The Effect of Office Security Measures on Job Performance of Administrative Staff of the University of Bamenda

This study examined the effect of office security measures on the job performance of administrative staff at the University of Bamenda, addressing a gap in empirical evidence regarding how surveillance cameras, physical security presence, information security protocols, and integrated safety sensors influence employee productivity, efficiency, accuracy, timeliness, and quality of work. A cross-sectional descriptive survey design was adopted targeting 78 secretaries across the university’s administrative structures. Primary data were collected through a structured four-point Likert scale questionnaire and analyzed using SPSS, employing descriptive statistics and multiple regression analysis (Ordinary Least Squares). Reliability was confirmed by Cronbach’s Alpha (all variables > 0.69), and multi-collinearity was ruled out by Variance Inflation Factor (all values < 1.34). The regression model was statistically significant (F = 6.840, p = 0.000) and explained 31.0% of the variation in job performance (R² = 0.310; Adjusted R² = 0.264). The findings revealed that physical security presence had the strongest positive and significant effect on job performance (B = 0.346, p = 0.004), followed by information security protocols (B = 0.170, p = 0.004) and surveillance cameras (B = 0.077, p = 0.001), while integrated safety sensors showed a negative and statistically insignificant effect (B = -0.193, p = 0.083). The study concluded that human-based security systems and structured information protection significantly enhance administrative staff performance, whereas poorly implemented sensor technologies fail to contribute positively. Recommendations include strengthening physical security deployment, enforcing information security protocols with regular training, ensuring full coverage and maintenance of surveillance cameras, and upgrading integrated safety sensors with centralized alert systems and staff sensitization. Future research should extend to other Cameroonian universities, adopt mixed methods, and explore emerging technologies such as AI-based surveillance and biometric access control.