IMPORTANCE OF SOCIAL CAPITAL FOR KNOWLEDGE ACQUISITION – DEEPLIFT LEARNING FROM INTERNATIONAL DEVELOPMENT PROJECTS

This paper aimed to examine the influence of internal and external social links within NGOs’ international development project ecosystems on the knowledge acquisition process. The goal was to propose a model that enhances the gathering and transformation of missing knowledge, leading to more effective solutions for the complex developmental challenges faced by different NGOs. A dataset was gathered from 215 NGOs operating in the European Union and Western Balkans, involved in international development projects. Neural network models were employed to develop a prediction model that accurately distinguished between high and low levels of knowledge acquisition (with AUC values exceeding 0.8 for each model). Additionally, by utilizing advanced methodology, we uncovered valuable insights into the key factors contributing to an NGO’s level of knowledge acquisition. These findings have significant implications for NGO international development efforts, growth, and performance. The predictive and interpretable mathematical models, based on neural networks, demonstrate the highest accuracy in identifying the social capital factors that most strongly influence organizations operating with varying levels of knowledge acquisition.