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Social Pressure on Heavy Thinkers? The Influence of Need for Cognition on Pre-Purchase Social Norm Nudges

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The design of user interfaces has seen an increasing use of digital nudging principles in recent years. Research has shown many nudging principles, like defaults or social norms, to be effective in persuasive systems. So far though, little research has focused on the user's personality and its influence on the efficacy of such nudges. This paper investigates the influence of an individual's need for cognition on the effectiveness of a digital social norms nudge. The experimental design operationalized an information research task for further education offerings. The results indicate that users with a higher need for cognition are 29.1% less likely to select the nudged option. This result aligns with theoretical findings but contrasts another study within the purchase stage of a customer journey that did not find significant moderation effects. It demonstrates the need for a careful consideration of users' personality traits when using digital nudges in persuasive systems.
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Social Pressure on Heavy Thinkers? The In6uence of Need for Social Pressure on Heavy Thinkers? The In6uence of Need for
Cognition on Pre-Purchase Social Norm Nudges Cognition on Pre-Purchase Social Norm Nudges
Armando Schär
University of Applied Science of the Grisons
, armando.schaer@fhgr.ch
Follow this and additional works at: https://aisel.aisnet.org/amcis2021
Schär, Armando, "Social Pressure on Heavy Thinkers? The In6uence of Need for Cognition on Pre-
Purchase Social Norm Nudges" (2021).
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Influence of Need for Cognition on Social Norms
Twenty-Seventh Americas Conference on Information Systems, Montreal, 2021
1
Social Pressure on Heavy Thinkers?
The Influence of Need for Cognition on Pre-
Purchase Social Norm Nudges
Completed Research
Armando Schär
University of Applied Science of the Grisons
armando.schaer@fhgr.ch
Abstract
The design of user interfaces has seen an increasing use of digital nudging principles in recent years.
Research has shown many nudging principles, like defaults or social norms, to be effective in persuasive
systems. So far though, little research has focused on the user’s personality and its influence on the efficacy
of such nudges. This paper investigates the influence of an individuals need for cognition on the
effectiveness of a digital social norms nudge. The experimental design operationalized an information
research task for further education offerings. The results indicate that users with a higher need for cognition
are 29.1% less likely to select the nudged option. This result aligns with theoretical findings but contrasts
another study within the purchase stage of a customer journey that did not find significant moderation
effects. It demonstrates the need for a careful consideration of users’ personality traits when using digital
nudges in persuasive systems.
Keywords
Digital Nudging, Social Norms, Need for Cognition, Customer Journey
Introduction
The targeted implementation of heuristics and biases to guide individuals in their decision-making
processes throughout user interfaces has become widespread in online platforms. Researchers have studied
this phenomenon termed digital nudging. The research stream around this term has gained attention
through the best-selling book Nudge by Thaler and Sunstein (2008) and has led to various scientific
substreams. Digital nudging is understood as the purposeful implementation of heuristics and biases in
choice environments, with the aim of guiding a user to make better decisions (Mirsch et al., 2017).
Such nudges make use of defaults, social cues, or anchoring biases, among others, to influence a user’s
decision toward a desired outcome (Schneider, Weinmann, & vom Brocke, 2017). Studies have shown a
general effectiveness of these nudging principles but have also found largely varying effect sizes (Hummel
& Maedche, 2019) as well as situations in which nudges tend to backfire (Burger et al., 1999; Schultz et al.,
2018). Hummel and Maedche (2019) predict that not only do nudge types and contexts have an influence
on their effect sizes (i.e., in which industries a nudge is applied) but also other moderators like an
individuals personality trait as demonstrated by Jung and Mellers (2016).
Therefore, it is of theoretical and practical relevance to deeply examine digital nudging principles beyond
design guidelines and investigate potential moderators. Studies imply that a user’s attributes like
personality (Jung & Mellers, 2016), cultural heritage (Hagman et al., 2015), and political preference (Fellner
et al., 2013) interact with a nudge’s effectiveness. As such interactions are scarcely studied, digital nudges
often show unexpected outcomes and largely varying effect sizes (Hummel & Maedche, 2019).
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Practitioners could benefit from more insights on how their customers personalities influence the
effectiveness of applied digital nudges. With the ongoing advancement of data collection and behavior
analysis applications in the design and usage of user interfaces, illuminating the effect of the personality on
digital nudges can allow partitioners to design better user interfaces and decision environments.
Current research streams are looking into moderation effects of various digital nudges in different contexts
and highlight the importance of gaining a better understanding of interactional effects (Hummel &
Maedche, 2019; Ingendahl et al., 2020; Maas et al., 2018; Schär & Stanoevska-Slabeva, 2019). The aim of
this research is to better understand how one of the most studied nudges, the social norms nudge (Hummel
& Maedche, 2019), is influenced by an individual’s personality.
