Introduction

University-industry collaborations (UIC) have contributed significantly to resources and research development opportunities for both universities and industry partners (Huang & Chen, 2017; Bhullar et al., 2019; Bozeman et al., 2013; Perkmann & Walsh, 2009). These collaborative relationships, which are known by a variety of terms including academia-industry collaboration and university-industry relations, involve members from academia and industry working on a project, typically through an agreement in which industry provides capital and practice-based problems to academics who provide systematic investigatory skills and labor in the form of research and development. While industry partners benefit primarily from the outputs of the research (e.g., reports, techniques, prototypes), they also gain human capital through developing a recruitment pipeline among new university graduates and building a network of academic subject-matter experts whom they may draw upon later for future collaborations and questions (Fraser et al., 2011). Similarly, from the academic perspective, participation in UIC relationships typically includes benefits associated with outputs (e.g., publications) and inputs (e.g., capital). University faculty may also benefit through improvements in core academic activities, such as teaching and research (Bhullar et al., 2019). Notably, these UICs support and develop a labor supply and infuse capital into operations, and the capital and labor lead to knowledge production. In short, there is a capital and labor relationship for the academic and corporate organizations that participate in these UICs (Bozeman et al., 2013).

The purpose of this study to analyze an intensive case experience, which drew on a nearly year-long engagement, about reported positive effects and extend the analysis to draw on human capital theory using collaborative management research, a modality of action research (Coghlan & Brydon-Miller, 2014). Adopting an action research approach, we sought to understand how the complementarity of investments made by university and industry in the development of a collaborative project led to collective growth outputs.

A university-industry collaboration (UIC) is a joint effort between a university and business entity leading to the “co-production of innovation” (Sjöö & Hellström, 2019). For this study, the UIC was between a public research university and a corporate entity within the healthcare industry, and the collaboration, which consisted of a contractual relationship like most UICs, was to co-produce a diversity, equity, inclusion, and belonging (DEIB) strategy for the healthcare company. More specifically, drawing on the university-industry contract for the healthcare company to advance its DEI strategy, a team at the university, including the two authors of this paper, engaged in preliminary discussions leading to an industry contract to collect data and advise the company through co-constructing the corporate (DEIB) plan. As part of the project, the UIC relationship included academic and professional research projects including a DEI benchmarking analysis, an organizational needs assessment, work culture inquiry, employee values/motivation analysis, and an apprenticeship learning study. Based on these experiences of the UIC, we constructed another study based off our intensive case focus with this guiding research question: How can universities complement capital and labor within a university-industry collaboration?

Literature Review

Extant literature about UICs present mixed experiences depending on a number of factors including industry expectations, university policies, and each party’s position and contribution in the relationship (Dougherty et al., 2004; O’Dwyer et al., 2022; Welsh et al., 2008). In this section, we review literature that presents both criticisms and benefits to UICs to highlight the breadth of experiences for those engaging in these collaborative projects.

University-Industry Collaborations Constraints

A growing body of literature within the study of higher education has captured the mounting pressures for universities to take on market behaviors and commodify knowledge. Such behaviors are becoming so prevalent that this type of commercial engagement has become to be known as the Third Mission for universities (Nelles & Vorley, 2010). Extant literature has typically analyzed these collaborations drawing on critical theories (e.g., Molesworth et al., 2009; Nixon et al., 2018; Kolsaker, 2008), conflict theories (e.g., Collins, 1971; Stoten, 2018), or negative connotations from other theories, such as political economy, presenting a neoliberal view to the relationship (Slaughter & Leslie, 1997). For instance, Slaughter and her co-authors have, for about 20 years, examined the emergence of university behaviors toward market-based approaches and have described institutional and professorial efforts to secure external funding as academic capitalism (Slaughter & Leslie, 1997). Building upon this work, Slaughter and Rhoades (2000, 2004) specifically note how academic capitalism displaces higher education’s ability to meet the needs of underserved student populations. Throughout this work, there is an emphasis on how these changes have commodified students as mere tuition sources who fund the university’s market-driven enterprises (Slaughter & Leslie, 1997; Slaughter & Rhoades, 2000, 2004).

