An application of Multi-Attribute Utility Theory (MAUT) to the prioritization of rural roads to improve rural accessibility in Nigeria

Akpan, Uduak; Morimoto, Risa

Abstract

Good quality rural road infrastructure seems to contribute substantially to improvements in several socio-economic indicators in rural areas: increases accessibility to markets, educational and health facilities, and stimulates economic activities. However, several millions of people in sub-Saharan Africa do not live in proximity to an all-season road. A robust process of prioritizing roads for upgrade is needed to ensure efficient allocation of scarce resources in a manner that will maximize accessibility to key social amenities and economic opportunities. This study uses Multi-Attribute Utility Theory (MAUT) to examine how rural roads in Akwa Ibom State, Nigeria may be prioritized for upgrade to maximize access to key socio-economic facilities. In our analysis, the rural roads to be prioritized are the alternatives while the decision criteria are: social, economic, demographic, financial, and political. The MAUT is preferred to the commonly-used Analytic Hierarchy Process (AHP) because the number of alternatives is large. Geographic information system (GIS) techniques are applied to process some of the data used in the performance matrix of the MAUT. We specify non-linear marginal utility functions for the criteria. Scenario analyses are also carried out to examine the impact of changes in the weights of the criteria on the utility score of each alternative. The study identifies 10 roads that will yield the highest socio-economic benefits and promote rural accessibility. Finally, the study recommends that decision-makers adopt a similar approach in selecting rural roads for upgrade, instead of selecting roads based on political considerations.

Citation

Akpan, U., & Morimoto, R. (2022). An application of Multi-Attribute Utility Theory (MAUT) to the prioritization of rural roads to improve rural accessibility in Nigeria. Socio-Economic Planning Sciences: The International Journal of Public Sector Decision-Making, 82(B), Article 101256. https://doi.org/10.1016/j.seps.2022.101256

• Journal Article Type: Article
• Acceptance Date: Jan 30, 2022
• Online Publication Date: Jun 13, 2022
• Publication Date: Aug 1, 2022
• Deposit Date: Feb 7, 2022
• Publicly Available Date: Jun 27, 2022
• Print ISSN: 0038-0121
• Electronic ISSN: 1873-6041
• Publisher: Elsevier
• Peer Reviewed: Peer Reviewed
• Volume: 82
• Issue: B
• Article Number: 101256
• DOI: https://doi.org/10.1016/j.seps.2022.101256
• Publisher URL: https://www.sciencedirect.com/science/article/pii/S0038012122000349