Knowledge Integration in Convergence Research: A Theoretical and Empirical Investigation

Convergence research has gained traction as an approach to address complex societal and environmental challenges by integrating diverse forms of knowledge across disciplines and sectors. We know relatively little about how such integration is defined, structured, and enacted in practice. This dissertation examines how convergence is conceptualized and operationalized in a large, cross-disciplinary and cross-sectoral project, particularly in relation to knowledge integration (KI). It comprises of three interconnected studies focused on answering an overarching research question: How is convergence conceptualized and operationalized in a National Science Foundation Growing Convergence Research (NSF-GCR) project, particularly in relation to knowledge integration (KI)? Study 1 provided the theoretical and conceptual foundations for this research. It focused on four key objectives: (a) understanding the ontological and epistemological perspective on KI, (b) identifying the meta-theoretical and methodological approaches to KI, (c) identifying dimensions of KI in cross-disciplinary collaborations, and (d) developing a conceptual framework of KI to identify the types of knowledge assembled (inputs), how knowledge is exchanged and integrated (processes), and what knowledge integration yields (outputs). To do so, it combines a scoping review methodology with a cited reference search and synthesized three domains of literature: (1) studies of inter- and transdisciplinarity; (2) studies of knowledge co-production in sustainability research; and (3) studies focusing on factors influencing knowledge integration in the Science of Team Science (SciTS) field. The study identifies eight dimensions of knowledge integration: (1) types of knowledge integrated, (2) competencies and education required to practice knowledge integration, (3) organizational structure, (4) types of actor involvement, (5) stages of collaboration, (6) contextual factors, (7) processes and mechanisms of knowledge integration, and (8) types of knowledge integration outcomes. It further organizes these dimensions into a conceptual framework of KI using an Input-Process-Output (IPO) model by O'Rourke et al., (2016). This framework is intended to function as a heuristic to prompt teams to adapt it to specific contexts, projects, and team configurations. It can also be used as a scaffold for designing and evaluating knowledge integration efforts in diverse collaborative settings. The second and third studies used this conceptual and theoretical framework to understand how the members of a National Science Foundation-funded Growing Convergence Research (NSF-GCR) project understand and practice convergence research. Specifically, the second study examined the social architecture of the team Using Social Network Analysis (SNA) and self-reported measures of members' transdisciplinary orientation (Misra et al., 2015), this study uncovered the types of collaborative communities, broker, and integrator roles that emerged in the team and examined how these communities and roles corresponded to team members' network positions and orientations. The study modeled an undirected, weighted collaboration network using twenty team members' levels and frequencies of collaboration with peers and contextualized the network patterns with open-ended responses on team dynamics. It identified three collaborative communities: a leadership core of experienced integrators, mentor-mentee pairs, and domain anchors who provided technical expertise. Broker (major brokers, information carriers, satellite collaborators) and integrator (cross-cluster, hidden, within-cluster, narrow) role classification revealed that boundary spanning depended on the interplay of personal orientation, opportunity, and project context. Influence was distributed beyond formal leadership, boundary spanning was not determined by seniority, and subgroup expertise and between-group reach reinforced each other. Study 2 further outlined practical applications of SNA for the evaluation and design of scientific teams that aim for knowledge integration across disciplinary boundaries. Finally, Study 3 addressed how knowledge is assembled, translated, and routed across science and policy arenas the NSF-GCR project. Using an abductive research methodology, and participant interviews, story maps, and archival research as methods, this study: (a) understood how convergence is conceptualized and operationalized by academic and professional experts in the team; and (b) elaborated an earlier conceptual framework for knowledge integration elaborated in study 1 (Punjabi et al., 2025). I found that participants understood convergence as their ability to co-reason together under evolving constraints through adaptable representations, with progress marked not by consensus or cognitive reframing, but by artifacts that were routable, durable, and auditable across different venues and audiences. I also identified the conditions under which boundary objects become interpretable and actionable in environmental policy contexts. It also determined how boundary orchestration can yield legible and credible decision-making outputs and offered transferable insights and hypotheses to inform the design and evaluation of future convergence efforts tackling complex environmental challenges. Together, this three-manuscript dissertation offers a layered and evolving account of how convergence is conceptualized and operationalized in practice, especially in relation to KI. I examined KI from three vantage points: (a) as a plural, multidimensional construct in the literature; (b) as a patterned social architecture of roles, ties, and orientations in a convergence team; and (c) as boundary orchestration work through which people co-reason under evolving constraints via shared representations. Across these lenses, the dissertation suggests that convergence is not a single endpoint or a stable state of integrated knowledge, but a capacity of the team that develops and evolves over time.

Name thesis:degree_name

Doctor of Philosophy

Level thesis:degree_level

doctoral

Discipline thesis:degree_discipline

Planning, Governance, and Globalization

Department dc:contributor.department

Public Administration/Public Affairs

Grantor dc:publisher

Virginia Tech

Year dc:date.issued

2026

Author dc:creator

• Punjabi, Shruti Rajesh

Chair dc:contributor.committeechair

• Misra, Shalini

Committee members dc:contributor.committeemember

• Lim, Theodore Chao
• Schenk, Todd Edward William
• Galappaththi, Eranga

• Convergence Research
• Knowledge Integration
• Inter- and Transdisciplinary Research
• Science of Team Science
• Knowledge Co-production

Statement dc:rights

• In Copyright

Licence dc:rights.uri

• http://rightsstatements.org/vocab/InC/1.0/

Language dc:language.iso

en

Dc Identifier Other

vt_gsexam:45525

OAI identifier oai:identifier

oai:vtechworks.lib.vt.edu:10919/140573