The erosion of the academic environment presents a real fear. Indeed, a significant line of UIC research adopting a neoliberal perspective emphasizes the environmental market pressures and managerial power relations as considerable conditions propelling the capitalist approaches in an adverse manner. The literature includes university efforts to commodify knowledge and reframe UIC research as serving the public good despite the limitations of academic researchers’ autonomy to examine issues freely and disseminate works broadly (Busch, 2017; Glenna et al., 2007; Sun, in press). Likewise, as Collyer (2015) suggests, the rise of university professional managers over academics, which is a function of the neoliberal infusion into higher education, identifies another restraint on higher education into a market-focused approach that buys into industry influences and has potential to limit academic freedom. These behaviors counter higher education norms, which have been associated with a culture of openness and a product with quality (Newby, 1999). In short, the higher education literature about university and industry relations highlights the negative influences industry has had on the academy’s autonomy and values.

Moving Beyond Constraint

Despite these criticisms, the prevalence of UICs has continued to grow, as has the body of literature seeking to understand their place in both university and industry contexts. These works have examined the evolving relationship (Plewa, et al., 2013; D’Este & Perkmann, 2011; Mowery et al., 2020; Franco & Haase, 2015), barriers to overcome toward success (Austin et al., 2021; Bruneel et al., 2010; Locket et al., 2008; Phan & Siegel, 2006; Tartari & Breschi, 2012), and key positive components to the relationship (De Fuentes & Dutrénit, 2012; Dougherty et al., 2004; Gertner et al., 2011; Owen-Smith, 2003; Van Looy et al., 2003).

Of note within the extant literature about UICs are the documented successes as well as approaches to improve the benefits for either academic institutions or industry partners. Over 30 years ago, Kenny (1989) espoused the benefits of corporate partnership, arguing that these relationships can revitalize an institution’s place in the community and its economic development while simultaneously contributing knowledge to the advancement of the private sector. More recently, Locket et al. (2008) have echoed these benefits, noting that UICs may strengthen connections to their environments through “reducing the ivory tower element” (p. 13) and may aid the local economy in industry growth and retention of recent graduates. Others elucidate benefits of UICs through examining the motivations of those engaging in this work, including advancing research (D’Este & Perkmann, 2011; Bhullar et al., 2019), increasing access to resources (Tartari & Breschi, 2012; Franco & Haase, 2015), and providing industry-relevant education and mentoring to students (Fraser et al., 2011).

Much of this literature recognizes that these relationships are not exclusively beneficial yet find that the benefits outweigh the drawbacks. For instance, Welsh et al. (2008) note reported hinderances emanating from UICs, including availing personnel to conflicts of interests and restricting scientific communications among academic researchers. However, they also present industry benefits associated with productivity enhancing activities (e.g., new knowledge, access to research tools), scientific interaction benefits (e.g., expanded networks), and industry support advantages (e.g., research funds, personnel supports). Similarly, Austin et al. (2021) found that UICs may lead to conflicts regarding timelines and unrealistic expectations about academic availability, but that, when successful, there is a two-way knowledge exchange and transfer of innovative ideas that can benefit both academics and industry.

While scholars have offered these benefits, the foci have been overwhelmingly in scientific fields with clear interest on market benefits including product inventions, service/process applications, and other intellectual property concerns (Mindruta, 2013). Nevertheless, not all UIC relationships lead to similar outcomes, as variability exists among institutional types, disciplines, and even academic units in the manner these units search or value capitalistic behaviors and rewards (Mendoza, 2012). Further, although inquiry into successful collaborations has emerged more recently in the future, these studies have limiting application to non-medical or engineering-based projects or the context or the data emerged outside of an actual UIC case experience (Awasthy et al., 2020; O’Dwyer et al., 2022). Thus, the extant literature is less clear how UICs have demonstrated significant value propositions for both parties across disciplines and may move beyond a critical or neoliberal view of this relationship when considering social and behavioral fields such as education. In this study, we explore these gaps and employ human capital theory to better understand this relationship.

