Why one perspective is not enough: theory-data alignment for dyadic, triadic, and network studies in supply chain management
Article
Patrucco, AS, Guntuka, L, Mukandwal, PS et al. (2026). Why one perspective is not enough: theory-data alignment for dyadic, triadic, and network studies in supply chain management
. International Journal of Production Economics, 297 10.1016/j.ijpe.2026.110022
Patrucco, AS, Guntuka, L, Mukandwal, PS et al. (2026). Why one perspective is not enough: theory-data alignment for dyadic, triadic, and network studies in supply chain management
. International Journal of Production Economics, 297 10.1016/j.ijpe.2026.110022
Supply chain management (SCM) research increasingly recognizes that single-informant designs cannot capture the complexity of interorganizational relationships. Dyadic, triadic, and network designs incorporate multiple actors and can yield richer evidence, but they also introduce substantial theoretical, methodological, and practical challenges. As the introductory article to the International Journal of Production Economics Special Issue “Revamping multi-tier supply chain relationships: Using dyadic, triadic, and network data to explore uncharted territory and discover new frontiers,” this paper synthesizes recent evidence on how multi-party designs are used and proposes how they can be executed rigorously in new research. We conduct a structured review of empirical SCM studies published between 2018 and 2025 in all of the eight journals from the SCM Journal List to assess how dyadic, triadic, and network designs have been used. We identify dominant research themes, theoretical perspectives, and methodological approaches across dyadic, triadic, and network studies, and we diagnose recurring misalignments between theoretical constructs and data structures, along with persistent barriers to data collection and analysis. Based on this evidence, we provide actionable recommendations on when and how to employ dyadic, triadic, and network designs and outline strategies for data collection, measurement, and analysis. Overall, this paper offers guidance to strengthen theoretical justification, methodological rigor, and practical feasibility for scholars using multi-party designs in the SCM domain.
