Emerging Trends in The Social and Behavioral Sciences

The Others as Social Context: On the Importance of Strategic Interaction

Item

Title

The Others as Social Context: On the Importance of Strategic Interaction

Author

Diekmann, Andreas

Research Area

The Individual and Society

Topic

Social Interactions in Everyday Life

Abstract

An action is defined as “strategic” when the consequences of ego's action depend on the action of alter. Situations of strategic interaction are numerous in daily life, business, and politics. Other peoples' opportunities of actions form ego's strategic context. The dynamics of the impact of the strategic context on ego's action can be modeled by means of game theory. We discuss three examples of strategic interaction models: “Diffusion of responsibility,” Boudon's “logic of relative frustration,” and the problem of social exchange and trust. We demonstrate the effects of the strategic context on the opportunities and beliefs of actors. In contrast to nonstrategic rational choice theory, beliefs and opportunities are not assumed as exogenous. The analysis of the strategic context contributes to a better understanding of the microlevel effects and the macrolevel implications. However, the strict rationality requirements of game models are often violated. In these situations, evolutionary models based on principles of learning and adaptions are more adequate than models based on assumptions of strict rationality.

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Identifier

etrds0396

extracted text

The Others as Social Context: On the
Importance of Strategic Interaction∗
ANDREAS DIEKMANN

Abstract
An action is defined as “strategic” when the consequences of ego’s action depend
on the action of alter. Situations of strategic interaction are numerous in daily life,
business, and politics. Other peoples’ opportunities of actions form ego’s strategic
context. The dynamics of the impact of the strategic context on ego’s action can be
modeled by means of game theory. We discuss three examples of strategic interaction
models: “Diffusion of responsibility,” Boudon’s “logic of relative frustration,” and
the problem of social exchange and trust. We demonstrate the effects of the strategic
context on the opportunities and beliefs of actors. In contrast to nonstrategic rational
choice theory, beliefs and opportunities are not assumed as exogenous. The analysis of the strategic context contributes to a better understanding of the microlevel
effects and the macrolevel implications. However, the strict rationality requirements
of game models are often violated. In these situations, evolutionary models based
on principles of learning and adaptions are more adequate than models based on
assumptions of strict rationality.

INTRODUCTION: CONTEXT AND SOCIAL ACTION
A patient goes to his doctor after receiving a positive result to a prophylactic
test. The doctor recommends special therapy. There is a risk that the doctor,
although acting to the best of his knowledge and belief, is not on top of latest developments in his science and prescribes a therapy with little chance
of success. A further risk lies in the fact that, although the doctor is indeed
well informed, he may not prescribe the optimal therapy because he himself profits from a certain method of treatment. The patient, therefore, has a
double trust problem (Gigerenzer, 2014), unlike an air passenger who trusts
the competence of the pilot. It is similar for the customer of a garage, the
client of an investment advisor in a bank, and for the client of a lawyer or
attorney. The behavior of the patient toward the doctor, the garage employee,
∗ This essay is based on Diekmann (2014). Many thanks to Rachel Matthey for translating the
manuscript.

Emerging Trends in the Social and Behavioral Sciences.
Robert Scott and Marlis Buchmann (General Editors) with Stephen Kosslyn (Consulting Editor).
© 2016 John Wiley & Sons, Inc. ISBN 978-1-118-90077-2.

1

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EMERGING TRENDS IN THE SOCIAL AND BEHAVIORAL SCIENCES

the investment advisor, or the attorney is, in the sense of Max Weber, social
action. However, the two trust problems are not both of a strategic character. Trust in the expertise of the doctor is a nonstrategic decision. In contrast,
the patient’s trust that, in a conflict of interest, the therapy recommended by
the doctor will be to his benefit is of a strategic nature. A distrustful patient
can solve the first trust problem by going to a doctor who has been recommended as competent. He can solve the second trust problem by obtaining a
second opinion, so that no conflict of interest exists. The second trust problem
is strategic because the decision results of patient and doctor, ego and alter,
are mutually dependent on the decisions of the other actor.
This essay will mainly be dealing with the “strategic social context,”
acknowledging that many sociological problems are of strategic character,
but this is often neglected in sociological analysis. In the section titled
“Context, Action, Aggregation, and Macro Effect”, the correlation among
context, action, and effects on the macro level is first explained. On the
basis of the hypothesis of diffusion of responsibility, the competition model
of Raymond Boudon and the trust game is discussed. Section titled “The
Actions of Others as Strategic Context” explains social action in the strategic
context. It shows that the strategic social context requires the application of
game-theoretic methods. When actions are strategic, the independent variables of the theory of social action can no longer be regarded as exogenous.
In addition, game-theoretic methods solve the problem of aggregation. Our
interest also focuses on the development of institutions as a reaction to
the problems of strategic action. Institutions can ease problems of strategic
action. In the section titled “Rational Action, ‘Beauty Contest,’ and Bounded
Rationality”, finally, we discuss the problem of rational action within the
context of strategically deciding actors.
CONTEXT, ACTION, AGGREGATION, AND MACRO EFFECT
Social context influences the action-relevant characteristics of actors. According to a simple heuristic scheme, action and decision theories refer to three categories of independent variables: (i) The value of the action consequences, (ii)
the perceived probability of the appearance of certain action consequences,
and (iii) the action resources. Using Hedström’s (2007) formulation, these are
(i) “desires,” (ii) “beliefs,” and (iii) “opportunities” (DBO), or Gintis’s (2007)
“beliefs, preferences, constraints” (BPC). Preferences correspond to desires,
and constraints correspond to opportunities or resources. Constraints are, for
example, time, income, and technological possibilities. Anyone who buys a
lottery ticket at a kiosk shows the desire (the preference) to make the highest
possible winnings, the belief that there is a certain (subjective) probability
that this wish will be fulfilled and he must carry the costs of the bet. The

The Others as Social Context: On the Importance of Strategic Interaction

3

three elements, DBO (or BPC), do not yet constitute a complete theory. For
this, further elements would be required, such as (i) a procedure for measuring D, B, and O for all action alternatives and action consequences and (ii) a
decision theory showing the probability with which an action is carried out
with any combination of D, B, and O. A theory of social action does not necessarily have to adhere to the principles of strict rationality, it can also follow
the assumptions of “bounded rationality.”
Via DBO, the social context influences the action results, which actors produce through their decisions. The aggregated action results correspond to
the effect on the macro level. The well-known “Coleman-boat” (Coleman,
1990) illustrates these relations for didactic reasons, omitting, however, the
dynamics of the processes and complexities such as local interactions.
Let us look at an example. Emile Durkheim (1952 [1897]) reported on the
analysis of statistical material regarding the frequency of suicide in different
social groups. It was shown that because of a higher degree of social integration, Catholics display a lower suicide rate than Protestants. The degree of
integration is a context characteristic that influences the resources and action
goals of the actors. Thus, in socially integrated groups, isolated and lonely
people are more seldom and that again reduces the tendency toward “egoistical” suicide.
Durkheim’s analysis of suicide deals with “social action” in the sense of
Max Weber. The actions are, however, not strategic. The aggregation is simple, as the rate of suicide in a social group results from the number of suicides
per annum, divided by the size of the population.
The situation is different if actions are strategically linked with each other.
The problem of aggregation is then no longer trivial and can take on a considerably more complex form. In daily interactions, in politics, and in business
life, the actions of individual actors are often mutually dependent on each
other. The resources (opportunities in the DBO scheme), such as the perceived probabilities of action consequences (the beliefs), are then no longer
given as exogenous, but as endogenous, dependent on the actions of others.
THE ACTIONS OF OTHERS AS STRATEGIC CONTEXT
THE PROBLEM OF AGGREGATION AND THE MACRO EFFECT: THE EXAMPLE OF THE “DIFFUSION
OF RESPONSIBILITY”
Strategic action means that the consequences of an action are dependent on
the actions of other actors. Let us take a look at the regularity of the diffusion
of responsibility examined by Darley and Latané (1968) in an experiment.
The more the people that witness an emergency of any kind, the smaller the
probability is that an individual person intervenes. Situations showing the

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EMERGING TRENDS IN THE SOCIAL AND BEHAVIORAL SCIENCES

diffusion of responsibility can also be found in many everyday situations and
in business life. If a seminar is conducted by several lecturers, the individuals
involved are often not as well prepared as when they alone are responsible.
Companies wait for others to develop innovations, which they can later copy
economically (Eger, Kraft, & Weise, 1992). The “volunteer’s dilemma” (Diekmann, 1985) has been proposed as a general model for such a situation.
The situation has a very simple structure. All actors are interested in the
collective good (assistance, good teaching, or innovation) materializing.
We shall call the value of the collective good U, the costs of achieving
it K, whereby U > K > 0. In each case, a cooperative actor gains U − K. A
noncooperative actor receives U, but only when at least one other actor
cooperates; otherwise, all will be left empty-handed.
The structure of an action is given by the type of game and the quantities
N, K, and U. They define the context of the strategic situation. With regard
to the “assistance” example, U can vary interculturally. In an egoistic society,
the value of the collective good will turn out to be lower than in a society that
shows solidarity.
In this situation, there is a symmetrical, individual, rational “solution”: the
Nash equilibrium strategy. It can be deduced with the methods of the classical game theory. Informally, a Nash equilibrium is defined as a combination
of strategies from which no actor is induced to deviate unilaterally—as long
as the other actors maintain the equilibrium strategy.
If p is the probability of cooperation and N is the number of actors, we get
the equilibrium strategy p* (Diekmann, 1985):
√√
N−1
∗
p =1−
K∕U)
The individual tendency to cooperate declines, as expected, with the
costs and increases with the value of the collective good. To be more
exact—although not completely obvious—the probability falls with the
quotients of the costs of the cooperative action and the value of the collective
good. Furthermore, the tendency to cooperate sinks with the number of
actors N. The effect of the diffusion of responsibility observed in experiments can be deduced from a simple model. This model of the structure of
interdependent actions can be extended in different directions. Examples
are the asymmetric volunteer’s dilemma (Diekmann, 1993), the volunteer’s
dilemma with cost sharing (Weesie & Franzen, 1998) and further variations.
These models generate several hypotheses linking structural conditions to
individual behavior.
The Nash equilibrium is also a central element in solving the aggregation
problem. The macro hypothesis about the production of collective good
results directly from the actors’ individual strategies. Both hypotheses can
be tested by empirical data (Franzen, 1995).

The Others as Social Context: On the Importance of Strategic Interaction

5

For a more exact analysis of strategic interaction, we need the models and
the solution concepts of game theory. This applies particularly when—as
in analytical sociology—we are interested in uncovering the explanatory
mechanism (Hedström, 2007). With the help of game theory, one can succeed
in defining the social context and the structure of action more exactly.
Furthermore, hypotheses on individual action strategies can be derived
from these models. Simultaneously, the Nash equilibrium helps to aggregate
individual actions, as well as to deduce the macro effect. In this way, the
three steps—context, individual action, and aggregated macro effect—can
be formulated precisely and the results tested with data.
SOCIAL CONTEXT AND OPPORTUNITIES: THE COMPETITION MODEL OF BOUDON
In their study, Stouffer, Suchman, Vinney, Star, and Williams (1965 [1949])
report on satisfaction with promotion in two army units. Paradoxically,
dissatisfaction is higher among the more frequently promoted pilots than
among the military policemen, who in comparison are rarely promoted.
This study stimulated the development and discussion of relative deprivation and reference groups. Considerably earlier, Tocqueville (2008 [1852])
brought attention to a similar paradox (Boudon, 1977), developing the
hypothesis that dissatisfaction and protests are more likely to culminate in
prosperous periods. Boudon (1977) took up Tocqueville’s thesis again and
tried to explain this remarkable correlation under the premise of rational
behavior with a game-theoretic model.
The essential feature of the theory is as follows: assume that a society’s
increasing prosperity stimulates actors to invest in upward mobility. Some
of the investors will win while others will lose. Under certain conditions,
the level of dissatisfaction in the society or the social group will rise. This
happens when the interaction system leads to a disproportionate growth
between losers and winners.
Game theory translates these ideas in a formal model (cf. Berger & Diekmann, 2015; Raub, 1984). In a social group with the size N, there are 0 ≤ k
≤ N positions available for promotion. Those wishing to be promoted have
to invest. The costs of this amount to C, and the gain from promotion is B.
Successful candidates achieve ? = B − C, losers receive ? = ? − C, and actors
who do not invest in applying receive a payoff in the amount of ? (Figure 1).
? > ? > ? applies. The number of investors is called n.
Here, investing means incurring general expenditure and taking risks,
in order to improve one’s social position. Whether a person is successful
depends, of course, on the behavior of the other competitors. In any case, in
a competition situation, n − k frustrated candidates drop out of the running.

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EMERGING TRENDS IN THE SOCIAL AND BEHAVIORAL SCIENCES

s
p

Invest
Player i

1-s

High payoff
B–C=α
Low payoff
β–C=y

p
1Not invest

Medium payoff
β

Figure 1 Investing in the competition model. Source: Adopted from Berger and
Diekmann (2015), see also Hedström (2007).

