@ARTICLE{26543117_316261302_2019, 
	author = {Ruben Hayrapetyan}, 
	keywords = {, citizen participation, local governance, binary logistic regression, participatory governancepublic administration},
	title = {Quantitative Analysis of Factors Affecting Citizen Participation in Local Governance: The Case of Yerevan},
	journal = {Public Administration Issues},
	year = {2019},
	number = {6},
	pages = {61-76},
	url = {https://vgmu.hse.ru/en/2019--6/316261302.html},
	publisher = {},
	abstract = {The purpose of this research was to identify the key factors affecting active citizen participation in local governance and understand the extent to which each of them affects the potential participation. A survey was conducted among 1004 citizens of Yerevan to reveal the main characteristics of those who were for and against active participation, their attitudes towards certain types of participation, as well as the reasons for not participating. The questions included in the questionnaire resulted in an input of both dependent and independent variables (predictors). Raw data were processed through Microsoft Excel and then imported into SPSS 20.0 software. Collected primary source data were used to build a binary logistic regression model. The 0.353 value of Nagelkerke R2, which characterizes the predictive power of the logistic regression, may be considered a significant result for analyses in social sciences. The models also revealed individual relationships between potential citizen participation and some specific variables that might enable local authorities to carry out more targeted and effective policies in terms of participatory governance. Disclosure of such relationships can be useful not only for ensuring active participation of citizens in local governance, but also in terms of contribution both to the theory and practice of public administration.},
	annote = {The purpose of this research was to identify the key factors affecting active citizen participation in local governance and understand the extent to which each of them affects the potential participation. A survey was conducted among 1004 citizens of Yerevan to reveal the main characteristics of those who were for and against active participation, their attitudes towards certain types of participation, as well as the reasons for not participating. The questions included in the questionnaire resulted in an input of both dependent and independent variables (predictors). Raw data were processed through Microsoft Excel and then imported into SPSS 20.0 software. Collected primary source data were used to build a binary logistic regression model. The 0.353 value of Nagelkerke R2, which characterizes the predictive power of the logistic regression, may be considered a significant result for analyses in social sciences. The models also revealed individual relationships between potential citizen participation and some specific variables that might enable local authorities to carry out more targeted and effective policies in terms of participatory governance. Disclosure of such relationships can be useful not only for ensuring active participation of citizens in local governance, but also in terms of contribution both to the theory and practice of public administration.}
}