Why Multi-Criteria Decision-Making Can Improve Rural Road Maintenance Planning: Insights from an AHP-Based Study in Myanmar

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Maintaining road infrastructure is one of the most challenging responsibilities faced by transportation agencies, particularly in developing countries where financial resources are limited and maintenance needs often exceed available budgets. Deciding which roads should receive immediate attention is therefore not only an engineering problem but also a strategic decision-making challenge. Traditional pavement assessment methods primarily evaluate physical road conditions, yet they may overlook the broader significance of different types of pavement distress when determining maintenance priorities.

The study reviewed here investigates how the Analytical Hierarchy Process (AHP), a widely recognized multi-criteria decision-making technique, can support more systematic and transparent road maintenance prioritization. Using a case study from Shan State, Myanmar, the authors compare AHP with the conventional Pavement Condition Index (PCI) approach to determine whether incorporating multiple engineering criteria leads to more informed maintenance decisions. The findings provide valuable insights for civil engineers, transportation planners, infrastructure managers, policymakers, and researchers interested in sustainable pavement management and evidence-based infrastructure investment.

Bibliographic Information

Item Information
Article Title An Analytical Hierarchy Process (AHP) Approach to Road Maintenance Prioritization: A Case Study in Shan State, Myanmar
Authors Nandar Tun, Kyaing, and Moe Thet Thet Aye
Journal Innovation in Engineering
Volume & Issue Volume 1, Issue 2
Publication Year 2024
Pages 60–72
DOI https://doi.org/10.58712/ie.v1i2.9
Publisher Researcher and Lecturer Society
License Creative Commons Attribution 4.0 International (CC BY 4.0)

1. Research Background

  • Road maintenance is essential for economic and social development. Rural roads provide critical connections between communities, markets, healthcare facilities, educational institutions, and urban centers. Maintaining these transportation networks is fundamental to regional development, especially in developing countries where road infrastructure directly influences accessibility and economic activity.
  • Limited maintenance budgets require effective prioritization. Transportation agencies frequently face financial and operational constraints that prevent simultaneous maintenance of all deteriorated roads. Consequently, selecting which road segments should receive immediate intervention becomes a crucial infrastructure management decision.
  • Conventional pavement evaluation methods have practical limitations. Widely used approaches such as the Pavement Condition Index (PCI) primarily assess pavement surface conditions. Although these methods provide valuable engineering information, they may not fully represent the relative importance of different pavement distress types when determining maintenance priorities.
  • Multi-Criteria Decision-Making (MCDM) methods have gained increasing attention. Previous infrastructure management studies have demonstrated that decision-support techniques such as the Analytical Hierarchy Process (AHP) enable engineers to evaluate multiple technical criteria simultaneously. These approaches incorporate both quantitative measurements and expert judgment to support more balanced maintenance decisions.
  • Research on rural road prioritization remains relatively limited. While AHP has been successfully applied to various infrastructure management problems, relatively few studies have focused specifically on rural road maintenance in developing countries, where pavement deterioration patterns, resource limitations, and maintenance challenges differ from those found in urban environments.
  • The study addresses this practical research gap. The authors apply the AHP framework to evaluate ten rural roads in Shan State, Myanmar, with the objective of developing a systematic, transparent, and replicable maintenance prioritization approach suitable for local infrastructure agencies.
  • The study introduces an accessible implementation approach. Instead of relying on specialized optimization software, the researchers implement the AHP calculations using an Excel-based tool, making the methodology easier to adopt by local practitioners and government agencies with limited computational resources.
  • The research also evaluates an alternative decision framework. By comparing AHP results with rankings obtained using the Pavement Condition Index, the study investigates whether a multi-criteria evaluation framework provides different—and potentially more informative—maintenance priorities than conventional pavement condition assessments alone.

