The Role of Package Color in Consumer Purchase
Consideration and Choice
Lawrence L. Garber, Jr.
Raymond R. Burke
J. Morgan Jones
WORKING PAPER SERIES
WORKING PAPER • REPORT NO. 00-104 • 2000
This article is based on the first author’s dissertation research at the University of North Carolina at Chapel Hill. The authors would like to thank Jim Bettman, Joel
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Copyright © 2000 Lawrence L. Garber, Raymond R. Burke, and J. Morgan Jones
Report Summary # 00-104
The Role of Package Color
in Consumer Purchase
Consideration and Choice
Lawrence L. Garber, Jr., Raymond R. Burke, and J. Morgan Jones
To gain notice and consideration at the point of purchase, brands must break
through the clutter of competitive products and messages. Package color is a
critical, but often overlooked, tool to gain such notice.
Using a computerized grocery store simulation, this study investigates how the
color of a product’s packaging affects consumer choice. The authors predict that
the shopper’s likelihood of picking up and purchasing a product depends, in part,
on his or her ability to identify the brand, the meaning communicated by the
package, and the package’s novelty and contrast—all of which are affected by
Their results suggest that for shoppers who are not loyal to a particular brand, a
change in package color can enhance brand consideration. Further, in relatively
small and stable categories like raisins, flour, and spaghetti, the revised package was
more likely to be picked up and purchased when the meaning it conveyed was
consistent with the brand’s original positioning. In highly competitive categories
like cereal (where it is more difficult to attract shoppers’ attention), having a strik-
ingly different package was more important than consistency of meaning for
attracting customers’ interest.
On the other hand, the results suggest that if the brand has a large base of loyal
customers, it may be better to retain the original package or a minor variation, as
large changes may reduce brand identification and confuse existing customers.
The research also revealed that a change in package color can increase the total
amount of search in the category.
Lawrence L. Garber, Jr., is Assistant Professor of Marketing at the John A. Walker
College of Business, Appalachian State University. Raymond R. Burke is the E.W.
Kelley Professor of Business Administration at Indiana University’s Kelley School of
Business. J. Morgan Jones is Associate Professor of Operations Management/
Quantitative Methods at the Kenan-Flagler Business School, the University of North
1000 Massachusetts Avenue
Cambridge, MA 02138
Packaging and Brand Performance ....................................................................5
Creating a New Package....................................................................................6
Consideration and Choice.................................................................................9
The Role of Package Color..............................................................................10
The Selection of Product Categories................................................................17
Creating and Classifying the Package Manipulations.......................................18
Experimental Design and Procedure................................................................22
Results and Discussion.........................................................................................25
Packaging, Brand Consideration, and Purchase...............................................27
Packaging and Category Search.......................................................................31
Table 1. Summary Results with Respect to Hypotheses Tested........................25
Figure 1. A Model of Packaging’s Effect on Brand Attention and
Figure 2. The Hypothesized Effect of Visual Package Type on
Brand Purchase Consideration and Choice.................................................15
Figure 3. Perceived Similarity of Alternative Gold Medal
Figure 4. Attribute Associations for Alternative Gold Medal
Figure 5. Selected Gold Medal Package Variations for the
Figure 6. Computer Simulated Shelf Display for the Flour Category ..............23
Figure 7. Mean Category Viewing Time and Number of Brands
Picked up by Shopping Trip and Condition...............................................26
Figure 8. Proportion of Shopping Trips Where the Target Brand
Was Picked up and Purchased as a Function of Visual Package Type..........28
With the ongoing fragmentation of mass media, point-of-purchase promotion
plays an increasingly important role in the promotional mix. Managers know that
to successfully compete in the store, they must find ways to break through the
bewildering clutter of products and messages stridently offered by competitors. In
a world becoming not only more cluttered, but also more graphic in nature, a
brand’s package is an often-overlooked but critical tool to gain notice and
consideration. But what is an effective package? How can a package be designed or
modified to ignite the interest of new customers while continuing to leverage the
brand’s existing equity?
Consider the case a few years ago when a spate of “clear” products were intro-
duced; from household cleaners to personal care items such as deodorants, to
beverages such as beers and colas. There was even a clear car degreaser! The fad was
started when Procter & Gamble changed Ivory Dishwashing Liquid’s characteristic
translucent white container and milky white fluid to a clear liquid in a clear bottle,
with good results. This prompted several other manufacturers to launch clear prod-
ucts in order to capitalize on this new look: success was seemingly assured by
Ivory’s pioneering example. Yet many of these products did not succeed; Miller
Clear Beer and Crystal Pepsi (a clear cola) were both withdrawn from the market,
while Windex clear window cleaner returned to its original blue color.
What went wrong? Managers overlooked the fact that the sales impact of a new
package depends not only on the novelty of its appearance, but also on how that
appearance interacts with the established equity of the brand, its product category,
and consumers’ expectations of the category.
In this paper, we introduce a new approach for addressing the package design issue.
Specifically, we: (1) present a theoretical framework which identifies the main fac-
tors that determine consumer response to a package change, (2) provide a method-
ology that allows the researcher to decompose and estimate the effects of each of
these factors, and (3) provide an empirical test of the framework’s predictions.
While the framework is applicable to all aspects of a package’s appearance, we
chose to focus on package color for several reasons. First, color is a major element
of a product’s package; one that is particularly salient because it is vivid, affect-
loaded, and memorable (cf. Cheskin 1957, p. 80). Second, a package’s color can
have a substantial effect on consumers’ ability to recognize the brand, the meaning
conveyed by the package, and its novelty and contrast relative to other brands and
consumers’ expectations. Furthermore, package color can be altered without
changing the cost, handling characteristics, and functionality of the product
(unlike other package attributes, such as size and shape).
Finally, there has been very little research on the effects of package color on
consumer choice. Most of the marketing research on color has focused on store
atmosphere and print advertising. With respect to store design, Bellizzi, Crowley,
and Hasty (1983) and Bellizzi and Hite (1992) test consumers’ color preferences
for retail store designs and find that blue is soothing and preferred while red is
arousing and less well liked. Several studies have compared the effectiveness of
color versus black-and-white print media. Sparkman and Austin (1980) find that
color ads sell more than black-and-white ads. Click and Stempel (1976) report that
newspaper readers prefer the front pages of newspapers with color. Meyers-Levy
and Peracchio (1995) demonstrate that black-and-white print ads have greater
impact than color ads when consumers have limited cognitive resources. Schindler
(1986) points out that the use of color in an ad can sacrifice contrast, reducing
legibility and readability. Gorn et al. (1997) analyze the effects of color in print ads
on consumer arousal, affect, and recall by breaking color into its constituent ele-
ments: hue, chroma, and value. They extend the notion that red is exciting by
noting that any highly saturated color can be arousing.
Packaging and Brand Performance
Roughly two-thirds of American shoppers make their brand selections at the point
of purchase (POPAI 1978). Within this context, product packaging can have a
substantial impact on consumer decision making (Raphael 1969). The package can
attract the consumer’s attention, communicate a brand’s name and image,
differentiate the brand from competitors, and enhance the product’s functionality,
thus contributing to the brand’s overall sales and profitability (cf. Prone 1993).
In recent years, packaging has played an expanded role in brand marketing. With
the growth of self-service retail outlets, including mass merchandise stores, dis-
count stores, warehouse clubs, supermarkets, and supercenters, merchants have
come to depend on product packaging to sell their goods. Hine (1996, p. 2) notes,
“Historically, packages are what made self-service retailing possible, and in turn
such stores increased the number and variety of items people buy.” He suggests
that, today, the package has largely replaced the salesperson as the primary means
of communicating with customers at the point of purchase. Packaging is especially
important when shoppers have little or no prior knowledge of a category or brand,
a common occurrence given the high frequency of new brand introductions,
extensions, repositionings, product changes, and improvements (16,000 a year,
according to Kotler and Armstrong ). For new or infrequently purchased
products, the package may be the only source of information about the brands
Consumers also appreciate the aesthetic value of a package as an inherently
enjoyable part of the shopping experience (Hirschman and Holbrook 1982). Such
feelings can translate into brand preference and choice. Moreover, these and other
forms of commercial images have become a significant part of our visual environ-
ment and culture. On the basis of these images, brands are seen and valued as an
expression of people’s lives and times (Belk 1988).
Manufacturers have recognized the strategic importance of packaging. In mature
product categories, the number of brands is increasing while actual brand perfor-
mance is approaching parity, with most brands being perceived as generally satis-
factory (BBDO 1987). Thus, marketers must increasingly rely on the augmented
product (including a product’s package) to differentiate their brands (Neal 1993).
The package design, as an integrated element of the promotional mix, is also an
important carrier of brand equity into the store (Aaker and Biel 1993). For exam-
ple, the curved shape of the Coca-Cola bottle has been made famous through years
of advertising and promotion. It communicates the Coke equity at the point of
purchase and at the time of consumption. When Coke employed the contour
shape in its 20-ounce plastic bottle, it experienced sales volume increases approach-
ing 45 percent in the United States (Jabbonsky 1995). Coca-Cola has recently
added a picture of its green contour bottle to its cans, again attempting to leverage
the equity communicated by the original packaging.
Creating a New Package
Given the potentially powerful influence of packaging on consumer behavior,
managers are now looking beyond the traditional communication tools of advertis-
ing and promotion and focusing on packaging as a way to keep their brands fresh,
contemporary, and popular. But how should a company change the look of its
brands in order to increase their on-shelf impact and appeal? Three factors must be
considered: (1) brand identification, (2) package comprehension, and (3) package
novelty and contrast.
Brand identification refers to the consumer’s ability to recognize and uniquely
identify a package as belonging to a particular brand. Certain characteristics of the
package, such as the brand name, its logo, color, package shape, typestyle, and
graphics, may be used for identification. For example, the curved shape of a Coke
bottle and the pink color of Corning fiberglass are each unique and familiar brand
cues for most consumers.
When changing a product’s package, a brand should retain those elements that are
used by its current customers for brand identification.1If these elements are modi-
fied, then customers will have difficulty locating the brand, reducing the probabili-
ty of purchase. For example, a major shampoo manufacturer changed the distinc-
tive curved shape of its brand’s bottle to a rounded rectangle in order to improve
shipping, handling, and stocking efficiencies. As a consequence, sales dropped. The
company confused its existing customers, turning a routine purchase into an exten-
sive search process that increased the level of brand switching. Another manufac-
turer observed the same, disappointing result when it changed its familiar red soup
can to green. One way to avoid this problem is to change the package gradually so
that customers have an opportunity to learn the new package elements. The appro-
priate rate of change will depend on the product’s repurchase cycle.
