ArticlePDF Available

Abstract and Figures

Current research on choice overload has been mainly conducted with choice options not associated with specific brands. This study investigates whether the presence of brand names in the choice set affects the occurrence of choice overload. Across four studies, we find that when choosing among an overabundance of alternatives, participants express more positive feelings (i.e., higher satisfaction/confidence, lower regret and difficulty) when all the options of the choice set are associated with familiar brands, rather than unfamiliar brands or no brand at all. We also find that choice overload only appears in the absence of brand names, but disappears when all options contain brand names—either familiar or unfamiliar. Theoretical and practical implications are discussed.
Content may be subject to copyright.
1 23
Mind & Society
Cognitive Studies in Economics and
Social Sciences
ISSN 1593-7879
Mind Soc
DOI 10.1007/s11299-019-00210-7
The Role of the Brand on Choice Overload
Raffaella Misuraca, Francesco Ceresia,
Ursina Teuscher & Palmira Faraci
1 23
Your article is protected by copyright and
all rights are held exclusively by Springer-
Verlag GmbH Germany, part of Springer
Nature. This e-offprint is for personal use only
and shall not be self-archived in electronic
repositories. If you wish to self-archive your
article, please use the accepted manuscript
version for posting on your own website. You
may further deposit the accepted manuscript
version in any repository, provided it is only
made publicly available 12 months after
official publication or later and provided
acknowledgement is given to the original
source of publication and a link is inserted
to the published article on Springer's
website. The link must be accompanied by
the following text: "The final publication is
available at link.springer.com”.
Vol.:(0123456789)
Mind & Society
https://doi.org/10.1007/s11299-019-00210-7
1 3
The Role oftheBrand onChoice Overload
RaaellaMisuraca1,2· FrancescoCeresia1· UrsinaTeuscher3· PalmiraFaraci4
© Springer-Verlag GmbH Germany, part of Springer Nature 2019
Abstract
Current research on choice overload has been mainly conducted with choice options
not associated with specific brands. This study investigates whether the presence of
brand names in the choice set affects the occurrence of choice overload. Across four
studies, we find that when choosing among an overabundance of alternatives, par-
ticipants express more positive feelings (i.e., higher satisfaction/confidence, lower
regret and difficulty) when all the options of the choice set are associated with
familiar brands, rather than unfamiliar brands or no brand at all. We also find that
choice overload only appears in the absence of brand names, but disappears when all
options contain brand names—either familiar or unfamiliar. Theoretical and practi-
cal implications are discussed.
Keywords Choice overload· Brand· Consumer decisions· Decision-making
On one hand, it is well known that giving people choices increases intrinsic moti-
vation, task performance, and life satisfaction (Deci 1975; Deci etal. 1981; Deci
and Ryan 1985; Glass and Singer 1972a, b; Langer and Rodin 1976; Rotter 1966;
Schulz and Hanusa 1978; Taylor 1989; Taylor and Brown 1988). On the other hand,
there is by now a large body of literature on choice overload, demonstrating that too
much choice can have strong negative consequences. Having too many alternatives
to choose from seems to lead to poorer decisions (Jacoby etal. 1974a, b), to a reduc-
tion of both intrinsic motivation to choose (Iyengar etal. 2004; Iyengar and Lepper
* Raffaella Misuraca
raffaella.misuraca@unipa.it
1 Department ofPolitical Science andInternational Relations, University ofPalermo, Via
Maqueda 324, 90134Palermo, Italy
2 Department ofPsychology, Washington State University, 14204 NE Salmon Creek Avenue,
Vancouver, WA98686-9600, USA
3 Department ofPsychology, Portland State University, 1721 S.W. Broadway, Portland,
OR97201, USA
4 Facoltà di Scienze Umane e Sociali, Università di Enna “Kore”, Cittadella Universitaria,
94100Enna, Italy
Author's personal copy
R.Misuraca et al.
1 3
2000), and post-choice satisfaction (Iyengar and Lepper 2000; Iyengar etal. 2006,
see also Fasolo etal. 2003). Furthermore, when people face too many options, they
experience negative emotions, such as disappointment and regret (Schwartz 2004).
For example, Iyengar and Lepper (2000) found that people are more motivated to
buy gourmet jams or Godiva chocolates, and are more satisfied with their selections,
when they are offered a small set of alternatives, rather than an large set of 24 or 30
different options.
The negative consequences of having too much choice (also known as choice
overload) have been replicated in numerous field and laboratory experiments (e.g.,
Chernev 2003; Fasolo etal. 2009; Iyengar etal. 2004, 2006; Iyengar and Lepper
2000; Misuraca and Teuscher 2013; Misuraca etal. 2016b; Mogilner et al. 2008;
Schwartz 2004; Shah and Wolford 2007; Reutskaja and Hogarth 2009). However, a
meta-analytic review by Scheibehenne etal. (2010) showed that the occurrence of
choice overload depends on several moderator variables, which may increase, reduce
or even cancel out the phenomenon. For example, Inbar etal. (2011) observed choice
overload only when participants felt under time pressure (see also Haynes 2009).
Mogilner etal. (2008) did not find choice overload when the options were arranged
in categories (a phenomenon known as the mere categorization effect). Scheibe-
henne etal. (2009) observed choice overload when participants had to justify their
choices. Given these important findings, Scheibehenne etal. (2010) suggested that
future researchers should continue to search for further possible moderators. Along
the same line, a more recent meta-analysis conducted by Chernev etal. (2015) out-
lined four key factors that drive choice overload: choice set complexity, decision
task difficulty, preference uncertainty, and decision goal. In particular, higher levels
of choice set complexity, decision task difficulty, preference uncertainty and a more
prominent goal of the decision maker to minimize the cognitive effort involved in a
decision, facilitate choice overload. Similarly to Scheibehenne etal. (2010), Chernev
et al. (2015) concluded their meta-analytic review by suggesting further research
investigate other factors, in addition to the four they identified, that may influence
the occurrence of choice overload.
Following the suggestions by Scheibehenne et al. (2010), and Chernev et al.
(2015), our research intends to investigate whether or not the brand can be consid-
ered another moderator variable of choice overload. In particular, we believe that
the brand, especially when it is familiar, influences all the moderating factors estab-
lished by Chernev etal. (2015), by reducing the complexity of the choice set, the
decision task difficulty, the preference uncertainty and the cognitive effort involved
in the decision, which in turn translates into a reduction of choice overload.
To the best of our knowledge, the role of brands in choice overload has never
been investigated. Except for an experiment by Iyengar and Lepper (2000), where
the choice was among Godiva chocolates, brand names were not shown or men-
tioned at all (e.g., Shah and Wolford 2007). In Iyengar and Lepper’s (2000) experi-
ment the name of the brand was kept the same for all the options and its role in
participants’ responses was not measured.
In contrast, the aim of the present study is to investigate the specific role of the
presence of brand names in choice overload. In particular, we expect that when
choosing among an overabundance of alternatives (which typically induce choice
Author's personal copy
1 3
The Role oftheBrand onChoice Overload
overload), participants express more positive affective responses (i.e., higher satis-
faction/confidence, lower regret and difficulty) when the options of the choice set
are associated to familiar brands rather than to unfamiliar brands or no brand at all.
1 Overview ofstudies
We designed four laboratory studies to test our hypothesis.
In all studies we compare, between-subjects, choice overload in a choice con-
dition where participants choose among products associated with familiar brand
names to two other conditions where participants choose among the same products
associated either to unfamiliar brand names or to no brand at all. Because our focus
is on choice overload, in Study 1, 2, and 3 we only included conditions with large
choice sets. However, because previous studies on choice overload typically com-
pared a small versus large assortment condition, in our Study 4 we also vary set size
(small 6 vs. large 24).
