University–industry collaborations create socioeconomic impacts for the areas where they are undertaken. Although these collaborations have recognized importance and a high potential to generate economic and social benefits, there is no consensus in the literature on a consolidated conceptual model for assessing their socioeconomic impacts.
Mechanisms produce outcomes . In the context of university–industry collaborations, the mechanisms are the channels for technology transfer. We analyzed the links between contexts, interventions, and outcomes to establish the mechanisms.
The mechanisms identified were intellectual property, spin-offs, hybrid organizations, sponsored research, consulting and hiring professionals with academic knowledge, and publications and conferences. Table 4 shows the dominant mechanisms. Intellectual property (47.87%) and spin-offs (45.75%) stood out from the rest of the dominant mechanisms. The relevance of intellectual property has been noted by Perkmann et al. , Mets et al.  Jones and De Zubielqui , and Secundo et al. . Licensing intellectual property provides legal rights that give companies access to technological solutions in the universities’ intellectual property . Spinning off companies and hiring professionals with academic knowledge enables more straightforward technology transfers through human resources movement .
Chiesa and Piccaluga  called academic spin-off enterprises one of the most promising ways to get scientific findings to the market.The triple helix concerns the relationships among universities, industries, and governments and the creation of such hybrid organizations as incubators, science parks, and technology transfer offices. The original business support structure of incubation has been reconsidered to emphasize its focus on the educational mission in training organizations .
Technology transfer offices differ considerably in their commercialization capacity. The license income distribution is highly localized, with a few big commercial hits yielding strong profits for a few universities . Many high-impact start-up projects have emerged from academic studies in many developed countries, with the majority of these firms originating with a limited group of strongly entrepreneurial universities . Sponsored research is a contract between a university and an industry. A sponsored research project supports university-commissioned studies and offers funding for facilities, graduate students, course launches, and faculty summer care . Examples include collaborative research , contract research ,, and the establishment of R&D organizations .
Several authors considered consulting and hiring professionals with academic knowledge an important mechanism, such as Bramwell and Wolfe  , Breznitz and Feldman  , Chen et al. , and Hope . Universities do not usually have individual consultancy agreements with the faculty member(s), as companies nearly always own all the created intellectual property and directly remunerate the faculty member; in these cases, the university does not have access to new investments and potential generation of intellectual property .
Dutrénit and Arza  argued that publications and conferences are traditional technology transfer mechanisms. They classified mechanisms into four types: (1) traditional (hiring professionals with academic knowledge and publication and conferences); (2) services (providing science and technical resources in exchange for funds, such as consulting, use of quality management facilities, tests, instruction, and so on); (3) commercialization of scientific results already obtained (academic spin-offs, licensing, patents, and incubators); and (4) bidirectional mechanisms motivated by long-term aims of knowledge (contract research, joint R&D projects, and scientific–technological parks). Their model was also used by Orozco and Ruiz  and Fernandes et al. . Serendipity is considered an unconventional mechanism that could possibly start relationships that later unfold through different mechanisms .
University offices are often regarded as displays for companies and treated as cooperation platforms for marketing their R&D results. The mechanisms vary depending on the context in which a university and a company are engaged (e.g., the country, region, and prevailing incentive policies). Hayter and Link  listed numerous university-affiliated proof-of-concept centers (PoCCs) in the United States that contributed to a rise in that country’s academic spin-offs. Chang et al.  presented a model created in China of a university–industry cooperation platform in which companies could seek partnerships with any higher education university in the country or vice versa. The China cooperation platform has improved the economic performance of that country’s high-tech companies; this suggests a positive connection between economic performance and the number of cooperating parties. Different cooperation mechanisms impact the economic performance of high-tech companies at different levels .
We classified the outcomes into three dimensions: (1) economic, (2) social, and (3) financial. We further subdivided each dimension as follows: (1) economic: infrastructure, production and processes, and scientific development; (2) social: jobs, skills, and qualification; and (3) financial: purchases, taxes, investments, and income generation. Figure 2 shows the proposed model for measuring the economic impact of university–industry collaborations.
Figure 2. Evaluation model for the socioeconomic impact of university–industry collaborations.
Several authors have addressed some of the socioeconomic impacts of university–industry collaborations on the technology transfer mechanism, such as the emerging of companies (startups and spin-offs), patents and licensing, and relevant scientific publications. Ahrweiler et al.  and Urbano and Guerrero  claimed that these collaborations could lead to new business opportunities.
