1. Aubrie Powell
11013088
Anthropology 490
Final Paper
December 9, 2013
Cooperation, Social Norms, and Tipping
Social norms are very important in human societies and thus important for the cooperation
within them. Fehr and Fishbacher define social norms as “standards of behavior that are based on
widely shared beliefs how individual group members ought to behave in a given situation” (Fehr et. Al,
2004). Through the shared understandings of appropriate and inappropriate behavior social norms
shape human interactions thereby playing a large part in human cooperation.
Our social instincts are shaped by situations of direct and indirect reciprocity (Rand, et. Al,
2009) which are two mechanisms for the evolution of cooperation. Direct reciprocity is the concept of
give-and-take. When I scratch your back, you scratch mine: my behavior towards you will depend on
your behavior towards me (Nowak, 2012). Indirect reciprocity is similar, but considers the reputation of
individuals. Now, my behavior towards you also depends on what you have done to others – I scratch
your back and someone will eventually scratch mine. “While direct reciprocity relies on your own
experience of another person, indirect reciprocity also takes into account the experience of other
people” (Nowak, 2012). Individuals use the reputation of others to help determine their own actions in
order to aid in more efficient decision making and in hopes for better outcomes.
Indirect reciprocity is prominent in human society because reputation matters. I am more
inclined to cooperate with an individual who has cooperated with three of my friends than with another
individual who notoriously known for defecting. That being said, the inverse it true as well: others will
be more inclined to cooperate with me if I have built up a reputation for myself as a good cooperator.
Others are constantly watching us and we adjust actions to build up our reputations. “Our behavior is
endlessly molded by the possibility that somebody else might be watching … we are often troubled by

2. the thought of what others may think of our deeds” (Nowak, 2012).
While indirect reciprocity deals with reputation, direct reciprocity deals with repetition. I am
more likely to cooperate with someone who has cooperated with me in the past. In one-shot scenarios,
this would not be the case because I could defect and not care about ever running into that individual
again. If I did run into them again, they would remember I did not cooperate and thus be less inclined
to cooperate with me again. “A person will think twice about defecting if it makes his co-player decide
to defect on the next occasion, and vice versa” (Nowak, 2012). The ideas of reputation and repetition
can be applied to many areas of human cooperation, but I will specifically focus on how direct
reciprocity (reputation) can be applied to social norms to help understand their enforcement and
adherence. However, before moving on it is necessary to explain how the need for a social norm
emerges.
The demand for social norms arises when actions cause positive or negative side-effects for
other people (Fehr et. Al, 2004). For example, the social norm for having your cellphone silenced while
in a movie theater may have arisen out of the negative side-effects for others watching the movie when
phones rang during the course of the movie such as interruption, disruption, or distraction. The
increasing amount of irritated movie-goers increased the demand for a social norm to silence
cellphones while in movie theater.
These negative or positive side-effects associated with individual actions can create a public
good problem. A public good is non-excludable and non-rival. This means that no group member is
kept from consuming the public good and one person consuming does not stop another from
consuming. Since no member is excluded from consumption, “all parties are better off if the public
good is provided and the group members share the cost, but each individual also has an economic
incentive to free ride” (Fehr, et. Al, 2009).
If we continue with the silencing of cellphones in movie theaters example, it would benefit all
members of the group to silence their phones. This way no one would be disturbed and the movie

