TECHNOLOGY ADVANCEMENTS AND PERFORMANCE OF PRIVATE SECURITY FIRMS IN NAIROBI CITY COUNTY, KENYA
Abstract
Purpose of the study: The study examined the influence of technological advancements on the performance of private security firms in Nairobi City County, Kenya. Specifically, the study examined the effects of IoT utilization, AI-driven analytics, mobile applications, and cloud computing on performance of private security firms.
Statement of the problem: The private security sector plays a critical role in safeguarding people, property, and business operations in Kenya. However, many private security firms continue to experience challenges related to operational efficiency, incident response, supervision, accountability, and information management due to reliance on traditional security management practices. Technological advancements such as the Internet of Things (IoT), Artificial Intelligence (AI), mobile applications, and cloud computing have emerged as important tools for enhancing security operations and improving organizational performance.
Methodology: A descriptive research design was adopted. The target population comprised 800 supervisors and managers working in licensed private security firms in Nairobi City County. Using Cochran’s formula, a sample size of 260 respondents was selected through simple random sampling. Data were collected using structured questionnaires. Data were analysed using the Statistical Package for Social Sciences (SPSS Version 25). Descriptive statistics, including frequencies, percentages, means, and standard deviations, were used to summarize the data, while inferential statistics, comprising Pearson correlation and multiple regression analyses were used to determine relationships among the study variables.
Findings: The findings revealed that Internet of Things utilization had a positive and significant influence on the performance of private security firms (β = 0.221, p < 0.05). Artificial Intelligence-driven analytics had the strongest positive and significant influence on performance (β = 0.314, p < 0.05). Mobile applications also had a positive and significant influence on performance (β = 0.289, p < 0.05), while cloud computing positively and significantly influenced the performance of private security firms (β = 0.247, p < 0.05). The regression model indicated that the four technological variables jointly explained 61.0% of the variation in the performance of private security firms (R² = 0.610), demonstrating the significant contribution of technological advancements to organizational performance.
Conclusion: The study concludes that technological advancements significantly improve the performance of private security firms through enhanced monitoring, communication, decision-making, operational oversight, and accountability.
Recommendations: The study recommends increased investment in IoT technologies, AI-driven analytics, mobile application platforms, and cloud-based systems to improve operational efficiency, service delivery, and overall firm performance. The findings contribute to the growing body of knowledge on technology adoption in the private security sector and provide useful insights for security practitioners, policymakers, and future researchers.
Keywords: Technology Advancements, Performance, Private Security Firms, Nairobi City County, Kenya
References
African Security Review. (2021). Security surveillance systems and operational efficiency in East Africa. African Security Review Journal, 30(2), 45–61.
Ali, M., Khan, S. U., & Vasilakos, A. V. (2015). Security in cloud computing: Opportunities and challenges. Information Sciences, 305, 357–383.
Allied Market Research. (2022). Global security services market report 2022–2030. Allied Market Research.
Ashton, K. (2009). That 'Internet of Things' thing. RFID Journal, 22(7), 97–114.
Atzori, L., Iera, A., & Morabito, G. (2017). Understanding the Internet of Things: Definition, potentials, and societal role of a fast evolving paradigm. Ad Hoc Networks, 56, 122–140.
Barney, J. (1991). Firm resources and sustained competitive advantage. Journal of Management, 17(1), 99–120.
Clarke, R. V. (1980). Situational crime prevention: Theory and practice. British Journal of Criminology, 20(2), 136–147.
Cochran, W. G. (1963). Sampling techniques (2nd ed.). John Wiley & Sons.
Cooper, D. R., & Schindler, P. S. (2013). Business research methods (12th ed.). McGraw-Hill Education.
Creswell, J. W. (2003). Research design: Qualitative, quantitative, and mixed methods approaches (2nd ed.). Sage Publications.
Creswell, J. W., & Creswell, J. D. (2018). Research design: Qualitative, quantitative, and mixed methods approaches (5th ed.). Sage Publications.
Daft, R. L., & Lengel, R. H. (1986). Organizational information requirements, media richness and structural design. Management Science, 32(5), 554–571.
Davenport, T. H., & Ronanki, R. (2018). Artificial intelligence for the real world. Harvard Business Review, 96(1), 108–116.