If a brand is new and unfamiliar to consumers, or it has a very small share, then
the manufacturer is not constrained by the previous look of the package. Yet brand
identification is still an issue. One approach is to select a unique and memorable
brand name and package that will serve as the foundation for building a distinctive
brand image through advertising and promotion. An alternative strategy is to copy
the salient elements of the leading brand’s packaging. While this is a powerful
method for gaining notice and consideration (and is frequently used by private
label products), it may also lead to brand confusion and litigation.
Package comprehension refers to the meaning that a product’s package conveys to
the customer. A package communicates through explicit claims and illustrations
that describe a product’s attributes, benefits, ingredients, and promotional offers. It
also communicates implicitly by triggering associations in consumer memory.
Visual, verbal, and tactile elements of the package (such as the brand name and
logo, package size, shape, color, texture, and graphics2) can bring to mind images
of product quality, performance characteristics, usage situations, and past con-
sumption experiences. Consumers’ mental associations are the result of idiosyncrat-
ic personal experiences, as well as the past marketing activities (including advertis-
ing and promotion) of the product’s manufacturer and its competitors. Over the
years, category-specific packaging norms develop. For example, in bar soap, the
color pink has come to mean that a product has cosmetic and conditioning bene-
fits while green suggests deodorizing qualities; in liquid soap, an orange-pink color
communicates antibacterial properties; in dishwashing liquid, yellow suggests a
lemon scent, green means gentleness, and blue conveys grease-cutting benefits.
When designing a new package, a manufacturer can borrow on the visual conven-
tions established by existing brands in the category. For example, a new dishwash-
ing liquid may use a green package similar to Palmolive to communicate gentle-
ness. This approach has the virtue of reassuring the shopper by fulfilling expecta-
tions of what a brand in the category should look like; thus providing a measure of
legitimacy and credibility (Dichter 1975). Consistent with this, Loken and Ward
(1990) report that consumers prefer products which tend to match their expecta-
tions. Another approach is to bring new concepts and imagery into the category.
The use of a well-chosen visual metaphor can capture, through association, desir-
able values associated with a brand (King 1989). For example, Gateway was the
first company to use the black-and-white cow pattern on its packaging in order to
communicate its South Dakota heritage and spur the interest of family buyers. The
strength and concreteness of positive associations increase the likelihood that the
brand will be considered for purchase.
Both brand identification and package comprehension have been discussed as
elements of brand equity (Biel 1993). Brand equity has generally been defined as
the added value endowed by the brand to the product (Farquhar 1989), and con-
sists of the brand’s recognition and familiarity to the consumer, as well as the
image associated with the brand (Agarwal and Rao 1996; Keller 1993; Park and
Srinivasan 1994). Packaging can either enhance or diminish this equity by facilitat-
ing or inhibiting brand identification and the retrieval of positive brand associa-
Package novelty and contrast refer to the package’s ability to stand out visually from
its surroundings, to draw attention to itself through its novel appearance. Novelty
and contrast are defined in relative rather than absolute terms. They are a function
of both a package’s distinctiveness relative to the other brands on the store shelf
(Veryzer and Hutchinson 1998), and its departure from consumer expectations
based on past shopping and consumption experiences. Take, for example, the
bright red package of Lifebuoy soap. We cannot say that the package is vivid and
attention-getting simply because of its color. The red package may not attract
attention because it has been seen hundreds of times before or because it is viewed
in the context of other red packages. If the Lifebuoy product were placed on a
shelf next to Lava soap in its red package, this would diminish the contrast
between Lifebuoy and its surroundings. In this particular instance, Lifebuoy would
be more noticeable if it was green (red’s complement), both because it is a change
from the original color and because it is different from the adjacent competitive
products (even though the color red may, in absolute terms, be more visible to the
A fourth factor, package function, also affects how customers respond to a product.
A package provides several practical benefits. As Hine (1996, p. 6) notes, “It
protects its contents from contamination and spoilage. It makes it easier to trans-
port and store goods. It provides uniform measuring of contents.” In many
instances, manufacturers have been able to improve the performance of their
brands by developing packaging innovations. These include lightweight plastic bot-
tles, shelf-stable aseptic packaging, individual serving sizes, childproof caps, and
no-drip spouts. Packaging can also be designed to reduce cost or waste. Because
the focus of this paper is on package appearance rather than function, an attempt
is made to hold the utility of product packaging constant throughout the experi-
The three goals of brand identification, package comprehension, and novelty/con-
trast can be conflicting. For example, let’s assume that a manager selects a new
package for an existing brand that is very similar to the original. Because the old
and new packages match on key visual attributes, the loyal user can easily locate
and identify the brand. Continuity of comprehension and purchase are main-
tained, as the consumer is able to generalize all the brand meaning associated with
the former package to the new package. However, in selecting such a visually con-
ventional repackaging strategy, the manager loses the opportunity to present an
altogether new and exciting look that will attract the attention of new customers.
On the other hand, if the package is very dissimilar to what came before, the
brand risks confusing its existing customers and conveying an image that conflicts
with its established equity.
In the next section, we will present a theoretical framework that suggests how these
two respective strategies may affect the consumer’s choice process. We will then
describe a method of identifying which of several visual types a given package
candidate belongs to, and an approach for predicting its success.
Consideration and Choice
For both frequently purchased nondurable goods (like soft drinks and cereal) and
infrequently purchased durable products (like computers, automobiles, and hous-
es), shoppers are faced with a tremendous variety of options. To cope with this
complexity, consumers often restrict their purchase decisions to a subset of the
available alternatives and then select a preferred brand from this subset. This con-
cept—the “evoked set”—was introduced by John Howard in 1963 and later incor-
porated into the Howard and Sheth (1969) model of consumer behavior.
Subsequent authors have alternatively called this the “consideration set” and have
offered several operational definitions. Roberts (1989) defined it as “the brands
which a consumer would evaluate.” Roberts and Lattin (1991) described it as “the
brands that a consumer would consider in the near future.” Shocker, Ben-Akiva,
Boccara, and Nedungadi (1991) referred to the consideration set as “those goal-sat-
isfying alternatives salient or accessible on a particular occasion.” And Nedungadi
(1990, p. 264) defined it as “the set of brands brought to mind on a particular
The evoked set was originally conceived to be a relatively static selection of
acceptable brands which the consumer would consider buying on any given
shopping occasion (Howard and Sheth 1969; Narayana and Markin 1975). Its size
depended on generally stable factors, such as the cost of searching for product
information (Shugan 1980; Stigler 1961) and the overall levels of advertising and
promotional spending in the product category (Hauser and Wernerfelt 1990).
More recent research has emphasized the dynamic and context-dependent aspects
of consideration set formation, and has sought to identify the marketing factors
that determine set membership.
The composition of the consideration set is a function of both personal and
situational factors and the interaction between them. A consumer is more likely to
consider a brand that he or she can readily recognize or recall as a result of a
recent, favorable consumption experience (cf. Wright 1975) or direct or incidental
exposure to advertising for that brand (Shapiro, MacInnis, and Heckler 1997) or
another brand in the same subcategory (Nedungadi 1990). Consumers will give
greater consideration to brands that they perceive to be personally relevant (Celsi
and Olson 1988), and that offer satisfactory performance on key attributes (Lussier
and Olshavsky 1979; Payne 1976). Once shoppers enter the store, they are more
likely to consider brands that are highlighted by end-of-aisle displays, feature
advertising (Allenby and Ginter 1995), promotions (Siddarth, Bucklin, and
Morrison 1995), merchandising (Inman, McAlister, and Hoyer 1990), and favor-
able shelf position (Hoch, Dréze, and Purk 1994).
The factors that drive consideration may be different from those that determine
brand evaluation (Nedungadi 1990; also see the discussion by Siddarth, Bucklin,
and Morrison 1995). A brand may offer desirable features, but, because of its
recent entry to the market, small share, or lack of merchandising, may not be
considered. On the other hand, a leading brand may have a high share because it is
considered more often than competitors (perhaps because of early entry into the
category), even though it is not strongly preferred.
The Role of Package Color
Given the importance of visual search in cluttered and time-constrained environ-
ments, one would expect that package appearance would play an important role in
the formation of brand consideration sets (cf. Pieters, Warlop, and Hartog 1997).
Unfortunately, past research on product appearance and package design has fre-
quently sidestepped the consideration issue by forcing customers to attend to and
evaluate product packages (e.g., Durgee and O’Connor 1994; Schoormans and
Robben 1996; Veryzer and Hutchinson 1998). While this may be realistic for
some high involvement decisions where consumers carefully evaluate each available
brand, it does not represent most retail shopping situations. As Alba, Hutchinson,
and Lynch (1991, p. 3) note, “Motivation levels are usually too low and time too
scarce for consumers to scan all brands displayed in a given product category.”
Consider the shopping process in a typical supermarket. Consumers are faced with
tens of thousands of different products and must make a large number of selec-
tions in a relatively short period of time. To cope with this task, consumers are
selective in acquiring category and brand information. In a study by Marsh
Supermarkets, category penetration ranged from a low of 5 to 25 percent for
general merchandise, health and beauty care, and flowers, to a high of 60 percent
for the meat department (Burke 1995). In a field study of consumer purchases of
laundry detergent, Hoyer (1984) found that the median time per purchase
decision was 8.5 seconds (including the time taken to walk down the grocery
aisle). Few consumers examined more than one brand: only 28 percent of the
sample looked at, and 17 percent picked up, two or more brands. Dickson and
Sawyer (1990) found that, for coffee, toothpaste, margarine, and cold cereal, the
mean category shopping time was less than 12 seconds, with 42 percent of shop-
pers spending 5 seconds or less. Shoppers examined an average of 1.2 brands.
Burke (1995) reported that, during a typical stock-up shopping trip, customers
purchased an average of 48 different items in just 39 minutes.
To encompass the several, diverse roles that package appearance in general and
package color in particular can play in consideration and choice, we adopt and
extend the theoretical framework developed by Roberts (1989). Roberts (1989,
p. 749) casts choice as a phased process consisting of three, sequential stages: “The
probability of brand choice (given category purchase) can be thought to have three
elements: the probability of being aware of brand j; the probability of considering
brand j, given awareness of it; and the probability of choosing brand j, given
awareness and consideration.” This framework forms the backbone of the extended
model shown in Figure 1.3
Figure 1. A Model of Packaging’s Effect on Brand Attention and Package Consideration
As illustrated in Figure 1, consumers proceed through a series of stages when
identifying and evaluating brands for purchase. Package color can have an impact at
several stages in this process (Garber, Hyatt, and Starr 2000). In most retail stores,
similar products (i.e., items sharing the same physical characteristics and/or satisfy-
ing the same consumer need) are grouped together in product categories. At the
first stage (Stage 0), consumers enter the store with a set of goals4and attempt to
identify product categories that satisfy their requirements. As the consumer walks
through the store, one or more product categories come into view. From this van-
tage point, the shopper can resolve only the largest physical and graphical features
of the products. However, the information is sufficient to allow the individual to
identify relevant and desired product categories and to set a course down the aisle.
