Apple Inc. v. Samsung Electronics Co. Ltd. et al
Filing
999
Administrative Motion to File Under Seal filed by Samsung Electronics America, Inc.(a New York corporation), Samsung Electronics Co. Ltd., Samsung Telecommunications America, LLC(a Delaware limited liability company). (Attachments: #1 Proposed Order Granting Motion to Seal, #2 Samsung's Opposition to Apple's Motion to Exclude Testimony of Samsung's Experts, #3 Declaration of Joby Martin in Support of Samsung's Opposition, #4 Exhibit A to the Martin Declaration, #5 Exhibit B to the Martin Declaration, #6 Exhibit C to the Martin Declaration, #7 Exhibit D to the Martin Declaration, #8 Exhibit E to the Martin Declaration, #9 Exhibit F to the Martin Declaration, #10 Exhibit G to the Martin Declaration, #11 Exhibit H to the Martin Declaration, #12 Exhibit I to the Martin Declaration, #13 Exhibit J to the Martin Declaration, #14 Exhibit K to the Martin Declaration, #15 Exhibit L to the Martin Declaration, #16 Exhibit M to the Martin Declaration, #17 Exhibit N to the Martin Declaration, #18 Exhibit O to the Martin Declaration, #19 Exhibit P to the Martin Declaration, #20 Exhibit Q to the Martin Declaration, #21 Exhibit R to the Martin Declaration, #22 Exhibit S to the Martin Declaration, #23 Proposed Order Denying Apple's Motion to Exclude Testimony of Samsung's Experts)(Maroulis, Victoria) (Filed on 5/31/2012)
EXHIBIT M
UNITED STATES DISTRICT COURT
NORTHERN DISTRICT OF CALIFORNIA
SAN JOSE DIVISION
__________________________________________
:
:
:
Plaintiff,
:
:
v.
:
:
SAMSUNG ELECTRONICS CO., LTD., a
:
Korean business entity; SAMSUNG
:
ELECTRONICS AMERICAN, INC., A New York :
Corporation; SAMSUNG
:
TELECOMMUNICATIONS AMERICA, LLC, a :
Delaware limited liability company
:
:
Defendants.
:
_________________________________________ :
APPLE INC., a California corporation
Case No. 11-cv-01846-LHK
______________________________________________________________________
REBUTTAL REPORT OF MICHAEL A. KAMINS, Ph.D.
______________________________________________________________________
1
I. BACKGROUND AND QUALIFICATIONS
1. I am presently Director of Research, Full Professor and Area Head of Marketing with tenure
at the Harriman School of Business at Stony Brook University-SUNY. At Stony Brook, I have
exclusively taught courses in marketing at the graduate level inclusive of Marketing Research,
Marketing Management and Marketing Strategy. Prior to my position at Stony Brook, I was an
Associate Professor of Marketing, with tenure, at the Marshall School of Business
Administration at the University of Southern California where I taught for over 24 years. While
at USC, I taught courses at the executive, doctoral, graduate and undergraduate level in strategic
marketing management and marketing research. I also taught in USC’s prestigious Global
Executive MBA program (GEMBA) in Shanghai, China, as well as in the USC Executive MBA
program.
2. My research has been recognized at the national level. For example, my paper with Valerie
Folkes titled, “Effects of Information about Firms Ethical and Unethical Actions on Consumers’
Attitudes,” was selected to represent the year “1999” in the Journal of Consumer Psychology’s
Special Issue celebrating 20 years of publication. I have also advised numerous companies
regarding their advertising, marketing and marketing-research practices, both in my capacity as
Director of the IBEAR (International Business Education and Research) International Business
Consulting Project at the University of Southern California, as well as in many other independent
consulting assignments.
3. In terms of research, my doctoral dissertation at New York University focused on consumers’
evaluation of brands as a function of varying advertising techniques and communication
strategies. My dissertation was published in the Journal of Marketing Research. Throughout my
career, I have focused on how consumers interpret advertising and promotional material through
the measurement of attitude, cognition, behavioral-intention and verbal protocols. I have also
conducted over 500 consumer surveys across various products and services in the last 25 years.
This academic experience derived through both theoretical development and applied primary
research (i.e., using both surveys and experiments) has enabled me to understand how the typical
consumer would react to advertising claims across a wide range of product categories.
2
4. One of my current research thrusts in the academic arena involves branding, specifically the
image conveyed by certain brand characteristics. My current research interests also include the
study of strategic bidding in an auction environment, as well as consumer perceptions of price
bundling. My publication in the Journal of Consumer Research (December, 2009) deals with
price bundling and BOGO’s (“buy one get one free”), and my paper in the Strategic
Management Journal focuses on the relative importance of employee and consumer perceptions
in the evaluation of a focal company (May, 2010). ). My most recent article in the Journal of
Interactive Marketing (2011) examines social factors and cues, both within the auction listing
and externally, that motivate sniping behavior.
5. I received a Bachelor of Business Administration in 1974 from Bernard M. Baruch College in
New York, with a major in Statistics. I received my MBA from the same institution in 1977. In
1984 I received my Ph.D. in Marketing from New York University. Since receiving my doctoral
degree, I have published over fifty academic articles and proceedings in major academic
journals, including the Journal of Marketing, Journal of Marketing Research, Journal of
Consumer Research, Strategic Management Journal, Journal of Consumer Psychology, Journal
of the Academy of Marketing Science, Journal of Interactive Marketing, Journal of Advertising
and the Journal of Advertising Research. I have also conducted extensive survey research in both
an academic and consulting environment, including surveys on the issue of confusion, secondary
meaning and dilution. I have testified in relation to confusion at both the state and federal court
level, and before the California Public Utilities Commission (CPUC) regarding issues of false
and deceptive advertising and consumer interpretation of that advertising.
6. Finally, I have consulted for such companies and individuals as Cingular Wireless, Con-Agra,
Hilton Hotels, AT&T, Bank One, Canon, LensCrafters, Pinkberry, Panda Express, Sears, The
State of California, The State of New York (Eliot Spitzer, AG), Bill Medley (Righteous
Brothers), Muhammad Ali, Kareem-Abdul Jabbar, and the Doors. I am compensated at the rate
of $600/hour for consultation, deposition, and trial time in this case. My curriculum vitae is
attached as Exhibit A, and a record of all cases in which I have testified at deposition or trial
within the past 4 years is attached as Exhibit B.
3
7. I reserve the right to consider and/or rely upon other expert reports that may be filed in this
matter, as well as the testimony of any fact or expert witnesses at a deposition or at trial and to
provide my opinion with respect to these facts and testimony. Moreover, I reserve the right to
offer rebuttal testimony to any evidence or argument presented by the opposing party in this
case. To the extent that any new information is made available to me after submission of this
report, I will evaluate that information to determine whether it has any impact on the opinions
and conclusions set forth in this report. I reserve the right to amend this report to take that
information into consideration.
