NIST GCR 02-829
Universities as Research Partners

3. Role of Universities: Reason for Inclusion in Projects

What research role do universities play in ATP-funded projects? At one level, the answer to this question comes from the organizational or administrative role that universities have in various projects. Universities participate either as formal partners or subcontractors in joint venture projects, or as subcontractors in single company applicant projects.

Four of the six groups of contact persons for the survey were asked the reason university subcontractors were selected for their projects. The most frequent response in the case of joint venture projects where a university is only involved as a subcontractor and in the case of single company applicant projects where the university is only involved as a subcontractor was selecting a university subcontractor to gain access to eminent researchers. Joint venture projects in which the university is only involved as a research partner reported that the university was invited to participate most commonly because of previous research interactions with other members of the joint venture. And, finally, the dominant response when universities are involved in a joint venture project as research partners and as subcontractors was that each was selected based on their overall research reputation.

The research role played by universities was explored by asking each contact person to respond to the following statement using the 7-point Likert scale noted below:

Respondents in general disagreed with this statement (e.g., responded to the statement with a 1 or a 2). Those who agreed with the statement (e.g., responded to the statement with a 6 or a 7) most frequently were involved in single company applicant projects with no university involvement. ⁽²¹⁾ To examine this issue of the research role that universities play in ATP-funded projects more systematically, ordered probit models were estimated to explain inter-project differences in responses by the contact person to the statement above. Held constant in these models are several characteristics of the project as determined from ATP information about the project and from responses to survey questions. The estimates are listed in Table 4. ⁽²²⁾

Table 4. Determinants of Difficulty Acquiring Basic Knowledge

Four observations about the ordered probit model estimates in Table 4 seem relevant:

• Respondents with a university participant (as a research partner or as a subcontractor) were more likely to agree that their projects had experienced difficulties acquiring and assimilating basic knowledge necessary for progress toward completion (a relationship opposite to that seen from the descriptive data in Table A4, because now we have controlled for project size, and experience). The university’s presence may create a greater awareness that such difficulties exist.
  
  
• Experience working with a university as a research partner or as a subcontractor is a significant factor in decreasing the difficulty of acquiring and assimilating basic knowledge.
  
  
• Acquisition and assimilation difficulties with basic knowledge decrease slightly as overall project size increases.
  
  
• Projects in the electronics area have substantially more difficulty in acquiring and assimilating basic knowledge than do projects in other technology areas.

ROLE OF UNIVERSITIES: EFFECT ON RESEARCH EFFICIENCY

Each contact person responded to a series of five statements. The first three of these statements investigate unexpected research problems encountered to date relative to when the project began. The last two statements relate to the productive use of complementary research resources. The first three statements were of the following form:

It appears from the univariate statistics that unexpected conceptual and personnel research problems occur more frequently among single company applicant projects than among joint venture projects, whereas equipment-related problems are more common among joint venture projects.⁽²³⁾ There is no clear response pattern that relates to the involvement of a university in the project with the exception that joint venture projects with universities involved as subcontractors reported the greatest number of unexpected personnel-related research problems.

Ordered probit models were estimated to examine responses to this statement more systematically. Held constant in these models are several characteristics of the project as determined from ATP information about the project and from responses to survey questions. Also held constant is the survey response hazard rate variable as discussed. ⁽²⁴⁾ As seen in the specifications in Table 5 (columns 1 and 2), none of the individual variables is significant in explaining the existence of unexpected conceptual or equipment-related research problems. Becauase only very few projects had fewer problems of any type than expected, the three categories "of less than/about the same as/more than" were collapsed into two: "more than expected, or about the same as or less than expected." Even when re-estimated in this form in probit models (results not shown), essentially no identifiable individual variable effects explained the existence of unexpected research problems. Thus, we suggest that the presence of unexpected problems is perhaps random or a complex result of many factors that we cannot disentangle; that is, that they are truly "unexpected" given the information available to the firm (and to us).

Table 5. Determinants of the Problems in the Project: Ordered the Probit Estimates

The estimates in column 3 of Table 5 suggest that the presence of “unexpected” personnel-related problems are associated mainly with the technology field. Project budget size is a marginally significant explanatory variable in explaining the presence of unexpected personnel problems: projects with non-profit lead partners are less likely to experience this kind of problem. Joint venture projects with university partners are both more likely to have personnel-related problems and also less likely to respond to the survey, so we cannot disentangle these two effects.

The fourth and fifth statements addressed aspects of research efficiency that are related to the productive use of complementary research resources. These statements were:

• To date, approximately ___ percent of the research time devoted to this project has, in retrospect, been unproductive.
  
• To date, approximately ___ percent of the financial resources devoted to this project has, in retrospect, been unproductive.
  

These two statements are analyzed together because of the high correlation between responses. Twenty-two of 42 contact persons responded to both questions with the same percentage.

According to the raw statistical data, the least amount of unproductive research time and cost was reported by single company applicant projects with a university as a subcontractor. ⁽²⁵⁾ However, our tobit estimates (Table 6) reveal that this is because the technology mix varies across project type. ⁽²⁶⁾ Although all variables in the estimation were originally included, only the size of the lead partner and the technology variables were significant in either equation. Unproductive time and cost seem to be most associated with electronics projects and least associated with information technology and manufacturing projects.

