From a514f350cbe070a1730c3bd8c5fb2b5870a5c36e Mon Sep 17 00:00:00 2001
From: Marder <fm58hufi@usr.idiv.de>
Date: Mon, 30 Sep 2024 11:05:50 +0200
Subject: [PATCH] matching

---
 README.md                                    |   93 +
 Scripts/interaction_plots_presi.R            |   35 +-
 Scripts/logit/chr_vol_treat.R                |   84 +-
 Scripts/ols/ols_time_spent.R                 |    2 +-
 Scripts/treatment.R                          |    2 +-
 custom_app.lua                               |   16 +
 project_start.qmd                            |  595 ++++++
 references.bib                               | 1981 ++++++++++++++++++
 ugs-dce-info-treatment/Grafics/FlowChart.tif |  Bin 0 -> 80172 bytes
 ugs_data-main.Rproj                          |   13 +
 10 files changed, 2802 insertions(+), 19 deletions(-)
 create mode 100644 README.md
 create mode 100644 custom_app.lua
 create mode 100644 project_start.qmd
 create mode 100644 references.bib
 create mode 100644 ugs-dce-info-treatment/Grafics/FlowChart.tif
 create mode 100644 ugs_data-main.Rproj

diff --git a/README.md b/README.md
new file mode 100644
index 0000000..3c4b02b
--- /dev/null
+++ b/README.md
@@ -0,0 +1,93 @@
+# UGS DCE Info Treatment
+
+
+
+## Getting started
+
+To make it easy for you to get started with GitLab, here's a list of recommended next steps.
+
+Already a pro? Just edit this README.md and make it your own. Want to make it easy? [Use the template at the bottom](#editing-this-readme)!
+
+## Add your files
+
+- [ ] [Create](https://docs.gitlab.com/ee/user/project/repository/web_editor.html#create-a-file) or [upload](https://docs.gitlab.com/ee/user/project/repository/web_editor.html#upload-a-file) files
+- [ ] [Add files using the command line](https://docs.gitlab.com/ee/gitlab-basics/add-file.html#add-a-file-using-the-command-line) or push an existing Git repository with the following command:
+
+```
+cd existing_repo
+git remote add origin https://git.idiv.de/idivnc71qaxa/ugs-dce-info-treatment.git
+git branch -M main
+git push -uf origin main
+```
+
+## Integrate with your tools
+
+- [ ] [Set up project integrations](https://git.idiv.de/fm58hufi/ugs_data/-/settings/integrations)
+
+## Collaborate with your team
+
+- [ ] [Invite team members and collaborators](https://docs.gitlab.com/ee/user/project/members/)
+- [ ] [Create a new merge request](https://docs.gitlab.com/ee/user/project/merge_requests/creating_merge_requests.html)
+- [ ] [Automatically close issues from merge requests](https://docs.gitlab.com/ee/user/project/issues/managing_issues.html#closing-issues-automatically)
+- [ ] [Enable merge request approvals](https://docs.gitlab.com/ee/user/project/merge_requests/approvals/)
+- [ ] [Set auto-merge](https://docs.gitlab.com/ee/user/project/merge_requests/merge_when_pipeline_succeeds.html)
+
+## Test and Deploy
+
+Use the built-in continuous integration in GitLab.
+
+- [ ] [Get started with GitLab CI/CD](https://docs.gitlab.com/ee/ci/quick_start/index.html)
+- [ ] [Analyze your code for known vulnerabilities with Static Application Security Testing (SAST)](https://docs.gitlab.com/ee/user/application_security/sast/)
+- [ ] [Deploy to Kubernetes, Amazon EC2, or Amazon ECS using Auto Deploy](https://docs.gitlab.com/ee/topics/autodevops/requirements.html)
+- [ ] [Use pull-based deployments for improved Kubernetes management](https://docs.gitlab.com/ee/user/clusters/agent/)
+- [ ] [Set up protected environments](https://docs.gitlab.com/ee/ci/environments/protected_environments.html)
+
+***
+
+# Editing this README
+
+When you're ready to make this README your own, just edit this file and use the handy template below (or feel free to structure it however you want - this is just a starting point!). Thanks to [makeareadme.com](https://www.makeareadme.com/) for this template.
+
+## Suggestions for a good README
+
+Every project is different, so consider which of these sections apply to yours. The sections used in the template are suggestions for most open source projects. Also keep in mind that while a README can be too long and detailed, too long is better than too short. If you think your README is too long, consider utilizing another form of documentation rather than cutting out information.
+
+## Name
+Choose a self-explaining name for your project.
+
+## Description
+Let people know what your project can do specifically. Provide context and add a link to any reference visitors might be unfamiliar with. A list of Features or a Background subsection can also be added here. If there are alternatives to your project, this is a good place to list differentiating factors.
+
+## Badges
+On some READMEs, you may see small images that convey metadata, such as whether or not all the tests are passing for the project. You can use Shields to add some to your README. Many services also have instructions for adding a badge.
+
+## Visuals
+Depending on what you are making, it can be a good idea to include screenshots or even a video (you'll frequently see GIFs rather than actual videos). Tools like ttygif can help, but check out Asciinema for a more sophisticated method.
+
+## Installation
+Within a particular ecosystem, there may be a common way of installing things, such as using Yarn, NuGet, or Homebrew. However, consider the possibility that whoever is reading your README is a novice and would like more guidance. Listing specific steps helps remove ambiguity and gets people to using your project as quickly as possible. If it only runs in a specific context like a particular programming language version or operating system or has dependencies that have to be installed manually, also add a Requirements subsection.
+
+## Usage
+Use examples liberally, and show the expected output if you can. It's helpful to have inline the smallest example of usage that you can demonstrate, while providing links to more sophisticated examples if they are too long to reasonably include in the README.
+
+## Support
+Tell people where they can go to for help. It can be any combination of an issue tracker, a chat room, an email address, etc.
+
+## Roadmap
+If you have ideas for releases in the future, it is a good idea to list them in the README.
+
+## Contributing
+State if you are open to contributions and what your requirements are for accepting them.
+
+For people who want to make changes to your project, it's helpful to have some documentation on how to get started. Perhaps there is a script that they should run or some environment variables that they need to set. Make these steps explicit. These instructions could also be useful to your future self.
+
+You can also document commands to lint the code or run tests. These steps help to ensure high code quality and reduce the likelihood that the changes inadvertently break something. Having instructions for running tests is especially helpful if it requires external setup, such as starting a Selenium server for testing in a browser.
+
+## Authors and acknowledgment
+Show your appreciation to those who have contributed to the project.
+
+## License
+For open source projects, say how it is licensed.
+
+## Project status
+If you have run out of energy or time for your project, put a note at the top of the README saying that development has slowed down or stopped completely. Someone may choose to fork your project or volunteer to step in as a maintainer or owner, allowing your project to keep going. You can also make an explicit request for maintainers.
diff --git a/Scripts/interaction_plots_presi.R b/Scripts/interaction_plots_presi.R
index 6ebd0ad..b498414 100644
--- a/Scripts/interaction_plots_presi.R
+++ b/Scripts/interaction_plots_presi.R
@@ -16,13 +16,15 @@ create_interaction_term_plot <- function(ols_summary, treatment_labels, ord, uni
   plot_data$Coefficient <- treatment_labels
   
   plot <- ggplot(data = plot_data) +
-    geom_bar(aes(x = factor(Coefficient, levels=c(ord)), y = Estimate, fill = Coefficient), stat = "identity", position = 'dodge', width = 0.5, alpha = 0.7) +
-    geom_errorbar(aes(x = Coefficient, ymin = Estimate - ME, ymax = Estimate + ME), width = 0.3, position = position_dodge(0.8)) +
-    scale_x_discrete(guide = guide_axis(angle = 0)) +
+    geom_point(aes(y = factor(Coefficient, levels=c(ord)), x = Estimate ,fill = Coefficient, color= Coefficient), stat = "identity", size =3) +
+    geom_errorbar(aes(y = Coefficient, xmin = Estimate - ME, xmax = Estimate + ME), width = 0.3, position = position_dodge(0.8)) +
+    scale_y_discrete(guide = guide_axis(angle = 0)) +
     guides(fill = "none") +
-    coord_cartesian(ylim=c(down, up)) +
-    xlab("Treatment Group") +
-    ylab(paste0(unit))
+    geom_vline(xintercept = 0, lty = 2) +
+    coord_cartesian(xlim=c(down, up)) +
+    ylab("") +
+    xlab(paste0(unit))+
+    guides(fill = "none", color = "none", shape = "none")
   
   return(plot)
 }
@@ -32,30 +34,33 @@ case_A_labels <- c("Treated", "Optional Treatment")
 case_C_labels <- c("No Info 2", "Text 1", "Text 2", "Video 1", "Video 2")
 case_C_labels_re <- c("Text 1", "Text 2", "Video 1", "Video 2", "No Info 2")
 case_D_labels <- c("No Info", "Treated", "Vol. Treated")
-case_D_labels_re <- c("Treated", "Vol. Treated", "No Info")
+case_D_labels_re <- c("No Info", "Vol. Treated", "Treated")
 
 plot_interview_A <- create_interaction_term_plot(ols_time_spent_control_A, case_A_labels, case_A_labels,
-                                                 "Interview Time in Seconds", -150, 150)
+                                                 "Difference in Interview Time in Seconds", -150, 150)
+plot_interview_A
 plot_interview_C <- create_interaction_term_plot(ols_time_spent_control_C, case_C_labels, case_C_labels_re,
                                                  "Interview Time in Seconds", -150, 150)
 
 plot_interview_D <- create_interaction_term_plot(ols_time_spent_control_D, case_D_labels, case_D_labels_re,
-                                                 "Interview Time in Seconds", -150, 150)
+                                                 "Difference in Interview Time in Seconds", -150, 150)
 
 plot_cc_A <- create_interaction_term_plot(ols_time_cc_control_A, case_A_labels, case_A_labels,
-                                          "Mean Choice Card Time in Seconds", -3, 3)
+                                          "Difference in Mean Choice Card Time in Seconds", -3, 3)
+
 plot_cc_C <- create_interaction_term_plot(ols_time_cc_control_C, case_C_labels, case_C_labels_re,
-                                          "Mean Choice Card Time in Seconds", -3, 3)
+                                          "Difference in Mean Choice Card Time in Seconds", -3, 3)
 
 plot_cc_D <- create_interaction_term_plot(ols_time_cc_control_D, case_D_labels, case_D_labels_re,
-                                          "Mean Choice Card Time in Seconds", -3, 3)
-
+                                          "Difference in Mean Choice Card Time in Seconds", -3, 3)
+ggpubr::ggarrange(plot_interview_A, plot_cc_A, nrow=2 )
+ggpubr::ggarrange(plot_interview_D, plot_cc_D, nrow=2 )
 plot_mani_A <- create_interaction_term_plot(ols_percentage_correct_control_A, case_A_labels, case_A_labels,
-                                            "Percentage of Correct Quiz Statements", -15, 15)
+                                            "Difference in Percentage Points of Correct Quiz Statements", -5, 10)
 plot_mani_C <- create_interaction_term_plot(ols_percentage_correct_control_C, case_C_labels, case_C_labels_re,
                                             "Percentage of Correct Quiz Statements", -15, 15)
 plot_mani_D <- create_interaction_term_plot(ols_percentage_correct_control_D, case_D_labels, case_D_labels_re,
-                                            "Percentage of Correct Quiz Statements", -15, 15)
+                                            "Difference in Percentage Points of Correct Quiz Statements", -5, 10)
 
 plot_cons_A <- create_interaction_term_plot(conseq_model_control_A, case_A_labels, case_A_labels,
                                             "Consequentiality Score", -0.8, 0.8)
diff --git a/Scripts/logit/chr_vol_treat.R b/Scripts/logit/chr_vol_treat.R
index 133e96c..004568b 100644
--- a/Scripts/logit/chr_vol_treat.R
+++ b/Scripts/logit/chr_vol_treat.R
@@ -1,5 +1,11 @@
+library(dplyr)
+library(tidyr)
 library(margins)
+library(lubridate)
+library(caret)
+library(randomForest)
 
