The status quo bias when casting a ballot.

The status quo bias when casting a ballot.

Jane and Robert enjoyed living in a country with a direct democracy system. They valued their right to directly vote on important issues that effect everyone. Whenever there was a public ballot they’d always attend to ensure their voices were heard by casting their ballots. They cast their ballots on issues such as drug policy, health care, finance and domestic policy.

Public ballots are important because they allow the public to directly influence, and have their say on, the direction of important government policies at the national and local level. Some ballots even include multiple propositions. Countries like Switzerland, Italy and the United States have regular public ballots. In the Italy there were 15 ballots between 1971 and 2004, in the United States there were 159 state-wide ballots in 2015 (across 42 states), and between 1960 and 2004 there were 125 ballots in Switzerland. At the local level there have been over 700 ballots in California and Oregon between 1970 and 1998.

image 1

Given that some of the ballots ask the public to decide on multiple issues (propositions) behavioural scientists have begun to investigate the impact that cognitive biases may have on voting behaviour. Since ballots can be concerned with a wide range of topics and the outcomes of ballots are often close even the smallest impact of cognitive biases can have a big effect. The status quo bias refers to one such bias, which is the tendency to prefer one option over another because the option is the status quo (Samuelson & Zeckhauser, 1988; Kahneman et al., 1991). Barber and colleagues (2017) investigated the impact of the status quo bias in a study by manipulating the wording of experimental ballots. They gave participants ballots on the topics of gambling, mental illness and same-sex marriage with neutral or biased (against or in favour) wording. The results indicated that the wording of the ballots had an impact on voters, furthermore the status quo bias influenced participants who were not well informed about the proposition (e.g., mental illness).

table 1
One study that investigated the length of public ballots reported that multiple propositions on a ballot can interfere with the ability to translate political preferences into consistent policy choices (Selb et al., 2008). This is important because although some countries run regular ballots simply changing the order and number of propositions can influence the outcome. At the national and local levels alike, the length of these ballots vary greatly (see Table 1). In the Californian and Oregon ballots there was a status quo effect on almost 700 ballots between 1970 and 1998 (Bowler & Donovan, 1998). For every additional proposition that was added to these local ballots the share of ‘No’ votes increased on average by 0.4 percent.

image 2.png

The status quo bias is not the only cognitive bias to influence voting behaviour on public ballots. The endowment effect and loss aversion can also explain some of the resistance to change through ballots (Heinemann, 2001). So, like Jane and Robert if you live in a country or state that has a direct democracy system and you enjoy taking part in public ballots one way in which you can avoid the effect of cognitive biases is to read and think carefully about the proposition at hand.


Heuristics in the age of the smartphone: how do heuristics help us decide which app to buy from the app markets?

Heuristics in the age of the smartphone: how do heuristics help us decide which app to buy from the app markets?

Louis had just been given a new smartphone for Christmas, he’d wanted a new smartphone for some months now. He charged the phone, setup his contacts and began to browse through the app stores. He searched for useful apps and entertainment apps. Whilst browsing the app store he noted that among the hundreds of apps a small selection of the apps were prioritised by positioning the apps at the top of the app list. Louis wondered some of the apps were displayed in a better position than others. He didn’t give it a second thought and continued to load apps onto his new smartphone.

Smartphone apps are small computer programmes that have become a useful and sometimes important part of life. These small apps have helped to change mobile phones from a basic communication device to a small personal computer that can complete a myriad of functions (e.g., listening to podcasts, searching the internet, playing games). The apps that enable the large variety of functions are primarily available through proprietary online shops such as Google’s Play Store, Apple’s App Store, and Amazon’s App store, these apps can be created by skilled computer programmers. Since the advent of smartphones (mobile phones with the ability to use apps) over a billion smartphone have been sold and 50 billion apps have been downloaded worldwide (ABI Research, 2013).

image 1.png

The popularity of smartphone apps have lead researchers to investigate how and why we choose to download one app whilst ignoring the vast amount of other apps that available. For example, when searching for a messaging app one must pick one app with the desired attributes from among a vast collection of apps that are all very similar. Some of the aids when choosing an app include graphic rating systems (Gage Kelley et al., 2013) and customer reviews (Poster Felt et al., 2012). Decision-making researchers have found that users (consumers) spend more time reading customers reviews than the privacy permissions, despite the importance of clearly understanding what you ought to allow the app to access on your smartphone (Should you rely allow a game to access your phone call log or photos?) (Porter Felt et al., 2012). Other researchers have revealed that graphic rating systems are considered to be a more reliable source of information and quality of an app than full-text customer reviews (Gage Kelley et al., 2013). Many user prefer to simply look at the number of stars that an app has been given by other users rather than reading customer reviews.

