Patterns of Interactive Learning in a High-tech Region

This paper aims at developing a theoretical framework that explains levels of interactive learning. Interactive learning is defined as the exchange and sharing of knowledge resources conducive to innovation between an innovator firm, its suppliers, and/or its customers. Our research question is: Why do levels of interactive learning of innovator firms, their customers, and/or suppliers vary? Our theoretical framework combines a resource-based perspective with an activity-based account of interactive learning. It starts with a resource-based argument, which is specified by introducing competing and complementary theoretical arguments such as the complexity and structuring of innovative activities, and sectoral technological dynamics. The strength of internal knowledge resources can either hamper or facilitate levels of interactive learning. We assume that more complex innovative activities urge firms to co-ordinate and exchange information between users and producers, which implies a higher level of interactive learning. The structuring of innovative activities, as well as sectoral technological dynamics can foster interactive learning. To test our theoretical claims, we estimated six models predicting the level of interactive learning of innovator firms with: (1) their customers (here the innovating firms are the producers); (2) their suppliers (here the innovating firms are the customers); (3) with customers and suppliers split by size (four separate models). These analyses allow a comparison of the antecedents of interactive learning of innovator firms performing dual roles, and having a different size. Both monotonic and non-monotonic effects of the complexity of innovative activities, the strength of the internal knowledge base, and monotonic effects of the structuring of innovative activities are tested. Our findings suggest that our theoretical model best fits the interactive learning of small- and medium-sized innovator firms. Interactive learning with customers is positively associated with the complexity and structuring of innovative activities, and with moderate scores of the cross-product term of `complexity of innovative activities and the strength of knowledge resources'. Interactive learning with customers is positively affected by higher technological dynamics. Stronger internal knowledge resources yield positive effects on interactive learning with suppliers up to a threshold point. Once this threshold is crossed, the effects of stronger kn