis helped verify whether the AHP results align with stakeholder perceptions in practice. This approach has been used in related decision-making contexts to evaluate internal validity and to explore the strength of association between computed priorities and empirical feedback [25,27]. Although not a substitute for CR analysis or eigenvalue checks, the regression model served as an additional robustness check to strengthen the reliability of the AHP outcome in a real-world setting.

3.3. Criteria Analysis

3.3.1. Client Criteria

The AHP analysis indicates that slow decision-making by owners (i) is the most critical factor affecting road construction projects. This is seen in the Cavite–Laguna Expressway (CALAX) project, where repeated delays were caused by slow approvals and right-of-way acquisition issues, significantly extending the project timeline and increasing costs. Owner interference (ii) ranks second, with excessive involvement from owners, such as frequent design changes and additional inspections, disrupting workflows and causing delays in various infrastructure projects. Finance and payments of completed work (iii) is also a key factor, ranking third. Payment delays have caused work stoppages in public infrastructure projects, as contractors face cash flow issues that halt progress. Late resolution of right-of-way issues (iv) and delays in site preparation (v) are positioned fourth and fifth, respectively. The CALAX project also faced significant delays due to unresolved right-of-way issues, highlighting the importance of addressing these challenges early.

Similarly, inadequate site preparation, including discovering unforeseen underground utilities, has caused delays and required additional work to meet construction standards. Late approval of shop drawings and sample materials (vi) has also slowed project timelines. Delays in securing necessary approvals can create bottlenecks in the construction process. Fraudulent practices in the organization (vii) have led to delays and inefficiencies in various infrastructure projects, as corruption and mismanagement stall progress and misappropriate funds. Finally, change orders (viii) during construction have caused significant delays. For example, last-minute changes requested by stakeholders in road construction projects often require rework, extending the project duration and increasing costs.

3.3.2. Contractor Criteria

The analysis results rank site management (iv) as the most critical factor in construction projects. Effective site management ensures that project schedules, quality, and safety are maintained. Poor site management has often led to significant delays and cost overruns, as seen in various infrastructure projects in the Philippines, where inadequate oversight has resulted in inefficient resource use and extended timelines [53]. Following this, inadequate construction methods (ii) are ranked second, highlighting the necessity of using appropriate techniques and technologies in construction. Outdated methods or improper use of equipment can lead to defects, rework, and delays, impacting overall project success. Subcontractors (iii) rank third, indicating their critical role in project execution. Poorly managed subcontractors can disrupt project timelines and quality, causing significant delays across the board.

Next, the poor qualification of the contractors’ technical staff (iv) is ranked fourth, emphasizing the importance of having skilled personnel to avoid construction errors and inefficiencies. Difficulties in financing projects by contractors (v) come in fifth. Financial instability often leads to halted progress as contractors struggle to maintain cash flow and secure necessary funding. Improper planning (vi) and mistakes during construction (vii) are also significant factors, as inadequate planning and errors during execution often result in costly delays and the need for rework. The mid-ranked factors include inadequate contractor experience (viii), which underscores the importance of having experienced contractors who can anticipate and manage the complexities of construction projects. Handling too many projects at a given time (ix) can lead to resource strain and diminished focus, resulting in delays and reduced quality across projects [6]. Improper handling of project progress by the contractor (x) can cause misaligned schedules, missed deadlines, and poor-quality work, further delaying project completion.

The lower-ranked factors, such as delay in mobilization (xi) and rework due to unaccepted quality (xiii), still play significant roles in project inefficiencies. Delays in mobilization can set back project timelines from the beginning, while poor-quality work that requires rework adds to delays and increases costs [54]. Finally, replacing key personnel (xii) during a project can disrupt workflow and decision-making, causing delays as new team members adjust to their roles.

