Running Head: A PROPOSAL TO REPLICATE THE SELF-LICENSING EFFECT
Do Reminders of Positive Traits Affect Prosocial Behavior?
A Proposal to Replicate the Self-Licensing Effect by Sachdeva, Iliev, & Medin (2009)
Irene Blanken¹, Niels van de Ven,¹ Marcel Zeelenberg¹, and Marijn H.C. Meijers²
¹ Tilburg University
² University of Amsterdam
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Do Reminders of Positive Traits Affect Prosocial Behavior?
A Proposal to Replicate the Self-Licensing Effect by Sachdeva, Iliev, & Medin (2009)
Prominent social psychological theories and findings, such as cognitive dissonance theory
(Festinger, 1957), the foot-in-the-door effect (Freedman & Fraser, 1966), and the sunk cost effect
(Arkes & Blumer, 1985) highlight consistency as an essential motivator of human behavior (for
reviews see, Abelson, Aronson, McGuire, Newcomb, Rosenberg, & Tannenbaum, 1968;
Gawronski & Strack, 2012). A high degree of consistency is regarded as indicative of personal
and intellectual strength (Falk & Zimmermann, 2010), whereas inconsistent behavior is
commonly regarded as undesirable (Allgeier, Byrne, Brooks, & Revnes, 1979; Asch, 1956). In
addition, self-affirmation theory (Steele, 1988) asserts that people want to maintain a positive
image of their self-integrity, morality, and adequacy (Aronson, Cohen, & Nail, 1999; Sherman &
Cohen, 2002). In the same vein, impression management theory posits that people are
continually attempting to create desired impressions on others (Schlenker, 1980). Therefore, we
generally expect people to act in accordance with their previous moral attitudes and behavior.
Conversely, recent research on self-licensing reveals that individuals who behave in a
socially desirable or morally laudable way, later feel justified performing a socially undesirable
or morally questionable action (Merritt, Effron, & Monin, 2010; Miller & Effron, 2010). Selflicensing theories and findings thus challenge established consistency and self-affirmation
theories that would predict the opposite of self-licensing, namely that people do not feel
comfortable behaving in a way that is inconsistent with their previous moral behaviors. An
important and already classic contribution to the literature on self-licensing examines how
reminders of people’s own positive or negative traits can influence donations to charity and
cooperative behavior in a commons dilemma (Sachdeva, Iliev, & Medin, 2009). Specifically, in
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Study 1, participants who were reminded of their positive traits later donated less money to
charity compared to a neutral control condition, whereas participants who were reminded of their
negative traits later compensated by donating more money to charity compared to a neutral
control condition1. In Study 2, this effect was replicated comparing a positive trait condition with
a negative trait condition and it was showed that this effect only occurred when participants
wrote specifically about themselves. In Study 3, participants who were reminded of their positive
traits subsequently acted less cooperative in a commons dilemma compared to the neutral control
condition, whereas participants who were reminded of their negative traits later acted more
cooperative compared to the neutral control condition. Thus, Sachdeva et al. (2009) were the first
to show that within the same paradigm, threatening moral self-worth led to moral cleansing,
whereas increasing moral self-worth resulted in moral licensing. They argue that both moral
licensing and moral cleansing are part of a larger moral self-regulation framework where internal
balancing of moral self-worth and the costs of inherent prosocial behavior determine whether
one will display (im)moral behavior. Therefore, we propose to replicate Study 1 and Study 3 by
Sachdeva et al. (2009).
The first studies on self-licensing were published over ten years ago (Monin & Miller,
2001). Since then, over 50 separate studies have been published in almost 20 papers.
Furthermore, self-licensing has received much interest in the media and is a widely discussed
topic on the Internet2. Self-licensing can elicit a broad spectrum of undesirable behaviors, such as
displaying prejudiced attitudes (Effron, Cameron, & Monin, 2009; Monin & Miller, 2001),
1
Note that the overall difference between the three conditions was significant. We do not have any statistics on posthoc comparisons.
2
For instance:
http://www.washingtonpost.com/wp-dyn/content/article/2010/07/16/AR2010071606839.html
http://www.newscientist.com/article/dn18686-exposed-green-consumers-dirty-little-secrets.html
http://newsfeed.time.com/2012/05/21/does-organic-food-turn-you-into-a-jerk/
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cheating (Jordan, Mullen, & Murnighan, 2011; Mazar & Zhong, 2010), displaying a preference
for hedonic over utilitarian products (Khan & Dhar, 2006), and indulging highly palatable food
(Mukhopadhyay, Sengupta, & Ramanathan, 2008).
We are currently conducting a meta-analysis on the effects of self-licensing (Blanken,
Van de Ven, & Zeelenberg, 2013). We analyzed a random effects model including 79 studies
with the following definition of licensing: The idea that people, who behave in a socially
desirable or morally laudable way, later feel justified performing a socially undesirable or
morally questionable action. So far, we found a small Cohen’s d effect size (0.26) for the
licensing effect. While conducting the meta-analysis, we noticed that a large amount of the
licensing studies contain low numbers of participants per cell, which substantially decreases the
power of the studies. We performed a power calculation based on the obtained mean effect size
(d = 0.26) of the meta-analysis, and this calculation indicated that studies would need at least 386
participants per cell to replicate the mean effect size with 95% statistical power when comparing
a single licensing condition to a single control condition3.
To the best of our knowledge, the exact methodology Sachdeva et al.’s Study 1 and Study
3 have not been replicated yet4, even though in the 4 years since publication, this paper has
already been cited 112 times (Google Scholar). We believe that the studies by Sachdeva et al.
(2009) are particularly important because they contribute to fundamental discussions on morality
and internal balancing behaviors. In terms of morality, their studies suggest that priming moral
3
This power analysis was done with a two-sided test. We think this is appropriate, because the alternative
hypothesis (consistency in behavior) would also be theoretically likely.
4
Conway and Peetz (2012) performed a close replication of Study 1; we do not consider this as a direct replication
because 1) their participant sample was recruited on Mturk, 2) they added additional manipulations and no condition
was thus an exact replication of the original manipulation, and 3) for the dependent variable participants entered a
draw for US$50 and were told that they could allocate part of this amount to a variety of charities. Thus, for the
dependent variable participants believed that they would donate ‘free’ money rather than money out of their own
pockets.
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behaviors leads to self-licensing, whereas other studies found that priming moral behaviors can
also lead to more cooperative and honest behaviors (Hertel & Fiedler, 1994; Liebrand, Jansen,
Rijken, & Suhre, 1986; Sattler & Kerr, 1991). In this respect it is important to notice that the
numbers of participants per cell are quite low in the Sachdeva et al. Study 1 (Positive traits
condition N = 15; Negative traits condition N = 17; Neutral control condition N = 14) and Study
3 (Positive traits condition N = 16; Negative traits condition N = 15; Neutral control condition N
= 15). Using G*Power (Faul, Erdfelder, Buchner, & Lang, 2009), we calculated that the post-hoc
power for finding the effect between the three conditions is 86.3% for Study 1 and 66.6% for
Study 3. These studies approach sufficient power and the d effect sizes indicate medium sized
effects (d = 0.62 for Study 1 and d = .59 for Study 3). However, note that because of the small
sample sizes, the found effects have large variances, implying that the true effect sizes could
range from a very minor to a very large effect. For the sake of scientific progress as well as for
policy implications of the licensing and cleansing effects, it is vital that we have reliable
estimates of these effect sizes.
Taken together, we think it is important to replicate these classic studies in the licensing
field for both theoretical reasons (licensing seems to be at odds with consistency theories) and
practical reasons (many studies in the licensing field are underpowered). Therefore, we aim to
conduct high-powered replication studies of Study 1 and Study 3 by Sachdeva et al. (2009). We
will replicate these studies both in a student sample with power based on the effect size of the
original study in two different labs (Study 1 and Study 2) and in an American population sample
on Amazon Mechanical-Turk with power based on the effect size we obtained in our metaanalysis (Study 3). Furthermore, work in progress by Cornelissen, Karelaia, and Soyer (2013)
suggests that individuals high in impression management concerns are more likely to display the
Header: A PROPOSAL TO REPLICATE THE SELF-LICENSING EFFECT
licensing effect. Therefore, we implemented the self-presentation items from self-monitoring
scale at the very end of the studies (Lennox & Wolfe, 1984). Replicating the original Study by
Sachdeva et al. (2009) has the further advantage that we can obtain additional insight in the
complete moral self-regulation framework through testing for both moral licensing and moral
cleansing effects contrasted to a neutral control condition. This is important to establish whether
the effect mainly arises due to the recall of moral behavior, that of immoral behavior, or a
combination of both.
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Pilot test
Sachdeva et al. chose their stimuli words from prior research showing that these words affected
moral identity (Reed, Aquino, & Levy, 2007); Since one of our proposed replication studies will
be conducted in a sample of Dutch participants, it is important that these words have a similar
effect in the Dutch language and cultural context as they have been shown to have in the USA.
