The Psychology of Queuing
Why is waiting in line so horrid?
Many businesses are rightly concerned about customer disgruntlement
at waiting times. Banks, hotels, airlines know how upset the modern consumer
can become if asked to queue for even a short time. Students complain
about having to wait ‘so long’ for their essays to be marked. We have
queue rage as a function of sometimes rather minor delays. It has been
estimated that we spend four years of our life in queues
People in line at airports now tweet their frustration. There are occasional revolts of nice, normal, well-behaved people, who have simply ‘had enough’. They shout, they sing, they rush the barricades to humiliate their tormentors.
Try visiting a place where you have no choices, usually government or council offices. Or, better still, the airport at a time when many planes are coming in at the same time. You aren’t really a customer, although you may be called that. You cannot take your business elsewhere. The Fast Track is not necessarily so. And you are compelled to shuffle along like a Soviet Russian, waiting for the monopoly-run shop to deliver its meagre and uninviting product.
Products are consumed, but services are experienced in real time. Delay is often the most important factor influencing restaurant evaluation. And it is a nightmare for management, who know the cost of hiring extra hands. Expectations have changed. People take their custom elsewhere, where they get what they want: instant gratification.
Waiting is often the cause of road rage. And consider all the issues about NHS patients on the waiting list for operations, waiting times in A&E, and those who, once admitted to a hospital, spend time waiting for a bed.
The calm, good-natured, do-your-duty, take-your-turn polite queue seems a thing of the past. All those virtues such as decency, fair play and democracy seem to be fading.
There are three ways of looking at those who phlegmatically and stoically endure the long, tedious and time-wasting queuing process.
First, the orderly queue is, and always was, a myth. It is a story we told ourselves that was never true. More a product of wartime propaganda movies than any reality. We never liked queuing, pushed ahead where we could, and mumbled and grumbled the whole time.
Second, the queue is associated with dull, sheep-like drones, beaten into submission by an inefficient system. We should adopt a "customers of the world unite" manifesto, and refuse to accept this result of incompetence. It is only the foolish who tolerate it.
Third, we should be amazingly proud of this quiet, orderly and dignified display of one of our great virtues. Too many people suffer from hurry sickness, dysfunctional impulsivity and childlike impatience and could learn a great deal from the fair play and equality of learning to wait. After all, postponement of gratification is one of the signs of maturity.
To the "modern" person, waiting can be described quite simply as aggravating, demoralising, and frustrating. It causes tension and is expensive.
There is a surprising big academic literature on the psychology of queuing. For instance Fagundes (2016) suggested the queue offer many rich insights into the social norms and human behaviour. There are social rules about queuing though these differ from culture to culture as do how people react to those who break the rules. He notes:
“There is little evidence that we are all selfish homines economici; rather, we tend to be strong reciprocators, inclined to cooperate when we see others doing so, provided that we do not see anyone free riding at the expense of our generosity. And queue norms and practices dovetail neatly with both the collaborative and punishing sides of our inclination toward reciprocity. Physical waiting lines send a clear and strong signal about the prevalence of mass cooperation. The sight of a thousand or even a few people waiting patiently in line communicates the essence of human cooperation (and tends to understate defection) in a way designed to trigger others' instinct for reciprocity. Moreover, the outsized rage people exhibit at breaches of queue protocol—especially the odious practice of line cutting—provides an effective disincentive for the small but problematic percentage of the population that is inclined not to cooperate. These non co-operators threaten to unravel informal systems of order by creating a widespread perception of free riding. However, the very real chance that they will meet with shouts, fists, or worse keeps even the relative minority of committed line-cutters at bay and preserves the stability of queues. As the conclusion to this article remarks, the mundane character of the line belies its richness as a source of insight for life and law alike.”(p2-3)
Waiting Frustration
People who study waiting behaviour have come up with certain laws and observations that have, of course, consequences.
1. Occupied Time feels shorter, so give people something to do or distract their attention. Make them walk round and round on maze-like paths. Give them television to watch, music to listen to. The worst is letting them grow surly and listless; they then mumble to each other about starting a revolt.
2. Uncertainty makes waiting seem longer. Tell them (roughly) how long they have to wait and people are more accepting of the delay. The tube and the buses have twigged this. The guestimations need not be accurate; precision does not matter. Information takes away the ambiguity and gives a person the confidence that the system is still running.
3. Anxiety makes the wait seem longer. “Will it ever come; will I make my next meeting; will I make the connection?” So explanation and reassurance works. Again, music might help. Too-frequent apologies don’t. Best to be the reassuring parent, as when junior says “Daddy, Daddy, are we nearly there yet?” And miles from your destination and profoundly lost, you confidently proclaim, “Nearly, darling, almost there!”
4. Unanticipated and Unexplained Waits are worse. Some organisations have twigged the explanation bit. Your train/flight is late (and we profoundly apologise) due to the late arrival of the other train/plane. Yes, but why was that? The guard did not pitch up; the points failed at Swindon; there were tropical storms over the Congo. Best appeal to "Act-of-God” explanations, which suggest possible danger.
5. Unfair Waits are much more aggravating than Equitable Waits. Nothing is worse than seeing someone semi-legitimately avoid the queue. The Fast Trackers who buy their way out; the cabin crew who get some privileged exit; the locals who have twice as many people manning the desks as the aliens. The spirit of "all in it together", "equal suffering" helps.
6. Solo Waits seem longer than Group or Social Waits. This is a difficult one, but explains the idea of a waiting room or one of those holding pens at airports.
There are fascinating studies of what people do in queues to reduce their frustration (Pamies, Ryan, & Valverde, 2016).All sorts of factors influence how people react to queues. For instance in a study of how people reacted at transportation stops found:
“Results from the survey and video observations show that the reported wait time on average is about 1.21 times longer than the observed wait time. Regression analysis was employed to explain the variation in riders’ reported waiting time as a function of their objectively observed waiting time, as well as station and stop amenities, weather, time of the day, personal demographics, and trip characteristics. Based on the regression results, most waits at stops with no amenities are perceived at least 1.3 times as long as they actually are. Basic amenities including benches and shelters significantly reduce perceived waiting times. Women waiting for more than 10min in perceived insecure surroundings report waits as dramatically longer than they really are, and longer than do men in the same situation. The authors recommend a focus on providing basic amenities at stations and stops as broadly as possible in transit systems, and a particular focus on stops on low-frequency routes and in less safe areas for security measures.”(p. 251)
Queue jumping
Stanley Milgram, famous for his research on obedience studied queuing many years ago. In one study his student assistants went to different queues in betting shops, railway stations and elsewhere. They were told to do the following:
Enter queue at between the third and fourth person.