3.3.3. Consultant Criteria

The results identify contract management (i) as the most crucial factor affecting construction projects. Effective contract management is essential for ensuring project timelines are adhered to, preventing cost overruns, and avoiding disputes. Recent studies highlight that poor contract management often leads to significant delays and increased costs, making it imperative to establish clear communication and well-defined contract terms to mitigate these risks [55]. Inappropriate design (ii) ranks second, emphasizing the critical need for accurate and practical designs at the project’s outset. Design flaws can cause extensive rework and delays, disrupting the project timeline [56]. Poor estimation practices and low-profit margins (iii) rank third, where inaccurate cost estimations can lead to financial strain, resource shortages, and project delays, significantly impacting the overall project delivery [57].

Quality assurance/control (iv) is fourth in the ranking, stressing the importance of maintaining construction standards to prevent defects and rework that could delay the project [56]. Preparation of drawings (v) ranks fifth, highlighting the necessity for detailed and accurate drawings to guide the construction process effectively. Errors in this stage can lead to construction issues and project delays [58]. Mid-ranked factors include delays in performing inspections (vi) and waiting time for approval of tests (viii), which can create bottlenecks in project timelines if not appropriately managed [59]. Incapable and insufficient inspectors (vii) further exacerbate these delays, as their lack of skill can lead to missed defects and the need for additional inspections [53]. Unrealistic contract durations (ix) and undefined scope of work (x) are also significant factors, where setting unachievable deadlines and unclear project scopes can cause project delays and disputes [60,61]. These rankings underscore the need for robust management, accurate planning, and effective quality control to enhance construction project outcomes.

3.3.4. Material Criteria

The ranking showed the delay in delivering materials (i) as the most critical factor affecting construction projects. Timely delivery is essential to maintain project schedules, and any delays can cause significant disruptions, leading to project overruns and increased costs. Recent studies emphasize the importance of an efficient supply chain to ensure that materials are delivered on time, which is crucial for project success [62]. Material shortage (ii) ranks second, underscoring the impact of material availability on construction projects. Material shortages can halt work, causing delays and escalating costs as projects struggle to secure the necessary resources. Quality of materials (iii) is ranked third, indicating the importance of using high-quality materials to avoid rework and ensure the longevity of the construction. Poor-quality materials often result in structural failures or defects, leading to delays as these issues are rectified [56]. Modifications in material specifications (iv) rank fourth, where changes in material specifications during construction can disrupt schedules and lead to additional costs due to reordering or reworking existing structures to accommodate the new specifications [63]. Lastly, price escalation (v) is ranked fifth, highlighting the financial challenges of rising material costs. Price fluctuations can strain project budgets, leading to delays as contractors renegotiate terms or seek alternative suppliers [61].

3.3.5. Labor and Equipment Criteria

The labor and equipment criteria results show that labor productivity (i) is the most critical factor in construction projects. According to a recent study, labor productivity directly impacts project timelines and profitability, with inefficiencies potentially leading to substantial financial losses. Improved management and strategic planning are vital in enhancing productivity, which is often compromised by poor coordination and insufficient training of workers [64]. Labor supply (ii) is ranked second, highlighting the significant impact of workforce shortages on construction timelines. Workforce shortages significantly cause project delays, particularly in large-scale infrastructure projects with high demand for skilled labor [65]. Equipment availability and failure (iii) rank third. The reliability of construction equipment is crucial to maintaining project schedules. Equipment breakdowns and unavailability can cause significant delays, especially in time-sensitive projects where timely completion is critical [66].

Low equipment-operator skill level (iv) is ranked fourth, emphasizing the importance of skilled operators in efficiently using construction machinery. Insufficient training and experience among operators can lead to improper use of equipment, resulting in decreased productivity and increased project delays [67]. Finally, labor disputes and contractor issues (v) are ranked fifth, underlining the impact of labor relations on project timelines. Conflicts between workers and contractors can halt progress, leading to delays and additional costs. Effective communication and dispute-resolution strategies are essential to prevent and mitigate these issues [68].

