Managing open innovation project risks based on a social network analysis perspective

• Autor(a) principal: Nunes, Marco
• Data de Publicação: 2020
• Outros Autores: Abreu, António
• Tipo de documento: Artigo
• Idioma: eng
• Título da fonte: Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
• Texto Completo: http://hdl.handle.net/10362/120350
• topic: Collaborative networks; Open innovation; Organizational competencies; Predictive model; Project critical success factors; Project lifecycle; Project management; Project outcome likelihood; Risk management; Social network analysis; Sustainability; Geography, Planning and Development; Renewable Energy, Sustainability and the Environment; Environmental Science (miscellaneous); Energy Engineering and Power Technology; Management, Monitoring, Policy and Law; SDG 7 - Affordable and Clean Energy

In today's business environment, it is often argued, that if organizations want to achieve a sustainable competitive advantage, they must be able to innovate, so that they can meet complex market demands as they deliver products, solutions, or services. However, organizations alone do not always have the necessary resources (brilliant minds, technologies, know-how, and so on) to match those market demands. To overcome this constraint, organizations usually engage in collaborative network models-such as the open innovation model-with other business partners, public institutions, universities, and development centers. Nonetheless, it is frequently argued that the lack of models that support such collaborative models is still perceived as a major constraint for organizations to more frequently engage in it. In this work, a heuristic model is proposed, to provide support in managing open innovation projects, by, first, identifying project collaborative critical success factors (CSFs) analyzing four interactive collaborative dimensions (4-ICD) that usually occur in such projects-(1) key project organization communication and insight degree, (2) organizational control degree, (3) project information dependency degree, (3) and (4) feedback readiness degree-and, second, using those identified CSFs to estimate the outcome likelihood (success, or failure) of ongoing open innovation projects.