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.

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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.

The gambler’s fallacy, framing, anchoring and hindsight bias in judicial decision-making.

The gambler’s fallacy, framing, anchoring and hindsight bias in judicial decision-making.

Months before William had moved into a new house with his wife, Sarah. They were excited about their move to their new home. William and Sarah unlocked the door to their new house and waited for the furniture removal staff to arrive at the end of their driveway. As the removal van drove up the driveway the van struck the side of William and Sarah’s car, writing the car off. Several months later William and Sarah headed to court to claim for the damages of their car against the removal company. Over many years their lawyer had learnt to be careful in the way that she words her cases in court. Their lawyer asked the judges “How much would you award the plaintiff in compensatory damages?” rather than “We are claiming ‘x’ amount from the defendant.” William and Sarah’s lawyer had learnt that framing a case in such away could exploit the framing bias.

The judicial system is one of the most important systems in all countries with a court of law. Judges play a significant role in society deciding on the outcome of many cases and setting precedencies for future cases. The public expect judges to decide on the outcome of each case fairly, without systematic errors or bias. However, like any instance where a person must make a judgement or decision judges are subject to systematic biases.

One of the most important aspects of law for many people is immigration law. Asylum judges must make decisions that can determine the fate of the individual in court. The United States offers asylum to foreign national who can (i) prove that they have a well-founded fear of persecution in their own countries, and (ii) that their race, religion, nationality, political opinions, or membership in a particular social group is one central reason for the threatened persecution. In 2016 a study by Harvard academics investigated the use of heuristics and biases in the asylum courts of the United States (Chen et al., 2016). Chen and colleagues accessed data through a Freedom of Information Act request of 699 decisions that were made by 357 judges in 45 courts from 1985 to 2013. All cases in the US are handled on a first-in-first-out basis with no quotas as to how many individuals are granted, or not granted asylum. On analysis of the data Chen et al found that judges were subject to the gambler’s fallacy. Judges were more likely to grant (or deny) asylum after denying (or granting) asylum to a previous applicant. The judges presiding over the fate of the asylum applications believes in a representation of randomness, as such, they were more likely to alternate between granting and denying asylum.

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There are many other heuristics and biases that play an important role in the judicial decisions of judges in the US these include framing (as demonstrated by William and Sarah’s lawyer), anchoring, and the hindsight bias. In a joint study with Cornell Law School researchers at a major conference issued questionnaires to 167 federal magistrates. The questionnaires contained examples of cases that a court judge would preside over. From the responses to the questionnaires Guthrie et al (2002) found that judges were subject to anchoring in personal injury claims, framing in copyright action cases, and the hindsight bias in cases of medical negligence.

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A retrospective study by Rachlinski et al (2000) examined the effect of the hindsight bias on decisions in real court cases. The hindsight bias is a mental shortcut that states that we have an inclination, after an event has occurred, to see that the event was predictable. The researchers found that judges failed to appreciate the problems associated with judging an event from hindsight. One example (Chase v. Pevear) from the Supreme Judicial Court of Massachusetts decided that the trustees of two high risk investments should have known the outcome of the investments with a nearly omniscient ability. In the case of First Alabama Bank v. Martin the Alabama Supreme Court held that another group of high risk, high yield equities were speculative, as shown by the fact that trustees lost money by selling ‘at the bottom of the market.’ The courts in both cases assumed that the investors should have known that the price of the equities were recovering, and hence the trustees should not have sold them. One court even held a trustee liable for failing to predict the stock market crash of 1929.

The public expects our judges to make well balanced judgements and decisions without falling for cognitive biases. As humans tasked with make important decisions the judicial system is not isolated from any of the shortcuts that we use to make decisions. For William and Sarah seeking their compensation for the damage to their car the experience that their lawyer had with the framing bias came in useful. In many of other cases, such as with the example of the gambler’s fallacy in the asylum courts these cognitive biases and mental shortcuts can become problematic. We have seen how the framing bias, anchoring heuristic and hindsight bias are all important when making decisions, even at the highest levels of decision-making in society.

 

 

 

How do we make decisions quickly when placing bets in a casino?

How do we make decisions quickly when placing bets in a casino?

Like many tourists, Rebecca and Catherine always wanted to visit Las Vegas. They took in the dazzling sights of the bright lights, enjoyed the stage magic and drifted into one of large casinos. When they walked into the casino they were amazed by the sounds and lights. Catherine had always enjoyed the game of roulette so headed straight to the roulette table. Catherine placed three consecutive bets, losing all three. Watching this Rebecca quietly said to Catherine “Maybe you should try another game, the odds are against you winning.” To this Catherine replied “No, I have lost three times I am overdue a win, I will win soon.”