2. Research Objectives

  • To develop a structured framework for prioritizing rural road maintenance using the Analytical Hierarchy Process (AHP).
  • To evaluate pavement maintenance priorities by considering multiple engineering criteria, including roughness, raveling, potholes, bleeding, and edge failure.
  • To collect and analyze pavement condition data from ten rural roads located in Shan State, Myanmar.
  • To compare maintenance priorities generated by the AHP method with those obtained using the conventional Pavement Condition Index (PCI).
  • To determine whether integrating multiple pavement distress indicators leads to more comprehensive maintenance decision-making.
  • To provide an objective and transparent decision-support approach that can assist infrastructure agencies in allocating maintenance resources more effectively.
  • To demonstrate the applicability of AHP for rural pavement management in developing-country contexts.

3. Why This Research Matters

  • Supports evidence-based infrastructure investment. Maintenance funding is often limited, making systematic prioritization essential for maximizing the benefits of available financial resources.
  • Improves engineering decision-making. Considering multiple pavement distress indicators simultaneously allows engineers to make maintenance decisions based on a broader understanding of pavement performance rather than relying on a single condition index.
  • Enhances transparency in maintenance planning. The AHP framework provides a clear and traceable decision-making process, helping transportation agencies justify maintenance priorities to stakeholders and funding authorities.
  • Promotes sustainable infrastructure management. Prioritizing roads according to engineering importance can extend pavement service life, optimize maintenance schedules, and reduce long-term rehabilitation costs.
  • Provides practical value for developing countries. The Excel-based implementation demonstrates that advanced decision-support methods can be applied without expensive software, increasing accessibility for local governments with limited technical resources.
  • Contributes to transportation engineering research. The comparison between AHP and PCI highlights how multi-criteria decision-making techniques can complement conventional pavement evaluation methods rather than replace them.
  • Supports broader socio-economic development. Better maintenance prioritization contributes to safer, more reliable rural transportation networks that facilitate mobility, trade, education, healthcare access, and regional economic growth.
  • Offers a transferable framework. Although the case study focuses on Myanmar, the proposed methodology can potentially be adapted for rural road maintenance planning in other developing regions facing similar infrastructure management challenges.

4. Research Methodology

  • Research Type

    The study employed a quantitative engineering research approach using the Analytical Hierarchy Process (AHP) as a Multi-Criteria Decision-Making (MCDM) technique to prioritize rural road maintenance. Rather than developing a new pavement evaluation index, the research focused on improving maintenance decision-making by integrating multiple pavement distress indicators into a structured ranking framework.

  • Study Area

    The case study was conducted on ten rural roads located in Shan State, Myanmar. All selected road sections are flexible pavements managed by the Department of Rural Road Development (DRRD). Each road was divided into twenty subsections of 25 meters, resulting in a total of 200 pavement segments for evaluation. This sampling strategy enabled a comprehensive assessment of pavement conditions across the selected rural network.

  • Data Collection

    Field observations were conducted to identify pavement distress and measure road conditions. The researchers collected Pavement Condition Index (PCI) data through visual inspections and measured the International Roughness Index (IRI) using the RoadLab Pro system. Multiple measurements were taken where necessary to improve data consistency before analysis.

  • Evaluation Criteria

    Five engineering criteria were incorporated into the AHP model:

    • Raveling
    • Bleeding
    • Potholes
    • Edge failure (edge drop)
    • Road roughness (IRI)

    Each criterion was further classified into severity levels, allowing the decision model to distinguish between different pavement deterioration conditions during the prioritization process.

  • Pavement Condition Assessment

    The Pavement Condition Index (PCI) was calculated following established pavement evaluation procedures based on the degree and extent of pavement distress. PCI results served as a benchmark against which the AHP prioritization outcomes were compared, enabling the researchers to evaluate differences between conventional pavement assessment and multi-criteria decision-making.

  • AHP Model Construction

    The researchers developed a hierarchical decision model consisting of one overall objective, five evaluation criteria, and fifteen sub-criteria representing different distress severity levels. Pairwise comparison matrices were established to quantify the relative importance of each criterion using Saaty's fundamental scale.

