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on Nudge and Boosting |
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Issue of 2024–12–09
three papers chosen by Marco Novarese, Università degli Studi del Piemonte Orientale |
| By: | Wendt, Charlotte; Kosin, Dominick; Adam, Martin; Benlian, Alexander |
| Abstract: | The growing adoption of smart meters enables the measurement of households' energy consumption, influenced not solely by building characteristics such as thermal insulation but also by residents' behavioural patterns, such as heating and ventilation practices. To motivate residents to adopt more sustainable behaviours, user interfaces on smartphones and laptops are increasingly using consumption data from households' smart meters to enable effective goal‐setting. In contrast to previous research largely focusing on goal‐setting in isolation, this study examines the role of specific social comparison‐related design features that future research and practitioners can consider along with goal‐setting to stimulate sustainable behaviours. Specifically, we look into the influence of residents' perception of their relative performance (i.e., whether their behaviour was better or worse than a reference group) on their ambition to act (i.e., targeted improvement goal) and their actual energy consumption behaviour. Moreover, we investigate the influence of a goal's evaluative standard (i.e., whether the goal refers to one's own or other's performance) on the relationship between relative performance, ambition to act, and energy consumption behaviour. Drawing on social comparison theory, we conducted a framed field experiment with 152 households. We find that a goal's evaluative standard influences residents' awareness of their relative performance, affecting their ambition to act and, ultimately, their energy consumption behaviour. More specifically, we find that whereas other‐ (vs. self‐) referencing goals encourage residents from worse‐than‐average performing households more strongly to improve their energy consumption behaviour, they discourage better‐than‐average ones. Overall, our study provides novel insights into the interplay between relative performance and evaluative standards as a means of fostering social comparison in smart meter‐facilitated goal‐setting, highlighting their crucial role in effectively supporting sustainable behaviours. |
| Date: | 2024–11 |
| URL: | https://d.repec.org/n?u=RePEc:dar:wpaper:150457 |
| By: | Mills, Stuart; Whittle, Richard |
| Abstract: | The UK Behavioural Insights Team transformed nudging and behavioural economics from nascent ideas to key policy tools for the UK Coalition Government. This article argues that political economic circumstances significantly contributed to the success of this ‘nudge’ programme. The Global Financial Crisis (GFC) created a ‘contest of authority’ over dominant policy approaches. By framing the crisis as a crisis of rationality, behavioural perspectives gained political support. The GFC also saw that the UK Government (from 2010) adopt a programme of fiscal austerity. Nudging complemented this programme by suggesting effective policy could be made cheaply. Using various accounts of nudging in the UK from those involved in its development, we demonstrate the role of the country’s political economy in the behavioural turn. We conclude by reflecting on the role of behavioural insights today, given a political–economic landscape much changed since 2010. |
| Keywords: | austerity; behavioural economics; nudge; political economy |
| JEL: | D90 |
| Date: | 2024–10–25 |
| URL: | https://d.repec.org/n?u=RePEc:ehl:lserod:126042 |
| By: | Athey, Susan (Stanford U); Castillo, Juan Camilo (U of Pennsylvania); Chandar, Bharat (Stanford U) |
| Abstract: | The rise of marketplaces for goods and services has led to changes in the mechanisms used to ensure high quality. We analyze this phenomenon in the Uber market, where the system of pre-screening that prevailed in the taxi industry has been diminished in favor of (automated) quality measurement, reviews, and incentives. This shift allows greater flexibility in the workforce but its net effect on quality is unclear. Using telematics data as an objective quality outcome, we show that UberX drivers provide better quality than UberTaxi drivers, controlling for all observables of the ride. We then explore whether this difference is driven by incentives, nudges, and information. We show that riders’ preferences shape driving behavior. We also find that drivers respond to both user preferences and nudges, such as notifications when ratings fall below a threshold. Finally, we show that informing drivers about their past behavior increases quality, especially for low-performing drivers. |
| JEL: | D83 L91 O33 |
| Date: | 2024–09 |
| URL: | https://d.repec.org/n?u=RePEc:ecl:stabus:3894 |