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
California

Iowa

34

73

28,801,211

2,351,233

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.

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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.

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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.

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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.

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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.

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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.

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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).

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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.

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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.

The framing effect on climate change communication and policy making.

The framing effect on climate change communication and policy making.

Hannah and Thomas had both recently become interested in the environment and the politics of climate change after seeing a few news articles on the topic. Last week Hannah watched a very convincing documentary by a leading politician about the dangers of climate change and how humans are contributing to it. Thomas’ father worked in manufacturing and was skeptical about the contributions of humans to the change in environment, his father had always said that humans could not change the environment. Both Hannah and Thomas agreed that although they had different views on climate change there are mixed messages in the press.

Many controversial topics in the media are framed in such a way that benefit the person or company that is responsible for placing the message. The framing effect is one of the major heuristics (short-cuts in decision-making) that is used in the media. Framing works by wording a message in a persuasive way to influence the thinking of the reader (Kuhn, 1997). Communicators can make a choice to present the possible outcomes of a medical interventions as either (a) 80% chance of surviving (i.e., positively framed) or (b) 20% chance of death (i.e., negatively framed). On the topic of climate change communication researchers have found that a negatively framed (highlighting losses) message decreases individual intentions to behave environmentally whilst positively framed messages (highlighting the possibility of losses not materializing) produce a stronger intention to act in a pro-environmental way (Morton et al., 2011).

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One important factor for policy makers is that in the United States the public do not think that climate change is a concern, compared to other policies. Every January the Pew Research Centre for The People and The Press conduct a large poll of the public’s belief in which of 20 policies are of most important.  Between 2007 and 2009 the policy of “dealing with global warming” was consistently ranked at the bottom of 20 priorities (see the table below).

% considering each as a “top priority” January 2007 January 2008 January 2009
Strengthening the nation’s economy 68 75 85
Securing social security 64 64 63
Securing Medicare 63 60 60
Reducing crime 62 54 46
Reducing health care costs 68 69 59
Strengthening the military 46 42 44
Dealing with illegal immigration 55 51 41
Reducing middle class taxes 48 46 43
Dealing with global trade 34 37 31
Dealing with global warming 38 35 30

To aid in breaking through the communication barrier policy makers can tailor their messages to specific audiences by framing their messages. News reporters (e.g., news about an event), policymakers (e.g., employment statistics), advertisers (e.g. vitamin advertisements), and public speakers (e.g., conference talks) already use framing effectively.

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The framing of climate change information has been used successfully by John Kerry in 2004 and Obama in 2008. In his 2004 election campaign the Democratic party presidential candidate Senator John Kerry made strategic use of the public accountability framing (i.e., we are responsible for our environment). Senator Kerry compared the use of different frames (i.e., denial or acceptance of climate change) to the administrations use of intelligence to invade Iraq. In Obama’s 2008 presidential candidate campaign he made use of a sound bite “creating green jobs and fuelling economic recovery.” Creating green jobs in industry with alternatives to gasoline (or petrol) was heralded as a way to benefit the economy by creating more jobs and as a way to reduce greenhouse emissions. We can see here that Kerry chose to use a public accountability frame whilst Obama used an economic frame – both frames were used towards the same aim but tailored differently. Famously, Gore in his 2008 WE campaign picked a moral frame for climate change communication.

We have seen here that the framing effect can be used effectively by communicators for any message (e.g., advertising, policies etc). On the topic of climate change communication, we can put the framing effect to work by carefully considering how we would like to frame a message to our intended audience. In the cases of Hannah and Thomas they may have both seen the same information presented in different ways (i.e., the frame), the frames that they have encountered helped them come to their own decisions about climate change.

The confirmation bias in the forensic sciences.

James and Nicki always wanted to work in the forensic sciences. Whilst reading towards their undergraduate degrees they would borrow as many books from the library as they could on forensics and watch the popular television programmes about ‘forensic experts.’ One day when looking though an interesting book about case studies in forensics Nicki came across an interesting case study.

In 1988, Barry Laughman confessed during interrogation to the charges of rape and murder of his neighbour. The following day tests revealed that the person who committed the crime had Type A blood whilst Laughman had Type B. Aware that Laughman had confessed to the crimes the state forensic chemists proposed four theories (none of which were scientific) to dismiss the mismatch. Laughman was in due course convicted and sentenced to 16 years in prison. He was eventually released in November 2003 after a re-examination of the DNA evidence.