When the consumer has located and entered a relevant category, he or she attends
to one or more brands on the shelf (Stage I). The consumer’s likelihood of attend-
ing to a brand is a joint function of his or her ability to identify the brand as a
familiar and desirable product, and the perceived novelty and contrast of the pack-
age. Consumers are most likely to attend to those brands which they can readily
identify as a result of prior advertising exposure, purchase and/or consumption,
and those brands which stand out from the competitive clutter because of their
new and different appearance.
Once the consumer attends to a selection of products on the shelf, he or she con-
siders a subset of these brands for purchase (Stage II). At this point, the shopper
may pick up one or more brands to acquire detailed information from the package.
Information acquisition occurs in gradations or stages, with earlier processing
limited to the coarser visual features such as size, shape, and color, and later stages
focusing on detailed brand information. The number of brands the shopper con-
siders depends on his or her motivation and ability to process product information
Stage 0 Stage I Stage II Stage III
Category Attention Brand Attention Brand Consideration Brand Choice
(attend to category i) P
(attend to brand ij) P
(consider brand ij) P
(choose brand ij)
and the amount of time available. More brands will be considered if the shopper is
new to the category, seeks variety, notices something new or different on the shelf,
and/or has a liberal time budget.
In the final decision step (Stage III), the consumer selects one or more brands from
the consideration set for purchase. This choice process has been discussed in detail
in prior research (e.g., Bettman, Johnson, and Payne 1991; Meyer and Kahn 1991)
and will not be reviewed again here. However, we should note that package factors
that increase consumer attention to and consideration of brands are also likely to
increase the probability of choice, everything else being equal. Brand attention and
consideration are necessary but not sufficient conditions for choice.
In the following discussion, we examine how the appearance of a brand’s package
affects the consumer’s likelihood of attending to, considering, and purchasing a
brand (stages I, II, and III).5We focus on the direct effects of a package color
change on brand identification, perceived novelty and contrast, and package
comprehension, as well as the interactions with consumer’s goals and expectations
and the competitive environment.
Brand Identification. The grocery shopping task may be framed as a process
whereby the consumer searches through a visual field comprised of an array of
competitor products (distractors) in order to find some preferred brand or brands
(target) matching his or her goals and expectations. This is analogous to the speed-
ed identification task that is often used in studies of attention, visual perception,
and object identification (see Yantis and Hillstrom 1994). A subject is asked to
locate some target object, usually a number or letter, which is “embedded” in a
field of characters.
Most current models of visual search are based on Feature Integration Theory
(Treisman 1991; Treisman and Gelade 1980), which portrays the identification
process as consisting of two stages. In the first stage, individual features of the
objects, including their size, shape, and color, are seen spontaneously across the
entire visual field. In a subsequent step, these features are integrated into overall
representations of the objects, a process requiring focused visual attention.
Early psychophysical experiments indicated that when the target is defined by a
single feature or a disjunctive set of features, the visual display can be searched in
parallel and at a high rate of speed (Treisman and Gelade 1980). That is, when a
target has one or more unique features, it can be correctly identified in approxi-
mately the same amount of time regardless of the number of distractors. When the
target consists of a conjunctive feature set (i.e., the specific combination of features
is unique to the target, but the individual features are not), then the visual field is
searched using a slower, serial process. Therefore, one would predict that consumers
would be fastest at identifying packages that are uniquely identified by a single
feature (such as a distinctive color or shape) rather than a conjunction of features.
More recent research suggests that people can search in parallel for patterns defined
by conjunctive feature sets when they have certain “emergent properties.” In some
cases, these properties seem to be programmed into the human perceptual system,
such as shape from shading or shadows (Aks and Enns 1992; Kleffner and
Ramachandran 1992) or perceptual groupings (Bravo and Blake 1990; Duncan
and Humphreys 1989). In other cases, they are learned through frequent and/or
recent exposure to the target stimulus. Lindsay and Lindsay (1966) and Hayes-
Roth (1977) contend that frequently occurring patterns eventually form unitary
cognitions that are recognized as a whole, without being analyzed at the individual
feature level. Research indicates that people can identify these well-learned feature
sets quickly and effortlessly (Chase and Simon 1973; Schneider and Shiffrin
1977). Concept priming studies reveal that propositions are verified faster when
they are immediately preceded (i.e., “primed”) by verification of other propositions
involving some of the same information (e.g., Collins and Quillian 1970; Hayes-
Roth and Hayes-Roth 1975).
This research suggests that when a manufacturer revises a product’s package, it will
be most readily perceived and identified by shoppers when (a) it shares many fea-
tures (e.g., color, shape, typestyle, illustration) with the original packaging, (b) the
features of the original package were well learned,6(c) the features are primed by
consumers’ goals and expectations, and (d) the features are distinctive relative to
A package that is easily identified may also be perceived as more familiar and
typical of the category, which can increase purchase consideration (Johnson and
Lehmann 1997) and preference (Loken and Ward 1990). From a behavioral
learning theory perspective, brand-identifying package elements are seen to act as
discriminative stimuli for repeat buying (Foxall 1990, pp.73, 88). The degree to
which consumers generalize their response from the original package to a new
package depends on the similarity of the two packages (cf. Spence 1936). The
closer the two packages are to each other in a multidimensional similarity space,
the higher the level of generalization (Shepard 1987).
We therefore hypothesize:
H1: A new package whose color is very similar to a brand’s original packaging is
more easily identified and familiar, and is therefore more likely to be con-
sidered for purchase than a package whose color is moderately dissimilar.
Package Novelty and Contrast. During the visual search process, consumers may
encounter packages that are strikingly different from their expectations and from
the packages of competitors. The novelty of a package relative to consumers’
expectations and its contrast relative to the competitive context will increase the
likelihood that the package will evoke an involuntary attentional response
(Kahneman 1973). In his adaptation-level theory, Helson (1964) suggested that
people learn to associate a stimulus set with a reference point or adaptation level,
defined in terms of contextual stimuli (background) and residual stimuli (past
experience). Attention is created when an object differs markedly from that level.
Pribram and McGuinness (1975) find physiological evidence that, when there is a
mismatch between the stimulus input and an expected pattern, there is an
There is support in the empirical aesthetics literature (Berlyne 1960, 1974), the
attention literature (Kahneman 1973), and the psychology of visual perception
literature (Bruce and Green 1992) for a positive relationship between novelty and
preference. Schema theory suggests that consumers prefer moderate levels of incon-
gruity (Meyers-Levy and Tybout 1989; Mandler 1982), which can be created by
new or different packaging. Similarly, Dichter (1975) argues that marketers can
play on consumers’ affinity for surprise by presenting packages that are visually
dissimilar, unfamiliar, and unexpected.
This leads us to hypothesize:
H2: A new package whose color is very dissimilar to a brand’s original package
color will attract the customer’s attention and is therefore more likely to be
considered for purchase than a package whose color is moderately dissimilar.
The relative importance of brand identification and package novelty and contrast
depend on the extent to which consumers are open to acquiring new information
at the point of purchase. If a high percentage of shoppers enter the store planning
to purchase a specific familiar brand, then a novel package may interfere with
brand identification, as predicted by H1. However, if customers have broadly-
defined goals and are searching for variety, then brand identification will be less
important, and novelty and contrast will have a positive effect, consistent with H2.
Package Comprehension. Once the consumer’s attention is drawn to a select group
of packages, he or she actively and sequentially considers a subset of these brands
for purchase (Stage II). Whether the individual considers a specific brand depends,
in part, on the meaning communicated by the package. This meaning is largely a
function of the package’s appearance, including both textual and visual informa-
tion. However, it is also affected by consumers’ goals and expectations and the
competitive context. As Bransford, Nitsch, and Franks (1977, p. 46) note, “‘mean-
ings’ cannot simply be construed as ‘things’ that are stored as particular entities.
Instead meaning appears to be better conceptualized as a momentary place or pat-
tern in a changing relation, structure or framework.”
Customers will recognize some brands as being on their current shopping lists or
as items they routinely purchase, and will include these in their consideration sets.
This step often translates directly into choice, as hurried shoppers attempt to
minimize the amount of time they spend in the store.
If customers are motivated to consider other brands, they will screen through the
(noticed) alternatives based on the perceived match between the products’ charac-
teristics and their salient goals and expectations. If they encounter a familiar brand
with a new and different package, they must ask themselves whether this is the
same product that they have seen advertised, purchased, and/or consumed in the
past. Is their knowledge of the product still relevant? If the image communicated
by the new package is consistent with the brand’s original positioning, then the
equity associated with the brand will transfer to the new package, enhancing the
likelihood of brand consideration and choice. If the new package conflicts with
shoppers’ expectations, then they are likely to reject the new package.
This parallels the situation where consumers encounter a well-known brand name
that has been extended into a new product category. The success of the brand
extension depends on the degree of “brand congruity” (Keller 1993), “perceptual
fit” (Tauber 1988) or “relatedness” (Dacin and Smith 1994) between the parent
brand’s positioning and the new extension. Consumers are more likely to purchase
a brand extension if it is consistent with, and leverages, the existing brand’s equity.
The importance of consistency of meaning is illustrated by reference to the clear
product example cited in the introduction. As noted previously, some of the new
clear products succeeded while others did not. Informal consumer research
revealed that Ivory Liquid’s clear package (a success) reinforced the brand’s tradi-
tional positioning on the attributes of mildness and purity, while the clear Windex
package (a failure) connoted that the product was watery and weak, which con-
flicted with the brand’s equity.
We therefore predict:
H3: When comparing two new packages, both of which are very dissimilar in
color to a brand’s original packaging, the package that conveys meaning
which is consistent with the brand’s original positioning is more likely to
be considered for purchase than the package that conveys meaning which
In summary, we expect that when the color of an existing brand’s package is changed,
consumers will be most likely to consider the brand if the package is very similar to
the original package (because it is familiar and easy to identify) or strikingly different
(due to its novelty). In the latter case, consumers will be most likely to consider the
brand if the novel package communicates an image that is consistent with the brand’s
original positioning.8The first three hypotheses are presented graphically in Figure 2.
Figure 2.The Hypothesized Effect of Visual Package Type on Brand Purchase Consideration
Very Similar Moderately Similar Very Dissimilar
Visual Package Type
Additional Effects of a Package Change. When a manufacturer makes a major
change to a product’s package, it can disrupt routine processing in the product
category, increasing consumers’ attention to both the changed package and com-
petitors’ products. Consistent with this point, Bettman (1979, pp. 86-7) argues,
“Disagreement between what was perceived and what was expected seems to be a
particularly important cause of interrupts. . . . One important type of goal change
in reaction to a conflict interrupt event may be to set up a goal for information
search.” More recently, Nedungadi (1990, p. 264) notes that a brand’s marketing
activities can stimulate the consideration of competitive products. As an example,
he states, “Advertising cues that help the consumer retrieve and consider a target
brand could simultaneously increase the likelihood of considering other competi-
tors. If the consumer prefers any of these competing brands, the target brand may
not be chosen.”