In the first study, participants chose energy bars, in the second study participants
chose coffee, in the third and fourth studies participants chose cell phones. The stud-
ies were designed to test the hypothesis first in the food domain (with energy bars
and coffee), then to test whether the effect may generalize to different consumer
domains, such as the choice among cell phones.
2 Design
All four studies used multivariate analysis of variance (MANOVA) in a between-
subjects design with three conditions (familiar brand, unfamiliar brand, no brand) to
examine choice condition as potential moderator of choice overload. Univariate tests
of between-subjects effects with choice condition as a between-subjects variable
were conducted as follow up tests to determine in which dependent variables choice
condition led to significant differences between the three experimental groups. Mul-
tiple comparisons based on Fisher’s Least Significant Difference (LSD) post hoc test
were also inspected to verify the hypothesized effect between choice condition and
choice overload measures.
3 Study 1
3.1 Method
3.1.1 Participants
One hundred and one (79.2% female, mean age = 20, SD = 1.77) undergraduate stu-
dents from an Italian University volunteered to participate in our first study. They
were not compensated for their participation.
Author's personal copy
R.Misuraca et al.
1 3
3.2 Procedure andmaterials
The participants were randomly assigned to one of three experimental conditions:
familiar brand (n = 34), unfamiliar brand (n = 35), no brand (n = 32). In each con-
dition, participants chose from a set of 24 options associated with either familiar
brands or unfamiliar brands or no brand at all. The products were energy bars.
In the first condition, participants were asked to choose one out of 24 bars rep-
resented by six well-known brands (Multipower, Enervit, Herbalife, Nestlé, Peso-
forma, Kellogg’s). There were thus four bars per brand. The bars were described
along six attributes: brand, price, calories, protein, carbohydrates, and fat. The bars
were presented on a comparison matrix, without pictures, in order to avoid the
choices being influenced by incidental factors in their appearance, rather than the
intentionally presented information.
The second and third conditions corresponded to the first condition in all respects,
except that the bars were associated with lesser-known brands (Ultimate Italia, Inko-
spor, Wander, +Watt, Sunny, Vitargo) and no brand at all, respectively. The only
attribute of the bars manipulated was thus the brand (well known; unknown; absent)
but the other attributes were held constant.
Participants were tested in small groups and were free to take as much time as
they needed to make their choice. Subjects were told that: “We’re doing a study to
examine how people decide which product(s) to buy out of the many products avail-
able on the supermarket shelf.” The participants were then asked to imagine that
they were in a grocery store shopping for energy bars.
After participants had made their decision, they were asked to express their satis-
faction with their choice, their confidence, the difficulty of the task, and their regret.
Responses were given on a 5-point Likert scale, ranging from 1 (not at all) to 5
(extremely).
Before leaving, participants were asked to supply basic demographic data.
To select the right mix of brands in the design of the choice task, we had con-
ducted a norming study beforehand, in which 30 Italian participants expressed
their degree of familiarity with various energy bar brand names. Responses were
collected on a 4-point Likert scale (1 = very unfamiliar; 4 = very familiar). Based
on these ratings, we selected the six most familiar brands and the six least familiar
brands as stimuli for this experiment.
3.3 Results
MANOVA results indicated that the brand condition significantly affected choice
overload measures, WilksɅ = .822, F(8, 190) = 2.438, p < .05, par tial η2 = .093.
Tests between subjects revealed that the familiar brand led to both more positive
and fewer negative effects of choice overload than both unfamiliar brand and no-
brand conditions. Namely, familiar brands presented higher positive effects as
measured with Satisfaction with the choice made [F(2, 98) = 3.572, p < .05, partial
η2 = .068] and Confidence [F(2, 98) = 3.929, p < .05, partial η2 = .012], as well as
Author's personal copy
1 3
The Role oftheBrand onChoice Overload
lower negative effects as measured with Difficulty [F(2, 98) = 3.391, p < .05, partial
η2 = .065], and Regret [F(2, 98) = 8.652, p < .001, partial η2 = .150]. Descriptive sta-
tistics are presented in Table1. Figure1 presents the direct comparisons of the three
sets of means.
3.3.1 Satisfaction withthechoice made
Participants choosing among 24 bars of familiar brands were significantly more satis-
fied with their choices (M = 3.47, SD = .79) than participants choosing among 24 bars
of unfamiliar brands (M = 2.94, SD = 1.16; Mean Difference = .53, p < .05), or among
24 bars with no brand (M = 2.84, SD = 1.11; Mean Difference = .63, p < .05). There was
Table 1 Descriptive statistics
for Study 1 Condition Mean SD
Satisfaction
Familiar brand 3.47 .788
Unfamiliar brand 2.94 1.162
No brand 2.84 1.110
Confidence
Familiar brand 3.26 .931
Unfamiliar brand 2.57 1.290
No brand 2.72 .958
Difficulty
Familiar brand 2.38 1.074
Unfamiliar brand 3.06 1.349
No brand 2.94 .948
Regret
Familiar brand 1.79 .808
Unfamiliar brand 2.60 1.355
No brand 2.91 1.146
0
1
2
3
4
familiar brand unfamiliar brand no brand
satisfaction
confidence
difficulty
regret
Fig. 1 Means of choice overload variables in the three conditions for Study 1
Author's personal copy
R.Misuraca et al.
1 3
no difference in the level of satisfaction with the choice made between the unfamiliar
brand and no brand conditions (Mean Difference = .10, p = .696).
3.3.2 Condence
The confidence with the choice made was highest when choosing among 24 bars of
familiar brands, M = 3.26, SD = .93, (vs. unfamiliar brands: M = 2.57, SD = 1.29; Mean
Difference = .69, p < .01; vs. no brand: M = 2.72, SD = .96; Mean Difference = .55,
p < .05), and lowest when choosing among 24 bars of either unfamiliar brands or
no brands, with no differences between these latter two conditions (Mean Differ-
ence = − .15, p = .577).
3.3.3 Diculty
Choosing among 24 bars of familiar brands was rated as significantly less difficult
(M = 2.38, SD = 1.07) than choosing among 24 bars of unfamiliar brands (M = 3.06,
SD = 1.35; Mean Difference = − .67, p < .05), or with no brand (M = 2.94, SD = .95;
Mean Difference = .56, p < .05). Choosing among 24 bars of unfamiliar brands was
rated as difficult as choosing among 24 bars with no brands (Mean Difference = .12,
p = .669).
3.3.4 Regret
Participants who chose among 24 bars of familiar brands reported significantly lower
levels of regret (M = 1.79, SD = .81) than participants who chose among 24 bars of
either unfamiliar brands (M = 2.60, SD = 1.36; Mean Difference = − .81, p < .01) or no
brand (M = 2.91, SD = 1.15; Mean Difference = − 1.11, p < .001). Regret did not dif-
fer between the unfamiliar brands and no brands conditions (Mean Difference = .31,
p = .276).
3.4 Conclusions
Study 1 supported our hypothesis that associating options to familiar brand names miti-
gated the typical negative consequences of choice overload, which we still saw when
large choice sets were brand free or associated to unfamiliar brands. In particular, par-
ticipants choosing from 24 energy bars of familiar brands expressed higher satisfac-
tion and confidence, as well as lower difficulty and regret than participants who chose
among 24 energy bars associated with unfamiliar brands or no brand at all. In Study
2 and 3 we sought to support our hypothesis by replicating the experiment with other
choice products, such as coffee and cell phones.
Author's personal copy
1 3
The Role oftheBrand onChoice Overload
4 Study 2
4.1 Method
4.1.1 Participants
Ninety three (62.4% female, mean age = 20.78, SD = 3.15) undergraduate Italian
students volunteered to participate in our second study. They were not compen-
sated for their participation.
4.2 Procedure andmaterials
The participants were randomized into one of three experimental conditions:
familiar brand (n = 32), unfamiliar brand (n = 32), no brand (n = 29). As in the
previous experiment, participants chose from a set of 24 options associated with
either familiar brands, unfamiliar brands, or no brand at all. The product was a
variety of espresso coffee.