+library(xgboost)
 # Test treatment effect
 
 database_full <- database_full %>%
@@ -15,7 +21,7 @@ database_full <- database_full %>%
 
 data <- database_full %>%
   group_by(id) %>%
-  slice(1) %>%
+  dplyr::slice(1) %>%
   ungroup()
 data <- data %>% 
   mutate(Choice_Treat = ifelse( Dummy_Video_2 == 1 | Dummy_Info_nv2 == 1, 1, 
@@ -51,6 +57,80 @@ data$predicted.classes <- ifelse(data$probabilities  >= 0.5, 1, 0)
 # Model accuracy
 mean(data$predicted.classes == data$Choice_Treat, na.rm = T)
 
-table(predicted.classes ,data$Choice_Treat)
 
 
+
+
+
+# Assuming your data is in a data frame called 'data'
+set.seed(123)  # For reproducibility
+data<-select(data, Choice_Treat, id, Age, Q02W123, Uni_degree, QFIncome,Z_Mean_NR, City, Screen,
+             Uni_degree, Q02W123,Q04W123,Q05W123, Q08W123,Q09W123,Q10W123,Q11W3,Q12W123,Q13W23,Q14S01W123,Q14S02W23,
+             Q14S03W123,Q14S04W123,Q14S05W123,Q14S06W23,Q14S07W3,Q14S08W2,Q14W23,
+             Q15S01W3,Q15S02W3,Q16W3,Q17W13,Q18W123,Q19W3,C02W23,Q20W23,Q21W23,
+             Q22S01W123,Q22S02W23,Q23W123,Q24S01W123,
+             Q24S02W123,Q24S03W123,Q24S04W23,Q24S05W123,Q25W23,Q26S01W123,Q26S02W123,
+             Q26S03W23,Q26S04W123,Q26S05W123,Q26S06W123,Q26S07W23,Q26S08W23,Q26S99W23,
+             Q27W123,Q30W23,Q31S01W23,Q31S02W23,Q31S03W23,Q31S04W23,
+             Q31S05W23,Q31S06W23,Q31S08W23,Q32S01W23,Q32S02W23,Q32S03W23,
+             Q33S01W3,Q33S02W3,Q33S03W3,Q33S04W3,Q33S05W3,Q33S06W3,Q33S07W3,Q33S99W3,
+             Q34W23,Q35W23,Q36W23,Q37W23,Q38S01W3,Q38S02W3,Q38S03W3,Q38S04W3,Q38S05W3,
+             Q38S06W3,Q38S07W3,Q38S08W3,Q38S09W3,Q38S10W3,Q38S11W3,Q38S12W3,Q38S13W3,
+             Q38S14W3,Q38S15W3,Q38S16W3,Q38S17W3,Q38S18W3,Q38S19W3,Q38S20W3,Q38S21W3,
+             V01W3,Q39S01W3,Q39S02W3,Q39S03W3,Q39S04W3,Q39S05W3,Q40W3
+             ,Q45W123,Q46S01W3,Q46S02W3,Q46S03W3,Q46S04W3,
+             Q47S01W23,Q47S02W3,Q47S03W3,Q47S04W3,Q47S05W3,Q47S06W3,Q47S07W3,Q47S08W3,
+             Q47S09W3,Q48S01W3,Q48S02W3,Q48S03W3,Q48S04W3,Q48S05W3,Q49W23,Q50W123)
+data <- data %>%
+  select(where(~ all(!is.na(.)) & all(. != "")) | any_of("Choice_Treat"))
+# Split the data into labeled and unlabeled sets
+labeled_data <- filter(data, Choice_Treat==1| Choice_Treat==0)
+unlabeled_data <- filter(data, is.na(Choice_Treat))
+labeled_data<-select(labeled_data,-id)
+# Assuming the group information is in the column called 'Group'
+labeled_data$Choice_Treat<- as.factor(labeled_data$Choice_Treat)
+unlabeled_data$Choice_Treat<- as.factor(unlabeled_data$Choice_Treat)
+
+trainIndex <- createDataPartition(labeled_data$Choice_Treat, p = 0.8, list = FALSE)
+trainData <- labeled_data[trainIndex, ]
+testData <- labeled_data[-trainIndex, ]
+
+
+
+
+
+
+tuneGrid <- expand.grid(
+  nrounds = c(300),
+  max_depth = c(15),
+  eta = c(0.05),
+  gamma = c(0, 0.1),
+  colsample_bytree = c(0.6, 0.8),     # Fraction of features to be used for each tree
+  min_child_weight = c(1, 3, 5),      # Minimum sum of instance weight (hessian) needed in a child
+  subsample = c(0.7, 0.8)             # Fraction of samples to be used for each tree
+)
+
+
+model3 <- train(Choice_Treat ~ ., 
+               data = trainData, 
+               method = "xgbTree", 
+               tuneGrid = tuneGrid,
+               trControl = trainControl(method = "cv", number = 5))
+
+
+# Get variable importance
+varImp(model3)
+
+
+
+# Evaluate the model
+predictions <- predict(model3, newdata = testData)
+confusionMatrix(predictions, testData$Choice_Treat)
+labeled_predictions <- predict(model3, newdata = labeled_data)
+labeled_data$PredictedGroup <- labeled_predictions
+
+table(labeled_data$Choice_Treat, labeled_data$PredictedGroup)
+
+unlabeled_predictions <- predict(model3, newdata = unlabeled_data)
+unlabeled_data$PredictedGroup <- unlabeled_predictions
+print(model3$bestTune)
diff --git a/Scripts/ols/ols_time_spent.R b/Scripts/ols/ols_time_spent.R
index 71dba63..b417979 100644
--- a/Scripts/ols/ols_time_spent.R
+++ b/Scripts/ols/ols_time_spent.R
@@ -2,7 +2,7 @@ library(car)
 
 data <- database_full %>%
   group_by(id) %>%
-  slice(1) %>%
+  dplyr::slice(1) %>%
   ungroup()
 
 
diff --git a/Scripts/treatment.R b/Scripts/treatment.R
index 0be11ce..f3f81fe 100644
--- a/Scripts/treatment.R
+++ b/Scripts/treatment.R
@@ -294,7 +294,7 @@ summary(always_opt_out$Z_Mean_NR)
   
   data <- database_full %>%
     group_by(id) %>%
-    slice(1) %>%
+    dplyr::slice(1) %>%
     ungroup()
   