The case of Barry Laughman gives us a clear example of the influence of confirmation bias in the forensic sciences. The confirmation bias is shown when an individual ignores evidence that goes against what they believe whilst trying to confirm the belief (Dror, 2006). In Barry’s case the Virginian state forensic chemist ignored contradictory evidence and persisted in dismissing the mismatch in DNA evidence.

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The confirmation bias causes problems in all areas of decision-making. In the forensic sciences errors in decision-making, as caused by the confirmation bias can have severe consequences innocent people can spend a lifetime in prison, and the actual criminal can go on to reoffend. In the forensic sciences, the confirmation bias has been reported by the National Academy of Sciences (2009) in firearms, hair and fibre analysis, blood splatter, hand-writing and fingerprints (Kossin et al., 2013; Garrett et al., 2011).

In a recent study investigators found an interesting example of how the confirmation bias can influence the outcome of a forensic analysis (Ulery et al., 2012). The investigators gave forensic fingerprint examiners the same evidence twice, at approximately 10% of the time the examiners reached different conclusions (Ulery et al., 2012). Three of the reasons as to why the examiners reached differing conclusions are (i) examiners often receive direct communication from the police (e.g., letters, phone calls etc), (ii) cross-communication between examiners, and (iii) examiners overstating the strength of evidence.

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There are measures that can be taken to prevent the confirmation bias. The FBI’s Latent Print Unit revised their Standard Operating Procedures (SOP) (Cole et al., 2005). They adopted a programme of masked verification whereby fingerprint comparisons that involve a single print are masked-verified (i.e., in isolation with no further information about the print). The change in SOP prevents the second examiner from inferring the first examiner’s conclusion when two examiners individually examine the evidence (Office of the Inspector General, 2011).

Other measures that can be undertaken to prevent the confirmation bias include training all forensic examiners so that they know about cognitive biases. Just two of the courses help to install knowledge of cognitive biases are the FBI’s week-long Facial Comparison and Identification Training and the Australian government’s 2-day long facial comparison course. The linear examination of evidence by multiple examiners (Heyer et al., 2013), cross-laboratory verification (Kossin et al., 2013) and peer verification (Heyer et al., 2011) can all help in reducing the impact of the confirmation bias in the forensic sciences.

So, like James and Nicki if you are interested in working in the forensic sciences it is important to learn about the influence of cognitive biases on decision-making. Some private forensic companies have begun to provide training for their employees, and some governments have started to provide training. With adequate training one day we may be able avoid false convictions.

The recognition heuristic in advertising

The recognition heuristic in advertising

Anton and Sarah were shopping for their weekly groceries in their local supermarket. They bought their regular fresh fruits, vegetables, meat and dairy. As they started down the cleaning aisle Anton and Sarah were trying to decide which furniture polish to buy. They looked at the choice of polishes that were stocked in the aisle. There was a supermarket own-brand choice, two little known choices and a well-known brand. Anton remembered the well-known brand of furniture polish from a television advertisement with a comical cartoon character. There was little difference between the prices so Anton and Sarah decided to opt for the well-known brand that they remembered from the television advertisement.

Like the furniture polish brand companies spend great fortunes on making their products well-known. Millions is spent on brand communication with the goal of achieving the aided and unaided awareness of products. In 2007 and 2008 two large brands, Proctor and Gamble and Unilever spent $5.2 billion and $7.8 billion respectively. The substantial resources that are committed to promoting brand awareness shows the importance of establishing and retaining the awareness of a brand.

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Because of the importance of brand awareness many companies and academics have sought to understand the decision processes that are involved when a consumer chooses one brand over another. In industry, a major US automobile brand invested substantial resources to study how they might persuade customers to choose their brand over their competitors. They found that although their brand had excellent new vehicles as judged by independent raters two thirds of US consumers did not consider their brand (Hauser et al., 2011). The automobile company lacked a memorable advertising campaign.

