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Biol. Lett.
doi:10.1098/rsbl.2011.0098
Published online
Animal behaviour
Too much of a good thing?
Variety is confusing in
mate choice
Alison P. Lenton1,* and Marco Francesconi2
1
Department of Psychology, University of Edinburgh, 7 George Square,
Edinburgh EH8 9JZ, UK
2
Department of Economics, University of Essex, Wivenhoe Park,
Colchester CO4 3SQ, UK
*Author for correspondence ([email protected]).
Choice variety is supposed to increase the likelihood that a chooser’s preferences are satisfied.
To assess the effects of variety on real-world
mate choice, we analysed human dating decisions
across 84 speed-dating events (events in which
people go on a series of sequential ‘mini-dates’).
Results showed that choosers made fewer proposals (positive dating decisions) at events in which
the available dates showed greater variety across
such attributes as age, height, occupation and
education, and this effect was particularly strong
when choosers were confronted with a larger
number of opposite-sex speed daters. Additionally, participants attending events in which the
available options showed greater variety across
these attributes were less likely to choose the consensually preferred mate option and more likely to
choose no one at all. In contexts in which time is a
limited resource, choice variety—rather than
facilitating choice quality or increasing choosiness—is confusing and potentially detrimental to
choice quality.
Keywords: choice variety; mate choice; choice quality; choice overload; human behaviour
1. INTRODUCTION
Humans and non-human animals alike are adept at
detecting variety [1], possibly because variety increases
the likelihood of satisfying one’s needs [2]. But how do
choosers manage choice variety? This study aimed to
advance researchers’ understanding of how the
choice environment shapes observed mate preferences.
In particular, we examined how choice variety—a term
we restrict to mean the degree to which a set of mate
options is heterogeneous versus homogeneous, over
and above the number of options—influences humans’
dating choices.
With respect to human behaviour, the relationship
between variety and choice has been investigated in
consumers. While some studies find that choice variety
is attractive and increases consumers’ product consumption (when the options are few; [3]), others
show that variety leads to dissatisfaction [4], poorer
quality choice [5] and lesser consumption [6].
Among ethologists, a related issue has been
addressed with theoretical modelling. One model
suggests that choices will be more assortative in a
Electronic supplementary material is available at http://dx.doi.org/
10.1098/rsbl.2011.0098 or via http://rsbl.royalsocietypublishing.org.
Received 25 January 2011
Accepted 11 February 2011
high than a low-variety environment [7]. Additionally,
Luttbeg’s [8] modelling indicates that perceived variety
will lead choosers to set a higher acceptance threshold
and thus, to increased choosiness (i.e. decreased responsiveness; [9]). A simple measure of choosiness is the
proportion of individuals rejected. Accordingly, one
might predict that this proportion increases with option
variety.
A crucial difference between the ethologists’ and
psychologists’ explanations for variety leading to
more rejections, however, is the latter’s proposal that
it results from confusion rather than choosiness. That
is, consumers are thought to be less likely to choose
from a high-variety option set because search, discrimination and evaluation costs are higher (more time and
effort); and if they choose at all, the probability of suboptimal choice increases [10]. To illustrate, imagine
two sets of five options, each of which possesses eight
attributes. In the lower variety set, the options are
the same on four of the eight attributes. In the higher
variety set, the options vary across all eight attributes.
Choosers facing the latter set may find it more difficult
to evaluate the options and choose between them.
Likewise, Heitmann et al. [10] found that ‘too much’
perceived variety decreased purchasing, because choosers associated variety with higher evaluation costs and
future regret.
Many ethologists have also discussed the notion of
perceiver errors in cue assessment and option discrimination [11 – 13], but what has yet to be addressed is
how the assumptions that (i) this error is likely to
increase with choice variety and (ii) greater choosiness
also increases with choice variety, play out against
one another. Jennions & Petrie [14] suggest one type
of evidence that could help tease apart perceiver
error (owing to confusion) from choosiness: if a population-level ‘bias’ (mean preference) strengthens in a
high-variety context, it would point to increasing choosiness, whereas if the ‘bias’ weakens, it would point to
increasing confusion. Assuming that a positive correlation exists between the number and variety of
options (but see below), chooser confusion may
explain why mating skew usually decreases with an
increasing number of options ([15,16]; but see [17]).
