Advancing Concepts and Models for Measuring Innovation Proceedings of a Workshop (2017) / Chapter Skim
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4 The Role of Individuals (and Networks of Individuals) in Innovation
4 The Role of Individuals (and Networks of Individuals) in Innovation
Pages 47-60
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From page 47... ...
She commented that entrepreneurship is not a destination, but a step in a longer career lifecycle, and thus the effect of entrepreneurial firm fates on individual career lifecycles needs more attention if it is to be fully understood. In her view, future research would benefit from a focus on human capital markets, which requires combining demand and supply factors to examine life-cycle choices and also considering selection effects as they relate to optimal allocation and reallocation of talent.
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From page 48... ...
For example, she queried, how does family composi TABLE 4-1 Factors Affecting Mobility and Entrepreneurship in Human Capital Markets Demand Side Supply Side Protection Mechanisms Mobility Costs • Noncompetes • Family ties • IP protection • Location preferences • Health care and other benefits Collusion/Thin Markets Information Asymmetries Competition versus cooperation in Knowledge contexts -- entrepreneurship firm interactions by users, employees, and academies Firm Specificity/Complementarities Individual Preferences for Job Attributes • Regional policy impacting • Security versus growth/risk knowledge flows preferences • Social support programs Social Complexity Individual Preferences for/against • Team-embedded knowledge Entrepreneurship • Technological complexity • Taste for autonomy, mastery, • Regional clustering of knowledge purpose SOURCE: Workshop presentation by Rajshree Agarwal, May 19, 2016.
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From page 49... ...
Agarwal argued that mobility, entrepreneurship, and innovation datasets need to be linked to study how entrepreneurship and innovation relate to career lifecycles. Figure 4-1 provides an example of the kind of linkages she said would be helpful in answering a range of important questions, such as: • What types of bias impact patent-based measures of mobility?
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From page 50... ...
• Advances in machine learning and natural language processing are useful, though they need thoughtful application. • Newly available data and tools provide opportunity to advance understanding of innovation.
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From page 51... ...
The advance by him and his collaborators came with the realization that an instrument could be developed using a principal components analysis to break out two components of innovative activity: exploitation and exploration. Exploitation captures portfolio measures of firms patenting in known classes, staying close to their previous technological proximity (and inventors are getting older)
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From page 52... ...
newly available data and tools provide opportunity -- for example, studying real-time inventor networks or exploiting natural language processing to see parts of the innovation economy that are not visible through patenting -- particularly when analyzed in collaboration with computer scientists. Alfonso Gambardella (Bocconi University)
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From page 53... ...
, in the sense of accepting lower paying jobs that promise scientific work, although to a varied extent (Sauermann and Roach, 2014)
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From page 54... ...
Scenario-based experiments -- for example, asking informed parties how they would respond under different scenarios -- and field experiments are also needed. MEASURING FLOWS OF HUMAN CAPITAL TO FIRMS AND THE ROLE OF UNIVERSITY ADMINISTRATIVE DATA Paula Stephan (Georgia State University)
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From page 55... ...
Stephan also noted the importance in the global economy of measuring the international mobility of highly trained individuals. Research suggests that internationally mobile scientists and engineers contribute disproportionately to innovation.
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From page 56... ...
Additionally, mobile scientists were found to be more likely to establish international links, have links with larger numbers of countries, and exhibit superior performance on international collaborations. They were also more productive than nonmobile scientists and returnees, and results persist even after instrumenting for mobility.
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From page 57... ...
Stephan closed by noting that surveys can take the research into international mobility of scientists and engineers only so far. She encouraged NCSES to continue to work with agencies in other countries to develop systematic ways to collect data providing consistent longitudinal information about internationally mobile scientists and engineers.
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From page 58... ...
One question that the IRIS team has asked is how to use the expansive set of university administrative data to explore the relationships between where people are situated in physical space and how networks evolve. Using administrative directory data to position every investigator in a two-building space, they mapped out how proximate they were to one another and calculated what was called a functional zone.
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From page 59... ...
One benefit of taking on these tasks as a community, he asserted, is to streamline linkages, systematize data use, and broker between data producers and parts of the federal statistical and science system to maximize the value of investments in data. One of the greatest challenges to creative data linking is the lack of stable individual identifiers outside of the context of the Census Bureau's Protected Identification Keys (PIKs)
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