Enhancing Discoverability and Sustaining Open Scholarship: Indexing Challenges in Multidisciplinary Repositories and Lessons from Disciplinary Platforms

Open access repositories are essential for modern scholarly communication, yet disparities in indexing practices limit their effectiveness and sustainability. This paper examines indexing constraints in Zenodo, a multidisciplinary repository, compared to the enhanced discoverability of the Social Science Research Network (SSRN). Using a hierarchical Bayesian framework with Monte Carlo simulations and sensitivity analyses, we quantify discovery delays due to incomplete integration with search engines like Google Scholar. Empirical validation is conducted using real data from the OpenAIRE Graph (September 2025 snapshot), revealing average delays of several weeks to months for Zenodo compared to days in SSRN. Advanced statistical analyses, including t-tests (\(p < 0.001\)), ANOVA (F=145.2, \(p<0.001\)), and Bayes factors (>150), confirm significant differences. Results indicate significant reductions in delay risks through optimized strategies. We provide evidence-based recommendations to improve Zenodo's metadata and crawling compatibility while upholding open access principles. This study underscores implications for equitable open scholarship, especially for independent researchers in resource-constrained settings, and calls for community-driven validation to inform repository advancements.