   ## Count correct answers after Treatment for Treatment Group (before CE)
diff --git a/custom_app.lua b/custom_app.lua
new file mode 100644
index 0000000..b9f5eff
--- /dev/null
+++ b/custom_app.lua
@@ -0,0 +1,16 @@
+local in_appendix = false
+
+Header = function(h)
+  if h.level == 1 then
+    if h.classes:includes("appendix") then
+      in_appendix = true
+      h.attributes["visibility"] = "uncounted"
+    else
+      in_appendix = false
+    end
+  end
+  if h.level == 2 and in_appendix then
+    h.attributes["visibility"] = "uncounted"
+  end
+  return h
+end
diff --git a/project_start.qmd b/project_start.qmd
new file mode 100644
index 0000000..f601cef
--- /dev/null
+++ b/project_start.qmd
@@ -0,0 +1,595 @@
+---
+title: "Hot Cities, Cool Choices:" 
+subtitle: "The Effect of Optional and Obligatory Information on Stated Preferences for Urban Green Spaces"
+title-slide-attributes:
+  data-background-image: Grafics/iDiv_logo_item.png
+  data-background-size: contain
+  data-background-opacity: "0.2"
+author: "Nino Cavallaro, Fabian Marder, Julian Sagebiel"
+institute: 
+- German Centre for Integrative Biodiversity Research (iDiv) Halle-Jena-Leipzig
+- Leipzig University 
+date: today
+date-format: long
+bibliography: references.bib
+filters:
+  - parse-latex
+  - custom_app.lua
+format: 
+  revealjs:
+    slide-number: true
+    smaller: true
+    logo: Grafics/iDiv_logo_item.PNG
+    footer: "DCE  Network meeting"
+    scrollable: true
+    embed-resources: true
+---
+
+```{r, include=FALSE, cache=FALSE}
+source("Scripts/MAKE_FILE.R")
+```
+
+```{r loadlibs, include=FALSE}
+library(tidyverse)
+library(apollo)
+library(texreg)
+
+list_ols <- list("(Intercept)" = "Intercept", "as.factor(Treatment_A)Treated" = "Treated", "as.factor(Treatment_A)Vol_Treated" = "Optional Treatment",
+                 "as.factor(Treatment_C)No Info 2" = "No Info 2", "as.factor(Treatment_C)No Video 1" = "Text 1",
+                 "as.factor(Treatment_C)No Video 2" = "Text 2", "as.factor(Treatment_C)Video 1" = "Video 1",
+                 "as.factor(Treatment_C)Video 2" = "Video 2", "as.factor(Treatment_D)Treated" = "Treated", "as.factor(Treatment_D)Vol. Treated" = "Vol. Treated",
+                 "as.factor(Treatment_D)No Info 2" = "No Info", 
+                 "Z_Mean_NR" = "NR-Index", "as.factor(Gender)2" = "Female",
+                 "Age_mean" = "Age", "QFIncome" = "Income", "Uni_degree" = "University Degree")
+```
+
+# Motivation & Research Contribution
+
+## Motivation (1)
+
+::: incremental
+-   **Stated preference** methods are frequently applied in **environmental valuation** to estimate economic values of policies, goods, and services that cannot be valued otherwise
+-   Stated preference methods face **validity challenges**
+-   Valid value estimation requires **sufficient information** provision about the good being valued
+-   Still unclear **what formats of information provision** and **how much information** are optimal for valid preference elicitation
+:::
+
+## Motivation (2)
+
+::: incremental
+-   Too **much information** may increase survey **complexity**, leading to respondents being overburdened with it and producing less consistent choices
+-   Too **little information** may lead respondents to **not** being able to make an **informed choice**
+-   Valid preference elicitation depends not only on the provision of information, but also on the **appropriate processing and recall** of the information by the respondent
+-   **Optional information** allows the respondents to gather required information if needed and might increase efficiency of information provision
+
+-  Providing optional information should enhance optimal information seeking leading to less heterogeneity in good-specific knowledge between the respondents 
+:::
+
+## Literature
+
+::: incremental
+-   There is **little research** on the effects of **optional information provision** on choice behavior and information recall
+-   In their study, @tienhaara2022information surveyed preferences for agricultural genetic resources, allowing respondents the option to access detailed information on the valued goods prior to preference elicitation
+-   Similarly, @hu2009consumers offered respondents the opportunity to access optional information about genetic modified food before participating in a choice experiment
+-   Both studies conclude that, on average, respondents who voluntary retrieve information have **larger willingness to pay** for the good to be valued
+-   Their study design, however, does not allow comparing the optional information retrieval to a version where the additional information was shown obligatory
+:::
+
+## Research Contribution
+
+::: incremental
+-   Our study explores the impact of additional obligatory and optional information on stated preferences using an exogenous split sample approach with three treatments
+-   We investigate the effects of information treatments on survey engagement, information recall, consequentiality, and stated preferences, similar to @welling2023information, expanding our understanding of treatment effects
+-   We test who chooses additional information and to what extent their preferences differ from those who do not choose additional information
+:::
+
+## Research Questions
+
+::: incremental
+1.  Do obligatory and optional information provision affect **survey engagement**, **information recall**, **consequentiality**, and **stated preferences**?
+
+- OLS and MXL with interactions
+
+2.  Do **socio-demographic** or **attitudinal** variables influence the decision to **access optional information**?
+
+- Logit regression
+
+3.  Do **survey engagement**, **information recall**, **consequentiality**, and **stated preferences** differ between respondents who **voluntary access information** and those who do not?
+
+- OLS and MXL with interactions
+:::
+
+# Survey & Data
+
+## Discrete Choice Experiment
+
+::: incremental
+-   To investigate the research questions, we use data from a **discrete choice experiment (DCE)** on naturalness of urban green spaces in the 14 largest German cities
+-   The survey is an exact **replication** of the choice experiment of @Bronnmann062321-0072R1 and differs only in the information provided to the respondents
+-   In the DCE, respondents were asked to imagine possible **changes** to their **most frequently used UGS**
+-   This **restructuring** involved adjustments to the UGS's **naturalness** and changes to the **walking distance**
+-   The associated **costs** of this restructuring were intended to be integrated into monthly **rental payments**
+<!-- -   Participants in the DCE were presented **ten** randomly assigned **choice cards** with a choice between **two alternative programs** for the renovation of the UGS and the **current status quo**. -->
+:::
+
+## Choice Card
+
+![](images/Figure%202.PNG){width="300"}
+
+## Treatment (Information Provision)
+
+-   Info text about the effect of **natural urban green spaces** on urban **heat islands**
+-   **Optional video** (2 minutes) with the almost the same information
+
+![](images/waermeinsel.png){width="200"}
+
+## Treatment (Quiz & Self Reference Questions)
+
+::: incremental
+-   **Seven quiz questions** with strict reference to the previously provided information
+
+-   Example: *The temperature difference between the city and the surrounding area can be up to 10 degrees Celsius. (true/false)*
+
+-   **Two self reference questions**
+
+-   Example: *The city should do more to avoid heat islands. (Strongly agree - Strongly disagree)*
+:::
+
+
+
+
+
+
+
+## Additional Data
+
+::: incremental
+
++   Quiz: Evaluation of the quiz we gave to everyone after the DCE.**-\>Information recall**
+
++   Timings: We saved the net interview time and the mean Choice Card time.-\> **Survey engagement**
+
++   Two questions on **consequentiality **
+
+- Example: *To what extent do you believe that the decisions you make will have an impact on how the green spaces in your neighborhood are designed in the future? (I believe in it very much - I don’t believe in it at all)*
+
++   **Socio-demographics**: Age, Gender, Income, Education
+
++   **Attitudinal variable**: Measure derived from 21 items on **nature relatedness** [@nisbet2009nature]
+
+:::
+
+
+## Experimental Setting
+
+![](Grafics/FlowChart_4_groups.png){width="300"}
+
+
+<!-- ## Methods (1) {auto-animate="true"} -->
+
+
+<!-- -   OLS regression (survey engagement, information recall, consequentiality): -->
+
+<!-- ```{=tex} -->
+<!-- \begin{equation} -->
+<!--     Y = \beta_0 +  \beta_{Treat} \cdot v_{Treat} + \beta_{Control} \cdot v_{Control} + \epsilon -->
+<!--     \label{ols} -->
+<!-- \end{equation} -->
+<!-- ``` -->
+<!-- -   Mixed logit model with interactions in WTP space: -->
+
+
+<!-- ## Methods (2) {auto-animate="true"} -->
+
+<!-- -   Mixed logit model with interactions in WTP space: -->
+
+<!-- ```{=tex} -->
+<!-- \begin{equation} -->
+<!--     U_i = -(\beta_{C_i} + \beta_{TreatC_i} \cdot v_{Treat}) \cdot (\beta_{X_i} \cdot v_{X_i} + \beta_{TreatX_i} \cdot v_{X_i} \cdot v_{Treat} - C_i) + \epsilon_i -->
+<!-- \end{equation} -->
+<!-- ``` -->
+<!-- with -->
+
+<!-- ```{=tex} -->
+<!-- \begin{equation} -->
+<!--   v_{X_i} = \{ASC_{sq_i}, Nat_i, WD_i\} -->
+<!-- \end{equation} -->
+<!-- ``` -->
+<!-- and -->
+
+<!-- ```{=tex} -->
+<!-- \begin{equation} -->
+<!--   v_{Treat_A} = \{Treated, Optional Treatment\} -->
+<!-- \end{equation} -->
+<!-- ``` -->
+<!-- ```{=tex} -->
+<!-- \begin{equation} -->
+<!--   v_{Treat_B} = \{Treated, Vol. Treated, No Info\} -->
+<!-- \end{equation} -->
+<!-- ``` -->
+
+# Case A: Obligatory vs. Optional Information
+
+
+## Case A
+
+1.  Do obligatory and optional information provision affect **survey engagement**, **information recall**, **consequentiality**, and **stated preferences**?
+
+![](Grafics/FlowChart_4_groups_A.png){width="300"}
+
+<!-- ::: {style="font-size: 45%;"} -->
+
+<!-- ```{r, results='asis'} -->
+
+<!-- htmlreg(l=list(ols_time_spent_control_A, ols_time_cc_control_A, ols_percentage_correct_control_A, conseq_model_control_A), -->
+
+<!--        custom.model.names = c("Interview Time",  "CC Time", "Quiz",  "Cons. Score"), -->
+
+<!--        custom.header = list("Model 1A" = 1:1, "Model 2A" = 2:2, "Model 3A" = 3:3, "Model 4A" = 4:4), -->
+
+<!--        custom.coef.map = list_ols,  stars = c(0.01, 0.05, 0.1), float.pos="tb",  -->
+
+<!--        label = "tab:olsA", -->
+
+<!--        caption = "Results of OLS regressions for Scenario Case A.") -->
+
+<!-- ``` -->
+
+<!-- ::: -->
+
+
+
+
+
+## OLS Specification
+
+```{=tex}
+\begin{equation}
+    Y = \beta_0 +  \beta_{Treat} \cdot v_{Treat} + \beta_{SocDem} \cdot v_{SocDem} + \epsilon
+    \label{olss}
+\end{equation}
+```
+
+with
+
+```{=tex}
+\begin{equation}
+  Y = \left\{
+  \begin{aligned}
+    &\text{Net Interview Time, Mean Choice Card Time} \\
+    &\text{Percentage of correct quiz statements, Consequentiality Score} 
