Effect of Simulation and Social Comparison Feedback in

Food Waste Reduction Applications

SUBMITTED IN PARTIAL FULLFILLMENT FOR THE DEGREE OF MASTER

OF SCIENCE

ANETA PENEVA

10672257

MASTER INFORMATION STUDIES

HUMAN-CENTERED MULTIMEDIA

FACULTY OF SCIENCE

UNIVERSITY OF AMSTERDAM

AUGUST 21, 2015

1st Supervisor 2nd Supervisor

Dr. Frank Nack Dr. Lynda Hardman

ISLA, UvA ISLA, UvA

Effect of Simulation and Social Comparison Feedback inFood Waste Reduction Applications

Aneta Peneva (10672257)

ABSTRACTIn developing countries, end consumers are the greatest con-tributors to the food waste problem. Based on the premisethat the practical reasons for this behaviour seem to be eas-ily avoidable, we assumed that if consumers have the inten-tion to change, they would do so. We designed and testedtwo interfaces, aiming at influencing their intentions. Bothprovided information about food waste’s environmental im-pact but enhanced in different ways. One used simulationto show accumulation of food waste’s impact over time. Theother used social comparison - displayed information aboutthe intentions for food waste reduction of others. We hy-pothesized that simulation and high social norms would in-crease intentions and that a low norm would lead to a de-crease. Our experiment showed only insignificant changes inall cases. However, the provided awareness information pro-voked our users to state high food waste reduction aims.Additionally, simulation was perceived better than socialcomparison feedback. When provided with a high socialnorm, users stated the highest food waste reduction aimsand low norm provided the lowest results.

General TermsBehaviour change

KeywordsApplication design, simulation, social comparison, social norms,food waste

1. INTRODUCTIONGlobally, it was estimated that around 1/3 of the food pro-duced for human consumption is lost or wasted each year,equal to about 1.3 billion tons [20]. At the same time, 925million people are chronically hungry [19].

Besides being a potential contributor to the world hungerproblem, food waste has serious impact on the environment.Food production and food waste disposal generate green-house gas emissions, mainly CO2, methane and nitrous ox-ide, which contribute to the global climate change (about20% of the global CO2 emissions [7]. Additionally, foodproduction involves enormous water consumption - it is es-timated that producing one calorie of food requires one literof water [21].

Food waste’s economic implications are worth noting as well- UK citizens annually throw away food worth 12 billioneuros every year, around 480 euros per household [5]; in the

US this ’luxury’ costs an average family of four between 1365and 2275 dollars [19].

Food is lost and wasted all along the Food Supply Chain– from agricultural production to consumption [26]. Con-sumers generate a surprisingly large amount of this waste,especially in developed countries. “For affluent economies,post-consumer food waste accounts for the greatest overalllosses” [26, p.3065]. The per capita food waste in Europeand North America amounts to 95 – 110 kg per year [20]. Inthe United States, consumers throw away about 25% of thefood they buy; for the UK the percentage is the same [26];for the Netherlands this is 8 – 11% [32].

According to [26], the greatest potential for food waste re-duction in developed countries lies within changing con-sumer behavior. Following this assumption, we investigatein this thesis ways to raise awareness of the problem offood waste to give people a start into changing their be-haviour [3, 15].

In this report, we first will discuss the reasons for foodwasting behaviour as identified in the literature, the cur-rent technological solutions addressing them, and will lookinto behaviour change theory. We then outline the problemstatement and define the research questions of the study.Afterwards, we explain the application prototypes designedand the experiment we conducted to evaluate them. Wewill also describe the collected data and the way it was pro-cessed. Finally, we discuss the results, the limitations of ourapproach, and opportunities for future work.

2. RELATED WORK

2.1 Practical causes for consumer food wasteLack of practical skills and basic knowledge related to foodmanagement have been associated with food wasting be-haviours. Lyndhurst [24] found out that people who re-ported poorer cooking skills waste larger amounts. Parfitt etal. [26] identify also the lack of knowledge about food stor-age, bad shopping habits (no shopping lists; impulse buy-ing); and failure to plan meal sizes among the reasons towaste food. Additionally, confusion around food labels (nodistinction between “Best before” and “Use by” dates) andfear of food poisoning push people to throw away edible food[17, 29]. Finally, inconvenience is also a factor - people buylarge amounts or cook more than they can consume with theinitial purpose of saving time [12].

2.2 Lack of knowledgeFor diverse reasons people do not prioritize food waste asa problem that needs to be addressed. Consumers appearto be unaware of the amount they waste - [24] discoveredthat 44% (N=1862) are not bothered by the issue as theyconsider they waste very little; [29] had similar findings(40%, N=2939). A reason for this attitude problem mightbe that it happens bit by bit [25].

Additionally, both studies reveal that many consumers (61%[29]; 39% [24]) are unaware of the environmental conse-quences related to food waste, as it seems natural and biodegrad-able. It is also notable, that even environmentally consciousrespondents were only slightly less likely to agree that foodhas no impact on the environment (34% as compared to 39%of all participants in [24]). Gunders [19] adds “devaluationof food” to the lack of awareness list, arguing that we do notcare if we throw away food, as in the last century our abilityto buy more is only growing.

Current research is inconclusive on which information sourcewould be more motivating – receiving information aboutcost of wasted food or about its environmental consequences.More of [29]’s respondents - 58.8% (N=2982) - agreed thatinformation about environmental consequences would helpthem compared to 51.1% (N=2982), who stated this for in-formation about the financial consequences. According toseveral other studies, environmental concerns are less mo-tivating than saving money (20% aginst 68% in [24]; 24%against 74% in [27]). However, these authors also acknowl-edge the fact that users were unaware of food waste’s nega-tive impact on the environment.

In our review we retrieved only one article [13] - a smallqualitative study (n=33), which gives an indication that, ifprovided with such information, consumers’ attitudes canshift positively. The participants received environmentalinformation during 3-hour long discussions. After the dis-cussions, all 33 participants agreed that they are concernedabout the environmental consequences of food waste, as op-posed to 16 before the focus groups.

2.3 Other food wasting issuesTucker [33] found out that the more widespread and visiblea pro-environmental action is, the more aware people be-come of their actions and more critical towards a diversionfrom these pro-environmental behaviours. Moreover, “Theassurance that others are also doing their bit can be an im-portant motivator” [33, p. 11]. Food waste prevention isless “visible” than other pro-environmental behaviours (re-cycling, second hand shopping) and this is an obstacle tousing social pressure to steer behaviour. Two qualitativestudies [17, 27] confirm that people do not engage in foodwaste minimization because they are convinced no one elseis doing it.

