Antonio Dottore

Understanding demand for innovation in the food industry

Purpose – This paper aims to focus on understanding how demand for innovation is articulated in low‐tech industries, dominated by SMEs, where innovation is often based on informal processes and uncodified knowledge, relying on intangible assets.Design/methodology/approach – The authors hypothesize that the problems found in the innovation area are exacerbated in a traditional industry. SMEs might have difficulty understanding what their requirements might be, let alone finding the optimal provider of technologies. The authors therefore expect to find three main forms of demand: real, latent, and potential. The specific case is the food industry in Apulia, Italy. First, focus groups identified general business and technology needs. Then in‐depth interviews were conducted with 87 firms, stratified in order to be representative of food firms in Apulia.Findings – The authors detected 285 different needs requiring an innovative solution. In most cases, firms understand the areas to be improved, but do not have...

A partnering business model for technology transfer: the case of the Muenster University of Applied Sciences

Theory and practice of technology transfer and entrepreneurial behaviour of academics are novel. We draw upon the literature of business models, transaction costs, professional and organisational culture and of agency theory to formulate a framework for a technology transfer business model. We present the range of options used by universities and we examine the spin out option, as context and contrast to the MUAS approach. The case of the MUAS is presented. It illustrates the conceptual framework developed and has thus far been successful in its specific environment. Replication might require adaptation, but this particular approach can offer useful lessons. Tentative hypotheses for research on business model adaptation are derived from the study.

Developing a new business model for enabling research – the case of the ACPFG in Australia

The way in which companies, research centres and educational institutions are organised and structured may provide a competitive advantage for commercialisation, in particular if companies are dependent on the deployment of complementary assets and capabilities by third parties. This paper presents the case of the Australian Centre for Plant Functional Genomics (ACPFG), a private agricultural biotechnology (agbiotech) company specialising in early stage Research and Development (R&D) to produce superior adapted cereal varieties, tolerant to abiotic stress conditions such as drought, frost, salt, or mineral toxicity, all of which have a direct and negative impact on plant growth and crop productivity. The organisational structure of the company has been influenced and shaped by Government policy, shareholders expectations and trends in the agbiotech industrial organisation. It has proved attractive to potential alliance partners for collaborative R&D and commercialisation. We present the ACPFG as a new business model to fund basic research and facilitate technology transfer.

Predicting Future Technopreneurs Among Inventors

High-technology new firms are an important source of strong economic value and spillovers. It is therefore theoretically and practically important to understand the antecedents to their creation. This study focuses on understanding attitudinal, situational and personal characteristics associated with entrepreneurial activity by academic inventors. We surveyed patent holders and examined differences between entrepreneur inventors (EIs) and non-entrepreneur inventors (NEIs) in many dimensions. In demographic variables, EIs are more likely male, who have had a career in academic institutions. They were actively involved in technology development with grants used to validate the commercial potential of the technology and in a large number of contacts in the industry. They were also involved in business activities outside of their employment that required technical skills. EIs who had commercialization support from their regions were more likely to become entrepreneurs. The ones who exhibited innovative behavior were also more likely to become entrepreneurs. We used these differences to predict inventors who were more likely to become entrepreneurs using these demographic, personal characteristics, situational and attitudinal descriptors using discriminant functions with very good success. The model to forecast the inventors’ likely path to commercializing their technologies can have practical implications for universities and public policy-makers.