We expect that a package change will increase the total amount of information
processing in the product category, causing shoppers to spend more time in the
category and pick up more packages.
H4: A new package that is very dissimilar in color to a brand’s original packag-
ing will disrupt routine processing in the category and increase the total
amount of time spent in the category and the number of packages picked
up, irrespective of the meaning displayed by the new package.
While a change in a product’s package can have a positive impact on consumer
attention, we would expect this effect to be short-lived as consumers habituate to
the novel stimulus. Hilgard and Bower (1975, p. 82) note, “Habituation is one of
the most primitive forms of stimulus learning or pattern perception; in habituating
to a recurrent stimulus, the organism is in effect saying, ‘I know that stimulus, and
it bores me.’” Similarly, Bettman (1979, p. 95) states, “Over time, even if conflict
is not handled, a conflicting stimulus will habituate from sheer repetition, and
cease to evoke an [orientation reaction].” We therefore hypothesize:
H5: The positive effects of a change in package color on consumer brand con-
sideration and choice will diminish with repeated exposure.
Of course, to the extent that a package change affects not only consumer attention,
but also consumer learning and experience, then the effects would be more enduring.
Studying the effects of a package change on consumer consideration and choice
presented several major challenges (cf. Roberts and Lattin 1997). On the one
hand, survey-based methods for assessing choice sets (e.g., Silk and Urban 1978)
depend on unreliable recollections of past cognitive states and are poorly suited for
measuring the dynamic impact of in-store factors on purchase consideration.
Laboratory research methods, on the other hand, present customers with a limited
selection of products in an unrealistic and highly involving context, effectively
eliminating the role of consideration in choice. As Alba, Hutchinson, and Lynch
(1991, p. 3) note, the selective attention paid by consumers to the brands in a
given product category “cannot be easily captured in laboratory studies of stimu-
To address these issues, we employed a virtual shopping simulation developed by
Burke (1996; Burke, Harlam, Kahn, and Lodish 1992). The simulation used 3D
computer graphics to recreate the appearance of a grocery shelf on a 20-inch touch-
screen monitor. Shoppers could pan down the aisles of the store using a 3D track-
ball, “pick up” products by touching their images on the screen, and rotate packages
and magnify labels for closer inspection. To purchase a product, the consumer
touched an image of a shopping cart and the package would fly into the basket.
The simulation offered several advantages over existing methodologies. It provided
the realism and visual clutter of an in-store experiment while delivering the control
and process tracing measures of laboratory research. The computer unobtrusively
recorded the amount of time consumers spent shopping in each category, the items
they picked up, the amount of time taken to examine individual packages and
labels, as well as the quantity of items purchased. Consumer behavior in the virtual
shopping simulation has been found to closely mirror behavior in the physical
store (see Burke 1996; Burke et al. 1992).
The Selection of Product Categories
The four product categories used in this study—flour, raisins, spaghetti, and
cereal—were selected according to several criteria. First, they were each high pene-
tration categories, purchased by most U.S. households. Shoppers had well-formed
perceptions of the leading brands in each category (e.g., Kellogg’s Cornflakes, Gold
Medal Flour, Sun-Maid Raisins, Mueller’s Spaghetti). Issues of brand identifica-
tion, package novelty and contrast, and consistency of meaning are likely to play a
greater role in these categories than in unfamiliar product categories.
Three of the four categories—flour, raisins, and spaghetti—met several additional
criteria. Each was a mature, stable product category with relatively low levels of
marketing activity such as product or package innovations, new product introduc-
tions, advertising, special store displays, or price promotions. In such categories,
consumer behavior is likely to be routine, as shoppers select their favorite brands
from the usual set of options. When the base level of brand consideration is low, a
packaging manipulation has a greater chance of increasing consideration and
choice. Also note that the products in these categories were relatively undifferenti-
ated according to their core performance attributes. If an effect of a package
change is observed, it is unlikely that this is due to the interaction between the
manipulation and the characteristics of a specific brand. Instead, the effect is likely
to generalize to the other brands in the category.
Finally, each of the three categories had a well-established set of visual conventions,
such as size, shape or color, which identified the category to consumers. In the
flour category, for example, each existing brand was packaged in a white paper bag.
If the package color were changed to something other than white, it would
increase the package’s novelty relative to the original, as well as increasing its
contrast relative to competitive brands. In the raisin category, all but one brand
had a primarily red box. In spaghetti, most packages featured red, white, and blue
color schemes. Such conventions provide experienced shoppers with the same visu-
al points of reference, increasing the likelihood that they will evaluate package
manipulations on the same basis.
The fourth category, cereal, was added to the design to serve as a point of contrast.
Unlike the categories of flour, raisins, and spaghetti, the cereal category is a hotbed
of new product activity. Hundreds of brands compete for shelf space with innova-
tive products and variegated package graphics. In this category, it is more difficult
to classify a new package as being typical or novel, because there are no category
conventions. Each consumer has a different reference point. We therefore defined
the novelty of a package in terms of its dissimilarity to the original package’s color.
To create a more realistic level of visual clutter, the test categories were displayed in
aisles with other, related product categories. Brands of flour were shown next to
cracker meal, cake, and muffin mixes; raisins were displayed with packaged
puddings and gelatin products; and spaghetti products were merchandised along-
side noodle and rice dishes. Because of the large number of brands in the cereal
category, no additional products were included in this aisle.
Creating and Classifying the Package Manipulations
The next step in the research process was to select one target brand in each of the
four categories and create new test packages representing the various conditions in
the experimental design. We selected Gold Medal Flour, Sun-Maid Raisins,
Mueller’s Spaghetti, and Kellogg’s Cornflakes as the target brands. These were the
leading-share brands in their respective categories and had high levels of consumer
familiarity and purchase incidence.
To create the various levels of package similarity and consistency for the experiment,
we manipulated the color of the target brand’s packaging. Color was chosen because
it is a dominant visual feature that is often used by manufacturers to attract atten-
tion and convey a favorable brand image. Unlike package shape, a change in color
does not affect the package’s function. Color can have a significant impact on how
consumers respond to marketing stimuli, as shown in advertising studies by Gorn,
Chattopadhyay, Yi, and Dahl (1997) and Meyers-Levy and Peracchio (1995).
The packages of each of the target brands were scanned into the computer and the
colors of selected package elements were systematically altered to create several new
looks. Packages were edited to remove any extraneous promotions or offers, but
most other visual features (including lines, borders, logos, characters, and other
graphic elements) were retained in order to preserve brand identification. A total of
25 new packages were created for Gold Medal Flour, 18 for Sun-Maid Raisins, 26
for Mueller’s Spaghetti, and 16 for Kellogg’s Cornflakes.
Three judges evaluated these candidate packages: an industrial designer and two
graphic designers. The judges were asked to select a subset of the candidates in
each of the four categories based on the design’s credibility as a professionally
executed, commercial package, and the degree to which it could be easily recog-
nized and identified as representing the target brand. The judges selected 9 pack-
ages in the flour category, 10 in raisins, 12 in spaghetti, and 9 in cereal.
The last steps in pretesting were to calibrate the new packages on the dimensions
of perceived dissimilarity, consistency of meaning, and preference, and to select
packages representing each of the experimental conditions (see Garber 1995). Gold
Medal Flour is used as an example to illustrate this process.
Eighty respondents (20 in each product category) first rated the perceived dissimilari-
ty of each pairwise combination of packages. These data were analyzed using the
KYST multidimensional scaling algorithm (Kruskal, Young, and Seery 1973) as
implemented in PC-MDS 5.1, from which we generated one- and two-dimensional
perceptual maps (see, for example, Figure 3).9The maps represent package alterna-
tives as points in a common, perceptual space, where the Euclidean distance from the
original (“actual”) package to each of the color-altered packages indicates the dissimi-
larity or novelty of the new package. New designs that were perceived to be most
similar to the original package (white bag with brown banner) in both the two- and
three-dimensional scaling solutions were classified as “very similar” (e.g., white bag
with orange banner, beige bag, orange bag). Candidates that were the farthest away
were classified as “very dissimilar”(e.g., the black and purple bags). Packages that fell
between these two extremes were categorized as “somewhat dissimilar.”
Figure 3. Perceived Similarity of Alternative Gold Medal Flour Packages
Second, respondents were asked to indicate which product attributes (9 in flour,
11 in raisins, 8 in spaghetti, and 9 in cereal) characterized each of the packages.10
They were told to base their evaluations solely on package appearance. The
frequencies with which packages were associated with attributes were mapped onto
a common, multidimensional space using the SIMCA correspondence analysis
package (Greenacre 1993). As shown in Figure 4, the original Gold Medal package
was seen as being “fresh quality,” “good value,” “naturally pure,” and “good tast-
ing.” New packages with similar benefit profiles (like the beige bag) were classified
as having “consistent meaning.” New designs with very different benefit profiles
(such as the black bag, which was seen as being “inexpensive”) were coded as hav-
ing “inconsistent meaning.” By combining the results from the similarity and
attribute scaling procedures, we were able to assign each package alternative to one
of the four visual categories. Examples of the various package alternatives created
for Gold Medal Flour are shown in Figure 5.
Finally, pretest respondents were asked to rate the degree to which they liked or
disliked each of the test packages. Packages with low evaluations were eliminated
from the set.
Figure 4. Attribute Associations for Alternative Gold Medal Flour Packages
Figure 5. Selected Gold Medal Package Variations for the Flour Category
Experimental Design and Procedure
One hundred twenty-eight adults, age 18 to 65, participated in the study.
Consumers were recruited through advertisements placed in local newspapers.
They were asked to participate in a test of a new home shopping system and were
paid $20 for one hour of their time. No computer experience was required. All
respondents were screened to be the primary grocery shoppers in their households.
Participants first completed a short questionnaire that gathered information on
their shopping habits, computer experience, and product category and brand
usage. Each person was then asked to take a series of five shopping trips through
an electronic grocery store. On each trip, the individual would make selections
from four product categories. (The shelf display for the flour category is shown in
Figure 6.) Participants were asked to purchase at least one item in each category
and to assume that they would pay the price shown on the shelf tag. The available
selection of products and associated prices closely matched local market condi-
tions. For the first shopping trip and product category, the interviewer demon-
strated how to “walk” down the grocery aisle by turning the trackball, zoom in on
the shelf by rotating a trackwheel, pick up products by touching their images on
the display screen, and purchase items by touching the on-screen shopping cart.
