116 RESPONSES DOES RUNNING OUT OF (SOME) TRADEMAR.docx

116
RESPONSES
DOES RUNNING OUT OF
(SOME) TRADEMARKS MATTER?†
Lisa Larrimore Ouellette∗
Professors Barton Beebe and Jeanne Fromer’s empirical tour de
force presents a strong challenge to the conventional wisdom
that there
are infinite potential trademarks.1 To be sure, the claim that
potential
trademarks, broadly defined, are inexhaustible is tautologically
true:
there are infinite combinations of letters and other symbols —
including
sounds and colors — any of which might serve as a mark.2 In
this sense,
the claim that we might run out of trademarks seems as absurd
as John
Stuart Mill’s concern that we might run out of music.3 But not
all marks
are created equal. Some combinations of letters are unwieldy or
un-
memorable; others have negative connotations. Beebe and
Fromer ar-
gue that the most valuable marks are common words, short and
pro-
nounceable neologisms, and common U.S. surnames.4 The

concern
about running out of these marks is far from absurd — just as
Mill’s
anxiety about running out of music makes much more sense
when con-
fined to three-note melodies such as the trademarked NBC
chimes,5 of
which there are only 469 possibilities.6
In this short space, I wish to laud the remarkable descriptive
contri-
bution of Are We Running Out of Trademarks? while sounding
a note of
caution on the normative implications. Beebe and Fromer’s
data con-
vincingly demonstrate that short, common word marks are
becoming
–––––––––––––––––––––––––––––––––––––––––––––––––––––
––––––––
† Responding to Barton Beebe & Jeanne C. Fromer, Are We
Running Out of Trademarks? An
Empirical Study of Trademark Depletion and Congestion, 131
HARV. L. REV. 945 (2018).
∗ Associate Professor of Law, Stanford Law School. For very
helpful comments, thanks to
Daniel Ho, Mark Lemley, and the editors of the Harvard Law
Review.
1 Barton Beebe & Jeanne C. Fromer, Are We Running Out of
Trademarks? An Empirical Study
of Trademark Depletion and Congestion, 131 HARV. L. REV.
945 (2018).
2 See Qualitex Co. v. Jacobson Prods. Co., 514 U.S. 159, 162
(1995).
3 JOHN STUART MILL, AUTOBIOGRAPHY OF JOHN
STUART MILL 102 (Columbia Univ.

Press 1960) (1873) (“I was seriously tormented by the thought
of the exhaustibility of musical com-
binations. The octave consists only of five tones and two semi-
tones, which can be put together in
only a limited number of ways, of which but a small proportion
are beautiful . . . .”).
4 Beebe & Fromer, supra note 1, at 951.
5 NBC — Entertainment — Chimes, U.S. PAT. &
TRADEMARK OFF., https://www.uspto.gov/
trademarks/soundmarks/72349496.mp3; see also Trademark
“Sound Mark” Examples, U.S.
PAT. & TRADEMARK OFF.,
https://www.uspto.gov/trademark/soundmarks/trademark-sound-
mark-examples [https://perma.cc/A6GL-BTTW]. But note that
none of the other well-known
sound marks are such simple melodies.
6 See Oli Freke, How Many Melodies Are There?, PLUS (Nov.
6, 2014), https://plus.maths.org/
content/how-many-melodies-are-there [https://perma.cc/D54H-
ZMBF].
2018] RUNNING OUT OF (SOME) TRADEMARKS 117
depleted and congested, and they present a number of plausible
hypoth-
eses about the negative welfare impact of this trend.7 Their
findings
suggest that trademark policy has been based on false
assumptions and
should be closely reexamined. But their data cannot elucidate
the actual
costs of depletion or congestion — particularly without noting
how the

market will adapt to reduce these costs — and cannot reveal if
there are
countervailing benefits. Generating concrete evidence of these
costs and
benefits seems like a necessary next step before recommending
any sig-
nificant changes to the current trademark system. After
offering a laud-
atory evaluation of the value of Beebe and Fromer’s descriptive
work,
I explore why reforms in reaction to their research should
proceed cau-
tiously, and I suggest important avenues for future empirical
work to
build on these results.
I. TRADEMARK DEPLETION AND CONGESTION:
FROM ANECDOTE TO EVIDENCE
In a recent trademark case, the Second Circuit asserted that
“[o]ne
seller’s monopolization of a particular term does not deprive
competitors
of anything of value because the number of arbitrary or fanciful
marks
available for use is infinite.”8 No citation was given; the court
merely
echoed the conventional wisdom that trademarks are
inexhaustible.9
Similarly, forcing an infringer to change its mark has been
found to cre-
ate little competitive harm because “there are infinite other
names under
which defendants may continue to operate.”10 In some cases
where the
trademark is well-known, the “choice of a confusingly similar

mark, out
of the infinite number of marks in the world, itself supports an
inference
[of] bad faith.”11
While a few courts have recognized that competitively effective
marks might not be limitless,12 these judges have had no more
data to
–––––––––––––––––––––––––––––––––––––––––––––––––––––
––––––––
7 Beebe & Fromer, supra note 1, at 950–53.
8 Guthrie Healthcare Sys. v. ContextMedia, Inc., 826 F.3d 27,
42 (2d Cir. 2016).
9 See, e.g., Union Nat’l Bank of Tex. v. Union Nat’l Bank of
Tex., 909 F.2d 839, 847 n.18 (5th
Cir. 1990) (“Much of trademark law seems predicated on the
assumption that there is an infinite
universe of acceptable words for businesses to choose for their
names . . . .”); Mead Data Cent., Inc.
v. Toyota Motor Sales, U.S.A., Inc., 875 F.2d 1026, 1037 (2d
Cir. 1989) (Sweet, J., concurring) (as-
serting that infringers have “infinite other words to choose
from” (quoting 1954 N.Y. Legis. Ann.
49)); W.T. Rogers Co. v. Keene, 778 F.2d 334, 339 (7th Cir.
1985) (noting that “useable” trademarks
are “for all practical purposes infinite”); William M. Landes &
Richard A. Posner, Trademark Law:
An Economic Perspective, 30 J.L. & ECON. 265, 274 (1987)
(“[W]ords that will serve as a suitable
trademark are as a practical matter infinite . . . .”).
10 Lettuce Entertain You Enters., Inc. v. Leila Sophia AR,
LLC, 703 F. Supp. 2d 777, 791 (N.D.
Ill. 2010).
11 Sands, Taylor & Wood Co. v. Quaker Oats Co., 978 F.2d
947, 963 (7th Cir. 1992); see also

WSM, Inc. v. Tenn. Sales Co., 709 F.2d 1084, 1087 (6th Cir.
1983).
12 See, e.g., In re Coors Brewing Co., 343 F.3d 1340, 1346
(Fed. Cir. 2003) (“[I]n light of the very
large number of restaurants in this country . . . the potential
consequences of [assuming confusion
118 HARVARD LAW REVIEW FORUM [Vol. 131:116
cite than the many judges and scholars who have argued that
trademark
depletion and congestion are impossible. Beebe and Fromer’s
Article
will help move these discussions from anecdote to evidence.
They show
that existing registrations do in fact substantially constrain the
ability of
new competitors to use common words and short neologisms as
marks.
Their Article is teeming with striking statistics — for example,
of the
1000 most frequently used nouns or adjectives in American
English,
all 1000 were claimed within an active registration in 2014, and
the av-
erage word appeared within registrations by 745 distinct
registrants.13
Other noteworthy findings are that single-word marks cover
79% of all
word usage14 and 81% of all syllable usage,15 and that 55% of
the U.S.
population has a surname that has been claimed as a single-word
mark.16 And the real problem is likely significantly worse than

these
statistics indicate because their dataset does not include
unregistered
marks or account for the broadening scope that trademarks seem
to be
acquiring.17
This evidence suggests that the Second Circuit and other courts
quoted above are simply wrong: based on depletion and
congestion of
the most sought-after trademarks, the “monopolization of a
particular
term” does in fact deprive competitors of something that they
appear to
value. And inferring bad faith based on the choice of a similar
mark
makes less sense when one realizes that firms are focused on a
finite
subset of possible trademarks. The question is not: “Given the
infinite
supply of marks, what is the chance that defendant would have
chosen
this plaintiff’s mark?” Rather, courts should ask: “Given the
finite sup-
ply of marks that are perceived to be effective, the large number
of those
marks that are already being used in this category, and the
expected
search effort, what is the chance that defendant would have
chosen a
mark that is similar to some existing mark?”18
–––––––––––––––––––––––––––––––––––––––––––––––––––––
––––––––
between a restaurant name and a food brand] would be to limit
dramatically the number of marks

that could be used by producers of foods and beverages.”).
13 Beebe & Fromer, supra note 1, at 1016 & fig.24.
14 Id. at 985.
15 Id. at 988.
16 Id. at 986.
17 On the expansion of trademark rights, see Mark A. Lemley
& Mark P. McKenna, Owning
Mark(et)s, 109 MICH. L. REV. 137 (2010).
18 Focusing on the probability of matching a particular mark
rather than matching some mark
in the relevant population is analogous to the error in the
criminal law context of finding a match
between DNA at a crime scene and DNA in a large database and
then focusing on the probability
of that particular match rather than the probability of matching
some DNA in the database. Cf.
Jonathan J. Koehler, Error and Exaggeration in the Presentation
of DNA Evidence at Trial, 34
JURIMETRICS J. 21, 33 (1993).
For example, consider the more than 5300 breweries in the
United
States.19 If we assume that each uses an average of 10 marks
and that
there are one million effective marks for beer, the probability
that a new
brewer who hasn’t done a thorough trademark search would
choose the
same trademark as an existing brewer — say, FIREMAN20 — is
not one
in a million (0.0001%); it is [1 − (1 − 1⁄1,000,000)10×5300] ≈

