@article {1298,
	title = {Editorial: Insights (January 2020)},
	journal = {Technology Innovation Management Review},
	volume = {10},
	year = {2020},
	month = {01/2020},
	pages = {3-4},
	publisher = {Talent First Network},
	chapter = {3},
	address = {Ottawa},
	keywords = {AI, artificial intelligence, B2B sales, big data, business-to-business sales, data-based value, digital solutions, ecosystem, ecosystems, Ethics, Gujarat State, Indian IT industry, innovation, IT clusters, Knowledge Innovation clusters, Networks Analysis, regional development, Roboethics, Smart robot, strategy, Systematic literature review, technology, value capture, value creation, value sales},
	issn = {1927-0321},
	doi = {http://doi.org/10.22215/timreview/1298},
	url = {timreview.ca/article/1298},
	author = {Stoyan Tanev and Gregory Sandstrom}
}
@article {1404,
	title = {Editorial: Insights (November 2020)},
	journal = {Technology Innovation Management Review},
	volume = {10},
	year = {2020},
	month = {11/2020},
	pages = {3-4},
	publisher = {Talent First Network},
	chapter = {3},
	address = {Ottawa},
	keywords = {AI innovation and maturity, and diaspora entrepreneurs., artificial intelligence, confidential information, criminal law, digitally enhanced teamwork, economic espionage, entrepreneurship, health technology, immigrants, Innovation management, living labs, migration, Multidisciplinarity, situated practice, small and medium-sized enterprises, stakeholder participation, sustainability, trade secrets, transnationals},
	issn = {1927-0321},
	doi = {http://doi.org/10.22215/timreview/1404},
	url = {timreview.ca/article/1404},
	author = {Stoyan Tanev and Gregory Sandstrom}
}
@article {1278,
	title = {Editorial: Insights (November 2019)},
	journal = {Technology Innovation Management Review},
	volume = {9},
	year = {2019},
	month = {11/2019},
	pages = {3-4},
	publisher = {Talent First Network},
	chapter = {3},
	address = {Ottawa},
	keywords = {artificial intelligence, competitive advantage, cybersecurity, deep learning, Deepfake, design rules, digitalization, entrepreneurial ecosystems, entrepreneurial university, entrepreneurship, entrepreneurship education, fake news, innovation, international entrepreneurship, leadership, Learning Capabilities, marketing, motivation, new venture teams, quadruple helix, sanctions, SMEs, teamwork, triple helix, university business incubation},
	issn = {1927-0321},
	doi = {http://doi.org/10.22215/timreview/1278},
	url = {timreview.ca/article/1278},
	author = {Stoyan Tanev and Gregory Sandstrom}
}
@article {1082,
	title = {Using Artificial Intelligence and Web Media Data to Evaluate the Growth Potential of Companies in Emerging Industry Sectors},
	journal = {Technology Innovation Management Review},
	volume = {7},
	year = {2017},
	month = {06/2017},
	pages = {25-37},
	publisher = {Talent First Network},
	address = {Ottawa},
	abstract = {In this article, we describe our efforts to adapt and validate a web search and analytics tool {\textendash} the Gnowit Cognitive Insight Engine {\textendash} to evaluate the growth and competitive potential of new technology startups and existing firms in the newly emerging precision medicine sector. The results are based on two different search ontologies and two different samples of firms. The first sample includes established drug companies operating in the precision medicine field and was used to estimate the relationship between the firms{\textquoteright} innovativeness and the extent of online discussions focusing on their potential growth. The second sample includes new technology firms in the same sector. The firms in the second sample were used as test cases to determine whether their growth-related web search scores would relate to the degree of their innovativeness. The second part of the study applied the same methodology to the real-time monitoring of the firms{\textquoteright} competitive actions. In our findings, we see that our methodology reveals a moderate degree of correlation between the Insight Engine{\textquoteright}s algorithmically computed relevance scores and independent measures of innovation potential. The existence of such correlations invites future work in attempting to analyze company growth potential using techniques founded in web content scraping, natural language processing, and machine learning.},
	keywords = {analytics, artificial intelligence, business intelligence, entrepreneurship, online textual data, precision medicine sector, startup growth potential},
	issn = {1927-0321},
	doi = {http://doi.org/10.22215/timreview/1082},
	url = {http://timreview.ca/article/1082},
	author = {Andrew Droll and Shahzad Khan and Ehsanullah Ekhlas and Stoyan Tanev}
}