When we make decisions, we like to think that we make all of our decisions rationally. Casino environments are designed to be one of the most complex environments that we ever encounter, there are colourful, flashing lights, loud machines playing music and people cheering. It is hard to deal with the environment, tune-out and make clear decisions. To deal with complex environments the brain has developed a number of judgement heuristics. Judgement heuristics are mental short cuts that enable us to make quick decisions whilst ignoring part of the decision-making environment. One classic example of a judgement heuristic was given by Catherine above when speaking to Rebecca at the roulette table. The aptly named gambler’s fallacy, as demonstrated above can also be seen in the following classic scenario. Imagine that someone is flipping a coin multiple times, the coin lands head side up three times in a row. Someone watching the coin flipping is asked to guess whether the next coin will land head side up or tail side up. If the person guesses tail side up they are using the gambler’s fallacy, a belief that randomness follows a pattern. Many people believe that for the coin flipping to be truly random the outcome of a sequence of five coin flips must be something like HEADS-TAILS-HEADS-TAILS-HEADS. If an outcome of five flips is HEADS-HEADS-HEADS-HEADS-HEADS then the coin is overdue to land with the tail side up otherwise this is not random. The belief in a pattern of randomness persists in most areas of life.

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In a field study by researchers at the University of Navada 18 hours worth of overhead security camera footage of a roulette table was obtained from a large Reno casino, consisting for 904 bets (Sundali & Croson, 2006). The researchers watched all of the bets and coded the patterns of betting for every gambler that sat down at the table. On an American-style roulette table there are 36 different sections of the roulette wheel, coloured as red or black (European-style roulette has 37 sections). Players can bet on more than one number and colour by placing their chips on the corners or side of each of the numbered squares. If a gambler bets randomly then after the researchers coded each bet there should be a 2.6% chance that a bet would fall on each number. The researchers found that after an outcome of RED-RED-RED gamblers responded with a gambler’s fallacy type logic by betting on BLACK. Like Catherine above and the coin flipping above, the gamblers believed in a representation, or pattern of randomness.

A study by Gal and Baron in 1996 investigated the gambler’s fallacy in a laboratory-based experiment. Gal and Baron examined whether a change in betting strategy was due to boredom by asking participants why they choose to bet in the way that they did. Most of the participants in the Gal and Baron study responded by saying that they were attempting to maximize their earnings by using the gambler’s fallacy-type logic. It would appear that the gambler’s fallacy is not simply caused by boredom.

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Besides gambling at the roulette table other casino games in which heuristics play a major role include the craps table and fruit machines. One prominent heuristic at the craps table is the belief in illusory correlations. When rolling the dice at the craps table gamblers often blow on the dice for luck or roll the dice softly in the belief that a low number will come up, and roll the dice harder when they want a higher number (Griffths. 1994). These gamblers believe that if a number comes up that they did not want then they did not through the dice hard or soft enough.

Cognitive short cuts as heuristics are used in every area of life where decisions need to be made. With respect to gambling, heuristics have been documented in fruit machine users, and at the poker, blackjack, roulette and craps tables. Even when betting on horse or dog races gamblers reliably use these mental short cuts (Terrell, 1998). I have highlighted two of uses of heuristics above, namely the gambler’s fallacy and illusory control. Like Catherine above many people fall for these heuristics and make sub-optimal decisions based on incorrect beliefs. When it comes to gambling, there are two ways to avoid these cognitive traps. If gambling alone take your time to think about the decisions that you want to make. When gambling in a group of with a friend you could listen to the advice of your friend as Catherine should have above.

Heuristics in food choice, how do we choose what to eat and how much to eat?

Heuristics in food choice, how do we choose what to eat and how much to eat?

Ian and Jill were on their lunch break from a long and busy day at work. They both worked in the same office and liked to get out of the office environment for an hour to eat their lunch. Just like on any other day Ian and Jill walked from their office down the street to the local food court. Neither Ian nor Jill were picky eaters they’d just eat whatever they felt like eating. As they got to the food court they both looked around at the large number of restaurants and cafes that they could choose from to purchase lunch. Jill looked at Ian and said “Well, where should we eat today? There are so many choices here.”