The present study is novel in empirically investigating
the effects of choice variety on human mate-choice behaviour, a domain in which the relationship between
number of options and variety occurs naturally. This
study also enables us to begin disentangling choosiness
from confusion. By doing so, we hope to further elucidate
the function and consequences of variety in choice
behaviour.
2. MATERIAL AND METHODS
(a) Sample
We analysed dating decisions made by 1868 female and 1870 male participants in 84 commercially run speed-dating events. In brief, single
individuals registered for an event. Participants then created an online
profile in which they reported their age, weight, height, educational
attainment, religion, occupation and smoking habits (‘attributes’). At
the event, several women met a comparable number of men for a
3 min mini-date each (male–female ratio: mean + s.d. ¼ 1.00 + 0.08,
range 0.85–1.23), with the events gathering an average of 24 speed
daters of each sex (range: 15–31). Usually within 48 h, participants
communicated their decisions (‘yes’ or ‘no’ for each opposite-sex
speed dater) to the agency. Consequently, our results are less relevant
to decision-rule models necessitating that a single option is chosen
This journal is q 2011 The Royal Society
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2
A. P. Lenton & M. Francesconi
Variety in mate choice
Table 1. Attribute definitions and descriptive statistics. (The descriptive statistics are based on the attributes of the 1868
female and 1870 male participants.)
attribute
number of levels
definition
descriptive statistics (mean + s.d.)
age
continuous
in years
education
2
occupation
3
smoking
2
university degree or more
(proportion)
any qualification below university level
(proportion)
professional/managerial
(proportion)
skilled non-manual
(proportion)
other occupations
(proportion)
smoker (proportion)
female 34.3 + 7.5
male 35.6 + 6.9
female 0.37 + 0.48
male 0.40 + 0.49
female 0.63 + 0.48
male 0.60 + 0.49
female 0.20 + 0.40
male 0.27 + 0.44
female 0.29 + 0.45
male 0.25 + 0.43
female 0.51 + 0.50
male 0.48 + 0.50
female 0.06 + 0.24
male 0.05 + 0.22
female 0.94 + 0.24
male 0.95 + 0.22
female 0.86 + 0.34
male 0.80 + 0.40
female 0.14 + 0.34
male 0.20 + 0.40
female 165.5 + 5.1
male 179.2 + 5.5
female 20.83 + 1.98
male 23.75 + 2.71
non-smoker (proportion)
religion
2
height
continuous
BMI
continuous
no religious affiliation
(proportion)
having a religious affiliation
(proportion)
in centimetres
weight in kilograms/square of
height in metres
than they are to models that allow for multiple choices and/or models in
which options are winnowed in stages [8,9,18,19].
(b) Variety index
For each of the 168 option sets (84 for male choosers and 84 for
female choosers), we calculated the variance in each attribute, and
then centred and standardized these scores by subtracting the
mean variance for each attribute and dividing by its standard deviation (table 1). To characterize the overall variability of a given
option set, we averaged these standardized variance scores across
all attributes. Thus, the attributes contribute equally to the overall
score. This average variance was our measure of variety. Variety
scores were strongly correlated with entropy (r ¼ 0.91), another
approach to assessing complexity [20], indicating that these
measures captured cue dispersion similarly.
Because we sought to investigate how the characteristics of an
option set influence choice and, further, because the characteristics
of any one set were the same for all choosers at a given event, the analyses were performed at the event level. We note that number of
options was strongly correlated with number of choosers (r ¼ 0.91,
p ¼ 0.0001), an inherent feature of speed-dating events. Variety
and number of options were also positively correlated, but only
weakly (r ¼ 0.25, p ¼ 0.002).
