A phrase mining and qualitative comparative analysis incorporating stakeholder perspectives in international engineering projects

Big data;Data mining;International development;Contextual engineering;Monitoring and evaluation;Rural water

Schreiber, Kelsey L. ; Hansen, Alan, ; ,Michelson, Hope ; Rodríguez ; Luis

关键词: Big data;    Data mining;    International development;    Contextual engineering;    Monitoring and evaluation;    Rural water;   

Others  :  https://www.ideals.illinois.edu/bitstream/handle/2142/106282/SCHREIBER-THESIS-2019.pdf?sequence=1&isAllowed=y

美国|英语

来源: The Illinois Digital Environment for Access to Learning and Scholarship

【 摘 要 】

Water projects in developing countries are often perceived as failures; however, with a variety of major actors involved in these projects, the definition of a successful project is hard to find. This research demonstrates and quantifies the mismatch in the project evaluation criteria of four main stakeholders: engineer, funder, government, and international non-governmental organizations (NGOs). I compile stakeholder project documentation and metadata into a novel Stakeholder Evaluation Database (SED), which I then mine to find top-ranked representative phrases for each stakeholder. The comparison of top representative phrases shows differing stakeholder priorities: Engineers focus on project travel and documentation, funders focus on budget and performance, governments focus on development issues like health, gender, and environment, and NGOs focus on motivation and technical specifications. These representative phrases are compared across stakeholders using cosine similarity to quantify the gap between stakeholder priorities. I find that governments and NGO representative phrases are the least similar, while engineers and NGOs are the most similar. I then use qualitative comparative analysis (QCA) to determine underlying patterns of success and failure by constructing success and failure pathways composed of top representative phrases for each stakeholder. QCA shows that a stakeholder's success and failure pathways are significantly correlated with predicting their outcomes but perform poorly at predicting other stakeholder's outcomes. This project contributes a new methodological approach to understanding the definition of success to better evaluate project sustainability in international engineering projects and emphasizes the importance of inter-stakeholder communication to support project success.