The Massachusetts model illustrates the latest approach to smart growth - the incentive based program. This study examines the reasons for and actual outcomes of local smart growth efforts through one of the Massachusetts’ smart growth incentives - the Commonwealth Capital (CC) Program. The main objectives of this research are built on two conceptual models through a mixed approach that combines qualitative and quantitative methods. The qualitative method is mainly utilized to evaluate the implementation of the CC program. The results indicate that the program is a good measure of municipal smart growth efforts representative of goals of the state. Communities with diverse land bases have some advantage, as a variety of zoning methods can be employed. It is not obvious that communities have changed their own zoning in response to the stimuli of the CC program. The first model is applied through various statistical tests to investigate the relationships among the towns’ characteristics and CC data. Homeownership, education and access to the highway system are significant factors related to municipal smart growth efforts in Massachusetts. Wealth, population and quantity of open spaces are only significant for certain type of communities (e.g. maturing suburbs, developing towns etc). Municipal political preferences (e.g. forms of municipal governance, DEM/GOP preference etc) and municipal planners’ efforts have some influence on the adoptions of smart growth policies, though the specific outcomes might vary case by case. The second model tests the statistical relationships between CC data and the Urban Sprawl in Massachusetts. The urban sprawl are defined by Urban Sprawl Indicator (USI) as the amount of residential land consumed per building permit in the five past years per community in Massachusetts. The CC scores and USIs negatively fit the regression line well, indicating that local smart growth efforts have generally controlled land consumption in the past. In particular, the USIs in developing suburbs appear more responsive to the CC data. The spatial lag model shows sprawl is a net-effect phenomena and the cluster of sprawl in a region might weaken the effectiveness of particular municipal smart growth efforts. Lastly, this research suggests that the design of state land use policies ought to follow the nature of geographic segmentation of municipal smart growth preferences.