Analysing heterogeneity in factors affecting adoption of ride-hailing services: a stepwise LCCA-MCDM modelling approach

被引:0
|
作者
Bhaduri, Eeshan [1 ]
Pal, Shagufta [2 ]
Goswami, Arkopal Kishore [3 ]
机构
[1] Univ Leeds, Inst Transport Studies, Leeds LS2 9JT, England
[2] Indian Inst Engn Sci & Technol Shibpur, Dept Architecture Town & Reg Planning, Howrah 711103, India
[3] Indian Inst Technol Kharagpur, Ranbir & Chitra Gupta Sch Infrastructure Design &, Kharagpur 721302, West Bengal, India
关键词
Ride-hailing services (RHS); Latent class cluster analysis (LCCA); Multi criteria decision making (MCDM); Prioritization; Motivators; Deterrents; CLASS CLUSTER-ANALYSIS; BUILT ENVIRONMENT; SPATIAL VARIATION; TRAVEL BEHAVIOR; SHARED MOBILITY; UBER; ATTITUDES; SATISFACTION; INSTRUMENT; PERCEPTION;
D O I
10.1007/s11116-024-10563-9
中图分类号
TU [建筑科学];
学科分类号
0813 ;
摘要
The study investigates the latent heterogeneity in travel behaviour among urban travellers, including ride-hailing service (RHS) users and non-users, by incorporating attitudes so as to reinforce conventional user-segmentation approaches. Simultaneously, prioritisation of ride-hailing specific attributes was carried out to assess how RHS will operate in a sustainable way. The study initially examines latent heterogeneity in travellers through a Latent Class Cluster Analysis (LCCA) model. Subsequently, it prioritises key RHS-specific attributes for each cluster using three established Multi Criteria Decision Making (MCDM) techniques. Three clusters were identified based on individuals' attitudes and covariates (socio-demographics, travel habits, and built environment attributes). The largest cluster is the Tech-savvy ride-hailing-ready individuals (48%) with higher technological literacy, showing maximum acceptance towards ride-hailing. The second largest cluster comprises the Traditional active-mobility individuals (28%) who display the least proclivity towards RHS, probably due to their technological inhibition coupled with greater attachment to traditional travel alternatives. Lastly, the PV-loving multimodal individuals (24%) are primarily vehicle owners but prefer RHS for occasional trips. The final ranking obtained from the analysis has revealed that travel time, reliability, and flexibility are the motivators, while travel cost and waiting time are the deterrents, as perceived by the users, that influence RHS in the Indian context.
引用
收藏
页数:40
相关论文
共 2 条
  • [1] Examining factors influencing the adoption of solo, pooling and autonomous ride-hailing services in Australia
    Irannezhad, Elnaz
    Mahadevan, Renuka
    TRANSPORTATION RESEARCH PART C-EMERGING TECHNOLOGIES, 2022, 136
  • [2] FACTORS AFFECTING INTENTION TO USE FOOD ORDER-DELIVERY FEATURE OF RIDE-HAILING APPLICATIONS: THE UTAUT APPROACH
    Surya, Ade Permata
    Sukresna, I. Made
    Mardiyono, Aris
    INTERNATIONAL JOURNAL OF BUSINESS AND SOCIETY, 2021, 22 (03): : 1363 - 1383