Therefore, we will test the ten-item measure on moral identity (Appendix 1) in a Dutch sample in
the lab (N ≥ 50) and an American sample on Mturk (N ≥ 50) sample to see whether these words
have similar effects on moral identity in both cultures. We will conduct a univariate ANOVA to
analyze the effect of nationality on moral identity. If our pilot test shows that the words differ in
meaning, we will translate, create, and test a different translation until we have a scale that is
similar in the Dutch and the U.S sample.
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Study 1– Replication of Sachdeva et al.’s Study 1 with a student sample in the lab
Participants
Using G*Power (Faul et al., 2009) we calculated that we would need to include at least
63 participants in our study to achieve 95% power for the effect size that Sachdeva et al. (2009)
obtained in their Study 1. In the original study, 46 students (18 males, 28 females, Mage = 18.8)
from Northwestern University took part in the experiment as a partial fulfillment of a
requirement in an introductory psychology course. In this study, we will include at least 63
students who participate as part of a course credit in the lab at Tilburg University. In this lab,
data is typically collected for 1 week and this will usually result in 70-120 participants. We will
run for one week and this will result in at least 63 participants. All participants will be randomly
assigned to one of three conditions: A positive trait condition, a negative trait condition, and a
neutral control condition.
Materials
We obtained the original study materials of Sachdeva et al. (2009) (Appendix 2) and
translated these materials to Dutch (Appendix 3). The materials will be presented as a paper-andpencil questionnaire. Similar to the original study by Sachdeva et al. (2009), as a cover story,
participants will be instructed that the study is about their handwriting styles. Depending on
assigned condition, participants will be exposed to nine positive trait words, nine negative trait
words, or nine neutral words and will be asked to copy each word four times and think about
each word for 5-10 seconds. Next, they will be instructed to write a short story about themselves
including the words they just copied. Subsequently, they will answer some neutral questions
about the stories they just wrote and they will complete a short math-based filler-task. The
dependent variable is the amounts of money (up to €10.00) participants are willing to donate to a
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worthy cause of their choice. They will be asked to indicate the cause they would like to support
and write down the amount of money they would like to donate. They will be told that they have
to pay this amount of money upon receiving confirmation e-mail from the experimenter. Finally,
participants will complete a set of demographic measures (Appendix 5) and seven selfpresentation items from self-monitoring scale (Lennox & Wolfe, 1984) (Appendix 7).
Procedure
Participants will complete the study as part of a series of experiments in separate cubicles
in the lab at Tilburg University, the Netherlands. The experimenter who will be present in the lab
is blind to condition. Prior to the experiment, participants will be asked to provide their informed
consent. The experimenter will instruct the participants to get seated in a separate cubicle and to
complete the paper-and-pencil questionnaire. After completing the series of experiments and the
demographic measures, the participant will be instructed to leave the cubicle and to approach the
experimenter to sign for their course credit. Participants will be debriefed and thanked for their
participation. Similar to Study 1 by Sachdeva et al. (2009), participants will be debriefed that
their willingness to donate is the dependent variable of the experiment and that they will
therefore not receive a confirmation e-mail.
Plan for Confirmatory Analyses
Prior to analyzing the data, we will exclude participants who did not complete the IV
correctly (i.e., participants who did not write a story about themselves using the 9 words) and
participants who did not complete the dependent variable (i.e., participants who did not indicate
an amount of money they are willing to donate). Next, we will analyze the demographic
variables by requesting the descriptives and frequencies of the mean age, the male/female gender
ratio and the nationality ratio of the participants. We will then analyze whether gender,
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nationality or age have any effects on the amount of money participants are willing to donate by
means of ANOVAs and a linear regression. If it turns out that one (ore more) of these variables
significantly (at the p = .05 level) affect willingness to donate, these variables will be included as
covariates in the following analyses.
In the original study of Sachdeva et al. (2009), the amount of money participants
indicated they would donate was compared across the three conditions using a one-way analysis
of variance (ANOVA); no post-hoc tests are mentioned. We will first perform a one-way
ANOVA similar to Sachdeva et al. (2009). If this one-way ANOVA is significant, we will
perform post-hoc Tukey tests to compare further differences between the three conditions.
The data may not be normally distributed, as we expect that a substantial amount of participants
are not willing to donate any money at all. If this is the case, a Tobit regression is the preferred
analysis to test the effect of recall on the amount of money participants are willing to donate,
taking into account the participants who decided not to donate at all. For the self-monitoring
scale, we will first calculate the Chronbach’s α. If the Chronbach’s α ≥ 0.65, we will analyze the
effects of self-monitoring. We will perform a regression to test the effect of self-monitoring on
the amount of money participants are willing to donate. We will perform spotlight analyses to
analyze the licensing effect separately for low self-monitors and high self-monitors (similar to
Cornelissen et al., 2013). For syntax of the planned analyses, see Appendix 8.
Known differences from original study

Participants in the study of Sachdeva et al. (2009) are from the USA and completed the
study in English, whereas our participants will be from the Netherlands and will complete
a Dutch translation of the study materials. We do not think that these differences in origin
and language are critical for a fair replication of the original study, since Dutch and
Header: A PROPOSAL TO REPLICATE THE SELF-LICENSING EFFECT
American cultures have proven to be very similar (Hofstede, Bond, & Luk, 1993). The
results of our pilot test will show whether the words that were used to affect moral
identity have similar effects for Dutch an American participants.

In the original study, participants indicated the amount of money they were willing to
donate in dollars; in our study, participants will indicate the amount of money they are
willing to donate in Euros.

In our study, participants will complete the self-monitoring scale at the very end of the
procedure, after the dependent variable is assessed.
We do not expect any of these differences to influence the main results of our studies.
Provisions for quality control.
Hereby we declare that we will ensure the highest quality implementation, data
collection, data analysis, and reporting of the research.
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Study 2 – Replication of Sachdeva et al.’s Study 3 with a student sample in the lab
Participants
Using G*Power (Faul et al., 2009) we calculated that we would need to include at least
96 participants in our study to achieve 95% power for the effect size that Sachdeva et al. (2009)
obtained in their Study 3. In the original study, 46 students (24 males, 22 females, Mage = 19.4)
from Northwestern University took part in the experiment as a partial fulfillment of a
requirement in an introductory psychology course. In this study, we will include at least 96
students who participate as part of a course credit in the lab at the University of Amsterdam. In
this lab, data is typically collected for 2 weeks and this will usually result in 180 participants. We
will run for one week and this will result in at least 96 participants. All participants will be
randomly assigned to one of three conditions: A positive trait condition, a negative trait
condition, and a neutral control condition.
Materials
We obtained the original study materials of Sachdeva et al. (2009) (Appendix 2) and
translated these materials to Dutch (Appendix 3). The materials will be presented as a paper-andpencil questionnaire. Similar to the original study by Sachdeva et al. (2009), as a cover story,
participants will be instructed that the study is about their handwriting styles. Depending on
assigned condition, participants will be exposed to nine positive trait words, nine negative trait
words or nine neutral words and will be asked to copy each word four times and think about each
word for 5-10 seconds. Next, they will be instructed to write a short story about themselves
including the words they just copied. Subsequently, they will answer some neutral questions
about the stories they just wrote and they will complete a short math-based filler-task. The
dependent variable is a commons dilemma; participants read in a scenario that they are a
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manager of a mid-sized industrial manufacturing plant. They are then told that all manufacturers
reached an agreement to install filters to eliminate toxic gasses and to run these filters 60% of the
time. Running the filters is very expensive for the company. Participants are then asked to
indicate the amount of time they would actually run these filters. Participants will also be asked
secondary prosocial measures (Percentage of time other managers would run the filters,
likelihood of getting caught, and the amount of environmental damage caused by not running
filters). Finally, participants will complete a set of demographic measures (Appendix 5) and
seven self-presentation items from self-monitoring scale (Lennox & Wolfe, 1984) (Appendix 7).
Procedure
Participants will complete the study as part of a series of experiments in separate cubicles
in the lab at the University of Amsterdam, the Netherlands. The experimenter who will be
present in the lab is blind to condition. Prior to the experiment, participants will be asked to
provide their informed consent. The experimenter will instruct the participants to get seated in a
separate cubicle and to complete the paper-and-pencil questionnaire. After completing the series
of experiments and the demographic measures, the participant will be instructed to leave the
cubicle and to approach the experimenter to sign for their course credit. Participants will be
debriefed and thanked for their participation.
Plan for Confirmatory Analyses
Prior to analyzing the data, we will exclude participants who did not complete the IV
correctly (i.e., participants who did not write a story about themselves using the 9 words) and
participants who did not complete the dependent variable (i.e., participants who did not indicate
the amount of time they would be willing to run the filters). Next, we will analyze the
demographic variables by requesting the descriptives and frequencies of the mean age, the
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male/female gender ratio and the nationality ratio of the participants. We will then analyze
whether gender, nationality or age have any effect on the amount of time participants are willing
to run the filters by means of ANOVAs and a linear regression. If it turns out that one (ore more)
of these variables significantly (at the p = .05 level) affect the amount of time participants are
willing to run the filters, these variables will be included as covariates in the following analyses.
To analyze the amount of time participants are willing to run the filters, we will perform
a one-way ANOVA similar to Sachdeva et al. (2009). If this one-way ANOVA is significant, we
will perform post-hoc Tukey tests to compare further differences between the three conditions.