5%. If there are
only 100,000 effective marks, the probability jumps to 41%.21
Of course,
if the new brewer does thoroughly search existing marks, then
the like-
lihood of choosing an existing mark decreases — but at a
corresponding
increase in the costs of entry. If nothing else, Beebe and
Fromer’s Article
should give courts a much better understanding of the difficulty
of find-
ing an unused, simple mark, and the resulting constraints that
might
cause a firm to choose a mark that is similar to others already in
use.
II. COSTS OF TRADEMARK DEPLETION
AND CONGESTION
Beebe and Fromer’s primary contribution is descriptive, but
they
also argue that the costs of depletion and congestion are
significant
enough to require policy reforms such as higher fees or
congestion pric-
ing, and a more stringent use requirement coupled with more
rigorous
auditing of the trademark register.22 “[T]he ecology of the
trademark
system is breaking down,”23 they say, and there is no “excuse
for inac-
tion.”24 They emphasize the costs to both firms and consumers,
con-
tending that new entrants face higher costs of entry or
expansion and
must settle for less effective marks, and that consumers face

higher
search costs due to firms choosing less memorable marks and
due to the
blurred distinctiveness of individual words.25
–––––––––––––––––––––––––––––––––––––––––––––––––––––
––––––––
19 Press Release, Brewers Ass’n, Steady Growth for Small and
Independent Brewers (Mar. 28,
2017), https://www.brewersassociation.org/press-releases/2016-
growth-small-independent-brewers
[https://perma.cc/X8Q7-MV9L].
20 See Jess Krochtengel, Texas Craft Brewer Blocks Calif.
Rival’s Use of ‘Fireman’ Mark,
LAW360 (Nov. 18, 2016, 7:34 PM),
https://www.law360.com/articles/864560/texas-craft-brewer-
blocks-calif-rival-s-use-of-fireman-mark
[https://perma.cc/E9VQ-9S33].
21 See Alastair Bland, Craft Brewers Are Running Out of
Names, and Into Legal Spats, NPR
(Jan. 5, 2015, 9:08 AM),
https://www.npr.org/sections/thesalt/2015/01/05/369445171/craf
t-brewers-
are-running-out-of-names-and-into-legal-spats
[https://perma.cc/X8FZ-AJRV] (noting that one
trademark lawyer “has never seen a brewery intentionally
infringe upon another’s trademarked
name” but that “with tens of thousands of brands in the
American beer market, it happens all the
time”).
23 Id. at 948.
24 Id. at 1041.
25 Id. at 1021–24, 1026–28. They also point to disturbing
examples of how cultural expression
has been harmed by trademark owners who prevent others from

using common words and expres-
sions even in nonconfusing ways, id. at 1025–26, though it is
unclear that depletion and congestion
make trademark bullying worse.
These hypothesized costs are both concerning and plausible.
But
there is not yet rigorous evidence that these mechanisms
actually create
a significant negative social welfare impact in practice. Further
empir-
ical research could help hone in on the actual costs of depletion
and
congestion, particularly given that market adaptations may
already be
mitigating what costs exist.
First, Beebe and Fromer’s argument lacks empirical support for
their assumption that depletion and consumption force entrants
to bear
significant financial burdens. Beebe and Fromer cite news
articles that
quote entrepreneurs who have trouble naming new firms or
products as
their primary evidence.26 But this evidence alone cannot show
how
trademark depletion actually affects the average costs of entry.
There
might be ways to at least approximate the financial costs: one
branding
guide estimates the low-end cost of name development and logo

creation
at $13,500.27 What remain untested are the different financial
costs that
may result depending on the particular trademark class, the size
of the
market entrant, and the depletion or congestion level of the
class.
Further empirical research would likely fill in these gaps in the
re-
search. For example, interviews with branding agents (or
branding
scholars) might clarify how much of these trademark-related
financial
costs to entry is driven by searching through existing marks,
whether
the cost is higher in more depleted classes, and how it has
changed over
time. Empirical research should also take into account the
possible ame-
liorating effect of technological changes, including the
increasing ease of
using search engines to quickly and cheaply test the
distinctiveness of
potential marks.28 In addition, technological developments
have re-
duced branding-related entry costs by making it easier to search
existing
registered marks29 or pay for low-cost searches,30 and by
allowing firms
to crowdsource logo design,31 connect online with low-cost
freelance de-
signers,32 or design their own logos.33
–––––––––––––––––––––––––––––––––––––––––––––––––––––
––––––––

26 Id. at 948–49.
27 See BILL CHIARAVALLE & BARBARA FINDLAY
SCHENCK, BRANDING FOR DUMMIES
19 (2d ed. 2015).
28 See Lisa Larrimore Ouellette, The Google Shortcut to
Trademark Law, 102 CALIF. L. REV.
351, 399–400 (2014).
29 See CHIARAVALLE & SCHENCK, supra note 27, at 127–
28.
30 See Jen Udan, How to Trademark a Name Cheaply, CHRON,
http://smallbusiness.
chron.com/trademark-name-cheaply-60984.html
[https://perma.cc/M563-5EYW].
31 See, e.g., Anthony St. Clair, Top 4 Crowdsourced Logo
Design Sites for Small Businesses,
BPLANS, https://articles.bplans.com/top-4-crowdsourced-logo-
design-sites-for-small-businesses
[https://perma.cc/Q8CD-K8SV].
32 See, e.g., Hire the Best Logo Designers, UPWORK,
https://www.upwork.com/hire/logo-
designers [https://perma.cc/GJ5U-LT32].
33 See, e.g., Maggie Aland, Best Logo Design Software: Tailor
Brands vs Logo Garden vs
Withoomph, FITSMALLBUSINESS.COM (Dec. 26, 2016),
https://fitsmallbusiness.com/best-logo-
design-software [https://perma.cc/WHD5-JC7V].
Another way to empirically tackle the problem of measuring the
costs of depletion and congestion may be through comparisons
with
other countries.34 The United States is an outlier in requiring

trademark
use to maintain registration, so if depletion and congestion
“have
reached chronic levels”35 in the United States, trademark
systems in
other countries should presumably be on life support. If Beebe
and
Fromer are correct, one would thus expect trademark
development costs
to be a significant barrier to entry outside the United States.
There is a
vast literature on how variations in regulatory barriers affect
entrepre-
neurship across countries;36 investigating how trademarks
affect these
barriers seems like an important avenue for further research.
Empirical work is also needed to understand the other
hypothesized
cost to new entrants: that after bearing this “ever-greater cost”
to find a
usable mark, applicants are forced to settle for “ever-less
benefit.”37
Beebe and Fromer argue with some support from the branding
litera-
ture that the areas of greatest trademark depletion and
congestion —
common words and neologisms — are also those with the most
desirable
trademarks.38 But it does not necessarily follow that a firm’s
inability
to use a common word or short neologism, such that it is left
with a
more complex mark than it initially desired, will have a
significant im-
pact on the firm’s value. The branding literature on “good”39

trade-
marks that Beebe and Fromer discuss does little to answer this
question.
Whether more complex marks actually reduce firm value is
linked
to the corresponding concern for consumer welfare: do these
marks in
fact significantly increase search costs for consumers? This is a
cogent
hypothesis, as is the idea that congestion will harm consumers
by blur-
ring the distinctiveness of nonfamous marks. But given the
difficulty
scholars have had finding any concrete harm caused by blurring
of fa-
mous marks,40 it seems worth empirical study. Furthermore, to
deter-
mine whether reforms such as decluttering the register of
underused
–––––––––––––––––––––––––––––––––––––––––––––––––––––
––––––––
34 International coordination may also be practically important
for implementing Beebe and
Fromer’s proposal for a heightened use requirement that applies
to foreign applicants as well as
U.S. applicants. See Crocker Nat’l Bank v. Can. Imperial Bank
of Commerce, 223 U.S.P.Q. 909,
927–28 (T.T.A.B. 1984) (holding that the Paris Convention for
the Protection of Industrial Property
requires that the Lanham Act be interpreted to allow foreign
nationals to register without demon-
strating use).
36 See, e.g., Leora Klapper et al., Entrepreneurship and Firm

Formation Across Countries, in
INTERNATIONAL DIFFERENCES IN ENTREPRENEURSHIP
129 (Josh Lerner & Antoinette
Schoar eds., 2010).
38 Id. at 964–70.
39 Id. at 969.
40 See Barton Beebe, Roy Germano, Christopher Jon Sprigman
& Joel Steckel, Is Trademark
Dilution a Unicorn? An Experimental Investigation (May 9,
2017) (unpublished manuscript),
marks will have any impact, it is necessary to determine how
much of
any consumer harm from depletion and congestion is caused by
these
inactive marks as opposed to a growing number of active
brands.
Unfortunately, the most concrete evidence of consumer harm
Beebe
and Fromer present seems insufficient to take as proof that the
current
trademark regime reduces consumer welfare. The Article
argues that
“trademark congestion can literally kill”41 because “between
eight and
twenty-five percent of medication errors are attributed to name
confu-
sion.”42 There is reason to doubt this statistic.43 But in any
case, the

pharmaceutical industry is not a good illustration of the harms
Beebe
and Fromer are focused on; as they note, it has low rates of
congestion
and depletion, and different branding practices.44 Given the
high non-
trademark-related barriers to entry, it seems unlikely that
reforms
related to trademark pricing or use requirements would have
much ef-
fect. Rather, any harms from drug-name confusion seem better
ad-
dressed by the computer systems that are already being used to
tackle
this concern.45
Another reason to exercise caution before implementing major
trade-
mark reforms is that markets may already mitigate at least some
of the
costs of depletion and congestion. For example, Beebe and
Fromer sug-
gest that “trademark law can more generally learn” from the
Food and
Drug Administration’s efforts in the pharmaceutical industry.46
Perhaps
one lesson from the pharmaceutical industry is that many harms
of con-
gestion and depletion can be addressed without any change in
trade-
–––––––––––––––––––––––––––––––––––––––––––––––––––––
––––––––
https://ssrn.com/abstract=2960082; see also Rebecca Tushnet,
Gone in Sixty Milliseconds: Trade-
mark Law and Cognitive Science, 86 TEX. L. REV. 507 (2008).

42 Id. at 1027–28.
43 Beebe and Fromer cite Amy Nordrum, Why Do Prescription
Drugs Have Such Weird Names?
Blame Branding Consultants and the FDA, INT’L BUS. TIMES
(June 24, 2015, 1:33 PM), http://
www.ibtimes.com/why-do-prescription-drugs-have-such-weird-
names-blame-branding-consultants-
fda-1981819 [https://perma.cc/ZG5T-T75S], which says that “8
to 25 percent of medication errors
were said to be caused by drugs sounding too much alike” based
on Ruth Filik et al., Drug
Name Confusion: Evaluating the Effectiveness of Capital (“Tall
Man”) Letters Using Eye Movement
Data, 59 SOC. SCI. & MED. 2597, 2597 (2004), which sources
the twenty-five percent figure from
James M. Hoffman & Susan M. Proulx, Medication Errors
Caused by Confusion of Drug Names,
26 DRUG SAFETY 445, 445 & 451 n.4 (2003), which bases this
number on unsubstantiated industry
sources such as Cynthia H. Starr, When Drug Names Spell
Trouble, DRUG TOPICS, May 15, 2000,
at 49 (quoting, for support of the twenty-five percent figure,
Susan M. Proulx, who is the president
of a for-profit organization focused on recognizing medical
errors).
45 See MEDICATION ERRORS 178–79 (Michael R. Cohen
ed., 2d ed. 2007). There are also
numerous patents focused on technological solutions to this
problem. See, e.g., Systems and Meth-
ods for Look-Alike Sound-Alike Medication Error Messaging,
U.S. Patent No. 7,716,068 (filed Jan.
9, 2003).