+  \end{aligned}
+  \right\}
+\end{equation}
+```
+
+
+```{=tex}
+\begin{equation}
+  v_{Treat} = \{\text{Treated, Optional Treatment}\}
+\end{equation}
+```
+
+```{=tex}
+\begin{equation}
+  v_{SocDem} = \{\text{Age, Gender, Income, Education, NR-Index}\}
+\end{equation}
+```
+
+
+## OLS: Engagement
+
+```{r}
+ggpubr::ggarrange(plot_interview_A, plot_cc_A)
+```
+
+
+## OLS: Information Recall & Consequentiality
+
+```{r}
+ggpubr::ggarrange(plot_mani_A, plot_cons_A)
+```
+
+## MXL: Effects on Stated Preferences
+
+
+
+```{=tex}
+\begin{equation}
+    U_i = -(\beta_{C_i} + \beta_{TreatC_i} \cdot v_{Treat}) \cdot (\beta_{X_i} \cdot v_{X_i} + \beta_{TreatX_i} \cdot v_{X_i} \cdot v_{Treat} - C_i) + \epsilon_i
+    \label{mxl_base}
+\end{equation}
+```
+with
+
+```{=tex}
+\begin{equation}
+  v_{X_i} = \{ASC_{sq_i}, Nat_i, WD_i\}
+\end{equation}
+```
+
+```{=tex}
+\begin{equation}
+  v_{Treat} = \{\text{Treated, Optional Treatment}\}
+\end{equation}
+```
+```{=tex}
+\begin{equation}
+  C_i = \{Rent_i\}
+\end{equation}
+```
+
+## MXL: Effects on Stated Preferences
+
+::: {style="font-size: 80%;"}
+```{r, results='asis'}
+htmlreg(c(case_A_cols[1], remGOF(case_A_cols[2:4])), single.row = TRUE,
+       custom.coef.map = list("natural" = "Naturalness", "walking" = "Walking Distance", "rent" = "Rent",
+                              "ASC_sq" = "ASC SQ", "_natural" = "Naturalness", "nat" = "Naturalness",
+                              "wd" = "Walking Distance", "asc" = "ASC SQ"),
+       custom.model.names = c("Mean", "SD", "Treated", "Optional Treatment"), custom.note = "%stars. Standard errors in parentheses.",
+       stars = c(0.01, 0.05, 0.1), float.pos="tb", 
+       label = "tab:mxl_A",
+       caption = "Results of mixed logit model with treatment interactions for Case A.")
+```
+
+
+
+:::
+
+# Case B: Voluntary Information Access
+
+## Voluntary Information Access
+
+2.  Do **socio-demographic** or **attitudinal** variables influence the decision to **access optional information**?
+
+![](Grafics/FlowChart_Optional_only.png){width="300"}
+
+
+
+## Logit Regression: Who chooses Optional Information?
+
+```{=tex}
+\begin{equation}
+    Y = \beta_0 + \beta_{SocDem} \cdot v_{SocDem} + \epsilon
+    \label{simple_logit}
+\end{equation}
+```
+
+::: {style="font-size: 58%;"}
+```{r, results='asis'}
+
+
+htmlreg(l=list(logit_choice_treat_uni), stars = c(0.01, 0.05, 0.1), float.pos="tb",
+       custom.model.names = c("Logit regression"),
+       custom.header = list("Dependent variable: Voluntary Information Access" = 1),
+       custom.coef.map = list_ols, custom.note = "%stars. Standard errors in parentheses.",
+       label = "tab:logit_vt", single.row = TRUE,
+       caption = "Results of logit regression on access of optional information.")
+
+
+```
+:::
+
+
+## Case B
+
+3.  Do **survey engagement**, **information recall**, **consequentiality**, and **stated preferences** differ between respondents who **voluntary access information** and those who do not?
+
+![](Grafics/FlowChart_4_groups_B.png){width="300"}
+
+## OLS Engagement: Interview & Choice Card Time
+
+```{r}
+ggpubr::ggarrange(plot_interview_D, plot_cc_D)
+```
+
+## OLS: Information Recall & Consequentiality
+
+```{r}
+ggpubr::ggarrange(plot_mani_D, plot_cons_D)
+```
+
+## MXL: Case B
+
+::: {style="font-size: 80%;"}
+```{r, results='asis'}
+htmlreg(c(case_B_cols[1], remGOF(case_B_cols[2:5])),
+       custom.coef.map = list("natural" = "Naturalness", "walking" = "Walking Distance", "rent" = "Rent",
+                              "ASC_sq" = "ASC SQ", "_natural" = "Naturalness", "nat" = "Naturalness",
+                              "wd" = "Walking Distance", "asc" = "ASC SQ",
+                              "ASC_sq_info" = "ASC SQ", "rent_info" = "Rent", "nat_info" = "Naturalness", "walking_info" = "Walking Distance"),
+       custom.model.names = c("Mean", "SD", "Treated", "Vol. Treated", "No Info"), custom.note = "%stars (one-sided). Robust standard errors in parentheses.",
+       stars = c(0.01, 0.05, 0.1), float.pos="tb",
+       label = "tab:mxl_C",
+       caption = "Results of mixed logit model with treatment interactions for Case B.")
+```
+:::
+
+## MXL: Case B with NR-index Interaction
+
+::: {style="font-size: 80%;"}
+```{r, results='asis'}
+htmlreg(c(case_B_cols_NR[1], remGOF(case_B_cols_NR[2:6])),
+       custom.coef.map = list("natural" = "Naturalness", "walking" = "Walking Distance", "rent" = "Rent",
+                              "ASC_sq" = "ASC SQ", "_natural" = "Naturalness", "nat" = "Naturalness",
+                              "wd" = "Walking Distance", "asc" = "ASC SQ", "ASC" ="ASC SQ",
+                              "ASC_sq_info" = "ASC SQ", "rent_info" = "Rent", "nat_info" = "Naturalness", "walking_info" = "Walking Distance"),
+       custom.model.names = c("Mean", "SD", "Treated", "Vol. Treated", "No Info", "NR-Index"), custom.note = "%stars (one-sided). Robust standard errors in parentheses.",
+       stars = c(0.01, 0.05, 0.1), float.pos="tb",
+       label = "tab:mxl_C_NR",
+       caption = "Results of mixed logit model with treatment interactions for Case B including NR-index.")
+```
+:::
+
+# Discussion
+
+## Discussion (1)
+
+1.  Do obligatory and optional information provision affect survey engagement, information recall, consequentiality, and stated preferences?
+
+::: incremental
+-   Obligatory and optional treatments do not increase survey engagement measured via time spend on the survey
+
+-   Both treatments increase information recall, stronger effect for obligatory treatment
+
+-   No effects on consequentiality
+
+-   Strong effects on stated preferences for both treatments, more pronounced effect for the obligatory treatment
+:::
+
+## Discussion (2)
+
+2.  Do socio-demographic or attitudinal variables influence the decision to access optional information?
+
+::: incremental
+-   Respondents that voluntary access information are younger, richer and have a higher natural relatedness index
+
+-   No effects of gender and education
+
+-   Respondents' preferences for the good to be valued (NR-index) influence the likelihood of accessing additional information
+:::
+
+## Discussion (3)
+
+3.  Do survey engagement, information recall, consequentiality, and stated preferences differ between respondents who voluntary access information and those who do not?
+
+::: incremental
+-   Respondents that voluntary access information do not engage more in the survey, but perform best in the quiz
+
+-   Respondents that decide to not access additional information engage less in the survey, have a lower consequentiality score and do not perform different in the quiz than the non-treated respondents
+
+-   Highest willingness to pay values in the group that voluntary accesses information
+:::
+
+## Conclusion
+
+::: incremental
+-   Providing optional information does not lead to optional information seeking
+
+-   Optional information is mostly accessed by people that are interested in the good to be valued
+
+-   We recommend to use obligatory information provision rather than optional one
+:::
+
+## References
+
+::: {#refs}
+:::
+
+# Appendix {.appendix}
+
+
+Information provision (Video) Link to the video: <https://idiv.limequery.com/upload/surveys/682191/files/urban-heat-island-effekt.mp4>
+
+## Summary Statistics
+
+::: {style="font-size: 55%;"}
+```{=latex}
+        \begin{table}[htbp]
+        \centering
+        \begin{tabular}{lcrcclc} \hline 
+         Characteristic& Sample & Treated & Opt. Treatment & Non-Treated & Vol. Treated &  No Info   \\ \hline
+         Gender & &&& &   \\
+          \hspace{0.3cm} Proportion Females&50.67\%&50.15\%&47.98\%&49.76\% &50.48\%  &  48.26\%  \\ \hline
+         Age &44.60&44.91 &44.24&44.63 & 42.51 &  44.97 \\ \hline
+         Net Household Income&&&&  & & \\
+          \hspace{0.3cm} Less than 1500\euro  &19.06\%&20.43\%&18.86\%&17.85\%&  22.12\% &  19.77\% \\ 
+          \hspace{0.3cm} 1500\euro -3000\euro &23.39\%&20.59\%&24.75\%&24.96\%&  15.87\% &  26.16\% \\
+          \hspace{0.3cm} 3000\euro -4000\euro &32.62\%&35.14\%&29.63\%&32.86\%&  34.13\% & 27.61\% \\ 
+          \hspace{0.3cm} More than 4000\euro  &19.65\%&19.04\%&20.70\%&19.27\%&   24.52\% & 18.31\% \\ \hline
+                   Education & &&&&  &   \\
+          \hspace{0.3cm} University degree &34.54\%&32.20\%&34.68\%&36.81\%&  33.17\% & 33.72\% \\ 
+          \hspace{0.3cm} No University degree &64.46\%&67.80\%&65.32\%&63.19\%&  66.83\%  &66.28\% \\ \hline
+          NR-index &0.00&0.00&-0.02&0.02&  0.15  &-0.19 \\ \hline
+           Correct quiz answers   &66.97\%&69.86\%&66.91\%&64.07\%&69.44\%&63.08\% \\ \hline
+           Consequentiality  score  &6.15&6.28&6.02&6.12&6.75   &5.76 \\ \hline
+          Net interview time   &1396&1340&1424&1426& 1441  &1350  \\
+          Mean Choice Card time &18.86&19.02&19.10&18.51 &19.03&19.24 \\ \hline
+                   Number of respondents &1873&646&594&633&  250  &344  \\ \hline
+                   \multicolumn{7}{p{\textwidth-2\tabcolsep}}{\scriptsize Notes: Age is measured in years; NR-index is z-standardized with mean=0 and standard deviation=1; Correct quiz answers measure the percentage of correctly answered quiz questions; Consequentiality score is the sum of the two Likert-type questions on consequentiality; Net interview time and Mean Choice card time are measured in seconds; Net interview time is measured as overall interview time minus treatment time; To avoid bias, we excluded the fastest 1\% and the slowest 1\% of net interview time and mean Choice Card time from the analysis.}
+    \end{tabular}
+        \caption{Summary statistics of the sample and by scenarios.}
+        \label{tab:summary}
+        \end{table}
+```
+:::
+
+
+## NR OLS
+
+::: {style="font-size: 65%;"}
+```{r, results='asis'}
+htmlreg(l=list(nr_model_treat_A), single.row = TRUE,
+       custom.model.names = c("OLS regression"),
+       custom.header = list("Dependent variable: NR-Index" = 1),
+       custom.coef.map = list("(Intercept)" = "Intercept", "as.factor(Treatment_A)Treated" = "Treated", "as.factor(Treatment_A)Vol_Treated" = "Vol. Treated",
+                              "as.factor(Treatment_C)No Info 2" = "No Info 2", "as.factor(Treatment_C)No Video 1" = "Text 1",
+                              "as.factor(Treatment_C)No Video 2" = "Text 2", "as.factor(Treatment_C)Video 1" = "Video 1",
+                              "as.factor(Treatment_C)Video 2" = "Video 2", "Z_Mean_NR" = "NR-Index", "as.factor(Gender)2" = "Female",
+                              "Age_mean" = "Age", "QFIncome" = "Income", "Uni_degree" = "University Degree", "Kids_Dummy" = "Children",
+                              "Naturalness_SQ" = "Naturalness SQ", "WalkingDistance_SQ" = "Walking Distance SQ"),
+       stars = c(0.01, 0.05, 0.1), float.pos="tb",
+       custom.note = "%stars. Standard errors in parentheses.",
+       label = "tab:nr_ols",
