Willingness To Pay for BIO waste sorting: A Combined Vignette and Referendum Study

2024-04-26

2024-05-17

After reading the vignette and the detailed hypothetical scenario, individuals are required to vote on whether they support or oppose the placement of a separate container for BIO waste in their apartment building's yard (binary variable).

Participants in the study will be randomly assigned to complete one of 30 versions of the survey. This design allows each respondent to encounter one of four vignettes, along with a control group that does not receive any vignette. Additionally, participants will be presented with one of six BIO waste management tariffs. This factorial design (vignettes × tariffs) aims to explore the interaction between the contextual information provided in the vignettes and the financial incentives associated with different tariffs for managing BIO waste. The random assignment ensures that any variation in responses can be attributed to the differences in the vignettes and tariffs rather than other external factors. This structured approach allows for a comprehensive analysis of the factors that motivate or deter BIO waste sorting among residents.

In this experiment, the interventions are structured around four different vignettes and a control group. Each vignette presents a unique scenario designed to influence the participants' voting behavior regarding the installation of BIO waste containers, compared to the control group that does not receive additional context.

Vignette 1: Imminent Closure of the Getliņi Landfill
Participants are informed that Latvia's largest landfill, Getliņi, will no longer be able to accept unsorted household waste within the next seven to ten years unless there is a significant increase in waste sorting. The closure of Getliņi would necessitate either finding another landfill location in Latvia or more likely, constructing one or more waste incineration plants.

Vignette 2: Cost Savings from Sorting
This vignette highlights that sorting waste can reduce household waste disposal costs by up to 30% because sorted waste containers are collected for a reduced fee or even for free. It is noted that BIO waste is currently collected at a 40% reduced cost, and that 30%-50% of what is thrown into the general waste container could actually be recyclable BIO waste.

Vignette 3: Fines for Non-Compliance
Participants learn that Latvia has been paying approximately 15 million euros annually to the European Union budget as a penalty for insufficient plastic waste recycling. This translates into each adult resident effectively paying around ten euros each year for inadequate sorting. If sorting does not improve, these penalties could increase as the EU mandates that only 10% of waste be landfilled by 2035, a significant reduction from the current 53% at Getliņi.

Vignette 4: Environmental Sustainability
This scenario discusses the role of new technologies in waste management, emphasizing that their effectiveness in reducing environmental impact depends on individual participation in waste sorting. It argues that without active participation, even the most advanced technologies will not achieve their full potential in preserving the environment. Participants are encouraged to engage actively for a sustainable future.

Following the vignette (or no vignette in case of random assignment to the control group), participants are presented with a hypothetical scenario: They are living in a multi-apartment building with another adult, sharing household expenses. Their monthly waste management bill is denoted as [X] euros, which covers the cost of removing unsorted waste containers shared by the building. The building manager has issued an invitation to all apartment owners to vote on whether to install a separate container on the property for sorted organic (BIO) waste. The collection cost for BIO waste containers would be [Y] euros less than that for unsorted waste containers. Consequently, if the vote is favorable, their household could save [Z] euros per year, assuming that an average of 40% of their unsorted waste is actually BIO waste. The participants are then asked how they would vote regarding the installation of this new BIO waste container.

Participants are randomly assigned to one of three different monthly invoice levels for waste management—15, 25, or 35 euros—representing the variable [X]. Additionally, they are assigned to one of two tariffs for collecting BIO containers, which are 40% or 60% less than the cost of collecting unsorted waste, representing the variable [Y]. These combinations result in six distinct potential savings amounts (variable [Z]) that a participant's household could realize over the course of a year.

The participant pool for this study will be recruited through the sociological firm SKDS, which maintains a panel representative of the Latvian population. The study will involve at least 5,000 participants who currently do not sort BIO waste. These participants will complete the survey online using Computer-Assisted Web Interviewing (CAWI).

Individual

No

5,000 individuals

5,000 individuals

Each of the 30 treatment arm will have an approximately equal number of participants, around 166 individuals per group. This experiment employs factorial design, combining different vignettes with various tariffs for managing BIO waste. Each vignette is designed to be presented to approximately 1,000 respondents, ensuring a robust sample size for detecting the influence of contextual narratives on participants' decisions. Additionally, each tariff level will be assigned to about 830 respondents.

The power calculations to determine the minimum detectable effect sizes (MDES) for the main outcomes take into account the factorial design of this study which integrates two factors: vignettes and fee levels. The experimental setup includes five vignette types and six fee levels, organized into 30 distinct treatment combinations. With a total of 5,000 observations evenly distributed among these combinations, each subgroup analysis—either by vignette type or by fee level—benefits from an adequately large sample size to allow for robust statistical analysis. Each vignette type, pooled across all six fee levels, is analyzed with approximately 1,000 observations. Conversely, each fee level, pooled across all five vignette types, is analyzed with about 833 observations. This uniform sample distribution facilitates the independent assessment of the main effects of each factor. For the purpose of these calculations, a conservative assumption was made regarding the baseline response probability, set at 30% for both factors. This establishes a common ground for measuring changes and enhances the reliability of the effect size estimates derived from the analysis. The study is designed to detect changes in response probability with a significance level of 5% and a statistical power of 80%. Under these conditions, the power analysis reveals that the minimum detectable effect size for vignettes is approximately 5.87 percentage points, which translates into detecting an increase in uptake from the baseline of 30% to at least 35.87%. For fee levels, the detectable effect size is slightly higher at about 6.45 percentage points, reflecting the smaller sample size for these groups, thus requiring a larger change to achieve the same level of statistical confidence. This corresponds to an increase in uptake from 30% to at least 36.45%. The standard deviation for these estimates, based on the binomial distribution for a proportion of 0.3, is approximately 0.458. This value represents the maximum variability expected in the response rates, providing a statistical basis for the precision of the findings expected from this factorial design.