mark law itself. If consumers have trouble keeping track of the
explod-
ing number of craft beers,47 they can keep track of favorites
with the
Untappd app — including by scanning barcodes rather than
searching
by name.48 Consumers can scan barcodes or take pictures of
other prod-
ucts to see reviews and prices with shopping tools such as the
Amazon
app.49 The drawbacks of longer brand names also are less
significant if
consumers simply search for the desired product type using
websites like
Amazon or Google and then choose a product based on its
prominence
in the search results, giving them little reason to pay attention
to the
brand name.
The market for domain names may be instructive. As Beebe and
Fromer note, appealing domain names are limited.50 But they
also rec-
ognize that technological developments such as the availability
of inter-
net search tools and the creation of “new top-level domains”
have alle-
viated many of the problems associated with the limited supply
of the
most desirable domain names.51 Similarly, new technologies
may be

able to reduce the negative externalities of constraints on
attractive
trademarks: if consumers can find products with unusual
trademarks
through search engines, then firms can decrease attempts to find
the
most desirable trademarks because they know consumers have
alterna-
tive effective means to identify their goods.
In sum, there is not yet any concrete evidence that trademark
deple-
tion and congestion impose any significant harms for either
firms or
consumers. Without such evidence, reforming the trademark
system
seems premature and likely unresponsive to the actual
challenges firms
and consumers face. Of course, one response might be that
policy re-
forms are still warranted simply to counteract a plausible risk of
harm.
But that would only be true if there were no offsetting benefits
— some-
thing Beebe and Fromer never consider.
–––––––––––––––––––––––––––––––––––––––––––––––––––––
––––––––
47 See supra notes 19–21 and accompanying text.
48 See Billy Steele, Beer-Tracking App Untappd Gets Barcode
Scanning, Hails an Uber,
ENGADGET (Feb. 9, 2016),
https://www.engadget.com/2016/02/09/untappd-update-barcode-
scanning-uber [https://perma.cc/AJT9-BE5Q].
49 Amazon Mobile LLC, Amazon Shopping, GOOGLE PLAY,
https://play.google.com/store/

apps/details?id=com.amazon.mShop.android.shopping&hl=en
[https://perma.cc/TQ9Z-9FSZ] (list-
ing a feature that allows users to “[s]can product barcodes and
images to compare prices and check
availability using Scan It”); see also Chandra Steele, The Best
Shopping Apps to Compare Prices,
PC MAG. (Dec. 3, 2017, 8:20 PM),
https://www.pcmag.com/feature/290959/the-best-shopping-
apps-
to-compare-prices [https://perma.cc/6DYS-W6VB].
51 Id.
III. POTENTIAL BENEFITS
OF …
Unit II:
Cultural and Social
Influences
Course Learning Objectives for Unit II
2. Relate consumer behavior to public policy issues.
2.1 Discuss how a company’s advocacy for environmental
issues or
other socially conscious public policy issues would impact a

buying
decision.
4. Examine how consumers are influenced by values as members
of a
particular culture.
4.1 Describe how a consumer’s cultural values and norms
would
influence a buying decision.
7. Explain the steps of the consumer decision-making process.
7.1 Explain the steps of the consumer decision-making process
and
how a decision progressed through each step.
Cultural Influences
• Culture systems: This entails ecology, social
structure, and ideology.
• Cultural values are listed below.
– Core values uniquely define a culture.
– Customs controls basic behaviors.
– Norms are customs with a strong moral overtones.
– Conventions are norms that regulate everyday lives.
Marketing and Culture

• Cultural selection: These choices we have are the culmination
of
a filtration process.
• Many factors influence the way consumers view products and
style.
• Culture production system: This is a set of individuals who
create
and market a cultural product.
– Create subsystem.
– Initiate managerial subsystem.
– Implement communications subsystem.
Reality Engineering
• Reality engineering: This occurs when marketers
appropriate elements of popular culture and use
them as promotional vehicles.
• Product placement: This is the insertion of real
products in fictional movies, TV shows, etc.
• Advergaming: This is when online games merge with
advertisements that let companies target specific
consumers.
Cultural Stories and Ceremonies

• Sacred consumption: This occurs
when consumers set apart objects
and events from normal activities and
treat them with respect and awe.
• Myth: This is a story with symbolic elements that
represent a culture’s ideals.
• Rituals: This is a set of multiple, symbolic behaviors
that occur in a fixed sequence (e.g., grooming, gift-
giving, holidays, rites of passage).
Candlelight
(Pexels, 2016)
Global Consumer Culture
• Standardized strategy vs. localized
strategy
• Hofstede’s dimensions of national
culture are listed below:
– Power distance, individualism vs.
collectivism, masculinity vs.
femininity, uncertainty avoidance,
long-term vs. short-term
orientation, and indulgence vs.
restraint.
Global culture
(Geralt, 2014)

• Global consumer culture unites people around the world by
their devotion to brand-name consumer goods, movie stars,
leisure activities, etc.
Business Ethics and Consumer Rights
• Business ethics are rules that guide actions in the
marketplace.
• Unhappy consumers can utilize the mediums below:
– voice response, private response, and third-party
response.
• Market regulation ensures marketers provide reliable
information about a reliable product.
Policy Issues
• Data privacy: How much should
companies know about their
consumers?
• Identity theft: This occurs when
someone steals one’s personal
information and uses it.
• Market access: This is the ability
to find and purchase goods and
services.
– disabilities, literacy, food

desert
Components of digital marketing
(Maialisa, 2016)
Environmental
– A financial bottom line provides
profit.
– A social bottom line gives back to
the community.
– An environmental bottom line
minimizes damage to the
environment.
• Green marketing is a strategy to
promote environmentally
friendly products.
• Product disposal can include an
exchange, a disposal, a return,
and a reuse.
Global environment
(Clker-Free-Vector-Images, 2012)
• Triple-bottom line orientation is described below.
Dark Side of Consumer Behavior

• Consumer terrorism: This can be bioterrorism (food)
or cyber-terrorism.
• Addictive consumption: This is a physiological
dependency on products or services (e.g., addiction
to technology).
• Compulsive consumption: This is repetitive shopping.
• Consumed consumers: These are people who are
used for commercial gain.
References
Clker-Free-Vector-Images. (2012). Recycle [Image]. Retrieved
from
https://pixabay.com/en/recycle-green-earth-environment-29227/
Geralt. (2014). Global culture [Image]. Retrieved from
https://pixabay.com/en/globalization-policy-society-452692/
Maialisa. (2016). Globalization mindmap [Image]. Retrieved
from
https://pixabay.com/en/marketing-blog-graphic-digital-1320699/
Pexels. (2016). Candle blurred [Image]. Retrieved from
https://pixabay.com/en/blurred-bokeh-candle-candlelight-
1869271/
This presentation is
copyrighted by Columbia

Southern University.
Use of this video without the express
written consent of Columbia Southern
University is prohibited.
MAR 3211, Consumer Behavior 1
Course Learning Outcomes for Unit II
Upon completion of this unit, students should be able to:
2. Relate consumer behavior to public policy issues.
2.1 Discuss how a company’s advocacy for environmental
issues or other socially conscious public
policy issues would impact a buying decision.
4. Examine how consumers are influenced by values as members
of a particular culture.
4.1 Describe how a consumer’s cultural values and norms would
influence a buying decision.
7. Explain the steps of the consumer decision-making process.
7.1 Explain the steps of the consumer decision-making process
and how a decision progresses

through each step.
Course/Unit
Learning Outcomes
Learning Activity
2.1
Unit Lesson
PowerPoint Presentation
Case Study
4.1
Unit Lesson
Morrison (2014) article
Garrett and Toumanoff (2010) article
Wu (2013) article
Case Study
7.1
Unit Lesson
Shugan (2006) article
Case Study
Reading Assignment
In order to access the following resources, click the links
below.
Click here to access the Unit II PowerPoint presentation. (Click

here to access a PDF version of the
presentation.)
Read pp. 3–20 of the article below.
Garrett, D. E., & Toumanoff, P. G. (2010). Are consumers
disadvantaged or vulnerable? An examination of
consumer complaints to the Better Business Bureau. Journal of
Consumer Affairs, 44(1), 3–23.
Retrieved from
https://libraryresources.columbiasouthern.edu/login?auth=CAS
&url=http://search.ebscohost.com/logi
n.aspx?direct=true&db=bth&AN=48392630&site=ehost-
live&scope=site
Morrison, M. (2014). Subway draws teens with online series.
Advertising Age, 85(21), 18. Retrieved from
&url=http://search.proquest.com.library
resources.columbiasouthern.edu/docview/1612406793?accounti
d=33337
UNIT II STUDY GUIDE
Cultural and Social Influences
https://online.columbiasouthern.edu/bbcswebdav/xid-
68746810_1
https://online.columbiasouthern.edu/bbcswebdav/xid-
68746794_1
&url=http://search.ebscohost.com/login.aspx?direct=true&db=bt

h&AN=48392630&site=ehost-live&scope=site
&url=http://search.proquest.com.libraryresources.columbiasouth
ern.edu/docview/1612406793?accountid=33337
&url=http://search.proquest.com.libraryresources.columbiasouth
ern.edu/docview/1612406793?accountid=33337
UNIT x STUDY GUIDE
Title
Shugan, S. M. (2006). Are consumers rational? Experimental
evidence? Marketing Science, 25(1), 1–7.
Retrieved from
&url=http://search.ebscohost.com/logi
n.aspx?direct=true&db=bth&AN=19991302&site=ehost-
live&scope=site
Wu, M.-Y. (2013). Cultural influences on consumers' on-line

shopping preferences: A cross-cultural study of
Taiwan and the United States. China Media Research, 9(3), 42–
51. Retrieved from
http://go.galegroup.com.libraryresources.columbiasouthern.edu/
ps/i.do?p=AONE&sw=w&u=oran9510
8&v=2.1&it=r&id=GALE%7CA340944540&asid=31c7f613b66e
d050c03e982e780ee098
Unit Lesson
What do you think of when you think of culture? Think about
your own personal culture and all of the
behavioral characteristics and practices associated with it. A
culture is a society’s personality, including its
values and ethics that are held within each group. At its core,
culture is defined as the accumulation of shared
meanings, rituals, norms, and traditions. Looking at the concept
of value, this is defined as a belief that some
condition is preferable to its opposite. For instance, everyone
values health, wisdom, and peace, but there are
numerous values that are specific to different groups. Applying
these values to cultures, there must be an
understanding that each culture places different levels of
importance on certain values, and this defines each
culture as unique. Certain cultures identify with certain
products and services that members seek and/or
avoid. There are several major microcultures in the United
States as identified below.
certain geographical locations.