3.3.6. Contractual Relationships Criteria

The analysis for the provided factors ranks major disputes and negotiations (i) as the most critical construction project issues. Significant disputes can delay project timelines, escalate costs, and disrupt workflow. Resolving these disputes involves lengthy negotiations, which can stall progress and lead to contractual disputes if not managed effectively [69]. Inappropriate overall organizational structure linking all parties to the project (ii) is ranked second. A poorly structured organization can lead to inefficiencies, miscommunication, and a lack of coordination between different stakeholders. This disorganization often results in delays and increased project costs as responsibilities are unclear and processes become fragmented [70]. Conflicts between the contractor and other parties (such as consultants and employers) rank third (iii). These conflicts often arise due to differences in expectations, miscommunication, or disagreements over project execution. Such conflicts can cause work stoppages and require mediation or legal resolution, further delaying the project [71].

Lack of communication between the parties (iv) ranks fourth. Effective communication is essential for ensuring all stakeholders are on the same page. Miscommunication or a lack of communication can lead to misunderstandings, errors, and delays, particularly in complex construction projects where coordination is critical [72]. Finally, mistakes and discrepancies in contract documents (v) are ranked fifth. Contract errors, such as unclear terms or conflicting clauses, can lead to disputes and require amendments or renegotiations, causing delays and potential legal challenges. Ensuring that contract documents are accurate and comprehensive is essential to avoid these issues [73].

3.3.7. External Factors Criteria

The AHP analysis ranks weather conditions (i) as the most critical factor affecting construction projects. Adverse weather conditions, such as extreme heat, cold, or heavy rainfall, can severely disrupt construction activities, causing delays and increasing costs. This is particularly impactful in regions prone to sudden weather changes, which can halt work unexpectedly [74]. Natural disasters such as flooding and landslides rank second (ii). These events can cause extensive damage to construction sites, leading to significant project delays as recovery efforts are made. In areas prone to such disasters, proactive planning and risk management strategies are essential to mitigate these risks [75]. Unforeseen ground conditions (iii) rank third, highlighting the challenges posed by unexpected subsurface conditions, such as rock formations or groundwater, which can complicate foundation work and other construction activities. This often leads to project delays as alternative strategies must be developed. Problems with neighbors (iv) are ranked fourth. Neighbor disputes or complaints can delay construction activities, especially in densely populated areas where noise, dust, and access issues are prevalent. Resolving these conflicts requires careful management and, often, negotiation. Inconvenient site access (v) ranks fifth, as difficulty in accessing construction sites can delay the delivery of materials and movement of equipment. This is particularly problematic in urban areas or sites with limited infrastructure.

Obtaining permits from the municipality (vi) is ranked sixth, where bureaucratic delays in securing necessary licenses can push back project timelines significantly. Ensuring compliance with local regulations and maintaining good relations with municipal authorities is crucial to avoid these delays. Economic problems (vii) rank seventh, indicating the impact of financial instability, inflation, and other economic factors on construction projects. Economic downturns can lead to reduced funding and resource shortages, causing delays. Regulatory changes and building code updates (viii) rank eighth, emphasizing the need for projects to adapt to new regulations, which can involve redesigns or additional compliance measures, leading to delays. Finally, disturbance to public activities and political situations (ix) ranks ninth. Public disturbances, such as protests or local events, can disrupt construction schedules, while unstable political situations can lead to uncertainties, policy changes, or even project cancellations.

3.4. Strategic Framework Development

The framework for mitigating delays in road construction, developed using the AHP, identifies several key factors that significantly impact project timelines and outcomes. The final framework is effectively visualized using an Ishikawa (Fishbone) Diagram, as shown in Figure 5, which categorizes these factors based on their significance and weight. This diagram was chosen for its ability to organize causes under thematic categories, reflecting the structured output of the AHP while making complex interrelationships among delay factors easier to interpret. Each “bone” of the diagram represents a stakeholder domain (e.g., contractor, consultant, client), enabling users to trace specific issues back to responsible parties. To provide a more detailed and actionable guide, an expanded version with proposed mitigation strategies is included in the Supplementary Material (Supplementary Figure S1), offering an implementation-oriented roadmap aligned with the framework’s prioritized delay factors.

