The Presence of Variety Reduces Perceived
Quantity
JOSEPH P. REDDENSTEPHEN J. HOCH*
Against common intuition, we find that variety in an assortment reduces its perceived quantity. Two studies show that people provide larger quantity estimateswhen shown random patterns of identical colored dots or geometric shapes thanwhen those patterns contain variety. The difference in perceived quantity does not
grow as the number of different types increases beyond two, and it disappears if
the overall area occupied by the set is made salient through context. We attributethe results to the natural consolidation of identical items into a single Gestalt wholethat makes the set seem larger. Two additional studies show that this perceptual
influence also causes people to pour more when using varied items to match asample of food. The article closes with a discussion of the potential implicationsof these findings for variety research and portion control.

D

used. Third, varied sets may attract more attention, andpeople sometimes misattribute attention to a greater quantity(Folkes and Matta 2004). Although these mechanisms suggest that variety could increase perceived quantity, past research has not tested whether it actually does.
Contrary to popular belief and the above reasoning, we
propose that the presence of variety actually makes it seem
like there are fewer items. Put another way, items seem more
numerous when they are all the same, or homogeneous. A
set composed of only identical items makes it easy for people to perceive the items as a single, unified whole. Focusing
on this larger, all-encompassing whole makes the set appear
to occupy more space. Since people rely on spatial area asa cue for quantity (Krueger 1972; Raghubir and Krishna
1996; Vos et al. 1988), a set appears to have more items
when they are all identical.
Our primary objective is to establish this perceptual influence. Four experiments provide this evidence as well as
support for a proposed mechanism. We also highlight a rolefor quantity perception in variety research. In particular,
perceived quantity is a potential mediator to consider infuture studies of how variety affects consumption. This article concludes with a discussion of the implications of thecurrent findings, especially for portion control and unintended overconsumption.

oes having variety in a set affect the perceived quantityof items? Does a bowl with both red and blue candies
seem to have more or less than a bowl with only one colorof candy? Despite research showing that quantity perceptions influence portion sizes (Wansink and van Ittersum2003), feelings of satiation (Raghubir and Krishna 1999),
and food intake (Wansink, Painter, and North 2005), we
know little about how variety affects perceived quantity.
To investigate intuition, we asked 121 students if “a package with a variety of items appears like it has less than apackage with just one type.” People could respond with
Agree, Disagree, or No Effect. The results indicate that mostpeople expected a relationship (overall x 2 (2) p 27.68,
p ! .0001). In particular, more people disagreed (n p 64)
with this statement than agreed (n p 40) or believed there
was no effect (n p 17). A majority believed that variety
makes a set appear to have more rather than less items.
There are several reasons for this belief. First, variety
makes it easier to notice each item among other nearby items(Frick 1987). Second, since people use more items as acue for more variety in an assortment (Broniarczyk, Hoyer,
and McAlister 1998), the reverse intuition could also be*Joseph P. Redden is assistant professor of marketing, Carlson School,
University of Minnesota (redde007@umn.edu). Stephen J. Hoch is the
Patty and Jay H. Baker Professor of Marketing, Wharton School, Universityof Pennsylvania (hochs@wharton.upenn.edu). The authors thank Selin
Malkoc, Manoj Thomas, and Kathleen Vohs for comments on an earlier
draft, and a reviewer for suggesting study 4.

BACKGROUND
Quantity Perceptions

John Deighton served as editor and Ann McGill served as associate editor
for this article.

We use the term “quantity” primarily as it pertains to howmuch (e.g., grams in a food serving). When the individual
items are nearly the same size, as in the subsequent studies,Electronically published March 25, 2009406
q 2009 by JOURNAL OF CONSUMER RESEARCH, Inc. ● Vol. 36 ● October 2009
All rights reserved. 0093-5301/2009/3603-0009$10.00. DOI: 10.1086/598971

VARIETY AND PERCEIVED QUANTITY

the question of how much is essentially the same as how
many. Even in the more general case, this distinction may
not matter much, as people rely heavily on the number of
items when judging quantity (Pelham, Sumarta, and Myaskovsky 1994). Thus, we use quantity to capture a general
sense of how much of something there is.
Numerosity research has identified four ways that people
quantify items. First, for up to six items, people can accurately and nearly instantaneously quantify the items (Kaufman et al. 1949). This ability, labeled “subitization,” is attributed to the recognition of patterns like triangles for three(Mandler and Shebo 1982). Second, people can keep a running count while enumerating each item. Counting can theoretically quantify any number of items but is time consuming with larger sets. Third, people can estimate or countthe number of items in a particular region and then extrapolate. This buildup method requires less effort than counting,especially when regions are small and easily identifiable, but
still requires attentional focus and nontrivial calculations.
Finally, people often rely on a more primitive approximation system specialized for approximating quantities (Dehaene 1992, 1997; Piazza et al. 2004), directly perceiving
numerosity much like other qualities, such as brightness orweight. Approximation takes 100–200 milliseconds (Mandler and Shebo 1982) and is seemingly automatic regardlessof the task (Dehaene 1997). With minimal effort people canreliably notice quantity differences of 17% (Piazza et al.
2004). It seems that, in lieu of more effortful methods, people can quickly approximate a total quantity with reasonableaccuracy.
One reason people can make these rapid approximations
is that they rely on cues. In particular, people use the area
occupied by the items as a cue for the total quantity. Youngchildren judge a set to have more items when toy cubes are
made larger (Binet 1890) or candies are more spaced out(Piaget 1968). People perceive a pattern to have more dots
if the display area is enlarged (Krueger 1972) and a jagged
line to have more dots when the endpoints are further apart(Krishna and Raghubir 1997). Empirical models have fit
quantity estimates using the filled area of the overall contourof the set (Vos et al. 1988) and the collective area occupiedby the items (Allik and Tuulmets 1991). These results allshow that a set appears to have more items as it seems tooccupy more space.

Perceptual Grouping and Perceived Quantity
We propose that the perceived area occupied by a set
depends on how people perceptually group the items in theset. Although people could attempt to combine the areas of
the individual items, they may instead process the set in aholistic fashion by envisioning a global figure that encompasses the items (e.g., an outside border). Such a figure may
spontaneously appear if the items naturally combine into aperceptual Gestalt (Palmer 1982; Wertheimer 1938). For
example, people see a wall rather than just a bunch of individual bricks and so will rely on the area of the wall as
a cue for the quantity of bricks.