Conceptual Framework

The UIC relationships further capital and skilled labor. Within the higher education literature, most other approaches to studying this relationship have been limited to studies on college access, enrollment, and success factors. For instance, foundational works in higher education have analyzed returns on capital investment through comparing associated costs of those who attend college and those who do not (Becker, 1960), those who pursue on-the-job training versus additional education (Mincer, 1962), and how this relationship is affected by the lifecycle of earning potential (Ben-Porath, 1967). Building upon Becker’s (1960) argument, these works largely posit that human capital is directly beneficial to production and that human capital and education are complementary, with the combination of human capital and education leading to larger returns on capital investment. Nonetheless, while the return on one’s individual educational production is significant and well established under human capital theories, less is known from this perspective to examine other educational relationships, which also offer knowledge acquisition and production. Mindruta (2013) suggests that complementary resources lead to innovative outputs, publications, and market products.

The capital-skill complementarity hypothesis emerged as a human capital approach to understand the capital and labor relationship in manufacturing (Griliches, 1969). The overall proposition was that capital equipment and unskilled labor is greater than the capital equipment and skilled labor when elasticity of substitution is sought, and capital and skilled labor hold greater complements as production inputs than the relationship between capital and unskilled labor when technological development or specialty processes or knowledge increases. Although the hypothesis has been tested largely from a macroeconomic analysis, the principles offer insights when examining capital-skill complementarity in a micro-behavior approach between two organizations and beyond physical capital to include financial and technological capital as applied in previous studies (see, e.g., Goos, 2018). These effects may be evaluating the effects of the skill premium associated with the inter-organizational relationship (Krusell et al., 2000). Viewed in the context of this study, we acknowledge how the expertise in corporate DEIB as a specialty process and knowledge is not great or limited in supply and the cost value to produce is higher than other input needs for corporate entities, so there is a general lack of supply and resource-based ability. Guided by this hypothesis, we examine how the relationship between capital resources of organizations (though beyond physical resources) to include social capital and skilled experts in a team-based specialty area offer complementary inputs to the production of a corporate diversity plan and how that dynamic presents a framework to elucidate a university-industry collaboration.

Methodology

Given that we were both members of the UIC and participant observers analyzing the UIC as it unfolded, we adopted an action research approach (Coghlan & Brydon-Miller, 2014). This methodology stands in contrast to previous research about UICs, which usually adopt case study (e.g., Austin et al., 2021; Gertner et al., 2011), or survey (e.g., Bruneel et al., 2010; D’Este & Perkmann, 2011; Plewa et al., 2013) approaches that lack a participatory, dynamic design.

Study Context

This study is based on a UIC between a Carnegie classified public research 1 university and a corporate entity within the healthcare industry that employs over 5,000 team members and generates over $1 billion annually in revenue.

This UIC began when a corporate healthcare company contracted our team of researchers in the college of education and human development at a Carnegie classified public research 1 university to develop their diversity, equity, inclusion, and belonging (DEIB) plan. The company is sizeable. It employs over 5,000 team members and generates over $1 billion annually in revenue. The contract with the university specified that over the course of approximately one year, we would collect data through focus groups with employees and analyze these data alongside secondary data from previous internal surveys and human resources to develop a DEIB plan tailored to their needs and contexts. We also agreed to meet weekly with our corporate partners to discuss progression of the plan and troubleshoot issues. Throughout the early stages of the UIC, our intention was to work with the company’s employees to develop a plan that could improve their daily practices, and we saw ourselves primarily as the beneficiary of this work through obtaining capital.

Early in the process, however, we realized that the relationship was not as linear as we had initially thought, and we began to see ways that our partnership was a case of a mutually beneficial UIC. We then became intentional about studying the UIC alongside the development of the DEIB plan. That is, while we were working with the company’s employees to develop the DEIB plan, we were also working with members of the company’s leadership team to study the effects, successes, and challenges of the UIC.