In this diagram, the central spine represents the overall goal of mitigating delays in road construction. The primary bones of the diagram are arranged from top to bottom, reflecting the weight of each factor and rank as determined by the AHP analysis. Factors with the highest weight values significantly impacting construction delays are placed at the top of the diagram. The factors have progressively lower weight values as you move downward, indicating their lesser impact. The diagram is divided into two main sections: ‘High Weight Factors’ and ‘Low/Mid-Weight Factors’. The high-weight factors in the upper section are the priority factors that require immediate attention due to their significant influence on construction delays. The low/mid-weight factors, found in the lower section, still contribute to delays but are of less priority than the high-weight factors.

Each criterion in the diagram is further broken down into sub-categories, representing specific factors contributing to road construction delays. These sub-categories are visually represented as secondary bones branching out from the primary bones. Additionally, mitigation strategies are linked to these specific factors, depicted as tertiary bones. These strategies are designed to address the root causes of the delays, preventing them from affecting subsequent stages of the project.

The fishbone diagram for mitigating delays in road construction provides a structured and prioritized approach to mitigating delays in road construction, ensuring that the most critical issues are identified and addressed first. The precise categorization and visualization of factors and their corresponding weights allow stakeholders to quickly understand which areas require the most attention, facilitating more effective decision-making and project management. While drafting the framework, it was found that some strategies share common solutions across multiple factors. These solutions emerged from the framework analysis and are designed to streamline processes, enhance planning, and improve overall project efficiency.

First, streamlining processes involves implementing strict timelines for approvals and standardizing payment procedures to ensure prompt decision-making and smooth operations, thereby reducing potential delays. Early planning and assessment are crucial, as they involve thorough site and document reviews during the planning phase to anticipate and address potential challenges, such as change orders or unforeseen site conditions, before they impact the project timeline.

Technology and digital tools, such as automated payment systems and digital platforms, are recommended to facilitate faster reviews, approvals, and decision-making processes, all essential for maintaining project schedules. Clear roles and communication within the project team are also emphasized, with clear responsibilities to prevent confusion and reduce unnecessary stakeholder involvement. Efficient communication channels, including regular meetings and dedicated liaisons, ensure that issues are addressed promptly and that all team members are aligned with the project’s goals.

Oversight and accountability are maintained through strict internal controls, regular audits, and the establishment of dedicated committees. These measures ensure transparency, prevent fraudulent practices, and uphold the project’s integrity. By focusing on these common solutions, the framework addresses key factors contributing to delays, leading to more efficient project management and timely completion of road construction projects.

While Figure 5 presents the core structure of the strategic AHP-based framework, a more detailed implementation roadmap is provided in Supplementary Figure S1. This supplementary diagram visualizes the full prioritization of delay factors based on AHP weights, categorized under key stakeholder domains (e.g., Client, Contractor, Consultant, External). High-weight and low-weight factors are grouped accordingly, enabling practitioners to identify not only root causes but also the sequence and urgency of recommended mitigation actions. This roadmap can serve as a decision-support tool for agencies like DPWH, allowing them to operationalize the framework in project planning, monitoring, and policy development. This fishbone diagram visually integrates the delay factors across stakeholder domains and illustrates how certain factors (e.g., material shortages, poor planning, or consultant delays) are not isolated, but can influence multiple project aspects.

For instance, material shortages (MA2) are closely linked to contractor-level issues such as inadequate planning (CO6), procurement delays (MA4), and subcontractor mismanagement (CO7). These implicit interconnections are reflected structurally in the supplementary figure, which organizes the framework not only by AHP ranking but also by domain-level cause-effect chains. This provides a more realistic and systemic view of delay mechanisms in Philippine road construction projects. By offering both a high-level overview and a detailed implementation roadmap (Supplementary Figure S1), we aim to meet the needs of both conceptual understanding and practical application.

The validation process involved ten (10) professionals specializing in road construction, including representatives from the academe, consultancy sector, inspection teams, and primarily from the DPWH (see

Table 7. Summary of expert respondents for the validation of the proposed framework.