407

Prior work supports the notion that people use a Gestalt
figure to estimate the quantity of items. For example, mostpeople incorrectly perceive that the solitaire illusion in figure
1A has more black dots than white dots (Frith and Frith
1972). The black dots presumably create a salient wholewith a clear height and width that spans a larger area than
the four isolated clusters of white dots (Frith and Frith 1972;
Vos et al. 1988). Likewise, as shown in figure 1B, people
estimate that there are more dots when they are regularly
versus randomly arranged (Ginsburg 1978), presumably because the regularly arranged dots appear as a giant squarethat occupies the entire space. These two illusions both showthat rearranging items to make the whole more salient canincrease perceived quantity.

Predictions
We explore whether, similar to spatial arrangement, thepresence of variety in a set can affect the salience of thewhole and in turn the perceived quantity. People group items
much faster when they are identical (Enns and Kingstone
1995; Mishra, Mishra, and Nayakankuppam 2006) and naturally see identical items as a single coherent figure (Palmer
1982; Wertheimer 1938). When items differ, people tend to
focus on one type or the other and find it difficult to merge
the multiple types into a whole. For example, judging theshape of an area is harder when it is two different colors
versus just one color (Huang, Pashler, and Treisman 2006).
FIGURE 1
EXAMPLES OF VISUAL ILLUSIONS

408

Identical items make the whole more salient, focusing attention on the largest possible area occupied by the set. Sincearea is a cue for quantity, an identical set seems more numerous than a varied one. Conversely, variety makes a set
appear to have fewer items.
The prediction that variety reduces perceived quantity is
not obvious for several reasons. Variety could make it lesslikely that people will overlook some items because each
item stands out. Variety also may serve as a cue for quantity
as sets with more items generally do have more variety (ifthe items were selected at random). Additionally, varied
assortments could attract more attention, which people may
misattribute to a greater quantity (Folkes and Matta 2004).
People might similarly rely on the ease of perception as acue for quantity, as they do for many other judgments(Schwarz 2004). However, it is not clear whether greater
perceptual fluency should indicate a larger quantity, because
bigger sets are easier to notice, or a smaller quantity, because
smaller sets have fewer items to process.
Despite any potential effects of variety on these othercues, we predict that all else equal variety reduces perceived
quantity because people rely so heavily on the area cue.
This proposed mechanism leads to an additional and quite
specific prediction as to the nature of this effect. What matters most is whether people perceive the set as a whole ornot, that is, it is a special property created by homogeneity.
Because the presence of any variety already breaks up thewhole, the perceived quantity of items should not changemuch with further variety. Thus, we predict that although
the perceived quantity of a set will decrease as the numberof types goes from one to two, it will not decrease whengoing from two to more than two types. If so, such a result
would provide some insight into the underlying process, asa monotonically decreasing relationship would be predictedby several alternative mechanisms (e.g., anchoring on thenumber of items of one subtype).
The prediction that adding greater variety does not continue to lower the perceived quantity may seem surprising
at first. The process we propose might be expected to apply
to each part, such that more types of items create smaller
Gestalt groupings throughout the set, suggesting a result
counter to the previous prediction. However, we do not expect people to simultaneously perceive and build up multiple
Gestalts in this way. Top-down processes, like using area
as a quantity cue, serve to help avoid the cognitive effort
of individually processing many items or groups of items
in a set. For example, past work has found that people recall
the mean size of an item for the set without recalling thesize of any particular item (Ariely 2001; Chong and Treisman 2003). So, given that the notion of the Gestalt applies
primarily to a single overall whole, we expect that any effects of variety on the perceived quantity will mostly occur
as soon as variety breaks up this whole.
Given that the salience of the whole is central to our
proposed mechanism, we can predict two additional boundary conditions. First, as long as the area of the whole remains
salient, the presence of variety should have little effect on

JOURNAL OF CONSUMER RESEARCH

perceived quantity. This implies that if the context highlights
the overall area so people focus on it (e.g., a border), thena varied set should appear to have the same quantity ofitems as an identical set. Second, although people often relyon the area cue, this reliance will diminish if other quantity
cues are salient. Past work has shown that one cue people
use is the extent to which the items fill their container (Hsee
1998). If the container is nearly full, people may instead
anchor on the quantity cue provided by the size of the container and pay less attention to the Gestalt whole created by
identical items. Similarly, if a container is nearly empty, theGestalt whole created by identical items may seem insignificant relative to the much larger container that holds it.
In both cases, we predict that the effect variety has of reducing
the perceived quantity will be attenuated because people instead rely somewhat on the container utilization cue.
To summarize, we predict that (1) a set appears to havemore items if the items are identical, (2) a set that alreadyhas variety does not appear to have even fewer items as
more variety is added, (3) variety has no effect on the perceived quantity of items when the context makes the overall
area salient, and (4) variety reduces the perceived quantity
less so when the container is nearly full or nearly empty.
We should point out that our research is silent on thequestion of perceived quantity accuracy. That said, if variety
reduces perceived quantity, it follows that introducing variety will lead to greater (less) accuracy in settings where
people tend to overestimate (underestimate) the quantity. For
example, people show an elongation bias whereby they overweight the height dimension (Piaget 1968), and so we would
expect that variety would make people less accurate whenestimating the quantity for a short, wide bowl and moreaccurate for a tall, thin bowl. Regardless of any such incidental effects, our focus is on how variety affects theabsolute level of perceived quantity, not the accuracy.

Empirical Studies
The first two studies follow the standard method in numerosity research of using simple random patterns. Study
1 shows that variety reduces the perceived quantity of items
using both different colored dots and different geometricshapes and that the effect does not change as the numberof types increases from two to five. Study 2 provides someinsights into the process as the effect disappears when theoverall area of the set is outlined by a shaded figure. Thissuggests that variety affects perceived quantity by making
the whole more salient.
After demonstrating the predicted perceptual effect in thestandard numerosity setup, two additional studies focus ona more interactive and pragmatic context. The pouring offood is used, since consumers need to do this nearly everyday. Study 3 shows that people unintentionally pour more
candy in a matching task when the candy has a variety ofcolors. This occurs even though people knew they could notconsume the candy. Study 4 rules out several alternative
explanations by manipulating variety in both the sample
candy serving and the poured candy. Process measures sug-

VARIETY AND PERCEIVED QUANTITY

409
FIGURE 2

gest that variety affects how much people pour through its
influence on perceived quantity.

SUBSET OF STIMULI USED IN STUDY 1

STUDY 1This study was designed to test whether variety decreases
the perceived quantity of items. People estimated the numberof items in random geometric patterns, making it easy toquickly gather a large number of estimates with experimental control. The simplicity of the task also reduces thenumber of possible explanations for any findings. This study
was also designed to test the generality of the predictedeffect, as items could differ in either color or shape, andthe number of different item types could vary from one to
five. This design eliminates alternative explanations uniqueto only colors or only shapes and also tests the predictionthat the effect depends on the presence of variety more than
the amount of variety.

