The food sector in Europe can be characterized as a complex, global and dynamically changing network of trade streams, food supply network relations and related product flows which offers a big spectrum for economic output and employment. Innovation is important for the competitiveness of the food industry that is to a large extent comprised of small and medium sized enterprises (SMEs). For them, innovation has grown extremely subordinate to interaction in networks. Network initiatives that could provide appropriate support involve social interaction and knowledge exchange, learning and competence development, and coordination (organization) and management of implementation. This paper is designed to assess the factors that affect the performance of German food SME formal networks. It also addresses the consequences at the network and macro level. The analysis was explored by using the laddering technique based on the means‐end chain theory. The findings will help to build up a “network learning toolbox” that is adapted to the particular requirements of the different target groups such as of SMEs, network managers and policy makers. The “network learning toolbox” should improve network learning, which is a driver for improvements in innovation, economic growth and sustainable competitive advantage for food SMEs.