image 2.png

One exploratory study by researchers at universities in Germany and the United States sought to investigate what decision strategies are used when deciding which app to download from an app store (Dogruel et al. 2015). They recruited 49 smartphone users with experience of the Google Play Store and asked them to browse through a total of 189 apps, after which they chose three apps to download from different categories. The researchers used screen capture software to monitor and record the activities of the participants so that they could observe which decisions were made. The researchers found that half of the selected apps (n=93) were chosen from the default list at the top of the screen, here the participants did not scroll down to look any other apps. In just 1 in 4 cases (approx. 48) apps were selected after viewing at least 10 other apps. The Take-the-first (TtF) heuristic which states that a user simply chooses the first option that they encounter explains about half of the decisions that were made.

So, like Louis if you have recently received a smartphone as a gift or had bought one and are now filling the smartphone with useful and entertaining apps, remember that many of the most popular apps (in the default list) may have simply been chosen by other users because of the Take-the-first heuristic. We like to think that we decide which app to download carefully however heuristics like Take-the-first can explain some of our decisions. As apps become more popular with the advancement of technology the heuristics-and-biases literature can inform us about how we make these decisions, decisions that app store creators can use to their benefit to make greater profit.

The Take-the-best heuristic in election forecasts

The Take-the-best heuristic in election forecasts

Denise and Thomas were sat having their lunch in the staff room. As always, their discussion turned to politics, they talked about how much the politics of United States and Europe have changed in the last year. Like many people Denise and Thomas did not expect the dramatic change in leadership. Denise remarked that there was not way that anyone could have predicted the political shift.

The forecasting of political votes (i.e., elections etc) is important as many businesses and governments make long-term plans, an incorrect prediction can cost a lot of money. Forecasts often predict shifts in political leadership that represent the political views of the majority of voters. The forecaster’s models for predicting the outcome of elections must therefore take a lot of factors into account that include public opinion polls, the candidate’s issues and the candidate’s popularity. Many of the forecasting models are complex but what if there was a quick and easy way to predict the outcome of an election?

image 1.png

The take-the-best heuristic is one of the decision-making short-cuts (heuristics) that can be taken from the cognitive psychology literature and adapted to political forecasting. The take-the-best heuristic enables users of the heuristic to choose between two competing alternatives with ease by comparing the values, or attributes, that they both share (Gigerenzer, 1999). When making a simple decision about which of two products to buy you can compare the products on attributes that are important, for example … how much memory does a laptop have? how many USB ports does it have? The take-the-best heuristic states that the laptop with the best (or largest) amount of memory and number of laptops will be chosen.

The recent U.S. Presidential Election in 2016 saw Donald Trump beat Hilary Clinton to become the President to the surprise of many observers. The forecasting models predicted a close election but ultimately a win for Hilary Clinton. Clinton won the popular vote but not the electoral college vote. In the popular vote Clinton had almost 3 million more votes than Trump with 51.1% to Trump’s 48.9%. Importantly in the U.S. it is the electoral college votes (of which Trump had more) which decide the presidential election, not the popular vote. Historically, there’s very little variance between the popular vote and electoral vote (Graefe et al., 2017)

image 2.png

Before the election of Trump to the Presidential office in 2016 researchers at the Karlsrube Institute of Technology in Germany and the University of Pennsylvania (in the U.S.) began to investigate the accuracy of political forecasting models (Graefe et al., 2012; 2013; 2014). The researchers compared the performance of forecasting models to simple heuristics such as the take-the-best heuristic. They developed a simple model that uses a variation of the take-the-best heuristic called the Big Issue voting model (BI-H model). The BI-H model identifies the issue that is most important for voters (e.g., higher wages, health care insurance) and predicts the candidate that is most likely to win based on the public support for this issue. When tested against other forecasting models the BI-H outperformed the more complex models.

Since the average person has little interest in politics, models that use simple heuristics like the take-the-best heuristic can be used to accurately predict the outcome of elections. There is one caveat though that two-step electoral systems (i.e., popular vote & electoral college votes) can make predicting the outcome of elections even harder. Nonetheless, when data from the popular vote is feed into the BI-H model the heuristics can easily outperform complex models. It clear that a great deal more work needs to be done in political forecasting but heuristics-and-biases can help in the development of forecasting models.