MethodEighty participants estimated the quantity of items in 50
random patterns of colored dots or common shapes for $5
or undergraduate course credit. Participants saw each pattern
on a computer screen for 750 milliseconds and then answered, “What percentage of the box was filled in on thelast screen?” Patterns were presented for only a brief timeso that people could not count the items. “Percentage filled”
was chosen as the response measure since it reduces outlier
responses yet still correlates highly with direct estimates ofnumerosity (Goldstone 1993). Percentage filled also captures the notion that people often judge the quantity of items
by how much they fill a container or plate (Wansink 2004).
The pattern stimuli were created using a 5 # 2 # 5 full
factorial design on percentage filled (30%, 40%, 50%, 60%,70%), basis of variety (colored dots, geometrical shapes),and number of different types (1, 2, 3, 4, 5). Figure 2 showsa subset of the stimuli used. A pattern for each level ofpercentage filled was randomly generated within a 10 #10 square matrix and used throughout. Because there were
100 total squares in the matrix, the percentage filled equaled
the number of items, and the two can be used interchangeably. A wide range of percentage filled levels was used toenhance the ecological validity and generalizability of any
findings and to test for any systematic patterns in the estimates. For patterns containing dots, the color of each dot
could randomly be red, green, blue, orange, or black. For
patterns containing geometric figures, each shape could randomly be an unfilled circle, triangle, square, diamond, or 5pointed star. The particular colors or shapes used in a patternwere randomly chosen for counterbalancing purposes when
the number of different types was less than five. When presented on the computer screen, patterns appeared 5.5 inchestall with a black border around the perimeter and a lightgray border dividing each of the 100 individual squares
within the matrix. The presentation order of the 50 patterns
was randomly determined for each participant.

NOTE.—Color version available as an online enhancement.

Results
Table 1 reports the mean quantity estimates for each condition. Quantity estimates were analyzed using a repeatedmeasures ANOVA with the percentage filled, basis of variety, and number of different types as within-subject factors.
There were main effects for each of the three factors: percentage filled (F(4, 76) p 495.31, p ! .0001), basis of variety(F(1, 79) p 5.02, p ! .03), and number of types (F(4, 76)
p 31.19, p ! .0001). The analysis also found evidence of apercentage filled by number of types interaction (F(16, 64)
p 4.85, p ! .0001), a percentage filled by basis of variety
interaction (F(4, 76) p 7.27, p ! .0001), and the three-way
interaction (F(16, 64) p 2.15, p ! .02). The only factor in
the model failing to reach statistical significance was thebasis of variety by number of different types interaction(F(4, 76) p 2.12, p 1 .08). Given these results, we could
proceed with detailed contrasts to understand the nature of
the effects and test our predictions.
First, a planned contrast compared the mean estimates forpatterns with only one item type versus the mean of thosewith more than one item type. As predicted, people judged
a pattern to have more items when it had only one color or
shape versus multiple colors or shapes (M p 56.8 vs. 53.5;
F(1, 79) p 110.19, p ! .0001). The magnitude of this contrast did not differ for colored dots versus geometric shapes(F(1, 79) p 1.59, p 1 .21). The results support our core pre-

JOURNAL OF CONSUMER RESEARCH

410
TABLE 1
MEAN QUANTITY ESTIMATES IN STUDY 1
Actual%filled1 dot

2 dots3 dots4 dots5 dots1 shape

2 shapes

3 shapes

4 shapes

5 shapes

30
40
50
60
70
Overall

31.6
49.0
57.4
70.7
79.2
57.6

27.8
44.1
55.2
67.3
78.0
54.5

29.4
41.1
54.0
69.6
76.8
54.2

26.1
42.6
54.8
66.0
76.3
53.1

27.7
42.9
54.9
69.1
77.3
54.4

24.8
46.1
62.7
67.6
78.0
55.9

25.4
44.3
55.8
65.0
78.1
53.7

27.2
41.7
53.0
64.4
77.7
52.8

24.4
43.2
53.7
66.8
77.9
53.2

25.1
41.6
53.3
64.2
78.1
52.4

Number of different item types

diction that the presence of variety lowers the perceived
quantity.
Second, we tested our prediction that the perceived quantity would decline little with further variety. There was a
downward linear trend as a pattern went from having one
to five different types as shown in the bottom row of table
1 (1 to 5 linear trend, F(1, 79) p 63.79, p ! .0001). However, this trend disappeared when considering only the effectof adding further variety (2 to 5 linear trend, F(1, 79) p
2.62, p 1 .10). Perceived quantity also did not differ ( p 1.10) in five of the six possible pairwise comparisons between
patterns with two to five different item types. This patternof results was also replicated in a follow-up study that manipulated the number of colors in the varied condition fromtwo to five as a between-subjects factor. Variety lowered theperceived quantity in each treatment group (all p ! .01), but
this effect did not show a trend as the number of different
colors increased (F(1, 157) p 0.66, p 1 .41). It appears that,as predicted, variety has its biggest influence on quantity
perceptions when a set goes from having identical items tohaving some variety.
Third, we tested our prediction that the effect of variety
on perceive quantity would attenuate as a container approached being nearly empty or full. A test of the interactionof variety with percentage filled (as a linear trend on thedeviation from 50%) found that variety tended to have lesseffect on the estimated quantity as the pattern became more
empty or more full (F(1, 79) p 17.71, p ! .0001). However,this effect was qualified by the three-way interaction(F(1, 79) p 23.80, p ! .0001). In particular, variety and percentage filled interacted for the unfilled shapes (F(1, 79) p
50.81, p ! .0001) but not the colored dots (F(1, 79) p
0.04, p 1 .84). Thus, we find only partial support for our
prediction that percentage filled moderates the effect of variety on perceived quantity.
Finally, we performed some additional analyses to understand the nature of the other effects found in the ANOVA
model. For the main effect of percentage filled, not surprisingly, people gave larger estimates as the percentage
filled increased (linear trend, F(1, 79) p 1,952.94, p ! .01).
For the main effect of basis of variety, people gave larger
estimates when the items consisted of colored dots rather
than unfilled shapes (F(1, 79) p 5.02, p ! .03). However,since we also found a basis of variety by percentage filledinteraction, we performed separate ANOVAs at each levelof percentage filled. The dots seemed more numerous than
the shapes for 30% filled (F(1, 79) p 19.56, p ! .0001) and
60% filled (F(1, 79) p 13.55, p ! .001) but not at any otherlevel of percentage filled (all p 1 .52). Any effect of dots
versus shapes on perceived quantity seems fairly weak andinconsistent. Finally, given the three-way interaction, separate two-way ANOVAs were performed at each level ofpercentage filled. These analyses still found the contrast
supporting the primary prediction that variety lowered theapparent quantity ( p ! .05) at every level of percentage
filled except 70% (F(1, 79) p 3.10, p 1 .08). It is also notable that the effect remained whether people tended to underestimate the total as they did for the 30% patterns(M p 26.9 vs. 30; F(1, 79) p 64.96, p ! .0001) or overestimate the total as they did for the 70% patterns (M p
77.7 vs. 70; F(1, 79) p 405.22, p ! .0001). Across the many
results in the different analyses, the predictions were consistently supported.