Category	Number of Respondents	Average Years of Experience
DPWH Officials	5	22
Consultants	1	8
Academe	1	15
Private Sector	3	24

). On average, participants had 17.25 years of industry experience, ensuring that the feedback reflected deep, field-based knowledge. While the group included only one representative each from the consultancy and academic sectors, the emphasis on DPWH officials was intentional and aligned with the study’s objectives. Given that DPWH is the primary implementing agency for public road projects in the Philippines and is directly accountable for addressing delays, focusing on their perspectives was deemed both relevant and essential. These officials regularly encounter systemic and operational challenges tied to delays, such as procurement bottlenecks, contractor non-performance, and right-of-way issues. Their front-line experience offers critical insights into delay mitigation strategies, making their input highly appropriate for validating a framework centered on national road infrastructure delivery. Although broader representation can enhance generalizability, the targeted engagement of DPWH experts ensures the framework is context-specific, practical, and policy-relevant. All experts were selected based on their direct involvement in road construction projects and familiarity with delay-related challenges. Participation was voluntary, and all responses were anonymized to reduce bias.

The mean scores and standard deviations from the expert evaluations are presented in

Table 8. Mean ratings and standard deviations of the framework evaluation based on the responses of 10 experts for validation.

Statement	Mean Score	Standard Deviation
The framework presents the significant factors affecting delays	4.6	0.49
The categorization of factors into high-weight and low-mid-weight factors is logical	4.4	0.49
The structure of the framework is easy to understand	4.6	0.49
The framework effectively mitigates delays	4	0
The weight assignment appropriately reflects delay impacts	4.5	0.52

. The results indicate a generally positive perception of the framework, with most ratings exceeding 4.0, signifying strong agreement among experts. The highest-rated aspects were “The framework presents the major factors affecting delays” and “The structure of the framework is easy to understand”, both receiving a mean score of 4.6. Meanwhile, the lowest-rated aspect was “The framework effectively mitigates delays”, with a mean of 4.0, suggesting potential areas for improvement.

The validation process provided valuable qualitative insights from experienced professionals in road construction. Experts highlighted several strengths of the framework, suggested areas for improvement, and recommended additional factors that could enhance its effectiveness. The summary of feedback is listed below (

Table 9. Summary of expert feedback on the proposed strategic framework for mitigating road construction delays in the Philippines.

Key Theme	Summary of Expert Feedback	Sample Responses
Strengths of the Framework	Clear, structured, and applicable; effectively prioritizes delay factors	“It is simple and can be applied in real situations.”
		“The framework prioritizes the factors that actually delay road construction.”
Suggested Improvements	Simplify wording and improve clarity for better usability	“Minimize wordings and enhance presentation.”
		“It is indeed effective but could be streamlined for better memorability.”
Additional Factors	Include safety precautions and contingency plans for pandemics	“Safety site precautions as construction is one of the high-risk industries.”
		“Safety provisions and contingencies in case of another pandemic or any other causes.”
Final Comments	Strengthen focus on worker and public safety	“More focus on safety both for the general public, the contractor’s personnel, and end users.”

).

• Strengths of the Framework

The experts generally found the framework to be clear, structured, and applicable to real-world road construction projects. Many respondents appreciated its detailed categorization of delay factors, which they believed helped in prioritizing the most critical contributors to project delays. One expert noted, “It is simple and can be applied in real situations”, while another emphasized, “The framework prioritizes the factors that actually delay road construction”. The respondents also highlighted that the framework effectively identifies and organizes high-weight and low-mid-weight factors, making it a practical tool for decision-makers.

2.

Suggested Improvements

While the framework was well-received, some experts suggested minor refinements to improve its readability and usability. A few respondents recommended simplifying the wording and enhancing presentation clarity to ensure better comprehension. One expert suggested “Minimize wordings and enhance presentation”, while another stated, “It is indeed effective but could be streamlined for better memorability”. These responses indicate that making the framework more concise and visually engaging could improve its accessibility.

3.

Additional Factors to Consider

Several respondents recommended incorporating safety-related considerations into the framework. Since road construction is a high-risk industry, experts suggested including safety site precautions and contingency plans for pandemics or unforeseen disruptions. One expert commented, “Safety site precautions as construction is one of the high-risk industries”. At the same time, another recommended: “Safety provisions and contingencies in case of another pandemic or any other causes”. These suggestions highlight the importance of integrating risk management measures into the framework.