Investors can expect the following payoff (Berger & Diekmann, 2015):
{
k
? + n−k
y für k < n
n
E(k, n) = n
?
für k ≥ n.
A rational actor will invest as long as E(k,n) is larger than ?. If this is the
case, independent of the number of competitors n, investing is the dominant
strategy. The situation is somewhat more complicated when “investing” is
not the dominant strategy. In this case, “investing” up to a threshold value
of n* is more advantageous than “not investing.” However, if the number of
candidates is greater than the threshold value, it would be better to abstain
from applying; but, of course, the actors do not know how many competitors
will invest. There are then several equilibria in “pure” strategies, which are
not attainable without coordination, as well as an equilibrium in “mixed”
strategies (Berger & Diekmann, 2015; Raub, 1984).
The structure of social action is given by the rules of the model, as are the
parameters ?, ?, ?, N, and k. These elements define the social context, which
provides the framework for carrying out the competition. The five parameters are exogenous. The opportunities follow from the decision dynamics
and are endogenous. The number of competitors, which considerably influences the candidate’s chances, only comes to light if we assume a hypothesis regarding the decision behavior of the actors. If, like Boudon, we make
the rationality assumption, various hypotheses about the effect of a growing number of chances on the degree of satisfaction or frustration can be
deduced. Under certain circumstances, it can be seen that the number of
losers rises with the growing number of chances (k) and then falls again. The
course of satisfaction, dependent on the number of chances, is U-shaped. The
Nash equilibrium hypothesis, derived from the model, provides information
about the conditions under which the course of satisfaction can be expected

The Others as Social Context: On the Importance of Strategic Interaction

7

to fall, that is, the “Tocqueville effect.” The hypotheses deduced from the theory can then be empirically tested. A first lab experiment shows that a more
refined measure of satisfaction is needed to observe the predicted U-shaped
function (Berger & Diekmann, 2015).
Social context defines the structure of social action, which in turn triggers
the interaction between action dynamics and opportunities. As social
context affects the strategic behavior of actors, simple parametric models
are unsuitable for analyzing the structure of social action. The opportunities
(O in the DBO scheme) are created endogenously. These depend on other
actors’ investment behavior. Only with the help of game-theoretic solution
approaches can the action dynamics be adequately examined. Furthermore,
the Nash equilibrium strategy makes it possible to aggregate the action
results. Under certain conditions, which it is possible to name, the macro
hypothesis follows via the U-shaped course of satisfaction.
SOCIAL CONTEXT AND BELIEFS: SIGNALS OF TRUST
As a rule, social and economic exchanges are linked with a double uncertainty. On the one hand, the exchange is time-delayed, that is, one of the
exchange partners makes an advance. On the other hand, it is not always
immediately clear whether the exchanged good corresponds to expectations.
A problem of trust arises, which can be described with a simple model, the
trust game.
In the trust game (Dasgupta, 1988), two actors interact: the trustor and the
trustee. The trustor has to decide between cooperation (C) or “noncooperation” (defection D). If he chooses D, no business takes place. No one wins and
no one loses; the payoff to both actors amounts to P. However, if the trustor
cooperates, he puts his fate in the hands of the trustee. The trustee, in turn,
can cooperate (e.g., by delivering the goods paid in advance) or defect, that
is, by exploiting the trustor’s position. With the usual symbols of the trust
game, both actors receive a payoff R after cooperation. On the other hand,
if the trustee defects, he receives the exploitation payoff T and the trustor
makes a loss S. The rank order of the payoffs is T > R > P > S.
In a single trust game, a self-interested, rational trustee will defect as soon
as it is his turn. The trustor anticipates this and will not trust him. The Nash
equilibrium is mutual defection with the result (P, P). A deal will not take
place, so both lose in comparison to the result of mutual cooperation, where
they would both receive R.
If, however, exchanges between partners take place repeatedly, cooperation
can develop if the gains expected from the exchange relationship in the future
are high enough. Moreover, it may be that the trustee complies with ethical
norms or has a reputation as an honest businessman, which he does not want

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EMERGING TRENDS IN THE SOCIAL AND BEHAVIORAL SCIENCES

to risk losing. The problem lies in the fact that, with a single transaction or at
the beginning of a series of transactions, the trustor does not know whether
his business partner is trustworthy or not.
These reflections could be more precise by extending the trust game (Voss,
1998). We assume that there are honest and dishonest trustees. The honest
trustees are interested in future business with the payoff R* > T, for the dishonest it is, as before, T > R. The actors are in this case “honest” or “dishonest” depending on where their interests lie. Trustors know that a portion of
the business partners are honest (?) and another portion fraudulent (1 − ?). If
they have no further information, they will always cooperate as long as ? is
larger than the threshold value ?*, whereby they can gain at least as much by
cooperating as by abstaining from business relations, or at least P. Trustors
always cooperate when ? ≥ ?* = (P−S)/(R−S) and accept the losses caused by
fraudulent partners.
However, if the portion of fraudulent actors becomes too big (? < ?*),
cooperation is no longer worthwhile. In that case, no business is carried out;
the market collapses and all actors, including the fraudulent trader, are left
empty-handed. In such situations, it is very probable that signals emerge
with which trustees can communicate to trustors that they are honest (for
more details, see Przepiorka & Diekmann, 2013). The fraudulent trustors are,
of course, also interested in appearing honest. So a signal is only useful if it is
credible. From the signal, one must be able to recognize the “type” to which
an actor belongs. Credible signals are connected with costs, or, to be more
exact, with the difference in the cost of producing signals. This difference
must be so high that honest actors profit from cooperation (R* − sA > P),
despite signaling costs, while fraudulent actors do not gain if they initiate
a signal (T − sB < P). sA and sB designate the signaling costs of honest and
fraudulent actors, respectively. Under these circumstances, a so-called
separating signaling equilibrium is to be expected. Tattoos were (in the past)
signals that transmitted the information that a person had been in prison and
in all probability would be reliable in any illegal business (Gambetta, 2009).
Police spies, in contrast, were usually not tattooed, provided that they led a
respectable life and the (social) costs of a tattoo were unacceptable. During
courtship, there can be a problem in most cultures when a young man is not
serious about a permanent relationship. Expensive engagement presents are
a signal that differentiates the honest suitor from the dishonest one.
Honest dealers in second-hand wares give a guarantee. If they are honest (and make no mistakes), the costs are zero. For dishonest dealers in
second-hand wares, on the other hand, the costs would be prohibitively
high. The promise of a guarantee is a signal that allows the customer to
distinguish between honest and fraudulent dealers.

The Others as Social Context: On the Importance of Strategic Interaction

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For this discussion, it is important to note that, in signaling games, the
subjective probability that an actor belongs to a certain type can only be determined by the actions of the actor.
The social context consists of the game structure (decision tree), the preferences of specific types of actors (the D in DBO), and the signaling costs.
These elements are exogenous. The beliefs (the B in DBO), in contrast, follow
from the action dynamics and are endogenous. The social context influences
the beliefs and these in turn the actions. In the trust game, this is the decision in favor of cooperation. As the macro result, markets emerge in which
cooperative exchanges are carried out.
INSTITUTIONS
In trust relationships, signals will emerge when legal or other institutional
regulations are not possible or are difficult to enforce (e.g., in illegal markets),
when most transactions are nonrepeated or seldom repeated, and also when
no reliable information about the reputation of the actors is available. Dependent on the specific context (e.g., nonrepeated vs repeated interactions and
access to reliable information), different cooperation solutions can develop
in the trust relationships (Buskens & Raub, 2013).
A study by Siamwalla (1978) about the market structure of agricultural
products in Thailand is instructive. The quality of rice, for example, is easily
recognizable before the purchase, so that no specific trust problem regarding
quality exists. On the other hand, the rubber farmer himself knows much better than the buyer whether the product is of high or low quality. The quality
of the raw product depends namely on the care taken by the farmer in eliminating impurities, as well as on the quality of the acid used (Siamwalla, 1978).
Because of the asymmetric information, a trust problem arises. Compared to
the rice market, therefore, the market structure that emerged for rubber is different. Loyalty between the seller and the purchaser is high; a rubber farmer
only deals with a few buyers, and they know the farmer and trust the quality
of the goods. In addition, there is the “chain structure” of the trade. A buyer
in the village sells to a dealer in the district and he in turn to a wholesaler or
large trading company (Siamwalla, 1978).
The characteristics of the different goods, in this case rubber versus rice, create trust problems to varying degrees. These problems are solved by different market structures or institutions. Rice markets are often auctions, while
long-term relationships between trading partners and reputation are characteristic of the markets for the raw material, rubber (Kollock, 1994). In an
imaginative experiment, Kollock (1994) was able to demonstrate the emergence of varying market structures.

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EMERGING TRENDS IN THE SOCIAL AND BEHAVIORAL SCIENCES

In digital trade, trust problems emerge because of the anonymity of the market participants, who often buy goods at auction per mouse click over great
distances. Given the standard trust game and assuming rational and selfish
preferences, there is a unique Nash equilibrium: exchanges should not even
take place; anonymous markets are expected to collapse. However, we are
not dealing here with a simple trust game. With the introduction of the possibility to assess the seller, the trust problem has been considerably defused.
Instead of the “shadow of the future” in the repeated game, the “shadow of
the past” was quasi created with the introduction of reputation. In their own
interests, sellers try to build up a reputation; purchasers, in turn, reward a
reputation. However, it cannot be completely taken for granted that the rating system functions, as self-interested actors may just save themselves the
bother of an assessment. Homo economicus would give no feedback, the rating system would collapse and with it the auction too. Thus, a small shot
of altruism and reciprocity, which goes over and above the self-interest of
homo economicus, is the lubricating oil of anonymous, electronic markets.
The reputation system is a simple, but extremely effective, institutional mechanism, which makes these markets—worth billions—really possible (Diekmann, Jann, Przepiorka, & Wehrli, 2014).
The strategic context of the trading actors creates a trust problem. Institutional regulations can alleviate the problem. The question as to what kind
of regulation emerges depends on various conditions, such as information
asymmetries, transaction costs, and technological progress. The context of
strategically trading actors is the starting point for explaining the development of institutions.
RATIONAL ACTION, “BEAUTY CONTEST” AND BOUNDED
RATIONALITY
There is scarcely another term in the social sciences that is as heavily burdened with misunderstandings as the term rationality or rational action. With
rationality, we understand here no more (and no less) than consistent decisions. Consistency is the defining characteristic. This means that decisions
are taken in agreement with the axioms of a rationality theory. Corresponding to this definition, there are more or less restrictive requirements for the
term rational action, as there are various decision theories with differing axiom
systems. However, when explaining social action, whether we describe the
behavior as “rational” or not is insignificant anyway. However, most decision
theories will probably prescribe the validity of one axiom, namely, the transitivity of preferences: When A is preferred to alternative B and B to alternative
C, then A should also be given preference over C.

The Others as Social Context: On the Importance of Strategic Interaction

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Rationality does not call for self-interest, and certainly not for material
self-interest. Homo economicus acts rationally per definition, but rational
action is not synonymous with the action of the fictive homo economicus.
Rationality and altruism do not have to be opposites. Andreoni and Miller
(2002) have shown that actors with altruistic preferences can act rationally
in the sense that they fulfill the axioms of decision theory. If people do
not correspond to the picture of homo economicus, and in addition they
even follow altruistic goals, this does not necessarily mean that they act
irrationally. In concurrence with the consistency criterion, their decisions
can be strictly rational. Here, “rationality” is defined in a “motive-free” way,
without excluding certain preferences, goals, or desires. The “wide version”
of rational choice theory (Opp, 1999) already follows from an axiomatic
approach.
Nevertheless, one can observe spectacular deviations from strict principles
of rationality in many situations. The “Beauty-Contest Game” received its
name from a quotation from Keynes, in which he compares the purchase of
stocks to a beauty contest (Selten & Nagel, 1998). On the stock market, it is
not about deciding which is the best share in one’s own opinion, but rather
which is the one that you believe others will think is the best decision; even
more than that, it is about the share that you believe everyone believes that the
others consider to be the best purchase, and so on. The rules of the game are
simple. There are N participants who have to choose a number between zero
and 100. The person who comes nearest to 2/3 of the (arithmetical) mean of
all numbers mentioned wins a prize. When there is more than one winner,
the prize is shared.
If one does not think strategically, one could say, “All numbers are evenly
distributed, the mean should therefore lie by 50. I choose 33 1/3, for that is
2/3 of 50.” Strategic thinking on this first level goes a step further. “If everyone thinks like this, the mean will be 33 1/3. I choose, therefore, 22 2/9.”
On the next level of strategic thinking, it is approximately 15 and so forth,
until finally in continual iteration one approaches at zero, the unique Nash
equilibrium strategy.
However, the equilibrium strategy is rarely chosen in the first round of
experiments. Typically, choices accumulate around 33 or 22. If one repeats
the decision situation and informs about the mean, values around 15 or 10
will result and, in a further round, numbers approaching the equilibrium will
be observed (Selten & Nagel, 1998). This process can also be seen when exact
information about the distribution in the previous round is given (Diekmann,
2009). One could now assume that the actors do not choose the equilibrium
strategy because they do not know about it. However, even if it is explained,
many actors by no means use this strategy. Why do actors act “irrationally”? The answer is as follows: Even if one knows that it is rational to choose

