@article {1415,
	title = {A Roadmap for Systematically Identifying Opportunities in Ecosystems Using Scientific Publications Data},
	journal = {Technology Innovation Management Review},
	volume = {11},
	year = {2021},
	month = {01/2021},
	pages = {34-55},
	publisher = {Talent First Network},
	chapter = {34},
	address = {Ottawa},
	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{\textquoteright} renewable energy ecosystem. },
	keywords = {ecosystem, knowledge, opportunity, roadmap, scientometrics, text mining},
	issn = {1927-0321},
	doi = {http://doi.org/10.22215/timreview/1415},
	url = {timreview.ca/article/1415},
	author = {Behrooz Khademi and Hannele Lampela and Kosmas X. Smyrnios}
}
@article {1253,
	title = {The Ecosystem Knowledge Explorer: A Tool to Systematically Discover External Knowledge},
	journal = {Technology Innovation Management Review},
	volume = {9},
	year = {2019},
	month = {07/2019},
	pages = {28-40},
	publisher = {Talent First Network},
	address = {Ottawa},
	abstract = {It is crucial for any organization to discover knowledge from ecosystem-specific sources of knowledge that are considered external to the organization. Since knowledge exploration is a resource-intensive task for organizations, untimely or excessive knowledge exploration have detrimental impacts on the innovativeness and competitiveness of organizations. The benefits of performance measurement and management tools for knowledge management in organizations have been known for many years now. Therefore, the application of similar tools in ecosystems may enable actors to have access to valuable external knowledge. However, there is a paucity of such tools in management scholarship. The purpose of this study is to bridge this gap by proposing a conceptual tool {\textendash} the Ecosystem Knowledge (EK) Explorer, which generates insightful knowledge for ecosystem actors using codified technical knowledge (e.g., scientific publications and patents). Not only does the EK Explorer reduce the uncertainty and fuzziness of the knowledge exploration phase for ecosystem actors, it also enables them to save resources and have access to strategic knowledge regarding competition, collaboration, technology management, and policy making in ecosystems. Bibliometric analysis, social network analysis, and text mining were used to conceptualize the constructs and measurable variables of the EK Explorer. },
	keywords = {ecosystem, knowledge management, performance measurement, social network analysis, text mining},
	issn = {1927-0321},
	doi = {http://doi.org/10.22215/timreview/1253},
	url = {https://timreview.ca/article/1253},
	author = {Behrooz Khademi}
}