In the first condition, participants were asked to choose one out of 24 coffees
represented by six well-known brands (Aiello, Vergnano, Lavazza, Kimbo, Sega-
fredo, ZiCaffè). The types of coffee were described along four attributes: brand,
price, brewing method, and flavor). The different types of coffee were presented
in a comparison table, without pictures to avoid incidental differences in appear-
ance to influence participants’ choices.
The second and third conditions corresponded to the first condition in all
respects, except that the coffees were associated with lesser-known brands
(Caffen, Guglielmo, Costadoro, Passalacqua, Saccaria, Quarta) and no brand at
all, respectively. The only attribute manipulated was thus the brand of the options
(well known; unknown; absent) but the other attributes were held constant.
Participants were tested in small groups and were free to take as much time as
they needed to make their choice. Subjects were told that: “We’re doing a study
to examine how people decide which product(s) to buy out of the many products
available on the supermarket shelf.” The participants were then asked to imagine
that they were in a grocery store shopping for coffee.
After participants had made their decision, they were asked to express their
satisfaction with their choice, their confidence, the difficulty of the task, and their
regret. Responses were given on a 5-point Likert scale, ranging from 1 (not at all)
to 5 (extremely).
Before leaving, participants were asked to supply basic demographic data.
As in study 1, to select the right mix of brands in the design of the choice task,
we had conducted a norming study in which 30 Italian participants expressed
their degree of familiarity with various real coffee brand names. Responses were
on a 4-point Likert scale (1 = very unfamiliar; 4 = very familiar). We picked the
six most familiar brands and the six least familiar brands based on their ratings.
Author's personal copy
R.Misuraca et al.
1 3
4.3 Results
MANOVA showed that overall the choice condition significantly affected choice
overload, WilksɅ = .762, F(8, 174) = 3.165, p < .01, partial η2 = .127. Tests of
between-subjects effects showed that participants in the familiar brand condition
scored significantly higher on Satisfaction with the choice made, F(2, 90) = 3.379,
p < .05, partial η2 = .070, and Confidence, F(2, 90) = 5.178, p < .01, partial
η2 = .103, than people in both unfamiliar brand and no brand conditions. For the
effects Difficulty and Regret, the pattern was exactly the opposite—participants
who were assigned to the familiar brand condition scored significantly lower on
both variables, F(2, 90) = 6.577, p < .01, partial η2 = .128 and F(2, 90) = 3.220,
p < .05, partial η2 = .067 for Difficulty and Regret, respectively. Descriptive sta-
tistics are presented in Table2. Figure 2 presents means and standard errors of
choice overload variables for the three experimental conditions.
4.3.1 Satisfaction withthechoice made
The satisfaction with the chosen option was higher in the condition with famil-
iar brands (M = 3.69, SD = .64) than in the other two conditions, with unfamil-
iar (M = 3.25, SD = .95; Mean difference = .44, p < .05) and no brand (M = 3.28,
SD = .59; Mean Difference = .41, p < .05), respectively. The satisfaction levels did
not differ between the unfamiliar-brand and no-brand conditions (Mean Differ-
ence = − .03, p = .893).
Table 2 Descriptive statistics
for Study 2 Condition Mean SD
Satisfaction
Familiar brand 3.69 .644
Unfamiliar brand 3.25 .950
No brand 3.28 .591
Confidence
Familiar brand 3.66 .653
Unfamiliar brand 3.25 .950
No brand 2.97 .906
Difficulty
Familiar brand 2.47 .950
Unfamiliar brand 3.31 1.148
No brand 3.14 .789
Regret
Familiar brand 1.78 .706
Unfamiliar brand 2.31 1.120
No brand 2.24 .830
Author's personal copy
1 3
The Role oftheBrand onChoice Overload
4.3.2 Condence
Participants were more confident in their decisions when choosing from coffees of
familiar brands (M = 3.66, SD = .65) rather than from coffees of unfamiliar brands
(M = 3.25, SD = .95; Mean Difference = .41, p < .05) or without brand (M = 2.97,
SD = .91; Mean Difference = .69, p < .01). There were no differences in the confi-
dence reported in these latter two conditions (Mean Difference = .28, p = .192).
4.3.3 Diculty
Choosing among coffees of familiar brands was rated as significantly less difficult
(M = 2.47, SD = .95) than choosing among coffees of unfamiliar brands (M = 3.31,
SD = 1.15; Mean Difference = − .84, p < .001), or no brand (M = 3.14, SD = .79;
Mean Difference = − .67, p < .01). Choosing among coffees of unfamiliar brands was
rated as difficult as choosing among options with no brands (Mean Difference = .12,
p = .669).
4.3.4 Regret
Participants choosing among coffees of familiar brands reported the least regret,
M = 1.78, SD = .71, (vs. unfamiliar: M = 2.31, SD = 1.12; Mean Difference = − .53,
p < .05; vs. no brand: M = 2.24, SD = .83; Mean Difference = − .46, p < .05). There
were no differences in the regret levels reported by the participants who chose
among coffees of unfamiliar brands compared to those who chose among brand-free
coffees (Mean Difference = .07, p < .760).
4.4 Conclusions
The results of Study 2 support our hypothesis that the presence of familiar brands
mitigates the negative effects normally produced by extensive arrays of options.
0
1
2
3
4
familiar brand unfamiliar brand no brand
satisfaction
confidence
difficulty
regret
Fig. 2 Means of choice overload variables in the three conditions for Study 2
Author's personal copy
R.Misuraca et al.
1 3
Participants choosing from 24 options associated to familiar brand names expressed
higher satisfaction and lower regret than participants choosing from 24 options asso-
ciated to unfamiliar brand names or no brand at all.
5 Study 3
5.1 Method
5.1.1 Participants
One hundred and eighteen (67.8% female, mean age = 23.31, SD = 2.4) undergradu-
ates in an Italian university participated in the third study. Participants were volun-
teers, and were not compensated for their time.
5.2 Procedure andMaterials
Participants were randomized into three experimental conditions: choice from 24
cell phones associated with familiar brand names (n = 40); choice from 24 cell
phones associated with unfamiliar brand names (n = 39); choice from 24 cell phones
without brand (n = 39).
In the first condition, 40 participants were asked to choose one out of 24 cell
phones represented by six very well-known brands (Nokia, Samsung, LG, Motorola,
Apple, and Alcatel). There were thus four cell phones per brand. The mobile phones
were presented in a comparison table displaying information on each of the mobile
phones on five attributes: brand, price, weight, duration of battery life, display, and
camera resolution. Products were not accompanied by pictures to avoid preferences
being influenced by appearances, such as different colors or designs.
The second and third conditions corresponded to the first condition in all respects
except that the cell phones were associated with lesser known brands (Haier, Amoi,
Bird, I-Mate, O2 and Maxon) and with no brand at all, respectively. The only attrib-
ute of the cell phones manipulated was thus the brand (well known; unknown;
absent) but the other attributes were held constant.
After the participants made their choice, they were asked to indicate the extent
of their satisfaction with the chosen cell phone, their confidence, their difficulty in
making the choice, and their regret about their choice. In this experiment we also
added several other variables commonly used in previous studies on choice over-
load, such as the sense of confusion perceived by the respondents, the level of enjoy-
ment of the task, the satisfaction with the decision-making process, and the expected
satisfaction (see Scheibehenne etal. 2010). We expected higher enjoyment and a
lower sense of confusion in the familiar brand condition than in the other two condi-
tions. We also expected that choosing among familiar brands enhances not only the
satisfaction with the choice made but also the satisfaction with the decision-making
process and the expected satisfaction. After participants had answered these ques-
tions, we administrated the shortened version of the Maximization Scale (Nenkov
Author's personal copy
1 3
The Role oftheBrand onChoice Overload
etal. 2008) to explore whether the brand effect observed in Study 1 and 2 extends
to individuals with a high tendency towards maximization (i.e., a tendency to
search for the very best option). Previous literature suggested that choice overload
is particularly strong in maximizers, because – with their aim to select the very best
option – maximizers would like to compare all available possibilities before decid-
ing. When the number of options is very high however, the limitations of human
information processing make it impossible for them to evaluate and compare all
available options. The result is a high dissatisfaction with the choice made (Iyengar
etal. 2006; Misuraca etal. 2015; Misuraca and Fasolo 2018; Misuraca etal. 2016a).