Discussion
This study asked people to estimate the number of items
in a random pattern on a computer screen. As predicted, thepresence of variety lowered the perceived quantity of items.
This effect appeared whether the items differed in color or
shape. This is important because it eliminates any explanations that are unique to differences in a particular feature,such as color contrast. It also suggests that the predictedeffect is general in nature and sets may appear to have fewer
items whenever the items vary on any easily discriminatedfeature.
The perceived quantity in a set dropped with the mere
introduction of variety, yet changed little with additionalvariety. Homogeneity among items seems to have a special
ability to make a set appear more numerous by making thewhole more salient, which leads people to perceive a set tobe larger and to have greater quantity. Once variety breaks
up the overall form, the addition of more variety cannot
further break up the whole. Hence, the effect depends on
the absence of variety more than the extent of variety.
We found only partial support for our prediction that thiseffect would become smaller as the pattern became nearly
empty or nearly full. For unfilled shapes, the cue provided

VARIETY AND PERCEIVED QUANTITY
FIGURE 3
SAMPLE STIMULI IN STUDY 2

411

presence of this shaded figure should make the overall areaof the set salient even when the set has a variety of different
items. We predict that this will diminish the effect of variety
on perceived quantity as people will still find it easy to see
the whole in spite of variety.

Results

NOTE.—Color version available as an online enhancement.

by the utilization of the container attenuated the effect ofvariety on perceived quantity. People acted as if they anchored on 0% for nearly empty patterns and 100% for nearlyfull patterns and simply underadjusted in these cases. In contrast, whether the pattern was nearly empty or full did not
matter for the colored dots. It could be that colored dots createa more salient Gestalt than unfilled shapes that easily garnerattention even in the presence of other cues for quantity.
If the salience of the whole plays an important role, as
we propose, then outlining the set of items such that theoverall area is obvious and clearly demarcated should reduceor eliminate the variety effect. The next study tested thisprediction by manipulating whether the items in the set were
outlined as a salient intact group or not.

STUDY 2
MethodFifty-seven people completed this study in exchange foran entry into a $50 lottery. People estimated the quantityof items in 20 different patterns of red and blue dots eachpresented for 750 milliseconds using the procedure fromstudy 1. The pattern stimuli were created using a 5 #2 # 2 full factorial design on percentage filled (30%, 40%,
50%, 60%, 70%), number of different colors (single, multiple), and salience of the overall area (not highlighted, highlighted by a shaded figure). The pattern of dots for eachlevel of percentage filled was randomly generated within a
10 # 10 matrix and used throughout. The single color condition randomly used either all red or all blue dots. The
multiple color condition individually assigned each dot torandomly be either red or blue. The salience of the overall
area was manipulated by including a shaded figure that outlined the entire set of items (see samples in fig. 3). The

Table 2 reports the mean quantity estimates for each condition. The quantity estimates were analyzed using a repeated-measures ANOVA with the percentage filled, number of colors, and salience of the overall area as withinsubject factors. The analysis found statistically significant
main effects for the percentage filled (F(4, 53) p 370.91,
p ! .0001), number of colors (F(1, 56) p 15.12, p ! .001),
and salience of the overall area (F(1, 56) p 8.50, p ! .01).
There was also a two-way interaction between the numberof colors and the salience of the overall area (F(1, 56) p
5.86, p ! .02). None of the other factors reached statisticalsignificance (all p 1 .10). Detailed contrasts were used tounderstand the effects and to test our predictions.
Planned contrasts indicated that when the overall area was
not highlighted, people estimated that there were more items
when they were a single color versus multiple colors(F(1, 56) p 18.13, p ! .0001). This replicates the finding
from the previous study. More importantly, this effect ofvariety on perceived quantity was not present when theshaded figure highlighted the overall area of the set(F(1, 56) p 1.51, p 1 .22). In fact, as shown in the bottom
row of table 2, the nonhighlighted multiple color groupdeviated from the other three (all three pairwise contrasts
have p ! .0001). The special status of this condition waspredicted since it was the lone condition in which the area
Gestalt was broken up by variety and not reestablished withshading.
In contrast, the perceived quantity did not differ among
the single color groups (highlighted and unhighlighted) or
the highlighted multiple color group (all pairwise contrasts
have p 1 .22). This pattern of results suggests that having
items of a single color and making the overall area salient
contribute in a similar way to quantity perceptions. If thetwo had completely independent effects, then we would
expect an additive relationship. Instead, we find that making
the overall area more salient has little effect when all of the
TABLE 2MEAN QUANTITY ESTIMATES IN STUDY 2
Actual%filled
30
40
50
60
70
Overall

Overall area not highlighted

Overall area highlighted

Single color Multiple colors Single color Multiple colors
24.3
42.1
53.2
63.1
75.4
51.6

20.4
38.5
48.1
59.5
73.9
48.1

24.4
41.5
54.0
66.8
76.9
52.7

22.9
40.8
53.6
66.2
75.5
51.8

JOURNAL OF CONSUMER RESEARCH

412

items are the same color, and vice versa. We propose that
this happens because in both cases the critical underlying
effect is to make the whole salient.
We also analyzed whether the effect of variety on perceived quantity would diminish for nearly empty and nearlyfull patterns. After recoding the percentage filled as a linear
trend on the deviation from 50%, this factor did not interact
with the number of colors (F ! 1), the salience of the overall
area (F(1, 56) p 1.38, p 1 .24), or the full three-way interaction (F ! 1). Thus, as in study 1, the predicted effects
seemed robust regardless of how much the dots filled theircontainer.

