The main objective of this study is to identify and prioritize the various factors affecting innovation systems in the food industry and to assess the impact of innovation system factors on regional sustainability. To achieve this goal, a descriptive-correlational research method was used, employing a structured questionnaire as the primary data collection tool, and the statistical population of this study included professors and experts in innovation who were selected through purposive sampling methods. Data analysis was performed using structural equation modeling (SEM) and fuzzy analytic hierarchy process (Fuzzy AHP) methods. The SEM approach facilitates the examination of complex relationships between variables, while the fuzzy AHP method increases the accuracy of assessments and decision-making in the face of uncertainty. The combination of these two methods provides more comprehensive and reliable insights into the factors affecting innovation systems. The findings show that individual, organizational, environmental, and material factors significantly influence regional sustainability, and individual factors appear as the most important element in enhancing innovation processes. Furthermore, the validity and reliability of the proposed model demonstrate its applicability in both theoretical and practical research fields. Despite the recognized importance of innovation systems in enhancing regional sustainability and supporting food industry companies, there is still a lack of comprehensive models in the marketing field that address this issue. Consequently, it is essential to develop a model that clarifies the relationships between innovation systems and sustainability. Such a model can enable organizations to understand better and effectively manage regional sustainability dynamics. Ultimately, this research contributes to the existing body of knowledge by providing actionable insights that can guide policymakers and industry leaders in fostering innovation-driven sustainable practices in the food sector.