+        caption = "Results of OLS on the NR-index.")
+```
+:::
+
+## OLS Models: Case A
+
+
+::: {style="font-size: 65%;"}
+```{r, results='asis'}
+htmlreg(l=list(ols_time_spent_control_A, ols_time_cc_control_A, ols_percentage_correct_control_A, conseq_model_control_A),
+       custom.model.names = c("Interview Time",  "CC Time", "Quiz",  "Cons. Score"),
+       custom.header = list("Model 1A" = 1:1, "Model 2A" = 2:2, "Model 3A" = 3:3, "Model 4A" = 4:4),
+       custom.coef.map = list_ols,  stars = c(0.01, 0.05, 0.1), float.pos="tb", 
+       custom.note = "Notes: (i) The dependent variables examined in this regression analysis are as follows: 
+       Model 1A refers to net interview time, 
+       Model 2A denotes choice card time, Model 3A represents the percentage of correct quiz questions, and Model 4A represents consequentiality score.
+       (ii) The variables included in the analysis are as follows: Treated is a dummy variable indicating membership 
+       in the obligatory treated group, Optional Treatment is a dummy variable indicating membership in the group with 
+       the choice to receive treatment or not, with the reference group being Non-Treated. NR-Index represents the z-standardized
+       natural relatedness index. Female is a dummy variable denoting gender, Age has been mean-centered and measured in years, 
+       Income is a continuous variable indicating a transition from one income group to the next higher, and University Degree is 
+       a dummy variable indicating whether an individual holds a university degree; (iii) %stars and standard errors in parentheses.",
+       label = "tab:olsA", single.row = TRUE,
+       caption = "Results of OLS regressions for Scenario Case A.")
+```
+:::
+
+## OLS Models: Case B
+
+::: {style="font-size: 60%;"}
+```{r, results='asis'}
+htmlreg(l=list(ols_time_spent_control_D, ols_time_cc_control_D, ols_percentage_correct_control_D,  conseq_model_control_D),
+       custom.model.names = c("Interview Time",  "CC Time", "Quiz",  "Cons. Score"),
+       custom.header = list("Model 1B" = 1:1, "Model 2B" = 2:2, "Model 3B" = 3:3, "Model 4B" = 4:4),
+       custom.coef.map = list_ols,  stars = c(0.01, 0.05, 0.1), float.pos="tb", 
+       custom.note = "Notes: (i) The dependent variables examined in this regression analysis are as follows: 
+       Model 1B refers to net interview time, 
+       Model 2B denotes choice card time, Model 1B represents the percentage of correct quiz questions, and Model 4B represents consequentiality score.
+       (ii) The variables included in the analysis are as follows: Treated is a dummy variable indicating membership 
+       in the obligatory treated group, Vol. Treated is a dummy variable indicating the group that voluntarily chose the optional treatment, 
+       while No Info indicates the group that did not opt for the treatment, with the reference group being Non-Treated. NR-Index represents the z-standardized
+       natural relatedness index. Female is a dummy variable denoting gender, Age has been mean-centered and measured in years, 
+       Income is a continuous variable indicating a transition from one income group to the next higher, and University Degree is 
+       a dummy variable indicating whether an individual holds a university degree; (iii) %stars and standard errors in parentheses.",
+       label = "tab:olsD",
+       caption = "Results of OLS regressions for Scenario Case B.", single.row = TRUE)
+```
+:::
+
+## MXL: Split Samples
+
+```{r}
+ggplot(data=mxl_melt_info, aes(x=Coefficent, y=abs(value), fill=variable)) +
+  geom_bar(stat="identity",  position='dodge', width = 0.9) +
+  geom_errorbar(aes(x=Coefficent, ymin=abs(value)-ME, ymax=abs(value)+ME), width=0.3, position=position_dodge(0.8)) +
+  ylab("Absolute Value") +
+  xlab("Coefficient") +
+  scale_x_discrete(guide = guide_axis(angle = 45)) +
+  scale_fill_brewer(palette = "Set2", labels = c("Treated", "Optional Treatment", "Not Treated"), name="Treatment") +
+  theme(legend.position = c(0.85, 0.8)) 
+```
diff --git a/references.bib b/references.bib
new file mode 100644
index 0000000..8e4b2f6
--- /dev/null
+++ b/references.bib
@@ -0,0 +1,1981 @@
+@article{hu2009consumers,
+  title={Consumers' preferences for GM food and voluntary information access: A simultaneous choice analysis},
+  author={Hu, Wuyang and Adamowicz, Wiktor L and Veeman, Michele M},
+  journal={Canadian Journal of Agricultural Economics/Revue canadienne d'agroeconomie},
+  volume={57},
+  number={2},
+  pages={241--267},
+  year={2009},
+  publisher={Wiley Online Library}
+}
+
+@article {Bronnmann062321-0072R1,
+	author = {Bronnmann, Julia and Liebelt, Veronika and Marder, Fabian and Meya, Jasper and Quaas, Martin},
+	title = {The Value of Naturalness of Urban Green Spaces: Evidence from a Discrete Choice Experiment},
+	elocation-id = {062321-0072R1},
+	year = {2023},
+	publisher = {University of Wisconsin Press},
+	abstract = {The range of benefits for humans and biodiversity conservation provided by urban green spaces (UGS) receives substantial attention in relation to urban planning and management. However, little is known about the value of nature in UGS. We developed a graphical measurement scale for the naturalness of UGS, with 5 steps between largely sealed and largely wilderness, which was embedded in an online survey and a discrete choice experiment. Using mixed logit models, we find that German citizens have a mean willingness to pay of {\texteuro}20.25 per month for an increase in the naturalness of the closest UGS by one step.},
+	issn = {0023-7639},
+	eprint = {https://le.uwpress.org/content/early/2023/02/17/le.99.4.062321-0072R1.full.pdf},
+	journal = {Land Economics}
+}
+
+@article{tienhaara2022information,
+  title={Information use and its effects on the valuation of agricultural genetic resources},
+  author={Tienhaara, Annika and Ahtiainen, Heini and Pouta, Eija and Czajkowski, Miko{\l}aj},
+  journal={Land Economics},
+  volume={98},
+  number={2},
+  pages={337--354},
+  year={2022},
+  publisher={University of Wisconsin Press}
+}
+
+@article{welling2023information,
+  title={Information processing in stated preference surveys: A case study on urban gardens},
+  author={Welling, Malte and Sagebiel, Julian and Rommel, Jens},
+  journal={Journal of Environmental Economics and Management},
+  volume={119},
+  pages={102798},
+  year={2023},
+  publisher={Elsevier}
+}
+
+% Master thesis papers %
+
+@article{aronson2017biodiversity,
+  title={Biodiversity in the city: key challenges for urban green space management},
+  author={Aronson, Myla FJ and Lepczyk, Christopher A and Evans, Karl L and Goddard, Mark A and Lerman, Susannah B and MacIvor, J Scott and Nilon, Charles H and Vargo, Timothy},
+  journal={Frontiers in Ecology and the Environment},
+  volume={15},
+  number={4},
+  pages={189--196},
+  year={2017},
+  publisher={Wiley Online Library}
+}
+
+
+
+@article{bertram2015preferences,
+  title={Preferences for cultural urban ecosystem services: Comparing attitudes, perception, and use},
+  author={Bertram, Christine and Rehdanz, Katrin},
+  journal={Ecosystem Services},
+  volume={12},
+  pages={187--199},
+  year={2015},
+  publisher={Elsevier}
+}
+
+@article{pulighe2016insights,
+  title={Insights and opportunities from mapping ecosystem services of urban green spaces and potentials in planning},
+  author={Pulighe, Giuseppe and Fava, Francesco and Lupia, Flavio},
+  journal={Ecosystem services},
+  volume={22},
+  pages={1--10},
+  year={2016},
+  publisher={Elsevier}
+}
+
+@article{niemela2010using,
+  title={Using the ecosystem services approach for better planning and conservation of urban green spaces: a Finland case study},
+  author={Niemel{\"a}, Jari and Saarela, Sanna-Riikka and S{\"o}derman, Tarja and Kopperoinen, Leena and Yli-Pelkonen, Vesa and V{\"a}re, Seija and Kotze, D Johan},
+  journal={Biodiversity and Conservation},
+  volume={19},
+  pages={3225--3243},
+  year={2010},
+  publisher={Springer}
+}
+
+@article{ripley1977modelling,
+  title={Modelling spatial patterns},
+  author={Ripley, Brian D},
+  journal={Journal of the Royal Statistical Society: Series B (Methodological)},
+  volume={39},
+  number={2},
+  pages={172--192},
+  year={1977},
+  publisher={Wiley Online Library}
+}
+
+@article{tiebout1956pure,
+  title={A pure theory of local expenditures},
+  author={Tiebout, Charles M},
+  journal={Journal of political economy},
+  volume={64},
+  number={5},
+  pages={416--424},
+  year={1956},
+  publisher={The University Press of Chicago}
+}
+
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+volume = {105},
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+year = {2015},
+issn = {1352-2310},
+author = {Sara Janhäll},
+keywords = {Urban, Air quality, Vegetation, Deposition, Dispersion, Particle size},
+}
+
+@article{kaul2013can,
+  title={What can we learn from benefit transfer errors? Evidence from 20 years of research on convergent validity},
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+}
+
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+}
+
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+  publisher={Springer}
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+}
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+
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+ author = {{EU Commission}},
+ year = {2020}
+}
+
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+}
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+}
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+}
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+}
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+  year = {2022},
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+
+@article{johnston2018benefit,
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+pages = {715-740},
+year = {2009},
+doi = {10.1177/0013916508318748},
+
+URL = { 
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+        https://doi.org/10.1177/0013916508318748  
+    
+    
+
+},
+eprint = { 
+    
+        https://doi.org/10.1177/0013916508318748  
+    
+    
+
+}
+,
+    abstract = { Disconnection from the natural world may be contributing to our planet's destruction. The authors propose a new construct, Nature Relatedness (NR), and a scale that assesses the affective, cognitive, and experiential aspects of individuals' connection to nature. In Study 1, the authors explored the internal structure of the NR item responses in a sample of 831 participants using factor analysis. They tested the construct validity of NR with respect to an assortment of environmental and personality measures. In Study 2, they employed experience sampling methodology examining if NR people spend more time outdoors, in nature. Across studies, NR correlated with environmental scales, behavior, and frequency of time in nature, supporting the reliability and validity of NR, as well as the contribution of NR (over and above other measures) to environmental concern and behavior. The potential of NR as a useful method for investigating human-nature relationships and the processes underlying environmental concern and behaviors are discussed. }