Study Design

Our examination of the UIC closely adheres to the definition of action research put forth by Coghlan and Brannick (2005) who describe action research as occurring alongside the action (the development of a DEIB plan), being borne out of a collaborative and democratic partnership (the UIC), and functioning as both a product-driven process (the DEIB plan) and a method of problem solving (increasing complementarity in UIC). More specifically, this study employs collaborative management research (CMR), an action modality in which external researchers and company management work collaboratively to address an issue of mutual concern. Unlike other forms of action research, which typically involve working with all organization members, in CMR “the organization does not seek help, and the researchers do not impose their studies; the collaboration here is really co-determined by the constructive dialogue between the researchers and the top management of the organization about a topic of mutual interest” (Coghlan & Brydon-Miller, 2014, p. 130).

Data Sources

We gathered data for this study over the course of the UIC. As with most action research projects, data sources varied and fluctuated as the project developed over the course of the yearlong partnership. We primarily drew data from three sources: meetings with our corporate partners, feedback collected on project deliverables, and our journaling. More specifically, meetings provided us with a range of documents for analysis, including minutes, administrative documents, and field notes. As participant observers, we were transparent about our roles as researchers in these meetings, yet we also tried to minimize our insertion of UIC research into conversations about plan development, as we sought to study the UIC as objectively as possible within the constraints of action research (Lindhult, 2019). That said, a natural part of these meetings included discussions about what was and was not working with the collaboration, and these discussions provided a rich data source for our analysis of the UIC. Separate from these regular meetings, we also received written and verbal feedback from company leadership regarding our plan development, which was delivered progressively in various forms so that leadership were able to help shape the structure of the plan. This feedback enabled us to better understand the company’s perception of the UICs efficacy, as well as identify challenges with communication and presentation styles. Finally, journaling provided the research team with a space to reflect on our observations of how the UIC was progressing and provided a source for discussion among research team members. The action research cycle is comprised of experiencing, reflecting, interpreting, and taking action, and thus journaling is a key component to this methodology as well as a primary data source (Coghlan & Brydon-Miller, 2014).

Data Analysis

We analyzed data using content analysis to uncover patterns and themes (Patton, 2002) Data analysis was an iterative process that occurred throughout the progression of the UIC, and, as with many action research projects, involved mapping the narrative of our experiences to understand how they either followed or diverged from the extant literature (Coghlan & Brydon-Miller, 2014). As our themes began to emerge, we discussed what we were seeing with our corporate partners to challenge our assumptions and identify differences in our perspectives. After several iterations of analysis and discussion, we arrived at the following four components of the complementary investment.

Findings

Our findings suggest that capital-skill complementarity as a conceptual lens offers numerous insights about the benefits associated with UICs. Specifically, when UICs move from input complements to collective growth outputs, this form of UIC can be seen as a “complementarity investment.” This complementarity investment is manifested in four ways.

Roles, Activities, and Contributions Clarified and Identified

First, the organizational heterogeneity between the corporate entity within the healthcare industry and the academic unit, which was a team from a research university’s college of education and human development unit (i.e., a unit with a non-corporate centric focus), equalized the power relations, so the parties could create a focused approach on equal footing. In fact, early-on, the team articulated a shared vision and clearly articulated their offered role expertise, which collectively contributed to a mutuality of benefit under this complementarity investment construct.

For instance, when we agreed to contract with the company to develop the DEIB plan, we began our discussions with a clear articulation of what each organizational partner would receive for the work beyond the exchange of capital and product development. The university team outlined our plans for academic publication based on the work, while company management expressed an interest in disseminating the work among their healthcare peers through trade journals and media outlets. Beyond establishing the products that would be created in addition to the DEIB plan, stating our goals early in the process clarified our values and motivations for completing the work.

