PROMOTING RECIPROCITY-BASED COOPERATIONBY DUAL LAYER GAMIFICATION
Takaya Arita and Nozomi Ogawa
Graduate School of Information Science
Nagoya University
Furo-cho, Chikusa-ku, Nagoya
464-8601, Japan
E-mail: arita@nagoya-u.jp

KEYWORDS
Gamification, Cooperation, Reciprocity, Image Scoring.
ABSTRACTThis paper presents a conceptual platform of gamified
systems with a dual layer structure and reports on the
prototype implementation for promoting reciprocity-based
cooperation in targeted social contexts. Level 1 gamification
is intended to leverage our innate ability to support
cooperative relationships by engaging in altruistic behavior
towards those who exhibit altruistic behavior, and the
addition of Level 2 gamification is intended to induce
gameful experience by a diversity of strategies. Coupling ofthese two layers can promote intrinsic motivation for
performing altruistic behavior and at the same time making
others perform altruistic behavior. We report on the
prototype implementation of the platform and the knowledge
gained from its preliminary evaluations repeated since July
2013.

gamification techniques impact users' subjective experiences(Rapp 2015). The result was that as their familiarity with thegamified features increased, participants characterized theusage of the apps as repetitive, static and scarcely rewarding.
Simply stated, based on these criticisms and findings,
gamification which merely adds a layer of game elements
motivating through external rewards promotes a simple
behavior pattern that does not require learning or thinking
and is unable to maintain the level of engagement.
Responding to the criticisms and aiming for the best
utilization of gamification, this paper presents a conceptual
platform of gamified systems with a dual layer structure. We
report on a prototype implementation focusing on creating an
opportunity to observe and learn own and others' altruistic
behavior and further to promote altruistic behavior intargeted social contexts, and also on its preliminary
evaluations.
RECIPROCITY-BASED COOPERATIONINTRODUCTION
Digital games have pervaded our daily life and humanculture on an unprecedented scale while analog games haveexisted in human culture since the dawn of recorded culture(McGonigal 2011). Furthermore, they are growing beyond
entertainment. Gamification is a relatively new term whose
first documented use dates back to 2008 (Deterding et al.
2011), and can be defined as using game elements, gamemechanics, and game thinking in attempt to engage people,
motivate action, promote learning, and solve problems in
non-game contexts (Deterding et al. 2011; Kapp 2012;
Seaborn and Fels 2015). The typical gamification approachis based on adding game elements (e.g. points and badges) tomake a target task more engaging.
While gamification is more and more employed in the designof digital services, interfaces and interactive systems,
gamification is widely criticized by academic and gamedesigners. Deterding summarized the criticism towards theexisting gamification just adding a layer of game elements
rather than taking a systematic approach to the design of theexperience: not systemic, reward-oriented, not user-centricand pattern-bound (Deterding 2013).
Recently, aiming at the users of popular and typical gamified
applications (Foursquare, Nike+ and GetGlue), Rappinvestigated qualitatively how the most common

One of the most significant problems in interdisciplinary
research fields, including evolutionary biology, ecology,
economics and sociology is to explain social behaviors suchas cooperation (Darwin 1871; Hamilton 1996; Arita 2012).
Cooperation seems to be difficult to reconcile with natural
selection. Why should one individual help another underDarwinian natural selection?
Theoretical explanations for the evolution of cooperation arebroadly classified into two categories, although both are notmutually exclusive: direct fitness benefits and indirect fitness
benefits (West et al. 2011). A cooperative behavior yields
direct fitness benefits when the reproductive success of theindividual who performs the cooperative behavior is also
increased while a cooperative behavior can be also explainedby indirect fitness benefits if it is directed towards otherindividuals who carry genes for cooperation (Hamilton1964).
Reciprocity is a key mechanism classified into the firstcategory whereby the evolution of cooperative or altruistic
behavior may be favored by the probability of future mutualinteractions. There are again two types of reciprocity: direct
and indirect (Figure 1). Direct reciprocity is a tit-for-tat
exchange of benefits by two individuals. Therefore, theevolution of cooperation by direct reciprocity requires
repetitive interaction presumably in a small group. In© EUROSIS-ETI