Nudging down theft of bicycles and from parked vehicles

Nudging down theft of bicycles and from parked vehicles

Hugh and Liz had just bought a new house. They had wanted to upgrade to a larger house for many years and now decided on an area to move to. Before moving home, they looked at the crime rates, schools for their children, local amenities for shopping, and things to do. The house seemed perfect so there was no hesitation in arranging the move. In the weeks following moving in to their new home they received all the usual junk mail, most of which went straight into the bin. One of the leaflets that they received through their letterbox was a leaflet saying to remember to check that they have locked their car, Hugh and Liz thought that was a nice a reminder and continued with their day.

Nudges are small, cheap and subtle modifications of choice architecture (i.e., changing a default option to the most favourable outcome) that can be used to help an individual make a better decision. Thaler and Sunstein published the idea of using nudging in the highly influential book ‘Nudge’ in 2008. Recently Richard Thaler has gone on to win the Nobel Memorial Prize in Economic Sciences for his work on nudging.

image 1

Nudging has been used to aid decision-making in many ways. In crime prevention nudging has helped to reduce thefts from parked vehicles (Roach et al., 2016). A pilot study in County Durham in the North of England between September 2015 and October 2015 investigated how nudging can be implemented to reduce thefts from cars. Firstly, Roach and colleagues examined the reasons for cars being left insecure finding that there are three reasons: i) forgetting to securely lock a car whilst going into a shop, ii) forgetting to lock a car on one’s driveway, and iii) forgetting to lock a car outside or adjacent to one’s property. They choose four target areas (2 x experimental and 2 x control) and tailored their nudging technique to the local demographic. One of the basic principles of nudging is that nudging is more effective when the message is tailored (i.e., worded or presented) to the recipient. Leaflets were distributed with simple messages saying to “Take care of your vehicle” and “More than 1/3 of thefts in your area involve unlocked cars. Why? Because it’s ….. EASY.” The results of this found a significant reduction in thefts from cars because reminding car owners to lock their cars reduced the number of opportunities for thieves. In the two experimental areas there were reductions of 33% and 25% in crime compared to the crime statistics of the last 3 years.

image 2

Another type of theft that nudging has aided in reducing is bicycle theft (Johnson et al., 2008; Nettle et al. 2012). In countries and cities where cycling is a popular past-time and way of commuting bicycle theft can be a major problem. Police statistics indicate that in England and Wales between April 2011 and May 2012 there were 115,905 bicycles thefts. Traditional interventions to tackle theft include (i) registering bicycles with local police forces, ii) improving bicycle parking facilities, and iii) improvements to bicycle locks and how they are applied. On average CCTV surveillance cameras alone only reduce crime by 7% (Nettle et al. 2012).

Simply placing small stickers depicting how to secure the lock correctly on parked bicycles has been an effective way in reducing bicycle theft (Sidebottom et al., 2009). A second nudging intervention at university locations found that placing signs with ‘watching eyes’ (an image of a pair of eyes) near bicycle stands reduced bicycle theft levels (Nettle et al., 2012). These signs decreased bicycle theft by 62% over 12 months.

We have seen that nudging can be used as a subtle technique to tackle crime rates. Nudging can take the form of small, cost-effective interventions such as distributing leaflets (Roach et al., 2016), strategically placing stickers (Sidebottom et al., 2009) and placing ‘watching eye’ signs near bicycle stands (Nettle et al., 2012). So like, Hugh and Liz moving into their new house if you receive a leaflet through the post simply reminding you to lock your car it may that nudging is being subtly used to reduce crime.

Hot-hand bias in rhesus monkeys (Macaca mulatta).

Hot-hand bias in rhesus monkeys (Macaca mulatta).

Henry and Elizabeth were at the zoo for a day out with their children. They walked around watching the birds-of-prey displays, elephant feeding and the primates. When they got to the rhesus monkeys it was feeding time. The monkey enclosures had food placed strategically in trees, on platforms and on top of boxes. One of Henry and Elizabeth’s children noticed that the monkeys moved around the enclosure a lot but kept on returning to the same part of the tree where the food was placed, she wondered why the monkey acted in this way.

One of the most interesting patterns of behaviour is the ‘hot hand bias.’ The hot hand bias was first observed in basketball players, it posits that we perceive a positive serial autocorrelation in independent sequential events (Blachard et al., 2014). In basketball players the hot band bias reflects the tendency to perceive that a player’s chance of hitting a shot is greater following a string of successful shots rather than misses. The hot hand bias goes against statistical probabilities that argue that past events (i.e., success shot in a basket) have no influence on current or future events (i.e., the current shot at the basket).

image 1.png

The origin of the hot hand bias remain unknown, in recent years researchers have begun to investigate the bias in animals that we share common ancestors with (Blanchard et al., 2014; Calhoun & Hayden, 2015). In 2014 researchers from the University of Rochester examined the hot hand bias in rhesus monkeys (Macaca mulatta) (Blanchard et al., 2014a). Blanchard and colleagues hypothesised that the hot hand bias is an adaptation to foraging in clumpy environments (i.e., environments with plentiful resources). The three monkeys in their study performed a novel gambling task. The results indicate that there were correlations between sequential decisions, for every sequential choice the change of choosing an option increased. The monkeys had better performance for clumped rather than dispersed distributions. These results support the suggestion that the hot hand bias evolved early during humanoid evolution and is an ancient bias.