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EMERGING TRENDS IN THE SOCIAL AND BEHAVIORAL SCIENCES

zero, one can still reckon on some of the players not doing so (Selten & Nagel,
1998). In that case, it makes more sense not to choose the equilibrium strategy
and, therefore, one does not choose this strategy oneself either.
The beauty-contest game has been used to explain speculative bubbles on
the stock and property markets. Even if one knows that it is a bubble it can
be worth investing. For the prices can rise further, up until the occurrence
of the catastrophe. Similarly, actors in the beauty-contest game choose the
“irrational” strategy at least occasionally, although they know about the equilibrium strategy. The head of the Citigroup, Charles Prince, formulated this
thought more concretely in the “Financial Times” in July 2007, shortly before
the crisis broke: “When the music stops, in terms of liquidity, things will be
complicated. But as long as the music is playing, you’ve got to get up and
dance. We’re still dancing” (Akerlof & Shiller, 2010, p. xii). In the following
year, the bubble burst!
The step-by-step approach to the equilibrium strategy during the growing number of rounds in the beauty contest demonstrates that equilibrium
points can be achieved by learning and adaptive behavior in the course of the
evolutionary process. Learning, adaptive and myopic behavior can often be
observed in experimental studies. In these cases, theories of bounded rationality, which are explicitly based on the principles of adaptive behavior, are
superior to strict rationality theories.
OUTLOOK
Pioneers in sociology, such as Erving Goffman and Raymond Boudon, recognized that in many cases strategic action is the key to explaining social
processes. Social actions in Max Weber’s sense are of strategic character when
they are not purely oriented on the actions of others but rather are dependent on the results of others’ actions. This distinguishes mere imitation from
a mass panic, a stock market crash, or the growth of a protest movement.
Today, there are increasingly improved models of classical and behavioral
game theory available, with the help of which it is now possible to describe
the strategic context or the structure of strategic interaction precisely and
to deduce testable conclusions. The fundamental problems of sociological
research are of strategic character: the emergence of social order, the problems of cooperation, conflict and the decline of order, compliance with social
norms and the problem of sanctioning, the emergence of institutions, social
exchange and the problem of trust, the development of protest movements,
social dilemmas, and collective goods. Modern methods of analyzing strategic interaction should be employed more widely in both the curriculum of
sociology students and in sociological research.

The Others as Social Context: On the Importance of Strategic Interaction

13

Undeniably, classical game theory requires strong rationality assumptions.
In situations where these models allow sufficiently valid predictions, there is
no reason to introduce alternative decision principles. Furthermore, the theory delivers a reference point. If the observed behavior deviates from that,
there is the challenge of explaining the “anomaly.” In this way, new hypotheses and explanations have often been produced. When the strict rationality
models fail—as demonstrated in the beauty contest—one can fall back on
models of “bounded” rationality. There is no general and mechanically applicable theory—otherwise, we could leave the theory building to a computer.
Rational choice theory, bounded rationality, analytical sociology, game theory, and psychological decision research should, instead, be understood as a
“tool box.” They deliver heuristic principles and instruments for building a
theory of the middle range (Merton, 1949) in a concrete area of application,
the findings of which can be tested on empirical data.
REFERENCES
Akerlof, G. A., & Shiller, R. J. (2010). Animal spirits (9th ed.). Princeton, NJ: Princeton
University Press.
Andreoni, J., & Miller, J. (2002). Giving according to GARP: An experimental test of
the consistency of preferences for Altruism. Econometrica, 70, 737–753.
Berger, J., & Diekmann, A. (2015). The logic of relative frustration. Boudon’s competition model and experimental evidence. European Sociological Review, 31, 725–737.
Boudon, R. (1977). Logic of relative frustration. Archives Europeennes de Sociologie, 18,
3–26.
Buskens, V., & Raub, W. (2013). Rational choice research on social dilemmas: Embeddedness effects on trust. In R. Wittek, T. A. B. Snijders & V. Nee (Eds.), The handbook
of rational choice social research. Stanford, CA: Stanford University Press.
Coleman, J. (1990). Foundations of social theory. Cambridge, MA: Harvard University
Press.
Darley, J. M., & Latané, B. (1968). Bystander intervention in emergencies. Diffusion
of responsibility. Journal of Personality and Social Psychology, 8, 377–383.
Dasgupta, P. (1988). Trust as a commodity. In D. Gambetta (Ed.), Trust. Making and
breaking cooperative relations (pp. 49–72). Oxford, England: Blackwell.
Diekmann, A. (1985). Volunteer’s dilemma. Journal of Conflict Resolution, 29, 605–610.
Diekmann, A. (1993). Cooperation in an asymmetric volunteer’s dilemma game.
Theory and experimental evidence. International Journal of Game Theory, 22, 75–85.
Diekmann, A. (2009). Rational choice, evolution and the “Beauty Contest”. In M.
Cherkaoui & P. Hamilton (Eds.), Raymond Boudon – a life in sociology (pp. 1–12).
Oxford, England: Bardwell Press.
Diekmann, A. (2014). Die Anderen als sozialer Kontext. In J. Friedrichs, A. Nonnenmacher, (Eds.), “Sozialer Kontext und soziale Mechanismen” der Kölner Zeitschrift
für Soziologie und Sozialpsychologie, 66(special issue), 47–66.

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Diekmann, A., Jann, B., Przepiorka, W., & Wehrli, S. (2014). Reputation formation and
the evolution of cooperation in anonymous online markets. The American Sociological Review, 79(1), 65–85.
Durkheim, E. (1952 [1897]). Suicide: A study in sociology. London, England: Routledge
and Kegan Paul.
Eger, T., Kraft, M., & Weise, P. (1992). On the equilibrium proportion of innovation
and imitation. A game-theoretic approach. Economics Letters, 38, 93–97.
Franzen, A. (1995). Group size and one-shot collective action. Rationality and Society,
7, 183–200.
Gambetta, D. (2009). Codes of the underworld: How criminals communicate. Princeton,
NJ: Princeton University Press.
Gigerenzer, G. (2014). Risk Savvy. How to make good decisions. New York, NY: Viking.
Gintis, H. (2007). A framework for the unification of the behavioral sciences. Behavioral and Brain Sciences, 30, 1–61.
Hedström, P. (2007). Dissecting the social. On the principles of analytical sociology. Cambridge, MA: Cambridge University Press.
Kollock, P. (1994). The emergence of exchange structures: An experimental study of
uncertainty, commitment, and trust. American Journal of Sociology, 100, 313–345.
Merton, R. K. (1949). Social theory and social structure. New York, NY: The Free Press.
Opp, K.-D. (1999). Contending conceptions of the theory of rational action. Journal of
Theoretical Politics, 11, 171–202.
Przepiorka, W., & Diekmann, A. (2013). Temporal embeddedness and signals of
trustworthiness: Experimental tests of a game theoretic model in the United Kingdom, Russia, and Switzerland. European Sociological Review, 29, 1010–1023.
Raub, W. (1984). Rationale Akteure, institutionelle Regelungen und Interdependenzen. Untersuchungen zu einer erklärenden Soziologie auf strukturell-individualistischer
Grundlage. Frankfurt am Main, Germany: Peter Lang.
Selten, R., & Nagel, R. (1998). Das Zahlenwahlspiel. Hintergründe und Ergebnisse.
Spektrum der Wissenschaft, 2(1998), 16–22.
Siamwalla, A. (1978). Farmers and middlemen. Aspects of agricultural marketing in
Thailand. Economic Bulletin for Asia and the Pacific, 38–50.
Stouffer, S. A., Suchman, E. A., Vinney, L. C. de, Star, S. A., & Williams, R. M. Jr. (1965
[1949]). The American soldier. Manhattan, KS: Military Affairs, Aerospace Historian
Publishing.
Tocqueville, A. de (2008 [1856]). Ancient regime and the French revolution. London,
England: Penguin.
Voss, T. (1998). Vertrauen in modernen Gesellschaften. In R. Metze, K. Mühler & K.-D.
Opp (Eds.), Der Transformationsprozess. Leipzig, Germany: Universitätsverlag.
Weesie, J., & Franzen, A. (1998). Cost sharing in a volunteer’s dilemma. Journal of
Conflict Resolution, 42, 600–618.

ANDREAS DIEKMANN SHORT BIOGRAPHY
Andreas Diekmann is a professor of sociology at the ETH Zurich. He earned
a doctoral degree from the University of Hamburg in 1979 (Dr. rer. pol.),

The Others as Social Context: On the Importance of Strategic Interaction

15

and received the “venia legendi” (Dr. rer. pol. habil.) from the University of
Munich (1987). His areas of research are social cooperation and experimental
game theory, environmental and population sociology, and methods of
empirical social research. He served as a member of the Humboldt Professor
Price Committee and is chairman and senator of the section “Economics and
Empirical Social Sciences” of the German Academy of Sciences Leopoldina.
He is also a fellow of the European Academy of Sociology and coeditor and
board member of several professional journals and research institutions.
Present research activities focus on experimental research on social norms
and energy consumption, an analysis of the environmental burden of
metropolitan areas with geo-referenced panel data (supported by grants
of the Swiss National Science Foundation) and experimental research on
reputation formation and social cooperation.
RELATED ESSAYS
Empathy Gaps between Helpers and Help-Seekers: Implications for Cooperation (Psychology), Vanessa K. Bohns and Francis J. Flynn
Close Friendships among Contemporary People (Sociology), Matthew E.
Brashears and Laura Aufderheide Brashears
Identity Fusion (Psychology), Michael D. Burhmester and William B. Swann
Jr.
Neighborhoods and Cognitive Development (Psychology), Jondou Chen and
Jeanne Brooks-Gunn
Peers and Adolescent Risk Taking (Psychology), Jason Chein
Trust and Economic Organization (Sociology), Karen S. Cook and Bogdan
State
Problems Attract Problems: A Network Perspective on Mental Disorders
(Psychology), Angélique Cramer and Denny Borsboom
Cognitive Processes Involved in Stereotyping (Psychology), Susan T. Fiske
and Cydney H. Dupree
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Theodore E. A. Waters
Controlling the Influence of Stereotypes on One’s Thoughts (Psychology),
Patrick S. Forscher and Patricia G. Devine
Family Relationships and Development (Psychology), Joan E. Grusec
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B. Drell
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Emotion and Intergroup Relations (Psychology), Diane M. Mackie et al.

16

EMERGING TRENDS IN THE SOCIAL AND BEHAVIORAL SCIENCES

Media and the development of Identity (Psychology), Adriana M. Manago
Neural and Cognitive Plasticity (Psychology), Eduardo Mercado III
A Bio-Social-Cultural Approach to Early Cognitive Development: Entering
the Community of Minds (Psychology), Katherine Nelson
Social Relationships and Health in Older Adulthood (Psychology), Theodore
F. Robles and Josephine A. Menkin
Stereotype Threat (Psychology), Toni Schmader and William M. Hall
Social Neuroendocrine Approaches to Relationships (Sociology), Sari M. van
Anders and Peter B. Gray



The Others as Social Context: On the
Importance of Strategic Interaction∗
ANDREAS DIEKMANN

Abstract
An action is defined as “strategic” when the consequences of ego’s action depend
on the action of alter. Situations of strategic interaction are numerous in daily life,
business, and politics. Other peoples’ opportunities of actions form ego’s strategic
context. The dynamics of the impact of the strategic context on ego’s action can be
modeled by means of game theory. We discuss three examples of strategic interaction
models: “Diffusion of responsibility,” Boudon’s “logic of relative frustration,” and
the problem of social exchange and trust. We demonstrate the effects of the strategic
context on the opportunities and beliefs of actors. In contrast to nonstrategic rational
choice theory, beliefs and opportunities are not assumed as exogenous. The analysis of the strategic context contributes to a better understanding of the microlevel
effects and the macrolevel implications. However, the strict rationality requirements
of game models are often violated. In these situations, evolutionary models based
on principles of learning and adaptions are more adequate than models based on
assumptions of strict rationality.

INTRODUCTION: CONTEXT AND SOCIAL ACTION
A patient goes to his doctor after receiving a positive result to a prophylactic
test. The doctor recommends special therapy. There is a risk that the doctor,
although acting to the best of his knowledge and belief, is not on top of latest developments in his science and prescribes a therapy with little chance
of success. A further risk lies in the fact that, although the doctor is indeed
well informed, he may not prescribe the optimal therapy because he himself profits from a certain method of treatment. The patient, therefore, has a
double trust problem (Gigerenzer, 2014), unlike an air passenger who trusts
the competence of the pilot. It is similar for the customer of a garage, the
client of an investment advisor in a bank, and for the client of a lawyer or
attorney. The behavior of the patient toward the doctor, the garage employee,
∗ This essay is based on Diekmann (2014). Many thanks to Rachel Matthey for translating the
manuscript.

Emerging Trends in the Social and Behavioral Sciences.
Robert Scott and Marlis Buchmann (General Editors) with Stephen Kosslyn (Consulting Editor).
© 2016 John Wiley & Sons, Inc. ISBN 978-1-118-90077-2.

