A roadmap for systematically identifying opportunities in ecosystems using scientific publications data

Abstract

Opportunity identification is a continuous process in ecosystems. However, ambiguities and challenges associated with knowledge exploration and exploitation can retard opportunity recognition processes. This in turn may culminate in excessive expenditure of resources or loss of latent opportunities. The present study adopts an analytical approach and proposes a methodological roadmap that utilizes scientometric and text mining techniques. The roadmap uses data from Web of Science as input, and generates insights that support decision-making about resource saving, strategic planning, investment, and policymaking. Our roadmap extends methods used in studying ecosystems by combining existing and novel techniques in data analytics. Using Python and VOSViewer, we show an exemplary application of the new roadmap, framed in the context of the Nordic countries' renewable energy ecosystem.