One previous study that investigated the personality trait “need for cognition” (NFC) within a purchase
decision context and found no significant interactions on social norms nudges (Ingendahl et al, 2020).
Building on these findings, this study adds an additional insight on the potential moderation by NFC
through shifting the focus to investigating decision making in the pre-purchase customer journey context.
The research question therefore states: How does the personality trait “need for cognition” influence the
efficacy of social norms nudges in the pre-purchase customer journey stage?
Following this research question, the presented paper provides premier insight into interactions of digital
social norm nudges in a pre-purchase customer journey stage.
Digital Nudging
Thaler and Sunstein (2003) described nudging as “[…] an approach that preserves freedom of choice but
that authorizes both private and public institutions to steer people in directions that will promote their
welfare” (p. 179). Nudges contain “any aspect of the choice architecture that alters people’s behavior in a
predictable way without forbidding any options or significantly changing their economic incentives” (Thaler
& Sunstein, 2008, p. 6). Thaler and Sunstein’s research has been applied to the digital realm and has found
broad application in user interface design throughout various industries. The transfer of nudging into
human computer interface applications has been called digital nudging and is described as the use of user-
interface design elements to guide people’s behavior in digital choice environments (Weinmann et al.,
2016). Including behavioral patterns and heuristics into persuasive system design has been common, for
example, in social support principles (Oinas-Kukkonen & Harjumaa, 2009).
Other definitions focus on the predictive analytics of digital nudges (Gregor & Lee-Archer, 2016) or refer to
the original definition of nudging by Thaler and Sunstein (2008) without discussing specific characteristics
of its digital application (Esposito et al., 2017; Li et al., 2018; Lieberoth et al., 2018; Maas et al., 2018). Not
least, Mirsch et al. (2017), as well as Schär & Stanoevska (2019), understand digital nudging as being
facilitated by information and communication technology. It is an attempt to influence decision making,
judgment, or behavior in a predictable way by counteracting cognitive boundaries, biases, routines, and
habits that hinder individuals from acting in their own self-interest in the digital sphere. It does not forbid
or add any rational-choice option, change incentives significantly, or provide rational argumentation.
Current research shows different classifications of the various types of digital nudges. While Sunstein
(2019) lists 10 nudge categories (e.g., default, simplification, social norms, pre-commitment strategies),
other researchers focus on examining the underlying psychological effects (Mirsch et al., 2017) that had
been used instead of nudge classifications. These effects had also been combined into the 5 overarching
digital nudging principles: status quo bias, social norms, loss aversion, anchoring and adjustment, as well
as hyperbolic discounting (Mirsch et al., 2018).
Social Norm Nudges
Cialdini & Trost (1998) define social norms as “rules and standards that are understood by members of a
group, and that guide and/or constrain social behavior without the force of laws” (p. 152). These social
norms may consist of societal or our own expectations for our behavior as well as standards that develop
from our observations of other people’s behavior (Cialdini & Trost, 1998). This study investigates how
observed behavior in a digital context influences a users’ decision making. A specific focus lies within
behavioral change when individuals are shown information about how many people decide in a specific
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choice situation as proposed by Sunstein (2019) and implemented in various studies (Maas et al., 2018;
Cialdini, 2013).
The effect of social norms has been intensely studied. Burnkrant and Cousineau (1975) provided support
for the informational social influence in a purchase stage context and made a statement for the importance
of social product evaluations long before e-commerce star ratings were en vogue. In their literature review,
Cialdini and Goldstein (2004) studied how compliance and conformity interact with external forces to
reduce social influence processes. In various experiments and field studies, researchers investigated the
effects of social norm nudges. Cialdini et al.s (2006) field experiment showed the persuasive impact of
social norms on people’s behavior (in that case, stealing petrified wood in a forest). Another field
experiment focusing on private energy consumption led to significant less consumption in a monitoring
group that experienced social norm nudges (Wong-Parodi et al., 2019). Experimental setups also included
studying preferred communication channel choice with an insurance in the pre-purchase context (Maas et
al., 2018) or using star ratings in an e-commerce purchase context (Djurica & Figl, 2017). The importance
of social norms to the design of persuasive systems has also been discussed (Castmo & Persson, 2018;
Oinas-Kukkonen & Harjumaa, 2009).
Customer Journey Perspective
Various researchers have attested to digital nudges leading to different behaviors across changing decision
environments and contexts. Hummel and Maedche (2019) showed significant differences based on the
nudge type (such as social norms or defaults) and context (industry in which nudges are applied such as
finances, policy making, or health) and further stated moderating effects (such as political preferences and
personality traits). Maas et al. (2018) first applied the customer journey perspective to the topic of nudging.