Further, role clarity and understanding role differences enabled us to better appreciate how projected outcomes would be achieved. As social scientists, our focus and skills centered on the process behind the plan development. We were primarily concerned with not only developing an effective DEIB plan, but also on understanding how other companies and universities could engage in similar work. Our company partners, however, prioritized the outcomes of the work. They were less concerned with how we created the plan than with how the plan would improve their business practices and employee experiences.

Equally important, each activity was intentional and mapped within the project. Even during the development of the plan, there were moments when we wanted to expand our analysis to better understand company culture and needs. When these events occurred, they were paired with discussions of how this additional work would further contribute to mutual benefit. For example, when the company asked that we analyze data from their human resources department alongside results of a recently administered employee survey, we extended these analyses to also look for larger trends in employee experiences with the aim of furthering our own research agendas.

Although university and industry partners differed in our goals and motivations for participating in the UIC, the organizational heterogeneity associated with our underlying interests did not interfere with our complementing approach and outputs. Instead, our shared vision on improving equity in the workplace led the university researchers to consider adopting recommendations from the DEIB plan to our own organizational context. For example, we recommended that our industry partners perform an audit of their current suppliers to identify if these companies are aligned with their values and commitment to DEI, and as a result of this work, the university is considering a similar audit of its own vendor contracts.

A design element of this relationship played a significant part to the output success. By studying the UIC alongside participating within it, we were able to consider how we might further this work in other contexts within the university. Our corporate partners valued our interest in knowledge management because it is a critical function within their space in which they regularly review their data and experiences to draw lessons and parallel applications for other parts of their strategic operations. We were doing the same. Essentially, we were able to treat this UIC as a model for both community DEI work and university consulting relationships. Thus, we experienced long-lasting benefits on better understanding how to engage in this work through the practical example of the UIC.

Learning Exchanges Engaged, Modified, and Valued

Our second finding is that the UIC led partners to feeling rewarded, reinforced, and rejuvenated through learning exchanges. Throughout the UIC, both teams were challenged to question their own processes and translate their work so that it was universally understood. Under this view, the parties captured learning exchanges associated with their work by engaging in these learning exchanges and valuing their impacts, which collectively represented a piece of the complementarity investment from this UIC arrangement.

Admittedly, the learning exchange was not seamless in the beginning. One of the challenges we encountered most frequently was a feeling that we were speaking different languages and not quite synchronized despite our role clarity and separation of duties toward a common set of goals. The challenge revolved around stylistic approaches and norms. For instance, the university team was accustomed to communicating results and recommendations according to academic and university standards, while the company team had devised its own internal mechanism for information sharing. Particularly in the early stages of plan development, we found ourselves frequently translating work to other formats to more effectively communicate with company stakeholders. At the same time, our company partners re-evaluated some of their processes to better align with university practices.

Beyond communication, we also changed our thinking. We entered the partnership with a design thinking model, which was nested into elements of the organization rather than individual people. Our company partners initially had a linear mindset when it came to plan development, as their priority remained on developing an actionable and efficient DEIB plan. Throughout the collaborative process, however, we both began to see limitations and flaws with how we approached the topic at-hand and began to see the benefits of incorporating both styles into our planning and processes.

One of the most substantial changes that we saw in the practices of both organizational partners was the treatment of data. To better communicate with the organization, we incorporated a higher frequency and variety of data visualization. Throughout the process, we spoke with employees of all levels—from the c-suite to the residential care teams—and we found that visualizations that worked for one group might not be as effective for others. One might surmise that this outcome was seemingly obvious: different audiences wanted different types of information. However, the concern was much more about the visual display of the information. Thus, we were challenged to become agile in the ways we presented and discussed our findings as we worked to obtain buy-in from the large employee base, so we could build trust and truly gather honest, productive data to enact change. At the same time, our analysis of the company’s human resources data required them to re-evaluate what data they collected and how they were stored. For example, one of the areas of concern for the company were how the differences between rural, urban, and suburban campuses affected the experiences of their employees, yet they were not tracking the location-type of their campuses in their data systems. Beyond our own analysis purposes, we explained to them how tracking data at a more granular level would enable them to better understand their employee experiences, and we provided recommendations for additional data points that they should incorporate into their systems.