We expect that choosing among familiar brands may mitigate the negative effects
of an overabundance of choice commonly observed in maximizers. Responses were
given on a 5-point scale, ranging from 1 (not at all) to 5 (extremely).
Before leaving, participants indicated their age and gender in a brief
questionnaire.
As in Studies 1 and 2, to select the right mix of brands in the design of the choice
task, we conducted a norming study in which 30 Italian participants expressed their
degree of familiarity with various cell phone brand names. Responses were given on
a 4-point Likert scale (1 = very unfamiliar; 4 = very familiar).
5.3 Results
Again, as predicted, the MANOVA with the choice overload measures as depend-
ent variables revealed a significant overall difference between the three experimental
conditions, Wilks’ Ʌ = .591, F(16, 216) = 4.067, p < .001, par tial η2 = .023, with peo-
ple in the familiar brand condition reporting significantly higher levels of positive
effects combined with lower levels of negative effects, compared to people in both
the unfamiliar brand and no brand conditions. In line with the overall effect, tests
between subjects also showed a significant effect of choice condition on Satisfaction
with the choice made, F(2, 115) = 10.232, p < .001, partial η2 = .151, Confidence,
F(2, 115) = 12.657, p < .001, partial η2 = .180, Difficulty, F(2, 115) = 3.137, p < .05,
partial η2 = .052, Regret, F(2, 115) = 6.397, p < .01, partial η2 = .100, Feeling of con-
fusion, F(2, 115) = 11.731, p < .001, partial η2 = .169, Enjoyment, F(2, 115) = 4.939,
p < .01, partial η2 = .079, Satisfaction with the process, F(2, 115) = 6.916, p < .001,
partial η2 = .107, Expected satisfaction, F(2, 115) = 9.215, p < .001, par tial η2 = .138.
Descriptive statistics are presented in Table3. Figure3 presents means and standard
errors of choice overload variables for the three experimental groups.
5.3.1 Satisfaction withthechoice made
A comparison among the three conditions showed that the presence of familiar
brands yielded higher post-choice satisfaction levels (M = 4.18, SD = .64) than the
presence of unfamiliar brands (M = 3.46, SD = 1.05; Mean Difference = .71, p < .01),
or the absence of brands (M = 3.18, SD = 1.25; Mean Difference = 1.00, p < .001).
There was no difference between choosing among 24 cell phones of unfamiliar
brands and 24 cell phones with no brand (Mean Difference = .28, p = .229).
Author's personal copy
R.Misuraca et al.
1 3
5.3.2 Condence
The confidence with the choice made was higher when choosing among 24 cell
phones of familiar brands (M = 3.97, SD = .86) vs. unfamiliar brands (M = 3.26,
SD = 1.02; Mean Difference = .72, p < .001), or no brand (M = 2.87, SD = 1.08;
Mean Difference = 1.10, p < .001), with no differences between the unfamiliar and
no brand conditions (Mean Difference = .38, p = .089).
Table 3 Descriptive statistics
for Study 3 Condition Mean SD
Satisfaction
Familiar brand 4.18 .636
Unfamiliar brand 3.46 1.047
No brand 3.18 1.254
Confidence
Familiar brand 3.97 .862
Unfamiliar brand 3.26 1.019
No brand 2.87 1.080
Difficulty
Familiar brand 2.63 1.125
Unfamiliar brand 3.23 1.287
No brand 3.21 1.239
Regret
Familiar brand 1.67 .656
Unfamiliar brand 2.36 1.386
No brand 2.59 1.371
Feeling of confusion
Familiar brand 2.42 .984
Unfamiliar brand 3.26 1.208
No brand 3.64 1.224
Enjoyment
Familiar brand 3.28 1.012
Unfamiliar brand 2.56 1.071
No brand 2.64 1.224
Satisfaction with the process
Familiar brand 4.02 .733
Unfamiliar brand 3.36 .843
No brand 3.44 1.021
Expected satisfaction
Familiar brand 4.15 .736
Unfamiliar brand 3.33 .955
No brand 3.62 .877
Author's personal copy
1 3
The Role oftheBrand onChoice Overload
5.3.3 Diculty
Choosing among 24 cell phones of familiar brands was rated as significantly less
difficult (M = 2.63, SD = 1.13) than choosing among 24 cell phones of unfamil-
iar brands (M = 3.23, SD = 1.29; Mean Difference = -.61, p < .05) or of no brand
(M = 3.21, SD = 1.24; Mean Difference = -.58, p < .05). Choosing among 24 cell
phones of unfamiliar brands was rated as equally difficult as choosing among 24 cell
phones with no brands (Mean Difference = .03, p = .926).
5.3.4 Regret
Regret was lowest in the familiar brand condition (M = 1.67, SD = .66), and high-
est in both the no brand (M = 2.59, SD = 1.37) and the unfamiliar brand conditions
(M = 2.36, SD = 1.39). (Familiar vs. unfamiliar brand: Mean Difference = -.68,
familiar brand vs no brand: Mean Difference = -.91, p < .001;, p < .01; no brand vs.
unfamiliar brand: Mean Difference = -.13, p = 391).
5.3.5 Feeling ofconfusion
In the familiar brand condition participants reported a lower sense of confusion
(M = 2.42, SD = .98), compared to the unfamiliar brand (M = 3.26, SD = 1.21; Mean
Difference = -.83, p < .01), and no brand conditions (M = 3.64, SD = 1.22; Mean Dif-
ference = -1.22, p < .001). The level of confusion was the same in the unfamiliar
brand and no brand conditions (Mean Difference = -.38, p = 140).
5.3.6 Enjoyment
Participants enjoyed choosing among cell phones of familiar brands (M = 3.28,
SD = 1.01) more than choosing among cell phones of unfamiliar brands (M = 2.56,
SD = 1.07; Mean Difference = .71, p < .01) or cell phones with no brands (M = 2.64,
0
1
2
3
4
5
familiar brandunfamiliar brandno brand
satisfaction
confidence
difficulty
regret
feeling of confusion
enjoym ent
satisfaction with th e process
expected satisfaction
Fig. 3 Means of choice overload variables (with error bars showing ± 1 SE) in the three conditions for
Study 3
Author's personal copy
R.Misuraca et al.
1 3
SD = 1.22; Mean Difference = .63, p < .01). The level of enjoyment did not dif-
fer in the condition with no brands and unfamiliar brands (Mean Difference = -.08,
p = .759).
5.3.7 Satisfaction withtheprocess
The satisfaction with the decision-making process was higher in the familiar
brand condition (M = 4.02, SD = .73) than in the other two conditions: unfamiliar
brand (M = 3.36, SD = .84; Mean Difference = .67, p < .001); no brand (M = 3.44,
SD = 1.02; Mean Difference = .59, p < .01). There was no significant difference
between the unfamiliar brand and the no brand conditions (Mean Difference = -.08,
p = .698).
5.3.8 Expected satisfaction
Participants choosing among familiar brands expected more satisfaction (M = 4.15,
SD = .74) than participants choosing among unfamiliar brands (M = 3.33, SD = .96;
Mean Difference = .82, p < .001) or among options without a brand (M = 3.62,
SD = .88; Mean Difference = .53, p < .01). The level of expected satisfaction was the
same in the latter two conditions (Mean Difference = -.28, p = .150).