II. MY TASKS IN THIS CASE
8. I was asked to review the expert reports submitted by Dr. Kent D. Van Liere in the matter of
Apple Inc. v. Samsung as to the reliability and validity of the primary research he conducted, as
well as to conduct my own study regarding association given actual usage and handling of the
smart phone. This research involved two empirical studies addressing: (1) post-sale confusion
between specific tablets of both companies, and (2) dilution, or more precisely the degree to
which consumers associate the look and design of two Samsung Galaxy smart phones with
Apple and its smart phones. It is my opinion that due to methodological flaws and
generalizations that are unsupported by the data, both studies offered by Dr. Van Liere are fatally
flawed. Therefore, the conclusions he draws based upon his research are unreliable and invalid.
My specific concerns regarding each study, which led to my conclusions, are detailed in the
sections of the report that follow.
III. EVALUATION OF DR. VAN LIERE’S POST-SALE CONFUSION STUDY FOR
TABLET COMPUTERS
9. For both the post-sale confusion study discussed in this section, and for the
dilution/association study discussed in the next section, the framework that I will use to evaluate
Dr. Van Liere’s research derives from that proposed by Fred W. Morgan (“Morgan”) in his
Journal of Marketing article entitled “Judicial Standards for Survey Research: An Update and
Guidelines.” The Journal of Marketing is a top-tier marketing and professional journal, and
Morgan is a respected authority in the area of survey research in the judicial arena. The Morgan
article both reviews and illustrates characteristics of trustworthy research as discussed in the
4
Handbook of Recommended Procedures and the Manual for Complex Litigation. Morgan’s
framework is designed to identify six critical areas in the assessment of the validity and
reliability and ultimately trustworthiness of survey evidence. These criteria are: 1) Universe
definition and sample selection; 2) Design of the survey instrument; 3) Administration of the
survey instrument; 4) Interviewers’ qualifications and techniques; 5) Data analysis and
presentation; and 6) Administration of the overall project. I will provide commentary as
appropriate in each area, but will begin by a broad overview of Dr. Van Liere’s research
protocol.
x
Problems With Dr. Van Liere’s Research Protocol
The Results Cannot Be Generalized Beyond the Situation Tested
10. As noted by Dr. Van Liere, “A post-sale confusion survey presents consumers with the
product as they might experience it in a real-world setting after it has been purchased by another
individual.” (Van Liere Report, page 3) This statement suggests that the construct of “post-sale
confusion” is extremely complex, because the researcher is faced with a multitude of variables
when attempting to establish the appropriate “real-world” setting to examine. For example, in a
post-purchase situation, is the consumer’s exposure to the product typically for only a short
period of time while quickly passing the user engaged in usage of the device? Or, is it for a
longer period of time, for example, as one sits on an airplane behind another passenger who uses
the product for the duration of the flight? Moreover, does one see the device alone and not in the
context of other devices, or does one observe it in the rather standard scenario where different
devices are being used in close proximity, such as on a long wooden table in a library or at a
Starbucks coffee house? The ability to see a device in the presence of another device likely
would reduce confusion between the two, because the consumer is presented with the actual
products and therefore does not have to rely upon his/her memory of another product to evaluate
whether they are the same or different, as is the case for the Samsung tablet in the Van Liere
confusion study. Moreover, is there a brand name on the product and is it visible for a long
period of time or is it even visible at all?
5
11. One study undertaken by one experimenter cannot account for all of these factors, and thus
choices in terms of the research design must be made that affect the generalizability of the study.
Whatever choice is made subsequently reduces the study of post-purchase confusion to the
specific exposure situation studied, reducing the generalizability of the findings to the localized
study as conducted by the researcher. Given its particularized context, detailed below, Dr. Van
Liere’s study is quite limited in its generalizability and thus cannot represent valid and reliable
conclusions regarding the overall presence of post-sale confusion, even for the tested products.
x
First, Dr. Van Liere showed each respondent a single short video clip of a woman
using, either a Samsung Galaxy tablet model or a Barnes & Noble Nook e-reader,
outside of the presence of any (other) tablet products. Hence the respondent was
never given the opportunity to evaluate the devices in the proximity of another
brand and instead had to rely upon his/her memory of other tablets, such as the
iPad, to consider the source of the product. Such an approach increases the
likelihood of confusion because memory is not as reliable as having the ability (as
in certain “real-world” contexts) of seeing the devices side-by-side or in
proximity to one another. Such pairwise comparisons highlight design
comparisons, which in turn clarify the similarities and differences between brands
and enable a more reliable and valid measure of actual confusion.
x
Second, Dr. Van Liere used two alternative videos of the Samsung product with
and without the brand name printed on the front face. I am informed that Samsung
sold the Galaxy Tab 10.1 tablet for a short time without the brand name printed on
the front side of the tablet, which is the side featured in the stimuli videos, and
since that time has sold only Galaxy Tab 10.1 tablets with the Samsung name
printed on the front. The results from the branded and unbranded tablets should
not have been combined and averaged.
x
Third, Dr. Van Liere presents each stimulus to the respondent using a video where
an individual user attempts to employ the device in a similar manner, and the
viewer is given the perspective of moving from left to right directly behind the
user. Therefore, results regarding the measurement of post-purchase confusion,
are by definition limited to this particular exposure in the Van Liere study, and
only to the Galaxy Tab 10.1 or Nook model shown, and hence are not
generalizable.
The Chosen Control Improperly Skews the Results
12. Dr. Van Liere exposed each respondent to one of three different conditions, two of which
were the “test” cells, and one was the “control” condition. The test cells involved exposing
respondents to a 48 second video of a woman using the Samsung Galaxy Tab 10.1, either with or
6
without the brand name visible to the user or the viewer of the video. The control cell involved
exposure to a Barnes & Noble’s Nook device, with the trademark “n” logo clearly visible on the
front of the device near the bottom. The visible stylized “n” logo resulted in an incomplete
experimental design, because there should have been a control for the brand-not-visible Samsung
tablet as well as a control for the brand-visible Samsung device. The research design should have
had four cells (i.e., two test cells and two control cells), as opposed to its three cells. The lack of
a brand-not-visible control cell rendered the study incomplete.
13. A more egregious error results from the fact that the single version of the Nook presented to
respondents in the video was the image with the brand logo present. Using the pattern observed
in Dr. Van Liere’s data for the Samsung branded and unbranded products, as well as simple
logic, the degree of confusion with the brand name visible is likely lower than when the brand
name is not visible. Choosing the version with the logo present to control against both test cells
(branded and unbranded) ensured that a smaller degree of confusion would be found in the
control cell – which is ultimately subtracted from both test cells. The research protocol
developed by Dr. Van Liere thus created an inherent bias toward finding higher net confusion in
the unbranded (brand name not visible) Samsung test cell, due to the application of an
inappropriate, unmatched control.
