Development of an Online Tax Calculation Web Application and Determinants of User Satisfaction

Abstract

      This research, titled “Development of an Online Tax Calculation Web Application and Determinants of User Satisfaction” aimed to 1) design and develop   a web application for an online tax calculation system in accordance with the regulations of the Revenue Department, 2) evaluate the efficiency of the web application by information system experts, 3) examine the level of satisfaction among online entrepreneurs toward the use of the web application and 4) investigate the information system quality factors influencing user satisfaction.
      This study employed a research and development approach by developing the system in the form of a web application based on the Software Development Life Cycle (SDLC). The study also analyzed factors influencing user satisfaction through both qualitative and quantitative data collection methods, including in-depth interviews with tax experts, system efficiency evaluation by information system experts, and user satisfaction assessment from online entrepreneurs. The statistical methods used for data analysis included percentage, mean, standard deviation, and multiple regression analysis.
     The results indicated that: 1) the developed web application for the online tax calculation system was able to accurately calculate taxes in accordance with the Revenue Department’s regulations, 2) the system efficiency evaluation by information system experts was at a very high level (M = 4.58), indicating that the system was accurate and performed effectively according to its functional requirements, 3) online entrepreneurs reported a very high level of satisfaction with the web application (M = 4.65), with adaptability and ease of use receiving the highest mean scores (M = 4.69), and 4) multiple regression analysis revealed that five information system quality factors information accessibility, security, collaboration support, adaptability, and ease of use had a significant positive influence on user satisfaction (p < .001). The model demonstrated a moderate level of explanatory power (R² = 0.243).