5.3.9 Maximizing
Since satisfaction with the choice, confidence in the choice, perceived difficulty,
and regret were highly correlated (satisfaction and confidence: r = .80; satisfaction
and difficulty: r = -.52; satisfaction and regret: r = -.67; confidence and difficulty:
r = -.56; confidence and regret: r = -.68; difficulty and regret: r = .42, p < .001 for all
comparisons), we combined them into a composite choice overload measure (with
satisfaction and confidence reversed), by averaging across these four items for each
participant.
In the conditions with unfamiliar brands and without brands, we found that
maximizing tendency was positively correlated with the composite choice overload
measure, showing the pattern commonly described in the literature with maximiz-
ers being more unhappy than other people when facing an overabundance of choice
(unfamiliar brand: r = .41, p = .02; no brand: r = .42, p = .02). However, in the famil-
iar brand condition we found that maximizing tendency was unrelated to the com-
posite measure of choice overload (r = .12, p = .51), suggesting that the presence of
familiar brands mitigated the negative feelings normally experienced by maximizers
when deciding among a high number of options.
5.4 Conclusions
The results of Study 3 again support our hypothesis that the presence of familiar
brands mitigates the adverse consequences of choice overload. Participants who
chose one out of 24 cell phones of familiar brands were more satisfied and confident
Author's personal copy
1 3
The Role oftheBrand onChoice Overload
than participants who chose one out of 24 cell phones of unfamiliar brands or with-
out brands. They also perceived the task as less difficult and were less regretful of
their choices. Choosing among familiar brands was also associated with a lower
sense of confusion, higher enjoyment, higher expected satisfaction, and higher pro-
cess satisfaction. Furthermore, in the familiar brand condition the usual correlations
between maximizing tendency and low choice satisfaction, low confidence, high dif-
ficulty, and high regret, all disappeared.
Because our focus is on choice overload, in Study 1, 2, and 3 we only presented
large choice sets, instead of small choice sets which do not pose the problem of
choice overload. However, it can be argued that the above studies only show that
well-known brands are easier to choose from than lesser-known or non-existent
brands. In order to actually test the presence of choice overload, we conducted a
follow up study, where we also varied set size (small 6 vs. large 24) to make sure
participants indeed felt more choice overload with 24 than 6 options when the brand
is unknown or not existent.
6 Study 4
6.1 Method
6.1.1 Participants
Two hundred and twenty-eight (72.8% female, mean age = 23.39, SD = 2.3) under-
graduates in an Italian university participated in the forth study. Participants were
volunteers, and were not compensated for their time.
6.2 Procedure andmaterials
Participants were randomly assigned to one of six experimental conditions: choice
from 24 cell phones associated with familiar brand names (n = 38); choice from 24
cell phones associated with unfamiliar brand names (n = 36); choice from 24 cell
phones without brand (n = 36); choice from 6 cell phones associated with familiar
brand names (n = 40); choice from 6 cell phones associated with unfamiliar brand
names (n = 39); choice from 6 cell phones without brand (n = 39).
The first three conditions corresponded to the three conditions used in Study 3
in all respects. In the fourth, fifth, and sixth condition the number of cell phones
included in the choice set was only six, instead of 24. Both the familiar and unfamil-
iar brand conditions still included six brands, that is, there was only one cell phone
per brand.
Following Chernev et al.’s (2015) meta-analytic findings that satisfaction/con-
fidence, regret, choice deferral, and switching likelihood are all equally powerful
measures of choice overload and can be used interchangeably, we used as our meas-
ure of choice overload the participants’ satisfaction with the chosen option. Before
Author's personal copy
R.Misuraca et al.
1 3
leaving, participants also responded to the same demographic questions presented in
the previous three studies.
6.3 Results
The 2-way ANOVA showed that the brand presence significantly affected choice
overload with a significant overall difference between the three experimental con-
ditions (familiar brand, unfamiliar brand, no brand), F(2) = 9.401, p < .001, partial
η2 = .078, whereas no significant overall difference between the two experimental
conditions (24 options, 6 options) was found with respect to the set size F(1) = 1.745,
p = .188, partial η2 = .008. The interaction between choice set size and brand condi-
tion was not significant F(2) = 2.799, p = .063, partial η2 = .025. Descriptive statistics
are presented in Table4. Figure4 presents means of satisfaction for the six experi-
mental groups.
A comparison among the six conditions showed that in the large choice sets,
choosing among familiar brands yielded higher satisfaction levels (M = 4.16,
SD = .64) than choosing among unfamiliar brands (M = 3.47, SD = 1.06; Mean Dif-
ference = .69, p < .001), or options with no brand at all (M = 3.33, SD = 1.17; Mean
Difference = .83, p < .001). There was no difference between choosing among 24
Table 4 Descriptive statistics
for Study 4 Condition Mean SD
Satisfaction
24 options, familiar brand 4.16 .638
24 options, unfamiliar brand 3.47 1.055
24 options, no brand 3.33 1.171
6 options, familiar brand 4.03 .620
6 options, unfamiliar brand 3.54 .913
6 options, no brand 3.87 .894
3
3,2
3,4
3,6
3,8
4
4,2
4,4
24 opons,
familiar brand
24 opons,
unfamiliar
24 opons, no
brand
6 opons,
familiar brand
6 opons,
unfamiliar brand
6 opons, no
brand
Fig. 4 Means of “Satisfaction with the choice made” in the six experimental conditions
Author's personal copy
1 3
The Role oftheBrand onChoice Overload
options associated to unfamiliar brands and 24 options with no brand (Mean Differ-
ence = .14, p = .512).
In the small choice sets, choosing among familiar brands also yielded higher
satisfaction levels (M = 4.03, SD = .62) than choosing among unfamiliar brands
(M = 3.54, SD = .91; Mean Difference = .49, p < .05). There was no difference
between choosing among 6 options associated to familiar brands and 6 options with
no brand (M = 3. 87, SD = .89; Mean Difference = .15, p = .449). There was also no
difference between choosing among 6 options associated to unfamiliar brands and 6
options with no brand (Mean Difference = − .33, p = .103).
Comparisons between the small and the large choice sets for each condi-
tion showed no differences for the familiar brand condition (6 options: M = 4.03,
SD = .62, vs. 24 options: M = 4.16, SD = .64, Mean Difference = .13, p = .514), nor
for the unfamiliar brand condition (6 options: M = 3.54, SD = .91, vs. 24 options:
M = 3.47, SD = 1.06, Mean Difference = − .07, p = .750). Only in the absence of
any brand at all did we find greater satisfaction in the small choice set (M = 3.87,
SD = .89) than in the large choice set (M = 3.33, SD = 1.17; Mean Difference = .54,
p < .01).
6.4 Conclusions
In line with our previous studies, the results of Study 4 again show that in large
choice sets, including 24 alternatives, choosing among familiar brands produces
higher levels of satisfaction than choosing among unfamiliar brands or among
options without a brand name. The same facilitation effect of familiar brands was
observed in our small choice sets: choosing among six familiar options produces
greater satisfaction than choosing among six either unfamiliar or no-brand options.
In addition, the results of Study 4 show that choice overload disappears in the
brand condition, surprisingly even when the brand is unfamiliar. As expected,
however, choice overload appears in the no-brand condition: participants choosing
among six options with no brand report higher levels of satisfaction with the chosen
option than participants choosing among 24 options with no brand.
The results of Study 4, thus, confirm only partially our predictions. Given the
higher satisfaction expressed in the first three studies with familiar brands com-
pared to unfamiliar brands or options with no brand, we expected that participants
of Study 4 would feel less choice overload in the familiar brand condition. The fact
that choice overload disappeared in both the familiar and unfamiliar brand condi-
tions leads us to think that other mechanisms, besides the familiarity with the brand,
affected our participants’ level of satisfaction. The “mere categorization effect”,
according to which the mere presence of categories (regardless of their content) has
a positive influence on satisfaction (Mogilner etal. 2008), could for example be a
potential responsible for our data. Indeed, the repartition of 24 products into 6 dif-
ferent brands (regardless of their familiarity) could have improved the satisfaction of
our decision-makers, compared to the condition without brand, where the products
Author's personal copy
R.Misuraca et al.