Say in a neutral tone: “Excuse me, I’d like to get in here.”
Step into line and face forward.
Only leave the queue when someone admonished them or after 1 minute, whichever was sooner.
Surprisingly only 10% of occasions were queue-jumpers physically ejected from the line. If fact people did very little—dirty looks, tut-tutting, shrugging shoulders. And this was New York. In further studies he found that doubling the number of jumpers doubled the rate of objections. So people are prepared to put up with the odd deviant but not if there are more. He argued from his findings:
People in line are not really a group. Group formation is difficult when people are stood one behind the other, all facing in the same direction. Consequently social order is weak.
It is costly to deal with deviants. Challenging queue-jumpers could mean losing your own place in the line.
We can cope with a few deviants. Social systems have to tolerate some deviance otherwise they may quickly break down, i.e. a fight may start and everyone is delayed while it is sorted out
What is the optimum length of time to queue for before we get itchy feet?
To understand when we would get itchy feet, it is important to understand why itchy feet occur. When we are in need of a service—e.g. buying your shopping, posting a letter, or using toilet—we appreciate that there is a psychological cost we may incur in the process of obtaining that service. Research into the psychology of queuing has assessed the psychological costs that consumers are willing to expend while waiting, and how to reduce them.
In situations where the service is non-essential, the consumer will make trade-off judgements whilst they are in the queue (Carmon Shanthikumar, & Carmon, 1995). Consumers will engage in an economic analysis of the opportunity cost of waiting (the psychological cost that could be used elsewhere; Becker, 1965) and the principles of marginal decision-making (Frank, 1994). How much additional psychological cost—e.g. waiting time, hassle, financial cost of moving through the queue quicker—is the consumer willing to expend in order to complete the queue situation? Consumers will decide to ‘renege’ and abandon the queue if the additional cost needed exceeds the threshold of what the consumer is will to ‘pay’.
These thresholds will vary depending on certain situational factors of the queue The optimal length of time we are willing to wait depends on several factors: the absolute time the consumer has been waiting; the number of people ahead of us in the queue; and the number of people behind us in the queue.
Time Spent in the Queue
The optimal amount of absolute time a consumer is willing to spend in a queue before reneging varies depending on the service they are waiting for. For instance, the average time people will queue for an ATM before reneging is 3 minutes (Zhou & Soman, 2003), whilst people will queue for 59 minutes on average for a Paul Gaugin art exhibit (Meyer, 1994). What is important to consider with queuing is how long the consumer expects and perceives to have been waiting for. The longer a consumer queues past the expected waiting time and greater the psychological cost of remaining in the queue, the more likely they are to renege.
Disneyland and Disney World have been experimenting with queuing and customer satisfaction for decades. They found to alter how long a customer is willing to wait, it is most effective to influence the expectations of the customer. Disney resorts will always generously overestimate the waiting times for their attractions, meaning customers come away grateful for getting through the queue in a much shorter time to what they expected.
Consumers have been found to be consistently inaccurate at estimating how long they think they have been waiting for. One study found that consumers retroactively estimate they waited 78% longer than they actually have (Katz et al., 1991). However, wait estimations dropped significantly 22% when consumers could see an electronic clock that gave an estimate for how long their wait would be.
Meyer (1994) ran a field observation to investigate how the subjective importance of reaching the end of the queue impacted how long a person was willing to wait. Over 6 days, researchers observed a naturally forming queue for a temporary art exhibit. The researchers measured how long the queuers had been waiting and interviewed them at fixed distances from the front of the queue (8, 16, 32, 56, 88, and 132m).
Meyer found that the importance the queuer placed on the exhibit (i.e. whether they ranked the artist as their favourite of that movement/period) influenced how long they were expected and willing to wait. High-importance queuers estimated there to be fewer people in front of them in the queue, to be a closer distance to the front of the queue, and expected to wait in line for less time. For low-importance queuers, the longer they spent queuing and further back they were, the more displeased and frustrated they were.
Previous research has demonstrated how mood (e.g. frustration, boredom, anxiety) predicts a greater likelihood of abandoning a queue (Janakirman, Meyer, & Hoyer, 2011). As time had no effect on the mood of high-importance queuers, it demonstrates the significance of goal-importance on reneging from a queue—the more important it is to get to the end of a queue, the less affected you are by queuing and the longer you are willing to wait.
Finally, consumers are also susceptible to the sunk-cost fallacy when waiting in line (Garland & Newport, 1991). As such, the longer a consumer has been queuing the amount of time they are willing to wait also increases (Katz et al., 1991). Consumers will feel that the psychological cost of waiting further in the queue is reasonable given the amount of time that they have already waited, despite having inaccurate perceptions of how long they have waited and how long it might take to reach the end of the queue.
Number of People in the Queue
A key factor in deciding whether to remain or renege from a queue depends upon the number of people who are ahead of us in the queue (Carmon & Kahneman, 1996). Evidence has shown that when there are more people ahead of us in the queue, we are more likely to renege (Zhou & Soman, 2003). Consumers will estimate how long they expect to be waiting by the number of people ahead of them (Meyer, 1994). When this number appears too high, consumers will either renege or refuse to join the queue in the first place.
As with the number of people in the queue ahead of us, the number behind us also influences our likelihood of reneging from the queue. This factor is of particular interest because, from a purely cost/benefit analysis, the number of people behind you in the queue has no objective impact on your additional waiting or position from the front. Yet, the evidence suggests that it does have a significant effect.
Consumers will make social comparisons with others behind them, deriving some form of comfort from looking behind and realising they do not have to wait as long as them (Zhou & Soman, 2003). A great deal of research suggests that when people are feeling anxious and unhappy about their current status, downward comparisons (looking at those behind you) are more likely to occur (Wills, 1981) over upward comparisons (looking at those ahead). As a result, individuals will feel more positive and less negative affect when there more people behind them in the queue (Zhou & Soman, 2003).