the societal expectations for men and
women.
-based microculture: These are cultures that imply that
people within the same age group share
similar values.
the characteristics of certain
generations.
religious affiliations and their beliefs.
re cultures that belong to certain
ethnic heritages.
practice certain lifestyles, opinions,
attitudes, and behaviors of a certain social class
Cultures are continually evolving and adapting to the changing
times and needs of society. With the transient
lifestyles today, people are sometimes placed into a situation of
learning the behaviors of another culture,
which is referred to as acculturation. Large corporations that
regularly transfer their employees benefit from
sophisticated services provided to these transferees, which
assist them and their families with this
acculturation process. Many of the elements within various
cultures could be considered as rituals. By
definition, a ritual is a set of multiple symbolic behaviors that
occur in a fixed sequence that tend to be
repeated. Examples of these related to consumption would be

gift giving, holiday observances, and grooming.
Think about some of your personal rituals. This could include
your morning trip to Starbucks, Friday night
pizza, Thursday morning grocery run, or your 7 a.m. workout
routine.
From a marketing standpoint, failure to understand a group’s
cultures and rituals could result in a product
failing in one culture and being highly successful in another. In
an attempt to further understand the
consumer, it is important to differentiate between sacred and
profane consumption. In general, sacred
consumption is something that consumers consider as special
and outside of the daily norm. Many times, this
is associated with religion but can be applied to other areas as
well. For instance, a once-in-a-lifetime cruise
or the purchase of a dream home may be considered sacred
consumption. Conversely, profane consumption
refers to consumer objects and events that are considered
ordinary, everyday objects and events that do not
share the special characteristics. This could include items on a
weekly grocery list or textbooks for classes.
Again, marketers need to understand these consumption patterns
and how they apply to the consumers that
are in their target market.
ps/i.do?p=AONE&sw=w&u=oran95108&v=2.1&it=r&id=GALE
%7CA340944540&asid=31c7f613b66ed050c03e982e780ee098

ps/i.do?p=AONE&sw=w&u=oran95108&v=2.1&it=r&id=GALE
%7CA340944540&asid=31c7f613b66ed050c03e982e780ee098
UNIT x STUDY GUIDE
Title
As our world is becoming increasingly flat, it is important to
apply the cultural discussion to the global
consumer culture. The advent of increased technology has made
communication easier and faster. Brands
can unite people around the world with a common devotion.
Having said that, companies need to
understand the different value systems within each culture and
possibly adapt to the needs in that culture.
Companies can take several different approaches with respect to
global marketing. The first is to adopt a
standardized strategy that tends to focus on the commonalities
of cultures. Companies such as Coca-Cola
employ this strategy with relatively standardized formulations,
packaging, positioning, and distribution. This
approach can save the company time and money in its marketing
efforts as a single standard marketing
approach is employed across many countries. It also creates
opportunities to present a unified, well-known
branding approach.
As not every market has the same needs, this approach might

not be effective with every product offered.
This warrants a discussion about another strategy identified as a
localized strategy that focuses on the
variations of needs across different cultures. This takes on the
appearance of tailored goods and products
that appeal to the local population. For instance, hamburgers in
Paris might be served with avocados, Oreos
may have a slightly different cream filling flavor to differing
taste preferences, or IKEA might adapt its
billboards to reflect appropriate dress of their models aligning
with cultural norms of a particular country. This
process can be a time-consuming and costly process as the
marketer attempts to customize the marketing
strategies directly to each individual market. A third approach
is globalization, which attempts to combine
both of the approaches above by taking a standardized product
and adapting it to the local culture. One
might consider this the best of both worlds. McDonald’s does
this well with its adaptation of its food products
to the local palates while maintaining many of the standardized
core processes that have made the company
so successful.
Another area of concern from the social standpoint is that of
ethics and public policy. Business ethics are
rules of conduct that guide actions across the marketplace or
standards that people within the culture use to
judge whether the behavior is right or wrong. This is
complicated because what is ethical in one culture may
be extremely unethical in another. Social marketing is an
emerging trend. This applies marketing techniques
to encourage positive behaviors directed at the common good of
society. Examples might include
discouraging drinking and driving, encouraging volunteering for
Relay for Life, or discouraging the abuse of
animals. Avoiding addictive behaviors and environmentalism

are also causes that would be represented
under social marketing. Many firms today employ this concept
through the integration of corporate social
Technology is increasingly making all areas of the globe
accessible.
(Ar130405, 2017)
UNIT x STUDY GUIDE
Title
responsibility (CSR) into their business models. CSR refers to
the processes that corporations have in place
to encourage members of the organization to take actions that
support social marketing causes. Examples of
this might include a firm allowing their employees to take a
workday to pack food at the local food pantry.
Companies will many times take this a step further, aligning
their company with a certain cause that
generates business and societal benefits at the same time. An
example of this is Kraft Foods aligning with
United Way.
Directly related to social marketing and CSR is the consumer
trend of preferring products that represent
environmental stewardship and sustainability. Green marketing
is a response to this whereby the firm
chooses to protect or enhance the natural environment within its

business model. While consumers prefer
this, they are not always willing to pay extra for these products,
and that brings forward the dilemma for firms.
Another area of pivotal concern is that of data privacy and
identity theft. As the firm attempts to learn more
about the consumer in order to serve his or her needs, there
appears a line where the consumer believes that
the firm knows too much about him or her. This can lead to
fears of identity theft and various other security
issues, creating a complicated scenario for companies. As our
world continues to evolve and become more
diverse, creating marketing messages that are relevant to each
diverse group of potential buyers becomes
increasingly complicated. Recognizing the need to completely
understand cultural and social influences and
their impact on consumer buying habits will lead to a more
effective marketing program for the company.
On a related topic, think about how you personally make
consumer buying decisions. What steps do you
move through as you make the decision to either buy or not buy
the product? Look at the steps below.
As marketers develop an understanding of these steps, they are
able to better provide the products/services
that their target market is interested in purchasing.
Additionally, they are able to provide the right level of
communication and marketing as well as the right pricing model
that will attract the target market.
Reference

Ar130405. (2017). Global, technology, network, globe [Image].
Retrieved from https://pixabay.com/en/global-
technology-network-globe-2082635/
Table 1.1: The illustration shows how consumers make buying
decisions.
Problem recognition:
Consumer realizes that there
is a need or problem
Information search: Consumer
searches for information on
what products/services might
fulfill the need
Evaluation of alternatives:
Consumer contemplates
between alternatives,
weighing benefits and
disadvantages
Product choice: Consumer
selects from the alternatives
Post purchase: Consumer

decides if this was a good
purchase
SPRING 2010 VOLUME 44, NUMBER 1 3
DENNIS E. GARRETT AND PETER G. TOUMANOFF
Are Consumers Disadvantaged or Vulnerable?
An Examination of Consumer Complaints
to the Better Business Bureau
Questions have emerged recently about the appropriateness of
defining
disadvantaged consumers based on their membership in certain
demographic categories, such as income, age, education, and
race.
This study assessed whether these traditional classifications are
useful
for understanding consumer complaining behavior with the
Better
Business Bureau. Results of analysis of more than 24,000
consumer
complaints filed with a local BBB office during a 13-year
period
do not provide consistent support for this disadvantaged
consumer
perspective. Instead, the emerging vulnerable consumer
perspective
may provide a more promising basis for future research.
The Better Business Bureau is the third-party complaint agency

most commonly used by dissatisfied consumers who are unable
to
obtain redress from companies (Best and Andreasen 1977;
Duhaime
and Ash 1979; Lee and Soberon-Ferrer 1996). In theory, the
BBB
may be a helpful ally of consumers, particularly those who are
most
disadvantaged in our society, as they struggle to resolve their
complaints
with businesses (Fisher et al. 1999). However, many studies
over
the years have investigated consumer usage of third-party
complaint
agencies and concluded that these agencies are primarily not
used by
disadvantaged consumers in our society. Instead, prior research
claims to
show that younger, nonminority consumers with relatively high
incomes
and educational levels are more likely to take advantage of
services from
third-party agencies, like the BBB.
The research of this report takes a new look at the conceptual
and methodological challenges involved in analyzing
disadvantaged
consumer usage of complaint services available through the
BBB.
Regarding conceptual issues, considerable debate has emerged
in recent
years regarding the appropriate definition of disadvantaged
consumers.
Dennis E. Garrett ([email protected]) is an Associate Professor
of Marketing and

Peter G. Toumanoff ([email protected]) is an Associate
Professor of Economics, both
at Marquette University. The authors appreciate the support for
this project from the Better Business
Bureau of Wisconsin.
The Journal of Consumer Affairs, Vol. 44, No. 1, 2010
ISSN 0022-0078
Copyright 2010 by The American Council on Consumer
Interests
4 THE JOURNAL OF CONSUMER AFFAIRS
Most of the prior research in this area has focused on certain
categories
of consumers as being disadvantaged due to their age, income,
education,
or racial/ethnic membership (e.g., Barnhill 1972; Andreasen
1975, 1976,
1993; Stein 1980; Bernhardt 1981; Singh 1989). In sharp
contrast,
Baker, Gentry, and Rittenburg (2005) have argued strongly that
this
approach is inappropriate because it suggests that all members
in these
categories are always at risk as consumers. Instead, they suggest
that
research should focus on the concept of vulnerable consumers
rather
than disadvantaged consumers. They assert that any individual
consumer,
regardless of membership in any particular class, may at various
times experience vulnerability in the marketplace. However,
Commuri

and Ekici (2008) have recently countered that researchers
should still
recognize the value of focusing on some categories of
consumers as
being more likely to be vulnerable than some other categories.
They
suggest that the traditional disadvantaged consumer
conceptualization
based on demographic categories may indeed be useful and
should not
be abandoned. Therefore, this study hopes to shed light on
which of these
two approaches, disadvantaged consumers or vulnerable
consumers, may
provide a stronger conceptual foundation for future research.
Beyond these conceptual issues, most research studies in this
area
have asked consumers to complete mail surveys in which they
were
instructed to recall a prior unsatisfactory purchase experience
and then
describe what they did in response to this single episode. This
method has
potentially serious limitations and leading researchers have long
argued
that alternative research methods should be used (Andreasen
1988; Singh
1989).
To address these conceptual and methodological issues, this
study
takes a fresh look at consumer usage of BBB complaint
services. Rather
than relying on consumers’ self-reports of complaint behavior,
this study

analyzes consumer complaints from a local BBB office and
matches
the complainants’ zip codes with U.S. Census Bureau data
regarding
the characteristics of consumers in these zip code areas.
Because the
proportion of potentially disadvantaged consumers varies
widely across
the zip code areas included in this study, this approach may
provide
a clearer view of the degree to which certain categories of
consumers
actually seek redress from the BBB. From our review of prior
research of
consumer usage of third-party complaints, this appears to be the
first time
this methodological approach has been used to address these
research
questions.
The remainder of this paper is organized as follows. First, the
debate
regarding disadvantaged versus vulnerable consumers is
discussed in
more detail. Then prior research of consumer use of the BBB as
a third-
party complaint agency is reviewed. After that, the research
methods
used in prior studies are discussed in more detail. Then the
specific
hypotheses addressed in this study are presented and the

methods used
to address these hypotheses are explained. Finally, the results of
this
study are presented and the significance of these findings
discussed.
DISADVANTAGED OR VULNERABLE CONSUMERS:
CONCEPTUAL ISSUES
Developing a conceptualization of consumer vulnerability that
is
widely accepted by researchers has proven to be exceedingly
elusive and
complex (Andreasen and Manning 1990; Brenkert 1998;
Halstead, Jones,
and Cox 2007; Mansfield and Pinto 2008). The term
“disadvantaged” was
commonly used in earlier research studies to describe those
categories of
consumers who were potentially most at risk in the market. In
his seminal
book The Disadvantaged Consumer, Andreasen (1975, 7)
asserted
The disadvantaged consumer hypothesis argues that the
problems of disadvan-
taged consumers are primarily attributable to their personal
characteristics, the
kind of people they are. It holds that the real problem is that
disadvantaged
consumers are just too old, too poor, too uneducated, too
unsophisticated, too
definitely of the wrong race, etc., to be able to be effective
consumers in the urban
marketplace.

