This paper presents a mathematical model for supporting the decision and policy making related to the optimal determination of shifts and fares of taxi services in a major city. The model is based on the system’s generalized cost function and uses continuous approximations and geometric probabilities for estimating the key performance indicators of the taxi market, which are waiting and access time for the customers (in-vehicle travel time does not depend on the offer side) and benefits for the drivers. The model is based on an econometric model with the inclusion of an elastic demand, which allows the estimation of the optimal values for the two decision variables of the problem: fare structure and the taxi fleet size. The model also accounts for a full-day time period instead of the one-hour time frame models used in most of the taxi models, which allows for providing insights on the daily duration and distribution of the shifts that should be defined by the policy makers.