@article {1214,
	title = {Editorial: Insights (February 2019)},
	journal = {Technology Innovation Management Review},
	volume = {9},
	year = {2019},
	month = {02/2019},
	pages = {3-4},
	publisher = {Talent First Network},
	address = {Ottawa},
	keywords = {digital innovation, digital transformation, innovation, innovation ecosystems, management, sharing economy, technology},
	issn = {1927-0321},
	doi = {http://doi.org/10.22215/timreview/1214},
	url = {https://timreview.ca/article/1214},
	author = {Chris McPhee}
}
@article {1218,
	title = {Understanding Digital Innovation from a Layered Architectural Perspective},
	journal = {Technology Innovation Management Review},
	volume = {9},
	year = {2019},
	month = {02/2019},
	pages = {51-63},
	publisher = {Talent First Network},
	address = {Ottawa},
	abstract = {Managing successful digital innovation processes is a challenging task, especially when it involves heterogeneous actors with different sets of knowledge. By gaining a better understanding of how different architectural layers of digital technology interplay with digital innovation, we can be better prepared for managing the complex and messy processes that often arise when working with digital innovation. In this article, we therefore ask: How does the layered architecture of digital technology interplay with digital innovation processes? A case study approach was selected to studied events involving multiple actors in an innovation and development project called the Smart Lock project. The theoretical basis for our study is digital innovation from the perspective of knowledge exchange and relationships. A temporal bracketing strategy was used to support a process analysis of the case data. The article primarily contributes to the body of research concerning digital innovation and provides an example to practitioners of how digital innovation processes can be coordinated and managed based on the innovation at hand.},
	keywords = {collaborative innovation, concept development, digital innovation, digital technology, innovation process},
	issn = {1927-0321},
	doi = {http://doi.org/10.22215/timreview/1218},
	url = {https://timreview.ca/article/1218},
	author = {Jesper Lund and Esbj{\"o}rn Ebbesson}
}
@article {1143,
	title = {Data Science as an Innovation Challenge: From Big Data to Value Proposition},
	journal = {Technology Innovation Management Review},
	volume = {8},
	year = {2018},
	month = {03/2018},
	pages = {16-25},
	publisher = {Talent First Network},
	address = {Ottawa},
	abstract = {Analyzing {\textquotedblleft}big data{\textquotedblright} holds huge potential for generating business value. The ongoing advancement of tools and technology over recent years has created a new ecosystem full of opportunities for data-driven innovation. However, as the amount of available data rises to new heights, so too does complexity. Organizations are challenged to create the right contexts, by shaping interfaces and processes, and by asking the right questions to guide the data analysis. Lifting the innovation potential requires teaming and focus to efficiently assign available resources to the most promising initiatives. With reference to the innovation process, this article will concentrate on establishing a process for analytics projects from first ideas to realization (in most cases: a running application). The question we tackle is: what can the practical discourse on big data and analytics learn from innovation management? The insights presented in this article are built on our practical experiences in working with various clients. We will classify analytics projects as well as discuss common innovation barriers along this process. },
	keywords = {analytics, big data, digital innovation, idea generation, innovation process},
	issn = {1927-0321},
	doi = {http://doi.org/10.22215/timreview/1143},
	url = {http://timreview.ca/article/1143},
	author = {Victoria Kayser and Bastian Nehrke and Damir Zubovic}
}