2.4 Current solutionsTucker [33] found out that the more widespread and visiblea pro-environmental action is, the more aware people be-come of their actions and more critical towards a diversionfrom these pro-environmental behaviours. Moreover, “Theassurance that others are also doing their bit can be an im-portant motivator” [33, p. 11]. Food waste prevention is

less “visible” than other pro-environmental behaviours (re-cycling, second hand shopping) and this is an obstacle tousing social pressure to steer behaviour. Two qualitativestudies [17, 27] confirm that people do not engage in foodwaste minimization because they are convinced no one elseis doing it.

2.5 Current solutionsGoogle’s Play Store displays a large number of applicationsunder the tag “food waste”. We categorize them accordingto their main features and provide one example per type:apps providing recipes for leftovers 1; apps helping to shopmore efficiently 2; apps for sharing shopping lists3, apps thathelp keep track of food stock and give alerts before the ex-piry dates 4; apps that facilitate sharing or donation of foodleftovers 5. These apps’ strategies for food waste reductionaddress mainly the practical reasons, outlined previously, byassisting users with different tasks related to food manage-ment. We found no formal evaluation of their effects but weassume that only persons who already consider food wastea problem would use them.

Another approach is raising awareness of the consequencesof food waste. We found a project focused on financial con-sequences, which is still under development by students atthe University of Guelph 6. The smart bin they designedis to be placed in a public canteen. It should weigh thefood thrown in and display its monetary value, based on theweight and the average price of recently purchased food inthe outlet. However, this system has not been evaluated yet.

Comber and Thieme [10] designed and tested a system forchanging food waste and recycling behaviour through socialengagement. BinCam is a bin, equipped with a smart-phonetaking a picture every time the lid is open. The item onthe image was then recognized (Amazon Turk crowd sourc-ing) and shared on a Facebook application. There, the par-ticipants could monitor group statistics about amount andtype of waste, browse the images and participate in differentactivities. The BinCam increased awareness of behaviourand of wastefulness. Although the participants did not con-sult the Facebook app for others’ behaviours, they did startdiscussing strategies about food storage and waste disposalamong themselves. The authors thus conclude that socialengagement is worth further exploration.

2.6 Changing behaviour by influencing inten-tions

Ajzen [3] argues in his Theory of Planned Behaviour thateach behaviour is preceded by a rational intention to per-

1https://play.google.com/store/apps/details?id=com.lovefoodhatewaste.lovefoodhatewaste2https://play.google.com/store/apps/details?id=com.gemoro.afgeprijsd&hl=en3https://play.google.com/store/apps/details?id=shopping.list.free.lista.compra.gratis.liston&hl=en4https://play.google.com/store/apps/details?id=th.co.crie.bestbefore&hl=bg5https://play.google.com/store/apps/details?id=com.greasedwatermelon.leftoverswap6http://news.uoguelph.ca/2015/06/smart-compost-bin-puts-a-dollar-value-on-food-waste/

form it. In short, if we want to change users’ food wastebehaviours we should first ensure that they have the inten-tion to minimize their waste. According to the Theory ofPlanned behaviour, intentions are determined by:

• Attitudes – beliefs about a certain behaviour’s out-comes;

• Subjective norms – beliefs about the social norms (ex-pectations of others), which form a perceived socialpressure;

• Perceived Behavioral Control (PBC) – beliefs aboutfactors that impede or facilitate the performance ofthe behaviour.

Favorable attitude towards the behaviour, perceived socialpressure and favorable PBC, would result in a person’s in-tention to perform the target behaviour [3].

2.7 Persuasive technologyFogg [15] defined the term “captology” - the area where per-suasion and technology overlap. Captology focuses on thedesign, research and analysis of interactive computer sys-tems created for the purpose of changing people’s attitudesand behaviours. Fogg describes different persuasion strate-gies that can be used depending on the role technology plays.Captology distinguishes among three:

• Tool – technology facilitates the performance of an ac-tion. Such is the approach taken by some of the appli-cations we found in Google’s Play Store – for example,apps like “Best Before” remind the user of a food’s ap-proaching expiry date, making it more likely to haveit used on time.

• Media (simulation) – technology provides an experi-ence, allowing users to experience cause – effect rela-tionships. The bin project by University of Guelph,described in chapter 2.4, should help users understandthat wasting food is the same as throwing away money.

• Social Actor – technology can use the same persuasivetechniques humans do. The BinCam system [10] de-scribed in chapter 2.4, allows users to compare theirwasting behaviour to the behaviour of other bin usersand thus motivates through competition.

3. PROBLEM STATEMENT ANDRESEARCH QUESTIONS

Although there are a number of practical issues contributingto consumers’ food wasting behaviour, none of them seemsto be insurmountable with some effort. At the same time,we assume that persons who do not acknowledge food wasteas a problem would not make any effort in the first place.Therefore, we consider it a necessary first step to persuadepeople of the gravity of the problem and their contributionto it. Our review of related work revealed some gaps thisstudy tries to address:

• Raising awareness about the environmental consequencesof food waste - Consumers are often not aware of the

environmental impact of food waste and informing themmight stimulate engagement in the issue.

• Raising awareness about users’ actual contribution tothe food waste problem - consumers are often not en-gaged with food waste reduction because they do notrealize the scale of their own contribution to the prob-lem

• Providing a social norm - food waste behavior is a hid-den process and therefore social norms cannot exercisemuch pressure. Related work leaves open questionsfor the potential of providing information about socialnorms related to food waste reduction.

Our goal is to test the power of raising awareness about en-vironmental impact of household food waste on intentions toreduce food waste as influenced by two factors determiningintentions – attitudes and subjective norm [3]. One of theassumptions that we make is that the practical obstacles toconsumers’ food waste reduction are rather easy to overcomewith simple efforts. Therefore, we will not aim to influenceusers’ PBC but their perception of the problem, with theassumption that once they realize it, they would feel theseefforts are worth it. Following Fogg’s framework about thepersuasive roles of computers, we will use simulation to en-hance the effect of awareness information on attitudes andtwo types of social feedback to affect users’ subjective norms.Therefore, we have three research questions:

RQ 1: Will enhancing awareness about food wastewith social feedback, influence people’s intentions toreduce food waste?