1

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EMERGING TRENDS IN THE SOCIAL AND BEHAVIORAL SCIENCES

the investment advisor, or the attorney is, in the sense of Max Weber, social
action. However, the two trust problems are not both of a strategic character. Trust in the expertise of the doctor is a nonstrategic decision. In contrast,
the patient’s trust that, in a conflict of interest, the therapy recommended by
the doctor will be to his benefit is of a strategic nature. A distrustful patient
can solve the first trust problem by going to a doctor who has been recommended as competent. He can solve the second trust problem by obtaining a
second opinion, so that no conflict of interest exists. The second trust problem
is strategic because the decision results of patient and doctor, ego and alter,
are mutually dependent on the decisions of the other actor.
This essay will mainly be dealing with the “strategic social context,”
acknowledging that many sociological problems are of strategic character,
but this is often neglected in sociological analysis. In the section titled
“Context, Action, Aggregation, and Macro Effect”, the correlation among
context, action, and effects on the macro level is first explained. On the
basis of the hypothesis of diffusion of responsibility, the competition model
of Raymond Boudon and the trust game is discussed. Section titled “The
Actions of Others as Strategic Context” explains social action in the strategic
context. It shows that the strategic social context requires the application of
game-theoretic methods. When actions are strategic, the independent variables of the theory of social action can no longer be regarded as exogenous.
In addition, game-theoretic methods solve the problem of aggregation. Our
interest also focuses on the development of institutions as a reaction to
the problems of strategic action. Institutions can ease problems of strategic
action. In the section titled “Rational Action, ‘Beauty Contest,’ and Bounded
Rationality”, finally, we discuss the problem of rational action within the
context of strategically deciding actors.
CONTEXT, ACTION, AGGREGATION, AND MACRO EFFECT
Social context influences the action-relevant characteristics of actors. According to a simple heuristic scheme, action and decision theories refer to three categories of independent variables: (i) The value of the action consequences, (ii)
the perceived probability of the appearance of certain action consequences,
and (iii) the action resources. Using Hedström’s (2007) formulation, these are
(i) “desires,” (ii) “beliefs,” and (iii) “opportunities” (DBO), or Gintis’s (2007)
“beliefs, preferences, constraints” (BPC). Preferences correspond to desires,
and constraints correspond to opportunities or resources. Constraints are, for
example, time, income, and technological possibilities. Anyone who buys a
lottery ticket at a kiosk shows the desire (the preference) to make the highest
possible winnings, the belief that there is a certain (subjective) probability
that this wish will be fulfilled and he must carry the costs of the bet. The

The Others as Social Context: On the Importance of Strategic Interaction

3

three elements, DBO (or BPC), do not yet constitute a complete theory. For
this, further elements would be required, such as (i) a procedure for measuring D, B, and O for all action alternatives and action consequences and (ii) a
decision theory showing the probability with which an action is carried out
with any combination of D, B, and O. A theory of social action does not necessarily have to adhere to the principles of strict rationality, it can also follow
the assumptions of “bounded rationality.”
Via DBO, the social context influences the action results, which actors produce through their decisions. The aggregated action results correspond to
the effect on the macro level. The well-known “Coleman-boat” (Coleman,
1990) illustrates these relations for didactic reasons, omitting, however, the
dynamics of the processes and complexities such as local interactions.
Let us look at an example. Emile Durkheim (1952 [1897]) reported on the
analysis of statistical material regarding the frequency of suicide in different
social groups. It was shown that because of a higher degree of social integration, Catholics display a lower suicide rate than Protestants. The degree of
integration is a context characteristic that influences the resources and action
goals of the actors. Thus, in socially integrated groups, isolated and lonely
people are more seldom and that again reduces the tendency toward “egoistical” suicide.
Durkheim’s analysis of suicide deals with “social action” in the sense of
Max Weber. The actions are, however, not strategic. The aggregation is simple, as the rate of suicide in a social group results from the number of suicides
per annum, divided by the size of the population.
The situation is different if actions are strategically linked with each other.
The problem of aggregation is then no longer trivial and can take on a considerably more complex form. In daily interactions, in politics, and in business
life, the actions of individual actors are often mutually dependent on each
other. The resources (opportunities in the DBO scheme), such as the perceived probabilities of action consequences (the beliefs), are then no longer
given as exogenous, but as endogenous, dependent on the actions of others.
THE ACTIONS OF OTHERS AS STRATEGIC CONTEXT
THE PROBLEM OF AGGREGATION AND THE MACRO EFFECT: THE EXAMPLE OF THE “DIFFUSION
OF RESPONSIBILITY”
Strategic action means that the consequences of an action are dependent on
the actions of other actors. Let us take a look at the regularity of the diffusion
of responsibility examined by Darley and Latané (1968) in an experiment.
The more the people that witness an emergency of any kind, the smaller the
probability is that an individual person intervenes. Situations showing the

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EMERGING TRENDS IN THE SOCIAL AND BEHAVIORAL SCIENCES

diffusion of responsibility can also be found in many everyday situations and
in business life. If a seminar is conducted by several lecturers, the individuals
involved are often not as well prepared as when they alone are responsible.
Companies wait for others to develop innovations, which they can later copy
economically (Eger, Kraft, & Weise, 1992). The “volunteer’s dilemma” (Diekmann, 1985) has been proposed as a general model for such a situation.
The situation has a very simple structure. All actors are interested in the
collective good (assistance, good teaching, or innovation) materializing.
We shall call the value of the collective good U, the costs of achieving
it K, whereby U > K > 0. In each case, a cooperative actor gains U − K. A
noncooperative actor receives U, but only when at least one other actor
cooperates; otherwise, all will be left empty-handed.
The structure of an action is given by the type of game and the quantities
N, K, and U. They define the context of the strategic situation. With regard
to the “assistance” example, U can vary interculturally. In an egoistic society,
the value of the collective good will turn out to be lower than in a society that
shows solidarity.
In this situation, there is a symmetrical, individual, rational “solution”: the
Nash equilibrium strategy. It can be deduced with the methods of the classical game theory. Informally, a Nash equilibrium is defined as a combination
of strategies from which no actor is induced to deviate unilaterally—as long
as the other actors maintain the equilibrium strategy.
If p is the probability of cooperation and N is the number of actors, we get
the equilibrium strategy p* (Diekmann, 1985):
√√
N−1
∗
p =1−
K∕U)
The individual tendency to cooperate declines, as expected, with the
costs and increases with the value of the collective good. To be more
exact—although not completely obvious—the probability falls with the
quotients of the costs of the cooperative action and the value of the collective
good. Furthermore, the tendency to cooperate sinks with the number of
actors N. The effect of the diffusion of responsibility observed in experiments can be deduced from a simple model. This model of the structure of
interdependent actions can be extended in different directions. Examples
are the asymmetric volunteer’s dilemma (Diekmann, 1993), the volunteer’s
dilemma with cost sharing (Weesie & Franzen, 1998) and further variations.
These models generate several hypotheses linking structural conditions to
individual behavior.
The Nash equilibrium is also a central element in solving the aggregation
problem. The macro hypothesis about the production of collective good
results directly from the actors’ individual strategies. Both hypotheses can
be tested by empirical data (Franzen, 1995).

The Others as Social Context: On the Importance of Strategic Interaction

5

For a more exact analysis of strategic interaction, we need the models and
the solution concepts of game theory. This applies particularly when—as
in analytical sociology—we are interested in uncovering the explanatory
mechanism (Hedström, 2007). With the help of game theory, one can succeed
in defining the social context and the structure of action more exactly.
Furthermore, hypotheses on individual action strategies can be derived
from these models. Simultaneously, the Nash equilibrium helps to aggregate
individual actions, as well as to deduce the macro effect. In this way, the
three steps—context, individual action, and aggregated macro effect—can
be formulated precisely and the results tested with data.
SOCIAL CONTEXT AND OPPORTUNITIES: THE COMPETITION MODEL OF BOUDON
In their study, Stouffer, Suchman, Vinney, Star, and Williams (1965 [1949])
report on satisfaction with promotion in two army units. Paradoxically,
dissatisfaction is higher among the more frequently promoted pilots than
among the military policemen, who in comparison are rarely promoted.
This study stimulated the development and discussion of relative deprivation and reference groups. Considerably earlier, Tocqueville (2008 [1852])
brought attention to a similar paradox (Boudon, 1977), developing the
hypothesis that dissatisfaction and protests are more likely to culminate in
prosperous periods. Boudon (1977) took up Tocqueville’s thesis again and
tried to explain this remarkable correlation under the premise of rational
behavior with a game-theoretic model.
The essential feature of the theory is as follows: assume that a society’s
increasing prosperity stimulates actors to invest in upward mobility. Some
of the investors will win while others will lose. Under certain conditions,
the level of dissatisfaction in the society or the social group will rise. This
happens when the interaction system leads to a disproportionate growth
between losers and winners.
Game theory translates these ideas in a formal model (cf. Berger & Diekmann, 2015; Raub, 1984). In a social group with the size N, there are 0 ≤ k
≤ N positions available for promotion. Those wishing to be promoted have
to invest. The costs of this amount to C, and the gain from promotion is B.
Successful candidates achieve ? = B − C, losers receive ? = ? − C, and actors
who do not invest in applying receive a payoff in the amount of ? (Figure 1).
? > ? > ? applies. The number of investors is called n.
Here, investing means incurring general expenditure and taking risks,
in order to improve one’s social position. Whether a person is successful
depends, of course, on the behavior of the other competitors. In any case, in
a competition situation, n − k frustrated candidates drop out of the running.

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EMERGING TRENDS IN THE SOCIAL AND BEHAVIORAL SCIENCES

s
p

Invest
Player i

1-s

High payoff
B–C=α
Low payoff
β–C=y

p
1Not invest

Medium payoff
β

Figure 1 Investing in the competition model. Source: Adopted from Berger and
Diekmann (2015), see also Hedström (2007).

Investors can expect the following payoff (Berger & Diekmann, 2015):
{
k
? + n−k
y für k < n
n
E(k, n) = n
?
für k ≥ n.
A rational actor will invest as long as E(k,n) is larger than ?. If this is the
case, independent of the number of competitors n, investing is the dominant
strategy. The situation is somewhat more complicated when “investing” is
not the dominant strategy. In this case, “investing” up to a threshold value
of n* is more advantageous than “not investing.” However, if the number of
candidates is greater than the threshold value, it would be better to abstain
from applying; but, of course, the actors do not know how many competitors
will invest. There are then several equilibria in “pure” strategies, which are
not attainable without coordination, as well as an equilibrium in “mixed”
strategies (Berger & Diekmann, 2015; Raub, 1984).
The structure of social action is given by the rules of the model, as are the
parameters ?, ?, ?, N, and k. These elements define the social context, which
provides the framework for carrying out the competition. The five parameters are exogenous. The opportunities follow from the decision dynamics
and are endogenous. The number of competitors, which considerably influences the candidate’s chances, only comes to light if we assume a hypothesis regarding the decision behavior of the actors. If, like Boudon, we make
the rationality assumption, various hypotheses about the effect of a growing number of chances on the degree of satisfaction or frustration can be
deduced. Under certain circumstances, it can be seen that the number of
losers rises with the growing number of chances (k) and then falls again. The
course of satisfaction, dependent on the number of chances, is U-shaped. The
Nash equilibrium hypothesis, derived from the model, provides information
about the conditions under which the course of satisfaction can be expected

The Others as Social Context: On the Importance of Strategic Interaction

7

to fall, that is, the “Tocqueville effect.” The hypotheses deduced from the theory can then be empirically tested. A first lab experiment shows that a more
refined measure of satisfaction is needed to observe the predicted U-shaped
function (Berger & Diekmann, 2015).
Social context defines the structure of social action, which in turn triggers
the interaction between action dynamics and opportunities. As social
context affects the strategic behavior of actors, simple parametric models
are unsuitable for analyzing the structure of social action. The opportunities
(O in the DBO scheme) are created endogenously. These depend on other
actors’ investment behavior. Only with the help of game-theoretic solution
approaches can the action dynamics be adequately examined. Furthermore,
the Nash equilibrium strategy makes it possible to aggregate the action
results. Under certain conditions, which it is possible to name, the macro
hypothesis follows via the U-shaped course of satisfaction.
SOCIAL CONTEXT AND BELIEFS: SIGNALS OF TRUST
As a rule, social and economic exchanges are linked with a double uncertainty. On the one hand, the exchange is time-delayed, that is, one of the
exchange partners makes an advance. On the other hand, it is not always
immediately clear whether the exchanged good corresponds to expectations.
A problem of trust arises, which can be described with a simple model, the
trust game.
In the trust game (Dasgupta, 1988), two actors interact: the trustor and the
trustee. The trustor has to decide between cooperation (C) or “noncooperation” (defection D). If he chooses D, no business takes place. No one wins and
no one loses; the payoff to both actors amounts to P. However, if the trustor
cooperates, he puts his fate in the hands of the trustee. The trustee, in turn,
can cooperate (e.g., by delivering the goods paid in advance) or defect, that
is, by exploiting the trustor’s position. With the usual symbols of the trust
game, both actors receive a payoff R after cooperation. On the other hand,
if the trustee defects, he receives the exploitation payoff T and the trustor
makes a loss S. The rank order of the payoffs is T > R > P > S.
In a single trust game, a self-interested, rational trustee will defect as soon
as it is his turn. The trustor anticipates this and will not trust him. The Nash
equilibrium is mutual defection with the result (P, P). A deal will not take
place, so both lose in comparison to the result of mutual cooperation, where
they would both receive R.
If, however, exchanges between partners take place repeatedly, cooperation
can develop if the gains expected from the exchange relationship in the future
are high enough. Moreover, it may be that the trustee complies with ethical
norms or has a reputation as an honest businessman, which he does not want

