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Talk to an Expert| Category | Assignment | Subject | Economics |
|---|---|---|---|
| University | Massey University | Module Title | 178230 The Economics of Human Behaviour |
| Word Count | 1500 words |
|---|
Consider nudging in behavioural economics and what it is designed to do. You are tasked with reflecting upon nudges and considering how they can be used to reduce traffic congestion and pollution in New Zealand. It could be achieved by various means, e.g., promoting walking and biking, promoting public transport usage, and discouraging driving in peak hours (or other means you can think of).
You are tasked with coming up with potential solution(s) to this issue. You can come up with your original ideas of nudges, or borrow from other countries’ experiences, or discuss both. If you borrow from other countries, you should explain how their nudges should be adapted to the New Zealand environment. You need to clearly describe the choice architecture of your solution(s) and show that they alter behaviour in a predictable way without restricting choice or incentives. You are also encouraged to consider some of the insights into biases and heuristics that you have learned in the course to explain how your solution will work.
It is up to you as to how you structure your essay, however you should bear in mind the marking rubric, which is in the assignment dropbox below.
If you use references, please be sure to use APA referencing style. Please also note that if you are quoting directly from a source, you must correctly attribute the source. Likewise, if you are paraphrasing from a source, please be sure to acknowledge that source.
Please submit your assignment in the dropbox below. Please submit the entire assignment as a single document, including the AI use statement as an appendix. Please include a title page and a header that includes your name and student ID. If you use references, a reference list should be included at the rear of your document. Your reference list will not be included in the word count.
For your reference, our discussion of nudging is discussed in Topic 9, the readings for which include the supplementary readings linked in the Topic 9 section of the Stream site. Once you have identified your nudge, you might also find it useful to review relevant connected biases or heuristics from earlier in the semester to inform this discussion.
| Criteria | 1 Point (Poor) | 2 Points (Limited) | 3 Points (Adequate) | 4 Points (Good) | 5 Points (Excellent) |
|---|---|---|---|---|---|
| Choice Architecture Design (10 marks) | Very poor or missing explanation. No clear understanding of behavioral influence through design. (2 points) | Limited or unclear explanation. Shows weak understanding of choice architecture principles. (4 points) | Adequate explanation with some relevant elements, but lacks depth or clarity in how behavior is predictably altered. (6 points) | Clearly explains the choice architecture with minor gaps in detail or clarity. Shows good understanding of behavioral influence. (8 points) | Provides a clear, detailed, and insightful explanation of the choice architecture. Demonstrates strong understanding of how it alters behavior predictably. (10 points) |
| Preservation of Freedom and Incentives (10 marks) | Fails to address or misunderstands the concept of preserving choice and avoiding incentives. (2 points) | Limited explanation; may confuse nudging with coercion or incentives. (4 points) | Addresses the issue but lacks clarity or depth in showing how freedom and incentives are preserved. (6 points) | Shows good understanding of preserving choice and minimizing incentives, with minor gaps in explanation. (8 points) | Clearly demonstrates that the solution preserves freedom of choice and avoids significant incentives. Strong justification provided. (10 points) |
| Application of Behavioral Insights (5 marks) | No meaningful application of behavioral economics concepts. (1 point) | Minimal or unclear use of behavioral insights. (2 points) | Includes some behavioral concepts but lacks depth or relevance. (3 points) | Uses relevant behavioral concepts with minor inaccuracies or limited integration. (4 points) | Integrates multiple relevant behavioral concepts (e.g., biases, heuristics) effectively to support the solution. (5 points) |
| Creativity and Feasibility of the Solution (5 marks) | No clear or viable solution presented. (1 point) | Solution lacks creativity or is impractical. (2 points) | Some originality shown, but feasibility or relevance is limited. (3 points) | Solution is creative and feasible, with minor limitations. (4 points) | Presents a highly original and practical solution tailored to New Zealand’s context. (5 points) |
| Use of Evidence and Examples (5 marks) | No meaningful evidence or examples provided. (1 point) | Limited or unclear use of supporting material. (2 points) | Some evidence used, but not always relevant or well-integrated. (3 points) | Good use of examples or evidence, with minor data or support gaps. (4 points) | Strong use of relevant examples, data, or course material to support arguments. (5 points) |
| Structure, Clarity, and Referencing (5 marks) | Disorganized and unclear writing. Referencing is missing or inappropriate. (1 point) | Poor structure or clarity. Referencing is minimal or incorrect. (2 points) | Adequate structure and clarity. Referencing is present but inconsistent or incomplete. (3 points) | Mostly clear and well-organized. Minor referencing or language issues. (4 points) | Writing is well-structured, clear, and academic. Referencing is accurate, consistent, and complete. (5 points) |
Hook: Open with a concrete NZ stat — e.g. Auckland is one of the most congested cities in the Asia-Pacific; transport is NZ’s second-largest source of greenhouse gas emissions (~17%). Cite Ministry for the Environment or MfE data.
