PUBLIC VERSION Electronically Filed Docket: 19-CRB-0005-WR (2021-2025) Filing Date: 01/14/2020 07:53:38 PM EST
Before the UNITED STATES COPYRIGHT ROYALTY BOARD LIBRARY OF CONGRESS Washington, D.C.
In the Matter of:
Determination of Rates and Terms for Docket No. 19-CRB-0005-WR Digital Performance of Sound Recordings (2021-2025) and Making of Ephemeral Copies to Facilitate those Performances (Web V)
WRITTEN REBUTTAL STATEMENT OF THE NATIONAL ASSOCIATION OF BROADCASTERS
Sarang Vijay Damle (D.C. Bar No. 1619619) [email protected] 555 Eleventh Street, NW, Suite 1000 Washington, D.C. 20004-1304 T: (202) 637-2200 F: (202) 637-2201 Joseph R. Wetzel (CA Bar No. 238008) [email protected] Andrew M. Gass (CA Bar No. 259694) [email protected] 505 Montgomery Street, Suite 2000 San Francisco, CA 94111-6538 T: (415) 391-0600 F: (415) 395-8095
Counsel for the National Association of Broadcasters
January 10, 2020 PUBLIC VERSION
Table of Contents for the Written Rebuttal Statement of The National Association of Broadcasters
A. Introductory Memorandum to the Written Rebuttal Statement
B. Index of Rebuttal Witness Testimony
C. Written Rebuttal Testimony of Gregory K. Leonard and Appendices
D. Written Rebuttal Testimony of John R. Hauser and Appendices
E. Written Rebuttal Testimony of Joseph Ritz
F. Confidentiality Declaration and Certification
G. Certificate of Service
NAB Written Rebuttal Statement Dkt. No. 19-CRB-0005-WR (2021-25) PUBLIC VERSION
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Before the UNITED STATES COPYRIGHT ROYALTY BOARD LIBRARY OF CONGRESS Washington, D.C.
In the Matter of:
Determination of Rates and Terms for Digital Performance of Sound Recordings Docket No. 19-CRB-0005-WR and Making of Ephemeral Copies to (2021-2025) Facilitate those Performances (Web V)
INTRODUCTORY MEMORANDUM TO THE WRITTEN REBUTTAL STATEMENT OF THE NATIONAL ASSOCIATION OF BROADCASTERS
The National Association of Broadcasters (“NAB”) presented evidence and expert opinion in its written direct case that digital simulcasts of over-the-air radio broadcasts are fundamentally different from other non-interactive services, and as a result, the Judges should establish a lower royalty rate for simulcasts. It should not have come as a surprise to SoundExchange that NAB would present such a case; NAB proposed just such a differential in Web IV, and SoundExchange’s own members have entered into numerous direct licenses applying materially different economic terms to simulcasts than to custom radio offerings. SoundExchange had every opportunity in its written direct case to demonstrate why simulcast transmissions should be treated the same as custom radio transmissions, or to address simulcasts at all.1 Instead, SoundExchange’s written direct case ignored completely the important distinctions between simulcasts and other non- interactive services. SoundExchange’s entire direct case simply assumes that simulcasters and
1 As noted in the NAB’s written direct case, although there are some non-custom, non- simulcast streaming services in the marketplace, they form a fairly small share of the market. See Written Direct Testimony of Gregory K. Leonard, ¶ 35. 1 NAB Written Rebuttal Statement Dkt. No. 19-CRB-0005-WR (2021-25)
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custom radio services occupy the same market and that consumers view them interchangeably.
But all of the available evidence demonstrates otherwise.
Based on the record to date, NAB has established that a separate, lower rate for simulcasts
is appropriate. In virtually every agreement between record labels and services that offer both
simulcasts and custom radio, the labels have agreed to license simulcasts at a substantially lower
rate than custom radio. So too for other music license agreements, such as those executed by
“performing rights organizations” like ASCAP and BMI. Moreover, NAB conducted a consumer
survey that shows that, if simulcasts were unavailable, almost a third of simulcast listeners would
switch to over-the-air broadcasts and not to any royalty-generating service. Using these survey
results, NAB’s economic expert Dr. Gregory Leonard performed an opportunity cost analysis that
shows that, in a hypothetical competitive marketplace, willing buyers and willing sellers of
licenses to stream sound recordings would agree to rates for simulcasts far below the current
statutory rate. Because the plurality of simulcast listeners would switch to over-the-air broadcasts
if they could not listen to simulcasts, sellers would recognize that the cost of not doing a deal
would be a substantial loss of accretive revenue, resulting in a lower royalty rate. This result makes sense: as NAB’s fact witnesses explained, people listen to simulcasts for reasons that are very different from the reasons they listen to music-centered services, including the on-air personalities, content about local events and emergencies, and human connection.
Nothing in SoundExchange’s written direct case is contrary to—or even addresses—any of these points. Indeed, without any support for doing so, SoundExchange lumps together simulcast and custom radio and proposes a single higher royalty rate for all non-interactive services. That rate is based on Dr. Robert Willig’s opportunity cost calculations and Mr. Jonathan
Orszag’s benchmarking analysis. Neither expert provides any reason that simulcasts and custom
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radio services should pay the same royalty rate, and both reports suffer from serious flaws that
inappropriately inflate SoundExchange’s rate proposal. To make matters worse, one of
SoundExchange’s core arguments for a rate increase is the alleged convergence between custom
radio services and interactive services—a rationale with no application whatsoever to simulcasts.
Dr. Willig’s opportunity cost calculations are unreliable because they are based on a flawed
consumer survey conducted by Professor Gal Zauberman, which purports to determine how
listeners of “streaming radio services” would listen to music if those “streaming radio services”
were no longer available. As an initial matter, this survey sheds no light at all on the switching behavior of simulcast listeners in particular, since the switching hypothetical asked respondents to
imagine that both simulcasts and custom radio were no longer available. Moreover, as NAB’s
survey expert Dr. John Hauser explains, flaws in the design of Professor Zauberman’s survey lead
to overestimates of switching to new, paid music subscriptions. For example, if a respondent
indicated that he or she had not listened to an existing paid on-demand streaming service in the
last thirty days, the respondent was only given the option to subscribe to a paid on-demand service;
there was no option to switch to the respondent’s existing paid on-demand service, even though
there are many reasons why someone might not have listened to (or remembered listening to) his
or her existing paid service in the prior thirty days. Likewise, the switching question—which
asked respondents which music-listening options they would choose—improperly encouraged
respondents to select music over non-music activities. In addition, the survey failed to distinguish between making new purchases of physical or digital records, and listening to an existing physical
or digital music collection. Finally, a basic flaw in the survey’s design means that the survey
cannot accurately measure how listeners would allocate their time across substitute options. Any
one of these flaws, standing alone, would render Professor Zauberman’s survey an unreliable tool
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to estimate switching to royalty-generating activities. Taken together, these flaws are so serious
that the survey should be ignored in its entirety.
Moreover, as Dr. Leonard explains, the flaws in Professor Zauberman’s survey infect
Dr. Willig’s opportunity cost calculations, and therefore his Shapley Value and Nash-in-Nash
analyses. By assuming that any respondent who did not report listening to a subscription service
in the prior thirty days is not already a subscriber and would pay a new subscription fee in the
absence of non-subscription non-interactive services, Dr. Willig overstates the opportunity cost.
Similarly, Dr. Willig inflates the opportunity cost by assuming that each respondent who said he
or she would switch to a CD or digital music collection would purchase new CDs or digital music rather than listen to an existing collection. Further, Dr. Willig implausibly assumes that, where a respondent indicated he or she would switch to more than one subscription service, that respondent would actually subscribe to multiple services instead of just one—again resulting in a magnified opportunity cost. Finally, even setting aside the problems with Dr. Willig’s opportunity cost inputs, his Shapley Value and Nash-in-Nash frameworks are not specific to simulcast, offer no justification for using Pandora’s financials as a proxy for simulcasters, and make a number of improper simplifying assumptions that may result in an overstated royalty calculation.
Mr. Orszag’s benchmarking analysis is an equally unsound basis for SoundExchange’s proposed rate. As a threshold matter, Mr. Orszag entirely ignores the most relevant non-interactive benchmarks: iHeartMedia Inc.’s (“iHeart”) renewed direct deals with independent record labels.
As Dr. Leonard explained in his Written Direct Testimony, direct licenses that have been renewed with the bilateral assent of both the buyer (the radio station) and the seller (the record label) are the best evidence of a willing-buyer willing-seller transaction at the effective per-play royalty rate that predated the renewal. Because of the complexity of the financial terms of sound recording
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license agreements, when they initially agree to a license, the radio station and the record label can only predict how those terms will play out. But once that license is up for renewal, the radio station and the record label know the actual financial performance of the deal. If the deal is renewed, both parties must have deemed it beneficial, both ex post as well as ex ante. Dr. Leonard thus relies for his benchmarking analysis on the fifteen instances in which independent record labels that originally entered into direct deals with iHeart have chosen to renew their agreements. Mr. Orszag overlooks these agreements completely.
Instead, Mr. Orszag bases his proposed royalty rate on the effective royalty rates as a percentage of revenue paid by subscription interactive services. He claims that subscription interactive rates are appropriate benchmarks because the functionality between interactive and non-interactive services has converged, particularly with respect to subscribers’ use of playlists.
But this alleged convergence has zero relevance to simulcasts, which do not allow users to have any control over what they hear. Indeed, simulcasts provide the least amount of interactivity of any non-interactive service, and cannot offer the core feature (and primary driver of demand) of an interactive service: the ability to listen to any song in the service’s library at any time.
Moreover, Mr. Orszag’s benchmark agreements are the product of the undisputed market power of the major record labels, yet his rate proposal fails to adjust for that power. Mr. Orszag admits—as he must, given the deposition testimony of Warner and Universal witnesses—that the major record labels are “must-haves” for the interactive services, at least in the long term. Indeed, nothing has changed since the Judges’ consistent findings in Web IV, SDARS III, and
Phonorecords III that the majors have complementary oligopoly power: an interactive service still needs the full catalog of each major to be successful; an interactive service cannot induce price
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competition by steering; and there is no evidence of price competition among the major labels to be included in the libraries of interactive services.
Nonetheless, Mr. Orszag claims that the interactive services have recently gained bargaining power that offsets the major labels’ complementary oligopoly power. He relies in
substantial part on the alleged ability of the interactive services to steer by placing songs on playlists or in other prominent locations on the service. But he ignores [
. In addition, the evidence developed in discovery contradicts Mr. Orszag’s
claim that .
For example, Universal’s Aaron Harrison testified that
Indeed, both publicly available materials and documents produced by the labels establish that the interactive services are
engaged in intense competition with one another for end users, which weakens their bargaining power in negotiations with the majors. The substitutability of Spotify and Apple Music, and thus
the likelihood that a user unsatisfied with one service could simply switch to the other, make it
imperative that the services continue to offer the core functionality of on-demand access to all
major content and maintain the longstanding $9.99 per month price point while offering discounted
family and student plans. Accordingly, if the Judges rely on the interactive benchmarks (which
they should not, for all the reasons explained in NAB’s submission), they must be adjusted for the
complementary oligopoly power of the major record labels.
Finally, SoundExchange’s proposed changes to the minimum fee and audit-related terms
of the statutory license are unworkable. With respect to minimum fees, Dr. Leonard explains why
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SoundExchange has not offered evidence sufficient to support the doubling it proposes. With respect to audits, iHeart’s Joe Ritz discusses how an audit is a complicated, detailed, and sometimes contentious process. Auditors frequently seek extensive raw data and related information that is several years old, requiring the licensee to task engineers, finance team members, and legal personnel with piecing together and interpreting data from multiple systems created by employees no longer working at the company. It simply is not possible to respond to every data request within sixty days, and allowing audits of multiple time periods in the same year—especially by an auditor that is not independent—would only slow the process down. Not surprisingly, SoundExchange’s proposals are inconsistent with the audit provisions of license agreements reached in the market.
Summary of the Written Rebuttal Testimony of NAB’s Witnesses
NAB’s Written Rebuttal Statement includes testimony from the following expert and fact witnesses.
Expert Witnesses
Dr. Gregory K. Leonard is an economist and Vice President at Charles River Associates.
In his Written Direct Testimony, Dr. Leonard explained that simulcast is differentiated from other non-subscription non-interactive services (such as custom radio) in economically important ways that dictate a lower per-play royalty rate for simulcasts. Further, Dr. Leonard reviewed the available direct license agreements and determined that iHeart’s renewed licenses with independent record labels provide a useful benchmark for both (i) the need for separate rates for simulcast and custom radio and (ii) what those rates should be. Dr. Leonard’s benchmarking analysis demonstrated that competitive rates for simulcasts and custom radio would fall somewhere between [ ] and [ ], and [ ] and [ ], respectively.
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Additionally, Dr. Leonard used consumer survey data provided by Dr. John Hauser (discussed below) to conduct an opportunity cost analysis to determine the net loss in royalties a label would
expect from licensing simulcasts. Using that approach, Dr. Leonard calculated the opportunity
cost of licensing simulcasts, and thus the appropriate per-play royalty rate for simulcasts, as falling
somewhere between $0.00065 and $0.00108.
Dr. Leonard submits Written Rebuttal Testimony in response to the Written Direct
Testimony of Dr. Robert Willig, Mr. Jonathan Orszag, and Dr. Catherine Tucker. Dr. Leonard
explains that SoundExchange’s experts assume—with no justification—that the royalty for
simulcast and the royalty for custom radio should be the same, despite economically significant
distinctions between those services. He further explains that Dr. Willig’s royalty proposal is
flawed because his improper use of SoundExchange’s consumer survey results in overstated
opportunity cost calculations. Dr. Leonard addresses various problems with Mr. Orszag’s benchmarking analysis, including that (i) he ignores non-interactive benchmarks that are more
comparable than his interactive benchmarks; (ii) his subscription interactive benchmark is not
appropriate for simulcasts, which have not “converged” with interactive services; and (iii) his
adjustment for interactivity based on ratio equivalency is insufficient. Moreover, Dr. Leonard
explains that Mr. Orszag is wrong in arguing that the complementary oligopoly problem posed by
the major sound recording companies no longer exists: Mr. Orszag admits that the major record
labels are “must-haves”; the interactive services still have no ability to steer; [
]; and the interactive services are engaged in intense competition for end
users that weakens their bargaining power vis-à-vis the major record labels. Dr. Leonard also
rebuts Dr. Tucker’s claim that the ability to pay higher rates somehow justifies higher rates and
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explains that SoundExchange’s proposed increase in the minimum fee is untethered from its
incremental administrative costs. Finally, in rebuttal to SoundExchange’s unitary rate proposal,
Dr. Leonard provides an update to his opinions on workably competitive royalty rates based on
the CRB’s recent announcement of the 2020 webcasting rates, and discusses additional evidence
of the promotional value of radio.
Dr. John Hauser is the Kirin Professor of Marketing at the Massachusetts Institute of
Technology (“MIT”) Sloan School of Management. He is an expert in survey design, demand
forecasting, product confusion, product feature valuation, and measurement of consumer preferences, beliefs, and willingness to pay. In his Written Direct Testimony, Dr. Hauser
conducted a consumer survey to measure what consumers would do in place of listening to Internet
simulcasts of terrestrial commercial radio if such simulcasts were not available. The survey also
determined consumers’ listening behavior with respect to Internet simulcasts of terrestrial
commercial radio including (1) how much they listen, (2) what content they listen to, and (3) the
importance of that content to consumers. The results of Dr. Hauser’s survey confirm that non-
music aspects of NAB members’ simulcasts drive listening behavior, and show that simulcast
listeners tend not to be people who would otherwise listen to content that would result in higher
royalties for record companies.
On behalf of NAB and Sirius XM/Pandora, Dr. Hauser submits Written Rebuttal
Testimony in response to the Written Direct Testimony of Professor Gal Zauberman, who designed
and administered a survey attempting to measure the music-listening behavior of listeners of music
streaming services and to determine how those listeners would listen to music if those music
streaming services were not available. In his rebuttal testimony, Dr. Hauser explains why
Professor Zauberman’s survey data cannot be used to reliably estimate such switching behavior,
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particularly with respect to simulcast listeners. Dr. Hauser also explains that flaws in the design
of Professor Zauberman’s survey likely lead to overestimates of switching to new, paid music
subscriptions. Further, he shows that the design of Professor Zauberman’s survey prevents it from
reliably estimating the switching behavior of listeners of Internet simulcasts of terrestrial
commercial radio and listeners of Sirius XM over the Internet in particular. As a result of the flaws
in the design of Professor Zauberman’s survey, and other differences between Dr. Hauser’s survey
and Professor Zauberman’s survey, only Dr. Hauser’s survey can be used to measure the switching behavior of listeners to Internet simulcasts of terrestrial radio.
Fact Witness
Joseph Ritz is Vice President, Finance, Digital Networks at iHeart. He submits Written
Rebuttal Testimony in response to SoundExchange’s proposed changes to the audit-related terms
of the statutory license. Mr. Ritz explains that, contrary to the testimony of SoundExchange’s
Chief Operating Officer Jonathan Bender, iHeart has strong business incentives to ensure its
royalty payments are timely and accurate. He discusses how iHeart takes its sound recording
royalty obligations seriously in order to foster and maintain its valued relationships with artists
and direct deal partners. He also explains the burdens that audits typically impose on iHeart,
especially when they require iHeart personnel to take substantial time away from their jobs to
reconstruct extensive raw data from many years prior. In particular, Mr. Ritz describes iHeart’s
ongoing 2011-2013 SoundExchange audit and highlights several logistical issues and delays on
the part of the auditors, including multiple requests for redelivery of already available files and a
15-month delay in receiving the draft audit report. Mr. Ritz explains why audits of multiple time periods in the same year, strict deadlines for responding to auditor requests and cost-shifting for
failure to comply, and SoundExchange’s participation in the audit are unworkable proposals. He
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testifies that these proposed changes will only lead to longer delays and more costs for both the licensee and SoundExchange. Lastly, Mr. Ritz supports NAB’s proposal to amend the interest rate for underpayments to the rate recently adopted in SDARS III.
Respectfully submitted,
LATHAM & WATKINS LLP
Sarang Vijay Damle (D.C. Bar No. 1619619) [email protected] 555 Eleventh Street, NW, Suite 1000 Washington, D.C. 20004-1304 T: (202) 637-2200 F: (202) 637-2201
Joseph R. Wetzel (CA Bar No. 238008) [email protected] Andrew M. Gass (CA Bar No. 259694) [email protected] 505 Montgomery Street, Suite 2000 San Francisco, CA 94111-6538 T: (415) 391-0600 F: (415) 395-8095
Counsel for the National Association of Broadcasters
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Before the UNITED STATES COPYRIGHT ROYALTY BOARD LIBRARY OF CONGRESS Washington, D.C.
In the Matter of:
Determination of Rates and Terms for Docket No. 19-CRB-0005-WR Digital Performance of Sound Recordings (2021-2025) and Making of Ephemeral Copies to Facilitate those Performances (Web V)
EXPERT REBUTTAL WITNESS STATEMENT OF DR. GREGORY K. LEONARD
January 10, 2020
NAB Written Rebuttal Statement Dkt. No. 19-CRB-0005-WR (2021-25)
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TABLE OF CONTENTS
I. QUALIFICATIONS ...... 1
II. ASSIGNMENT AND SUMMARY OF OPINIONS ...... 1
III. SOUNDEXCHANGE’S EXPERTS DID NO ANALYSIS OF THE APPROPRIATE ROYALTY FOR SIMULCAST, BUT INSTEAD ASSUMED (WITH NO ATTEMPT AT JUSTIFICATION) THAT THE ROYALTY FOR SIMULCAST SHOULD BE THE SAME AS THAT FOR CUSTOM RADIO ...... 3
IV. DR. WILLIG’S ROYALTY PROPOSAL IS FLAWED ...... 7
A. SoundExchange’s Consumer Survey Provides an Unreliable Basis for Calculating the Opportunity Cost of Licensing Simulcast ...... 7
B. Dr. Willig’s Flawed Use of the SoundExchange Survey Results in Overstated Opportunity Cost Calculations ...... 11
C. The “Share of Ear” Survey Also Provides an Unreliable Basis for Dr. Willig’s Opportunity Cost Calculations ...... 17
D. Dr. Willig’s Use of the Shapley Value and Nash-in-Nash Frameworks Is Flawed ...... 22
V. MR. ORSZAG’S ROYALTY PROPOSAL IS FLAWED ...... 25
A. Mr. Orszag’s Subscription Interactive Streaming Services Benchmark Is Not Appropriate for Non-Subscription Non-Interactive Streaming Services ...... 25
B. Mr. Orszag’s Adjustment for Interactivity Based on Ratio Equivalency Is Insufficient ...... 35
C. Mr. Orszag’s Claim That the Complementary Oligopoly Problem No Longer Exists Is Incorrect ...... 40
1. The Major Labels Still Have Complementary Oligopoly Power ...... 40
2. The Interactive Services Have No Ability to Steer ...... 43
3. The Evidence Shows the Major Labels Recognized Their Strong Bargaining Positions Vis-à-vis the Services ...... 49
4. The Interactive Services Are Engaged in Intense Competition With Each Other, Which Weakens Their Bargaining Positions Vis-à-vis the Major Labels ...... 51 i NAB Written Rebuttal Statement Dkt. No. 19-CRB-0005-WR (2021-25)
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VI. DR. TUCKER’S OPINIONS DO NOT SUPPORT A HIGHER ROYALTY RATE FOR SIMULCAST ...... 63
VII. SOUNDEXCHANGE HAS FAILED TO DEMONSTRATE THAT THE MINIMUM FEE SHOULD BE INCREASED ...... 65
VIII. UPDATED SIMULCAST ROYALTY RATE BASED ON AN OPPORTUNITY COST FRAMEWORK ...... 68
IX. PROMOTIONAL VALUE OF RADIO ...... 69
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I. QUALIFICATIONS
1. My qualifications are discussed in my opening report.
II. ASSIGNMENT AND SUMMARY OF OPINIONS
2. I have been asked by counsel for the National Association of Broadcasters to review and respond to the opinions expressed by SoundExchange’s witnesses in their written direct testimony. My opinions are based on the information and data cited herein. I reserve the right to update my analysis and opinions if more information and data become available through discovery. I also reserve the right to respond to any further opinions and analysis offered by other experts in this case.
3. Based on my analysis, as described in greater detail below, I have reached the following opinions:
• SoundExchange’s experts did not perform any analysis of simulcast. Indeed, simulcast is barely mentioned in their reports. Instead, they calculated a royalty for custom radio and then assume, without justification, that this royalty should also apply to simulcast. • A separate analysis for simulcast is necessary because simulcast is an economically distinct service from custom radio and because the distinction has been recognized in market transactions that [ ]. • The SoundExchange user survey and Dr. Willig’s use of the survey results are unreliable for the purpose of analyzing the royalty for simulcast because: o By virtue of its design, the survey does not measure how simulcast users would respond to the absence of simulcast. o The survey shows different diversion patterns than the Hauser survey, which is designed to study simulcast user behavior. o The survey does not provide a reliable means to identify existing subscribers to paid services or to identify diversion to CDs/Vinyl/Digital Downloads. o The survey shows diversions of questionably large size to alternatives requiring a payment, suggesting the hypothetical nature of the exercise may have induced an overstatement of willingness to make a payment. o Dr. Willig assumes that respondents who chose multiple paid alternatives in an initial question would actually pay for each of those alternatives, despite many
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survey instrument did not allow respondents to provide different answers concerning their likely
behavior in the absence of simulcast versus the absence of other “free Streaming Radio”
services. As discussed further below, the evidence suggests that survey respondents do, in fact,
provide different answers for simulcast and custom radio, if allowed by the survey instrument to
do so.
6. Dr. Willig based his Shapley Value and Nash-in-Nash calculations for non-subscription
non-interactive services on financial information from Pandora.2 He did not do a version of the
calculations based on the financial information of any simulcaster, nor did he demonstrate that
the financial situation for any simulcaster is the same as that of Pandora.
7. Mr. Orszag uses subscription interactive service royalties as benchmarks for non-
interactive service royalties.3 In doing so, he makes no distinction between simulcast and custom radio. In attempting to justify subscription interactive services as a valid benchmark for non- interactive services, Mr. Orszag’s discussion is almost entirely directed at custom radio. Indeed,
many of his claimed justifications do not even apply to simulcast. For example, Mr. Orszag
claims that the subscription interactive benchmarks include the same sellers (i.e., record
companies) and similar buyers; however, in his application of ratio equivalency to non-
subscription non-interactive streaming services Mr. Orszag uses effective revenue per play
information for Pandora’s and iHeart’s ad-supported custom radio services and does not use any
information pertaining to simulcast. Thus, the “buyers” in his benchmark analysis are
Artists, American Association of Independent Music, Sony Music Entertainment, UMG Recordings, Inc., Warner Music Group Corp., and Jagjaguwar Inc., p. 10; see generally Written Direct Testimony of Gal Zauberman, September 20, 2019 (“Zauberman Report”), Appendix D. 2 Written Direct Testimony of Robert Willig, September 23, 2019 (“Willig Report”), p. 20-21, 24-26. 3 See Sections III and IV of the Written Direct Testimony of Jonathan Orszag, September 23, 2019 (“Orszag Report”).
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exclusively custom radio services and do not include simulcasters. Additionally, Mr. Orszag claims that the subscription interactive benchmarks are relevant because of the convergence between interactive services’ and non-interactive services’ functionality over time, and that this alleged convergence stems primarily from the growing use of playlists by interactive service subscribers. However, none of Mr. Orszag’s supposed evidence of increased “lean-back listening” by subscribers of interactive streaming services applies to simulcast at all, and Mr.
Orszag makes no attempt to establish convergence between interactive services’ and simulcasting’s functionality over time. Nor could he, because there is no such convergence to speak of.
8. In short, neither Dr. Willig nor Mr. Orszag has performed any actual analysis of simulcast. Indeed, the word “simulcast” appears in their reports a total of two times combined.
Rather than analyzing simulcast, Dr. Willig and Mr. Orszag assume that the conclusions they reach based on what are essentially analyses of custom radio apply to simulcast as well and that therefore the royalty for simulcast should be equal to the royalty for custom radio. However, they provide no justification for this assumption.
9. As I discussed in my opening report, this assumption is invalid because simulcast differs in economically important respects from custom radio.4 For example, Dr. Willig argues that ad- supported non-interactive services should be viewed as a part of a service’s broader business model in which the ad-supported service is used as a way to funnel users into the service’s more profitable subscription services.5 However, it is not even possible for many simulcasters to use
4 Written Direct Testimony of Dr. Gregory K. Leonard, September 23, 2019 (“Leonard Report”), p. 20. 5 Willig Report, pp. 27-31.
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11. In short, neither Dr. Willig nor Mr. Orszag has provided any reliable analysis of what the
royalty rate for simulcast should be. They have instead assumed, without providing any
justification and contrary to actual willing-buyer willing-seller (“WBWS”) agreements, that the
royalty rate for simulcast should be the same as that for custom radio.
IV. DR. WILLIG’S ROYALTY PROPOSAL IS FLAWED
A. SoundExchange’s Consumer Survey Provides an Unreliable Basis for Calculating the Opportunity Cost of Licensing Simulcast
12. A key input into Dr. Willig’s opportunity cost calculations is a consumer survey
commissioned by SoundExchange.10 Respondents to the survey were asked a screening question
about the entertainment services that they use. Those who indicated they used a music streaming
service continued the survey and were asked which music-listening options they had used in the
past 30 days.11 Next, each respondent was randomly assigned to either the scenario where (1) free streaming radio was no longer available or (2) paid streaming radio was no longer available.
If the service assumed to be no longer available in the scenario to which the respondent was assigned was a service the respondent had previously indicated he or she had used within the past
30 days, the respondent moved forward in the survey.12 The survey then directed respondents to
select how they would fill their music-listening time in the assigned scenario. The options listed
were paid on-demand streaming; free on-demand streaming; paid streaming radio service (in the
no free scenario); free streaming radio service (in the no paid scenario); satellite receiver in the
car; AM/FM radio on a traditional radio receiver; CDs, vinyl records, or MP3 files; and do
10 Willig Report, pp. 21-22. 11 Zauberman Report, pp. 13-14, 16. 12 Zauberman Report, pp. 14-15.
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something other than listen to music.13 A subset of respondents was further asked how they would allocate their time among the options they had picked.14
13. I understand that NAB’s survey expert Dr. John Hauser is providing a critique of the
SoundExchange survey from a survey perspective. Here, I only discuss the economic
implications of the survey’s flaws.
14. First, as explained in the Hauser Rebuttal Report, the SoundExchange survey is biased
against respondents expressing preferences for non-music alternatives, as Q2 asks respondents
“which of the following music-listening option(s)” they would use as substitutes for listening to music with a free (or paid, depending on the scenario) streaming radio service.15 This has the effect of overstating the opportunity cost that Dr. Willig ultimately calculates because non-music alternatives do not generate any royalties for SoundExchange. In contrast, the Hauser survey listed specific non-music alternatives such as “non-music digital content” and “print or online content.”16 Absent the survey’s bias, more users would have expressed a preference for non-
music alternatives, thereby resulting in a lower opportunity cost.
15. Second, as discussed above, the SoundExchange survey was not separately implemented
for simulcast. Instead, all non-subscription non-interactive services were lumped together.
Specifically, the SoundExchange survey asked respondents to “Imagine that all FREE [PAID]
streaming radio services were no longer available”; it did not ask respondents to imagine that
only simulcasts were no longer available.17 Even if the survey were otherwise free of flaws, it
13 Zauberman Report, pp. 16-19. 14 Zauberman Report, pp. 19-22. 15 Written Rebuttal Testimony of John R. Hauser, January 10, 2020 (“Hauser Rebuttal Report”), p. 3. 16 Written Direct Testimony of John R. Hauser, September 23, 2019 (“Hauser Report”), p. R-2. 17 Zauberman Report, pp. 16-17.
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would not be appropriate to apply the SoundExchange survey results to simulcast unless the
distribution of survey responses would have been the same for a simulcast-only version of the
survey. A comparison of the SoundExchange survey results (all non-subscription non-interactive
services lumped together) to the Hauser survey results (simulcast only) provides a rough test of
whether the distribution of survey responses is the same for simulcast as for other non-
subscription non-interactive services.18 Table 1 below compares the diversion ratios from non- subscription non-interactive services to other options derived from the results of the
SoundExchange and Hauser surveys.19 There are substantial differences between the two sets of
diversion ratios. Specifically, the SoundExchange survey produced uniformly higher diversion ratios for royalty-bearing alternatives than did the Hauser survey. This difference suggests that simulcast users would have a lower opportunity cost to SoundExchange than would users of other non-subscription non-interactive services.20 With a lower opportunity cost for simulcast,
all else equal, Dr. Willig’s Shapley Value and Nash-in-Nash calculations would have yielded a
lower royalty for simulcast than, e.g., custom radio.
18 It is a “rough” test because the SoundExchange survey is flawed in other ways that could have led to biased and unreliable results. 19 Note that the Hauser survey asked respondents about a hypothetical scenario which did not include simulcasting but did include custom radio. This means that the respondents were allowed to “switch” to custom radio in the absence of simulcast in the Hauser survey, but not in the SoundExchange survey. To account for this difference in posed hypothetical scenarios, I have calculated the percentage of the subset of respondents who did not choose custom radio who said they would switch to each of the other alternatives. 20 Another possibility, of course, is that the flaws in the SoundExchange survey render it unreliable for any purpose.
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Table 1: SoundExchange and Hauser Survey Diversion Ratios
SoundExchange Hauser
Subscription On-Demand 9.1% 1.5% SiriusXM 5.5% 3.4% Ad-supported On-Demand 16.4% 10.3% CDs/Vinyl/Digital Downloads 14.8% 1.9%
16. One particularly notable difference between the two surveys is with respect to the
diversion ratio from non-subscription non-interactive services (SoundExchange)/simulcast
(Hauser) to purchases of CDs/Vinyl/Digital Downloads. The SoundExchange survey finds a diversion ratio for this alternative of 14.8%, while the Hauser survey finds a diversion ratio of only 1.9%. The SoundExchange survey’s 14.8% figure is implausibly high given the sharp decline in purchases of CDs/Vinyl/Digital Downloads in recent years. From 2014-2018, the
RIAA reports that [
].22
Furthermore, Universal documents demonstrate [
].23 Research from MusicWatch demonstrates that [
21 RIAA 2018 Year-End Music Industry Revenue Report and RIAA 2014 Year-End Industry Shipment and Revenue Statistics. Vinyl is classified as LP/EP and both CD and vinyl sales excludes singles. 22 RIAA 2018 Year-End Music Industry Revenue Report and RIAA 2014 Year-End Industry Shipment and Revenue Statistics. 23 SOUNDEX_W5_000046466 (Universal Music Group U.S. Recorded Music, 2012 – 2019 YTD Revenue Sources).
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].24 It is unlikely that such a large
percentage of simulcast users (for whom the service is zero-fee and who likely have relatively
low willingness to pay (“WTP”) for music) would switch to the small, declining, and costly
alternative of purchasing CDs/Vinyl/Digital Downloads in the absence of simulcast. Moreover,
the SoundExchange survey’s finding of a large diversion to CDs/Vinyl/Digital Downloads is
inconsistent with evidence in the record that shows that [
].25 The implausible results of the SoundExchange survey may be the result of having a
single response option for switching to CDs/Vinyl/Digital Downloads that the respondent
already owns or would purchase, as discussed in more detail below.
B. Dr. Willig’s Flawed Use of the SoundExchange Survey Results in Overstated Opportunity Cost Calculations
17. In incorporating the SoundExchange survey results into his calculations, Dr. Willig makes several flawed assumptions that result in an overstatement of his calculation of opportunity cost and, ultimately, the royalty.
18. First, Dr. Willig effectively identifies a survey respondent as a subscriber or non- subscriber to a given service depending on whether the respondent reported listening to the
service in the last 30 days.26 Any respondent who reported not listening to a subscription service in the last 30 days is assumed by Dr. Willig not to be a subscriber to that service. However, not all subscribers of a service use the service within any given 30-day period. For example, in the
24 SOUNDEX_W5_000045448 (Research Snapshot Alexa, Streaming & Social, May 2018), at SOUNDEX_W5_000045455. 25 SOUNDEX_W5_000186861 at SOUNDEX_W5_000186861 and SOUNDEX_W5_000186883. 26 Willig Report, Appendix E, p. E-1.
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third quarter of 2018, Spotify had 5 million inactive premium subscribers, which is 6% of total
premium subscribers and up from 1% earlier the same year.27 As explained in the Hauser
Rebuttal Report, a respondent may not have used his or her subscription service in the past 30
days because the respondent instead listened to the option that the SoundExchange survey
instructed was no longer available, or for some other reason.28 Moreover, as discussed in the
Hauser Rebuttal Report, many respondents may not accurately recall the services they used in
the past 30 days.29 Thus, some of the survey respondents Dr. Willig has classified as non-
subscribers may in fact be subscribers. In that case, Dr. Willig overstates the opportunity cost
associated with such survey respondents, because he assumes they would pay a subscription fee
in the absence of non-subscription non-interactive services when in fact they had already paid the subscription fee.
19. Second, the SoundExchange survey asks each respondent to indicate which music- listening options he or she would use in the absence of non-subscription non-interactive services.30 Some of the survey respondents indicated they would use more than one subscription
service.31 Dr. Willig assumes that each such respondent would, in fact, subscribe to multiple
services, paying multiple subscription fees, rather than subscribing to just one.32 For example,
27 Inactive users are defined as users who did not listen to any music on Spotify in the last thirty days of a given quarter. See “1 Potentially Troubling Trend for Spotify,” The Motley Fool, November 6, 2018, https://www fool.com/investing/2018/11/06/1-potentially-troubling-trend-for-spotify.aspx. Performing the same calculation from this article using data from Spotify’s SEC filings from October 2019, the number of inactive users has increased to around 6 million. See Spotify Form 6-K, October 2019. 28 Hauser Rebuttal Report, p. 10-14. 29 Hauser Rebuttal Report, pp. 11-13. 30 Zauberman Report, pp. 16-17. In the case of the “no paid radio streaming” hypothetical, each respondent was asked to indicate which music-listening options he or she would use in the absence of subscription non- interactive services. 31 SOUNDEX_W5_000044743 (Zauberman Survey Data) 32 Willig Report, Appendix E.