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EMERGING TRENDS IN THE SOCIAL AND BEHAVIORAL SCIENCES

to risk losing. The problem lies in the fact that, with a single transaction or at
the beginning of a series of transactions, the trustor does not know whether
his business partner is trustworthy or not.
These reflections could be more precise by extending the trust game (Voss,
1998). We assume that there are honest and dishonest trustees. The honest
trustees are interested in future business with the payoff R* > T, for the dishonest it is, as before, T > R. The actors are in this case “honest” or “dishonest” depending on where their interests lie. Trustors know that a portion of
the business partners are honest (?) and another portion fraudulent (1 − ?). If
they have no further information, they will always cooperate as long as ? is
larger than the threshold value ?*, whereby they can gain at least as much by
cooperating as by abstaining from business relations, or at least P. Trustors
always cooperate when ? ≥ ?* = (P−S)/(R−S) and accept the losses caused by
fraudulent partners.
However, if the portion of fraudulent actors becomes too big (? < ?*),
cooperation is no longer worthwhile. In that case, no business is carried out;
the market collapses and all actors, including the fraudulent trader, are left
empty-handed. In such situations, it is very probable that signals emerge
with which trustees can communicate to trustors that they are honest (for
more details, see Przepiorka & Diekmann, 2013). The fraudulent trustors are,
of course, also interested in appearing honest. So a signal is only useful if it is
credible. From the signal, one must be able to recognize the “type” to which
an actor belongs. Credible signals are connected with costs, or, to be more
exact, with the difference in the cost of producing signals. This difference
must be so high that honest actors profit from cooperation (R* − sA > P),
despite signaling costs, while fraudulent actors do not gain if they initiate
a signal (T − sB < P). sA and sB designate the signaling costs of honest and
fraudulent actors, respectively. Under these circumstances, a so-called
separating signaling equilibrium is to be expected. Tattoos were (in the past)
signals that transmitted the information that a person had been in prison and
in all probability would be reliable in any illegal business (Gambetta, 2009).
Police spies, in contrast, were usually not tattooed, provided that they led a
respectable life and the (social) costs of a tattoo were unacceptable. During
courtship, there can be a problem in most cultures when a young man is not
serious about a permanent relationship. Expensive engagement presents are
a signal that differentiates the honest suitor from the dishonest one.
Honest dealers in second-hand wares give a guarantee. If they are honest (and make no mistakes), the costs are zero. For dishonest dealers in
second-hand wares, on the other hand, the costs would be prohibitively
high. The promise of a guarantee is a signal that allows the customer to
distinguish between honest and fraudulent dealers.

The Others as Social Context: On the Importance of Strategic Interaction

9

For this discussion, it is important to note that, in signaling games, the
subjective probability that an actor belongs to a certain type can only be determined by the actions of the actor.
The social context consists of the game structure (decision tree), the preferences of specific types of actors (the D in DBO), and the signaling costs.
These elements are exogenous. The beliefs (the B in DBO), in contrast, follow
from the action dynamics and are endogenous. The social context influences
the beliefs and these in turn the actions. In the trust game, this is the decision in favor of cooperation. As the macro result, markets emerge in which
cooperative exchanges are carried out.
INSTITUTIONS
In trust relationships, signals will emerge when legal or other institutional
regulations are not possible or are difficult to enforce (e.g., in illegal markets),
when most transactions are nonrepeated or seldom repeated, and also when
no reliable information about the reputation of the actors is available. Dependent on the specific context (e.g., nonrepeated vs repeated interactions and
access to reliable information), different cooperation solutions can develop
in the trust relationships (Buskens & Raub, 2013).
A study by Siamwalla (1978) about the market structure of agricultural
products in Thailand is instructive. The quality of rice, for example, is easily
recognizable before the purchase, so that no specific trust problem regarding
quality exists. On the other hand, the rubber farmer himself knows much better than the buyer whether the product is of high or low quality. The quality
of the raw product depends namely on the care taken by the farmer in eliminating impurities, as well as on the quality of the acid used (Siamwalla, 1978).
Because of the asymmetric information, a trust problem arises. Compared to
the rice market, therefore, the market structure that emerged for rubber is different. Loyalty between the seller and the purchaser is high; a rubber farmer
only deals with a few buyers, and they know the farmer and trust the quality
of the goods. In addition, there is the “chain structure” of the trade. A buyer
in the village sells to a dealer in the district and he in turn to a wholesaler or
large trading company (Siamwalla, 1978).
The characteristics of the different goods, in this case rubber versus rice, create trust problems to varying degrees. These problems are solved by different market structures or institutions. Rice markets are often auctions, while
long-term relationships between trading partners and reputation are characteristic of the markets for the raw material, rubber (Kollock, 1994). In an
imaginative experiment, Kollock (1994) was able to demonstrate the emergence of varying market structures.

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EMERGING TRENDS IN THE SOCIAL AND BEHAVIORAL SCIENCES

In digital trade, trust problems emerge because of the anonymity of the market participants, who often buy goods at auction per mouse click over great
distances. Given the standard trust game and assuming rational and selfish
preferences, there is a unique Nash equilibrium: exchanges should not even
take place; anonymous markets are expected to collapse. However, we are
not dealing here with a simple trust game. With the introduction of the possibility to assess the seller, the trust problem has been considerably defused.
Instead of the “shadow of the future” in the repeated game, the “shadow of
the past” was quasi created with the introduction of reputation. In their own
interests, sellers try to build up a reputation; purchasers, in turn, reward a
reputation. However, it cannot be completely taken for granted that the rating system functions, as self-interested actors may just save themselves the
bother of an assessment. Homo economicus would give no feedback, the rating system would collapse and with it the auction too. Thus, a small shot
of altruism and reciprocity, which goes over and above the self-interest of
homo economicus, is the lubricating oil of anonymous, electronic markets.
The reputation system is a simple, but extremely effective, institutional mechanism, which makes these markets—worth billions—really possible (Diekmann, Jann, Przepiorka, & Wehrli, 2014).
The strategic context of the trading actors creates a trust problem. Institutional regulations can alleviate the problem. The question as to what kind
of regulation emerges depends on various conditions, such as information
asymmetries, transaction costs, and technological progress. The context of
strategically trading actors is the starting point for explaining the development of institutions.
RATIONAL ACTION, “BEAUTY CONTEST” AND BOUNDED
RATIONALITY
There is scarcely another term in the social sciences that is as heavily burdened with misunderstandings as the term rationality or rational action. With
rationality, we understand here no more (and no less) than consistent decisions. Consistency is the defining characteristic. This means that decisions
are taken in agreement with the axioms of a rationality theory. Corresponding to this definition, there are more or less restrictive requirements for the
term rational action, as there are various decision theories with differing axiom
systems. However, when explaining social action, whether we describe the
behavior as “rational” or not is insignificant anyway. However, most decision
theories will probably prescribe the validity of one axiom, namely, the transitivity of preferences: When A is preferred to alternative B and B to alternative
C, then A should also be given preference over C.

The Others as Social Context: On the Importance of Strategic Interaction

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Rationality does not call for self-interest, and certainly not for material
self-interest. Homo economicus acts rationally per definition, but rational
action is not synonymous with the action of the fictive homo economicus.
Rationality and altruism do not have to be opposites. Andreoni and Miller
(2002) have shown that actors with altruistic preferences can act rationally
in the sense that they fulfill the axioms of decision theory. If people do
not correspond to the picture of homo economicus, and in addition they
even follow altruistic goals, this does not necessarily mean that they act
irrationally. In concurrence with the consistency criterion, their decisions
can be strictly rational. Here, “rationality” is defined in a “motive-free” way,
without excluding certain preferences, goals, or desires. The “wide version”
of rational choice theory (Opp, 1999) already follows from an axiomatic
approach.
Nevertheless, one can observe spectacular deviations from strict principles
of rationality in many situations. The “Beauty-Contest Game” received its
name from a quotation from Keynes, in which he compares the purchase of
stocks to a beauty contest (Selten & Nagel, 1998). On the stock market, it is
not about deciding which is the best share in one’s own opinion, but rather
which is the one that you believe others will think is the best decision; even
more than that, it is about the share that you believe everyone believes that the
others consider to be the best purchase, and so on. The rules of the game are
simple. There are N participants who have to choose a number between zero
and 100. The person who comes nearest to 2/3 of the (arithmetical) mean of
all numbers mentioned wins a prize. When there is more than one winner,
the prize is shared.
If one does not think strategically, one could say, “All numbers are evenly
distributed, the mean should therefore lie by 50. I choose 33 1/3, for that is
2/3 of 50.” Strategic thinking on this first level goes a step further. “If everyone thinks like this, the mean will be 33 1/3. I choose, therefore, 22 2/9.”
On the next level of strategic thinking, it is approximately 15 and so forth,
until finally in continual iteration one approaches at zero, the unique Nash
equilibrium strategy.
However, the equilibrium strategy is rarely chosen in the first round of
experiments. Typically, choices accumulate around 33 or 22. If one repeats
the decision situation and informs about the mean, values around 15 or 10
will result and, in a further round, numbers approaching the equilibrium will
be observed (Selten & Nagel, 1998). This process can also be seen when exact
information about the distribution in the previous round is given (Diekmann,
2009). One could now assume that the actors do not choose the equilibrium
strategy because they do not know about it. However, even if it is explained,
many actors by no means use this strategy. Why do actors act “irrationally”? The answer is as follows: Even if one knows that it is rational to choose

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EMERGING TRENDS IN THE SOCIAL AND BEHAVIORAL SCIENCES

zero, one can still reckon on some of the players not doing so (Selten & Nagel,
1998). In that case, it makes more sense not to choose the equilibrium strategy
and, therefore, one does not choose this strategy oneself either.
The beauty-contest game has been used to explain speculative bubbles on
the stock and property markets. Even if one knows that it is a bubble it can
be worth investing. For the prices can rise further, up until the occurrence
of the catastrophe. Similarly, actors in the beauty-contest game choose the
“irrational” strategy at least occasionally, although they know about the equilibrium strategy. The head of the Citigroup, Charles Prince, formulated this
thought more concretely in the “Financial Times” in July 2007, shortly before
the crisis broke: “When the music stops, in terms of liquidity, things will be
complicated. But as long as the music is playing, you’ve got to get up and
dance. We’re still dancing” (Akerlof & Shiller, 2010, p. xii). In the following
year, the bubble burst!
The step-by-step approach to the equilibrium strategy during the growing number of rounds in the beauty contest demonstrates that equilibrium
points can be achieved by learning and adaptive behavior in the course of the
evolutionary process. Learning, adaptive and myopic behavior can often be
observed in experimental studies. In these cases, theories of bounded rationality, which are explicitly based on the principles of adaptive behavior, are
superior to strict rationality theories.
OUTLOOK
Pioneers in sociology, such as Erving Goffman and Raymond Boudon, recognized that in many cases strategic action is the key to explaining social
processes. Social actions in Max Weber’s sense are of strategic character when
they are not purely oriented on the actions of others but rather are dependent on the results of others’ actions. This distinguishes mere imitation from
a mass panic, a stock market crash, or the growth of a protest movement.
Today, there are increasingly improved models of classical and behavioral
game theory available, with the help of which it is now possible to describe
the strategic context or the structure of strategic interaction precisely and
to deduce testable conclusions. The fundamental problems of sociological
research are of strategic character: the emergence of social order, the problems of cooperation, conflict and the decline of order, compliance with social
norms and the problem of sanctioning, the emergence of institutions, social
exchange and the problem of trust, the development of protest movements,
social dilemmas, and collective goods. Modern methods of analyzing strategic interaction should be employed more widely in both the curriculum of
sociology students and in sociological research.

The Others as Social Context: On the Importance of Strategic Interaction

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Undeniably, classical game theory requires strong rationality assumptions.
In situations where these models allow sufficiently valid predictions, there is
no reason to introduce alternative decision principles. Furthermore, the theory delivers a reference point. If the observed behavior deviates from that,
there is the challenge of explaining the “anomaly.” In this way, new hypotheses and explanations have often been produced. When the strict rationality
models fail—as demonstrated in the beauty contest—one can fall back on
models of “bounded” rationality. There is no general and mechanically applicable theory—otherwise, we could leave the theory building to a computer.
Rational choice theory, bounded rationality, analytical sociology, game theory, and psychological decision research should, instead, be understood as a
“tool box.” They deliver heuristic principles and instruments for building a
theory of the middle range (Merton, 1949) in a concrete area of application,
the findings of which can be tested on empirical data.
REFERENCES
Akerlof, G. A., & Shiller, R. J. (2010). Animal spirits (9th ed.). Princeton, NJ: Princeton
University Press.
Andreoni, J., & Miller, J. (2002). Giving according to GARP: An experimental test of
the consistency of preferences for Altruism. Econometrica, 70, 737–753.
Berger, J., & Diekmann, A. (2015). The logic of relative frustration. Boudon’s competition model and experimental evidence. European Sociological Review, 31, 725–737.
Boudon, R. (1977). Logic of relative frustration. Archives Europeennes de Sociologie, 18,
3–26.
Buskens, V., & Raub, W. (2013). Rational choice research on social dilemmas: Embeddedness effects on trust. In R. Wittek, T. A. B. Snijders & V. Nee (Eds.), The handbook
of rational choice social research. Stanford, CA: Stanford University Press.
Coleman, J. (1990). Foundations of social theory. Cambridge, MA: Harvard University
Press.
Darley, J. M., & Latané, B. (1968). Bystander intervention in emergencies. Diffusion
of responsibility. Journal of Personality and Social Psychology, 8, 377–383.
Dasgupta, P. (1988). Trust as a commodity. In D. Gambetta (Ed.), Trust. Making and
breaking cooperative relations (pp. 49–72). Oxford, England: Blackwell.
Diekmann, A. (1985). Volunteer’s dilemma. Journal of Conflict Resolution, 29, 605–610.
Diekmann, A. (1993). Cooperation in an asymmetric volunteer’s dilemma game.
Theory and experimental evidence. International Journal of Game Theory, 22, 75–85.
Diekmann, A. (2009). Rational choice, evolution and the “Beauty Contest”. In M.
Cherkaoui & P. Hamilton (Eds.), Raymond Boudon – a life in sociology (pp. 1–12).
Oxford, England: Bardwell Press.
Diekmann, A. (2014). Die Anderen als sozialer Kontext. In J. Friedrichs, A. Nonnenmacher, (Eds.), “Sozialer Kontext und soziale Mechanismen” der Kölner Zeitschrift
für Soziologie und Sozialpsychologie, 66(special issue), 47–66.