In academia, researchers at the Max Planck Institute have suggested a rule-of-thumb (i.e., heuristic) that attempts to explain why consumers choose one brand over another (Gigerenzer & Goldstein, 1999, 2011). In a now famous experiment where participants were given the names of two cities (e.g., Oxford or Lannion), and then asked to judge which of the two cities had the largest population, participants reliably choose the city they knew (i.e. Oxford) over the city that they did not (i.e. Lannion). The researchers recorded this rule-of-thumb as… If one of two objects is recognized and the other is not, then infer that the recognized object had the higher values with respect to the criterion. The researchers called this rule-of-thumb the recognition heuristic. In consumer psychology, the recognition heuristic works equally well when consumers are asked to choose one brand over another (Thoma et al., 2013; Oeusanthornwattana & Shanks, 2010).

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In purchases with higher stakes (compared to simply buying a product in a shop) such as stock market investments the recognition heuristic is also of use. Imagine that you wish to invest a particular amount of money in stocks. If one person recognises a stock name over another they are more likely to choose the known stock over the unknown stock. Having a recognised stock name can increase the number of investors in a certain stock (Erdfelder et al., 2011).

In the case of Anton and Sarah shopping for their furniture polish it is clear why they choose the well-known brand over the unknown polish. The advertising campaign of the branded furniture polish with the comical cartoon character aided in the recognition of this brand thereby resulting in one more sale. If you multiple Anton and Sarah’s purchase by thousands or millions then you can clearly see the huge amounts of money that are involved. Many of us, like Anton and Sarah stick to brands we know simply because we know them, we buy the same cleaning products and food stuffs because of successful brand awareness campaigns that act on the recognition heuristic. Perhaps if we wish to avoid making unconscious choices based on the recognition heuristic we could simply try a different product, afterall the new product is not as we expect we can change back to our regular shopping pattern next time.

The home advantage bias and attribution bias during football refereeing in the German Bundesliga and the English Premier League.

The home advantage bias and attribution bias during football refereeing in the German Bundesliga and the English Premier League.

Andrew had always dreamt of a career in professional sports, unlike most people that want to work in sports he wasn’t interested in the fame and money. Andrew had spent the last 10 years working up to where he is. He had refereed for many small clubs and matches in the lower leagues. Now Andrew had been selected to referee for the top leagues. During his first big match Andrew was the top referee, he found himself in a stadium with 60,000 cheering and yelling fans. One of the star strikers went down after being tackled, he was holding is leg in pain. Andrew had a decision to make, was this a foul? He felt the pressure as the crowds began to yell. His decision would influence the outcome of the whole match.

Referees, judges and umpires all have an important role to play when it comes to sporting events. In a lot of sports the decisions of these officials can have a big impact on the position of a team in the league tables. The position of a team in the league table can furthermore affect the finances of a team, it’s investors and in some cases, it’s supporters.

One well known phenomena in sporting events is the home team advantage (Garicano et al., 2005; Rickman and Witt, 2008). The home team advantage phenomena states that a team playing in their home stadium will have an advantage over the opposing team simply because they are in their home stadium. The home team advantage has been shown in almost all sports. In football, researchers have investigated the home team advantage in the Italian Serie A league (Scoppa, 2008), the US leagues (Garicano et al., 2005), German Bundesliga (Kocher et al., 2004) and the English Premier League (Rickman and Witt, 2008). The decisions that referees make play a major role in the home team advantage.

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In 2007 Perrersson-Lidbom and colleagues at the Universities of Stockholm and Munich had an opportunity to study the home team advantage in 24 matches after a serious of problems in the Italian Serie A and Serie B leagues. On February the 2nd 2007 supporters of the Italian football clubs Calcio Catania and Palermo Calcio clashed with each other and police in a violent and serious act of hooliganism. Filippo Raciti, a police officer in Catonia was killed during the rioting and around a hundred people were injured. Following the rioting police forced some of the clubs to play their home games without spectators. The researchers found that the presence of the supporters had an influence on the decisions of referees. When matches were played in front of spectators referees would punish away team players more harshly and home team players more lightly for the same offences (e.g., fouls). The home team advantage disappeared when there were no spectators. This reveals that although referees are expected to be unbiased factors such as cheering spectators can influence their decisions.

