AI-Powered Multi-Stakeholder Ecosystems for Global Development: A Design Research Study on the GSI D-Hub Proof-of-Concept Platform

TL;DR

This paper introduces the GSI D-Hub, a data-driven platform utilizing explainable AI to facilitate transparent collaboration among stakeholders in global development, improving trust and decision-making.

Contribution

It presents a novel design of an explainable AI-powered platform that enhances transparency and trust in multi-stakeholder digital ecosystems for development.

Findings

Explainable recommendations increase stakeholder trust.

Contextual dashboards improve decision confidence.

The platform reduces data asymmetries and enhances data quality.

Abstract

Digital platforms increasingly support collaboration across organizations, yet many remain constrained by fragmented data and limited transparency. This paper presents the Global Solutions Initiative (GSI) D-Hub, a data-driven coordination platform that applies explainable artificial intelligence (AI) for transparent matchmaking among deployers, solution providers, and financiers. The system integrates structured data models, interpretable algorithms, and synthetic data pipelines to reduce information asymmetries and improve data quality. Using a design-science approach, the platform was developed and validated with stakeholders from development, technology, and finance sectors. Results show that explainable recommendations and contextual dashboards enhance trust, usability, and decision confidence. The study contributes to data mining and data governance research by demonstrating how explainable, verifiable algorithms can enable scalable, trustworthy digital ecosystems for public collaboration.