Respondents were then asked to complete the remaining shopping trips on their
own, behaving as they normally would in a conventional store. On the first three
shopping trips, a few (non-target) items were placed “on sale” to create a realistic
level of category activity, but none of the packages were altered. All package
manipulations occurred on the fourth and fifth shopping trips.
Figure 6. Computer Simulated Shelf Display for the Flour Category
Sixteen respondents were randomly assigned to each of the eight treatment
conditions in the 4 x 4 x 2 confounded block, mixed-factorial design (Kirk 1968,
pp. 327-39; Winer 1971, pp. 639-50). The first factor in the design was a within-
subject manipulation of the color similarity of the target brand’s revised package to
its original packaging. Color similarity varied across four levels: same package (i.e.,
no color change), very similar package, moderately dissimilar package, and very
dissimilar package. On the fourth shopping trip, the package colors of three of the
four target brands were changed, with the fourth category serving as a no-change
control condition. (These changes also carried over into the fifth and final shop-
ping trip.) Each participant saw only one experimental condition in each product
category, but the group as a whole saw all possible combinations of conditions and
categories. The second factor in the study was a within-subject manipulation of the
product category. As noted earlier, four product categories were used in this
research: flour, raisins, spaghetti, and cereal. The presentation order of product
categories was counterbalanced across conditions.
The third factor of the design was a two-level, between-group manipulation of the
consistency of the target brand’s new package with the meaning conveyed by its
original packaging. This factor was only manipulated for the very dissimilar pack-
aging (because when package color similarity was high, the consistency of meaning
was also necessarily high). Half of the respondents saw a very color-dissimilar, con-
sistent package in one of the four categories on the fourth and fifth shopping trips,
while the other half saw a very color-dissimilar, inconsistent package.
The computer unobtrusively recorded which packages shoppers picked up and
examined, and this served as a measure of brand consideration. While package
examination and brand consideration are both necessary but not sufficient condi-
tions for choice, the two constructs are not identical. Brands that are picked up
are, by definition, considered for purchase. However, customers may consider buy-
ing a product but then reject it without ever picking it up. Therefore, this measure
may underestimate the absolute levels of consideration. This was not a serious
problem since we were primarily interested in the relative levels of consideration
across experimental conditions.
Results and Discussion
Table 1 summarizes the main findings of the research with respect to the five
hypotheses tested. The detailed results of the study are discussed in the following
Table 1. Summary Results with Respect to Hypotheses Tested*
H1A new package whose color is very similar to a brand’s Partially Supported
original packaging is more easily identified and familiar,
and is therefore more likely to be considered for purchase
than a package whose color is moderately dissimilar.
H2A new package whose color is very dissimilar to a brand’s Supported
original package color will attract the customer’s attention
and is therefore more likely to be considered for purchase
than a package whose color is moderately dissimilar.
H3When comparing two new packages, both of which are Partially Supported
very dissimilar in color to a brand’s original packaging,
the package that conveys meaning which is consistent
with the brand’s original positioning is more likely to be
considered for purchase than the package that conveys
meaning which is inconsistent.
H4A new package that is very dissimilar in color to a brand’s Supported
original packaging will disrupt routine processing in the
category and increase the total amount of time spent in
the category and the number of packages picked up,
irrespective of the meaning displayed by the new package.
H5The positive effects of a change in package color on Supported
consumer brand consideration and choice will diminish
with repeated exposure.
* The results supported these hypotheses conditional on the characteristics of the product category and the loyalty of consumers to the
target brand. Across all conditions, the package manipulations generally had a greater effect on brand consideration than on choice.
Across all shopping trips, respondents took an average of 82 seconds to make their
product selections in a given category. The average time per shopping trip declined
monotonically across trips, from 178 seconds for the first trip to 71, 61, 54, and
47 seconds for trips 2 through 5, respectively (see Figure 7). People were able to
shop more quickly as they became familiar with the computer procedure and the
layout of the shelf displays. While each successive trip took significantly less time
than the previous shopping trip (p < .05), purchase decision times were relatively
stable by the fourth shopping trip when package manipulations were introduced.
Figure 7. Mean Category Viewing Time and Number of Brands Picked up by Shopping Trip
Breaking apart the average purchase decision times for the control and package-
change conditions (collapsed across levels of similarity and consistency), we found
that the mean category viewing times were greater in the change conditions than in
the control condition for both the fourth and fifth shopping trips (Figure 7), sup-
porting H4. The mean difference was significant for trip four (t = 2.478, p < .01, df
= 122, one-tailed test), but not significant for the fifth trip. This attenuation indi-
cates that consumers quickly adapted to the new package, in support of H5.
Figure 7 also shows the average number of brands picked up per shopping trip,
which fell from 2.3 packages on the first trip to 1.6 packages by the fifth trip. We
found that more packages were picked up in the package-change conditions than
in the control condition, as predicted by H4. The mean difference approached sig-
nificance for trip four (t = 1.269, p < .12, df = 193), but was not significant for
the fifth trip, again consistent with the attenuation effect suggested by H5.
Mean Number of
Brands Picked up
Viewing Time in Seconds
1 2 3 4 5
Means for “change” conditions
(split out only for shopping trips 4 & 5)
Means for control condition
(split out only for shopping trips 4 & 5)
Packaging, Brand Consideration, and Purchase
Of the 128 people who participated in the study, 5 individuals reported being
colorblind, so their results were excluded from the analyses. We expected that
consumers who regularly purchased the target brand would react differently to
changes in its packaging than individuals who did not routinely purchase the
brand. Therefore, respondents who bought the target brand on the third shopping
trip (prior to the package color manipulations) were classified as “target-brand
users,” and their data were analyzed separately from the data of “other-brand
To test the effects of package similarity and consistency-of-meaning manipulations
on consumer behavior towards the target brand, we calculated the proportions of
shoppers picking up and purchasing the target brand in each condition and prod-
uct category for the fourth and fifth shopping trips. A series of generalized logit
models were fit to these data using the SAS CATMOD procedure (SAS Institute
1989). We tested the significance of differences between individual cells in the
design using Kanji’s “Z-test for the equality between two proportions (binomial
distribution)” (Kanji 1993, p. 25).
Other-brand Users. Among consumers who did not routinely purchase the target
brand, the manipulation of package color had a significant main effect on shoppers’
likelihood of picking up the target brand on the fourth or fifth shopping trips
(χ2= 9.16, p < .03, df = 3). As the color of the revised package became increasingly
dissimilar from the original package, the proportion of people picking up the brand
increased from 18 percent (“no change”) to 27 percent (“very similar”; p < .07), and
from 28 percent (“moderately dissimilar”) to 42 percent (“very dissimilar/consistent;”
p < .05; see Figure 8a). This suggests that, for shoppers who are not loyal to a partic-
ular brand, a change in package color can enhance brand consideration, as predicted
by H2, without the negative effects on brand identification anticipated by H1.
Figure 8. Proportion of Shopping Trips Where the Target Brand Was Picked up and Purchased
as a Function of Visual Package Type
No Very Moderately Very
Change Similar Dissimilar Dissimilar
Visual Package Type
“Picking up” the target brand
“Buying” the target brand
A. Aggregating Across Product Categories
No Very Moderately Very
Change Similar Dissimilar Dissimilar
Visual Package Type
B.The Raisin Category (Sun-Maid)
No Very Moderately Very
Change Similar Dissimilar Dissimilar
Visual Package Type
C.The Cereal Category (Kellogg’s Corn Flakes)
Within the “very dissimilar” level of the package manipulation, consumers were
somewhat more likely to pick up a package whose color conveyed a meaning that
was consistent rather than inconsistent with the original packaging, as predicted by
H3. This overall effect across categories was not significant (χ2= .35, p > .20, df =
1), though, as one might expect, it was stronger for some categories than others.
The aggregate analysis of the effects of package similarity and consistency reported
above masked important differences between product categories. At one end of the
spectrum, the raisin category (the smallest of the four categories with only six
brands) showed results that were entirely consistent with the first three hypotheses.
As the color of the target brand’s package changed from “very similar” to “moder-
ately dissimilar,” the proportion of shoppers who picked up the package dropped
from 43 percent to 24 percent (p < .09). This suggests that customers were less
likely to automatically notice and pick up the revised package, as predicted by H1.
However, as the dissimilarity increased to the “very dissimilar/consistent” level,
package examination shot up to 76 percent from 24 percent (p < .001). This was
significantly higher than the 36 percent of people who examined the package in
the “very dissimilar/inconsistent” condition (p < .04; see Figure 8b).
The effects of package similarity and consistency in the flour and spaghetti cate-
gories were directionally similar to the raisin category, but not as pronounced. In
all three cases, consumers were more likely to purchase the brand when its package
color was “very dissimilar” rather than “moderately dissimilar” to the original
package (p < .03), in support of H2, but only when the conveyed meaning was
consistent with the original packaging (p < .10), as predicted by H3.
At the other end of the spectrum, the cereal category showed strong positive effects
for package novelty, but not for brand identification or consistency of meaning. As
the appearance of the cereal package was changed from “very similar” to
”moderately dissimilar,” the proportion of shoppers who picked up the package
jumped from about 8 percent to 38 percent (p < .01). It stayed at this high level
for the “very dissimilar/inconsistent” package, but was only 29 percent for the
“very dissimilar/consistent” package. The difference between consistent and
inconsistent packages was not significant (p > .20, see Figure 8c).
As noted earlier, the cereal category was quite different from the other three
categories (flour, raisins, and spaghetti) because of the large number of brands (38
in this study), the heterogeneity of package designs, the high level of promotional
activity, and the relatively small (4 percent) share of the target brand. It appears
that in this highly competitive category, having a novel package is critical to
gaining the customer’s attention, even if the image communicated by the package
is inconsistent with the brand’s original positioning. On the other hand, in smaller
categories like raisins, spaghetti, and flour, a novel package needs to be consistent
with the brand’s equity in order to enhance brand consideration.
It is not surprising that brand identification and consistency of meaning had the
greatest impact on customer behavior in the raisin category. The target brand, Sun-
Maid, has commanded as much as a 50 percent share of the retail raisin category
(Cuneo 1988). It has achieved high levels of consumer awareness through extensive
distribution and heavy advertising and promotion. The Sun-Maid name and logo
have been extended to many categories through co-branding, including raisin
bread, bagels, English muffins, ice cream, candy, and cereal. Unlike the three other
target brands, the Sun-Maid trademark features a person, which has been shown to
enhance logo recognition (Gillespie 1993). We found that the target brand for
raisins, Sun-Maid, was the most popular of the target brands tested in this study
(χ2= 9.90, p < .02, df = 3).
