Evaluating the effectiveness of vehicle tracking systems in reducing road traffic accidents: A case study of the Tanzania Police Traffic Headquarters in Dar es Salaam

Salumu Jumanne; Mzomwe Y. Mazana; Yustina A.  Liana

doi:10.51867/ajernet.7.4.43

Authors

Salumu Jumanne College of Business Education, Tanzania
Mzomwe Y. Mazana College of Business Education, Tanzania https://orcid.org/0000-0001-7350-7011
Yustina A. Liana College of Business Education, Tanzania https://orcid.org/0000-0003-1687-0492

DOI:

https://doi.org/10.51867/ajernet.7.4.43

Keywords:

Operational Performance, Perceived Usefulness, Perceived Ease of Use, Technology Acceptance Model, Traffic Police, Road safety, Tanzania, Vehicle Tracking System

Abstract

This study evaluated the effectiveness of Vehicle Tracking Systems (VTS) in supporting traffic monitoring and operational performance among traffic police officers at the Tanzania Police Traffic Headquarters in Dar es Salaam. The study was guided by the Technology Acceptance Model (TAM) and focused on perceived usefulness, perceived ease of use, attitude toward system use and continuous system usage. The study used a quantitative cross-sectional research design. Data were collected from 193 traffic police officers using a structured questionnaire with a five-point Likert scale. Descriptive statistics, Pearson correlation and multiple regression analysis were used to analyze the data. The findings showed that officers generally viewed the system as useful and easy to use in their traffic monitoring activities. The regression results showed that perceived ease of use had a positive and significant influence on operational performance (B = 0.186, p = 0.017), while attitude toward system use had a negative but significant influence (B = -0.164, p = 0.045). Perceived usefulness (B = -0.044, p = 0.532) and continuous system usage (B = -0.040, p = 0.607) did not have a significant influence on operational performance. The overall regression model was significant, F (4, 188) = 3.287, p = 0.012, with R² = 0.065. The study concludes that making the system easy to use can help in supporting operational performance. It also shows that using the system regularly or seeing it as useful may not be enough on their own to improve performance. The study recommends regular training, technical support and improvement of the system to help officers use it properly in their daily traffic monitoring activities.

Downloads

Download data is not yet available.

References

African Development Bank. (2020, April). Road safety framework and guidelines. Infrastructure and Urban Development Department.

Almaiah, M. A., Al-Otaibi, S., Shishakly, R., Hassan, L., Lutfi, A., Alrawad, M., et al. (2023). Investigating the role of perceived risk, perceived security and perceived trust on smart m-banking application using SEM. Sustainability, 15(13), Article 9908. https://doi.org/10.3390/su15139908

Benbasat, I., & Barki, H. (2007). Quo vadis TAM? Journal of the Association for Information Systems, 8(4), 211-218. https://doi.org/10.17705/1jais.00126

Bhattacherjee, A. (2001). Understanding information systems continuance: An expectation-confirmation model. MIS Quarterly, 25(3), 351-370. https://doi.org/10.2307/3250921

Burton-Jones, A., & Straub, D. W., Jr. (2006). Reconceptualizing system usage: An approach and empirical test. Information Systems Research, 17(3), 228-246. https://doi.org/10.1287/isre.1060.0096

Chang, S.-C., & Tung, F.-C. (2008). An empirical investigation of students' behavioural intentions to use the online learning course websites. British Journal of Educational Technology, 39(1), 71-83.

https://doi.org/10.1111/j.1467-8535.2007.00742.x

Creswell, J. W., & Creswell, J. D. (2023). Research design: Qualitative, quantitative, and mixed methods approaches. SAGE Publications.