Social feedback could influence the effect of awareness aboutfood waste’s environmental impact on users’ intentions toreduce food waste. We expect two possible outcomes, whichwe will test with the following hypotheses:

H1: Providing users with a descriptive norm about others’intentions to reduce food waste would increase their own in-tentions to reduce food waste, where it is higher than theiroriginal intentions.

H2: Providing users with a descriptive norm about others’intentions to reduce food waste would decrease their own in-tentions to reduce food waste, where it is lower than theiroriginal intentions.

RQ2: Will enhancing awareness about food wastewith simulation increase people’s intentions to re-duce food waste?

H3: Simulation can enhance awareness information aboutthe consequences of food waste on the environment by in-creasing its effect on the intentions to reduce food waste.

We would also like to compare the strength of each enhance-ment. The third question of this study is:

RQ 3: Is there a significant difference between in-creasing environmental awareness for food waste withsocial feedback or simulation feedback? If yes, in whatways does their effect differ?

4. EXPERIMENTIn this section, we describe the prototypes, explain the ex-periment setup and procedure.

We designed two prototypes for applications aiming to influ-ence users’ intentions to reduce food waste. One targetingattitudes and the other subjective norms, as these are thetwo main factors forming intentions [3]. We then conductedan experiment in order to evaluate the effect of each of thetwo approaches. The experiment consisted of user testing ofthe prototypes and questionnaires. With the prototypes, wecollected quantitative data about the amount of food wastereduction our participants would be willing to commit to, be-cause of receiving feedback about food waste’s environmen-tal impacts. The questionnaires gathered qualitative dataabout the factors we aimed to influence – changes in atti-tudes and subjective norms. Although we did not attemptto influence PBC, we did include some questions about ex-ternal factors identified in the literature as influencing foodwaste behaviour.

4.1 Prototypes4.1.1 Simulation feedback

One of the reasons consumers do not engage in food waste re-duction is because they think they waste insignificant amounts[24, 29]. According to [25], this is because wasting food hap-pens bit by bit. We aimed at changing this non-engagedattitude with simulation feedback. We applied two of thefeatures of simulation that Fogg [15] describes.

Simulation can provide an experience of a cause-effect re-lationship. In our interfaces, users could see the environ-mental effect of wasting food, at a certain weekly rate ac-cumulated over a longer period. The first simulation wasfor his/her one-year impact. Afterwards, the user could in-put his/her age and see the impact for his/her remaining“lifetime” (based on the average lifetime expectancy in Bul-garia, 75 years [1]). This intended to let them experiencethe true scale of the consequences of their food waste, whichcould not be possible with feedback concerning only one-offwastage.

Our second goal with providing a “lifetime” feedback was toprovoke a feeling of moral standards guilt. Moral standardsguilt results from violating personal values [4] and it canbe used to encourage pro-environmental behaviours [4]. Weexpected that seeing one’s lifetime“prognosis”could provokesuch a feeling of guilt. Due to a desire to compensate forit, we expected users to increase their intentions to avoidwasting food.

Simulation can also help people “rehearse a behaviour” [15,location 855]. Such rehearsal has been found to increaseconfidence that one can accomplish a certain task or targetbehaviour. In our case, after seeing their lifetime impact,users could “Try again”. They could then select a differ-ent weekly amount (the time unit selected was one week,as shopping is usually done at least once weekly 1) and seean alternative lifetime impact. We expected that seeing this

1The weekly waste amounts were based on data for foodwasting of bread and bananas in the UK, due to lack ofsuch for Bulgaria.

(a) 1 year (b) ”Lifetime”

Figure 1: Simulation for water footprint if wasting 1banana per week

change of effect would have a significant impact on the en-vironment look feasible.

4.1.2 Social comparison feedbackThe social comparison theory holds that people naturallyseek to compare themselves to others’ behaviour and atti-tudes, and adjust when forming their own [15]. Our secondinterface design relied on this theory - the belief that provid-ing users with information about others’ food waste reduc-tion attitudes (social norms) can influence their intentionstowards food waste reduction.

Social norms for pro-environmental behaviours can provokefeelings of state guilt and can be used to encourage pro-environmental behaviours [4]. State guilt is felt from breach-ing social norms and harms one’s self-esteem, which can leadto reparative actions, i.e. a behaviour change [4]. For exam-ple, if the person finds out she/he were wasting more thanthe norm, she/he would probably feel state guilt and tryto waste less, in order to repair her/his self-esteem. Socialnorms can also act only as an external motivation [4]. Theperson complies with the norm only to avoid a feeling of so-cial embarrassment [31]. In this case, the behaviour changewould not be sustainable, i.e. as soon as the social pressuredisappears, the person might resume his previous behaviour[4]. This is in line with findings described in our literaturereview – people do not engage in food waste reduction be-cause of lack of social pressure, i.e. they assume others wasteas well [17, 33]. Therefore, our design considers two possibleeffects. If users receive a social norm higher than they cur-rently believe to be normal, their intentions to reduce foodwaste will increase. A norm lower than currently believed,would decrease their intentions to reduce food waste.

Low normsThe interface displayed feedback about environmental im-pact of a piece of wasted food (banana) and enhanced it with

(a) Low norm (b) High norm

Figure 2: Social comparison feedback for food wastereduction aims

several low benchmarks. These represented others’ reactionsto the same information. The benchmarks were three: themajority of others would not reduce their food waste in or-der to decrease their environmental impact, the rest aim fora low reduction (by 25-50%) and finally, they expect it is“likely” that they achieve their goal. Example is provided inFigure 2(a).

High normsThis app also gave feedback about environmental impactof one piece of wasted food (banana) but enhanced it withhigh benchmarks. The benchmarks were similar but withthe opposite direction: the majority of others would reducetheir food waste to improve their environmental impact, themajority of others aim for a high reduction (by 75-100%) andfinally, they expect it is “likely” that they achieve their goal.Figure 2(b) shows an example of the high norm interface.

In both cases the provided norms were moderate, (i.e. in-stead of “up to 25%”, the low norm was “25-50%”). Thiswas because moderate norms are more likely to provoke as-similation (the individual conforms) and extreme contrast(the individual wants to distinguish her/himself from thegroup) [11]. The criteria for choosing the social referents, isthat they should be similar by a key attribute to the users[11, 15]. We decided on “the other participants in the exper-iment”, as this was the only certain common denominatorfor all testing users.

4.2 SetupIn order to address the three research questions of the study,we used a mixed between and within-subjects experimentdesign. Our between-subject factor was presence of enhance-ment and the within-subject was type of enhancement. Our40 participants were randomly assigned to one of two groups:

• Control Group (20 participants) only received aware-

(a) Feedback for 1 banana (b) Choose a food waste reduc-tion aim

Figure 3: Non-enhanced feedback(control condition)

ness information about the consequences of food wasteon the environment.