3. would go on uninterrupted. However, the individuals in the movie theater have an incentive to free-
ride, or not contribute anything to the public good. In this case, free-riding individuals would not
silence their phones and/or choose to answer a call in while the movie is running, thus disturbing others
in the process. And this is exactly the problem: if members behave according to their economic
incentives, they do not cooperate and, therefore the public good will not be provided (Fehr, et. Al,
2009). While my example is of a public good that is more based on personal incentives rather than
economic as most examples of public goods are, the underlying issue is still explained. So, it should be
clear that there is some social norm in place that keeps individuals from free-riding as well as
contributing to the provision of the public good (Fehr, et. Al, 2009) The basic framework for this norm
would simply be to not exploit the public good.
It is now easier to observe how reputation can be applied to the adherence social norms, such as
contributing to a public good. On the one hand are those who gain a good reputation by conforming to
the norm, while on the other hand are those who build up a bad reputation for not conforming. Having
a better reputation enables us to have more successful interactions with others. “We cooperate with
those who have a good reputation … we like to give to those who have given to others” (Nowak,
2012).
There is also a substantial amount of research on social norms that focuses on the idea of
conditional cooperation. “People who follow this behavioral pattern condition their cooperation on the
cooperativeness of others or on their beliefs about others’ behavior” (Traxler, et. Al, 2010) meaning
individuals are willing to cooperate more, the more others are also cooperating. However, if others
defect we are also allowed to defect (Fehr, et. Al, 2004). Some researchers such as Traxler and Spichtig
question under what circumstances evolution fosters preferences which then induce conditional
cooperation and use social norms as an answer. They support their claim by stating “as the sanctions for
a norm deviation are harsher the more people adhere to the norm, a social norm for cooperation can
trigger conditionally cooperative behavior” and then go on to study the evolution of a cooperation norm

4. and the coevolution of behavior in order to discuss what requirements are necessary for condtional
cooperation to emerge. They find “norm-sensitive” individuals to behave conditionally cooperative by
defecting the more “norm-insensitive” individuals there are in the population. Societies can function on
a high level of cooperation would have norm deviations with very severe sanctions, a low level with
widespread free-riding individuals with weak norm-enforcement, or at an intermediate stage. They
conclude that our heterogenous environment, consisting of strong norm and low norm states, is what
individual preferences (or norm-sensitivities) and it is in these environments that “conditional
cooperation successful over any unconditional strategy” (Traxler, et. Al, 2010).
Gachter and Herrmann emphasize conditional cooperation into their research as well. In a cross-̈
cultural perspective, the review existing evidence for how people solve cooperation problems. They
combat Nowak's claim for repetition in order to promote cooperation with evidence supporting
cooperation and punishment in one-shot games and is thus evidence for strong reciprocity. It is easy to
draw parallels between that of Traxler and Spichtig's findings of how our heterogenous environments
shape our preferences. In a similar fashion Gachter and Herrmann stated̈ “cooperation and punishment
are substantially shaped by the cultural background across a range of diverse societies”. They believe
many people are conditional cooperators and “if cooperators know that they are among other ‘like-
minded’ individuals, they are able to maintain very high levels of cooperation.” Due to conditionally
cooperative behavior of cooperating with those observed around them,“any factor that shifts people’s
beliefs will shift their behaviour” as well. In their summary, they conclude conditional cooperation
probably stemmed from reciprocity because “cooperating is a nice act towards the other group
members and people may want to return the favour” (Gachter, et. Al, 2009).̈
Still remains the issue of the enforcement of social norms. Why is it people conform to these
standards of behavior? Norms are enforced due to the expectation that violations of the behavioral
standard will be punished (Fehr, et. Al, 2004). The sanctioning of violators is imposed by an
independent third party who, observers the behavior, but is not directly affected by the violation.