  • Consistency Validation

    To ensure reliable expert judgment, the consistency of the pairwise comparison matrix was evaluated through the Consistency Index (CI) and Consistency Ratio (CR). The calculated CR value was below the commonly accepted threshold of 0.10, indicating that the comparison matrix was sufficiently consistent for decision analysis.

  • Analysis Tools

    An Excel-based decision-support tool was developed to perform the AHP calculations, including matrix normalization, priority vector estimation, weighted scoring, and road ranking. The use of spreadsheet software demonstrates that the methodology can be implemented without specialized optimization software, increasing its accessibility for local infrastructure agencies.

  • Comparative Analysis

    The final maintenance priorities generated by AHP were compared with rankings obtained using the Pavement Condition Index. This comparison enabled the researchers to examine similarities and differences between the two approaches and evaluate whether a multi-criteria framework provides a more comprehensive basis for maintenance planning.

5. Key Findings

Road R4 Emerged as the Highest Maintenance Priority

The most notable outcome of the study is that Road R4 received the highest maintenance priority according to the AHP analysis, despite not having the lowest Pavement Condition Index (PCI). This result demonstrates that maintenance urgency cannot always be determined solely by an overall pavement condition score. Instead, the combination of different distress types and their relative engineering importance significantly influences maintenance decisions.

The AHP framework assigned greater importance to critical pavement defects such as potholes and edge failures, allowing Road R4 to receive the highest priority score. This finding illustrates how multi-criteria decision-making can reveal maintenance needs that may not be apparent when relying exclusively on traditional pavement condition indicators.

AHP Produced Different Priorities from the Conventional PCI Method

One of the study's most important findings is the noticeable difference between rankings generated by the Analytical Hierarchy Process and those obtained using the Pavement Condition Index. While several roads received similar rankings under both approaches, others experienced substantial changes in priority.

The comparison indicates that PCI primarily reflects overall pavement condition, whereas AHP evaluates multiple engineering considerations simultaneously. By incorporating several distress characteristics into the decision process, AHP provides a broader perspective on maintenance planning and resource allocation.

Multiple Pavement Distresses Improve Decision Quality

The research demonstrates that evaluating several pavement distress indicators together results in a more comprehensive assessment of maintenance requirements. Rather than treating all pavement deterioration equally, the AHP framework differentiates between distress types according to their relative importance in pavement performance and safety.

This multi-criteria approach enables transportation engineers to identify road sections that require urgent intervention even when their overall pavement condition appears acceptable. Consequently, maintenance decisions become more representative of actual engineering priorities.

The AHP Framework Demonstrated Consistent Decision Reliability

The pairwise comparison matrix satisfied the accepted consistency requirement by producing a Consistency Ratio (CR) below 0.10. This result indicates that the weighting assigned to the evaluation criteria was logically consistent and suitable for maintenance prioritization.

Consistency verification is an important feature of the AHP methodology because it provides confidence that maintenance rankings are based on coherent engineering judgments rather than arbitrary weighting decisions.

The Methodology Is Practical for Infrastructure Agencies

An important practical contribution of the study is the implementation of the AHP procedure using Microsoft Excel rather than specialized optimization software. This significantly lowers the technical barriers for government agencies and local infrastructure managers that may have limited computational resources.

Because spreadsheet software is widely available, the proposed framework offers an accessible decision-support tool that can be incorporated into routine pavement management practices without requiring substantial additional investment in software or technical infrastructure.

Combining PCI and AHP Provides a More Comprehensive Evaluation

Instead of suggesting that the Pavement Condition Index should be replaced, the study indicates that PCI and AHP can complement one another. PCI supplies an objective measurement of pavement condition, while AHP incorporates engineering judgment and multiple deterioration criteria into maintenance prioritization.

The integration of both approaches creates a more balanced decision-making framework that supports transparent resource allocation, more effective maintenance scheduling, and improved long-term pavement management, particularly for rural road networks operating under budget constraints.

