Description
Relevance is a central concern in information science. Innovation is central to theories of economic competitiveness and prosperity. Yet, like relevance, innovation is difficult to categorize and measure.Widely used metrics for innovation are acknowledged to be problematic. Although acknowledged to have many limitations, patent applications, for example, are frequently used as a proxy measure for innovation when describing a particular firm, industry, or region. Alternative metrics for innovation have been widely used, such as investment in research and development. Newer measures are emerging, such as measures for assessing eco-innovation. Relevance has been formulated in a similarly wide variety of ways — objective relevance, subjective relevance, situational relevance — to name only a few. Widely used relevance metrics are likewise acknowledged to be problematic.
This presentation will explore the possibility that conceptions of innovation and relevance as they have been formulated in the economic and information science literature respectively share a central theoretical challenge. It will suggest that a theory of the problems presented by the concepts in their respective fields can be more clearly articulated by contextualizing theories of relevance in information science with theories of innovation in the business and economic literature.
| Period | Sep 29 2023 |
|---|---|
| Event title | Information Access Seminar |
| Event type | Seminar |
| Organizer | UC Berkeley School of Information |
| Location | Berkeley, United States, CaliforniaShow on map |
| Degree of Recognition | Local |