In general, the results for consumer choice paralleled those for brand consideration
reported above, but the effects of the manipulations were not as strong (see Figure
8). Across all four categories, there was a non-significant increase in the proportion
of consumers purchasing the target brand as the package was changed from its
original form (13 percent) to “very dissimilar” (17 percent). In the raisin category,
an increase in the dissimilarity of the target brand’s package caused a gradual (but
insignificant) decline in the proportion of people who purchased the brand, from
33 percent (“no change”) to 22 percent (“very similar”) to 16 percent (“moderately
dissimilar”). For the “very dissimilar” package, shoppers were more likely to pur-
chase the brand when the package meaning was consistent (33 percent) rather than
inconsistent (9 percent) with the brand’s original positioning, p < .09.
On the other hand, in the cereal category, consumers were significantly more likely
to purchase the “moderately dissimilar” and “very dissimilar” packages than they
were to buy the “very similar” or the unchanged packages (p < .05). They were
slightly more likely to choose the inconsistent (23 percent) than consistent (21
percent) package, although this effect was not significant. Once again, it appears
that, in the highly cluttered cereal category, package novelty was more important
than consistency of meaning for attracting customers’ attention and interest.
Target-brand Users. As one might expect, regular users of the target brand were very
likely to pick up and purchase that brand on the fourth and fifth shopping trips.
On the fourth trip, 78 percent of “target brand users” picked up the brand and 95
percent of examiners followed through and purchased the product. Among these
shoppers, the manipulation of package similarity had a marginally significant main
effect on their likelihood of selecting the target brand (χ2= 7.76, p < .06, df = 3).
The proportion of people picking up the brand was approximately the same for the
“no change” (79 percent), “very similar” (80 percent), and “moderately dissimilar”
(82 percent) package conditions, but then dropped off to 77 percent for the “very
dissimilar/consistent” condition and to 71 percent for the “very dissimilar/ inconsis-
tent” condition. The difference between the “moderately dissimilar” condition and
the “very dissimilar/inconsistent” condition was marginally significant (p < .07).
One can assume that this segment of shoppers already included the target brand in
their consideration sets. When a highly novel package was introduced onto the
shelf, some consumers may have been confused by the change and had difficulty
finding their preferred brand.
Package similarity also had a significant main effect on target users’ likelihood of
purchasing the brand (χ2 = 8.61, p < .04, df = 3). The proportion of shoppers buy-
ing the brand was approximately 76 percent in the “no change,” “very similar,” and
“very dissimilar/consistent” conditions, falling off to 73 percent in the ”moderately
dissimilar” condition and 71 percent in the “very dissimilar/inconsistent” condi-
tion. Although directionally consistent with H3, the main effects of consistency of
meaning on the likelihood of target brand examination and purchase were not sig-
nificant (χ2= 0.98, p > .20, df = 1; and χ2= 1.41, p > .20, df = 1, respectively).
Based on these results, it appears that, for loyal brand users, a package change
generally has a negative (if any) effect on brand consideration and choice.
Packaging and Category Search
In addition to the direct effects of a package change on target-brand consideration,
we expected that new packaging would increase the total amount of information
search in the product category (H4). To test this hypothesis, we looked at the
effects of package similarity on the amount of time that other-brand users spent
shopping in the category and the number of brands they picked up. We excluded
data for the target brand because we were only interested in the effects of the
manipulations on the remaining brands in the category. Effects were tested using
analysis of variance and pairwise t-tests.
When the color of the target brand’s package was altered, the total amount of time
spent in the product category increased from 47 seconds to 51, 51, 58, and 60
seconds for the “very similar,” “moderately dissimilar,” “very dissimilar/consistent,”
and “very dissimilar/inconsistent” conditions, respectively. Consumers spent
significantly longer shopping in the product category in the two “very dissimilar”
conditions than in the no-change, “control” condition (p < .02), as predicted by H4.
The package change manipulation also affected the average number of brands
picked up by consumers (excluding the target brand). The number of brands
examined changed from 1.6 packages in the control condition to 1.6, 1.5, 1.7,
and 1.8 for the “very similar,” “moderately dissimilar,” “very dissimilar/consistent,”
and “very dissimilar/inconsistent” conditions, respectively. The contrast between
the “moderately dissimilar” and “very dissimilar/inconsistent” conditions was
significant (p < .05).
The evidence in support of H4is somewhat surprising. For most marketing variables,
a change that helps the target brand (e.g., a price cut or promotion) would tend to
hurt consideration of the other brands. Here we see that a package change for the
target brand can increase its consideration and consideration of other brands.
We also evaluated the effects of package manipulations on the amount of time
customers spent examining the target brand’s package. In those cases when the
package was picked up, the average amount of time spent by other-brand users
examining the target brand increased from 6.8 seconds in the control condition to
12.3, 14.9, 19.9, and 21.1 seconds for the “very similar,” “moderately dissimilar,”
“very dissimilar/consistent,” and “very dissimilar/inconsistent” conditions, respec-
tively. The pattern was similar for the target-brand users, increasing from 6.9 sec-
onds in the control condition to 13.8, 11.6, 16.2, and 12.3 seconds in the remain-
ing conditions. Viewing times for all of the package change conditions were signif-
icantly higher than for the control condition (p < .03 or greater). It would appear
that a package change can increase brand evaluation (Stage III in Figure 1) as well
as attention and consideration (Stages I and II).
This research was necessarily limited in terms of the range of marketing stimuli
and responses investigated. We manipulated only one dimension of a package’s
appearance—its color—while holding constant other elements of the marketing
mix. A package’s color is a dominant visual attribute that can be seen by shoppers
at a considerable distance from the shelf. It is likely to have a greater effect on
brand attention and consideration than visual elements requiring closer inspection,
such as the brand’s logo, typestyle, and package graphics.12
We looked at the effects of revising a package while holding constant other aspects
of the marketing mix. However, packaging may interact with other marketing
variables. For example, a revised package may attract more attention when it is
used to introduce a new and improved product, or when accompanied by a free-
standing display or promotion.
A third issue is whether the results can be extended to other purchase contexts. In
this study, individuals could take as much time as they wanted to shop in each cat-
egory. However, in the physical store, people often face significant time con-
straints. Pieters, Warlop, and Hartog (1997) report that, under high time pressure
conditions, consumers are more likely to look at package illustrations but less likely
to examine ingredient information and even entire brands. This suggests that time-
pressed shoppers may use superficial package cues in order to reduce the size of
their consideration sets, magnifying the effects reported here.
The present study focused on the packaging of grocery products. The results are
most relevant to other retail environments where products are shown in the con-
text of many competitors (e.g., mass merchandise outlets, drug stores, hardware
stores, etc.). Yet the basic notions of brand identification, novelty/contrast, and
appropriateness may apply to a broader range of products, markets, and marketing
stimuli. Take print advertising, for example. A consumer’s likelihood of attending
to and considering a new product (e.g., Cadillac Catera) advertised in a specialty
magazine filled with competitors’ products is likely to be affected by the individ-
ual’s ability to identify the brand (Cadillac), the novelty and contrast of the ad
(duck driving a car), and the appropriateness of the conveyed meaning (Why is a
duck driving a Cadillac?). The framework shown in Figure 1 could also be used to
predict how customers will respond to a product’s physical appearance (industrial
design), the look of retail spaces (e.g., show rooms, trade show booths, professional
offices), and the appearance of service people (dress, demeanor).
As illustrated in Figure 1, the competitive context can have a significant impact on
how customers respond to a brand’s packaging. It affects the ease with which shop-
pers can identify the brand, the perceived novelty and contrast of the packaging, and
the comprehension of the package’s meaning. In the present study, we held constant
the appearance of competitive products and focused on the effects of changing a tar-
get brand’s package color. However, the virtual shopping simulation has the flexibili-
ty to manipulate the appearance of all of the displayed brands. This allows one to test
how a new package would perform under alternative competitive scenarios.
One promising avenue for future research would be to study the direct effects of
competitive activity (including package changes) on brand consideration. On the
one hand, a consumer may be more likely to consider a target brand because he or
she considers another, similar competitive brand. Lattin and Roberts (1992) and
Lehmann and Pan (1994) find that similar products tend to appear together in
consideration sets. Nedungadi (1990) discovered that advertising for a competitive
brand can stimulate consideration of a related target brand, increasing its likeli-
hood of purchase. On the other hand, competitors’ actions can distract consumers’
attention away from the target brand. Burke reported that consumers were less
likely to notice a new grocery product when competing brands were on sale (see
Andrews 1995). Additional merchandising and promotional support for the target
brand were required to counter these negative effects.
Another direction for future research is to isolate the components of perceptual
similarity. In this study, similarity was treated as a single, continuous dimension. A
new package could either be very similar to the original, in which case it would be
easily identified but unexciting; or it could be very dissimilar to the original, mak-
ing it more novel and attention getting, but harder to identify. To the extent that
consumers use a subset of package attributes for brand identification, it would be
possible to create a single package that is both easily identified as well as novel and
attention getting. Models of stimulus generalization based on stimulus sampling
theory (e.g., Atkinson and Estes 1963; Bush and Mosteller 1951) suggest that a
stimulus should be treated as a collection of elements that may individually enter
into associations when learning takes place. Through research, we can isolate which
specific elements are critical to generalization.
One way to isolate these brand-identifying characteristics would be to conduct a
speeded brand recognition test. Consumers would be asked to locate the target
brand as quickly as possible from a competitive display. Across trials, package
elements of the target brand would be manipulated according to an experimental
design. Those elements having the greatest impact on the speed of brand recogni-
tion are the ones being used for identification.13
In 1928, Franken and Larabee noted, “The display container is as much a sales-
man as any flesh-and-blood clerk, and often more, for it works night and day for
one product and emphasizes only those sales arguments which the manufacturer
knows are best.” Their point is still true today, as manufacturers and retailers con-
tinue to rely on packaging to sell their products in self-service shopping environ-
ments. New packaging technologies allow marketers to create an almost unlimited
range of alternatives. An article in Marketing News (October 11, 1985) suggested
that Coca-Cola tried over 150 package designs for Diet Coke. Unfortunately, there
has not been a corresponding increase in the sophistication of packaging theory
and research to help guide managers in the selection of a successful package.
In this paper, we identified the four main factors that managers should consider
when designing or revising a product’s package: brand identification, package
novelty and contrast, package comprehension, and package function. We focused
on the first three factors and described a methodology that can be used to isolate
their independent effects on consumer consideration and choice. We presented an
example application in the grocery context and reported the effects of various
package changes on purchase consideration and choice.
As noted earlier, consumer shopping is both goal-directed and opportunistic, and
packaging can influence both aspects of information search. While brand
identification is largely guided by consumer goals (what Kahneman  refers to
as “voluntary attention”), package novelty and contrast stimulate exploration (“invol-
untary attention”). The extent to which one would emphasize brand identification or
novelty when revising a package depends on the percentage of shoppers who are loyal
to the brand (planning their purchases before entering the store) versus brand switch-
ers or variety seekers (who make their decisions at the point of purchase).
