INSTITUTIONAL DRIVERS OF RESPONSIBLE OPEN SCIENCE IN EURASIA: AN EXTENDED PLS-SEM FRAMEWORK

Research systems across Eurasia are being asked to improve transparency, integrity, data reuse, and international engagement while operating under uneven legal, technological, and institutional conditions. This paper develops a revised survey-based framework for explaining responsible open science at universities and research organisations, with particular relevance to Central Asia. Unlike models that treat ethics, data management, and training as the only antecedents, the proposed framework adds digital research infrastructure, incentive alignment, leadership support, and researchers’ practical open-science competence. Seven latent constructs are connected through direct, mediating, and moderating relationships and can be tested using partial least squares structural equation modelling (PLS-SEM). The model assumes that ethical-regulatory governance and digital infrastructure build data stewardship capability; competence, incentives, and stewardship then shape the institutionalisation of open science; and institutionalisation improves international scientific connectivity. The study proposes a multilingual questionnaire, a cross-country sampling strategy, and an analysis procedure incorporating measurement invariance, multi-group analysis, mediation, moderation, predictive assessment, and importance-performance mapping. The framework offers universities, funding bodies, and public authorities a diagnostic instrument for moving from formal open-science declarations toward reliable, rewarded, and reusable research practices.