Customersactions are different at the beginning of the journey. Potential customers recognize their needs,
search for solutions, and consider a purchase in the pre-purchase stage. They then focus transactional tasks
like choice, ordering, and payment within the purchase stage. Finally, they focus on usage, consumption,
and support requests in the post-purchase stage (Lemon & Verhoef, 2016). Maas et al.s (2018) study
showed significant differences in nudge efficacy across the customer journey. They argued that different
customer goals in the three stages (pre-purchase, purchase, and post-purchase) and the varying
consequences of a decision lead to the changing efficacy of the same nudging principle throughout the
customer journey. Consequently, understanding how digital nudges work in a pre-purchase stage, where
customers consider a purchase and gather information, can lead to a more goal-oriented implementation
of nudging principles and allow practitioners to use the right nudge at the right moment of the customer
journey.
While several studies have focused on purchase-driven decision environments (Schär & Stanoevska-
Slabeva, 2019), investigations into decision behavior at early stages of a customer journey are scarce. Schär
and Stanoevska-Slabeva (2019) classified 29 studies into the three customer journey stages and offered
insights into the effectiveness of the various nudges in the pre-purchase context. Their findings listed 10
studies in the pre-purchase stage that examined various nudges such as framing (Chen, Kyaw, & Ross,
2008; Hall & Towers, 2017), social norms (Moran, Muzellec, & Nolan, 2014; Wolny & Charoensuksai, 2014),
color coding (Maas et al., 2018), among others.
Moderators for Social Norm Nudges
While social norm nudges have been proven in various contexts to have a large effect on decision behavior,
Hummel and Maedche (2019) compared effect sizes of 12 studies that investigated 49 social reference
effects. While the median effect sizes of social references show a positive median effect (20%), the compared
studieseffects sizes ranged from 20.5% (Kallbekken & Sælen, 2013) to +165% (Demarque et al., 2015).
The authors discussed various potential interactions such as nudging context (in terms of industry like
environment, energy, health) and foreshadowed several further moderation effects. Stutzer et al.’s (2011)
study on blood donation behavior speculates the personality trait conscientiousness to have an influence
on donation behavior when using default nudges but fails to report significant results. Jung and Mellers
(2016) measured attitudes toward nudges and found various individual dispositions and perceptions to
oppose or support different types of nudges. Furthermore, studies have linked people’s personality to their
consuming behavior in a marketing context (Mulyanegara, Tsarenko, & Anderson, 2009). These insights
indicate a potential moderation of the various digital nudging principles through the recipient’s personality.
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Several cognitive theories have studied which personality traits influence human decisions. The elaboration
likelihood model of persuasion offers a dual-process theory that tries to explain individual decision making
(Morris, Woo, & Singh, 2005; Petty & Cacioppo, 1986; Tam & Ho, 2005). This theory states that an
individual that is motivated and has the ability to process central variables of a decision will process given
information in more depth. In contrast, the person’s thinking and decision-making process will follow a
peripheral route when NFC is not given. Research indicates that social norm nudges have a larger impact
on an individual’s attitudes and decision behavior on the peripheral decision route compared to the central
decision route. NFC is an individual’s intrinsic motivation to think about information before making a
decision (Cacioppo et al., 1984). Therefore, NFC serves as an important and stable individual personality
trait that moderates behavior in a wide range of domains (Petty et al., 2009). It has become a key moderator
in dual-process persuasion theories. One study that investigated the influence of personality on social norm
nudges is Ingendahl’s et al.’s (2020) approach. Following a theoretical rationale, they observed social norms
and defaults to be robust against the NFC personality traits in their purchase stage experiments.
Another insight was Maas et al.’s (2018) experimental study showing that in all social cue nudges, there was
significantly higher influence of the nudge in the group with lower cognitive reflection skills. This implies a
negative interaction of high NFC values on a social norms nudge efficacy. Following this theoretical
reasoning, NFC should have an impact on social norms in the pre-purchase context. Following this
theoretical discussion, we hypothesize that a high NFC leads individuals to take the central decision route,
which makes them less susceptible to social norm nudges:
H1: High “need for cognition” values negatively moderate the digital social norms nudge in a pre-
purchase decision environment.
The hypothesis will be tested through an experimental research design, like several studies that investigated
digital nudging and its correlating effects (Fonseca & Grimshaw, 2017; Maas et al., 2018; Székely et al.,
2016; Tietz et al., 2016).
Experimental Design
The online experiment aims to analyze moderating effects of a digital social norms nudge in a pre-purchase
decision context that is defined by users recognizing their needs, searching for solutions, and considering a
purchase (Lemon & Verhoef, 2016). As the effects of social norms emerge from observing how others behave
(Cialdini & Trost, 1998), the experimental design aims at simulating how others decide when searching for
solutions and considering a purchase. To operationalize this, a search task where users inform themselves
about a recognized need seems appropriate for an online experiment, especially since users are used to
searching the internet via their digital devices when considering a purchase. To set up a realistic
experimental scenario, the search task focuses on an individual’s further education, as this topic is of
individual relevance and involves much information to make a decision.