(c) Data analysis
We regressed the number of proposals (i.e. number of yes decisions)
made by sets of choosers on (simultaneously): (i) the variety of their
option set (standardized and centred about the mean); (ii) the
number of options (standardized and centred about the mean);
(iii) the sex of the chooser set (male ¼ 0, female ¼ 1, centred
about the mean); and (iv) all two- and three-way interactions.
3. RESULTS
Table 2 presents the results. As found elsewhere [21],
men made significantly more proposals than women
did. More interestingly, as overall option variety
increased, the number of proposals decreased. Supplementary analyses suggest that these results are
unlikely to be accounted for by increasing option
variety making it less probable that choosers’ idiosyncratic preferences were satisfied or by increasing
Biol. Lett.
option variety yielding higher quality options (electronic supplementary material, tables S1 and S2).
Nevertheless, future research should investigate these
alternative explanations further.
As the number of options increased, so did the
number of proposals. A significant variety choosersex interaction revealed that, although the variety–
proposal relationship was significantly negative for both
sexes (ps , 0.01), it was stronger among men
(h2p ¼ 0:21) than women h2p ¼ 0:17). A significant interaction between variety and number of options (figure 1)
showed that the negative effect of variety on choice was
greater when choosers faced many (more than 23 participants; h2p largeset ¼ 0:24) rather than fewer (less than or
equal to 23 participants; h2p smallset ¼ 0:14) options.
A significant interaction between number of options
and chooser sex indicated that the positive effect of
number of options on choice was greater for men
(h2p ¼ 0:19) than for women (h2p ¼ 0:13), though both
remained statistically significant (ps , 0.001). Overall,
women and men managed choice variety similarly. The
three-way interaction was non-significant.
We performed an additional analysis using a modified dependent variable to understand the effects of
these variables on individual (rather than group)
choice behaviour. This dependent variable was
formed by dividing number of proposals in an event
by the number of available choosers. The new results
showed that the predictors related to the new dependent variable in the same way as before, except for
the chooser-sex main effect and the chooser sex number of options interaction (which remained
negative, but were no longer significant).
Returning to number of proposals as the dependent variable, regression analyses for each attribute
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Variety in mate choice
A. P. Lenton & M. Francesconi
3
Table 2. Predictors of number of proposals. (For all t-tests, degrees of freedom ¼ 167.)
predictor
coefficient (s.e.)
p-value
effect size (h2p Þa
alternative coefficientb (s.e.)
constant
variety (variance)
number of options
sex of chooser set
variety number of options
variety chooser sex
number of options chooser sex
variety number of options chooser sex
82.16 (4.82)
27.72 (2.34)
4.47 (0.47)
244.67 (12.11)
0.17 (0.05)
3.62 (0.95)
21.03 (0.36)
20.13 (0.32)
0.001
0.001
0.001
0.001
0.001
0.001
0.005
0.683
—
0.19
0.17
0.24
0.10
0.04
0.01
0.01
83.66 (5.55)
21.49 (0.28)
0.71 (0.07)
256.22 (6.65)
0.06 (0.01)
0.42 (0.13)
20.53 (0.25)
20.03 (0.04)
a
Partial h2 indicates the proportion of variability attributable to a given predictor, over and above the other predictors.
This column reports coefficients (s.e.) from a regression with raw (unstandardized, uncentred) predictors.
mean no. proposals per event
b
130
120
110
100
90
80
70
60
50
40
30
20
10
0
overall
mean
small
large
Figure 1. Mean (+s.e.) number of proposals made at speeddating events with a small (less than or equal to 23) or large
(greater than 23) number of options showing either lower
(less than or equal to 0.21) or higher (greater than 0.21)
attribute variety. The mean number of options in the small
events was 19.80, while it was 26.67 in the large events.
