revisions before wonv

project_start.qmd

@@ -65,7 +65,7 @@ list_ols <- list("(Intercept)" = "Intercept", "as.factor(Treatment_A)Treated" =
 -   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 voluntary information about genetic modified food before participating in a choice experiment.
--   Both studies conclude that, on average, respondents who retrieve voluntary information have **larger willingness to pay** for the good to be valued.
+-   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.
 :::
 
@@ -80,9 +80,9 @@ list_ols <- list("(Intercept)" = "Intercept", "as.factor(Treatment_A)Treated" =
 ## Research Questions
 
 ::: incremental
-1.  How do obligatory and optional information provision affect **survey engagement**, **information recall**, **consequentiality**, and **stated preferences**?
-2.  Do **socio-demographic** or **attitudinal** variables influence the decision to **access voluntary information**?
-3.  Do **survey engagement**, **information recall**, **consequentiality**, and **stated preferences** differ between respondents who **access voluntary information** and those who do not?
+1.  Do obligatory and optional information provision affect **survey engagement**, **information recall**, **consequentiality**, and **stated preferences**?
+2.  Do **socio-demographic** or **attitudinal** variables influence the decision to **access optional information**?
+3.  Do **survey engagement**, **information recall**, **consequentiality**, and **stated preferences** differ between respondents who **voluntary access information** and those who do not?
 :::
 
 # Survey & Data
@@ -95,7 +95,7 @@ list_ols <- list("(Intercept)" = "Intercept", "as.factor(Treatment_A)Treated" =
 -   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**.
+<!-- -   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
@@ -104,8 +104,8 @@ list_ols <- list("(Intercept)" = "Intercept", "as.factor(Treatment_A)Treated" =
 
 ## Treatment (Information Provision)
 
--   Short info text about the effect of **natural urban green spaces** on urban **heat islands**.
--   **Optional video** with the almost the same information.
+-   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"}
 
@@ -121,19 +121,13 @@ list_ols <- list("(Intercept)" = "Intercept", "as.factor(Treatment_A)Treated" =
 -   Example: *The city should do more to avoid heat islands. (Strongly agree - Strongly disagree)*
 :::
 
-## Experimental Setting
 
-![](Grafics/FlowChart_4_groups.png){width="300"}
 
-## Case A
 
-![](Grafics/FlowChart_4_groups_A.png){width="300"}
 
-## Case B
 
-![](Grafics/FlowChart_4_groups_B.png){width="300"}
 
-## Data
+## Additional Data
 
 ::: incremental
 
@@ -141,30 +135,25 @@ list_ols <- list("(Intercept)" = "Intercept", "as.factor(Treatment_A)Treated" =
 
 +   Timings: We saved the net interview time and the mean Choice Card time.-\> **Survey engagement**
 
-+   **Consequentiality**:
++   Two questions on **consequentiality **
 
-1. 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 )
-
-2. To what extent do you believe that the decisions you make will affect whether you have to pay a contribution for urban greening in the future? (I believe in it very much - I don’t believe in it at all )
+- 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)
++   **Attitudinal variable**: Measure derived from 21 items on **nature relatedness** [@nisbet2009nature]
 
 :::
 
-# Methods
+
+## Experimental Setting
+
+![](Grafics/FlowChart_4_groups.png){width="300"}
+
 
 ## Methods (1) {auto-animate="true"}
 
--   Logit regression (voluntary information access):
 
-```{=tex}
-\begin{equation}
-    Y = \beta_0 + \beta_{Control} \cdot v_{Control} + \epsilon
-    \label{simple_logit}
-\end{equation}
-```
 -   OLS regression (survey engagement, information recall, consequentiality):
 
 ```{=tex}
@@ -211,6 +200,11 @@ and
 ```
 # Case A: Obligatory vs. Optional Information
 
+
+## Case A
+
+![](Grafics/FlowChart_4_groups_A.png){width="300"}
+
 <!-- ::: {style="font-size: 45%;"} -->
 
 <!-- ```{r, results='asis'} -->
@@ -231,7 +225,14 @@ and
 
 <!-- ::: -->
 
-## OLS Engagement: Interview & Choice Card Time
+## OLS: Engagement
+
+```{=tex}
+\begin{equation}
+    Y = \beta_0 +  \beta_{Treat} \cdot v_{Treat} + \beta_{Control} \cdot v_{Control} + \epsilon
+    \label{olss}
+\end{equation}
+```
 
 ```{r}
 ggpubr::ggarrange(plot_interview_A, plot_cc_A)
@@ -245,7 +246,7 @@ ggpubr::ggarrange(plot_mani_A, plot_cons_A)
 
 ## MXL: Effects on Stated Preferences
 
-::: {style="font-size: 60%;"}
+::: {style="font-size: 80%;"}
 ```{r, results='asis'}
 htmlreg(c(case_A_cols[1], remGOF(case_A_cols[2:4])),
        custom.coef.map = list("natural" = "Naturalness", "walking" = "Walking Distance", "rent" = "Rent",
@@ -260,9 +261,20 @@ htmlreg(c(case_A_cols[1], remGOF(case_A_cols[2:4])),
 
 # Case B: Voluntary Information Access
 
-## Logit Regression: Who chooses Treatment?
+## Case B
 
-::: {style="font-size: 65%;"}
+![](Grafics/FlowChart_4_groups_B.png){width="300"}
+
+## Logit Regression: Who chooses Optional Information?
+
+```{=tex}
+\begin{equation}
+    Y = \beta_0 + \beta_{Control} \cdot v_{Control} + \epsilon
+    \label{simple_logit}
+\end{equation}
+```
+
+::: {style="font-size: 58%;"}
 ```{r, results='asis'}
 
 
@@ -291,7 +303,7 @@ ggpubr::ggarrange(plot_mani_D, plot_cons_D)
 
 ## MXL: Case B
 
-::: {style="font-size: 60%;"}
+::: {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",
@@ -301,13 +313,13 @@ htmlreg(c(case_B_cols[1], remGOF(case_B_cols[2:5])),
        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 including NR-index.")
+       caption = "Results of mixed logit model with treatment interactions for Case B.")
 ```
 :::
 
 ## MXL: Case B with NR-index Interaction
 
-::: {style="font-size: 60%;"}
+::: {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",
@@ -317,13 +329,15 @@ htmlreg(c(case_B_cols_NR[1], remGOF(case_B_cols_NR[2:6])),
        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.")
+       caption = "Results of mixed logit model with treatment interactions for Case B including NR-index.")
 ```
 :::
 
+# Discussion
+
 ## Discussion (1)
 
-1.  How do obligatory and optional information provision affect survey engagement, information recall, consequentiality, and stated preferences?
+1.  Do obligatory and optional information provision affect survey engagement, information recall, consequentiality, and stated preferences?
 
 ::: incremental
 -   Obligatory and voluntary treatments do not increase survey engagement measured via time spend on the survey
@@ -339,19 +353,19 @@ htmlreg(c(case_B_cols_NR[1], remGOF(case_B_cols_NR[2:6])),
 
 ## Discussion (2)
 
-2.  Do socio-demographic or attitudinal variables influence the decision to access voluntary information?
+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 influence the likelihood of accessing additional information
+-   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 access voluntary information and those who do not?
+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 engage more in the survey & have a higher consequentiality score