Zhou and Soman (2003) demonstrated the importance of people behind you not only in altering mood, but also in reducing reneging behaviour. In a series of experimental and naturalistic studies, it was found that an increased number of people behind significantly reduced the likelihood of reneging (after controlling for the number of people ahead in the queue).
However, these effects were only noted in linear queues, and not in ‘take a ticket’ style queuing. "Take a ticket"-style queuing reduces the ability for consumers to make social comparisons to where they are in the queue. People behind also had less impact on positive and negative affect in ‘take a ticket’ queues.
The number of people behind has a significant impact on how long it takes before queuers get itchy feet and renege. A longer queue behind us causes two psychological changes in the queuer: firstly, it acts as social validation that the queue is worth waiting for (Cialdini, 1985); secondly, it leads the consumer to expect a longer a queue if they renege and re-join at a later point in time (Zhou & Soman, 2003). These two effects cause consumers to become more likely to wait in queues longer.
What is the Ideal Amount of Personal Space?
Queues are social in nature. Most queues involve the strategic and logical positioning of people who are trying to achieve the same goal in physical proximity of each other. The question is whether the amount of personal space we are given impacts our queuing experience.
There is a lot of research on the psychology of personal space. There are social norms about the interpersonal distance that should be maintained in social environments. For instance, Fry and Wills (1967) tested this concept in queues by sending ‘invader-children’ to stand less than 6 inches behind adults in line for the theatre. The researchers found that the reactions of adults differed depending on the age of the child: 5-year olds were elicited a positive response, whereas 10-year olds were greeted with negative responses. As adults felt that the 10-year old was old enough to understand to spatial patterns and norms, the direct violation of these norms elicited frustration and annoyance to queuers.
Personal comfort when waiting is also affected by the environmental space provided. One study experimented with the level of discomfort displayed in people waiting at the California State Department of Motor Vehicles. When the room was partitioned (ropes and standards; solid wooden partitions), queuers displayed greater discomfort and agitation than when the room had minimal or no partitioning (Stokols, Smith & Prostor, 1975). As queuers felt more crowded, their discomfort grew. This evidence is further supported by the distinction that people make between pre-process and in-process crowding. For instance, people are experience high levels of negative affect with crowding in queues, whilst being crowded or physically close to others in a concert is seen positively (Mowen et al., 2003).
Proximity to others has also been shown to influence the evaluations we make of queues. Schachter (1959) found that the closer we are physically to others, the easier it is for us to make social comparisons. We have discussed how queuers will make upwards and downwards social comparisons when deciding whether to renege from a queue. When we are stood closer to others, these evaluations are made quicker and with greater impact, affecting our chances of leaving the queue.
What is the ideal queuing environment?
1. Retail Distractions
Katz et al. (1991) tried to influence consumers’ perceptions and emotional response to waiting in line by providing distractions. The first was a news board, displaying live news bulletins. Whilst the news board did not reduce the amount of time consumers felt they had waited, it did make it more palatable. Consumers who spent longer in the queue (4-12 minutes) were more satisfied with the customer service they received, and rated their queuing experience as significantly more interesting, entertaining and relaxing than when no news board was present. The second distraction was an electronic clock that provided estimates of how long the consumers would have to wait. Whilst the electronic clock significantly decreased consumers perceived waiting time, it did not significantly improve the consumers’ level of stress or satisfaction with the customer service. This is because the clock provided consumers with more awareness of how much time was wasted standing in line. The clock also was noted to increase frustration when consumers were not able to ‘beat the clock’.
Borges et al. (2015) investigated the effect of having a retail distractor (e.g. TV for consumers to watch) on the perceived waiting times and waiting satisfaction. Customers queuing in drugstores and restaurants perceived their waiting time to be significantly shorter with a distractor present, even though objective wait time was the same. What was being played on the distractor also had a marginal impact; when images were congruent with the retail setting consumers reported shorter perceived waiting times (e.g. videos of food being made in a restaurant vs. the news). Customers also were significantly more satisfied with their queuing experience with a retail distractor, with congruent material having a greater effect than incongruent material.
2. Music
There have been several studies that have demonstrated the impact of music on queuing behaviour. Music causes reactions to occur in our limbic system; the emotional centre of the brain (Gard, 1997). As such, music influences both the mood of the queuer as well as their perception of time (Tom et al., 1997; Antonides et al., 2002).
The question becomes what type of music is best for the ideal queuing environment. Bruner’s (1990) review of the effect of music on mood revealed that fast music was associated with positive emotions (happiness and excitement) whilst slow music was associated with feelings of sadness. Familiar music (e.g. contemporary pop music) has been recommended as the most appropriate for waiting situations, since unfamiliar music has been noted to create the perception that time is slowing down (Yalch & Spangenberg, 1988; 2000).
McDonnell’s (2007) experimentally investigated the effect of music on waiting frustration and concern. McDonnell (2007) noted that introducing familiar music (a contemporary radio station as background sound) significantly reduced negative emotions and increased positive evaluations of customer service at banks. Furthermore, ‘likable’ music has been found to improve both mood and reduce the perceived annoyance of waiting (Cameron et al., 2003).
This effect remains influential in high-anxiety waiting situations. Fenko & Loock (2014) investigated the role of music on patient anxiety when waiting for plastic surgery. The results indicated that music significantly reduced patient anxiety compared to the absence of music, with instrumental and natural sounds being the most anxiety reducing compared to classical and modern.
3. Scent
Studies by Hirsch and Gay (1991) found that certain scents, even in fairly low concentrations can affect peoples' moods. Concentrations so weak that they are below the threshold of consciousness still affect peoples' moods subconsciously.
McDonnell (2007) used scent as an environmental variable to affect the mood of customers waiting in line. McDonnell used a scent diffuser in the corner of the room to disperse a blended fragrance of lavender, with sagebrush and nutmeg (which has previously been found to reduce anger; Burns et al., 2002). McDonnell’s investigation found that service evaluation significantly improved when scent is introduced compared to no intervention. Whilst scent was noted to reduce the level of frustration reported by the customer, the effect was not statistically significant.