4.

Final Comments and Recommendations

Some experts emphasized the need for stronger safety measures to protect workers and the general public. One respondent stated, “More focus on safety both for the general public, the contractor’s personnel, and end users”. These comments reinforce the need to expand the framework’s scope beyond time-related delays to include broader project risks.

To further contextualize the findings, a representative road project implemented by DPWH was briefly examined. The project experienced a six-month delay primarily due to issues identified in this study: right-of-way acquisition, limited contractor capacity, and delays in fund disbursement. By mapping these real-world issues against the top-ranked delay factors derived from AHP analysis, we found strong alignment. Moreover, the proposed mitigation strategies, such as early community engagement for right-of-way clearance, prequalification enhancement for contractors, and phased fund releases, were partly adopted in the latter phase of the project, which helped improve schedule adherence. This case highlights the practical relevance and effectiveness of the developed AHP-based framework when applied to actual road construction settings in the Philippines.

4. Discussion

The results of the AHP revealed six major categories of delay factors: client-related, contractor-related, consultant-related, material-related, labor and equipment-related, and external factors. Table 6 summarizes the final priority weights assigned to each factor based on expert responses. The ranking highlights that the most critical contributors to delays in road construction projects in the Philippines are predominantly associated with client-side inefficiencies, contractor mismanagement, and regulatory bottlenecks.

Client-related factors, such as delays in fund disbursement (CL1) and slow decision-making (CL3), received high weights in the AHP analysis. These findings are aligned with the operational realities within the Department of Public Works and Highways (DPWH), where bureaucratic procedures often lead to approval lags. To address this, streamlining budget approvals and implementing digital payment systems are recommended.

Contractor-related delays also ranked highly, particularly poor planning and scheduling (CO6), inadequate subcontractor performance (CO7), and limited technical capacity (CO3). These results emphasize the need for a more rigorous contractor prequalification process, as well as real-time performance monitoring. DPWH can strengthen oversight by enforcing tighter timelines and adopting construction management software for better tracking of contractor deliverables.

Consultant-related delays, though relatively lower in weight compared to the top-ranking domains, still present significant challenges. Factors such as delayed approvals of drawings and inadequate contract management highlight the importance of standardized documentation protocols. As seen in Table 7, experts noted that performance-based incentives could further motivate consultants to meet deadlines without compromising quality.

Material-related issues, such as procurement delays (MA4) and poor quality of materials (MA3), also emerged as key concerns. Establishing framework agreements with trusted suppliers, coupled with predictive procurement planning, can improve supply chain reliability. Similarly, labor and equipment-related constraints, particularly labor shortages (LE2) and equipment breakdowns (LE3), stress the need for workforce upskilling and equipment maintenance systems.

Lastly, external factors, especially those beyond the direct control of project implementers, such as right-of-way issues (EX1) and extreme weather events (EX3)—were recognized for their compound effects on project timelines. DPWH can improve resilience to these external disruptions by integrating weather forecasting tools, streamlining right-of-way acquisition processes, and establishing flexible implementation schedules.

Overall, the results provide a structured understanding of the root causes of road construction delays, validated through expert insights. The prioritization matrix in Table 6 offers actionable direction for policymakers, while Table 7 provides context on the professional backgrounds of the respondents involved in the AHP process. To further support interpretation and practical implementation, the synthesized mitigation strategies are visually represented in Figure 5, with a more detailed version presented in Supplementary Figure S1.

