Research & Methodology
Research basis and design
This page documents the research supporting each intervention, how the simulator assigns conditions, what data is recorded, the assumptions behind every figure, and the limits of what the results can show.
Research question
Which evidence-based psychological interventions are most effective at encouraging sustainable decision-making across different socioeconomic circumstances?
Interventions and supporting research
Financial incentive
Monetary incentives change the immediate cost of a choice. Because people tend to discount future benefits and weigh losses more heavily than equivalent gains, the form of an incentive matters as much as its size: a small fee on a disposable item can shift behavior more than an equivalent bonus (Homonoff, 2018; Kahneman & Tversky, 1979). Incentives can also have limits, particularly when they crowd out intrinsic motivation (Gneezy et al., 2011).
Information and feedback
Information interventions make costs and consequences visible. Reviews of household energy studies find that information alone has mixed effects, while specific, personalized feedback tends to work better (Abrahamse et al., 2005). The gap between the cost-effectiveness of energy efficiency and its adoption is partly attributed to how operating costs are presented (Allcott & Greenstone, 2012).
Descriptive social norms, information about what similar people do, have reduced energy use in large field experiments with home energy reports (Allcott, 2011) and increased towel reuse in hotels (Goldstein et al., 2008). Norm messages can backfire for people already performing better than average unless paired with approval cues (Schultz et al., 2007).
Simulator design
| Design element | How it works | Why |
|---|---|---|
| Within-subject comparison | Each participant records a choice before and after an intervention in every scenario. | Allows a direct before-and-after comparison for each person. |
| Balanced intervention assignment | Each participant sees each intervention type exactly once, randomly paired with one of the three scenarios. | Every person experiences all three intervention types, and pairings vary across participants. |
| Randomized scenario order | The order of the three scenarios is shuffled for each session. | Reduces order and fatigue effects. |
| Randomized circumstances | Each scenario randomly assigns a tight, moderate, or comfortable budget. | Supports comparison across socioeconomic conditions, a central part of the research question. |
| Motivation and reflection items | One motivation question per scenario and ten optional five-point questions at the end. | Helps interpret why decisions did or did not change. |
Data recorded
Responses are saved only when a participant confirms that they are 18 or older and agrees to share anonymous responses. No names, email addresses, or IP addresses are stored.
| Field | Purpose |
|---|---|
| Session ID | Random code linking one participant's three decisions |
| Scenario ID and position | Which scenario was presented, and in what order |
| Circumstance | Assigned budget condition |
| Intervention | Financial, information, or social |
| Initial choice and motivation | Original decision and the reason given |
| Final choice | Decision after the intervention |
| Change indicators | Whether the decision changed, and whether it moved to the sustainable option |
| Reflection responses | Optional five-point ratings for ten dimensions |
| Timestamps | Start and completion time of the session |
Calculation assumptions
| Scenario | Assumption | Value used |
|---|---|---|
| Household energy | Extra purchase cost of efficient model | $200 |
| Household energy | Annual electricity savings | $50 |
| Household energy | Service life; discounting | 12 years; none |
| Household energy | Utility rebate | $150 |
| Transportation | Commute distance; workdays per year | 15 miles each way; 230 |
| Transportation | Vehicle operating cost | $0.30 per mile |
| Transportation | Vehicle CO₂ emissions | ≈ 400 g per mile (U.S. EPA, 2023) |
| Transportation | Transit fare; transit CO₂ per rider | $2 each way; estimated at ≈ 20% of driving |
| Transportation | Parking permit | $120 per month |
| Consumer behavior | Bottles per day; price per bottle | 2; $1.25 |
| Consumer behavior | Single-use bottle fee; reusable bottle | $0.25; $20 |
Limitations
- Stated, not observed, behavior. Participants make hypothetical choices; intentions often differ from what people actually do.
- Demand effects. Seeing an intervention may signal the expected answer and encourage a change that would not occur naturally.
- Sample. Participants are self-selected and the sample is small, so results are descriptive rather than statistically generalizable.
- Simplified scenarios. Real decisions involve more options, constraints, and information than a short scenario can represent.
- Unvalidated items. The reflection questions are proposed items, not validated psychological scales, and do not constitute a psychological assessment.
The simulator therefore distinguishes between findings established by published research and exploratory results generated by the simulator itself.
References
- Abrahamse, W., Steg, L., Vlek, C., & Rothengatter, T. (2005). A review of intervention studies aimed at household energy conservation. Journal of Environmental Psychology, 25(3), 273–291. https://doi.org/10.1016/j.jenvp.2005.08.002
- Allcott, H. (2011). Social norms and energy conservation. Journal of Public Economics, 95(9–10), 1082–1095. https://doi.org/10.1016/j.jpubeco.2011.03.003
- Allcott, H., & Greenstone, M. (2012). Is there an energy efficiency gap? Journal of Economic Perspectives, 26(1), 3–28. https://doi.org/10.1257/jep.26.1.3
- Gneezy, U., Meier, S., & Rey-Biel, P. (2011). When and why incentives (don't) work to modify behavior. Journal of Economic Perspectives, 25(4), 191–210. https://doi.org/10.1257/jep.25.4.191
- Goldstein, N. J., Cialdini, R. B., & Griskevicius, V. (2008). A room with a viewpoint: Using social norms to motivate environmental conservation in hotels. Journal of Consumer Research, 35(3), 472–482. https://doi.org/10.1086/586910
- Homonoff, T. A. (2018). Can small incentives have large effects? The impact of taxes versus bonuses on disposable bag use. American Economic Journal: Economic Policy, 10(4), 177–210. https://doi.org/10.1257/pol.20150261
- Kahneman, D., & Tversky, A. (1979). Prospect theory: An analysis of decision under risk. Econometrica, 47(2), 263–291. https://doi.org/10.2307/1914185
- Schultz, P. W., Nolan, J. M., Cialdini, R. B., Goldstein, N. J., & Griskevicius, V. (2007). The constructive, destructive, and reconstructive power of social norms. Psychological Science, 18(5), 429–434. https://doi.org/10.1111/j.1467-9280.2007.01917.x
- Steg, L., & Vlek, C. (2009). Encouraging pro-environmental behaviour: An integrative review and research agenda. Journal of Environmental Psychology, 29(3), 309–317. https://doi.org/10.1016/j.jenvp.2008.10.004
- Thaler, R. H., & Sunstein, C. R. (2008). Nudge: Improving decisions about health, wealth, and happiness. Yale University Press.
- U.S. Environmental Protection Agency. (2023). Greenhouse gas emissions from a typical passenger vehicle. https://www.epa.gov/greenvehicles/greenhouse-gas-emissions-typical-passenger-vehicle