Exploring Uber Taxi Application Using the Technology Acceptance Model

Abstract

The goal of this study was to investigate the accountability of the technology acceptance model (TAM) for Uber taxi applications. As antecedents of usefulness, this study selected three elements: time information, price information, and driver information. Data was collected using a survey on Amazon Mechanical Turk. The survey participants were users of the Uber taxi application. The number of valid observations for the data analysis was 412. For data analysis, frequency analysis, confirmatory factor analysis, correlation matrix, and structural equation modeling were utilized. The results show that the usefulness is significantly influenced by time and driver information. They further indicate that ease of use positively affects both usefulness and attitude. In addition, usefulness significantly determines attitude, and attitude toward the Uber taxi application exerts a substantial effect on intention to use. This study contributes to the literature by demonstrating the explanatory power of TAM using the Uber taxi application as a research subject.

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