Multi-criteria analysis and network analysis for walkability score in Amphoe Muang, Nonthaburi, Thailand

Abstract

Aim: This study aims to improve Amphoe Mueang and Nonthaburi’s quality of life by identifying the best path forward by examining geographical factors.
Method: The Multi-Criteria Analysis (MCA) used to calculate the walk score is a helpful instrument for examining geographical factors that impact people’s social and economic well-being. Network analysis and the Analytic Hierarchy Process (AHP) form the basis of the walkability score. Two groups of nine factors were used. Before anything else, we look at two aspects of connectivity: 1) betweenness and 2) centrality. Second, factors close to the facility include 1) retail. Seven categories are considered: 2) public transportation, 3) landmarks, 4) recreation, 5) the workplace, 6) the home, and 7) security.
Findings: Findings indicated that the east side of the study area contained the majority of the highest scores. As a result of the need for private automobiles rather than walking and purpose to residents only, the low walkability score is located opposite the high score. One method of recognising people who walk around cities is the Walkability Score derived from network analysis. Correct, analyse, score, and prioritise factors with MCA’s efficient tools. It can normalise Factor 1 by adding a good factor or removing a bad factor. The disparity in importance demonstrates that society needs to take the path down which its members can find happiness, ease their minds, and engage in more physical activity. That way, they can keep their work, food, and sleep all in one place.
Implications/Novel Contribution: Apartment-seekers and business patrons alike can benefit from the walkability score results by making decisions based on the relative attractiveness of walkable neighbourhoods and the costs of various living arrangements.