14. Another significant issue is the use of the Nook as a control in the first place. The Nook is
much smaller than an iPad and has a unique frame in which the bottom left corner of the device
is cut out, which creates the impression of a handle or connector. This physical design difference
is very obvious in the video and is likely to trigger an association or memory of the specific
device in a number of respondents. In addition, while one can generously – but incorrectly –
describe the Nook as a “tablet,” it is more appropriately classified as an “e-ink-reader.” (John
Falcone C/net 3/13/12- news.cnet.com/8301-17938_105-20009738-1). Falcone describes three
categories of products: 1) black and white e-ink-readers; 2) 7 inch color LCD media tablets; and
3) full-size color tablet computers. The black and white Nook as featured in Dr. Van Liere’s
research fits into the first category. The Nook is primarily a book reader that can run a limited
number of applications. It is priced significantly lower and does not have the same features or
capabilities as Apple’s or Samsung’s tablet computers. While the iPad and Galaxy tablets can
7
serve as e-readers, the converse is not true. This was quite evident in Dr. Van Liere’s video
because the Nook displayed a rather drab page of text from a document or book, as opposed to
the colorful internet sites displayed by the Galaxy Tab products in the test videos. It is also worth
noting that Barnes & Noble released a product called the Nook Tablet last year, which has
additional features found on tablet computers, but Dr. Van Liere did not use the Nook Tablet
product for his control. Because the Nook device used by Dr. Van Liere is markedly different in
size, visual design, and function and form from the Samsung Galaxy (as well as the Apple iPad),
use of the Nook as the control minimizes the degree of confusion evident in the control cell.
Because control-cell confusion is subtracted from confusion in the test condition, artificially
reduced control data improperly and inaccurately increases the overall confusion level shown in
Dr. Van Liere’s study.
15. The intrinsic differences between the Nook and iPad and Galaxy Tab are to be expected,
given that the Nook serves a different function. On page 10 of his report, Dr. Van Liere quotes
Shari Diamond as noting, in regard to the control stimulus, that it should “share as many
characteristics with the experimental stimulus as possible, with the key exception of the
characteristic whose influence is being assessed.” (Diamond, 2011, p. 258) The Nook fails in
this regard, because its size, functionality, case design and general look are not consistent with
the product class at issue in this action, namely tablet computers. Lacking a proper control,
Dr. Van Liere’s study did not generate accurate data on which to base reliable findings.
16. Better control devices, for example, would have been an LG Slate or Motorola Xoom or
other tablet computers that perform essentially the same functions as the Apple iPad and the
Samsung Galaxy devices and have a general look and appearance that is closer to the brands at
issue.
x
Improper Sample Selection
17. Dr. Van Liere selected a sampling plan where men and women were equally represented in
his final sample, as were individuals between the age of 18-24; 25-34; 35-44; 45-54; 55-64 and
65+. As his source for the demographic representation of his sample, Dr. Van Liere uses a Pew
8
Research report (“Pew Report”) on tablet and e-book reader users. (Van Liere Report, page 7,
footnote 8.) Notably, however, the Pew Report characterizes the Nook separately from the
Galaxy Tablet and iPad. The Nook is characterized as an “e-book reader,” while the Galaxy
Tablet and iPad are classified as tablet computers. The Pew Report identifies different
demographic growth rates for e-readers and tablets. If different demographic growth rates are
indicated, this implies that the Pew report separates the e-reader and tablet into different
categories, since a uniform growth rate would have been shown if both products were believed to
belong to the same market. (See page 5 of the Pew Report, attached as Exhibit C). Notably, the
Pew Report shows that those in the 30-49 year old category were almost 4 times as likely to own
a tablet computer (as of mid-January 2012), relative to those who were 65+. (See Pew Report,
p. 3.) Dr. Van Liere’s sample neither accounts for nor reflects these relative demographic
percentages.
18. The greatest variance in ownership across a given demographic variable occurred for income,
where those in the $75,000+ annual income category were 4.5 times more likely than those who
earned less than $30,000 to own a tablet computer. In addition, college graduates were more than
six times more likely to own a tablet versus those who identified “some high school” as their
education. (Pew Report, p. 3.) Dr. Van Liere’s report is silent regarding these variables, and,
given this great variance in percentage of ownership, at minimum Dr. Van Liere should report
the degree to which his sample fits these demographic characteristics
19. When one considers race/ethnicity, the Pew Report shows the following ownership statistics
of tablets for various ethnic groups as of mid-January 2012: White 19%; African American
21%; and Hispanic 21%. When weighted by the relative presence of each ethnic group in the
United States population as of 2012 (White 64.86%; Hispanic 15.1% and African American
12.85%), the relative percentage of each ethnic group in Dr. Van Liere’s confusion study should
have been as shown in the first column of Table 1 below. This column reflects the proper
weighting as a function of usage and relative percentage of the United States population,
9
accounting for both the relative presence of each ethnic group in the United States population
and the relative degree of tablet ownership by each ethnic group:1
TABLE 1
REPRESENTATIVE AND ACTUAL PERCENTAGE OF ETHNIC
GROUPS IN THE SAMPLE FOR THE CONFUSION STUDY:
REPRESENTATIVE
SAMPLE
ACTUAL
SAMPLE
White:
67.79%
60.50%
African American:
14.80%
26.54%
Hispanic:
17.41%
12.96%
20. The actual relative percentage of ethnic groups considered in the sample by Dr. Van Liere is
noted in the right column of Table 1 above. It becomes evident that when compared to what
would be considered a “representative” sample, Dr. Van Liere has over sampled African
Americans by 80% and under-sampled Hispanics by 25%. Because his sample is not
representative of the actual ethnic user base of tablet computers, Dr. Van Liere’s findings are not
reliable nor are they valid, hence the numbers reported by Dr. Van Liere in terms of confusion
cannot be trusted as representative of those who actually own tablet computers.2
•
The Design of Dr. Van Liere’s Survey Instruments Is Biased
21. The first question in Dr. Van Liere’s survey is improperly leading. It asks respondents: “In
your opinion, what tablet computer was shown in the video?” This question biases respondents
into believing the device shown was a tablet when they may not have initially perceived it as
such. Even if the subject’s initial inclination might not have been to believe there was a tablet
computer in the video, the question directs him/her to understand that the product in the video
1
The relative percentages were calculated only as a function of the three main ethnicities: White,
Hispanic and African American.
2
It may also lack representativeness on other demographic factors as well; ethnicity was chosen
as a test case.
10
was a tablet computer. By this suggestion, the question discourages responses based solely on
what respondents independently would have known about the product category. The question
therefore causes a set of respondents to guess at the answer, and when people guess they
typically think of the market leader, namely Apple. (see Kamins, Alpert and Perner, 2003). By
generating confusion unrelated to the trade dress at issue, Dr. Van Liere’s initial question
improperly drives up the level of confusion in his test results. Particularly because this is the lead
question in the survey, it renders the results invalid and unreliable.3
•
Improper Coding
22. Dr. Van Liere mentions that “respondents were coded as confused if they named iPad or
Apple when asked what device was shown or what company makes the device.” As written, this
suggests that the respondent had two attempts to name Apple or iPad. While this approach
seemingly makes sense on the surface, it does not if there is an inconsistency between a
respondent’s answer to both questions (what device was shown and who makes the device). For
example, if a given respondent named Samsung as the device shown, but Apple as the company
that makes the device, it become necessary to ascertain the reason for the perceived affiliation
between Apple and Samsung. It could have nothing to do with the look or trade dress of the iPad,
but rather could stem from an independent notion, perhaps formed by reading a newspaper
article or watching a news program, that the two companies had entered into a business
arrangement. There are several responses such as these in the data (e.g., respondents 570, 573,
825), and the only way to disentangle trade-dress confusion from confusion triggered by
extraneous, irrelevant information is to examine the follow-up question, “What makes you say
that?” There is no evidence that Dr. Van Liere analyzed that data, however, because it is not
mentioned in his report. Nor were subjects directly asked to address this issue in their openended responses. Towards the end of his survey Dr. Van Liere could have asked questions as to
whether respondents believed generally that Samsung and Apple enjoyed a business relationship
3
It is also confusing in and of itself, because the word “what” in the question can mean almost
anything to the respondent. For example, it could relate to sub-brand identification like
“Galaxy,” model designation such as “Tab 10.1,” or simply a brand name like “Samsung.”
