Abstract

Based on the United Nations (UN), the 9th Sustainable Development Goal is to build resilient infrastructure, promote inclusive and sustainable industrialization, and foster innovation. They have defined eight targets and 12 indicators for this SDG. Based on the UN SDG Framework, Target 9.1 focuses on the development of quality reliable, sustainable, and resilient infrastructure, including regional and transborder infrastructure to support economic development and human well-being, with a focus on affordable and equitable access for all. The indicator 9.1.1 was described as the proportion of the rural population who live within 2 km of an all-season road. All-season road is defined as a road that is motorable/passable all year round by the prevailing means of rural transport and is not likely to be inaccessible for seven days or more each year. Being said, the Rural Access Index (RAI), developed by the World Bank in 2006, is one of the most used methodologies and an important global development indicator for measuring people’s transport accessibility in rural areas where the majority of the deprived individuals live. This index measures the proportion of the rural population who lived within 2 km of an all-season road meeting the requirement of the SDG indicator 9.1.1. Although the RAI is one of the most utilized policy indicators for identifying rural accessibility, however, this indicator focuses only on the mobility and proximity of the rural population to nearby roads, while overlooking the need to consider other key indicators such as the closeness of households to a critical facility. These critical facilities are defined as the primary physical structures, technical facilities, and systems that are socially, economically, or operationally important to the functioning of a community. With the ongoing implementation of the Community-Based Monitoring System (CBMS) spearheaded by the Philippine Statistics Authority (PSA), a proposed methodology to measure RAI can be developed by integrating critical facilities such as health, educational, and service facilities in the computation of RAI. Additionally, existing government projects were also collected during the operations, which can be utilized to predict potential changes to the RAI if new roads or infrastructure are constructed within the community. The primary motivation of this study is to develop a new integrated RAI (iRAI) methodology by incorporating the collected critical facilities from the CBMS operations such as health centers, hospitals, schools, public markets, and evacuation centers to be able to determine further those households that are living in deprived areas if they have sufficient and/or immediate access to these infrastructures/services. This study would also be essential and the basis of the local government units (LGUs) in planning and/or identifying what programs, services, or infrastructure they could develop to increase the accessibility and condition of those communities with the least computed iRAI.