• Treatment Group (20 participants) received the sameinformation but enhanced once with simulation andonce with social feedback.

To counterbalance for learning effects, for the TreatmentGroup we followed an AB/BA crossover design. The ControlGroup tested the same combinations and order of awarenessinformation. Appendices A and B provide tables displayingthe setup for both groups.

4.2.1 SettingThe experiment was conducted in Sofia, Bulgaria. We choseone of the parks as a setting because the procedure wasrather long (20 - 40 minutes depending on the test condition)and people there have some free time.

4.2.2 The “system”We pretended that the participants work with a fully func-tional system, where the prototypes were connected to asmart bin and an underlying reasoning engine which in factdid not exist. We took this approach as our interests layonly in the interfaces. The other components of the sys-tem were presented as a Wizard of Oz setup, solely for thepurpose of evaluation of the interfaces. What we providedwas a version of the smart bin, which was equipped witha camera and a device that supposedly communicated withthe interface. We also provided participants with a tablet(Lenovo A10-70 A7600) on which our prototype interfacewas available in a functional version. All participants re-ceived information about the environmental impact of foodwaste on the tablet, after throwing some food in the ”smart”bin. They were lead to believe that the tablet is connectedto the “smart” bin, which can recognize the type of food bymaking use of the camera, which sends the image to the

Figure 4: Setting.

application on the tablet, so that an appropriate feedbackcould be provided. The main role of the bin was to helpparticipants imagine that it is possible to receive feedbackrelated precisely to their personal waste.

4.2.3 The opportune momentAsking users to throw food into a bin aimed at creating anopportune feedback moment. Sending feedback right afterthrowing food should have the increased effect of the “kairo”principle, as described by [15], as directly after throwingaway food people (are expected to) feel uncomfortable be-cause they did something wrong.

4.2.4 The food thrown and awareness contentEach participant had to throw away four items of food - twobananas and two pieces of bread. We selected these foodtypes based on two criteria. First, it had to be food thatmost people waste. Due to lack of such data about Bulgaria,we based our choice on a study in the UK, according towhich bread and banana are the most wasted food types [28],and on statistics that bread and fruits are among the mostconsumed foods in Bulgaria [2].

The second criteria concerned the delivered information. Allparticipants received information about two aspects of theenvironmental impact of food waste – its carbon [7] andwater footprints [22]. As the size of both footprints variesamong products, we wanted to choose one product with alow and one with a high impact. In our case, banana haslower carbon and water footprints then bread. This allowedus to see to what extent value has an effect on intentions.

4.2.5 ProcedureBefore taking part, the participants completed a short ques-tionnaire collecting demographic information and assessingtheir current behaviour and attitudes towards food waste.The main goal of this questionnaire was to detect possiblehistory threats and to filter our target population - only per-sons who did admit to wasting food and were aged 18 - 65were included in the study. We took into consideration thatpeople above 65 almost do not waste food [24].

We had users test the two prototypes shown in Figure 1and Figure 2. A control group received the same awarenessinformation with no enhancement(Figure 3). To test theprototypes both groups had to perform four sets of tasks(dispose four pieces of food), following the same procedure:

I. State their current beliefs about the water/ carbon foot-print of banana/ bread on the environment.II. Throw a piece of bread/ a banana in a “smart” bin. Afterthis, they received awareness information about the specificfood item on the tablet. Depending on the condition, it waseither supported by social comparison or by simulation feed-back or non - enhanced.III.State whether, as a result of receiving the information,they would like to reduce their food waste for the throwntype of food or not.IV. In case they stated a positive intention, they were promptedto choose by what percentage.V. State how confident they feel about following their aim.

(Appendix E shows an information flow diagram for thethree conditions.)Once the participants did a cycle, they had to fill in a ques-tionnaire related to the tested feedback type. The question-naire assessed the three determinants of intention [3] - theirattitudes towards food waste reduction, subjective normsand perceived behavioural control. Once finished with theexperiment, they were thanked and received a small pack ofplums1.

5. RESULTS AND ANALYSIS

5.1 PopulationWe recruited 45 participants, out of which 40 were includedin the final sample. Our population was mostly young – 36were aged 18 – 45 and 4 were above 45. Both groups werepredominantly female – 11 in the Treatment group and 16in the Control group. Twenty had children (8 in the Controlgroup and 12 in the Treatment group). They were relativelyhighly educated (24 had a master’s degree or higher, 7 bach-elor degree and 8 high school) and all but 3 had an incomeabove the average for Bulgaria (only 2 received the minimumwage; 1 had no income).

Most of the participants we can consider low food wastersfor Bulgaria [9] - 21 admitted to waste 0,8 kg weekly or less,15 fall in the range of 0,8 – 1,6 kg and only 3 waste morethan 1,6 kg per week. All 40 participants agreed that theycould reduce their food waste if they made an effort.

Concerning their attitude towards global warming – 2 didnot answer, 25 disagree that the human factor is exagger-ated, 8 remained neural and 5 agreed (five participants whostrongly agreed, were not included in the final sample, withthe assumption that they could not be possibly influencedby the information about carbon footprint).

1This refers to a popular Bulgarian fairy tale called ”Plumsfor waste” which we also used as a title to announce theexperiment. In the story, the king offers plums in exchangefor household waste. The person who brought in the leastgarbage received a greater reward - to marry his daughter.

5.1.1 Lack of AwarenessOverall, our population was environmentally conscious – allparticipants stated that they try to consider the environ-mental consequences of their actions. However, more thanhalf (23) agreed or strongly agreed with “Food waste hasno negative impact on the environment because it is nat-ural and biodegradable” and only 13 disagreed or stronglydisagreed, 4 remained neutral.

Additionally, all participants were prompted to estimate thesizes of water and carbon footprints for banana and bread.Concerning the water footprint, estimations were close (ta-ble provided in the Appendix D), but informal conversationsshowed that no one was aware of the notion of “grey wa-ter” [22] and most considered water simply to be used forirrigation. They were asked to compare the food’s footprintto a car’s footprint - “Try to estimate the distance that acar needs to travel so that it cases the same damage as a ba-nana/ piece of bread”. Their guesses about carbon footprintsshow that they do not have any intuition of the problem (ta-bles are provided in the Appendix C). These results are inline with previous studies stating that people are unawareand often mistaken about the connection between climatechange and food waste [24, 29].