We will also perform ANOVAs on the secondary prosocial measures (percentage of time other
managers would run the filters, likelihood of getting caught, amount of environmental damage
caused by not running filters). We will perform a regression to test the effect of self-monitoring
on the amount of time participants will run the filters. We will perform spotlight analyses to
analyze the licensing effect separately for low self-monitors and high self-monitors (similar to
Cornelissen et al., 2013). For syntax of the planned analyses, see Appendix 9.
Known differences from original study

Participants in the study of Sachdeva et al. (2009) are from the USA and completed the
study in English, whereas our participants will be from the Netherlands and will complete
a Dutch translation of the study materials. We do not think that these differences in origin
and language are critical for a fair replication of the original study, since Dutch and
American cultures have proven to be very similar (Hofstede, Bond, & Luk, 1993). The
results of our pilot test will show whether the words that were used to affect moral
identity have similar effects for Dutch an American participants.
Header: A PROPOSAL TO REPLICATE THE SELF-LICENSING EFFECT

In our study, participants will complete the self-monitoring scale at the very end of the
procedure, after the dependent variable is assessed.
We do not expect any of these differences to influence the main results of our studies.
Provisions for quality control.
Hereby we declare that we will ensure the highest quality implementation, data
collection, data analysis, and reporting of the research.
15
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Study 3 – A replication of Sachdeva et al.’s Study 1 and Study 3 with a non-student sample
on Amazon Mechanical-Turk
Participants
Based on the original effect size (F = .13) we obtained in our meta-analysis (Blanken,
Van de Ven, & Zeelenberg, 2013), we calculated with G*Power (Faul et al., 2009) that we would
need at least 918 participants in our study to achieve 95% power. To achieve such a big sample
size, we will run Study 2 on Amazon Mechanical-Turk. We will include at least 918 participants
from the USA. Participants will receive $0.35 for participation. These participants will be
randomly assigned to one of three conditions: A positive-trait condition, a neutral-trait condition
and a control condition. We will stop data collection when 918 participants have correctly
completed our study. To obtain a reliable sample, we will exclude participants with a rejection
rate below 95%.
Materials
The experiment exists of the original study materials of Sachdeva et al.’s Study 1 and
Study 3 (Appendix 2). As explained below, we made to slight changes to these materials to
increase the credibility of the online study (Appendix 4). The materials will be presented online
in a Qualtrics survey program.
We adopted the cover story of the experiment; we will tell participants that the study is
about general writing styles (instead of handwriting). Depending on assigned condition,
participants will be exposed to nine positive trait words, negative trait words or neutral words
and will be asked to re-type each word four times and to think about each word for 5-10 seconds.
Subsequently, they will be instructed to type a short story about themselves including the words
they just typed. Participants will be told that they have to do this seriously and if they do not
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seriously answer this question their HIT will be rejected. Subsequently, they will answer some
neutral questions about the stories they just wrote and they will complete a short math-based
filler-task. Subsequently, participants will complete both dependent variables from Sachdeva et
al’s Study 1 (i.e., donating) and Study 3 (i.e., commons dilemma) in a counterbalanced order. In
this way, we can also establish whether there are any order effects; we will test whether the
licensing and compensation effects still occur after the first dependent variable.
The dependent variable from Study 1 consists of the amount of money (up to $10.00)
participants are willing to donate to a worthy cause of their choice. Since we cannot use the
cover story of the original experiment (‘Our lab usually asks participants if they would like to
contribute to a worthy cause in an effort to increase social responsibility’), we made slight
changes to the donation measure that Sachdeva et al. (2009) used. We will tell participants that
10 participants who will be randomly selected will win an additional $10 MTurk worker bonus
next to their payment in return for their participation. They will then be asked that, in an effort to
increase social responsibility, we would like to ask them that if they would be one of the
winners, whether they are willing to donate a portion of the money to a cause of their choice.
They will be asked to indicate the cause they would like to support and indicate the amount of
money they would like to donate. They will be told that they have to pay this amount of money
upon receiving a confirmation e-mail. The dependent variable from Study 3 is the commons
dilemma, as described in the section of our Study 2. Finally, participants will complete the 7 selfpresentation items from self-monitoring scale (Lennox & Wolfe, 1984), (Appendix 7).
Procedure
Participants will complete all study instructions and materials online. Prior to the
experiment, participants will be asked to provide their informed consent. Next, participants will
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receive the instructions and complete the instruction check, the questionnaire and the
demographic measures, respectively. At the end of the online experiment, participants will be
debriefed and thanked for their participation.
Confirmatory Analyses plan
We will analyze the data in the same way as described in the confirmatory analysis
sections of Study 1 and Study 2. To test whether there are any order effects for the dependent
variables, we will include the order in which the dependent variables are presented as an extra
predictor in our ANOVA models. In addition, we will request the descriptives and frequencies of
the extra demographic variables level of education and family income and we will analyze
whether gender or nationality have any effect on the amount of money participants are willing to
donate or the amount of time participants are willing to run the filters and the secondary
prosocial measures by means of a one-way ANOVA. If it turns out that one (or more) of these
variables significantly (at the p = .05 level) affect willingness to donate or amount of time
participants are willing to run the filters, these variables will be included as covariates in the
main analyses of condition on willingness to donate. For syntax of the planned analyses, see
Appendix 9.
Known differences from original study

The original study was presented as a paper-and-pencil task in the lab, whereas the
current study will be completed online without the presence of an experimenter. In both
samples of participants, the donation is anonymous, and therefore we do not expect any
differences between responses on the dependent variable.

The original study was completed by a student sample from Northwestern University,
whereas the current study will be completed by a more general population from the USA
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on Amazon Mechanical-Turk. Therefore, we included additional demographics (level of
education and family income). As stated in the analyses section, we will control for the
possibility that these variables affect the willingness to donate money dependent variable.

Since we are planning to perform this study online, we made two slight changes to the
original cover story. First, participants in the original study were told that the study is
about their handwriting styles, whereas we will instruct the participants that the study is
about general writing styles. Secondly, participants in the original study were told that the
lab usually asks participants if they would like to contribute to a worthy cause in an effort
to increase social responsibility, whereas we will ask participants that if they would be
one of the $10 winners, whether they are willing to donate a portion of the money to a
cause of their choice.
We do not expect any of these differences to influence the main results of our studies.
Provisions for quality control.
Hereby we declare that we will ensure the highest quality implementation, data
collection, data analysis and reporting of the research.
Header: A PROPOSAL TO REPLICATE THE SELF-LICENSING EFFECT
Proposed Meta-Analysis
In addition to the proposed replication studies, we are planning to conduct a metaanalysis on the studies investigating the effect of the positive-trait versus neutral control stories
on the amount of money one is willing to donate to charity to establish the mean effect size and
the consistency of the effects.
We will include Sachdeva et al.’s Study 1 and Study 3 and our four replication effect
sizes (two effect sizes for the dependent variable of Sachdeva et al.’s Study 1, and two effect
sizes for the dependent variable of Sachdeva et al.’s Study 3). We will test a random-effects
meta-analytic model using the ‘metafor’ package (Viechtbauer, 2010) in the statistical software
program R. See Appendix 10 for the syntax.
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Appendix 1: Reed, Aquino and Levy (2007) original ten-item measure of moral identity
Listed below are some characteristics that might describe a person:
Caring, Compassionate, Fair, Friendly, Generous, Helpful, Hardworking, Honest, Kind
The person with these characteristics could be you or it could be someone else. For a moment,
visualize in your mind the kind of person who has these characteristics. Imagine how that person
would think, feel, and act. When you have a clear image of what this person would be like,
answer the following questions.
1. It would make me feel good to be a person who has these characteristics.
2. Being someone who has these characteristics is an important part of who I am.
3. I often wear clothes that identify me as having these characteristics.
4. I would be ashamed to be a person who had these characteristics. (R)
5.The types of things I do in my spare time (e.g., hobbies) clearly identify me as having these
characteristics.
6. The kinds of books and magazines that I read identify me as having these characteristics.
7. Having these characteristics is not really important to me. (R)
8.The fact that I have these characteristics is communicated to others by my membership in
certain organizations.
9. I am actively involved in activities that communicate to others that I have these characteristics.
10. I strongly desire to have these characteristics.
(1 = “strongly disagree,” and 7 = “strongly agree”)
Dutch translation:
Hieronder zie je een aantal eigenschappen die een persoon zouden kunnen omschrijven:
Zorgzaam, Empatisch, Rechtvaardig, Vriendelijk, Gul, Behulpzaam, Hardwerkend, Eerlijk,
Aardig.
De persoon met deze eigenschappen zou jij of een ander kunnen zijn. Probeer nu in gedachten
voor te stellen wat voor een persoon deze eigenschappen zou hebben. Stel je voor hoe deze
persoon zou denken, zich zou voelen en zich zou gedragen. Als je een duidelijk beeld hebt van
hoe deze persoon zou zijn, beantwoord dan onderstaande vragen.
