The Dawn of Advanced Collaborative Practices
Authors: Gaudio Eva Lorraine 
Published: January 2025

The likelihood of academic collaboration is influenced by specific characteristics that
vary across attributes and associations. For instance, social networks have been found to
influence the adoption of evidence-based instructional practices and interdisciplinary
research performance. This study examines research collaboration practices at a university
to support initiatives in increasing interdisciplinary collaboration.
Purpose: The study has three aims: 1) to characterize existing
collaborative research practices under the university systems and policies in effect at
the start of this project in a sample of faculty researchers; 2) to gain a better
understanding of the historical network structure of research using collaborative grant
proposal data; and 3) to understand the network characteristics of recently-established,
thematically-focused research teams that the university-sponsored to address Grand
Challenges (GCs) — wicked problems as they manifest regionally in Idaho. Thus, the
thesis provides two baselines for assessing future social networks of research
collaboration and collaborative practices: the overall collaborative grant proposal
network and the effectiveness of research team support strategies.
Hypothesis: Diverse social networks lead to more innovative thinking,
greater productivity, and the overall value of research. Networks that exhibit
parochialism and inequality are less innovative and productive and tend to benefit those
already successful. Networks with limited brokerage tend to have disciplinary connections.
Methods: I conducted semi-structured interviews of n = 5 faculty and
utilized focus group data on research collaboration. Social network analysis methods
analyze a network of collaborative grant proposals at Boise State from 2016 to 2020,
including whole network statistics and predictive modeling using exponential random graph
methods (ERGM) to assess predictors of tie formation. Survey responses from researchers in
GCs teams outline team interactions and experience diversity before the infusion of
network treatments. Statistical Analysis: ERGM results of the grant
proposal network indicate uniform homophily (intra-college co-proposing) and selective
mixing (connection patterns based on proposal volume) also significantly predict tie
formation. Results: Thematic analysis reveals that collaboration is
shaped by academic culture, institutional structures, and interpersonal dynamics,
influencing its perception and practice and affecting the balance between collaborative
and individual research efforts. Analysis of the collaborative grant proposal network
uncovers disparities in collaborative opportunities. Furthermore, the network's
year-over-year analysis, particularly in 2020, spotlighted the pandemic's disproportionate
impact on collaborative efforts, with the highest levels of network connectivity and
cumulative advantage observed alongside the lowest number of collaborators and proposals.
Selective mixing analysis exposed a clear preferential attachment pattern that intensified
as the researchers increased their grant proposal activity. The distribution of
researchers with high betweenness centrality (brokers) reveals a select few occupy
significant broker roles, potentially facilitating interdisciplinary collaborations within
the research network. A comprehensive strategy details network treatment methods and
evaluation of support strategies to foster exemplary research teams while expanding
campus-wide research opportunities. Discussion: The analysis highlighted
significant disparities in collaborative opportunities within Boise State's grant proposal
network, emphasizing the emergence of scientific stars due to cumulative advantage. This
imbalance suggests a need for strategic interventions to foster more equitable
collaboration. There is a noted tendency among researchers to collaborate within their
disciplines, indicating potential obstacles to interdisciplinary efforts. This thesis
proposes measuring interdisciplinary treatments to evaluate and enhance the success of
efforts to increase interdisciplinary collaboration. The study advocates for using the
betweenness centrality metric in selecting GCs team members to include researchers not
currently serving as interdisciplinary brokers. This approach aims to expand the network's
capacity for diverse connections across research communities. Empirical evidence supports
that increasing interconnections between research communities will elevate
interdisciplinary collaborations. The study underscores the potential of well-connected
networks to create a self-sustaining environment for interdisciplinary partnerships,
reducing the need for additional interventions.