Another study of the home team advantage phenomena was conducted at the California Polytechnic State University by Richard Pollard in 2002. Between 1987 and 2001 there was a building boom for new sporting stadiums in United States. Pollard gathered data from 37 teams as they moved to new stadiums. If the home team advantage was in part to do with the stadium itself then the advantage should temporarily disappear when teams move stadium. Pollard found that 24% of the advantage of playing at a team’s home stadium is lost in the months after moving stadium. A large bit of the home team advantage remains which may be in part due to the referee’s decision-making.

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One influence on a referee’s decision-making that many readers may find surprising are seemingly unimportant perceptual cues such at the height of a footballer (Quaquebeke and Giessner, 2010). Perceptual cues such as height can influence a referee’s decisions through a cognitive bias called the attribution bias. The attribution bias states that an attribute that does not implicitly seem important to the referee can influence a decision, when prompted the referee would not acknowledge that the attribute was an important factor in their decision. Quaquebeke and Giessner (2010) investigated what factors can influence the decision of a referee to punish a foul. They found that since height can sometimes be associated with the concepts of strength and aggression height can have an influence on decision-making. When an ambiguous tackle is seen by a referee the referee is more likely to attribute the wrongdoing to the taller of two players. Field data of decision-making by referees in seven UEFA Champion Leagues, three FIFA World Cups and the German Bundesliga league all support the attribution bias in refereeing.

So, although many of us are unlikely to find ourselves in the position of Andrew presiding over important decisions in a football match it is important to remember that we cannot always be unbiased in our decision-making. When Andrew finds himself deciding which of two players were in the wrong when going into a tackle he should bear-in-mind that factors that he is not aware of (e.g., height and crowd noise) play a role in his decision-making.

The framing effect in bonobos, chimpanzees and capuchin monkeys.

The framing effect in bonobos, chimpanzees and capuchin monkeys.

Noam Chimpsky had had a long day playing with the other chimpanzees. Noam was starting to feel hungry so headed towards the eating area of his enclosure. He had previously stored some fruit on a branch of a large tree. On the way to collect his fruit Noam noticed that one of the other chimpanzees had a new fruit that he had never seen before. Noam was determined to try some of the new fruit. He collected some of his fruit from his stash of fruit and went towards the other chimpanzee who was still carrying the new fruit. Noam wanted to trade some of his fruit for the new fruit. He stopped in front of the other chimpanzee, placed his fruit on the ground and tried to trade. The chimpanzee with the new fruit was happy to trade but wanted more fruit then Noam was willing to give. Noam decided that trading was a bad idea if he had give away too much fruit so he went off to his tree, with his fruit in hand and settled down to eat – afterall, Noam could try some of the new fruit another day.

Noam’s choice was to trade a small amount of food for the new fruit or to trade a lot of his fruit for the new fruit. In the end, Noam decided that the new fruit was not worth a lot of his fruit. Like humans Noam is susceptible to the framing effect. For Noam, his dilemma was to accept a negatively framed trade were he would lose out by giving away too much of his fruit or to broker a positively framed trade were he would give away a small amount of fruit for the new fruit.

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The framing effect states that the manner in which options are presented (or framed) can influence how we evaluate choices. We evaluate the options relative to a reference point (i.e., the amount of fruit the Noam had to start with). Changes that seem to worsen the status quo (i.e., Noam giving away a lot fruit for the new fruit) are treated differently to changes that improve the status quo (i.e., Noam gaining the new fruit after trading for a small amount of fruit). The way in which we (and Noam) perceive the choice is important because we are more willing to invest in a choice that is positively framed, rather than negatively framed. The framing effect has been documented extensively in human decision-making in areas such as financial trading (Seo et al., 2010) and medical decision-making (Bornstein et a., 2001). However, as we have seen in the case of Noam other animals, other than humans also exhibit the framing effect. According to molecular-clock estimates our genus split with other primates around 23 million years ago (Schneider et al., 2001), which means that we share a common ancestor with other primates. We share some of our decision-making processes (e.g., the framing effect) with the other animals.

One study the sought to investigate the framing effect in other primates used 40 bonobos (Pan paniscus) and chimpanzees (Pan trogladytes) (Krupenye et al., 2015). The apes were required to make choices between a positively framed option that provided a preferred food item (fruit) and a negatively framed option with a different food item (peanuts). The apes completed 5 sessions of 12 trials on separate days. Both the bonobos and the chimpanzees choose the positively framed option more than the negatively framed option demonstrating that they were susceptible to the framing effect. Furthermore, male apes were more susceptible then female apes to the framing effect.