1. Ik zou me goed voelen als ik een persoon zou zijn die over deze eigenschappen beschikt.
2. Het hebben van deze eigenschappen is een belangrijk onderdeel van wie ik ben.
3. Ik draag vaak kleding die laat zien dat ik over deze eigenschappen beschik.
4. Ik zou me schamen als ik een persoon zou zijn met deze eigenschappen. (R)
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22
5. De dingen die ik doe in mijn vrije tijd (bijvoorbeeld hobby’s) laten zien dat ik over deze
eigenschappen beschik.
6. Het soort boeken en tijdschriften dat ik lees laat zien dat ik over deze eigenschappen beschik.
7. Beschikken over deze eigenschappen is vrij onbelangrijk voor me. (R)
8. Het feit dat ik over deze eigenschappen beschik wordt naar anderen gecommuniceerd door
mijn lidmaatschap van bepaalde organisaties.
9. Ik neem deel aan activiteiten die aan anderen laten zien dat ik over deze eigenschappen
beschik.
10. Ik heb een sterke behoefte om over deze eigenschappen te beschikken.
(1 = “sterk mee oneens,” and 7 = “sterk mee eens”)
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23
Appendix 2: Original study materials of Sachdeva et al. (2009)
Participant #___________
The purpose of this exercise is to examine people’s handwriting styles as they tell stories. There is no
right or wrong way of writing, so just relax and write in your natural style.
Listed below are nine words in alphabetical order.
Please take a few moments (about 5-10 seconds per word) to think about what each word means to you.
Then follow the “Example” and write down each word 4 times in the boxes provided
Example

Caring
Compassionate
Fair
Friendly
Generous
Hardworking
Helpful
Honest
Kind
Please go to the next page
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Now take a few moments to think about each of these words. In the box below, write a brief story about
yourself (in one or two paragraphs) which uses each of these words at least once. It may help if you
visualize each word as it is relevant to your life.
Here are the words again for your convenience:
Caring
Compassionate
Fair
Friendly
Generous
Hardworking
Helpful
Honest
Kind
Write your brief story here:
Please go to the next page
24
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25
Please go back and re-read the story you just wrote, and then answer the following questions (circle one
number per question):
1. To what extent does your story reflect how you see yourself as a student?
Somewhat
Exceptionally
1--------------2--------------3--------------4--------------5--------------6--------------7
2. To what extent does your story reflect how you see yourself as a person concerned with cleanliness?
Somewhat
Exceptionally
1--------------2--------------3--------------4--------------5--------------6--------------7
3. To what extent does your story reflect how you see yourself as a person who feels that material
possessions are important?
Somewhat
Exceptionally
1--------------2--------------3--------------4--------------5--------------6--------------7
4. To what extent does your story reflect how you see yourself as a person who is safety-conscious?
Somewhat
Exceptionally
1--------------2--------------3--------------4--------------5--------------6--------------7
5.
How much difficulty did you experience writing your story?
Not much
A lot
1--------------2--------------3--------------4--------------5--------------6--------------7
6.
Writing the story was harder than you thought it would be
Disagree
Agree
1--------------2--------------3--------------4--------------5--------------6--------------7
7.
Writing the story took you a lot of effort
Disagree
Agree
1--------------2--------------3--------------4--------------5--------------6--------------7
8. What is your major? If undecided, right down what seems to be the likeliest choice right now.
_______________________________________________
Header: A PROPOSAL TO REPLICATE THE SELF-LICENSING EFFECT
Neutral Words:
Book
Car
Folder
House
Keys
Radio
Shopping
Temperature
Window
Negative Traits:
Disloyal
Greedy
Harm
Indifferent
Mean
Selfish
Stingy
Uncaring
Unfair
26
Header: A PROPOSAL TO REPLICATE THE SELF-LICENSING EFFECT
Below are some simple math problems. Please try to solve them as quickly as
possible.
1.
A man has to be at work by 9:00 a.m. and it takes him 15 minutes to get
dressed, 20 minutes to eat and 35 minutes to walk to work. What time
should he get up? ____________
2. Which of the following numbers represents the biggest risk of getting a
disease?
1 in 100 1 in 1000 1 in 10
3. Replace each blank with the correct digit.
4 3 _ 2
4 5 _
_ 1 2 7
--------8 8 9 3
4. If Jane is older than Kim, Kim is older than Shawn. Shawn is younger than
Jane and Rachel is older than Jane
List the people from oldest to youngest.
27
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28
DV Sachdeva et al.’s Study 1
Before you leave, our lab usually asks participants if they would like to contribute to a worthy
cause in an effort to increase social responsibility. If you would like, you can pledge to make a
small donation (up to $10) to any cause of your choice. You will pay this amount at a later time
upon receiving a confirmation e-mail from the experimenter. Please select which of the causes
you would like to donate to, or enter the name of your charity and the amount you would like to
donate. If you have any questions, please ask your experimenter.
______ Cancer Research
______ Environmental Preservation
______ Animal Rights
______ Human Rights
______ World Hunger
______ Veterans’ Affairs
______ Other (Please Specify: __________________________ )
Amount
$0
$1
$2
$3
$4
$5
$6
$7
$8
$9
$ 10
Other _______
End.
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29
DV Sachdeva et al.’s Study 3
You are the manager of a mid-sized industrial manufacturing plant with
annual revenue of $20 million. Lately, environmental lobbyists have been vying
for your industry to decrease emissions of a toxic gas, VS-1, that is produced
during the production process of your product. The environmentalists are
becoming increasingly concerned about this problem and are proposing that all
smokestacks be equipped with filters that would eliminate the toxic gas if they
operated 100 percent of the time. The environmentalists have been lobbying for
legislation for 100 percent utilization of the filters.
With the potential threat of legislation looming large, the manufacturers in
the industry have gotten together and reached an agreement under which all
manufacturers would install filters and run them 60 percent of the time. This
solution is acceptable to the environmentalists and one way to avoid legislation.
Analysts predict legislation and compliance costs will amount to $3 million.
You, as the manger of a manufacturing plant, have two options:
1) Run the filters 60% of the time at an estimated cost of $1.2 million
or
2) Run the filters less than 60% of the time, with each 10% interval costing $.2
million i.e., if the filters are run 10% of the time, the cost is $.2 million; if the
filters are run 30% of the time, the cost is $.6 million, etc.
All other managers have the same choice. If most of the other manufacturers
cooperate by running their filters 60% of the time, there will not be a press for
legislation and the plant will not have to pay compliance costs. But, if most of the
other manufacturers do not cooperate and run their filters less than 60% of the
time, legislation and compliance costs will be incurred.
Header: A PROPOSAL TO REPLICATE THE SELF-LICENSING EFFECT
30
Please continue to the next page
It is now time for you to make some decisions:
What percentage of the time will you operate your filters? Please circle the
appropriate response:
0%----10%-----20%----30%-----40%-----50%-----60%----70%-----80%----90%----100%
Header: A PROPOSAL TO REPLICATE THE SELF-LICENSING EFFECT
31
Please continue to the next page
Please explain your decision briefly:
__________________________________________________________________
__________________________________________________________________
__________________________________________________________________
__________________________________________________________________
__________________________________________________________________
__________________________________________________________________
__________________________________________________________________
__________________________________________________________________
__________________________________________________________________
Please continue to the next page
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32
Out of all the managers in your field, what percentage do you estimate will operate
the filters less than 60% of the time? _____________________ (0 to 100%)
How much environmental damage do you think will be caused by operating the
filters less than 60% of the time?
1
None
2
3
Little
4
5
6
7
8
A Moderate Amount
9
10
A Great Amount
How likely do you think it is that you will be caught if you operate the filters less
than 60% of the time?
1
2
Impossible
3
4
5
Unlikely
6
7
8
Reasonably Likely
9
10
Certain
Doesn’t
Matter
What do you think the responsibility of the plant manager is?
a. To run the plant profitably, no matter what
b. To run the plant profitably, and also to protect the environment
c. To protect the environment, and to run the plant profitably while doing so
d. To protect the environment, no matter what
e. Other, please describe
_______________________________________________
If you had to choose one description for this decision, what would it be?
____ A personal decision
____ A business decision
____ An ethical decision
____ An environmental decision
____ A legal decision
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33
Appendix 3: Dutch translation of the original study materials
Proefpersoon #___________
Het doel van deze taak is om het handschrift te onderzoeken dat mensen gebruiken als ze verhalen
vertellen. Er is geen goede of foute manier van schrijven, dus ontspan en gebruik je normale handschrift.
Hier onder staan negen woorden in alfabetische volgorde.
Denk per woord 5-10 seconden na wat dit woord voor jou betekent.
Volg vervolgens het “voorbeeld” en schrijf elk woord 4 keer over in de hokjes naast het woord.
Voorbeeld

Zorgzaam
Empatisch
Rechtvaardig
Vriendelijk
Gul
Hardwerkend
Behulpzaam
Eerlijk
Aardig
Ga aub naar de volgende pagina.
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34
Neem nu even een klein momentje om over deze woorden na te denken. Schrijf vervolgens in het vak
hieronder een verhaal over jezelf (1 a 2 alinea’s) waarin je al deze woorden ten minste één keer gebruikt.
Het helpt misschien als je bij elk woord visualiseert hoe belangrijk dit is in jouw leven.
