Harnessing success determinants of university technology licensing performance
This presentation is the property of its rightful owner.
Sponsored Links
1 / 23

Harnessing Success: Determinants of University Technology Licensing Performance PowerPoint PPT Presentation


  • 67 Views
  • Uploaded on
  • Presentation posted in: General

Harnessing Success: Determinants of University Technology Licensing Performance. Sharon Belenzon Nuffield College, Oxford University Mark Schankerman London School of Economics and CEPR Presentation for Lausanne September 2006. Introduction. Many studies find that private universities

Download Presentation

Harnessing Success: Determinants of University Technology Licensing Performance

An Image/Link below is provided (as is) to download presentation

Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author.While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server.


- - - - - - - - - - - - - - - - - - - - - - - - - - E N D - - - - - - - - - - - - - - - - - - - - - - - - - -

Presentation Transcript


Harnessing success determinants of university technology licensing performance

Harnessing Success: Determinants of University Technology Licensing Performance

Sharon Belenzon

Nuffield College, Oxford University

Mark Schankerman

London School of Economics and CEPR

Presentation for Lausanne

September 2006


Introduction

Introduction

  • Many studies find that private universities

    outperform public ones in technology transfer

    (Thursby and Kemp, 2002; Siegel, Waldman and Link, 2003)

  • Royalty incentives have more effect in private universities (Lach and Schankerman, 2003)

  • Why? The “gatekeeper” effect can explain both findings: in the U.S. the TLO is monopsonist over inventions, thus its effectiveness has both direct and indirect effects.

  • This paper focuses on what makes TLO’s in private universities more effective, on average.


Key findings

Key findings

  • Private universities are much more likely to use high-powered incentives within the TLO.

  • Private universities, on average, have higher income per license, however, this is entirely explained by their use of such incentives.

  • Moreover, public universities are much more likely to care about local development objectives and face stronger government constraints on their licensing activity – these are found to be “costly” in terms of foregone license income.

    Hence – we may be able to generate “private” performance in public institutions using these policy instruments.


Impact of incentives objectives and government constraints on tlo performance

Impact of Incentives, Objectives andGovernment Constraints on TLO Performance

  • whether the university TLO uses any form of performance-based pay (“high-powered” incentives): merit pay or bonus pay.

    2. the importance that the university TLO attaches to local development objectives: measured by low, medium and high importance

    3. the severity of government constraints on licensing (formal or informal): measured by number of “important” constraints


An agency model of the tlo with incentives and local development objectives

An Agency Model of the TLO with Incentivesand Local Development Objectives

TLO licenses inventions in national or local market.

Unit cost:

Unit payoff:

= fraction of effort devoted to licensing in the local market

Quadratic effort costs:

The TLO compensates the worker in two ways: a fixed-wage and a performance-based pay (in the form of a constant fraction of licensing revenues).


Harnessing success determinants of university technology licensing performance

There is a divergence of interest between the TLO and the worker. The worker cares only about her share of license income net of effort costs. The TLO cares about total license income and license income in local market. Worker:TLO:

An Agency Model of the TLO with Incentivesand Local Development Objectives, cont’d


Harnessing success determinants of university technology licensing performance

Effort cost to the worker

An Agency Model of the TLO with Incentivesand Local Development Objectives, cont’d

Suppose the TLO can contract on the worker’s allocation of effort. The first best efforts solves:

First-best level of effort:


Harnessing success determinants of university technology licensing performance

An Agency Model of the TLO with Incentivesand Local Development Objectives, cont’d

Suppose the TLO cannot contract on the worker’s allocation of effort.

Second stage (worker’s choice):

Second stage (TLO contract):


Harnessing success determinants of university technology licensing performance

where

An Agency Model of the TLO with Incentivesand Local Development Objectives, cont’d

Assume there is a fixed cost of adopting high powered incentives, F.

TLO adopts high-powered incentives if gains of adoption exceed F:

Can show that

Prediction 1: Universities that care more about local development objectives, and those that are more constrained, are less likely to adopt incentive pay.


Harnessing success determinants of university technology licensing performance

where

An Agency Model of the TLO with Incentivesand Local Development Objectives, cont’d

We observe only total licensing income, R. The effect of adopting incentive pay on licensing income is

One can show

Prediction 2: Universities that care more about local development objectives, and those that are more constrained, generate less licensing income, other things equal.

Prediction 3: Universities which use incentive pay generate greater licensing income, other things equal.


Data description

Data description


Data description1

Data description


Data description2

Data description


Parametric estimation performance based pay

Parametric estimation: Performance-Based Pay


Harnessing success determinants of university technology licensing performance

Key Findings on Adoption of Incentive Pay

  • The effect of private ownership is positive and significant -- moving from public to private doubles the probability of using bonus pay (from the mean of 35 to 71 percent).

  • With controls for heterogeneity, we find that the use of incentives is also negatively related to local development objectives and to the number of effectiveconstraints, but the latter in statistically insignificant.

  • It is difficult to distinguish between the effect of private ownership and the number of constraints because they are highly, negatively correlated

  • When dropping private ownership, the coefficient on the number of constraints becomes more negative and statistically significant.


Parametric estimation licensing income

Parametric estimation: licensing income


Harnessing success determinants of university technology licensing performance

License income: Additional control variables

(3)(4) (5)(6)


Harnessing success determinants of university technology licensing performance

Key Findings on Income per License:

  • Private ownership has no independent effect on licensing performance, once we control for the adoption of incentive pay (yet, private ownership has a strong positive effect on the adoption of performance-based pay).

  • Using performance-based pay is associated with about 30-45% more income per license. As with royalty incentives for research scientists, incentives for TLO licensing activities are also important.

  • Having strong local development objectives is associated with about 30% less income per license.

  • Each “important” government constraint is associated with 17% less income per license (average number of constraints reported as “important” is 1.5).

    These findings are robust to using non-parametric estimation methods.


Parametric estimation licenses executed

Parametric estimation: licenses executed


Harnessing success determinants of university technology licensing performance

Licenses executed: Additional control variables

(3)(4) (5)(6)


Harnessing success determinants of university technology licensing performance

Key Findings on the Number of Licenses:

  • Incentive pay does not affect the number of licenses executed per invention. With non-parametric estimation, we find a positive effect of about 10%. This is weaker than for license income because numbers are easier to monitor by managers than income per license (“what might have been”).

  • Having strong local development objectives is associated with 30% more licenses per invention. With non-parametric estimation methods, we find no effect of such objectives.

  • Having strong government constraints have no significant effect on the number of licenses per invention.


Nonparametric estimation licensing income and licenses executed

Nonparametric estimation: licensing income and licenses executed

Bootstrapped standard errors are in brackets. *, **, *** denote statistical significance at the 1, 5 and 10 percent levels, respectively.

Obs=1 is the number of observations for which the "treatment" applies (e.g., the universities that have bonus pay). Obs=0 is the number of observations for the "untreated" universities. In the second stage, observations are weighed using the kernel method.


Summary impact of incentives objectives and government constraints on total license income

Summary: Impact of Incentives, Objectives and Government Constraints on Total License Income

  • Using bonuses raises total license income by about 30-50%. The full effect is due to increasing the quality of licenses, not their quantity.

  • Private ownership has no independent effect on licensing performance, once we control for the adoption of incentive pay. Yet, private ownership has a strong positive effect on the use of incentive pay.

  • Strong local development objectives have a net negative effect on total license income: they clearly reduce the value per license, and do not have a robust positive effect on the quantity of licenses on inventions.

    4. Strong government constraints reduce total license income. The effect works by reducing the quality of licenses, not their quantity.


  • Login