5. However, the third party may not be affected directly by the violation, but does incur costs from
sanctioning. “Costs associated with punishing others include the risk of retaliation or at least the
potential loss of relationship, the loss of time or money, emotional tensions, and so forth” (Fehr, et. Al,
2004).
Third-party sanctioning has proven effective in promoting cooperation. Fehr and Fischbacher's
review on evidence involving third-party punishment in a public goods experiment found cooperation
decreases when individuals were not given the option of punishing those who did not contribute to the
public good. However, when these individuals were presented with the opportunity to punish,
cooperation thrived (Fehr, et. Al, 2004). Social norms are comparable to a public goods game because
in both it is better for the entire group if all cooperate by conforming. Fehr and Fischbacher's work is
then able to show how social norms, which are enforced by sanctioning of violators, can promote
cooperation in a society because once punishment is introduced, cooperation flourishes.
Why would someone who is not directly affected by the violation of a social norm want to
punish violators? It would make the most sense if the punishment was administered by self-interested
third-parties rather than those who are uninterested and unaffected. However, research has shown little
evidence for self-interested sanctions. On the contrary, there is much evidence supporting sanctions by
non-selfishly motivated third-parties (Fehr, et. Al, 2004). Strong reciprocators, in this case the
punishing third-parties, “incur personal costs to punish and reward others even when this behaviour
cannot be justified by kinship, reciprocal altruism or reputational concerns” (Gachter, et. Al, 2009).̈
In a separate study, it was reported a large percentage of subjects who “were not directly harmed
by norm violations, enforced norms despite incurring costs and reaping no economic benefits from
their sanctions” (Fehr, et. Al, 2004). The individuals in both studies seem to punish violators for a
variety of reasons including such as to establish more egalitarian outcomes or simply because they
view the violation as unfair an act which deserves retaliation. It then suggested that while economic
self-interest and the desire to rebuild equality do drive some non-selfish sanctions, punishment seems

6. to also result from norms of fairness and reciprocity (Fehr, et. Al, 2004).
While it is evident that third-parties administer the sanctions to violators of norms, but there are
other contributing factors such as emotions. Bowels and Gintis write stated, “Adherence to social
norms is underwritten not only by cognitively mediated decisions, but also my emotions” (Bowles, et.
Al, 2011). Fehr and Fischbacher even noted the questionnaire results from their 2004 Prisoner's
Dilemma experiments on third-party punishment and social norms were consistent with the view that
negative emotions and negative fairness judgments cause the sanctioning decisions that enforce social
norms (Fehr, et. Al, 2004).
To support their claim that social emotions play a part in enforcement of social norms, Bowel
and Gintis gave an example of individuals who had heightened levels of activation in areas of the brain
associated with disgust and anger coinciding with the rejection of low offers in an ultimatum game
(Bowles, et. Al, 2011). In their explanation, the punishment of violators “reduces material payoffs of
those who violate norms, but can also recruit emotions of shame toward modification of behavior.”
They believe shame to be one of the most important emotions in sustaining cooperation. Shame is
defined as “the feeling of discomfort at having done something wrong not only by one's own norms but
also in the eyes of those whose opinions matter to you … it is induced by others' knowing about the
violation and making their displeasure known” (Bowles, et. Al, 2011).
When a social norm is violated, say in a public goods game, an individual can feel shameful not
by contributing too little, but instead by feeling as if they took too much. It is the susceptibility to
shame, guilt (an emotion induced by self-interested action, unlike shame) and other culturally specific
emotions that increase the strength of punishment, thus reducing the cost of punishment. Simply put,
the higher a culture's susceptibility to shame or other social emotions like guilt, the lower the resulting
punishment. Therefore, “high levels of cooperation are sustained with minimal levels of costly
punishment, resulting in mutually beneficial interactions at limited costs” (Bowles, et. Al, 2011).
With understanding of the adherence, enforcement, some determinants conformity and role