We remind the reader that our predictor variables were
centred and standardized, but we describe ‘number of
options’ here in its raw form, as these values are more comprehensible. The values used to categorize ‘number of
options’ (small versus large) and ‘variety’ (high versus low)
were their medians. Light grey bars represent low variance
and dark grey bars represent high variance.
separately showed that the main effect of variety was
significantly negative for every attribute and for both
male and female choosers, except for variability
in the options’ smoking habits for both male
(t83 ¼ 20.59, p ¼ 0.559) and female choosers
(t83 ¼ 20.44, p ¼ 0.663). Similarly, the interaction
effect was at least marginally significant (p , 0.10)
and in the same direction (a positive coefficient) for
every attribute and for both sexes, with the exception
of variability in women’s occupations for male choosers (t83 ¼ 1.58, p ¼ 0.123). The primary findings
were not driven by a subset of the attributes.
To assess whether the reduction in number of proposals might reflect increasing confusion rather than
increasing choosiness, we examined how variety
related to the proportion of choosers: (i) selecting the
top-ranked opposite-sex speed dater, as positive consensus by choosers is used as a marker of choice
quality among those studying non-human animals [2]
and, further, increasing consensus is supposed to be
indicative of greater choosiness [14]; and (ii) making
no proposals, as deciding not to choose is interpreted
Biol. Lett.
as uncertainty by consumer researchers [5,6]. The
set of predictors described previously was used.
Being proportions, both dependent variables were
first arcsine root transformed; and although correlated,
they were not redundant (r ¼ 20.35, p ¼ 0.001). We
focus here on the main effect of variety (see the
electronic supplementary material, tables S3 and S4
for complete results). Increasing variety was associated
with choosers being significantly less likely to select the
top-ranked speed dater (t167 ¼ 22.26, p ¼ 0.025) and
more likely to make 0 proposals (t167 ¼ 3.93, p ¼ 0.001).
When these behaviours were simultaneously added to
the regression model, the joint effect of variety and
the variety number of options interaction was nonsignificant (F2,158 ¼ 1.82, p ¼ 0.17), suggesting that
these behaviours, at least in part, explained the negative
effect of variety on proposals.
4. DISCUSSION
Variety is detectable by mate choosers, and it increases
with the number of options; but variety and number of
options are not substitutable. Indeed, choosers made
more proposals when faced with more options, but
fewer proposals when these options were highly variable in their attributes; suggesting that choice variety
yields greater confusion rather than greater choosiness.
Also this effect was stronger when there were more
options available. Such an interaction is not predicted
by the choosiness account, while it accords with the
confusion account. Notably, there is nothing to prevent
speed daters from ‘hedging bets’ by choosing several
options. Instead, increasing variety led some participants not to choose at all and some to make ‘lower
quality’ choices. As with the number of mate options
[2], there may be a natural range of variability in mate
options that a given species is adapted to select
among, with variability outside this range yielding confusion (see [22]). Overall, our findings strengthen
evidence for the bounded rationality of human mate
choice [18].
1 Wasserman, E. A., Young, M. E. & Cook, R. G. 2004 Variability discrimination in humans and animals. Am. Psychol.
59, 879–890. (doi:10.1037/0003-066X.59.9.879)
2 Hutchinson, J. M. C. 2005 Is more choice always desirable? Evidence and arguments from leks, food selection,
and environmental enrichment. Biol. Rev. 80, 73–92.
(doi:10.1017/S1464793104006554)
Downloaded from http://rsbl.royalsocietypublishing.org/ on June 14, 2017
4
A. P. Lenton & M. Francesconi
Variety in mate choice
3 Kahn, B. E. & Wansink, B. 2004 The influence of assortment structure on perceived variety and consumption
quantities. J. Consum. Res. 30, 519– 534. (doi:10.1086/
380286)
4 Greifeneder, R., Scheibehenne, B. & Kleber, N. 2010
Less may be more when choosing is difficult: choice complexity and too much choice. Acta Psychol. 133, 45– 50.
(doi:10.1016/j.actpsy.2009.08.005)
5 Lurie, N. H. 2004 Decision making in information-rich
environments: the role of information structure.