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Table 2: SoundExchange Actual vs. Hypothetical Music Listening Last 30 Days Hypothetical Difference Paid On-Demand 34.0% 40.2% 6.3% Paid Noninteractive 23.0% 35.1% 12.1% Sirius XM 28.8% 32.6% 3.7% CDs, Vinyl Records, or MP3 Files 56.9% 68.4% 11.4%
Ad-Supported Noninteractive 100.0% n/a n/a Ad-Supported On-Demand 73.1% 84.6% 11.5% AM/FM Radio on a receiver 84.7% 89.0% 4.2%
The largest gain in respondents in the hypothetical scenario is in paid non-interactive services, with ad-supported on-demand services and CDs/Vinyl/MP3 approximately tied for second place.36 In total, the sum of gains across the paid alternatives is more than twice the sum of gains across the free alternatives. If the survey is to be believed, respondents are quite willing to incur additional expenses in the hypothetical scenario even though free services are available. There is further evidence of a large stated hypothetical willingness to make a payment. Of respondents with no listening to subscription services in the last 30 days, 14% stated they would add a subscription service category (i.e., paid on-demand, paid non-interactive, or Sirius XM) and, of these, a third (5%) stated they would add two or all three subscription service categories in response to the absence of free non-interactive services. Of respondents who reported to listening to two of the subscription service categories in the last 30 days, 19% stated that they would add the third category in response to the absence of free non-interactive services. While some greater willingness to make a payment might be expected given the (hypothetical)
36 Another anomaly in the SoundExchange survey results is that, as shown in Table 2, 59.9% of respondents indicated listening to CDs, Vinyl Records, or MP3 Files in the last 30 days. Other evidence suggests this figure is quite high. A study prepared for the RIAA found that [ ]. SOUNDEX_W5_000187914 at SOUNDEX_W5_000187919.
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elimination of the free non-interactive alternative (although this would be tempered by the
continued availability of free on-demand alternatives), the question is whether the observed
hypothetical stated willingness to make a payment is economically plausible. I find the
respondents’ stated willingness to make payments implausible, particularly given other evidence
that users of free services have low willingness to pay and given that the stated diversion to paid
alternatives outstrips diversion to free alternatives. The academic literature recognizes that the
hypothetical nature of the “payment” in this type of survey can lead respondents to overstate their true willingness to pay, as they do not actually have to make the payment that they say they
would make.37
21. Another notable result of the SoundExchange survey is that, of the subset of respondents
who were asked to allocate their time among the options they had picked, 37% of them said they
would spend zero additional time on at least one of the choices they had previously indicated.38
Indeed, of the 376 respondents who said they would turn to at least one paid alternative and were subsequently asked to allocate their time, 101 zeroed out one of the paid alternatives they had chosen previously. This demonstrates that when pressed to further think about their time, many of the respondents narrowed their choices and often eliminated a paid alternative. However, because this question was only asked to a subset of the respondents -- namely those who chose more than one option, and among those at least one free on-demand service39 -- it is not possible to observe the time allocation of anyone that picked more than one subscription service, but not a
free service. It is likely that some of the respondents who were not asked about their time
37 See, e.g., F. Voelckner, “An Empirical Comparison of Methods for Measuring Consumers’ Willingness to Pay,” Marketing Letters, 2006; J. Murphy, et al., “A Meta-analysis of Hypothetical Bias in Stated Preference Valuation,” Environmental and Resource Economics, 2005. 38 Calculated using SOUNDEX_W5_000044743 (Zauberman Survey Data). 39 Zauberman Report, p. 19-22.
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allocation and who said they would “switch” to more than one subscription service would have
allocated zero time to at least one of the subscriptions if also pressed. To the extent this is the case, Dr. Willig’s opportunity cost is again overstated.
22. Third, a sizable percentage of the SoundExchange survey respondents said that they would listen to CDs/Vinyl/Digital Downloads in the absence of non-subscription non-interactive services.40 However, the survey did not ask respondents to specify whether the
CDs/Vinyl/Digital Downloads to which they would listen would be from their existing collection
or new purchases; instead, this listening option was described as “Listen to CDs, vinyl records,
or MP3 files that you currently own or would purchase.”41 The distinction is important because
a simulcast user who states he or she would listen more to their existing CD/Vinyl/Digital
Download collection in the absence of simulcast would not represent an opportunity cost to
SoundExchange. Dr. Willig, however, assumes that each respondent who said that he or she
would switch to CDs/Vinyl/Digital Downloads and who said that he or she had not listened to
CDs in the last 30 days would purchase new CDs/Vinyl/Digital Downloads rather than listen to
an existing collection.42 To the extent any of these respondents would listen to their existing
collections, rather than purchase new CDs/Vinyl/Digital Downloads, Dr. Willig’s opportunity
cost calculation is again overstated.
40 SOUNDEX_W5_000044743 (Zauberman Survey Data). 41 Zauberman Report, Appendix D, p. 60 (emphasis added). 42 Willig Report, Appendix E, p. E-6.
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C. The “Share of Ear” Survey Also Provides an Unreliable Basis for Dr. Willig’s Opportunity Cost Calculations
23. As an alternative to the SoundExchange survey, Dr. Willig uses Edison Research’s Q2
2019 “Share of Ear” survey.43 This survey asks respondents to track time spent listening to
music in various channels and then calculates percentage of listening time spent on each channel.
Dr. Willig assumes that the diversion ratio from non-subscription non-interactive services to an
alternative is equal to the listening share of that alternative divided by one minus the listening
share of non-subscription non-interactive services.44
24. Dr. Willig’s use of the “share of ear” survey is flawed for a number of reasons. First, Dr.
Willig’s Shapley Value framework using the “share of ear” survey again combines simulcast
with other ad-supported non-interactive services rather than analyzing simulcast separately.45
25. Second, because the “share of ear” survey attributes no share to non-music alternatives,
Dr. Willig’s approach does not account for such alternatives at all. That is, in his approach based on the “share of ear” survey, Dr. Willig assumes zero diversion to non-music alternatives.46
Given that both the SoundExchange and Hauser surveys find an appreciable percentage of respondents saying they would turn to non-music alternatives, Dr. Willig has no justification for making this assumption.47 Moreover, this assumption necessarily results in an overstatement of
43 Willig Report, p. 32, Appendix F. Edison Research, “Share of Ear,” Q2 2019 (SoundExchange Exhibit 44). 44 Willig Report, Appendix F, pp. F-6 to F-11. 45 Willig Report, pp. 32-34. In fact, Dr. Willig’s assumption discussed further below that diversion ratios are proportional to shares means that Dr. Willig assumes that the diversion ratio from simulcast to, say, subscription interactive services is equal to the diversion ratio from custom radio to subscription interactive services. This assumption makes no economic sense given the economic evidence that degree of interactivity affects substitution, which implies that the diversion ratio from custom radio (greater interactivity) to subscription interactive services should be greater than the diversion ratio from simulcast (lesser interactivity) to subscription interactive services (see, e.g., SOUNDEX_W5_000186861 at SOUNDEX_W5_000186880). 46 Willig Report, pp. 21-23, 32-33, Appendix F, pp. F-8 to F-11. 47 Of the SoundExchange survey respondents, 39% selected non-music alternatives as one of the alternatives they would use in the hypothetical scenario. Zauberman Survey Data. Of the Hauser survey respondents, 19% 17 NAB Written Rebuttal Statement Dkt. No. 19-CRB-0005-WR (2021-25)
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the opportunity cost because non-music alternatives represent no opportunity cost to
SoundExchange. Recalculating Dr. Willig’s opportunity cost, assuming 19% diversion to non-
music alternatives, reduces it from [ ].
26. Third, Dr. Willig assumes that the “share of ear” associated with CDs is indicative of the percentage of non-subscription non-interactive plays that would be diverted to the purchase of
new CDs in the absence of the non-subscription non-interactive services.48 However, the CD-
listening that makes up the reported “share of ear” for CDs is based on owned CDs and does not
specify how recently these were purchased, meaning that both new and existing CDs would be
included.49 By Dr. Willig’s own logic that listener diversion is accurately represented by the various alternatives’ “share of ear,” he should have assumed that listeners would have diverted plays to new CDs only in proportion to new CD share of ear (rather than total CD share of ear,
which is by definition greater than new CD share of ear), or, put another way, that some of the
total diversion to CDs would have been to existing CDs, which do not represent an opportunity
cost to SoundExchange. By assuming that the entire diversion of plays to CDs represents
diversion to new CDs, Dr. Willig overstates the number of plays diverted to CDs that would
represent an opportunity cost to SoundExchange. Dr. Willig makes a similar incorrect
assumption regarding diversion of plays to the subscription services. He assumes that the
selected non-music alternatives as the alternative they would use in the hypothetical scenario. Hauser Report, Appendix R, items 16-19, 21-24. Note that, as discussed above, the SoundExchange survey respondents could choose multiple alternatives. A subset was asked how they would allocate time among the alternatives identified in the first step, and many respondents assigned zero time to one or more alternatives previously identified. If a respondent was asked how they would allocate their time between their chosen options, and they allocated zero time to the “Do something else” option, this respondent is not included in the percentage of people who chose to “Do something else.” 48 Willig Report, Appendix F. 49 Edison Research, “Share of Ear,” Q2 2019 (SoundExchange Exhibit 44); “‘Share of Ear’ Documents the Transition from Owned to Rented Music,” Edison Research, February 1, 2019, https://www.edisonresearch.com/share-of-ear-documents-the-transition-from-owned-to-rented-music/.
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entirety of the diversion of non-subscription non-interactive plays to a given subscription service would invoke the payment of a royalty to SoundExchange. However, based on the results of the
SoundExchange survey, a substantial fraction of users of non-subscription non-interactive services are already subscribers to other subscription services. Diversion of plays by these users to their existing subscription services would not invoke the payment of any additional royalty to
SoundExchange. Thus, by ignoring the fact that some non-subscription non-interactive users are already subscribed to subscription services, Dr. Willig again overstates the number of diverted plays that represent an opportunity cost to SoundExchange.
27. Fourth, economic literature undermines Dr. Willig’s assumption that shares provide reliable estimates of diversion ratios in this type of differentiated product market.50 For example, in a market with “premium” and “economy” segments, the premium products likely have higher diversion ratios with each other than they do with the economy products, regardless of what the market shares would suggest. In other words, users of a premium product are likely to view
50 Dr. Willig’s assumption that diversion ratios are proportional to shares imposes the “independence of irrelevant alternatives” (IIA) property, which underlies, for example, the “logit” model of demand. The IIA assumption places strong restrictions on substitution patterns between products (i.e., the own- and cross-price elasticities of demand and related diversion ratios). Because of IIA’s restrictiveness regarding substitution patterns, the literature warns about imposition of the IIA property and associated use of the logit model of demand in circumstances when the nature of substitution patterns is a central question of interest. See, e.g., D. McFadden, “Econometric Models of Probabilistic Choice,” in Structural Analysis of Discrete Data with Econometric Applications, 1981, pp. 222-223 (“…models satisfying [IIA] yield implausible conclusions when there are strong contrasts in the similarity of the alternatives”); S. Berry, “Estimating Discrete Choice Models of Product Differentiation,” RAND Journal of Economics, 1994, p. 250 (“[t]he logit model products unreasonable substitution patterns”); J. Hausman and G. Leonard, “Economic Analysis of Differentiated Products Mergers Using Real World Data,” George Mason Law Review, 1997, p. 322 (“…the [IIA] assumption…implicitly restricts the demand structure by constraining the pattern of demand substitution between products”); D. Brownstone and K. Train, “Forecasting New Product Penetration with Flexible Substitution Patterns,” Journal of Econometrics, 1999, p. 110 (“…identification of the correct substitution patterns is an empirical issue, and the IIA property…imposes a particular substitution pattern rather than allowing the data analysis to find and reflect whatever substitution pattern actually occurs”); A. Nevo, “Mergers with Differentiated Products: The Case of the Ready-to-Eat Cereal Industry,” RAND Journal of Economics, 2000, p. 402 (“the logit model greatly restricts the own- and cross-price elasiticities”); P. Davis and E. Garces, Quantitative Techniques for Competition and Antitrust Analysis, 2010, pp. 477-478 (“…the logit model imposes severe limitations on own- and cross-price elasticities…we recommend strongly against using [logit] models in situations where we must learn something about substitution patterns…”).
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services. Yet, this is inconsistent with the economic evidence that degree of interactivity affects
substitution, which implies that the diversion ratio from custom radio (greater interactivity) to subscription interactive services should be greater than the diversion ratio from simulcast (lesser interactivity) to subscription interactive services.55
29. The Hauser survey results provide support for the conclusion that listening shares provide poor estimates of diversion ratios from simulcast to other alternatives. Table 3 compares the
diversion ratios implied by the listening shares to the diversion ratios from the Hauser survey.
As with the SoundExchange survey, there are substantial differences between the two sets of
diversion ratios. Specifically, the “share of ear” survey (along with the assumption that diversion
ratios are proportional to shares) produces uniformly higher diversion ratios for royalty-bearing
alternatives than does the Hauser survey. This difference suggests that either (1) the “share of
ear” survey and assumption that diversion ratios are proportional to shares produces unreliable
diversion ratios, or (2) simulcast users have a different and lower opportunity cost to
SoundExchange than users of other non-subscription non-interactive services. With lower
diversion ratios, all else equal, Dr. Willig’s Shapley Value calculations would have yielded a
lower royalty for simulcast than, e.g., custom radio.
Table 3: Share of Ear and Hauser Diversion Ratios
Share of Ear Hauser
Subscription On Demand 1.5% SiriusXM 3.4% Ad-supported On Demand 10.3% CDs/Vinyl/Digital Downloads 1.9%
55 See, e.g., SOUNDEX_W5_000186861 at SOUNDEX_W5_000186880.
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D. Dr. Willig’s Use of the Shapley Value and Nash-in-Nash Frameworks Is Flawed
30. As inputs into the Shapley Value and Nash-in-Nash frameworks that he uses to calculate
his proposed royalty, Dr. Willig uses (i) the opportunity cost information based on the
SoundExchange survey and his calculation of royalty rates for alternatives to non-subscription
non-interactive services and (ii) financial information from Pandora.56 These frameworks are
flawed not only because they rely on the unreliable survey information and assumptions
addressed above, but also for additional reasons.
31. As noted above, the inputs for Dr. Willig’s Shapley Value and Nash-in-Nash frameworks
are not specific to simulcast, and Dr. Willig provides no justification for assuming that the values
of the inputs are accurate for simulcast. Of particular note is Dr. Willig’s use of Pandora’s
financial information as a stand-in for the financial situation of every non-subscription non-
interactive service.57 Given the substantial difference between Pandora and simulcast in terms of business model, there is no reason to believe that Pandora is representative of the simulcast services provided by, e.g., Mel Wheeler, Inc. Indeed, as discussed in my opening report, the economic evidence suggests that [ ].58 Thus, there is no
basis to conclude that the royalties that emerge from Dr. Willig’s Shapley Value and Nash-in-
Nash frameworks are appropriate for simulcast.
32. Moreover, in constructing his Shapley Value and Nash-in-Nash frameworks, Dr. Willig makes a number of simplifying assumptions. While it is common in economic modeling to make
simplifying assumptions, one must be careful lest the omission of an important factor renders the
56 Willig Report, pp. 16-26, 34-37, Appendices D, E, G. 57 Willig Report, Appendix D. 58 Leonard Report, pp. 27-29.
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model misleading as applied to a real-world situation. There are several respects in which
Dr. Willig’s frameworks make simplifying assumptions that may result in an overstatement in
the calculation of the royalty.
33. First, Dr. Willig assumes that the royalties for musical compositions are set exogenously
outside of his frameworks.59 Yet, for Pandora, historically the royalties for musical compositions have been closely and contractually linked to sound recording royalties.60 Thus, in the real
world, if sound recording royalties were increased by the amount that Dr. Willig proposes based
on his models, music composition royalties would be expected to increase as well. But, in that
event, Dr. Willig’s frameworks incorrectly model the music composition royalties as exogenous
and, moreover, assume a level of musical composition royalties that is too low. If Dr. Willig’s
frameworks were made more realistic to allow musical composition royalties to be endogenous
(for example, set to be positively related to sound recording royalties), the frameworks would
generate lower royalties than they do with the unrealistic assumption that musical composition royalties are exogenously determined.61
34. Second, and similarly, Dr. Willig’s frameworks implicitly assume that any royalty for
sound recordings would be assessed as a lump sum that would have no effect on service
providers’ decisions regarding pricing, use of music versus non-music content, and other
59 Willig Report, pp. 14-15, Appendix C. 60 PANWEBV_00005062, at PANWEBV_00005076; “Pandora Details Its Pay Raise to Publishers,” Billboard, February 12, 2016, https://www.billboard.com/articles/business/6874911/pandora-publisher-pay; “Pandora Is Now Paying Publishers 1/5th of the Money It Gives Labels,” Music Business Worldwide, February 17, 2016, https://www musicbusinessworldwide.com/pandora-is-paying-major-publishers-fifth/. 61 When the musical composition royalties are assumed to be a positive function of the sound recording royalties, an increase in the sound recording royalties decreases the surplus available to split among the labels and services because the musical composition copyright holders capture more of the surplus.
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characteristics of their services.62 In reality, however, [
] and thus represent a marginal cost to services that, under
economic principles, would be expected to affect service providers’ decisions regarding pricing
and product characteristics. Indeed, Dr. Willig even converts his calculated lump sum royalty to
a per-play royalty that he argues should be imposed in the future.63 If this per-play royalty were
imposed in the real world, however, it would affect services’ decision-making, and the services’
economic outcomes (revenue, plays, and profitability) would be different than the levels assumed
as inputs in Dr. Willig’s frameworks. That means the inputs to Dr. Willig’s frameworks that led
to his per-play royalty proposal are incorrect. The result is that the royalty Dr. Willig proposes
may give SoundExchange an excessive share of the surplus.64
35. Third, a flaw specific to Dr. Willig’s Nash-in-Nash framework is his assumption that each pair of negotiating parties would split the surplus 50/50. Dr. Willig seems to imply that a
50/50 split is a necessary implication of the Nash Bargaining Solution (“NBS”).65 However, a
50/50 split necessarily emerges from the NBS only if the negotiating parties are assumed to have
the same utility function. In general, if the parties have different utility functions (e.g., different
levels of risk-aversion), the split of the surplus will not be 50/50.66 Dr. Willig provides no
62 Willig Report, p. 16. A lump sum royalty would not affect a service’s marginal costs and thus would not affect decisions on the margin regarding pricing and product characteristics. However, a lump sum royalty may affect a service’s decision as to whether to participate in the market. If the lump sum royalty makes participation unprofitable, the service would decide not to participate. 63 Willig Report, pp. 27, 31-32. 64 Specifically, the surplus available to split among labels and services would be less than Dr. Willig assumes. This, in turn, means that the royalty Dr. Willig proposes (which assumes the incorrect higher level of surplus) gives too much of the correct level of surplus to the labels. 65 Willig Report, pp. 35-36. 66 For example, see M. Osborne and A. Rubinstein, A Course in Game Theory, 1994, p. 303 (“A main goal of Nash’s theory is to provide a relationship between the players’ attitudes towards risk and the outcome of the bargaining...We compare two bargaining problems that differ only in that one player’s preference relation in one 24 NAB Written Rebuttal Statement Dkt No 19-CRB-0005-WR (2021-25)
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justification for the assumption that labels and services all have the same utility function. Absent
such an assumption, Dr. Willig would have to determine the split between each pair of
negotiating parties. He has not shown how that could be done given available information.
36. Finally, there is a question as to whether the Shapley Value framework is appropriate given the task in this proceeding, which I understand to be modeling the outcome of a WBWS negotiation assuming effective competition. Shapley Values provide a specific split of surplus among contributing factors that possess certain properties. Shapely Values are not meant to mimic a WBWS outcome and, indeed, a WBWS outcome may well differ from the outcome implied by Shapley Values, depending on the institutional structure.67 This point is underscored
by the fact that Dr. Willig’s Nash-in-Nash framework gives a different answer than his Shapley
Value framework.68 In contrast to the Shapley Value framework, the Nash-in-Nash framework
is an attempt to model WBWS outcomes—but Dr. Willig’s Nash-in-Nash framework here
remains flawed for all the reasons described above.
V. MR. ORSZAG’S ROYALTY PROPOSAL IS FLAWED
A. Mr. Orszag’s Subscription Interactive Streaming Services Benchmark Is Not Appropriate for Non-Subscription Non-Interactive Streaming Services
37. Mr. Orszag’s proposed royalty rate for non-subscription non-interactive streaming services of $0.0025 per play is based on the effective royalty rates as a percentage of revenue paid by subscription interactive streaming services. Specifically, Mr. Orszag’s recommended
of the problems is more risk-averse than it is in the other; we verify that the outcome of the former problem is worse for the player than that of the latter.”). 67 See, e.g., F. Gul, “Bargaining Foundations of Shapley Value,” Econometrica, 1989. In an experiment described in C. Moellers, et al., “Communication in Vertical Markets: Experimental Evidence,” International Journal of Industrial Organization, 2017, the Shapley Value framework failed to predict “market” outcomes accurately. 68 Willig Report, p. 36.
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rate is equal to the effective royalty rate as a percentage of revenue paid by Spotify to the major
record labels and Merlin for its subscription interactive streaming service for the year ending
April 2019 of [ ], multiplied by the effective revenue per play paid for Pandora and
iHeart’s non-subscription non-interactive services for the year ending April 2019 of ].69
Mr. Orszag’s rationales for using subscription interactive streaming services as a benchmark for subscription and non-subscription non-interactive streaming services are: the subscription interactive benchmarks are market-based and were used in prior webcasting proceedings; the subscription interactive benchmarks include the same sellers (i.e., record companies) and similar buyers; and there has been a convergence between interactive services’ and non-interactive services’ functionality over time.70 Each of Mr. Orszag’s rationales is flawed.
38. First, the complementary oligopoly power of the major record labels in the interactive
market renders this market less than effectively competitive. This is the conclusion that was
reached by the Judges in Web IV, where the Judges determined that an effective competition
adjustment was necessary to account for major record labels’ complementary oligopoly power.71
Mr. Orszag incorrectly believes that such an effective competition adjustment is no longer necessary because the major record labels’ bargaining power is now offset by the interactive services’ supposed bargaining power resulting from their alleged must-have status vis-à-vis the major labels.72 As I discuss in Section V.C below, however, the complementary oligopoly power
of the major record labels is not offset by the supposed bargaining power of the subscription
interactive streaming services. Thus, even though the interactive streaming services benchmarks
69 Orszag Report, pp. 41-43. 70 Orszag Report, pp. 19-29. 71 Web IV Determination, 81 Fed. Reg. 26316, 26343-44 (CRB May 2, 2016). 72 Orszag Report, Section V.
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are market-based, they do not reflect effective competition and therefore still need to be adjusted
if they are to be used as benchmarks in this proceeding. Mr. Orszag did not perform an effective
competition adjustment, which inflates his recommended royalty rate for non-subscription non-
interactive streaming services. As discussed in my opening report, to ensure that the royalty
rates for non-subscription non-interactive services (including simulcast) reflected effective
competition, in Web IV, the Judges used as benchmarks royalties from actual license agreements
between labels and services that contained steering provisions.73 Steering is a means by which a
service can create competition among labels, mitigating the complementary oligopoly problem.
The steering discount applied in Web IV was 12%.74 Applying this discount to Mr. Orszag’s
$0.0025 per-play rate lowers his recommended rate for all webcasting (custom radio and
simulcast combined) to $0.0022.
39. Second, although the interactive services benchmarks used by Mr. Orszag include the
same sellers—i.e., labels—they do not include similar buyers. Mr. Orszag’s per-play rate is
based solely on the effective royalty rate as a percentage of revenue of that one buyer,
Spotify, paid to major record labels and Merlin for its subscription interactive streaming service.
As I explain in the following paragraphs, that service is a fundamentally different service from non-subscription non-interactive streaming services, especially simulcasts.
40. Third, and relatedly, Mr. Orszag’s assessment of the increased comparability between interactive and non-interactive streaming services is incorrect as a general matter, and has no application at all to simulcasts specifically. Mr. Orszag argues that there has been a convergence between interactive services’ and non-interactive services’ functionality over time, which makes
73 Web IV Determination, 81 Fed. Reg. 26316, 26365-69 (CRB May 2, 2016). 74 Id. at 26405.
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them comparable to each other. This alleged convergence stems primarily from the growing use
of playlists by subscribers of interactive streaming services.75 In other words, Mr. Orszag claims
that increased “lean-back listening” by subscribers of interactive streaming services has made
their user experience more similar to the user experience of a non-interactive streaming service.
This claim is flawed for several reasons.
41. Most importantly, the evidence of “convergence” that Mr. Orszag cites does not apply to
simulcast. For example, Mr. Orszag classifies various types of activities as “lean-back listening” and claims that “as of 2017, up to 68 percent of listening on Spotify is lean-back.”76 Mr. Orszag
further claims:
Apple’s and Spotify’s increasing focus on the lean-back listening experience illustrates the convergence between interactive and noninteractive services in terms of user behavior and the type of services they offer; in the noninteractive world, the stations are effectively playlists. The playlists on interactive services and the stations on noninteractive services are not necessarily identical, but they attempt to achieve the same goals, which is to provide listeners with a lean-back listening experience and sometimes music discovery options, which attract and retain users on the platform. A person unfamiliar with the services simply listening to the music programming would not necessarily know the difference between lean-back listening with interactive service-generated playlists and lean-back listening with noninteractive service stations.77
But while 68% of Spotify listening is lean-back—i.e., playlists—only 15% of monthly content
hours are from editorially curated playlists, which is the closest type of playlist to what one
would get listening to simulcast.78 The rest of the Spotify activities that Mr. Orszag classifies as
lean-back listening are algorithmically-curated playlists created by Spotify for each user (17%)
75 Orszag Report, pp. 65-67. 76 Orszag Report, pp. 23-24. 77 Orszag Report, p. 26. 78 Orszag Report, pp. 23-24.
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and a user’s own-generated playlists (36%).79 Neither of these types of playlists are available on
a simulcast. SoundExchange witnesses Aaron Harrison, UMG Recordings, Inc.’s Senior Vice
President, Business & Legal Affairs, Digital, and Reni Adadevoh, Warner’s Vice President of
Legal and Business Affairs, [
].80 Thus, there is, in fact, little to no evidence of overlap and thus convergence between interactive services and simulcast.81 With regard to custom radio, the addition of lean-back features to
interactive services is an effort to provide an additional functionality to a subset of interactive
users who may value such functionality. Many interactive users do not use the functionality (and
thus do not value it significantly). Moreover, even among the subset of interactive users that use
the functionality, its existence does not necessarily create “convergence.” Two products sharing
a feature does not necessarily make them substitutes. For example, collision avoidance features
are available on both a Honda Civic or a Mercedes E-series sedan, but these two car models are
hardly close substitutes.
42. Moreover, interactive services provide other playlist-related features that are valuable to
users but are not even possible on simulcast (and, indeed, are not permitted under the statutory
license for non-subscription non-interactive services). For example, on an interactive service a
user can view the entire playlist, including upcoming songs, and can skip songs and move
79 Orszag Report, pp. 23-24. 80 Harrison Dep., pp. 105, 118-119; Adadevoh Dep., pp. 116-117. 81 There is also relatively little overlap between ad-supported interactive services and custom radio given that custom radio users cannot listen to user-generated playlists. Mr. Orszag ignores the distinctions between the playlist categories.
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functionality demonstrates that interactive service users are subscribing to take advantage of on- demand functionality, exercising specific music choices as opposed to listening to pre- programmed simulcasts.
47. Simulcasts contain limited, pre-selected music content and provide the listener with no in-platform on-demand functionality. As long as such on-demand features have a significant value to users (as they currently do, as demonstrated, for example, by the higher subscription price for interactive than non-interactive services90 and established user behavior on these platforms), economically meaningful divergence exists between interactive services and simulcast.
48. SoundExchange expert Dr. Tucker highlights the value of on-demand features to users in her report, which is contrary to Mr. Orszag’s claims about convergence. Dr. Tucker discusses how on-demand services have gained popularity in recent years, and that “[i]ndustry analysts generally agree that paid subscriptions to services that offer interactive functionalities (such as
Spotify Premium) are the future of music.”91 If there is “convergence,” as Mr. Orszag claims, there would be no basis for Dr. Tucker to distinguish interactive services. In fact, the increasing demand for on-demand services demonstrates that they are significantly differentiated from services that do not offer on-demand functionality.
90 Pandora’s non-interactive subscription service, Pandora Plus, is priced monthly at $4.99, whereas its interactive subscription service, Pandora Premium, is priced monthly at $9.99. See “Upgrade to Pandora Plus or Premium,” Pandora Help, https://help.pandora.com/s/article/Upgrade-to-Pandora-Plus-or-Pandora-Premium- 1519949306612?language=en_US. iHeartRadio also prices its non-interactive subscription service, iHeartRadio Plus, and its interactive subscription service similarly at $4.99 and $9.99 per month respectively. See “How much is iHeartRadio All Access? What can I use to pay for it?” iHeartRadio, https://help.iheart.com/hc/en- us/articles/235721027-How-much-is-iHeartRadio-All-Access-What-can-I-use-to-pay-for-it- and “How much is iHeartRadio Plus? What can I use to pay for it?” iHeartRadio, https://help.iheart.com/hc/en- us/articles/235720747--How-much-is-iHeartRadio-Plus-What-can-I-use-to-pay-for-it-. 91 See Written Direct Testimony of Catherine Tucker, September 23, 2019 (“Tucker Report”), pp. 7-8.
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49. While Mr. Orszag has failed to demonstrate convergence of interactive services with
custom radio, he has not even addressed convergence of interactive services with simulcast. In
fact, interactive services have not converged toward simulcast, and simulcast has not converged toward interactive services, both because it is not possible given the nature of simulcast and because it is not allowed under the statutory license. Convergence of functionality would require moving outside of the statutory license and, therefore, is not relevant for determining the rate
within the statutory license. Accordingly, Mr. Orszag’s justification for using subscription
interactive services as a benchmark for simulcast is not valid.
50. Fourth, Mr. Orszag ignores non-interactive benchmarks that are more comparable than
his interactive benchmarks. As discussed extensively in my opening report, iHeart’s direct deals
with the renewal indies are the most relevant benchmarks for establishing the statutory rate for
non-subscription non-interactive streaming services including custom radio and simulcast.
These deals represent the best benchmarks for several reasons, including that they are market
transactions consistent with Section 114’s WBWS standard and (i) cover the licensing of rights
for the public performance of sound recordings; (ii) cover custom radio and simulcast services;
and (iii) include the same sellers (i.e., record companies) and same buyers (i.e., non-subscription
non-interactive streaming services) that would be involved in the statutory license. Moreover, by limiting my analysis to iHeart’s agreements with the renewal indies and calculating iHeart’s effective per-play royalty rates paid to these renewal indies during the pre-renewal period, I have focused on rates that must have been acceptable to both parties because both parties agreed to renew the direct deal at the same contractual rate with knowledge of the actual per-play rate.92
Further, the rates in these agreements are relatively free of complementary oligopoly power due
92 Leonard Report, pp. 31-37.
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to the fact that the renewal indies likely have less complementary oligopoly power than the major record labels. Finally, any argument that these non-interactive benchmarks are in the shadow of regulation ignores the fact that when the renewal indies agreed to the lower effective rates than the statutory rate those rates were freely negotiated. The renewal indies must have understood that iHeart could and perhaps would steer toward the labels’ recordings or that licensing iHeart offers other (e.g., promotional) benefits.93 Indeed, I have reviewed evidence
produced in discovery that [
].94
51. Finally, Mr. Orszag also ignores ad-supported interactive services as a potential
benchmark. Such services share all of the characteristics of subscription interactive services that
Mr. Orszag pointed to as support for their use as benchmarks, plus they are also ad-supported,
which makes them more comparable to non-subscription non-interactive services. Spotify’s ad-
supported interactive service had a per-play royalty of [ ] and a percentage-of-revenue
royalty of [ ] from January through April of 2019.95 Both of these figures are well below the respective figures ($0.0025 per play and [ ] of revenue) that Mr. Orszag derives from his subscription interactive benchmark. I note that, if the Spotify ad-supported interactive
service rate were to be used as a benchmark for non-subscription non-interactive services, adjustments would need to be made to account for effective competition and lack of interactivity.
93 Leonard Report, pp. 34-35. 94 See, e.g., NAB00003944; NAB00003948; NAB00003969; NAB00004024. 95 Calculated using Orszag data.
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have no willingness to pay.”98 However, Mr. Orszag argues that users of non-subscription non- interactive services do pay “with their time spent listening to advertisements,”99 and, therefore,
“a benchmark analysis that uses subscription interactive services is appropriate if the interactivity
adjustment is calculated using the revenue of noninteractive ad-supported services (thus
reflecting their particular willingness to pay) rather than the revenue of noninteractive
subscription services.”100 Mr. Orszag concludes that his “approach to this analysis appears to
have been tacitly endorsed by the Judges in Web IV, who suggested that any attempt to apply
ratio equivalency to the ad-supported market would have to consider the revenue earned by the
services in that market.”101 He also concludes that the subscription interactive benchmark is now
more applicable to the non-subscription non-interactive market because “consumers increasingly
view subscription interactive services as a viable (and sometimes preferred) alternative to an ad-
supported noninteractive service.”102 Mr. Orszag’s interactivity adjustment as it pertains to non-
subscription non-interactive streaming services, and in particular simulcast, is flawed for several
reasons.
54. First, Mr. Orszag misses an important distinction between subscription and ad-supported
services that undermines his argument regarding the applicability of ratio equivalency, namely
that the relationship between interactivity and revenue generation differs between the two types
of services. Subscription services generate revenues through subscription fees paid by users. To
the extent some users value interactivity, a subscription service may be able to charge a higher
98 Orszag Report, p. 38. 99 Orszag Report, pp. 38-39. 100 Orszag Report, p. 39. 101 Orszag Report, p. 39. 102 Orszag Report, p. 41.
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price for an interactive service than a non-interactive service. An ad-supported service, in
contrast, generates revenue through placing advertisements. Advertisers have no reason to prefer
advertising on a service with greater interactivity. In particular, they would not be willing to pay
more per impression for an ad on an interactive service than a non-interactive service (unless an
interactive service attracts more valuable impressions than a non-interactive service, a
proposition for which I have seen no evidence). In any event, the relationship between revenue
generation and interactivity is substantially different for ad-supported than for subscription
services. Moreover, there is no reason to think that the elasticities of demand of the buyers for
the respective types of services (advertisers for ad-supported and users for subscription) are the
same or that the cost structures are the same (e.g., ad-supported services may have costs and
investments associated with an advertising platform). These key economic differences cause Mr.
Orszag’s rationale for ratio equivalency between subscription and ad-supported services to fail.
Relatedly, Mr. Orszag overstates the case on user WTP. While it is true that users of ad-
supported services “pay” with the time spent with ads, they had the choice to pay for a
subscription service and avoid ads. Thus, by revealed preference, their WTP to avoid ads (and
by implication their WTP for more music in place of ads) is less than that of subscribers to paid
services (moreover, as discussed above, the ad-supported service receives revenue from the
advertiser, not based on the user’s time). This distinction is the one the Judges appear to have
been making,103 and it is correct.
