Being financially and technologically worse off than their counterparts in developed nations, many developing countries face natural disasters that cut them off from the rest of the world and cause excessive damage to invaluable human life and property. Sudden disasters require timely and accurate response from stakeholders to provide immediate relief while deploying scarce resources effectively. However, due to the large number of humanitarian aid agencies from different developed countries and a lack of knowledge, there is duplication of relief in many areas while countless more are left unattended. In this thesis, Resource Dependence Theory and Stakeholder Theory were employed to analyse how humanitarian organisations deliver services during a disaster. Systematic literature review was utilised for collecting data and the data was analysed using thematic analysis. During the data collection process, 300 papers were initially identified however, after further reassessment, 33 papers were left to be further analyzed. From this the researcher was able to identify that the use of Big Data in developing countries is proving to be extremely beneficial to humanitarian efforts, according to this thesis. It also explains how humanitarian organizations can make better use of big data by overcoming obstacles. The thesis suggests that increasing the number of data scientists and specialists by conducting big data training for staff, improving data governance (regulations, controls, and transparency), and enhancing privacy and security will result in major improvements in humanitarian operations. Give the importance of private stakeholders, companies' roles extend far beyond delivering profits to their shareholders, they must also address social issues by participating in disaster and humanitarian operations in developing countries.
