반복영역 건너뛰기
지역메뉴 바로가기
주메뉴 바로가기
본문 바로가기

연구정보

[IT] Predicting Parking Availability in Singapore with Cross-Domain Data: A New Dataset and A Data-Driven Approach

싱가포르 국외연구자료 연구보고서 - ResearchGate 발간일 : 2024-05-01 등록일 : 2024-06-05 원문링크

This research invests the impact of ride-hailing driver behavior on the operational performance of drivers in Indonesia. Previous research in Texas, America (Idug, 2023) objectively research the preexisting impacts of a ride-hailing driver's operational performance. The research showed that there is a significant impact of the driver’s intention to comply with rules to the rating, acceptance rate and declination rate of the drivers. However, based on this study, further research is required in Indonesia to determine if the same variables are also significant to the driver understanding of a companies’ guideline of operation and their intentions to comply with the company’s rule thorugh a random sampling of 302 respondents. General deterrence theory, understanding resource vulnerability of information, protection motivation and intention to comply do not affect the rating, indicating bias in ratings, drivers acceptance affected by intention to comply and significant influence between protection motivation and cancellation rate, despite the drivers have an understanding of data vulnerabilities, fear of penalties and motivated to protect themselves it has no effect on how many orders they complete, Drivers tend to cancel the order to protect themselves. The result of this research have some unique findings on the ride-hailing operation dynamics in Indonesia, the relationship between drivers, rider, and system through ride-hailing platforms that have much insight for ride-hailing company management to be applied for performance improvement.

본 페이지에 등재된 자료는 운영기관(KIEP)EMERiCs의 공식적인 입장을 대변하고 있지 않습니다.

목록