The results of the research indicated that a manufacturer can encourage shoppers
who are not currently loyal to its brand to consider purchasing the product by using
a highly novel package. In relatively small and stable categories like raisins, flour,
and spaghetti, we found that the revised package was more likely to be picked up
and purchased when the meaning it conveyed was consistent with the brand’s origi-
nal positioning. In highly competitive categories like cereal (where it is more diffi-
cult to attract shoppers’ attention), having a strikingly different package was more
important to the success of the brand than maintaining a consistent image.
On the other hand, if the brand has a large base of loyal customers, the results
suggest that it may be better to retain the original package or a minor variation, as
large changes may reduce brand identification and confuse existing customers.
1. Of course, if the original brand was disliked, the manufacturer may intention-
ally design the new package to look different in order to minimize associations
with the old product.
2. These may be the same or different from the elements that are used for brand
3. There are two notable differences between Roberts’ model and the one present-
ed in Figure 1. First, we include an initial Stage 0 of category attention.
Category attention is a necessary but not sufficient condition for brand-level
information processing. Second, we focus on brand attention rather than brand
awareness at Stage I. Whereas brand awareness is typically defined as the con-
sumer’s ability to recognize or recall the brand name when prompted (see, e.g.,
Lavidge and Steiner’s 1961 “Hierarchy of Effects” model), we define attention as
being when the consumer actually recognizes, recalls, or notices a brand at the
point of purchase (e.g., Strong’s 1925 “AIDA” model). Attention differs from
consideration (Stage II) in that consideration requires more active processing of
brand information. While Stages I and II are conceptually distinct, we do not
attempt to discriminate between them in the empirical research.
4. In some cases, these goals are recorded on a shopping list. In others, they are
stored in consumer memory. Goals can identify general needs (e.g., bath sup-
plies), product categories (soap), brands (Dove), or individual shop-keeping
units (Dove bar soap, white, three-pack). When goals are narrowly specified
(either in memory or on a shopping list), the consumer is said to have
“planned” the purchase.
5. In the laboratory study to be described, we have no way of empirically
discriminating between stages I and II, so they are collapsed into a single stage
called “Consideration Set Formation.”
6. In further support of this point, Spence and Engel (1970) reported that per-
ceptual thresholds were lower for preferred brands.
7. Research by Duncan and Humphreys (1989) suggests that a shopper’s ability
to identify a target brand’s package will increase as it becomes more distinctive
from competitors’ packages and as competitors’ packages become more similar
to each other.
8. When a revised package is very similar to the original design, we assume that it
communicates an image that is consistent with the brand’s positioning.
9. Maps with higher dimensionality did not explain substantially more variance.
10. These attributes were identified by two judges with brand management experi-
ence in the consumer packaged goods industry as being the key performance
dimensions in the four test categories.
11. Because an individual may use a target brand in one category but not in anoth-
er, the classification of “target-brand user” was done at the product category
level. There were a total of 102 subject/category observations for “target-brand
users” and 390 observations for “other-brand users” (excluding the 20 observa-
tions for the five colorblind respondents).
12. Package size and shape are also visually dominant attributes, and are likely to
be used for product screening.
13. Similar techniques have been used to test the visibility of billboard ads and yel-
low-page directory listings.
Aaker, David A., and Alexander L. Biel (1993), Brand Equity and Advertising:
Advertising’s Role in Building Strong Brands. Hillsdale, NJ: Lawrence
Erlbaum and Associates.
Agarwal, Manoj K., and Vithala R. Rao (1996), “An Empirical Comparison of
Consumer-Based Measures of Brand Equity.” Marketing Letters 7 (July),
Aks, D. J., and J. T. Enns (1992), “Visual Search for Direction of Shading Is
Influenced by Apparent Depth.” Perception and Psychophysics 52, 63-74.
Alba, Joseph W., J. Wesley Hutchinson, and John G. Lynch, Jr. (1991), “Memory
and Decision Making.” In Handbook of Consumer Behavior, eds. Thomas S.
Robertson and Harold H. Kassarjian, 1-49. Englewood Cliffs, NJ:
Allenby, Greg M., and James L. Ginter (1995), “Using Extremes to Design
Products and Segment Markets.” Journal of Marketing Research 32
Andrews, Katherine Zoe (1995), “Market Research: Shaking Up Consumers at the
Point of Purchase.” Harvard Business Review 73 (November-December),
Atkinson, R. C., and W. K. Estes (1963), “Stimulus Sampling Theory.” In
Handbook of Mathematical Psychology, vol. 3, eds. R. D. Luce, R. B. Bush,
and E. Galanter, 121-268. New York: Wiley.
BBDO Advertising (1987), “Consumer Perceptions of Parity in Brands Across
Product Categories.” Internal marketing research study, New York.
Belk, Russell W. (1988), “Possessions and the Extended Self.” Journal of Consumer
Research 15 (September), 139-68.
Bellizzi, Joseph A., and Robert E. Hite (1992), “Environmental Color, Consumer
Feelings and Purchase Likelihood.” Psychology and Marketing 9 (5)
______ , Ayn E.Crowley, and Ronald W. Hasty (1983), “The Effects of Color in
Store Design.” Journal of Retailing 59, 21-45.
Berlyne, E. E. (1960), Conflict, Arousal and Curiosity. New York: McGraw-Hill
Book Co., Inc.
______ (1974), Studies in the New Experimental Aesthetics. New York: John Wiley
Bettman, James R. (1979), An Information Processing Theory of Consumer Choice.
______ , Eric J. Johnson, and John W. Payne (1991), “Consumer Decision
Making.” In Handbook of Consumer Behavior, eds. Thomas S. Robertson
and Harold H. Kassarjian, 85-123. Englewood Cliffs, NJ: Prentice-Hall.
Biel, Alexander L. (1993), “Converting Image into Equity.” In Brand Equity &
Advertising: Advertising’s Role in Building Strong Brands, eds. Aaker and Bell.
Hillsdale, NJ: Lawrence Erlbaum and Associates.
Bransford, John D., K. E. Nitsch, and J. J. Franks (1977), “Schooling and the
Facilitation of Knowing.” In Schooling and the Acquisition of Knowledge,
eds. R. C. Anderson, R. J. Spiro, and W. E. Montague. Hillsdale, NJ:
Bravo, M., and R. Blake (1990), “Preattentive Vision and Perceptual Groups.”
Perception 19, 515-22.
Bruce, Vicki, and Patrick R. Green (1992), Visual Perception: Physiology, Psychology
and Ecology. Hillsdale: Lawrence Erlbaum Associates.
Burke, Raymond R. (1995), “Marsh Supermarkets, Inc. (A): The Marsh Super
Study.” Boston: Harvard Business School Publishing, Case number 9-594-
______ (1996), “Virtual Shopping: Breakthrough in Marketing Research.”
Harvard Business Review (March-April), 120-31.
______ , Bari A. Harlam, Barbara E. Kahn, and Leonard Lodish (1992),
“Comparing Dynamic Consumer Choice in Real and Computer-simulated
Environments.” Journal of Consumer Research 19 (June), 71-82.
Bush, R. R., and F. Mosteller (1951), “A Model for Stimulus Generalization and
Discrimination.” Psychological Review 58, 413-23.
Celsi, Richard L., and Jerry C. Olson (1988), “The Role of Involvement in
Attention and Comprehension Processes.” Journal of Consumer Research
15 (September), 210-24.
Chase, William G., and Herbert A. Simon (1973), “Perception in Chess.”
Cognitive Psychology 4 (January), 55-81.
Cheskin, Louis (1957), How to Predict What People Will Buy. New York: Liveright.
Click, J.W., and Guido H. Stempel III (1976), “Reader Response to Front Pages
with Four-Color Halftones.” Journalism Quarterly 53 (4), 736-8.
Collins, A. M., and M. R. Quillian (1970), “Facilitating Retrieval from Semantic
Memory: The Effect of Repeating Part of an Inference.” Acta Psychologica
Cuneo, Alice Z. (1988), “Sun-Maid, Dole Boost Raisins.” Advertising Age
(October 10), 44.
Dacin, Peter A., and Daniel C. Smith (1994), “The Effect of Brand Portfolio
Characteristics on Consumer Evaluation.” Journal of Marketing Research
Dichter, Ernest (1975), Packaging: The Sixth Sense? A Guide to Identifying
Consumer Motivation. Boston: Cahners Books.
Dickson, Peter R., and Alan G. Sawyer (1990), “The Price Knowledge and Search
of Supermarket Shoppers.” Journal of Marketing 54 (July), 42-54.
Duncan, John, and Olyn W. Humphreys (1989), “Visual Search and Stimulus
Similarity.” Psychological Review 96 (3), 433-58.
Durgee, Jeffrey, and Gina Colarelli O’Connor (1994), “Perceiving What Package
Designs Express: A Multisensory Exploratory Study Using Creative Writing
Measurement Techniques.” New York: Rensselaer Polytechnic Institute,
Farquhar, Peter H. (1989), “Managing Brand Equity.” Marketing Research
Foxall, Gordon (1990), Consumer Psychology in Behavioral Perspective. London:
Garber, Lawrence L., Jr. (1995), “The Role of Package Appearance in Consumer
Choice.” Chapel Hill: University of North Carolina at Chapel Hill,
Unpublished Ph.D. dissertation,
______ , Eva M. Hyatt, and Richard G. Starr, Jr. (2000), “The Effects of Food
Color on Flavor Perception.” Boone, NC: Appalachian State University,
Gillespie, Phyllis (1993), “Corporate Symbolism: Valley Group Surveys Global
Impact of Logos.” The Arizona Republic (August 15), Section F, 1.
Gorn, Gerald J., Amitava Chattopadhyay, Tracey Yi, and Darren W. Dahl (1997),
“Effects of Color as an Executional Cue: They’re in the Shade.”
Management Science 43 (October), 1387-1400.
Greenacre, Michael J. (1993), Correspondence Analysis in Practice. New York:
Hauser, John R., and Birger Wernerfelt (1990), “An Evaluation Cost Model of
Consideration Sets.” Journal of Consumer Research 16 (March), 393-408.
Hayes-Roth, Barbara (1977), “Evolution of Cognitive Structures and Processes.”
Psychological Review 84 (May), 260-78.
Hayes-Roth, Barbara, and Frederick Hayes-Roth (1975), “Plasticity in Memorial
Networks.” Journal of Verbal Learning and Verbal Behavior 14, 506-22.
Helson, H. (1964), Adaptation-Level Theory. New York: Harper and Row.
Hilgard, Ernest R., and Gordon H. Bower (1975), Theories of Learning 4th ed.
Englewood Cliffs, NJ: Prentice-Hall.
Hine, Thomas (1996), The Total Package. New York: Little, Brown and Co.