Hier zijn de woorden nog een keer:
Zorgzaam
Empatisch
Rechtvaardig
Vriendelijk
Gul
Hardwerkend
Behulpzaam
Eerlijk
Aardig
Schrijf hier je korte verhaal:
Ga aub naar de volgende pagina
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35
Ga aub terug naar de vorige pagina en lees het verhaal dat je net schreef nog een keer. Beantwoord
vervolgens onderstaande vragen (omcirkel een nummer per vraag):
1. In hoeverre geeft je verhaal weer hoe jij jezelf als student ziet?
Een beetje
Heel veel
1--------------2--------------3--------------4--------------5--------------6--------------7
2. In hoeverre geeft je verhaal weer hoe jij jezelf als persoon ziet met betrekking tot hygiëne?
Een beetje
Heel veel
1--------------2--------------3--------------4--------------5--------------6--------------7
3. In hoeverre geeft je verhaal weer hoe jij jezelf als persoon ziet die materieel bezit belangrijk vindt?
Een beetje
Heel veel
1--------------2--------------3--------------4--------------5--------------6--------------7
4.
In hoeverre geeft je verhaal weer hoe jij jezelf als persoon ziet die zich bewust is van veiligheid?
Een beetje
Heel veel
1--------------2--------------3--------------4--------------5--------------6--------------7
5.
Hoe moeilijk vond je het om dit verhaal te schrijven?
Helemaal niet moeilijk
Heel moeilijk
1--------------2--------------3--------------4--------------5--------------6--------------7
6.
Het verhaal schrijven was moeilijker dan ik had gedacht.
Mee oneens
Mee eens
1--------------2--------------3--------------4--------------5--------------6--------------7
7.
Het verhaal schrijven kostte me veel moeite.
Mee oneens
Mee eens
1--------------2--------------3--------------4--------------5--------------6--------------7
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Neutrale woorden:
Boek
Auto
Folder
Huis
Sleutels
Radio
Winkelen
Temperatuur
Raam
Negatieve karakteristieken:
Onbetrouwbaar
Inhalig
Kwetsend
Onverschillig
Gemeen
Egoïstisch
Gierig
Harteloos
Onrechtvaardig
36
Header: A PROPOSAL TO REPLICATE THE SELF-LICENSING EFFECT
Hier staat een aantal korte wiskundevraagstukken. Probeer deze zo snel
mogelijk op te lossen.
1.
Een man moet om 9:00 a.m. op zijn werk zijn en het kost hem 15 minuten
om zich aan te kleden, 20 minuten om te eten en 35 minuten om te lopen
naar zijn werk. Hoe laat moet hij opstaan? ____________
2. Welke van de onderstaande nummers representeert het grootste risico om
een ziekte te krijgen?
1 op de 100 1 op de 1000 1 op de 10
3 Vul de lege plaatsen in met het juiste cijfer.
4 3 _ 2
4 5 _
_ 1 2 7
--------8 8 9 3
4. Jane is ouder dan Kim, Kim is ouder dan Sam. Sam is jonger dan Jane en
Rachel is ouder dan Jane. Zet deze namen in volgorde van de oudste naar de
jongste persoon.
37
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38
DV Sachdeva et al.’s Study 1
Ons lab vraagt normaliter aan proefpersonen of zij bereid zijn om bij te dragen aan een goed doel
om in een poging om maatschappelijke verantwoordelijkheid te vergroten. Als je wilt, kun je
tekenen om een kleine donatie (tot €10.00) te maken naar een goed doel van jouw keuze. Je zult
dit bedrag later betalen op het moment dat je een bevestiging e-mail van de experimentleider
ontvangt. Selecteer hier onder het goede doel waaraan je zou willen doneren, of schrijf de naam
van een doel naar keuze en selecteer het bedrag dat je wilt doneren. Als je vragen hebt, laat dit
dan weten aan de experimentleider.
______ Kanker Onderzoek
______ Behoud van het Milieu
______ Dierenrechten
______ Mensenrechten
______ Wereldhonger
______ Oorlogsveteranen
______ Anders (Specificeer: __________________________ )
Bedrag
€0
€1
€2
2
€3
3
€4
4
€5
€6
6
€7
7
€8
8
€9
9
€ 10
10
Anders _______
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39
DV Sachdeva et al.’s Study 3
Je bent de manager van een middelgrote industriële fabriek met een jaarlijkse
omzet van 20 miljoen euro. De laatste tijd hebben milieulobbyisten gepleit voor het
verminderen van de uitstoot van een giftig gas, VS-1, dat vrijkomt bij het
productieproces van jullie product. De milieulobbyisten maken zich ernstig zorgen
over dit probleem en stellen voor dat de schoorstenen met filters worden uitgerust,
die de uitstoot van dit giftige gas tot nul reduceren als ze 100% van de tijd draaien.
De milieulobbyisten hebben gelobbyd voor een wet om deze filters overal te
installeren en voor 100% van de tijd te laten draaien.
Met de potentiële dreiging van deze verandering in de wetgeving zijn de
fabrikanten uit de industrie samen tot de overeenkomst gekomen dat alle
fabrikanten deze filters zouden installeren en deze filters 60% van de tijd zouden
draaien. De milieuactivisten vinden dit een acceptabele oplossing En daardoor is
dit een manier om de eerder voorgestelde wetsverandering te voorkomen. Experts
voorspellen dat de kosten van de verandering in wetgeving en het naleven hiervan
zouden oplopen tot 3miljoen euro.
Jij hebt als manager van de industriële fabriek twee opties:
1) De filters 60% van de tijd laten draaien voor de geschatte kosten van 1.2
miljoen euro
2) De filters minder dan 60% van de tijd laten draaien, waarbij elk 10% interval
0.2 miljoen euro kost. Dus, als je de filters 10% van de tijd laat draaien dan
kost dit 0.2 miljoen euro; als je de filters 30% van de tijd laat draaien dan
kost dit 0.6 miljoen euro, etc.
Alle andere fabrieksmanagers hebben dezelfde keuze. Als de meeste andere
fabrieksmanagers meedoen door hun filters ook 60% van de tijd te laten draaien,
zal er geen druk ontstaan om de wetgeving te veranderen en hoeft de fabriek geen
Header: A PROPOSAL TO REPLICATE THE SELF-LICENSING EFFECT
40
compensatiekosten te betalen. Maar, als de meeste van de andere fabrikanten niet
meewerken en hun filters minder dan 60% van de tijd laten draaien, dan zal de
wetgeving veranderen en zal de fabriek compensatiekosten moeten betalen.
Welk percentage van de tijd zul je de filters laten draaien? Omcirkel je
antwoord:
0%----10%-----20%----30%-----40%-----50%-----60%----70%-----80%----90%----100%
Ga aub naar de volgende pagina
Header: A PROPOSAL TO REPLICATE THE SELF-LICENSING EFFECT
41
Geef een korte uitleg van je beslissing:
__________________________________________________________________
__________________________________________________________________
__________________________________________________________________
__________________________________________________________________
__________________________________________________________________
__________________________________________________________________
__________________________________________________________________
__________________________________________________________________
__________________________________________________________________
Ga aub naar de volgende pagina
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42
Hoeveel procent van alle managers in het vakgebied schat jij dat de filters minder
dan 60% laat draaien?
_____________________ (0 tot 100%)
Hoeveel millieuschade denk je dat wordt veroorzaakt door de filters minder dan
60% van de tijd te laten draaien?
1
2
3
4
Geen Een beetje
5
6
7
8
9
gemiddeld
10
Veel
Hoe waarschijnlijk acht jij de kans dat je betrapt wordt wanneer je de filters minder
dan 60% van de tijd draait?
1
2
3
4
5
6
7
8
Onmogelijk Onwaarschijnlijk Waarschijnlijk
9
10
Zeker
Maakt niet
uit
Wat denk jij dat de verantwoordelijkheid van de fabrieksmanager is?
a. Om winst te maken, ongeacht wat er gebeurt
b. Om winst te maken en om daarnaast het milieu te beschermen
c. Om het milieu te beschermen en om daarnaast winst te maken
d. Om het milieu te beschermen, ongeacht wat er gebeurt.
e. Anders, namelijk:
f. _______________________________________________
Als je een beschrijving zou mogen kiezen voor deze beslissing, wat zou dat dan
zijn?
____ Een persoonlijke beslissing
____ Een zakelijke beslissing
____ Een ethische beslissing
Header: A PROPOSAL TO REPLICATE THE SELF-LICENSING EFFECT
____ Een milieugerelateerde beslissing
____ Een juridische beslissing
43
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44
Appendix 4: Materials for the proposed Amazon Mechanical-Turk study
[Note that our adjustments to the original study materials are highlighted in yellow]
Participant #___________
The purpose of this exercise is to examine people’s general writing styles as they tell stories. There is no
right or wrong way of writing, so just relax and write in your natural style.
Listed below are nine words in alphabetical order.
Please take a few moments (about 5-10 seconds per word) to think about what each word means to you.
Then follow the “Example” and copy each word 4 times in the boxes provided
Example

Caring
Compassionate
Fair
Friendly
Generous
Hardworking
Helpful
Honest
Kind
Please go to the next page
Header: A PROPOSAL TO REPLICATE THE SELF-LICENSING EFFECT
Now take a few moments to think about each of these words. In the box below, write a brief story about
yourself (in one or two paragraphs) which uses each of these words at least once. It may help if you
visualize each word as it is relevant to your life.