contrast, indirect reciprocity occurs when an altruist is
rewarded by third parties for behaving generously towards
others, in other words, A helps B, making it more likely that
C will later help A. Furthermore, another type of indirect
reciprocity can be identified if an act of altruism causes therecipient to perform a later act of altruism in the benefit of athird party, in other words, A helps B, making it more likelythat B will later help C. The former is referred to as
downstream reciprocity while the latter upstream reciprocity.
Theoretically, the evolution of cooperation based on
upstream reciprocity is considered to be difficult. For
example, Nowak and Roch showed that upstream reciprocity
enables the evolution of cooperation only in combination
with another mechanism such as direct reciprocity or spatialreciprocity (the effect of forming clusters on the promotionof cooperation dynamics) (Nowak and Roch 2007).
Hereafter, we refer to downstream indirect reciprocity
simply as indirect reciprocity.

2000). Furthermore, according to reputation-based
cooperation theories, individuals should be more cooperative
than when alone. It was indeed shown that even underconditions of anonymity, presenting participants withstylized eyespots on a screen (Haley and Fessler 2005) or arobot constructed with objects that are obviously not humanwith the exception of its eyes (Burnham and Hare, 2007)
make them cooperative.
PROMOTING COOPERATION BY DUAL LAYERGAMIFICATION
Basic idea
Aiming for the best utilization of gamification, we extend thebasic gamification scheme (Figure 2) and design an abstract
platform with a dual-layer structure utilizing gamification(Figure 3). Level 1 is designed to directly promote a targetedbehavior of users using typical game design elements (e.g.
points and badges), while Level 2 is designed to interact with
Level 1 by manipulating the elements of Level 1, possibly
resulting in affecting the behavior of users indirectly.
In this paper, we describes a prototype termed DERC (Duallayergamification
Encouraging
Reciprocity-based
Cooperation) as an instance of the dual-layer gamification
scheme, in which altruistic behavior of each user is intended
to be promoted by quantifying and sharing the image scoreof each member (in the context of indirect reciprocity). The
supposed dynamics caused by adding Level 2 mechanics (i.e.
betting on the change in other's image score) is notstraightforward in general. As is described later in thissection, a reasonable behavior induced by it is to promotealtruistic behavior of (non-altruistic) others.

Figure 1: Classification of Cooperative Reciprocity: a)
Direct, b) Indirect (left: downstream, right: upstream)

The most influential model for indirect reciprocity (Nowak& Sigmund 1998) was based on a simple reputation measure
called image score that increases when the individual isobserved to give aid. Evolutionary simulations using
randomly chosen pairwise encounters between members of a
population showed that cooperation could be establishedthrough discriminatory strategies which helped those withhigher image scores.
Besides the theoretical work towards understanding theevolution of the cooperative behavior, many studies withbehavioral experiments have provided strong support forindirect reciprocity based on some kind of reputation system.
Milinski and others performed the experiments in which
subjects could transfer money to a third-party without thepossibility of direct reciprocation and showed that
reputational incentive works well at maintaining high levelsof cooperation (Milinski et al. 2002). Wedekind and Milinski
also showed that in an experimental setting, participants of
the high image score received money more frequently thanthose with a lower image score (Wedekind and Milinski

Figure 2: Basic Gamification Scheme

Figure 3: Two Layer Gamification Scheme© EUROSIS-ETI

Level 1 gamification
Image score, that is one of the core elements of the theory of
indirect reciprocity, is quantified and shared as points inLevel 1 layer. We seem to have a psychological disposition
helping the image scoring mechanism work and thus making
altruistic behavior adaptive, to a greater or lesser extent. In
this sense, gamification here is used for leveraging our innate
ability to support cooperative relationships between humans
instead of creating some new motivation to do a target
behavior by offering an extrinsic reward.
In the Level 1 system (Figure 4b)), each user anonymously
approves some behavior from another user as altruistic.
When User A approves User B as the most altruistic member
towards A (or the people including A), some proportion ofpoints (10% in the prototype) of A is moved to B. All users
select a user every set timing that depends on the situation
the gamified system was introduced (e.g. every after meetingor until Friday night every week). If a user does not select,
one of the users is selected randomly.
The approval of altruistic behavior completely depends on its
recipient, and this uncertainty can create an opportunity forthinking and learning concerning how to perform better
altruistic behavior, in contrast with the case of simple money
systems with a certainty (Figure 4a)). The adopted pointcollection mechanism can also create a specific innate drive
to increase own points other than pure motivations which
typical gamification systems create (e.g. respects from others
and self-actualization). As the increase in points of B is
proportional to the points of A, B is better off doing altruistic
behavior to a user with more points. Therefore, if a user
wants to increase the probability to get altruistic behavior,
she should increase her points in some way.