Define nudging: Reference Thaler & Sunstein (2008) — a nudge is any aspect of choice architecture that alters behaviour in a predictable way without restricting options or changing economic incentives. One sentence, precise.
Scope statement: Briefly flag your structure — you will propose [X] nudge solution(s) targeting [walking/PT/peak driving], drawing on international examples adapted for the NZ context.
Thesis: Argue that behavioural insights — particularly defaults, social norms, and present bias — offer a low-cost, liberty-preserving pathway to reduce congestion and emissions in NZ cities.
Choice architecture defined: The environment in which decisions are made — the “choice architect” designs how options are presented. Even “neutral” design shapes choices.
Key biases to introduce here (then apply later):
The nudge: Partnering with Google Maps / Waka Kotahi to make walking or cycling the default route shown for journeys under 3 km in NZ cities, with driving shown as the secondary option. Users can freely switch — no option is removed.
Choice architecture mechanism: Exploits default bias — the default option has outsized influence because it requires no active decision. By reordering route display, the architecture makes the active option salient without mandating it. Also exploits salience — a prominent “You’ll arrive at the same time walking!” prompt makes the trade-off concrete at the moment of decision.
International evidence to borrow: UK’s “nudge unit” (BIT) trip-planning interventions; Google Maps’ eco-routing default in Europe (defaulted to lowest-emission route) showed measurable shift in route selection. Adapt for NZ: focus on flat urban corridors in Auckland, Wellington, Christchurch where walking is genuinely feasible.
Freedom & incentives preserved: The driving option is always present — no route is hidden or made more expensive. This is purely information architecture. No fine, no congestion charge, no subsidy.
Biases activated: Status quo bias (default is now active transport), salience (time comparison shown), present bias partially addressed by showing real-time ETA equivalence.
NZ-specific adaptation: note that NZ’s relatively compact city centres (Wellington’s CBD, Christchurch post-rebuild flat grid) make this more feasible than in sprawling US cities.
The nudge: Personalised monthly “travel reports” sent to Auckland/Wellington commuters (via HOP card data or Council app) showing: “You took the bus 8 times this month — that’s more than 62% of commuters in your area. Your trips saved X kg CO₂.” Modelled on Opower energy reports.
Choice architecture mechanism: Descriptive social norms — what most people actually do — are a powerful default anchor. When people believe PT use is normal/common, the psychological cost of using it drops. The comparison to neighbours triggers injunctive norms (what others approve of) and mild loss aversion if you’re below average.
Evidence: Opower (now Oracle Utilities) used social norm energy reports and achieved 2–3% reductions in energy consumption at scale (Allcott, 2011 — cite this). Cialdini’s hotel towel experiments established descriptive norm effects. Adapt to NZ: use AT HOP card data (already collected) for low-cost implementation.
Freedom & incentives: Purely informational — no penalty, no reward. People can drive as much as they like. The report simply reframes what “normal” looks like, leaving all choices open.
Biases activated: Social norm bias, loss aversion (below-average framing), identity effects (“I’m someone who takes the bus”).
This is a strong nudge because it uses existing infrastructure (HOP cards) — makes it very feasible and NZ-specific, earning creativity/feasibility marks.
The nudge: A voluntary “off-peak pledge” app where Auckland commuters pre-commit (the night before) to travelling outside peak hours. The act of committing leverages consistency bias and implementation intentions — people who set a specific plan are far more likely to follow through.
Choice architecture: Pre-commitment is a self-imposed constraint — the person freely chooses it. The system then sends a reminder at 7am: “You pledged to leave at 9am today.” This exploits the planning fallacy correction — we follow through more when we’ve publicly or privately committed. Optional social sharing (“I’m going off-peak today”) adds norm reinforcement.
International parallel: Singapore’s voluntary off-peak rail travel incentive programme reduced peak-hour crowding. The NZ version removes the financial incentive — it is purely a commitment/reminder device, keeping it a true nudge rather than an incentive scheme.
Freedom preserved: Entirely voluntary — no cost to breaking the pledge, no tracking of compliance by authorities. The only mechanism is the individual’s own prior commitment.
Explicitly noting “this is not an incentive — there is no reward or fine” directly addresses the 10-mark freedom/incentives criterion.
Address NZ-specific factors: Car dependency culture, limited PT in smaller cities, geographic terrain (hills in Wellington/Dunedin affect walking feasibility). Your nudges should acknowledge these — e.g. the default-route nudge should only activate where walking/cycling infrastructure exists.
Cultural considerations: Mana Whenua perspectives on communal wellbeing align with reducing pollution; this is a genuine NZ-specific framing opportunity. Social norm messaging could be localised to suburb/iwi level.