Davis, F. D. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Quarterly, 13(3), 319-340. https://doi.org/10.2307/249008

Davis, F. D., Bagozzi, R. P., & Warshaw, P. R. (1989). User acceptance of computer technology: A comparison of two theoretical models. Management Science, 35(8), 982-1003.

https://doi.org/10.1287/mnsc.35.8.982

Fishbein, M., & Ajzen, I. (1975). Belief, attitude, intention, and behavior: An introduction to theory and research. Addison-Wesley.

Land Transport Regulatory Authority. (2024). Annual performance report 2023/2024.

Goodhue, D. L., & Thompson, R. L. (1995). Task-technology fit and individual performance. MIS Quarterly, 19(2), 213-236. https://doi.org/10.2307/249689

Hair, J. F., Babin, J. B., Anderson, R. E., & Black, W. C. (2019). Multivariate data analysis (8th ed.). Cengage Learning. https://www.cengage.uk/c/multivariate-data-analysis-8e-hair-babin-anderson-black/9781473756540/

King, W. R., & He, J. (2006). A meta-analysis of the technology acceptance model. Information & Management, 43(6), 740-755.

https://doi.org/10.1016/j.im.2006.05.003

Legris, P., Ingham, J., & Collerette, P. (2003). Why do people use information technology? A critical review of the technology acceptance model. Information & Management, 40(3), 191-204.

https://doi.org/10.1016/S0378-7206(01)00143-4

Matemba, E. D., Li, G., Gogan, I. C. W., & Maiseli, B. J. (2020). Technology acceptance model: Recent developments, future directions, and proposal for hypothetical extensions. International Journal of Technology Intelligence and Planning, 12(4), 315-348.

https://doi.org/10.1504/IJTIP.2020.109769

Motsi, L., Chipangura, B., & Musanhi, N. (2023). A model for the adoption of transport management systems in the South African taxi industry. South African Journal of Information Management, 25(1), Article a1713. https://doi.org/10.4102/sajim.v25i1.1713

Ngumbi, D. N. (2016). A model for vehicle tracking and monitoring systems adoption in the Kenya Police Service [Master's thesis, Strathmore University]. https://su-plus.strathmore.edu/handle/11071/4845

Nyamawe, A. S., & Mbosso, E. C. (2014). Road safety: Adoption of ICT for tracking vehicles' over-speeding in Tanzania. International Journal of Computer Applications, 96(16), 12-15. https://doi.org/10.5120/16877-6876

Saunders, M., Lewis, P., & Thornhill, A. (2011). Research methods for business students (4th ed.). Pearson.

Sumuer, E., & Yildirim, S. (2015). Exploring user acceptance of an electronic performance support system. Performance Improvement Quarterly, 27(4), 29-48. https://doi.org/10.1002/piq.21178

Taber, K. S. (2018). The use of Cronbach's alpha when developing and reporting research instruments in science education. Research in Science Education, 48(6), 1273-1296.

https://doi.org/10.1007/s11165-016-9602-2

Tavasoli, M., Sarrafzadeh, A., Khaleghi, M., Zakaria, M., Barahouei Pasandi, H., & Karimoddini, A. (2025). Data communication challenges of connected and automated vehicles in rural areas. IEEE Access, 13, 29220-29251. https://doi.org/10.1109/ACCESS.2025.3539598

Venkatesh, V., & Davis, F. D. (2000). A theoretical extension of the technology acceptance model: Four longitudinal field studies. Management Science, 46(2), 186-204.

https://doi.org/10.1287/mnsc.46.2.186.11926

Venkatesh, V., Morris, M. G., Davis, G. B., & Davis, F. D. (2003). User acceptance of information technology: Toward a unified view. MIS Quarterly, 27(3), 425-478.

https://doi.org/10.2307/30036540

World Bank. (2017). The high toll of traffic injuries: Unacceptable and preventable. https://hdl.handle.net/10986/29129

World Health Organization. (2023). Global status report on road safety 2023. https://www.who.int/publications/i/item/9789240086517

Yamane, T. (1967). Statistics: An introductory analysis (2nd ed.). Harper and Row.