Ride or Not to Ride: Does the Customer Deviate toward Ridesharing?

Area of Science:

• Technology adoption
• Transportation services
• Human-computer interaction

Background:

• E-hailing applications (EHAs) have transformed traditional taxi services globally, driven by smartphone proliferation.
• Despite widespread adoption, users encounter challenges, and research on influencing factors for EHA adoption remains limited.
• Understanding customer intention is crucial for improving EHA design and acceptance.

Purpose of the Study:

• To empirically investigate the factors influencing customer intentions towards e-hailing applications (EHAs).
• To extend the Technology Acceptance Model (TAM) with relevant external factors for EHA adoption.
• To provide insights for developing better guidelines for EHA developers and designers.

Main Methods:

• An extended Technology Acceptance Model (TAM) was employed, incorporating perceived mobility value, effort expectancy, perceived locational accuracy, and perceived price.
• Data was collected through a questionnaire survey administered to 211 users of e-hailing applications.
• Structural Equation Modeling (SEM) was utilized for data analysis.

Main Results:

• Perceived usefulness, perceived price, and perceived ease of use were found to significantly affect the behavioral intention to use EHAs.
• Effort expectancy, perceived locational accuracy, and perceived mobility were identified as key determinants of perceived ease of use.
• The study highlights the interplay between user expectations and the perceived attributes of EHAs.

Conclusions:

• The findings confirm the importance of perceived usefulness, price, and ease of use in driving EHA adoption.
• Effort expectancy, locational accuracy, and mobility perceptions are critical for enhancing the perceived ease of use of EHAs.
• This research offers a foundation for creating more effective and user-centric e-hailing platforms.