A second study by the same research group at the University of Rochester examined decision biases in another three rhesus monkeys (Blanchard et al., 2014b). The monkeys performed a similar task to the first study where researchers gave monkeys a sequence of rewards to choose between and the choice to repeat the same sequence or start a new one. The findings indicate that adding a small reward to the end of a sequence can reduce its value. This study supports the cross-species nature of decision biases and that these biases have evolutionary ancient origins.

A third study to investigate the evolutionary origins of decision biases in monkeys trained monkeys to perform a computerized version of a foraging decision task called the patch-leaving task. The monkeys could make a choice between moving between two patches of food, one in the foreground and the other in the background. When the monkey chooses to ‘move’ from one patch to the other there is a delay called travel time that results in a delay between receiving rewards. When adjusted for travel time there was nearly optimal performance across all of the monkeys. This study suggests that the foraging context (i.e., patches and delay) can reduce the influence of decision biases (Calhoun & Hayden, 2015).

Taken together these studies demonstrate that humans and monkeys alike share some of the same decision biases that have evolved over the course of evolution. The decision biases that we observe in all animals (including humans) have evolved to aid in survival by ensuring sufficient food through foraging. When Henry and Elizabeth took their children to the zoo the monkey’s behaviour reflected one of the many uses of the hot hand bias as it repeatedly went back to the place where the food was waiting.

Confirmation bias in suspect interviews

Confirmation bias in suspect interviews

Richard had always wanted to be a police officer. He had achieved all of the grades that he needed at college and was accepted to train as a police officer. Richard passed all of his classes during training and eventually got to a point in in his training were he had to learn interview techniques. With his friend Samuel, Richard role-played interview techniques. Together they were told that they should familiarise themselves with the facts of the case before interviewing a suspect. When Richard was told to familiarise himself with the facts prior to interviewing he thought it odd because he knew that the interviewing officer would then suspect guilt or innocence. Despite his initial suspicions about the interviewing method like all of his colleagues he continued to interview in the way that he was trained.

The justice system is one of the most important systems a country can have, it keeps order and ensures that anyone who commits a crime is treated in the relevant way to that country. One of the main ways in which the justice system operates is through the use of law enforcement (i.e., police officers). Police officers get called to the scene of a crime, assess the scene, collect evidence and detain anyone that is suspected of the crime. We like to think that police officers always make the correct decisions, however like anyone else they are fallible.


One the most problematic cognitive biases (errors in decision-making) is the confirmation bias. The confirmation bias happens when an individual is required to make a decision but set about trying to prove a hypothesis that they already have. By making a decision based on what they already believe the individual is therefore at risk of making an incorrect decision.

One study that set out to investigate the confirmation bias in experienced police officers recruited 89 police officers. Charman and colleagues (2017) gave fictional criminal cases to participants and asked them to make a judgement about the guilt or innocence of the fictional suspect. Participants were then presented with ambiguous evidence in the form of either an alibi statement, handwriting sample, composite, or details of an informant (see Table 1) and asked to evaluate the ambiguous evidence. The results of this experiment found that the evaluation of the ambiguous evidence was related to the initial judgement of evidence in police officers: the stronger an officer’s initial belief in a suspect’s guilt the more incriminating they perceived the ambiguous evidence to be. The confirmation bias clearly had a strong effect in the evidence gained from interviews.