Here are the words again for your convenience:
Caring
Compassionate
Fair
Friendly
Generous
Hardworking
Helpful
Honest
Kind
Write your brief story here:
Please go to the next page
45
Header: A PROPOSAL TO REPLICATE THE SELF-LICENSING EFFECT
46
Please go back and re-read the story you just wrote, and then answer the following questions (circle one
number per question):
2. To what extent does your story reflect how you see yourself as a person?
Somewhat
Exceptionally
1--------------2--------------3--------------4--------------5--------------6--------------7
2. To what extent does your story reflect how you see yourself as a person concerned with cleanliness?
Somewhat
Exceptionally
1--------------2--------------3--------------4--------------5--------------6--------------7
3. To what extent does your story reflect how you see yourself as a person who feels that material
possessions are important?
Somewhat
Exceptionally
1--------------2--------------3--------------4--------------5--------------6--------------7
4. To what extent does your story reflect how you see yourself as a person who is safety-conscious?
Somewhat
Exceptionally
1--------------2--------------3--------------4--------------5--------------6--------------7
5.
How much difficulty did you experience writing your story?
Not much
A lot
1--------------2--------------3--------------4--------------5--------------6--------------7
6.
Writing the story was harder than you thought it would be
Disagree
Agree
1--------------2--------------3--------------4--------------5--------------6--------------7
7.
Writing the story took you a lot of effort
Disagree
Agree
1--------------2--------------3--------------4--------------5--------------6--------------7
Header: A PROPOSAL TO REPLICATE THE SELF-LICENSING EFFECT
Neutral Words:
Book
Car
Folder
House
Keys
Radio
Shopping
Temperature
Window
Negative Traits:
Disloyal
Greedy
Harm
Indifferent
Mean
Selfish
Stingy
Uncaring
Unfair
47
Header: A PROPOSAL TO REPLICATE THE SELF-LICENSING EFFECT
Below are some simple math problems. Please try to solve them as quickly as
possible.
1.
A man has to be at work by 9:00 a.m. and it takes him 15 minutes to get
dressed, 20 minutes to eat and 35 minutes to walk to work. What time
should he get up? ____________
2. Which of the following numbers represents the biggest risk of getting a
disease?
1 in 100 1 in 1000 1 in 10
3. Replace each blank with the correct digit.
4 3 _ 2
4 5 _
_ 1 2 7
--------8 8 9 3
4. If Jane is older than Kim, Kim is older than Shawn. Shawn is younger than
Jane and Rachel is older than Jane
List the people from oldest to youngest.
48
Header: A PROPOSAL TO REPLICATE THE SELF-LICENSING EFFECT
At the end of this study we randomly select 10 participants who will receive an additional $10
Mturk worker bonus (in addition to the regular payment for this study). In an effort to increase
social responsibility, we would like to ask you that, if you would be one of these winners,
whether you are willing to make a small donation (up to $10) to any cause of your choice.
If you are one of the winners, you will be noticed by e-mail, and you will pay this amount at a
later time upon receiving a confirmation e-mail from the experimenter.
Please select which of the causes you would like to donate to if you would be one of these
winners, or enter the name of your charity and the amount you would like to donate.
______ Cancer Research
______ Environmental Preservation
______ Animal Rights
______ Human Rights
______ World Hunger
______ Veterans’ Affairs
______ Other (Please Specify: __________________________ )
Amount
$0
$1
$2
$3
$4
$5
$6
$7
$8
$9
$ 10
Other _______
End.
49
Header: A PROPOSAL TO REPLICATE THE SELF-LICENSING EFFECT
50
You are the manager of a mid-sized industrial manufacturing plant with
annual revenue of $20 million. Lately, environmental lobbyists have been vying
for your industry to decrease emissions of a toxic gas, VS-1, that is produced
during the production process of your product. The environmentalists are
becoming increasingly concerned about this problem and are proposing that all
smokestacks be equipped with filters that would eliminate the toxic gas if they
operated 100 percent of the time. The environmentalists have been lobbying for
legislation for 100 percent utilization of the filters.
With the potential threat of legislation looming large, the manufacturers in
the industry have gotten together and reached an agreement under which all
manufacturers would install filters and run them 60 percent of the time. This
solution is acceptable to the environmentalists and one way to avoid legislation.
Analysts predict legislation and compliance costs will amount to $3 million.
You, as the manger of a manufacturing plant, have two options:
1) Run the filters 60% of the time at an estimated cost of $1.2 million
or
2) Run the filters less than 60% of the time, with each 10% interval costing $.2
million i.e., if the filters are run 10% of the time, the cost is $.2 million; if the
filters are run 30% of the time, the cost is $.6 million, etc.
All other managers have the same choice. If most of the other manufacturers
cooperate by running their filters 60% of the time, there will not be a press for
legislation and the plant will not have to pay compliance costs. But, if most of the
other manufacturers do not cooperate and run their filters less than 60% of the
time, legislation and compliance costs will be incurred.
Header: A PROPOSAL TO REPLICATE THE SELF-LICENSING EFFECT
51
Please continue to the next page
It is now time for you to make some decisions:
What percentage of the time will you operate your filters? Please circle the
appropriate response:
0%----10%-----20%----30%-----40%-----50%-----60%----70%-----80%----90%----100%
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52
Please continue to the next page
Please explain your decision briefly:
__________________________________________________________________
__________________________________________________________________
__________________________________________________________________
__________________________________________________________________
__________________________________________________________________
__________________________________________________________________
__________________________________________________________________
__________________________________________________________________
__________________________________________________________________
Please continue to the next page
Header: A PROPOSAL TO REPLICATE THE SELF-LICENSING EFFECT
53
Out of all the managers in your field, what percentage do you estimate will operate
the filters less than 60% of the time? _____________________ (0 to 100%)
How much environmental damage do you think will be caused by operating the
filters less than 60% of the time?
1
None
2
3
Little
4
5
6
7
8
A Moderate Amount
9
10
A Great Amount
How likely do you think it is that you will be caught if you operate the filters less
than 60% of the time?
1
2
Impossible
3
4
5
Unlikely
6
7
8
Reasonably Likely
9
10
Certain
Doesn’t
Matter
What do you think the responsibility of the plant manager is?
a. To run the plant profitably, no matter what
b. To run the plant profitably, and also to protect the environment
c. To protect the environment, and to run the plant profitably while doing so
d. To protect the environment, no matter what
e. Other, please describe
_______________________________________________
If you had to choose one description for this decision, what would it be?
____ A personal decision
____ A business decision
____ An ethical decision
____ An environmental decision
____ A legal decision
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54
Appendix 5: Demographic measures Study 1 and Study 2
Geslacht:
 Man
 Vrouw
[gender]
Leeftijd:____________________
[age]
Nationaliteit:
 Autochtone Nederlander
 Allochtone Nederlander
 Anders, namelijk ____________________
[nationality]
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Appendix 6: Demographic measures Study 3
Gender:
 Male
 Female
Age:
Ethnicity
 Caucasian
 African American
 Latino
 Asian American
 Other (please specify) ____________________
Highest level of education
 No degree
 High school degree or GED certificate
 Associates degree
 Bachelors degree
 Masters degree, MBA, MPA, LLM, etc. .
 Doctoral degree
What is your annual family income?
 UNDER $20,000
 $20,000 to $39,999
 $40,000 to $59,999
 $60,000 to $79,999
 $80,000 to $99,999
 $100,000 to $119,999
 $120,000 to $139,999
 $140,000 to $159,999
 $160,000 and OVER
55
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56
Appendix 7: Items from the Lennox and Wolfe (1984) Self-Monitoring Scale designed to
capture one’s ability to modify self-presentation.
1. In social situations, I have the ability to alter my behavior if I feel that something else is
called for.
2. I have the ability to control the way I come across to people, depending on the impression
I wish to give them.
3. When I feel that the image I am portraying isn’t working, I can readily change it to
something that does.
4. I have trouble changing my behavior to suit different people and different situations.
5. I have found that I can adjust my behavior to meet the requirements of any situation I
find myself in.
6. Even when it might be to my advantage, I have difficulty putting up a good front.
7. Once I know what the situation calls for, it’s easy for me to regulate my actions
accordingly.
1 = Strongly disagree; 7 = Strongly agree
Dutch translation:
1. In sociale situaties kan ik mijn gedrag aanpassen als ik het gevoel heb dat de situatie daar
om vraagt.
2. Ik kan de manier waarop ik op anderen over kom beïnvloeden afhankelijk van het beeld
dat ik wil dat zij van mij hebben.
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57
3. Wanneer ik het gevoel heb dat het niet lukt om bij andere mensen op een bepaalde manier
over te komen, dan kan ik dit veranderen.
4. Ik vind het lastig mijn gedrag aan te passen aan verschillende mensen en verschillende
situaties.
5. Ik heb ontdekt dat ik mijn gedrag zodanig kan veranderen dat ik voldoe aan de
verwachting van die specifieke situatie.
