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‘Nudging’ hotel guests to reduce food waste as a win–win environmental measure

June 2013
Economics Letters 119(3):325–327

DOI:10.1016/j.econlet.2013.03.019

Authors:

Steffen Kallbekken

CICERO Center for International Climate Research

Håkon Sælen

University of Oslo

We show that two simple and nonintrusive ‘nudges’–reducing plate size and providing social cues–reduce the amount of food waste in hotel restaurants by around 20%. The results are statistically significant. They are also environmentally substantial as food waste is a major contributor to climate change and other forms of environmental degradation. Given the magnitude of the contribution of food waste to global environmental change, it is surprising that this issue has not received greater attention. The measures reduce the amount of food the restaurants need to purchase, and there is no change in guest satisfaction, making it likely that profits will increase. The measures thus constitute potential win–win opportunities.

Estimated coefficients (and the associated standard errors) from the difference-in- difference analysis.

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Estimated coefficients, standard errors and p-values for the observational analysis.

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Author's personal copy

Economics Letters 119 (2013) 325–327

Contents lists available at SciVerse ScienceDirect

Economics Letters

journal homepage: www.elsevier.com/locate/ecolet

‘Nudging’ hotel guests to reduce food waste as a win–win

environmental measure

Steffen Kallbekken 1, Håkon Sælen ∗

CICERO Center for International Climate and Environmental Research – Oslo, P.O. Box 1129 Blindern, 0318, Oslo, Norway

highlights

•Wasted food embodies large environmental impacts.

•We conduct a field experiment to test two ‘nudges’ to reduce food waste.

•Both measures reduce food waste in hotel restaurants by around 20%.

•The measures also reduce private costs, making a win–win outcome likely.

article info

Article history:

Received 20 December 2012

Received in revised form

23 February 2013

Accepted 8 March 2013

Available online 18 March 2013

JEL classification:

Keywords:

Field experiment

Food waste

Behavioral economics

Climate policy

Choice architecture

Nudge

abstract

We show that two simple and nonintrusive ‘nudges’ – reducing plate size and providing social cues

– reduce the amount of food waste in hotel restaurants by around 20%. The results are statistically

significant. They are also environmentally substantial as food waste is a major contributor to climate

change and other forms of environmental degradation. Given the magnitude of the contribution of food

waste to global environmental change, it is surprising that this issue has not received greater attention.

The measures reduce the amount of food the restaurants need to purchase, and there is no change in guest

satisfaction, making it likely that profits will increase. The measures thus constitute potential win–win

opportunities.

1. Introduction

The environmental impact of food provision is well-known.

Food accounts for 20% of global greenhouse gas emissions

(Hertwich and Peters, 2009), and 92% of the global water footprint

is related to agriculture (UNEP, 2012). In addition are issues such as

land degradation, overfishing and local air and water pollution. The

fact that roughly one-third of all food is lost or wasted (Gustavsson

et al., 2011) has received less attention. It therefore appears that

food waste is a substantial, but largely neglected contributor to

environmental change. The IPCC (Metz et al., 2007), for instance,

∗Corresponding author. Tel.: +47 22 85 85 63.

E-mail addresses: steffen.kallbekken@cicero.uio.no (S. Kallbekken),

hakon.salen@cicero.uio.no,correctomundo@gmail.com (H. Sælen).

1Tel.: +47 22 85 87 58.

does not list any measures to reduce food waste among the more

than 50 mitigation policies highlighted in its summary for policy

makers.

Choice architecture can be used to alter people’s behavior in

predictable ways (Thaler and Sunstein, 2008). From obesity and

nutritional research we know that ‘‘the eating situation often (but

not always) provides clues allowing us to infer how much we can

eat without eating an inappropriately large amount’’ (Herman and

Polivy, 2005). These clues form a part of the choice architecture,

and can be used to alter behavior. Our focus is on reducing food

waste, and thereby also reducing emissions of greenhouse gases.

We take as our starting point the observation that some of the

measures aimed at reducing food intake have been reported to also

reduce food waste (Freedman and Brochado, 2010).

Our study includes a field experiment (Harrison and List,

2004) where we intervene to change two variables of interest,

and a complementary observational study, based on pre-existing

variation in one of the variables of interest. In the field experiment

http://dx.doi.org/10.1016/j.econlet.2013.03.019

Author's personal copy

326 S. Kallbekken, H. Sælen / Economics Letters 119 (2013) 325–327

we test the effectiveness of two treatments in reducing the amount

of food waste generated. Both treatments rely on influencing

consumption norms through external cues.