Tabel 1.png

An extreme case of confirmation bias during suspect interviewing can be demonstrated by what is one of the most publicised criminal case in recent years, the November 2007 murder of Meredith Kercher in Perugia, Italy. On the second of November 2007, British exchange student Meredith Kercher was found dead by her roommate, American, Amanda Knox. Knox had no history of violent crime and lacked a motive. When the police took a statement from Knox they believed she was hiding something because she showed no sign of emotion and behaved immaturely. She stated that on the night of the murder she was with her Italian boyfriend Raffaele Sollecito. With the prejudgement of Knox’s guilt, the police interrogated her for four days in Italian, a language that she was not fluent in, and without a lawyer present. In the early hours (1:45 am) of the fourth day of interrogations Knox eventually broke down, started screaming and without the support of her family and friends confessed to the murder. Later, when left alone she retracted her confession in a written statement. Interestingly, the confession contained no new information and was in part factually incorrect on important details. Knox was then officially arrested with Sollecito and provided with a lawyer. Her lawyer had the confession ruled inadmissible in court. Nonetheless, in the investigation that followed set about a motion of hypothesis-confirming (i.e., try to confirm a prior belief of guilt) with the detectives determined to prove that Knox was guilty (Kassin et al., 2011). In due course, on the 5th of December 2009 a jury convicted Knox and Sollecito of murder. Knox was sentenced to 26 years in prison and Sollecito to 25 years in prison. Eventually, on the 3rd of October 2011 after being granted a new trial, both Knox and Sollecito were acquitted. A short time after the release of Knox and Sollecito the Italian appeals court released a 143-page opinion criticising the prosecution concluding that there was no credible evidence or motive to presume Knox’s guilt.

image 2.png

One of the possible influences that brings about the confirmation bias in police interviews are the guidelines from the United States Department of Justice (Eyewitness evidence: a guide for law enforcement. U.S. Department of Justice, Office of Justice Programmes). These guidelines state that an interviewer should review the case information prior to conducting an interview, of course, at first thought this seems like ‘common sense’. A study by Rivard and colleagues in 2015 investigated this and how to prevent confirmation bias errors in suspect interviews. The results of their study found that blind interviewers (those that do not know the details of the case prior to the interview) produced more correct judgements of guilt or innocence than those that knew the details prior to interviewing a suspect. Another benefit of using blind interviewers is that in this study they did not start the interview with a suggestive / leading question.

In the United States alone the Innocence Project (2015) estimates that more than 300 innocent people have been wrongfully accused and convicted of crimes that they did not commit because of investigator bias and eyewitness error. Although some section of our justice systems are aware of the confirmation bias, and train their staff in the knowledge of the confirmation bias, it is hard to avoid this entirely. We have seen one way of the ways in that we can use to avoid the confirmation bias in the study by Rivard et al (2015), although this method may cause other problems itself. The confirmation bias is not unique to suspect interviews since these types of errors in decision-making are a problem in many situations when decision needs to be made (e.g., medical, legal, sports etc). So like Richard going through his police training, if you are unsure about a decision you can simply get a second opinion or take a step back and think carefully.

Nudging organ donation

Nudging organ donation

Steven had been a driver for over twenty years. In his country, as in many other, Steven had to renew his driver’s licence every ten years. Recently, the driving licence authority in his country changed their licence renewal process to an online system. After Steven filled out his licence number, confirmed his home address and clicked through to the next page he was prompted with a message about organ donation. Following the message, he was asked if he’d like to register to be an organ donor, he wondered for a while as to why this was included in the driving licence renewal process, clicked yes and continued.

Organ donation rates vary dramatically from country-to-country, despite the universal need for organ donors. In 2012, some countries such as The United Kingdom had about 13 people per a million signed up to the organ donors register, whilst other countries such as Belgium had over double this with 27 people per million signed up (see Table 1). Even within individual countries the numbers of people signed up to organ donors registers very a lot (see Table 2). There are many reasons for the differences in the rate of organ donors across countries including how to sign-up (opt-in or opt-out method), religious beliefs and cultural norms (Morgan et al., 2015).


Country Opt-in or opt-out Donors per million population Population
Belgium Opt-out 27.1 10,827,519
Denmark Opt-in 11.5 5,547,088
France Opt-out 23.2 64,709,480
Germany Opt-in 15.3 81,757,595
United Kingdom Opt-in (Opt-out in Wales) 12.9 63,230,000
United States Opt-in 25.97 305,529,237

Table 1. Data from EU Directorate General for Health & Consumers, March 2012


US State % Donors (18+) Population






Montana 82 782,161
New York 20 15,307,107
Texas 17 19,073,315
Vermont 5 502,060

Table 2. Data from National Donor Designation Report Card, April 2013

The modification of choice architecture (i.e., nudging) is one way in which donor numbers can be increased by making it easier for individuals to sign-up to be an organ donor (Rodriguez-Arias et al., 2016). The two ways for individuals to join the donors register are through an ‘opt-in’ or ‘opt-out’ registration system. In the ‘opt-in’ system individuals have to acquire an organ donor’s application form and make the effort to sign-up. In the ’opt-out’ system everyone is by default an organ donor if a person does not want to be an organ donor then they need to unregister from the organ donors register. As we can see in Table 1 the system of registration for organ donors vary from country-to-county.

