Paul E. Shao

Work place: The Nelson Mandela African Institution of Science and Technology, P. O. Box 447, Arusha, Tanzania

E-mail: shaopaultz@gmail.com

Website:

Research Interests: Computational Engineering, Engineering

Biography

Paul E. Shao received his BSc in Com-puter Science from the St. Augustine University of Tanzania, Tanzania, in 2011. Currently, he is at the Nelson Mandela African Institution of Science and Technology (NM-AIST) pursuing Master’s Degree in Information and Communications Science and Engineer-ing (ICSE). Currently he is working with Mwenge Catholic University in Kilimanjaro, Tanzania as a lecturer. He has experience in systems development and net-working. His research interests include system development, tracking systems, and mobile application development.

Author Articles
Embedding Stock Tracking Module into Elec-tronic Fiscal Device Machine and its Manage-ment System to Reduce Tax Evasion: A case of Tanzania

By Paul E. Shao Mussa Ally Dida

DOI: https://doi.org/10.5815/ijieeb.2019.05.04, Pub. Date: 8 Sep. 2019

The Electronic Fiscal Device (EFD) Machines have been operating in Tanzania since the year 2010 for the purpose of helping the Tanzania Revenue Authority (TRA) to increase revenues from tax collection. Regard-less of years of its existence, there are still reported cases of tax evasion, and this study was conducted to review the current tax collection system and analyze require-ments for the development of Stock Tracking Module (STM) to be embedded in the current tax collection sys-tem. This paper earmarked some problems relating to Electronic Fiscal Device Machine Management System (EFDMS) and EFD machine. Data collection was done in Kilimanjaro and Arusha, the two regions of Tanzania that involved tax officers and Information Technology (IT) personnel from TRA and drug traders. Data collection process involved both qualitative and quantitative methods to gather data for the development of the system Stock Tracking Module (STM) such as interview, questionnaire, role-playing and observation. The major findings of the study: The efficiency of the EFDMS is at average, thus, need some improvements. The major problems encountered by TRA are; under declaration of sales by traders, non-usage of EFD machines, usage of fake EFD, overestimate of expenses, division of business and conducting business in unknown areas. The proposed solution will reduce the existing challenges and increase revenue collections, reduce manual work and human resource, and improve accuracy on tax estimation process.

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