R&D 분야 디지털 구매 플랫폼 이용 요인 연구: KANO 모델과 제도이론, 혁신 확산이론, 기술 수용 모형의 통합적 접근
A Study on Factors Influencing Digital Procurement Platform Use in R&D Settings: Integrating KANO Model, Institutional Theory, Diffusion of Innovation, and Technology Acceptance Model
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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.
Abstract
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.