The average price bias choice quasi-experiment is designed to elicit consumers’ perceptions about different pricing schemes. The experiment aims to correlate the findings with participants’ characteristics, potential behavioural biases and the participants’ financial and environmental literacy levels.

The experiment consists of five discrete key sections: 1) a section about participant’s demographic data, 2) a small set of questions related to behavioural biases, 3) a set of questions related to financial literacy, 4) a section with questions related to environmental literacy and 5) the choice experiment about price perceptions.

Section 5 presents a hypothetical scenario about the participant’s yearly energy consumption and several pricing tariff options. The participant has to choose a pricing tariff they think is the most cost-effective. There are six (1-6) broader cases, each including four subcategories (a-d). The further the case is from the beginning, the more complicated it is.

The implementation of the experiment is as follows:

Step 1. The participant first receives the following message: “Assuming that your yearly energy consumption is exactly 6,000 kWh, which one of the following tariffs would you choose as the most cost-effective?”

Step 2. Each participant will be asked to participate in only 2 cases (all subcategories of each case are included). A case will be randomly chosen from cases 1-3 (simple case) and a second random choice will be made from cases 4-6 (complex case). Thus, all participants will answer a simple and a complicated set of questions.

Step 3. The participant receives the first set of choices.

If the participant answers correctly, he receives the next subcategory’s choice set. If he answers false, he gets the next set of choices within the same subcategory. Thus, as soon the participant answers correctly, he skips the following set of choices and moves to the next subcategory. For a participant answering correctly, this will be a short survey. However, for someone answering wrong, the survey will last longer.

More information can be found on the public deliverables of the EVIDENT project https://evident-h2020.eu/deliverables/. More specifically, the experiment’s theoretical framework and motivation are described in deliverable D1.2 Assessing behavioural biases and financial literacy, in section 5 while the final design is reported in D3.2 Implementation of preparatory actions for RCT, surveys and serious game.

Cite as: Pragidis, Ioannis, & Karypidis, Paris-Alexandros. (2023). EVIDENT H2020 – Average Price Bias Dataset (0.1.0) [Data set]. Zenodo. https://doi.org/10.5281/zenodo.7825632

The EVIDENT Discrete Choice Experiment seeks to explore the impact of energy related financial literacy, consumer motivation, point-of-sale information and demographic factors on discount rate and willingness to pay for efficient household appliances. Across a series of choice experiments, the impact of factors such as financial information (purchase price, operating cost, salience of financial information), risk reduction (i.e. extended warranty), and financial capacity (i.e. low cost loans) on implicit discount rates for home appliances is examined. Further, the impact of direct rebound rates on efficient appliance selection is examined.

The experiment consists of the following sections: 1) demographic information; 2) current home appliance purchasing behaviour; 3) financial literacy; 4) environmental literacy; 5) stated preference experiment consisting of four choice points; 6) discount rates; 7) discrete choice experiment consisting of ten choice points; and 8) questions examining direct rebound rates associated with the novel appliance selected.

As noted above, two choice experiments are included within the current use case. The first of these is a stated preference experiment which examines the impact of financial and energy framing on willingness-to-pay for energy efficient appliances. Four choice points are presented within this experiment. Choice 1 presents five identical versions of an appliance which differ only by key feature, and seeks to reduce hypothetical bias across the choice experiment. For example, for a washing machine the key features are cost, capacity, spin speed, quick wash time and pause wash functionality. Choice 2 consists of the participants initial choice (at choice 1) alongside alternatives which differ only in purchase price and energy rating, with purchase price greater for more efficient appliances (I.e. A rated appliances are most expensive; D rated appliances are least expensive). Choice 3 is similar to choice 2, however in this instance operational costs per month are also presented. Again, operational costs are lower for more efficient appliances. Choice 3 is similar to choice 3 however in this instance operational costs per year are presented.

