Bridging the Gap Between Academia and Industry

Technological Hubs

When it comes to understanding the differences between academia and industry, an essential element to bridge the gap is the link between these two entities. Historically, establishing industry and organizational communication, however, has not been easy. This issue primarily stems from a need for industrial innovation, while academia needs to provide up-to-date information and practices that ensure newly trained professionals possess the essential knowledge, skills and abilities. According to Bikard and Marx (2020), the creation of technological firms can serve as the bridge between academia and industrial technologies. With focus from both parties, efficient and effective direction towards industry and academic innovation illuminates the importance of the technological hub (Bikard and Marx, 2020; Ocasio, 1997). 

To ensure essential aspects of industry and theory are comprehensively represented, collaborative efforts between industry and academia demands sustained link between theory and industry activities (Green and Erdem, 2016). This requires a close review of the differences between industry and academia and their experiences, both current and historical (Kolb, 1984; Svinicki & Dixon, 1987). By looking back and forth, industry and academia can study where each came from and  build their collective future.

A key challenge in transferring technology between universities and industry is bridging the organizations through their institutional processes (Murray, 2010; Sauermann and Stephan, 2012; Thornton et al., 2012), which may have conflicting sets of rules and norms (Tartari et al., 2012). Thus, another tool for integration in the technology hub is the  use of an intermediary. The need for knowledge management and retention is vital to organizational viability and healthcare information technology (IT) and academia are not exempt; therefore, using an intermediary may allow organizations to streamline their efforts, while the intermediary does the heavy lifting.

Sharing Information

For industry and academia to arrive at a shared understanding of what is required for success in healthcare IT, all parties must dispense of previous and current misgivings. Personal perspectives should not apply and only the collaborative outcome of both entities should remain. One such process to advance accomplishment is through application of a six-stage outer-loop workflow. According to Kross and Guo (2021), the ubiquitous nature of industry in the last decade, coupled with rapidly changing technology, calls for applying such a workflow for clarification. And through adaptation of this workflow, industry and academic can facilitate shared governance. This includes:

1. Laying groundwork by building trust between entities
2. Orienting the entities to potential constraints from shared efforts
3. Collaboratively framing a common goal
4. Bridging the gap between industry and academia
5. Establishing a Vinn diagram of the parties
6. Communicating with organizational stakeholders to facilitate the transition

From the academic perspective, application of the outer-loop workflow assists collaboration, which emanates from the teacher. Teachers serve on the front line of industry and academic collaboration. The instructional interaction between teacher and student affords opportunities to apply varying learning styles (e.g., physical, visual, auditory, verbal, etc.) to industry information and practices, and establishes teachers as the technological and knowledgeable decision-makers to ensure that students are prepared (Lalley and Miller, 2007). “One of the most essential ways of transferring knowledge is to facilitate the mobility of academics to industry and vice versa,” (Kunttu, Hutu and Nuevo, 2018), therefore, to ensure a smooth transition when students transition to the work sector, teachers must prepare them for the crossing into different organizational boundaries (Rajalo and Vadi, 2017).

From the industry perspective, while selecting an intermediary to facilitate knowledge management is a significant issue to address, addressing organizations barriers is equally important. These include: cultural differences (Bjerregaard, 2010), institutional differences (Bruneel et al., 2010), regulatory barriers (Jacobsson and Karltorp, 2013), and geographical distance (D'Este et al., 2013). These barriers are linked to the essential capital every organization needs to ensure its financial longevity—personnel. Given the increased demand to fill vacant industry positions with personnel trained in academic institutions, industry understands the challenge of balancing collaboration. The healthcare IT industry constantly needs academic institutions to produce graduates with indepth knowledge to make an impact in a rapidly changing labor market (Bongomin et. al., 2020).

Advisory Boards

Creating an advisory board can be great benefit for knowledge management of academic and IT industry and information continuity. Establishing a collaborative relationship to ensure that academic and IT industry stakeholders are represented can be challenging, but the process can be streamlined  by an advisory board. According to Mandviwalla, Fadem, Goul, George and Hale (2015), “Advisory boards offer an effective way to achieve mutually beneficial and sustained collaboration,” and increase collaborative value. But creating an advisory board requires effort and purpose. It involves merging the mission, goals and objectives of both organizations and arriving at a shared perspective. The initial stage of creating an advisory board is essential to its overall success, and to ensure there is a clear understanding of its mission (Koong, 2003). 

Creating the board’s mission can be done by each organization arriving at a common agreement about who should lead the board. In order to ensure both entities are properly represented, the best course of action in selecting the board leader is to hire an organization  to conduct the process. Each organization will provide their perspective as to how they would like the board to be constructed and the hiring entity will take this into account. Advisory boards in today’s environment are best served  by recruiting a diverse number of administrators who can offer differing perspectives. This would greatly assist the success and viability of the board for the IT organization and the academic institution (Summers, 2002).

