project_start.qmd

---
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