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- Interaction between innovation in small firms and their environments: modelling entrepreneurial patternsPublication . Noronha, Teresa de; Cesário, M.; Fernandes, L.Small food firms make up an important sector in the European economy and are particularly significant in rural areas where they are potential sources of employment and growth. Despite this, their behaviour as regards innovation has been relatively little studied to date. This exploratory investigation finds different types of innovative behaviours among small agro-food firms in peripheral regions and identifies some of the factors with which they are associated. The research reported here is based on a sample of 323 small and very small food and drink (hereafter “food”) firms drawn from 11 regions in six European countries. The food industry is generally regarded as a mature, low-technology industry, but this study identifies different clusters of small food firms according to innovative behaviours. It finds that, although a substantial number of firms may be defined as non-innovators, by far the largest cluster of food firms is involved in multiple forms of innovative activity. Recent studies have demonstrated the complexity of the determinants of technological progress. This may be modelled as a learning process in which small innovative firms tend to draw on internal and external sources of expertise and are both influenced by and influence the broader socio-economic environment in which they operate. This study uses cluster analyses to identify four types of innovative behaviours and examines the factors influencing these. It takes first steps to incorporate both measures of innovative capacity at the firm level as well as of the local development environment in order to explore links between the innovative capacity of small food firms and the characteristics of their regional contexts.
- Behavioural patterns towards innovation: the case of European rural regionsPublication . Noronha, Teresa de; Cesário, M.Contrarily to big firms, small firms interact intensively with the territory in which they locate, as a signal of their embeddedness. The particular tight links they develop with their external environment reduce uncertainty risks. In general, for them, geographical and sociological proximities constitute the main sources of assets and information determining their perspectives and strategic choices. The present study uses a set of enquires, developed within the framework of a European research project, with the purpose of modelling the determinants of innovation in a bi-univocal relationship of interdependencies between small firms and their environmental contexts. We dealt mainly with lagging regions and a panel of 323 firms from the agro-food sector, located in 11 different European rural regions from six different countries. Using a set of variables able to characterise the innovative processes and through the application of k-mean clusters statistical analysis, it was possible to detect behavioural patterns towards innovation among those firms. Non-innovators, pioneer innovators and follower innovators were the identified patterns. Using cross tabs analysis between those patterns and a set of attributes dealing with the importance of human capital, the profile of each group were drawn.
- Driving forces for innovation: are they measurable?Publication . Noronha, Teresa de; Cesário, M.This paper outlines a synthetic framework based on the concept of the learning process as a driver to redress stakeholders’ attitudes and strategic choices. The discussion is focused on the advantages that may result from institutional proximity, knowledge diffusion and coordination for the specific building up of a territorial knowledge base and the consequent achievement of sustainable regional development. This theoretical framework is applied to an empirical exercise identifying a number of variables supposed to be able to characterise firms and regional performances towards different forms of innovation. Modelling techniques are used to demonstrate that firms’ capacity to innovate is a complex attribute whose determinants change. The results permit to conclude causal links that may be useful for a better understanding of innovation and as support instruments for policy-makers which intend to search for specificities in the regional development process.