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Diekmann, A., Jann, B., Przepiorka, W., & Wehrli, S. (2014). Reputation formation and
the evolution of cooperation in anonymous online markets. The American Sociological Review, 79(1), 65–85.
Durkheim, E. (1952 [1897]). Suicide: A study in sociology. London, England: Routledge
and Kegan Paul.
Eger, T., Kraft, M., & Weise, P. (1992). On the equilibrium proportion of innovation
and imitation. A game-theoretic approach. Economics Letters, 38, 93–97.
Franzen, A. (1995). Group size and one-shot collective action. Rationality and Society,
7, 183–200.
Gambetta, D. (2009). Codes of the underworld: How criminals communicate. Princeton,
NJ: Princeton University Press.
Gigerenzer, G. (2014). Risk Savvy. How to make good decisions. New York, NY: Viking.
Gintis, H. (2007). A framework for the unification of the behavioral sciences. Behavioral and Brain Sciences, 30, 1–61.
Hedström, P. (2007). Dissecting the social. On the principles of analytical sociology. Cambridge, MA: Cambridge University Press.
Kollock, P. (1994). The emergence of exchange structures: An experimental study of
uncertainty, commitment, and trust. American Journal of Sociology, 100, 313–345.
Merton, R. K. (1949). Social theory and social structure. New York, NY: The Free Press.
Opp, K.-D. (1999). Contending conceptions of the theory of rational action. Journal of
Theoretical Politics, 11, 171–202.
Przepiorka, W., & Diekmann, A. (2013). Temporal embeddedness and signals of
trustworthiness: Experimental tests of a game theoretic model in the United Kingdom, Russia, and Switzerland. European Sociological Review, 29, 1010–1023.
Raub, W. (1984). Rationale Akteure, institutionelle Regelungen und Interdependenzen. Untersuchungen zu einer erklärenden Soziologie auf strukturell-individualistischer
Grundlage. Frankfurt am Main, Germany: Peter Lang.
Selten, R., & Nagel, R. (1998). Das Zahlenwahlspiel. Hintergründe und Ergebnisse.
Spektrum der Wissenschaft, 2(1998), 16–22.
Siamwalla, A. (1978). Farmers and middlemen. Aspects of agricultural marketing in
Thailand. Economic Bulletin for Asia and the Pacific, 38–50.
Stouffer, S. A., Suchman, E. A., Vinney, L. C. de, Star, S. A., & Williams, R. M. Jr. (1965
[1949]). The American soldier. Manhattan, KS: Military Affairs, Aerospace Historian
Publishing.
Tocqueville, A. de (2008 [1856]). Ancient regime and the French revolution. London,
England: Penguin.
Voss, T. (1998). Vertrauen in modernen Gesellschaften. In R. Metze, K. Mühler & K.-D.
Opp (Eds.), Der Transformationsprozess. Leipzig, Germany: Universitätsverlag.
Weesie, J., & Franzen, A. (1998). Cost sharing in a volunteer’s dilemma. Journal of
Conflict Resolution, 42, 600–618.

ANDREAS DIEKMANN SHORT BIOGRAPHY
Andreas Diekmann is a professor of sociology at the ETH Zurich. He earned
a doctoral degree from the University of Hamburg in 1979 (Dr. rer. pol.),

The Others as Social Context: On the Importance of Strategic Interaction

15

and received the “venia legendi” (Dr. rer. pol. habil.) from the University of
Munich (1987). His areas of research are social cooperation and experimental
game theory, environmental and population sociology, and methods of
empirical social research. He served as a member of the Humboldt Professor
Price Committee and is chairman and senator of the section “Economics and
Empirical Social Sciences” of the German Academy of Sciences Leopoldina.
He is also a fellow of the European Academy of Sociology and coeditor and
board member of several professional journals and research institutions.
Present research activities focus on experimental research on social norms
and energy consumption, an analysis of the environmental burden of
metropolitan areas with geo-referenced panel data (supported by grants
of the Swiss National Science Foundation) and experimental research on
reputation formation and social cooperation.
RELATED ESSAYS
Empathy Gaps between Helpers and Help-Seekers: Implications for Cooperation (Psychology), Vanessa K. Bohns and Francis J. Flynn
Close Friendships among Contemporary People (Sociology), Matthew E.
Brashears and Laura Aufderheide Brashears
Identity Fusion (Psychology), Michael D. Burhmester and William B. Swann
Jr.
Neighborhoods and Cognitive Development (Psychology), Jondou Chen and
Jeanne Brooks-Gunn
Peers and Adolescent Risk Taking (Psychology), Jason Chein
Trust and Economic Organization (Sociology), Karen S. Cook and Bogdan
State
Problems Attract Problems: A Network Perspective on Mental Disorders
(Psychology), Angélique Cramer and Denny Borsboom
Cognitive Processes Involved in Stereotyping (Psychology), Susan T. Fiske
and Cydney H. Dupree
Patterns of Attachments across the Lifespan (Psychology), Robyn Fivush and
Theodore E. A. Waters
Controlling the Influence of Stereotypes on One’s Thoughts (Psychology),
Patrick S. Forscher and Patricia G. Devine
Family Relationships and Development (Psychology), Joan E. Grusec
The Development of Social Trust (Psychology), Vikram K. Jaswal and Marissa
B. Drell
Herd Behavior (Psychology), Tatsuya Kameda and Reid Hastie
From Individual Rationality to Socially Embedded Self-Regulation (Sociology), Siegwart Lindenberg
Emotion and Intergroup Relations (Psychology), Diane M. Mackie et al.

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EMERGING TRENDS IN THE SOCIAL AND BEHAVIORAL SCIENCES

Media and the development of Identity (Psychology), Adriana M. Manago
Neural and Cognitive Plasticity (Psychology), Eduardo Mercado III
A Bio-Social-Cultural Approach to Early Cognitive Development: Entering
the Community of Minds (Psychology), Katherine Nelson
Social Relationships and Health in Older Adulthood (Psychology), Theodore
F. Robles and Josephine A. Menkin
Stereotype Threat (Psychology), Toni Schmader and William M. Hall
Social Neuroendocrine Approaches to Relationships (Sociology), Sari M. van
Anders and Peter B. Gray


The Others as Social Context: On the
Importance of Strategic Interaction∗
ANDREAS DIEKMANN

Abstract
An action is defined as “strategic” when the consequences of ego’s action depend
on the action of alter. Situations of strategic interaction are numerous in daily life,
business, and politics. Other peoples’ opportunities of actions form ego’s strategic
context. The dynamics of the impact of the strategic context on ego’s action can be
modeled by means of game theory. We discuss three examples of strategic interaction
models: “Diffusion of responsibility,” Boudon’s “logic of relative frustration,” and
the problem of social exchange and trust. We demonstrate the effects of the strategic
context on the opportunities and beliefs of actors. In contrast to nonstrategic rational
choice theory, beliefs and opportunities are not assumed as exogenous. The analysis of the strategic context contributes to a better understanding of the microlevel
effects and the macrolevel implications. However, the strict rationality requirements
of game models are often violated. In these situations, evolutionary models based
on principles of learning and adaptions are more adequate than models based on
assumptions of strict rationality.

INTRODUCTION: CONTEXT AND SOCIAL ACTION
A patient goes to his doctor after receiving a positive result to a prophylactic
test. The doctor recommends special therapy. There is a risk that the doctor,
although acting to the best of his knowledge and belief, is not on top of latest developments in his science and prescribes a therapy with little chance
of success. A further risk lies in the fact that, although the doctor is indeed
well informed, he may not prescribe the optimal therapy because he himself profits from a certain method of treatment. The patient, therefore, has a
double trust problem (Gigerenzer, 2014), unlike an air passenger who trusts
the competence of the pilot. It is similar for the customer of a garage, the
client of an investment advisor in a bank, and for the client of a lawyer or
attorney. The behavior of the patient toward the doctor, the garage employee,
∗ This essay is based on Diekmann (2014). Many thanks to Rachel Matthey for translating the
manuscript.

Emerging Trends in the Social and Behavioral Sciences.
Robert Scott and Marlis Buchmann (General Editors) with Stephen Kosslyn (Consulting Editor).
© 2016 John Wiley & Sons, Inc. ISBN 978-1-118-90077-2.

1

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EMERGING TRENDS IN THE SOCIAL AND BEHAVIORAL SCIENCES

the investment advisor, or the attorney is, in the sense of Max Weber, social
action. However, the two trust problems are not both of a strategic character. Trust in the expertise of the doctor is a nonstrategic decision. In contrast,
the patient’s trust that, in a conflict of interest, the therapy recommended by
the doctor will be to his benefit is of a strategic nature. A distrustful patient
can solve the first trust problem by going to a doctor who has been recommended as competent. He can solve the second trust problem by obtaining a
second opinion, so that no conflict of interest exists. The second trust problem
is strategic because the decision results of patient and doctor, ego and alter,
are mutually dependent on the decisions of the other actor.
This essay will mainly be dealing with the “strategic social context,”
acknowledging that many sociological problems are of strategic character,
but this is often neglected in sociological analysis. In the section titled
“Context, Action, Aggregation, and Macro Effect”, the correlation among
context, action, and effects on the macro level is first explained. On the
basis of the hypothesis of diffusion of responsibility, the competition model
of Raymond Boudon and the trust game is discussed. Section titled “The
Actions of Others as Strategic Context” explains social action in the strategic
context. It shows that the strategic social context requires the application of
game-theoretic methods. When actions are strategic, the independent variables of the theory of social action can no longer be regarded as exogenous.
In addition, game-theoretic methods solve the problem of aggregation. Our
interest also focuses on the development of institutions as a reaction to
the problems of strategic action. Institutions can ease problems of strategic
action. In the section titled “Rational Action, ‘Beauty Contest,’ and Bounded
Rationality”, finally, we discuss the problem of rational action within the
context of strategically deciding actors.
CONTEXT, ACTION, AGGREGATION, AND MACRO EFFECT
Social context influences the action-relevant characteristics of actors. According to a simple heuristic scheme, action and decision theories refer to three categories of independent variables: (i) The value of the action consequences, (ii)
the perceived probability of the appearance of certain action consequences,
and (iii) the action resources. Using Hedström’s (2007) formulation, these are
(i) “desires,” (ii) “beliefs,” and (iii) “opportunities” (DBO), or Gintis’s (2007)
“beliefs, preferences, constraints” (BPC). Preferences correspond to desires,
and constraints correspond to opportunities or resources. Constraints are, for
example, time, income, and technological possibilities. Anyone who buys a
lottery ticket at a kiosk shows the desire (the preference) to make the highest
possible winnings, the belief that there is a certain (subjective) probability
that this wish will be fulfilled and he must carry the costs of the bet. The

The Others as Social Context: On the Importance of Strategic Interaction

3

three elements, DBO (or BPC), do not yet constitute a complete theory. For
this, further elements would be required, such as (i) a procedure for measuring D, B, and O for all action alternatives and action consequences and (ii) a
decision theory showing the probability with which an action is carried out
with any combination of D, B, and O. A theory of social action does not necessarily have to adhere to the principles of strict rationality, it can also follow
the assumptions of “bounded rationality.”
Via DBO, the social context influences the action results, which actors produce through their decisions. The aggregated action results correspond to
the effect on the macro level. The well-known “Coleman-boat” (Coleman,
1990) illustrates these relations for didactic reasons, omitting, however, the
dynamics of the processes and complexities such as local interactions.
Let us look at an example. Emile Durkheim (1952 [1897]) reported on the
analysis of statistical material regarding the frequency of suicide in different
social groups. It was shown that because of a higher degree of social integration, Catholics display a lower suicide rate than Protestants. The degree of
integration is a context characteristic that influences the resources and action
goals of the actors. Thus, in socially integrated groups, isolated and lonely
people are more seldom and that again reduces the tendency toward “egoistical” suicide.
Durkheim’s analysis of suicide deals with “social action” in the sense of
Max Weber. The actions are, however, not strategic. The aggregation is simple, as the rate of suicide in a social group results from the number of suicides
per annum, divided by the size of the population.
The situation is different if actions are strategically linked with each other.
The problem of aggregation is then no longer trivial and can take on a considerably more complex form. In daily interactions, in politics, and in business
life, the actions of individual actors are often mutually dependent on each
other. The resources (opportunities in the DBO scheme), such as the perceived probabilities of action consequences (the beliefs), are then no longer
given as exogenous, but as endogenous, dependent on the actions of others.
THE ACTIONS OF OTHERS AS STRATEGIC CONTEXT
THE PROBLEM OF AGGREGATION AND THE MACRO EFFECT: THE EXAMPLE OF THE “DIFFUSION
OF RESPONSIBILITY”
Strategic action means that the consequences of an action are dependent on
the actions of other actors. Let us take a look at the regularity of the diffusion
of responsibility examined by Darley and Latané (1968) in an experiment.
The more the people that witness an emergency of any kind, the smaller the
probability is that an individual person intervenes. Situations showing the