In many countries, we live in very food-rich environments. In supermarkets, we can choose from thousands of different items of food, and from this we can combine these food items into tens of thousands of different dishes, albeit with a little help from our recipe books. When we go out to eat like Ian and Jill we encounter vast numbers of dishes to choose from. Most consumers are not aware of it but on a day-to-day basis we make an estimated 200 food choices (Wansink & Sobal, 2007). Of course, we don’t like to agonise of what to eat for lunch so we like to use simple effortless strategies. The lack of any deliberation leaves us susceptible to ‘rules-of-thumb’ (mental shortcuts known as heuristics).

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So, what heuristics are involved in food choice?

When stood at the doors of the food court looking at the dozen or so restaurants ahead of us many us like to consider one attribute of food to be the most important (e.g., low in calories, inexpensive, convenient etc.). A heuristic known as the lexicographic decision rule, LEX for short, accounts for this by saying that we make our decision based on the food that satisfies an attribute the most (e.g., the food alternative with the lowest number of calories). If two foods are equal on the first attribute the second most important attribute of the food acts as the tie-breaker (e.g., convenience and inexpensive).

Academics at the Max Planck Institute in Berlin have investigated the lexicographic decision rule in food choice (Schiebehenne et al., 2007). In 2006 the researchers conducted a study at the Potsdamer Platz Arkaden, a large shopping centre in Berlin. They had students rate food along 38 different attributes (e.g., price etc.). The researchers then used the information from the students in a study were participants were shown 10 photographs of food dishes with the name of a restaurant, the price and type of food (e.g., Indian or Italian food). Participants choose a food and rated their choice on the 38 attributes. Example foods from this study include Big Mac burgers, Bockwurst with potato salad, chocolate muffins, lasagne, sushi and pizza. The results of the study found that participants did mainly consider only one attribute when making their decision about which food to eat. When tied on the single attribute with another food they simply considered the second most important attribute (is this low-calorie food as inexpensive as the second low-calorie food?). The lexicographic decision rule was able to predict the food choice that participants in this study made after considering what single attribute was of the most importance to a participant.

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Another strategy for food choice that many people use is evident in people who keep to strict diets for religious reasons or health reasons. Experienced dieters often practice rules that become habitual, for example, avoid all chocolate. When practiced frequently dietary rules become internalized and can be used as rules-of-thumb, however, this lack of conscious deliberation can leave us susceptible to other cognitive processes, even when trying to avoid sugary chocolate. The size of plates and serving utensils are just one of the things have been shown to influence how much we eat when serving our own food. People tend to serve themselves more, and eat more from larger bowls and plates than when given smaller plates, even when given the option to return for a second serving had they received a small plate (Gier et al., 2006). As for beverages, when given a tall drinking glass people pour more than when they have a short glass (Wansink & Van Ittersum, 2003).

For most of us who do not follow a particular diet and like to try different foods the lexicographic decision rule can be a great decision aid because when using this we don’t have to consider a lot different competing attributes of a food dish. In the case of Ian and Jill walking into the food court satisfying their joint desire to eat healthy the lexicographic decision rule works well to help them avoid the many fast food outlets. However, for those who are aiming to avoid chocolate (or any other single food) we should be aware of the other cognitive processes at work, after all a large plate does not mean that we all have to fill the plate completely.

Dan Edgcumbe

Heuristics in political voting.

Heuristics in political voting.

On the way to vote in the general election John and Sarah were discussing which candidate and political party they were going to vote for. There were two main candidates up for consideration in the general election. The first candidate was seeking a second term in office whilst the second candidate was opposed to the first on policies but had higher approval ratings. Sarah mentioned to John that she was going to vote for the first candidate because the economy had done well under his administration. John said that he was going to vote for the second candidate because she had higher approval ratings, as such, was more popular than the first candidate. They both went on to cast their votes for their favoured candidates and continued on in the day as normal.

In the example of John and Sarah above we see a typical quick discussion with some reasons given for choosing one candidate over another in a general election. Like many voters, John and Sarah think about the state of the economy and approval ratings when trying to decide on who to endorse for public office. Voting in this way is not necessarily the most rational way to vote, however, this demonstrates some of the cognitive biases that influence our decisions during the voting process. When pressed to give a reason why we have voted in the way that we did many of us would say that we weighed up the policies of each candidate (and political party). We like to think of ourselves as rational decision makers however this is not so. Cognitive biases influence our decisions far more than would like to think so.

