Establishing a Relationship Model of Project Finance Factors Influencing Economic Development: Case Study of Abu Dhabi Economic Department - Ahmed Alhashmi, Saif Fadhel Kamel; Omar, Abdul Jalil (International Journal of Sustainable Construction Engineering and Technology, 2023)
Project finance plays a key role in supporting UAE’s infrastructure projects, driving economic growth and job creation. This financing approach isolates project funding from a sponsor’s corporate debt, simplifying investment tracking and reducing the risk of underinvestment due to excessive debt. Nevertheless, it faces challenges from government regulations, political factors, environmental concerns, and complex procedures. Thus, this paper presents a study to investigate the relationship between project finance factors and economic development indicators. The relationship is translated to a PLS-SEM model development and assessment. To develop the model, the study adopted quantitative research approach where the data for the model was collected through a questionnaire survey using judgmental sampling for convenience. The sample size for the model is from 269 respondents, who are the employees in the Economic Department workforce in Abu Dhabi. The model’s development and evaluation were conducted using SmartPLS software. The evaluation encompassed two stages: measurement and structural components, with the model successfully meeting all evaluation criteria. The results of hypothesis testing revealed that the relationships between Project Scope and Identifying Risk constructs with Economic Development construct are statistically significant with the strength 0f 0.520 and 0.227 respectively. Unfortunately, the relationships between Market Entry Strategy and Origination Capabilities with Economic Development are not statistically significant. In terms of model’s goodness of fit, the model demonstrated a substantial overall explanatory power with GoF values of 0.667. While, the model’s predictive relevancy with Q² value is 0.443, indicating how well the model can forecast economic development. In suggesting that the model explains approximately 44.3% of the variability in economic development. The findings of this study hold potential benefits for Economic Department employees dealing with project finance challenges