• Journal of Korean Society of Transportation
• /
• v.31 no.5
• /
• pp.79-88
• /
• 2013

Recently, due to THE MOBILITY ENHANCEMENT FOR THE MOBILITY IMPAIRED ACT, local governments have tired to make various efforts on special transport services(STS), low-flow bus, and installing elevator in subway stations for handicapped people. But in case of STS, insufficient numbers of taxi are raised against the increasing demand of hadicapped people due to the limited budget. This study investigated actual use condition of STS and characteristics of selection of handicapped people on Duribal. In addition, an ordered-logistic model was employed for developing taxi use prediction model considering taxi fare discounts for diverting Duribal demands to taxies. The results can be a significant basic data for transportation policies to improve travel efficiency of the handicapped.

• The Journal of Information Systems
• /
• v.32 no.2
• /
• pp.137-152
• /
• 2023

Purpose The purpose of this study is to analyze big data related to DURIBAL from the operation of taxis reserved for the disabled to identify the issues and suggest solutions. ESG management should be translated into "environmental factors, social responsibilities, and transparent management." Therefore, the current study used Big Data analysis to analyze the factors affecting the standby of taxis reserved for the disabled and relevant problems for implications on convenience of social weak. Design/methodology/approach The analysis method used R, Excel, Power BI, QGIS, and SPSS. We proposed several suggestions included problems with managing cancellation data, minimization of dark data, needs to develop an integrated database for scattered data, and system upgrades for additional analysis. Findings The results showed that the total duration of standby was 34 minutes 29 seconds. The reasons for cancellation data were mostly use of other modes of transportation or delayed arrival. The study suggests development of an integrated database for scattered data. Finally, follow-up studies may discuss government-initiated big data analysis to comparatively analyze the use of taxis reserved for the disabled nationwide for new social value.