Other practical changes that we made centered around how we collaborated, particularly in terms of expectations for personnel and timing. At the time of the partnership, developing the DEIB plan was a high priority for the company and the top priority for the DEI team. This team was therefore interested in developing the plan as quickly as possible, and they developed a meeting and communication schedule that was aligned with this goal. At the university, however, this project was one of many research projects the team was currently working on, in addition to other teaching and service responsibilities. Although we were committed to meeting the needs of our corporate partner, the development of the plan was not as urgent for the university team as it was for the corporate team. These differences led us to negotiate how the collaboration would work and to be creative with our solutions. In one such instance, the corporate team wanted to meet weekly to discuss the work, but the senior faculty members on the project were unable to commit this time on a weekly basis due to prior standing commitments. The doctoral researcher on the team, however, had substantially more flexibility in their schedule and thus a compromise was accepted in where the doctoral student would attend all the weekly meetings and the faculty would attend when they were able.

Unintended, yet Positive, Outcomes Emerged

Our third finding was that there were unintended outcomes of the UIC; namely, that we saw extended collaborations within and beyond the UIC. In this way, the UIC led to additional projects and relationships beyond this team, so the complementarity effects created new production lines. These additional collaborations came in the form of additional work with the company’s DEI team, partnerships with the company’s leadership for other topics of interest, and additional external work related to DEI.

One of the avenues for continued collaboration was borne out of our data analysis and our shared interest in work-based learning. When analyzing the human resources data, we found evidence that the company’s internal apprenticeship program was leading to improved work experiences for their employees, and this created a springboard for further joint exploration of apprenticeships, co-designing learning with industry partners, and competency development. Our collaboration extended to such a degree that the university and the company began discussing the relationship with their respective peers, and in this way led to discussions that dispelled myths about UICs for organizations in the local community.

Our successful relationship also led to additional collaborative projects with the company and with other community businesses. With the company itself, we discussed returning to this work on an annual basis to measure progress of the company’s DEI efforts and revise the plan as needed. Additionally, we undertook other projects with them unrelated to DEI, and these will likely lead to even further collaborations.

Expert Development as Apprenticeships

Our final finding relates to the development opportunities and the structure of our research teams. The opportunity of the UIC was used as a learning and developmental activity for undergraduate and graduate students. The university research team included a doctoral student, who was guided by two faculty members, while the industry team included two undergraduate and one graduate student interns, who were guided by the three corporate staff including members of the c-suite. This student-based structure enabled the UIC to function as an enhanced practicum in which the students gained real-world consulting experience that was directly relevant to their academic fields and professional goals. This type of experience shares several commonalities with other forms of work-based learning, such as apprenticeships, which involve significant invest in student-apprentices and capital.

The doctoral student researcher and the graduate intern were both pursuing careers in higher education. Besides their hands-on experience for future career development, the graduate students gained insights from both the academic team and the corporate team. The academic team mentored the students in an apprenticeship-like manner about research design, methodology, data collection, and analysis. The corporate team mentored the students in a work-based learning environment about organizational structure, culture, resources, supervision, systems, and operations.

All student team members gained experience in real-world research applications and corporate decision-making by working collaboratively across both teams. In this way, the UIC functioned as a type of interdisciplinary work-based learning in which participants were able to apply the skills learned for their internships and work towards an organizational goal in an environment that was still centered on learning and development.

