Impact of Digital Economy on Tax Administration Performance:

Abstract

The role of tax administration has undergone significant changes in recent years, primarily driven by the rapid development and implementation of new technologies. However, the effectiveness of digitalization in addressing the challenges faced by tax administrations is not solely dependent on technological advancements. Each tax administration needs to navigate the complexities of digitalization based on its unique context, needs, and priorities. Nonetheless, learning from the experiences of other tax administrations can greatly enhance the success of a country's digital transformation journey. In Tanzania, despite the increasing integration of digital platforms and technology in tax administration, there is a lack of comprehensive understanding regarding the current state and specific impact of the digital economy on tax administration performance. This knowledge gap hampers the ability of policymakers and tax authorities to harness the potential benefits of the digital economy in optimizing tax collection, enhancing compliance levels, and improving operational efficiency. Therefore, this study aims to investigate and evaluate the current situation of the digital economy in Tanzania and its impact on tax administration. The research will focus on the Njombe Region as a case study, exploring the influence of the digital economy on tax collection performance, tax compliance levels, and operational efficiency. The study will adopt the Technology Acceptance Model (TAM) and Efficiency Theory as the theoretical frameworks to analyze the impact of the digital economy on tax administration in Tanzania. The research approach will be quantitative, employing a descriptive research design with correlation analysis. The target population will include tax authorities, taxpayers, and tax administration officials within the Njombe Region, and purposive sampling techniques will be used to select participants with specific expertise relevant to the study objectives. Data analysis will involve descriptive statistics and inferential analysis using statistical software such as SPSS.