Questionnaire data for assessing what determines urban residents' engagement in activities for the protection of urban green spaces (UGS)

This dataset contains the core data used to investigate what determines Munich’s residents’ engagement in activities for the protection of urban green spaces (UGS). We conducted an exploratory factor analysis and a structural equation modelling based on the data from an online and in-person questionnaire.

List of data and content

Questionnaire_English: The content of the questionnaire in English (*.pdf)

Questionnaire_RawData_ Munchen_German: Core data from the questionnaire in German (*.xlsx)

InputEFA1: Core data for the first exploratory factor analysis with the input for analysis in Mplus (*.xlsx)

InputEFA2: Core data for the second exploratory factor analysis with the input for analysis in Mplus (*.xlsx)

InputSEM: Core data for the structural equation modelling with the input for analysis in Mplus (*.xlsx)

ResultsSEM: Results of the structural equation modelling (*.xlsx)

InputCFA1: Core data for the first confirmatory factor analysis with the input for analysis in Mplus (*.xlsx)

ResultsCFA1: Results of the confirmatory factor analysis (*.xlsx)

InputCFA2: Core data for the second confirmatory factor analysis with the input for analysis in Mplus (*.xlsx)

ResultsCFA2: Results of the confirmatory factor analysis (*.xlsx)

Acronyms_Shortings: Acronyms and shortings used in the uploaded files (*.pdf)

Data processing

The software for performing the exploratory factor analysis and structural equation modelling was Mplus 8.8 (Muthén and Muthén, 1998). The details on the methodological steps are available in the published publication. To quickly understand the EFA, CFA and SEM model and settings the details are provided in the hyperlinks.

Acknowledgments

The authors thank to all participants for their participation in the online and in-person questionnaires. Data processing and analysis would not have been possible without the help of Tomomi Saito.

This work was supported by a grant from the Alexander von Humboldt Foundation and by the Leibniz Best Minds Competition, Leibniz-Junior Research Group, Grant J76/2019.