Shows local staff improve project outcomes in international organizations, indicating effective localization strategies.
International organizations (IOs) rely on locally hired staff to translate global mandates into local action, yet the performance implications of localization remain contested. Addressing this gap, this study combines natural language processing (NLP) with a novel dataset of 5,230 project evaluations and staffing information from five United Nations organizations (2007–2022). Building on current research on local staff employment in IO projects together with insights from expert interviews, we test two dominant competing arguments: local capture versus local knowledge. Multilevel and fixed-effects analyses show that projects with higher shares of local staff perform significantly better, but only once local employees constitute at least 60% of the team. The results advance theory on IO effectiveness by shifting attention from local discretion to staff composition, demonstrating that locally embedded knowledge, when institutionally represented in staffing, constitutes a key organizational resource for adaptive implementation.
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Eckhard et al. (2026) studied this question.
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