Following this classification approach, considerable research
has
focused on the following four demographic variables as being
the
most definitive markers of a consumer’s potential vulnerability
in the
marketplace:
1. Income: The poor are considered to be vulnerable compared
to con-
sumers with higher incomes (Barnhill 1972; Andreasen 1975,
1976,
1988, 1993; Stein 1980; Morgan and Riordan 1983; Kolodinsky
et al. 2005).
2. Age: The elderly are considered to be vulnerable because
they
have more difficulty than younger people navigating the
marketplace
(Barnhill 1972; Andreasen 1975, 1976, 1988; Morgan and
Riordan
1983).
3. Education: Vulnerable consumers include individuals who
have
received less formal education (Andreasen 1975, 1988, 1993;
Smith
and Cooper-Martin 1997; Mitra et al. 1999; Ringold 2005).
4. Race and ethnicity: A number of studies have concentrated on
the challenges faced primarily by African-American consumers

and Hispanic consumers (Andreasen 1975, 1976, 1982, 1988;
Stein 1980; Morgan and Riordan 1983; Penaloza 1995; Smith
and
Cooper-Martin 1997; Crockett, Grier, and Williams 2003;
D’Rozario
and Williams 2005; Marlowe and Atiles 2005). Minority
immigrants
with poor English-language skills are included among
disadvantaged
consumers (Barnhill 1972; Andreasen 1982; Marlowe and Atiles
2005).
More recently, this conceptualization of disadvantaged
consumers
based on membership in certain demographic categories has
been
sharply criticized (Ringold 1995, 2005; Baker, Gentry, and
Rittenburg
2005). They argue that it is inappropriate because it implies that
some
consumers are always vulnerable, simply because of their
membership
in a certain class. Instead, Baker, Gentry, and Rittenburg (2005)
assert
that a comprehensive, individual-based conceptualization is
more robust
and is more appropriate for understanding and researching
vulnerable
consumers:
Consumer vulnerability is a state of powerlessness that arises
from an imbalance
in marketplace interactions or from the consumption of
marketing messages
and products. It occurs when control is not in an individual’s
hands, creating

a dependence on external factors (e.g., marketers) to create
fairness in the
marketplace. The actual vulnerability arises from the interaction
of individual
states, individual characteristics, and external conditions within
a context where
consumption goals may be hindered and the experience affects
personal and social
perceptions of self. (p. 134)
However, their proposed conceptualization of vulnerable
consumers
has not been met with universal acceptance. Using a
macromarketing per-
spective to defend the traditional definition of disadvantaged
consumers,
Commuri and Ekici (2008) have argued that this newer
conceptualization
of consumer vulnerability ignores marketplace realities. They
suggest that
researchers should acknowledge that unscrupulous marketers
may target
certain types of consumers and therefore some classes of
consumers are
more likely than others to be at risk at some point. They
propose that
“the key, therefore, is to rethink our classification system and
capture
the relevant classificatory variables but not to abandon a class-
based per-
spective altogether” (p. 185). By better understanding which
categories
of consumers may be most at risk, they argue that public policy
deci-
sion makers will be able to proactively establish necessary rules
and

regulations to protect these groups.
Given this ongoing debate, one of our goals is to determine
which
of these two opposing conceptualizations, disadvantaged
consumers
or vulnerable consumers, may be more appropriate for
understanding
complaining behavior. More specifically, as suggested by
Commuri
and Ekici (2008), we seek to determine which, if any,
classification
variables are useful for understanding disadvantaged consumer
usage of
the BBB. The next section reviews prior empirical research
regarding the
complaining behavior of disadvantaged and vulnerable
consumers.
COMPLAINING BEHAVIOR OF DISADVANTAGED AND
VULNERABLE CONSUMERS
Disadvantaged or vulnerable consumers may potentially be
affected
at various stages of the consumption process. In the beginning
of
the buying process consumers may lack the skills, education,
liter-
acy or experience to gather the requisite information to evaluate
the
relative quality of competitive products and vendors in the

market
(Barnhill 1972; Andreasen 1975; Marlowe and Atiles 2005;
Adkins
and Ozanne 2005a). In addition, due primarily to their lower
incomes,
they may lack the mobility to travel to shop at more attractive
and
desirable stores (Andreasen 1976, 1993; Stein 1980). When they
do
interact with salespeople, they may face discriminatory
practices, higher
prices and lower levels of customer service (Andreasen 1976,
1982;
Stein 1980; Crockett, Grier, and Williams 2003). Finally, if they
do
experience an unsatisfactory purchase, disadvantaged consumers
may
lack the resources needed to seek appropriate redress
(Andreasen
1975, 1976).
This last stage in the consumption process, seeking redress for
an
unsatisfactory purchase, is of particular interest in this study. In
their
earlier review of research in this area, Andreasen and Manning
(1990,
14) noted, “Despite the fact that vulnerable consumers often
have more
to lose if something goes wrong with a purchase, they seem less
likely
than other consumers to do something about it.” Similarly,
Halstead,
Jones, and Cox (2007) recently concluded from their qualitative
research
that disadvantaged consumers often fail to complain when they

are
dissatisfied. This apparent reticence on the part of
disadvantaged or
vulnerable consumers to complain is troubling. One would hope
that
those consumers who are most at risk and have the most to lose
from
their dissatisfying purchase experiences would actually be more
inclined
to push forward with their complaints.
The BBB, with 125 local offices throughout the United States
and
Canada, plays a potentially pivotal role in the consumer
complaining
behavior process, especially as it relates to disadvantaged or
vulnerable
consumers. Although consumers may now choose to express
their
dissatisfaction against companies in online forums (Cho et al.
2002;
Ward and Ostrom 2006), the BBB has maintained its relevance,
as the
number of consumer complaints filed with the BBB increased
from
626,081 in 2002 to 862,128 in 2008. The BBB strongly
encourages
dissatisfied consumers to contact companies directly, but the
BBB will
accept consumer complaints even if this step is not taken.
Therefore, for

disadvantaged or vulnerable consumers who are either unwilling
to seek
or unable to achieve resolution for their complaints from
companies, the
BBB offers a viable option for them to pursue.
However, do disadvantaged or vulnerable consumers actually
take
advantage of the complaint services offered by the BBB? Not
surpris-
ingly, this important question has attracted considerable
research attention
over the past few decades. Because the bulk of this research has
adopted
the category-based conceptualization of disadvantaged
consumers, this
review is organized on the leading classification variables of
income,
age, education, and minority status, as shown in Table 1.
Income
In general, the research regarding the relationship between a
con-
sumer’s income and his/her subsequent complaining behavior is
quite
consistent. A number of prior studies have shown that lower-
income con-
sumers are less likely than higher-income consumers to engage
in any
form of complaining behavior. Similarly, most previous
research has also
shown that lower-income consumers are less likely than higher-
income
consumers to seek assistance from third-party agencies. The one
excep-

tion is a study by Hogarth et al. (2001) that concluded that
lower-income
consumers were more likely to use third-party agencies.
Age
The research regarding the impact of age on complaining
behavior is
also fairly consistent. Most prior studies have shown that older
consumers
are generally less likely than younger consumers to complain
about their
dissatisfaction. Regarding the specific use of third-party
complaint agents,
older consumers are also reportedly less likely than younger
consumers
to pursue this option, according to the results of most studies.
However,
studies by Bernhardt (1981) and Hogarth, English, and Sharma
(2001)
found that older consumers were more likely than younger
consumers to
use third-party agencies.
T
A
B
L
E
1

D
is
a
d
va
n
ta
g
ed
C
o
n
su
m
er
C
o
m
p
la
in
in
g
B

eh
a
vi
o
r
L
it
er
a
tu
re
R
ev
ie
w
D
is
ad
va
nt
ag
ed
V

ar
ia
bl
e
T
yp
e
of
C
om
pl
ai
ni
ng
D
is
ad
va
nt
ag
ed
C
on
su

m
er
s
C
om
pl
ai
n
M
or
e
D
is
ad
va
nt
ag
ed
C
on
su
m
er
s

C
om
pl
ai
n
L
es
s
In
co
m
e
G
en
er
al
co
m
pl
ai
ni
ng
A
nd

re
as
en
(1
98
8)
;
B
ea
rd
en
(1
98
3)
;
F
ra
nc
ke
n
an
d
va
n

R
aa
ij
(1
98
5)
;
L
ie
fe
ld
,
E
dg
ec
om
be
,
an
d
W
ol
fe
(1

97
5)
;
M
or
ga
ns
ky
an
d
B
uc
kl
ey
(1
98
7)
;
M
oy
er
(1
98
4)

;
T
A
R
P
(1
98
6)
;
V
ol
ko
v,
H
ar
ke
r,
an
d
H
ar
ke
r
(2

00
5)
In
co
m
e
T
hi
rd
-p
ar
ty
co
m
pl
ai
ni
ng
H
og
ar
th
et
al

.
(2
00
1)
A
nd
re
as
en
(1
98
8)
;
D
uh
ai
m
e
an
d
A
sh
(1
97

9)
;
H
og
ar
th
,
E
ng
li
sh
,
an
d
S
ha
rm
a
(2
00
1)
;
L
ie

fe
ld
,
E
dg
ec
om
be
,
an
d
W
ol
fe
(1
97
5)
;
S
in
gh
(1
98
9)