The recommendations derived from this analysis are highly applicable to DPWH, given its mandate to execute large-scale infrastructure projects across the Philippines. To apply these solutions effectively:

• Streamlining Bureaucratic Processes: DPWH should work towards reducing bureaucratic bottlenecks by adopting digital solutions such as electronic procurement and approval systems. This would accelerate payment processes and reduce delays caused by manual approvals;
• Enhancing Contractor Management: DPWH can ensure that only qualified and capable contractors are engaged by implementing a more robust contractor evaluation and monitoring system. Regular performance reviews and project management software will help track progress and address issues before they cause significant delays;
• Strengthening Consultant Accountability: DPWH can improve consultants’ efficiency by setting clear expectations and implementing a performance-based evaluation system. This approach will ensure that consultants deliver high-quality work on time, reducing delays associated with poor contract management and documentation;
• Improving Material Supply Chain: DPWH should establish strategic partnerships with suppliers to secure timely material delivery. A centralized tracking system will enable better management of supply chains, reducing the likelihood of delays caused by material shortages;
• Optimizing Labor and Equipment Use: DPWH can enhance labor productivity by providing ongoing training and ensuring the availability of skilled workers and equipment. A resource pool and equipment monitoring system will ensure that projects do not stall due to labor shortages or equipment failure. In this case, a training plan was developed since the DPWH does not directly manage laborers and skilled workers but rather contracts private firms to execute projects; a structured training framework must be established to ensure that contractors integrate workforce development into their operations;
• Proactive Risk Management: DPWH should integrate advanced planning tools for weather conditions and regulatory changes to deal with external factors. Developing flexible project schedules and contingency plans will allow for quick adaptation to unforeseen events, ensuring that projects remain on track.

DPWH can significantly reduce delays in road construction projects, leading to more timely and cost-effective infrastructure development across the Philippines. These measures will improve the efficiency of DPWH and contribute to the country’s overall economic growth by ensuring that critical infrastructure projects are completed as planned.

However, for this study, identifying criteria and factors contributing to delays in road construction projects began with a thorough literature review, a common approach in scientific research. This review, similar to studies by Odeh and Battaineh (2002) [45] and Abdul-rahman et al. (2011) [7], helped pinpoint key issues like contractor inefficiencies and financial management problems. Based on this, a list of potential delay factors was created, focusing on economic matters, contractor performance, and external influences, following methods seen in studies like Dolage (2015) [6]. To ensure the practical relevance of these factors, expert consultations were conducted, aligning with practices in other research where stakeholder input is vital. Discussions with representatives from DPWH and private sector entities highlighted specific challenges, such as bureaucratic delays, which are critical in the Philippine context. This feedback refined the factors into categories like subcontractor management and site supervision, similar to the refinement seen in studies like Fouladgar et al. (2012) [21].

The refined factors were systematically organized into a hierarchical structure using the AHP framework. AHP is a widely recognized multi-criteria decision-making tool for risk assessment, suitability assessment, etc. It allows for the structured comparison of factors based on their relative importance to a specific goal—in this case, mitigating delays in road construction projects. By employing AHP, the factors were categorized into six main groups: client-related factors (such as delays in payments), contractor-related factors (like site management), consultant-related factors (including contract management), material-related factors (such as delays in delivery), labor and equipment-related factors (like labor availability), and external factors (such as weather conditions). Each category was further broken down into specific factors directly assessed and compared within the AHP framework.

Using AHP, pairwise comparisons were conducted within each category to assess the relative importance of factors. The resulting weights reflected the criticality of each factor. To ensure reliability, the consistency of these comparisons was checked using the CR. Despite its limitations, a key advantage of AHP is its ability to incorporate geometric adjustment when the CR exceeds acceptable thresholds (usually 0.1). This adjustment refines the comparisons, ensuring that even slight inconsistencies do not undermine the overall reliability of the results. Geometric adjustment in AHP helps correct inconsistencies in judgment without compromising the integrity of the decision-making process, making AHP more robust than other methods that may not offer such refinement. This ability to ensure consistency and reliability, even when initial comparisons are imperfect, makes AHP an effective and reliable tool for complex decision-making.

