The purpose of the research presented in this poster is to investigate factors impacting farmers’ decisions to engage in multifunctional activities, which are hypothesized to enhance the sustainability and prosperity of farms and their communities. To achieve this research goal, we break it up into two specific objectives. The first objective is to identify statistically significant hot spots of farms participating in multifunctional activities (i.e., clusters of zipcodes with highly correlated, large numbers of farms participating in multifunctional activities). To complete this objective, we use the results of a short, postcard survey completed by small and medium sized farms in the northeastern United States. The survey contains four questions related to multifunctional practices (specifically, agritourism, direct sales, value added products and off-farm income) and also provides the zip codes of the respondents. Using the Geographic Information Systems software (GIS), we find statistically significant hot spots of farms participating in multifunctional activities based on the Local Moran’s I test statistic for spatial autocorrelation (Anselin, 1995). We perform these analyses for different types of multifunctional activities. Our second objective is to investigate the variables that are correlated with the distribution of farms participating in multifunctional activities, while controlling for the possibility of spatial autocorrelation. To complete this objective, we use Spatial Autoregressive Models (LeSage, 1998). Our independent variables consist of county/sub-county level variables related to demographics, economics, climate, and policy. Most of these variables can be obtained from publicly available sources such as the Census of Agriculture, the U.S. Census, and the Bureau of Economic Analysis, to name a few. The results of this research may have implications for policies related to encouraging farm participation in multifunctional activities.