Once the board chair and its members have been selected, the work of the board truly begins. The associated entities, who have a vested interest, can ultimately agree on shared governance and the purpose of the board. The very nature of shared governance on an advisory board can bring about slow decision-making, reduced efficiency and possible confusion (Donohue, 2014). So when creating an advisory board, there needs to be a clear understanding of the board and its processes. While advisory boards can help bridge the gap between industry and higher education, it is incumbent upon academic institutions and IT industry organizations to understand that togetherness brings success. This will help mitigate their historical challenges in communication and for those that may arise in the future.

Wrapping Up

There is work that needs to be done between academia and industry when it comes to sharing current and relevant information. The teachers in academia spend a lot of time ensuring they are teaching the current concepts to have students be career-ready, but they will be presented with challenges. Industry organizations should consider developing strategic partnerships with their local academic organizations to provide guidance on curricula, offer internships, fellowships and co-op opportunities, and to foster relationships between with teachers and the health IT industry. As innovation continues to advance in the industry, the best way to prepare future workers is to share knowledge with teachers in academia to ensure they are delivering instruction that meets the needs of the workforce. These efforts between industry and academia will support a path to bridging the gap.

References

1. Bjerregaard, T. (2010). Industry and academia in convergence: micro-institutional dimensions of R&D collaboration. Technovation 30 (2), 100–108.
2. Bongomin, O., Ocen, G. Gilbert., Nganyi, E., Musinguzi, A. and Omara, T. (2020). Exponential Disruptive Technologies and the Required Skills of Industry 4.0 Review Article Hindawi Journal of Engineering., Volume 2020, 1-17.
3. Bruneel, J., D'Este, P., Salter, A. (2010). Investigating the factors that diminish the barriers to university–industry collaboration. Res. Policy 39 (7), 858–868.
4. D'Este, P., Guy, F., Iammarino, S., 2013. Shaping the formation of university–industry re- search collaborations: what type of proximity does really matter? J. Econ. Geogr. 13 (4), 537–558.
5. Donohue, S. L. (2014). Shared governance at community colleges: Challenges and successes. ADFL Bulletin, 43(1), 58.
6. Jacobsson, S. & Karltorp, K. (2013). Mechanisms blocking the dynamics of the European offshore wind energy innovation system — challenges for policy intervention. Energ Policy 63, 1182–1195.
7. Kolb, D.A. (1984). Experiential learning: experience as the source of learning and development. Englewood Cliffs, New Jersey: Prentice Hal
8. Koong, K. S. (2003). Teaching Tip: Forming an Effective Information Systems Advisory Board. Journal of Information Systems Education, 14(2), 133.
9. Kross, S. & Guo, P. (2021). Orienting, Framing, Bridging, Magic, and Counseling: How Data Scientists Navigate the Outer Loop of Client Collaborations in Industry and Academia. Proc. ACM Hum.-Comput. Interact. 5, CSCW2, Article 311 (October 2021), 28 pages. https://doi.org/10.1145/3476052
10. Kunttu, L., Huttu, E., & Neuvo, Y. (2018). How doctoral students and graduates can facilitate boundary spanning between academia and industry.
11. Lalley, J. P., & Miller, R. H. (Fall 2007). The Learning Pyramid: Does It Point Teachers in the Right Direction? Education, 128(1), 64-79.
12. Mandviwalla, M., Fadem, B., Goul, M., George, J. F., & Hale, D. P. (2015). Achieving academic-industry collaboration with departmental advisory boards. MIS Quarterly Executive, 14(1), 17-37.
13. Michaël Bikard, Matt Marx (2020) Bridging Academia and Industry: How Geographic Hubs Connect University Science and Corporate Technology. Management Science 66(8):3425-3443. https://doi.org/10.1287/mnsc.2019.3385.
14. Murray, F., 2010. The oncomouse that roared: Hybrid exchange strategies as a source of dis-tinction at the boundary of overlapping institutions. Am. J. Sociol. 116 (2), 341–388.
15. Ocasio W (1997) Towards an attention-based view of the firm. Strategic Management J. 18:187–206.
16. Rajalo, S. & Vadi, M. (2017). University-industry innovation collaboration: Reconceptualization. Technovation, 62-63 (April) 42-54. Doi: https://doi/10.1016/j.technovation.2017.04.003.
17. Sauermann, H., Stephan, P., 2012. Conflicting logics? A multidimensional view of industri- al and academic science. Organ. Sci. 24 (3), 889–909.
18. Summers, M. (2002, June). Developing a college industry relationship: The use of industrial advisory boards. In 2002 Annual Conference(pp. 7-388).
19. Svinicki, M. D., & Dixon, N. M. (1987). Kolb model modified for classroom activities. College Teaching, 35 (4), 141-146.
20. Tartari, V., Salter, A., D'Este, P., 2012. Crossing the Rubicon: exploring the factors that shape academics' perceptions of the barriers to working with industry. Camb. J. Econ. 36 (3), 655–677.
21. Thornton, P.H., Ocasio, W., Lounsbury, M., 2012. The Institutional Logics Perspective: A New Approach to Culture, Structure, and Process. Oxford University Press, Oxford.