However, the effect of introducing ambient scent was found to significantly reduce patient anxiety when waiting for plastic surgery (Fenko & Loock, 2014). In particular, scents such as vanilla and lavender were more effective in reducing wait anxiety than scents of mango, lemon, magnolia, and orange.
However, Fenko and Loock (2014) found that there can be ‘too much of a good thing’ when trying to create an ambient and anxiety-reducing waiting environment. In their study, they found that the combination of music and scent had no effect on relaxing patients. When there is ‘too much going on’ in the waiting environment, this heightens the waiter’s arousal and causes them to become more anxious and aware of how long they have been waiting.
4. Colour
Whilst no study has directly looked at the impact of colour on queuing conditions, several papers have extrapolated the possible effects of colour based on similar evidence (e.g. Baker & Cameron, 1996).
Colour researchers generally have categorized colours as being either warm (e.g., red, orange, yellow) or cool (e.g., blue, green). In experimental settings, the effect of the colour has been investigated with perceived time duration (Shibaski & Masatka, 2014). The results showed that the perceived duration of warm colours (red) was longer than was that of cool colours (blue). In real-life settings, it has been observed that the passage of time tends to be overestimated in a room painted with warm colours and underestimated in a cool-coloured room (National Aeronautics and Space Administration, Johnson Spacecraft Center 1976).
It is therefore hypothesised that warm colours (defined in terms of hue, brightness, and saturation) are less appropriate for waiting environments due to increasing negative affect, stress, and perceived waiting time (Baker & Cameron, 1996).
5. Lighting
As with colour, there have not been any direct studies looking at the effect of lighting on queuing experience. However, research has demonstrated a link between room lighting and mood. Light level has been found to predict the comfort experienced by individuals, with increased (decreased) comfort in relatively low (high) levels of light (Hopkinson, Petherbridge, and Longmore 1966). In experimental conditions, participants have overestimated time duration under conditions of higher illumination compared to that under lower illumination (Delay and Richardson 1981) and estimated longer time duration under higher intensity lights compared to that under lower intensity lights (Goldstone, Lahmon, and Sechzer 1978). This suggests that high light levels will cause lower waiting satisfaction due to decreased comfort and an increase in the perceived passage of time.
6. Employee Visibility
The patience of queuers has also been known to fluctuate depending on the visibility of employees. In particular, whether the queuers perceive the employees to be working hard to serve all those who are queuing. Studies have shown that customer satisfaction in banks is strongly predicted by whether queuers believed all tellers to be doing their best to serve all customers (Clemmer & Schneider, 1989). Furthermore, queuers become more frustrated when service providers are not working hard (e.g. talking with their coworkers) as this information is used to predict a longer wait (Larson, 1987).
Social Norms in Queuing
Research into queuing phenomenon has indicated that it is a social system with rules, norms, and obligations (e.g. Schmitt et al., 1992). Anger, frustration, and upset occur when these norms are violated. In this section, we discuss the research on different ‘no nos’ for British queuers.
Queue Jumping and Social Justice
One of the most well known and researched ‘no no’ in British queuing is when someone cuts ahead of us in the line. Illegitimate intrusion sparks outrage as it appears to violate the socially accepted norms of the queuing environment. It usually sparks a chorus of tutting, eye-rolling, and groaning in the direction of the queue jumper.
Traditionally social justice in queues is defined and measured with adherence to the ‘first in, first out’ principle (Larson, 1987); that because I was here first, I get to be served first. First-order justice is maintained when the first in, first out principle is upheld. Second-order justice, however, states that people should wait an equal amount of time to you, regardless of its effect on your waiting. For instance, at a busy restaurant servers may decide to open a new seating area to accommodate. This means people who have waited longer (those at the front of the queue) may be served at the same time as those who have just arrived. Whilst those who arrived first are still seated first, evidence demonstrates that second-order justice violations still decrease positive affect and increase negative affect (Zhou & Soman, 2008).
Despite this being something most people (especially British queuers) are outraged by, the response can often be very different. In a classic study by Stanley Milgram and his colleagues (1986), researchers cut into 129 queues at in various locations (including train stations and betting parlours) by simply saying “Excuse me, I’d like to get in there”. In only 10% of cases did the queuer physically not allow the experimenter to cut in line. For roughly 50% of cases the queuer reacted (with a mean look, tutting, an eye-roll, or verbal objections) but allowed the researcher to cut in. However, when Milgram upped the number of queue cutters to two people instead of one, the rate of objection increased to 91%.
Ellen Langer (1978) also found that the type of excuse offered by a queue-jumper could change how successful they are. When cutting in line to use a photocopier, Langer presented three types of excuse. In the first, experimenters offer the Request Only excuse of “Excuse me, I have 5 copies to make. May I use the Xerox machine?”, resulting in 60% allowing her to go ahead. The second excuse presented Placebo Information by stating “Excuse me, I have 5 copies to make. May I use the Xerox machine because I need to make copies?”resulting in 93% allowing her to go ahead. The final excuse was Real Information, where experimenters asked “Excuse me, I have 5 copies to make. Make I use the Xerox machine because I am in a rush?”, resulting in 94% allowing her to go ahead. The results suggest that when you are making a small request (i.e. only 5 pages), it does not matter what your excuse is as long as you make one. However, when the request is bigger (e.g. needing to make 20 copies), excuses start to matter. Presenting Request Only (20%) or Placebo Information (24%) excuses have similarly unsuccessful results, whereas presenting a Real Information excuse (42%) causes people to be more obliging.
Helwig-Larsen & LoMonaco (2008) examined the effects of cutting in line with fans queuing for a U2 concert. Queuers reacted more negatively when the intruder was a stranger than a friend of another queuer. The effects were equivalent for when the cutting in occurred in front or behind them, and was not altered by queue position (30th vs. 175th). Fan commitment also moderated the level of upset, with more committed fans experiencing greater upset than casual fans. However, if the queue-cutter is a friend of another queuer, upset is significantly reduced if the queuer is informed beforehand of a late-arriving (and thus queue-jumping) friend.
