This study proposes the implementation of a Strategic Ontological Police Force Knowledge Management Framework with the Dubai Police Force. Recent research in knowledge management has reiterated the potential benefits of effective knowledge management in both public and private sector organisations. Effective knowledge management allows organisations to accrue rewards such as increased productivity, enhanced performance, and competitive advantage. However, the process of transitioning to new models and frameworks of knowledge management can pose a number of difficulties, particularly within organisations that have entrenched managerial practices. This study posits that the implementation of an effective knowledge management strategy must take into account the cultural and administrative specificity of the organisation, and the wider socio-cultural context in which it operates, in order to ensure that an appropriate framework is devised. The core characteristics of the proposed Knowledge Management framework of the Dubai Police Force must be one where the organisational structure first and foremost permits transparency and an avenue stream for sharing knowledge. This framework must enhance common understanding within the organisation hence ontology is utilised to capture this. New technology must be shared amongst all levels within the organisation and training at all levels is required to be homogenous. The thesis finds that knowledge sharing within the Dubai Police Force to be largely absent with a degree of apathy amongst staff members. Further, the findings show the staff to be unaware of the nature to which knowledge sharing could benefit the police force in the long run. There was also an attitude whereby staff members concentrated on their own particular tasks, goals and achievements and not those of other individuals, which if noted, would be to the benefit of the organisation. The thesis found that the entire infrastructure lacked cooperation at all levels to the detriment of the entire police force. In light of the knowledge framework and contribution, the recommendations serve to consider how people, cultures and technology interact to create a strategy for knowledge transfer within the institution rather than an environment consisting of workers the knowledge management technologies should ensure a process that includes personal development contributing to the overall organisation and training programmes.

In recent years, call centres have been considered as an integral part of the modern businesses, since they play an important role in providing service delivery functions to their customers. A well-managed call centre, therefore, is crucial to ensure high level of customer satisfaction in today’s competitive market. In order to achieve a high standard, managers of call centres face a very difficult set of challenges. At the top level, they must strike a balance between two powerful competing interests: low operating costs and high service quality. On a day-to-day basis, while simultaneously keeping low costs and high service quality, those managers must also employ appropriate techniques and tools in order to evaluate the true performance of their operations accurately. Such tools play a vital role in understanding the current system performance, evaluation of any proposed enhancement scenarios, and optimising operations management decisions under any unexpected operating conditions. One of traditional operations management challenges for call centre managers is to tackle the multi-period human resources allocation problem. In this thesis, the staffing and staff scheduling decisions in single-skill inbound call centres were studied. These decisions are normally made under strict service level constrain in the presence of highly uncertain operations and demand of call centre services. Neglecting such uncertainty may lead to unrealistic decisions. The objective of this research thesis was to propose a framework to enhance the call centre performance through taking realistic optimal staffing and scheduling decisions. Realistic optimisation requires realistic modeling (evaluation) of call centre operations which is the main focus and contribution of this research. The proposed framework has combined statistical, simulation, and Integer Programming (IP) techniques in achieving realistic optimisation. The framework begins by developing stochastic statistical data models for call centre operations parameters which are divided into service demand (arrival volumes) and service quality (service times, abandonment volumes, and patience time) parameters. These data models are then fed into a simulation model which was developed to determine the minimum staffing levels in daily an-hour periods. Finally, these staffing levels are considered as input to an IP model that optimally allocates the service agents to the different operating shifts of a typical working day. Application of the proposed framework to a call centre in Libya will also be presented to illustrate how its staffing and scheduling decisions could be improved by using the model.