The paper presents a novel approach to the conceptual development of bikeshare systems to create healthy cities and economic development using GIS and optimization modeling. Additionally, we test the applicability of Reilly's law of retail gravitation to bikeshare programs and their potential impact on economic development. The Central District Health Department of Boise, Idaho, is in the conceptual phase of creating a bikeshare system for Boise and considering funding and location needs. In a collaborative effort between Boise State University and the Central District Health Department, we developed a GIS driven approach to allocate and rank stations. The paper demonstrates methodologies and policy recommendations for a bikeshare system. Bikes, as a healthy alternative to automobiles or to incomplete public transit options, provide the opportunity to travel within a city, or region, in a fast and flexible pattern for reasonable trip distances. Bikes present an ideal platform to facilitate short commutes, recreational rides, and even trips for small errands. The post‐modern divide with work and home in potentially significant distances from one another often means the bike (if any is owned) usually stays in suburbia while its owner commutes to work in the city. This forces the owner to use the car for short‐distance trips within the city. Bikeshare systems go beyond the regular relationship of one owner, one bike, and just one location. With stations allocated in a network across the city, they offer bicycling interested customers an opportunity to "check out" a bike at one station and ride it to a station close to the preferred destination. Most systems offer a 30 minutes check‐out without charge and contribute, with a proper distribution of stations and amount of bikes available, to zero‐emission traffic and to an active healthy city. This raises the question of what is the proper spatial distribution and amount of stations/bikes to create a functional system. The paper builds on a review of existing systems in the US and the way demand/supply was modeled. We apply a GIS feasibility analysis as the first level in this allocation/location problem. This contains an evaluation of the built environment and creation of a composite measure to identify preferred areas. Second, a GIS based optimization model evaluates this measure and creates automatically a network of proposed locations. The model considers the amount and size of possible stations due to funding opportunities and creates scenarios for later policy discussion. We conclude with findings for Boise, ID, but also set emphasis on the model's transferability to other cities considering a bikeshare‐system.