Discussion
This study replicated the finding from the previous study
that variety lowers perceived quantity. It also helped us
better understand why this happens by linking this effect tothe perception of the whole. When a shaded figure highlighted the area occupied by the set, variety no longer had
an effect on perceived quantity. A set with its area highlighted, regardless of whether the items varied, had the same
perceived quantity as a set of identical items. This suggeststhat the area cue plays a critical role in the predicted effects.
If the whole has already been made salient by the context,
then adding variety has no effect on perceived quantity because it cannot break up the whole.
The next two studies extend the effect of variety on perceived quantity to the pouring of food, a task that is bothcommon and consequential. If variety lowers perceived
quantity estimates, then it should result in the pouring of
more food. (Note that these two measures are inversely related so the direction of any predicted effects will reverse.)
The final two studies did not allow consumption so that theeffects of variety on quantity perception could be separated
out from any effects that variety might exert on anticipatedsatiation. However, it is easy to imagine that people would
have consumed all of the servings they poured, as they doin other settings (Wansink 2004).
The generalization of the findings in the first two studies
to a pouring task should not be taken for granted. Pouring
food differs from the previous estimation task in several
ways: people are more active in their engagement with quantity, there is more time to deliberate, an explicit quantity
estimate is not required, the task is more familiar, and thearea cue may not be as obvious. In regards to this last point,
we suggest that when people pour food into a container(such as a bowl or plate), they typically judge the size ofthe serving while standing above the container. From thisbirds-eye perspective, the cross section of food could appear
much like the two-dimensional dot patterns used in the previous two studies. Hence, variety will affect perceived quantity when it breaks up the whole. The final two studies test
whether this prediction indeed generalizes to the pouring offood.

STUDY 3
MethodThis study examined how variety affects the quantity thatpeople judge is in a food sample. A matching task was used
to infer perceptions of quantity. Specifically, people poured
candy into a bowl until they thought it had the same amountas a sample bowl of candy. If variety decreases perceived
quantity, then people should create larger portions when they
pour candy of multiple colors. To control for the expectationthat variety makes consumption more enjoyable (Kahn andWansink 2004), people were told that they would not consume the candy and should only match the quantity of thesample they had been shown.
One hundred five participants completed this study for$5 of compensation or undergraduate course credit. As acover story, participants were told that this study examined
how quickly people pour servings of candy. So that everyone knew how much to pour, participants first were showna sample (52 grams) of brown M&M’s candies in a clear
plastic bowl (identical 6-inch-diameter plastic bowls wereused throughout the study). Once the participants indicatedthat they were ready to begin, the lab assistant removed thesample so participants could not use it as a reference in thesubsequent matching tasks. Participants were then given alarge, 32-ounce plastic cup containing 416 grams of brown
M&M’s and asked to pour the candy into an empty plastic
bowl until it matched the sample they had seen. While they
poured the candy, a lab assistant timed them with a stopwatch to support the cover story. This practice task allowed
people to get used to pouring from the cup and provided abaseline where the color poured matched the sample color(i.e., both brown).
After completing the practice task, participants were given
a new, 32-ounce plastic cup with 416 grams of M&M’s tocreate four more plastic bowls of candy with the same quantity as the sample. The candy in this cup was manipulated
between-subjects to be either a single color or an even mixture of three colors (red, green, blue). The particular color
given to a person in the single color condition was counterbalanced across the three different colors. The quantity
poured did not differ between any of the specific colors used(all p 1 .15), so the results were collapsed for reporting purposes. After participants finished pouring the last bowl, thelab assistant weighed the amount poured in the bowls.

Results
The primary dependent variable was the average amountof candy poured per bowl in grams. Before conducting theanalysis, the data were removed for one participant who
poured an amount more than four standard deviations fromthe mean. The results were analyzed using an ANCOVA
with the color of the candy (single color vs. mixed) poured
as a between-subjects factor and the amount poured in thepractice task as a covariate. The practice task covariate explained a decent amount of variance in the second pouring

VARIETY AND PERCEIVED QUANTITY

task (F(1, 99) p 50.95, p ! .0001). The results indicate thatpeople poured more when using mixed colors (M p 59.2
grams) than a single color (M p 53.0 grams). The planned
contrast was statistically significant (F(1, 99) p 4.00, p !
.05). This confirms that having variety leads people to pourmore candy, presumably because variety lowers the perceived quantity.
We also performed two additional analyses. First, we analyzed the pouring times using an ANCOVA with the treatment group as a between-subjects factor and the time takenin the practice task as a covariate. A planned contrast foundno difference between the single color and the multiple color
conditions (F(1, 99) p 0.14, p 1 .70). Second, we tested
whether it was easier to match the sample in one of theconditions to see if this could potentially account for the
results. We analyzed the unsigned deviations from the correct amount using an ANCOVA with the treatment groupas a between-subjects factor and the deviation in the practicetask as a covariate. A planned contrast did not find any
difference in accuracy between the single color and the multiple color conditions (F(1, 99) p 1.42, p 1 .23). Variety did
not affect the time required or the accuracy in pouring theservings in this study.

Discussion
This study extended the findings from the previous studies
to pouring food. People poured 12% more into a bowl when
the candy was multicolored. This effect occurred eventhough people knew that they could not consume the candyand everyone had been told to match the quantity with agiven sample. Thus, beyond any separate effects variety
might have on choosing an amount to consume, variety
caused people to pour more candy into a bowl. People did
this because variety presumably made them perceive thatthey had put less in the bowl so far.
Because this study tried to make the pouring task as natural and simple as possible, it had several limitations. First,
although people were told to match the sample quantity,
some may have ignored this goal. Although it is not clearthat ignoring accuracy would lead people to pour more when
the items had variety, we still ran a follow-up study that
had people pour the candy directly on a weighing scale (withthe readout covered) and found the same effects. Second,the current study did not provide any evidence that quantity
perceptions contributed to the effect, although it is unclear
what else people could be relying on in a matching task.
The next study will link explicit quantity estimates to themagnitude of the effects. Third, this study manipulated thevariety only in the items being poured and not the sample
serving. This allows for the possibility of several alternative
explanations, such as variety is more enjoyable to watch
while pouring or variety is more difficult because it is amismatch to the single color of the sample. The next study
manipulates the variety of both the sample items and thepoured items to rule out these alternative accounts. If greater
pleasure of pouring variety causes the effect, then adding
variety to the sample should have no effect on the quantity

413

poured. If greater difficulty of mismatched conditions causes
the effect, then the effect of pouring less with variety should
reverse if the sample has mixed colors instead of a single
color (i.e, an interaction). However, if our proposed process
underlies the effect, then having variety in the sample shouldhave only a main effect of making people pour less since
the quantity to match will seem like less.