To acquire participants for experiments, current behavioral research often utilizes online clickworker
platforms. The validity of scientific data collected via MTurk has been investigated, and researchers have
found that participants produce reliable results that are consistent with decision-making biases (Goodman
et al., 2013). Therefore, this experimental study recruits its participants on this platform. To address
documented drawbacks of utilizing clickworker portals, an instructional manipulation check (Oppenheimer
et al., 2009) assures the participantsattention on the task, and a manipulation check toward the end of the
experiment validates the manipulationspersistence. A pre-test has taken place to validate questions, the
procedure, and the compensation offered to the participants.
Procedure and Materials
The experimental setup was implemented as follows. After giving consent to the data usage policy,
participants are instructed to think about further educating themselves. As a warm-up question and to
support individual relevance of the taskas discussed by Morris et al. (2005) and Petty and Cacioppo
(1986)participants are told to think of and write down one to three educational courses/subjects that are
of interest to them. Following this short brainstorming session, the participants are told that they have
decided to further inform themselves about available education programs for their most favorite subject
and to type in their query in the search box to search for such an offering.
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The participants are then randomly assigned to the control group or the treatment group and presented a
search results page that contains the main manipulation. The results page represents a choice architecture,
where participants are shown two search results and decide which one to further consider. Figure 1 shows
the choice architecture consisting of the individual search query (that is copied from the participants
previous input), two generalized search results, and a question asking about which of the two results one
desires further education. The treatment group is shown a social norms hint below the question, whereas
the control group is not.
Figure 1: Search results page with individual search query and the social norms nudge
The order in which the answer options are presented is randomized. To compare control group (without
the nudging hint) with the treatment group, the nudge consistently guides the user toward the “Institute of
Andeer” option. Sunstein (2019) described the social norms nudge to be most effective when it is local and
emphasizes what most people do. Based on Sunsteins (2019) guide to nudging, the user is told that 87% of
other users (picked as a random number above the threshold that triggers pro-social behavior) are tending
toward one of the options. The operationalization of the nudge is purely textual to prevent confounds like
color coding or pop-ups that had significant influences in other studies (Maas et al., 2018).
After making a decision for one of the options (dependent variable), the participants are presented with an
instructional manipulation check question based on Oppenheimer et al.’s (2009) suggestions, where they
are asked to choose the no answer option of a 7-point-likert scale for a question with the title search
frequency.” Taking into account Goodman et al.s insights (2013) on working with online surveys in
behavioral experiments, failure to pass the instructional manipulation check leads the participant to be
excluded from the evaluated data set. After the decision has been made, the participants are asked to fill out
a questionnaire. It first evaluates the participants’ NFC. The questions include the validated short-item
inventory (Beißert et al., 2014) of Petty and Cacioppo’s (1986) original questionnaire, containing the
questions 25, 39, 40, and 41. The answers are recorded using a 7-point-likert scale (1 = doesn’t apply at all
to 7 = applies completely).
To compare user behavior with other studies, the participants are then presented with a standardized
cognitive reflection test (Frederick, 2005). A manipulation check raises the persistence of the social norms
nudge to see if participants remain conscious of the given information. Finally, participants are asked for
relevant demographic information (gender, age, and educational background) and thanked for their
participation.
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Results
The experiment was conducted in late 2020 and 484 participants were recruited. 89 participants (18.4%)
failed the instructional manipulation check and were excluded from further analysis. Demographic
statistics reported a male majority (male = 63%, female = 36.2%, unspecified/empty = 0.8%) and
predominantly high educational background (graduate = 33.7%, undergraduate = 46.1%, junior college and
rest = 20.2%), with a mean age of 33.86 years (Median = 32 years, SD = 20.284).
The impact of the social norms nudge on decision behavior showed a significant correlation of treatment
allocation and choice behavior (Chi2(1) = 21.117, p = .000, n = 395). The effect is considered to be small to
medium (Phi = .231, p = .000). Cross-tabulation analysis of the participants’ choices demonstrated
significant impact of the social norms nudge toward a user’s choice, as illustrated in Figure 2. While 46.2%
of the users in the control group decided on the option of “Institute of Andeer,” the favorable response with
the applied social norms nudge reached 69%.
Figure 2: Percentage of participants choosing the nudged/intended option
The questionnaire consisted of the NFC items and the cognitive reflection test of Frederick (2005). The
cognitive reflection test showed no significant correlation of cognitive reflection abilities and click behavior
(Chi2 (4) = .778, p = .941, n = 395).
