Discrete Choice Experiment data for street-level urban greening in Berlin

Published: 2 December 2019| Version 2 | DOI: 10.17632/sjgr3w28n7.2
Contributors:
Erik Fruth,
Michele Kvistad,
Joseph Marshall,
Lena Pfeifer,
Julian Sagebiel,
Daniel Soto,
John Tarpey,
Jessica Weir,
Bradyn Winiarski

Description

The data presented here are the outcome of a survey implemented in a Berlin neighborhood from January to March 2018. To begin to put a monetary value on street-level aspects of urban green, we used a discrete choice experiment to explore people’s preferences and willingness to pay for green features in an urban Neighborhood Management development zone in Berlin. An analysis was performed on the survey results using conditional logit and latent class logit models done in R. This dataset is complementary to the full research article, “Economic valuation of street-level urban greening: A case study from an evolving mixed-use area in Berlin” (Fruth et al., 2019). The analysis provided in the full article can be used to guide decision-making regarding urban greening and green building practices at both policy- and project-level, while the dataset available here can be used to provide insight about how our sample population responded and how the experiment could be replicated in context or elsewhere in Berlin. “Deutsch_potsdamer_covariates” = IP address and user comments have been removed to protect respondents’ confidentiality; used in our sociodemographic analysis “Deutsch_potsdamer_experiment_15” = raw choice data from the DCE portion of the German-language survey; used in the logistic regression analysis to establish WTP “English_potsdamer_covariates” = IP address and user comments have been removed to protect respondents’ confidentiality; used in our sociodemographic analysis “English_postdamer_experiment_15” = raw choice data from the DCE portion of the English-language survey; used in the logistic regression analysis to establish WTP “SB_O02-03-00_2013j05_BE” = household income data; source file for the Berlin (parent population) income data points in our sociodemographic analysis “table_2019-07-27_11-28-18” = age/gender/population figures from StatIS-BBB; source file for the Berlin (parent population) age/gender/population data points in our sociodemographic analysis

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