5.2 Quantitative dataWe compared the aims for food waste reduction of the par-ticipants in the two groups – control group receiving onlyawareness information and the treatment group, receivingthe same information but enhanced with social informationand simulation. We measured the size of intentions on thefollowing scale: reduction by 0-25%; 25 – 50%, 50-75%, 75-100%, 100%. For the analysis, each interval answer was as-signed to the upper value of the range. Persons who statedthey do not want to reduce their waste, were assumed tohave 0% reduction aims. This assumption should be takeninto account when considering the provided results.

Positive effect on intentionsAll three conditions – control, social feedback, simulationfeedback - provoked a desire to reduce food waste. All 40participants stated that based on the received information,they would like to reduce their food waste for at least oneof the tasks. Moreover, for all cases the average stated aimswere rather high - above 70% reduction (Figure 5).

The “No” food waste reduction casesThere were several cases, in which the participants statedthey would not like to reduce their food waste. Althoughthese were few, we found it important to look for a possibleexplanation to the lack of effect of the provided information.Two persons in the Control group stated that they would notlike to reduce their food waste on one or more tasks. Oneparticipant’s “No” answers were related to the two tasks re-lated to bananas. It is important to note also that this sameparticipant stated she/he almost never wastes bananas. Theother person stated “No” for three tasks – carbon footprintof bread, water and carbon footprints of banana. In theTreatment group, 3 stated “No” for one of the social feed-back tasks (throwing banana and receiving feedback for itscarbon footprint) and 1 for a simulation task (wasting a ba-nana and receiving feedback for its water footprint).

Figure 5: Food waste reduction aims for the different con-ditions.

From the above, it appears that feedback for banana wasless influential. This is in line with our expectations, asboth banana footprints are lower than footprints of bread.However, comparing all food waste reduction aims for tasksrelated to each food type revealed the difference is small –mean 85% +/- 27.2, as opposed to 83% +/- 32 for bananas.Wilcoxon Signed Rank Test confirmed it is insignificant (p= 0.5).

5.2.1 Testing hypothesesThe results from our quantitative data show that we haveno sufficient evidence that either social comparison feedbackor simulation feedback can affect consumers’ intentions toreduce food waste. For brevity, we report only the outcomesand leave here for reference Figure 5 showing the changes inintentions in the different conditions. The complete resultscan be found in Appendix F.

H1: Effect of Comparison with high social normsNevertheless, the aims set for high social norm feedback werehigher than the aims stated for the same information with-out enhancement, as can be seen in Figure5, H1. A MannWhitney U test was run and determined that this differenceis statistically insignificant (p = 0.7).

H2: Effect of comparison with low social normsOn the other hand, the data indicates that providing socialnorms could also have a negative effect, i.e. reduction aimswere lower for low social norm feedback responses, as op-posed to the corresponding control group aims (Figure5,H2). It should also be noted that under this condition thegreatest number of persons stated they would not like to re-duce their food waste (3/20). However, a Mann Whitney Utest determined that the decrease is statistically insignificant(p = 0.2).

H3: Effect of SimulationSimilarly, the results do show an increase in aims for foodwaste reduction when comparing simulation feedback to thecontrol condition (Figure5, H3). However, the Mann Whit-ney U Test we ran showed that the increase is statisticallyinsignificant again (p=0.6).

Figure 6: Attitude change across the three conditions.

Social comparison vs simulation feedbackWhen comparing the two enhancements, high social normsfeedback appears to have had stronger effect on reductionaims than simulation (Figure5). In this case again, theincrease is statistically insignificant - Wilcoxon Signed RankTest, p = 0.5.

Although none of our hypothesis was confirmed, we haveindications supporting each of them. We will next reviewthe questionnaire responses for possible strengths and weak-nesses of each prototype.

5.3 Qualitative dataWe collected qualitative information about factors identi-fied in the literature as influencing intentions to reduce foodwaste and about the way the prototypes were perceived. Be-low, we examine each factor separately and look for possibleconnections to the quantitative data. Unless stated other-wise, for all of the questions discussed, the scale was Likert, 5points, coded as 1= Strongly Agree, 2=Agree, 3 = Neutral,4 = Disagree and 5 = Strongly disagree.

5.3.1 Attitude changesAfter testing the prototypes, all participants answered threequestions about attitudes change in the three conditions.The scale was positive, i.e. agreement showed a positiveeffect.

The set inquired: to what extent the presented informationclarified the connection between food waste and its waterfootprint, food waste and its carbon footprint, and to whatextent the gravity of the environmental impact of food wastewas made clear. As can be seen in Figure6, the partici-pants largely agreed with all three statements. In order to

Figure 7: Perceived effect of simulation, strongerthan social comparison.

compare the effect of each type of feedback, we took themean of all responses to each question. The mean of thesemeans we assume to represent the attitude change effect.The means show slightly better results for the control condi-tion than for both simulation and social feedback(Figure6).The differences are very small thus we could only state thataccording to this measure, there is positive attitude changeregardless of the condition.

5.3.2 Simulation perceived as having a stronger ef-fect than social comparison

Participants from the Treatment group were also asked towhat extent the information specific to each of the enhance-ments (information about others’ reduction aims and infor-mation about their own food waste’ environmental impactover time) helped them decide about the waste reductionaims they set. The responses for this question show an ad-vantage for simulation over social comparison as can be seenon Figure7 – 19/20 participants agreed that simulation in-formation was helpful and 1/20 remained neutral; as op-posed to 9/20 agreeing and 5/20 disagreeing; 6/20 neutral.The difference is significant as a Sign test showed (p = 0.02).

5.3.3 SimulationFood waste environmental impacts over timeThe main feature of the simulation feedback was present-ing our participants their food waste environmental impactas accumulating over time. The assumption was this wouldhelp them to understand the scale of their contribution tothe problem. The participants were led through three steps:first receiving information about the food they throw away,afterwards they could opt to see information about its im-pact (if wasted) for one year, and, last, information aboutimpact for their remaining ”lifetime”. We wanted to knowwhich one had the strongest effect. According to 12/20participants information for one year had a stronger effecton them than information for one item and the “lifetime”simulation was more effective than the 1 year simulation(Figure8). This positive response might be the explana-tion to the perceived stronger effect of simulation over socialfeedback on their intentions.

Experimenting with different amountsUsers also had the option to try the change of impact byselecting different weekly amounts of waste. We were ex-pecting this would help them make a better informed de-cision and feel more confident about following it through.However, only 3/20 participants actually tried this option.