In comparing the estimates in the two columns of Table 6, projects in electronics have the largest share of time and money that is unproductively used whereas projects in manufacturing have the least. ⁽²⁷⁾ Unproductive research time and money in electronics may be related to the fact that projects in this field also have difficulty acquiring and assimilating the basic research they need. Biotechnology projects have relatively little unproductive research cost, although somewhat more unproductive research time. Larger (profit-making) lead partners seem to be better at making productive use of research time and expenditure, or at least they perceive that to be the case.

ROLE OF UNIVERSITIES: EFFECT ON ACCELERATION AND COMMERCIALIZATION TECHNOLOGY

Contact people were asked to respond to two statements. The first statement posed to the lead participant was:

A much larger percentage of joint venture projects with a university involved as a research partner reported agreement to this statement than did joint venture projects with no university or with only a university serving as a subcontractor. On average, though, respondents from single company applicant projects agreed more often to the statement than did respondents from joint ventures. ⁽²⁸⁾

Ordered probit estimates for this question (corrected for response probability) were for the most part insignificant. Column 1 of Table 7 shows a minimal specification of the model. It may be that the generation of new applications from a technology project in process cannot be attributed to any particular individual project characteristic and is essentially unpredictable regardless of the technology area. Projects with a higher ATP share of the costs are more likely to develop unanticipated applications for the technology. Perhaps a higher ATP share of the costs brings greater resources for ATP monitoring or imparts to the research performers a greater leveraging effect to search for or to recognize new applications of the technology. University participation seems to have no impact on the generation of new applications of the technology.

The second statement posed to the lead participant was:

Table 7. Performance Determinants: Ordered Estimates with Correction for Response Probability

Single company applicant respondents were more optimistic than joint venture respondents about completing the research and commercializing the results sooner than expected, and the most optimistic of all were single company applicant projects with no university involvement.⁽²⁹⁾ , ⁽³⁰⁾

The response-corrected ordered probit estimates for this question are shown in column 2 of Table 7. A number of variables are significant leading to five interesting conclusions.

• Projects involving universities as partners are less likely to develop and commercialize technology sooner than expected. Universities perhaps are involved in more difficult projects to begin with.
  
  
• Large projects and/or projects with large lead participants are less likely to expect to develop and commercialize their technology sooner than expected in comparison with projects with non-profit or medium-sized lead participants. To the extent that larger research budgets are associated with research projects that can stretch the frontiers of knowledge then less time will be devoted toward looking for early-on commercialization opportunities of the technology. An alternative explanation is that if there are near-term commercialization opportunities, then a large company will be more likely to do the R&D on their own rather than partner with the government, especially if the project is not large.
  
  
• Projects with a small lead participant are less likely to expect to develop and commercialize technology sooner than expected. Recall that this group is very small firms, and this may reflect resource constraints they face in development when the project budget does not cover the full cost of making the technology commercially viable.
  
  
• Lack of experience with a university partner reduces the expectation of early commercialization, as does university involvement, perhaps because the award recipients are not familiar with the technical abilities of the university researchers or are more uncertain about the success of university work. Another possible reason could be that some adjustment costs are included as the participants learn to work with a university.
  
  
• Projects in information technology, chemicals, energy and the environment, and materials are significantly more likely to commercialize earlier than expected than are projects in manufacturing, electronics, and biotechnology.

___________________
21. See Table A4. In estimation, responses 1 and 2 and responses 6 and 7 were combined because of the small number of responses.

22. In column 1 we include the hazard rate for non-termination (the conditional probability density that the project will go forward to completion) and the proxy for the survey response hazard (joint ventures with universities participating as both partner and subcontractor) in the model. Neither of these enters into the equation significantly, implying that selection bias is unlikely to be a problem for our estimates. However, the full model for sample selection (an ordered probit equation plus an equation for the probability that the survey was returned) is barely identified in these data, with a correlation coefficient between the disturbances near minus one with a large standard error.

23. See Tables A5, A6, and A7 in Appendix A. In estimating the models for the presence of unexpected conceptual, equipment, or personnel problems, the response scale (1–7) was collapsed as follows: (1 and 2), (3, 4, and 5), and (6 and 7) were combined because of the small number of responses.

24. Ordered probit models that allowed for sample selection were also estimated, but proved to be difficult to identify because of the small sample. Therefore, we rely mainly on the ad hoc correction terms discussed in the footnotes above.

25. See Tables A8 and A9 in Appendix A.

26. Note that this survey statement addresses realized unproductive research time and not expected unproductive research time. The same is true for the unproductive use of financial resources.

27. This is a hard question for participants in projects that are still active to answer. Often there is a significant lag between obtaining the research result and knowing with certainty that it will or will not apply to the problem. Projects in the electronics area might have the answer more quickly and that might be the reason their numbers are higher.

28. See Table A10 in Appendix A.

29. See Table A11 in Appendix A.

30. In future work, it would be interesting to look at these data with only completed projects to see if this optimism holds since companies may be more optimistic in their outlook when the projects are underway.

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Date created: October 18, 2002
Last updated: August 2, 2005

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