| In general, the level of marketization of taxi industry is high in other country where thepopulation density is low. China has a large population density and is experiencinghigh-speed development and urbanization. Such unique characteristics indicate that the taxiindustry in China cannot be completely dependent on the market. Otherwise, the marketcompetition can end up in chaos, resulting in the loss of level of service. Therefore, the taxiservices in most cities in China are currently managed mainly by the government andregarded as a supplement for the public transportation. Nevertheless, the taxi services inChina are operated primarily based on a “hailing” mode, which has inherent drawbacks formanagement. For example, there is a lack of source of information; the decisions are not wellsupported by sound references; and it is difficult for the government to make reasonabledecisions and balance benefits of different stakeholders.Regarding the problems mentioned above, this dissertation presents a research thatstudied a method to collect the information of taxi operations using intelligent on-vehicledevices, based on the analysis of existing management modes, problems and related nationaland international researches in the taxi industry. This research also investigated some keyproblems related to the decision and management activities in the taxi industry, including thequantity of taxis in a market, the pricing of taxi services and the staff scheduling strategies ofthe taxi call centers. Further, this research introduced a new design of a management systemfor taxi services. The innovation of this work can be elaborated with the following aspects:(1) A prediction model to determine the quantity of taxis in a market was developedbased on the real-time data of taxi operations. This model combined precise and mid-to-longterm prediction and was based on a full analysis of existing problems regarding thedetermination of the quantity of taxis in a market. The precise prediction model used somecharacteristics of a city, including the basic urban parameters, the historical data and thereal-time data of taxi operations, as model inputs and was developed under the constraint ofaverage time of taxi in operation and average citizen income, etc. The mid-to-long termprediction model used some characteristics of a city, including the gross domestic product, thepopulation, the household consumption level, the average waiting time for taxis and the totallength of public transport lines, etc in each of many historical years, as model inputs and adopted the wavelet neutral network as a tool to predict the mid-to-long term quantity of taxisin the market of this city.(2) An urban taxi pricing method was developed based on the hedonic price theory. Thismodel used vehicle type and some characteristics of a city, including the per capita disposableincome, the development level of public transport systems, the ratio of the taxis in idlingstates, the quantity of taxis in the market, the total number of permanent residents, the level oftraffic congestion and the development level of tourism, etc as the model inputs anddetermined the pricing strategy using a multiple linear regression.(3) A staff scheduling method for taxi call centers was introduced based on a genericalgorithm. This method used the call center’s workload in different time-of-day as one of thebasic input data and applied a generic algorithm to determine the staff scheduling. Anoptimized schedule could be achieved in a fast fashion, overcoming the disadvantages of thetraditional manual scheduling method, reducing the cost of staff in call centers and bringingbenefits to both customers and drivers.The models and systems developed in this research described by this dissertation hadbeen showcased in30pioneer cities in China. The result showed that this work could providescientific methods to guide the management and decision activities in the taxi industry inChina and had a relatively high value in both theory and application. |
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