PROBLEM FRAMING IN UNIVERSITY-INDUSTRY COLLABORATIONS: THE CASE OF KNORR
Editor: Bohemia, Erik; Kovacevic, Ahmed; Buck, Lyndon; Brisco, Ross; Evans, Dorothy; Grierson, Hilary; Ion, William; Whitfield, Robert Ian
Author: Laursen, Linda Nhu; Haase, Louise M
Institution: Aalborg University, Denmark
Section: Industrial 2
DOI number: https://doi.org/10.35199/epde2019.75
Universities increasingly welcome student-industry collaborations. The rationale is, while the collaborating firm are introduced to new valuable knowledge, students gain experience with real life challenges. However, experience shows it may be challenging for a firm, to get the desired outcome from university collaborations. Firms report, that the students’ work outcome is disappointing; it does not add any new knowledge. Opposite many university teachers reject industry projects, as they find that the learning may be compromised, in favour for industry demands.
In this study, we examine, how to frame problems for successful industry-university collaborations. We explore two key dimensions in respect to the problem framing. First of all we explore the value of students tapping into knowledge and experience domains, where their expertise is higher than the industry partners’. And we explore the influence problem framing openness have on the outcome of student work, as well as the satisfaction on both sides.
In this study, we have set up an university-industry collaboration, where we connect the problem framing directly with one of the students’ experience domain, to explore whether and if this may produce more valuable output. Secondly, we have set up two quasi-experiments, where we vary the openness of the problem frame. The study indicate, that connecting the problem framing to a experience domain, where the students have more expertise than the industry partner, can be highly valuable for the result. More over the study highlight the importance identifying the firms’ implicit assumptions and challenges these in order to identify the right level of openness (or abstraction) in the problem frame.