The Philippine government is taking advantage of the advancement of digital technology to bring and provide an accessible, sustainable, and broader version of its service and connection to its citizens by adapting digitalization and launching a mobile app called eGov PH. This application integrates with multiple sectors of the government, providing a sustainable and convenient way to conduct transactions between government agencies and citizens. This study aimed to investigate and assess the various factors that affect the accessibility of the eGov PH mobile app from the citizens’ viewpoint via an online questionnaire. A comprehensive 64-item research questionnaire was constructed and answered by 320 respondents. This study determined the key factors that influence the accessibility of the application, which will be assessed to improve the service efficiency of the mobile application. The technology acceptance model was used to correlate perceived ease of use and perceived usefulness to attitude toward using. Structural equation modeling (SEM) results revealed a noteworthy correlation between awareness of service and technology readiness and perceived ease of use. Furthermore, perceived ease of use was shown to have an insignificant direct relationship with perceived usefulness and the attitude toward using the eGov mobile application. These findings offer valuable insights into critical factors influencing the accessibility of the eGov app, contributing to enhanced sustainability and overall service efficiency. The identified model constructs from this study can serve as informative guidelines for researchers and various sectors exploring user-software interactions in relevant government applications.

In our increasingly digital world, grasping consumer preferences for internet service providers (ISPs) is paramount. This study was conducted in Occidental Mindoro, Luzon, the Philippines, and surveyed 280 respondents across ten municipalities with 81 in-person and online questionnaires. The research focused on twelve latent variables: internet speed, assurance, tangibility, responsiveness, reliability, empathy, data privacy, service quality, value-added services, price, customer satisfaction, and customer loyalty. Methods such as Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS), Structural Equation Modeling (SEM), and an Artificial Neural Network (ANN) were integrated for the analysis. The study utilized TOPSIS to rank ISPs based on Service Quality (SERVQUAL) parameters, followed by SEM to delve into variable connections affecting preferences, and through as ANN, consumer behavior and loyalty were predicted. The SEM–ANN results revealed that assurance, responsiveness, empathy, and data privacy directly impacted service quality. Moreover, a significant correlation was found between customer satisfaction and service quality, influencing further customer loyalty alongside pricing. By integrating these methodologies, the study provides a comprehensive understanding of ISP preferences and emphasizes service quality as the most significant factor in industry decision-making.