Comparison With Other Approaches
The Evidence Network's methodology is the key component of
overall evaluations of innovation enablers because it provides for
direct evidence of innovation enabler impact on client or member
firms - evidence that innovation enablers are fulfilling their
There are, however, other ways to evaluate innovation
enablers. Innovation enablers themselves or consultants
acting on their behalf may undertake client satisfaction surveys or
may collect data on capacity measures such as funds raised, funds
dispersed, number of members, number of clients, and number and
types of services. Innovation enablers that provide
technology-related services may measure publications, citations, or
patents. Enablers may also use approaches such as Kaplan and
Norton's Balanced Scorecard that measure organizational
Academics also contribute to the evaluation of innovation
enabler performance. Using a case study approach researchers
have evaluated the impact of organizations such as SEMATECH
(Grindley, Mowery & Silverman, 1994)1 , and using
economic approaches researchers have measured the performance, or
effect of the activities of the US Advanced Technology Program
(Feldman & Kelley, 2006 2; Sakakibara &
Branstetter, 2003 3), the Advanced Technology
Development Center of the Georgia Institute of Technology
(Rothaermel & Thursby, 2005 4 ), US regional
institutes (McEvily & Zaheer, 1999 5 ),
Japanese research consortia (Branstetter Sakakibara, 2002
6), Canadian industry associations (Dalziel, 2006
7 ), US small firm manufacturing networks (Human
& Provan, 1997 8 ), Swedish (Löfsten &
Lindelöf, 2002 9) and Chinese (Yu & Heshmati,
2007 10) science parks, US (Di Gregorio & Shane,
2003 11) and European (Kaufmann & Tödtling,
2001 12 ) university technology transfer offices,
and international standards organizations (Rosenkopf, Metiu &
George, 2001 13; Rysman & Simcoe 2006
While these methods contribute a great deal to our understanding
of the impact of innovation enablers, The Evidence Network's
approach is unique in its ability to provide evidence of innovation
enabler impact that is both reliable and systematic while at the
same time providing in-depth data on the quality of organizational
processes. Our method is generalizable across all types of
innovation enablers and provides timely feedback using scales that
are suitable for recurring assessments. As shown in the
following table, The Evidence Network's approach is the only
approach that achieves all of these benefits.
- Grindley, P. Mowery, D.C., & Silverman, B.
1994. SEMATECH and collaborative research design:
Lessons in the design of high-technology consortia. Journal
of Policy Analysis and Management, 13: 723-758.
- Feldman, M.P. & Kelley, M.R. 2006. The ex-ante
assessment of knowledge spillovers: Government R&D
Policy, economic incentives and private firm behavior.
Research Policy, 35: 1509-1521.
- Sakakibara, M. & Branstetter, L.G. 2003.
Measuring the impact of US research consortia. Managerial and
Decision Economics, 24: 51-69.
- Rothaermel, F.T. & Thursy, M. 2005.
University-incubator firm knowledge flows: assessing their
impact on incubator firm performance. Research Policy,
- McEvily, B. & Zaheer, A. 1999. Bridging
ties: A source of firm heterogeneity in competitive
capabilities. Strategic Management Journal, 20:
- Branstetter, L.G. & Sakakibara, M. 2002. When
do research consortia work well and why? Evidence from
Japanese panel data. American Economic Review, 92:
- Dalziel, M. 2006. The impact of industry
associations. Innovation: Management, Policy &
Practice, 8: 296-306.
- Human, S.E. & Provan, K.G. 1997. An emergent
theory of structure and outcomes in small-firm strategic
manufacturing networks. Academy of Management Journal,
- Löfsten, H. & Lindelöf, P. 2002.
Science parks and the growth of new technology-based
firms-academic-industry links, innovation and markets.
Research Policy, 31: 859-876.
- Yu, Z. & Heshmati, A. 2007. Growth and
performance of science parks in China. In Heshmati, Almas
(Ed.) Recent Developments in the Chinese Economy. pp.
- Di Gregorio, D. & Shane, S. 2003. Why do some
universities generate more start-ups than others? Research
Policy, 32: 209-227.
- Kaufmann, A. & Tödtling, F. 2001.
Science-industry interaction in the process of innovation:
The importance of boundary-crossing between systems. Research
Policy, 30: 791-804.
- Rosenkopf, L., Metiu, A. & George, V.P. 2001.
From the bottom up? Technical committee activity and alliance
formation. Administrative Science Quarterly, 46:
- Rysman, M. & Simcoe, T. 2006. Patents and the
performance of voluntary standard setting organizations. NET
Institute Working Paper No. 05-22. Available at SSRN:
http://ssrn.com/abstract=851245 [Accessed January 12th,