7. social norms play in human cooperation, it is now possible to move on to studying a specific social
norm that is very prevalent in our culture, and one that is very important when it comes to research on
social norms: the social norm of tipping.
Tipping is a norm that accounted for $26 billion dollars in United States restaurants alone (Azar,
2004), so it undoubtedly deserves some attention. This social norm is a bit understudied and research is
“scattered across several disciplines—that is, economics, hospitality management, and social
psychology” (Lynn, et. Al, 2000) so it proves to be difficult for comparison studies. However, there are
a handful which have proven to be quite prevalent and I will use them as a basis for this discussion on
tipping.
It would be appropriate to begin with a bit of background on the history of tipping from both a
historical and functional perspective. In the historical sense, scholars aim to trace the origins of tipping
to older customs, but these are not entirely clear. Some scholars will argue that tipping goes as far back
as the “Middle Ages when journeying feudal lords would toss handfuls of coins to groups of beggars to
ensure a safe passage” (Lynn, et. Al, 1993) but some say tipping can be traced to earlier customs.
Economists try to make sense of the norm of tipping using a functional explanation based the
transaction-cost perspective of the firm. In economist view, firms exist because it is too costly to
monitor and price the various inputs to production and firms are much more efficient at doing this than
consumers. Tipping is a very similar step down this chain of command. The inputs of employees are
“difficult and costly to monitor and price, and customers are in a better position than firms to evaluate
the rewards for employees' efforts” (Lynn, et. Al, 1993). Tipping is then a way of enlisting the help of
customer's in performing quality control functions.
There are other explanations attempting to explain the norm of tipping as well, such as the
commonly held assumption that people tip as a reward for good service. The equity model fits in nicely
with this assumption by presenting people as “socialized to feel anxiety or distress when their
relationships with others are inequitable” (Lynn, et. Al, 2000) meaning when one individual's outcomes

8. from the relationship are unequal to the inputs.
The motives behind tipping are more or less the same for the motives behind adhering to social
norms. One thing to keep in mind is that tipping is voluntary. Whether or not to leave a tip, as well as
how much one should leave for a tip are some of the decisions that are shaped by the social norm itself
as well as complicated by the voluntary aspect of the norm. While tipping seems to be an internalized
norm in our culture, it is a vague one. The underlying motives behind customer's decisions on how
much to tip is the topic of the bulk of the research regarding this social norm. Common variables that
are observed to determine the effect they place on the size of the tip are desire for social approval,
desire to reward server for efforts, desire for status and power (Lynn, et. Al, 1993), as well as the
compelling emotions of embarrassment, anxiety, guilt, shame (Conlin, et. Al, 2003) and even those of
generosity, the desire to impress others, gratitude and empathy (Azar, 2003).
Research on tipping also aims to uncover determinants not so closely related to the adherence of
the social norm, but factors within the setting that could play a role in the size of the tip. Some of
determinants that were commonly used in experiments include size of bill, group size, food assessment,
gender of the server, physical appearance of the server, knowledge of the server, speed of service, and
payment method. The most notable of all the studies however are determinants that cannot be
expressed numerically: service quality and effort. Service quality and effort are both frequently used as
subjects of study when researching the tipping norm. However, due to the customer's individual
perception of service quality and effort, the servers perceptions, as well as taking into consideration all
the factors that go into the category of “service quality” the proper way to go about calculating these
two factors is debated. Nonetheless, these are both very important factors to take notice of because
when asked why they leave tips, people most often reply that they tip to reward workers for their
service (Lynn, et. Al, 2000). Also consistent with this commonly held motive, research has found that
consumers leave larger tips the more favorably they evaluate the service and that consumers reward
better service with larger tips only when they attribute the quality of the service to the server's efforts

9. (Lynn, et. Al, 1993).
Perhaps some of the most referenced pieces of work that I have discovered in my research is,
The norm of restaurant tipping, by Conlin, Lynn and O'Donoghue (2003) and, Gratitude and gratuity:
a meta-analysis of research on the service-tipping relationship, by Lynn and McCall (2000). Lynn and
McCall went a different route of all the other research, especially at the time of publishing, by taking
seven published and six unpublished studies on tipping in restaurants and reanalyzed all of the data to
“maximize the compatibility of analyses and effects across studies as well as to provide tests of
relationships that were not reported by the original investigators” (Lynn, et. Al, 2000). In this meta-
analysis, Lynn and McCall looked at the relationship between tip sizes and service evaluations. They
hypothesized if tips were rewards to servers based off of their service, tips should then be positively
correlated to evaluations of the service. After looking at service evaluations as well as taking into
account the heterogeneity to indicate the variability in effect sizes, they were able to conclude that
tipping is related to the service from the data they studied, but the positive relationship was quite small
(accounting for only 5% variability in the bill-adjusted tip sizes). Although small, the positive
relationship between tip size and service evaluations was a reliable one and that the relationship
generalizes across several types of restaurants. (Lynn, et. Al, 2000)
The study done by Conlin et. Al (2003) was a much more extensive study that not only obtained
new and unique data from 112 survey sessions, but also implemented a theoretical model to attempt to
demonstrate why people tip. They believe “while it is possible that direct social sanctions play a minor
role in restaurant tipping behavior, it cannot be the major enforcement mechanism” and describe their
approach to the behavior of tipping in restaurants as “closely related to the literature on norms of gift
giving and reciprocity” (Conlin, et. Al, 2003). The data that is most relevant to this essay is the
information of the size of the tip, size of the bill, service quality (appearance of the server, knowledge
of the menu, friendliness, speed, and attentiveness), and the number of times the customer frequents the
restaurant and their empirical results focus on the determinants of the percent tip and service quality.