The second choice experiment is the DCE which explores the relative impacts of risk reduction (extended warranty), and financial supports (low cost loan, loan term) on willingness to invest in more efficient energy appliances. Attributes were selected based on literature review, focus group analyses, cognitive walk-through and usability analyses. Once final attributes were determined, choice cards were developed using a fractional factorial design. A statistically efficient main-effects design with 10 choice sets was created in R studio using the idefix package. As such, participants are presented with a series of ten choice points, each consisting of two appliances and a ‘no preference’ option.

More information on the EVIDENT Discrete Choice Experiment can be found on the public deliverables of the EVIDENT project https://evident-h2020.eu/deliverables/. More specifically, the experiment’s theoretical framework and motivation are described in deliverable D1.2  Assessing behavioural biases and financial literacy, in section 5 while the final design is reported in D2.2  Optimised Protocols Design.

Cite as: Delemere, Emma, & Liston, Paul. (2023). EVIDENT H2020 – Discrete Choice Experiment Dataset [Data set]. Zenodo. https://doi.org/10.5281/zenodo.7825986

The EVIDENT serious game explores consumer behaviour in response to a malfunctioning home appliance. Specifically, it examines how consumers approach decisions to repair or replace a broken home appliance and the impact of behavioural biases on these decisions. There are two key aims addressed within the EVIDENT serious game. 1) Determine the impact of socio-demographic factors, environmental literacy, and financial literacy on consumer willingness to pay for the repair of home appliances. 2) Determine the impact of information and education mediated through a serious game on consumer in-game and real-world repair/replace decision-making.

The serious game itself is a life-simulation game in which users are tasked with maintaining their virtual home while ensuring their avatar remains comfortable (i.e. basic needs such as hunger, warmth and hygiene are met) while monitoring their financial and energy consumption. Within this game, users learn that an appliance has malfunctioned, and a repairperson is called. Users must then determine how best to proceed by entering a negotiation with the repairperson.

The experiment consists of the following sections: 1) demographic information; 2) financial literacy; 3) environmental literacy; 4) serious game. The game receives as input the replies of the participant on the demographics information section to provide a personalized gameplay experience. Replies regarding participant’s age (“What is your age?”), role (“Which of the following apply to you?”), income (“What is your household’s annual income?”), gender (“Which character would you like to play with?”) and family status (“How many people live in your home (including you) – Children”) will be used to adjust players’ avatar, starting amount of money, size of the house, age of the player and the negotiation process with the repair person.

The negotiation process differs based on the participants’ role (“Which of the following apply to you?”). In this question, the participant can choose one of the following replies: 1) I am a homeowner, 2) I am a tenant (i.e. I pay someone to rent my accommodation), 3) I am a landlord (i.e. I receive payment for accommodation from someone else). Participants who rent (2) or are landlords (3) will be assigned to an additional in-game scenario to explore the unique context in which their energy decisions are made. Random allocation to a role will be applied for participants who select multiple options (i.e., homeowners who are also landlords).

More information on the EVIDENT Serious Game Experiment can be found on the public deliverables of the EVIDENT project https://evident-h2020.eu/deliverables/. More specifically, the serious game implementation design is described in deliverable D2.3 Serious game implementation design, the design of the experiment is reported in D2.2 Optimised Protocols Design, and the experiment preparatory actions are described in D3.1 Specifications of preparatory actions for RCT, surveys and serious game and D3.2 Implementation of preparatory actions for RCT, surveys and serious game.

Finally, the EVIDENT serious game can be found in the following locations:

EVIDENT Website: https://evident-h2020.eu/seriousgame
Google Play: https://play.google.com/store/apps/details?id=com.CERTH.EvidentSeriousGame
App Store: https://apps.apple.com/gr/app/evident-serious-game/id6447255106
EVIDENT Platform (participation in the experiment): https://platform.evident-h2020.eu/sessions/participate_session/1560d6e6-732a-470c-807a-c70472d51c53

Cite as:Delemere, Emma, Liston, Paul, Karypidis, Paris-Alexandros, & Pragidis, Ioannis. (2023). EVIDENT H2020 – EVIDENT Serious Games Dataset (0.1.0) [Data set]. Zenodo. https://doi.org/10.5281/zenodo.7956164