Conclusion
Understanding the Psychology of Queuing is clearly important for many organisations. It is complex social behaviour with its own implicit and explicit rules. Many organisations have to make a decision about employing an optimal number of staff to deal with unpredictable changes in customer demand. They know that most people do not like to wait in lines and therefore attempt to make the experience better for their customers. The “science” of queuing reviewed above gives various recommendations of what to do.
People in line at airports now tweet their frustration. There are occasional revolts of nice, normal, well-behaved people, who have simply ‘had enough’. They shout, they sing, they rush the barricades to humiliate their tormentors.
Try visiting a place where you have no choices, usually government or council offices. Or, better still, the airport at a time when many planes are coming in at the same time. You aren’t really a customer, although you may be called that. You cannot take your business elsewhere. The Fast Track is not necessarily so. And you are compelled to shuffle along like a Soviet Russian, waiting for the monopoly-run shop to deliver its meagre and uninviting product.
Products are consumed, but services are experienced in real time. Delay is often the most important factor influencing restaurant evaluation. And it is a nightmare for management, who know the cost of hiring extra hands. Expectations have changed. People take their custom elsewhere, where they get what they want: instant gratification.
Waiting is often the cause of road rage. And consider all the issues about NHS patients on the waiting list for operations, waiting times in A&E, and those who, once admitted to a hospital, spend time waiting for a bed.
The calm, good-natured, do-your-duty, take-your-turn polite queue seems a thing of the past. All those virtues such as decency, fair play and democracy seem to be fading.
There are three ways of looking at those who phlegmatically and stoically endure the long, tedious and time-wasting queuing process.
First, the orderly queue is, and always was, a myth. It is a story we told ourselves that was never true. More a product of wartime propaganda movies than any reality. We never liked queuing, pushed ahead where we could, and mumbled and grumbled the whole time.
Second, the queue is associated with dull, sheep-like drones, beaten into submission by an inefficient system. We should adopt a "customers of the world unite" manifesto, and refuse to accept this result of incompetence. It is only the foolish who tolerate it.
Third, we should be amazingly proud of this quiet, orderly and dignified display of one of our great virtues. Too many people suffer from hurry sickness, dysfunctional impulsivity and childlike impatience and could learn a great deal from the fair play and equality of learning to wait. After all, postponement of gratification is one of the signs of maturity.
To the "modern" person, waiting can be described quite simply as aggravating, demoralising, and frustrating. It causes tension and is expensive.
There is a surprising big academic literature on the psychology of queuing. For instance Fagundes (2016) suggested the queue offer many rich insights into the social norms and human behaviour. There are social rules about queuing though these differ from culture to culture as do how people react to those who break the rules. He notes:
“There is little evidence that we are all selfish homines economici; rather, we tend to be strong reciprocators, inclined to cooperate when we see others doing so, provided that we do not see anyone free riding at the expense of our generosity. And queue norms and practices dovetail neatly with both the collaborative and punishing sides of our inclination toward reciprocity. Physical waiting lines send a clear and strong signal about the prevalence of mass cooperation. The sight of a thousand or even a few people waiting patiently in line communicates the essence of human cooperation (and tends to understate defection) in a way designed to trigger others' instinct for reciprocity. Moreover, the outsized rage people exhibit at breaches of queue protocol—especially the odious practice of line cutting—provides an effective disincentive for the small but problematic percentage of the population that is inclined not to cooperate. These non co-operators threaten to unravel informal systems of order by creating a widespread perception of free riding. However, the very real chance that they will meet with shouts, fists, or worse keeps even the relative minority of committed line-cutters at bay and preserves the stability of queues. As the conclusion to this article remarks, the mundane character of the line belies its richness as a source of insight for life and law alike.”(p2-3)
Waiting Frustration
People who study waiting behaviour have come up with certain laws and observations that have, of course, consequences.
1. Occupied Time feels shorter, so give people something to do or distract their attention. Make them walk round and round on maze-like paths. Give them television to watch, music to listen to. The worst is letting them grow surly and listless; they then mumble to each other about starting a revolt.
2. Uncertainty makes waiting seem longer. Tell them (roughly) how long they have to wait and people are more accepting of the delay. The tube and the buses have twigged this. The guestimations need not be accurate; precision does not matter. Information takes away the ambiguity and gives a person the confidence that the system is still running.
3. Anxiety makes the wait seem longer. “Will it ever come; will I make my next meeting; will I make the connection?” So explanation and reassurance works. Again, music might help. Too-frequent apologies don’t. Best to be the reassuring parent, as when junior says “Daddy, Daddy, are we nearly there yet?” And miles from your destination and profoundly lost, you confidently proclaim, “Nearly, darling, almost there!”
4. Unanticipated and Unexplained Waits are worse. Some organisations have twigged the explanation bit. Your train/flight is late (and we profoundly apologise) due to the late arrival of the other train/plane. Yes, but why was that? The guard did not pitch up; the points failed at Swindon; there were tropical storms over the Congo. Best appeal to "Act-of-God” explanations, which suggest possible danger.
5. Unfair Waits are much more aggravating than Equitable Waits. Nothing is worse than seeing someone semi-legitimately avoid the queue. The Fast Trackers who buy their way out; the cabin crew who get some privileged exit; the locals who have twice as many people manning the desks as the aliens. The spirit of "all in it together", "equal suffering" helps.
6. Solo Waits seem longer than Group or Social Waits. This is a difficult one, but explains the idea of a waiting room or one of those holding pens at airports.
There are fascinating studies of what people do in queues to reduce their frustration (Pamies, Ryan, & Valverde, 2016).All sorts of factors influence how people react to queues. For instance in a study of how people reacted at transportation stops found:
“Results from the survey and video observations show that the reported wait time on average is about 1.21 times longer than the observed wait time. Regression analysis was employed to explain the variation in riders’ reported waiting time as a function of their objectively observed waiting time, as well as station and stop amenities, weather, time of the day, personal demographics, and trip characteristics. Based on the regression results, most waits at stops with no amenities are perceived at least 1.3 times as long as they actually are. Basic amenities including benches and shelters significantly reduce perceived waiting times. Women waiting for more than 10min in perceived insecure surroundings report waits as dramatically longer than they really are, and longer than do men in the same situation. The authors recommend a focus on providing basic amenities at stations and stops as broadly as possible in transit systems, and a particular focus on stops on low-frequency routes and in less safe areas for security measures.”(p. 251)
Queue jumping
Stanley Milgram, famous for his research on obedience studied queuing many years ago. In one study his student assistants went to different queues in betting shops, railway stations and elsewhere. They were told to do the following:
Enter queue at between the third and fourth person.
