Advancing Concepts and Models for Measuring Innovation Proceedings of a Workshop (2017) / Chapter Skim
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8 Key Themes and Possible Next Steps
8 Key Themes and Possible Next Steps
Pages 99-106
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From page 99... ...
measures and datasets changing the understanding of innovation? Stern noted that an objective of the workshop organizing committee was to envision how the range of measures could potentially be improved and expanded to more fully capture, on a reliable basis, aspects of innovation processes that are currently missed or not completely measured.
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From page 100... ...
termed the "dark matter" -- aspects of innovation that are not measured and, consequently, not well understood. Over the course of the presentations, Stern observed, it became clear that shedding light on this dark matter will entail individual and organizational initiatives on domains outside the current scope of the Oslo Manual and the CIS upon which it is based.
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From page 101... ...
data collection and data organization, as well as what measurements based on those data will be illuminating. Subsequently, when measurements are used in research, a feedback mechanism is created that further shapes the framework and helps to identify data and indicator gaps that, if filled, could help answer key questions about the pace, location, and nature of innovation activity (Hall and Jaffe, 2012)
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From page 102... ...
To portray innovation fully, data systems should be capable of detecting knowledge linkages between people and companies -- and business and household interactions generally -- over time (as noted by Javier Miranda, Chapter 3) , and the division of labor, which means that people engaged in idea development are often different than those commercializing the innovations (Wesley Cohen and Ashish Arora, Chapter 3)
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From page 103... ...
Services and experiences increasingly dominate value-added and employment in the United States and other advanced economies, they pointed out, but there is still a manufacturing orientation in many measures of innovation. Martin noted, for example, that if more had been known about the characteristics of innovation in the financial sector, policy makers and researchers would have been better placed to anticipate the events leading to the 2007 crisis.
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From page 104... ...
One example among the many kinds of new data that will aid a greater understanding of innovation are those tracking angel funding and crowd funding, but currently, the data are still not sufficiently detailed and available to enable sustained high-quality research on new innovation funding. Regarding what has been learned and continuing gaps, Stern observed that researchers are able to measure some aspects of innovation extremely well.
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From page 105... ...
Stern described the following areas for future research identified by workshop participants as key to shedding light on some of the innovation "dark matter": • The division of innovative labor: Research by Cohen, Arora, and others is demonstrating that a surprisingly high fraction of important innovations come from outside the firm, albeit some times cooperatively, Stern said. The linkages among innovating individuals and organizations need to be better understood.
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From page 106... ...
The Census Bureau's Business Dynamics Statistics group has done pioneering work to reveal the analogous skewedness of job creation and destruction, firm survival, and other areas. Stern suggested that this work might provide a blueprint for further work on the topic.
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