The first treatment concerns the effect of plate size on the

amount of food waste. It has been argued that ‘‘plate shape and size

delineate norms for appropriate amounts of food to eat at a meal

(Sobal and Wansink, 2007) and it has been shown that’’. .. big bowls

lead to overserving, small bowls lead to underserving. .. ? (Ittersum

and Wansink, 2012). In addition to the social cue it provides, larger

plates might also contribute to people serving and consuming

more food due to visual illusions that lead to biased perceptions

of how much food is served or consumed (Ittersum and Wansink,

2012). Combining this with the finding that increased portion

size leads to both increased food intake and increased food waste

(Freedman and Brochado, 2010), it seems a reasonable hypothesis

that decreasing plate size will decrease the amount of food waste.

In the field experiment the typical plate size reduction was from

24 to 21 cm (the plates were used for breakfast buffets, and, if

applicable, also at lunch and dinner buffets). In the observational

study the average plate size ranged from 15 to 28 cm (average

24.0 cm).

The second treatment is to provide a more direct social cue by

displaying a sign at the buffet that encourages restaurant guests

to help themselves more than once. The text reads, in seven

different languages: ‘‘Welcome back! Again! And again! Visit our

buffet many times. That’s better than taking a lot once’’. The sign

is intended to make it salient that it is socially acceptable to

help yourself more than once from the buffet, which might affect

behavior as ‘‘just as people often look to portion size for guidance

in eating situations ... so they may rely on the example of others

for guidance, when such examples are salient’’ (Herman and Polivy,

2005). The hypothesis is that the sign will encourage guests to load

less food on their plates each time they serve themselves, in turn

reducing the amount left over.

2. Method

The two treatments are tested in an experiment conducted

in collaboration with hotel restaurants. From a hotel chain we

recruited individual hotels to implement the two treatments, and

the remaining hotels made up the control group. A total of 52 hotels

delivered data which we could use in the final analysis. There

were 7 in each treatment group. The experiment was implemented

between June 1st and August 15th 2012. All hotel restaurants in

the study recorded and reported the amount of food waste daily

during the whole period. The treatment hotels implemented their

respective treatments from July 1st until August 15th.

We estimate a difference-in-difference model (Card and

Krueger, 1994) using a fixed effects panel regression to analyze the

treatment effects. The difference-in-difference method controls for

pre-treatment differences between the hotels and for trends over

time that are unrelated to the intervention. In addition, we control

for the number of guests staying at the hotel (expected to be a

good predictor of the number of breakfasts served), and food sales

revenue (in 1000s of NOK, a useful proxy for the number of meals

served, excluding breakfast as this is commonly included in the

price). Food waste from hotel iat time tis modeled as follows:

Wasteit =β11D1i+β12 D2i+ · · · + β1nDni +β2Guestsit

+β3Food salesit +γti+δ(Ti×ti)+eit

where D1i. . . Dni are hotel specific intercept dummy variables

defined so that

D1i=1i=1

0 otherwise,D12 =1i=2

0 otherwise, . . . ,

D1n=1i=n

0 otherwise.

Table 1

Average amount of food waste (kg) per hotel in the control group (38 hotels) and

test groups (7 hotels in each group), before and after the treatment was introduced.

Standard deviations in brackets.

Group Pre-treatment food

waste (kg, average per

hotel)

Post-treatment food

waste (kg, average per

hotel)

Control 35.07 32.98

(34.63) (30.77)

Reduced plate size 36.88 25.84

(51.06) (27.15)

Salient sign 47.76 34.25

(38.88) (25.84)

These control for average permanent differences between hotels,

while

ti=0 before treatment begins

1 after treatment begins

controls for time trend common to control and treatment groups.

Tiis defined so that

Ti=0 for hotels in control group

1 for hotels in treatment group.

The random error term eit is assumed to be i.i.d. normal. It is the

coefficient of the interaction between tiand Tithat measures the

effect of the treatment. A separate regression is estimated for each

of the treatments.

In the observational study, we utilize pre-existing differences

in plate size across hotels in the control group. We use a panel

regression also here. Food sales revenue and guests are still

controlled for. As the fixed effect model cannot handle variables

that are constant within hotels over time, which plate size is in this

case, we specify a random effects model:

Wasteit =β1+β2Plate sizeit +β3Guestsit

+β4Food salesit +eit +vi

where β1is the average intercept and viare random hotel-specific

deviations from the average.