55. Second, Mr. Orszag’s application of ratio equivalency as it relates to simulcast is completely unsupported. In fact, he treats simulcast the same as all other non-subscription non- interactive streaming services without providing any support for such an assumption. For
103 Web IV Determination, 81 Fed. Reg. 26316, 23650, n. 110 (CRB May 2, 2016).
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example, Mr. Orszag’s application of ratio equivalency to non-subscription non-interactive
streaming services uses the effective revenue per play for Pandora and iHeart for their ad-
supported custom radio services for the year ending April 2019 of ].104 Thus,
Mr. Orszag’s analysis relies exclusively on the effective revenue per play for custom radio and
assumes with no support that simulcast should be treated the same as custom radio. As
previously discussed, simulcast differs in economically important ways from custom radio and,
therefore, Mr. Orszag’s assumption is unsupported. A more appropriate (but still incorrect)
application of ratio equivalency pertaining to simulcast would be to calculate the effective
revenue per play for simulcasters. Mr. Orszag has not done this. As discussed in my opening report, the revenue per play for many simulcasters is likely low due to difficulties in generating
revenues on the simulcast. Even using the simulcaster revenue per play would be incorrect,
however. As discussed in my opening report, many simulcasts, unlike interactive services or
custom radio, contain significant non-music content, and thus some of the simulcast revenue
should be attributed to this content rather than music.105 Dividing revenue by music plays
without any adjustment for non-music content would fail to account for the value of the non-
music content.
56. Third, Mr. Orszag wrongly states that there is no connection in the marketplace between
percentage-of-revenue rates and the degree of interactivity offered. Mr. Orszag claims: “We do
104 Revenue per play for Pandora is ]
enue per play. He does not explain how his proposal makes economic sense given this context. Any claim that iHeart and Pandora are perfect substitutes for users is unsupported. 105 Leonard Report, pp. 19-24. Additionally, Mr. Orszag ignores that Mr. Harrison testified that [ ]. Harrison Dep., pp. 138-139; Written Direct Testimony of Aaron Harrison, September 22, 2019 (“Harrison Report”), pp. 24-25. However, simulcast is not a close substitute for interactive services.
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not see in the marketplace [
.]”106 This statement is incorrect. As previously discussed, marketplace evidence provided by music copyright licensing agreements have specified different percentage- of-revenue royalty rates for simulcast and custom radio, which have different degrees of interactivity. This evidence includes iHeart’s direct deals with independent record labels and the recent PRO licenses (and offered licenses) for rights to publicly perform musical compositions.
Specifically, iHeart’s direct deals with several renewal indies specify [
].107
57. Finally, Mr. Orszag’s conclusion that the subscription interactive benchmark is now more applicable to the non-subscription non-interactive market because “consumers increasingly view subscription interactive services as a viable (and sometimes preferred) alternative to an ad- supported noninteractive service” is unsupported, particularly with respect to simulcast, for the reasons discussed above. Mr. Orszag also claims that the SoundExchange survey finds a cross elasticity between non-interactive ad-supported services and interactive services, with 14% of users of non-interactive ad-supported services (who did not use interactive subscription services) stating that they would start listening to interactive subscription services if the ad-supported services were not available.108 Cross (price) elasticity is not well-defined when the price charged
for the product is zero. However, even so, Mr. Orszag ignores the fact that several other
106 Orszag Report, p. 33. 107 See Leonard Report, pp. 31-36, which specifies these royalty terms for iHeart’s direct deal with Big Machine, a representative agreement for iHeart’s agreements with renewal indies. 108 Orszag Report, pp. 40-41.
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services, such as ad-supported interactive services and CDs/Vinyl/Digital Downloads, are found
by the SoundExchange survey to have higher diversion ratios than subscription interactive
services109, implying they are closer substitutes for ad-supported non-interactive services than interactive services. A diversion ratio of 14% is not particularly large in any event. Moreover, as discussed above, the SoundExchange survey does not address simulcast users and likely biases responses in favor of subscription services. As seen in Table 1 above, when the Hauser
survey results are used, the diversion ratio from simulcast to subscription interactive services is
only 1.5% and lower than the diversion ratios to other alternatives.
C. Mr. Orszag’s Claim That the Complementary Oligopoly Problem No Longer Exists Is Incorrect
58. Mr. Orszag argues that the royalty rates from subscription interactive services need not be adjusted to account for any complementary oligopoly power of the major labels before using these rates as benchmarks for non-subscription non-interactive services.110 Mr. Orszag’s
argument is incorrect.
1. The Major Labels Still Have Complementary Oligopoly Power
59. As an initial point, Mr. Orszag does not even attempt to demonstrate that the
complementary oligopoly power of the majors with respect to the interactive services has
diminished. Rather, he admits that it “likely remains the case that the Majors are ‘must-haves’
for the interactive services, at least in the long run.”111 That is consistent with the testimony of
109 Willig Report, p. F-9. 110 Orszag Report, pp. 75-76. 111 Orszag Report, p. 45.
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64. Warner and Universal personnel testified that [
]. For example, Reni Adadevoh testified that Warner wants to ensure
] and that [
]125 Ms. Adadevoh furthered testified that [
].126 Similarly, Aaron Harrison testified that [
].127 Mr. Harrison testified that if
.]128 He further testified that [
.]”129 He explained that these provisions “[
.]”130
125 Adadevoh Dep., pp. 31-34. 126 Adadevoh Dep., p. 54. 127 Harrison Dep., p. 59. 128 Harrison Dep., pp. 63-64. 129 Harrison Dep., pp. 168-169, 188. 130 Harrison Dep., pp. 169-170.
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conditions must be conducted before a conclusion of market power is reached. [
].144 The remaining market share is held by other services, such as Google and Amazon. Thus, using market share as a screen would suggest the inquiry should end without further analysis, with the conclusion that Spotify and Apple have no market power.
71. Nevertheless, looking more deeply into the industry’s economic conditions confirms the conclusion of no market power. The conditions under which a firm may have market power are that its rivals face barriers to expansion and there are barriers to entry by new rivals. Otherwise, an attempt by the firm to increase unilaterally its price to buyers (or decrease unilaterally its price to input suppliers) will be met with switching by buyers (or input suppliers) to its competitors, which will have no trouble accommodating the increased demand given no substantial barriers to expansion, thereby defeating the attempted price increase. HHIs and market shares are not indicative of a firm’s market power when there are no substantial barriers to expansion and entry.145 As discussed below, these conditions hold for interactive services. Thus, Mr. Orszag’s
144 According to the Department of Justice, “[a]lthough the courts ‘have not yet identified a precise level at which monopoly power will be inferred’, they have demanded a dominant market share…A high share indicates that it is appropriate to examine other relevant factors. In this regard, if a firm has maintained a market share in excess of two-thirds for a significant period and market conditions (for example, barriers to entry) are such that the firm’s market share is unlikely to be eroded in the near future, the Department believes that such evidence ordinarily should establish a rebuttable presumption that the firm possesses monopoly power…In many decades of section 2 enforcement, we are aware of no court that has found monopoly power when defendant’s share was less than fifty percent, suggesting instances of monopoly power below such a share, even if theoretically possible, are exceedingly rare in practice.” (emphasis added). See “Competition and Monopoly: Single-Firm Conduct under Section 2 of the Sherman Act : Chapter 2,” DOJ, https://www.justice.gov/atr/competition-and- monopoly-single-firm-conduct-under-section-2-sherman-act-chapter-2. See also D. Carlton and J. Perloff, Modern Industrial Organization, 4th Edition, 2005, p. 644: “There is no agreement as to exactly what share (or change in share) is ‘high,’ but many economists regard a share in the range of 30 to 50 percent as too low to indicate significant market power in an industry with a competitive fringe comprising the remainder of the market.” 145 D. Carlton and J. Perloff, Modern Industrial Organization, 4th Edition, 2005, p. 644: “Market shares are imperfect indicators of market power… For example, if entry is easy, then the industry pricing is severely constrained regardless of whether an existing firm has a large market share.”
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HHI and market share calculations are economically meaningless and, moreover, the interactive
services do not have increased market power/bargaining power in their negotiations with the
major labels.
72. It is undisputed that Spotify and Apple Music compete for users. Spotify points out in
public filings with the U.S. Securities and Exchange Commission that its “closest competitor” is
Apple Music.146 As articulated in Spotify’s 2018 filing, it faces “increasing competition for
Users from a growing variety of businesses, including other subscription music services around
the world, many of which offer services that seek to emulate our Service.”147 Interactive, on-
demand services emulate and enhance the same user-valued features to ensure user retention.148
For Spotify, user retention (i.e., competition) depends in large part on its “ability to continue to offer leading technologies and products, compelling content, superior functionality, and an engaging User experience.”149 Without these offerings, users can easily switch to Spotify’s
closest competitor, Apple Music, or any other on-demand streaming service. Third-party apps
such as Soundiiz further facilitate switching by enabling users to transfer personal playlists
between streaming services, another contributing factor to these services’ substitutability.150
73. From the point of view of users, interactive services are substitutable, and therefore, each
interactive service must continue to be competitive to retain its users. While the interactive
146 SOUNDEX_W5_000033096, at SOUNDEX_W5_000033103. 147 SOUNDEX_W5_000033096, at SOUNDEX_W5_000033131 (emphasis added). 148 SOUNDEX_W5_000033096, at SOUNDEX_W5_000033131. “Why Do We Still Pay Only $10 a Month for Music?,” Rolling Stone, December 11, 2019, https://www-rollingstone- com.cdn.ampproject.org/c/s/www.rollingstone.com/music/music-news/music-streaming-10-month-fee- 924809/amp/. 149 SOUNDEX_W5_000033096, at SOUNDEX_W5_000033117; SOUNDEX_W5_000026604, at SOUNDEX_W5_000026613. 150 “How to transfer playlists from Spotify to Apple Music,” AppleInsider, August 18, 2019, https://appleinsider.com/articles/19/08/18/how-to-transfer-playlists-from-spotify-to-apple-music.
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discounts from this base price have been offered through, e.g., family plans.162 If anything, competition among interactive services has grown more intense.
76. The effects of this downstream competition flow back upstream, weakening the services’ bargaining positions in licensing negotiations with the labels. The downstream competition for users makes it crucial for an interactive service to be able to offer the core functionality of broad access to music. This need, and the inability of services to steer, means that the services have little leverage in negotiations with the major labels. From the labels’ perspective, because the services are substitutable from the point of view of users, they are also substitutable from the point of view of labels seeking to reach those users (and, of course, the labels have other channels for reaching users as well). A service could have market power over a label only to the extent that it was a conduit between the label and users for which there was no close substitute.
However, the services are substitutes for each other. Consistent with these points, none of the major interactive services has ever attempted to go without one of the major labels.
77. Mr. Orszag claims that a label would be hurt more than a service by a bargaining impasse between them. This claim is unsupported. Following a significant decrease in its library of songs, a subscription interactive service likely would have to give immediate discounts on subscription fees to disgruntled users who were not getting what they paid for, would suffer subscriber losses given the ease of switching to other services, and would sustain lasting harm to its reputation. Mr. Orszag points to pre-payment of subscriber fees, but he fails to show that the extent of pre-payment is significant, either in terms of users who do it or length of time covered.
In any event, a service would have to refund a significant portion of the pre-payments to avoid
162 See, e.g., “Best Music Streaming Services,” Consumer Reports, September 18, 2019, https://www.consumerreports.org/streaming-media/best-music-streaming-service-for-you/.
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harm to reputation that would otherwise occur by providing less than was promised. The label,
in contrast, would recapture a portion of the royalties via other channels to which users turned to
hear the label’s music. Moreover, a label would have a greater ability to wait out the impasse, given that it would continue to receive royalties from other sources, whereas the service’s entire subscription revenues would potentially be at risk given that it was not able to meet the primary driver of demand for an interactive service.
78. A further important factor is that the services face no substantial barriers to expansion.
Thus, any service could easily expand to accommodate users switching from other services.
Again, Apple and Amazon have shown how easy expansion is. Apple has participated in the
U.S. interactive subscription service segment for less than five years but expanded quickly and has overtaken Spotify in paid U.S. subscribers.163 There are also no significant barriers to entry.
In fact, potential entrants may face lower entry barriers since Congress’s adoption of the Music
Modernization Act (“MMA”). Starting in January 2021—the start of the rate term being decided here—the MMA will establish a new blanket license for the musical composition rights that are necessary to launch an interactive streaming service.164 As the then-CEO of the Digital Media
Association testified to Congress, “[b]y reducing uncertainty and increasing efficiency, the
MMA will result in greater consumer choice in the on-demand music streaming space, as new
entrants will be able to launch a service with lower barriers to entry.”165 Entry by a new service faces no significant barriers. This is particularly the case for a platform with economies of scope, as in the cases of Apple, Google, and Amazon. Since 2015, several new interactive
163 “Apple Music Overtakes Spotify in Paid U.S. Subscribers,” The Wall Street Journal, April 5, 2019, https://www.wsj.com/articles/apple-music-overtakes-spotify-in-u-s-subscribers-11554475924. 164 Public Law 115-264: Music Modernization Act, 132 Stat. 3676, October 11, 2018, Title I. 165 Statement of Christopher Harrison (Chief Executive Officer Digital Media Association), at the Hearing on “Protecting and Promoting Music Creation for the 21st Century,” May 15, 2018.
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services have entered in the US, including Apple Music (2015), iHeartRadio and iHeartRadio All
Access (2016), Primephonic (2017), Pandora Premium (2017), YouTube Music (2018), and
Qobuz (2019).166 Furthermore, the fact that industry revenue has been growing makes entry more attractive. Even the major labels have acquired or launched interactive streaming services to enter the market – e.g., Sony has launched its own Hi-Res interactive service in Japan.167
79. Furthermore, similar to other internet industries, interactive services participate in a segment that is dynamic and subject to rapid change, as demonstrated by the entry and subsequent growth of Apple and Amazon. Even firms with leading shares can lose that share quickly to existing or new competitors. For example, SoundCloud, despite being one of the top five interactive services as of 2018, struggled to maintain its position as indicated by its mass layoffs and rapid decline in its market valuation in 2017 due to intense competition from other services that blunted its growth.168
166 “Introducing Apple Music — All The Ways You Love Music. All in One Place,” Apple, June 8, 2015, https://www.apple.com/newsroom/2015/06/08Introducing-Apple-Music-All-The-Ways-You-Love-Music-All-in- One-Place-/ ; “iHeartMedia Launches First Ever -- and Only – Interactive on Demand Radio Services, ‘iHeartRadio Plus’ & ‘iHeartRadio All Access,’” BusinessWire, December 1, 2016, https://www.businesswire.com/news/home/20161201005685/en/iHeartMedia-Launches----%E2%80%93- Interactive-Demand-Radio/; “Primephonic launches hi-res classical-music streaming service,” Musically, June 14, 2017, https://musically.com/2017/06/14/primephonic-classical-music-streaming/; “Pandora’s on-demand music service finally arrives,” TechCrunch, March 13, 2017, https://techcrunch.com/2017/03/13/pandoras-on- demand-music-service-finally-arrives/; “YouTube Music and YouTube Premium Officially Launch in US, Canada, UK, and Other Countries,” The Verge, June 18, 2018, https://www.theverge.com/2018/6/18/17475122/youtube-music-premium-launch-us-canada-uk; “New high-res music streaming service Qobuz launches in US, takes aim at Spotify, Pandora,” USA Today, February 14, 2019, https://www.usatoday.com/story/tech/news/2019/02/14/spotify-pandora-have-new-competitor-music-streaming- service-qobuz/2860467002/. 167 “Why Has Sony Music Just Launched A Streaming Service (And Spotify Rival) In Japan?” Music Business Worldwide, December 11, 2018, https://www.musicbusinessworldwide.com/why-has-sony-just-launched-a- music-streaming-service-and-spotify-rival-in-japan/. 168 “Most popular music streaming services in the United States as of March 2018, by reach”, Statista, November 20, 2019, https://www.statista.com/statistics/798715/most-popular-us-music-streaming-services-ranked-by- reach/; “As Streaming Services Boom, SoundCloud Strives for Relevancy,” Wired, April 25, 2017, https://www.wired.com/2017/04/soundcloud-crossroads/; “SoundCloud, the ‘YouTube for audio’, cuts 173 jobs, closes San Francisco, London offices” TechCrunch, July 6, 2017, 58 NAB Written Rebuttal Statement Dkt. No. 19-CRB-0005-WR (2021-25)
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80. Mr. Orszag claims that [
], which he argues is a further sign that the interactive services are exercising increased bargaining power in licensing negotiations with the labels.169 (Mr. Orszag, however, ignores the
labels’ ] on interactive services, which as discussed
above is a sign of the labels’ continued greater relative bargaining power over the services.) Mr.
Orszag’s claim is flawed for the following reasons.
81. First, in making this argument, Mr. Orszag only considers subscription interactive
services as a benchmark, and ignores ad-supported interactive services which are a better
benchmark for non-subscription non-interactive services (although still substantially flawed for the reasons discussed throughout this report).170 In fact, [
]. The reason
that [
], by making efforts and investment to improve the value of its advertising platform to advertisers. Indeed, according to
Spotify’s Form 20-F of 2018, its ad-supported service generates revenue “from the sale of
display, audio, and video advertising delivered through advertising impressions.”172 In order to
increase its advertising revenue, Spotify has “introduced a number of new advertising products,
https://techcrunch.com/2017/07/06/soundcloud-the-youtube-for-audio-cuts-173-jobs-closes-san-francisco- london-offices/. 169 Orszag Report, pp. 73-75. 170 Orszag Report, pp. 35-37, 42-43. 171 Calculated using Orszag data. 172 SOUNDEX_W5_000026604, at SOUNDEX_W5_000026653.
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including sponsored playlists … and continue[d] to focus on analytics and measurement tools to
evaluate, demonstrate, and improve the effectiveness of advertising campaigns on [its]
platform.”173 These efforts have been made to “improve the efficiency and scalability of
[Spotify’s] advertising platform.”174 As Dr. Tucker acknowledges, Spotify launched its
“programmatic advertising” offering in 2015. She explains that such programmatic advertising
“enhances the attractiveness of digital music services to advertisers and enables digital music
services to compete better with large players in online advertising such as Google and
Facebook.”175 Dr. Tucker also acknowledges that Spotify launched its fast-growing self-service
advertising platform in 2017, “Ad Studio.” She notes that self-service advertising platforms such
as these “platforms can help digital music services increase their advertising inventory.”176 To the extent [ ] is the result of Spotify’s efforts and investments in building its advertising platform, it would be incorrect to interpret [
] as due to increased Spotify bargaining power. Instead, the
[
] provides no support for an increase in Spotify market power – rather, it reflects Spotify’s
173 SOUNDEX_W5_000026604, at SOUNDEX_W5_000026653. 174 SOUNDEX_W5_000026604, at SOUNDEX_W5_000026658. 175 Tucker Report, pp. 21-22. 176 Tucker Report, pp. 22-23. Spotify notes that the Ad Studio is their “fastest growing advertising channel” based on quarterly revenue and advertiser growth. See “Spotify’s Ad Studio is its fastest-growing advertising channel,” Music Ally, January 30, 2019, https://musically.com/2019/01/30/spotifys-ad-studio-is-its-fastest- growing-advertising-channel/. Additionally, Spotify’s Global Head of Advertising said, “The self-serve tool Ad Studio that allows smaller businesses to activate the Spotify free audience is a big growth area for us.” See “Spotify: Our Ads Business is a real Trigger for Growth,” Music Business Worldwide, October 31, 2018, https://www musicbusinessworldwide.com/spotify-our-ads-business-is-a-real-trigger-for-growth-moving- forward/.
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continuous efforts to improve its product quality and revenue generating ability in order to
maintain its market position in a highly competitive market.
82. Moreover, Mr. Orszag is mistaken as a matter of economics in his claim that a decrease
in the royalty as a percentage of revenue implies increasing market power on the part of the
interactive services. Mr. Orszag’s fundamental assumption—that the royalty should be the same
percentage of revenue, not only across services (which is wrong for the reasons discussed
above), but also across time, even as the downstream revenue per play fluctuates—is simply
wrong as a matter of economics. Indeed, if the interactive services are competitive in the
upstream licensing market and the downstream demand curve each service faces flattens (which
would occur, for example, with increased downstream competitiveness among them), the
percentage-of-revenue royalty would be expected to fall, [ ].
Thus, Mr. Orszag has no basis in economics to claim that the [
] is an indication that those services have
increased market power or bargaining power in upstream licensing negotiations.
83. This can be illustrated in a simplified, but instructive example. Suppose a monopolist
label of sound recordings sells a license to plays to a perfectly competitive intermediary industry
(i.e., services) at a royalty of r per unit. Each unit of the input is transformed by the
intermediaries into one unit of (homogeneous) output. Assume the intermediaries are perfectly
competitive and exhibit constant returns to scale with cost c per unit to transform the input.
Suppose downstream demand is Q(p), where p is the downstream unit price. Under these assumptions, downstream price equals to marginal cost177 (i.e., = + ) and the label chooses
177 In the competitive equilibrium, a competitive firm’s price equals marginal cost. See D. Carlton and J. Perloff, Modern Industrial Organization, 4th Edition, 2005, pp. 58-59.
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r to maximize its revenue that is equal to ∙ ( + ). The royalty as a percentage of revenue is
then = . Assuming first that c is fixed, if the demand curve flattens in a manner that causes the downstream price p to fall, the royalty per unit r will decline (since = + and c is fixed) and the percentage-of-revenue royalty will also necessarily decline, since the royalty percentage
decreases as r decreases. If c increases at the same time, the percentage-of-revenue royalty will decline even more.
84. As this simplified model indicates,178 the difference between the downstream and upstream prices represents the margin available to pay the service’s other costs. In a competitive setting, this margin just covers those other costs. Assuming those costs remain roughly constant over time,179 a decrease in the downstream price would, through normal competitive processes, lead to a decrease in the upstream royalty as well so that the service continues to just cover its other costs.180 Indeed, [
178 The result does not depend on the assumption of constant returns to scale for the intermediary (here, the service). For example, if the intermediaries each have capacity A, a fixed cost F, and marginal cost m, the cost parameter c can be reinterpreted as = + . 179 In fact, according to Spotify’s Form 20-F in 2018, its cost including R&D, sales and marketing, and general and administrative has been increasing between 2014 and 2018. See SOUNDEX_W5_000026604, at SOUNDEX_W5_000026653. An increase in cost would further reduce its percentage royalty. 180 This is related to the idea that the incidence of a tax is greater on the more inelastic party. See, e.g., H. Varian, Microeconomic Analysis, 2nd Ed., 1984, pp. 90-91. Here, the competitiveness of the interactive services (including the lack of barriers to entry) means that they are elastically supplied. In contrast, rights to sound recordings are relatively inelastically supplied. 181 “The Average Spotify Subscriber Pays $5.50 a Month — and Record Labels Hate It,” Rolling Stone, January 11, 2019, https://www rollingstone.com/music/music-features/the-average-spotify-subscriber-is-paying-5-50-a- month-and-record-labels-hate-it-776925/; “Spotify’s Average Revenue per User Is Shrinking,” Market Realist, May 13, 2019, https://articles2 marketrealist.com/2019/05/spotifys-average-revenue-per-user-is-shrinking/#; 62 NAB Written Rebuttal Statement Dkt. No. 19-CRB-0005-WR (2021-25)
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two largest noninteractive webcasting services, Pandora and iHeart Media,”185 and ignores simulcasters specifically. Furthermore, in Dr. Tucker’s analysis of iHeart’s financials she reviews iHeartMedia’s historical worldwide income statement and projected digital segment profit and loss statement, neither of which pertain specifically to iHeart’s revenues and profits associated with just its simulcast business (in other words, they contain revenues and costs associated with other non-interactive (custom radio) and on-demand services). As a result, Dr.
Tucker’s analysis and conclusions are not relevant for determining the appropriate per-play rate for simulcasting.
86. In the end, Dr. Tucker’s argument boils down to the claim that Pandora and iHeart could pay higher rates than they currently do (see Section III of the Tucker Report titled, “Commercial
Webcasters Are Well Positioned To Pay Higher Statutory Rates Than They Are Currently
Paying”).186 However, by itself, that says nothing about whether Pandora and iHeart should pay higher rates than they currently do, i.e., whether a WBWS negotiation assuming effective competition would lead to higher rates. Dr. Tucker has not analyzed how steering might allow
Pandora and iHeart (custom radio) to keep royalties relatively low in an effectively competitive environment. Nor has she analyzed whether the margin Pandora and iHeart have left after paying royalties at the current (or lower) level represents a competitive return on these services’ investments and other contributions. Additionally, Dr. Tucker completely ignores the financial position of the other party to the WBWS negotiation, the record labels, and whether they are well positioned to receive lower statutory rates than they are currently receiving. It is inappropriate for Dr. Tucker to only look at one party to the negotiation, commercial webcasters, but ignore
185 Tucker Report, p. 40. 186 Tucker Report, pp. 40-81.
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the other party to the negotiation, record labels, which from a financial perspective are profitable
and have enjoyed considerable financial success as a result of the increased popularity of
streaming services over the past several years.187
87. Finally, because Dr. Tucker failed to analyze any of the many simulcasters other than iHeart, she has no basis to conclude that any other simulcaster can “afford” to pay higher royalty rates.
VII. SOUNDEXCHANGE HAS FAILED TO DEMONSTRATE THAT THE MINIMUM FEE SHOULD BE INCREASED
88. Under the Web IV decision, commercial webcasters must pay a $500 minimum royalty
fee per channel or station, which is recoupable against royalties owed based on actual
usage. The cumulative minimum fees paid by a single webcaster are capped at $50,000, to
account for the fact that some webcasters offer large numbers of channels or stations.
89. I understand that SoundExchange seeks to double both the minimum fee from $500 to
$1000 and the cap on cumulative minimum fees from $50,000 to $100,000. SoundExchange’s
asserted justifications, as expressed by its COO Jonathan Bender in his written testimony, are
“inflation, increasing royalty rates, current costs of administering the statutory license and
generally increasing per-channel usage.”188
187 See, e.g., SOUNDEX_W5_000070877 (Warner’s “US Recorded Music P&L”); SOUNDEX_W5_000046469 (Universal’s “US Market Margin P&L”); and SOUNDEX_W5_000021930 (Sony’s “Total US P&Ls”). See also “Music streaming hailed as industry’s savior as labels enjoy profit surge,” The Guardian, December 29, 2016, https://www.theguardian.com/technology/2016/dec/29/music-streaming-industry-saviour-labels-spotify-apple- music; “The Major Labels’ Revenues Grew by $1 BN In 2017. But Who Had the Biggest Year?,” Music Business Worldwide, February 19, 2018, https://www musicbusinessworldwide.com/major-labels-revenues- grew-1bn-2017-biggest-year/; and “2018 Global Label Market Shares: Stream Engine,” Midia, March 13, 2019, https://www midiaresearch.com/blog/2018-global-label-market-share-stream-engine/. 188 Written Direct Testimony of Jonathan Bender, September 20, 2019 (“Bender Written Testimony”), p. 19.
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90. None of these factors justifies doubling the minimum fee (and the cap on cumulative minimum fees). With respect to the costs of administering the license, the minimum fee, as I understand it, is meant to cover SoundExchange’s incremental administrative costs of an additional licensee so that SoundExchange does not sustain an incremental loss on processing a licensee with a low number of plays (and thus low royalties).189 The minimum fee is not meant
to cover SoundExchange’s average administrative cost per licensee.190 Given the likely
significant fixed costs involved in SoundExchange’s operations, SoundExchange’s incremental
administrative cost is likely substantially less than its average administrative cost. In light of
this, an increase in the minimum fee would be justified only to the extent that the incremental
administrative costs of processing a low volume licensee had increased and would be limited to
the amount of such increase.
91. SoundExchange has not demonstrated that its incremental administrative costs have
increased. SoundExchange fails even to identify any costs that are incremental with respect to
processing an additional licensee. This failure is crucial, as only costs of this type could provide a justification for an increase in the minimum fee. Instead of identifying and analyzing incremental cost, SoundExchange incorrectly points to its overall costs as justification.191
However, an increase in its overall costs could well be due to an increase in its fixed costs, which are not incremental costs and thus not a justification for increasing the minimum fee. A doubling
189 Intercollegiate Broad. Sys., Inc. v. Copyright Royalty Bd., 574 F.3d 748, 761 (D.C. Cir. 2009); Web I, pp. 32, 94- 96; Web II, pp. 24096-7. I also understand that the CARP/CRB has stated that the minimum fee has another purpose of covering the intrinsic value of access to the blanket license. As for this potential purpose of the minimum fee, SoundExchange has not attempted to value it and instead focuses on the administrative costs, and I do the same for purposes of this rebuttal report. 190 Put another way, the minimum fee is not meant to pay for costs of the licensing collective. I understand that the collective is to cover its costs out of royalties received, except for the incremental costs associated with small licensees, which are covered by the minimum fee as described above. 191 Bender Written Testimony, pp. 21-23.
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of the minimum fee would be justified only if the incremental administrative costs of processing
a licensee had doubled. Given the modest levels of inflation over the Web IV term, such a large increase in the incremental cost is economically implausible.
92. I note that SoundExchange and College Broadcasters, Inc. (“CBI”) recently entered into
the Joint Motion to Adopt Partial Settlement covering the terms and royalties associated with
certain non-subscription internet transmissions by non-commercial webcasters for the period
from 2021 through 2025.192 The proposed settlement includes minimum fees starting at $550 in
2021 increasing by $50 per year to $750 in 2025.193 I have seen no evidence for why the
incremental administrative costs of administering a college broadcasters license would be any
different than administering a small commercial broadcasters license. As a result, this market
transaction supports the conclusion that SoundExchange’s proposal to increase the minimum fee
from $500 to $1,000 starting in 2021 for commercial broadcasters is not justified or supported.
93. SoundExchange’s other justifications for increasing the minimum fee relate to increasing
royalties and increasing usage. Neither of these has anything to do with the incremental
administrative cost of processing a licensee and thus they do not provide any justification for an
increase in the minimum fee. Moreover, increasing usage and royalties would suggest that a
decreasing number of licensees would be subject to the minimum fee.
192 Joint Motion to Adopt Partial Settlement between SoundExchange, Inc. and College Broadcasters, Inc., September 23, 2019. 193 Joint Motion to Adopt Partial Settlement between SoundExchange, Inc. and College Broadcasters, Inc., September 23, 2019, pp. 6-7.
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VIII. UPDATED SIMULCAST ROYALTY RATE BASED ON AN OPPORTUNITY COST FRAMEWORK
94. In response to Dr. Willig’s opportunity cost analysis, which as described above suffers
from numerous methodological errors, the proper opportunity cost approach is what I presented
in my opening report. Based on the CRB’s recent announcement of the 2020 webcasting rates,
which after applying the inflation adjustment provision under the Web IV rates and terms resulted
in an updated per-play royalty rate for subscription non-interactive music streaming services that
increased from $0.0023 to $0.0024 per play,194 I have updated my opportunity cost analysis to
reflect this rate change.
95. I have used the updated royalty rate of $0.0024 for the per-play royalty rate for the New
Subscription – Paid Non-Interactive service type in my opportunity cost analysis. This results in an estimate of the label’s direct loss in royalty revenue from users being diverted from other royalty-bearing services to simulcast of [ per play.195 A confidence interval for this figure can be calculated that reflects the statistical variation inherent in the survey. The 95% confidence interval for the per-play rate is ]. Applying the Web IV
steering discount of 12% to adjust these rates toward the rates that would prevail under effective
competition results in a steering-adjusted rate of [ ] per play with a 95% confidence
interval of ].
194 Cost of Living Adjustment to Public Broadcasters Compulsory License Royalty Rate, November 21, 2019, 84 FR 64205. 195 Updated Appendix B1. I also calculated the total expected direct royalty loss per play due to simulcast based on two additional scenarios. The first scenario uses diversion ratios for the alternatives that are calculated by excluding respondents to the survey who did not select “Music” as a type of content that they had listened to through simulcast over the last three days. The second scenario uses diversion ratios for the alternatives that are calculated by including only those respondents to the survey who only selected “Music” as a type of content that they had listened to through simulcast over the last three days. The results for these two additional scenarios are presented in Updated Appendices B4-B5 and are consistent with the result based on all the survey respondents.
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96. I have also used the updated royalty rate of $0.0024 for the New Subscription – Paid
Non-Interactive service type in my sensitivity analysis of the rate calculated using the
opportunity cost framework. In the first scenario of my sensitivity analysis, I used the $0.0024
updated rate and an alternative per-play royalty rate for the Ad Supported Non-Interactive
service type equal to the effective per-play royalty rate for custom radio calculated from the
direct deals between iHeart and the renewal indies assuming [
]. The result is [ .196 In the second scenario of my sensitivity analysis, I used the $0.0024 updated rate and an alternative per-play royalty rate for the Ad Supported Video service type equal to the effective per-play royalty rate for only Premium/Produced Content. The result is [ ].197
IX. PROMOTIONAL VALUE OF RADIO
97. SoundExchange witnesses claim that [ ] are some of the most important vehicles for promoting artists.198 They largely ignore, however, the promotional value of radio
and the corresponding simulcast, particularly as compared to other non-interactive services.
98. As I discussed in my opening report, record labels perceive radio broadcasts to be highly
promotional. In Web IV, the Judges stated that the record was “replete with statements concerning
the promotional value of terrestrial radio play for introducing new artist and new songs to the
public and stimulating sales of sound recordings,” with “consensus, or near-consensus, on this
point.”199 As I explained in my opening report, the importance of radio (and thus simulcast) to
196 Updated Appendix B2. 197 Updated Appendix B3. 198 See, e.g., Written Direct Testimony of Jennifer Fowler, September 22, 2019, pp. 2, 11-12; Written Direct Testimony of Mike Sherwood, September 23, 2019, pp. 5, 12. 199 Web IV Determination, 81 Fed. Reg. 26322 (CRB May 2, 2016).
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101. Further, while interactive services may also help promote an artist, the evidence I have reviewed indicates that radio (and the corresponding simulcast) remains one of the most important promotional tools, including for gaining streams on interactive services. For example,
Warner concluded in September 2019 that
]208 That same year, Warner found that
[“
.”]209 Similarly, Sony concluded in 2018 that [
]210
208 SOUNDEX_W5_000033374 (Warner Music Group), at SOUNDEX_W5_000033374. 209 SOUNDEX_W5_000092521 (July Update, Digital Strategy), at SOUNDEX_W5_000092532. 210 SOUNDEX_W5_000056950, (GDB, Digital Strategy Update), at SOUNDEX_W5_000057001.
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Rebuttal Appendix A Rebuttal Documents Relied Upon
Bates Documents NAB00003944. NAB00003948. NAB00003969. NAB00004024. PANWEBV_00005062. SOUNDEX_W5_000026604. SOUNDEX_W5_000021930. SOUNDEX_W5_000033096. SOUNDEX_W5_000033374. SOUNDEX_W5_000033401 SOUNDEX_W5_000044743. SOUNDEX_W5_000044967. SOUNDEX_W5_000045448. SOUNDEX_W5_000046050. SOUNDEX_W5_000046466. SOUNDEX_W5_000046469. SOUNDEX_W5_000052770. SOUNDEX_W5_000052820. SOUNDEX_W5_000053188. SOUNDEX_W5_000053352. SOUNDEX_W5_000055164. SOUNDEX_W5_000056950. SOUNDEX_W5_000092521. SOUNDEX_W5_000108335. SOUNDEX_W5_000186111. SOUNDEX_W5_000186164. SOUNDEX_W5_000186170. SOUNDEX_W5_000186194. SOUNDEX_W5_000186205. SOUNDEX_W5_000186211. SOUNDEX_W5_000186239. SOUNDEX_W5_000186253. SOUNDEX_W5_000186314. SOUNDEX_W5_000186336. SOUNDEX_W5_000186340. SOUNDEX_W5_000186367. SOUNDEX_W5_000186424. SOUNDEX_W5_000186470. SOUNDEX_W5_000186472. SOUNDEX_W5_000186474. SOUNDEX_W5_000186516. SOUNDEX_W5_000186522. SOUNDEX_W5_000186543. SOUNDEX_W5_000186551. SOUNDEX_W5_000186564. SOUNDEX_W5_000186585. SOUNDEX_W5_000186590. SOUNDEX_W5_000186633. SOUNDEX_W5_000186654. SOUNDEX_W5_000186661. SOUNDEX_W5_000186668. SOUNDEX_W5_000186680. SOUNDEX_W5_000186687. SOUNDEX_W5_000186692. SOUNDEX_W5_000186788. SOUNDEX_W5_000186803. SOUNDEX_W5_000186893. SOUNDEX_W5_000187045. SOUNDEX_W5_000187914.