11
or partnership, or if indeed they were part of the same corporate entity, and the basis for their
belief.
23. Moreover, there is evidence within Dr. Van Liere’s study of individuals who answered iPad
simply as a default, due to the strong presence in the market of Apple’s iPad and the fact that the
iPad is the market leader of the category and some consider it to be the pioneer. One of the
characteristics of such a brand is that it sets the consumer’s expectation as to what the prototype
paradigm for the product class should look like, (Carpenter and Nakamoto, 1989), and hence
becomes the default option when consumers are presented with a product in the category and
asked for the source. There is significant evidence of such a perspective on the part of
respondents in the sample. Consider respondent 331, who responded “Apple” when shown the
“Nook,” and then stated “Because they are the number one leading computer manufacturer in the
world besides Microsoft, they come out with the latest inventions.” Respondent 388 answered
“Apple” as the source for the unbranded Samsung, and gave as his/her rationale: “Because they
were the first ones with it.” Respondent 674, who answered “Apple” for the unbranded Samsung
tablet, noted that it was because it was “the most common one I could ever think of.” See also
respondents 444, 610, and 629 for interesting comments which reflect the same theme.
Obviously, if the goal is to address confusion as a function of “look” or “design,” it would be
improper to count such responses as evidence of this construct because these answers
demonstrate that the respondents’ confusion was not based on anything related to the product
design.
24. Also problematic is the fact that although “test[ing] whether the look and design of a
Samsung Galaxy Tab 10.1 caused consumers to confuse this product with an iPad or Apple
product,” Dr. Van Liere coded as confused respondents who simply “named iPad or Apple when
asked what device was shown or what company makes the device.” (Van Liere Report, p. 11.)
But without knowing why respondents named iPad or Apple, those mentions alone may not have
any relationship to trade dress confusion. Dr. Van Liere should have classified respondents as
confused only if they mentioned or made clear that the look of the product or a design element
was the cause for their confusion. Counting every single mention of Apple or iPad is not
consistent with trustworthy research and exaggerates the level of alleged trade dress confusion
12
beyond how it should be fairly measured. Thus, Dr. Van Liere’s findings are not reliable nor
valid.4
x
Inaccurate and Unverified Data Analysis and Presentation
25. Using this overly broad net that captures confusion wholly unrelated to trade dress, Dr. Van
Liere claims that 6% of respondents believed the branded Samsung tablet was made by Apple
and that 19% of respondents believed the unbranded Samsung tablet was made by Apple.
Remarkably, however, Dr. Van Liere then averages the alleged confusion responses when the
Samsung product is presented in branded and unbranded form to arrive at a “net” confusion rate
of 12%. Averaging confusion rates is wrong—as evidence by the very fact that respondents had
such different reactions to them. I understand that an ultimate question for the fact finder will be
whether a particular device is likely to cause confusion, not whether Samsung’s overall sales of
products are likely to cause confusion. If that were the proper inquiry, Dr. Van Liere should
have tested other Samsung products as well, such as different sized tablet products.
26. All that can properly be stated is that the level of confusion present in Dr. Van Liere’s study,
according to his overbroad calculations, is that it can be as low as 6% for the branded Tab 10.1
or as high as 19% for the unbranded Tab 10.1. A pairwise t-test designed to detect whether or not
confusion of 6% is significantly different from the absence of confusion shows that it is not (t(397)
= 1.38, p = non-significant). Therefore, the interval estimate of confusion can include within it
no confusion at all (t(397) = 1.38, p = non-significant). That is, the use of a t-test allows for the
examination of whether a specific degree of confusion (6% in the present case) is statistically
different from a zero confusion rate. The result presented shows that we can be highly confident
that no difference exists between the measured degree of confusion (6%) and the presence of no
confusion – in other words, simply that 6% confusion is not significantly greater than zero
confusion – to conclude that no confusion is present. Statistically then, Dr. Van Liere’s findings
support the assertion that exposure to the Samsung tablets relative to the control does not
generate confusion.
4
In the next section of my Report, I recalculate the degree of confusion based on mentions of
Apple or iPad together with a design or “look” reason.
13
27. Dr. Van Liere did not report a measure of reliability for his findings above, nor did he
indicate which specific respondents were coded in any condition as indicative of confusion
between the stimuli presented, with an Apple tablet. Moreover, Dr. Van Liere’s criteria for
determining confusion between the given stimuli and Apple seemed overly broad as noted in
Paragraph 23 above, because Dr. Van Liere broadly coded as confused respondents who simply
“named iPad or Apple when asked what device was shown or what company makes the device,”
without regard for whether or not the rationale given related to “design” or “look.”
28. In order to evaluate the conclusions and coding decisions of Dr. Van Liere, open-ended
questions (specifically, question numbers 2, 3, 3a and 3b) were coded by the use of a team of
three coders who independently evaluated each statement made by each respondent for each
question, and then combined them into an assessment of the brand or company that makes or
sells the product.
29. Coders were trained by Dr. Kamins and were given instructions as set forth in Exhibit D.
30. Dr. Kamins’ coding protocol was sufficiently detailed to detect finer details and nuances in
subjects’ responses and thereby create a tougher standard of reliability. That is, coders were
instructed to note whether or not the rationale supplied by respondents for their answers, and
used by the coders as a basis for determination of brand designation, was strong or weak. In
addition, they were to make note of confusion between brands as a function of source. Such
individuals, who also appeared to confuse trade dress issues, were counted as confused, however
if their confusion was limited to source issues, they were not counted as confused. Thus, for all
three coders to agree on a brand designation, not only did they have to identify the same brand
independently, but they had to also indicate agreement as to the strength of the rationale.
31. The three coders were graduate students from Stony Brook University, who were currently
taking a course in Marketing Strategy. The students were compensated for their coding duties by
the law firm representing the defendants at a rate of $65.00 per hour. Each student was provided
the printed version of the first two pages of every respondent’s Excel sheet from the Van Liere
confusion study. The students were not told the nature of the Van Liere study nor were they
alerted to the significance or meaning of the video-selection column. This procedure was
14
followed so as not to bias the students in terms of their coding tasks. They were simply asked to
determine if a brand/company assignment could be identified from the responses to Dr. Van
Liere’s four open-ended questions. To further disguise the study, the students coded for the
presence of any and all brands, not just Apple or Samsung. Essentially, they coded what they
were presented by the respondent.