10. (Conlin, et. Al, 2003).
They assume the norm of tipping to be a substitute for a service contract that would otherwise
have to be employed upon every visit to a restaurant, so it instead acts as a mode of convenience. They
hypothesize “[if] under the reasonable assumptions that the customer cares about service quality [then]
the tip should increase with service quality” and develop a theoretical model based off of this
hypothesis. The framework is that of a utility function in terms of the customer. They then use this
model to investigate whether or not the tipping behavior observed is consistent with the model.
The model below is the theoretical framework developed to exhibit how a customer decides
how much to tip. Suppose at the end of the meal, the customer chooses their tip to maximize the
preferences represented in the following model:
Uc(T,Q,θ)=v(Q,θ)−T −γ(θ)h(TN(Q,θ)−T).
The first two terms, v(Q,θ) and T, are the customer's material payoffs. The third term, γ(θ)h(TN(Q,θ)
−T, reflects the disutility from not adhering to the norm. TN(Q, θ), is the norm, or the appropriate tip as
a function of service quality and other factors. he customer suffers disutility when- ever she deviates
from this norm, where we assume the function h is increasing, convex, and satisfies h(0) = 0. Finally,
the factor γ(θ) captures the degree that the per- son cares about deviating from the norm (relative to
material payoffs). We assume that the magnitude of this concern depends on features of the
environment.
(Conlin, Lynn, O'Donoghue, 2003)

11. Terms Used:
e = effort of server
Q = quality observed by customer in relation to effort because they cannot observe the server's effort level
F(Q|e, θ) = cumulative distribution function of service quality Q experienced by customer when server choose
effort level e
θ represents other factors over which the server and customer have no control.
E(·|e, θ) = expectation operator given that Q is distributed according to F(Q|e, θ).
T = tip paid by customer to server
Uc(Q,T,θ) = v(Q,θ) − T → utility function which characterizes preferences of the customer
v = increasing, concave in Q
Us(T, e) = T − c(e) → utility function which characterizes preferences of the server
c = increasing, convex
e = argmaxe[E(v(Q, θ)|e, θ)−c(e)] → efficient level of effort∗
T(Q) = tip paid as a function of perceived service quality, Q
T(Q) = T0 + v(Q, θ) → tipping contract which internalizes customer's marginal preference for service quality
(if v is increasing in Q, the customer prefers higher service quality)
γ(θ)h(TN(Q,θ)−T → disutility from not adhering to norm
h = increasing, convex
γ(θ) = degree customer cares about deviating from norm (relative to material payoffs)
From the analysis of their data they show customers leave tips due to their behavior which his
disciplined by a tipping norm. using their model, they found that tips do increase with service quality. It