1 3
could not be grouped into categories. However, further research is needed to confirm
this potential explanation.
7 General discussion
Across four studies we found that the presence of familiar brands reduces the dis-
advantages of choosing from an extensive number of options. When facing a choice
among 24 items, participants reported to be more satisfied and confident when
choosing among familiar brands than when choosing among unfamiliar brands or
options without brand information. The presence of familiar brands was also associ-
ated with lower perceived task difficulty and fewer feelings of regret. In the third
experiment, we additionally found that participants who chose between familiar
brands felt less confused, enjoyed the choice task more, were more satisfied with
their decision process, and expected more satisfaction than participants who chose
between unfamiliar brands or brand-free items.
These results align well with theory and research on ambiguity aversion, that is
the tendency to prefer known risks over unknown risks (Ellsberg 1961). The higher
knowledge of potential risks of dissatisfaction associated to familiar brands, com-
pared to that of choosing among unfamiliar brands, could be responsible for the
more positive feelings reported when choosing among familiar brands.
The results of experiment 3, showing that the presence of familiar brands is asso-
ciated with less confusion and higher enjoyment, higher expected satisfaction, and
higher satisfaction with the choice process, could suggest that familiar brands release
the decision maker from the fear of making a wrong decision and from the tendency
to overthink the pros and cons of options. Consequently, the decision maker might
feel happier about his/her decision, about the process, and the task. However, this
speculation requires more research to provide causal evidence.
In the fourth study we tested the actual presence of choice overload and showed
that while 24 options produce greater choice overload than 6 in the absence of any
brand (in line with previous findings), this was not the case when the options of the
choice sets were associated to brand names. Indeed, choice overload disappeared
when the choice options were associated to familiar or unfamiliar brands: in both the
familiar and unfamiliar brand conditions, choosing among 24 options was not asso-
ciated with a lower level of satisfaction than choosing among 6 options. These find-
ings could be explained in the light of the “mere categorization effect” (Mogilner
etal. 2008) according to which the mere presence of categories (regardless of their
content) improves satisfaction.1
Our results have both theoretical and practical implications. From a theoretical
perspective, they add to the growing knowledge on choice overload. Scheibehenne
et al. (2010) and Chernev et al. (2015) concluded their meta-analytic studies by
1 Note that this is different from the experiment by Iyengar and Lepper (2000) with Godiva chocolates.
Given that all their chocolates were represented by only one brand (Godiva), the mere categorization
effect could not apply, since with only one brand the choice items could not be grouped into categories.
Author's personal copy
1 3
The Role oftheBrand onChoice Overload
proposing that future research should investigate the role of further possible modera-
tors of choice overload. Our current research has added to this literature by suggest-
ing that the brand may play a moderating role.
Furthermore, our study brings choice overload closer to real-world decision sce-
narios, where consumers evaluate options strongly characterized by specific brand
names, rather than options described only in terms of their objective attributes, such
as technical characteristics or nutritional values.
From an applied perspective, our study invites caution with reducing large choice
sets. Indeed, while the common suggestion of reducing assortments in order to boost
consumer satisfaction might work when people choose among items without brand
names, we have no reason to believe it would increase choice satisfaction for people
who choose among brands, given that decision makers seem to cope well with large
choice sets characterized by brands, especially if they are familiar.
Our study comes with some limitations regarding the generalizability of the
results. First, most of the research on choice overload has so far been conducted with
American participants. Our experiments took place in Italy, with Italian participants.
A replication of the studies involving participants of different cultures is needed to
verify whether or not cultural differences affect the affective responses recorded.
Second, the experiments were conducted without testing the relevance of the brand
name for the specific product category in which the participants were making a deci-
sion. Future research should incorporate this variable and explore the generalizabil-
ity of our results with products for which the brand name is perceived as less or
more relevant than ours in order to increase our understanding of the phenomenon
and its limitations. An interesting topic for further research could be the effect of
individual differences, such as brand sensitivity (Kapferer and Laurent 1988) on
the affective responses when facing an overabundance of choice. Other limitations
of our study concern the fact that the choices were hypothetical rather than real,
and that the choice sets contained either familiar or unfamiliar brands rather than a
mix of both familiar and unfamiliar brands (as is usually the case in real consumer
environments). Future research should be conducted in more realistic settings where
participants make real choices from arrays of options containing both familiar and
unfamiliar brands.
References
Chernev A (2003) When more is less and less is more: the role of ideal point availability and assortment in
consumer choice. J Consum Res 30:170–183
Chernev A, Böckenholt U, Goodman J (2015) Choice overload: a conceptual review and meta-analysis. J
Consum Psychol 25:333–358
Deci E (1975) Intrinsic motivation. New York, London
Deci EL, Ryan RM (1985) Intrinsic motivation and self-determination in human behavior. Springer Science
& Business Media, New York
Deci EL, Nezlek J, Sheinman L (1981) Characteristics of the rewarder and intrinsic motivation of the
rewardee. J Pers Soc Psychol 40:1–10
Ellsberg D (1961) Risk, ambiguity, and the savage axioms. Quart J Econ 75:643–669
Fasolo B, Misuraca R, McClelland GH (2003) Individual differences in adaptive choice strategies. Res Econ
57:219–233
Author's personal copy
R.Misuraca et al.
1 3
Fasolo B, Carmeci FA, Misuraca R (2009) The effect of choice complexity on perception of time spent
choosing: when choice takes longer but feels shorter. Psychol Market 26:213–228
Glass DC, Singer JE (1972a) Urban stress: experiments on noise and social stressors. Academic, New York
Glass DC, Singer JE (1972b) Behavioral aftereffects of unpredictable and uncontrollable aversive events:
although subjects were able to adapt to loud noise and other stressors in laboratory experiments, they
clearly demonstrated adverse aftereffects. Am Sci 60:457–465
Haynes GA (2009) Investigating the dynamics of choice overload. Psychol Market 26:204–212
Inbar Y, Botti S, Hanko K (2011) Decision speed and choice regret: when haste feels like waste. J Exp Soc
Psychol 47:533–540
Iyengar SS, Lepper MR (2000) When choice is demotivating: can one desire too much of a good thing? J
Pers Soc Psychol 79:995–1006
Iyengar SS, Huberman G, Jiang W (2004) How much choice is too much? Contributions to 401 (k) retire-
ment plans. Pension Des Struct New Lessons Behav Finance 83–95:84–87
Iyengar SS, Wells RE, Schwartz B (2006) Doing better but feeling worse looking for the “best” job under-
mines satisfaction. Psychol Sci 17:143–150
Jacoby J, Speller DE, Berning CK (1974a) Brand choice behavior as a function of information load: replica-
tion and extension. J Consum Res 1:33–42
Jacoby J, Speller DE, Kohn CA (1974b) Brand choice behavior as a function of information load. J Mark Res
11:63–69
Kapferer JN, Laurent G (1988) Consumer brand sensitivity: a key to measuring and managing brand equity.