In an effort to improve donor numbers the government of Belgium changed their system of organ donor’s registration in 2002. Initially Belgium employed the opt-in system were individuals had to put in an effort to sign-up to donate (Rodriguez-Arias et al., 2016). The change to an opt-out system doubled the number of organ donations in the first 3 years of implementing this change.


Another nudge that has been applied with the aim of increasing organ donor rates other than changing the default opt-in / opt-out system include increasing awareness of the need for organ donors. In New Zealand, individuals who register for a driving licence are made aware that they can sign-up to be an organ donor (Rosenblum et al., 2012). From 2011, British citizens applying for a driver’s licence, or to renew their licence online, are required to answer a question about organ donation (British Medical Association, 2012). Whilst in The United States, in Texas new drivers in the 1990s were asked to state their views on organ donation before acquiring their licence, unfortunately this has now been abandoned in Texas (Klassen & Klassen, 1996). The states of Illinois, trialled a similar system to Texas (Thaler et al., 2010).

Two demographics that are underrepresented among organ donors are Black and South Asian people (Morgan et al. 2015). Morgan and colleagues (2015) suggested tailoring nudges to individuals to improve organ donor rates among Black and South Asian people. In 22 focus groups across London Morgan’s group investigated the views of Nigerian Christians, Indian Hindus, Indian Sikhs, Pakistani Muslims and Bangladeshi Muslims. Most of the interviewees stated that they regard organ donation as allowable regardless of their faith, they simply had not signed-up to the organ donor register because it is something that is not done in their immediate social groups. Tailoring nudges (i.e., messages) to these social groups can be one way improving donor rates among Black and South Asian people.


One large survey of the public’s view of organ donation in The United Kingdom found that 90% of people support organ donation whilst less than a third are registered (James, 2015). The UK’s Behavioural Insight Team (BIT) tailored nudge messages to investigate their effect on organ donation rates (BIT paper: Applying Behavioural Insights to Organ Donation, Cabinet Office and Department of Health, 2013). On a government website BIT ran a randomised study for 5 weeks where over a million people saw one of eight messages (see Table 3). Both presenting a message as a social norm with an image and asking the reader about the fairness of donating and organ with reciprocation increased registration rates. This large study clearly shows that tailoring a message can make a nudge more or less effective depending on the target audience.


Message variant Attribute Message
1 Control Please join the NHS Organ Donor Register
2 Social norm + basic message Every day thousands of people who see this page decide to register
3 Variant 2 + images  
4 Variant 2 + images  
5 Loss frame + basic message Three people die every day because there are not enough organ donors…
6 Gain frame + basic message You could save or transform up to 9 lives as an organ donor
7 Fairness + reciprocity If you need an organ transplant would you have one? If so please help others
8   If you support organ donation please turn your support into action

Table 3. Tailored nudge messages employed in BIT study.

Therefore, like Steven if you sign-up to renew your driving licence and you are asked about organ donation it may be that you are seeing a message that is aimed at increasing organ donation rates. Depending on whether you would like someone to donate an organ to you if needed you may want to opt-in to donate. As we have seen nudges can be used in a variety of ways to increase donation rates. The default organ registration system (i.e., opt-in / opt-out) and public awareness of the need for donations through messages can all dramatically improve donations rates. More work needs to be done on nudging for organ donation to investigate all of the factors involved.

Nudging menu design for healthier food choices.

Nudging menu design for healthier food choices.

Jessica and Jack had just been seated at their favourite restaurant. They enjoyed the ambiance of the restaurant, the service and the quality of the food. They ate in the restaurant every couple of months as a treat. When the waiter handed Jessica and Jack their menus the noticed a few small changes, the low-calorie had been moved to the top of menu. They wondered why but continued their evening like normal without thinking about it any further.

Small and discrete changes to a menu or choice architecture can significantly impact the sales of a restaurant (Magrini & Kim, 2016). In the psychology literature, the manipulation of choice architecture is known as ‘nudging’. Nudges are subtle change to the choice architecture that make positive decisions (e.g., healthy eating) easier to make. Choice architecture is not limited to, but can take the form of the layout of a tax form, organ donation form, layout of a menu, placing of a food item on a shop floor, or the design of a pay-slip. The design of choice architecture depends on what the designers intend to achieve.