STUDY 4
MethodSixty-four participants completed this study for undergraduate course credit. A matching task paradigm was employed similar to the previous study. Participants first wereshown a sample of M&M’s candy on a plate (identical 9inch-diameter plates were used throughout the study). Participants were then given a 32-ounce plastic cup with 400
grams of M&M’s and asked to pour the same amount as
the sample onto three other plates. The sample was thenhidden from view during the pouring task so it could not
be used as a reference. While participants created the threeplates of candy, a lab assistant timed them as part of thecover story of how quickly people pour servings. Participants repeated this matching task four times such that each
person poured a total of 12 plates of candy.
The four matching tasks followed a 2 # 2 full-factorial
design with the number of colors in the sample candy serving (one, four) and the number of colors in the candy poured(one, four) manipulated as within-subject factors. The four
different colors used were red, green, blue, and yellow. The
particular color used in the single color cases always stayed
the same for a given participant, but it varied across participants in a counterbalanced fashion across the four different
colors. The order of the tasks was also counterbalanced acrossparticipants such that each of the four combinations of themain factors appeared equally often as the first, second, third,
and fourth tasks using a Latin square design. Neither ofthese counterbalancing factors changed the conclusions fromthe statistical analyses, so they will not be discussed further.
After pouring the final plate of candy, participants estimated the quantity in each of the four samples of candy
they had been previously shown. With the sample withinview, they answered by stating the percentage of the plate
covered by the candy. We chose this measure instead of amore direct quantity estimate (e.g., grams) because a pretest
showed that people found it difficult to estimate candy quantities in grams. Participants were provided examples of 0%,50%, and 100% to make sure they understood the task. After
participants finished giving these quantity estimates, the lab
assistant weighed the amount that had been poured onto
each of the 12 plates.
We were concerned that participants might get suspicious
about the study’s purpose or blindly give the same percentage estimates if the samples were all exactly the same
size. Therefore, we varied the size of the sample serving tohave either 55 grams or 66 grams of candy. We felt confident
that this difference would be large enough that the samples

JOURNAL OF CONSUMER RESEARCH

414

would look different in spite of any predicted effects, giventhat 22% was nearly twice as large as the size of the effects
found in the previous study. The size of the sample wascounterbalanced such that each participant had two samples
with 55 grams and two samples with 66 grams as part of afractional design. In particular, everyone had a one-color
sample with 55 grams, a four-color sample with 55 grams,
a one-color sample with 66 grams, and a four-color sample
with 66 grams. Likewise, everyone poured with one color
for a 55-gram sample, with four colors for a 55-gram sample,
with one color for a 66-gram sample, and with four colors
for a 66-gram sample. This counterbalancing design ensured
that the total quantity in the samples across all the tasks wasequal between the two levels for each of the experimental
factors to facilitate direct comparisons.

Results
The dependent variable was the amount of candy poured
onto each of the 12 plates. Before conducting the analysis,
the data were removed for five poured plates that were morethan four standard deviations from the mean. Table 3 reports
the means for each condition. A repeated-measures ANOVA
was performed with the number of colors in the sample
candy, the number of colors in the poured candy, and thesize of the sample as within-subject factors. The analysis
found a main effect of the number of colors poured(F(1, 63) p 6.45, p ! .02), indicating that people poured
more when pouring multiple colors versus a single color.
People presumably perceived that they had poured less onto
the plate so far when it had a variety of colors, replicating
study 3. There was also the predicted main effect for thenumber of colors in the sample (F(1, 63) p 6.48, p ! .02),
whereby people poured less when matching a sample that
had multiple colors versus a single color. People did sopresumably because a sample appeared to have less quantity
when it had a variety of colors. These two main effects wereadditive, not multiplicative, as indicated by the lack of aninteraction between the two variety factors (F(1, 63) p
1.66, p 1 .20). The last two results argue against alternative
explanations based on enjoyment while pouring that would
not predict any effects for variety in the sample or a mismatch between the number of colors in the sample andpoured candy that would predict an interaction. The patternof results is instead consistent with our notion that a varietyof colors reduced perceived quantity whether in the sample
or the poured items.
The sample size and number of colors in the sample didinteract (F(1, 63) p 6.69, p ! .02), such that introducing variety into the sample candy did not decrease the amountpoured for the larger sample size of 66 grams. Although we
did not explicitly expect this interaction, a post hoc explanation is that the larger sample mostly covered the surfaceof the plate. People may have used this as a cue for quantity
instead of any Gestalt created by a single color, in line with
our hypothesis that container cues can attenuate the effectof variety on perceived quantity. There was also an expected
main effect of sample size such that people poured more when
given the larger sample (F(1, 63) p 81.94, p ! .0001). Noneof the other factors in the model reached statistical significance (all had p 1 .20).
We also tested to see if the effect changed as people
poured more bowls. When the number of bowls poured so
far was included in the model, neither the main effect nor
any of the interaction terms for this additional factor reachedsignificance (all p 1 .35). Experience with the task did notseem to matter. We also performed the original analysis
using other dependent variables. We instead used the unsigned deviation from the correct amount that was in thesample serving as the dependent variable. Neither of themain effects of variety nor their two-way interaction approached statistical significance (all p 1 .20 ). We finally used
the pouring time as the dependent variable. Again, neitherof the main effects of variety nor their two-way interaction
reached statistical significance (all p 1 .06). The presence ofa variety of colors appeared to have little effect on people’s
accuracy in pouring or the time required for pouring.
We also analyzed people’s quantity perceptions of how
much each sample filled the plate. Two particular results
provide evidence that quantity perceptions underlie the previous pouring findings. First, percentage filled estimates
were subjected to a repeated-measures ANOVA with thenumber of colors in the sample and the size of the sample
as within-subject factors. This analysis found a significant
main effect of the number of colors in the sample (F(1, 63)
p 5.05, p ! .03). This gives us direct evidence that people
estimated that a sample appeared to have more when it hada single color of candy (M p 49%) versus multiple colors(M p 46%). Second, we tested whether these percentage
filled estimates could help account for the pouring results.