Figure 8: State and moral standards guilt.

5.3.4 Social comparisonPerceived effects of low social normOne of our hypotheses was that providing a low social normmight decrease intentions for food waste reduction by lower-ing the perceived social pressure. However, to the statement“I would feel I have accomplished my duty in case I follow afood waste reduction goal at least as high as the goal of oth-ers” only three participants agreed, 16/20 disagreed and oneremained neutral. This strong negation is contradictory toour quantitative results, which showed lower aims (althoughinsignificantly) connected to low social norm(Figure8).

Moral standards and state guilt As food wasting is usuallyassociated with feelings of guilt [24, 29], we wanted to seewhether simulation or social treatments could enhance thisfeeling with the aim of stimulating food waste reductionintentions. In the pre-test, almost all 34/40 participantsagreed that they feel guilty when wasting food and 5/40admitted they do not; 1/40 remained neutral.

However, neither simulation, nor social feedback elicited astrong feeling of guilt. For simulation, only 3/20 participantsin the Treatment group, agreed and 14/20 disagreed that iftheir lifetime impact was large, they felt guilty(Figure8).For social comparison, 7/20 agreed and 9/20 disagreed thatthey felt guilty to aim for a lower food waste reductionamount than the others(Figure8). Previous studies sug-gesting that guilt is associated with food waste were con-firmed [24, 29]. Nevertheless, influencing moral standardsguilt (felt from breaking internal values) was not successfulwith the simulation feedback we provided. Social feedback,which we expected to affect state guilt (felt when breakingsocial norms), elicited stronger results.

5.3.5 Perceived Behavioral Control (PBC)Following [3], we asked all our participants about their PBC,i.e. to what extent they think reducing food waste is a fea-sible task.

ConfidenceFor each task, participants had to state how likely it is thatthey achieve their food waste reduction aims. In all cases,they showed a high confidence, with a small advantage forsocial comparison condition (Figure9).However, the differ-ences are insignificant(Wilcoxon Signed Rank Test, p=0.966;Mann Whitney U, p = 0.705). Considering the experimentdesign, we interpret these results only as an encouraging in-dication that none of the participants saw serious obstaclesto achieve their aims. In order to assess the validity of thestated confidence, users’ future behaviour would need to be

Figure 9: Confidence responses for all 4 tasks acrossthe three conditions.

observed.

External factorsParticipants were also asked to what extent they feel theyare responsible for their food waste and its consequences onthe environment. The Lyndhurst [24] survey showed thatone reason people do not engage in food waste reduction isthat it is not a priority. So, our first question was “I will notbe able to engage in food waste reduction, as I have othermore important worries”. Lindenberg and Steg [23] pointout that people can shift their own responsibility towardsa pro-environmental behaviour to larger actors. Therefore,our second question was “The contribution of industries toglobal warming would make my own efforts for food wastereduction meaningless”. To both statements, all participantsdisagreed and only one admitted that food waste is not apriority of hers. Although this is good news, we did notask questions related to practical obstacles for food wastereduction as our prototypes were not addressing these. It ispossible that such factors play a significant role in reality.

5.3.6 PreferencesAll participants but one in the control condition agreed thatthey would like to use such an application if available. Inthe treatment group, there was one person who would notlike to use simulation. It should be noted, that this sameparticipant did not actually see the simulation informationbut opted to skip it.

How long will the effect lastAccording to our participants, the provided awareness infor-mation will have a lasting effect. About half of the responsesfor all three conditions were that it will influence their at-titude towards bananas and bread “For my whole life” (8of 17 for simulation (Treatment group); 9 out of 18 for so-cial comparison(Treatment group) and 9 out of 19 for thecontrol condition). For social feedback, the range for the re-maining half was from “1 week” to “More than 1 month”, forsimulation was “1 month” and “More than 1 month”. Whenparticipants in the treatment group were asked to rate thesimulation and social feedback on the expected longevity oftheir effect (on a scale from 1 to 5, with 5 = longest effect),simulation also shows a small and statistically insignificant(Wilcoxon Signed Rank Test, p=0.151) advantage. For sim-ulation the mean = 4.1053 (std. dev = 1.04853 min = 2,max = 5); for social feedback mean = 3.6316 (std. dev =1.6479, min = 2, max = 5). This is however, merely a one-time indication that could only serve as a possible directionfor future work.

More or lessFor all three conditions, participants mostly agreed that themore often they receive such feedback, the more likely itis that they will attempt to reduce their food waste (20agreed in the control group; 16 agreed or strongly agreedand 1 disagreed in the simulation condition; and 16 agreedor strongly agreed and 3 disagreed in the social feedback con-dition). Nevertheless, a following question revealed that thepreferred frequency of such messages varied greatly amongindividuals and not among conditions. The most frequentanswer in the control group was “Once per week” (6 per-sons). Whereas, for both simulation and social feedback, 5stated they would like to receive such messages “Every timethey waste food”; 5 opted for “Once per type of food” and 5stated they would like to receive it “Once monthly”. As canbe seen, the answers are quite heterogeneous. This mightindicate that such information is not always welcome andshould not be forced upon users, but rather be adjusted totheir personal preferences.

6. DISCUSSIONWe derive the main findings of this research and take itslimitations into account. The most important is that weonly measured stated intentions for food waste reduction,with the assumption that more serious intentions lead tolarger behaviour change [34]. In order to claim validity,we would need to trace whether the participants actuallystarted wasting less food.

6.1 Raising awarenessOur results show that information about the environmentalimpact of food waste did influence participants’ intentionsto reduce food waste but this was independent of the con-ditions. For all three conditions aiming to motivate users,the stated reduction aims were high – 80%. Moreover, allbut one participant felt confident of being able to achievethem. Considering that our population was largely unawareof both water and carbon footprints of food waste, it seemsnatural that providing pure information caused a strong re-action. Moreover, they agreed that the information madethe connection between food waste and its environmentalimpact clear. Our findings support [13]’s that environmen-tal concerns can be a motivation for food waste reduction.It is worth following to what extent such information leadsto actual change of behaviour after a possible novelty effect[8] has passed. We should also note that a social desirabilityeffect [16] cannot be excluded, especially since all partici-pants admitted to generally feeling guilty for throwing awayfood.