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General elections are some of the most important decisions that we can make. Although general elections in the United Kingdom are every four years the political party that goes on to win an election can influence our lives in almost every way. The incumbent Prime Minister takes charge of the direction of economic, health, judicial, educational and defence policy. If you have been saving up for the deposit for that nice first home and you are planning to take out the mortgage on the home in the next couple of years the housing policies of the Prime Minister are important, some ministers may help first time buyers whilst others may not.

When putting the ‘X’ next to the preferred candidate’s name and political party at the ballot box we all have a preference for some policies over another (e.g., conservative or liberal policies). John may like the idea of the nationalisation of railways, as such he decides to vote for the party that has historically been in favour of nationalising the railway network. By voting in this way John has made an affective (i.e. emotional) response towards a political party and voted by using the likability heuristic rather than thinking through all of the policies of each political party (Brady & Sniderman, 1985). The likeability heuristic has help John make a quick decision about who to vote without the need for agonising over the decision.

Another rule of thumb (or heuristic) is to evaluate the incumbent Prime Minister on the basis of the economy’s current performance – if the economy is doing well than the Prime Minister is a good candidate (Popkin et al., 1992; Schneider et al., 1985). One problem with this ‘economic performance heuristic’ is that it makes the assumption that the Prime Minister controls the economy, for the most part this is incorrect. The Prime Minister can decide on policies, but they do not control the economy. This ‘economic performance heuristic’ merely rewards good economic luck whilst punishing poor economic luck. For the Prime Minister’s cabinet, this rules of thumb provides incentives to sacrifice long-term economic growth for small boosts in activity, particularly, in election years (Fiorina et al., 1981).

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A third heuristic that many of us use when deciding on who to vote for in a general election, or even local elections, is the ‘approval rating heuristic’. One cleverly designed study in 1993 by Jeffery Mondak at the University of Pittsburgh, Pennsylvania showed that participants used Ronald Reagan’s approval ratings as a cue to performance. When Reagan had high approval ratings, participants said that they would be more willing to vote for him, compared to when he had low approval ratings, Reagan’s policies did not differ with popularity. The study by Mondak demonstrates one important heuristic, that is that, we are more likely to vote for a candidate with high approval ratings than low approval ratings simply because they are more popular than the other candidates.

Heuristics aren’t only important when making decisions in elections they also play a role in the outcome of referendums. Under the direct democracy system of Switzerland, the Swiss have more referendums than any other country. In 2016 alone the Swiss had 13 referendums on a variety of subjects such as highway construction, wine production and economic policy (see Table 1 for an example). At first thought the idea of having a lot of referendums seems like a good idea because the public get their say on all government policies, however this system has its problems. When voting in a referendum we are expected to become informed about a diverse and highly complex serious of issues in our spare-time. One study by Gruner and Hertig (1983) collected data from the regular referendum voters in Switzerland after each vote from 1977 to 1983, they found that only 20% of the voters were actually well informed about the issues at stake, many of the voters only knew the name of the referendum.

(Table 1)

table

So, how do we make these decisions about the referendums that are crucial for the direction of government policy? Two of the heuristics that are important decision-making tools for referendum voting are the status quo bias and the likeability heuristic (Passy, 1993; Clarke et al., 2012). The status quo bias suggests that we favour the known over unknown, and reject the new and untested in favour of the familiar. As we can see in the table above many voters choose to stick with the familiar and reject the new without any clear reason. One example of this is the Swiss referendum on joining the European Economic Area (EEA) in December 1992. Following the voting academics asked the voters for their reasons and how they voted (Passy, 1993). On average 30% of the voters could not give any reason for how they voted (despite voting), 50% were able to give one reason and 20% gave two reasons, we can take this as an indication of the level of knowledge that each voter had. Many of the voters voted to reject joining the EEA by using the status quo heuristic.

The second of the heuristics that is involved in decision-making in referendums was demonstrated in Britain’s Alternative Vote referendum on the 5th of May 2011. This referendum is unique because there were some strong political personalities involved in campaigning for and against the alternative ballot. By the time of the referendum Nick Clegg, leader of the Liberal Democrat party had become decidedly unpopular, he was part of the coalition government and went back on many of his campaign policies. Nick Clegg campaigned for the Alternative Ballot. Following the voting many voters stated that they voted against the alternative vote because they no longer liked Nick Clegg (Clarke et al., 2012). Voters used the likeability heuristic rather than weighing up the consequences of voting for or against the referendum.