East African Security Association. (2022). Annual report on technology adoption in East African security firms. EASA Publications.
Gubbi, J., Buyya, R., Marusic, S., & Palaniswami, M. (2013). Internet of Things (IoT): A vision, architectural elements, and future directions. Future Generation Computer Systems, 29(7), 1645–1660.
Hair, J. F., Black, W. C., Babin, B. J., & Anderson, R. E. (2013). Multivariate data analysis (7th ed.). Pearson Education.
Karani, P. (2020). Challenges affecting technology adoption in Kenyan private security firms. Journal of African Security Studies, 8(3), 55–70.
Kenya National Bureau of Statistics. (2021). Economic survey 2021. KNBS.
Kim, J., & Lee, H. (2020). Artificial intelligence applications in security management systems. Journal of Information Security, 11(4), 245–259.
Kothari, C. R. (2004). Research methodology: Methods and techniques (2nd ed.). New Age International Publishers.
Kumar, R., & Singh, P. (2020). Mobile reporting systems and operational efficiency in security organizations. International Journal of Information Systems, 15(2), 44–58.
Kuo, A. M. H. (2019). Opportunities and challenges of cloud computing to improve security operations. Journal of Technology Management, 14(2), 77–89.
Lee, I., & Lee, K. (2015). The Internet of Things (IoT): Applications, investments, and challenges for enterprises. Business Horizons, 58(4), 431–440.
Markets and Markets. (2023). Security technology market – Global forecast to 2028. Markets and Markets Research.
Mazerolle, L., & Ransley, J. (2006). Third party policing. Cambridge University Press.
Mell, P., & Grance, T. (2011). The NIST definition of cloud computing (Special Publication No. 800-145). National Institute of Standards and Technology.
Mugambi, J., & Wanjiru, P. (2022). AI-powered surveillance systems and patrol efficiency in Rwanda. East African Journal of Information Systems, 6(1), 23–39.
Mugenda, O. M. (2008). Social science research: Theory and principles. Applied Research & Training Services.
Mugenda, O. M., & Mugenda, A. G. (2003). Research methods: Quantitative and qualitative approaches. Acts Press.
Mugenda, O. M., & Mugenda, A. G. (2012). Research methods dictionary. Applied Research & Training Services.
Mugenda, O. M., & Mugenda, A. G. (2013). Research methods dictionary. Applied Research & Training Services.
Mutua, S. (2021). Technology adoption barriers in private security firms in Kenya. Kenya Journal of ICT Management, 5(2), 66–81.
Mwakalebela, H. (2021). Mobile security applications and communication efficiency in Tanzania. Tanzania Journal of Information Systems, 9(1), 50–64.
Nilsson, N. J. (2010). The quest for artificial intelligence. Cambridge University Press.
O'Brien, J. A., & Marakas, G. M. (2011). Management information systems (10th ed.). McGraw-Hill/Irwin.
Ochieng, P., & Otieno, J. (2021). Mobile applications and cloud computing in Kenyan private security firms. African Journal of Information Systems, 13(3), 201–217.
Private Security Regulatory Authority. (2022). Licensed private security service providers in Kenya. PSRA.
Rogers, E. M. (1962). Diffusion of innovations. Free Press.
Russell, S., & Norvig, P. (2016). Artificial intelligence: A modern approach (3rd ed.). Pearson Education.
Russell, S., & Norvig, P. (2021). Artificial intelligence: A modern approach (4th ed.). Pearson.
Saunders, M., Lewis, P., & Thornhill, A. (2009). Research methods for business students (5th ed.). Pearson Education.
Saunders, M., Lewis, P., & Thornhill, A. (2019). Research methods for business students (8th ed.). Pearson.
Turban, E., Pollard, C., & Wood, G. (2018). Information technology for management (11th ed.). Wiley.
UST. (2023). Cloud-based security operations and efficiency report. UST Research Publications.
Vintra Technologies. (2023). AI-powered video analytics case study report. Vintra Technologies.
Willie, M. M. (2024). Research population and sampling techniques in social sciences. Academic Press.
Young, P. V. (2009). Scientific social surveys and research (4th ed.). Prentice Hall.