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EMERGING TRENDS IN THE SOCIAL AND BEHAVIORAL SCIENCES

diffusion of responsibility can also be found in many everyday situations and
in business life. If a seminar is conducted by several lecturers, the individuals
involved are often not as well prepared as when they alone are responsible.
Companies wait for others to develop innovations, which they can later copy
economically (Eger, Kraft, & Weise, 1992). The “volunteer’s dilemma” (Diekmann, 1985) has been proposed as a general model for such a situation.
The situation has a very simple structure. All actors are interested in the
collective good (assistance, good teaching, or innovation) materializing.
We shall call the value of the collective good U, the costs of achieving
it K, whereby U > K > 0. In each case, a cooperative actor gains U − K. A
noncooperative actor receives U, but only when at least one other actor
cooperates; otherwise, all will be left empty-handed.
The structure of an action is given by the type of game and the quantities
N, K, and U. They define the context of the strategic situation. With regard
to the “assistance” example, U can vary interculturally. In an egoistic society,
the value of the collective good will turn out to be lower than in a society that
shows solidarity.
In this situation, there is a symmetrical, individual, rational “solution”: the
Nash equilibrium strategy. It can be deduced with the methods of the classical game theory. Informally, a Nash equilibrium is defined as a combination
of strategies from which no actor is induced to deviate unilaterally—as long
as the other actors maintain the equilibrium strategy.
If p is the probability of cooperation and N is the number of actors, we get
the equilibrium strategy p* (Diekmann, 1985):
√√
N−1
∗
p =1−
K∕U)
The individual tendency to cooperate declines, as expected, with the
costs and increases with the value of the collective good. To be more
exact—although not completely obvious—the probability falls with the
quotients of the costs of the cooperative action and the value of the collective
good. Furthermore, the tendency to cooperate sinks with the number of
actors N. The effect of the diffusion of responsibility observed in experiments can be deduced from a simple model. This model of the structure of
interdependent actions can be extended in different directions. Examples
are the asymmetric volunteer’s dilemma (Diekmann, 1993), the volunteer’s
dilemma with cost sharing (Weesie & Franzen, 1998) and further variations.
These models generate several hypotheses linking structural conditions to
individual behavior.
The Nash equilibrium is also a central element in solving the aggregation
problem. The macro hypothesis about the production of collective good
results directly from the actors’ individual strategies. Both hypotheses can
be tested by empirical data (Franzen, 1995).

The Others as Social Context: On the Importance of Strategic Interaction

5

For a more exact analysis of strategic interaction, we need the models and
the solution concepts of game theory. This applies particularly when—as
in analytical sociology—we are interested in uncovering the explanatory
mechanism (Hedström, 2007). With the help of game theory, one can succeed
in defining the social context and the structure of action more exactly.
Furthermore, hypotheses on individual action strategies can be derived
from these models. Simultaneously, the Nash equilibrium helps to aggregate
individual actions, as well as to deduce the macro effect. In this way, the
three steps—context, individual action, and aggregated macro effect—can
be formulated precisely and the results tested with data.
SOCIAL CONTEXT AND OPPORTUNITIES: THE COMPETITION MODEL OF BOUDON
In their study, Stouffer, Suchman, Vinney, Star, and Williams (1965 [1949])
report on satisfaction with promotion in two army units. Paradoxically,
dissatisfaction is higher among the more frequently promoted pilots than
among the military policemen, who in comparison are rarely promoted.
This study stimulated the development and discussion of relative deprivation and reference groups. Considerably earlier, Tocqueville (2008 [1852])
brought attention to a similar paradox (Boudon, 1977), developing the
hypothesis that dissatisfaction and protests are more likely to culminate in
prosperous periods. Boudon (1977) took up Tocqueville’s thesis again and
tried to explain this remarkable correlation under the premise of rational
behavior with a game-theoretic model.
The essential feature of the theory is as follows: assume that a society’s
increasing prosperity stimulates actors to invest in upward mobility. Some
of the investors will win while others will lose. Under certain conditions,
the level of dissatisfaction in the society or the social group will rise. This
happens when the interaction system leads to a disproportionate growth
between losers and winners.
Game theory translates these ideas in a formal model (cf. Berger & Diekmann, 2015; Raub, 1984). In a social group with the size N, there are 0 ≤ k
≤ N positions available for promotion. Those wishing to be promoted have
to invest. The costs of this amount to C, and the gain from promotion is B.
Successful candidates achieve 𝛼 = B − C, losers receive 𝛾 = 𝛽 − C, and actors
who do not invest in applying receive a payoff in the amount of 𝛽 (Figure 1).
𝛼 > 𝛽 > 𝛾 applies. The number of investors is called n.
Here, investing means incurring general expenditure and taking risks,
in order to improve one’s social position. Whether a person is successful
depends, of course, on the behavior of the other competitors. In any case, in
a competition situation, n − k frustrated candidates drop out of the running.

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EMERGING TRENDS IN THE SOCIAL AND BEHAVIORAL SCIENCES

s
p

Invest
Player i

1-s

High payoff
B–C=α
Low payoff
β–C=y

p
1Not invest

Medium payoff
β

Figure 1 Investing in the competition model. Source: Adopted from Berger and
Diekmann (2015), see also Hedström (2007).

Investors can expect the following payoff (Berger & Diekmann, 2015):
{
k
𝛼 + n−k
y für k < n
n
E(k, n) = n
𝛼
für k ≥ n.
A rational actor will invest as long as E(k,n) is larger than 𝛽. If this is the
case, independent of the number of competitors n, investing is the dominant
strategy. The situation is somewhat more complicated when “investing” is
not the dominant strategy. In this case, “investing” up to a threshold value
of n* is more advantageous than “not investing.” However, if the number of
candidates is greater than the threshold value, it would be better to abstain
from applying; but, of course, the actors do not know how many competitors
will invest. There are then several equilibria in “pure” strategies, which are
not attainable without coordination, as well as an equilibrium in “mixed”
strategies (Berger & Diekmann, 2015; Raub, 1984).
The structure of social action is given by the rules of the model, as are the
parameters 𝛼, 𝛽, 𝛾, N, and k. These elements define the social context, which
provides the framework for carrying out the competition. The five parameters are exogenous. The opportunities follow from the decision dynamics
and are endogenous. The number of competitors, which considerably influences the candidate’s chances, only comes to light if we assume a hypothesis regarding the decision behavior of the actors. If, like Boudon, we make
the rationality assumption, various hypotheses about the effect of a growing number of chances on the degree of satisfaction or frustration can be
deduced. Under certain circumstances, it can be seen that the number of
losers rises with the growing number of chances (k) and then falls again. The
course of satisfaction, dependent on the number of chances, is U-shaped. The
Nash equilibrium hypothesis, derived from the model, provides information
about the conditions under which the course of satisfaction can be expected

The Others as Social Context: On the Importance of Strategic Interaction

7

to fall, that is, the “Tocqueville effect.” The hypotheses deduced from the theory can then be empirically tested. A first lab experiment shows that a more
refined measure of satisfaction is needed to observe the predicted U-shaped
function (Berger & Diekmann, 2015).
Social context defines the structure of social action, which in turn triggers
the interaction between action dynamics and opportunities. As social
context affects the strategic behavior of actors, simple parametric models
are unsuitable for analyzing the structure of social action. The opportunities
(O in the DBO scheme) are created endogenously. These depend on other
actors’ investment behavior. Only with the help of game-theoretic solution
approaches can the action dynamics be adequately examined. Furthermore,
the Nash equilibrium strategy makes it possible to aggregate the action
results. Under certain conditions, which it is possible to name, the macro
hypothesis follows via the U-shaped course of satisfaction.
SOCIAL CONTEXT AND BELIEFS: SIGNALS OF TRUST
As a rule, social and economic exchanges are linked with a double uncertainty. On the one hand, the exchange is time-delayed, that is, one of the
exchange partners makes an advance. On the other hand, it is not always
immediately clear whether the exchanged good corresponds to expectations.
A problem of trust arises, which can be described with a simple model, the
trust game.
In the trust game (Dasgupta, 1988), two actors interact: the trustor and the
trustee. The trustor has to decide between cooperation (C) or “noncooperation” (defection D). If he chooses D, no business takes place. No one wins and
no one loses; the payoff to both actors amounts to P. However, if the trustor
cooperates, he puts his fate in the hands of the trustee. The trustee, in turn,
can cooperate (e.g., by delivering the goods paid in advance) or defect, that
is, by exploiting the trustor’s position. With the usual symbols of the trust
game, both actors receive a payoff R after cooperation. On the other hand,
if the trustee defects, he receives the exploitation payoff T and the trustor
makes a loss S. The rank order of the payoffs is T > R > P > S.
In a single trust game, a self-interested, rational trustee will defect as soon
as it is his turn. The trustor anticipates this and will not trust him. The Nash
equilibrium is mutual defection with the result (P, P). A deal will not take
place, so both lose in comparison to the result of mutual cooperation, where
they would both receive R.
If, however, exchanges between partners take place repeatedly, cooperation
can develop if the gains expected from the exchange relationship in the future
are high enough. Moreover, it may be that the trustee complies with ethical
norms or has a reputation as an honest businessman, which he does not want

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EMERGING TRENDS IN THE SOCIAL AND BEHAVIORAL SCIENCES

to risk losing. The problem lies in the fact that, with a single transaction or at
the beginning of a series of transactions, the trustor does not know whether
his business partner is trustworthy or not.
These reflections could be more precise by extending the trust game (Voss,
1998). We assume that there are honest and dishonest trustees. The honest
trustees are interested in future business with the payoff R* > T, for the dishonest it is, as before, T > R. The actors are in this case “honest” or “dishonest” depending on where their interests lie. Trustors know that a portion of
the business partners are honest (𝛼) and another portion fraudulent (1 − 𝛼). If
they have no further information, they will always cooperate as long as 𝛼 is
larger than the threshold value 𝛼*, whereby they can gain at least as much by
cooperating as by abstaining from business relations, or at least P. Trustors
always cooperate when 𝛼 ≥ 𝛼* = (P−S)/(R−S) and accept the losses caused by
fraudulent partners.
However, if the portion of fraudulent actors becomes too big (𝛼 < 𝛼*),
cooperation is no longer worthwhile. In that case, no business is carried out;
the market collapses and all actors, including the fraudulent trader, are left
empty-handed. In such situations, it is very probable that signals emerge
with which trustees can communicate to trustors that they are honest (for
more details, see Przepiorka & Diekmann, 2013). The fraudulent trustors are,
of course, also interested in appearing honest. So a signal is only useful if it is
credible. From the signal, one must be able to recognize the “type” to which
an actor belongs. Credible signals are connected with costs, or, to be more
exact, with the difference in the cost of producing signals. This difference
must be so high that honest actors profit from cooperation (R* − sA > P),
despite signaling costs, while fraudulent actors do not gain if they initiate
a signal (T − sB < P). sA and sB designate the signaling costs of honest and
fraudulent actors, respectively. Under these circumstances, a so-called
separating signaling equilibrium is to be expected. Tattoos were (in the past)
signals that transmitted the information that a person had been in prison and
in all probability would be reliable in any illegal business (Gambetta, 2009).
Police spies, in contrast, were usually not tattooed, provided that they led a
respectable life and the (social) costs of a tattoo were unacceptable. During
courtship, there can be a problem in most cultures when a young man is not
serious about a permanent relationship. Expensive engagement presents are
a signal that differentiates the honest suitor from the dishonest one.
Honest dealers in second-hand wares give a guarantee. If they are honest (and make no mistakes), the costs are zero. For dishonest dealers in
second-hand wares, on the other hand, the costs would be prohibitively
high. The promise of a guarantee is a signal that allows the customer to
distinguish between honest and fraudulent dealers.