Like John and Sarah if you are agonising about who to vote for in a general election of which way to vote during a referendum bear-in-mind that there are many cognitive biases (heuristics) can help you make the decision. For better or for worse even when making highly important decisions cognitive biases such as the likeability heuristic, approval rating heuristic, the status quo bias and economic performance rule of thumb influence our decisions. To avoid these cognitive biases, we can start by thinking about the reasons why are considering voting the way we are.

Cognitive reflection and cognitive reflection-like items

Cognitive reflection and cognitive reflection-like items.

Below are a list of items from the academic literature.

Original CRT (3 – item Frederick, 2005)

  1. A bat and a ball cost £1.10 in total. The bat costs a dollar more than the ball. How much does the ball cost? (Intuitive answer 10 pence; correct answer 5 pence).
  1. If it takes 5 machines 5 minutes to make 5 widgets, how long would it take 100 machines to make 100 widgets? (Intuitive answer 100 minutes; correct answer 5 minutes).
  1. In a lake, there is a patch of lily pads. Every day, the patch doubles in size. If it takes 48 days for the patch to cover the entire lake, how long would it take for the patch to cover half the lake? (Intuitive answer 24 days; correct answer 47 days).

4 –items from Toplak (2014).

  1. If John can drink one barrel of water in 6 days, and Mary can drink one barrel of water in 12 days, how long would it take them to drink one barrel of water together? (Intuitive answer 9; correct answer 4).
  1. A man buys a pig for £60, sells it for £70, buys it back for £80, and sells it finally for £90. How much has he made? (Intuitive answer £10; correct answer £20).
  1. Simon decided to invest £8,000 in the stock market one day early in 2008. Six months after he invested, on July 17, the stocks he had purchased were down 50%. Fortunately for Simon, from July 17 to October 17, the stocks he had purchased went up 75%. At this point, Simon has: a.  broken even in the stock market. b. is ahead of where he began. c. has lost money. (Intuitive answer b; correct answer c  value is £7000).
  1. Jerry received both the 15th highest and the 15th lowest mark in the class. How many students are in the class? (Intuitive answer 30; correct answer 29).

2016 CRT (Thomson & Oppenheimer, 2016)

  1. If you’re running a race and you pass the person in second place, what place are you in? (Intuitive answer 1st; correct answer 2nd).
  1. A farmer had 15 sheep and all but 8 died. How many are left? (Intuitive answer 7; correct answer 8).
  1. Emily’s father had three daughters. The first two are named April and May. What is the third daughter’s name? (Intuitive answer June; correct answer Emily).
  1. How many cubic feet of dirt are there in a hole that 3’ deep x 3’ wide x 3’ long? (Intuitive answer 27; correct answer none).

Decoy / control items.

  1. A cargo hold ship had 500 crates of oranges. At the ship’s first stop, 100 crates were unloaded. At the second stop, 200 more were unloaded. How many crates or oranges were left after the second stop? (answer 200 crates)
  1. Sara, Emma, and Sophia embark on a river trip. Each of them brings one supply item for the trip: a kayak, a cooler of sandwiches, and a bag of apples. Sara brought the apples and Emma didn’t bring anything edible. What did Sophia bring? (answer cooler of sandwiches)
  1. An expedition on a mountain climbing trip was traveling with eleven horse packs. Each horse can carry only three packs. How many horses does the expedition need?(answer 4 horses)
  1. A mechanic shop had five silver cars, two red cars, and one blue car in the garage. During the day, three silver cars and one red car were picked up, and one black car was dropped off. How many silver cars were in the garage at the end of the day?(answer two silver cars)  

2-items used for boosting in Shtulman & McCallum (2014).

  1. A house contains a living room and a den that are perfectly square. The living room has 4 times the square footage of the den. If the walls in the den are 10 feet long, how long are the walls in the living room? (Intuitive answer 40; correct answer 20)
  1. A store owner reduced the price of a $100 pair of shoes by another 10 percent. How much do the shoes cost now? (Intuitive answer 80; correct answer 81)

Baron et al., (2015)

Arithmetic items with lures.

  1. If it takes 2 nurses 2 minutes to measure the blood pressure of 2 patients, how long would it take 200 nurses to measure the blood pressure of 200 patients?
  1. Soup and salad cost $5.50 in total. The soup costs a dollar more than the salad. How much does the salad cost?
  1. Sally is making sun tea. Every hour, the concentration of the tea doubles. IF it takes 6 hours for the tea to be ready, how long would it take for the tea to reach half of the final concentration? (Finucane & Gullion, 2010)

Other items.

