Can Universities Do It All? The Strategic Role of Dynamic Capabilities in Driving Innovation

Redacción HC
22/04/2024

As higher education institutions are increasingly tasked with contributing to economic and societal development beyond teaching and research, the so-called "third mission"—technology transfer and knowledge commercialization—has emerged as a key performance metric. But as universities strive to balance innovation with academic excellence, a pressing question arises: can they successfully pursue all missions at once?

In a recent study published in Small Business Economics (October 2024), Maribel Guerrero (Arizona State University & Universidad del Desarrollo) and Matthias Menter (Friedrich Schiller University Jena) provide empirical evidence from 90 German universities over 16 years. Their findings challenge assumptions about the benefits of investing broadly across academic functions, revealing instead the critical role of dynamic capabilities—and the risks of trying to "do it all."

Understanding the Third Mission and University Capabilities

Universities today are not just centers of education and research—they are expected to serve as engines of innovation. This third mission typically manifests in patent generation, spin-offs, and collaboration with industry.

To explore how universities succeed in this role, the authors focus on two types of institutional capabilities:

• Ordinary capabilities: traditional performance metrics like student-faculty ratios and publication volume.
• Dynamic capabilities: adaptive mechanisms such as digital innovation in teaching (e.g., MOOCs) and high-impact research output.

The study investigates whether these capabilities act independently, complement each other, or substitute one another in promoting patent activity as a proxy for the third mission.

A Longitudinal Look at German Universities

The researchers compiled a dataset of 1,478 observations from 90 universities in Germany between 2000 and 2016. Their methodological rigor included:

• Zero-inflated negative binomial regression to address excess zeros in patent output.
• Panel logistic regression as robustness check.
• Control variables like institutional size, funding type, gender diversity, and regional effects.

Teaching-related capabilities were captured via MOOCs and faculty-student ratios; research-related capabilities through citation metrics and publication volume. Patents were used as the proxy for third-mission performance.

Key Findings: When Innovation Is a Trade-Off

Dynamic Beats Ordinary—But Not Always Together

• Teaching: MOOCs had a strong positive effect on patent production (β ≈ 0.97; p < 0.01), while higher student-to-faculty ratios had a negative effect.
• Research: Both high publication rates and highly cited research positively influenced patent counts (β ≈ 0.20 for ordinary; β ≈ 0.014–0.017 for dynamic; p < 0.01).

This suggests that while ordinary and dynamic capabilities both matter, dynamic capabilities—those that reflect adaptability and innovation—have a disproportionately stronger influence, especially in teaching.

Substitution, Not Synergy

Surprisingly, the interaction between ordinary and dynamic capabilities was negatively significant, indicating a substitution effect. When universities invest in both simultaneously, their combined effect on patents diminishes.

The message is clear: trying to excel in all areas may dilute a university's third-mission effectiveness. Strategic focus—not breadth—is what pays off.

"Investing strongly across multiple fronts—innovative teaching, elite research—can stretch resources too thin, weakening overall technology transfer outcomes." — Guerrero & Menter (2024)

Institutional Traits Also Matter

• Larger universities tended to produce more patents.
• Unexpectedly, industrial orientation showed a negative correlation with patent output, challenging assumptions about the benefits of close industry ties.
• Control variables showed complex interactions that merit further research but underscore the multifactorial nature of institutional performance.

Implications: Strategy Over Scope

For Policymakers and Administrators

Universities—and the public agencies funding them—should avoid the temptation to mandate across-the-board excellence. Instead, institutions must prioritize and specialize. For example, fostering MOOCs aligned with tech transfer goals or incentivizing elite research with commercialization potential may yield better outcomes than spreading efforts thin.

For Emerging Regions like Latin America

This framework offers valuable insights for universities in Latin America that are scaling their third-mission activities. With limited resources, strategic prioritization of dynamic capabilities may deliver better returns than emulating broader global university models.

For the Innovation Ecosystem

By sharpening the focus on dynamic capabilities, universities can become more agile in translating knowledge into economic impact—essential for addressing today's global challenges through innovation.

Conclusion: Rethinking "Excellence" in Higher Education

This study underscores a counterintuitive truth: more is not always better. Universities that attempt to excel simultaneously in teaching, research, and innovation may find themselves underperforming in the very areas that define institutional impact in the 21st century.

Instead, Guerrero and Menter argue for a targeted, data-driven approach to capacity building, one that understands the trade-offs and embraces specialization where it matters most.

"Dynamic capabilities are not just enablers of institutional change—they are strategic levers for societal impact."

As the third mission becomes central to how universities are evaluated and funded, it is time to rethink what it means to be excellent—and to invest accordingly.

Topics of interest

Academia