In: Leuthesser L (ed) Defining, measuring and managing brand equity. Market Sci Inst, Cambridge, pp
12–15
Langer EJ, Rodin J (1976) The effects of choice and enhanced personal responsibility for aged: a field experi-
ment in an institutional setting. J Pers Soc Psychol 34:191–198
Misuraca R, Fasolo B (2018) Maximizing versus satisfying in the digital age: disjoint scales and the case for
“construct consensus”. Pers Individ Differ 121:152–160
Misuraca R, Teuscher U (2013) Time flies when you maximize—maximizers and satisfiers perceive time dif-
ferently when making decisions. Acta Physiol (Oxf) 143:176–180
Misuraca R, Faraci P, Gangemi A, Carmeci FA, Miceli S (2015) The decision making tendency inventory: a
new measure to assess maximizing, satisfying, and minimizing. Pers Individ Differ 85:111–116
Misuraca R, Teuscher U, Carmeci FA (2016a) Who are maximizers? Future oriented and highly numerate
individuals. Int J Psychol 51:307–311
Misuraca R, Teuscher U, Faraci P (2016b) Is more choice always worse? Age differences in the overchoice
effect. J Cogn Psychol 28:242–255
Mogilner C, Rudnick T, Iyengar SS (2008) The mere categorization effect: how the presence of catego-
ries increases choosers’ perceptions of assortment variety and outcome satisfaction. J Consum Res
35:202–215
Nenkov GY, Morrin M, Schwartz B, Ward A, Hulland J (2008) A short form of the maximization scale: fac-
tor structure, reliability and validity studies. Judgm Decis Mak 3:371–388
Reutskaja E, Hogarth RM (2009) Satisfaction in choice as a function of the number of alternatives: when
“goods satiate”. Psychol Market 26:197–203
Rotter JB (1966) Generalized expectancies for internal versus external control of reinforcement. Psychol
Monogr Gen Appl 80:1–28
Scheibehenne B, Greifeneder R, Todd PM (2009) What moderates the too-much-choice effect? Psychol Mar-
ket 26:229–253
Scheibehenne B, Greifeneder R, Todd PM (2010) Can there ever be too many options? A meta-analytic
review of choice overload. J Consum Res 37:409–425
Schulz R, Hanusa BH (1978) Long-term effects of control and predictability-enhancing interventions: find-
ings and ethical issues. J Pers Soc Psychol 36:1194–1201
Schwartz B (2004) The paradox of choice: why more is less. Ecco, New York
Shah AM, Wolford G (2007) Buying behavior as a function of parametric variation of number of choices.
Psychol Sci 18:369–370
Taylor SE (1989) Positive illusions: creative self-deception and the healthy mind. Basic Books, New York
Taylor SE, Brown JD (1988) Illusion and well-being: a social psychological perspective on mental health.
Psychol Bull 103:193–210
Publisher’s Note Springer Nature remains neutral with regard to jurisdictional claims in published
maps and institutional affiliations.
Author's personal copy
... Participants' tendency towards maximization was then assessed with the 11 maximizing items of the Decision-Making Tendency Inventory ( [25] see Appendix B), in which the answers ranged from 1 (=strongly disagree) to 7 (=strongly agree). This scale distinguishes between two independent facets of maximizing: the resolute and the fearful maximizing. ...
... From a practical point of view, our findings may provide suggestions and insights for the development of new decision aids in accordance with the specific decision-making tendency of the individuals who are supposed to be helped (see [34,35]). As pointed out by Misuraca et al. [9], individuals low in resolute and fearful maximizing may benefit from a decision aid different from that benefiting individuals high in these maximizing tendencies (see also [25,36]). Another important practical implication of our findings concerns the hiring process: since resolute maximizers make more optimal decisions, it might be wiser for organizations to select more resolute maximizers for tasks that require them to make strategical decisions. ...
Article
Full-text available
The present study explored the susceptibility of maximizers to the effect of the specific information format—frequency vs. percentage—in a risk assessment task. One-hundred and fourteen participants were randomized into two experimental conditions: a frequency format and a percentage format. In both conditions, participants had to rate the level of risk that a mental patient would harm someone after his discharge from a mental health facility, based on the information reported in the psychologist’s assessment for that patient. In the frequency condition, the information was presented in terms of frequencies, whereas in the percentage condition the same information was presented in terms of percentage. Our experiment showed that resolute maximizers are less affected by the specific format of the task than fearful maximizers. Thus, we conclude that resolute maximizers are more normative decision-makers. Theoretical and practical implications are discussed.
... In the discussion on Local Economic Development in Banjarnegara Regency, some people were concerned that the large number of local coffee brands did not contribute in creating the uniqueness of local coffee products. Consumers will prefer a purchasing situation with many choices, as long as the available brands are familiar (Misuraca et al., 2019). Even though the availability is large or excessive, brand familiarity will reduce the cognitive burden of consumers in choosing. ...
... Another study confirmed that similarities were felt to have a significant effect on decision-making difficulties (Agarwal & Chatterjee, 2003). This indicates that the many choices of brands actually make it difficult for consumers to choose so as not to cause positive feelings of consumers (Misuraca et al., 2019). The difficulty of consumers in differentiating between brands can also have an impact on consumer confusion which in turn will make it difficult to make decisions (Tjiptono et al., 2014). ...
Article
Full-text available
p>Coffee is one of the leading commodities in the plantation sub-sector in Indonesia because it has good market opportunities both locally and globally. The purpose of this research was to find out how the effect of perceived product similarity, product choices overload in the market toward decisions making difficulty, and knowledge of product classes as moderating variable. Data were collected using Google Forms and a self-administered questionnaire. Respondents in this study were 300 coffee consumers which were drawn using the purposive sampling method. Moderated regression was used to analyze this study. The results showed that perceived product similarity influences product choices overload positively and decision-making difficulties negatively. Choice overload had an insignificant effect on decision-making difficulties, and product class knowledge moderates the effect of perceived product similarity on decision-making difficulty. These findings provide insight into the importance of the brand as a distinguishing identity from other products.</p
... With the popularity of positive psychology, there has been an increasing number of studies focusing on the positive effects of the well-being on individuals and exploring the general and situation-specific factors that influence individual well-being in different cultural and social contexts [5][6][7]. ...
Article
Full-text available
Psychology has long conceived of individuals in terms of psychopathology and dysfunction [...]
... In our opinion, the most interesting focus of our study concerns the elicitation of prosocial priming in an online context, such as e-mail. Most research on priming in an online context has been carried out mainly in marketing (Smith and Wheeldon, 2001;Misuraca et al., 2019Misuraca et al., , 2021aDennis et al., 2020;Tanford et al., 2020). We do not know of any study investigating the impact of priming on bystander apathy in the online context. ...
Article
Full-text available
The present study tested the effect of priming the concept of prosociality on the bystander effect in an online environment. Participants were sent an e-mail requesting a plea for help and randomly assigned to one of four conditions in a 2 (Bystander: 0 vs. 14) × 2 (Priming: present vs. absent) design. The results demonstrated support for the study hypothesis. As expected, the virtual presence of many others significantly reduced e-mail responsiveness except when the request for help is preceded by prosocial priming. Implications of these findings for the literature on the bystander effect and priming are discussed.
... Subjects showed the same level of satisfaction when choosing from small and large sets of branded cellphones. However, when the same cellphones were presented without brand names, a higher level of dissatisfaction was observed for larger sets compared to smaller sets (Misuraca, Ceresia, Teuscher, & Faraci, 2019). ...
Book
Previous research has shown that neither too much nor too little choice is optimal. Choice sets of an intermediate size offer more positive cognitive and emotional consequences to the decision maker than small and large choice sets. However, the ideal number of choices depends on many factors. This chapter describes the main factors that moderate the effect of choice overload and so determine how much choice is enough. Consistent with Herbert A. Simon’s analogy of a pair of scissors to describe his conception of bounded rationality, where one blade represents the individual cognitive characteristics of the decision maker and the other the structures of the environment, this chapter presents these factors, regrouping them into two main categories: contextual and individual variables.
... Evidence from more than 30 experiments supports the empathy-altruism hypothesis, the hypothesis that empathic concern produces altruistic motivation [11,[69][70][71]. Empathic concern has been conceptualized as the main source of altruistic motivation. ...