32. I classified the response as representative of a given brand if one of the following results
occurred:
x
All three coders named the same brand without any caveat.5
(reliability = 100%)
x
All three coders named the same brand and one coder noted a “weaker” reason for
classification (reliability = .333)6
x
All three coders named the same brand and two coders noted a “weaker” reason for
classification (reliability = .333)7
The results of the re-coding of Dr. Van Liere’s data reveals the findings in Table 2 below based
upon the unbiased approach taken by the trio of coders (the number of those confused and the
reliability factor are presented in brackets).
TABLE 2
CONFUSION BETWEEN CELLS WITH APPLE OR IPAD
Samsung Unbranded
31.15% (62…r=.807)
Samsung Branded
17.59% (35…r=.867)
Nook (Control)
16.00% (32…r=.792)8
5
That is, the reason given for classification was not characterized as “weaker.” (n=50 for
“Samsung unbranded” condition; n=28 for Samsung branded; n=22 for Nook-Control).
6
(n=9 for “Samsung unbranded;” n=5 for “Samsung branded;” and n=4 for Nook-Control).
7
(n=3 for “Samsung unbranded;” n=2 for “Samsung branded;” and n=6 for Nook-Control).
8
All of these reliabilities exceed that required in exploratory research as specified by Nunnally
(1970).
15
33. Just as Dr. Van Liere did in his study, I subtract the amount of confusion associated with the
control product from each of the tested Samsung products to obtain the net confusion level.
Using Dr. Van Liere’s underlying data – which is inherently flawed for various reasons set forth
above – the net confusion rate with Apple actually amounts to 15.15% when the product is
unbranded and 1.59% when it is branded. If, for the sake of comparison, we were to imitate
Dr. Van Liere’s “average” of confusion rates, confusion would be reported at 8.37%. Exhibit E is
an Excel spreadsheet containing the final coding information for this analysis.
34. Dr. Van Liere’s study suffers from serious methodological flaws directly affecting the
reliability of the data. There is no information provided in terms of who coded the data as being
indicative of confusion. If Dr. Van Liere was the only coder, then there is a further issue
regarding the reliability and validity of his interpretation of the data. There would be inherent
and inescapable bias, because Dr. Van Liere was hired by Apple to conduct the report and he
was aware of the goals of the survey and what Apple hoped to prove with it. In addition, if he
were the only coder, there is no way to measure the reliability or validity of the coding. At
minimum three coders should have interpreted the verbal responses to the questions focusing on
“What tablet computer was shown in the video” as well as “What brand or company puts out the
tablet shown in the video?” The use of three coders would have enabled measurement of
reliability as a function of the relative agreement rate among the coders, as was evident in the
recoding of the data.
35. Dr. Van Liere does not inform the reader whether or not the data were validated nor what
percentage of the sample was validated. This information should be provided in order to assess
the trustworthiness of the underlying data. The absence of this information casts further doubt on
Dr. Van Liere’s findings.
36. Finally, some cell counts do not make sense, causing concern about the overall validity of the
data. For example, in Dr. Van Liere’s Table 2, the number of “Samsung branded” subjects was
199 while the number of “Samsung unbranded” subjects was also 199; however, the total of
“Combined Samsung” subjects was only 397. (Van Liere Report, p. 12.) In addition, one
respondent indicated that he/she worked for Apple (respondent 787) and thus should have been
16
deleted, which leads one to wonder how many other individuals also had potentially biasing
experiences, yet slipped though the inadequate screens set up by Dr. Van Liere.
IV. EVALUATION OF DR.VAN LIERE’S “ASSOCIATION” STUDY FOR PHONES
x
Flawed Research Protocol
37. Dr. Van Liere used an internet panel of respondents to test the strength of association
between Apple and two different Samsung phones, the Samsung Fascinate, which is also known
as the Galaxy Showcase, and the Samsung Galaxy SII Epic 4G Touch. He makes the claim that
he “used two different phones to test an array of Samsung phones that allegedly infringe the
trade dress elements at issue here.” (Van Liere Report, page 14.) The results from two stimuli,
however, cannot be generalized into findings for other Samsung models that were not tested.
Despite what Dr. Van Liere claims, he cannot extend his findings or conclusions to Samsung
phones other than the two models used in his study.
38. Dr. Van Liere’s research design included three cells, two of which were “test” cells that
exposed each respondent to two photographic images of one of the two Samsung phones, and a
third “control” cell that exposed respondents to two photographic images of the Blackberry
Storm 9550. The Blackberry Storm 9550 is a poorly chosen control, however, because the
general look or design of the phone is very different from that of the iPhone. Alternative control
brands could have been the HTC Touch Pro 2 or the LG G2x. As in the previous study on
confusion, the limitation to the use of only one control brand ties results down to the specific
control brand utilized, reducing the generalizability of the study.
39. In conducting his dilution/association survey, Dr. Van Liere failed to take a somewhat
obvious precaution to avoid the introduction of significant bias into the testing procedure. He
should have asked respondents about the brand name of the device they were using to view the
images and participate in the internet survey, but he did not ask that question. If the device were
made by one of the parties (a Samsung or Apple brand), then the respondent should have been
eliminated from consideration. Such exposure during the survey could well have exerted an
17
impact, subliminal or otherwise, upon the respondent’s evaluation of the images. Without inquiry
into such exposure, there is now absolutely no way of knowing if bias resulted. Because Dr. Van
Liere did not use the necessary screening devices in his research protocol, he introduced the
potential for significant bias. As a result, his findings are neither valid nor reliable.
x
Improper Universe Definition
40. According to Dr. Van Liere, the appropriate population to study regarding the construct of
association is the “general population of the United States 18 years or older.” (Van Liere Report,
page 13.) The logic that he provides for studying such a population is that “dilution is intended to
protect trademarks/trade dresses that have some degree of fame. For a mark to be famous it must
be recognized by the general population. See McCarthy, 24:92.” (Van Liere Report, page 13,
footnote 16.) While the general population may be relevant for the degree of fame to be
attributed to a trademark or service mark, the standard to be applied for the association of that
mark with another is the perceptions of consumers of the junior user’s products, as in forward
confusion analysis. (McCarthy, 24:119)
x
Biased Survey Questions
41. Dr. Van Liere’s initial question significantly biases the entirety of his study. Addressing
“association” – the ultimate and underlying purpose of the study – his initial question asked:
“Does the look and design of the phone bring to mind or create any association for you with
other phones?” This first question improperly introduces significant bias by suggesting to the
respondent that indeed there is an association between the phone shown and some other phone.
However, a purpose of the study was to determine whether or not there was such an association,
so to suggest an association exists at the outset represents an egregious violation of proper basicresearch protocol. By asking right from the start if there is an association between the stimulus
(an image of a given phone) and another phone, the thought of association is placed in the
consumer’s mind when it may have not been there before. The question also fails to include the
converse option (“Does or doesn’t the look and design of the phone bring to mind or create any
18
association for you with other phones?”), which is itself another violation of basic research
methodology.
