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One of the greatest challenges facing every society today is crime control and management. It could be as little as pick–pocketing, or human trafficking, or even as deadly as terrorism. As criminal’s perfect ways of avoiding being detected, Law Enforcement Agencies (LEAs) must adopt innovative ways on crime prevention and control. This research applies Queuing Network (QN) model to evaluation the performance of LEAs on crime information management. The QN comprise two queuing theory models; single server (M/M/1) and multiple server (M/M/m) queuing models. To implement this model, crime data was collected from Eleme (2012) and Nsukka (2013) police stations with a table format to capture the timing such as case arrival time, service time (investigation and handling time) and termination time. The model was implemented using PHP programming language Excel application was used to plot some graphs to observe the system’s behaviour. The case timing captured (input data) were used to calculate the queuing theory performance measures (model parameters). Results from the analysis shows how many cases were handled by how many staff members in a specified period of time. This model will make LEA’s crime management system visible at different levels (local, state and federal) to both government, LEA’s admins and general public. Government can assess the LEA’s performance at any time. Use of this model will improve LEA’s productivity and public security as well.   Key words: Crime management, information system, law enforcement agency, performance evaluation, queueing network, single server queuing model, multiple server queueing model.

Performance evaluation of law enforcement agency on crime information management using queuing network model