Etzkowitz  contended that universities have emerged as leading actors in a society predicated on knowledge owing to their nature as creators of original ideas. University–industry collaborations often result in new scientific and technological development partnerships that generate intellectual properties and market opportunities, such as industrial applications and new enterprises. Scientific novelty is of interest to academics, too, because it can generate new avenues for research. An enhanced mechanism from a university–industry collaboration can directly lead to such positive results as higher productivity, new products, increased sales, and commercial and societal value creation. Most of the authors in the systematic literature review regarded job creation as a socioeconomic impact of university–industry collaborations that could be quantified and influences people’s quality of life.
Entrepreneurial universities can contribute through an advisory role in public policy formulation . In this role, universities engage with local communities on a variety of themes. Nevertheless, most of the services and activities supplied by institutions cannot be easily quantified . A university–industry collaboration can have several socioeconomic impacts on the actors in  triple helix; therefore, we propose a conceptual model of socioeconomic impact based on the main benefits from the actors in the triple helix. Figure 3 illustrates our Socioeconomic Triple Helix Conceptual Model.
Figure 3. Socioeconomic triple helix.
The triple helix model puts the institutional spheres into perspective. An understanding of the most significant impacts and the stakeholders who benefit from such impacts facilitates negotiation between the constituents and enables strategies to be defined with the objective of enhancing the socioeconomic impacts based on interests and priorities.
The advantage of organizing the model according to the triple helix thesis is that the model has a visual and didactic advantage that makes it possible to quickly map the impacts and the main stakeholders, allow cuts or partial indicator applications for more specificity, and evaluate the impact of particular actions or public policies.
University–industry collaborations can have appropriate economic and social advantages. We developed the socioeconomic triple helix, a conceptual model of socioeconomic impacts identified in the systematic literature review based on Etzkowitz and Leydesdorff’s  triple helix model. Our model has significant academic and managerial contributions.
The triple helix model puts the institutional spheres into perspective. An understanding of the most significant impacts and the stakeholders who benefit from such impacts facilitates negotiation between the constituents and enables strategies to be defined with the objective of enhancing the socioeconomic impacts based on interests and priorities. The advantage of organizing the model according to the triple helix thesis is that the model has a visual and didactic advantage that makes it possible to quickly map the impacts and the main stakeholders, allow cuts or partial indicator applications for more specificity, and evaluate the impact of particular actions or public policies.
Any authors, including Galan-Muros and Davey , Audretsch et al. , Alessandrini et al. , Bercovitz and Feldman , and Etzkowitz et al. , have claimed that traditional metrics and indicators cannot capture the socioeconomic benefits of university– industry collaborations. Our work enables a deeper analysis of the socioeconomic impacts of university–industry collaborations, highlighting the existing effects in the literature through synthesizing high-value insights into the theory of socioeconomic development based on strategic knowledge management, R&D, and technological innovation. Our model complements the triple helix model with a socioeconomic perspective of the interactions among government, universities, and industries, thus adding knowledge and elaborating on the theory. This work provides a guide for researchers and scholars who are interested in university–industry collaborations.
In addition to its academic contributions, this research and our new conceptual model benefit all the actors in the triple helix: (1) universities and companies can use the model to assess the socioeconomic impacts of individual collaborations; (2) public agents can use it to evaluate the impacts of their investments; and (3) government agencies can use it to inform their development of public policies for innovation and technology management.
Based on the results and the discussion on the socioeconomic impact of university– industry collaborations, we offer a few suggestions for future research: (1) an application of an evaluation model to university and companies and (2) a development of methods for the indirect impact assessment in local communities.
Future research should pursue applications of the proposed model, which will require developing metrics for each indicated variable. These additional metrics will enable the assessment of the socioeconomic impact of collaborative activities of university–industry partnerships by creating indicators that can be controlled and enhanced based on actions focused on the technology transfer mechanisms. Research has shown that conventional and
quantitative metrics are not sufficient to measure the socioeconomic impact of university–industry collaborations fully . In addition, a more qualitative assessment is suggested that addresses the indirect impact of university–industry collaborations—for instance, the creation of public policies , regional human capital attraction, and community and city development.