Discussion

Given the dearth of research in this area, the focal project is just a starting point to this “complementarity investment” analysis. Specifically, this study finds that in a social science-based UIC, a complementarity investment framework presents four components explaining capital and skilled labor complements that enhance production inputs and advance project outcomes and party relationships. These four components of the framework are: (a) the parties identify and clarify their roles, activities, and contributions to manage expectations; (b) the parties participate in learning exchanges, which are significantly valued as a component to this UIC; (c) the parties are open to experiences including unintended, yet positive, outcomes emerging from the UIC; and (d) the parties capitalize on the Expert Development by guiding and mentoring students as apprentices. This UIC has led to additional partnerships in which all involved parties have room to expand work through new production channels and experiences, and the findings are significant for future UICs that examine project inputs and outputs using a complementarity investment framework.

Our findings suggest that complementary inputs can help minimize the barriers to successful and mutually beneficial UICs. Plewa et al. (2013) found that trust and understanding were critical for the engagement phase of UICs, and the first element of the framework, where parties establish roles and project vision, echo these findings. The UIC began with a shared vision, grounded within trust and understanding, and enabled us to openly communicate our goals and motivations for the work, which extended beyond the exchange of capital and labor to include advancing our research agenda and seeking publication of the work in academic journals. These early conversations allowed each party to clarify their role expertise and set realistic expectations for both product deliverables and timelines. This contributions-focused approach overcame concerns related to compromising academic freedom, which Tartari and Breschi (2012) have suggested may be a substantial barrier to successful UICs. While the magnitude of this threat necessarily differs between disciplines, in the social sciences, we found that open communication and discussion about product outcomes and features dispelled these concerns. Furthermore, clarifying role expertise worked to equalize power relations, which, when unchecked, has been shown to negatively affect UICs (Dougherty & Bakia, 2000), while setting realistic expectations at the outstart of the partnership helped mitigate future disagreements about timelines or conflicting expectations (Austin et al., 2021; Locket et al., 2008). As a whole, we found that open, candid, and frequent exchanges were paramount to our collaboration with industry.

These preliminary complementary inputs in the UIC led to collective growth outputs, as these inputs helped create a relationship built on mutual engagement, a key element in successful UICs (Gertner et al., 2011). In the second factor of the framework, where parties participate in and value learning exchanges, we began to see the development of collective growth outputs. The extant literature about UICs clearly documents differences in values and processes between academia and industry (Bruneel et al., 2010); however, less discussed are the benefits that can arise from these differences. For example, through these learning exchanges, all parties were challenged to re-evaluate their own processes, which not only aided in process improvements (e.g., the university auditing the diversity of its suppliers), but also further facilitated open communication that reduced barriers from misaligned processes (Bruneel et al., 2010) and preconceived judgments (Locket et al., 2008; Siegel et al., 2003). It was in the third factor of the framework, however, where we saw the greatest development of collective growth output.

Just as we began this partnership with an understanding that our goals extended beyond the exchange of capital and labor, we were also open to further collaborations and extensions of the current work, and this area is where we saw the greatest amount of collective growth outputs resulting from the UIC. While a common criticism of UICs is that they may stifle research and innovation (Collyer, 2015), our experiences echo previous studies showing how industry collaboration can benefit academic research (Bhullar et al., 2019; D’Este & Perkmann, 2011; O’Dwyer et al., 2022). Austin et al. (2021) found that successful UICs are marked by a critical evaluation of ideas and increased ambitions, and we saw markers of both these elements within our own experience. Given that our work was focused on diversity, equity, and inclusion (DEI) within a corporate environment, the critical feedback we received from our industry partners highlighted the differences between academic and corporate DEI strategies and led to a desire for increased community engagement, an outcome also demonstrated in previous literature (e.g., Kenny, 1989). Moreover, while previous literature has questioned whether UICs restrict communication between academics (Welsh et al., 2008), we found that this experience increased our networks both internally and externally.