;
V
ol
ko
v,
H
ar
ke
r,
an
d
H
ar
ke
r
(2
00
5)
A
ge
G
en
er
al

co
m
pl
ai
ni
ng
L
ee
an
d
S
ob
er
on
-F
er
re
r
(1
99
6)
A
nd
re

as
en
(1
98
8)
;
B
ea
rd
en
(1
98
3)
;
L
ie
fe
ld
,
E
dg
ec
om
be

,
an
d
W
ol
fe
(1
97
5)
;
M
oy
er
(1
98
4)
;
S
in
gh
(1
98
9)
;

T
A
R
P
(1
98
6)
;
W
ar
la
nd
,
H
er
rm
an
n,
an
d
M
oo
re
(1

98
4)
A
ge
T
hi
rd
-p
ar
ty
co
m
pl
ai
ni
ng
B
er
nh
ar
dt
(1
98
1)

;
H
og
ar
th
,
E
ng
li
sh
,
an
d
S
ha
rm
a
(2
00
1)
A
nd
re
as

en
(1
98
8)
;
D
uh
ai
m
e
an
d
A
sh
(1
97
9)
;
H
og
ar
th
et
al

.
(2
00
1)
;
L
ie
fe
ld
,
E
dg
ec
om
be
,
an
d
W
ol
fe
(1
97
5)

;
S
in
gh
(1
98
9)
E
du
ca
ti
on
G
en
er
al
co
m
pl
ai
ni
ng
A
nd

re
as
en
(1
98
8)
;
H
ue
fn
er
an
d
H
un
t
(2
00
0)
;
K
ol
od
in

sk
y
(1
99
3)
;
L
ee
an
d
S
ob
er
on
-F
er
re
r
(1
99
6)
;
L
ie

fe
ld
,
E
dg
ec
om
be
,
an
d
W
ol
fe
(1
97
5)
;
M
or
ga
ns
ky
an

d
B
uc
kl
ey
(1
98
7)
;
M
oy
er
(1
98
4)
;
V
ol
ko
v,
H
ar
ke
r,

an
d
H
ar
ke
r
(2
00
5)
;
W
ar
la
nd
,
H
er
rm
an
n,
an
d
M
oo

re
(1
98
4)
E
du
ca
ti
on
T
hi
rd
-p
ar
ty
co
m
pl
ai
ni
ng
H
og
ar

th
et
al
.
(2
00
1)
;
S
in
gh
(1
98
9)
A
nd
re
as
en
(1
98
8)
;
B

ea
rd
en
(1
98
3)
;
B
es
t
an
d
A
nd
re
as
en
(1
97
7)
;
D
uh
ai

m
e
an
d
A
sh
(1
97
9)
;
L
ee
an
d
S
ob
er
on
-F
er
re
r
(1
99

6)
;
L
ie
fe
ld
,
E
dg
ec
om
be
,
an
d
W
ol
fe
(1
97
5)
;
V
ol

ko
v,
H
ar
ke
r,
an
d
H
ar
ke
r
(2
00
5)
R
ac
e
G
en
er
al
co
m

pl
ai
ni
ng
∗
A
nd
re
as
en
(1
98
8)
;
B
es
t
an
d
A
nd
re
as
en

(1
97
7)
;
V
il
la
re
al
-C
am
ac
ho
(1
98
3)
R
ac
e
T
hi
rd
-p
ar

ty
co
m
pl
ai
ni
ng
H
og
ar
th
,
E
ng
li
sh
,
an
d
S
ha
rm
a
(2

00
1)
;
H
og
ar
th
et
al
.
(2
00
1)
∗ T
A
R
P
(1
98
6)
fi
nd
s

no
di
ff
er
en
ce
be
tw
ee
n
di
sa
dv
an
ta
ge
d
co
ns
um
er
s
an
d

ge
ne
ra
l
po
pu
la
ti
on
.
Education
Consumers with less formal education appear to be less likely to
complain than do more highly educated consumers. Although
most
studies have reported that less-educated consumers were less
likely to
pursue third-party actions, two studies have concluded that less-
educated
consumers were actually more likely to be third-party
complainers (Singh
1989; Hogarth et al. 2001).
Minority Consumers
TARP (1986) reported that race does not affect the likelihood of
a consumer filing a complaint. However, Best and Andreasen

(1977),
Villareal-Camacho (1983), and Andreasen (1988) argued that
minority
consumers are less likely to complain. In terms of third-party
agent usage,
recent research has reported that minority consumers are
actually more
likely than nonminority consumers to use third-party agents for
their
complaints (Hogarth, English, and Sharma 2001; Hogarth et al.
2001).
Also, Cornwell, Bligh, and Babakus (1991) concluded that the
English-
language ability of Hispanic consumers apparently does not
inhibit their
ability to file complaints with the BBB.
Because the studies by Hogarth, English, and Sharma (2001)
and
Hogarth et al. (2001) reported consistently different results
from most
other studies, their research foci and methods deserve further
attention.
Hogarth, English, and Sharma (2001) analyzed consumer
complaints
filed with the U.S. Federal Reserve complaint program. They
collected
data on consumer attitudes and behaviors by contacting
consumers
who had recently had their complaint cases closed and asking
them
to complete a mail questionnaire. Again working with the
Federal
Reserve, Hogarth et al. (2001) analyzed consumer problems
with credit
cards by conducting telephone interviews, including detailed

follow
up questions regarding how consumers dealt with their
complaints.
Although these studies focused specifically on consumer
problems
with financial services, it is not immediately clear why these
studies
reported results so different from the bulk of previous research
in this
area.
In summary, prior research generally appears to provide support
for
the hypothesis that disadvantaged consumers are less likely to
complain,
including the use of third-party complaint agencies. However,
as the
next section details, serious concerns have been raised
regarding the
methods used in these research studies. Because this prior
research relies
heavily on self-reported data regarding complaining behavior, a
different
method of collecting data may help to clarify the current debate
between
proponents of the disadvantaged consumer perspective and the
vulnerable
consumer perspective.
PREVIOUS RESEARCH METHODS

Research regarding the demographic characteristics of
complaining
consumers has relied mainly on surveys (primarily by mail) in
which
respondents are asked to recall a single previous purchase that
was
unsatisfactory and then describe what actions they took (e.g.,
Liefeld,
Edgecombe, and Wolfe 1975; Day and Landon 1977; Warland,
Her-
rmann, and Moore 1984; Francken and van Raaij 1985; TARP
1986;
Gronhaug 1987; Singh 1988, 1989, 1991; Kolodinsky 1993,
1995).
This practice may create issues because it is uncertain which
types of
prior purchases consumers will choose to focus on when they
respond.
Because of this limitation, Andreasen (1988, 702) argued, “If
we are
to avoid confounding our findings about how often consumers
com-
plain, who complains and in what manner, we must not permit
con-
sumers the freedom to choose the occasion of dissatisfaction we
will
explore” (emphasis included in original). This approach may be
fur-
ther limited because of respondents’ recall and memory
abilities, espe-
cially for episodes that may have occurred several months
earlier (Singh
1989).
In addition, this use of consumer surveys may be problematic
when

the research focus is specifically on third-party complaining
behavior. It
is generally accepted that consumers engage in third-party
complaining
behavior in fewer than 10% of unsatisfactory purchase
experiences
(TARP 1986; Andreasen 1988; Fisher et al. 1999; Garrett 2004).
Because
third-party complaints tend to be “needles in haystacks,” most
prior
studies using consumer surveys have identified and analyzed
very small
numbers of relevant cases of third-party complaining behavior,
which has
limited the robustness of their results (Andreasen and Best
1977; Best
and Andreasen 1977; Day and Landon 1977; Moyer 1984; Singh
1991;
Kolodinsky 1993; Hogarth et al. 2001).
Therefore, the use of alternative research methods to examine
con-
sumer usage of third-party complaint agencies may add valuable
insight.
In the next section, the hypotheses evaluated in this study are
pre-
sented, followed by a discussion of the methodology used in
this
study.
HYPOTHESES

The following hypotheses evaluate whether disadvantaged
consumer
usage of BBB complaint services is indeed a function of the
four
dominant demographic characteristics proposed in prior
research:
H1: Consumers with lower incomes are significantly less likely
to complain to the
BBB than consumers with higher incomes.
H2: Older consumers are significantly less likely to complain to
the BBB than
younger consumers.
H3: Consumers with less formal education are significantly less
likely to complain
to the BBB than consumers with more formal education.
H4: Consumers from minority backgrounds are significantly
less likely to complain
to the BBB than consumers from nonminority backgrounds.
We have stated these hypotheses in the manner implied by the
disad-
vantaged consumer perspective. Therefore, to the extent that our
study
accepts or rejects these null hypotheses, the disadvantaged
consumer
perspective is supported or rejected.
METHOD
As noted above, most prior research in this area has used mail
surveys
of consumers and asked them to recall the actions they took in
response
to a single unsatisfactory purchase. To address the limitations
inherent in

the methods used in these earlier studies, this study used an
alternative
approach that has not been previously employed in this area.
Data
With the cooperation of the BBB office serving Wisconsin, the
complete record of complaints filed with this office during a 13-
year period (1994–2006) was obtained. The BBB recorded
complaints
by zip code address of the complainant. The BBB collected
24,256
complaints from 175 zip code areas in 11 counties in southeast
Wisconsin.
Milwaukee is the largest city in this geographic area and, based
on
U.S. Census data, is the most segregated city in the United
States
(Milwaukee Is Most Segregated City 2002). For this reason, this
provides
a very appropriate setting for this research, particularly in terms
of the
high variation in minority membership in various zip codes.
Twelve of
these zip codes were dropped from this analysis because of their
small
population size (less than 500) and inherent sensitivity to minor
changes
TABLE 2
Variable Descriptions, Means, and Ranges∗

Variable and Description Mean Value Range
COMPLAINTSPC 0.012 0.0012–0.024
Ratio of BBB complaints to population (≥18)
HHINCPC 19.66 5.18–33.80
Median household income/household size (in thousands of
dollars)
OVER65 36.5 22.2–46.1
Proportion of population ≥65
COLLEGE 0.19 0.012–0.61
Proportion of college graduates in population (≥18)
HS 0.56 0.21–0.72
Proportion of high school graduates in population not included
in COLLEGE
ASIAN 0.01 0–0.085
Proportion of population of Asian ethnicity
BLACK 0.06 0–0.96
Proportion of population of black ethnicity
HISPANIC 0.036 0–0.65
Proportion of population of Hispanic ethnicity
ESL 0.063 0.012–0.54
Proportion of population that speaks language other than
English at home
FEMALE 0.50 0.34–0.55
Proportion of population that is female
CITY
Zip codes within the city limits of
Milwaukee, Kenosha, Racine (binary variable) 0.23 0–1