The Others as Social Context: On the Importance of Strategic Interaction

9

For this discussion, it is important to note that, in signaling games, the
subjective probability that an actor belongs to a certain type can only be determined by the actions of the actor.
The social context consists of the game structure (decision tree), the preferences of specific types of actors (the D in DBO), and the signaling costs.
These elements are exogenous. The beliefs (the B in DBO), in contrast, follow
from the action dynamics and are endogenous. The social context influences
the beliefs and these in turn the actions. In the trust game, this is the decision in favor of cooperation. As the macro result, markets emerge in which
cooperative exchanges are carried out.
INSTITUTIONS
In trust relationships, signals will emerge when legal or other institutional
regulations are not possible or are difficult to enforce (e.g., in illegal markets),
when most transactions are nonrepeated or seldom repeated, and also when
no reliable information about the reputation of the actors is available. Dependent on the specific context (e.g., nonrepeated vs repeated interactions and
access to reliable information), different cooperation solutions can develop
in the trust relationships (Buskens & Raub, 2013).
A study by Siamwalla (1978) about the market structure of agricultural
products in Thailand is instructive. The quality of rice, for example, is easily
recognizable before the purchase, so that no specific trust problem regarding
quality exists. On the other hand, the rubber farmer himself knows much better than the buyer whether the product is of high or low quality. The quality
of the raw product depends namely on the care taken by the farmer in eliminating impurities, as well as on the quality of the acid used (Siamwalla, 1978).
Because of the asymmetric information, a trust problem arises. Compared to
the rice market, therefore, the market structure that emerged for rubber is different. Loyalty between the seller and the purchaser is high; a rubber farmer
only deals with a few buyers, and they know the farmer and trust the quality
of the goods. In addition, there is the “chain structure” of the trade. A buyer
in the village sells to a dealer in the district and he in turn to a wholesaler or
large trading company (Siamwalla, 1978).
The characteristics of the different goods, in this case rubber versus rice, create trust problems to varying degrees. These problems are solved by different market structures or institutions. Rice markets are often auctions, while
long-term relationships between trading partners and reputation are characteristic of the markets for the raw material, rubber (Kollock, 1994). In an
imaginative experiment, Kollock (1994) was able to demonstrate the emergence of varying market structures.

10

EMERGING TRENDS IN THE SOCIAL AND BEHAVIORAL SCIENCES

In digital trade, trust problems emerge because of the anonymity of the market participants, who often buy goods at auction per mouse click over great
distances. Given the standard trust game and assuming rational and selfish
preferences, there is a unique Nash equilibrium: exchanges should not even
take place; anonymous markets are expected to collapse. However, we are
not dealing here with a simple trust game. With the introduction of the possibility to assess the seller, the trust problem has been considerably defused.
Instead of the “shadow of the future” in the repeated game, the “shadow of
the past” was quasi created with the introduction of reputation. In their own
interests, sellers try to build up a reputation; purchasers, in turn, reward a
reputation. However, it cannot be completely taken for granted that the rating system functions, as self-interested actors may just save themselves the
bother of an assessment. Homo economicus would give no feedback, the rating system would collapse and with it the auction too. Thus, a small shot
of altruism and reciprocity, which goes over and above the self-interest of
homo economicus, is the lubricating oil of anonymous, electronic markets.
The reputation system is a simple, but extremely effective, institutional mechanism, which makes these markets—worth billions—really possible (Diekmann, Jann, Przepiorka, & Wehrli, 2014).
The strategic context of the trading actors creates a trust problem. Institutional regulations can alleviate the problem. The question as to what kind
of regulation emerges depends on various conditions, such as information
asymmetries, transaction costs, and technological progress. The context of
strategically trading actors is the starting point for explaining the development of institutions.
RATIONAL ACTION, “BEAUTY CONTEST” AND BOUNDED
RATIONALITY
There is scarcely another term in the social sciences that is as heavily burdened with misunderstandings as the term rationality or rational action. With
rationality, we understand here no more (and no less) than consistent decisions. Consistency is the defining characteristic. This means that decisions
are taken in agreement with the axioms of a rationality theory. Corresponding to this definition, there are more or less restrictive requirements for the
term rational action, as there are various decision theories with differing axiom
systems. However, when explaining social action, whether we describe the
behavior as “rational” or not is insignificant anyway. However, most decision
theories will probably prescribe the validity of one axiom, namely, the transitivity of preferences: When A is preferred to alternative B and B to alternative
C, then A should also be given preference over C.

The Others as Social Context: On the Importance of Strategic Interaction

11

Rationality does not call for self-interest, and certainly not for material
self-interest. Homo economicus acts rationally per definition, but rational
action is not synonymous with the action of the fictive homo economicus.
Rationality and altruism do not have to be opposites. Andreoni and Miller
(2002) have shown that actors with altruistic preferences can act rationally
in the sense that they fulfill the axioms of decision theory. If people do
not correspond to the picture of homo economicus, and in addition they
even follow altruistic goals, this does not necessarily mean that they act
irrationally. In concurrence with the consistency criterion, their decisions
can be strictly rational. Here, “rationality” is defined in a “motive-free” way,
without excluding certain preferences, goals, or desires. The “wide version”
of rational choice theory (Opp, 1999) already follows from an axiomatic
approach.
Nevertheless, one can observe spectacular deviations from strict principles
of rationality in many situations. The “Beauty-Contest Game” received its
name from a quotation from Keynes, in which he compares the purchase of
stocks to a beauty contest (Selten & Nagel, 1998). On the stock market, it is
not about deciding which is the best share in one’s own opinion, but rather
which is the one that you believe others will think is the best decision; even
more than that, it is about the share that you believe everyone believes that the
others consider to be the best purchase, and so on. The rules of the game are
simple. There are N participants who have to choose a number between zero
and 100. The person who comes nearest to 2/3 of the (arithmetical) mean of
all numbers mentioned wins a prize. When there is more than one winner,
the prize is shared.
If one does not think strategically, one could say, “All numbers are evenly
distributed, the mean should therefore lie by 50. I choose 33 1/3, for that is
2/3 of 50.” Strategic thinking on this first level goes a step further. “If everyone thinks like this, the mean will be 33 1/3. I choose, therefore, 22 2/9.”
On the next level of strategic thinking, it is approximately 15 and so forth,
until finally in continual iteration one approaches at zero, the unique Nash
equilibrium strategy.
However, the equilibrium strategy is rarely chosen in the first round of
experiments. Typically, choices accumulate around 33 or 22. If one repeats
the decision situation and informs about the mean, values around 15 or 10
will result and, in a further round, numbers approaching the equilibrium will
be observed (Selten & Nagel, 1998). This process can also be seen when exact
information about the distribution in the previous round is given (Diekmann,
2009). One could now assume that the actors do not choose the equilibrium
strategy because they do not know about it. However, even if it is explained,
many actors by no means use this strategy. Why do actors act “irrationally”? The answer is as follows: Even if one knows that it is rational to choose

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EMERGING TRENDS IN THE SOCIAL AND BEHAVIORAL SCIENCES

zero, one can still reckon on some of the players not doing so (Selten & Nagel,
1998). In that case, it makes more sense not to choose the equilibrium strategy
and, therefore, one does not choose this strategy oneself either.
The beauty-contest game has been used to explain speculative bubbles on
the stock and property markets. Even if one knows that it is a bubble it can
be worth investing. For the prices can rise further, up until the occurrence
of the catastrophe. Similarly, actors in the beauty-contest game choose the
“irrational” strategy at least occasionally, although they know about the equilibrium strategy. The head of the Citigroup, Charles Prince, formulated this
thought more concretely in the “Financial Times” in July 2007, shortly before
the crisis broke: “When the music stops, in terms of liquidity, things will be
complicated. But as long as the music is playing, you’ve got to get up and
dance. We’re still dancing” (Akerlof & Shiller, 2010, p. xii). In the following
year, the bubble burst!
The step-by-step approach to the equilibrium strategy during the growing number of rounds in the beauty contest demonstrates that equilibrium
points can be achieved by learning and adaptive behavior in the course of the
evolutionary process. Learning, adaptive and myopic behavior can often be
observed in experimental studies. In these cases, theories of bounded rationality, which are explicitly based on the principles of adaptive behavior, are
superior to strict rationality theories.
OUTLOOK
Pioneers in sociology, such as Erving Goffman and Raymond Boudon, recognized that in many cases strategic action is the key to explaining social
processes. Social actions in Max Weber’s sense are of strategic character when
they are not purely oriented on the actions of others but rather are dependent on the results of others’ actions. This distinguishes mere imitation from
a mass panic, a stock market crash, or the growth of a protest movement.
Today, there are increasingly improved models of classical and behavioral
game theory available, with the help of which it is now possible to describe
the strategic context or the structure of strategic interaction precisely and
to deduce testable conclusions. The fundamental problems of sociological
research are of strategic character: the emergence of social order, the problems of cooperation, conflict and the decline of order, compliance with social
norms and the problem of sanctioning, the emergence of institutions, social
exchange and the problem of trust, the development of protest movements,
social dilemmas, and collective goods. Modern methods of analyzing strategic interaction should be employed more widely in both the curriculum of
sociology students and in sociological research.

The Others as Social Context: On the Importance of Strategic Interaction

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Undeniably, classical game theory requires strong rationality assumptions.
In situations where these models allow sufficiently valid predictions, there is
no reason to introduce alternative decision principles. Furthermore, the theory delivers a reference point. If the observed behavior deviates from that,
there is the challenge of explaining the “anomaly.” In this way, new hypotheses and explanations have often been produced. When the strict rationality
models fail—as demonstrated in the beauty contest—one can fall back on
models of “bounded” rationality. There is no general and mechanically applicable theory—otherwise, we could leave the theory building to a computer.
Rational choice theory, bounded rationality, analytical sociology, game theory, and psychological decision research should, instead, be understood as a
“tool box.” They deliver heuristic principles and instruments for building a
theory of the middle range (Merton, 1949) in a concrete area of application,
the findings of which can be tested on empirical data.
REFERENCES
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University Press.
Andreoni, J., & Miller, J. (2002). Giving according to GARP: An experimental test of
the consistency of preferences for Altruism. Econometrica, 70, 737–753.
Berger, J., & Diekmann, A. (2015). The logic of relative frustration. Boudon’s competition model and experimental evidence. European Sociological Review, 31, 725–737.
Boudon, R. (1977). Logic of relative frustration. Archives Europeennes de Sociologie, 18,
3–26.
Buskens, V., & Raub, W. (2013). Rational choice research on social dilemmas: Embeddedness effects on trust. In R. Wittek, T. A. B. Snijders & V. Nee (Eds.), The handbook
of rational choice social research. Stanford, CA: Stanford University Press.
Coleman, J. (1990). Foundations of social theory. Cambridge, MA: Harvard University
Press.
Darley, J. M., & Latané, B. (1968). Bystander intervention in emergencies. Diffusion
of responsibility. Journal of Personality and Social Psychology, 8, 377–383.
Dasgupta, P. (1988). Trust as a commodity. In D. Gambetta (Ed.), Trust. Making and
breaking cooperative relations (pp. 49–72). Oxford, England: Blackwell.
Diekmann, A. (1985). Volunteer’s dilemma. Journal of Conflict Resolution, 29, 605–610.
Diekmann, A. (1993). Cooperation in an asymmetric volunteer’s dilemma game.
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Diekmann, A. (2009). Rational choice, evolution and the “Beauty Contest”. In M.
Cherkaoui & P. Hamilton (Eds.), Raymond Boudon – a life in sociology (pp. 1–12).
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Diekmann, A. (2014). Die Anderen als sozialer Kontext. In J. Friedrichs, A. Nonnenmacher, (Eds.), “Sozialer Kontext und soziale Mechanismen” der Kölner Zeitschrift
für Soziologie und Sozialpsychologie, 66(special issue), 47–66.

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Diekmann, A., Jann, B., Przepiorka, W., & Wehrli, S. (2014). Reputation formation and
the evolution of cooperation in anonymous online markets. The American Sociological Review, 79(1), 65–85.
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and Kegan Paul.
Eger, T., Kraft, M., & Weise, P. (1992). On the equilibrium proportion of innovation
and imitation. A game-theoretic approach. Economics Letters, 38, 93–97.
Franzen, A. (1995). Group size and one-shot collective action. Rationality and Society,
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Gambetta, D. (2009). Codes of the underworld: How criminals communicate. Princeton,
NJ: Princeton University Press.
Gigerenzer, G. (2014). Risk Savvy. How to make good decisions. New York, NY: Viking.
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Raub, W. (1984). Rationale Akteure, institutionelle Regelungen und Interdependenzen. Untersuchungen zu einer erklärenden Soziologie auf strukturell-individualistischer
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Conflict Resolution, 42, 600–618.

ANDREAS DIEKMANN SHORT BIOGRAPHY
Andreas Diekmann is a professor of sociology at the ETH Zurich. He earned
a doctoral degree from the University of Hamburg in 1979 (Dr. rer. pol.),

The Others as Social Context: On the Importance of Strategic Interaction

15

and received the “venia legendi” (Dr. rer. pol. habil.) from the University of
Munich (1987). His areas of research are social cooperation and experimental
game theory, environmental and population sociology, and methods of
empirical social research. He served as a member of the Humboldt Professor
Price Committee and is chairman and senator of the section “Economics and
Empirical Social Sciences” of the German Academy of Sciences Leopoldina.
He is also a fellow of the European Academy of Sociology and coeditor and
board member of several professional journals and research institutions.
Present research activities focus on experimental research on social norms
and energy consumption, an analysis of the environmental burden of
metropolitan areas with geo-referenced panel data (supported by grants
of the Swiss National Science Foundation) and experimental research on
reputation formation and social cooperation.
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EMERGING TRENDS IN THE SOCIAL AND BEHAVIORAL SCIENCES

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F. Robles and Josephine A. Menkin
Stereotype Threat (Psychology), Toni Schmader and William M. Hall
Social Neuroendocrine Approaches to Relationships (Sociology), Sari M. van
Anders and Peter B. Gray



Media

The Others as Social Context: On the Importance of Strategic Interaction