6. Scientific Contribution

  • Extends the application of the Analytical Hierarchy Process (AHP) to rural road maintenance. Although AHP has been widely adopted in infrastructure management, this study demonstrates its practical application in prioritizing maintenance for rural road networks in a developing-country context, where infrastructure challenges and resource limitations differ from those of urban environments.
  • Introduces a structured multi-criteria maintenance framework. The research integrates five important pavement evaluation criteria—roughness, potholes, raveling, bleeding, and edge failure—into a single decision-making model, allowing maintenance priorities to reflect multiple engineering considerations rather than relying on a single pavement condition indicator.
  • Demonstrates the complementary use of PCI and AHP. Instead of positioning the Pavement Condition Index (PCI) and AHP as competing methods, the study illustrates how they can be combined to improve maintenance decision-making by integrating objective pavement assessment with systematic multi-criteria evaluation.
  • Provides a transparent engineering decision-support methodology. The AHP framework offers a logical sequence of pairwise comparisons, consistency evaluation, weighting, and ranking that makes maintenance decisions easier to justify and communicate to engineers, infrastructure managers, and policymakers.
  • Shows that accessible digital tools can support engineering analysis. By implementing the entire AHP procedure in Microsoft Excel, the study demonstrates that sophisticated decision-support methods can be applied without specialized optimization software, increasing practical usability in local government agencies.
  • Contributes empirical evidence from Myanmar. Research on rural pavement management in developing countries remains relatively limited. This case study enriches the existing literature by providing empirical evidence from Shan State and broadening the geographical diversity of transportation infrastructure research.

7. Industrial Implications

  • Improves maintenance planning. Transportation agencies can use the proposed framework to establish maintenance priorities based on multiple engineering criteria, helping ensure that limited budgets are allocated to road sections requiring the most urgent intervention.
  • Supports infrastructure asset management. More systematic prioritization enables infrastructure owners to optimize pavement life-cycle management by scheduling maintenance before severe deterioration results in expensive rehabilitation or reconstruction.
  • Enhances engineering decision-making. Engineers responsible for pavement management can incorporate both objective pavement condition measurements and expert engineering judgment within a single decision-support framework, improving consistency across maintenance projects.
  • Improves resource allocation. Government agencies operating under financial constraints can use the AHP methodology to justify maintenance investments transparently while maximizing the effectiveness of available funding.
  • Supports digital engineering practices. The spreadsheet-based implementation demonstrates how digital decision-support tools can be incorporated into routine infrastructure management without requiring advanced computational platforms.
  • Promotes sustainable transportation infrastructure. Earlier identification of critical pavement deterioration allows preventive maintenance to be performed before road conditions worsen, reducing long-term maintenance costs and improving network sustainability.
  • Provides a transferable framework. Although developed for rural roads in Myanmar, the methodology may also be adapted for highway maintenance, municipal road management, airport pavements, industrial access roads, and other transportation infrastructure requiring multi-criteria prioritization.
  • Supports future smart asset management systems. The AHP framework could be integrated with Geographic Information Systems (GIS), pavement management systems, and digital asset databases to strengthen infrastructure planning under Industry 4.0 and digital government initiatives.

8. Research Limitations

  • The study evaluated only ten rural roads located within Shan State, Myanmar. Although sufficient for demonstrating the methodology, broader geographical coverage would improve the generalizability of the findings.
  • The analysis focused exclusively on flexible pavements managed by a single government agency. Additional studies involving different pavement types and administrative jurisdictions would provide wider validation.
  • The maintenance prioritization considered five pavement distress criteria. Other engineering, environmental, economic, or traffic-related factors were beyond the scope of the present research.
  • Pairwise comparison weights were established within the AHP framework. Although consistency testing confirmed acceptable reliability, different expert judgments could produce alternative weighting schemes in other regions.
  • The implementation relied on manually collected pavement condition data. Future applications incorporating automated monitoring technologies may further improve data quality and decision efficiency.
  • The comparison was limited to the Pavement Condition Index (PCI). Evaluating the proposed framework alongside additional multi-criteria decision-making methods would provide a broader performance assessment.
  • Economic analysis, maintenance costs, and long-term life-cycle optimization were not explicitly incorporated into the prioritization model, leaving opportunities for more comprehensive infrastructure management studies.