∗ Source of complaints data: Wisconsin Better Business Bureau.
Economic and demographic data
are from the U.S. Department of the Census.
in number of BBB complaints, leaving a total of 24,153
complaints in
the final database registered from 163 zip code areas.
Economic and demographic data for the census year 2000 are
also
available at the zip code level from the U.S. Census
Department.
We include variables that represent the categories of
disadvantaged
consumers: income, age, education, and minority status. We
also include
variables to account for gender and whether or not the zip code
is within
major city limits. We did this to avoid omitted variable bias
because there
is reason to believe that these attributes may affect complaining
behavior.
These variables and their mean values are described in Table 2.
Because these data do not rely on consumer surveys and self-
selected
complaints, this research does not suffer from nonresponse or
self-
selection bias, and the limitations of imperfect memory.
However, it is
important to note that our sample has its own limitations, which

we have
acknowledged and addressed whenever possible. Our unit of
observation
is the zip code from which complaints are made, not the
individual
complainant. Thus, our data do not directly link complaints to
consumers
with particular demographic and economic characteristics.
Instead, we
have average numbers of complaints from particular zip codes
and these
are correlated with the average demographic and economic
characteristics
of the populations of these zip codes.
Also, our dependent variable is the number of complaints made
over
a 13-year period, whereas our census data are for the year 2000,
the
median year of the period over which complaints were made.
This could
lead to inaccurate results if the economic and demographic
characteristics
of the zip codes varied systematically over the 13 years. To
cross check
this possibility, we were able to extract and analyze the
complaint data
for a more recent three-year period (2003–2005). Using these
data from
this three-year period does not yield substantially different
results of the
estimation that was derived from data for the 13-year period.
Although southeastern Wisconsin has relatively low populations
of
ethnic minorities, there is a high degree of variation in the

numbers
of these populations across zip codes. Thus, we believe our
sample
can accurately capture the effects of minority status on
complaining
behavior. Another potential problem with our sample is the
possibility
of multicollinearity between income and the other variables.
Although
this does not bias our estimates, it may increase the standard
errors
of the coefficients. Multicollinearity may be responsible for
estimated
coefficients that are statistically insignificant.
Empirical Model
Ordinary Least Squares is used to estimate the following
multiple
regression model in which BBB complaints per population age
18 and
older is the dependent variable:
COMPLAINTSPC = a0 + a1HHINCPC + a2PCTOVER65
+a3HS + a4COLLEGE + a5ASIAN
+a6BLACK + a7HISP + a8ESL
+a9FEMALE + a10CITY + ERROR
We have hypothesized that BBB complaints increase with
income,
so we expect a positive coefficient on household income per
capita

(HHINCPC). Older and less-educated consumers …
Vol. 25, No. 1, January–February 2006, pp. 1–7
issn 0732-2399�eissn 1526-548X�06�2501�0001
informs ®
doi 10.1287/mksc.1060.0196
©2006 INFORMS
Editorial
Are Consumers Rational? Experimental Evidence?
Steven M. Shugan∗
Warrington College of Business, University of Florida, 201
Bryan Hall, Box 117155, Gainesville, Florida 32611,
[email protected]
Despite some misconceptions, consumer rationality is a property
of the researcher rather than the consumer.Consumers become
more rational as we are better able to predict their behavior or
other important out-
comes influenced by their behavior. Perfect rationality results
when we achieve accurate predictions. Conse-
quently, at least for many Marketing Science articles,
consumers are becoming more rational as we find better
ways to predict. However, some experimental consumer
behavior articles find the opposite. The difference
between experimental and statistical controls explains the
divergence in conclusions. Experimental controls test
rationality based on whether previously absent variables exhibit
significant explanatory power holding known

explanatory variables constant. Statistical controls test
rationality based on the incremental explanatory power of
previously absent variables after accounting for known
explanatory variables. Moreover, experimental tests tend
to isolate consumer behavior predictions while statistical tests
check for sufficient accuracy to choose among
different firm strategies. Both perspectives are correct but ask
very different questions.
Key words: bounded rationality; experiments; predicted choice;
consumption; consumer behavior; econometrics
1. Rationality
1.1. The Importance of Consumer Behavior to
Marketing
Most marketing activities seek to influence markets
involving interactions among suppliers, competitors,
regulators, the courts, government agencies, and cus-
tomers. Some research topics, including contingent
contracts (Biyalogorsky and Gerstner 2004), auctions
(e.g., Shugan 2005), and exploiting historic data bases
for marketing interventions (Rust and Verhoef 2005),
examine marketing issues applicable in both con-
sumer and business-to-business settings. However,
most academic studies in marketing focus exclusively
on consumer markets (Ankers and Brennan 2002),
perhaps because we are all consumers. Consequently,
the study of how marketing activities influence con-
sumer buying behavior is a central part of the disci-
pline of marketing.
A clear and fundamental understanding of con-
sumer behavior should help us more accurately pre-
dict consumer response to marketing interventions.

Editorial pages are not part of the regular Marketing Science
page
budget. We thank the INFORMS Society of Marketing Science
for
paying for all editorial pages. We also thank the Society for
grant-
ing every page supplement requested by the current editor.
We welcome and often post responses to editorials. Please see
mktsci.pubs.informs.org.
∗ Steven M. Shugan is the Russell Berrie Foundation Eminent
Scholar in Marketing.
Those predictions would certainly be instrumental, if
not invaluable, for designing more effective market-
ing tactics and more profitable strategies. Understand-
ing consumer behavior should allow both the iden-
tification of the critical variables influencing behav-
ior and the nature of that influence. It should also
reveal which variables have relatively little impact
on behavior and which marketing activities, conse-
quently, might be ineffective.
1.2. The Debate About Consumer Rationality
Given our great interest in consumer behavior,
researchers in marketing sometimes find themselves
entangled in debates about consumer behavior (e.g.,
see Firat et al. 1995, Howard and Sheth 1969). For
example, one area of debate concerns consumer
rationality. Sometimes, consumer rationality debates
involve important implications for the effectiveness
and implementation of numerous marketing activ-
ities. Many marketing activities, such as signaling,
require highly rational consumers (Kirmani and Rao
2000). Other marketing activities, such as the con-
struction of loyalty programs, might require irrational

consumers (e.g., Taylor et al. 2004). Unfortunately,
these debates about consumer behavior, despite their
fascinating aspects, are sometimes distracting, confus-
ing, and divert research efforts into directions with no
apparent direct impact on marketing activities.
The manuscript review process reveals that some
researchers summarily dismiss marketing models that
1
Shugan: Editorial: Are Consumers Rational? Experimental
Evidence?
2 Marketing Science 25(1), pp. 1–7, ©2006 INFORMS
assume extreme consumer rationality, i.e., extreme
forms of optimal behavior where consumers effort-
lessly ratiocinate through highly complex tasks with
capacious memory. Other more moderate researchers
suggest that marketing models should account for
documented so-called departures from rationality
found in experimental studies (e.g., Smith 2003). Some
researchers, at the opposite extreme, summarily reject
models that assume less than perfect rationality.
2. Some Definitions of Rationality
Before discussing the debate over rationality, perhaps
we should define the term “rationality.” As with other
technical terms (e.g., utility, probability, product, opti-
mization, equilibrium), the term “rationality” can con-
vey different meanings in different disciplines. In fact,
different meanings exist within the same discipline.
Let us limit the following discussion to the meaning
of rationality in the discipline of marketing and, pos-

sibly, some sister disciplines.
The everyday definition of “rationality” is “having
the ability to reason.” Technical definitions, in quest
of precision, sometimes become far more complex and
confusing. Confusion over the technical definitions of
some technical terms often causes many unproductive
debates about meaningless differences. Perhaps that
confusion is, in part, deliberate. Researchers occasion-
ally adopt less precise, simple everyday terms for their
theories, both to better communicate the intended con-
cept and to make assumptions appear more palatable.
It seems far more reasonable to posit, for example,
a normal distribution than to posit a Gaussian dis-
tribution for the ubiquitous error term. Similarly, it
seems more defensible to assume that consumers are
rational, rather than to assume that consumers are
adept optimizers, with perfect foresight and knowl-
edge of the firm’s cost structure and never tire. In this
sense, the usage of the term “rationality” is a market-
ing strategy for selling (i.e., making more palatable)
a set of technical mathematical assumptions that are
sufficient for building a theory of consumer behavior.
Like other assumptions, the attractiveness of “rational-
ity” assumptions (as approximations to some complex
real-world situations) will depend on whether the sub-
sequent theory is able to explain (i.e., predict) impor-
tant observables.
In the economics literature, rationality is usually
associated with the sufficient conditions for the exis-
tence of a consumer utility function (e.g., Malinvaud
1972). Traditional economic theory implicitly defines
consumer rationality in terms of expected utility max-
imization and a set of explicit axioms sufficient for
utility functions to exist (Herstein and Milnor 1953).

The econometrics literature defines rationality as util-
ity maximization with an individual-specific addi-
tive error term (Lewbel 2001). Game-theoretic applica-
tions often define rationality as taking the best action,
given well-defined payoffs and rules of play (Bern-
heim 1984). Hence, rational consumers do what is best
for them in a context where all players (consumers,
manufacturers, retailers, etc.) have different incentives
(e.g., see Alba et al. 1997 for a discussion of conflict-
ing incentives in interactive home shopping). Lipman
(1991) defines rationality as choosing the best proce-
dure for deciding. Of course, other disciplines have
other definitions, including the idea that rationality is
merely normal behavior.
3. The “Best-Action” Definition
Most Marketing Science applications are consistent
with the “taking-the-best-action” definition of ratio-
nality. This definition implies that rationality is neces-
sarily a function of the model (or theory) being pro-
posed or tested because the best action depends on
the postulated world of the model (e.g., parameters,
decisions variables, relationships, measures).
For example, when proposing a model of search
and consideration sets, Mehta et al. (2003) state that
“consumer rationality implies that consumers will
engage in price search to reduce [price] uncertainty.”
Acquisti and Varian (2005) define consumer aware-
ness of firm incentives to lower future prices as one
property of rationality. Zwick et al. (2003) define opti-
mal search behavior and the size of the consumer con-
sideration set as properties of rationality. Akçura et al.
(2004) define consumer learning as one property of
rationality. Kalra et al. (1998) define consumer skepti-

cism of manufacturer quality claims (i.e., without sup-
porting evidence) as one property of rationality. Xie
and Shugan (2001) argue consumer skepticism about
service provider claims regarding future spot prices
(i.e., that are not consistent with future spot profit
maximization), ala Coase (1972), as one property of
rationality. A variety of other factors might also pro-
duce other definitions for rationality (e.g., dynamics,
uncertainty, the preferences of others, cultural pres-
sures, etc.).
In sum, a rational consumer takes the best action
within the world of the model. Given that the dif-
ferent models employ different decisions variables,
different exogenous factors, different situations, and
exhibit different properties, the precise meaning of the
term “rationality” varies from model to model.
3.1. Why the Best-Action Assumption Is Really A
Weak Assumption
The assumption that consumers will take the best
action (within the world of the model) is often an
extremely powerful assumption because it allows
extraordinary consistency across and within myr-
iad models that might appear completely unrelated.
Hence, we can link diverse models related to advertis-
ing budgets, promotions, advertising copy, shopping
Evidence?
Marketing Science 25(1), pp. 1–7, ©2006 INFORMS 3
behavior, and so on with this high-level assumption.