3. Results

The experiment indicates that reducing the plate size reduces

food waste by 19.5% (p<0.001), and that introducing the sign

pointing out that guests can help themselves more than once

reduces food waste by 20.5% (p<0.001). Descriptive statistics by

time period and treatment group are reported in Table 1, while

the regression results are shown in Table 2. All the estimated

regression coefficients are significant at 0.1% level or lower. The

percentage treatment effects are found by dividing the coefficient

by the mean pre-treatment level from Table 1. The hotel-specific

coefficients are not reported. Random effect estimations were also

run, giving essentially the same results, however Hausman tests

conclude that these estimators are inconsistent and we hence

report the fixed effect estimations. The R2values are 0.36 and 0.39

respectively.

The plate size treatment in the field experiment is supported

by the observational study, where we measure the strength

of association between plate size and food waste among the

untreated hotels. The results from the latter are reported in Table 3.

The R2value is 0.42. The percentage effect is approximated by

dividing the coefficient by the overall mean waste level in the

control group (33.82 kg). The results suggest that a 1 cm reduction

in plate size reduces food waste by 2.5 kg (p<0.01), which is

7.4% of the overall mean in the control group. This implies that

a 3 cm reduction reduces waste by approximately 22%, which is

Author's personal copy

S. Kallbekken, H. Sælen / Economics Letters 119 (2013) 325–327 327

Table 2

Estimated coefficients (and the associated standard errors) from the difference-in-

difference analysis.

Plate size Salient sign

Guests 0.033 0.038

0.004 0.005

Food sales 0.138 0.171

0.015 0.016

Time trend −4.317 −4.428

0.754 0.749

Treatment effect −7.179 −9.772

1.825 1.848

well within the 95% confidence interval for the treatment effect.

While lacking the within-subject design of the experiment, the

observational study benefits from a larger number of observations

than contained in the treatment groups.

4. Discussion

We have identified and quantified two no-regrets measures

that can substantially reduce the amount of food waste from

hotel restaurants. The findings, at least for the effect of reduced

plate size, are likely to be transferable to other contexts such as

food services at institutions (schools, hospitals, retirement homes,

prisons, workplace canteens, etc.) where buffet meals are served.

The results for the effect of plate size are the strongest, since the

experimental results are supported by an observational study.

The cost of the plate size measure is negative. All restaurants

regularly have to replace plates, and as smaller plates are cheaper

to purchase than larger one, the cost of the measure will be

negative as long as the rate of replacement remains the same.

The cost of the second measure is minimal (printing 10–30 small

posters per hotel). Reducing food waste represents a financial

saving to the hotel, estimated at around NOK 50/kg (USD 9/kg) by

one of the hotels. As 1 kg of food waste is responsible for lifecycle

emissions of around 1.9 kg of CO2e (European Commission, 2010),

the negative cost of each measure is perhaps as large as USD 4700

per ton of CO2.

One potential concern is that customer satisfaction could be

negatively affected, for instance because customers have to return

to the buffet more often to fill the smaller plates, or because

larger plates produce a more luxurious feeling. The hotels use

an online survey tool to record customer satisfaction with the

restaurants. Customer satisfaction with the buffet breakfast within

each treatment group was essentially constant from the pre-

treatment period to the treatment period. A simple difference-

in-difference with more than 45,000 observations shows no

significant change for the treatment hotels relative to the hotels

in the control group.

Our study leaves many important questions unaddressed, e.g.

the effect of implementing the two measures jointly or the optimal

plate size in terms of minimizing food waste, but it provides a

strong indication that using simple nudges to reduce food waste

might represent a very fruitful approach to achieving significant

greenhouse gas emission reductions. There is reason to believe

that the measures are also privately profitable as they reduce

food expenditure while having no effect on customer satisfaction

Table 3

Estimated coefficients, standard errors and p-values for the observational analysis.

Plate size

2.515

0.917

0.006

Guests

0.033

0.005

0.000

Food sales

0.172

0.016

0.000

Intercept

−35.188

22.045

0.110

and requiring minimal costs of implementation. As such, they

represent an example of a strategy that makes both environmental

and business sense, giving anecdotal support to the controversial

Porter-hypothesis (Porter and van der Linde, 1995).

Acknowledgments

We thank Cathrine Dehli at Nordic Choice Hotels for substantial

help with planning and implementing the experiment, as well

as the hotel employees who recorded data on food waste, and

helped us implement the treatments. We are indebted to Bård

Romstad for helpful support with data management. Thanks to

Hege Westskog, Kristin Linnerud, Torben Mideksa and Todd Cherry

for valuable comments. The research was funded by the not-for-

profit organization GreeNudge.

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