Innovation Against Gender Inequalities in Agri-Food Industry

Abstract: In recent years, industrialization and globalization have prompted small and medium-sized enterprises (SMEs) to implement a significant technological and managerial innovation process. In Italy, it leads to new entrepreneurial pathways, such as innovative start-ups. The new solutions' implementation becomes even more crucial for a company's sustainability during crises since it improves the organization's flexibility and encourages the development of new tools and techniques. Previous research recognized the intangible assets' relevance in the innovation's creation process, mainly referring to Intellectual Capital (IC) and its components. In particular, Relational Capital (RC) fosters reactive firms' resilience, whereas Structural Capital (SC) helps SMEs respond to challenges proactively. Focusing on the agri-food sector, it has recently reached considerable results in terms of innovation, but it still appears insufficient to stimulate female entrepreneurship. Recent data confirm a remarkable gender gap: for 107 innovative agri-food start-ups in Italy, only 14 are led by women. Given all this, the paper aims to answer the following Research Questions (RQ). RQ1: How could RC and SC promote women innovative start-ups in agri-food? RQ2: How did these factors foster proactive and reactive firms' resilience during the pandemic? The work uses an exploratory, descriptive qualitative analysis performed during the pandemic emergency and applies the CAOS model, an interpretative model widely used in SMEs' studies since it allows a deep analysis of relational capital. Moreover, the CAOS model can be helpful to observe the SC's innovation. From a theoretical point of view, the research contributes to gender studies, identifying critical, innovative elements that similar women start-ups could implement. From a managerial perspective, findings could increase the firms' competitiveness in the current crisis period and reduce gender inequality. The application of a single case study could represent a research's limit. Thus, in the future, the authors aim at replicating the analysis considering a more comprehensive sample.