Influence on Social Norms
To analyze the moderating effect of individualsNFC on the nudging effect, the NFC value of each
participant was calculated and put into perspective using a regression. The participants answers to the 7-
point NFC items have been recoded by inverting answers to the questions 41, “Simply knowing the answer
rather than understanding the reasons for the answer to a problem is fine with meand 25, “I primarily
think because I have toand were then computed into a mean NFC value with question 39, I prefer my life
to be filled with puzzles that I solveand 40, “I would prefer complex to simple problemson a scale of 1 to
7. The NFC value resulted in a mean of 4.334 (SD = 1.21).
Due to the dichotomous dependent variable (0 = not nudged option, 1 = nudged option), a logistic
regression was calculated to analyze the overall effect of social norms on click behavior. Then, the
hypothesized moderation of NFC on the social norms nudging effect was tested by inserting the interaction
into the logistic model. Finally, the control variables age, gender, and education were inserted into the
equation. The regression, as illustrated in Table 1, shows that the summarized model (Chi2 (5) = 30.470, p
= .000, n = 395) as well as the coefficient of the social norms nudge and its moderation through the NFC
value of the participants are significant. Consequently, an individual’s likelihood to make the nudged
decision decreases by 29.1% by every additional point in the NFC scale.
Table 1: Logistic Regression on Click Behavior
Independent Variables
B
df
Exp(B)
Social Norms Nudge
2.510
1
12.310
Social Norms Nudge ×
Need for Cognition
-0.344
1
0.709
Education
0.085
1
1.089
Gender
-0.063
1
0.939
Age
0.007
1
1.007
Constant
-0.288
1
0.750
*p > .05. **p > .005.
46.2%
69.0%
0% 20% 40% 60% 80% 100%
Control Group
Social Norms Nudge
% of people choosing the nudged/intended option
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To exclude the confound that NFC also moderates the control groups choice behavior, both treatment and
control group had been examined on a potential correlation through a Pearson chi-square analysis.
Consistent with the above findings, the calculation shows that the NFC and click behavior significantly
correlate in the treatment group (Chi2 (30) = 48.539, p = .018, n = 200) and does not correlate in the control
group (Chi2 (30) = 30.246, p = .453, n = 195).
Discussion
This online experiment investigated how a social norms nudge is influenced in a pre-purchase customer
journey stage, where users research information before considering a purchase. Based on previous research
and theorizing, it was expected that the social norms nudge would have a positive impact on the desired
clicking behavior. Concluding the literature research, it was further hypothesized that a user with a high
individual NFC would be less prone to social norms nudges.
As meta-studies have postulated (Hummel & Maedche, 2019), the social norms nudge had a significant
impact on potential customersdecision behavior. Previous studies have described that digital nudges are
moderated by external factors like a user’s personality (Jung & Mellers, 2016) or political preference
(Fellner et al., 2013). The undertaken experiment shows that a digital social norms nudge implemented in
a pre-purchase customer journey context is indeed influenced by the potential customer’s NFC. While the
experimental context was able to demonstrate the social norms effect, the effect size might likely vary in
other contexts, as Hummel and Maedche (2019) have shown in their comparison of empirical nudging
studies. The main effect of the social norms nudge had been proven by various researchers (Cialdini et al.,
2006; Cialdini & Trost, 1998; Maas et al., 2018; Thaler & Sunstein, 2008) and served to investigate the
potential moderation through the NFC personality trait. The study indicates a significant influence of a
user’s NFC on the efficacy of social norms nudges in the pre-purchase context. In line with H1, this study
shows that for every 1-point increase in the NFC scale, the social norms nudging effect is reduced by 29.1%.
Theoretical Implications
Although theoretical derivation has led to the verified hypothesis, this study sheds new light on moderating
effects in comparison to other research. Worth mentioning is the contrast to Ingendahl et al.’s (2020)
findings that did not show a significant effect of NFC on social norms in a purchase context. The presented
study adds additional insight to previous research. In both studies, the digital nudge had been designed
according to Sunstein’s (2019) guide and has shown a positive effect on decision behavior. Thus, the
difference of the moderation effect between the two studies likely stems from the differing context of the
studies. Contextual differences were the domain of the decision (buying coffee beans vs. information
research on further education offerings), the stage of the customer journey (purchase vs. pre-purchase), as
well as potential cultural differences as one study had been implemented in a U.S. context and the other in
a German cultural frame. In line with Ingendahl et al.’s (2020) research though, social norm nudges remain
effective, even for those with a high individual NFC score. A main conclusion of these insights is that the
strength of a moderation varies in different contexts. It cannot be assumed that NFC has the same impact
on a digital social norms nudge in different settings. Rather, the result of this study, in contrast to Ingendahl
et al., demonstrates that varying contexts and dimensions may lead to contradicting influences of potential
moderators. NFC serves as a key differentiator in the elaboration likelihood model of persuasion (Petty &
Cacioppo, 1986). The finding that NFC moderates social norm nudges leads to the question of whether other
nudges are also influenced by NFC and different nudging principles (e.g., defaults, loss aversion).
The results imply an investigation of digital nudges from a dual-process perspective. A classification of
nudges into central or peripheral decision route, as postulated by the elaboration likelihood model theory
could be a potential research branch. Researchers have already discussed classifying nudges in system one
and system two in terms of dual-process theory (Kahneman, Knetsch, & Thaler, 1991; Tversky &
Kahnemann, 1981).