9. Future Research Opportunities

  • Expand the study to larger regional and national road networks to evaluate the robustness of the AHP framework under more diverse infrastructure conditions.
  • Integrate additional decision criteria such as traffic volume, accident frequency, maintenance costs, economic importance, environmental impacts, and social accessibility into future prioritization models.
  • Compare the Analytical Hierarchy Process with other Multi-Criteria Decision-Making (MCDM) techniques, including TOPSIS, VIKOR, PROMETHEE, ELECTRE, and Best-Worst Method, to examine differences in maintenance rankings.
  • Develop hybrid decision-support systems that combine AHP with machine learning or artificial intelligence to improve predictive pavement maintenance planning.
  • Integrate Geographic Information Systems (GIS) to visualize maintenance priorities spatially and support regional infrastructure planning.
  • Incorporate real-time pavement monitoring using IoT sensors, mobile inspection technologies, and automated distress detection to enhance decision accuracy.
  • Extend the framework by incorporating pavement life-cycle cost analysis, maintenance scheduling optimization, and sustainability assessment.
  • Evaluate stakeholder perspectives by including engineers, local governments, transportation authorities, and community representatives in determining decision weights.
  • Assess the applicability of the proposed methodology to other transportation infrastructure, including urban roads, highways, airport pavements, bridges, and industrial transportation networks.
  • Develop web-based or cloud-based decision-support platforms that enable transportation agencies to perform maintenance prioritization more efficiently within digital asset management systems.

10. Potential for Public Policy Citation (Overton)

This article demonstrates a moderate to high potential for citation in public policy documents because it addresses one of the most fundamental responsibilities of transportation authorities: prioritizing road maintenance under limited financial resources. The proposed Analytical Hierarchy Process (AHP) framework provides a transparent and evidence-based methodology that supports rational infrastructure investment decisions while improving accountability in public asset management.

Government agencies responsible for rural transportation could use the findings to strengthen maintenance planning frameworks, particularly where funding is insufficient to rehabilitate all deteriorated road sections simultaneously. By integrating multiple pavement distress indicators into a structured decision-making process, the methodology supports more balanced and justifiable allocation of maintenance resources.

The research also aligns with broader objectives related to sustainable infrastructure management, efficient public expenditure, and improved transportation accessibility. Although the study does not directly evaluate government policies, its decision-support framework could serve as technical evidence for planning documents and infrastructure management guidelines.

Potential policy applications include:

  • National and regional road maintenance strategies.
  • Rural infrastructure development programs.
  • Transportation asset management guidelines.
  • Government infrastructure investment planning.
  • Sustainable transportation policies.
  • Engineering decision-support manuals.
  • Public infrastructure budgeting frameworks.
  • Digital infrastructure management initiatives.

Its relevance to formal engineering standards is somewhat more limited because the study focuses primarily on maintenance prioritization methodology rather than introducing new pavement design specifications or construction standards. Nevertheless, the framework could serve as supporting evidence for future technical guidelines that promote systematic and transparent maintenance planning.

11. Who Should Read This Paper?

  • Civil engineers specializing in pavement engineering.
  • Transportation engineers.
  • Infrastructure asset managers.
  • Road maintenance engineers.
  • Researchers in transportation infrastructure.
  • Researchers working in Multi-Criteria Decision-Making (MCDM).
  • Graduate students in civil engineering.
  • Government agencies responsible for road maintenance.
  • Local government infrastructure planners.
  • Public works departments.
  • Transportation policymakers.
  • Consultants in pavement management.
  • Infrastructure investment planners.
  • Researchers interested in sustainable transportation systems.
  • Educators teaching transportation engineering and infrastructure management.

12. Final Thoughts

This study provides a valuable contribution to transportation infrastructure management by demonstrating how the Analytical Hierarchy Process (AHP) can improve maintenance prioritization for rural road networks. Rather than relying solely on conventional pavement condition assessments, the authors present a structured decision-making framework that evaluates multiple pavement distress indicators simultaneously, allowing maintenance priorities to reflect broader engineering considerations.