6.2 SimulationThe simulation condition induced higher food waste reduc-tion aims than the control condition. Although the differ-ence is insignificant, the questionnaire responses point outthat one feature of the simulation might have contributedto this effect. Participants stated that seeing long-term im-pacts helped them decide on their reduction aims and influ-enced them more than the impact of only one wasted item.Lifetime was perceived as more influential than one year.Therefore, we assume that helping users realize the scale oftheir environmental impact does have a potential to moti-vate food waste reduction behaviour.

Besides seeing their future environmental impact, users couldalso see what they can do about it - to what extent theycould affect it, if they change the amount they waste. Thisfeature was disappointingly neglected - only three people ac-tually tried it. This suggests that providing users with tai-lored information is a better strategy than expecting themto make an effort to look for it. It is also possible that par-ticipants did not make a conscious choice but simply did notnotice the “Try again” button. This we infer because someof them asked about the meaning of question referring tothis function.

6.3 Social comparisonHigh social norm provoked the highest reduction goals com-pared with the two other conditions. On the other hand,when provided with a low norm, participants set the lowestgoals. Although the differences were insignificant in bothcases, we believe that they give an important indication -the social norms we provided only acted as an external mo-tivation. When the social pressure was lowered, the inten-tions also reduced. Therefore, even the encouraging resultsof high norm feedback should be considered with care, astheir effect might be only temporary [30].

Feelings of social guilt provoked by others potentially hav-ing higher food waste was the main feature we expected tomotivate food waste reduction. Fewer than half of the par-ticipants admitted to feeling such guilt. The questionnaireresponses did not confirm the low norm results either. Al-most all participants disagreed that they would feel theyhad done “their bit” as long as they do not aim lower thanthe rest. Although these responses are contradictory to thequantitative results, they are not unexplainable. It is possi-ble that participants were more influenced by social normsthan they would admit, since “participants deny conformityas an explanation for their behaviour” [14, p. 246].

6.4 Simulation or social comparison?When comparing the two enhancements, there appears tobe a contradiction between our qualitative and quantitativeresults. If we look at the reduction aims, participants seemmore influenced by the social comparison feedback but theyself-reported to be affected stronger by simulation. Thisdifference in perception could be attributed to two charac-teristics of the study. First, the newly received factual infor-mation was apparently impressive. As simulation is directlyresultant from it, it is possible that a novelty effect enhancedthe way it was perceived. Measuring the perceptions aftersome time of using the prototypes, might reveal a diminishedeffect of the simulation. Second, as mentioned in section 6.3,it is possible that participants were more influenced by so-cial norms than they self-reported. It is worth noting thatsimulation could be the more sustainable approach towardsbehaviour change - our participants perceived it as poten-tially having a longer lasting effect than social comparison.These answers are not a surprise - they are in line with otherresearch suggesting that internal motivation could lead to amore stable change of behaviour than external motivation[4]. In our case, simulation aimed to affect our participants’moral standards, so it can be considered internal motiva-tion [4]. The provided social norms we categorize as an ex-ternal motivation. Although it is possible that they become

internalized [18], we believe this was not the case with ourexperiment.

6.5 Guilt and food waste reductionOur attempt to invoke moral standards and social guiltseems to be unsuccessful, despite the fact that all partici-pants did agree to feeling guilty about wasting food. Onepossible explanation could be that they did not actually feelresponsible for wasting the food while testing the prototypesas they followed a scenario. Guilt usually increases when theperson feels in control of the impact of her/his actions be-cause this implies responsibility for these actions [6].

7. CONCLUSION AND FUTURE WORKWe designed and tested two prototypes of interfaces aim-ing to influence users’ intentions to reduce their food waste.Both presented users with information about food waste’simpact on the environment, one with simulation and theother with social comparison feedback. The purpose of ourexperiment was to assess whether either of these two ap-proaches holds a potential for behaviour change.

We have no sufficient quantitative evidence that enhancingenvironmental awareness information with either social orsimulation feedback can have an effect on intentions to re-duce food waste. Participants did aim for a greater reduc-tion percentage with simulation and positive social feedbackwhen compared to the control condition. Despite this, theireffect seems to have been less salient than the effect of raisingawareness, as in all cases the aims for food waste reductionusers set were relatively high in all three conditions. Sup-porting previous research, participants were unaware aboutthe environmental impact of their food waste. Once theyrealized it, they declared a strong desire to avoid it.

Among the two prototypes, users preferred simulation oversocial comparison. Information about food waste’s impactaccumulated over time was perceived as significantly moreuseful when deciding on one’s aims for food waste reduction,than information about others’ food waste reduction inten-tions. Furthermore, simulation for a “lifetime” was reportedto be more influential than for one year. The participantsdid not admit to conforming to social norms, however wehave indications that they do affect them - social pressurestimulated the higher food waste reduction goals in our ex-periment but also the lowest when the norm was low. Thisin line with literature suggesting external motivations do notprovide a stable behaviour change [30].

In conclusion, although we have to reject our hypothesesthat simulation and social comparison can influence foodwaste reduction, we find both worthy of future work. Simu-lation mainly because it was well accepted. Social compar-ison should be considered with care in view of its possiblenegative effects.

7.1 Future workFor future research we recommend the following:

• Inclusion of a phase in which the following behaviouris measured, not only stated intentions.

• The provided feedback might elicit different results if itwere related to actual food wasting by the participants,instead of them following a scenario.

• Additionally, if the prototypes were tested over time,the experienced effects might be different as the nov-elty effect of the awareness information would dimin-ish.

• Giving feedback on user’s behaviour change in realityand its lifetime impact might be more motivating thanour one-off study.

• Future studies should consider using known peers associal referents. According to [11], the effect of socialcomparison feedback might be greater in both negativeand positive directions.

8. ACKNOWLEDGEMENTSI would like to thank my supervisor Frank Nack for the sup-port, detailed feedback and understanding to my situation.I am also very grateful to Lynda Hardman for agreeing tobecome second reader on such a short notice. Special thanksgo to Svetlin Stoev as well, for helping with the prototypesand to Florian Amersdorffer for crafting the “smart” bin.Thank you to all participants.

References[1] National statistical institute - lifetime expectancy for

bulgaria, 2013.

[2] Report of the bulgarian national statistics insti-tute for household incomes, expenses and consump-tion. http://www.nsi.bg/sites/default/files/

files/pressreleases/HBS2014_GO8KJYP.pdf, 2014.

[3] I. Ajzen. The theory of planned behavior. Orga-nizational Behavior and Human Decision Processes,50(2):179 – 211, 1991.

[4] T. Bedford, P. Collingwood, A. Darnton, D. Evans,B. Getersleben, W. Abrahamse, and T. Jackson. Guilt:an effective motivator for pro-environmental behaviourchange? Working paper, University of Surrey, 2011.

