Addressing complex problems through industry-academic collaboration: A temporal perspective on scientific knowledge production

TY - ABST

T1 - Addressing complex problems through industry-academic collaboration:

T2 - Open<br/>Innovation in Science Research Conference 2022

AU - Hilbolling, Susan

AU - Smith, Pernille

PY - 2022/5

Y1 - 2022/5

N2 - Open science collaborations, such as research consortia, are particularly suited for tackling complex problems or grand challenges because they bring together diverse knowledge. At the same time however, when open science collaborations involve a heterogeneity of parties, this can create tensions in the knowledge production process. For example, industry partners' involvement potentially impair university scientists’ opportunities to do basic research (e.g., Beck at al., 2021) because they are driven by commercial incentives (e.g., patents, innovation). This raises the question of how scientific knowledge production activities for complex problems can be organized in open science collaborations, so that it accommodates both individual parties and collective knowledge goals. This question might not be completely new, however, in recent years we are witnessing a growth in huge and much more complex industry-university collaborations, and we believe that we are dealing with a different kind of collaboration setting than traditional more confined industry-university collaborations. By adopting a process research approach (e.g., Langley et al., 2011), we aim to unpack how parties accommodate differences in interests as the collaborative process unfolds over time. To address our research question, we perform an in-depth longitudinal case study of a large research consortium in the healthcare sector. The goal of the consortium is to advance knowledge on a serious but understudied complication of diabetes that has severe consequences for patients’ health and well-being and society at large. We have been following the work between scientists from universities and companies for over three years through meeting observations, interviews, and documents (data collection and analysis are still ongoing). Our preliminary analysis revealed that while the consortium is “pre-competitive”, the parties were highly strategic about their involvement, yet this didn’t create the expected tensions but instead fostered the scientific collaborations. We explain this empirical surprise through analyzing three complementary types of knowledge production activities that were key in the collaborative process: (1) “knowledge organization and validation” aimed at collecting prior research evidence through e.g., pooling past clinical data in a big database and literature reviews, (2) “knowledge expansion” aimed at building a foundation for future research (i.e., basic science), and (3) “knowledge alignment” aimed at bringing together dispersed knowledge together through e.g., creating new standards and measurement tools. Interestingly, the (strategic) relevance and impact of the knowledge output of each of these activities had a time-horizons that span far beyond the duration of the consortium (4 years), i.e., long after the collaboration would officially be dissolved. Stated differently, the relatively short time frame of consortium enabled collaboration that would benefit the involved parties in the long term. This study provides insight into how open science collaboration with industry partners can be designed by balancing knowledge work within and outside the temporal boundaries of the collaboration. By doing so we address a call for more research on industry-academia collaboration on scientific activities that are not aimed at innovation (Heimstadt and Friesike, 2020).

AB - Open science collaborations, such as research consortia, are particularly suited for tackling complex problems or grand challenges because they bring together diverse knowledge. At the same time however, when open science collaborations involve a heterogeneity of parties, this can create tensions in the knowledge production process. For example, industry partners' involvement potentially impair university scientists’ opportunities to do basic research (e.g., Beck at al., 2021) because they are driven by commercial incentives (e.g., patents, innovation). This raises the question of how scientific knowledge production activities for complex problems can be organized in open science collaborations, so that it accommodates both individual parties and collective knowledge goals. This question might not be completely new, however, in recent years we are witnessing a growth in huge and much more complex industry-university collaborations, and we believe that we are dealing with a different kind of collaboration setting than traditional more confined industry-university collaborations. By adopting a process research approach (e.g., Langley et al., 2011), we aim to unpack how parties accommodate differences in interests as the collaborative process unfolds over time. To address our research question, we perform an in-depth longitudinal case study of a large research consortium in the healthcare sector. The goal of the consortium is to advance knowledge on a serious but understudied complication of diabetes that has severe consequences for patients’ health and well-being and society at large. We have been following the work between scientists from universities and companies for over three years through meeting observations, interviews, and documents (data collection and analysis are still ongoing). Our preliminary analysis revealed that while the consortium is “pre-competitive”, the parties were highly strategic about their involvement, yet this didn’t create the expected tensions but instead fostered the scientific collaborations. We explain this empirical surprise through analyzing three complementary types of knowledge production activities that were key in the collaborative process: (1) “knowledge organization and validation” aimed at collecting prior research evidence through e.g., pooling past clinical data in a big database and literature reviews, (2) “knowledge expansion” aimed at building a foundation for future research (i.e., basic science), and (3) “knowledge alignment” aimed at bringing together dispersed knowledge together through e.g., creating new standards and measurement tools. Interestingly, the (strategic) relevance and impact of the knowledge output of each of these activities had a time-horizons that span far beyond the duration of the consortium (4 years), i.e., long after the collaboration would officially be dissolved. Stated differently, the relatively short time frame of consortium enabled collaboration that would benefit the involved parties in the long term. This study provides insight into how open science collaboration with industry partners can be designed by balancing knowledge work within and outside the temporal boundaries of the collaboration. By doing so we address a call for more research on industry-academia collaboration on scientific activities that are not aimed at innovation (Heimstadt and Friesike, 2020).

KW - Industry-University collaborations

KW - Complex Problems

KW - Knowledge production

KW - Scientific knowledge

KW - Process Theory

M3 - Conference abstract for conference

SP - 15

EP - 15

Y2 - 11 May 2022 through 13 May 2022

ER -