image 1.png

In the restaurant business, small changes to choice architecture can make significant changes to income, bringing in a lot of extra money to the restaurant. Restaurants can change their menus to promote the sales of the ‘special-dishes-of-the-day’, to increase the sales of healthy food, or to increase revenue. In one study by Gothenburg University in Sweden researchers studied the effects of changing menu design in a fifty-two-seat restaurant in the city centre (Gravert & Kurz, 2017). Over the course of three weeks customers arriving during a two-hour lunch break were randomly presented with two different menus. One of the two menus offered a meat dish and a fish dish with a note on the menu saying that a vegetarian option was available upon request. The second menu offered a vegetarian dish and a fish dish, with a note stating that a meat dish was available upon request. Despite the meat, fish and vegetarian dishes having the same prices (around 13 USD or 110 SEK) the slight inconvenience of ordering the meat dish significantly decreased the share of the dishes sold at lunch. The results of this study clearly show that slight changes in the menu can promote the sales of vegetarian dishes.

In 2014, the United States Food and Drug Administration produced a rule with the aim of reduce obesity levels, the Menu Calorie Labelling Rule. This rule requires large food service chains to post calorie information next to all food items on menus. Shortly, after beginning to use this rule the sales of healthier foods significantly improved. Nudging by putting calorie information next to the dishes significantly nudged customers towards eating healthier than they would otherwise eat.

image 4

Another study of the use of nudging for the promotion of healthy eating at Cornell University examined the effect of menu design on 200 college students (Mancino, 2009). The researchers at Cornell University simply added green stickers next to the healthy food choices on the menu, which was enough to increase the sales of healthy dishes.

Furthermore, another way that nudging has been used in menu design to increase the sales of certain dishes was assessed by Wansink and Love (2014). Wansink and Love analysed 373 descriptions of dishes on menus. They found that there are four simple ways to use the description of dish to nudge consumers into healthy eating: (i) the use of sensory names describing texture, smell or taste (e.g., Crispy Snow Pease, Fork-tender Beef Stew), (ii) the use geographic names to create an image of a geographic area that is associated with the food (e.g., Southwestern Tex-Mex Salad, Georgia Peach Tart), (iii) the use nostalgic names that allude to tradition, family or national origin (e.g., Oktoberfest Red Cabbage), and (iv) the use of brand names (e.g., Jack Daniels BBQ Ribs).

These studies of the use of nudging have all found that nudging can be used in different ways to promote the sales of healthy food – dishes can be rearranged on the menu with a note to customers to ask for information about the dish that is not being promoted, calorie information can be positioned next to each dish, green stickers can indicate which dishes are healthy, and descriptions can be used to tactically promote a dish. These studies all show that like Jessica and Jack when we sit down at a table to choose our food in a restaurant we may not notice subtle nudges that can have a big impact on the way we eat. Nudging can be a step forward in promoting healthy eating to reduce obesity levels.

How do investors prefer to save for their pensions: the 1/N heuristic.

How do investors prefer to save for their pensions: the 1/N heuristic.

Mark and Harvey were sat having coffee in their regular café that they visited every Thursday for breakfast before work. They discussed the latest football results and eventually ended up on the subjects of retirement. Harvey had never got around to starting an investment for his retirement so wanted to ask Mark for advice. Mark simply suggested that Harvey allocate his retirement investments equally across several funds, explaining that this reduce risk.

Saving or investing for retirement is one of the most important decisions that a person can make in their lifetime. Picking the right pension plan and / or allocating resources to the right fund(s) is crucial for enjoying their retirement years. Pension plans and retirement schemes differ from country-to-country. In some pension schemes investors have the choice of how to allocate their funds. When planning for their retirement individuals with a pension plan that allows them to allocate resources to different funds must choose how to invest their money. One popular strategy for making decisions about how to allocated resources is to use the 1/N heuristic (Benartzi & Thaler, 2001). The 1/N heuristic removes the confusion and stress of weighing up the pros and cons of how to invest resources and simply states that a given amount of resources should be divided equally between ‘x’ funds, for example, when a sum of £100,000 is to be invested this would be distributed into £20,000 into 5 different funds.

Image 1.png

In the Swedish pension system investors have the option of deciding how to invest 2.5% of their income. They can allocate 2.5% of their income to either a stock or interest fund (Hedesstrom et al., 2007). Once an individual makes the decision to invest part of their income they receive a brochure with 655 potential funds, they are then required to decide which of the funds they’d like to invest in. In 2004 researchers at Goteborg University analysed 392 investment decisions. The researchers found that investors used at least 5 different heuristics and biases to make their decisions. Investors had a tendency to avoid funds with extreme high and low risks (extremeness aversion – Simonson & Tversky, 1992), a tendency to select the default option (default bias – Johnson et al., 1992), to choose many funds in an attempt to seek maximal variety (diversification heuristic – Read & Loewenstein, 1995), to select domestic funds (home bias – Kilka & Weber, 2000), and to use the 1/N heuristic (Benartzi & Thaler, 2001).