42. Moreover, Dr. Van Liere’s follow-up question also forces the issue. He asks: “You may have
already told us this, but what company or companies do you associate with the look and design
of the phone?” If an association with another company is not teased out of the consumer after the
first question, it is almost certainly extracted by this second question. The respondent has not
necessarily provided any foundation for an association with any company at all, yet is now being
asked to pinpoint one. By this time, the respondent may feel that the “correct” answer to the
question series is “yes,” and the company that comes to mind is the one with the largest market
share, namely Apple (Seitz, 2012).9
43. Dr. Van Liere could have easily asked the “association” question without making the link for
the consumer. Consider the option of asking the open-ended question: “What does the look and
design of the phone make you think of?” His failure to do so renders the results of his study
unreliable, as potentially the product of respondents’ guesswork.
x
The Data Simply Reflect Apple as the Default Brand
44. The data presented in Table 3 of Dr. Van Liere’s report underscore that many Apple
mentions are due to its being the brand or market leader. Consider the fact that there is a stronger
association between the experimental stimulus presented and the Apple iPhone when Apple is
the only brand mentioned. Relative to those who associate the stimulus with Apple as well as
other brands (in other words, analyzing the number of respondents who associate the phone
exclusively with Apple (“A”) against the number who associate the phone with several brands,
of which Apple is one; an A to A+x ratio), the findings for the percentage of those subjects who
associate it uniquely with Apple can be seen across experimental conditions in my Table 3
below:
9
Dr. Van Liere’s confusion study demonstrates that some respondents named Apple because of
its brand strength– the market leader/founder springing first to mind.
19
TABLE 3
ASSOCIATION OF GIVEN PHONE WITH APPLE
Fascinate/
Showcase
Galaxy S II
(EPIC 4G)
Blackberry
Storm
Percentage of respondents who
associate stimuli uniquely with Apple (A)
35.0%
Percentage of respondents who
Associate stimuli with Apple &
other brands
(A+X)
17.0%
16.0%
6.0%
(A/A+X)
67.3%
68.6%
57.1%
35.0%
8.0%
45. These percentages of unique associations with Apple are not significantly different among
the three brands (chi-square = 1.10, p>n.s.). This closeness suggests that a given brand’s
strength of association with Apple is independent of its overall degree of association with
Apple. This data implies that for any brand, be it Samsung or Blackberry, the strength of
association with Apple is the same – Apple is the default brand to mention when shown a smart
phone image and asked to identify a brand of phone. This default position may be due to Apple’s
strength in smart phone market share, (AppleInsider 4/3/12 reports that Apple has a 30.2% share
of the domestic smart-phone market, second to Google), or simply to the strength of the Apple
brand generally. However, it is not due to trade dress. If it were, the control condition would
reflect different relative strength of association than the test condition, especially given the
distinct appearance of the Blackberry device.
IV. DR. KAMINS’ MALL INTERCEPT STUDY FOR ASSOCIATION
46. This section of the report describes a survey I designed and conducted to examine the degree
to which consumers associate Samsung phones with Apple phones in a mall environment where
they are able to handle and use them rather than only seeing photographic images of them as in
Dr. Van Liere’s survey. I tested the same Samsung and control phones as did Dr. Van Liere, but I
also added another control phone to my survey.
20
a. Research Protocol
47. In this study, I replicated Dr. Van Liere’s methodology as closely as possible by testing the
identical phones (with one additional phone) and asking the identical substantive questions.
Specifically, I tested the Samsung Fascinate/Galaxy Showcase and Galaxy S II Epic 4G Touch,
as well as the Blackberry Storm 9550. The main difference is that the study was conducted in a
mall environment rather than on the internet. A mall setting enables the respondents to handle
and use the phone, unlike a survey over the internet where subjects are only able to examine
photos of a phone from specific angles limiting generalizability. Essentially, my study of the
exact brands and models of smart phones that Dr. Van Liere studied, allows me to test for the
effect of actual handling and usage of a real product – rather than merely viewing photos – on the
degree of association that the average consumer makes with Apple.
48. The second difference in my study was that in addition to the Blackberry Storm 9550 used by
Dr. Van Liere, I included a second control smart phone in my study, the LG G2x. This additional
control enables examination of the presence of net incremental association, if any, introduced by
Dr. Van Liere into his experiment through the use of the Blackberry Storm as a control as
opposed to another brand.
49. The survey methodology involved a mall intercept approach of the general population 18
years of age or older in order to match Dr. Van Liere’s population description. The requirement
was to expose each of the four smart phones to approximately 100 respondents (for a total of
roughly 400 respondents). The four phones tested were the Samsung Fascinate/Galaxy
Showcase, Samsung Galaxy SII Epic 4G Touch; LG G2x, and Blackberry Storm 9550.
Approximately 90 interviews were completed in each of five mall locations in or near Tampa,
Atlanta, Chicago, San Francisco and Philadelphia.
21
b. Design of the Survey Instrument
50. The survey began as potential participants were intercepted in the mall and told the
following:
“Hello, my name is ____ and I’m with Quick Test/Heakin Research, an independent research
firm. We are conducting a research project and we would very much like to include your opinions.
I would like to ask you a few questions to see if you qualify for this study and, if so, invite you to
come back with me to our office to participate in the short survey. The interview will take just 10
minutes and if you complete the survey, we will pay you $5 for taking the time to help us out.”
The interviewer then recorded the potential participant’s gender in Screener 1 (S1), and asked
them their age in categorical form which was required to be 18 years old or older (S2). To attain
consistency with Dr. Van Liere, potential respondents were asked in S3: “In the last year, which
if any of the following products have you purchased,” the choice options were: “laptop
computer,” “tablet computer,” “desktop computer,” “digital music player, such as an mp3
player,” or “mobile phone or cell phone.” Response options noted alongside the products were
“yes,” “no” or “Don’t know.”
51. In S4, respondents were given the same choice and response options, however the question
asked was slightly different as potential respondents were asked: “In the next year, which if any
of the following products do you expect to purchase?” Again following Dr. Van Liere’s screener,
potential respondents were then asked in S5: “Are you or any member of your household
employed by: “A company that sells travel packages?,” “A company that sells videos or
DVD’s,” and/or a “market research company.” Only those who responded “No” to the third
option were allowed to continue. In S6 potential respondents were asked: “Have you participated
in another survey regarding mobile phones or tablet computers in the last 12 months?” Only
those who responded “No” were allowed to continue with the research screening process.
Finally, potential respondents were asked in S7: “Do you usually wear glasses or contact lenses
when shopping?” If a given individual had proceeded through all of these screeners, and did not
wear glasses or contact lenses when shopping, they then were given an invitation to participate in
the main survey. If they indicated in S7 that they indeed required glasses or contact lenses to
shop, they were then asked in S8: “Do you have your eyeglasses with you or are you wearing
22
contact lenses?” If they had their eyeglasses or contact lenses on, then they were invited to
participate in the research, if not, the interview was terminated, and the individual was thanked.
(The screener questionnaire is attached as Exhibit F).
52. The invitation appeared as follows below and was read by the interviewer to the potential
respondent:
“Great; you qualify for the study. I have some additional questions and we need to show you a
product before asking you these questions. Please come with me to the interviewing area where
you can look at the item. We will give you $5 for taking the time to help us and the interview
should take less than 10 minutes.”