NAB Written Rebuttal Statement Dkt. No. 19-CRB-0005-WR (2021-25) Page 1 of 4 PUBLIC VERSION
SoundExchange Exhibit 12, SOUNDEX_W5_000004474. SoundExchange Exhibit 39, SOUNDEX_W5_000017684. SoundExchange Exhibit 40, SOUNDEX_W5_000011145. SoundExchange Exhibit 42, SOUNDEX_W5_000053019. SoundExchange Exhibit 44, Edison Research, “Share of Ear,” Q2 2019. SoundExchange Exhibit 122, SOUNDEX_W5_000006792. SoundExchange Exhibit 123, SOUNDEX_W5_000006326. SoundExchange Exhibit 134, SOUNDEX_W5_000013098. SoundExchange Exhibit 152, Sony-Spotify 2011 Agreement. SoundExchange Exhibit 190, Universal Spotify 2011 Agreement. Zauberman Survey Data, SOUNDEX_W5_000044743.
Depositions Deposition and Exhibits of Aaron Harrison, December 19, 2019. Deposition and Exhibits of Leonard Wheeler, December 4, 2019. Deposition and Exhibits of Reni Adadevoh, December 13, 2019.
Written Direct Testimony Expert Rebuttal Witness Statement of Professor John R. Hauser, January 10, 2020. Written Direct Testimony of Aaron Harrison, September 23, 2019. Written Direct Testimony of Catherine Tucker, September 23, 2019. Written Direct Testimony of Dr. Gregory K. Leonard, September 23, 2019. Written Direct Testimony of Gal Zauberman, September 23, 2019. Written Direct Testimony of Jennifer Fowler, September 23, 2019. Written Direct Testimony of Johnathan Bender, September 23, 2019. Written Direct Testimony of Jonathan Orszag, September 23, 2019. Written Direct Testimony of Mike Sherwood, September 23, 2019. Written Direct Testimony of Professor John R. Hauser, September 23, 2019. Written Direct Testimony of Robert Willig, September 23, 2019. Written Direct Testimony of Robert Willig (SDARS III ).
Webcaster Determinations "Digital Performance Right in Sound Recordings and Ephemeral Recordings," Copyright Royalty Board, Library of Congress, 72 Fed. Reg. 24804 ("Web II "). Determination of Royalty Rates and Terms for Ephemeral Recording and Webcasting Digital Performance of Sound Recordings (Web IV), Docket No. 14-CRB-0001-WR (2016-2020) ("Web IV "). Report of the Copyright Arbitration Royalty Panel to the Librarian of Congress, In the Matter of Rate Setting for Digital Performance Right in Sound Recordings and Ephemeral Recordings, Docket No. 2000-9, February 20, 2002 (“Web I ”).
Court Documents Broadcast Music, Inc. v. Pandora Media, Inc. , 140 F. Supp. 3d 267 (S.D.N.Y. 2015). Cost of Living Adjustment to Public Broadcasters Compulsory License Royalty Rate, November 21, 2019, 84 FR 64205. Determination of Royalty Rates and Terms for Making and Distributing Phonorecords, Docket No. 16-CRB-0003-PR (2018-2022) ("Phonorecords III "). Determination of Royalty Rates and Terms for Transmission of Sound Recordings by Satellite Radio and "Preexisting" Subscription Services," Docket No. 16-CRB-0001 SR/PSSR (2018-2022) ("SDARS III "). Intercollegiate Broad. Sys., Inc. v. Copyright Royalty Bd. , 574 F.3d 748, 761 (D.C. Cir. 2009). Introductory Memorandum to the Written Direct Statement of SoundExchange, Inc., American Federation of Musicians of the United States and Canada, Screen Actors Guild-American Federation of Television and Radio Artists, American Association of Independent Music, Sony Music Entertainment, UMG Recordings, Inc., Warner Music Group Corp., and Jagjaguwar Inc. Joint Motion to Adopt Partial Settlement between SoundExchange, Inc. and College Broadcasters. Inc., September 23, 2019. Public Initial Brief for Appellees, Johnson v. CRB and Librarian of Congress, Nov.12, 2019. Public Law 115-264: Music Modernization Act, 132 Stat. 3676, October 11, 2018. Supplemental and Corrected Responses and Objections to First Set of Interrogatories to SoundExchange, Inc., American Federation of Musicians of the United States and Canada, Screen Actors Guild-American Federation of Television and Radio Artists, American Association of Independent Music, Sony Music Entertainment,MG Recordings, Inc., Warner Music Group Corp., and JagJaguwar Inc. from Licensee Participants, Response to Interrogatory No. 1.
NAB Written Rebuttal Statement Dkt. No. 19-CRB-0005-WR (2021-25) Page 2 of 4 PUBLIC VERSION
Academic Articles and Books Ariv Nevo, “Mergers with Differentiated Products: The Case of the Ready-to-Eat Cereal Industry,” RAND Journal of Economics, Vol. 31, No.3 (2000). Claudia Moellers, Hans-Theo Normann and Christopher Snyder, "Communication in Vertical Markets: Experimental Evidence," International Journal of Industrial Organization, Volume 50, Issue C (2017). Daniel McFadden, “Econometric Models of Probabilistic Choice,” in Structural Analysis of Discrete Data with Econometric Applications, 1981. David Brownstone and Kenneth Train, “Forecasting New Product Penetration with Flexible Substitution Patterns,” Journal of Econometrics, 1999. Dennis W. Carlton and Jeffrey M. Perloff, Modern Industrial Organization, 4th Edition, Pearson, 2005. Faruk Gul, "Bargaining Foundations of Shapley Value," Econometrica, Volume 57, No. 1 (1989). Franziska Voelckner, "An empirical comparison of methods for measuring consumers' willingness to pay," Marketing Letters, (2006). Hal Varian, Microeconomic Analysis, 2nd Edition, W.W. Norton & Company, 1984. James J. Murphy, P. Geoffrey Allen, Thomas H. Stevens, and Darryl Weatherhead, “A Meta-analysis of Hypothetical Bias in Stated Preference Valuation,” Environmental and Resource Economics, Volume 30, No.3 (2005). Jerry Hausman and Greg Leonard, “Economic Analysis of Differentiated Products Mergers Using Real World Data,” George Mason Law Review, Vol. 5, No.3 (1997). Martin J. Osborne and Ariel Rubinstein, A Course in Game Theory, The MIT Press, 1994. Peter Davis and Eliana Garces, Quantitative Techniques for Competition and Antitrust Analysis, Princeton University Press, 2010. Steven Berry, “Estimating Discrete Choice Models of Product Differentiation,” RAND Journal of Economics, Vol. 25, No.2 (1994).
Others “1 Potentially Troubling Trend for Spotify,” The Motley Fool, November 6, 2018, https://www fool.com/investing/2018/11/06/1-potentially-troubling-trend-for-spotify.aspx. “2018 Global Label Market Shares: Stream Engine,” Midia, March 13, 2019, https://www midiaresearch.com/blog/2018-global-label-market-share-stream-engine/. “2020 Rates,” SoundExchange Website, https://www.soundexchange.com/service-provider/rates/. “A Lawsuit Against Apple’s App Store Could Be a Big Bonus for Spotify,” Rolling Stone, November, 29, 2018, https://www rollingstone.com/music/music-news/apple-app-store-spotify-lawsuit-760636/. “Apple Music Overtakes Spotify in Paid U.S. Subscribers,” The Wall Street Journal, April 5, 2019, https://www.wsj.com/articles/apple-music-overtakes-spotify-in-u-s-subscribers-11554475924. “Apple Music vs Spotify: the music streaming titans go head-to-head,” TechRadar, June 18, 2019, https://www.techradar.com/news/audio/apple-music-vs-spotify-vs-play-music-vs-tidal-vs-deezer-1296240. “As Streaming Services Boom, SoundCloud Strives for Relevancy,” Wired, April 25, 2017, https://www.wired.com/2017/04/soundcloud-crossroads/. “Best Music Streaming: Spotify, Apple Music and More, Compared,” CNET, November 24, 2019, https://www.cnet.com/how-to/best-music-streaming-service-of-2019-spotify-pandora-apple-music/. "Best Music Streaming Services," Consumer Reports, https://www.consumerreports.org/streaming-media/best-music-streaming-service-for-you/. “Competition and Monopoly: Single-Firm Conduct under Section 2 of the Sherman Act : Chapter 2,” DOJ, https://www.justice.gov/atr/competition-and-monopoly-single-firm-conduct-under-section-2-sherman-act-chapter-2. “Consumer Price Index: Total All Items for the United States, Growth Rate Same Period Previous Year, Annual, Not Seasonally Adjusted,” Federal Reserve Bank of St. Louis. “How much is iHeartRadio All Access? What can I use to pay for it?” iHeartRadio, https://help.iheart.com/hc/en-us/articles/235721027-How-much-is-iHeartRadio-All-Access-What-can-I-use-to-pay-for-it-. “How much is iHeartRadio Plus? What can I use to pay for it?” iHeartRadio, https://help.iheart.com/hc/en-us/articles/235720747--How-much-is-iHeartRadio-Plus-What-can-I-use-to-pay-for-it-. “How to transfer playlists from Spotify to Apple Music,” AppleInsider, August 18, 2019, https://appleinsider.com/articles/19/08/18/how-to-transfer-playlists-from-spotify-to-apple-music. “iHeartMedia Launches First Ever -- and Only – Interactive on Demand Radio Services, ‘iHeartRadio Plus’ & ‘iHeartRadio All Access’,” BusinessWire, December 1, 2016, https://www.businesswire.com/news/home/20161201005685/en/iHeartMedia-Launches----%E2%80%93 -Interactive-Demand-Radio/. “Introducing Apple Music — All The Ways You Love Music. All in One Place,” Apple, June 8, 2015, https://www.apple.com/newsroom/2015/06/08Introducing-Apple-Music-All-The-Ways-You-Love-Music-All-in-One-Place-/. “Music Streaming,” Goldman Sachs, December 18, 2018, available at https://www.goldmansachs.com/insights/pages/infographics/music-streaming/.
NAB Written Rebuttal Statement Dkt. No. 19-CRB-0005-WR (2021-25) Page 3 of 4 PUBLIC VERSION
"Music streaming hailed as industry’s savior as labels enjoy profit surge,” The Guardian, December 29, 2016, https://www.theguardian.com/technology/2016/dec/29/music-streaming-industry-saviour-labels-spotify-apple-music. “New high-res music streaming service Qobuz launches in US, takes aim at Spotify, Pandora,” USA Today, February 14, 2019, https://www.usatoday.com/story/tech/news/2019/02/14/spotify-pandora-have-new-competitor-music-streaming-service-qobuz/2860467002/. “Pandora Details Its Pay Raise to Publishers,” Billboard, February 12, 2016. “Pandora Is Now Paying Publishers 1/5th of the Money It Gives Labels,” Music Business Worldwide, February 17, 2016. “Pandora’s on-demand music service finally arrives,” TechCrunch, March 13, 2017, https://techcrunch.com/2017/03/13/pandoras-on-demand-music-service-finally-arrives/. “Primephonic launches hi-res classical-music streaming service,” Music Ally, June 14, 2017, https://musically.com/2017/06/14/primephonic-classical-music-streaming/. ““Share of Ear” Documents the Transition from Owned to Rented Music,” Edison Research, February 1, 2019, https://www.edisonresearch.com/share-of-ear-documents-the-transition-from-owned-to-rented-music/. "SoundCloud, the ‘YouTube for audio’, cuts 173 jobs, closes San Francisco, London offices," TechCrunch, https://techcrunch.com/2017/07/06/soundcloud-the-youtube-for-audio-cuts-173-jobs-closes-san-francisco-london-offices/ “Spotify Hits 108M Paying Users and 232M Overall, But Its Average Revenue Per User Declines,” Tech Crunch, July 31, 2019, https://techcrunch.com/2019/07/31/spotify-108-million/. “Spotify: Our Ads Business is a real Trigger for Growth,” Music Business Worldwide, October 31, 2018, https://www musicbusinessworldwide.com/spotify-our-ads-business-is-a-real-trigger-for-growth-moving-forward/. “Spotify’s Ad Studio is its fastest-growing advertising channel,” Music Ally, January 30, 2019, https://musically.com/2019/01/30/spotifys-ad-studio-is-its-fastest-growing-advertising-channel/. “Spotify’s Average Revenue per User Is Shrinking,” Market Realist, May 13, 2019, https://articles2 marketrealist.com/2019/05/spotifys-average-revenue-per-user-is-shrinking/#. “The Average Spotify Subscriber Pays $5.50 a Month — and Record Labels Hate It,” RollingStone, January 11, 2019, https://www rollingstone.com/music/music-features/the-average-spotify-subscriber-is-paying-5-50-a-month-and-record-labels-hate-it-776925/. “The Major Labels’ Revenues Grew by $1 BN In 2017. But Who Had the Biggest Year?,” Music Business Worldwide, February 19, 2018, https://www musicbusinessworldwide.com/major-labels-revenues-grew-1bn-2017-biggest-year/ "Top U.S. music streaming services by reach 2018," Statista, https://www.statista.com/statistics/798715/most-popular-us-music-streaming-services-ranked-by-reach/ “Upgrade to Pandora Plus or Premium,” Pandora Help, https://help.pandora.com/s/article/Upgrade-to-Pandora-Plus-or- Pandora-Premium-1519949306612?language=en_US. “Why Do We Still Pay Only $10 a Month for Music?,” Rolling Stone, December 11, 2019, https://www-rollingstone-com.cdn.ampproject.org/c/s/www rollingstone.com/music/music-news/music-streaming-10-month-fee-924809/amp/. “Why Has Sony Music Just Launched A Streaming Service (And Spotify Rival) In Japan?” Music Business Worldwide, December 11, 2018, https://www musicbusinessworldwide.com/why-has-sony-just-launched-a-music-streaming-service-and-spotify-rival-in-japan/. “YouTube Music and YouTube Premium Officially Launch in US, Canada, UK, and Other Countries,” The Verge, June 18, 2018, https://www.theverge.com/2018/6/18/17475122/youtube-music-premium-launch-us-canada-uk. RIAA 2018 Year-End Music Industry Revenue Report. RIAA 2015 Year-End Industry Shipment and Revenue Statistics. Sirius XM 2018 Form 10-K. Spotify 2018 Form 20-F. Spotify October 2019 Form 6-K. Statement of Christopher Harrison (Chief Executive Officer, Digital Media Association (DiMA)), Hearing on “Protecting and Promoting Music Creation for the 21st Century,” May 15, 2018.
NAB Written Rebuttal Statement Dkt. No. 19-CRB-0005-WR (2021-25) Page 4 of 4 PUBLIC VERSION
UPDATED APPENDIX B1 RESTRICTED IN ITS ENTIRETY - NO REDACTED VERSION AVAILABLE SUBJECT TO PROTECTIVE ORDER IN DOCKET NO. 19-CRB-0005-WR (2012-25) PUBLIC VERSION
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UPDATED APPENDIX E PUBLIC VERSION PUBLIC VERSION Gregory K. Leonard Charles River Associates Page 2
“Competitive Analysis with Differentiated Products.” With J. Hausman and D. Zona. Annales d'Economie et de Statistique 34, 1994, pp. 159-180.
“A Utility Consistent, Combined Discrete Choice and Count Data Model: Assessing Recreational Use Losses Due to Natural Resource Damage.” With J. Hausman and D. McFadden. Journal of Public Economics 56, 1995, pp. 1-30.
“Market Definition Under Price Discrimination.” With J. Hausman and C. Vellturo. Antitrust Law Journal 64, 1996, pp. 367-386.
“Achieving Competition: Antitrust Policy and Consumer Welfare.” With J. Hausman. World Economic Affairs 1, 1997, pp. 34-38.
“Economic Analysis of Differentiated Products Mergers Using Real World Data.” With J. Hausman. George Mason Law Review 5, 1997, pp. 321-346.
“Superstars in the NBA: Economic Value and Policy.” With J. Hausman. Journal of Labor Economics 15, 1997, pp. 586-624.
“Efficiencies From the Consumer Viewpoint.” With J. Hausman. George Mason Law Review 7, 1999, pp. 707-727.
“Documents Versus Econometrics in Staples.” With J. Hausman. Available at https://papers.ssrn.com/sol3/papers.cfm?abstract_id=1305691.
“The Competitive Effects of a New Product Introduction: A Case Study.” With J. Hausman. Journal of Industrial Economics 30, 2002, pp. 237-263.
“Does Bell Company Entry into Long-Distance Telecommunications Benefit Consumers?” With J. Hausman and J. G. Sidak. Antitrust Law Journal 70, 2002, pp. 463-484.
“On Nonexclusive Membership in Competing Joint Ventures.” With J. Hausman and J. Tirole. RAND Journal of Economics 34, 2003.
“Correcting the Bias When Damage Periods are Chosen to Coincide With Price Declines.” With D. Carlton. Columbia Business Law Review, 2004, pp. 304-306.
“Competitive Analysis Using a Flexible Demand Specification.” With J. Hausman. Journal of Competition Law and Economics 1, 2005, pp. 279-301.
“Using Merger Simulation Models: Testing the Underlying Assumptions.” With J. Hausman. International Journal of Industrial Organization 23, 2005, pp. 693-698.
“Application of Empirical Methods in Merger Analysis.” With C. Dippon and L. Wu. Report to the Fair Trade Commission of Japan, June 27, 2005. PUBLIC VERSION Gregory K. Leonard Charles River Associates Page 3
“A Practical Guide to Damages.” With L. Stiroh. In Economic Approaches to Intellectual Property, Policy, Litigation and Management, ed. by G. Leonard and L. Stiroh, 2005.
“Applying Merger Simulation Techniques to Estimate Lost Profits Damages in Intellectual Property Litigation.” In Economic Approaches to Intellectual Property, Policy, Litigation and Management, ed. by G. Leonard and L. Stiroh, 2005.
“Antitrust Implications of Pharmaceutical Patent Litigation Settlements.” With R. Mortimer. In Economic Approaches to Intellectual Property, Policy, Litigation and Management, ed. by G. Leonard and L. Stiroh, 2005.
“Framework for Policymakers to Analyze Proposed and Existing Antitrust Immunities and Exemptions.” With D. Bush and S. Ross. Report to the Antitrust Modernization Commission, October 24, 2005.
“Real Options and Patent Damages: The Legal Treatment of Non-Infringing Alternatives and Incentives to Innovate.” With J. Hausman. Journal of Economic Surveys 20, 2006, pp. 493-512 (reprinted in Economic and Legal Issues in Intellectual Property, M. McAleer and L. Oxley, eds., Blackwell Publishing, 2007).
“The Competitive Effects of Bundled Discounts.” In Economics of Antitrust: Complex Issues in a Dynamic Economy, ed. by L. Wu, 2007.
“Estimation of Patent Licensing Value Using a Flexible Demand Specification.” With J. Hausman. Journal of Econometrics 139, 2007, pp. 242-258.
“Patent Damages and Real Options: How Judicial Characterization of Non-Infringing Alternatives Reduces Incentives to Innovate.” With J. Hausman and J. G. Sidak. Berkeley Technology Law Journal 22, Spring 2007, pp. 825-853.
“Don’t Feed the Trolls.” With N. Attenborough and F. Jimenez. les Nouvelles, Vol. 42, September 2007, pp. 487-495 (reprinted in Patent Trolls: Legal Implications, C.S. Krishna, ed., The Icfai University Press, 2008). With J. Johnson, C. Meyer, and K. Serwin. “Are Three to Two Mergers in Markets with Entry Barriers Necessarily Problematic?” European Competition Law Review 28, October 2007, pp. 539-552.
“Economics and the Rigorous Analysis of Class Certification in Antitrust Cases.” With L. Wu. Journal of Competition Law and Economics 3, 2007, pp. 341-356. With J. Johnson. “Assessing the Competitive Effects of a Merger: Empirical Analysis of Price Differences Across Markets and Natural Experiments.” Antitrust, Fall 2007, pp. 96-101.
“Incentives and China’s New Antimonopoly Law.” With F. Deng. Antitrust, Spring 2008, pp. 73-77.
“Use of Simulation in Competitive Analysis.” With J.D. Zona. In Issues in Competition Law and Policy, ed. by W. Dale Collins, 2008. PUBLIC VERSION Gregory K. Leonard Charles River Associates Page 4
“Allocative and Productive Efficiency.” With F. Deng. In Issues in Competition Law and Policy, ed. by W. Dale Collins, 2008.
“In the Eye of the Beholder: Price Structure as Junk Science in Antitrust Class Certification Proceedings.” With J. Johnson. Antitrust, Summer 2008, pp. 108-112.
“Merger Retrospective Studies: A Review.” With G. Hunter and G. S. Olley. Antitrust, Fall 2008, pp. 34-41.
“Roundtable Discussion: Developments—and Divergence—In Merger Enforcement.” Antitrust, Fall 2008, pp. 9-27.
“Dispatch From China.” Antitrust, Spring 2009, pp. 88-89.
“A Hard Landing in the Soft Drink Market – MOFCOM’s Veto of the Coca-Cola/Huiyuan Deal.” With F. Deng and A. Emch. Antitrust Chronicle, April 2009(2).
“Predatory Pricing after linkline and Wanadoo.” With A. Emch. Antitrust Chronicle, May 2009(2).
“Farrell and Shapiro: The Sequel.” With M. Lopez. Antitrust, Summer 2009, pp. 14-18.
“掠夺性定价—美国与欧盟的法律及经济学分析” (“Predatory Pricing – Economics and Law in the United States and the European Union”), 法学家 (Jurists’ Review), 2009, pp. 100-110. With A. Emch.
“Revising the Merger Guidelines: Second Request Screens and the Agencies’ Empirical Approach to Competitive Effects.” With L. Wu. Antitrust Chronicle, December 2009(1).
“How Private Antitrust Litigation May Be Conducted in China.” With F. Deng and W. Tang. Competition Law360, January 6, 2010.
“Merger Screens: Market-Share Based Approaches and ‘Upward Pricing Pressure,’” Antitrust Source, February 2010. With E. Bailey, G. S. Olley, and L. Wu.
“Minimum Resale Price Maintenance: Some Empirical Evidence From Maryland.” With E. Bailey. BE Journal of Economic Analysis & Policy 10, 2010.
“Three Cases Reshaping Patent Licensing Practice.” With E. Bailey and A. Cox. Managing Intellectual Property, March 2010.
“Econometrics and Regression Analysis.” With J. Langenfeld, W. Li, and J. Morris. in Proving Antitrust Damages: Legal and Economic Issues, ABA Section of Antitrust (2nd Edition), 2010.
“Patent Damages: What Reforms Are Still Needed?.” With M. Lopez. Landslide 2, May/June 2010.
“The Google Books Settlement: Copyright, Rule 23, and DOJ Section 2 Enforcement.” Antitrust, Summer 2010, pp. 26-31. PUBLIC VERSION Gregory K. Leonard Charles River Associates Page 5
“The 2010 Merger Guidelines: Do We Need Them? Are They All We Need?.” Antitrust Chronicle, October 2010(2).
“Evaluating the Unilateral Competitive Effects of Mergers Among Firms with High Profit Margins.” With E. Bailey and L. Wu. Antitrust, Fall 2010, pp. 28-32.
“Predatory Pricing in China—In Line With International Practice?.” With A. Emch. Legal Issues of Economic Integration 37, 2010, pp. 305-316.
“What Can Be Learned About the Competitive Effects of Mergers From ‘Natural Experiments’?.” With G. S. Olley. International Journal of the Economics of Business 18, 2011, pp. 103-107.
“District Court Rejects the Google Books Settlement: A Missed Opportunity?.” Antitrust Source, April 2011.
“Making Sense of ‘Apportionment’ in Patent Damages.” With E. Bailey and M. Lopez. Columbia Science and Technology Law Review 12, pp. 255-271, 2011.
“Rigorous Analysis of Class Certification Comes of Age.” With J. Johnson. Antitrust Law Journal 77, 2011, pp. 569-586.
“Economic Analysis in Indirect Purchaser Class Actions.” With F. Deng and J. Johnson. Antitrust, Fall 2011, pp. 51-57.
“Merger Assessment and Frontier of Economic Analyses (4): Empirical Methods in Antitrust Merger Review.“ With L. Wu. Kokusai Shoji Houmu (International Business Law and Practice), Vol. 40, No. 3, 2012, pp. 391-401.
“Merger Assessment and Frontier of Economic Analyses (5): Empirical Methods in Antitrust Merger Review.“ With L. Wu. Kokusai Shoji Houmu (International Business Law and Practice), Vol. 40, No. 4, 2012, pp. 557-564.
“Merger Assessment and Frontier of Economic Analyses (6): Empirical Methods in Antitrust Merger Review.“ With L. Wu. Kokusai Shoji Houmu (International Business Law and Practice), Vol. 40, No. 5, 2012, pp. 731-739.
“Economists’ Roundtable on Hot Patent-Related Antitrust Issues.” With D. Carlton, C. Meyer, C. Shapiro. Antitrust, Summer 2013, pp. 10-21.
“Not So Natural Experiments.” Competition Policy International, July 2013 (2).
“The Role of China’s Unique Economic Characteristics in Antitrust Enforcement.” With F. Deng. In China’s Anti-Monopoly Law: The First Five Years, ed. by Adrian Emch and David Stallibrass, 2013.
“Reflections on Bazaarvoice.” With P. Normann. CPI Antitrust Chronicle, March 2014 (1). PUBLIC VERSION Gregory K. Leonard Charles River Associates Page 6
“An Introduction to Econometric Analysis.” In Econometrics: Legal, Practical and Technical Issues, ABA Section of Antitrust (2nd Edition), 2014.
“The Econometric Framework.” in Econometrics: Legal, Practical and Technical Issues, ABA Section of Antitrust (2nd Edition), 2014.
“Applying Econometrics to Estimate Damages.” With J. Langenfeld, W. Li, and J. Morris. in Econometrics: Legal, Practical and Technical Issues, ABA Section of Antitrust (2nd Edition), 2014.
“Determining RAND Royalties for Standard-Essential Patents.” With M. Lopez. Antitrust, Fall 2014, pp. 86-94.
“Reflections on the Debates Surrounding Standard-Essential Patents.” The Antitrust Source, August 2015.
“Turning Daubert on Its Head: Efforts to Banish Hypothesis Testing in Antitrust Class Actions.” Antitrust, Spring 2016, pp. 53-59.
“Roundtable with Economists: Discussing Practice and Theory with the Experts.” With D. Carlton, P. Johnson, M. Maher, and C. Shapiro. Antitrust, Spring 2018, pp. 11-23.
“Comparative Analysis of Court-Determined FRAND Royalty Rates.” With F. Deng and M. Lopez. Antitrust, Summer 2018, pp. 47-51.
“A Comparison of the Almost Ideal Demand System and Random Coefficients Logit Models For Use with Retail Scanner Data.” With F. Deng. Working Paper, 2007.
Presentations
“Merger Analysis with Differentiated Products,” paper presented to the Economic Analysis Group of the US Department of Justice, April 1991 (with J. Hausman and D. Zona).
“Assessing Use Value Losses Due to Natural Resource Injury,” paper presented at “Contingent Valuation: A Critical Assessment,” Cambridge Economics Symposium, April 3, 1992 (with J. Hausman and D. McFadden).
“Contingent Valuation and the Value of Marketed Commodities,” paper submitted to the Contingent Valuation Panel of the National Oceanic and Atmospheric Administration, U.S. Department of Commerce, August 12, 1992 (with J. Hausman).
“Economic Analysis of Differentiated Products Mergers Using Real World Data,” paper presented to the George Mason University Law Review Antitrust Symposium, October 11, 1996 (with J. Hausman).
“Documents Versus Econometrics in Staples,” paper presented to a program of the Economics Committee of the ABA Antitrust Section, September 5, 1997 (with J. Hausman).
PUBLIC VERSION Gregory K. Leonard Charles River Associates Page 7
Discussant, “New Developments in Antitrust” session, AEA meetings, January 7, 2000.
“In Defense of Merger Simulation,” Department of Justice and Federal Trade Commission Merger Workshop, Unilateral Effects Session, February 18, 2004.
Discussant, “Proving Damages in Difficult Cases: Mock Trial & Discussion,” NERA Antitrust & Trade Regulation Seminar, July 10, 2004.
“Network Effects, First Mover Advantage, and Merger Simulation in Damages Estimation,” LSI Workshop on Calculating and Proving Patent Damages, July 16, 2004.
“Early Exchange of Documents,” LSI Workshop on Pre- and Early Stage Patent Litigation, July 23, 2004.
“Lessons Learned From Problems With Expert Testimony: Antitrust Suits,” LSI Workshop on Effective Financial Expert Testimony, November 4, 2004.
“Price Erosion and Convoyed Sales,” LSI Workshop on Calculating & Proving Patent Damages, January 19, 2005.
“Economic Analysis of Rule 23(b)(3),” LSI Litigating Class Action Suits Conference, June 6, 2005.
“Early Exchange of Documents,” LSI Workshop on Pre- & Early-Stage Patent Litigation, July 22, 2005.
“Issues to Consider in a Lost Profits Damages Analysis,” Patent Litigation 2005, Practicing Law Institute, September 30, 2005.
“Antitrust Issues in Standard Setting and Patent Pools,” Advanced Software Law and Practice Conference, November 3, 2005.
“New Technologies for Calculating Lost Profits,” LSI Workshop on Calculating & Proving Patent Damages, February 27, 2006.
“Estimating Antitrust Damages,” Fair Trade Commission of Japan, April 21, 2006.
“Economic Analysis of Rule 23(b)(3),” LSI Litigating Class Action Suits Conference, May 11, 2006.
“Permanent Injunction or Damages: What is the Right Remedy for Non-Producing Entities?,” San Francisco Intellectual Property Law Association/Los Angeles Intellectual Property Law Association Spring Seminar, May 20, 2006.
“Antitrust Enforcement in the United States” and “Economic Analysis of Mergers,” Sino-American Symposium on the Legislation and Practice of Anti-Trust Law, Beijing Bar Association, Beijing, People’s Republic of China, July 17, 2006. PUBLIC VERSION Gregory K. Leonard Charles River Associates Page 8
“Economic Analysis in Antitrust,” Chinese Academy of Social Sciences, Beijing, People’s Republic of China, July 20, 2006.
“Issues to Consider in a Lost Profits Damages Analysis,” Patent Litigation 2006, Practicing Law Institute, September 26, 2006.
“Comparison of the Almost Ideal Demand System and Random Coefficient Models for Use With Retail Scanner Data,” Pacific Rim Conference, Western Economic Association, Beijing, People’s Republic of China, January 12, 2007 (with F. Deng).
Discussant, “Applied Economics” Session, Pacific Rim Conference, Western Economic Association, Beijing, People’s Republic of China, January 12, 2007.
“Balancing IPR Protection and Economic Growth in China,” International Conference on Globalization and the Protection of Intellectual Property Rights, Chinese University of Political Science and Law, Beijing, People’s Republic of China, January 20, 2007.
“The Use and Abuse of Daubert Motions on Damages Experts: Lessons from Recent Cases,” LSI Workshop on Calculating & Proving Patent Damages, February 27, 2007.
“Will Your Licenses Ever be the Same? Biotechnology IP Strategies,” BayBio 2007 Conference, April 26, 2007.
“Tension Between Antitrust Law and IP Rights,” Seminar on WTO Rules and China’s Antimonopoly Legislation, Beijing, People’s Republic of China, September 1, 2007.
“Issues to Consider in a Lost Profits Damages Analysis,” Patent Litigation 2007, Practicing Law Institute, September 25, 2007.
Discussant, “Dominance and Abuse of Monopoly Power” Session, China’s Competition Policy and Anti-Monopoly Law, J. Mirrlees Institute of Economic Policy Research, Beijing University, and the Research Center for Regulation and Competition, Chinese Academy of Social Sciences, Beijing, People’s Republic of China, October 14, 2007.
“Opening Remarks,” Seminar on China’s Anti-monopoly Law and Regulation on Abuse of Intellectual Property Rights, Beijing, People’s Republic of China, April 26, 2008.
“Issues to Consider in a Reasonable Royalty Damages Analysis,” Patent Litigation 2008, Practicing Law Institute, October 7, 2008.
“Econometric Evaluation of Competition in Local Retail Markets,” Federal Trade Commission and National Association of Attorneys General Retail Mergers Workshop, December 2, 2008,
“Merger Review Best Practices: Competitive Effects Analysis,” International Seminar on Anti- Monopoly Law: Procedure and Substantive Assessment in Merger Control, Beijing, People’s Republic of China, December 15-17, 2008.
PUBLIC VERSION Gregory K. Leonard Charles River Associates Page 9
“The Use of Natural Experiments in Antitrust,” Renmin University, Beijing, People’s Republic of China, December 18, 2008.
“China’s Antimonopoly Law: An Economist’s Perspective,” Bloomberg Anti-Monopoly Law of China Seminar, January 29, 2009.
Panelist, “Standards for Assessing Patent Damages and Their Implementation by Courts,” FTC Hearings on the Evolving IP Marketplace, February 11, 2009.
“Economic Analysis of Agreements Between Competitors” and “Case Study: FTC Investigates Staples’ Proposed Acquisition of Office Depot,” Presentation to Delegation of Antitrust Officials from the People’s Republic of China, Washington, DC, March 23, 2009.
“Reasonable Royalties in the Presence of Standards and Patent Pools,” LSI Workshop, April 20, 2009.
Presentations on Unilateral Effects, Buyer Power, and the Intellectual Property-Antitrust Interface to Delegation from the Anti-Monopoly Bureau of MOFCOM of the People’s Republic of China, Washington, DC, May 10-11, 2009.
Panelist, “The Use of Economic and Statistical Models in Civil and Criminal Litigation,” Federal Bar Association, San Francisco, May 13, 2009.
“Trends in IP Rights Litigation and Economic Damages in China,” Pursuing IP in the Pacific Rim, May 14, 2009.
Presentation on the Economics of Antitrust, National Judicial College of the People’s Republic of China, Xi’an, People’s Republic of China, May 25-26, 2009.
“Case Study: The Use of Economic Analysis in Merger Review,” Presentation to the Anti-Monopoly Bureau of MOFCOM, Beijing, People’s Republic of China, May 27, 2009.
“Economics and Antitrust Law,” China University of Political Science and Law, Beijing, People’s Republic of China, September 21, 2009.
“Case Study: Economic Analysis of Coordinated Interaction,” Presentation to the Anti-Monopoly Bureau of MOFCOM, Beijing, People’s Republic of China, September 22, 2009.
“Relevant Market Definition,” 4th Duxes Antitrust Law Seminar, Beijing, People’s Republic of China, September 26, 2009.
“Expert Economic Testimony in Antitrust Litigation,” Supreme People’s Court, Beijing, People’s Republic of China, February 2, 2010.
“New Case Law for Patent Damages,” Law Seminars International Telebriefing, April 28, 2010.
PUBLIC VERSION Gregory K. Leonard Charles River Associates Page 10
“China/India: Sailing in Unchartered Waters: Regulating Competition in the Emerging Economies – New Laws, New Enforcement Regimes and No Precedents,” The Chicago Forum on International Antitrust Issues, Northwestern University School of Law Searle Center, May 20, 2010.
“Antitrust and Intellectual Property,” Supreme People’s Court, Beijing, People’s Republic of China, May 26, 2010.
“Cartel Enforcement Trends in the United States,” 2nd Ethical Beacon Anti-Monopoly Summit, Beijing, People’s Republic of China, May 27, 2010.
Panelist, “The Future of Books and Digital Publishing: the Google Book Settlement and Beyond,” 2010 American Bar Association Annual Meeting, August 7, 2010.
“Coordinated Effects” and “Non-Horizontal Mergers,” Presentations to Delegation from India Competition Commission, US Chamber of Commerce, Washington, DC, October 26, 2010.
“UPP and Merger Simulation,” Annual Conference of the Association of Competition Economics, Norwich, UK, November 11, 2010.
“Uniloc v. Microsoft: A Key Ruling For Patent Damages,” Law Seminars International Telebriefing, January 21, 2011.