  1. Jack is looking at Anne but Anne is looking George. Jack is married but George is not. Is a married person looking at an unmarried person? a. Yes b. No   c. Cannot be determined (Toplak & Stanovich, 2002)
  1. Ann’s father has a total of five daughters: Lala, Lele, Lili, Lolo and__. What is the name of the fifth daughter?
  1. On the side of a boat hangs a ladder with six rungs. Each rung is one foot from the next one, and the bottom rung is resting on the surface of the water. The tide rises at a rate of one foot an hour. How long will it take the water to reach the top rung? a. 5 hours b. 6 hours c. never.

Primi et al., (2015) Cognitive reflection test – long scale.

  1. If three elves can wrap three toys in an hour, how many elves are needed to wrap six toys in 2 hours? (Intuitive answer 6 elves: correct answer 3 elves)
  1. In an athletics team, tall members are three times more likely to win a medal than short members. This year the team had won 60 medals so far. How many of these have been won by short athletes? (Intuitive answer 20 medals; correct answer 15 medals)
  1. If you flipped a fair coin three times, what is the probability that it would land ‘Heads’ at least once? _____ percent
  1. A car and a bus are on a collision course, driving toward each other. The car is going 70 miles an hour. The bus is going 80 miles an hour. How far apart are they one minute before they collide? ___ miles
  1. Ellen and Kim are running around a track. They run equally fast but Ellen started later. When Ellen has run 5 laps, Kim has run 15 laps. When Ellen had run 30 laps, how many has Kim run? ___ laps
  1. An ice cream vendor sells 2/3 of her stock of ice creams on sunny days and 1/3 of her stock on cloudy days. Yesterday, it was a sunny day, and she sold 300 ice creams. Today is a cloudy day. How many can she expect to sell?
  1. In a class, there are 42 children. There are 12 more girls than boys. How many girls are there in the class?

Ackerman (2014) items – translated from Hebrew

  1. A frog fell into a hole 30 meters deep. Every day it climbs up 3 m, but during the night it slides 2 m back down. How many days will it take the frog to climb out of the hole?(Intuitive answer 30 days; correct answer 28 days)
  1. Apple mash is comprised of 99% water and 1% apple solids. I left 100 kg mash in the sun and some of the water evaporated. Now the water is 98% of the mash. What is the mash weight? (Intuitive answer 99; correct answer 50)
  1. If a test to detect a disease whose prevalence is 1/1000 has a false positive rate of 5% what is the chance that a person found to have a positive result actually has the disease, assuming that you know nothing about the person’s signs or symptoms?(Intuitive answer 95; correct answer 2)
  1. Every day, a bakery sells 400 cookies. When the manager is not there, 20% of the cookies made that day are eaten by the staff. How many additional cookies should be made on the manager’s day off to ensure that 400 cookies can be sold? (Intuitive answers 80, 500; correct answers 100)
  1. Steve was standing in a long line. To amuse himself he counted the people waiting, and saw that he stood 38th from the beginning and 56th from the end of the line. How many people are stood in the line? (Intuitive answers 94 or 92; correct answers 93)
  1. Ants are walking in a line. A bad-mannered ant cuts in front of the ant waling second. What is the rude ant’s place in the line? (Intuitive answer 1st; correct answers 2nd)

Tremoliere & De Neys (2014) modified congruent and incongruent versions of the bat-and-ball.

Incongruent

  1. A Ferrari and a Ford together cost $190,000. The Ferrari costs $100,000 more than the Ford. How much does the Ford cost? (Intuitive answer $90,000: correct answer $45,000)

Congruent

  1. A Rolls-Royce and a Ferrari together cost $190,000. The Rolls-Royce costs $100,000 more than the Ferrari. How much does the Ferrari cost? (No intuitive answer; correct answer $45,000)

De Neys et al., (2013) control version of the bat-and-ball

  1. A magazine and a banana together cost $2.90. The magazine costs $2. How much does the banana cost? (No intuitive answer; correct answer 90 cents)

Oldrati (2016) booster items.

