Determinants of contract renewals in university–industry contract research:
Going my way, or good Sam?
Tohru Yoshioka-Kobayashi* and Makiko Takahashi*** Institute of Innovation Research, Hitotsubashi University** Graduate School of Innovation Management, Kanazawa Institute of Technology
Supplemental material
Cross-tabulation of renewal and extension by initial contract terms

1 year and lessMore than 2 years
2 years
3–4 years
5–7 years
8+ years

Proportion of a subsequently renewed orextended contract
63%
56%
47%
50%
86%
69%

Distribution of the dependent variable of Analysis 11# Contracts
1,214348
1641056316

Robustness check for Analysis 1: OLS regression results for quarterly research budgets
without zero budget contracts

For the robustness check of our Analysis 1, we excluded 96 contracts that concluded with 0budgets. The results of our dependent variable are almost the same as our main results. The
effect of the time elapsed from the first contract hit the peak at 2.3 years (whereas our main
result shows at 2.2 years).
Ln (quarterly research budgets + 1)
Model 1Model 20.016(0.027)
0.089*(0.031)−0.019**(0.004)
0.197***(0.027)
0.203***(0.025)−0.027***(0.004)−0.026***(0.004)
0.064(0.061)
0.066(0.060)−0.023***(0.001)−0.024***(0.001)

Time elapsed from the first contract
squaredExtension
Initial contract periods (quarters)
On-site industry researchers
PIs’ U–I linkages
Position (baseline: Lecturer/assistant professor)
Professor
0.503***(0.034)
Associate Professor
0.376***(0.055)
Department (baseline: Humanities/social sciences)
Medical/Pharmaceutical−0.033(0.044)
Biology/Other Medical−0.230**(0.046)
Science/Engineering
0.079***(0.012)
Constant
12.635***(0.033)
Year dummies
Yes
Observations
1,466
R-squared
0.042
Cluster robust standard errors in parentheses (clustered by PI’s department).
***: p < 0.001, **: p < 0.01, *: p < 0.05

0.503***(0.034)
0.375***(0.058)−0.030(0.044)−0.228**(0.047)
0.082***(0.013)
12.601***(0.039)
Yes
1,466
0.044

Robustness check for Analysis 2:
Logit regression results of the probability of extension or renewal (sampling bias test andestimations with a control variable of objective-outcomes matching)First, we checked a sampling bias in our observation. As explained in the Methodology section,a total of 18 firms refused to respond to outcome-related question items. We prepared a dummy
variable that represents whether the counterparty responded to these questions and used it as anindependent variable. Its result is shown in Model 0 in the table below. The coefficient of thedummy variable is not statistically significant. We reject the concern of sampling bias.
Next, we inserted an additional control variable. In our empirical test, we do not test aninfluence of differences on goal specificity. As the available data are limited, the construct is notdirectly operationalized. But assuming that the matching between the initial primary objective
and primary outcome is correlated highly with goal specificity, we construct a dummy variable
that takes a value of one if the most high-impact outcome category (ranked as one among ten) ismatched to initial primary objectives (ranked as one among ten). The mean of the variable is 0.47.

2The results are shown in Models 1 and 2 in the table below. We found that the coefficient of thevariable is significantly negative. The odds ratios of some coefficients are different from our main
results, but their signs and significance levels are consistent with our main results.
Subsequent extension or renewal
Model 0Model 1Model 2
Sampling bias test
With additional
With additional
control variable
control variable
Response to outcome-related questions

1.069(0.119)

Satisfaction with outcomes

1.366**(0.210)

1.685***(0.338)

Outcomes
Technological knowledge acquisition

7.388***(2.811)

Patent application

0.849(0.531)

Academic paper publication

4.666***(1.518)

Valuable data acquisition

0.844(0.203)

Building human capital

0.210***(0.088)

Creating social ties with faculty

2.070***(0.491)

New project establishment

1.640(1.283)

Contribution to R&D/NPD
Matching between the primary objective
0.588**(0.132)
and outcome
Time elapsed from the first contract
2.088***(0.505)
1.737(0.657)
squared
0.889**(0.043)
0.934(0.070)
On-site industry researchers0.906(0.153)
0.831(0.113)
Ln(research budgets + 1)
1.140***(0.055)
1.360***(0.143)
Contract periods (quarters)
1.074**(0.031)
1.073(0.067)
PIs’ U–I linkage
1.117(0.089)
1.041(0.051)
Baseline: Lecturer/Assistant Professor
Professor
0.620(0.603)
0.173(0.296)
Associate Professor
0.655(0.847)
0.175(0.328)
Baseline: Humanities/Social Sciences
Medical/Pharmaceutical
3.644***(0.275)
3.188***(0.283)
Biology/Other Medical
4.437***(0.557)
3.575***(0.328)
Science/Engineering
5.362***(0.410)
5.953***(0.489)
Constant
0.040***(0.012)
0.006*(0.018)
Observations
155
137
Pseudo R-squared
.082
.117
Odds ratio. Cluster robust standard errors in parentheses (clustered by PI’s department).
***: p < 0.001, **: p < 0.01, *: p < 0.05.

3

0.353***(0.044)
0.207***(0.070)
1.942*(0.755)
0.872*(0.064)
0.775**(0.085)
1.404***(0.017)
1.111**(0.049)
1.157*(0.101)
0.270(0.397)
0.226(0.390)
3.402***(0.791)
4.074***(1.037)
10.062***(1.177)
0.000***(0.001)
137.234