The individuals who agreed to participate in the main survey were then asked for their name and
telephone number, and had to provide a first name and telephone number at minimum to
qualify for inclusion in the main study.
53. When the respondents arrived at the interviewing site within the mall, they were told the
following, which mirrors Dr. Van Liere’s questionnaire language:
“Today, we are going to ask you to look at a mobile phone, after which we will ask you some
questions about what you saw. We are interested in your honest opinions. There are no right or
wrong answers. If for any question you don’t know the answer or don’t have an opinion, please do
not guess.”
54. The respondents were then given a mobile phone to hold, and the interviewer told them:
“Here is a mobile phone. Please look at the phone as long as you like. Feel free to move through
the various pages and handle the phone. But since the phone is not activated you won’t be able to
make calls or connect to the internet. Let me know when you are done and ready to answer a few
short questions.”
55. After each individual had finished examining and using the phone, he/she was then asked the
first question in the survey, identical to that in Dr. Van Liere’s study, as follows: “Does the look
and design of this phone bring to mind or create any association with any other phones?” If the
response was affirmative, respondents were asked Question #2 in an open-ended form identical
to Dr. Van Liere’s study: “What other phones do you associate with the look and design of this
phone?” To imitate Dr. Van Liere’s study as closely as possible, the instructions required the
interviewer to record the verbatim responses and not to ask for additional responses. Question #3
followed, again in open-ended form: “What makes you say that?” The instructions for the
interviewer were to record the verbatim responses and not to clarify or probe for any additional
responses,” because Dr. Van Liere’s internet study had no such probes or prompts. Respondents
23
who answered “no” or “don’t know” to Question #1, on the other hand, proceeded immediately
to Question #6 about their purchasing and shopping habits regarding smart phones.
56. Question #4, continued on this theme and was identical to that asked by Dr. Van Liere: “You
may have already told us this, but what company or companies do you associate with the look
and design of this phone?” Responses were recorded verbatim without additional prompts.
Finally, Question #5 again asked “What makes you say that” as in Question #3, with the same
instructions given to the interviewer as in Question #3.
57. The set of the first five questions thus properly duplicated those asked by Dr. Van Liere in
his study of association, so that comparisons could later be made between the studies. All
respondents answered some additional questions to obtain additional information about their
purchase habits related to smart phones. Questions 6, 7 and 8 asked in sequence the following:
”In the past six months have you purchased or shopped for a smartphone?” (options provided to
Q6 were “Yes” “No” and “Don’t Recall”); then “Do you currently own a smartphone?” (options
for Q7 were “Yes” or “No”); and for those who answered “Yes” to Q7 “Which brand and
model?” was asked in Q8. Validation of the sample was undertaken and 63.2% of those sampled
were validated a number which exceeds industry standards. (The main questionnaire is attached
as Exhibit G).
c. Results
58. The data was coded by a team of five individuals inclusive of Dr. Kamins and the original set
of three coders who coded Dr. Van Liere’s tablet study on confusion. The categories chosen in
which to code the data were selected to match as closely as possible those selected by Dr. Van
Liere in his “association” study. Specifically, the coding team was told to code the data for the
first five questions, which had been asked in identical form by Drs. Van Liere and Kamins.
59. I met with the team of four graduate students and explained to them that coding was to be
based on an overall impression that they received from the entire set of five questions, evaluated
together. The coding categories were as follows: 1) “Only Apple brand mentioned;” 2) “Apple
and other brands mentioned;” 3) “Other brands mentioned but not Apple;” 4) “Only Samsung
24
mentioned;” 5) “Samsung and other brands mentioned;” and 6) “Respondent does not mention
any brand.”10
60. The coding team was informed that cell-phone carriers such as “Boost,” “T-Mobile” and
“AT&T” were not to be counted as a brand of cell phone manufacturer since they were
providers. I personally met with the team of coders and led a practice coding session on a limited
set of questionnaires, so that the team would understand the nuances of coding in this study
before they began. A code was assigned for a given respondent as a function of majority
agreement. The reliability was assessed as follows: if all coders agreed it was 100%; if four of
five coders agreed it was 60%; if three of five coders agreed it was 30%.11 The overall degree of
reliability across coders was high at 89.87%, lending a great degree of trustworthiness to the
findings.
61. A total of 428 respondents completed the survey, and of these respondents, 237 (55.4%)
indicated that the look and design of the phone they were presented with brought to mind an
association with another phone or phones. In the study, 106 respondents were exposed to the
Blackberry Storm phone, 105 to the LG G2x, 111 to the Samsung Galaxy S II Epic Touch, and
106 to the Samsung Galaxy Showcase. When asked whether or not the phone was associated
with any other phones, 33 individuals indicated that the Samsung Galaxy SII Epic Touch was so
associated (29.7%), whereas the number for the Galaxy Showcase was 29 (27.4%). The
percentage of association for the two control phones with another phone or phones was 14
individuals (13.2%) for the Blackberry Storm and 37 individuals for the LG G2x (35.2%) control
phone.12
62. This data shows two important findings. First, the degree of association that the LG G2x
phone has with another phone or phones is as high as, or higher than the Samsung phones tested.
10
Consistent with Dr. Van Liere’s report, this code is reserved for those respondents who
indicate that they associate the look and design with other phones, but then provide no specific
brand or type of phone.
11
In only one case, two individuals represented the majority (e.g., two of five coders had
identical codes, the other three had different codes). In that case the reliability score was 10%.
12
The categories used for association with other phones for the Samsung phones included the
“Apple” code; “Apple with other brands” code; and “Samsung with Other Brands” code. For the
“control” phones, I used the following categories: “Apple” “Apple with other brands”
“Samsung” and “Samsung with other brands”.
25
This finding is also evident when the “other” phone association is restricted to Apple. Second,
the results for the Blackberry phone, the sole “control” phone used in Dr. Van Liere’s study, are
inconsistent with the control I added, the LG G2x, as well as with both of the Samsung phones.
This stark inconsistency (13.2% vs. 35.2%) casts significant doubt on the validity of Dr. Van
Liere’s choice of a control.