Practical Implications
Regarding the results of this study in comparison with existing research, it seems obvious that it is a far way
to postulate a set of rules for practical operationalization of digital nudges that allow a precise prediction
for their effects on decision behavior. Hence, it comes as a small surprise that researchers had been aiming
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at developing guides on how to design and implement digital nudges in a trial-and-error manner
recommending A/B and split testing approaches (Schneider et al., 2018) and controlled trails (Sunstein,
2019). Currently, it is unknown when to utilize which digital nudge at which (industry) context and point
in time (of a customer journey). This study implies that practitioners should not only carefully choose and
shape digital nudges but also consider their customers personalities like their NFC.
Limitations and Further Research
This study provides support that an individuals NFC moderates digital social norm nudges. An integration
of these findings into a customer journey perspective could shed light on how personality traits or other
potential moderators influence single nudges throughout the customer journey. Further research could aim
at creating a theoretical framework for nudging throughout the customer journey and make the application
of nudging more predictable for practitioners.
While the experimental approach has been conducted following scientific protocol, the experimental setting
represents a limitation. On one hand, the experimental context of information research for educational
offerings cannot be adapted to any other user case like buying a car or making policies. Furthermore, the
participants had been recruited in the North American region and, as Hagman et al. (2015) demonstrated,
cultural differences have significant impact on the efficacy of digital nudges. Other potentially correlating
factors such as the personality trait “need for uniqueness” (as used by Ingendahl, 2020) or general
intelligence (shown as potentially correlating by Petty & Cacioppo, 1982) were not considered. Last,
although Goodman et al. (2013) provided evidence that data collection through clickworker portals satisfy
scientific requirements (and their recommendations had been followed in this study), these types of
participants are extrinsically monetary motivated. A field study that includes intrinsically motivated
customers would enrichen the study’s findings.
Conclusion
This paper has shown that NFC significantly moderates a digital social norms nudge in a specific context.
Within a pre-purchase information context, it supports the foreshadowed interaction of personality and
digital nudges. There is significant interaction between an individual’s NFC and the decision behavior when
confronted with a digital social norms nudge. These findings add to the current scientific discussion on
interactions of digital nudges and deepen the current discussion, as the findings were able to primarily back
up theoretical claims that digital nudges are significantly impacted by an individual’s personality traits.
These findings may lead to further investigations across other digital nudging principles, industries, and
customer journey contexts. Finally, the study shows that interactions may vary throughout the customer
journey and the context where digital nudges are being applied. As this study further elaborates on the
complexity of digital nudges, practitioners are advised to apply trial-and-error guides when designing
digital nudges to minimize unwanted effects by their nudges and maximize their impacts.
REFERENCES
Beißert, H., Köhler, M., Rempel, M., & Beierlein, C. (2014). Eine deutschsprachige Kurzskala zur Messung
des Konstrukts Need for Cognition [A German short-scale for measuring the construct need for
cognition]. GESIS- Working PapersWorking Papers, 32.
Burger, J. M., Reed, M., DeCesare, K., Rauner, S., & Rozolis, J. (1999). The effects of initial request size on
compliance: More about the that’s-not-all technique. Basic and Applied Social Psychology, 21(3),
243249.
Burnkrant, R. E., & Cousineau, A. (1975). Informational and normative social influence in buyer behavior.
Journal of Consumer Research, 2(3), 206.
Cacioppo, J. T., Petty, R. E., & Feng Kao, C. (1984). The efficient assessment of need for cognition. Journal
of Personality Assessment, 48(3), 306307.
Cacioppo, J. T., & Petty, R. E. (1982). The need for cognition. Journal of Personality and Social Psychology,
42(1), 116131.
Castmo, M., & Persson, R. (2018). The alliance of digital nudging & persuasive design: The
complementary nature of the design strategies. Master’s thesis, Lund University.
Chen, J. V., Kyaw, P. L. N., & Ross, W. H. (2008). The customer journey when purchasing a new mobile
Influence of Need for Cognition on Social Norms
Twenty-Seventh Americas Conference on Information Systems, Montreal, 2021
9
phone: Testing a dual mediation model. Journal of Direct, Data and Digital Marketing Practice,
10(2), 116132.
Cialdini, R. B. (2003). Crafting normative messages to protect the environment. Current Directions in
Psychological Science, 12(4), 105109.
Cialdini, R. B., Demaine, L. J., Sagarin, B. J., Barrett, D. W., Rhoads, K., & Winter, P. L. (2006). Managing
social norms for persuasive impact. Social Influence, 1(1), 315.
Cialdini, R. B., & Goldstein, N. J. (2004). Social influence: Compliance and conformity. Annual Review of
Psychology, 55(1974), 591621.
Cialdini, R. B., & Trost, M. R. (1998). Social influence: Social norms, conformity and compliance. In D. T.