“Correlation, Regression, and Common Proof of Impact,” New York City Bar Association, January 19, 2011.
“Private Litigation Under China’s New Antimonopoly Law,” Bar Association of San Francisco, February 17, 2011.
“Competition Law and State Regulation: Setting the Stage and Focus on State-Owned Enterprises,” Competition Law and the State: International and Comparative Perspectives, Hong Kong, People’s Republic of China, March 18, 2011.
Panelist, “Booking it in Cyberspace: The Google Book Settlement and the Aftermath,” American Intellectual Property Law Association, San Francisco, May 13, 2011.
“Econometric Estimation of Cartel Overcharges,” ZEW Conference on Economic Methods and Tools in Competition Law Enforcement, Mannheim, Germany, June 25, 2011.
Panelist, “Antitrust and IP in China,” Antitrust and IP in Silicon Valley and Beyond, American Bar Association and Stanford University, Palo Alto, October 6, 2011.
Panelist, University of San Diego School of Law Patent Law Conference: The Future of Patent Law Remedies, January 18, 2013.
“Economics Framework,” US-China Workshop on Competition Law and Policy for Internet Activities, China’s State Administration for Industry and Commerce (SAIC) and the U.S. Trade and Development Agency (USTDA), Shenzhen, People’s Republic of China, June 4-5, 2013.
PUBLIC VERSION Gregory K. Leonard Charles River Associates Page 11
Panelist, “China Inside and Out,” American Bar Association, Beijing, People’s Republic of China, September 16-17, 2013.
Panelist, “Remedies in Patent Cases,” Fifth Annual Conference on The Role of the Courts in Patent Law & Policy, Berkeley and Georgetown Law Schools, November 1, 2013.
“Royalty Base,” LeadershIP Conference, Qualcomm Incorporated, March 21, 2014.
“Reflections on Natural Experiments,” DG Comp, April 8, 2014.
Panelist, “Antitrust in Asia: China,” American Bar Association Section of Antitrust Law, Beijing, People’s Republic of China, May 21-23, 2014.
Panelist, “Patent Damages Roundtable,” 2015 Intellectual Property Institute, University of Southern California Gould School of Law, Los Angeles, March 23, 2015.
Panelist, “IP and Antitrust – The Current State of Economic Analysis,” Global Competition Review Live 2nd Annual IP & Antitrust USA, Washington, DC, April 14, 2015.
Panelist, “FRAND Royalty Rates After Ericsson v. D-Link,” American Bar Association, May 15, 2015.
Participant, Patent Damages Workshop, University of California-Berkeley, March 3, 2016.
Panelist, “FRANDtopia – In a Perfect World,” LAIPLA Spring Conference, May 5, 2018.
Panelist, “Chicago Forum on International Antitrust Issues,” Northwestern Pritzker School of Law, June 15, 2018.
Panelist, “Competition in Digital Advertising: Is There Online and Offline Convergence?,” Challenges to Antitrust in a Changing Economy, Harvard Law School, November 8, 2019.
Testimonies given in the last five years
Open Text SA v. Box Inc., United States District Court for the Eastern District of Virginia, Norfolk Division, Civil Action No. 2:13-CV-00319-MSD-DEM, 2013-2015 (Deposition, Trial Testimony).
Affinity Labs of Texas, LLC v. General Motors LLC, United States District Court for the District of Eastern District of Texas, Beaumont Division, C.A. No. 1:12‐CV‐00582‐RC, 2014 (Deposition).
W.L. Gore & Associates, Inc. v. C.R. Bard, Inc. and Bard Peripheral Vascular, Inc., United States District Court for the District of Delaware, C.A. No. 11-515-LPS-CJB, 2014 (Deposition).
Richard Noll and Rhythm Motor Sports, LLC v. eBay Inc., eBay Europe S.A.R.L., and eBay International AG, Inc., United States District Court for the Northern District of California, San Jose Division, Case No. 5:11-CV-04585-EJD, 2014 (Deposition).
PUBLIC VERSION Gregory K. Leonard Charles River Associates Page 12
Bristol-Myers Squibb Company v. Genentech Inc. and City of Hope, United States District Court for the Northern District of California, Western Division, Case No. 2:13‐CV‐05400‐MRP (JEMx), 2014 (Deposition).
Eli Lilly and ImClone v. Genentech Inc. and City of Hope, United States District Court for the Northern District of California, Western Division, Case No. 2:13-CV-07248-MRP, 2014 (Deposition).
Graftech International Ltd. and Graftech International Holdings Inc. F/K/A UCAR Carbon Company Inc. v. Carbone Savoie, Alcan France and Rio Tinto Alcan, International Chamber of Commerce, International Court of Arbitration, Case Ref.: 19798/AGF, 2014 (Hearing Testimony).
Samsung Electronics Co., Ltd. (Korea) v. Nokia Corporation (Finland), International Chamber of Commerce, International Court of Arbitration, Case Ref.: 19602/AGF/RD (c.19638/AGF), 2015 (Hearing Testimony).
In the Matter of CERTAIN NETWORK DEVICES, RELATED SOFTWARE, AND COMPONENTS THEREOF (I), before the United States International Trade Commission, Investigation No. 337-TA- 944, 2015 (Deposition).
Broadband iTV, Inc. v. Hawaiian Telecom, Inc., Oceanic Time Warner Cable, LLC, and Time Warner Cable, Inc., United States District Court for the District of Hawaii, Case No. 14-00169 ACK- RLP, 2015 (Deposition).
In the Matter of CERTAIN NETWORK DEVICES, RELATED SOFTWARE, AND COMPONENTS THEREOF (II), before the United States International Trade Commission, Investigation No. 337-TA- 945, 2015 (Deposition, Hearing Testimony).
Largan Precision Co., Ltd. v. Samsung Electronics Co., Ltd., et al., United States District Court, Southern District of California, Case No. 13-CV-2740 DMS (NLS), 2015 (Deposition).
Oracle America, Inc. v. Google, Inc., United States District Court, Northern District for California, Case No. 3:10-CV-03561-WHA, 2011 (Deposition), 2016 (Deposition, Trial Testimony).
SRI International, Inc. v. Cisco Systems, Inc., United States District Court for the District of Delaware, Case No. 13-1534 (SLR), 2016 (Deposition, Trial Testimony).
ChriMar Systems, Inc., et al. v. Cisco Systems, Inc., et al., United States District Court for the District of Northern California, Oakland Division, Case No. 4:13‐CV‐01300‐JSW, 2016 (Deposition).
TCL Communication Technology Holdings, LTD., et al., v. Telefonaktiebolaget LM Ericsson, et al., United States District Court for the Central District of California, Southern Division, Case No. SACV14−00341 JVS (DFMx), 2016-2017 (Deposition, Trial Testimony).
PUBLIC VERSION Gregory K. Leonard Charles River Associates Page 13
Chevron North America, Inc., Positec Tool Corporation, Positec USA, Inc. and Hilti, Inc. v. Milwaukee Electric Tool Corporation, United States Patent and Trademark Office Before the Patent Trial and Appeal Board, Case IPR2015-00595, Case IPR2015-00596, and Case IPR2015-00597, 2016 (Deposition).
Sanofi-Aventis U.S. LLC and Regeneron Pharmaceuticals, Inc. v. Genentech, Inc. and City of Hope, United States District Court, Central District of California, Western Division, Case No. 2:15-CV- 05685, 2016 (Deposition).
Irori Technologies, Inc. v. Procopio, Cory, Hargreaves & Savitc, LLP, and Eleanor Musick, JAMS Arbitration Reference No. 1240022033, 2016-2017 (Deposition, Hearing Testimony).
SD3, LLC and SawStop LLC v. Black and Decker (U.S.), Inc., et al., United States District Court for the Eastern District of Virginia, Civil Action No.: 1:14-CV-00191, 2016 (Deposition).
Intellectual Ventures II LLC v. Nextel Operations, Inc., Sprint Spectrum L.P., Boost Mobile LLC, and Virgin Mobile USA, L.P., United States District Court for the District of Delaware, Civil Action No. 13- CV-1635-LPS, 2016 (Deposition).
In Re Lidoderm Antitrust Litigation, United States District Court for the District of Northern California, Case No. 14-MD-02521-WHO, 2016 (Deposition).
The Dow Chemical Company, Dow Global Technologies Inc. and Dow Chemical Canada ULC v. Nova Chemicals Corporation, Federal Court of Canada, Federal Court File No.: T-2051-10, 2016 (Trial Testimony).
In the Matter of: Determination of Rates and Terms for Making and Distributing Phonorecords (Phonorecords III), before the Copyright Royalty Board Library of Congress, Docket No. 16-CRB- 0003-PR (2018-2022), 2017 (Deposition, Hearing Testimony).
Intel Corporation v. Future Link Systems, LLC, United States District Court for the District of Delaware, Civil Action No.: 14-377-LPS, 2017 (Deposition).
Joel Simkhai, et al. v. KL Grindr Holdings Inc. et al., American Arbitration Association, Case No. 01- 16-0003-7637, 2017 (Deposition).
In Re Capacitors Antitrust Litigation (Indirect), United States District Court for the District of Northern California, San Francisco Division, Case No. 3:14-CV-03264, 2017 (Deposition).
Evolved Wireless, LLC v. HTC Corporation and HTC America, Inc., United States District Court for the District of Delaware, Civil Action No. 15-543-SLR-SLF, 2017 (Deposition).
In Re Solodyn (Minocycline Hydrochloride) Antitrust Litigation, United States District Court for the District of Massachusetts, Case No. 1:14-md-02503, 2017 (Deposition).
PUBLIC VERSION Gregory K. Leonard Charles River Associates Page 14
Boston Scientific Corporation and Boston Scientific Scimed, Inc. v. Edwards Lifesciences Corporation; Edwards Lifesciences Corporation, Edwards Lifesciences PVT, Inc. and Edwards Lifesciences LLC v. Boston Scientific Corporation, Boston Scientific Scimed, Inc., and Sadra Medical, Inc., United States District Court for the District of Delaware, Case No. 16-CV-275 (SLR), 2017 (Deposition), 2018 (Trial Testimony).
Depomed, Inc. v. Purdue Pharma L.P., The P.F. Laboratories, Inc., and Purdue Pharmaceuticals L.P., United States District Court for the District of New Jersey, Civil Action No. 3:13-00571 (BRM/TJB), 2018 (Deposition).
Rembrandt Diagnostics, LP, v. Innovacon, Inc., United States District Court for the Southern District of California, Case No. 16-CV-00698 CAB (NLS), 2018 (Deposition).
Janssen Biotech, Inc. v. Celltrion Healthcare Co., Ltd., Celltrion, Inc., and Hospira, Inc., United States District Court for the District of Massachusetts, Civil Action No. 1:17-CV-11008, 2018 (Deposition).
SPEX Technologies, Inc. v. Apricorn, United States District Court for the Central District of California Southern Division, Case No. 2:16-CV-07349-JVS-AGR, 2018 (Deposition).
Huawei Technologies, Co., Ltd. et al. v. Samsung Electronics Co. Ltd., et al., United States District Court for the Northern District of California, San Francisco Division, Case No. 16-CV-02787-WHO, 2018 (Deposition).
Asustek Computer Incorporated, et al. v. InterDigital, Inc., et al., United States District Court for the Northern District of California, San Jose Division, Case No. 15-CV-1716 BLF, 2018 (Deposition).
Amgen Inc. v. Coherus Biosciences Inc., Superior Court of the State of California, County of Ventura, Case No. 56-2017-00493553-CU-VT-VTA, 2018 (Deposition).
Plexxikon Inc. v. Novartis Pharmaceuticals Corporation, United States District Court for the Northern District of California, Case No. 4:17-CV-04405-HSG (EDL), 2019 (Deposition).
Press Ganey Associates, Inc. v. Qualtrics, LLC, American Arbitration Association, Case No. 01-18- 0004-4674, 2019 (Deposition).
Professional activities
Member, American Economic Association
Member, Econometric Society
Member, American Bar Association
Contributor, www.antitrust.org
Contributor, ABA Section of Antitrust Law, Econometrics, 2005
PUBLIC VERSION Gregory K. Leonard Charles River Associates Page 15
Associate Editor, Antitrust, 2007-2010
Senior Editor, Antitrust Law Journal, 2012-; Associate Editor, 2010-2012
Co-Editor, ABA Section of Antitrust Law Economics Committee Newsletter, 2009-2012
Member, Economics Task Force, ABA Section of Antitrust Law, 2011-2012
Member, ABA Delegation to International Seminar on Anti-Monopoly Law: Procedure and Substantive Assessment in Merger Control, Beijing, People’s Republic of China, December 15-17, 2008.
Member, Working Group for drafting the “Joint Comments of the American Bar Association Section of Antitrust Law and Section of International Law on the MOFCOM Draft Guidelines for Definition of Relevant Markets,” 2009.
Member, Working Group for drafting the “Joint Comments of the American Bar Association Section of Antitrust Law and Section of International Law on the SAIC Draft Regulations on the Prohibition of Acts of Monopoly Agreements and of Abuse of Dominant Market Position,” 2009.
Member, Working Group for drafting the “Joint Comments of the American Bar Association Section of Antitrust Law and Section of International Law on the SAIC Draft Regulations on the Prohibition of Acts of Monopoly Agreements and of Abuse of Dominant Market Position,” 2010.
Referee: Econometrica, Review of Economics and Statistics, International Journal of Industrial Organization, Review of Industrial Organization, Journal of Sports Economics, Journal of Environmental Economics and Management, Research in Law and Economics, Labour Economics, Eastern Economic Journal, Journal of Forensic Economics, Antitrust, Antitrust Law Journal, Journal of Competition Law and Economics, Advances in Econometrics.
Professional history
12/2019–Present Vice President, Charles River Associates
2012–2019 Partner, Edgeworth Economics
2008–2012 Senior Vice President, NERA Economic Consulting
2004–2008 Vice President, NERA Economic Consulting
2000–2004 Senior Vice President, Lexecon, Inc.
1991–2000 Director, Cambridge Economics, Inc.
1990–1991 Senior Analyst, NERA Economic Consulting
1989–1990 Assistant Professor, Columbia University
Econometrics
Statistics
Labor Economics PUBLIC VERSION PUBLIC VERSION
7$% ' PUBLIC VERSION
Before the UNITED STATES COPYRIGHT ROYALTY BOARD LIBRARY OF CONGRESS Washington, D.C.
In the Matter of:
Determination of Rates and Terms for Digital Performance of Sound Recordings and Making of Ephemeral Copies to Docket No. 19-CRB-0005-WR (2021-2025) Facilitate those Performances (Web V)
WRITTEN REBUTTAL TESTIMONY OF PROFESSOR JOHN R. HAUSER January 10, 2020
NAB Written Rebuttal Statement Dkt. No. 19-CRB-0005-WR (2021-25) PUBLIC VERSION
Table of Contents
I. Introduction ...... 1 A. Qualifications ...... 1 B. Assignment ...... 1 II. Summary of Opinions ...... 2 III. Overview of the Zauberman Survey ...... 5 IV. Flaws in the Design of the Zauberman Survey Likely Lead to Overestimates of Switching to New, Paid Music Subscriptions ...... 10 A. The Zauberman Survey Likely Caused Respondents to Indicate They Would Switch to New Subscriptions to Paid Services Instead of Switching to Their Existing Subscriptions to Paid Services ...... 10 B. The Switching Question in the Zauberman Survey Likely Biased Responses Toward Music Options and Away from the Non-Music Option ...... 14 C. The Zauberman Survey Did Not Include Attention Checks to Verify That Respondents Were Engaged in the Survey and Provided Reliable and Accurate Answers to the Survey Questions ...... 16 V. The Zauberman Survey Cannot Reliably Measure the Switching Behavior of Listeners of Internet Simulcasts of Terrestrial Commercial Radio and Listeners of Sirius XM Over the Internet ...... 19 VI. The Limited Number of Response Options in the Zauberman Survey Prevented Respondents from Making Distinctions between Different Types of Listening ...... 23 VII. The Zauberman Survey Does Not Estimate How Current Listeners of Streaming Radio Services Would Allocate Their Listening Time Across Replacement Music-Listening Options ...... 26 VIII. Between the Hauser Survey and the Zauberman Survey, Only the Hauser Survey Can Be Used to Measure Switching Behavior of Listeners of Internet Simulcasts of Terrestrial Commercial Radio ...... 27 A. The Zauberman Survey and the Hauser Survey Differ in How They Elicit Switching Behavior, Which May Have Caused the Results of the Zauberman Survey and the Hauser Survey to Differ ...... 28 B. The Results of the Zauberman Survey and the Hauser Survey, While Different in Magnitude, Are Directionally Similar and Only the Hauser Survey Provides Valid Estimates for the Switching Behavior of Listeners of Internet Simulcasts of Terrestrial Commercial Radio ...... 30 IX. Summary ...... 33
NAB Written Rebuttal Statement Dkt. No. 19-CRB-0005-WR (2021-25) PUBLIC VERSION
I. Introduction
A. Qualifications
1. I am the Kirin Professor of Marketing at the Massachusetts Institute of Technology (“MIT”) Sloan School of Management. I previously submitted a report (the “Hauser Report”) on September 23, 2019 in the Web V proceedings that has the details of my qualifications.1 As part of that report, I conducted a survey of listeners of Internet simulcasts of terrestrial commercial radio (the “Hauser Survey”).2 2. My curriculum vita reflecting updates since the Hauser Report was submitted on September 23, 2019 is attached as Appendix A, and my testimony at deposition or trial within the last five years is attached as Appendix B.
B. Assignment
3. I have been asked by Latham & Watkins, counsel for the National Association of Broadcasters (“NAB”), and Weil, Gotshal & Manges, counsel for Sirius XM and Pandora, to evaluate the survey conducted by Professor Gal Zauberman (the “Zauberman Survey”) and written direct testimony submitted by Professor Zauberman (the “Zauberman Report”).3 4. In undertaking this assignment, I utilized my extensive expertise in developing, testing, and analyzing surveys, as well as my experience in interpreting qualitative and quantitative research about consumer attitudes, intentions, and behavior. I include, as Appendix C to this report, a list of materials I have relied upon to date in connection with this particular assignment. To the extent that I review additional information after this report is submitted, I will supplement this list.
1 Written Direct Testimony of Professor John R. Hauser, September 20, 2019 (“Written Direct Testimony of Professor John R. Hauser”), ¶¶ 1–5. 2 Written Direct Testimony of Professor John R. Hauser. 3 Written Direct Testimony of Gal Zauberman, September 20, 2019 (“Written Direct Testimony of Gal Zauberman”).
1 NAB Written Rebuttal Statement Dkt. No. 19-CRB-0005-WR (2021-25) PUBLIC VERSION
II. Summary of Opinions
5. Professor Gal Zauberman designed and administered an online survey “to measure the music-listening behavior of listeners to Streaming Radio services”4 and to determine “how they would listen to music if their Streaming Radio services were no longer available.”5 I opine that the results of the Zauberman Survey cannot be used to reliably estimate such switching behavior. Flaws in the design of the Zauberman Survey likely lead to overestimates of switching to new, paid music subscriptions. The Zauberman Survey also suffers from at least three additional flaws. First, the design of the Zauberman Survey prevents it from reliably estimating the switching behavior of listeners of Internet simulcasts of terrestrial commercial radio and listeners of Sirius XM over the Internet in particular. Second, the Zauberman Survey offered limited response options, which prevented respondents from making distinctions between different types of music listening. Third, the design of the Zauberman Survey renders it incapable of achieving one of its stated goals. As a result of the flaws in the design of the Zauberman Survey, and other differences between the Hauser Survey and the Zauberman Survey, only the Hauser Survey can be used to measure the switching behavior of listeners to Internet simulcasts of terrestrial radio. 6. The design of the Zauberman Survey likely overestimates switching to new, paid music subscriptions in at least three ways. First, the Zauberman Survey asked respondents, in Q1, to recall their behavior over thirty days, and then limited subsequent questions based on respondent recall over that time period. If a respondent indicated that he or she listened to an existing paid on-demand streaming service in the last thirty days in Q1, the respondent was presented with the option to switch to the respondent’s existing paid on-demand streaming service in Q2. Alternatively, if the respondent indicated that he or she did not listen to a paid on-demand streaming service in the last thirty days in Q1, the respondent was only presented with the option to subscribe to a (new) paid on-demand streaming service in Q2. That is, the respondent was not given the option of listening to a paid on-demand streaming service to which the respondent already subscribed. Paid streaming radio services and Sirius XM satellite radio service were also treated in this manner. This survey design is problematic, because research shows that survey respondents may have difficulty recalling emotionally neutral or routine events, and events that
4 Written Direct Testimony of Gal Zauberman, ¶ 12. 5 Written Direct Testimony of Gal Zauberman, ¶ 19. 2 NAB Written Rebuttal Statement Dkt. No. 19-CRB-0005-WR (2021-25) PUBLIC VERSION
are not recent. There is no indication that the Zauberman Survey was pretested to determine if the thirty-day window used was too long for respondents to recall their listening behavior, while insights from the Hauser Survey pretests suggest that respondents would have difficulty remembering their listening behavior accurately over a period of time longer than three days. In addition, the Zauberman Survey cannot distinguish between a respondent who did not have an existing paid subscription and a respondent who did have an existing paid subscription but either did not use it or did not remember using it in the prior thirty days. Both types of respondents are likely to select (and were in fact only presented the choice of selecting) a new paid subscription in Q2 of the Zauberman Survey. This lack of realistic options would result in an upward bias in estimated switching to new, paid subscriptions. There is no way to assess the extent of this upward bias in the Zauberman Survey. 7. Second, the specific instructions in Q2 of the Zauberman Survey asked respondents “which of the following music-listening option(s)” (emphasis added) the respondents would use as substitutes for listening to music with a free (paid) streaming radio service.6 Although Q2 of the Zauberman Survey did provide respondents with an option to “do something other than listen to music,” that does not entirely mitigate the explicit instruction to focus on music-listening options.7 This explicit instruction may have suggested to respondents that the researcher was interested only in switching to music-listening options, thus prompting respondents to favor music-listening options relative to “do[ing] something other than listen[ing] to music.”8 Further, the non-music option was not described in any detail, in contrast to the Hauser Survey and the surveys conducted by Professor Dominique Hanssens (the “Hanssens Surveys”). Providing more specific information about “do something other than listen to music” may have been especially informative to respondents who listen to non-music content. Based on results of the Hauser Survey, many listeners of Internet simulcasts listen to, and consider as important, the non-music content available on such simulcasts. In the absence of specificity about what “do something other than listen to music” might entail, respondents may not have immediately known, recalled, or considered alternatives that were available to them if they were not listening to music, leading them to select music-listening options instead.
6 Written Direct Testimony of Gal Zauberman, Appendix D, Q2. 7 Written Direct Testimony of Gal Zauberman, Appendix D, Q2. 8 Written Direct Testimony of Gal Zauberman, Appendix D, Q2. 3 NAB Written Rebuttal Statement Dkt. No. 19-CRB-0005-WR (2021-25) PUBLIC VERSION
8. Third, the Zauberman Survey did not include any attention checks or other ways to confirm that respondents paid sufficient attention to the questions and the scenarios. Attention checks represent best practices in survey research and address the relevant issue that some panelists may focus more on the rewards for completing a survey than on providing accurate answers. Attention check questions are used in both the Hauser Survey and the Hanssens Surveys, and respondents in each of the surveys were removed if they failed the attention checks. Because the Zauberman Survey did not use attention checks, the results of the Zauberman Survey may not accurately reflect what respondents would do if free or paid streaming radio services were unavailable. Respondent inattention could have exacerbated the flaws cited above, further biasing the Zauberman Survey toward overestimating switching to paid, music-listening options to the extent that inattentive respondents did not reflect carefully about their music- listening habits over the past thirty days, or only indicated switching to music-listening options because of the explicit instruction to focus on music-listening options. 9. The Zauberman Survey suffers from at least three additional flaws. First, the design of the Zauberman Survey prevents it from being used to reliably measure the switching behavior of listeners of Internet simulcasts of terrestrial commercial radio, or the switching behavior of listeners of Sirius XM over the Internet. The Hauser Survey was specifically designed to estimate the switching behavior of listeners of Internet simulcasts of terrestrial commercial radio if such simulcasts were no longer available. In contrast, the Zauberman Survey’s “free hypothetical” scenario is unable to shed light on the switching behavior of this population because the hypothetical provided in the Zauberman Survey is overly broad, and because the Zauberman Survey’s free hypothetical scenario did not specifically identify and study the population of listeners of Internet simulcasts of terrestrial commercial radio. Results from the Hauser Survey suggest that it is unlikely that listeners of Internet simulcasts of terrestrial commercial radio would exhibit the same switching behavior as listeners of other free streaming radio services. Similarly, the Hanssens Sirius XM Survey was specifically designed to estimate how the listening habits of subscribers of Sirius XM over the Internet would change following a service degradation.9 In contrast, the Zauberman Survey’s “paid hypothetical” scenario included
9 Written Direct Testimony of Dominique M. Hanssens, September 23, 2019 (“Written Direct Testimony of Dominique M. Hanssens”), ¶¶ 13, 60. 4 NAB Written Rebuttal Statement Dkt. No. 19-CRB-0005-WR (2021-25) PUBLIC VERSION
among its respondents subscribers to services such as Pandora Plus, which I understand from counsel include features that are not covered under the statutory license. As a result, the Zauberman Survey’s paid hypothetical scenario is unable to shed light on the switching behavior of subscribers to paid streaming radio services that operate under the statutory license at issue in this proceeding, let alone subscribers to Sirius XM over the Internet specifically. 10. Second, the Zauberman Survey offered limited response options in its switching question (Q2), which prevented respondents from making distinctions between different types of music listening. 11. Third, the design of the Zauberman Survey renders it incapable of achieving one of its stated goals, to “assess how current listeners of Streaming Radio services would allocate their listening time across the replacement music-listening options they selected.”10 12. Despite the flaws in the Zauberman Survey, and additional differences between the Hauser Survey and the Zauberman Survey in how each survey elicits switching behavior, the results of the two surveys are directionally similar to one another. Only the Hauser Survey measured the switching behavior of listeners of Internet simulcasts of terrestrial commercial radio if such simulcasts were no longer available. As a result, only the Hauser Survey provides valid estimates for the switching behavior of listeners of Internet simulcasts of terrestrial commercial radio.
III. Overview of the Zauberman Survey
13. Professor Gal Zauberman designed and administered an online survey “to measure the music-listening behavior of listeners to Streaming Radio services”11 and determine “how they would listen to music if their Streaming Radio services were no longer available.”12 The Zauberman Survey targeted U.S. residents ages 16 and older who, in the past thirty days, listened to at least one free or paid Streaming Radio service, defined as follows:13
A FREE streaming radio service, such as personalized radio services like free Pandora and free iHeart Radio, and online steams of AM/FM radio
10 Written Direct Testimony of Gal Zauberman, ¶ 14. 11 Written Direct Testimony of Gal Zauberman, ¶ 12. 12 Written Direct Testimony of Gal Zauberman, ¶ 19. 13 Written Direct Testimony of Gal Zauberman, ¶ 36.
5 NAB Written Rebuttal Statement Dkt. No. 19-CRB-0005-WR (2021-25) PUBLIC VERSION
stations, where you cannot choose a specific song, and must listen to advertisements.14
A PAID streaming radio service, such as Pandora Plus, iHeart Radio Premium, and Rhapsody unRadio, where you can listen to customized radio stations commercial free, but cannot choose a specific song, at a price of approximately $4.99 per month. (This option includes Sirius XM streamed over the internet or on a phone, but not on a satellite receiver.)15 14. Prior to Q1 of the Zauberman Survey, after answering initial screening questions, respondents who selected that they listen to “music streamed through an app or website” were asked to read descriptions of seven ways they could listen to music.16 The seven ways of listening to music were:17
A PAID on-demand streaming service, such as Spotify Premium, Apple Music, YouTube Premium, and Amazon Music, where you can choose the specific songs you want to hear on-demand and/or listen to playlists, all commercial free, at a price of approximately $9.99 per month.
A FREE on-demand streaming service, such as free Spotify and free YouTube, where you can choose the specific songs you want to hear on- demand and/or listen to playlists, but must listen to advertisements.
A PAID streaming radio service, such as Pandora Plus, iHeart Radio Premium, and Rhapsody unRadio, where you can listen to customized radio stations commercial free, but cannot choose a specific song, at a price of approximately $4.99 per month. (This option also includes Sirius XM streamed over the internet or on a phone, but not on a satellite receiver.)
A FREE streaming radio service, such as personalized radio services like free Pandora and free iHeart Radio, and online streams of AM/FM radio stations, where you cannot choose a specific song, and must listen to advertisements.
Sirius XM satellite radio on a satellite receiver in your car, home or somewhere else, at a price of approximately $10.99 to $20.99 per month. (This option does not include Sirius XM streamed over the internet or on a phone.)
14 Written Direct Testimony of Gal Zauberman, Appendix D, S7, Q1 (emphasis in original). 15 Written Direct Testimony of Gal Zauberman, Appendix D, S7, Q1 (emphasis in original). As discussed below, several of these services offer features (e.g., unlimited skips and station caching) that go above and beyond the functionality that I understand from counsel is allowed under the statutory license at issue in this proceeding. I am not offering a legal opinion as to whether a particular service or feature is included under the statutory license at issue in this proceeding. I understand from counsel that services included under the statutory license include both paid and free streaming radio stations over the Internet where listeners cannot choose a specific song. 16 Written Direct Testimony of Gal Zauberman, Appendix D, S6, S7. 17 Written Direct Testimony of Gal Zauberman, Appendix D, S7.
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AM/FM radio on a traditional radio receiver. (This option does not include AM/FM radio streamed over the internet or on a phone.)
CDs, vinyl records, or MP3 files that you own.18 After reading the descriptions respondents were asked the following question in Q1:
In the past 30 days, which of the following music-listening options have you used to listen to music?19 For each of the seven ways of listening, respondents were asked to select “yes,” “no,” or “unsure.”20 15. Next, respondents were randomized into one of two hypothetical scenarios, independently of whether they had used free streaming radio, paid streaming radio, or both in the past thirty days.21 In one scenario (the “free hypothetical” scenario), respondents were asked to assume that free streaming radio services were no longer available:22
You indicated that you use a FREE streaming radio service. Imagine that all FREE streaming radio services were no longer available.23 In the other scenario (the “paid hypothetical” scenario), respondents were asked to assume that paid streaming radio services were no longer available:24
You indicated that you use a PAID streaming radio service. Imagine that all PAID streaming radio services were no longer available.25 16. In Q2 (the “Zauberman switching question”), respondents were then asked the following question, which was tailored to the hypothetical scenario (i.e., free hypothetical or paid hypothetical) to which they were assigned:
18 Written Direct Testimony of Gal Zauberman, Appendix D, S7. 19 Written Direct Testimony of Gal Zauberman, Appendix D, Q1. 20 Written Direct Testimony of Gal Zauberman, Appendix D, Q1. 21 Written Direct Testimony of Gal Zauberman, ¶ 50, Appendix D, Q1. If a respondent selected “unsure” to one or more music-listening options in Q1, then the respondent was terminated before this randomization. If, in Q1, a respondent selected neither free streaming radio nor paid streaming radio, then the respondent was terminated after this randomization. See Written Direct Testimony of Gal Zauberman, Appendix D, Q1, Appendix F, Table F-2. 22 Written Direct Testimony of Gal Zauberman, ¶ 50. If a respondent was assigned to the scenario where free streaming radio services were no longer available, but did not select “free streaming radio” in Q1, the respondent was terminated. See Written Direct Testimony of Gal Zauberman, n.18, ¶ 50, Appendix F, Table F-2. 23 Written Direct Testimony of Gal Zauberman, Appendix D, pp. 58–59. 24 Written Direct Testimony of Gal Zauberman, ¶ 50. If a respondent was assigned to the scenario where paid streaming radio services were no longer available, but did not select “paid streaming radio” in Q1, the respondent was terminated. See Written Direct Testimony of Gal Zauberman, n.18, ¶ 50, Appendix F, Table F-2. 25 Written Direct Testimony of Gal Zauberman, Appendix D, pp. 58–59.
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If you could no longer listen to music with a [FREE or PAID] streaming radio service(s), which of the following music-listening option(s) would you now use instead during that time?26 Respondents were asked to indicate “yes,” “no,” or “unsure” for each of the remaining six music-listening options that were not eliminated by the hypothetical, as well as a seventh option to “do something other than listen to music.”27 For music-listening options that require paid subscriptions, the specific wording seen by a respondent in Q2 depended on the respondent’s selections in Q1.28 For other music-listening options, such as “Listen to CDs, vinyl records, or MP3 files that you currently own or would purchase,” all respondents saw the same wording.29 The survey terminated after Q2 for respondents who selected “no” for all free streaming service options in Q2 or “yes” for one free streaming service option, but “no” for all other options in Q2.30 The survey terminated for respondents who selected “unsure” for any options in Q2.31
26 Written Direct Testimony of Gal Zauberman, Appendix D, Q2 (emphasis in original). 27 Written Direct Testimony of Gal Zauberman, Appendix D, Q2. 28 Written Direct Testimony of Gal Zauberman, Appendix D, Q2. The wordings of paid music-listening options were adaptive to a respondent’s selections in Q1. For example, a respondent who answered “yes” to “Sirius XM satellite radio on a satellite receiver in your car, home or somewhere else, at a price of approximately $10.99 to $20.99 per month. (Please do not select this option if you only stream Sirius XM over the internet or on a phone.)” in Q1 was presented with the option “Listen to your Sirius XM satellite radio service and listen on a satellite receiver in your car, home or somewhere else (but not streamed over the internet).” A respondent who answered “no” to “Sirius XM satellite radio on a satellite receiver in your car, home or somewhere else, at a price of approximately $10.99 to $20.99 per month. (Please do not select this option if you only stream Sirius XM over the internet or on a phone.)” in Q1 was presented with the option “Subscribe to Sirius XM satellite radio and listen on a satellite receiver in your car, home or somewhere else (but not streamed over the internet) at a price of approximately $10.99 to $20.99 per month.” Likewise, the wordings of the paid streaming radio and paid on- demand streaming service options were adaptive to a respondent’s selections in Q1. See Written Direct Testimony of Gal Zauberman, Appendix D, Q2 (emphasis in original). 29 Written Direct Testimony of Gal Zauberman, Appendix D, Q2 (emphasis in original). The wordings of free music-listening options (free on-demand streaming, free streaming radio, and AM/FM radio on a traditional radio receiver) were also not adaptive to a respondent’s selections in Q1. See Written Direct Testimony of Gal Zauberman, Appendix D, Q2. 30 Written Direct Testimony of Gal Zauberman, ¶ 58. The survey terminated for respondents who did not select at least one free streaming service. Free streaming services include free streaming radio (for respondents assigned to the paid hypothetical) and free on-demand streaming services. See Written Direct Testimony of Gal Zauberman, ¶ 58, Appendix D, Q2. Note that the logic in the Zauberman Survey is somewhat ambiguous. The Zauberman Report states, “Following Q2, the survey concluded for (i) respondents who answered “Unsure” to any of the music- listening options, and (ii) respondents who answered “Yes” to only one free streaming service and “No” to all other options.” However, Appendix D of the Written Direct Testimony of Gal Zauberman contains “programming notes” and indicates “Terminate (status = 1) if respondent answers unsure to one or more options in Q2” and “Respondent qualifies for Q3 if they answer yes to free streaming radio and/or free on-demand streaming. Disqualified if they answer unsure to any of the options.” Thus, it is unclear whether a respondent who answered “yes” to only free streaming radio (or free on-demand streaming), but “no” to all other options would terminate after Q2 or would qualify for Q3. See Written Direct Testimony of Gal Zauberman, ¶ 58, n.36, Appendix D, p. 60 (emphasis in original). 31 Written Direct Testimony of Gal Zauberman, ¶ 58.
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17. Respondents who selected “yes” for two or more options, at least one of which was the free streaming radio service option or the free on-demand streaming service option, were asked up to two additional questions.32 In Q3, respondents were asked to switch back to the scenario in which “all music-listening options were still available,” including the free or paid streaming radio service to which they listened.33 Respondents were prompted as follows:
Please think about the amount of time you would expect to listen to your [FREE or PAID] streaming radio service(s) on [INSERT DOW] of next week if all music- listening options were still available.