J. Consum. Res. 30, 473–486. (doi:10.1086/380283)
6 Swait, J. & Adamowicz, W. 2001 The influence of task complexity on consumer choice: a latent class model of decision
strategy switching. J. Consum. Res. 28, 135–148. (doi:10.
1086/321952)
7 Johnstone, R. A., Reynolds, J. D. & Deutsch, J. C.
1996 Mutual mate choice and sex differences in
choosiness. Evolution 50, 1382–1391. (doi:10.2307/
2410876)
8 Luttbeg, B. 2002 Assessing the robustness and optimality
of alternative decision rules with varying assumptions. Anim. Behav. 63, 805 –814. (doi:10.1006/anbe.
2001.1979)
9 Bailey, N. W. 2008 Love will tear you apart: different
components of female choice exert contrasting selection
on males. Behav. Ecol. 19, 960 –966. (doi:10.1093/
beheco/arn054)
10 Heitmann, M., Herrmann, A. & Kaiser, C. 2007 The effect
of product variety on purchase probability. Rev. Manag. Sci.
1, 111–131. (doi:10.1007/s11846-007-0006-6)
11 Fawcett, T. W. & Johnstone, R. A. 2003 Optimal assessment of multiple cues. Proc. R. Soc. Lond. B 270, 1637–
1643. (doi:10.1098/rspb.2003.2328)
12 Johnstone, R. A. & Earn, D. J. D. 1999 Imperfect female
choice and male mating skew on leks of different sizes.
Behav. Ecol. Sociobiol. 45, 277–281. (doi:10.1007/
s002650050562)
Biol. Lett.
13 Luttbeg, B. 2004 Female mate assessment and choice behavior affect the frequency of alternative male mating
tactics. Behav. Ecol. 15, 239– 247. (doi:10.1093/
beheco/arh002)
14 Jennions, M. D. & Petrie, M. 1997 Variation in mate
choice and mating preferences: a review of causes and
consequences. Biol. Rev. Camb. Phil. Soc. 72, 283 –327.
(doi:10.1111/j.1469-185X.1997.tb00015.x)
15 Kokko, H., Sutherland, W. J., Lindström, J., Reynolds,
J. D. & Mackenzie, A. 1998 Individual mating success,
lek stability, and the neglected limitations of statistical
power. Anim. Behav. 56, 755 –762. (doi:10.1006/anbe.
1998.0815)
16 Widemo, F. & Owens, I. P. F. 1995 Lek size, male mating
skew, and the evolution of lekking. Nature 373, 148 –151.
(doi:10.1038/373148a0)
17 Lenton, A. P., Fasolo, B. & Todd, P. M. 2009 The
relationship between number of potential mates and
mating skew in humans. Anim. Behav. 77, 55– 60.
(doi:10.1016/j.anbehav.2008.08.025)
18 Miller, G. F. & Todd, P. M. 1998 Mate choice turns cognitive. Trends Cogn. Sci. 2, 190–198. (doi:10.1016/
S1364-6613(98)01169-3)
19 Valone, T. J., Nordell, S. E., Giraldeau, L.-A. & Templeton, J. J. 1996 The empirical question of thresholds and
mechanisms of mate choice. Evol. Ecol. 10, 447 –455.
(doi:10.1007/BF01237729)
20 Shannon, C. E. 1948 A mathematical theory of communication. Bell Syst. Tech. J. 27, 379–423. and 623–656.
21 Todd, P. M., Penke, L., Fasolo, B. & Lenton, A. P. 2007
Different cognitive processes underlie human mate choices
and mate preferences. Proc. Natl Acad. Sci. USA 104, 15
011–15 016. (doi:10.1073/pnas.0705290104)
22 Lenton, A. P., Fasolo, B. & Todd, P. M. 2008 ‘Shopping’
for a mate: expected versus experienced preferences in
online mate choice. IEEE Trans. Prof. Commun. 51,
169 –182. (doi:10.1109/TPC.2008.2000342)