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Research Study on the Satisfaction Level of Uber Users with Respect to Ahmedabad City Deep P, Baraiya; Rajapara, Monil; Sinh Zala, Harshvadhan; Patel, Kavya; Chauhan, Rahul; Maseleno, Andino; Rizal Isnanto, R
Greenation International Journal of Tourism and Management Vol. 1 No. 4 (2023): (GIJTM) Greenation International Journal of Tourism and Management (December 20
Publisher : Greenation Research & Yayasan Global Resarch National

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.38035/gijtm.v1i4.254

Abstract

This study investigates user satisfaction among Uber users in Ahmedabad, India, focusing on key factors such as digital media consumption, the impact of the COVID-19 pandemic on household income, spending priorities, binge-watching habits, and perceptions of work-life balance. Using ANOVA analysis, significant differences were found in users' feelings of being overwhelmed by work and personal responsibilities, while other factors showed uniformity across demographic groups. These findings highlight the influence of socioeconomic factors on digital life balance, emphasizing the need for tailored strategies to enhance user satisfaction. By contributing to the understanding of the sharing economy's impact on urban mobility, this research provides valuable insights for improving user experiences in similar contexts. Future studies should consider longitudinal trends and cross-cultural comparisons to further enrich this evolving field.
Development of a Web-Based Electronic Data Capture Monitoring System Using the PIECES and Waterfall Models Iskandar, Akbar; Aji Bimantara, Vitara; Kamaruddin, Kamaruddin; Kherani, Riska; Patel, Kavya; Amiruddin, Erwin Gatot; Sobirov, Bobur
Jurnal Abdimas Cendekiawan Indonesia Vol. 2 No. 3 (2025): September
Publisher : Yayasan Cendekiawan Digital Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56134/jaci.v2i3.148

Abstract

The development of digital transactions has driven the need for more accurate and easily monitored Electronic Data Capture (EDC) devices to support payment processes in the retail and distribution sectors. However, the manual and unintegrated EDC monitoring mechanism leads to data inconsistencies, delays in operational information, and low device traceability throughout its lifecycle. This research develops a real-time, web-based EDC population monitoring system to improve device management efficiency and operational data quality. The needs analysis was conducted using the PIECES framework, while the development process adopted the Waterfall model, encompassing analysis, design, implementation, and testing. The resulting system supports device registration, distribution monitoring, activation tracking, mutation recording, and device closure. Test results show significant improvements in data accuracy, reporting speed, and monitoring process effectiveness compared to manual methods. These findings contribute to the literature on enterprise digital asset management and demonstrate that a structured development approach can optimize the EDC device monitoring process in large-scale retail networks.