TABLE 3
QUANTITY OF GRAMS POURED IN STUDY 4
Sample size of 55 grams

Poured color:
Single color
Multiple colors
Overall

Sample size of 66 grams

Single color

Multiple colors

Overall

Single color

Multiple colors

Overall

58.8
63.3
61.6

54.1
54.5
54.3

56.4
58.9
57.7

66.4
70.3
68.4

66.6
69.8
68.2

66.5
70.1
68.3

VARIETY AND PERCEIVED QUANTITY

Because we did not have quantity estimates for the bowls
actually poured, for each subject we used their sample perceived quantity estimates as a proxy for quantity perceptions. Specifically, we created an individual difference scorethat equaled mean percentage filled estimates for the singlecolored samples divided by mean percentage filled estimates
for all the samples. The latter adjustment accounts for thefact that some people generally had much larger quantity
estimates than others. Hence, as a person’s quantity estimates show the effects of variety more for the sample, they
will have a higher individual difference score, and we would
expect variety to have a greater effect on the quantity they
pour. We next reran the original model on the quantity poured
adding only this individual difference variable as a betweensubjects factor. There was a significant colors poured by individual difference score interaction (F(1, 62) p 4.23, p !
.05). This indicates that those people whose perceived quantity judgments were more influenced by variety tended topour an increased amount when pouring a variety of colors.
There was not a similar interaction between the number ofcolors in the sample candy and the individual difference
score (F(1, 62) p 2.30, p 1 .13). It is not obvious why wefail to find an effect here as we would expect people witha larger individual difference score to show a greater effectfrom introducing variety into the sample (though the results
were in the expected direction). Regardless, these analyses
provide some evidence that the effect of variety on quantity
poured is partially attributable to the effect of variety on
quantity perceptions.

Discussion
This study replicated the finding that people pour morein a matching task when pouring from a varied assortment.
It also extended the previous results in three important ways.
First, the effect is not limited to just the act of pouring. By
showing that the effect can also happen even when variety
is in the sample, it rules out several alternative explanations
such as enjoyment while pouring, misunderstanding that the
food could be consumed, and so forth. Second, this study
simultaneously manipulated the variety in both the sample
candy and the candy used for pouring. This two-factor design helped rule out any alternative explanation based on amatching account whereby it might be easier for people torecreate a sample when the number of colors in the candy
poured matched that in the sample serving. The results did
not find any support for the interactive effects predicted bya matching hypothesis. Third, this study linked the predictedeffects to quantity perceptions. People judged a sample tohave less when it had a variety of colors versus a single
color, and those people who showed this influence to agreater extent also tended to pour more candy when pouringwith a variety of colors versus a single color. This patternof results suggests that their quantity perceptions led people
to put more candy on a plate when pouring with a varietyof colors.

415

GENERAL DISCUSSION
The effects of variety on enjoyment and decision making
have been widely studied. This article complements thisresearch by asking how variety affects people’s perceptionof quantity. Four studies showed that having variety madepeople perceive that a set had fewer items. This documentsa perceptual influence that adds to both the variety and thenumerosity literatures. This article also identifies perceived
quantity as a potentially important construct for understanding how variety influences how much people consume. Variety seems to make people unknowingly pour larger servings. Given that people typically finish what they serve
themselves (Wansink 2004), the current findings have potential implications for how much people consume.
We propose that these effects occur because identicalitems naturally consolidate into a single whole, making theset seem to occupy a larger area. Because people especiallyrely on the area cue when making quantity judgments (Krueger 1972; Raghubir and Krishna 1996; Vos et al. 1988), a
set of identical items appears to have a greater quantity. The
studies provided some evidence to support this explanation.
The predicted influence appeared once a set had some items
that differed but did not further increase as the set had morevariety. This would be expected only if there is something
special about complete homogeneity, such as it could makethe whole more salient. The predicted influence disappeared
if the overall area was highlighted so it remained readily
apparent even when a set had variety. This suggests thathaving variety lowered perceived quantity largely throughits influence on the salience of the whole area. This explanation helps us understand not only the current findings but
also adds to our theoretical understanding of how people
judge the quantity in an assortment. In particular, it shows
the importance of Gestalt-type processes and the effect ofindividual item features on these processes. It also takes adifferent spin on Gestalt psychology in that the Gestalt has
an extra perceptual weight beyond the simple count of items.
The current studies found that having variety reduced
perceived quantity from 5% to 12%. The size of this effecttypifies those found in other quantity research (Goldstone
1993; Krider, Raghubir, and Krishna 2001; Krishna and Raghubir 1997; Raghubir and Krishna 1999). Although a 10%
effect may not seem that large, a person increasing their
daily diet of 2,000 calories by 10% could expect to gain 20
pounds after a year (Wansink 2006). Two studies show thatvariety leads people to unknowingly pour larger servings.
Future work should explore whether the same effects spontaneously appear in natural consumption settings. Given thelikely automatic and hard-wired nature of quantity perception, we expect that the effects will extend to portion sizes
and subsequent consumption.
Researchers could also consider how the current findings
might help explain other phenomena. Past work shows thatvariety increases consumption (Kahn and Wansink 2004;
Rolls, van Duijvenvoorde, and Rolls 1984). In addition to
any sensory-specific satiety or anticipated enjoyment, variety may increase consumption also because it leads people

416

to estimate smaller quantities and serving portions. People
will eat more from a varied assortment if they underestimate
how much they have already eaten (Raghubir and Krishna
1999; Wansink et al. 2005). Future work in this area should
consider designing studies that can parcel out any effects
due to perceived quantity. Likewise, future studies of variety
should also gather quantity estimates as a potential explanatory variable. It is important to understand the extent towhich quantity misperception might contribute to the overconsumption that can result from having variety.
The current studies focused on establishing the predictedeffects and identifying boundary conditions to provide insight into the process. Future work should test how theseresults depend on the conditions. For example, the effectmay increase when people do not explicitly focus on quantity as they were instructed to do in the current experimental
setting. Alternatively, variety may not affect perceived quantity when the items vary on a feature that people do not
automatically notice (e.g., small letters printed on M&M’scandies). There may similarly be no effect if nearly all theitems in a set are identical, such as when only a single item
differs from hundreds of others. It might also be interesting
to see how the effect depends on the extent to which thevarious items in a set are related (e.g., food items seen asa single meal versus a plate of varied snacks). Future work
should also explore when the results could reverse. It could
be that variety can increase the perceived quantity when an
explicit variety judgment is made before the quantity judgment because people anchor on the number of types andunderadjust. Likewise, people may also overrely on thenumber of types as a cue for quantity when recalling a pastamount because the perceptual whole of the Gestalt is notsalient compared to recalling the variety in the set.
We found some mixed evidence that the effect can attenuate when the container capacity can serve as a cue. Oncea set nearly fills its container, variety may have little effecton perceived quantity because people simply use the container capacity as a cue. The effect may similarly dependon the shape of the container or the arrangement of the itemsin the set. For example, nicer restaurants often add multiple
shapes and colors to create a richer presentation, which our
results suggest could create a misperception that they havesmaller portions (a seemingly common complaint). However, the effect of variety on the perceived quantity in a set
may diminish if the items are arranged along a dimension,
especially vertically, given that people tend to focus on theheight dimension more when making quantity judgments(Piaget 1968). In fact, the presence of variety might evenmake the whole more salient if a different type of item isused to create a border around the perimeter of the set.
Future work needs to determine how these and other factors
influence how people perceive the quantity of varied sets.
The findings in this area could potentially lead to clear recommendations for marketers in the areas of product packaging and retail presentation.