We also get consistency between models of very dif-
ferent phenomena (e.g., borrowing behavior and mar-
riage).
At first, this might seem like a strong assumption.
It is not. In virtually all situations, we could introduce
ad hoc factors or arbitrarily modify the payoff func-
tion to make any outcome appear best. We might, for
example, allow consumers to consider the perceived
fairness of the outcome, imagined legal constraints,
perceived risks of litigation, social acceptability, pos-
sible reputation effects, regret, intuition, and so on.
A consumer might pay a higher price than necessary
as a form of charity or a subsidy to help a valued
firm stave off bankruptcy. A consumer might choose
a lower-quality alternative as a means of experimen-
tation (i.e., information gathering). A consumer might
want to signal modesty in a social setting. Some
consumers might deliberately try to make their own
behavior unpredictable (as part of a more general
strategy). Of course, some modifications might appear
to resemble ad hoc ruses attempting to explain the
irrational.
This is not to say that all actions are reason-
able. Not all models are reasonable approximations
of any conceivable real-world setting or real-world
decision. This is only an argument that assuming that
consumers take the best action is not as strong an
assumption as it appears to be. The critical assump-
tion, as argued later, is whether the model itself
(i.e., the entire package of assumptions and condi-
tions) provides a sufficient approximation of real-
world settings. Moreover, outcomes might remain
rational despite violations of the rationality assump-
tions (e.g., see Mandler 2005).

3.2. Why Best Is Really Best
Before arguing that model prediction is the key to
testing rationality, we should concede that assum-
ing that consumers do take the best action is still an
assumption that warrants justification. Here are sev-
eral justifications.
1. Most consumers would prefer to make the best
decision ceteris paribus.
2. The best action is often unambiguous (at least,
if the model is properly specified) and, hence, this
assumption is directly testable—unlike assumptions
that are less precise about which action will be taken.
3. Possible ambiguity related to the best action
alerts us of possible problems with the model’s spec-
ification or formulation.
4. Given that firms seek to maximize expected prof-
its, assuming consumer maximization creates a sense
of symmetry and consistency in the model formation.
5. Rather than requiring predictions for all con-
sumers, many marketing decisions need only consider
marginal consumers (i.e., only those few consumers
who will change their purchase decisions—to buy or
not—when we adopt a different marketing strategy).
Hence, only marginal consumers need do what is
best.
6. We are more interested in the eventual outcome
rather than in blips along the way (although, the blips
are also interesting). Equilibria, for example, represent

our targeted outcomes.
7. We would expect that learning and experience
would lead consumers toward the best actions.
8. When trying to persuade consumers, the conser-
vative assumption might be that we face the arduous
task of persuading very astute consumers rather than
the relatively easier task of fooling naïve ones.
3.3. A Practical Definition of Rationality
Rather than quibbling with either the theoretical
meaning of rationality or the particular rationality
assumptions in any particular model, we should
instead focus our concern on whether the rationality
assumptions are sufficient to approximate the situa-
tion being modeled. The key test is whether the model
can accurately predict outcomes in that situation, at
least, better than could be done without the model.
Another way of looking at assumptions is that
the assumptions provide sufficient conditions when
the model’s conclusions are justified. That viewpoint
is true for every type of model (e.g., normative,
descriptive, statistical, behavioral, aggregate, disag-
gregate, etc.). The question is not whether the mod-
eling assumptions are each good approximations for
every situation or even most situations; the question
is whether the model’s results are applicable in a suf-
ficient number of situations so that the contribution
justifies publication and application of the model. We
hope that the conditions are sufficiently good approx-
imations so that the model can accurately predict in a
sufficient number of real-world situations.
4. Testing Whether Consumers are

Rational
4.1. Rationality as a Model Property
Inaccurate model predictions do not necessarily imply
that reality is complex or unpredictable. High lev-
els of uncertainty (in some situations) might only
reflect an inadequate state of the art in modeling. As
modeling technology improves, we expect that reality
will appear simpler and more predictable. For exam-
ple, navigation on the high seas was once onerous,
but global positioning systems technology now allows
accurate predictions and, consequently, easier naviga-
tion.
A similar argument is possible for consumer ratio-
nality. Consumers appear rational in situations in
Evidence?
4 Marketing Science 25(1), pp. 1–7, ©2006 INFORMS
which our models can predict their behavior. Con-
sequently, consumers in well-studied choice situa-
tions appear to exhibit high degrees of rationality
because we have accurate models for these familiar
situations. In other less-studied situations, consumers
might appear irrational because our extant models are
unable to accurately predict outcomes. In this sense,
rationality is a property of our models and not a prop-
erty of the consumer.
The concept of a subjective probability is analo-
gous. The world is in some true state. For example,
we might wonder whether the true box office of a

movie is $1 million, $10 million, or $100 million. How-
ever, there is some true box office. It is likely that
time will reveal that true box office. In fact, we might
know that true box office, but rather than using that
information, we might predict it from other informa-
tion to validate a model. A better model is better at
predicting outcomes (i.e., explaining variance) than
other models. However, the uncertainty in the out-
comes (i.e., the variance) is a feature of the model and
not reality. Reality consists of true states (which may
or may not be known when predictions are made)
while probabilities represent the researcher’s uncer-
tainty about the true states. There are no correct prob-
abilities, but there are correct predictions. Subjective
probability reflects the researcher’s uncertainty. Simi-
larly, irrationality reflects the researcher’s inability to
predict behavior.
Most marketing models (perhaps all) should be
tested on their predictions. Usually, predictions are
made for qualitative or quantitative observations that
are not used in the formulation, estimation, or calibra-
tion of the model. Hence, a model should be capable of
making predictions that we would be unable to make
without the model.
4.2. What Is Being Predicted
The prior argument suggests how we should test the
rationality assumptions of a model. Given that con-
sumer rationality assumptions are just a few of the
many assumptions that comprise a model, it would
be unproductive to test each assumption in isolation.
Consider a road map that is a model of a geo-
graphic terrain. A particular map might show all
the major highways but fail to show the location of

hotels. The map model represents a simplification and
approximation of the real geography. It can’t show
every detail of reality, nor should it. It is difficult
to evaluate, in isolation, whether ignoring lodging
is a good or bad assumption. If the map is being
used to navigate across the state, other assumptions
in the map’s construction may trump the inclusion
of lodging. If, in contrast, the user wishes to find
lodging, ignoring hotels is a fatal flaw in the model.
We are unable to evaluate the assumption in isola-
tion. This argument also implies that the quality of
an assumption depends on the intent of the model,
as well as on the other modeling assumptions. We
are unable to conclude, in isolation, that some mod-
els comprise more realistic behavioral assumptions
than other models. A model for predicting industry
sales, for example, might require different assump-
tions about consumer behavior than a model attempt-
ing to predict a particular consumer’s reaction to a
direct-mail solicitation.
Hence, the proper predictive test for rationality
assumptions need not focus on consumer behavior.
Those assumptions only indirectly impact the valid-
ity of the conclusions. For example, consider a model
built to help select one of several new products for
development. That decision might involve assump-
tions related to consumer reactions, development fea-
sibility, supply chain issues, costs, competitive reac-
tions, inventory requirements, and so on. Whether
a naïve consumer rationality assumption is an ade-
quate approximation for expected consumer behavior
depends on whether replacing that assumption with
a more complex or realistic assumption would change
the selection decision. In general, the adequacy of

the rationality assumption depends on whether the
assumptions lead to the adoption of the wrong mar-
keting strategy, rather than on whether the assump-
tions predict consumer behavior at some absolute
level of accuracy. For example, the assumptions that
consumers price shop at many or few outlets might
each yield the same optimal marketing strategy when
each assumption tends to yield the same prices across
outlets.
Of course, the rationality assumption might be
questionable if the model is unable to predict desired
outcomes (e.g., profits, sales, market share) with suffi-
cient accuracy to discriminate among strategies. Then,
every assumption becomes suspect. Moreover, several
assumptions could be flawed (i.e., bad approxima-
tions).
4.3. A Brief Comment on Prediction Versus
Explanation
Although the technical terms “prediction” and
“explanation” certainly vary in meaning, this discus-
sion treats the words as almost synonymous. Usually,
after observing some qualitative or quantitative obser-
vations, we propose a model or theory that explains
those observations. We partially assess the validity of
the theory or model by predicting different observa-
tions (qualitative or quantitative). In some cases, the
researcher arbitrarily defines explained observations
(e.g., based on a point in time in the dataset, based
on previous research at the time of submission, and
so on). However, this distinction is less relevant here.

Evidence?
Marketing Science 25(1), pp. 1–7, ©2006 INFORMS 5
4.4. Irrationality Is the Default Assumption
Authenticating irrationality is not necessarily our
task. Our default assumption is that consumers are
irrational, either because their behavior is inherently
unpredictable or because we have not yet discovered
how to predict it. The proof of rationality is straight-
forward but, perhaps, daunting. We need only cre-
ate a model that accurately predicts (i.e., explains the
variance) in consumer behavior. If we are able to pre-
dict consumer behavior as a function of the relevant
variables in the situation of interest, we can conclude
that consumers are rational (at least in that situation)
and that our model accurately represents that ratio-
nality.
5. Conflicting Findings on Rationality
The prior reasoning suggests that consumers will
appear to grow more rational over time as advances
in model building technology ameliorate our ability
to predict. For example, Wolfgang and Kannan (2005)
discover how spatial multinomial models can bet-
ter predict the spatial correlations among customer
choices. Mittal et al. (2005) discover how customer
satisfaction can better predict firm long-term finan-
cial performance. Divakar et al. (2005) discover how
to better predict microlevel consumer behavior. Nair
et al. (2005) discover how aggregate data can better
predict purchase incidence, brand choice, and pur-
chase quantities.
5.1. Are Consumers Becoming More Rational?
It seems clear that Marketing Science articles report

116 RESPONSES DOES RUNNING OUT OF (SOME) TRADEMAR.docx

116 RESPONSES DOES RUNNING OUT OF (SOME) TRADEMAR.docx

Recommended

Recommended

More Related Content

Similar to 116 RESPONSES DOES RUNNING OUT OF (SOME) TRADEMAR.docx

Similar to 116 RESPONSES DOES RUNNING OUT OF (SOME) TRADEMAR.docx (17)

More from jesusamckone

More from jesusamckone (20)

Recently uploaded

Recently uploaded (20)

116 RESPONSES DOES RUNNING OUT OF (SOME) TRADEMAR.docx