Would you expect to listen to your [FREE or PAID] streaming radio service(s) on [INSERT DOW] of next week?34 “DOW” refers to the “day of the week.”35 That is, if a respondent were taking the survey on a Tuesday, Q3 would have asked that respondent to indicate his or her expectations for listening to free or paid streaming radio service(s) on the Tuesday of the next week. The survey terminated for respondents selecting “no” or “unsure” in response to Q3.36 18. Respondents who selected “yes” in response to this question were then asked a “time allocation” question, Q3A.37 Respondents were asked to switch back again to assuming that all “[FREE or PAID] streaming radio service(s) were no longer available.”38 Respondents were then prompted as follows:
Please allocate the time you would have listened to your [FREE or PAID] streaming radio service(s) on [INSERT DOW] next week by indicating the percentage of time you would listen to each of the options you would use instead.39 19. After answering this question, the survey terminated for all remaining respondents.
32 Written Direct Testimony of Gal Zauberman, ¶ 59. 33 Written Direct Testimony of Gal Zauberman, Appendix D, Q3. 34 Written Direct Testimony of Gal Zauberman, ¶ 60, Appendix D, Q3 (emphasis in original). 35 Written Direct Testimony of Gal Zauberman, ¶ 61. 36 Written Direct Testimony of Gal Zauberman, ¶ 63. 37 Written Direct Testimony of Gal Zauberman, ¶ 64, Appendix D, p. 61. 38 Written Direct Testimony of Gal Zauberman, ¶¶ 55, 64, Appendix D, Q3A (emphasis in original). 39 Written Direct Testimony of Gal Zauberman, ¶ 64, Appendix D, Q3A (emphasis in original).
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IV. Flaws in the Design of the Zauberman Survey Likely Lead to Overestimates of Switching to New, Paid Music Subscriptions
A. The Zauberman Survey Likely Caused Respondents to Indicate They Would Switch to New Subscriptions to Paid Services Instead of Switching to Their Existing Subscriptions to Paid Services
20. The Zauberman Survey asked respondents, in Q1, to recall their behavior over thirty days, and then limited subsequent questions based on respondent recall over that time period.40 Specifically, respondents were asked to recall whether, during those thirty days, they listened to music using paid on-demand streaming, free on-demand streaming, paid streaming radio, free streaming radio, Sirius XM satellite radio,41 AM/FM radio, or CDs, vinyl records, or MP3 files.42 21. The respondent’s selections in Q1 dictated the response options the respondent was shown and could select in Q2. If a respondent indicated that he or she listened to an existing paid on-demand streaming service in the last thirty days in Q1, the respondent was presented with the option to switch to the respondent’s existing paid on-demand streaming service in Q2. Alternatively, if the respondent indicated that he or she did not listen to a paid on-demand streaming service in the last thirty days in Q1, the respondent was presented with the option to subscribe to a (new) paid on-demand streaming service in Q2; the option to switch to an existing subscription service was not offered. Similarly, if the respondent indicated that he or she listened to an existing paid streaming radio service in the last thirty days in Q1, the respondent was presented with the option to switch to the respondent’s existing paid streaming radio service. And, again, if the respondent indicated that he or she did not listen to a paid streaming radio service in the last thirty days in Q1, the respondent was presented with the option to subscribe to a (new) paid radio streaming service (in the free hypothetical). The Sirius XM satellite radio service was also treated in this manner.43
40 Written Direct Testimony of Gal Zauberman, Appendix D, Q1. 41 In the Written Direct Testimony of Professor John R. Hauser and the Hauser Survey, I refer to “SiriusXM.” Because the Zauberman Report and the Zauberman Survey refer to “Sirius XM,” I write “Sirius XM” in this report for consistency and to avoid confusion. Across my reports, both “Sirius XM” and “SiriusXM” refer to the same entity. See Written Direct Testimony of Professor John R. Hauser; Written Direct Testimony of Gal Zauberman. 42 Written Direct Testimony of Gal Zauberman, Appendix D, Q1. 43 Written Direct Testimony of Gal Zauberman, Appendix D, Q2.
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22. This survey design is problematic in two respects. First, a respondent who actually had a paid subscription to an on-demand streaming service, paid streaming radio service, or Sirius XM satellite radio service but did not listen to this service in the past thirty days would not have been presented with the option of switching to the respondent’s existing subscription to a paid on- demand streaming service, paid streaming radio service, or Sirius XM satellite radio service, respectively, in Q2.44 A respondent may not have listened to an existing paid subscription in the last thirty days for several reasons. For example, the respondent may have listened to free or paid radio options or podcasts in the last thirty days instead. Or the respondent may not have listened to an existing paid subscription within the past thirty days because the respondent was trying out a different paid service. But in each of these cases the respondent would have only been presented in the next question with the option to “subscribe to a paid on-demand streaming service” or “subscribe to Sirius XM satellite radio,” and therefore could not have opted to switch to his or her existing paid on-demand streaming service or Sirius XM satellite radio service even if the respondent had a paid subscription and wished to do so. In other words, the Zauberman Survey assumed that respondents did not have paid subscriptions at all, if they indicated that they have not listened to a paid subscription in the last thirty days. This question could lead to a pattern of responses that falsely inflates the number of respondents who indicate they would have subscribed to a new paid on-demand streaming service, paid streaming radio service, or Sirius XM satellite radio service if the respondent could no longer listen to music via streaming radio services. 23. Second, even if a respondent actually did listen to a paid subscription to an on-demand streaming service, a paid subscription to a streaming radio service, or a subscription to a Sirius XM satellite radio service during the past thirty days, the respondent might not have remembered that he or she did so. As a result, for similar reasons outlined above, the design of the Zauberman Survey inflates the number of respondents in the Zauberman Survey who would be counted as purchasing new paid subscriptions.
44 The paid streaming radio service option was only available in the free hypothetical scenario, as the option was by definition unavailable in the paid hypothetical scenario, because the paid hypothetical was testing the unavailability of such services. Written Direct Testimony of Gal Zauberman, Appendix D, Q2.
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24. Accurate recall depends on how unusual the activity or event is that an individual is attempting to recall. Research shows that it is difficult to recall the details of activities that are emotionally neutral, or routine, in nature.45 For example, on a typical day, a commuter may have difficulty remembering the details of his or her commute even shortly after arriving at his or her destination. This is even more difficult if the time period requiring recall is longer, such as the past thirty days. Because listening to music is a routine, frequent activity and music listeners frequently use or subscribe to multiple music-listening services,46 respondents to the Zauberman Survey may not have accurately remembered every way they listened to music over the prior thirty days. When asked about the details of their listening, respondents would have been more likely to report activities they do often, such as listening to a particular option frequently, and may have forgotten activities that they do not do frequently. If the Zauberman Survey were only seeking a census of the current frequencies of listening across respondents, this flaw would have a minor effect. However, the Zauberman Survey was focused on respondents’ hypothetical switching behavior contingent on an option not being available. The Zauberman Survey’s dependence on respondents’ ability to recall the details of their music listening, regardless of frequency over a thirty-day period, means that the Zauberman Survey may have removed from consideration an option that the respondent had available and would likely have chosen under the hypothetical situation, even if this option were only chosen infrequently in the normal course of listening. 25. Accurate recall also depends on the recency of the occurrence.47 Experiments on autobiographical memory demonstrate that the most recent event in a series of events is more readily available in people’s memory and therefore is easier to recall.48 For example, if a respondent listened to a free on-demand streaming service two days ago and a paid on-demand
45 Buchanan, Tony W., “Retrieval of Emotional Memories,” Psychological Bulletin Journal 133, 5, 2007, pp. 761– 779, at p. 765. 46 According to Morgan Stanley Research, many individuals use multiple music-listening services. For example, based on 2018 data, of all Apple Music users, 37 percent also used Sirius XM, 36 percent also used Amazon Unlimited, and 49 percent also used Spotify. Further, of all Sirius XM users, 26 percent also used Amazon Unlimited, 35 percent also used Spotify, and 22 percent also used Apple Music. See Morgan Stanley, “5th Annual Music & Radio Survey,” January 10, 2019, at p. 13. 47 Aaker, David A., V. Kumar, and George S. Day, Marketing Research, Fifth Edition, John Wiley & Sons, Inc., 1995, at p. 203. 48 Bradburn, Norman M., Lance J. Rips, and Steven K. Shevell, “Answering Autobiographical Questions: The Impact of Memory and Inference on Surveys,” Science 236, 4798, 1987, pp. 157–161, at p. 158.
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streaming service twenty-nine days ago, the respondent may only recall having listened to the free on-demand streaming service. Longer reference periods, such as thirty days in the Zauberman Survey, increase a respondent’s burden to perform a recall task, thereby likely reducing the accuracy of the survey responses.49 When asked about routine behavior, respondents may not remember the specifics of their behavior over longer periods of time, and may instead report “generic” or “usual” behavior.50 Thus, if a respondent does not listen frequently to a paid service the respondent already subscribes to, the respondent may not remember listening to the paid service in the past thirty days. The flaw in the Zauberman Survey is that if such a respondent did not report listening to the respondent’s paid service in the past thirty days, the respondent would not have been offered the option to switch to the respondent’s existing paid service, and may inaccurately have indicated that he or she would have subscribed to a new paid service in Q2. 26. The Zauberman Report states that “the survey questions and description of all alternatives were pretested.”51 Pretesting a survey is a standard practice to determine whether a small sample of “the same type of respondents who would be eligible to participate in the full-scale survey” can accurately answer the questions posed to them in a survey.52 There is no indication, however, that the Zauberman Survey was pretested to determine if the thirty-day window was too long for respondents to recall their music-listening behavior. By contrast, the Hauser Survey pretests revealed that periods longer than three days would be too long for respondents to remember their own listening behavior accurately.53 Given that the recall task is similar for the respective target populations in the two surveys,54 the insights from the Hauser Survey pretests suggest that respondents would have difficulty remembering their listening behavior accurately
49 Krosnick, Jon A. and Stanley Presser, “Question and Questionnaire Design,” in Handbook of Survey Research, Second Edition, Bingley, U.K.: Emerald Group Publishing Limited, 2010, pp. 263–313, at p. 289. 50 Tourangeau, Roger, Lance J. Rips, and Kenneth Rasinski, The Psychology of Survey Response, Tenth Edition, New York, NY: Cambridge University Press, 2009, at pp. 69–70. 51 Written Direct Testimony of Gal Zauberman, ¶ 30. 52 Diamond, Shari S., “Reference Guide on Survey Research,” in Reference Manual on Scientific Evidence, Third Edition, Washington, D.C.: Federal Judicial Center and National Research Council of the National Academies, 2011, pp. 359–423, available at https://www fjc.gov/content/reference-guide-survey-research-2, at pp. 388–389; Written Direct Testimony of Professor John R. Hauser, ¶ 58. 53 Written Direct Testimony of Professor John R. Hauser, ¶ 28. 54 Written Direct Testimony of Professor John R. Hauser, Appendix D, QS10; Written Direct Testimony of Gal Zauberman, Appendix D, Q1. 13 NAB Written Rebuttal Statement Dkt. No. 19-CRB-0005-WR (2021-25) PUBLIC VERSION
over a window that is ten times as long as the three days found to be reliable in the Hauser Survey pretests. 27. In sum, the Zauberman Survey cannot distinguish between a respondent who did not have an existing paid subscription and a respondent who did have an existing paid subscription, but either did not use it or did not remember using it in the prior thirty days. The inability to distinguish these different scenarios is likely to result in an upward bias in estimated switching to new, paid subscriptions. There is no way to assess the extent of this upward bias in the Zauberman Survey. The Zauberman Survey could have avoided this upward bias if it had not removed options from Q2 based on lengthy recall or just because an option that might have been available was not used in the past thirty days. Furthermore, the Zauberman Survey should have presented respondents with a complete set of options in Q2 (i.e., separate options for switching to an existing subscription of a paid on-demand streaming service and switching to a new subscription of a paid on-demand streaming service), as was done in the Hauser Survey.55
B. The Switching Question in the Zauberman Survey Likely Biased Responses Toward Music Options and Away from the Non-Music Option
28. Q2 of the Zauberman Survey asked respondents “which of the following music-listening option(s)” (emphasis added) the respondents would use as substitutes for listening to music with a free (paid) streaming radio service.56 Although Q2 of the Zauberman Survey did provide respondents with an option to “do something other than listen to music,” this option does not entirely mitigate the explicit instruction to focus on music-listening options.57 The explicit instruction to focus on music-listening options may have encouraged respondents to indicate that they would substitute to music-listening options. In particular, that explicit instruction may have suggested to respondents that the researcher was interested only in respondents switching to
55 Written Direct Testimony of Professor John R. Hauser, Appendix D, Q4. While the Hanssens Surveys always allow a respondent to switch to a new paid subscription, the Hanssens Surveys only allow the respondent to switch to an existing service if the respondent indicated listening to an existing service in the last seven days. Similar to the bias in the Zauberman Survey, this could lead to a downward bias in the number of respondents who choose an existing service and an upward bias in the number of respondents who choose a new paid subscription. However, I understand from counsel that, based on other expert reports submitted in this case, this bias works in SoundExchange’s favor. Written Direct Testimony of Dominique M. Hanssens, Appendix 6, P30, Appendix 12, X30; SXMWEBV_00005909. 56 Written Direct Testimony of Gal Zauberman, Appendix D, Q2. 57 Written Direct Testimony of Gal Zauberman, Appendix D, Q2.
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music-listening options, thus prompting respondents to favor music-listening options relative to “do[ing] something other than listen[ing] to music.”58 The Zauberman Report claims that “no demand artifacts were present,”59 i.e., no aspects of the survey procedure were detected that would influence the research results.60 However, it is still possible that this bias toward music options was undetected in pretesting. 29. Moreover, the Zauberman Survey did not describe the “do something other than listen to music” option in any detail. By contrast, the Hauser Survey and Hanssens Surveys offered specific non-music options for respondents to consider, such as watching video content, or reading print or online content.61 Providing more specific information about “do something other than listen to music” may have been especially informative to respondents who listen to non- music content. For example, Internet simulcasts of terrestrial commercial radio include non- music content such as news, weather, and traffic, sports, talk, and comedy. Based on results of the Hauser Survey, many listeners of Internet simulcasts listen to, and consider as important, the non-music content available on such simulcasts.62 In the absence of specificity about what “do something other than listen to music” might entail, respondents may not have immediately known, recalled, or considered alternatives that were available to them if they were not listening to music. As a result, respondents may have been more inclined to choose the more specific and more clearly-stated music-listening options than to choose the “do something other than listen to music” option. 30. It is difficult to test the extent to which the instructions in the Zauberman Survey biased respondents. For example, in the Hauser Survey, recognizing the well-established consider-then- choose paradigm,63 respondents were asked which options they would consider (Q4) and then the
58 Written Direct Testimony of Gal Zauberman, Appendix D, Q2. 59 Written Direct Testimony of Gal Zauberman, ¶ 30. 60 Demand artifacts are analogous to leading questions asked to a witness during testimony. For a discussion of demand artifacts, see, e.g., Sawyer, Alan G., “Demand Artifacts in Laboratory Experiments in Consumer Research,” Journal of Consumer Research 1, 4, 1975, pp. 20–30; Shimp, Terence A., Eva M. Hyatt, and David J. Snyder, “A Critical Appraisal of Demand Artifacts in Consumer Research,” Journal of Consumer Research 18, 3, 1991, pp. 273–283. 61 Written Direct Testimony of Professor John R. Hauser, Appendix D, Q4; Written Direct Testimony of Dominique M. Hanssens, Appendix 6, P30, Appendix 12, X30. 62 Written Direct Testimony of Professor John R. Hauser, Tables 1, 2. 63 See Written Direct Testimony of Professor John R. Hauser, n.111, Appendix D, Q4, Q5.
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one option they would choose to replace their last listening experience (Q5).64 In the Zauberman Survey, respondents were asked which options they would use and were allowed to select multiple options by indicating “yes” to more than one option (Q2).65 Indeed, based on calculations from Figure 8 of the Zauberman Report, Zauberman Survey respondents in Q2 selected “yes” to approximately 3.7 to 3.9 options that they would “use instead.”66 By comparison, Hauser Survey respondents indicated they would consider an average of 12.6 alternatives in Q4, and Hauser Survey respondents selected a single alternative in Q5.67 These differences in magnitude illustrate that the three survey questions attempt to measure different, but related, aspects of switching.68 Therefore, it is difficult to assess exactly the extent to which the instructions in the Zauberman Survey biased respondents through comparison to the Hauser Survey.69
C. The Zauberman Survey Did Not Include Attention Checks to Verify That Respondents Were Engaged in the Survey and Provided Reliable and Accurate Answers to the Survey Questions
31. The Zauberman Survey did not include any attention checks or other ways to confirm that the respondent paid sufficient attention to the questions and the scenarios. Attention checks represent best practices in survey research and address the relevant issue that some panelists may focus more on the rewards for completing a survey than on providing accurate answers. In order to complete a survey quickly, some respondents pay less attention to the questions and, hence, are identified and eliminated from analysis when they fail attention checks. The Zauberman Report removes respondents who answer too quickly, but merely evaluating how these
64 See Written Direct Testimony of Professor John R. Hauser, n.111, Appendix D, Q4, Q5. 65 Written Direct Testimony of Gal Zauberman, Appendix D, Q2. 66 Written Direct Testimony of Gal Zauberman, Figure 8. The “use instead” percentages add to 372 percent in the “all respondents” panel of the figure and 385 percent in the “respondents who completed survey” panel of the figure. Thus, on average, respondents selected approximately 3.7 options when the sample includes all respondents and 3.9 options when the sample includes only respondents who completed the survey. 67 Written Direct Testimony of Professor John R. Hauser, ¶¶ 103, 105. 68 Written Direct Testimony of Professor John R. Hauser, ¶¶ 103, 105; Written Direct Testimony of Gal Zauberman, Figure 8. 69 It is natural and expected that respondents would consider more options than they would “use instead.” It is also natural that, when respondents are replacing a particular listening activity, they would choose a single activity. The relative values (12.6, 3.7 to 3.9, and 1) are consistent in rank order with theory, but without further research we cannot evaluate the appropriate ratios between the various measures.
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“speeders” affect the results and removing them is not sufficient.70 Attention check questions are screens to assure that the respondent paid sufficient attention and read the instructions carefully. 32. Attention-check questions are standard in surveys to ensure that respondents are sufficiently engaged in the survey, and are providing reliable and accurate responses to the survey questions.71 For example, I used QS6 and one of the response options in QS9 as two attention checks in the screening questions of the Hauser Survey. The QS6 attention check required respondents to select “Lenovo” from a list of computer, tablet, and smartphone brand options, regardless of what brand computer, tablet, or smartphone they were using.72 The second attention check was included in QS9 as the option “I watched on-demand holographic telecast(s)” when respondents were asked to select which activities they engaged in over the last three days.73 Because on-demand holographic telecasts were not available, respondents who were paying attention and providing thoughtful responses should not have selected this “red herring” option. 33. Similarly, the Hanssens Surveys used attention check questions and decoy options.74 According to the Hanssens Report, “[t]he two attention check questions are screening question SP100 and Question P60 in the Pandora Survey, and screening question SX110 and Question X60 in the Sirius XM Survey.”75 Besides these two attention check questions, the Hanssens Surveys “included a decoy music streaming service option called ‘RadioStream’ in screening questions SP70 of the Pandora Survey and SX60 of the Sirius XM Survey.”76 According to the Hanssens Report, the “decoy option allowed [Professor Hanssens] to identify and terminate
70 Written Direct Testimony of Gal Zauberman, n.31. Note that the Hauser Survey results are reported with the 5 percent of respondents who completed the survey the fastest and the slowest because the results do not differ when excluding those respondents. Written Direct Testimony of Professor John R. Hauser, ¶ 81. 71 Written Direct Testimony of Professor John R. Hauser, ¶¶ 40–42. 72 Written Direct Testimony of Professor John R. Hauser, Appendix D, QS6. 73 Written Direct Testimony of Professor John R. Hauser, Appendix D, QS9. 74 Written Direct Testimony of Dominique M. Hanssens, Appendix 4, ¶¶ 15–16. 75 Written Direct Testimony of Dominique M. Hanssens, Appendix 4, n.24. SP100 and SX110 asked respondents “Please select Yellow from the following list in order to continue the survey.” P60 and X60 asked respondents “Please select Thursday from the following list in order to continue the survey.” See Written Direct Testimony of Dominique M. Hanssens, Appendix 6, SP100, P60, Appendix 12, SP110, X60. 76 Written Direct Testimony of Dominique M. Hanssens, Appendix 4, ¶ 16. SP70 prompted respondents as follows: “You identified that you personally use music streaming services in a typical week. Please indicate which of the following music streaming services, if any, you personally use in a typical week.” SX60 prompted respondents as follows: “You identified that you personally use services that provide access to music in a typical week. Please indicate which of the following, if any, you personally use in a typical week.” See Written Direct Testimony of Dominique M. Hanssens, Appendix 6, SP70, Appendix 12, SX60.
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respondents who were selecting options simply to qualify for the survey rather than selecting music streaming services they actually use in a typical week.”77 In addition, “[t]he Sirius XM Survey included an additional data quality assurance measure, screening question SX85, which provided respondents with a list of real and decoy music channels on Sirius XM and asked respondents to indicate which channels they listen to in a typical month.”78 According to the Hanssens Report, “[a]ny respondent who selected a decoy music channel was immediately terminated.”79 34. Typically, many respondents fail attention checks in surveys. This is what was observed in the Hauser Survey and the Hanssens Surveys.80 If similar numbers of respondents would have failed attention checks in the Zauberman Survey, then similar percentages of the Zauberman Survey’s respondents should have been screened out as not reliable. For example, out of 8,752 participants to the Hauser Survey who responded to QS6, 3,376 individuals failed to select “Lenovo” in QS6 (38.6 percent) and 172 respondents who reached QS9 (3.5 percent of the 4,971 respondents who answered QS9) selected “I watched on-demand holographic telecast(s).”81 As is proper in reliable surveys, the respondents who failed the attention checks did not qualify to take the survey. Because the Zauberman Survey did not use attention checks, the results of the Zauberman Survey may not accurately reflect what respondents would do if free or paid streaming radio services were unavailable. Respondent inattention could have exacerbated the flaws cited above, further biasing the Zauberman Survey toward overestimating switching to paid options to the extent that inattentive respondents did not reflect carefully about their music- listening habits over the past thirty days (discussed in Section IV.A), or only indicated switching
77 Written Direct Testimony of Dominique M. Hanssens, Appendix 4, ¶ 16. For both SP70 and SX60, the programmer instructions indicated “terminate if respondent selects ‘RadioStream,’ the decoy option.” See Written Direct Testimony of Dominique M. Hanssens, Appendix 6, SP70, Appendix 12, SX60 (emphasis omitted). 78 Written Direct Testimony of Dominique M. Hanssens, Appendix 4, ¶ 16. SX85 prompted respondents: “You indicated that you personally use Sirius XM to listen to music in a typical week. Which of the following Sirius XM music channels, if any, have you personally listened to in the last month?” See Written Direct Testimony of Dominique M. Hanssens, Appendix 12, SX85 (emphasis in original). 79 Written Direct Testimony of Dominique M. Hanssens, Appendix 4, ¶ 16. For SX85, the programmer instructions indicated “terminate if respondent chooses any option from 8 through 22.” See Written Direct Testimony of Dominique M. Hanssens, Appendix 12, SX85 (emphasis omitted). 80 The exact number of respondents who were terminated is not reported in the Hanssens Report. However, at my request Cornerstone Research verified that respondents were indeed terminated as a result of the attention checks and decoy options described in the Hanssens Report. See Written Direct Testimony of Dominique M. Hanssens, Appendix 4, ¶¶ 15–16; Hanssens Pandora Survey Start Data; Hanssens Sirius XM Survey Start Data. 81 Hauser Survey Data. 18 NAB Written Rebuttal Statement Dkt. No. 19-CRB-0005-WR (2021-25) PUBLIC VERSION
to music-listening options because of the explicit instruction to focus on music-listening options (discussed in Section IV.B).
V. The Zauberman Survey Cannot Reliably Measure the Switching Behavior of Listeners of Internet Simulcasts of Terrestrial Commercial Radio and Listeners of Sirius XM Over the Internet
35. The Hauser Survey was specifically designed to estimate the switching behavior of listeners of Internet simulcasts of terrestrial commercial radio if such simulcasts were no longer available. In contrast, the Zauberman Survey’s free hypothetical scenario is unable to shed light on the switching behavior of this population. Similarly, the Hanssens Sirius XM Survey was specifically designed to estimate how the listening habits of subscribers of Sirius XM over the Internet would change following a service degradation.82 In contrast, the Zauberman Survey’s paid hypothetical scenario is unable to shed light on the switching behavior of subscribers to paid streaming radio services that I understand from counsel operate under the statutory license, let alone subscribers to Sirius XM over the Internet specifically. I discuss these opinions in more detail below. 36. First, the free hypothetical provided in the Zauberman Survey is overly broad and cannot be used to measure switching in the event that Internet simulcasts of terrestrial commercial radio were not available. In the Hauser Survey, listeners of Internet simulcasts of terrestrial commercial radio were asked to “suppose that live AM/FM radio broadcasts from commercial radio stations over the Internet were not available for the next five years.”83 In contrast, in the Zauberman Survey free hypothetical scenario, respondents were asked to “[i]magine that all FREE streaming radio services were no longer available,” where free streaming radio includes Internet simulcasts of terrestrial commercial radio as well as free not-on-demand music streaming services, such as ad-supported Pandora.84 In other words, the Zauberman Survey asked respondents to assume that Internet simulcasts of terrestrial commercial radio were no longer available, as in the Hauser Survey, but also asked respondents to assume that other free not-on-demand music streaming services that offer higher degrees of customization and
82 Written Direct Testimony of Dominique M. Hanssens, ¶¶ 13, 60. 83 Written Direct Testimony of Professor John R. Hauser, Appendix D, Q4 (emphasis in original). 84 Written Direct Testimony of Gal Zauberman, Appendix D, pp. 58–59 (emphasis in original).
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personalization to users were also no longer available.85 As a result, the Zauberman Survey cannot be used to estimate the switching behavior of respondents under the scenario that only Internet simulcasts of terrestrial commercial radio were no longer available. 37. Second, the Zauberman Survey’s free hypothetical scenario did not specifically identify and study the population of listeners of Internet simulcasts of terrestrial commercial radio. It was designed to target respondents who listened to free streaming radio more generally.86 As a result, the Zauberman Survey cannot be used to estimate the switching behavior of listeners of Internet simulcasts of terrestrial commercial radio separately from the switching behavior of listeners of other free streaming radio services such as ad-supported Pandora. In contrast, the Hauser Survey identified the population of listeners of Internet simulcasts of terrestrial commercial radio and asked only those individuals about their switching behavior when Internet simulcasts of terrestrial commercial radio were no longer available. 38. It is a fundamental principle of good survey design to identify the target population of interest. According to the Reference Guide on Survey Research,
One of the first steps in designing a survey or in deciding whether an existing survey is relevant is to identify the target population (or universe). The target population consists of all elements (i.e., individuals or other units) whose characteristics or perceptions the survey is intended to represent…The definition of the relevant population is crucial because there may be systematic differences in the responses of members of the population and nonmembers.87 39. Results from the Hauser Survey suggest that it is unlikely that listeners of Internet simulcasts of terrestrial commercial radio would exhibit the same switching behavior as listeners
85 Internet simulcasts of terrestrial commercial radio are customizable to the extent that users may select which radio station they listen to. Other not-on-demand music streaming services, such as ad-supported Pandora, offer personalized stations which may allow users to influence which genres of music or artists they may hear and are more personalized in that they may suggest to users other content they may want to listen to based on their observed listening patterns. See “Choose How You Want to Listen,” Pandora, available at https://www.pandora.com/; “Recommendations and Personalization on Pandora,” Pandora Help, available at https://help.pandora.com/s/article/000001078?language=en_US. 86 The target population for the Hauser Survey was U.S. residents over the age of 18 who listened to Internet simulcasts of terrestrial commercial radio during the prior three days. The target population for the Zauberman Survey free hypothetical scenario was U.S. residents age 16 and older who listened to free streaming radio services during the prior thirty days. See Written Direct Testimony of Professor John R. Hauser, ¶ 22; Written Direct Testimony of Gal Zauberman, ¶ 36. 87 Diamond, Shari S., “Reference Guide on Survey Research,” in Reference Manual on Scientific Evidence, Third Edition, Washington, D.C.: Federal Judicial Center and National Research Council of the National Academies, 2011, pp. 359–423, available at https://www.fjc.gov/content/reference-guide-survey-research-2, at pp. 376–377.
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of other free streaming radio services. While many free streaming radio services offer listeners primarily music content, Internet simulcasts of terrestrial commercial radio offer listeners other audio content such as news, weather, and traffic, talk, and sports.88 In particular, the results of the Hauser Survey show that 55.3 percent, 49.5 percent, and 36.3 percent of listeners of Internet simulcasts of terrestrial commercial radio listened to news, weather, and traffic, talk, and sports, respectively.89 In addition, a plurality of listeners to each of these types of audio content indicated that these types of simulcast content were “very important” to them.90 Because listeners of Internet simulcasts of terrestrial commercial radio listen to audio content other than music, and because such listeners consider this non-music audio content to be important, it is unlikely that these listeners would exhibit similar switching behavior as listeners of other free streaming radio services. Therefore, the Zauberman Survey cannot purport to isolate and measure the switching behavior of the listeners of Internet simulcasts of terrestrial commercial radio. 40. Third, the Zauberman Survey’s paid hypothetical scenario also did not appropriately define the target population to measure the switching behavior of listeners of what I understand from counsel to be statutory paid streaming radio services such as Sirius XM over the Internet. The Zauberman Survey’s definition of “paid streaming radio service” included services such as Pandora Plus.91 I understand from counsel that such services offer functionality—e.g., unlimited skips, caching of stations on user devices, and replays—that extends beyond what is allowed under the statutory license and requires direct licensing from record companies. As a result, the target population for the Zauberman Survey’s paid hypothetical scenario includes respondents who use (and likely pay for) features that are not covered by the statutory license. Therefore, the Zauberman Survey’s paid hypothetical scenario cannot purport to have reliably measured the switching behavior of the subset of subscribers to paid streaming radio services that are statutorily licensed. 41. In fact, the inclusion of subscribers to services such as Pandora Plus in the target population is particularly problematic if subscribers to such services value those services (and
88 Written Direct Testimony of Professor John R. Hauser, ¶ 64, Appendix D, Q2. 89 Written Direct Testimony of Professor John R. Hauser, Table 1, Appendix O. 90 Written Direct Testimony of Professor John R. Hauser, Table 2, Appendix P. 91 Written Direct Testimony of Gal Zauberman, Appendix D, Q1.
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are willing to pay for them) especially because they offer certain music-listening features that are not provided by statutorily-licensed services (e.g., as noted, Pandora Plus offers replays or unlimited skips that I understand from counsel are not allowed under the statutory license).92 To the extent that the Zauberman Survey’s target population included such subscribers, they may have been more likely to switch to alternative services that also offer these features (e.g., paid on-demand music streaming services) as opposed to alternative services that do not offer these features (e.g., AM/FM radio). Some of the services that offer these features (e.g., paid on- demand music streaming services) may be more expensive than services that do not offer these features (e.g., AM/FM radio). Thus, the Zauberman Survey may have biased respondents towards selecting more expensive options by including subscribers to services such as Pandora Plus, resulting in an inaccurate estimate of the switching behavior of listeners of statutory paid streaming radio services. 42. Fourth, because the Zauberman Survey included subscribers to services such as Pandora Plus in the target population and made such services unavailable in the paid hypothetical scenario, such services were (by definition) also not available as an alternative to which other respondents could switch. For example, current subscribers to Sirius XM over the Internet also did not have Pandora Plus as an alternative to which they could switch in the Zauberman Survey. To the extent that some respondents valued features offered by Pandora Plus that are not covered by the statutory license such as unlimited skips, caching of stations on user devices, and replays, the only switching alternative available to them with similar features would be a paid on-demand streaming service. Paid on-demand streaming services tend to have higher subscription prices than paid services such as Pandora Plus,93 which means the omission of paid streaming services from the Zauberman Survey’s list of potential substitutes may have biased such respondents towards choosing more expensive options as substitutes in the paid hypothetical scenario. As a result, the Zauberman Survey may have skewed switching behavior towards more expensive options.
92 Pandora Plus allows unlimited skips on most devices and replays for most songs. See “Choose How You Want to Listen,” Pandora, available at https://www.pandora.com/; “Skips and Replays,” Pandora Help, available at https://help.pandora.com/s/article/Skips-1519949305278?language=en_US. 93 See, e.g., Written Direct Testimony of Professor John R. Hauser, Appendix F.
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43. Fifth, while I understand from counsel that Sirius XM pays statutory rates to SoundExchange for transmitting music to subscribers via Sirius XM over the Internet, Sirius XM over the Internet also offers a wide variety of non-music content to subscribers, including content which is exclusively available on Sirius XM.94 For reasons similar to those discussed above, it is likely that Sirius XM over the Internet subscribers listen to, and consider as important, that non- music content. As a result, there may be systematic differences in the responses of Sirius XM over the Internet subscribers and subscribers to other paid streaming radio services. However, the Zauberman Survey did not and cannot measure the switching behavior of Sirius XM over the Internet subscribers separately from subscribers of other paid streaming radio services. In contrast, the Hanssens Sirius XM Survey specifically sought to answer questions about the switching behavior of listeners to music on Sirius XM over the Internet if “Sirius XM over the Internet were degraded.”95
VI. The Limited Number of Response Options in the Zauberman Survey Prevented Respondents from Making Distinctions between Different Types of Listening
44. The Zauberman Survey asked respondents to choose among a limited number of response options. The limited number of response options prevented respondents from making distinctions between different types of listening. 45. While both the Zauberman Survey and the Hauser Survey asked respondents to choose among a number of response options, the Zauberman Survey offered respondents fewer response options. The Zauberman Survey, in Q2, asked respondents to select “yes,” “no,” or “unsure” to each of the seven options that respondents may use or do instead of listening to free (or paid) streaming radio: paid on-demand streaming, free on-demand streaming, paid (or free) streaming radio, Sirius XM satellite radio, AM/FM radio on a traditional radio receiver, CDs, vinyl records,
94 See, e.g., “SiriusXM’s Huge Library of On Demand Content - Featuring Howard Stern and Much More - Now Available on Amazon Alexa and Echo Devices,” SiriusXM, November 19, 2019, available at http://investor.siriusxm.com/investor-overview/press-releases/press-release-details/2019/SiriusXMs-Huge-Library- of-On-Demand-Content---Featuring-Howard-Stern-and-Much-More---Now-Available-on-Amazon-Alexa-and- Echo-Devices/default.aspx; Andrea Zarczynski, “Record High 34.9 Million Paid Subscribers Marks SiriusXM Milestone Year,” Forbes, January 7, 2020, available at https://www forbes.com/sites/andreazarczynski/2020/01/07/record-high-349-million-paid-subscribers-marks- siriusxm-milestone-year/#695fe3283787. 95 Written Direct Testimony of Dominique M. Hanssens, ¶ 22.