A larger study of more than half a million pension plan participants in Defined Contribution pension plans from the records of the Vanguard Group investigated the use of the 1/N heuristic (Huberman & Jiang, 2004). They found that when deciding how to allocate pension funds participants tended to use the 1/N to divide their funds over 3 or 4 funds.

Image 3.png

A third study of 1000 people examined how Dutch citizens planned for their retirement (Van Rooij et al., 2007). After analysing retirement decisions the results of this study revealed that Dutch citizens are risk-averse and considered themselves to be financially unsophisticated. When given the option these investors used one three strategies (i) the default bias, (ii) the 1/N heuristic, or were susceptible to (iii) framing.

So, depending on what country you work in and decide to retire to there are many different ways to prepare for your retirement. Since most of us, like Harvey, are not financial experts when given complex important decisions to make for our retirement we choose to avoid risk by allocating our money equally across several funds by using the 1/N strategy. When planning for retirement the 1/N heuristic can be an effective and useful way to decrease risk and ensure a substantial retirement fund.

So, depending on what country you work in and decide to retire to there are many different ways to prepare for your retirement. Since most of us, like Harvey, are not financial experts when given complex important decisions to make for our retirement we choose to avoid risk by allocating our money equally across several funds by using the 1/N strategy. When planning for retirement the 1/N heuristic can be an effective and useful way to decrease risk and ensure a substantial retirement fund.

The sunk cost effect in pigeon behaviour.

The sunk cost effect in pigeon behaviour.

Eva and Jason had just finished a long morning trading in stocks in Canary Wharf. Every day at lunch time they liked to like to get out of the grey, poorly lit office and eat their lunch outside in Jubilee Park. They always sat on the same patch of grass and watched the pigeons and people pass by. As they ate Eva noticed that one of the pigeons tended to stick to the same area of the park, pecking around and looking for food rather than move to another area of the park where more people were sat around enjoying their lunches. Eva mentioned the pigeon to Jason and they both wondered why the pigeon would not move to the area of the park with more food.

In humans when an individual is given the choice between two or more investment decisions people often stick with the investment they are already involved in rather than moving to a new investment (Novemsky & Kahneman, 2005). The initial investment of resources (money, time, energy etc) make switching investments less likely even if the new investment could produce a better outcome than the original investment – psychologists call this tendency to stick with the original investment the sunk cost effect (or bias) (Avila et al., 2010). One explanation of the sunk cost effect is that people have strong misgivings about wasting resources, a disposition that economists call loss aversion (Novemsky & Kahneman, 2005).

image 4

Like humans, other animals (other than humans) often show the same decision behaviours. Several studies have investigated the sunk cost effect in pigeons (for a review see White & Magalhaes, 2015). In one study by Pattison and colleagues (2012) at the University of Kentucky researchers examined decision behaviour in pigeons (Columba livia). The pigeons were trained to peck at coloured keys with a potential reward (food). The pigeons could make a choice between pecking at one key for 30 pecks with a potential reward (e.g., a red key) or switching to another key (e.g., a green key) with a potential reward after 10 or 20 pecks. The pigeons showed a bias towards continuing with the sequence of pecks that they had invested in rather than switching to peck on another key that would produce a reward after fewer pecks. These results show that pigeons, like humans, show a bias to stay with an initial investment.

image 2.png

A second study investigating decision behaviour in pigeons used a slightly different method to Pattison and colleagues (Watanabe, 2009). The pigeons in this study still had the same choice of sticking with an initial investment (in pecks) or switching. After training the pigeons to peck 30 times at one colour for food and 10 times to another colour for food Watanabe gave the pigeons the choice of switching to the 10-peck option after they had already started the 30-peck option. The experimenters found that three of the four pigeons showed a preference for completing the initial investment, despite the fact that switching to the second option would need pecks overall. So, like humans the pigeons in this second study were also susceptible to the sunk cost effect. Although these results are interesting the resources conceded that there may be one alternative explanation for the behaviour pigeons – switching to the new alternative would require the pigeon to move to the new colour.

Therefore, although most people would like to think that we do not act in the same way as other animals some of our behaviour is not uniquely human. Next time you find yourself sat on a patch of grass like Eva and Jason enjoying your lunch whilst watching the local wildlife and wondering why that pigeon is acting so strangely simple think “what would I be doing if I were that pigeon?” Afterall, the pigeon stubbornly sticking to its little patch of the park is not too unlike the way that our investment bankers and stock brokers behave.