+}
+@Inbook{mathews2007,
+author="Mathews, Kristy E.
+and Freeman, Miranda L.
+and Desvousges, William H.",
+editor="Kanninen, Barbara J.",
+title="How and How Much?",
+bookTitle="Valuing Environmental Amenities Using Stated Choice Studies: A Common Sense Approach to Theory and Practice",
+year="2007",
+publisher="Springer Netherlands",
+address="Dordrecht",
+pages="111--133",
+isbn="978-1-4020-5313-9",
+doi="10.1007/1-4020-5313-4_5",
+url="https://doi.org/10.1007/1-4020-5313-4_5 "
+}
+
+
+%julian
+
+@book{mariel2021environmental,
+  title={Environmental valuation with discrete choice experiments: Guidance on design, implementation and data analysis},
+  author={Mariel, Petr and Hoyos, David and Meyerhoff, J{\"u}rgen and Czajkowski, Mikolaj and Dekker, Thijs and Glenk, Klaus and Jacobsen, Jette Bredahl and Liebe, Ulf and Olsen, S{\o}ren B{\o}ye and Sagebiel, Julian and others},
+  year={2021},
+  publisher={Springer Nature}
+}
+
+
+@article{welling2023information,
+  title={Information processing in stated preference surveys: A case study on urban gardens},
+  author={Welling, Malte and Sagebiel, Julian and Rommel, Jens},
+  journal={Journal of Environmental Economics and Management},
+  volume={119},
+  pages={102798},
+  year={2023},
+  publisher={Elsevier}
+}
+
+
+@Article{zeileis2008,
+    title = {Regression Models for Count Data in {R}},
+    author = {Achim Zeileis and Christian Kleiber and Simon Jackman},
+    journal = {Journal of Statistical Software},
+    year = {2008},
+    volume = {27},
+    number = {8}
+  }
+
+@article{bergstrom1990impact,
+  title={The impact of information on environmental commodity valuation decisions},
+  author={Bergstrom, John C and Stoll, John R and Randall, Alan},
+  journal={American Journal of Agricultural Economics},
+  volume={72},
+  number={3},
+  pages={614--621},
+  year={1990},
+  publisher={Wiley Online Library}
+}
+
+@article{hensher1998combining,
+  title={Combining sources of preference data},
+  author={Hensher, David and Louviere, Jordan and Swait, Joffre},
+  journal={Journal of Econometrics},
+  volume={89},
+  number={1-2},
+  pages={197--221},
+  year={1998},
+  publisher={Elsevier}
+}
+
+@article{CAMPSCALVET2016,
+title = {Ecosystem services provided by urban gardens in Barcelona, Spain: Insights for policy and planning},
+journal = {Environmental Science \& Policy},
+volume = {62},
+pages = {14-23},
+year = {2016},
+note = {Advancing urban environmental governance: Understanding theories, practices and processes shaping urban sustainability and resilience},
+issn = {1462-9011},
+author = {Marta Camps-Calvet and Johannes Langemeyer and Laura Calvet-Mir and Erik Gómez-Baggethun},
+keywords = {Barcelona, Ecosystem services, Green infrastructure, Nature-based solutions, Urbanism, Urban agriculture}
+}
+
+@article{deshazo2002designing,
+  title={Designing choice sets for stated preference methods: the effects of complexity on choice consistency},
+  author={DeShazo, JR and Fermo, German},
+  journal={Journal of Environmental Economics and Management},
+  volume={44},
+  number={1},
+  pages={123--143},
+  year={2002},
+  publisher={Elsevier}
+}
+
+
+
+@book{kenski_state_2014,
+	title = {The {State} of {Framing} {Research}},
+	volume = {1},
+	abstract = {This chapter provides an assessment of the state of research on framing, and examines how the concept of framing has been used across different disciplines. Using this overview, the authors explore two of the most common conceptual misunderstandings related to framing and their implications for political communication research. This includes an overview of the different approaches to framing in political communication research, more specifically, and of the relationship between framing and related effects models, such as priming and agenda setting. The authors conclude with a recommendation that framing research be redirected away from confounded “emphasis frames” toward “equivalence frames” in the original tradition by expanding the sample of potential frames to include nonverbal visual cues.},
+	language = {en},
+	urldate = {2019-12-03},
+	publisher = {Oxford University Press},
+	author = {Scheufele, Dietram A. and Iyengar, Shanto},
+	editor = {Kenski, Kate and Jamieson, Kathleen Hall},
+	month = oct,
+	year = {2014},
+	doi = {10.1093/oxfordhb/9780199793471.013.47}
+}
+
+@article{czajkowski_controlling_2016,
+	title = {Controlling for the {Effects} of {Information} in a {Public} {Goods} {Discrete} {Choice} {Model}},
+	volume = {63},
+	issn = {0924-6460, 1573-1502},
+	language = {en},
+	number = {3},
+	urldate = {2019-12-03},
+	journal = {Environmental and Resource Economics},
+	author = {Czajkowski, Mikołaj and Hanley, Nick and LaRiviere, Jacob},
+	month = mar,
+	year = {2016},
+	pages = {523--544}
+}
+
+@article{tourangeau_cognitive_1988,
+	title = {Cognitive processes underlying context effects in attitude measurement.},
+	volume = {103},
+	language = {en},
+	number = {3},
+	journal = {Psychological Bulletin},
+	author = {Tourangeau, Roger and Rasinski, Kenneth A.},
+	year = {1988},
+	pages = {299--314}
+	}
+
+@article{liebe_context_2016,
+	title = {Context effects and the temporal stability of stated preferences},
+	volume = {60},
+	language = {en},
+	urldate = {2019-12-03},
+	journal = {Social Science Research},
+	author = {Liebe, Ulf and Hundeshagen, Cordula and Beyer, Heiko and Cramon-Taubadel, Stephan von},
+	month = nov,
+	year = {2016},
+	pages = {135--147}
+}
+
+@article{moore_measuring_2002,
+	title = {Measuring {New} {Types} of {Question}-{Order} {Effects}: {Additive} and {Subtractive}},
+	volume = {Vol. 66},
+	number = {1},
+	journal = {The Public Opinion Quarterly},
+	author = {Moore, David. W.},
+	year = {2002},
+	pages = {80--91}
+}
+
+@book{tourangeau_psychology_2000,
+	address = {Cambridge New York Melbourne},
+	title = {The psychology of survey response},
+	isbn = {978-0-521-57246-0 978-0-521-57629-1},
+	language = {eng},
+	publisher = {Cambridge University Press},
+	author = {Tourangeau, Roger and Rips, Lance J. and Rasinski, Kenneth A.},
+	year = {2000}
+}
+
+@article{pouta_attitude_2004,
+	title = {Attitude and belief questions as a source of context effect in a contingent valuation survey},
+	volume = {25},
+	issn = {01674870},
+	language = {en},
+	number = {2},
+	urldate = {2019-12-03},
+	journal = {Journal of Economic Psychology},
+	author = {Pouta, Eija},
+	month = apr,
+	year = {2004},
+	pages = {229--242}
+}
+
+@book{bateman_economic_2002,
+	title = {Economic {Valuation} with {Stated} {Preference} {Techniques}},
+	isbn = {978-1-78100-972-7},
+	language = {en},
+	urldate = {2019-12-03},
+	publisher = {Edward Elgar Publishing},
+	author = {Bateman, Ian and Carson, Richard and Day, Brett and Hanemann, Michael and Hanley, Nick and Hett, Tannis and Jones-Lee, Michael and Loomes, Graham},
+	year = {2002}
+}
+
+@article{jacobsen_whats_2008,
+	title = {What’s in a name? {The} use of quantitative measures versus ‘{Iconised}’ species when valuing biodiversity},
+	volume = {39},
+	issn = {0924-6460, 1573-1502},
+	shorttitle = {What’s in a name?},
+	language = {en},
+	number = {3},
+	urldate = {2019-12-03},
+	journal = {Environmental and Resource Economics},
+	author = {Jacobsen, Jette Bredahl and Boiesen, John Halfdan and Thorsen, Bo Jellesmark and Strange, Niels},
+	year = {2008},
+	pages = {247--263}
+}
+
+@article{johnston_contemporary_2017,
+	title = {Contemporary {Guidance} for {Stated} {Preference} {Studies}},
+	volume = {4},
+	language = {en},
+	number = {2},
+	urldate = {2019-12-03},
+	journal = {Journal of the Association of Environmental and Resource Economists},
+	author = {Johnston, Robert J. and Boyle, Kevin J. and Adamowicz, Wiktor (Vic) and Bennett, Jeff and Brouwer, Roy and Cameron, Trudy Ann and Hanemann, W. Michael and Hanley, Nick and Ryan, Mandy and Scarpa, Riccardo and Tourangeau, Roger and Vossler, Christian A.},
+	month = jun,
+	year = {2017},
+	pages = {319--405},
+	file = {Akzeptierte Version:P\:\\Zotero\\storage\\8ZC8Y7ZF\\Johnston et al. - 2017 - Contemporary Guidance for Stated Preference Studie.pdf:application/pdf}
+}
+
+@article{holmes1998effect,
+  title={The effect of response time on conjoint analysis estimates of rainforest protection values},
+  author={Holmes, Thomas and Alger, Keith and Zinkhan, Christian and Mercer, D Evan},
+  journal={Journal of Forestry Economics},
+  number = {2},
+  volume={4},
+  year={1998}
+}
+
+@article{vista2009if,
+  title={If you provide it, will they read it? Response time effects in a choice experiment},
+  author={Vista, Arvin B and Rosenberger, Randall S and Collins, Alan R},
+  journal={Canadian Journal of Agricultural Economics/Revue canadienne d'agroeconomie},
+  volume={57},
+  number={3},
+  pages={365--377},
+  year={2009},
+  publisher={Wiley Online Library}
+}
+
+@article{johnston_willingness_2007,
+	title = {Willingness to {Pay} for {Agricultural} {Land} {Preservation} and {Policy} {Process} {Attributes}: {Does} the {Method} {Matter}?},
+	volume = {89},
+	issn = {0002-9092, 1467-8276},
+	shorttitle = {Willingness to {Pay} for {Agricultural} {Land} {Preservation} and {Policy} {Process} {Attributes}},
+	language = {en},
+	number = {4},
+	urldate = {2019-12-03},
+	journal = {American Journal of Agricultural Economics},
+	author = {Johnston, R. J. and Duke, J. M.},
+	month = nov,
+	year = {2007},
+	pages = {1098--1115}
+}
+
+@article{oehlmann_uncovering_2017,
+	title = {Uncovering context-induced status quo effects in choice experiments},
+	volume = {81},
+	issn = {00950696},
+	language = {en},
+	urldate = {2019-12-03},
+	journal = {Journal of Environmental Economics and Management},
+	author = {Oehlmann, Malte and Meyerhoff, Jürgen and Mariel, Petr and Weller, Priska},
+	month = jan,
+	year = {2017},
+	pages = {59--73}
+}
+
+@article{oehlmann2017stated,
+	title = {Stated preferences towards renewable energy alternatives in {Germany} – do the consequentiality of the survey and trust in institutions matter?},
+	volume = {6},
+	issn = {2160-6544, 2160-6552},
+	language = {en},
+	number = {1},
+	urldate = {2019-12-03},
+	journal = {Journal of Environmental Economics and Policy},
+	author = {Oehlmann, Malte and Meyerhoff, Jürgen},
+	month = jan,
+	year = {2017},
+	pages = {1--16}
+}
+
+@misc{andor_consequentiality_2017,
+	title = {Consequentiality and the {Willingness}-{To}-{Pay} for {Renewables}: {Evidence} from {Germany}.},
+	author = {Andor, Mark and Frondel, Manuel and Horvath, Marco},
+	month = sep,
+	year = {2017}
+}
+
+@article{carson_incentive_2007,
+	title = {Incentive and informational properties of preference questions},
+	volume = {37},
+	issn = {0924-6460, 1573-1502},
