Developing Criteria for Priority Ranking of Bridges Construction: A Case Study of Bagmati Province, Nepal
Year: 2025
Type: article
Abstract: Prioritizing the implementation of projects is seen as being of great importance after the institutionalization of federalism. Federal, provincial, and local governments execute infrastructure development in their jurisdiction. This study identifies criteria for federal, provincial, and local governments to select bridges based on the prevalent practice of multi-criteria prioritization on the bridge sector at the national and international levels and discussions with officials from organizations like DOR and LRBP. Sub-criteria are developed using secondary data on traffic, population, cost of the bridge, and all-weather road length, as well as multi-criteria analysis techniques like linear value function, series of verbal pairwise assessments, and direct rating. AHP analysis assigned weights to criteria with input from 12 professionals, including elected representatives and experts in the bridge sector. Three criteria for the federal level, five for the province level, and four for the local level are identified. Among the three criteria for the federal level, the strategic importance of road weighs 58.1%, AADT weighs 28.4%, and project readiness weighs 13.5%. For the province-level matrix, strategic road importance weighs 34.3%, access to socio-economic activities weighs 22.9%, all-weathered road length weighs 16.6%, present traffic volume weighs 14.9%, and per capita investment weighs 11.3 %. Local-level criteria highlighted the most significant road closure duration (34%). While additional criteria were suggested, they were not measurable due to data limitations. The matrix developed from this study provides a valuable reference for bridge project prioritization and can guide public authorities in making more effective decisions.
Authors: Suraj Hari Adhikari, Vishnu Prasad Shrestha, Anil Marsani
Institutions: Institute of Engineering, Pulchowk Campus, World Bank
Language: English
Field: Decision Sciences
Domain: Social Sciences
Open Access status: hybrid
OpenAlex ID: W4411090596