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Testing Citizen Satisfaction in the Local Government: Focusing on the Vision 2020 Umurenge Program in Rwanda
Author(s) -
Pierre Celestin Bimenyimana,
Moon-Gi Jeong
Publication year - 2021
Publication title -
east african journal of arts and social sciences
Language(s) - English
Resource type - Journals
eISSN - 2707-4285
pISSN - 2707-4277
DOI - 10.37284/eajass.3.1.282
Subject(s) - expectancy theory , government (linguistics) , structural equation modeling , local government , psychology , political science , public relations , business , public administration , social psychology , computer science , linguistics , philosophy , machine learning
It is very important for public administration scholars and practitioners to understand how citizens form judgments regarding programs implemented at the local government level. The expectancy disconfirmation model of citizen satisfaction (EDM) focuses on comparing performance and expectations and was found important to understand that. This study tests the application of the expectancy disconfirmation model of citizen satisfaction in the local government of Rwanda focusing on the Vision 2020 Umurenge Program (VUP), which is a flagship of the social protection programs in Rwanda since 2008. It predicts that satisfaction with the program may increase the level of citizen participation. Data was collected from 379 VUP beneficiaries of the program in the Gicumbi district of Rwanda using an online survey questionnaire. We applied the Structural Equation Model and correlation analysis to analyze the data. The results found EDM applicable to how citizen forms judgment about satisfaction with VUP where there is a positive relationship between expectations and actual performance of the program (positive disconfirmation) and a positive influence of EDM with VUP to citizen participation. The study suggests that the governments should take into consideration the citizens’ feedback so as to meet their expectations and their satisfaction which may increase the level of citizen participation.

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