Say in a neutral tone: “Excuse me, I’d like to get in here.”
Step into line and face forward.
Only leave the queue when someone admonished them or after 1 minute, whichever was sooner.
Surprisingly only 10% of occasions were queue-jumpers physically ejected from the line. If fact people did very little—dirty looks, tut-tutting, shrugging shoulders. And this was New York. In further studies he found that doubling the number of jumpers doubled the rate of objections. So people are prepared to put up with the odd deviant but not if there are more. He argued from his findings:
People in line are not really a group. Group formation is difficult when people are stood one behind the other, all facing in the same direction. Consequently social order is weak.
It is costly to deal with deviants. Challenging queue-jumpers could mean losing your own place in the line.
We can cope with a few deviants. Social systems have to tolerate some deviance otherwise they may quickly break down, i.e. a fight may start and everyone is delayed while it is sorted out
What is the optimum length of time to queue for before we get itchy feet?
To understand when we would get itchy feet, it is important to understand why itchy feet occur. When we are in need of a service—e.g. buying your shopping, posting a letter, or using toilet—we appreciate that there is a psychological cost we may incur in the process of obtaining that service. Research into the psychology of queuing has assessed the psychological costs that consumers are willing to expend while waiting, and how to reduce them.
In situations where the service is non-essential, the consumer will make trade-off judgements whilst they are in the queue (Carmon Shanthikumar, & Carmon, 1995). Consumers will engage in an economic analysis of the opportunity cost of waiting (the psychological cost that could be used elsewhere; Becker, 1965) and the principles of marginal decision-making (Frank, 1994). How much additional psychological cost—e.g. waiting time, hassle, financial cost of moving through the queue quicker—is the consumer willing to expend in order to complete the queue situation? Consumers will decide to ‘renege’ and abandon the queue if the additional cost needed exceeds the threshold of what the consumer is will to ‘pay’.
These thresholds will vary depending on certain situational factors of the queue The optimal length of time we are willing to wait depends on several factors: the absolute time the consumer has been waiting; the number of people ahead of us in the queue; and the number of people behind us in the queue.
Time Spent in the Queue
The optimal amount of absolute time a consumer is willing to spend in a queue before reneging varies depending on the service they are waiting for. For instance, the average time people will queue for an ATM before reneging is 3 minutes (Zhou & Soman, 2003), whilst people will queue for 59 minutes on average for a Paul Gaugin art exhibit (Meyer, 1994). What is important to consider with queuing is how long the consumer expects and perceives to have been waiting for. The longer a consumer queues past the expected waiting time and greater the psychological cost of remaining in the queue, the more likely they are to renege.
Disneyland and Disney World have been experimenting with queuing and customer satisfaction for decades. They found to alter how long a customer is willing to wait, it is most effective to influence the expectations of the customer. Disney resorts will always generously overestimate the waiting times for their attractions, meaning customers come away grateful for getting through the queue in a much shorter time to what they expected.
Consumers have been found to be consistently inaccurate at estimating how long they think they have been waiting for. One study found that consumers retroactively estimate they waited 78% longer than they actually have (Katz et al., 1991). However, wait estimations dropped significantly 22% when consumers could see an electronic clock that gave an estimate for how long their wait would be.
Meyer (1994) ran a field observation to investigate how the subjective importance of reaching the end of the queue impacted how long a person was willing to wait. Over 6 days, researchers observed a naturally forming queue for a temporary art exhibit. The researchers measured how long the queuers had been waiting and interviewed them at fixed distances from the front of the queue (8, 16, 32, 56, 88, and 132m).
Meyer found that the importance the queuer placed on the exhibit (i.e. whether they ranked the artist as their favourite of that movement/period) influenced how long they were expected and willing to wait. High-importance queuers estimated there to be fewer people in front of them in the queue, to be a closer distance to the front of the queue, and expected to wait in line for less time. For low-importance queuers, the longer they spent queuing and further back they were, the more displeased and frustrated they were.
Previous research has demonstrated how mood (e.g. frustration, boredom, anxiety) predicts a greater likelihood of abandoning a queue (Janakirman, Meyer, & Hoyer, 2011). As time had no effect on the mood of high-importance queuers, it demonstrates the significance of goal-importance on reneging from a queue—the more important it is to get to the end of a queue, the less affected you are by queuing and the longer you are willing to wait.
Finally, consumers are also susceptible to the sunk-cost fallacy when waiting in line (Garland & Newport, 1991). As such, the longer a consumer has been queuing the amount of time they are willing to wait also increases (Katz et al., 1991). Consumers will feel that the psychological cost of waiting further in the queue is reasonable given the amount of time that they have already waited, despite having inaccurate perceptions of how long they have waited and how long it might take to reach the end of the queue.
Number of People in the Queue
A key factor in deciding whether to remain or renege from a queue depends upon the number of people who are ahead of us in the queue (Carmon & Kahneman, 1996). Evidence has shown that when there are more people ahead of us in the queue, we are more likely to renege (Zhou & Soman, 2003). Consumers will estimate how long they expect to be waiting by the number of people ahead of them (Meyer, 1994). When this number appears too high, consumers will either renege or refuse to join the queue in the first place.
As with the number of people in the queue ahead of us, the number behind us also influences our likelihood of reneging from the queue. This factor is of particular interest because, from a purely cost/benefit analysis, the number of people behind you in the queue has no objective impact on your additional waiting or position from the front. Yet, the evidence suggests that it does have a significant effect.
Consumers will make social comparisons with others behind them, deriving some form of comfort from looking behind and realising they do not have to wait as long as them (Zhou & Soman, 2003). A great deal of research suggests that when people are feeling anxious and unhappy about their current status, downward comparisons (looking at those behind you) are more likely to occur (Wills, 1981) over upward comparisons (looking at those ahead). As a result, individuals will feel more positive and less negative affect when there more people behind them in the queue (Zhou & Soman, 2003).