  1. A rope ladder hangs over the side of a boat with the bottom rung on the surface of the water. The rope ladder has 6 runs that are 30 cm apart from each other. The tide rises 70 cm. How many rungs will stick out of the water at high tide? (Intuitive answer 3 rungs; correct answer 6 rungs)
  1. There are 12 one-cent stamps in a dozen. How many two-cent stamps are there in a dozen? (Intuitive answer 6 stamps; correct answer 12 stamps)
  1. A farmer makes 4 piles of hay in one corner of a field and other 5 piles in another corner. If he merges them how many piles will he have? (Intuitive answer 9 piles; correct answer 1 pile)
  1. You are participating in a run. You overtake the second runner in the last meters before the finish line. In what position did you finish? (Intuitive answer first position; correct answer second position)
  1. 25 soldiers are standing in a row 3 m from each other. How long is the row? (Intuitive answer 75 m; correct answer 72 m)
  1. A snail starts climbing up a five-meter-high wall in the morning. During day it climbs 2 m and during the night it slips back 1 m. How many days will it take the snail to reach the top of the wall? (Intuitive answer 5 days; correct answer 4 days)
  1. A brick weighs 1 kg plus half a brick. How much does half a brick weigh? (Intuitive answer .5 kg; correct answer 1 kg)
  1. There are 5 white and 5 black socks in Franco’s drawer. Franco’s room is in the dark. How many socks should Franco take out of the drawer to be sure that he gets a matching pair? (Intuitive answer It cannot be determined; correct answer 3 socks)
  1. You go to bed at eight. You set your old analogue alarm clock to wake you up at nine. How many hours of sleep will you get? (Intuitive answer 13 h; correct answer 1 h)
  1. One month has 28 days. How man of the 11 months left have 30 days? (Intuitive answer 4 months; correct answer 11 months)

 References

If you use any of these please reference the original source paper (cited in brackets above the items) and if possible this blog.

In APA format this blog is cited as…

Edgcumbe, D (2017). Cognitive reflection and cognitive reflection-like items [Blog post]. Retrieved from https://absolutedecisionsblog.wordpress.com/2017/01/08/cognitive-reflection-and-cognitive-reflection-like-items/

 

Frederick, S. (2005). Cognitive reflection and decision making. The Journal of Economic Perspectives. 19(4), 25-42.

Toplak, M., West, R. & Stanovich, K. (2014). Assessing miserly information processing: An expansion of the Cognitive Reflection Test. Thinking & Reasoning, 20(2), 147-168.

Thomson, K. & Oppenheimer D. (2016). Investigating an alternate form of the cognitive reflection test. Judgment and Decision Making, 11(1), 99.

Shtulman, A. & McCallum, K. (2014). Cognitive reflection predicts science understanding. In Proceedings of the 35th Annual Conference of Cognitive Science Society (pp. 2937-2942).

Baron, J., Scott, S., Fincher, K. & Metz, S. (2015). Why does the Cognitive Reflection Test (sometimes) predict utilitarian moral judgment (and other things)? Journal of Applied Research in Memory and Cognition, 4(3), 265-284.

Toplak, M. & Stanovich, K. (2002). The domain specificity and generality of disjunctive reasoning: Searching for a generalizable critical thinking skills. Journal of Educational Psychology, 94(1), 197.

Primi, C., Morsanyi, K., Chiesi, F., Donati, M. & Hamilton, J. (2015). The development and testing of a new version of the cognitive reflection test applying item response theory (IRT). Journal of Behavioral Decision Making,

Finucane, M. & Gullion, C. (2010). Developing a tool for measuring the decision-making competence of older adults. Psychology and aging, 25(2), 271.

Ackerman, R. (2014). The diminishing criterion model for metacognitive regulation of time investment. Journal of Experimental Psychology: General, 143(3), 1349.

Tremoliere, B., De Neys, W. & Bonnefon, J. (2014). The grim reasoner: Analytical reasoning under mortality salience. Thinking & Reasoning, 20(3), 333-351.

De Neys, W., Rossi, S. & Houde, O. (2013). Bats, balls, and substitution sensitivity: Cognitive misers are no happy fools. Psychonomic Bulletin & Review, 20(2), 269-273.

Oldrati, V., Patricelli, J., Colombo, B. & Antonietti, A. (2016). The role of dorsolateral prefrontal cortex in inhibition mechanism: A study on cognitive reflection test and similar through neuromodulation. Neuropsychologia, 91, 499-508.

Cognitive reflection test

The anchoring and adjustment heuristic in real estate transactions.

The anchoring and adjustment heuristic in real estate transactions.

