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Abstract
ASSESSMENT OF TRANSPORT TERMINAL OPERATION WITH RESPECT TO VEHICLE ASSIGNMENT AND PASSENGERS’ PERCEPTION: CASE STUDY AT JIMMA BUS TERMINAL
Fikraddis Jima*, Elmer Agon and Murad Mohammed
ABSTRACT
Movements of people, goods and information have always been fundamental components of human societies. Transport system is one of the most essential services and a vital force for determining the upward direction of development. To achieve the desired transportation balance and the system to be effective and efficient, it is essential to provide organized facilities in all parts of the system. One such facility is a bus terminal. This research primarily focused on assessments of transport terminal operation with respect to vehicle assignment and passengers’ perception regarding to the service given in the terminal. Descriptive cross sectional study research type is used to identify problems in the area. Desk study was used to check vehicles’ data from terminal and questionnaires were distributed to passengers to analyze their level of satisfaction regarding to internal facilities of the terminal. In order to carry out this research, similar researches as a literature review were reviewed and different books and documents written on the subject matter from internet and library were also reviewed. Finally, in this research, IBM SPSS version 20 is used to develop regression model for vehicle assignment in order to have proportional distribution of vehicles through the routes. And Microsoft Excel was used to represent data by chart and in addition AUTOCAD 2007 was used to visualize the bus terminal. Based on finding of this thesis it is indicated that there was unproportioned vehicle assignment throughout the route. In addition, there were also problems such as insufficient vehicles, absence of route information, issue of theft and discomfort of terminal to passsengers is available in terminal and passengers were not satisfied regarding to service given in the area. Therefore, to get proportional distribution of vehicles, such regression model was developed Y=21.487+0.017*No. passenger, for routes categorized under short distance routes, Y=16.363+0.066*No. passen-0.707*N. seat, for medium distance routes and Y=42.789-0.632*No. seats for long distance routes, where Y stands for number of predicted vehicles and accuracy of model depends on R values in the output table and vary from 0.3-1.0 for best correlation. Finally, internal facilities should have to provide to solve mentioned problems in the terminal.
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