system applied for predicting which user will increase herpoints (Figure 4c)). Specifically, users can bet their arbitrary
points on a user likely to increase her points by the next set
timing. When selecting, the odds (multiplier) are assigned tousers and are presented to all users. If her prediction iscorrect, she will receive her bet points multiplied by the odds
corresponding to the user she bet on. Otherwise, she will losea half of her bet points.
A possible behavior which Level 2 system can generate is toincrease the probability of an increase in the points of theUser A whom she bet on by assisting A in performing
altruistic behavior. As an additional mechanism, the systemassigns greater odds to persons with fewer points. The
intention of this design is that users who are not altruistic
should have more opportunities to become altruistic.
Suppose that this gamified system is introduced for making
regular discussion more fruitful and User A just bet on User
B. A successful strategy for A to increase the points of B
should be to bring up a subject concerning programming in
the next meeting if he is good at programming.
Loop dynamics induced by dual layer gamification
Engagement is the most important aspect all gamification
projects aim at. It should be attained using some continuous
loop dynamics. Figure 5 (top) shows a basic loop dynamics
consisting of motivation -> targeted action -> reward.
Gamification projects tried to achieve the loop dynamics,
which, however, seems very difficult as is shown by Rapp
(Rapp 2015).

Figure 4: Basic Operations in a) Simple Money System,b) Level 1, and c) Level 2

Level 2 gamification
Adding Level 2 gamification can give users a gamefulexperience by manipulating the points of users in Level 1.
For this purpose, in the prototype, we introduce a betting

Figure 5: Loop Dynamics of Basic Gamified System (top)and the System with Two Layer Gamification (bottom)© EUROSIS-ETIThe platform has a dual-layer structure shown in Figure 5(bottom), which expands the strategies of users and aims atachieving a loop dynamics to promote intrinsic motivationby providing users with gameful experience. Users arepromoted to consider and learn what kind of behavior will bepositively accepted by each specific member or how theadvantage of each member is utilized. It should solve or
reduce the pattern-bounded problem resulting in a decreasing
the intrinsic motivation of users.
In general, this type of mutual surveillance or evaluation
using gamelike techniques can increase the psychic cost (i.e.
the uncomfortable sensation of being watched and measured)
which might stifle creativity and flexibility (Manjoo 2014).
However, multiple ways of scoring including approved
altruistic behavior and successful betting, and anonymity andrandomness in approving altruistic behavior can decrease thepsychic cost. For example, a user with a high score is notnecessarily altruistic, but might be just good at betting.
PROTOTYPE IMPLEMENTATION AND
PRELIMINARY EVALUATIONS
Prototype implementation DERC
DERC was implemented as a web application using HTML,PHP and Java script. The database component was
implemented using SQL. Users can access DERC to see thechange of her own points, select the most altruistic user toher or select a user she wants to bet on. According to theapproval of altruistic behavior and the success of betting,points of all users are updated at the fixed timing. Odds are
assigned on an equal interval basis with 1.2 to the member
with the most points and 3.0 to the member with the fewest
points.

Figure 6: Screen Shots of User Interface

DERC can be introduced into basically any kind of socialgroups where altruistic behaviors are needed. It will becustomized depending on the situation into which it isintroduced. Hereafter, two cases are assumed in the
explanation. In Case 1, DERC is introduced to someorganization or community in order to increase altruistic
behavior in not specific but general social relationships, andin Case 2, DERC is introduced to regular meetings toactivate the discussion.
The DERC user interface is specially designed for use withsmartphones and tablets (Figure 6). In case 1, by the end of
the period, each user selects a user who is most altruistic
towards her during the period, and, if she wants, bets someher points on a user who is likely to increase his points
during the next period considering his odds. In Case 2, after
each meeting, each user selects a user who said something
most useful to her during the meeting, and, if she wants, bets
some points on a user who is likely to say something good in
the next meeting also considering his odds. The
administrator user interface allows a person who introduced
DERC to the group or organization to see the status ofsystem utilization and the usage history of each user (Figure
7).