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or MP3 files, and “Do something other than listen to music.”96 The Hauser Survey, in Q4, asked respondents to select “Would consider,” “Would not consider,” or “Don’t know/Unsure” to each of the 22 response options.97 Similarly, the Hanssens Surveys, in P40/X40, asked respondents to select “I would do this,” “I would not do this,” or “Don’t know/unsure” to each of the 16 or 17 response options.98 46. The limited response options in the Zauberman Survey did not allow respondents to make distinctions between different types of listening behavior. For example, respondents in the Zauberman Survey were prompted to select “yes,” “no,” or “unsure” to “listen to CDs, vinyl records, or MP3 files, that you currently own or would purchase.”99 The formulation of this question combines two options that I understand from counsel are very different from a royalty perspective—listening to already-purchased copies of music, and buying new copies of music. As a result, when presented with the hypothetical scenario, the following respondents all would have selected the same option:
a respondent who would choose to listen to CDs, vinyl records, or MP3 files that they currently own, but who would not purchase additional CDs, vinyl records, or MP3 files;
a respondent who would choose to listen to CDs, vinyl records, or MP3 files that they would purchase, but would not listen to CDs, vinyl records, or MP3
96 Written Direct Testimony of Gal Zauberman, Appendix D, Q2. 97 Written Direct Testimony of Professor John R. Hauser, Appendix D, Q4. Respondents could also provide an open-ended response in the text box following “I would consider doing the following instead.” 98 Written Direct Testimony of Dominique M. Hanssens, Appendix 6, P40, Appendix 12, X40. In the Hanssens Pandora Survey, respondents who indicated in P30 “I would increase doing this” to “Listen to music using ways other than Free Internet Radio” were asked to select “I would do this,” “I would not do this,” or “Don’t know/unsure” to each of the 16 response options in P40. In the Hanssens Sirius XM Survey, respondents who indicated in X30 “I would increase doing this” to “Listen to music using ways other than Sirius XM over the Internet” were asked to select “I would do this,” “I would not do this,” or “Don’t know/unsure” to each of the 17 response options in X40. The Hanssens Sirius XM Survey, in X40, had one additional response option relative to the Hanssens Pandora Survey, in P40. The response options “Sign up for and listen to a new Free Internet Radio service with ads (for example, free Pandora with ads or free Slacker Radio with ads) I do not already use” and “Listen more to a Free Internet Radio service with ads (for example, free Pandora with ads or free Slacker Radio with ads) I already use” are unique to X40 of the Hanssens Sirius XM Survey. The response option “Purchase a new Sirius XM subscription (for example, Sirius XM Essential at $8 per month for ad-free music, news, talk shows, and comedy or Sirius XM Premier at $13 per month for ad-free music, news, talks shows, and comedy plus live sports and other content) and listen to music on Sirius XM over the Internet” is unique to P40 of the Hanssens Pandora Survey. Respondents could also provide an open-ended response in the text box following “Other [Please specify ______].” See Written Direct Testimony of Dominique M. Hanssens, Appendix 6, P30, P40, Appendix 12, X30, X40. 99 Written Direct Testimony of Gal Zauberman, Appendix D, Q2.
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files that they currently own (or who does not currently own CDs, vinyl records or MP3 files); and
a respondent who would choose to listen both to CDs, vinyl records, or MP3 files that they currently own and to CDs, vinyl records, or MP3s that they would purchase. 47. In contrast, the Hauser Survey and Hanssens Surveys allowed respondents to distinguish between listening to CDs or digital music files that respondents owned and listening to CDs or digital music files that respondents would purchase. In the consideration question (Q4) of the Hauser Survey, 52 percent of respondents indicated they would consider listening to CDs or digital music files they do not already own, while 79 percent of respondents said they would consider listening to CDs or digital music files they already purchased.100 In the choice question (Q5) of the Hauser Survey, 1.8 percent of respondents said that they would purchase CDs or digital music files, while 6.0 percent of respondents said they would listen to digital music files or CDs they already purchased.101 In the Hauser Survey, the number of respondents who indicated that they would listen to their existing collection of CDs or digital music files is three times as large as the number of respondents who indicated that they would purchase new CDs or digital music files. The small share of new digital downloads and CDs is not surprising: sales of CDs and digital downloads have been declining.102 48. Similarly, in the Hanssens Surveys, more respondents indicated they would increase their use of physical or digital recordings of music they already owned than indicated they would purchase new physical or digital recordings of music.103 In addition, on average, respondents allocated more “points” (a way of measuring usage of different alternatives) to listening to physical or digital recordings of music they already owned than to listening to purchases of new physical or digital recordings of music.104 It is likely that the Zauberman Survey would have yielded similar results had the Zauberman Survey given respondents the opportunity to make this distinction. As a result, the Zauberman Survey cannot be used to estimate the incidence of new
100 Written Direct Testimony of Professor John R. Hauser, Appendix Q. 101 Written Direct Testimony of Professor John R. Hauser, Appendix R. 102 According to the Recording Industry Association of America, as a percentage of U.S. recorded music revenues, CD sales decreased from a peak of 95.5 percent in 2002 to 7.1 percent in 2018. Similarly, digital downloads (singles and albums) decreased from a peak of 40.6 percent of U.S. recorded music revenue in 2012 to 10.1 percent in 2018. See “U.S. Sales Database,” Recording Industry Association of America, available at https://www riaa.com/u-s-sales-database/. 103 Written Direct Testimony of Dominique M. Hanssens, Tables 4, 8. 104 Written Direct Testimony of Dominique M. Hanssens, Tables 4, 8. 25 NAB Written Rebuttal Statement Dkt. No. 19-CRB-0005-WR (2021-25) PUBLIC VERSION
purchases of CDs or digital music files as compared to use of existing collections of CDs or digital music files. Based on the Hauser Survey and the Hanssens Surveys, respondents appear to be more likely to listen to existing collections of CDs or digital music files than to listen to new CDs or digital music files they would purchase.
VII. The Zauberman Survey Does Not Estimate How Current Listeners of Streaming Radio Services Would Allocate Their Listening Time Across Replacement Music- Listening Options
49. The Zauberman Report claims that one purpose of the Zauberman Survey is to “assess how current listeners of Streaming Radio services would allocate their listening time across the replacement music-listening options they selected.”105 However, the Zauberman Survey does not solicit sufficient information to evaluate how listeners would allocate their time across substitute options, rendering the Zauberman Survey incapable of achieving this stated aim. 50. In the Zauberman Survey’s Q2, respondents were asked “which of the following music- listening option(s) would you now use instead” during the time they would have listened to paid or free streaming radio.106 After this question, any respondents who did not select “yes” to free on-demand streaming services or free streaming radio (in the paid hypothetical) and at least one other option were terminated, and did not proceed to the next question (Q3).107 This survey skip logic eliminated respondents who might have selected, for example, only AM/FM radio either alone or with other options that were not free streaming radio or free on-demand streaming services. As a result, the Zauberman Survey does not collect the information needed to determine how these respondents would allocate their listening time across substitute options. 51. The Zauberman Report notes that at the request of counsel for SoundExchange, this information was only collected for a subset of respondents.108 However, this design renders the Zauberman Survey incapable of determining how all respondents who selected free music streaming services would have allocated their listening time across substitute music-listening
105 Written Direct Testimony of Gal Zauberman, ¶ 14. 106 Written Direct Testimony of Gal Zauberman, Appendix D, Q2 (emphasis in original). 107 According to the Zauberman Report, “[a]t the request of counsel,” respondents were asked Q3 and (if relevant) Q3A, because “it was necessary to gather this information because free music streaming services generally pay royalties on a per-play basis.” See Written Direct Testimony of Gal Zauberman, ¶ 59 (emphasis in original). 108 Written Direct Testimony of Gal Zauberman, ¶ 59.
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options. In particular, respondents who selected “yes” for only one of the free on-demand streaming service or free streaming radio options, and “no” for all other options, were terminated, and were not asked Q3.109 52. This is an omission that renders the Zauberman Survey incapable of determining whether respondents would logically allocate their time to the single option they selected in Q2. For example, if a respondent selected only that they would listen to a free on-demand service in Q2, but would not have expected to listen to the unavailable streaming service on the indicated day in the next week, that respondent would logically have allocated 0 percent of time to listening to the free on-demand service. By contrast, if the respondent did expect to listen to the unavailable streaming service on the indicated day in the next week, that respondent would have logically allocated 100 percent of time to listening to the free on-demand service. Whether a respondent would have logically allocated 0 percent or 100 percent to the single option selected in Q2 could only be determined if the respondent was asked the filter question (Q3). However, the Zauberman Survey did not ask this question of these respondents. As a result, the responses to the Zauberman Survey cannot be used to determine how these respondents would allocate their listening time on average to the one option they selected in Q2. 53. Had the Zauberman Survey asked Q3 and Q3A of all respondents, the results of the Zauberman Survey would have been closer to achieving the aim of measuring how respondents would allocate their listening time across different music-listening options. However, the Zauberman Survey did not do this and as a result cannot be used to produce an unbiased estimate of “how current listeners of Streaming Radio services would allocate their listening time across the replacement music-listening options they selected.”110
VIII. Between the Hauser Survey and the Zauberman Survey, Only the Hauser Survey Can Be Used to Measure Switching Behavior of Listeners of Internet Simulcasts of Terrestrial Commercial Radio
54. In addition to the flaws in the Zauberman Survey discussed above, the Zauberman Survey and the Hauser Survey differ in how they elicit switching behavior. I first describe these
109 17 respondents across both the paid and free hypothetical scenarios in the Zauberman Survey provided this type of response to Q2, among respondents that were included in the results provided in the Zauberman Report. See Zauberman Survey Data; Written Direct Testimony of Gal Zauberman, ¶¶ 58, 75. 110 Written Direct Testimony of Gal Zauberman, ¶ 14. 27 NAB Written Rebuttal Statement Dkt. No. 19-CRB-0005-WR (2021-25) PUBLIC VERSION
differences, and discuss how these may lead the results of the Zauberman Survey and the Hauser Survey to differ. I then show that despite these differences the results of the Hauser Survey and the Zauberman Survey are directionally similar to one another and, thus, the results of the Zauberman Survey lend credence to the Hauser Survey. Because of the flaws in the Zauberman Survey, only the Hauser Survey can be used to measure switching behavior of listeners of Internet simulcasts of terrestrial commercial radio.
A. The Zauberman Survey and the Hauser Survey Differ in How They Elicit Switching Behavior, Which May Have Caused the Results of the Zauberman Survey and the Hauser Survey to Differ
55. In addition to the differences described above that make the Zauberman Survey inappropriate for estimating the switching behavior of listeners of Internet simulcasts of terrestrial commercial radio if such simulcasts were no longer available, the Hauser Survey and the Zauberman Survey’s free hypothetical scenario differ in how they elicit switching behavior, which may have caused the results of the two surveys to differ. 56. After prompting respondents with hypothetical scenarios, the Hauser Survey and the Zauberman Survey asked respondents different questions. The Hauser Survey used the well- established consider-then-choose paradigm.111 In Q4, the Hauser Survey asked respondents “Which of the following, if anything, would you consider doing in place of listening to such broadcasts over the Internet during the next five years?”112 This question in the Hauser Survey asked respondents what they would consider doing to replace Internet simulcasts of terrestrial commercial radio. The Hauser Survey then asked nearly all respondents a “choice question,” Q5, in which respondents were asked to “think about the most recent time you listened to live AM/FM radio broadcasts from commercial radio stations over the Internet.”113 Respondents were then asked “Which one of the following would you do in place of listening to such broadcasts over the Internet in similar situations during the next five years?”114
111 See Written Direct Testimony of Professor John R. Hauser, n.111, Appendix D, Q4, Q5. 112 Written Direct Testimony of Professor John R. Hauser, Appendix D, Q4 (emphasis in original). 113 Written Direct Testimony of Professor John R. Hauser, ¶ 105, Appendix D, Q5 (emphasis in original). A total of three respondents who did not select “Would consider” for any options in Q4 were not shown Q5. See, Written Direct Testimony of Professor John R. Hauser, Appendix Q. 114 Written Direct Testimony of Professor John R. Hauser, Appendix D, Q5 (emphasis in original).
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57. Rather than using the consider-then-choose paradigm, the Zauberman Survey’s free hypothetical scenario, in Q2, directly asked respondents “which of the following music-listening option(s) would you now use instead” during the time they would have listened to free streaming radio.115 The Zauberman Survey then asked a filter question, Q3, and a time-allocation question, Q3A (though, as explained above, did so for only some respondents).116 Respondents are first asked the filter question Q3: “Would you expect to listen to your [FREE or PAID] streaming radio service(s) on [INSERT DOW] of next week?”117 The purpose of this filter question was to ask different respondents to think about different days of the week in order to “measure listening time across all days of the week.”118 For respondents who answered “yes” to the filter question Q3 (and only for those respondents), the Zauberman Survey asked the time-allocation question, which instructed respondents to “allocate [as a percentage] the time you would have listened to your [FREE or PAID] streaming radio service(s) on [INSERT DOW] next week by indicating the percentage of time you would listen to each of the options” that the respondent selected in Q2.119 58. The differences in how the Hauser Survey and the Zauberman Survey’s free hypothetical scenario elicit switching behavior may result in further differences between the results of the two surveys.
115 Written Direct Testimony of Gal Zauberman, Appendix D, Q2 (emphasis in original). 116 Written Direct Testimony of Gal Zauberman, ¶¶ 59, 76, Appendix D, Q3, Q3A. In the scenario where free streaming radio is not available, respondents are only asked the time allocation if they selected (1) free on-demand streaming radio and at least one other option in Q2; and (2) indicated in Q3 that they would expect to listen to free streaming radio on the same day the following week. 117 Written Direct Testimony of Gal Zauberman, ¶ 60, Appendix D, Q3 (emphasis in original). 118 Written Direct Testimony of Gal Zauberman, ¶ 62, Appendix D, Q3A (emphasis in original). The Hauser Survey sampled a random draw in time of listening instances. Written Direct Testimony of Professor John R. Hauser, ¶ 36. This is a valid and unbiased manner in which to obtain a distribution of time across options. Payne, Stanley L. B., “Isn’t that Loaded?” in The Art of Asking Questions, Princeton, NJ: Princeton University Press, 1980, pp. 177–202, at pp. 200–201. 119 Written Direct Testimony of Gal Zauberman, Appendix D, Q3A (emphasis in original). 29 NAB Written Rebuttal Statement Dkt. No. 19-CRB-0005-WR (2021-25) PUBLIC VERSION
B. The Results of the Zauberman Survey and the Hauser Survey, While Different in Magnitude, Are Directionally Similar and Only the Hauser Survey Provides Valid Estimates for the Switching Behavior of Listeners of Internet Simulcasts of Terrestrial Commercial Radio
59. The flaws in the Zauberman Survey discussed above, and the differences in how switching behavior is elicited in the Hauser Survey and the Zauberman Survey, mean that the Hauser Survey results and the Zauberman Survey’s free hypothetical scenario results are not directly comparable in magnitude.120 As discussed above in Section V, only the Hauser Survey is valid for measuring the switching behavior of listeners of Internet simulcasts of terrestrial commercial radio if such simulcasts were no longer available. However, the results from the two surveys are directionally similar, which lends support to the validity of the Hauser Survey. 60. Respondents in the Hauser Survey reported music-listening habits that are directionally similar, while different in magnitude, to those of respondents in the Zauberman Survey.121 Appendix D compares the results of Hauser Survey QS10 and Zauberman Survey Q1, both of which measured the ways respondents reported listening to music. Appendix D shows the share of respondents who indicated that they listened to music in each category included in the Zauberman Survey Q1, after aggregating across some response options from the Hauser Survey to make the results comparable.122 It is reproduced here as Table 1.123
120 The Written Direct Testimony of Gal Zauberman separately reports the results of the Zauberman Survey for the free hypothetical scenario and for the paid hypothetical scenario. Because Internet simulcasts of terrestrial commercial radio are accessed at no cost, in this section, I discuss only the results of the Zauberman Survey for the free hypothetical scenario. See, e.g., Written Direct Testimony of Gal Zauberman, Figures 8 and 9. 121 Initial analyses suggest that the results of the Hanssens Surveys are also correlated with the relevant results of the Zauberman Survey. However, I have not evaluated all the details of the Hanssens Surveys, nor have I evaluated all of the differences between the Hanssens Surveys and the Zauberman Survey. 122 Because the response options in QS10 of the Hauser Survey and Q1 of the Zauberman Survey are not identical, I first matched response options from QS10 of my survey to the corresponding response options from Q1 of the Zauberman Survey, and aggregated the results from some response options in the Hauser Survey to match to the response options in the Zauberman Survey. See notes to Appendix D for more details. 123 See notes to Appendix D for details. 30 NAB Written Rebuttal Statement Dkt. No. 19-CRB-0005-WR (2021-25) PUBLIC VERSION
Table 1: Ways Survey Respondents Listened to Music
Hauser QS10 Zauberman Q1 Response Last 3 Days Last 30 Days
AM/FM Radio on a Receiver 75.9% 77.9%
Free On-Demand Streaming Service 44.9% 67.6%
CDs, Vinyl Records, or MP3 Files 35.7% 52.4%
Free Streaming Radio Service 32.5% 65.6%
Paid On-Demand Streaming Service 23.5% 39.5%
SiriusXM Satellite Radio Service 19.5% 28.8%
Paid Streaming Radio Service 7.0% 20.8%
Number of Respondents 3,889 6,146
Average Number of Responses per Respondent 2.4 3.5
Source: Appendix D; Written Direct Testimony of Professor John R. Hauser; Hauser Survey Data; Written Direct Testimony of Gal Zauberman.
61. Although respondents in the Hauser Survey were asked about their listening over the prior three days and respondents in the Zauberman Survey were asked about their listening over the prior thirty days, the shares of respondents listening to music by each way of listening, while different in magnitude, are directionally similar across both surveys. 62. To assess statistically the directional similarity of the two measures of current listening behavior, I computed the correlation coefficient between the two sets of percentages. The correlation coefficient between the percentage of respondents selecting each category in the Zauberman Survey and the percentage of respondents selecting response options within each of the categories in the Hauser Survey is highly correlated (𝜌 0.90, 𝑝 ). 0.01 63. Respondents in the Hauser Survey reported switching behavior that is directionally similar, while different in magnitude, to that of respondents in the Zauberman Survey. Appendix E compares the results of Hauser Survey Q5 and Zauberman Survey Q2, both of which measure switching behavior, after aggregating across response options from the Hauser Survey to make the results comparable. It is reproduced here as Table 2.124
124 See notes to Appendix E for details. 31 NAB Written Rebuttal Statement Dkt. No. 19-CRB-0005-WR (2021-25) PUBLIC VERSION
Table 2: Approximate Survey Response Comparison
Hauser Zauberman Q5 Figure 8 (Percent of Q5 (Percent of Figure 8 Response Respondents) (Normalized) Respondents) (Normalized)
Paid On-Demand Streaming Service 8.8% 10.5% 38.7% 10.1% Free On-Demand Streaming Service 9.6% 11.4% 79.9% 20.8% Paid Streaming Radio Service 4.4% 5.2% 33.4% 8.7% Free Streaming Radio Service 10.0% – – – SiriusXM Satellite Radio Service 8.4% 10.0% 30.9% 8.0% AM/FM Radio on a Receiver 28.9% 34.4% 84.6% 22.0% CDs, Vinyl Records, or MP3 Files 8.4% 10.0% 69.2% 18.0% Do Something Other than Listen to Music 15.6% 18.5% 48.2% 12.5% Other (not listed above) 6.0% – – –
Total (Percentage) 100% 100% 385% 100%
Source: Appendix E; Written Direct Testimony of Professor John R. Hauser; Hauser Survey Data; Written Direct Testimony of Gal Zauberman.
64. To compare the two surveys it was also necessary to rescale the results of the switching questions to interpret the results of the two surveys.125 The first reason for rescaling is that response options were available to respondents to the Hauser Survey Q5 that did not have equivalent options in the Zauberman Survey Q2, such as free streaming radio options other than Internet simulcasts of terrestrial radio broadcasts.126 After matching the response options in the Hauser Survey and the Zauberman Survey, I rescaled the Hauser Survey results for Q5 by removing the percentage of respondents who selected free streaming radio and “other” options. The second reason for rescaling is that respondents in the Zauberman Survey may have selected multiple options. To address this difference in response format, I rescaled all results from Q2 in the Zauberman Survey to sum to 100 percent.
125 Because the response options in Q5 of the Hauser Survey and Q2 of the Zauberman Survey are not identical, I first matched response options from Q5 of the Hauser Survey to the corresponding response options from Q2 of the Zauberman Survey, and aggregated the results from some response options in the Hauser Survey to match to the response options in the Zauberman Survey. See notes to Appendix E for more details. 126 In Q5 of the Hauser Survey, 84.0 percent of respondents selected a response option that is not classified as free streaming radio or “Other (not listed above),” which is composed of options not available to respondents in the Zauberman Survey. After I matched response options from the Hauser Survey to the corresponding response options from the Zauberman Survey, I rescaled the matched results to this question by dividing all percentages by 0.84. In Q2 of the Zauberman Survey, on average, respondents selected “yes” to 3.85 response options. I rescaled the results to this question by dividing all reported percentages by 3.85. See notes to Appendix E for more details.
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65. To assess statistically the directional similarity of the two measures of switching, I computed the correlation coefficient between the two sets of percentages. The percentage of respondents who selected each category in the Zauberman Survey and the percentage of respondents who selected response options within each of the categories in the Hauser Survey is correlated (𝜌 0.61, 𝑝 ). 0.16 Although the correlation is not significant statistically, the results are nevertheless qualitatively similar as evidenced by the high rank correlation which is statistically significant (𝜌 0.72, 𝑝 ). 0.05 127 66. Thus, despite differences in the survey design of the Hauser Survey and the Zauberman Survey, the results of the Hauser Survey and the Zauberman Survey are directionally similar. Only the Hauser Survey measured the switching behavior of listeners of Internet simulcasts of terrestrial commercial radio if such simulcasts were no longer available. As a result, only the Hauser Survey provides valid estimates for the switching behavior of listeners of Internet simulcasts of terrestrial commercial radio.
IX. Summary
67. In sum, I opine that the results of the Zauberman Survey cannot be used to reliably estimate the switching behavior of listeners to free or paid streaming radio services. 68. Flaws in the design of the Zauberman Survey likely lead to overestimates of switching to new, paid music subscriptions. The Zauberman Survey asks respondents to recall their music listening behavior over a period of thirty days, which the Hauser Survey’s pretests suggest would be difficult for respondents. Because the response options in the Zauberman Survey are based on respondent recall, if respondents did not listen to or did not recall listening to existing subscriptions such subscriptions will not be offered to respondents in subsequent questions
127 To calculate the statistical significance of two ranks, we compute the Spearman rank correlation coefficient, which is numerically equal to the Pearson correlation coefficient between two rank variables. This is equivalent to the formula of 𝜌 1 6∑ where 𝑑 is the difference in rank of the 𝑖 option and 𝑛 is the number of objects being ranked. If there were 11 or more observations, we could approximately test the significance of the Spearman coefficient with a 𝑡-statistic equal to 𝜌 𝑛 2 / 1 𝜌 . Because 𝑛 8, I use the more conservative test of arctanh 𝜌 which is approximately distributed normally. The one-tailed test returns 𝑝 0.039. If we were to . use a two-tailed test we obtain 𝑝 0.078, which is marginally significant. More qualitatively, the two ranks are related, albeit not perfectly. See Fieller, E.C., H.O. Hartley, and E.S. Pearson, “Tests for Rank Correlation Coefficients. I.,” Biometrika 44, 3/4, 1957, pp. 470–481. 33 NAB Written Rebuttal Statement Dkt. No. 19-CRB-0005-WR (2021-25) PUBLIC VERSION
alongside new, paid subscriptions. Further, the language of the switching question in the Zauberman Survey is likely to bias respondents towards music-listening options, and away from non-music-listening options. In addition, the Zauberman Survey does not include attention checks to ensure that respondents were engaged in the survey and providing reliable and accurate answers to the survey questions. Taken together, these flaws are likely to lead to overestimates of switching to new, paid music subscriptions. 69. The Zauberman Survey design suffers from additional flaws that render the results of the Zauberman Survey unreliable. The design of the Zauberman Survey prevents it from reliably estimating the switching behavior of specific populations targeted by the Hauser Survey (listeners of Internet simulcasts of terrestrial radio) and Hanssens Sirius XM Survey (listeners of Sirius XM over the Internet). The Zauberman Survey offers limited response options to respondents, which prevents them from making distinctions between different types of music listening. And finally, the design of the Zauberman Survey renders it incapable of achieving one of its stated goals, “to assess how current listeners of Streaming Radio services would allocate their listening time across the replacement music-listening options they selected.”128 70. As a result of the flaws in the design of the Zauberman Survey, and further differences between the Hauser Survey and the Zauberman Survey, only the Hauser Survey can be used to measure the switching behavior of listeners to Internet simulcasts of terrestrial radio.
128 Written Direct Testimony of Gal Zauberman, ¶ 14. 34 NAB Written Rebuttal Statement Dkt. No. 19-CRB-0005-WR (2021-25) PUBLIC VERSION
APPENDIX A
PUBLIC VERSION
Update December 11, 2019
ACADEMIC VITA (long version) John R. Hauser
Address
MIT Sloan School of Management Massachusetts Institute of Technology, E62-538 Cambridge, Massachusetts 02142 (617) 253-2929 https://mitmgmtfaculty.mit.edu/jhauser/ [email protected]; web mit.edu/hauser/www
Education
Sc.D. M.I.T., 1975, Operations Research Dissertation: "A Normative Methodology for Predicting Consumer Response to Design Decisions: Issues, Models, Theory and Use.”
Advisor: John D. C. Little. Committee members: Glen L. Urban and Moshe Ben-Akiva.
S.M. M.I.T., 1973, Civil Engineering (Transportation Systems Division)
S.M. M.I.T., 1973, Electrical Engineering
S.B. M.I.T., 1973, Electrical Engineering Joint Thesis (S.M.'s and S.B.): "An Efficient Method to Predict the Impacts of Operating Decisions for Conventional Bus Systems." Advisor: Nigel Wilson.
Honorary Degree
Doctor Honoris Causa, Erasmus School of Economics, Erasmus University, Dies Natalis 2016.
Lifetime Achievement Awards
Buck Weaver Award 2013, INFORMS Society of Marketing Science (ISMS).This award recognizes lifetime contributions to the theory and practice of marketing science.
Parlin Award 2001, The American Marketing Association describes this award as “the oldest and most distinguished award in the marketing research field.”
Converse Award 1996, the American Marketing Association, for “outstanding contributions to the development of the science of marketing.”
Churchill Award 2011, the American Marketing Association, Market Research Special Interest Group, for “Lifetime achievement in the academic study of marketing research.”
Fellow of the Institute for Operations Research and Management Science (INFORMS)
Inaugural Fellow of the INFORMS Society of Marketing Science (ISMS)
Highly Cited Researcher (ISI Web of Science), Since 2006.
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Awards for Published Papers
INFORMS Society of Marketing Science ISMS Long Term Impact Award, 2019, Finalist ISMS Long Term Impact Award, 2018, Finalist (formerly The Institute ISMS Long Term Impact Award, 2017, Finalist of Management Science) ISMS Long Term Impact Award, 2012, Finalist ISMS Long Term Impact Award, 2011, Finalist John D.C. Little Best-paper Award, 2015, Finalist John D.C. Little Best-paper Award, 2009, Finalist John D.C. Little Best-paper Award, 2003, First Place John D.C. Little Best-paper Award, 1998, Finalist John D.C. Little Best-paper Award, 1994, Finalist John D.C. Little Best-paper Award, 1993, First Place John D.C. Little Best-paper Award, 1990, Honorable Mention Best paper in Marketing Sciences Literature, 1984, Honorable mention. Best Paper in Marketing Sciences Literature, 1983, First Place. Best Paper in Marketing Sciences Literature, 1982, First Place. Two published articles were cited in 2007 as one of “the top 20 marketing science articles in the past 25 years.
American Marketing Association: Explor Award (Leadership is on-line market research), 2004, First-Place Finalist, Paul Green Award for contributions to marketing research, 2004 MSI Award for Most Significant Contribution to Practice of Marketing in 1996. Finalist, O'dell Award for best paper in the Journal of Marketing Research, published in 1986, awarded in 1991.
One of the top 50 most prolific marketing scholars (top journals) in the last 25 years (1982-2006). Total articles, rate of publication, and author-adjusted rate.
Product Development Management Assoc. Best Paper Award, Finalist, 2003. Best Paper Award, Finalist, 2002. One of ten most-cited papers in the Journal of Product Innovation Management. One of the top articles in educational citations in the last twenty years.
European Marketing Academy Best Paper in IJRM, Finalist, 2014
Sawtooth Software Conference Best Presentation and Paper, 2006; Runner-up, 2008, Honorable Mention, 2016.
European Society of Marketing Research Best Paper at Rome conference, September 1984.
Emerald Management Reviews 2010 Citation of Excellence (top 50 of 15,000 published papers in 2009)
Doctoral Consortia Faculty American Marketing Association, 1979, 1984, 1985, 1986, 1988, 1989, 1991, 1993, 1995, 1997, 1998, 2001, 2003, 2004, 2005, 2006, 2007, 2008, 2009, 2012, 2013, 2014.
INFORMS Society of Marketing Science, 2002 (founding member), 2003, 2004, 2012, 2014, 2015, 2017, 2018.
European Marketing Academy, 1985 Awards, Teaching
MIT Sloan School of Management: Nominated for Excellence in Teaching Award 2000, 2007, 2008. Named "Outstanding Faculty" by Business Week Guide to the Best Business Schools (1995).
Excellence in Teaching Award 1994 (Awarded by the Master's Student class).
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Awards for Thesis Supervision
American Marketing Association (Ph.D.): Winner John Howard Dissertation Award (2010, Matt Selove, Committee) Co-winner John Howard Dissertation Award (2005, Olivier Toubia) 1st Place (1981, Ken Wisniewski) Honorable Mention (1979, Patricia Simmie).
INFORMS (Ph.D.) ISMS Doctoral Dissertation Proposal Award (2016, Artem Timoshenko) Winner of the Frank Bass Award (2004, Olivier Toubia, awarded 2005) Winner of the Frank Bass Award (1989, Abbie Griffin, awarded 1995)
MIT Sloan School of Management (Ph.D.): 1st Place (1987, Peter F a d e r )
MIT Sloan School of Management (Master's): 1st Place (1991, Jon Silver and John Thompson) 1st Place (1983, Steve Gaskin) Honorable Mention (1982, Larry Kahn).
Marketing Science Institute MSI Alden G. Clayton Doctoral Dissertation Proposal Competition 2017, Artem Timoshenko
Awards, Other
Who’s Who in America Since 1997
Who’s Who in Management Science Since 2000
Who’s Who in Economics Since 2003
Who’s Who in Finance and Business Since 2009
Harvard Business School: Marvin Bower Fellow, 1987 - 1988.
National Science Foundation Fellowship: 1971 - 1974.
M.I.T. National Scholar, 1967 - 1971.
Honor Societies: Tau Beta Pi, Eta Kappa Nu, Sigma Xi
Directorships, Trustee, Advisory Board
2016 – Present Founder, Board of Directors, Hyper Morphing Technologies, B.V.
1988 – Present Founder, Senior Product Development Consultant at Applied Marketing Science, Inc.
March 2003 – July 2009 Trustee, Marketing Science Institute
Academic Appointments
January 1989 - Present Kirin Professor of Marketing MIT Sloan School of Management Massachusetts Institute of Technology Cambridge, Massachusetts 02142
July 2017 – present Head, Marketing Group
July 2010 – June 2011 Head, Marketing Group
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July 2005 – June 2009 Area Head, Management Science Area
July 1988 – June 2003 Head, Marketing Group
September 1993 - May 2000 co-Director, International Center for Research on the Management of Technology
September 1997 - May 2000 Research Director, Center for Innovation in Product Development
June 2001 – June 2006 Virtual Customer Initiative Leader, Center for Innovation in Product Development
July 1984 - January 1989 Professor of Management Science MIT Sloan School of Management Massachusetts Institute of Technology Cambridge, Massachusetts 02142
July 1987 - June 1988 Marvin Bower Fellow Harvard Business School Harvard University Cambridge, Massachusetts 02163
March 1985 - May 1985 Visiting Lecturer European Institute of Business Administration Fontainebleau, FRANCE
September 1980 - June 1984 Associate Professor of Management Science MIT Sloan School of Management Massachusetts Institute of Technology Cambridge, Massachusetts 02142
September 1975 - August 1980 Assistant Professor of Marketing and of Transportation (granted tenure and promoted in 1980) Graduate School of Management and Transportation Center Northwestern University Evanston, Illinois 60201
Teaching Interests Marketing Management, New Product and Service Development, Competitive Marketing Strategy, Marketing Models, Measurement and Marketing Research, Research Methodology, Marketing Analytics.
Research Interests Consumer decision measurement: conjoint analysis, non-compensatory methods, adaptive methods, machine- learning methods, strategic importance of accuracy. Product forecasting: information acceleration, really-new products, incentive-aligned games. Consumer behavior: cognitive simplicity in decision making and in dynamic models, theory-based models, vivid stimuli. Morphing: website, banner, product assortment. Voice of the customer methods, defensive and competitive strategy, new product development, experimental and quasi-experimental methods.
Books
Hauser, John R. and Glen L. Urban (2016), From Little's Law to Marketing Science: Essays in Honor of John D. C. Little, MIT Press: Cambridge MA.
This is an edited volume that serves as a Festschrift to honor the lifetime achievements of John D. C. Little.
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Urban, Glen L. and John R. Hauser (1993), Design and Marketing of New Products, 2E, Prentice-Hall.
A comprehensive text that integrates advanced, state-of-the-art techniques to provide graduate-level students and marketing professionals with an understanding of the techniques and an operating ability to design, test, and implement new products and services.
This text has been honored by being selected for both the Prentice-Hall International Series in Management and the Series in Marketing. It has been adopted at a number of major universities. In a 1988 survey it was identified the 1980 version as the most widely used new product textbook at the graduate level.
The revision includes new material on designing for quality, reduced cycle times, prelaunch forecasting, quality improvement, defensive and competitive strategy, value mapping, the integration of marketing and engineering, new issues of organization, customer satisfaction, and new international examples. It is available in Korean and is being translated into Japanese and Chinese. Many current texts draw heavily from our material.
Third most cited work in the Journal of Product Innovation, 1984-2004. (Cited May 2010.)
Urban, Glen L., John R. Hauser, and Niki Dholakia (1986), Essentials of New Product Management, Prentice Hall.
This is an undergraduate textbook which presents the essential concepts but written for a non-technical audience. It has been translated to Japanese and has sold well in Japan.
Hauser, John R. (1986), Applying Marketing Management: Four Simulations, Scientific Press.
This mini-text and software package contains four tutorial exercises for marketing management concepts. With this package students learn positioning, competitive strategy, new product development, and life cycle forecasting while using the personal computer to simulate marketing management problems. A detailed instructor's manual and transparency masters are also available. It is available in Japanese.
Hauser, John R. (1989), ENTERPRISE: An Integrating Management Exercise, Scientific Press.
This mini-text and software package contains a comprehensive competitive simulation. Students compete in six markets by making marketing and production decisions. A detailed instructor's manual and administrative software is also available. It is available in Japanese.
Journal Editor
Marketing Science, Editor-in-Chief for volumes 8, 9, 10, 11, 12, and 13 (1989-1994). Four issues per year including periodic editorials and journal management. Processed about 120 new papers per year. Special Editor for issues on the Theory and Practice of Marketing (2014) and Big Data (2016).
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Journal Publications (Almost all available for download at web.mit.edu/hauser/www.)
Citations Reports: December 28, 2018 Google Scholar; 27,697 citations and an H-index of 56. ISI Web of Science (automated, December 28, 2018): 6,214 citations with an H-index of 36. Not included in automatic ISI report: Design and Marketing of New Products (474 2E, 286 1E, 35 UG), Defensive Marketing Strategies (236), Testing Competitive Market Structures (94). Application of Defender (45), Dynamic Markov Application (28). Revised total of 7,412; revised ISI H-index of 38. Addition citations updated January 2018 (books) & December 2018 (articles).
Glen Urban, Artem Timoshenko, Paramveer Dhillon, and John Hauser (2020), “Cutting Through the Hype of Deep Learning," MIT Sloan Management Review, Winter, 71-76..
Hauser, John R., Felix Eggers, and Matthew Selove (2019), "The Strategic Implications of Scale in Choice-Based Conjoint Analysis," Marketing Science, 38, 6, 1059-1081..
Dzyabura, Daria and John R. Hauser (2019), "Recommending Products When Consumers Learn their Preferences," Marketing Science, 38, 3, 417-441.
