Structural Relationship Model of Factors Affecting to The Artificial Intelligent Technology Implementation in the UAE Government Energy Sector 

Abstract

This paper presents a development of structural relationship model of factors affecting to the artificial intelligent technology implementation in the UAE government energy sector. The data used to develop the relationship was derived from questionnaire survey amongst the staffs of the UAE energy department. The model was developed and assessed using SmartPLS software. The model evaluated at measurement level based on two criteria which are convergent validity and discriminant validity and found that the model measurement has achieved the goodness-of-fit. Evaluation at the structural level is based on path coefficients (β), coefficient of determination (R² value), effect size (f²), predictive relevance (q²) and goodness-of-fit (GoF). The structural assessment found that the developed model has substantial validating power of 0.462 in representing the impact of the four groups of factors affecting the AI technology implementation. On the hypothesis testing of the model, it was found that AIT construct having the strongest influenced to the AIE construct but UEX path is not significant. The model was further verified by ten experts on the model outcomes practicality and all the experts had agreed with the model outcomes. These findings are beneficial for to academicians, researchers, practitioners and authority of UAE artificial intelligence and energy related sector.