[5] A. Bektes. Research and product design to minimizefood waste in Western domestic kitchens. PhD thesis,TU Delft, Delft University of Technology, 2010.

[6] M. Berndsen and A. S. Manstead. On the relationshipbetween responsibility and guilt: antecedent appraisalor elaborated appraisal? European Journal of SocialPsychology, 37(4):774–792, 2007.

[7] M. Berners-Lee. How bad are bananas. The carbonfootprint of everything. London: Green Profile, 2010.

[8] G. H. Bracht and G. V. Glass. The external validityof experiments. American educational research journal,pages 437–474, 1968.

[9] K.-R. Brautigam, J. Jorissen, and C. Priefer. The ex-tent of food waste generation across eu-27: Differentcalculation methods and the reliability of their results.Waste Management & Research, 32(8):683–694, 2014.

[10] R. Comber, A. Thieme, A. Rafiev, N. Taylor,N. Kramer, and P. Olivier. Bincam: designingfor engagement with facebook for behavior change.In Human-Computer Interaction–INTERACT 2013,pages 99–115. Springer, 2013.

[11] K. Corcoran, J. Crusius, and T. Mussweiler. Social com-parison: Motives, standards, and mechanisms. Theoriesin social psychology, pages 119–139, 2011.

[12] J. Cox, S. Giorgi, V. Sharp, K. Strange, D. C. Wil-son, and N. Blakey. Household waste prevention—areview of evidence. Waste Management & Research,28(3):193–219, 2010.

[13] N. Doron. Waste not, want not: How fairness concernscan shift attitudes to food waste, 2012.

[14] M. Eysenck. Psychology for AS Level. PsychologyPress, 2005.

[15] B. Fogg. Persuasive technology: Using computers tochange what we think and do (interactive technologies).2002.

[16] A. Furnham. Response bias, social desirability anddissimulation. Personality and individual differences,7(3):385–400, 1986.

[17] E. Graham-Rowe, D. C. Jessop, and P. Sparks. Iden-tifying motivations and barriers to minimising house-hold food waste. Resources, Conservation and Recy-cling, 84:15–23, 2014.

[18] V. Griskevicius, R. B. Cialdini, and N. J. Goldstein.Social norms: An underestimated and underemployedlever for managing climate change. International Jour-nal of Sustainability Communication, 3(1):5–13, 2008.

[19] D. Gunders. Wasted: How america is losing up to 40percent of its food from farm to fork to landfill. NaturalResources Defense Council Issue Paper. August. Thisreport was made possible through the generous supportof The California Endowment, 2012.

[20] J. Gustavsson, C. Cederberg, U. Sonesson, R. Van Ot-terdijk, and A. Meybeck. Global food losses and foodwaste. Food and Agriculture Organization of the UnitedNations, Rom, 2011.

[21] M. Halstead, T. Kober, and B. van der Zwaan. Under-standing the energy water nexus, 2014.

[22] A. Y. Hoekstra. The water footprint of food. 2008.

[23] S. Lindenberg and L. Steg. Normative, gain and hedonicgoal frames guiding environmental behavior. Journal ofSocial Issues, 63(1):117–137, 2007.

[24] B. Lyndhurst. Food behaviour consumer re-search—findings from the quantitative survey. BriefingPaper. UK: WRAP, 2007.

[25] L. McKnight-Yeates. Out of sight, out of mind: whatinfluences our perception of waste and activates our in-tention to live more sustainably? PhD thesis, RoyalRoads University, 2009.

[26] J. Parfitt, M. Barthel, and S. Macnaughton. Food wastewithin food supply chains: quantification and potentialfor change to 2050. Philosophical Transactions of theRoyal Society B: Biological Sciences, 365(1554):3065–3081, 2010.

[27] T. Quested, E. Marsh, D. Stunell, and A. Parry.Spaghetti soup: The complex world of food wastebehaviours. Resources, Conservation and Recycling,79:43–51, 2013.

[28] T. Quested and L. Murphy. Household food and drinkwaste: A product focus, a report for warp, 2014.

[29] E. M. Research. Wrap. we don’t waste food! a house-holder survey, 2007.

[30] R. M. Ryan and E. L. Deci. Intrinsic and extrinsic mo-tivations: Classic definitions and new directions. Con-temporary educational psychology, 25(1):54–67, 2000.

[31] T. J. Scheff. Shame and the social bond: A sociologicaltheory. Sociological Theory, 18(1):84–99, 2000.

[32] R. Thonissen. Food waste: The netherlands. In Presen-tation to the EU Presidency Climate Smart Food Conf,2009.

[33] P. Tucker and P. Douglas. Understanding householdwaste prevention behaviour. Final report. WR0112,2007.

[34] T. L. Webb and P. Sheeran. Does changing behavioralintentions engender behavior change? a meta-analysisof the experimental evidence. Psychological bulletin,132(2):249, 2006.

Appendix A. Experiment setup for the Treatment group

A = Social comparison, B = Simulation;

H = high, L= low;

ln = low social norm, hn = high social norm

Participant Level Content Food 1 Level Content Food 2 Level Content Food 3 Level Content Food 4

1-5

A

H / hn

C02 bread L / ln

H20 banana B H H20 bread L C02 banana

6 -10

A L / ln

C02 banana H /hn

H20 bread B L H20 banana H C02 bread

11-15 B H H20 bread L C02 banana A

H /hn

C02 bread L / ln

H20 banana

16 -20

B L H20 banana H C02 bread A L / ln

C02 banana H /hn

H20 bread

Appendix B. Experiment setup for the Control group

C = Control condition

H = high, L= low;

Participant Level Content Food1 Level Content

Food 2

Level Content Food 3 Level Content Food

1 - 5

C H C02 bread L H20 banana

H H20 bread L C02 banana

6 - 10

C L C02 banana H H20 bread L H20 banana H C02 bread

11 - 11 C H H20 bread L C02 banana

H C02 bread L H20 banana

16 - 20

C L H20 banana H C02 bread L C02 banana H H20 bread

Appendix C. Estimations for carbon footprint if compared to a car’s footprint driven for a certain

distance (meters)

Bananas Bread

mean 72146 283170

SD 230182 1580121

true value 114 170

Appendix D. Estimations for water footprint (liters)

Bananas Bread

mean 56 58

SD 52 173

true value 86 130

Appendix E. Information flow for simulation, social comparison and control condition.

Appendix F.