Policy fit: NZ’s emissions reduction plan and Urban Development Act provide institutional backing. Mention briefly to show feasibility.
Synthesise: three complementary nudges targeting different behavioural barriers — default bias (route), social norms (PT reports), present bias / commitment (off-peak pledge). Each preserves full freedom of choice.
Acknowledge limits: nudges work best alongside structural improvements (better PT infrastructure); they are not a substitute for policy. Shows intellectual nuance.
End with the core insight: behavioural economics reveals that the problem isn’t just infrastructure — it’s the choice architecture people navigate daily. Small, low-cost redesigns of that architecture can yield meaningful, liberty-preserving behavioural change.
Thaler, R. H., & Sunstein, C. R. (2008). Nudge: Improving decisions about health, wealth, and happiness. Yale University Press.
Allcott, H. (2011). Social norms and energy conservation. Journal of Public Economics, 95(9–10), 1082–1095. — The Opower study.
Kahneman, D. (2011). Thinking, fast and slow. Farrar, Straus and Giroux. — System 1/2 framing.
Cialdini, R. B. (2007). Influence: The psychology of persuasion. — Social norms evidence.
Ministry for the Environment (2023). New Zealand’s greenhouse gas inventory — NZ transport emissions data.
Behavioural Insights Team (BIT) reports on active travel nudges — search at bi.team for relevant UK case studies.
| INTRO: |
|
| BACKGROUND: | Thaler (2008) – choice architecture – the environment in which decisions are made. A choice architect designs how decisions are made. The order, structure, context, in which choices are presented systematically influences the decisions people make
|
| NUDGE 1: DEFAULT ACTIVE TRANSORT ROUTES: |
|
| NUDGE 2: SOCIAL NORM MESSAGING ON PT: | |
| NUDGE 3:PEAK HOUR COMMITMENT DEVICE: | |
| ADAPTATION DISCUSSION | |
| CONCLUSION: |
The nudge: Partnering with Google Maps / Waka Kotahi to make walking or cycling the default route shown for journeys under 3 km in NZ cities, with driving shown as the secondary option. Users can freely switch — no option is removed.
Choice architecture mechanism: Exploits default bias — the default option has outsized influence because it requires no active decision. By reordering route display, the architecture makes the active option salient without mandating it. Also exploits salience — a prominent “You’ll arrive at the same time walking!” prompt makes the trade-off concrete at the moment of decision.
International evidence to borrow: UK’s “nudge unit” (BIT) trip-planning interventions; Google Maps’ eco-routing default in Europe (defaulted to lowest-emission route) showed measurable shift in route selection. Adapt for NZ: focus on flat urban corridors in Auckland, Wellington, Christchurch where walking is genuinely feasible.
Freedom & incentives preserved: The driving option is always present — no route is hidden or made more expensive. This is purely information architecture. No fine, no congestion charge, no subsidy.
Biases activated: Status quo bias (default is now active transport), salience (time comparison shown), present bias partially addressed by showing real-time ETA equivalence.
NZ-specific adaptation: note that NZ’s relatively compact city centres (Wellington’s CBD, Christchurch post-rebuild flat grid) make this more feasible than in sprawling US cities.
Chaudhuri, A (2021) Behavioural Economics and Experiments (1st Edition). London: Routledge
Frerich, J. (2025). Walk this way: harnessing digital nudges to promote walking for transportation.
Behavioural Public Policy, 1–15. https://doi.org/10.1017/bpp.2025.10
Steele, A. (2024). Nudge Theory. The Decision Lab. Retrieved May 28, 2026, from https://thedecisionlab.com/reference-guide/psychology/nudge-theory
Oliver, A. (2013). From Nudging to Budging: Using Behavioural Economics to Inform Public Sector Policy. Journal of Social Policy, 42(4), 685–700. https://www.cambridge.org/core/journals/journal-of-social-policy/article/from-nudging-to-budging-using-behavioural-Economics-to-inform-public-sector-policy/D98361CED793BE761AA22BF49299BF43
Thaler, R. H., & Sunstein, C. R. (2008). Nudge: Improving decisions about health, wealth, and happiness. Yale University Press.
Allcott, H. (2011). Social norms and energy conservation. Journal of Public Economics, 95(9–10), 1082–1095. — The Opower study.
Kahneman, D. (2011). Thinking, fast and slow. Farrar, Straus and Giroux. — System 1/2 framing.
Cialdini, R. B. (2007). Influence: The psychology of persuasion. — Social norms evidence.
Ministry for the Environment (2023). New Zealand’s greenhouse gas inventory — NZ transport emissions data.
Behavioural Insights Team (BIT) reports on active travel nudges — search at bi.team for relevant UK case studies.
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