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Solving the knowledge filter puzzle: absorptive capacity, entrepreneurship and regional development

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Abstract

New growth theory addresses the important role of knowledge in regional economic growth. However, knowledge is not always commercially exploited. The obstacles preventing knowledge commercialization are known as the knowledge filter. The literature has identified entrepreneurship as a mechanism of overcoming the knowledge filter. This article further argues that absorptive capacity is another effective factor that can solve the knowledge filter puzzle. To test this hypothesis, we introduce a new approach to measuring regional absorptive capacity and, via exploratory factor analysis, identifies two types of absorptive capacity: cognitive capacity and technical capacity. Multivariate analysis finds a significant moderating role of cognitive capacity (and to a lesser extent technical capacity) in the impact of knowledge on regional economic performance and therefore supports absorptive capacity as an effective mechanism for the penetration of the knowledge filter. The empirical results also provide additional evidence on the role of entrepreneurship in commercializing new knowledge and penetrating the knowledge filter.

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Notes

  1. A full regression model with interaction terms is generally in the format of: A (knowledge) + B (entrepreneurship, absorptive capacity) + A × B. We use only A + A × B. We did not include B, first, because in theory we believe the effect of entrepreneurship and absorptive capacity are basically moderating effects between new knowledge and productivity, as discussed in theoretical section. Empirically speaking, it is also problematic to include B in our case. Perhaps not surprisingly, our measures of entrepreneurship and absorptive capacity (i.e., B) are highly correlated with our measures of knowledge (i.e., A), as shown in the correlation table later. It would cause multicollinearity if B is also included in the regression models.

  2. To execute this step, employment data by industry and by MSA are needed. Such data provided by the US County Business Patterns (CBP) include many suppressed data due to confidentiality concerns, giving only a range of the employment size in an industry. We unsuppressed the data by using the mid-point values. For instance, for the range of “100 to 249 employees,” we used 175 employees; for the largest range “100,000 or more employees,” we used 175,000 employees.

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Acknowledgments

This research is funded by the Early Career Grant Scheme of the Regional Studies Association (Recipient: Haifeng Qian).

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Authors and Affiliations

  1. School of Urban and Regional Planning, University of Iowa, 338 Jessup Hall, Iowa City, IA, 52242, USA

    Haifeng Qian

  2. School of Industrial Management, Korean University of Technology and Education, 415 Budaedong Seobukgu, Cheonan City, Chungnam, 31079, South Korea

    Hyejin Jung

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  1. Haifeng Qian
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Correspondence to Haifeng Qian.

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Qian, H., Jung, H. Solving the knowledge filter puzzle: absorptive capacity, entrepreneurship and regional development. Small Bus Econ 48, 99–114 (2017). https://doi.org/10.1007/s11187-016-9769-y

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