Analysis reveals technological efficiency and training are key predictors of digital procurement platform use in R&D, suggesting an integrated adoption approach.
Purpose: This study integrates the KANO model, Institutional Theory, DOI, and TAM to identify factors affecting the adoption and use intention of digital procurement platforms in R&D.Methods: A two-stage mixed-methods design was used. Study 1 (KANO model) analyzed user satisfaction with platform functions. Study 2 (PLS-SEM) tested adoption factors using data from 188 R&D practitioners.Results: Most platform functions were classified as attractive or one-dimensional quality attributes. Technological efficiency and external support & training were key predictors of use intention; supply chain pressure was not. The effect of technological efficiency was stronger for office workers than for researchers.Conclusion: Effective platform diffusion requires an integrated approach considering organizational support and user satisfaction. This research expands the theoretical foundation for R&D technology adoption and provides practical, data-driven guidelines for platform strategy.
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Song et al. (2025) studied this question.
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