Technology entrepreneurship eGosystem: a collective intelligence perspective to drive knowledge-based innovation

Purpose – To be successful, the innovation and entrepreneurship processes require a systemic and dynamic search, evaluation and matching of purposeful knowledge, expertise and tangible assets. In this vein, the concept of ecosystem has been largely adopted at macro and organizational level to indicate the network of complementary actors needed by one company to succeed in this endeavor. This paper aims to define an individual perspective of innovation ecosystem and propose a model to drive the creation of entrepreneur-centric ecosystems aimed to support a more effective “idea-to-venture” process. Design/methodology/approach – The review of relevant literature and the analysis of international initiatives has been used to identify the main theoretical constituents of the study. A design science approach has been thus adopted to conceptualize and define the components of the model through the phases of problem identification, objectives definition, artifact development, demonstration, evaluation and research communication. The model has been submitted to a preliminary face-validity test with experts in the areas of entrepreneurship and collective intelligence. Originality/value – The paper presents an innovative application of the collective intelligence paradigm to design technology entrepreneurship ecosystems which are: a) context-independent, i.e. virtually global; b) specific, i.e. tailored to given technology domains and individual needs; and c) dynamic, i.e. able to gather relevant knowledge needed for the specific phase of the entrepreneurial process. The collective intelligence perspective allows to capitalize distributed ideas, knowledge, and competencies to take better decisions and actions respect to the case in which decisions and actions are taken by individuals alone. Practical implications – The model can contribute to maximize the incubation, growth and sustainability of entrepreneurial initiatives thanks to a better gathering of critical resources and knowledge which is dispersed in a large network of actors. In particular, the model can support the design and implementation of technology entrepreneurship ecosystems tailored to the real needs of a specific entrepreneur as well as support more effective entrepreneurial processes within corporations and organizations in general.