Prototype using demonstration data. Final scores will be replaced by computed RAI-Next results.

Methodology

A road-network distance-based index beyond roads

RAI-Next measures rural accessibility by combining service reachability across nine dimensions with transparent open-data inputs and placeholder BWM-derived weights.

What is RAI-Next?

RAI-Next is a global, open-data, rural accessibility index designed to look beyond whether a rural settlement is near a road. It asks what essential opportunities can actually be reached through the road network.

The prototype normalizes dimension scores to a 0-100 scale, weights them, and aggregates them into a composite score:

RAI-Next = sum of dimension weight x dimension score

Current method

Road-network distance-based accessibility index using rural population-weighted scores and BWM-derived dimension weights.

Nine dimensions

Health Services

13.3%

Access to clinics, hospitals, pharmacies, and primary care points.

Education

12.3%

Reachability of schools and other educational services.

Administrative Services

9.5%

Access to public offices and core administrative support.

Basic Consumer Needs

12.0%

Availability of markets, shops, and everyday essentials.

Transportation

13.8%

Road-network access to mobility infrastructure and corridors.

Public Transportation

13.6%

Access to bus, rail, and shared public transport nodes.

Digital Connectivity

10.2%

Proxy access to connectivity and digital service readiness.

Social and Religious Facilities

8.6%

Access to social, cultural, and religious facilities.

Financial and ATM Services

9.1%

Access to banks, ATMs, and basic financial services.

Open-data approach

  • Service locations and roads can be sourced from OpenStreetMap and national open-data portals.
  • Rural population-weighted scoring gives greater influence to places where rural residents live.
  • CSV and JSON files keep the prototype transparent and replaceable.

Limitations

  • Prototype uses demonstration data only.
  • OSM completeness varies between countries.
  • Country-level comparability depends on consistent source coverage.
  • Digital connectivity data gaps may affect rural interpretation.
  • A future version may use travel time instead of road-network distance.