Hirschman, Elizabeth, and Morris Holbrook (1982), “Hedonic Consumption:
Emerging Concepts, Methods and Propositions.” Journal of Marketing 46
Hoch, Stephen J., Xavier Dréze, and Mary E. Purk (1994), “Shelf-Management
and Space Elasticity.” Journal of Retailing 70 (Winter), 301-27.
Howard, John A. (1963), Marketing Management, 2nd. ed. Homewood, IL: Irwin.
______ , and Jagdish N. Sheth (1969), The Theory of Buyer Behavior. New York:
Hoyer, Wayne D. (1984), “An Examination of Consumer Decision Making for a
Common Repeat Purchase Product.” Journal of Consumer Research 11
Humphreys, Glyn W., P. T. Quinlan, and M. J. Riddoch (1989), “Grouping
Processes in Visual Search: Effects with Single- and Combined-Feature
Targets.” Journal of Experimental Psychology: General 118, 258-79.
Inman, J. Jeffrey, Leigh McAlister, and Wayne D. Hoyer (1990), “Promotion Signal:
Proxy for a Price Cut?” Journal of Consumer Research 17 (June), 74-81.
Jabbonsky, Larry (1995), “Damn, This is Different.” Beverage World (June), 24-31.
Johnson, Michael D., and Donald R. Lehmann (1997), “Consumer Experience
and Consideration Sets for Brands and Product Categories.” In Advances in
Consumer Research, vol. 24, eds. Merrie Brucks and Deborah J. MacInnis,
295-300. Provo, UT: Association for Consumer Research.
Kahneman, Daniel (1973), Attention and Effort. Englewood, N.J: Prentice-Hall.
Kanji, Gopal K. (1993), 100 Statistical Tests. London: Sage Publications Ltd.
Keller, Kevin Lane (1993), “Conceptualizing, Measuring, and Managing
Customer-Based Brand Equity.” Journal of Marketing 57 (January), 1-22.
King, S. H. M. (1989), “Branding Opportunities in Financial Services.”
Proceedings of the Market Research Society Conference on Advertising and
Marketing Financial Services. London: MRS Press.
Kirk, Roger E. (1968), Experimental Design: Procedures for the Behavioral Sciences.
Belmont, CA: Brooks/Cole.
Kleffner, D. A., and V. S. Ramachandran (1992), “On the Perception of Shape
from Shading.” Perception and Psychophysics 52, 18-36.
Kotler, Philip, and Gary Armstrong (1991), Principles of Marketing, 5th ed.
Englewood Cliffs, NJ: Prentice Hall.
Kruskal, Joseph B., Forrest W. Young, and Judith B. Seery (1973), How to Use
KYST, a Very Flexible Program to Do Multidimensional Scaling and
Unfolding. Murray Hill, NJ: Bell Laboratories.
Lattin, James M., and John H. Roberts (1992), “Testing for Probabilistic
Independence in the Consideration of Ready-to-Eat Cereals.” Palo Alto:
Stanford University, Graduate School of Business, Research Paper No. 1208.
Lavidge, Robert J., and Gary A. Steiner (1961), “A Model for Predictive
Measurements of Advertising Effectiveness.” Journal of Marketing 25
Lehmann, Donald R., and Yigang Pan (1994), “Context Effects, New Brand Entry,
and Consideration Sets.” Journal of Marketing Research 31 (August), 364-75.
Lindsay, Robert K., and Jane M. Lindsay (1966), “Reaction Time and Serial versus
Parallel Information Processing.” Journal of Experimental Psychology 71,
Loken, Barbara, and James Ward (1990), “Alternative Approaches to
Understanding the Determinants of Typicality.” Journal of Consumer
Research 17 (September), 111-26.
Lussier, Denis A., and Richard W. Olshavsky (1979), “Task Complexity and
Contingent Processing in Brand Choice.” Journal of Consumer Research 6,
Mandler, George (1982), “The Structure of Value: Accounting for Taste.” In Affect
and Cognition: The 17th Annual Carnegie Symposium, eds. Margaret S. Clark
and Susan T. Fiske, 3-36. Hillsdale, NJ: Lawrence Erlbaum Associates.
Meyer, Robert J., and Barbara E. Kahn (1991), “Probabilistic Models of Consumer
Choice Behavior.” In Handbook of Consumer Behavior, eds. Thomas S.
Robertson and Harold H. Kassarjian, 85-123. Englewood Cliffs, NJ:
Meyers-Levy, Joan, and Laura A. Peracchio (1995), “Understanding the Effects of
Color: How the Correspondence Between Available and Required Resources
Affects Attitudes.” Journal of Consumer Research 22 (September), 121-38.
______ , and Alice M. Tybout (1989), “Schema Incongruity as a Basis for Product
Evaluation.” Journal of Consumer Research 16 (June), 39-54.
Narayana, Chem L., and Ram J. Markin (1975), “Consumer Behavior and
Product Performance: An Alternative Conceptualization.” Journal of
Marketing 39 (October), 1-6.
Neal, William (1993), Presentation to Triangle AMA, Research Triangle Park,
Nedungadi, Prakash (1990), “Recall and Consumer Consideration Sets:
Influencing Choice Without Altering Brand Evaluations.” Journal of
Consumer Research 17 (December), 263-76.
Park, Chan Su, and V. Srinivasan (1994), “A Survey Based Method for Measuring
and Understanding Brand Equity and its Extendability.” Journal of
Marketing Research 31 (May), 271-88.
Payne, John W. (1976), “Task Complexity and Contingent Processing in Decision-
Making: An Information Search and Protocol Analysis.” Organizational
Behavior and Human Performance 16 (August), 366-87.
Pieters, Rik, Luk Warlop, and Michel Hartog (1997), “The Effect of Time Pressure
and Task Motivation on Visual Attention to Brands.” In Advances in
Consumer Research, vol. 24, eds. Merrie Brucks and Deborah J. MacInnis,
281-7. Provo, UT: Association for Consumer Research.
Point-of-Purchase Advertising Institute (POPAI) (1978), POPAI/Dupont Consumer
Buying Habits Study: Special Report. New York: POPAI.
Pribram, Karl H., and Diane McGuinness (1975), “Arousal, Activation and Effort
in the Control of Attention.” Psychological Review 82 (March), 116-49.
Prone, Michael (1993), “Package Design Has Stronger ROI Potential Than Many
Believe.” Marketing News (October), 13.
Raphael, Harold J. (1969), Packaging: A Scientific Marketing Tool. East Lansing,
MI: Michigan State University Bookstore.
Roberts, John H. (1989), “A Grounded Model of Consideration Set Size and
Composition.” In Advances in Consumer Research, vol. 16, ed. T. Srull, 749-
57. Provo, UT: Association for Consumer Research.
______ , and James M. Lattin (1991), “Development and Testing of a Model of
Consideration Set Composition.” Journal of Marketing Research 28
______ , and James M. Lattin (1997), “Consideration: Review of Research and
Prospects for Future Insights.” Journal of Marketing Research 34 (August),
SAS Institute Inc. (1989), SAS/STAT User’s Guide, Version 6, 4th ed., vol. 1, 405-
517. Cary, NC: SAS Institute Inc.,
Schindler, Pamela S. (1986), “Color and Contrast in Magazine Advertising.”
Psychology and Marketing 3, 69-87.
Schneider, Walter, and Richard M. Shiffrin (1977), “Controlled and Automatic
Human Information Processing: Detection, Search, and Attention.”
Psychological Review 84 (1), 1-66.
Schoormans, Jan P. L., and Henry S. J. Robben (1996), “The Effect of New
Package Design on Product Attention, Categorization and Evaluation.”
Delft, The Netherlands: Delft University of Technology, Working paper.
Shapiro, Stewart, Deborah J. MacInnis, and Susan E. Heckler (1997), “The Effects
of Incidental Ad Exposure on the Formation of Consideration Sets.”
Journal of Consumer Research 24 (June), 94-104.
Shepard, R. N. (1987), “Toward a Universal Law of Generalization for
Psychological Science.” Science 237, 1317-23.
Shocker, Allan D., Moshe Ben-Akiva, Bruno Boccara, and Prakash Nedungadi
(1991), “Consideration Set Influences on Consumer Decision-Making and
Choice: Issues, Models, and Suggestions.” Marketing Letters 2 (3), 181-97.
Shugan, Steven M. (1980), “The Cost of Thinking.” Journal of Consumer Research
7 (September), 99-111.
Siddarth, S., Randolph E. Bucklin, and Donald G. Morrison (1995), “Making the
Cut: Modeling and Analyzing Choice Set Restriction in Scanner Panel
Data.” Journal of Marketing Research 32 (August), 255-66.
Silk, Alvin J., and Glen L. Urban (1978), “Pre-Test-Market Evaluation of New
Packaged Goods: A Model and Measurement Methodology.” Journal of
Marketing Research 15 (May), 171-91.
Sparkman, Richard R., Jr., and Larry M. Austin (1980), “The Effect on Sales of
Color in Newspaper Advertisements.” Journal of Advertising 9 (4), 39-42.
Spence, Homer E., and James F. Engel (1970), “The Impact of Brand Preference
on the Perception of Brand Names: A Laboratory Analysis.” In Research in
Consumer Behavior, eds. David T. Kollat, Roger D. Blackwell, and James F.
Engel, 61-70. New York: Holt, Rinehart and Winston.
Spence, K. W. (1936), “The Nature of Discrimination Learning in Animals.”
Psychological Review 43, 427-49.
Stigler, George J. (1961), “The Economics of Information.” Journal of Political
Economy 69 (June), 213-25.
Strong, E. K. (1925), The Psychology of Selling. New York: McGraw-Hill.
Tauber, Edward M. (1988), “Brand Leverage: Strategy for Growth in a Cost-Control
World.” Journal of Advertising Research 28 (August/September), 26-31.
Treisman, Anne (1991), “Search, Similarity, and Integration of Features Between
and Within Dimensions.” Journal of Experimental Psychology: Human
Perception and Performance 40A, 201-37.
Treisman, Anne, and G. Gelade (1980), “A Feature-Integration Theory of
Attention.” Cognitive Psychology 14, 107-41.
Veryzer, Robert W., and J. Wesley Hutchinson (1998), “The Influence of Unity
and Prototypicality on Aesthetic Responses to New Product Designs.”
Journal of Consumer Research 24 (March), 374-94.
Winer, B. J. (1971), Statistical Principles in Experimental Design, 2nd ed. New
Wright, Peter L. (1975), “Consumer Choice Strategies: Simplifying vs.
Optimizing.” Journal of Marketing Research 11 (February), 60-7.
Yantis, Steven, and Anne P. Hillstrom (1994), “Stimulus-Driven Attentional
Capture: Evidence From Equiluminal Visual Objects.” Journal of
Experimental Psychology: Human Perception and Performance 20 (1), 95-107.