Article
Full-text available
Research on the effects of guilt on interpersonal relationships has shown that guilt frequently motivates prosocial behavior in dyadic social situations. When multiple persons are involved, however, this emotion can be disadvantageous for other people in the social environment. Two experiments were carried out to examine the effect of guilt and empathy on prosocial behavior in a context in which more than two people are involved. Experiment 1 investigates whether, in three-person situations, guilt motivates prosocial behavior with beneficial effects for the victim of one’s actions but disadvantageous effects for the third individual. Participants were faced with a social dilemma in which they could choose to take action that would benefit themselves, the victim, or the other individual. The findings show that guilt produces disadvantageous side effects for the third individual person present without negatively affecting the transgressor’s interest. In Experiment 2, participants were faced with a social dilemma in which they could act to benefit themselves, the victim, or a third person for whom they were induced to feel empathic concern. Again, the results show that guilt generates advantages for the victim but, in this case, at the expense of the transgressor and not at the expense of the third person, for whom they were induced to feel empathic concern. Therefore, guilt and empathy seem to limit the transgressor’s interest. The theoretical implications are discussed.
... Communication should be simple, and it should illustrate what people should do and not do, in a way that it is easy to understand for everyone. Giving people too much information and too many choices can lead to the effect of people avoiding making decisions altogether, if they become overwhelmed by the complexity [74][75][76][77][78][79]. ...
Article
Full-text available
During the outbreak of COVID-19 in Italy, people often failed to adopt behaviors that could have stopped, or at least slowed down, the spread of this deadly disease. We offer cognitive explanations for these decisions, based on some of the most common heuristics and biases that are known to influence human judgment and decision-making, especially under conditions of high uncertainty. Our analysis concludes with the following recommendations: policymakers can and should take advantage of this established science, in order to communicate more effectively and increase the likelihood that people choose responsible actions in a public health crisis.
Chapter
Full-text available
The antecedents and consequences of choice overload, or overchoice, have been largely investigated. However, the aspect of comprehensively evaluating a large assortment of options and mitigating subsequent choice overload is absent. By adopting a growth mindset and comprehensively evaluating alternatives , it is possible to combat the menace known as overchoice. This chapter conceptualises a unique model that examines choice overload mitigation from a deeper psychological lens. Moreover, it also adds a new dimension to the concept by integrating the aspect of rigorous choice evaluation. Overall, future research propositions have been made that will enable researchers to validate the novel model. Implications of validating said model include strengthening the field of choice overload by offering comprehensive mitigation strategies.
Article
Evidence regarding the impact of product line breadth (PLB) on brand performance remains fragmented; the current research proposes an influential effect of product equity in determining PLB success. To test these predictions, Study 1 first identifies heterogeneous effects of PLB on brand performance according to the levels of product equity. Specifically, PLB hinders (improves) the performance of low (high) product equity brands. Then Study 2 identifies two drivers of PLB effectiveness, product attribute differences and competitive intensity, that have contrasting influences for brands with high versus low product equity. These influences exert long-term, cumulative effects (i.e., over 104 weeks). To ensure the generalizability and applicability of the findings, this research effort spans a vast consumer scanner data set, involving 268 brand panels, 14 product categories, and three retailers. Based on this collected evidence, the authors propose a matrix of managerial actions that practitioners can adopt to increase their PLB effectiveness.
Article
The present study tested the hypothesis that maximizers – people who routinely seek to make optimal decisions rather than quickly settling for an acceptable one – are less susceptible to cognitive biases. Experiment 1 showed that high maximizers are less swayed by irrelevant differences in the framing of a decision-making scenario than are low maximizers. Experiment 2 confirmed that maximizers are also less likely to neglect important base rate information when making decisions. Experiment 3 showed that maximizers are less likely to stick with a bad plan in which they have already invested (the sunk-cost bias) and therefore are quicker to switch to a more attractive alternative plan. Thus, we conclude that maximizers are generally more normative decision-makers. The present study also confirms the importance of using refined maximizing scales.
Article
A currently popular position among consumer advocates and many public policy makers is that more product information is better. A 3 (number of brands) × 3 (number of items of information per brand) factorial experiment which tested this contention revealed that, while consumers do feel more satisfied and less confused, they actually make poorer purchase decisions with more information.
Article
Examined the long-term effects of participating in a field experiment on the effects of control and predictability-enhancing interventions. 40 retirement home residents who had initially benefited from being exposed to a specific positive predictable or controllable event (visits by college students) were assessed at 3 different intervals after the study was terminated. Health and psychological status data collected 24, 30, and 42 mo after the study indicated no positive long-term effects attributable to the interventions. In fact, groups that had initially benefited from the interventions exhibited precipitous declines once the study was terminated, whereas groups that had not benefited remained stable over time. Theoretical and ethical implications are discussed. (11 ref) (PsycINFO Database Record (c) 2006 APA, all rights reserved).
Article
A question facing us today, in the new and rapidly evolving digital age, is whether searching for the best option – being a maximizer – leads to greater happiness and better outcomes than settling on the first good enough option found – or “satisficing.” Answers to this question inform behavioural insights to improve well-being and decision-making in policy and organizational settings. Yet, the answers to this fundamental question of measurement of the happiness of a maximizer versus a satisficer in the current psychological literature are: 1) conflicting; 2) anchored on the use of the first scale published to measure maximization as an individual-difference, and 3) unable to describe the search behaviour of decision makers navigating the digital world with tools of the 21st century - apps, smartphones or tablets, and most often all of them. We present, based on a review and analysis of the literature and scales, a call to stop the development of more maximization scales. Furthermore, we articulate the argument for a re-definition of maximizing that balances the face validity of the construct and the relevance to decision making in an age of digital tools so that future scales are useful for future choice architects and researchers.
Book
I: Background.- 1. An Introduction.- 2. Conceptualizations of Intrinsic Motivation and Self-Determination.- II: Self-Determination Theory.- 3. Cognitive Evaluation Theory: Perceived Causality and Perceived Competence.- 4. Cognitive Evaluation Theory: Interpersonal Communication and Intrapersonal Regulation.- 5. Toward an Organismic Integration Theory: Motivation and Development.- 6. Causality Orientations Theory: Personality Influences on Motivation.- III: Alternative Approaches.- 7. Operant and Attributional Theories.- 8. Information-Processing Theories.- IV: Applications and Implications.- 9. Education.- 10. Psychotherapy.- 11. Work.- 12. Sports.- References.- Author Index.
Article
Current research on the overchoice effect has been mainly conducted from an adult point of view and with adult subjects. This study investigates whether children, adolescents, and seniors suffer the same negative consequences as adults when facing an overabundance of choice. Findings showed that the overchoice effect did not equally extend to all age groups. While adolescents were affected by the phenomenon in a very similar way as adults, children and seniors suffered fewer negative consequences of an overabundance of choice. Theoretical and practical implications are discussed.
Article
We introduce the Decision Making Tendency Inventory (DMTI), a new scale for measuring the decision-making tendencies to maximize, to satisfice, and to minimize. The scale has promising psychometric properties. Our findings show that the revealed tendencies are independent from each other and from the specific decision-making domain. Each factor is differently related to a set of indices of well-being and functioning, suggesting intriguing considerations regarding the distinctive characteristics of maximizing, satisficing, and minimizing. The DMTI extends previous research on maximizing and might contribute to explain the inconsistent results in the literature. Directions for future research are suggested. http://authors.elsevier.com/a/1R1R0heKdP~As
Article
Two studies investigated cognitive mechanisms that may be associated with people's tendency to maximize. Maximizers are individuals who are spending a great amount of effort in order to find the very best option in a decision situation, rather than stopping the decision process when they encounter a satisfying option. These studies show that maximizers are more future oriented than other people, which may motivate them to invest the extra energy into optimal choices. Maximizers also have higher numerical skills, possibly facilitating the cognitive processes involved with decision trade-offs. © 2015 International Union of Psychological Science.