While many of our findings recall previous studies about which factors lead to successful UICs, our research extends this work through the final element of the framework, in which the UIC becomes an apprenticeship experience for students. Much of the higher education literature presents UICs as decentralizing student needs and removing faculty from their core responsibilities of teaching and research (Slaughter & Leslie, 1997; Slaughter & Rhoades, 2000, 2004). Yet, by incorporating heterogeneous members into the team, the UIC project created a different narrative from the common criticisms regarding UICs deviating from the purpose of higher education and core faculty responsibilities. Instead, our findings suggest that when UICs adopt the complementarity investment framework, these experiences can serve as opportunities for experiential learning and student development. While previous studies have not addressed the potential work-based learning benefit of UICs in the social sciences, this arrangement reflects benefits found in other work. For example, students who participate in UICs can become intellectual boundary spanners, or individuals familiar with both university and industry contexts, who can provide critical linkages in future UICs (Gertner et al., 2011). The students and industry involved in the UIC may also benefit from establishing a recruitment pipeline that both meets industry needs and provides gainful employment for recent graduates (Fraser et al., 2011), and this retention may also benefit the economic development of the local communities (Locket et al., 2008).

Finally, our findings suggest that a complementarity investment is possible across university settings, including in colleges of education and human development, which is often viewed as an academic unit without a corporate centric focus. Although many UICs exist within applied science and technology fields, this study suggests that education scholars have more to offer industry than perhaps we might initially perceive. In certain domains, industry relations and education are largely untapped, and this UIC prompts further consideration about how education researchers may partner with industry to achieve mutual benefits. While the case presented here is only one example of social scientists engaging in a successful UIC, other research has shown that faculty engaging in UICs may improve both their teaching and research (Bhullar et al., 2019).

In fact, UICs may be particularly well-suited to social science research. McNall et al. (2009) found that successful collaborations may increase research on community needs and issues and working collaboratively to co-create knowledge may lead to improved client outcomes. Although their work was specifically looking at community-university partnerships, rather than university-industry partnerships, the findings retain relevance for those UICs focused on addressing social needs (e.g., a corporate DEIB plan). Expanding UICs to other disciplines also opens the possibility for newly found benefits, for, as Mendoza (2012) observed, not all universities or academic departments experience UICs as a negative event that circumscribes or eliminates the academy’s autonomy and values for commodification of knowledge that abdicates control.

Implications

This study presents implications for research and practice. First, our findings, building off the work of Mendoza (2012), suggest that the relational structures along with the partners’ exercise of agency offers another view to the UIC that differs from its typical operations within science and technology disciplines. Rather than being constrained by disciplinary norms, researchers across the academy should explore how they might be able to advance their goals through collaborative work with industry. While this study makes advances towards showing the effects of this collaboration within education, further research is needed to explore the effects of these collaborations based on field of study, researcher aims, and institutional characteristics.

Furthermore, our findings suggest that there is an unexplored connection between social science-based UICs and work-based learning (e.g., apprenticeships) that should be further explored. In practice, those involved in social science UICs should work to include undergraduate and graduate students in this work as a form of experiential learning. In turn, research should build upon the previous work of Fraser et al. (2011) and Locket et al. (2008) through examining the effects of these experiences on student development, employment outcomes, and community benefits. Beyond the social sciences, future research should also build upon our findings about the benefits to students through exploring differential effects on students who participate in UICs based upon their own disciplines.

Conclusion

As with many financially embedded relationships involving contractual commitments and academic research support, these arrangements, sometimes viewed as UICs, may come with benefits and drawbacks. On the one hand, critics associate knowledge commodification with researcher constraints, pressures dictated by perceived financial drivers, and secrecy and knowledge restraint as cornerstones to the relationship. On the other hand, supporters associate the work as a partnership built on mutual goals with proper capital to collaborate in meaningful ways. At times, there is also a hybrid version of these two dichotomous experiences. In all arrangements, there is an opportunity for the social sciences to benefit from industry collaborations when complementarity is considered at the outset of the relationship. D’Este and Perkmann (2011) suggest that “policy should refrain from overly focusing on monetary incentives for industry engagement and consider a broader range of incentives for promoting interaction between academia and industry” (p. 316), and we believe these incentives will be more apparent when parties clarify their roles and expectations, value learning exchanges, are open to new experiences, and make UICs learning experiences so that all parties may benefit from the complementarity investment.