6. Zelfs als het in mijn eigen voordeel is, heb ik moeite om goed op anderen over te komen.
7. Als ik weet wat de situatie van mij verwacht, is het makkelijk om mijn gedrag daarop aan
te passen.
1 = Sterk mee oneens; 7 = Sterk mee eens
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Appendix 8: Syntax planned analyses Study 1 and Study 2
*** SYNTAX STUDY 1
*** Descriptives & frequencies age, gender ratio, nationality ratio
DESCRIPTIVES VARIABLES=age
/STATISTICS=MEAN STDDEV MIN MAX.
FREQUENCIES VARIABLES=gender nationality
/ORDER=ANALYSIS.
*** Analyze whether the responses on the willingness to donate DV are normally distributed
PPLOT
/VARIABLES=donation_amount
/NOLOG
/NOSTANDARDIZE
/TYPE=P-P
/FRACTION=BLOM
/TIES=MEAN
/DIST=NORMAL.
FREQUENCIES VARIABLES=donation_amount
/NTILES=4
/STATISTICS=STDDEV VARIANCE RANGE MINIMUM MAXIMUM SEMEAN MEAN
MEDIAN MODE SKEWNESS SESKEW
KURTOSIS SEKURT
/ORDER=ANALYSIS.
*** Analyze the effects of age, gender & nationality on willingness to donate DV
REGRESSION
/MISSING LISTWISE
/STATISTICS COEFF OUTS R ANOVA
/CRITERIA=PIN(.05) POUT(.10)
/NOORIGIN
/DEPENDENT donation_amount
/METHOD=ENTER age.
UNIANOVA donation_amount BY gender
/METHOD=SSTYPE(3)
/INTERCEPT=INCLUDE
/CRITERIA=ALPHA(0.05)
/DESIGN=gender.
58
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UNIANOVA donation_amount BY nationality
/METHOD=SSTYPE(3)
/INTERCEPT=INCLUDE
/CRITERIA=ALPHA(0.05)
/DESIGN=nationality.
*** If willingness to donate is normally distributed:
Analyze the main hypothesis: The effects of condition on willingness to donate
UNIANOVA donation_amount BY condition
/METHOD=SSTYPE(3)
/INTERCEPT=INCLUDE
/POSTHOC=condition(TUKEY)
/CRITERIA=ALPHA(0.05)
/DESIGN=condition.
*** If willingness to donate is not normally distributed:
Analyze the main hypothesis: The effects of condition on willingness to donate, taking into
account the participants who decided not to donate at all
SPSSINC TOBIT REGR DEPENDENT = donation_amount
ENTER = condition
LOWERBOUND=0 DISTRIBUTION=GAUSSIAN
/OPTIONS MISSING=LISTWISE
/SAVE.
*** Analyze the potential moderating effect of self-monitoring
RELIABILITY
/VARIABLES= self-monitoring1 self-monitoring2 self-monitoring3 self-monitoring4 selfmonitoring5 self-monitoring6 self-monitoring7
/SCALE('ALL VARIABLES') ALL
/MODEL=ALPHA
/STATISTICS=DESCRIPTIVE SCALE
/SUMMARY=TOTAL.
DESCRIPTIVES VARIABLES= Selfmonitoring_score
/SAVE
/STATISTICS=MEAN STDDEV MIN MAX.
COMPUTE ZSelfmonitoring_scoreHigh = ZSelfmonitoring_score+1.
COMPUTE condition.ZSelfmonitoring_scoreHigh = condition*ZSelfmonitoring_scoreHigh.
REGRESSION
/DEPENDENT = donation_money
59
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60
/METHOD = ENTER lic ZSelfmonitoring_scoreHigh.
/METHOD = ENTER lic.ZSelfmonitoring_scoreHigh.
COMPUTE ZSelfmonitoring_scoreLow = ZSelfmonitoring_score-1.
COMPUTE condition.ZSelfmonitoring_scoreLow = condition*ZSelfmonitoring_scoreLow.
REGRESSION
/DEPENDENT = donation_money
/METHOD = ENTER condition ZSelfmonitoring_scoreLow.
/METHOD = ENTER condition.ZSelfmonitoring_scoreLow.
*** SYNTAX STUDY 2
*** Descriptives & frequencies age, gender ratio, nationality ratio
DESCRIPTIVES VARIABLES=age
/STATISTICS=MEAN STDDEV MIN MAX.
FREQUENCIES VARIABLES=gender nationality
/ORDER=ANALYSIS.
*** Analyze whether the responses on the commons dilemma DVw are normally distributed
PPLOT
/VARIABLES= time_filters [other_managers_filters likelihood_getting_caught amount_of
environmental_damage]
/NOLOG
/NOSTANDARDIZE
/TYPE=P-P
/FRACTION=BLOM
/TIES=MEAN
/DIST=NORMAL.
FREQUENCIES VARIABLES= time_filters [other_managers_filters likelihood_getting_caught
amount_of environmental_damage]
/NOLOG
/NTILES=4
/STATISTICS=STDDEV VARIANCE RANGE MINIMUM MAXIMUM SEMEAN MEAN
MEDIAN MODE SKEWNESS SESKEW
KURTOSIS SEKURT
/ORDER=ANALYSIS.
*** Analyze the effects of age, gender & nationality on the commons dilemma DV
REGRESSION
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61
/MISSING LISTWISE
/STATISTICS COEFF OUTS R ANOVA
/CRITERIA=PIN(.05) POUT(.10)
/NOORIGIN
/DEPENDENT time_filters [other_managers_filters likelihood_getting_caught amount_of
environmental_damage]
/NOLOG
/METHOD=ENTER age.
UNIANOVA time_filters [other_managers_filters likelihood_getting_caught amount_of
environmental_damage] BY gender
/METHOD=SSTYPE(3)
/INTERCEPT=INCLUDE
/CRITERIA=ALPHA(0.05)
/DESIGN=gender.
UNIANOVA time_filters [other_managers_filters likelihood_getting_caught amount_of
environmental_damage] BY nationality
/METHOD=SSTYPE(3)
/INTERCEPT=INCLUDE
/CRITERIA=ALPHA(0.05)
/DESIGN=nationality.
*** If the commons dilemma dv is normally distributed: Analyze the main hypothesis: The
effects of condition on amount of time participants run the filters
UNIANOVA time_running_filters [other_managers_filters likelihood_getting_caught amount_of
environmental_damage] BY condition
/METHOD=SSTYPE(3)
/INTERCEPT=INCLUDE
/POSTHOC=condition(TUKEY)
/CRITERIA=ALPHA(0.05)
/DESIGN=condition.
*** Analyze the potential moderating effect of self-monitoring
RELIABILITY
/VARIABLES= self-monitoring1 self-monitoring2 self-monitoring3 self-monitoring4 selfmonitoring5 self-monitoring6 self-monitoring7
/SCALE('ALL VARIABLES') ALL
/MODEL=ALPHA
/STATISTICS=DESCRIPTIVE SCALE
/SUMMARY=TOTAL.
DESCRIPTIVES VARIABLES= Selfmonitoring_score
Header: A PROPOSAL TO REPLICATE THE SELF-LICENSING EFFECT
/SAVE
/STATISTICS=MEAN STDDEV MIN MAX.
COMPUTE ZSelfmonitoring_scoreHigh = ZSelfmonitoring_score+1.
COMPUTE condition.ZSelfmonitoring_scoreHigh = condition*ZSelfmonitoring_scoreHigh.
REGRESSION
/DEPENDENT = time_filters
/METHOD = ENTER lic ZSelfmonitoring_scoreHigh.
/METHOD = ENTER lic.ZSelfmonitoring_scoreHigh.
COMPUTE ZSelfmonitoring_scoreLow = ZSelfmonitoring_score-1.
COMPUTE condition.ZSelfmonitoring_scoreLow = condition*ZSelfmonitoring_scoreLow.
REGRESSION
/DEPENDENT = time_filters
/METHOD = ENTER condition ZSelfmonitoring_scoreLow.
/METHOD = ENTER condition.ZSelfmonitoring_scoreLow.
62
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63
Appendix 9: Syntax planned analyses Study 3
*** SYTNAX STUDY 3
*** Descriptives and frequencies age, gender, ethnicity, family_income, education_level
DESCRIPTIVES VARIABLES=age
/STATISTICS=MEAN STDDEV MIN MAX.
FREQUENCIES VARIABLES=gender ethnicity family_income education_level
/ORDER=ANALYSIS.
*** Analyze whether the responses on the willingness to donate DV and the commons dilemma
DV are normally distributed
PPLOT
/VARIABLES=donation_amount
/NOLOG
/NOSTANDARDIZE
/TYPE=P-P
/FRACTION=BLOM
/TIES=MEAN
/DIST=NORMAL.
FREQUENCIES VARIABLES=donation_amount
/NTILES=4
/STATISTICS=STDDEV VARIANCE RANGE MINIMUM MAXIMUM SEMEAN MEAN
MEDIAN MODE SKEWNESS SESKEW
KURTOSIS SEKURT
/ORDER=ANALYSIS.
PPLOT
/VARIABLES=time_filters [other_managers_filters likelihood_getting_caught amount_of
environmental_damage]
/NOLOG
/NOSTANDARDIZE
/TYPE=P-P
/FRACTION=BLOM
/TIES=MEAN
/DIST=NORMAL.
