Accelerating Innovation: Increasing the Velocity of Ecosystem Development in Higher Education

Abstract

The increasing demand for impactful innovation from higher education institutions (HEIs) has elevated their role as engines of economic growth, technological progress, and societal advancement. This dissertation, Accelerating Innovation: Increasing the Velocity of Ecosystem Development in Higher Education, investigates how universities can systematically cultivate high-performance innovation ecosystems capable of producing sustained, market-driven outcomes. The study is guided by the central question: If an academic institution seeks to build a thriving innovation ecosystem that consistently produces high-value outcomes, what practices, structures, and strategies should be implemented? To address this, a mixed-methods approach integrates nine large-scale data sources, including NSF and NIH funding, SBIR/STTR awards, AUTM technology transfer data, Innovation Development Institute (IDI) company profiles, PrivCo financial outcomes, and institutional metrics. A multivariate modeling framework using SIMCA software was applied to analyze 127 U.S. HEIs from 2013–2023, producing a comprehensive Academic Innovation Performance Index (AIPI). Key findings reveal that company-focused outcomes, such as the number and performance of academic spinouts, are the strongest indicators of ecosystem health. Multivariate modeling identified a clear set of institutional characteristics positively associated with innovation success: active engagement in SBIR/STTR programs, robust participation in NSF I-Corps, high levels of NSF funding, strong regional partnerships, significant research expenditures, a deep pipeline of PhD-level researchers, a large STEM faculty presence, and substantial on-campus research space. Conversely, heavy reliance on NIH funding, higher transfer-out rates, and weaker local engagement were negatively associated with commercial outcomes. This work highlights the pivotal role of STTR partnerships, particularly those involving academic spinouts and “super government contractors,” as catalysts for downstream innovation. It also underscores that innovation velocity depends not only on research excellence but also on structured, deliberate ecosystem strategies that bridge on-campus discovery and market translation. The findings offer a replicable, data-driven framework for assessing and advancing HEI innovation ecosystems. These insights provide actionable guidance for academic leaders, policymakers, and industry partners seeking to strengthen their innovation impact and accelerate the transformation of research into societal value.