Zhou and Soman (2003) demonstrated the importance of people behind you not only in altering mood, but also in reducing reneging behaviour. In a series of experimental and naturalistic studies, it was found that an increased number of people behind significantly reduced the likelihood of reneging (after controlling for the number of people ahead in the queue).
However, these effects were only noted in linear queues, and not in ‘take a ticket’ style queuing. "Take a ticket"-style queuing reduces the ability for consumers to make social comparisons to where they are in the queue. People behind also had less impact on positive and negative affect in ‘take a ticket’ queues.
The number of people behind has a significant impact on how long it takes before queuers get itchy feet and renege. A longer queue behind us causes two psychological changes in the queuer: firstly, it acts as social validation that the queue is worth waiting for (Cialdini, 1985); secondly, it leads the consumer to expect a longer a queue if they renege and re-join at a later point in time (Zhou & Soman, 2003). These two effects cause consumers to become more likely to wait in queues longer.
What is the Ideal Amount of Personal Space?
Queues are social in nature. Most queues involve the strategic and logical positioning of people who are trying to achieve the same goal in physical proximity of each other. The question is whether the amount of personal space we are given impacts our queuing experience.
There is a lot of research on the psychology of personal space. There are social norms about the interpersonal distance that should be maintained in social environments. For instance, Fry and Wills (1967) tested this concept in queues by sending ‘invader-children’ to stand less than 6 inches behind adults in line for the theatre. The researchers found that the reactions of adults differed depending on the age of the child: 5-year olds were elicited a positive response, whereas 10-year olds were greeted with negative responses. As adults felt that the 10-year old was old enough to understand to spatial patterns and norms, the direct violation of these norms elicited frustration and annoyance to queuers.
Personal comfort when waiting is also affected by the environmental space provided. One study experimented with the level of discomfort displayed in people waiting at the California State Department of Motor Vehicles. When the room was partitioned (ropes and standards; solid wooden partitions), queuers displayed greater discomfort and agitation than when the room had minimal or no partitioning (Stokols, Smith & Prostor, 1975). As queuers felt more crowded, their discomfort grew. This evidence is further supported by the distinction that people make between pre-process and in-process crowding. For instance, people are experience high levels of negative affect with crowding in queues, whilst being crowded or physically close to others in a concert is seen positively (Mowen et al., 2003).
Proximity to others has also been shown to influence the evaluations we make of queues. Schachter (1959) found that the closer we are physically to others, the easier it is for us to make social comparisons. We have discussed how queuers will make upwards and downwards social comparisons when deciding whether to renege from a queue. When we are stood closer to others, these evaluations are made quicker and with greater impact, affecting our chances of leaving the queue.
What is the ideal queuing environment?
1. Retail Distractions
Katz et al. (1991) tried to influence consumers’ perceptions and emotional response to waiting in line by providing distractions. The first was a news board, displaying live news bulletins. Whilst the news board did not reduce the amount of time consumers felt they had waited, it did make it more palatable. Consumers who spent longer in the queue (4-12 minutes) were more satisfied with the customer service they received, and rated their queuing experience as significantly more interesting, entertaining and relaxing than when no news board was present. The second distraction was an electronic clock that provided estimates of how long the consumers would have to wait. Whilst the electronic clock significantly decreased consumers perceived waiting time, it did not significantly improve the consumers’ level of stress or satisfaction with the customer service. This is because the clock provided consumers with more awareness of how much time was wasted standing in line. The clock also was noted to increase frustration when consumers were not able to ‘beat the clock’.
Borges et al. (2015) investigated the effect of having a retail distractor (e.g. TV for consumers to watch) on the perceived waiting times and waiting satisfaction. Customers queuing in drugstores and restaurants perceived their waiting time to be significantly shorter with a distractor present, even though objective wait time was the same. What was being played on the distractor also had a marginal impact; when images were congruent with the retail setting consumers reported shorter perceived waiting times (e.g. videos of food being made in a restaurant vs. the news). Customers also were significantly more satisfied with their queuing experience with a retail distractor, with congruent material having a greater effect than incongruent material.
2. Music
There have been several studies that have demonstrated the impact of music on queuing behaviour. Music causes reactions to occur in our limbic system; the emotional centre of the brain (Gard, 1997). As such, music influences both the mood of the queuer as well as their perception of time (Tom et al., 1997; Antonides et al., 2002).
The question becomes what type of music is best for the ideal queuing environment. Bruner’s (1990) review of the effect of music on mood revealed that fast music was associated with positive emotions (happiness and excitement) whilst slow music was associated with feelings of sadness. Familiar music (e.g. contemporary pop music) has been recommended as the most appropriate for waiting situations, since unfamiliar music has been noted to create the perception that time is slowing down (Yalch & Spangenberg, 1988; 2000).
McDonnell’s (2007) experimentally investigated the effect of music on waiting frustration and concern. McDonnell (2007) noted that introducing familiar music (a contemporary radio station as background sound) significantly reduced negative emotions and increased positive evaluations of customer service at banks. Furthermore, ‘likable’ music has been found to improve both mood and reduce the perceived annoyance of waiting (Cameron et al., 2003).
This effect remains influential in high-anxiety waiting situations. Fenko & Loock (2014) investigated the role of music on patient anxiety when waiting for plastic surgery. The results indicated that music significantly reduced patient anxiety compared to the absence of music, with instrumental and natural sounds being the most anxiety reducing compared to classical and modern.
3. Scent
Studies by Hirsch and Gay (1991) found that certain scents, even in fairly low concentrations can affect peoples' moods. Concentrations so weak that they are below the threshold of consciousness still affect peoples' moods subconsciously.
McDonnell (2007) used scent as an environmental variable to affect the mood of customers waiting in line. McDonnell used a scent diffuser in the corner of the room to disperse a blended fragrance of lavender, with sagebrush and nutmeg (which has previously been found to reduce anger; Burns et al., 2002). McDonnell’s investigation found that service evaluation significantly improved when scent is introduced compared to no intervention. Whilst scent was noted to reduce the level of frustration reported by the customer, the effect was not statistically significant.
However, the effect of introducing ambient scent was found to significantly reduce patient anxiety when waiting for plastic surgery (Fenko & Loock, 2014). In particular, scents such as vanilla and lavender were more effective in reducing wait anxiety than scents of mango, lemon, magnolia, and orange.