Figure 7: Screen Shots of Administrator Interface

Preliminary evaluations
We have conducted preliminary evaluations with theprototype DERC seven times since July 2013. The first four
evaluations were very preliminary in the sense that their
purpose was to develop and improve the basic design of theplatform, and the users were the approximately 20 volunteers
in our laboratory. The targeted situations were general social© EUROSIS-ETIrelationships (six times) and discussion at meetings (once).
The recent three evaluations were conducted withapproximately 10 volunteers each from ACE (action groupfor cross-cultural exchange) in Nagoya University (twice) or
GRAMPUS, Nagoya University American football team(once), all targeted to general social relationships. Each of
the recent three evaluations conducted questionnaire surveys
two or three times: before (, in the middle of) and after eachperiod, which asked the change in the consciousness, attitudeand behavior concerning altruistic behavior from various
perspectives, mainly using a multiple choice format.
The results of the conducted evaluations, especially with thecurrent implementation described above, can be summarized
as follows.
1) Almost all users enjoyed the gameful experience and few
users felt the psychic cost.
2) Approximately a half of the users did an altruistic
behavior promoted by DERC.
3) Successful Level 2 gamification needs successful Level 1
gamification. In other words, the motivation to access
DERC and increase her points supports the considerationof the betting. After realizing that, we implemented abadge system from which badges can be obtained bysatisfying various conditions (Figure 8).
4) There was a diversity of strategies to get points. For
example, some users focused more on Level 1(performing altruistic behavior) and some more on Level
2 (successful betting).
5) It was gradually shown that making a person makeanother person be altruistic is difficult more than we hadthought. Few users behaved as our Level 2 design
intended. However, we believe that this type of process oftrial and error itself is essential to improve social
relationships, for example, from the perspective of action
research (Reason and Bradbury 2007).
6) Some unexpected comments were obtained inquestionnaire responses, including the one that the user
became altruistic towards non-users and out of the period,
affected by DERC. Although there is no intention here to
generalize this comment, it would be important when
considering whether the enhanced motivation was
intrinsic or extrinsic (Ryan and Deci 2000).

Figure 8: List of Badges (left) and Fulfillment Conditions to
Unlock Them (right)

CONCLUSIONSThis paper proposed a platform of gamified systems with adual-layer structure, responding to the criticisms thatconventional gamification simply with a layer of gameelements promotes a simple behavior pattern that does not
require learning or thinking and is unable to maintain thelevel of engagement. We focused on the promotion ofaltruistic behavior in daily social contexts and presented
preliminary evaluations of the prototype implementation.
The implemented prototype was designed primarily forpromoting cooperation based on the theory of indirect
reciprocity with image scoring. However, we believe thatemphasizing the altruistic behavior by quantifying andsharing the image score tends to have a positive effect onother mechanisms including direct reciprocity and upstream
indirect reciprocity.
The most familiar difficulty when understanding theevolution of cooperation or designing a better society (e.g.
mechanism design) is the free-rider problem. In the proposedsystem, altruistic users tend to increase their points, and theusers whose behaviors are not approved as altruistic are
considered as free riders. At the same time, there is anotherway for increasing points and furthermore, being free riders
without seeming to be free riders: betting. However, themost successful strategy of free riders is to let other freeriders be altruistic. Utilization of free riders for eliminating
free riders might be the most remarkable feature of DERC.
The platform could be extended in several directions. We are
implementing real-time version of DERC for stimulating
discussions, in which during meetings, using a small
dedicated device each participant approves a remark ofanother participant as altruistic, and it will be recognized byvibration of the device. Another promising direction might
be incorporation of population structure (groups) expecting
the effect of multilevel selection (Ichinose and Arita 2008),
or consideration in the game dynamics, of mental
representation (e.g. theory of mind) (Arnold et al. 2015).
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