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Capuchin monkeys (Cebus appella) have also shown the framing effect in several different studies (Chen et al., 2017; Lakshminarayanan et al., 2011). In their natural environments capuchins live in complex environments, they are socially sophisticated primates whose native environment requires careful management of their scarce resources. The study by Lakshminarayanan et al., (2011) found that capuchins are able to learn how to trade tokens for food. When trading tokens they are susceptible to framing effect for positively and negatively framed choices.

The results of the capuchin, bonobo and chimpanzee studies suggest that the mechanisms that drive the framing effect is evolutionarily ancient. Some of our ‘human’ economic biases are shared by Noam and the other primates throughout the primate order. These studies highlight the importance of comparative research in understanding the origins of cognitive biases and individual differences in human decision-making. To understand the human brain and decision-making we should complement of research by looking towards our distant relatives.

The sunk cost effect in customer loyalty schemes.

The sunk cost effect in customer loyalty schemes.

Gary was bored at work sat at his desk. He was wasting time before a meeting by browsing some of the popular shopping websites looking for a new book to read for his commute to work. Like many of us, Gary has several membership subscriptions for websites that he shops on a lot. The subscriptions that he buys for with a small annual cost guarantees Gary quick delivery, priority ordering and discounts on a large range of products. Since he was bored at work Gary thought that he’d take advantage of his subscription and order another book – afterall he pays for the service so why not make the most of it?

Almost all large companies have subscription membership schemes that offer their customers exclusive benefits. Mobile phone (cell phone), internet, utility (e.g., gas and electricity), insurance, and travel providers all offer their main services alongside additional schemes with small membership charges for exclusive offers. These schemes are everywhere. Subscription-based membership schemes are very profitable for most companies, and rely on customers opting for easy, lazy decision-making over well thought through decision-making. The historical cost of purchasing the subscription for a small fee is an important aspect of this easy decision-making.

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Traditional economic theories explain that when making decisions historical costs should be irrelevant, they should not factor into present decisions (Kramer, 2017). One of the most prominent cognitive biases were historical costs are an important influencer of decision-making is known at the sunk cost fallacy. Kelly (2004) summarized the sunk cost fallacy into two claims: i) individuals give weight to sunk costs in their decision-making (i.e., subscription costs), and ii) it is irrational for them to do so.

Two popular examples of subscription-based membership schemes that benefit from the sunk cost fallacy are the Bahn Card 50 and Amazon Prime. The Bahn Card 50 is the original customer loyalty scheme for Deutsche Bahn, the main German railway operator. The Bahn Card 50 was introduced in 1992, as of 2014 it had 5 million subscribers. The fee for the card is EUR 255 per year which gives the owner of the card a 50% discount on train fares. Like all of the other subscription-based membership schemes the owner of the Bahn Card 50 regards the subscription cost as a sunk cost (historical cost), in doing so they try to make the most of the scheme (Tacke & Firmer, 1992).

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Amazon’s subscription-based membership scheme is called Amazon Prime. Prime was introduced 2004. For a fee of $99 (as of November 2014) subscribers get faster delivery and priority to access to products on Amazon’s shopping website. Prime has become an important part of Amazon’s business model. After the introduction of Prime Amazon recorded a 150% increase in purchases by Prime members in the year immediately after joining the scheme. Prime is responsible for 20% of Amazon’ overall sales in the United States. For a company that makes billion in profits every year exploiting the sunk cost fallacy has proven to be very profitable.

The sunk cost fallacy is just one of many cognitive biases that influence decision-making. As we have seen above for people like Gary, and of course most of us, the sunk cost bias can affect the way in which we make decisions through subscription-based membership schemes. It is easier to think that since we have already paid a membership fee that gives us a discount we should take advantage of this and use it. If you sit back and think about the situation not exploiting the discount actually saves us more money than the discount would because we are not spending anything more. Big companies such as Amazon have learnt to use these cognitive biases, thereby making huge profits from our quick, easy and effortless decision-making.