However, Fenko and Loock (2014) found that there can be ‘too much of a good thing’ when trying to create an ambient and anxiety-reducing waiting environment. In their study, they found that the combination of music and scent had no effect on relaxing patients. When there is ‘too much going on’ in the waiting environment, this heightens the waiter’s arousal and causes them to become more anxious and aware of how long they have been waiting.
4. Colour
Whilst no study has directly looked at the impact of colour on queuing conditions, several papers have extrapolated the possible effects of colour based on similar evidence (e.g. Baker & Cameron, 1996).
Colour researchers generally have categorized colours as being either warm (e.g., red, orange, yellow) or cool (e.g., blue, green). In experimental settings, the effect of the colour has been investigated with perceived time duration (Shibaski & Masatka, 2014). The results showed that the perceived duration of warm colours (red) was longer than was that of cool colours (blue). In real-life settings, it has been observed that the passage of time tends to be overestimated in a room painted with warm colours and underestimated in a cool-coloured room (National Aeronautics and Space Administration, Johnson Spacecraft Center 1976).
It is therefore hypothesised that warm colours (defined in terms of hue, brightness, and saturation) are less appropriate for waiting environments due to increasing negative affect, stress, and perceived waiting time (Baker & Cameron, 1996).
5. Lighting
As with colour, there have not been any direct studies looking at the effect of lighting on queuing experience. However, research has demonstrated a link between room lighting and mood. Light level has been found to predict the comfort experienced by individuals, with increased (decreased) comfort in relatively low (high) levels of light (Hopkinson, Petherbridge, and Longmore 1966). In experimental conditions, participants have overestimated time duration under conditions of higher illumination compared to that under lower illumination (Delay and Richardson 1981) and estimated longer time duration under higher intensity lights compared to that under lower intensity lights (Goldstone, Lahmon, and Sechzer 1978). This suggests that high light levels will cause lower waiting satisfaction due to decreased comfort and an increase in the perceived passage of time.
6. Employee Visibility
The patience of queuers has also been known to fluctuate depending on the visibility of employees. In particular, whether the queuers perceive the employees to be working hard to serve all those who are queuing. Studies have shown that customer satisfaction in banks is strongly predicted by whether queuers believed all tellers to be doing their best to serve all customers (Clemmer & Schneider, 1989). Furthermore, queuers become more frustrated when service providers are not working hard (e.g. talking with their coworkers) as this information is used to predict a longer wait (Larson, 1987).
Social Norms in Queuing
Research into queuing phenomenon has indicated that it is a social system with rules, norms, and obligations (e.g. Schmitt et al., 1992). Anger, frustration, and upset occur when these norms are violated. In this section, we discuss the research on different ‘no nos’ for British queuers.
Queue Jumping and Social Justice
One of the most well known and researched ‘no no’ in British queuing is when someone cuts ahead of us in the line. Illegitimate intrusion sparks outrage as it appears to violate the socially accepted norms of the queuing environment. It usually sparks a chorus of tutting, eye-rolling, and groaning in the direction of the queue jumper.
Traditionally social justice in queues is defined and measured with adherence to the ‘first in, first out’ principle (Larson, 1987); that because I was here first, I get to be served first. First-order justice is maintained when the first in, first out principle is upheld. Second-order justice, however, states that people should wait an equal amount of time to you, regardless of its effect on your waiting. For instance, at a busy restaurant servers may decide to open a new seating area to accommodate. This means people who have waited longer (those at the front of the queue) may be served at the same time as those who have just arrived. Whilst those who arrived first are still seated first, evidence demonstrates that second-order justice violations still decrease positive affect and increase negative affect (Zhou & Soman, 2008).
Despite this being something most people (especially British queuers) are outraged by, the response can often be very different. In a classic study by Stanley Milgram and his colleagues (1986), researchers cut into 129 queues at in various locations (including train stations and betting parlours) by simply saying “Excuse me, I’d like to get in there”. In only 10% of cases did the queuer physically not allow the experimenter to cut in line. For roughly 50% of cases the queuer reacted (with a mean look, tutting, an eye-roll, or verbal objections) but allowed the researcher to cut in. However, when Milgram upped the number of queue cutters to two people instead of one, the rate of objection increased to 91%.
Ellen Langer (1978) also found that the type of excuse offered by a queue-jumper could change how successful they are. When cutting in line to use a photocopier, Langer presented three types of excuse. In the first, experimenters offer the Request Only excuse of “Excuse me, I have 5 copies to make. May I use the Xerox machine?”, resulting in 60% allowing her to go ahead. The second excuse presented Placebo Information by stating “Excuse me, I have 5 copies to make. May I use the Xerox machine because I need to make copies?”resulting in 93% allowing her to go ahead. The final excuse was Real Information, where experimenters asked “Excuse me, I have 5 copies to make. Make I use the Xerox machine because I am in a rush?”, resulting in 94% allowing her to go ahead. The results suggest that when you are making a small request (i.e. only 5 pages), it does not matter what your excuse is as long as you make one. However, when the request is bigger (e.g. needing to make 20 copies), excuses start to matter. Presenting Request Only (20%) or Placebo Information (24%) excuses have similarly unsuccessful results, whereas presenting a Real Information excuse (42%) causes people to be more obliging.
Helwig-Larsen & LoMonaco (2008) examined the effects of cutting in line with fans queuing for a U2 concert. Queuers reacted more negatively when the intruder was a stranger than a friend of another queuer. The effects were equivalent for when the cutting in occurred in front or behind them, and was not altered by queue position (30th vs. 175th). Fan commitment also moderated the level of upset, with more committed fans experiencing greater upset than casual fans. However, if the queue-cutter is a friend of another queuer, upset is significantly reduced if the queuer is informed beforehand of a late-arriving (and thus queue-jumping) friend.
Conclusion
Understanding the Psychology of Queuing is clearly important for many organisations. It is complex social behaviour with its own implicit and explicit rules. Many organisations have to make a decision about employing an optimal number of staff to deal with unpredictable changes in customer demand. They know that most people do not like to wait in lines and therefore attempt to make the experience better for their customers. The “science” of queuing reviewed above gives various recommendations of what to do.