Jack and Sally were looking forward to buying their first house. Like many of us they browsed real estate websites and searched through the real estate agent shop windows looking for that ideal first home. As Jack and Sally browsed the potential properties they kept in mind their budget. Jack made note of a few potential properties with the correct number of bedrooms, bathrooms, reception rooms and garden size whilst noting the seller’s asking price. Eventually after visiting a few properties for viewings they decided to put an offer in for one of the properties. Jack noticed the asking price saying that it was above their budget and for a moment began to lose hope. After discussing with Sally as to how much to offer for the house Sally reminded Jack that although the house was on offer for £500,000 they could in fact put in an offer below the asking price. Jack and Sally went on to offer £450,000 and after some consideration the seller agreed to the price. Jack and Sally won the property that they wanted to buy and in the process demonstrated one of the most prevalent cognitive biases in human decision-making, namely the anchoring effect.

door-keys

The anchoring effect (also called the anchoring and adjustment bias or anchoring and adjustment heuristic) is one of the cognitive biases that occurs most often when making a judgement about the quality, value or worth of an item. The effect works because when you are given a number (e.g., 1200 meters) that relates to a property of an item (the quality etc) with a question about that property you are likely to, whether knowingly or not, anchor your judgement by using the number as a reference point (i.e. the anchor). Imagine a boat tethered to a lowered anchor, the boat cannot move far from the anchor and remains within range of the length of the tether. We typically do not deviate a lot from the anchor. The anchoring effect has been observed to influence factors such as charitable giving, price valuations, fairness judgements, loyalty judgements, judgements of guilt, and prosocial motives among many other factors (Soule & Madrigal, 2015). The anchoring effect is just one of many cognitive biases that influences our judgements in a systematic and predictable fashion. It is simply easier to accept the anchor (e.g., the house seller’s asking price) and adjust closely to the anchor (e.g., £50,000 less rather than £150,000) than to make an entirely new judgement about something (e.g., the value of the house).

In the case of Jack and Sally there is a clear anchoring effect (albeit to no negative effect to the seller). Jack and Sally see the initial asking price (the anchor) and consider making offers that are close to this, they are anchored by the seller’s asking price. Of course, in the case of buying a house deviating from the asking price by too much (toward a lower price) will result in a rejected offer.

It is important to understand the anchoring effect because prices are by nature simple numeric information that can act as the anchor or reference point. Since the majority of the most agonising judgements that we must make in life revolve around pricing (e.g., buying that first house, holiday home, car or a big holiday) understanding the role of cognitive biases in decision-making is important. To avoid falling into the trap of the cognitive biases we should make ourselves aware of these biases. We are not the rational decision makers that we think we are.

anchor

One large study investigating the anchoring effect in residential home sales recorded data from 14,000 separate transactions (Bucchioneri & Minson, 2013). The researchers noted that the literature on housing economics, negotiations and auctions converge on the notion that home prices are an objective function of the property’s neighbourhood and characteristics (e.g., number of rooms, size of the house and characteristics). However, as we have seen above the judgement and decision-making literature on the anchoring effect suggest that there is a positive relationship between the listing price (asking price) and the sale price. The analysis of the 14,000 transactions found that higher asking prices are associated with higher sales prices independent of the property’s features, which is consistent with the anchoring effect. For the average property in the study overpricing by 10 to 20% lead to an increase in sales price because buyers were anchored by this higher sales price. So, whether a property has 5 large bedrooms in a desirable area of the countryside or 2 small bedrooms in a noisy part of a city asking for higher price for the 2-bedroom property (compared to the 5-bedroom property) could result in a higher sales price than the 5-bedroom property despite the larger property being initially more desirable than the smaller.

In the domain of property rentals the same study by Bucchianeri and Minson found that by adopting the same strategy of overpricing the asking rental price by 10 to 20% there was an increase in rental value of $117 to $163.

The data from transactions on house sales and rental pricing suggest that although we tend to believe that it is the characteristics of a property that determines the value of the property this is not the case. Pricing strategies are the major determiner of the value of the property. So, whether you are buying you first starter home, buying your dream family home, renting your house or looking to rent a house being aware of the anchoring effect will save you or make you more money. If you are selling your house to take full advantage of anchoring set your asking price 10-20% higher than the valuation, after all, if your property does not sell you can simply reduce the price at a later point. If like Jack and Sally you are buying your first home, to take advantage of the anchoring effect you can start by being aware that the asking price is not absolute, you can put in a lower offer if this is reject simply increase the offer by a small amount.

The finance room