+	language = {en},
+	number = {1},
+	urldate = {2019-12-03},
+	journal = {Environmental and Resource Economics},
+	author = {Carson, Richard T. and Groves, Theodore},
+	month = may,
+	year = {2007},
+	pages = {181--210}
+}
+
+@article{ballco2019consumer,
+  title={Consumer preferences for nutritional claims: An exploration of attention and choice based on an eye-tracking choice experiment},
+  author={Ballco, Petjon and de-Magistris, Tiziana and Caputo, Vincenzina},
+  journal={Food Research International},
+  volume={116},
+  pages={37--48},
+  year={2019},
+  publisher={Elsevier}
+}
+
+@article{balcombe2017examining,
+  title={Examining the relationship between visual attention and stated preferences: A discrete choice experiment using eye-tracking},
+  author={Balcombe, Kelvin and Fraser, Iain and Williams, Louis and McSorley, Eugene},
+  journal={Journal of Economic Behavior \& Organization},
+  volume={144},
+  pages={238--257},
+  year={2017},
+  publisher={Elsevier}
+}
+
+@incollection{munro_information_2001,
+	address = {Oxford},
+	series = {Oxford {University} {Press}},
+	title = {Information, uncertainty, and contingent valuation.},
+	booktitle = {Valuing {Environmental} {Preferences}: {Theory} and {Practice} of the {Contingent} {Valuation} {Method} in the {US}, {EU}, and {Developing} {Countries}},
+	author = {Munro, Alistair and Hanley, Nick},
+	year = {2001},
+	pages = {258--274}
+}
+
+@article{oh_citizens_2012,
+	title = {Citizens’ trust in government and their willingness-to-pay},
+	volume = {115},
+	issn = {01651765},
+	language = {en},
+	number = {3},
+	urldate = {2019-12-03},
+	journal = {Economics Letters},
+	author = {Oh, Hyungna and Hong, Jong Ho},
+	month = jun,
+	year = {2012},
+	pages = {345--347}
+}
+
+@book{mitchell1989,
+  title={Using surveys to value public goods: the contingent valuation method},
+  author={Mitchell, Robert Cameron and Carson, Richard T},
+  year={1989},
+  publisher={Resources for the Future}
+}
+
+@article{remoundou_is_2012,
+	title = {Is the value of an environmental public good sensitive to the providing institution?},
+	volume = {34},
+	issn = {09287655},
+	language = {en},
+	number = {3},
+	urldate = {2019-12-03},
+	journal = {Resource and Energy Economics},
+	author = {Remoundou, Kyriaki and Kountouris, Yiannis and Koundouri, Phoebe},
+	month = sep,
+	year = {2012},
+	pages = {381--395}
+}
+
+@article{needham2018causal,
+  title={What is the causal impact of information and knowledge in stated preference studies?},
+  author={Needham, Katherine and Czajkowski, Miko{\l}aj and Hanley, Nick and LaRiviere, Jacob},
+  journal={Resource and Energy Economics},
+  volume={54},
+  pages={69--89},
+  year={2018},
+  publisher={Elsevier}
+}
+
+@article{vossler_understanding_2013,
+	title = {Understanding the consequences of consequentiality: {Testing} the validity of stated preferences in the field},
+	volume = {86},
+	journal = {Journal of Economic Behavior \& Organization},
+	author = {Vossler, Christian A. and Watson, Sharon B.},
+	month = feb,
+	year = {2013},
+	pages = {137--147}
+}
+
+@article{kataria_scenario_2012,
+	title = {Scenario realism and welfare estimates in choice experiments – {A} non-market valuation study on the {European} water framework directive},
+	volume = {94},
+	language = {en},
+	number = {1},
+	urldate = {2020-01-07},
+	journal = {Journal of Environmental Management},
+	author = {Kataria, M. and Bateman, I. and Christensen, T. and Dubgaard, A. and Hasler, B. and Hime, S. and Ladenburg, J. and Levin, G. and Martinsen, L. and Nissen, C.},
+	month = feb,
+	year = {2012},
+	pages = {25--33}
+}
+
+@article{vasquez2019,
+  title={Willingness to pay for the restoration of the Paraiba do Sul River: A contingent valuation study from Brazil},
+  author={Vasquez, William F and de Rezende, Carlos Eduardo},
+  journal={Ecohydrology \& Hydrobiology},
+  volume={19},
+  number={4},
+  pages={610--619},
+  year={2019},
+  publisher={Elsevier}
+}
+
+@misc{mcfadden1974,
+  title={Frontiers in Econometrics, chapter Conditional logit analysis of qualitative choice behavior},
+  author={McFadden, Daniel},
+  year={1974},
+  publisher={Academic Press}
+}
+
+@techreport{arrow_report_1993,
+	title = {Report of the {NOAA} panel on contigent valuation},
+	number = {58(10)},
+	author = {Arrow, K and Solow, R and Portney, PR and Leamer, EE and Radner, R and Schuman, H},
+	month = jan,
+	year = {1993},
+	pages = {4601--14}
+}
+
+@article{blomquist_resource_1998,
+	title = {Resource quality information and validity of willingness to pay in contingent valuation},
+	volume = {20},
+	issn = {09287655},
+	language = {en},
+	number = {2},
+	urldate = {2020-01-28},
+	journal = {Resource and Energy Economics},
+	author = {Blomquist, Glenn C. and Whitehead, John C.},
+	month = jun,
+	year = {1998},
+	pages = {179--196},
+	file = {Submitted Version:P\:\\Zotero\\storage\\R8JJQU6R\\Blomquist and Whitehead - 1998 - Resource quality information and validity of willi.pdf:application/pdf}
+}
+
+@article{aadland_bayesian_2007,
+	title = {A {Bayesian} examination of information and uncertainty in contingent valuation},
+	volume = {35},
+	language = {en},
+	number = {2},
+	urldate = {2020-01-28},
+	journal = {Journal of Risk and Uncertainty},
+	author = {Aadland, David M. and Caplan, Arthur J. and Phillips, Owen R.},
+	month = sep,
+	year = {2007},
+	pages = {149--178},
+	file = {Submitted Version:P\:\\Zotero\\storage\\CNGTLFS7\\Aadland et al. - 2007 - A Bayesian examination of information and uncertai.pdf:application/pdf}
+}
+
+@article{harris_improving_1989,
+	title = {Improving the contingent valuation method: {A} psychological perspective},
+	volume = {17},
+	issn = {00950696},
+	shorttitle = {Improving the contingent valuation method},
+	language = {en},
+	number = {3},
+	urldate = {2020-01-28},
+	journal = {Journal of Environmental Economics and Management},
+	author = {Harris, Charles C and Driver, B.L and McLaughlin, William J},
+	month = nov,
+	year = {1989},
+	pages = {213--229}
+}
+
+@article{hu2009consumers,
+  title={Consumers' preferences for GM food and voluntary information access: A simultaneous choice analysis},
+  author={Hu, Wuyang and Adamowicz, Wiktor L and Veeman, Michele M},
+  journal={Canadian Journal of Agricultural Economics/Revue canadienne d'agroeconomie},
+  volume={57},
+  number={2},
+  pages={241--267},
+  year={2009},
+  publisher={Wiley Online Library}
+}
+
+@incollection{van1988information,
+  title={Information Processing and Decision making Cognitive Aspects of Economic Behaviour},
+  author={Van Raaij, W Fred},
+  booktitle={Handbook of Economic Psychology},
+  pages={74--106},
+  year={1988},
+  publisher={Springer}
+}
+
+@incollection{mathews2006and,
+  title={How and how much?},
+  author={Mathews, Kristy E and Freeman, Miranda L and Desvousges, William H},
+  booktitle={Valuing environmental amenities using stated choice studies},
+  pages={111--133},
+  year={2006},
+  publisher={Springer}
+}
+
+@article{rogers1977self,
+  title={Self-reference and the encoding of personal information.},
+  author={Rogers, Timothy B and Kuiper, Nicholas A and Kirker, William S},
+  journal={Journal of Personality and Social Psychology},
+  volume={35},
+  number={9},
+  pages={677},
+  year={1977},
+  publisher={American Psychological Association}
+}
+
+@article{craik1972levels,
+  title={Levels of processing: A framework for memory research},
+  author={Craik, Fergus IM and Lockhart, Robert S},
+  journal={Journal of Verbal Learning and Verbal Behavior},
+  volume={11},
+  number={6},
+  pages={671--684},
+  year={1972},
+  publisher={Elsevier}
+}
+
+@article{hutchinson_measuring_1995,
+	title = {{MEASURING} {NON}-{USE} {VALUE} {OF} {ENVIRONMENTAL} {GOODS} {USING} {THE} {CONTINGENT} {VALUATION} {METHOD}: {PROBLEMS} {OF} {INFORMATION} {AND} {COGNITION} {AND} {THE} {APPLICATION} {OF} {COGNITIVE} {QUESTIONNAIRE} {DESIGN} {METHODS}},
+	volume = {46},
+	issn = {0021857X, 14779552},
+	shorttitle = {{MEASURING} {NON}-{USE} {VALUE} {OF} {ENVIRONMENTAL} {GOODS} {USING} {THE} {CONTINGENT} {VALUATION} {METHOD}},
+	language = {en},
+	number = {1},
+	urldate = {2020-01-28},
+	journal = {Journal of Agricultural Economics},
+	author = {Hutchinson, W. George and Chilton, Susan M. and Davis, John},
+	month = jan,
+	year = {1995},
+	pages = {97--112}
+}
+
+@article{blomquist_resource_1998-1,
+	title = {Resource quality information and validity of willingness to pay in contingent valuation},
+	volume = {20},
+	issn = {09287655},
+	language = {en},
+	number = {2},
+	urldate = {2020-01-28},
+	journal = {Resource and Energy Economics},
+	author = {Blomquist, Glenn C. and Whitehead, John C.},
+	month = jun,
+	year = {1998},
+	pages = {179--196},
+	file = {Submitted Version:P\:\\Zotero\\storage\\3WFSNZ8W\\Blomquist and Whitehead - 1998 - Resource quality information and validity of willi.pdf:application/pdf}
+}
+
+@article{boyle_commodity_1989,
+	title = {Commodity {Specification} and the {Framing} of {Contingent}-{Valuation} {Questions}},
+	volume = {65},
+	number = {1},
+	urldate = {2020-01-28},
+	journal = {Land Economics},
+	author = {Boyle, Kevin J.},
+	month = feb,
+	year = {1989},
+	pages = {57}
+}
+
+@article{hess2019apollo,
+  title={Apollo: a flexible, powerful and customisable freeware package for choice model estimation and application},
+  author={Hess, Stephane and Palma, David},
+  journal={Journal of Choice Modelling},
+  volume={32},
+  pages={100170},
+  year={2019},
+  publisher={Elsevier}
+}
+
+@article{lee_information_2018,
+	title = {Information and order of information effects on consumers’ acceptance and valuation for genetically modified edamame soybean},
+	volume = {13},
+	issn = {1932-6203},
+	language = {en},
+	number = {10},
+	urldate = {2020-01-28},
+	journal = {PLOS ONE},
+	author = {Lee, Ji Yong and Popp, Michael P. and Wolfe, Elijah J. and Nayga, Rodolfo M. and Popp, Jennie S. and Chen, Pengyin and Seo, Han-Seok},
+	editor = {Ezura, Hiroshi},
+	month = oct,
+	year = {2018},
+	pages = {e0206300},
+	file = {Full Text:P\:\\Zotero\\storage\\98YG6H7S\\Lee et al. - 2018 - Information and order of information effects on co.pdf:application/pdf}
+}
+
+@article{bateman_first_2004,
+	title = {First impressions count: interviewer appearance and information effects in stated preference studies},
+	volume = {49},
+	issn = {09218009},
+	shorttitle = {First impressions count},
+	language = {en},
+	number = {1},
+	urldate = {2020-01-28},
+	journal = {Ecological Economics},
+	author = {Bateman, Ian J and Mawby, James},
+	month = may,
+	year = {2004},
+	pages = {47--55}
+}
+
+@article{hoehn2002effect,
+  title={The effect of resource quality information on resource injury perceptions and contingent values},
+  author={Hoehn, John P and Randall, Alan},
+  journal={Resource and Energy Economics},
+  volume={24},
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+  publisher={Elsevier}