AHP is particularly well-suited for this type of analysis because it allows decision-makers to break down a complex problem into smaller, more manageable parts. Each part can be analyzed independently, and the results can be aggregated to provide a comprehensive overview of the problem. This approach contrasts with other decision-making methods, such as the Delphi technique or simple weighted scoring models, which may not offer the same level of granularity and systematic comparison. For example, the Delphi method relies on expert consensus and may not capture the nuances of relative importance among factors as effectively as AHP. Similarly, while weighted scoring models assign scores to factors, they do not offer a structured way to compare these factors in pairs, which is a crucial strength of AHP. The recent literature supports the use of AHP in complex decision-making scenarios. According to a study by Kullaya (2022) [76], AHP is superior in handling qualitative and quantitative data, making it ideal for projects where different types of information need to be integrated into the decision-making process. The results of this study are largely consistent with earlier AHP-based investigations into construction delays [12,21], which also identified poor financial planning and contractor inefficiencies as dominant causes. However, this research uniquely integrates local institutional challenges such as right-of-way clearance and inter-agency coordination, which are seldom emphasized in the broader AHP literature, making it more applicable to the Philippine road construction context.

However, when discussing the AHP, it is crucial to consider the number of experts involved in pairwise comparisons. There are no strict guidelines on the minimum sample size for AHP analysis in management and engineering. Studies show varying sample sizes, typically four to nine participants, indicating the method’s flexibility. When selecting judges for decision-making, strategically choosing individuals with the necessary expertise is essential. One expert judge is usually sufficient unless political factors require representation from multiple constituencies. In such cases, selecting several judges may be appropriate, provided they possess the necessary expertise, ensure balanced decision-making, and promote credibility [77].

Additionally, AHP’s ability to check for consistency in judgments enhances the reliability of the results, a feature not present in more straightforward methods like weighted scoring. Another study by Ahmed et al. (2023) [57] highlights AHP’s flexibility in adjusting to different contexts and its effectiveness in prioritizing factors in infrastructure projects, further emphasizing its suitability for developing a framework to mitigate construction delays. AHP’s structured approach, ability to handle diverse data types, and consistency checks make it the optimal method for organizing and comparing the factors contributing to delays in road construction projects. This method provides a clear hierarchy of factors and ensures that the most critical issues are prioritized effectively, leading to more informed decision-making and better project outcomes.

5. Conclusions

This study developed a strategic and stakeholder-informed framework to mitigate delays in road construction projects in the Philippines using AHP. By evaluating multiple dimensions—ranging from client-side inefficiencies to external regulatory challenges—the study provides a comprehensive, data-driven approach to improve infrastructure delivery performance.

The key findings of the study include:

• The most critical delay factors identified through AHP are poor financial and cash flow management, inadequate subcontractor performance, deficient planning and scheduling, and regulatory and permitting challenges;
• These factors were grouped under seven domains: client, contractor, consultant, materials, labor and equipment, contractual relationships, and external factors;
• The framework offers targeted strategies for both pre-construction and post-construction phases, such as: (a) enhancing stakeholder communication and coordination, (b) strengthening financial oversight and risk management, (c) incorporating environmentally sustainable practices through material efficiency, energy optimization, and EIA compliance;
• The framework is visualized through a Fishbone Diagram and supported by expert validation, making it adaptable for implementation by the DPWH, particularly in regional offices facing recurring construction issues.

While the framework offers practical value, this study has certain limitations. The expert validation sample was heavily skewed toward DPWH officials, with limited representation from consultants and academia, which may influence the prioritization outcomes. Furthermore, while regression analysis was used to validate the consistency of AHP weights, it remains a non-traditional approach in the MCDM literature and may require further scrutiny. Lastly, future research should broaden stakeholder participation, apply hybrid MCDM approaches for robustness, and pilot the framework in active road construction projects to assess its practical effectiveness.

This study concludes that addressing the root causes holistically and focusing on high-weight factors through this strategic framework can significantly improve the efficiency and timeliness of road construction projects in the Philippines, ultimately leading to more sustainable and resilient infrastructure development. The comprehensive framework developed in this study can be effectively adopted by the DPWH, particularly in regional districts that frequently encounter common road construction issues. DPWH can enhance project management practices, reduce delays, and achieve more efficient and timely road infrastructure delivery across its regional operations by implementing strategic recommendations and focusing on the prioritized high-impact factors.