12. is not the case that people are simply leaving a 10 percent, 15 percent, 20 percent tip, instead they are
tipping as a function of the service received. They also found that larger tip sizes are positively related
to repeated interaction. Why? Customers are then able to punish the server for bad service, and the
server is able to punish the customer for a bad tip. According to Nowak, repeated interactions promote
cooperation, so if more interactions create a collusive agreement, repeated interactions between server
and customer may lead to larger tips and better service quality. (Conlin, 2003)
According to their findings, these authors concluded that tipping is based off of a degree in
which people adhere to the norm of tipping. This makes sense for why there is so much variability in
tipping among customers and no collectively established norm for how much to tip. They also suspect
emotions could also play a role in reason for why people tip. They state, “negative feelings associated
with violating a norm is the main enforcement mechanism for restaurant tipping” and reasons for why a
person would have these negative feelings range from a possibility of an internalized standard of
fairness, to simply disliking disapproval of others.
They continue on in their analysis to include factors that influence the degree that the customer
cares about deviating from the norm, γ(θ), which they identify as the susceptibility the customer has to
feelings of guilt and shame. This can be from how much the customer identifies with the server and
how much they value the social approval of the server. Repetition also influences γ(θ). Finally they
look at factors which influence the tip norm which is given by, TN(Q,θ) = T ̃(Ee(e|Q,θ)). Basically, the
factors that influence the tip norm are factors which influence expected effort of the server, such as
additional effort by the server. (Conlin, 2003)
Overall, I believe this work done by Conlin, Lynn, and O'Donoghue really encompasses a lot of
the reality when it comes to tipping in restaurants. I appreciate them for taking into consideration the
perceived service quality, the effort of the server, the degree to which the customer cares about
deviating from the norm, as well as factors that cannot be controlled by the server or customer.

13. Compared to other theoretical models, such as the one presented by Azar (2003) which does not
incorporate nearly any realistic variables. His, presented below, only takes into account the disutility of
tipping instead of both the approval and disapproval you would have to weigh by adhering to the social
norm or not. In my opinion, his model is one that he formed to fit around his hypothesis which states
that in addition to determinants for tip size including service quality and negative emotions associated
with guilt, embarrassment, shame, etc. there are also positive feelings that are related to tip size. These
include empathy for the server, impressing other, gratitude, and generosity (Azar, 2003).
However, in his model he presented p and θ as variables that are correlated with the positive
feelings attained from tip size. There was no need to put both variables in here except for the fact to
better fit in with his hypothesis. He assumes if θ = 0, then no positive feelings would be associated
with tipping (as most of the existing research mentions), and because of this the social norm of tipping
would decrease over time until it vanishes. However, he claims this is not the case and uses historical
evidence for support by showing tip percentages have not decreased, but increased over time. If θ = 0,
then this is true for his model, but not reality. Again, he is only representing the disutility in his function
so when θ = 0 the best you can do is have an outcome of 0 because there will always be a bill. All other
values will be negative and this correlates with his hypothesis, but not how things actually work.
u(g; n, θ) = d(g – n) + θp(g) – bg
(Azar, 2003)
u = utility of customer
n = norm (appropriate tip)
g = tip in percentage of the biill
d = function representing the disutility from social disapproval

14. b = bill size (b > 0)
p = the utility from tipping that arises from feeling generous, impressing others, etc.
θ = how much the customer gets positive feelings from tipping
In conclusion, the social norms are very important to how human societies cooperate. The social
norm of tipping in America is just one of many norms that help facilitate human interactions on a daily
basis. Those who adhere to the norm do so most likely due to negative feelings they associate with not
following the norm, such a guilt, shame, or embarrassment. They also feel pressure from third-party
sanctions to conform to the norm or else face direct social consequences.
The social norm of tipping is an interesting topic due to the the voluntary payments by
customers. These payments are shown in a number of studies to be positively related to the service
quality where the better the service, the higher the tip amount. This specific subject does need more
work done in areas that will begin to answer questions on how the social norm of tipping evolved as
well as more applicable models to interpret data on tipping. Most research is out of date and much has
changed, including the “norm” on how much one should tip. Future research should also look into the
internalization of the tip norm, how it changes, and the rate at which the “norm” of how much to tip
changes over time.

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