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+  year={2016},
+  publisher={Elsevier}
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+issn = {0048-9697},
+author = {Iris Vanermen and Roselinde Kessels and Kris Verheyen and Bart Muys and Liesbet Vranken},
+keywords = {Forest management decision making, Soil biodiversity, Environmental valuation, Discrete choice experiment, Information treatment, Preference heterogeneity}
+}
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+	title = {Effects of different descriptions of the ecological good on willingness to pay values},
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+	booktitle = {Valuing Environmental Preferences}
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+
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+	year = 2009,
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+
+@article{herriges2010consequences,
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+
+@article{groothuis2017endogenous,
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+	year = 2017,
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+	volume = {93},
+	number = {2},
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+}
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+@book{dillman2011mail,
+  title={Mail and Internet surveys: The tailored design method--2007 Update with new Internet, visual, and mixed-mode guide},
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+  year={2011},
+  publisher={John Wiley \& Sons}
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+
+
+@article{Vossler_2018,
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+	year = 2018,
+	month = {sep},
+	publisher = {Elsevier {BV}},
+	volume = {165},
+	pages = {133--145},
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+	journal = {Journal of Public Economics}
+}
+
+@article{broadbent2012hypothetical,
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+
+@article{hole2017dcreate,
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+}
+
+@article{zawojska2019disentangling,
+  title={Disentangling the effects of policy and payment consequentiality and risk attitudes on stated preferences},
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+  journal={Journal of Environmental Economics and Management},
+  volume={93},
+  pages={63--84},
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+}
+
+@article{vossler2018alternative,
+  title={Alternative value elicitation formats in contingent valuation: Mechanism design and convergent validity},
+  author={Vossler, Christian A and Holladay, J Scott},
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+  pages={133--145},
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+}
+
+@article{Mariel_2016,
+  title={Hybrid discrete choice models: Gained insights versus increasing effort},
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+  pages={433--443},
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+}
+
+@article{Walker_2002,
+  title={Generalized random utility model},
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+
+@article{Chorus_2014,
+  title={On the (im-) possibility of deriving transport policy implications from hybrid choice models},
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+}
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+
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+
+@article{lloyd2019incorporating,
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+	url = {https://doi.org/10.3368%2Fle.95.3.293},
+	year = 2019,
+	month = {jul},
+	publisher = {University of Wisconsin Press},
+	volume = {95},
+	number = {3},
+	pages = {293--306},
+	author = {Patrick Lloyd-Smith and Wiktor Adamowicz and Diane Dupont},
+	title = {Incorporating Stated Consequentiality Questions in Stated Preference Research},
+	journal = {Land Economics}
+}
+
+@article{hoehn2002,
+  title={The effect of resource quality information on resource injury perceptions and contingent values},
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+}
+
+@article{hasselstrom2014,
+  title={Detailed vs. fuzzy information in non-market valuation studies: the role of familiarity},
+  author={Hasselstr{\"o}m, Linus and H{\aa}kansson, Cecilia},
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+  pages={123--143},
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+}
+
+@article{zawojska_2019,
+title= {Eliciting Consequentiality in Stated Preference Surveys: An Application to Urban Green},
+author = {Zawojska, Ewa and Welling, Malte and Sagebiel, Julian},
+year = {2019},
+journal = {Paper presented at the 24th European Association of Environmental and Resource Economists Annual Conference, Manchester, United Kingdom. Retrieved on December 21, 2019, from \url{www.fleximeets.com/eaere2019/getpaper.php?fid=1239}.}
+}
+
+@article{tienhaara2020,
+  title={Information use and its effects on the valuation of agricultural genetic resources},
+  author={Tienhaara, Annika and Ahtiainen, Heini and Pouta, Eija and Czajkowski, Miko{\l}aj},
+  journal={Land Economics},
+  pages={090319--0127R1},
+  year={2021},
+  publisher={University of Wisconsin Press}
+}
+
+@article{berrens2004,
+  title={Information and effort in contingent valuation surveys: application to global climate change using national internet samples},
+  author={Berrens, Robert P and Bohara, Alok K and Jenkins-Smith, Hank C and Silva, Carol L and Weimer, David L},
+  journal={Journal of Environmental Economics and Management},
+  volume={47},
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+}
+@article{Ben_Akiva_2002,
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+	title = {Hybrid Choice Models: Progress and Challenges},
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+}
+
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+@book{greeneeconometric,
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+
+@article{faccioli2020environmental,
+  title={Environmental attitudes and place identity as determinants of preferences for ecosystem services},
+  author={Faccioli, Michela and Czajkowski, Miko{\l}aj and Glenk, Klaus and Martin-Ortega, Julia},
+  journal={Ecological Economics},
+  volume={174},
+  pages={106600},
+  year={2020},
+  publisher={Elsevier}
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+
+@article{abate2020valuation,
+  title={Valuation of marine plastic pollution in the European Arctic: Applying an integrated choice and latent variable model to contingent valuation},
+  author={Abate, Tenaw G and B{\"o}rger, Tobias and Aanesen, Margrethe and Falk-Andersson, Jannike and Wyles, Kayleigh J and Beaumont, Nicola},
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+}
+
+@article{thorhauge2019role,
+  title={The role of intention as mediator between latent effects and behavior: application of a hybrid choice model to study departure time choices},
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+  journal={Transportation},
+  volume={46},
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+  pages={1421--1445},
+  year={2019},
+  publisher={Springer}
+}
+
+@article{schmid2019store,
+  title={In-store or online shopping of search and experience goods: A hybrid choice approach},
+  author={Schmid, Basil and Axhausen, Kay W},
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+  pages={156--180},
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+  publisher={Elsevier}
+}
+
+@article{albaladejo2020effects,
+  title={The effects of motivations to go to the country on rural accommodation choice: A hybrid discrete choice model},
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+}
+
+@article{golkebiowska2020energy,
+  title={Energy Demand Management and Social Norms},
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+  pages={3779},
+  year={2020},
+  publisher={Multidisciplinary Digital Publishing Institute}
+}
+
+@book{train2009discrete,
+  title={Discrete choice methods with simulation},
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+  year={2009},
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+}
+
+@article{scarpa2008utility,
+  title={Utility in willingness to pay space: a tool to address confounding random scale effects in destination choice to the Alps},
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+  publisher={Oxford University Press}
+}
+
+
+@article{thiene2009deriving,
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+  author={Thiene, Mara and Scarpa, Riccardo},
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+  year={2009},
+  publisher={Springer}
+}
+
+
+@article{daly2012using,
+  title={Using ordered attitudinal indicators in a latent variable choice model: a study of the impact of security on rail travel behaviour},
+  author={Daly, Andrew and Hess, Stephane and Patruni, Bhanu and Potoglou, Dimitris and Rohr, Charlene},
+  journal={Transportation},
+  volume={39},
+  number={2},
+  pages={267--297},
+  year={2012},
+  publisher={Springer}
+}
+
+@article{raveau2012practical,
+  title={Practical and empirical identifiability of hybrid discrete choice models},
+  author={Raveau, Sebastian and Yanez, Maria Francisca and de Dios Ortuzar, Juan},
+  journal={Transportation Research Part B: Methodological},
+  volume={46},
+  number={10},
+  pages={1374--1383},
+  year={2012},
+  publisher={Elsevier}
+}
+
+
+@article{czajkowski2019simulation,
+  title={Simulation error in maximum likelihood estimation of discrete choice models},
+  author={Czajkowski, Miko{\l}aj and Budzi{\'n}ski, Wiktor},
+  journal={Journal of Choice Modelling},
+  volume={31},
+  pages={73--85},
+  year={2019},
+  publisher={Elsevier}
+}
+
+@article{welling2022information,
+  title={Information, consequentiality and credibility in stated preference surveys: A choice experiment on climate adaptation},
+  author={Welling, Malte and Zawojska, Ewa and Sagebiel, Julian},
+  journal={Environmental and Resource Economics},
+  volume={82},
+  number={1},
+  pages={257--283},
+  year={2022},
+  publisher={Springer}
+}
+
+@article{stigler1961economics,
+  title={The economics of information},
+  author={Stigler, George J},
+  journal={Journal of political economy},
+  volume={69},
+  number={3},
+  pages={213--225},
+  year={1961},
+  publisher={The University of Chicago Press}
+}
+
+@article{nisbet2009nature,
+  title={The nature relatedness scale: Linking individuals' connection with nature to environmental concern and behavior},
+  author={Nisbet, Elizabeth K and Zelenski, John M and Murphy, Steven A},
+  journal={Environment and behavior},
+  volume={41},
+  number={5},
+  pages={715--740},
+  year={2009},
+  publisher={Sage Publications Sage CA: Los Angeles, CA}
+}
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diff --git a/ugs_data-main.Rproj b/ugs_data-main.Rproj
new file mode 100644
index 0000000..8e3c2eb
--- /dev/null
+++ b/ugs_data-main.Rproj
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-- 
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