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The Usability of Transport Network Vehicle Service Apps Amidst the Pandemic in the Philippines: A Comparison of the Convenient Usage of Grab, Angkas, and JoyRide

Published:22 August 2023Publication History

ABSTRACT

Due to the high demand for transportation in the Philippines, commuters use Transport Network Vehicle Service (TNVS) apps, which are “ride-sharing” or “app-based ride-hailing services”, as an option to travel from one point to another. This paper aims to assess the usability of three TNVS apps available in the Philippines: Grab, Angkas, and JoyRide, using the System Usability Scale (SUS) and satisfaction rating with the criteria: functionality, accessibility, design, content, and organization. Slovin's formula was employed to obtain the minimum number of respondents. In addition, ANOVA was utilized to determine the significant difference among the three apps and Tukey's test to determine the substantially distinct app. The results revealed that Grab outperformed Angkas and JoyRide based on the analysis and post-hoc tests conducted on the system usability scale scores and satisfaction rating categories: functionality, design, and content. Therefore, the results concluded that Grab was the most usable app for transportation, followed by Angkas and JoyRide as the least usable for transportation. With these and the other significant variables analyzed in the research, the overall result may be of great help in providing insights to Grab on how they are performing in the Philippine market and on what factors they should concentrate on improving their influence in terms of mobile technology and services. The researchers recommend that an increase in respondents who have experienced riding all TNVS apps, a different research setting, and another set of TNVS apps be used for further research, as these could give light to various perspectives and more accurate results.

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    • Published in

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      MSIE '23: Proceedings of the 2023 5th International Conference on Management Science and Industrial Engineering
      April 2023
      375 pages
      ISBN:9798400708381
      DOI:10.1145/3603955

      Copyright © 2023 ACM

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      Publication History

      • Published: 22 August 2023

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