Gilbert, S. T. Fiske, & G. Lindzey (Eds.), The handbook of social psychology (pp. 151-192). McGraw-
Hill.
Demarque, C., Charalambides, L., Hilton, D. J., & Waroquier, L. (2015). Nudging sustainable consumption:
The use of descriptive norms to promote a minority behavior in a realistic online shopping
environment. Journal of Environmental Psychology, 43, 166174.
Djurica, D., & Figl, K. (2017). The effect of digital nudging techniques on customers’ product choice and
attitudes towards e-commerce sites. Twenty-third Americas Conference on Information Systems, 1
5.
Esposito, G., Hernández, P., van Bavel, R., & Vila, J. (2017). Nudging to prevent the purchase of
incompatible digital products online: An experimental study. PLOS ONE, 12(3), e0173333.
Fellner, G., Sausgruber, R., & Traxler, C. (2013). Testing enforcement strategies in the field: Threat, moral
appeal and social information. Journal of the European Economic Association, 11(3), 634660.
Fonseca, M. A., & Grimshaw, S. B. (2017). Do behavioral nudges in prepopulated tax forms affect
compliance? Experimental evidence with real taxpayers. Journal of Public Policy and Marketing,
36(2), 213226.
Frederick, S. (2005). Cognitive reflection and decision making. Journal of Economic Perspectives, 19(4),
2542.
Goodman, J. K., Cryder, C. E., & Cheema, A. (2013). Data collection in a flat world: The strengths and
weaknesses of Mechanical Turk samples. Journal of Behavioral Decision Making, 26(3), 213224.
Gregor, S., & Lee-Archer, B. (2016). The digital nudge in social security administration. International Social
Security Review, 69(34), 6383.
Hagman, W., Andersson, D., Västfjäll, D., & Tinghög, G. (2015). Public views on policies involving nudges.
Review of Philosophy and Psychology, 6(3), 439453.
Hall, A., & Towers, N. (2017). Understanding how Millennial shoppers decide what to buy: Digitally
connected unseen journeys. International Journal of Retail and Distribution Management, 45(5),
498517.
Hummel, D., & Maedche, A. (2019). How effective is nudging? A quantitative review on the effect sizes and
limits of empirical nudging studies. Journal of Behavioral and Experimental Economics,
80(February), 4758.
Ingendahl, M., Hummel, D., Maedche, A., & Vogel, T. (2020). Who can be nudged? Examining nudging
effectiveness in the context of need for cognition and need for uniqueness. Journal of Consumer
Behaviour, July, 113.
Jung, J. Y., & Mellers, B. A. (2016). American attitudes toward nudges. Judgment and Decision Making,
11(1), 6274.
Kahneman, D., Knetsch, J. L., & Thaler, R. H. (1991). Anomalies: The Endowment Effect, Loss Aversion,
and Status Quo Bias. Journal of Economic Perspectives, 5(1), 193206.
Kallbekken, S., & Sælen, H. (2013). “Nudging” hotel guests to reduce food waste as a win-win environmental
measure. Economics Letters, 119(3), 325327.
Lemon, K. N., & Verhoef, P. C. (2016). Understanding customer experience throughout the customer
journey. Journal of Marketing, 80(6), 69–96.
Li, Y., Fan, W., Liu, F., Lim, E., Liu, Y., & Tan, C. (2018). Exploring the nudging and counter-nudging
effects of campaign updates in crowdfunding. Proceedings of Pacific Asia Conference on Information
Systems, Japan, 281, https://aisel.aisnet.org/pacis2018/281
Lieberoth, A., Holm Jensen, N., & Bredahl, T. (2018). Selective psychological effects of nudging,
gamification and rational information in converting commuters from cars to buses: A controlled field
experiment. Transportation Research Part F: Traffic Psychology and Behaviour, 55, 246261.
Maas, P., Bieler, M., Borchert, M., & Barwitz, N. (2018). Nudging along the customer journey. Marketing
Review St. Gallen, 35(4), 8896.
Influence of Need for Cognition on Social Norms
Twenty-Seventh Americas Conference on Information Systems, Montreal, 2021
10
Mirsch, T., Lehrer, C., & Jung, R. (2017). Digital nudging: Altering user behavior in digital environments.
Proceedings der 13. Internationalen Tagung Wirtschaftsinformatik (WI 2017), 634648.
Mirsch, T., Lehrer, C., & Jung, R. (2018). Making digital nudging applicable: The digital nudge design
method. In Proceedings of the 39th International Conference on Information Systems, San Francisco,
1-16.
Moran, G., Muzellec, L., & Nolan, E. (2014). Consumer moments of truth in the digital context: How
“search” and “E-word of mouth” can fulel consumer decision making. Journal of Advertising
Research, 54(2), 200204.
Morris, J. D., Woo, C., & Singh, A. J. (2005). Elaboration likelihood model: A missing intrinsic emotional
implication. Journal of Targeting, Measurement and Analysis for Marketing, 14(1), 7998.
