目前計程車業者面對同業競爭壓力及空車率偏高，與經濟不景氣、失業率逐漸提升、捷運通車及公 車專用道設立(使計程車產業進入全面蕭條及計程車之競爭優勢下降)的情況之下，如何有效進行計程車的 派遣以提升服務品質及競爭優勢，謀求轉型以吸引消費者搭乘，提升消費者搭乘意願，來增加計程車乘 客率及降低營運成本，實為重要之課題。 針對上述的問題，本研究不僅探討現行智慧型計程車營運、派遣方式與派遣公平性原則，更重要係 納入乘客搭乘計程車的決策考量因素來建構一智慧型計程車與乘客指派決策支援的雛型系統，以期提高 計程車服務品質、增加消費者滿意度及提升計程車營運績效。藉由多目標整數線性規劃(multi-objective integer linear programming, MOILP)、分析層級過程(analytic hierarchy process, AHP)及地理資訊系統 (geographic information system, GIS)等方法，系統能夠與管理者互動而推薦出最適派遣的智慧型計程車以 滿足乘客偏好需求以提升消費者搭乘意願並擴大市場需求，而形成車隊規模經濟及附加價值效用，並能 有效提高乘車安全及進一步減少空車所造成的空氣污染嚴重性。最後，本研究在更多實證結果中推論出 重要管理涵義，以作為未來應用之參考。

Currently taxi operators facing competition pressure of the same business, low taxi loading rate, and economic recession, the unemployment rate gradually rises, mass transit and public vehicle special-purpose road establishment (causes the taxi industry to enter the depression and competitive advantage of the taxi descends), how effectively carrying on taxi dispatching to promote service quality and competitive advantage, seeking reforming to attract the passengers to travel by taking the will, increasing the taxi passenger rate and reducing the operating cost, really become important topics. As described earlier, this study not only examines the taxi operation and the intelligent taxi dispatching model, but also it is more important to include the passengers’ preference for taking intelligent taxi to construct an intelligent decision model for assigning taxi to passenger to improve the service quality, effectiveness of taxi operation and consumers’ satisfaction. This study mainly applies several quantitative methods such as multi-objective integer linear programming (MOILP), analytic hierarchy process(AHP), geographic information system (GIS) and other methods to obtain an optimal solution for assigning intelligent taxi to passenger to fulfill passengers’ preference and expand the market demand to increase the quantities of taxi vehicle for improving the operation effectiveness and value added efficiency. Further, this study can improve security of taking taxi and reduce air pollution. Finally, experimental results can derive some important managerial implications for the references of future applications.