Patterns of ride sourcing adoption among age groups in three metropolitan cities of Indonesia

Abstract

This paper aims to investigate the pattern of ride sourcing adoption among different age groups in Indonesia, represented by the three metropolitan regions. Using descriptive analysis and multivariate analysis (Principal Component Analysis), two distinct models were segmented according to age (under 25-year-old and over 25-year-old) and their characteristics that influence ride sourcing adoption were explored. The paper found some interesting patterns. Firstly, the average users of ride sourcing-based goods movement services are women under 25 years old, are college students, live in rented/boarding houses, have a high school degree or equivalent level of education, have 3 to 4 family members, on average have 2 cars and 1 motorcycle per family, have better access to shopping center facilities, educational facilities, restaurant, pharmacies or drug stores, main roads, medical facilities, pedestrian and cyclist facilities, and green open spaces, have a high time allocation for online activities or work/study, and have a high frequency of use of services for the food category before the pandemic. Secondly, comparing both age groups, 4 (four) types of ride sourcing services were formed among the groups in different ways, i.e., parcels; medicine and groceries; non-food; inner-city package and food service grouping were formed among the “under 25 years age” users; while the “above 25 years age” were grouping into users of medicines, groceries, non-food; inner-city parcels and out of the city packages; big parcels and out of the city letters; and foods. Thirdly, in both age group, the services of ride sourcing adoption were significantly correlated with socio-demographic factors like gender, employment status, income level, and ownership of a vehicle. Fourth, in both age group, the services were also positively and significantly impacted by increased time allocated for work and study, outside socializing, and online shopping. In contrast, a greater allocation of out-of-home maintenance had a negative effect. Fifth, in both age group, the services were significantly correlated with the different characteristics of the built environment. However, there were different pattern as well among the two groups such as for those over the age of 25, an increase in income will also result in an increase in service usage across all the services and the usage were in line with the high intensity of work/study from home. On the other hand, the under 25 age group tended to use all services more frequently if they spend more time for work or study.