Designing a Causal Model of the Key Drivers of Online Research Platform Development: A Grounded Theory and DEMATEL Approach

Abstract

This study aimed to design and explain a causal model of the key drivers of online research platform development and determine their relative importance, influence, and dependence. This applied-developmental and exploratory study employed a qualitative–quantitative mixed-methods design. In the qualitative phase, data were collected through semi-structured interviews with experts in research management, information technology, digital research infrastructure, and scientific platform management. Participants were recruited through purposive and snowball sampling, and interviews continued until theoretical saturation was achieved. The data were analyzed using grounded theory through open, axial, and selective coding. The extracted dimensions and components were subsequently validated and refined using the fuzzy Delphi method. In the quantitative phase, 16 experts evaluated the pairwise effects among the finalized components. The causal relationships, overall prominence, and net influence or dependence of the components were examined using the Decision-Making Trial and Evaluation Laboratory method. The test–retest reliability coefficient for interview coding was 87.50%. The fuzzy Delphi results indicated that the differences between the experts’ mean assessments were below the 0.20 threshold for all components; therefore, all nine components were retained, demonstrating expert consensus. The DEMATEL analysis showed that alignment with the institutional research order ((R-C=1.826)) and platform management and governance ((R-C=1.276)) were the strongest net causal drivers. Trust formation or erosion ((R+C=7.431)) and networking and collective action ((R+C=7.101)) had the highest overall prominence and interaction within the causal network. Perceived research outcomes ((R-C=-1.710)), trust formation or erosion ((R-C=-0.699)), networking and collective action ((R-C=-0.515)), researcher competence development or weakness ((R-C=-0.289)), and data protection and research ethics ((R-C=-0.241)) were classified as effect-group components. Sustainable online research platform development should begin with institutional reforms and transparent, accountable platform governance, followed by investment in technological infrastructure, data protection, research ethics, and scientific networking. Strengthening these causal and intermediary drivers can enhance user trust, researchers’ digital competencies, and the perceived benefits of platform-based research.