Knowledge creation and innovation in the Hoosier state.

Author:Zheng, Ping
 
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Does knowledge production at institutions like universities or research and development (R&D) facilities lead to innovation? Does it lead to more innovative activities the closer one is to those knowledge anchor institutions?

It is often suggested that the intensity of knowledge production and its related innovative activities depends upon the geographic proximity of knowledge and information sources. On the other hand, with the rapid development of communication technologies, the importance of geographic proximity on innovative outcomes would be greatly reduced.

Does distance matter? This article proposes a measure for the importance of proximity to knowledge creation and explains how it may be useful for business and macroeconomic policies that relate to technological innovations. We use this measure to see if there is a geographic link between knowledge creation and innovation for Hoosiers.

Review on Knowledge and Proximity

Laboratories and universities that produce knowledge are tangible: One can count the number of scientists in white lab coats, the number of microscopes or length of a linear accelerator. One cannot see, much less count, the flow of knowledge. That said, the diffusion of knowledge is important for creating new products or services. Thus, academic researchers have been interested in measuring knowledge production and diffusion. Many of these researchers have used the number or rate of patents as a metric for knowledge creation (for example, Bontazzi & Peri, 2003; Jaffe, 1986; Jaffe et al., 1993).

According to Krugman (1991), knowledge flows are invisible: "They leave no paper trail by which they may be measured and tracked, and there is nothing to prevent theorists from assuming anything about them that she likes..." Tracking these invisible knowledge flows was pioneered by Jaffe (1986). Patent citations are something of a paper trail for knowledge spillovers. But using patent citations as a gauge to measure the spillover from creating knowledge and innovation is not perfect: "Only a small fraction of research output is ever patented. In particular, much of the results of very basic research cannot be patented" (Jaffe et al., 1993).

Proximity is also critical to the notion of knowledge spillovers. Many researchers explicitly incorporate geographic proximity into measuring the impact of knowledge creation sources. Knowledge is embedded in people and, as a result, the face-to-face interaction of people is needed in the exchange and diffusion of knowledge, for example, within professional associations and communities (Bontazzi & Peri, 2003; Pond et al., 2009).

There are several ways universities as knowledge producers can measure their potential or actual effect on innovation.

  1. The number of STEM degrees an institution graduates. While many, if not most, of the graduates would get jobs far removed from the degree-granting university, the number of STEM graduates would reflect the STEM programs and faculty that would diffuse knowledge locally.

  2. The number of patents that the university itself files.

  3. The number of technology startups by faculty or students that can be attributed to the university. Many large universities support innovation centers and technology parks.

  4. The level of research and development funding a university receives to conduct scientific exploration. University R&D expenditures may also help to develop collateral businesses, collaborative networks and supply chains in the surrounding area.

Given that we are attempting to determine knowledge spillovers, university R&D expenditures may be the most direct and comprehensive metric for determining the level of innovative activities in a locale. The question then becomes, how far away are the effects of R&D expenditures felt? University knowledge creation may also spill over to neighboring counties or regions. Many researchers attempted to quantify such knowledge spillovers by constructing different measures that attenuate the R&D effects as the distance from the research university and its neighborhoods increases (Anselin et al., 1997, 2000; Audretsch et al., 2005; Fischer & Varga, 2003; Woodward et al., 2006).

Anselin and colleagues (1997) find that university R&D spillovers positively affect patent and innovation creation in the regions within the university's proximity extending over 50 miles. Woodward and colleagues (2006) suggest that the optimum radius for the effect of university R&D on new plant formation is 60 miles. The effect of distance, however, may also depend on the type of industry.

Empirical Analysis and Findings

The critical core assumption of the causal relationship is that R&D produces knowledge and knowledge promotes innovation and that innovative activities culminate in creating patents.

Thus, in our exploration of knowledge spillovers in Indiana, we use university R&D expenditures as the foundation for our metric of knowledge spillovers and use a decay function to reflect the diminishing influence of those...

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