Travel behaviour regression modeling of urban housewives in the great metropolitan Bandung area

Abstract

Abstract The Millennial Situation and Condition are now changing the lifestyles of the urban societies, especially for women. It is also changing their travel behaviour to do their daily activities to meet their family needs. Including in The Great Metropolitan Bandung Area, the urban women have high demand for their daily journey and tend to increase. By the theme of Gender Mainstream philosophy, urban women have the freedom to get their accessibilities of going anywhere with their own transportation modes, including non-working urban women or as housewives in the region of Bandung. As WRI (2015) said that was more than 50% of women’s mobility have a complex daily trip to meet their needs by doing their daily activities. It was done to meet the needs of family and home care in the terms of rising family’s welfare. While less than 60% of men’s travel behaviour have a simple trip. This kind of condition is very interesting to be analysed, especially in The Great Metropolitan Bandung Area. This study explains how complex the daily travel behaviour of non-working urban women and as housewives with activities based approach that were done outdoor in a week. The quantitative data that is performed by socioeconomic and household demographic variables serve as the basis to measure the independent variables affecting family welfare, as well as the type, time, and duration of each daily activities and daily traveling data of non-working urban women. Using Clustering Methods approach to describe the width of research area, we could find the differences of models by Regression Analysis. So, we have 3 kinds of Regression Models to figure out the each of cluster from 3 Clusters that we find by Clustering Method in The Great Metropolitan Bandung Area. The result of this study could be used to make a change of city transportation policy and also to analyse the economic potential area by the models for the government officers and the business owner to increase their profit. By the regression models result, it could be used to estimate many variables ini the future to increase the economic growth of the City from the transportation by user’s perspective.