FREQUENCIES VARIABLES=time_filters [other_managers_filters likelihood_getting_caught
amount_of environmental_damage]
/NTILES=4
/STATISTICS=STDDEV VARIANCE RANGE MINIMUM MAXIMUM SEMEAN MEAN
MEDIAN MODE SKEWNESS SESKEW
Header: A PROPOSAL TO REPLICATE THE SELF-LICENSING EFFECT
KURTOSIS SEKURT
/ORDER=ANALYSIS.
*** Analyze the effects of age, gender, ethnicity, family_income,& education_level on
willingness to donate DV and the commons dilemma DV
REGRESSION
/MISSING LISTWISE
/STATISTICS COEFF OUTS R ANOVA
/CRITERIA=PIN(.05) POUT(.10)
/NOORIGIN
/DEPENDENT donation_amount
/METHOD=ENTER age.
UNIANOVA donation_amount BY gender
/METHOD=SSTYPE(3)
/INTERCEPT=INCLUDE
/CRITERIA=ALPHA(0.05)
/DESIGN=gender.
UNIANOVA donation_amount BY nationality
/METHOD=SSTYPE(3)
/INTERCEPT=INCLUDE
/CRITERIA=ALPHA(0.05)
/DESIGN=nationality.
REGRESSION
/MISSING LISTWISE
/STATISTICS COEFF OUTS R ANOVA
/CRITERIA=PIN(.05) POUT(.10)
/NOORIGIN
/DEPENDENT donation_amount
/METHOD=ENTER family_income.
REGRESSION
/MISSING LISTWISE
/STATISTICS COEFF OUTS R ANOVA
/CRITERIA=PIN(.05) POUT(.10)
/NOORIGIN
/DEPENDENT donation_amount
/METHOD=ENTER eduction_level.
REGRESSION
/MISSING LISTWISE
/STATISTICS COEFF OUTS R ANOVA
64
Header: A PROPOSAL TO REPLICATE THE SELF-LICENSING EFFECT
65
/CRITERIA=PIN(.05) POUT(.10)
/NOORIGIN
/DEPENDENT time_filters [other_managers_filters likelihood_getting_caught amount_of
environmental_damage]
/METHOD=ENTER age.
UNIANOVA time_filters [other_managers_filters likelihood_getting_caught amount_of
environmental_damage] BY gender
/METHOD=SSTYPE(3)
/INTERCEPT=INCLUDE
/CRITERIA=ALPHA(0.05)
/DESIGN=gender.
UNIANOVA time_filters [other_managers_filters likelihood_getting_caught amount_of
environmental_damage] BY nationality
/METHOD=SSTYPE(3)
/INTERCEPT=INCLUDE
/CRITERIA=ALPHA(0.05)
/DESIGN=nationality.
REGRESSION
/MISSING LISTWISE
/STATISTICS COEFF OUTS R ANOVA
/CRITERIA=PIN(.05) POUT(.10)
/NOORIGIN
/DEPENDENT time_filters [other_managers_filters likelihood_getting_caught amount_of
environmental_damage]
/METHOD=ENTER family_income.
REGRESSION
/MISSING LISTWISE
/STATISTICS COEFF OUTS R ANOVA
/CRITERIA=PIN(.05) POUT(.10)
/NOORIGIN
/DEPENDENT time_filters [other_managers_filters likelihood_getting_caught amount_of
environmental_damage]
/METHOD=ENTER eduction_level.
*** If willingness to donate is normally distributed:
Analyze the main hypothesis: The effects of condition on willingness to donate and include order
as a second predictor to check for the effects of counterbalancing
UNIANOVA donation_amount BY condition order
/METHOD=SSTYPE(3)
/INTERCEPT=INCLUDE
/POSTHOC=condition(LSD)
Header: A PROPOSAL TO REPLICATE THE SELF-LICENSING EFFECT
/CRITERIA=ALPHA(0.05)
/DESIGN=condition order condition*order.
*** If willingness to donate is not normally distributed:
Analyze the main hypothesis: The effects of condition on willingness to donate, taking into
account the participants who decided not to donate at all
SPSSINC TOBIT REGR DEPENDENT = donation_amount
ENTER = condition order
LOWERBOUND=0 DISTRIBUTION=GAUSSIAN
/OPTIONS MISSING=LISTWISE
/SAVE.
*** If the commons dilemma DV is normally distributed:
Analyze the main hypothesis: The effects of condition on the amount of time and include order
as a second predictor to check for the effects of counterbalancing
UNIANOVA time_filters BY condition order
/METHOD=SSTYPE(3)
/INTERCEPT=INCLUDE
/POSTHOC=condition(LSD)
/CRITERIA=ALPHA(0.05)
/DESIGN= condition order condition*order.
*** Analyze the potential moderating effect of self-monitoring
RELIABILITY
/VARIABLES= self-monitoring1 self-monitoring2 self-monitoring3 self-monitoring4 selfmonitoring5 self-monitoring6 self-monitoring7
/SCALE('ALL VARIABLES') ALL
/MODEL=ALPHA
/STATISTICS=DESCRIPTIVE SCALE
/SUMMARY=TOTAL.
DESCRIPTIVES VARIABLES= Selfmonitoring_score
/SAVE
/STATISTICS=MEAN STDDEV MIN MAX.
COMPUTE ZSelfmonitoring_scoreHigh = ZSelfmonitoring_score+1.
COMPUTE condition.ZSelfmonitoring_scoreHigh = condition*ZSelfmonitoring_scoreHigh.
REGRESSION
/DEPENDENT = time_filters donation_amount
/METHOD = ENTER lic ZSelfmonitoring_scoreHigh.
/METHOD = ENTER lic.ZSelfmonitoring_scoreHigh.
66
Header: A PROPOSAL TO REPLICATE THE SELF-LICENSING EFFECT
COMPUTE ZSelfmonitoring_scoreLow = ZSelfmonitoring_score-1.
COMPUTE condition.ZSelfmonitoring_scoreLow = condition*ZSelfmonitoring_scoreLow.
REGRESSION
/DEPENDENT = time_filters donation_amount
/METHOD = ENTER condition ZSelfmonitoring_scoreLow.
/METHOD = ENTER condition.ZSelfmonitoring_scoreLow.
67
Header: A PROPOSAL TO REPLICATE THE SELF-LICENSING EFFECT
Appendix 10: Syntax planned meta-analysis in R
### META-analysis SIM (2009) replications
### Upload metaphor package
install.packages ("metafor")
library(metafor)
### Upload data textfile
dat <- read.table("Meta_SIM.txt", header=TRUE)
dat
### Run random effects model on meta datafile
res <- rma (yi,vi,method="DL", data=dat)
res
predict (res, level=95, transf=NULL)
confint(res)
### Create forest plot of meta datafile
forest(res, slab=paste(dat$author, dat$year, sep=", "),
ilab = cbind(dat$study),
ilab.xpos = c(-1.5))
op <- par(cex = 0.75, font=2)
text(c(-1.5),86,c("Study"))
text(-5.3,86, "Author(s) and Year", pos=4)
text(6.4,86, "Cohen's d [95% CI]", pos=2)
par(op)
68
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69
Appendix 11: Replication Grant Application for the Center for Open Science
We would like to apply for funds to pay participants for our replication studies. We will conduct two
studies in the lab (Study 1 at Tilburg University and Study 2 at the University of Amsterdam) and one
study on Amazon Mechanical-Turk.
For our proposed lab study (Study 1), we are planning to collect data from approximately 100
participants. The typical payment in the Tilburg University lab is €5 for a 30 minute experimental session.
100*5= €500 (approximately $654).
For our proposed lab study (Study 2), we are planning to collect data from approximately 100
participants. The typical payment in the University of Amsterdam lab is €5 for a 30 minute experimental
session. 100*5= €500 (approximately $654).
For both labs, we are planning to recruit participants for course credit. However, these studies
will take time at the expense of other planned studies (which we now have to run for money). Therefore,
we always calculate €5 for a 30 minute experimental session. The “profit” that we make with participants
who participate for course credit is used to cover the general expenses of the labs (assistants, computers,
etc).
For our proposed Amazon Mechanical-Turk study (Study 3), we are planning to include 918
participants. We are planning to offer participants $0.35 for their participation. 918*.35= $321.30.
Furthermore, 10 participants will receive an additional $10 for their participation. 10*10= $100. Thus, in
total, the Amazon Mechanical-Turk study will cost $421.30.
A possibility to more effectively use the available funds from the Center for Open Science is to
merge participant payment for any other replication proposals from the Social Psychology Department at
Tilburg University. We know of at least two other research groups who are also submitting proposal and
we would be happy to share funds for Lab resources with these other groups.
Budget
56
Payment for Lab Study 1
$ 654.005
Payment for Lab Study 2
$ 654.006
Payment for Mturk Study
$ 321.30
Money Mturk winners
$ 100.00
Total Requested Amount
$ 1729.30
Note that these rates are susceptible to change depending on the amount of participants that will participate
Header: A PROPOSAL TO REPLICATE THE SELF-LICENSING EFFECT
70
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