JOURNAL OF CONSUMER RESEARCHREFERENCES
Allik, Jüri and Tiia Tuulmets (1991), “Occupancy Model of Perceived Numerosity,” Perception and Psychophysics, 49 (4),303–14.
Ariely, Dan (2001), “Seeing Sets: Representation by Statistical
Properties,” Psychological Science, 12 (2), 157–62.
Binet, Alfred (1890), “La perception des longeurs et des nombreschez quelques petits enfants,” Revue philosophique de laFrance et de l’étranger, 30, 68–81.
Broniarczyk, Susan M., Wayne D. Hoyer, and Leigh McAlister(1998), “Consumers’ Perceptions of the Assortment Offeredin a Grocery Category: The Impact of Item Reduction,” Journal of Marketing Research, 35 (2), 166–76.
Chong, Sang Chul and Anne Treisman (2003), “Representation of
Statistical Properties,” Vision Research, 43, 393–404.
Dehaene, Stanislas (1992), “Varieties of Numerical Abilities,” Cognition, 44, 1–42.
——— (1997), The Number Sense: How the Mind Creates Mathematics, New York: Oxford University Press.
Enns, James T. and Alan Kingstone (1995), “Access to Global andLocal Properties in Visual Search for Compound Stimuli,”
Psychological Science, 6 (5), 283–91.
Folkes, Valerie and Shashi Matta (2004), “The Effect of Package
Shape on Consumers’ Judgments of Product Volume: Attention as a Mental Contaminant,” Journal of Consumer Research, 31 (2), 390–401.
Frick, Robert W. (1987), “The Homogeneity Effect in Counting,”
Perception and Psychophysics, 41 (1), 8–16.
Frith, Christopher D. and Uta Frith (1972), “The Solitaire Illusion:
An Illusion of Numerosity,” Perception and Psychophysics,
11 (6), 409–10.
Ginsburg, Norman (1978), “Perceived Numerosity, Item Arrangement, and Expectancy,” American Journal of Psychology, 91(2), 267–73.
Goldstone, Robert L. (1993), “Feature Distribution and Biased
Estimation of Visual Displays,” Journal of Experimental
Psychology: Human Perception and Performance, 19 (3),564–79.
Hsee, Christopher K. (1998), “Less Is Better: When Low-Value
Options Are Valued More Highly than High-Value Options,”
Journal of Behavioral Decision Making, 11 (2), 107–21.
Huang, Liqiang, Hal Pashler, and Anne Treisman (2006), “Can We
Select Two Colors Simultaneously?” Journal of Vision, 6 (6),1101a.
Kahn, Barbara E. and Brian Wansink (2004), “The Influence ofAssortment Structure on Perceived Variety and Consumption
Quantities,” Journal of Consumer Research, 30 (4), 519–33.
Kaufman, E. L., M. W. Lord, T. W. Reese, and J. Volkman (1949),“The Discrimination of Visual Number,” American Journalof Psychology, 62, 498–525.
Krider, Robert E., Priya Raghubir, and Aradhna Krishna (2001),“Pizzas: P or Square? Psychophysical Biases in Area Comparisons,” Marketing Science, 20 (4), 405–25.
Krishna, Aradhna and Priya Raghubir (1997), “The Effect of Line
Configuration on Perceived Numerosity of Dotted Lines,”
Memory and Cognition, 25 (4), 492–507.
Krueger, Lester E. (1972), “Perceived Numerosity,” Perception andPsychophysics, 11, 5–9.
Mandler, George and Billie Jo Shebo (1982), “Subitizing: An Analysis of Its Component Processes,” Journal of Experimental
Psychology: General, 111 (1), 1–22.
Mishra, Himanshu, Arul Mishra, and Dhananjay Nayakankuppam

VARIETY AND PERCEIVED QUANTITY(2006), “Money: A Bias for the Whole,” Journal of Consumer
Research, 32 (4), 541–49.
Palmer, Stephen E. (1982), “Symmetry, Transformation, and theStructure of Perceptual Systems,” in Organization and Representation in Perception, ed. Jacob Beck, Hillsdale, NJ: Erlbaum, 95–144.
Pelham, Brett W., Tin Tin Sumarta, and Laura Myaskovsky (1994),“The Easy Path from Many to Much: The Numerosity Heuristic,” Cognitive Psychology, 26 (2), 103–33.
Piaget, Jean (1968), “Quantification, Conservation, and Nativism,”
Science, 162, 976–79.
Piazza, Manuela, Veronique Izard, Philippe Pinel, Denis Le Bihan,
and Stanislas Dehaene (2004), “Tuning Curves for Approximate Numerosity in the Human Intraparietal Sulcas,” Neuron,
44 (October), 547–55.
Raghubir, Priya and Aradhna Krishna (1996), “As the Crow Flies:
Bias in Consumers’ Map-Based Distance Judgments,” Journal of Consumer Research, 23 (June), 26–39.
——— (1999), “Vital Dimensions in Volume Perception: Can the
Eye Fool the Stomach?” Journal of Marketing Research, 36(3), 313–26.
Rolls, Barbara J., P. M. van Duijvenvoorde, and Edmund T. Rolls

417(1984), “Pleasantness Changes and Food Intake in a Varied
Four-Course Meal,” Appetite, 5 (4), 337–48.
Schwarz, Norbert (2004), “Metacognitive Experiences in Consumer Judgment and Decision Making,” Journal of Consumer
Psychology, 14 (4), 332–48.
Vos, Piet G., Michiel P. van Oeffelen, Hein J. Tibosch, and Jüri
Allik (1988), “Interactions between Area and Numerosity,”
Psychological Research, 50, 148–54.
Wansink, Brian (2004), “Environmental Factors That Unknowingly
Increase Food Intake and Consumption,” Annual Review ofNutrition, 24, 341–78.
——— (2006), Mindless Eating, New York: Bantam Dell.
Wansink, Brian, James E. Painter, and Jill North (2005), “Bottomless Bowls: Why Visual Cues of Portion Size May Influence
Intake,” Obesity Research, 13 (1), 93–100.
Wansink, Brian and Koert van Ittersum (2003), “Bottoms Up! The
Influence of Elongation on Pouring and Consumption Volume,” Journal of Consumer Research, 30 (3), 455–63.
Wertheimer, Max (1938), “Laws of Organization in PerceptualForms,” in A Source Book of Gestalt Psychology, ed. Willis
D. Ellis, London: Routledge & Kegan Paul, 71–88.