One of the principal strengths of the research is its practical orientation. The proposed methodology is implemented using an Excel-based decision-support tool, making it accessible to infrastructure agencies without requiring specialized optimization software. This practical implementation enhances the potential for adoption by local governments, particularly in developing countries where technical and financial resources may be limited.

The comparison between the Pavement Condition Index (PCI) and AHP further demonstrates that maintenance decisions may change considerably when multiple engineering criteria are evaluated simultaneously. Rather than replacing conventional pavement assessment methods, the study shows that combining objective pavement evaluation with structured multi-criteria decision-making can produce more comprehensive maintenance strategies.

Although the research focuses on a relatively small number of rural roads within a single region, its methodological contribution extends beyond the specific case study. The proposed framework offers a transparent, replicable, and adaptable approach that may support more effective infrastructure planning in other regions facing similar maintenance challenges. Overall, this article represents a meaningful contribution to pavement management research and provides practical guidance for engineers and decision-makers seeking more systematic approaches to infrastructure maintenance prioritization.

Suggested Citation

UNP–Teknomekanik Style

Tun, N., Kyaing, & Aye, M. T. T. (2024). An Analytical Hierarchy Process (AHP) Approach to Road Maintenance Prioritization: A Case Study in Shan State, Myanmar. Innovation in Engineering, 1(2), 60–72. DOI: https://doi.org/10.58712/ie.v1i2.9

APA (7th Edition)

Tun, N., Kyaing, & Aye, M. T. T. (2024). An Analytical Hierarchy Process (AHP) approach to road maintenance prioritization: A case study in Shan State, Myanmar. Innovation in Engineering, 1(2), 60–72. https://doi.org/10.58712/ie.v1i2.9

IEEE Style

N. Tun, Kyaing, and M. T. T. Aye, "An Analytical Hierarchy Process (AHP) Approach to Road Maintenance Prioritization: A Case Study in Shan State, Myanmar," Innovation in Engineering, vol. 1, no. 2, pp. 60–72, 2024, doi: 10.58712/ie.v1i2.9.

Harvard Style

Tun, N., Kyaing and Aye, M.T.T., 2024. An Analytical Hierarchy Process (AHP) Approach to Road Maintenance Prioritization: A Case Study in Shan State, Myanmar. Innovation in Engineering, 1(2), pp.60–72. Available at: https://doi.org/10.58712/ie.v1i2.9.

Vancouver Style

Tun N, Kyaing, Aye MTT. An Analytical Hierarchy Process (AHP) Approach to Road Maintenance Prioritization: A Case Study in Shan State, Myanmar. Innovation in Engineering. 2024;1(2):60–72. Available from: https://doi.org/10.58712/ie.v1i2.9

Chicago (Author–Date)

Tun, Nandar, Kyaing, and Moe Thet Thet Aye. 2024. "An Analytical Hierarchy Process (AHP) Approach to Road Maintenance Prioritization: A Case Study in Shan State, Myanmar." Innovation in Engineering 1 (2): 60–72. https://doi.org/10.58712/ie.v1i2.9.

MLA (9th Edition)

Tun, Nandar, Kyaing, and Moe Thet Thet Aye. "An Analytical Hierarchy Process (AHP) Approach to Road Maintenance Prioritization: A Case Study in Shan State, Myanmar." Innovation in Engineering, vol. 1, no. 2, 2024, pp. 60–72. https://doi.org/10.58712/ie.v1i2.9.

Editorial Note

Editorial Note: This blog post is an independent scholarly review intended for educational and scientific communication purposes. It summarizes and discusses the published article in the author's own words while providing full attribution to the original publication, consistent with the principles of the Creative Commons Attribution 4.0 International (CC BY 4.0) license.

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A comprehensive scholarly review of an AHP-based approach for rural road maintenance prioritization in Myanmar. Explore the methodology, key findings, engineering contributions, industrial implications, policy relevance, and future research opportunities.

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