We are taking advantage of the development of a new sustainability label in German fruit production that is aimed at the end consumer as a case study to conduct an ex-ante assessment of consumer and producer acceptance of a new label. We present here the first steps toward a decision analysis project, which includes the evaluation of two surveys and the design of a graphical influence model. The results of the two surveys summarize the specific conditions under which a new label can be successful from a producer and consumer perspective. The model visualizes the influence pathways opened up by the introduction of the label. We attempt to predict the success of such a label based on the theory of innovation diffusion by examining niches in fruit production that could influence the mainstream of fruit growing and marketing through a window of opportunity. Labels are a proven means to accomplish several objectives in the field of sustainable resource management. Among these, we explored the role of a label in satisfying consumer information needs and in promoting innovation in a production system in order to forecast the system change potential of the label. We further assume that the impact of the label on the system largely depends on the acceptance of the innovative label. The acceptance of an innovation such as a new label can be decisively promoted if it corresponds to the habits, norms and needs of customers. We therefore asked 1000 German consumers what developments they would welcome in fruit production and where they see the greatest need for action. In order to be able to keep the sustainability promises of the label, a change in production processes is necessary. To do this, the criteria of the label must be incorporated into the decisions of the fruit growers. We therefore asked the fruit growers what changes they would be willing to make and what means they consider suitable for making fruit growing more sustainable. The results of the surveys were used to compute a forecast of the diffusion of the innovative label. The results will be incorporated into a conceptual decision support model that will provide recommendations for the further development of the label.