Mulyanegara, R. C., Tsarenko, Y., & Anderson, A. (2009). The Big Five and brand personality: Investigating
the impact of consumer personality on preferences towards particular brand personality. Journal of
Brand Management, 16(4), 234247.
Oinas-Kukkonen, H., & Harjumaa, M. (2009). Persuasive systems design: Key issues, process model, and
system features. Communications of the Association for Information Systems, 24(1), 485500.
Oppenheimer, D. M., Meyvis, T., & Davidenko, N. (2009). Instructional manipulation checks: Detecting
satisficing to increase statistical power. Journal of Experimental Social Psychology, 45(4), 867872.
Petty, R. E., Brinol, P., Loersch, C., & McCaslin, M. J. (2009). The need for cognition. In Handbook of
individual differences in social behavior (pp. 318329). Guilford Press.
Petty, R. E., & Cacioppo, J. T. (1986). The elaboration likelihood model of persuasion. In Communication
and Persuasion: Central and Peripheral Routes to Attitude Change (pp. 124). Springer New York.
Schär, A., & Stanoevska-Slabeva, K. (2019). Application of digital nudging in customer journeys A
systematic literature review. In Twenty-fifth Americas Conference on Information Systems, Mexico,
1–10.
Schneider, C., Weinmann, M., & vom Brocke, J. (2017). Digital nudgingGuiding choices by using interface
design. Schneider, C., Weinmann, M., and vom Brocke, J.(2018). Digital NudgingGuiding Choices
by Using Interface Design, Communications of the ACM, 61(7), 6773.
Schneider, C., Weinmann, M., & vom Brocke, J. (2018). Digital nudging: Guiding online user choices
through interface design. Communications of the ACM, 61(7), 6773.
Schultz, P. W., Nolan, J. M., Cialdini, R. B., Goldstein, N. J., & Griskevicius, V. (2018). The constructive,
destructive, and reconstructive power of social norms: Reprise. Perspectives on Psychological
Science, 13(2), 249254.
Stutzer, A., Goette, L., & Zehnder, M. (2011). Active decisions and prosocial behaviour: A field experiment
on blood donation. Economic Journal, 121(556), 476493.
Sunstein, C. R. (2014). Why nudge? The politics of libertarian paternalism. Yale University Press.
Sunstein, C. R. (2019). Nudging: A very short guide. Business Economics, 54(2), 127129.
Székely, N., Weinmann, M., & vom Brocke, J. (2016). Nudging people to pay CO2 offsetsthe effect of
anchors in flight booking processes. Proceedings of the European Conference on Information
Systems, Turkey, 62. https://aisel.aisnet.org/ecis2016_rip/62
Tam, K. Y., & Ho, S. Y. (2005). Web personalization as a persuasion strategy: An elaboration likelihood
model perspective. Information Systems Research, 16(3), 271291.
Thaler, R. H., & Sunstein, C. R. (2003). Libertarian paternalism. American Economic Review, 93(2), 175
179.
Thaler, R. H., & Sunstein, C. R. (2008). Nudge: Improving decisions about health, wealth, and happiness.
Yale University Press.
Tietz, M., Simons, A., Weinmann, M., & vom Brocke, J. (2016, December). The decoy effect in reward-based
crowdfunding: Preliminary results from an online experiment. 2016 International Conference on
Information Systems.
Tversky, A., & Kahnemann, D. (1981). The framing of decisions and the psychology of choice. Science,
211(4481), 453458. https://doi.org/10.1126/science.7455683
Weinmann, M., Brocke, J., & Schneider, C. (2016). Digital nudging. Business and Information Systems
Engineering, 58(6), 433436.
Wolny, J., & Charoensuksai, N. (2014). Mapping customer journeys in multichannel decision-making.
Journal of Direct, Data and Digital Marketing Practice, 15(4), 317326.
Wong-Parodi, G., Krishnamurti, T., Gluck, J., & Agarwal, Y. (2019). Encouraging energy conservation at
work: A field study testing social norm feedback and awareness of monitoring. Energy Policy, 130,
197205.
... In addition, we controlled for need for cognition (NFC). Based on research studying this construct (Schär, 2021), it is expected that people with high NFC are less likely to be influenced by a social norms nudge. We used an established scale (Beissert et al., 2014) consisting of four items, which were derived from the original scale to measure NFC by Cacioppo and Petty (Cacioppo et al., 1984). ...
... As users presumably are very motivated to organize safe and relaxing summer holidays after months of lockdowns and quarantine, they may have a high intrinsic motivation to inform themselves about how the pandemic will likely affect their travel plans, independent from any other social opinion that is shown to them. Further support for this argument has been shown by Schär (2021) who demonstrated a negative moderation effect of NFC on social norm nudges. People who tend to think things through are less likely to change their behavior based on what others do. ...
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