Interdisciplinary Collaborations in Academia: Modeling the Roles of Perceived Contextual Norms and Motivation to Collaborate

Abstract

ABSTRACTIn academia, interdisciplinary collaborations allow individuals with different areas of expertise and resources to accomplish shared goals. Nevertheless, because interdisciplinary scholars often have different knowledge areas or methodological training, such collaborations may be less likely to form. In this manuscript, we provide a step toward understanding how interdisciplinary collaborations form within academic contexts. Specifically, we propose a model in which the effect of organizational norms on collaborative outcomes are mediated by departmental norms and motivation, sequentially. To test this model, 197 interdisciplinary faculty members from a large university in the Northeast were surveyed. Overall, the results provide some support for our proposed model, such that if organizations provide structural support and foster an environment that welcomes collaborations, interdisciplinary collaborative relationships will be more likely to form (i.e. faculty members will be increasingly motivated to engage in interdisciplinary research).KEYWORDS: Interdisciplinarycollaborationsnormsmotivationmultilevel Disclosure statementNo potential conflict of interest was reported by the authors.Notes1. The hypothesized model is unidirectional for model testing purposes, and the chosen direction is based on theoretical considerations (e.g., multilevel theory). Although, this is not to suggest that only one direction is possible (e.g., the reverse causal model is also plausible). This matter is addressed further in the discussion.2. Given the nature of the sample and data collection, it was possible for respondents to choose intra-departmental members as collaborators. If these types of relationships were removed from the analysis, the results and conclusions remained virtually identical. As such, their inclusion or exclusion made no difference in the analysis.3. Preliminary analyses showed that none of the main variables differed significantly when making comparisons between the different departmental groups.4. Because this was a global variable, respondents were not able to report different attendance numbers for workshops, colloquia, etc.5. PATH is a DOS-based program that can be used to perform path analysis. This program was run using the DOS emulator DOSBox (Veenstra et al., Citation2019), and a free copy of PATH can be attained from the first author.6. This model also fits the data when controlling for the demographic variables (χ2[6] = 3.25, p = .77), and when using full information maximum likelihood estimation procedures (χ2[6] = 6.04, p = .42). These analyses were performed using the lavaan package in the R software environment (R Core Team, Citation2023; Rosseel et al., Citation2023).Additional informationNotes on contributorsBrian ManataBrian Manata (PhD Michigan State University, 2015) is an assistant professor in the Department of Communication Arts and Sciences at Pennsylvania State University, University Park, Pennsylvania, USA. His research focuses on organizational behavior, especially as it pertains to groups and teams. His work has appeared in Management Communication Quarterly, Project Management Journal, International Journal of Project Management, and Human Communication Research.Jessica BozemanJessica Bozeman (MA Northern Illinois University, 2019) is a doctoral student in the Department of Communication Arts and Sciences at Pennsylvania State University, University Park, Pennsylvania, USA. Her research investigates the social nature of group communication and has previously appeared in Communication Studies.Karen BoyntonKaren Boynton (BA University of Minnesota Duluth, 2020) is a graduate student in the Department of Communication Arts and Sciences at Pennsylvania State University, University Park, Pennsylvania, USA. Her research focuses on disclosures in interpersonal communication. Her work has appeared in Interpersona: An International Journal on Personal Relationships and Technology, Mind, and Behavior.Zachary NealZachary Neal (PhD University of Illinois at Chicago, 2009) is a Professor in the Department of Psychology at Michigan State University, East Lansing, MI, USA. He studies network methods and theory, and he has written and edited numerous books on these topics. His work has also appeared in numerous journals (e.g., Scientific Reports, Nature Reviews Methods Primers, and Psychological Methods).