63. In terms of “association” with Apple, for the Samsung Galaxy SII Epic Touch, 20 individuals
made a unique association with the Apple brand (18.0%) and five more individuals associated it
with Apple and other phones (4.5%). For the Samsung Galaxy Showcase, 21 respondents
associated the phone uniquely with Apple (19.8%), and four more individuals associated it with
Apple and other brands (3.8%). In the control condition, 22 individuals (21.0%) expressed a
unique association between the LG G2x phone and an Apple phone; one additional individual
associated the LG G2x phone with Apple and other phones (.9%). By comparison, 1 respondent
(.9%) associated the Blackberry Storm exclusively with Apple, and 4 respondents (3.8%)
associated it with Apple as well as other brands. Exhibit H is an Excel spreadsheet containing
the final coding information for this analysis. This data is presented in table 4 below:
26
TABLE 4
PERCENT OF RESPONDENTS ASSOCIATING PHONE SHOWN WITH APPLE
Samsung Galaxy
SII Epic Touch
Samsung
Showcase
LG G2x
Blackberry
Storm
(n=111)
(n=106)
(n=105)
(n=106)
Total Association With Apple
25 (22.5%)
25(23.6%)
23(22.0%)
5 (4.7%)
Apple Only Brand Mentioned
Apple and Other Brands Mentioned13
20 (18.0%)
5 (4.5%)
21 (19.8%)
4 (3.8%)
22(21.0%)
1(.9%)
1 (.9%)
4 (3.8%)
Total Association With Samsung
22 (19.8%)
20 (18.9%)
15(14.3%)
9 ( 8.5%)
Samsung Only Brand Mentioned
Samsung and Other Brands Mentioned
14 (12.6%)
8 ( 7.2%)
16 (15.1%)
4 ( 3.8%)
13(11.6%)
2 ( 1.9%)
2 (1.9%)
7 (6.6%)
Other Brands Mentioned (Not Apple)
14 (12.6%)
7 (6.6%)
13 (12.4%)
23 (21.7%)
Don’t Know
9 ( 8.1%)
6 (5.7%)
11 (10.5%)
9 ( 8.5%)
Not Associated With other Phones
41(36.9%)
48 (45.3%)
43 (40.9%)
60 (56.6%)
64. Table 4 above suggests the following conclusions in terms of association. First, the
Blackberry Storm is not an effective control; it appears to be perceived a brand that is not
associated with Apple at all (4.7% total association). The Blackberry Storm also is not perceived
as being associated with Samsung (8.5%). In fact, it has the highest frequency among all of the
brands studied not to be associated with other smart phones (56.6%) and significantly higher
than the LG G2x (40.9%). Further, in terms of relative strength of association (Apple only brand
mentioned/Apple and other brands mentioned), it is significantly lower (1/5 = 20%) than the LG
G2x control (22/23= 95.6%). The data thus suggest that the Blackberry Storm is a poor choice of
control, because it is perceived by the relevant target market as a distinct device, separate and
apart from Apple and Samsung in the smart-phone industry; the LG G2x by contrast is not so
perceived.
Seven subjects were coded as both being Apple and other brands AND Samsung and other
brands since they mentioned BOTH Apple and Samsung in their verbal protocol.
13
27
65. To gain the fullest indication of the degree of association between control brands and Apple
through a larger sample size of “control” objects, we can combine the results from both the LG
G2x and the Blackberry Storm conditions and then use the average for the control percentage.
66. The “net” rate of association in terms of the degree to which respondents link the look and
design of either Samsung phone with Apple can be calculated as the rate at which they mention
Apple in the test conditions minus the degree to which they make such an association in the
control condition. When this calculation is performed the results are as below in Table 5:
TABLE 5
NET ASSOCIATION WITH APPLE
[Average of LG G2x and Blackberry Storm]
Samsung Epic 4G Touch
22.5% -13.3% = 9.2%
Samsung Galaxy Showcase
23.6% -13.3% = 10.3%
67. These findings are significantly lower than that reported by Dr. Van Liere, and can be
explained from two perspectives. First, in the present study individuals were allowed to handle
and use the phones as opposed to seeing two images on the internet as stimuli. The present study
therefore effectively replicated the standard-usage environment in which one would engage the
phone post purchase in the field, lending to strength in external validity. Secondly, the present
findings show that the control phone that Dr. Van Liere chose is not appropriate because
respondents do not consider it to be a competitive phone to those produced by Apple, Samsung
and LG, among others. Hence, the low association caused by using an inappropriate control
served to artificially inflate Dr. Van Liere’s association numbers.
68. Furthermore, if I were to use only the more trustworthy control, the LG G2x, then association
would range from .5% for the Samsung Galaxy SII Epic Touch (22.5% – 22.0%) and 1.6% for
the Samsung Galaxy Showcase (23.6% - 22.0%). These numbers are not significantly different
from no association at all. If I used only the poorly selected Blackberry Storm as a control, which
is what Dr. Van Liere did in his report, then association levels would be 17.8% for the Samsung
28
Galaxy SII Epic Touch (22.5% – 4.7%) and 18.9% for the Samsung Galaxy Showcase (23.6% 4.7%). Thus, the exact same comparison done by Dr. Van Liere, as flawed as it may be, still
yields approximately half of the net association levels he claimed to find in his internet study.
IV. CONCLUSIONS FOR THE CONFUSION STUDY
69. Dr. Van Liere’s confusion study is fatally flawed for many reasons. The major flaws
rendering the study unreliable, invalid and untrustworthy include the following:
x
The “Nook” e-reader is an invalid control because it is not a tablet computer.
x
The product exposure in both the test and control cells does not capture exposure when
the Apple is seen alongside another product, and thus the survey protocol inflates
confusion. This could easily have been accounted for in the research protocol.
x
The research protocol relies upon memory for the Apple tablet but not for Samsung,
which increases the potential for confusion.
x
The design is incomplete and is missing a control cell for the unbranded Samsung
condition, inflating confusion.
x
The sample studied admittedly does not match the demographic profile of tablet users,
and hence is not generalizable.
x
Confusion is recorded for any mention of Apple or iPad, instead of properly being
restricted to those who are confused because of a design feature. Hence, confusion is
over-estimated.
x
Individuals who work in the computer industry or for Apple should have been excluded,
yet were not.
V. CONCLUSIONS FOR THE ASSOCIATION STUDY
70. This study also suffers from significant and fatal flaws which make the findings unreliable:
x
The brand name of the device the respondent used to participate in the study was not
accounted for, which introduced significant bias into the results.
29
Bibliography
Carpenter, Gregory S., and Kent Nakamoto (1989), “Consumer Preference Formation and
Pioneering Advantage,” Journal of Marketing Research, 26 (August), pp. 285-98.
Diamond, Shari (2012), “Reference Manuel on Scientific Evidence, 2nd Edition.
Falcone, John P. (2012), “Kindle vs. Nook vs. iPad: Which eBook reader Should You Buy?”
c/Net, March 13th 2012.
Kamins, Michael A., Frank H. Alpert and Lars Perner (2003), “Consumers’ Perceptions and
Misperceptions of Market Leadership and Market Pioneership, Journal of Marketing
Management, 19, pp. 807-834.
McCarthy, C. Thomas (2012), McCarthy on Trademarks and Unfair Competition, 4th Edition.
Morgan, Fred W. (1990), “Judicial Standards for Survey Research: An Update and Guidelines,”
Journal of Marketing, Vol. 54(January), pp. 59-70.
Nunnally, Jum C. (1970), Introduction to Psychological Measurement. New York, New York,
McGraw-Hill.
Pew Report (2012), “Tablet and e-Book Readership Nearly double Over the Holiday Period,” On
e-Readers and Tablets,” January 23rd 2012.
Seitz, Patrick (2012), “Apple iPhone Expanding its Smart Phone Market Share,” Investor’s
Business Daily, April 2nd 2012.
31
Disclaimer: Justia Dockets & Filings provides public litigation records from the federal appellate and district courts. These filings and docket sheets should not be considered findings of fact or liability, nor do they necessarily reflect the view of Justia.
Why Is My Information Online?