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Title: Location Models of Emergency Service Public Facilities with Special Reference to the Strategic Planning of Fire Service Provision
Author: Kim, Yeong
ISNI:       0000 0001 3599 4875
Awarding Body: University of Liverpool
Current Institution: University of Liverpool
Date of Award: 2007
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The mam mm of this research is to develop a framework for both the location/allocation and planning/management of emergency services/facilities. The research explores the most suitable models for these facilities taking into account both equity and efficiency. This research also explores holV policy-based planning/management should be carried out with particular reference to fire services/stations but partially also to rescue/emergency medical services. We apply location/allocation models and decision-making models for these perspectives based on a variety of analyses of emergency services/facilities. The former relate to coverage models such as traditional p-median models (PMM) and modified maximal coverage models (MCM); .the latter relate to multiple criteria (attribute) decision-making models (MCDMlMADM) using TOPSIS (entropy method) and AHP (HAW) methods. In applying these models, we basically take into consideration the characteristics of emergency services/facilities, planning criteria, delivery systems, and the results of statistical data analysis and questionnaire survey. This is to explore which critical factors influence the location/allocation of emergency facilities and how they are applied to the models and the case study area. This research draws on the results of the model application and explores how to manage the much extended emergency services that now include rescue and emergency medical services. As a result of this model application, we first of all found that response time and population were most critical to location/allocation models and the MCM is most suited to the case study area in terms of efficiency and equity. In the evaluation of models, we also found that backup and workload problems were critical and should be evaluated when the service equipment and manpower were busy. Secondly, we found that the MADM would be useful to overcome the disadvantages of coverage models which mainly focus on accessibility dependent upon the response time. This MADM enabled to provide improvements in service quality to be provided by taking into consideration a variety of variables such as fire incidence, manpower, equipment, and cooperation with other agencies. In addition, policy-based planning and management were required so that the models can be effective in reality. Therefore, we explored recent technologies and techniques to enable decision-makers to make emergency service delivery much more efficient. As a result, we found that recent communication equipment and spatial information systems raised the possibilities of substantial improvements in management, planning skills, and service quality as well as a means of exploring optimum location/allocation. This was intended to overcome the service management problems of both location/allocation methods and decision-making methods. In conclusion, we recommend equitable and efficient location/allocation models such as coverage models suitable for the areas more remote from inner cities. We strongly recommend multiattribute decision making models to take into account a range of variables resulting from emergency services that have recently much more diversified and extended. Corresponding to rapidly changing technologies in service delivery systems, we need to establish effective policies/strategies and develop new techniques/skills for fire/rescue and emergency planning and management. In addition, these policies and techniques/skills are intended for fire experts, research scientists, planners, administrators, policy-makers, and legislators. We suggest an integrated approach both for both urban planning and for emergency service planning/management in the hope that an integrated system of fire and rescue services (FRS) and emergency medical services (EMS) will be able to save properties and lives.
Supervisor: Not available Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID:  DOI: Not available