Timoshenko, Artem and John R. Hauser (2019), "Identifying Customer Needs from User-Generated Content," Marketing Science, 38, 1, 1-20.
Lin, Song, Juanjuan Zhang, and John R. Hauser (2015), “Learning from Experience, Simply,” Marketing Science, 34, 1, (January-February), 1-19.
Finalist, John D. C. Little Award for Best Article in the Marketing Sciences Literature, 2015.
Hauser, John R., Guilherme Liberali , and Glen L. Urban (2014), “Website Morphing 2.0: Switching Costs, Partial Exposure, Random Exit, and When to Morph,” Management Science, 60, 6, (June), 1594–1616.
Hauser, John R. (2014), “Consideration-Set Heuristics,” Journal of Business Research, 67 (8), 1688-1699.
Urban, Glen L., Guilherme Liberali, Erin MacDonald, Robert Bordley, and John R. Hauser (2014), “Morphing Banner Advertisements,” Marketing Science, 33, 1.
Hauser, John R., Songting Dong, and Min Ding (2014), “ Self-Reflection and Articulated Consumer Preferences,” Journal of Product Innovation Management, 31, 1, 17-32.
Liberali, Guilherme, Glen L. Urban, and John R. Hauser (2013), “ Competitive Information, Trust, Brand Consideration, and Sales: Two Field Experiments ” International Journal for Research in Marketing, 30, 2, (June), 101-113.
Finalist, IJRM Best Paper Award, 2014.
Dzyabura, Daria and John R. Hauser (2011), “Active Machine Learning for Consideration Heuristics,” Marketing Science, 30, 5, (September-October), 801-819.
Hauser, John R. (2011), “A Marketing Science Perspective on Recognition-Based Heuristics (and the Fast and Frugal Paradigm),” Judgment and Decision Making, 6, 5, (July), 396-408.
Ding, Min, John Hauser, Songting Dong, Daria Dzyabura, Zhilin Yang, Chenting Su, and Steven Gaskin (2011), “Unstructured Direct Elicitation of Decision Rules,” Journal of Marketing Research, 48, (February), 116-127.
Hauser, John R., Olivier Toubia, Theodoros Evgeniou, Daria Dzyabura, and Rene Befurt (2010), “Disjunctions of Conjunctions: Cognitive Simplicity and Consideration Sets,” Journal of Marketing Research, 47, (June), 485-496.
Urban, Glen L., John R. Hauser, Guilherme Liberali, Michael Braun, and Fareena Sultan (2009), “Morph the Web to Build Empathy, Trust, and Sales,” Sloan Management Review, 50, 4, (Summer), 53-61.
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Hauser, John R., Glen L. Urban, Guilherme Liberali, and Michael Braun (2009), “Website Morphing,” Marketing Science., 28, 2, (March-April), 202-224. Lead article with commentaries by Andrew Gelman, John Gittins, and Hal Varian. Includes rejoinder.
Finalist, John D. C. Little Award for Best Article in the Marketing Sciences Literature, 2009.
Finalist, INFORMS Society for Marketing Science Long Term Impact Award, 2017, 2018, 2019
2010 Emerald Management Reviews Citation of Excellence for one of best articles published in the top 400 business and management journals in 2009. (Top 50 of 15,000 articles.)
Toubia, Olivier, John R. Hauser and Rosanna Garcia (2007), “Probabilistic Polyhedral Methods for Adaptive Choice- Based Conjoint Analysis: Theory and Application,” Marketing Science, 26, 5, (September-October), 596-610.
Co-winner, American Marketing Association, John Howard Dissertation Award, 2005
Yee, Michael, Ely Dahan, John Hauser, and James Orlin (2007), “Greedoid-Based Non-compensatory Two-Stage Consideration-then-Choice Inference,” Marketing Science, 26, 4, (July-August), 532-549.
First Place, American Marketing Association Explor Award, 2004
Toubia, Olivier and John R. Hauser (2007), “On Managerial Efficient Designs,” Marketing Science, 26, 6, (November- December), 851-858.
Garcia, Rosanna, Paul Rummel, and John R. Hauser (2007), “Validating Agent-Based Marketing Models Using Conjoint-Analysis,” Journal of Business Research, 60, 8, (August), 848-857.
Hauser, John R., Gerald Tellis, and Abbie Griffin (2006), “Research on Innovation: A Review and Agenda for Marketing Science,” Marketing Science, 25, 6, (November-December), 687-717.
Cited by Thomson Reuters’ Essential Science Indicators as a Fast Breaking Paper in Economics and Business in April 2009.
Cited in 2014 by the International Journal of Research in Marketing as one of the top 10 impactful articles published in Marketing Science during 2004-2012..
Hauser, John R. and Olivier Toubia (2005), “The Impact of Utility Balance and Endogeneity in Conjoint Analysis,” Marketing Science, 24, 3, (Summer), 498-507.
Glen L. Urban and John R. Hauser (2004), “’Listening-In’ to Find and Explore New Combinations of Customer Needs,” Journal of Marketing, 68, (April), 72-87.
Toubia, Olivier, John R. Hauser, and Duncan Simester (2004), “Polyhedral Methods for Adaptive Choice-based Conjoint Analysis,” Journal of Marketing Research, 41, 1, (February), 116-131.
Finalist, Paul Green Award for contributions to the practice of marketing research.
Toubia, Olivier, Duncan I. Simester, John R. Hauser, and Ely Dahan (2003), “Fast Polyhedral Adaptive Conjoint Estimation,” Marketing Science, 22, 3, (Summer), 273-303.
First Place, John D. C. Little Award for Best Article in the Marketing Sciences Literature, 2003
First Place, Frank M. Bass Award for Best Article Based on a Dissertation, 2005.
Finalist, INFORMS Society for Marketing Science Long Term Impact Award, 2011
Finalist, INFORMS Society for Marketing Science Long Term Impact Award, 2012
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Dahan, Ely and John R. Hauser (2002), “The Virtual Customer,” Journal of Product Innovation Management, 19, 5, (September), 332-354.
Finalist, PDMA Best Paper Award in 2003.
Hauser, John R. (2001), "Metrics Thermostat," Journal of Product Innovation Management, 18, 3. (May), 134-153.
Finalist PDMA Best Paper Award in 2002.
Cited by the PDMA in 2007 as one of the top articles in the last twenty years in educational citations.
Simester, Duncan I, John R. Hauser, Birger Wernerfelt, and Roland Rust (2000), "Implementing Quality Improvement Programs Designed to Enhance Customer Satisfaction: Quasi-experiments in the United States and Spain," Journal of Marketing Research, 37, 1, (February), 102-112.
Hauser, John R. (1998), "Research, Development, and Engineering Metrics." Management Science, 44, 12, December, 1670-1689.
Hauser, John R. and Gerry Katz (1998), “Metrics: You Are What You Measure!.” European Management Journal, 16, 5, (October), 516-528. Highlighted in “A Round-up of Important Articles from Business Periodicals,” in Mastering Management Review published by the Financial Times.
Hauser, John R., Duncan I. Simester, and Birger Wernerfelt (1997), "Side Payments in Marketing," Marketing Science, 16, 3, 246-255.
Finalist, John D. C. Little Award for Best Article in the Marketing Sciences Literature, 1997.
Urban, Glen L., John R. Hauser, William J. Qualls, Bruce D. Weinberg, Jonathan D. Bohlmann and Roberta A. Chicos (1997), "Validation and Lessons from the Field: Applications of Information Acceleration," Journal of Marketing Research, 34, 1, (February), 143-153.
Hauser, John R. and Florian Zettelmeyer (1997), “Metrics to Evaluate R,D&E,” Research Technology Management, 40, 4, (July-August), 32-38.
Griffin, Abbie, and John R. Hauser (1996), "Integrating Mechanisms for Marketing and R&D," Journal of Product Innovation Management, 13, 3, (May), 191-215.
One of ten most-cited papers in the Journal of Product Innovation Management (JPIM 24, 3, 2007, p.209)
Hauser, John R., Duncan I. Simester, and Birger Wernerfelt (1996), "Internal Customers and Internal Suppliers," Journal of Marketing Research, 33, 3, (August), 268-280. Urban, Glen L., Bruce Weinberg and John R. Hauser (1996), "Premarket Forecasting of Really-New Products," Journal of Marketing, 60,1, (January), 47-60. Abstracted in the Journal of Financial Abstracts, 2, 23A, (June) 1995.
1996 MSI Award for the most significant contribution to the advancement of the practice of marketing. Hauser, John R., Duncan I. Simester, and Birger Wernerfelt (1994), "Customer Satisfaction Incentives," Marketing Science, 13, 4, (Fall), 327-350.
Finalist, John D. C. Little Award for Best Article in the Marketing Sciences Literature, 1994. Hauser, John R., Glen L. Urban, and Bruce Weinberg (1993), "How Consumers Allocate their Time When Searching for Information," Journal of Marketing Research,30, 4, (November), 452-466.
Hauser, John R. (1993), "How Puritan Bennett Used the House of Quality," Sloan Management Review, 34, 3, (Spring), 61-70. Reprinted in Taiwan Philips News (in Chinese), 23, 1, (Feb), 1994.
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Griffin, Abbie and John R. Hauser (1993), "The Voice of the Customer," Marketing Science, 12, 1, (Winter), 1-27.
First-place, John D. C. Little Award for Best Article in Marketing Sciences Literature, 1993.
First Place, Frank M. Bass Award for Best Article Based on a Dissertation, 1995.
Cited in 2007 by the INFORMS Society of Marketing Science as one “of the top 20 marketing science articles in the past 25 years.
Cited in 2014 by the International Journal of Research in Marketing as one of the top 10 academically most impactful marketing science papers.
Griffin, Abbie and John R. Hauser (1992), "Patterns of Communication Among Marketing, Engineering, and Manufacturing -- A Comparison between Two New Product Teams," Management Science, 38, 3, (March), 360- 373.
One of the 500 most-cited articles in the first 50 years of Management Science.
Urban, Glen. L., John. R. Hauser, and John. H. Roberts (1990), "Prelaunch Forecasting of New Automobiles: Models and Implementation," Management Science, 36, 4, (April), 401-421. Reprinted in Modeling for Management, Vol. 1, George P. Richardson, ed., Dartmouth Publishing Co., Hampshire England.
INFORMS (TIMS) Finalist, Best Article in Marketing Science Literature, 1990.
Hauser, John R. and Birger Wernerfelt (1990), "An Evaluation Cost Model of Consideration Sets," Journal of Consumer Research, 16, (March), 393-408.
Hauser, John R. and Birger Wernerfelt (1989), "The Competitive Implications of Relevant-Set/Response Analysis," Journal of Marketing Research, 26, 4, (November), 391-405.
Hauser, John R. and Don Clausing (1988), "The House of Quality," Harvard Business Review, 66, 3, (May-June), 63-73. Reprinted in The Product Development Challenge, Kim B. Clark and Steven C. Wheelwright, eds., Harvard Business Review Book, Boston MA 1995. Reprinted in IEEE Engineering Management Review, 24, 1, Spring 1996. Translated into German and published in Hermann Simon and Christian Homburg (1998), Kunderzufriedenheit, (Druck and Buchbinder, Hubert & Co.: Gottingen, Germany).
Fader, Peter and John R. Hauser (1988), "Implicit Coalitions in a Generalized Prisoner's Dilemma," Journal of Conflict Resolution, 32, 3, (September), 553-582.
Hauser, John R. (1988), "Competitive Price and Positioning Strategies," Marketing Science, 7, 1, (Winter), 76-91.
Hauser, John R. (1986), "Agendas and Consumer Choice," Journal of Marketing Research, 2 , 3, (August), 199-212. (Includes unpublished appendix containing "Proofs of Theorems and Other Results." ) Reprinted in Gregory S. Carpenter, Rashi Glazer, and Kent Nakamota (1997), Readings on Market-Driving Strategies, Towards a New Theory of Competitive Advantage, (Reading, MA: Addison-Wesley Longman ,Inc.)
Finalist, 1991 American Marketing Associations O'dell Award for Best Paper in JMR (5-year lag)
Hauser, John R. and Glen L. Urban (1986), "Value Priority Hypotheses for Consumer Budget Plans," Journal of Consumer Research, 12, 4, (March), 446-462.
Eliashberg, Jehoshua and John R. Hauser (1985), "A Measurement Error Approach for Modeling Consumer Risk Preference," Management Science, 31, 1, (January), 1-25.
Hauser, John R., and Steven P. Gaskin (1984), "Application of the `DEFENDER' Consumer Model," Marketing Science, 3, 4, (Fall), 327-351. Reprinted (in French) in Recherche et Applications on Marketing, Vol. 1, April 1986,
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pp. 59-92.
Urban, Glen L., P. L. Johnson and John R. Hauser (1984), "Testing Competitive Market Structures," Marketing Science, 3, 2, (Spring), 83-112.
INFORMS (TIMS) Finalist, Best Article in Marketing Science Literature, 1984.
Hauser, John R. (1984), "Consumer Research to Focus R&D Projects" Journal of Product Innovation Management, 1, 2, (January), 70.84.
Hauser, John R., and Steven M. Shugan (1983), "Defensive Marketing Strategy," Marketing Science, 2, 4, (Fall), 319-360.
INFORMS (TIMS) Best Article in Marketing Science Literature, 1983.
Cited in 2007 by the INFORMS Society of Marketing Science as one “of the top 20 marketing science articles in the past 25 years.
Republished in 2008 as one of eight “classic” articles in Marketing Science.
Cited in 2014 by the International Journal of Research in Marketing as one of the top 10 academically most impactful marketing science papers.
Hauser, John R., and Kenneth J. Wisniewski (1982), "Application Predictive Test, and Strategy Implications of a Dynamic Model of Consumer Response," Marketing Science, 1, 2, (Spring), 143-179.
Hauser, John R., and Kenneth J. Wisniewski (1982), "Dynamic Analysis of Consumer Response to Marketing Strategies," Management Science, 28, 5, (May), 455-486.
INFORMS (TIMS) Best Article in Marketing Science Literature, 1982.
Tybout, Alice M. and John R. Hauser (1981), "A Marketing Audit Using a Conceptual Model of Consumer Behavior: Application and Evaluation," Journal of Marketing, 45, 3, (Summer), 81-101.
Hauser, John R., and Patricia Simmie (1981), "Profit Maximizing Perceptual Positions: An Integrated Theory for the Selection of Product Features and Price," Management Science, 27, 2, (January), 33-56.
One of the 500 most-cited articles in the first 50 years of Management Science.
Hauser, John R., Frank S. Koppelman and Alice M. Tybout (1981), "Consumer-Oriented Transportation Service Planning: "Consumer Analysis and Strategies," Applications of Management Science, 1, 91-138.
Hauser, John R., and Steven M. Shugan (1980), "Intensity Measures of Consumer Preference," Operation Research, 28, 2, (March-April), 278-320.
Hauser, John R., and Frank S. Koppelman (1979), "Alternative Perceptual Mapping Techniques: Relative Accuracy and Usefulness, Journal of Marketing Research, 16, 4, (November), 495-506.
Hauser, John R., and Glen L. Urban (1979), "Assessment of Attribute Importances and Consumer Utility Functions: von Neumann-Morgenstern Theory Applied to Consumer Behavior," Journal of Consumer Research, 5, (March), 251-262.
Koppelman, Frank S. and John R. Hauser (1979), "Destination Choice Behavior for Non-Grocery Shopping Trips," Transportation Research Record, 673, 157-165.
Hauser, John R. (1978), "Consumer Preference Axioms: Behavioral Postulates for Describing and Predicting Stochastic Choice," Management Science, 24, 13, (September), 1331-1341.
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Hauser, John R. (1978), "Testing the Accuracy, Usefulness and Significance of Probabilistic Models: An Information Theoretic Approach," Operations Research, 26, 3, (May-June), 406-421.
Hauser, John R. and Glen L. Urban (1977), "A Normative Methodology for Modeling Consumer Response to Innovation," Operations Research, 25, 4. (July-August), 579-619.
Published Notes and Commentaries Hauser, John R. (2016), “The Marketing Science Revolution and Subsequent Evolution,” 103rd Dies Natalis of Erasmus University, November 2016.
Hauser, John R. (2016), “Phenomena, Theory, Application, Data, and Methods all Have Impact,” Journal of the Academy of Marketing Sciences, forthcoming.
Chintagunta, Pradeep, Dominique Hanssens, John R. Hauser (2016), “Marketing Science and Big Data,” Marketing Science, 35, 1, 1-2.
Hauser, John R. (2016), “Paul E. Green: An Applications’ Guru,” in Vithala Rao and V. Srinivasan, Eds., Paul Green’s Legends Volume: Conjoint Analysis Applications, (Newbury Park, CA: Sage Publications). Forthcoming.
Hauser, John R. (2016), “Perspectives on Paul E. Green,” in Vithala Rao and V. Srinivasan, Eds., Paul Green’s Legends Volume: Paul Green’s Contributions to Conjoint Analysis – Early Years, (Newbury Park, CA: Sage Publications). Forthcoming.
Sunil Gupta, Dominique Hanssens, John Hauser, Donald Lehmann, and Bernd Schmitt (2014), “Theory and Practice in Marketing Special Section in Marketing Science,” Marketing Science, 33, 1.
Chintagunta, Pradeep, Dominique Hanssens, John R. Hauser, Jagmohan Singh Raju, Kannan Srinivasan, and Richard Staelin (2013), “Marketing Science: A Strategic Review,” Marketing Science, 33, 1, (January-February).
Hauser, John R. (2011), “New Developments in Product-Line Optimization,” International Journal on Research in Marketing, 28, 26-27. Commentary on papers by Michalek, Ebbes, Adigüzel, Feinberg, and Papalambros, “Enhancing Marketing with Engineering,” and Tsafarakis, Marinakis, and Matsatsinis, “Particle Swarm Optimization for Optimal Product Line Design.”
Hauser, John R. and Steven M. Shugan (2007), “Comments on ‘Defensive Marketing Strategy,’” Marketing Science, 27, 1, (January-February), 85-87.
Rangaswamy, Arvind , Jim Cochran, Tülin Erdem, John R. Hauser, and Robert J. Meyer (2007), “Editor-in-Chief Search Committee Report: The Digital Future is Here,” Marketing Science, 27, 1, (January-February), 1-3.
Hauser, John R. (2006), “Twenty-Five Years of Eclectic Growth in Marketing Science,” Marketing Science (invited commentary), 25, 6, (November-December), 557-558.
Hauser, John R., Greg Allenby, Frederic H. Murphy, Jagmohan Raju, Richard Staelin, and Joel Steckel (2005), “Marketing Science – Growth and Evolution,” Marketing Science, 24, 1, (Winter), 1-2, invited editorial.
Hauser, John R., Scott Carr, Barbara Kahn, James Hess, and Richard Staelin (2002), "Marketing Science: A Strong Franchise with a Bright Future," Marketing Science, 21, 1, (Winter), invited editorial.
Hauser, John R. (1984), "Price Theory and the Role of Marketing Science," Journal of Business, Vol. 57, No. 1, (January), S65-S72. Hauser, John R. (1980), "Comments on 'Econometric Models of Probabilistic Choice Among Products'," Journal of Business, 53, 3, Part 2, (July 1980), S31-S34.
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Papers in Edited Volumes and/or Proceedings
Eggers, Felix, John R. Hauser, Matthew Selove (2016), “The Effects of Incentive Alignment, Realistic Images, Video Instructions, and Ceteris Paribus Instructions on Willingness to Pay and Price Equilibria,” forthcoming, Proceedings of the Sawtooth Software Conference, Park City, Utah ,September 28-30, 2016.
Honorable Mention, Best Paper at Sawtooth Software Conference, 2016.
Timoshenko, Artem and John R. Hauser (2016). “Mining and Organizing User-Generated Content to Identify Attributes and Attribute Levels,” forthcoming, Proceedings of the Sawtooth Software Conference, Park City, Utah ,September 28-30, 2016.
Hauser, John R. (2016), “Comments on “How Many Options? Behavioral Responses to Two Versus Five Alternatives Per Choice” by Martin Meissner, Harmen Oppewal, And Joel Huber, Proceedings of the Sawtooth Software Conference, Park City, Utah ,September 28-30, 2016.
Liberali, Gui, John R. Hauser, and Glen L. Urban (2017), "Morphing Theory and Applications," forthcoming, Handbook of Marketing Decision Models (New Edition, 2017), International Series in Operations Research & Management Science published by Springer Science and Business Media, Berend Wierenga and Ralf van der Lans, Editors.
Selove, Matthew and John R. Hauser (2010), “How Does Incorporating Price Competition into Market Simulators Affect Product Design Decisions?,” Proceedings of the Sawtooth Software Conference, Newport Beach, CA, Oct 6- 8, 2010.
Hauser, John R. and Glen L. Urban (2009), “Profile of John D. C. Little,” in Saul I. Gass and Arjang A. Assad eds. Profiles in Operations Research, (New York, NY: Springer).
Ding, Min, Steven Gaskin, and John Hauser (2009), “A Critical Review of Non-compensatory and Compensatory Models of Consideration-Set Decisions,” 2009 Sawtooth Software Conference Proceedings, Delray, FL, March 23- 27, 2009, 207-232.
Runner-up, Best Paper at Sawtooth Software Conference, 2009.
Gaskin, Steven, Theodoros Evgeniou, Daniel Bailiff, John Hauser (2007), “Two-Stage Models: Identifying Non- Compensatory Heuristics for the Consideration Set then Adaptive Polyhedral Methods Within the Consideration Set,” Proceedings of the Sawtooth Software Conference in Santa Rosa, CA, October 17-19, 2007.
Hauser, John R. and Ely Dahan (2010), “New Product Development,” in Rajiv Grover, Ed., Essentials of Marketing Management, (Englewood Cliffs, NJ: Prentice Hall), forthcoming January 2011.
Toubia, Olivier, Theodoros Evgeniou, and John Hauser (2007), “Optimization-Based and Machine-Learning Methods for Conjoint Analysis: Estimation and Question Design,” in Anders Gustafsson, Andreas Herrmann and Frank Huber, Eds, Conjoint Measurement: Methods and Applications, 4E, (New York, NY: Springer). 231-258.
Hauser, John R., Ely Dahan, Michael Yee, and James Orlin (2006), ““Must Have” Aspects vs. Tradeoff Aspects in Models of Customer Decisions,” Proceedings of the Sawtooth Software Conference in Del Ray Beach, FL, March 29-31, 2006
Best Paper at the Sawtooth Software Conference, 2006.
Hauser, John R. and Vithala Rao (2004), “Conjoint Analysis, Related Modeling, and Applications,” Advances in Market Research and Modeling: Progress and Prospects,, Jerry Wind and Paul Green, Eds., (Boston, MA: Kluwer Academic Publishers), 141-168.
Dahan, Ely and John R. Hauser (2003), "Product Management: New Product Development and Launching," Handbook of Marketing, Barton Weitz and Robin Wensley, Eds, Sage Press, (June), 179-222.
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Hauser, John R. (1997), “The Role of Mathematical Models in the Study of Product Development,” Proceedings of the 14th Paul D. Converse Awards Conference, University of Illinois, Champaign-Urbana, IL, 72-90.
Swanson, Derby A. and John R. Hauser (1995), "The Voice of the Customer: How Can You Be Sure You Know What Customers Really Want?," Proceedings of the 1st Pacific Rim Symposium of Quality Function Deployment, MacQuarie University, NSW Australia, February 15-17.
Little, John D. C., Leonard M. Lodish, John R. Hauser, and Glen L. Urban (1993), "Comment on `Marketing Science's Pilgrimage to the Ivory Tower' by Hermann Simon," in Research Traditions in Marketing, Gary L. Lilien, Bernard Pras, and Gilles Laurent, eds, (Kluwer), 45-51.
Hauser, John R. (1986), "Theory and Application of Defensive Strategy" in The Economics of Strategic Planning, Lacy G. Thomas, ed., (Lexington Books, D. C. Heath & Co.: Lexington, MA), 113-140. Reprinted by the Marketing Science Institute.
Hauser, John R. (1985), "The Coming revolution in Marketing Theory," in R. Russell, ed., Marketing in an Electronic Age, (Harvard Business School Press: Boston, MA), 344-363.
Hauser, John R. and Glen L. Urban (1984), "Consumer Durables: Actual Budgets Compared to Value Priority Model - Preliminary Results and Managerial Implications," Proceedings of the ESOMAR-Congress, Rome, Italy, (September).
Best Paper at ESOMAR Rome Conference, 1984.
Hauser, John R., John H. Roberts and Glen L. Urban (1983), "Forecasting Sales of a New Consumer Durable: A Prelaunch Modeling and Measurement Methodology," Advances and Practices of Marketing Science, Fred S. Zufryden, ed., (The Institute of Management Science: Providence, RI), 115-128.
Hauser, John R., and Glen L. Urban (1982), "Prelaunch Forecasting of New Consumer Durables: Ideas on a Consumer Value-Priority Model," in A. D. Shocker and R. Srivastava, eds., Analytic Approaches to Product and Market Planning, Vol. 2, (Marketing Science Institute: Cambridge Massachusetts), 276-296.
Hauser, John R. (1982), "Comments on 'A Survey of Experimental Market Mechanisms for Classical Environments'," Research in Marketing, Supplement 1: Choice Models for Buyer Behavior, L. McAlister, ed., (JAI Press: Greenwich, CT), Spring, 49-56.
Hauser, John R. (1981), "Comments on 'Violations of Regularity and the Similarity Hypothesis by Adding Asymmetrically Dominated Alternatives to the Choice Set'," Proceedings of the Special Conference on Choice Theory, Joel Huber, ed., (Duke University: Durham, NC), June.
Hauser, John R., and Frank S. Koppelman (1979), "An Empirical Comparison of Techniques to Model Consumer Perceptions and Preferences," in A. D. Shocker, ed., Analytic Approaches to Product and Marketing Planning, (Marketing Science Institute: Cambridge, Massachusetts), 216-238.
Tybout, Alice M., John R. Hauser, and Frank S. Koppelman (1977), "Consumer-Oriented Transportation Planning: An Integrated Methodology for Modeling Consumer Perceptions, Preferences and Behavior," Advances in Consumer Research, Vol. 5, (Chicago, Illinois), October. Hauser, John R. and Steven M. Shugan (1977), "Extended Conjoint Analysis with Intensity Measures and Computer Assisted Interviews: Applications to Telecommunications and Travel, " Advances in Consumer Research, Vol. 5, (Chicago, Illinois), October.
Hauser, John R. and Frank S. Koppelman (1977), "Designing Transportation Services: A Marketing Approach." Proceedings of the Transportation Research Forum, (Atlanta, GA), October, 638-652.
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Hauser, John R. and Peter R. Stopher (1976), "Choosing an Objective Function Based on Modeling Consumer Perceptions and Preferences," Proceedings of the International Conference on Cybernetics and Society, (Washington, D.C.), November, 26-31.
Magazine Article, Etc.
Hauser, John R (2017). "How companies like United and Wells Fargo can win back consumer trust." The Conversation, April 19, 2017.
Chintagunta, Pradeep, Dominique Hanssens, John R. Hauser (2016), “Marketing and Data Science: Together the Future is Ours,” forthcoming, The GfK Marketing Intelligence Review, Special Issue on Data Science, November 2016
Hauser, John R., Abbie Griffin, and Steve Gaskin (2011), “The House of Quality,” Wiley International Encyclopedia of Marketing, (Chichester, West Sussex UK: John Wiley & Sons, Ltd.).
Abbie Griffin, Steve Gaskin, Robert Klein, Gerry Katz, and John R. Hauser (2009), “The Voice of the Customer,” Wiley International Encyclopedia of Marketing, (Chichester, West Sussex UK: John Wiley & Sons, Ltd.).
Hauser, John R. (2002), “Marketing Makes a Difference,” Marketing Management, (January/February), 11, 1, 46- 47.
Hauser, John R. (2000), “Going Overboard on Platforms,” AMS Voices, 8.
Hauser, John R. (1997), “The Problem with Pinball,” AMS Voices, 4.
Hauser, John R. (1996), "You Are What You Measure," AMS Voices, 1.
Hauser, John R. (1995), "Internal Customers," Insight, 4, 1.
Hauser, John R. (1994), "Quality Function Deployment," Marketing Encyclopedia for the Year 2000, Jeffrey Heilbrunn, ed., American Marketing Association, Chicago, IL, 60606.
Hauser, John R. (1993), "Are Customer-Satisfaction Programs Profitable?, Insight, 3.
Hauser, John R. (1988), "Customer Driven Engineering," Design News, (July 18), p. 50.
Hauser, John R. and Robert L. Klein (1988), "Without Good Research, Quality is a Shot in the Dark," Marketing News, Vol. 22, No. 1, January 4. Page 1.
Hauser, John R. (1986), "`Defender' Helps Mature Brands Ward off New Foes," Marketing Educator, 5, 3, (Fall), 5.
Working Papers
Dzyabura, Daria, Siham El Kihal, John R. Hauser, and Marat Ibragimov (2019), "Leveraging the Power of Images in Predicting Product Return Rates, " (Cambridge, MA: MIT Sloan School of Management). Under review, Marketing Science.
Eggers, Felix, John R. Hauser, Matthew Selove (2017), “Scale Matters: How Craft in Conjoint Analysis Affects Price and Positioning Strategies,” (Cambridge, MA: MIT Sloan School of Management).
Burnap, Alex and John R. Hauser (2019), "Design and Evaluation of Product Aesthetics: A Human-Machine Hybrid Approach," (Cambridge, MA: MIT Sloan School of Management). Under review, Marketing Science.
Burnap, Alex and John R. Hauser (2019), "Predicting “Design Gaps” in the Market: Deep Consumer Choice Models under Probabilistic Design Constraints," (Cambridge, MA: MIT Sloan School of Management).
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Davide Proserpio, John R. Hauser, Tomomichi Amano, Alex Burnap, Tong Guo, Dokiun Lee, Xiao Liu, Randall Lewis, Kanishka Misra, Eric Schwarz, Artem Timoshenko, Lilei Xu, Hema Yoganarasimhan (2019), „Soul and Machine (Learning),“ (Cambridge, MA: MIT Sloan School of Management). Under review, Marketing Letters.
Classic Working Papers (Support published papers with additional information)
Braun, Michael, Clarence Lee, Glen L. Urban, and John R. Hauser (2009), “Does Matching Website Characteristics to Cognitive Styles Increase Online Sales?,” (Cambridge, MA: MIT Sloan School of Management).
Zettelmeyer, Florian and John R. Hauser (1995), "Metrics to Evaluate R&D Groups: Phase I, Qualitative Interviews," Working Paper, International Center for Research on the Management of Technology, MIT, Cambridge, MA, 02142.
Hauser, John R. (1991), "Comparison of Importance Measurement Methodologies and their Relationship to Consumer Satisfaction," (Cambridge, MA: MIT Sloan School of Management).
Shugan, Steven M. and John R. Hauser (1978), „Designing and Building a Marketing Research Information System,“ Working Paper, Northwestern University, Evanston, IL.
Research in Progress
Field application and test of website morphing.
The effect of vivid stimuli in conjoint analysis. Machine learning to identify non-linearities.
Fractional updating for Multiarm bandit approaches to the design of randomized medical clinical trials
Research Reports (not otherwise listed)
Hauser, John R. (1996), “R&D Metrics: An Annotated Bibliography,” ICRMOT Working Paper, M.I.T., Cambridge, MA 02142. (June) Also available as a Marketing Science Institute Working Paper (November).
Hauser, John R. and Greg Cirmak (1987), "Consumer Driven Engineering for the CHEK Automobiles," Information Resources, Inc. Report to General Motors, Inc. Details the results of a major study on consumer perceptions and preferences of luxury automobiles. April.
Hauser, John R. (1983), "Critique of Market Studies for Cellular Radio Telephone:. Affidavits before the FCC evaluating market studies, June and September.
Hauser, John R. (1983), "Forecasts of Demand and Cellular Radio Telephone,: Affidavits before the FCC for five major and nine minor markets. June and April.
Hauser, John R., and J. Bertan (1982), "Auto Show Interviews," Internal Report to Buick Division of General Motors, June.
Hauser, John R., and Kenneth J. Wisniewski (1981), "Monitoring the Implementation of Innovative Transportation Services, Phase I: Final Report," Technical Report to the Urban Mass Transit Administration, Research Grant IL-11- 0012, May.
Hauser, John R. and Kenneth J. Wisniewski (1979), "Consumer Analysis for General Travel Destinations," Technical Report, Transportation Center, Northwestern University, March.
Hauser, John R. and Steven M. Shugan (1978), "Designing and Building a Market Research Information System," Technical Report, Transportation Center, Northwestern University, February.
Hauser, John R. (1978), "Forecasting and Influencing the Adoption of Technological Innovations," Technical
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Report, Transportation Center, Northwestern University, October.
Hauser, John R., Alice M. Tybout and Frank S. Koppelman (1978), "Consumer-Oriented Transportation Services Planning: The Development and Implementation of a Questionnaire to Determine Consumer Wants and Needs," Technical Report, Transportation Center, Northwestern University, October.
Tybout, Alice M., Frank S. Koppelman and John R. Hauser (1977), "Consumer Views of Transportation in Evanston: A Report Based on Focus Group Interviews," Technical Report, Transportation Center, Northwestern University, June.
Koppelman, Frank S., John R. Hauser and Alice M. Tybout (1977), "Preliminary Analysis of Perceptions, Preferences, Beliefs and Usage of Transportation Services for Travel to Downtown Evanston," Technical, Report, Transportation Center, Northwestern University, May.
Hauser, John R. (1977), "Results of the Focus Group Interviews for Shared Ride Auto Transit," Cambridge Systematics Consultant's Report, May.
Hauser, John R. (1976), "Report on the Applicability of Attitudinal research for Improving the Effectiveness of Transportation Demand Models," Position Paper commissioned by Cambridge Systematics, Inc., April.
Wilson, Nigel, R. W. Weissberg and John R. Hauser (1976), "Advanced Dial-a-Ride Algorithms--Final Report," M.I.T. Department of Civil Engineering Technical Report, April.
Hauser, John R., et al. (1974), "The Chemung County Transit Survey." Volunteers in Technical Assistance (a division of VISTA) publication for Chemung County, NY, June. (Includes analysis of transportation options based on the results of the survey designed and implemented by the technical team.)
Hauser, John R. (1974), "A Cost Model for RTS (Rochester, NY) Conventional Bus Routes," M.I.T., Department of Civil Engineering Report, January.
Hauser, John R. (1973), "An Efficient Model for Planning Bus Routes in Communities with Populations Between 20,000 and 250,000," M.I.T., Operations Research Center Working Paper OR-029-993, November.
Research Grants
July 2007 – June 2008 Understanding Non-compensatory Decision Making for Consideration Decisions (under Consortium with MIT Center for eBusiness and General Motors, Inc.)
June 2000 – May 2006 Center for Innovation in Product Development, MIT, Initiative Leader, Virtual Customer.
January 2001 – May 2002 eBusiness Center at MIT. Design and Delivery of Online Promotions. (with John Little, Duncan Simester, and Glen Urban).
January 1997 – May 2000 Center for Innovation in Product Development, Engineering Research Center Grant from the National Science Foundation. Research Director. In addition, research grants for non-monetary incentives, procurement metrics, and virtual customer methods.
June 1999 – May 2000 “Metrics Thermostat,” International Center for Research on the Management of Technology (Principal Investigator).
June 1999- May 2001 “New Product Metrics at Ford and the US Navy,” Center for Innovation in Product Development
June 1999- May 2001 “Lean Sustainment Metrics at the USAF,” Lean Sustainment Initiative at MIT
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June 1994 - May 1999 "Metrics to Value R&D," International Center for Research on the Management of Technology (Principal Investigator). General topic. Detailed proposals were for various aspects of the problem.
June 1991 - May 1994 "Customer Needs, Customer Satisfaction, Sales, and Profit: Providing the Right Incentives to Engineering and R&D," International Center for Research on the Management of Technology (co-Principal Investigator with Birger Wernerfelt)
January 1990 - June 1992 "Information Acceleration and Preproduction Forecasting of New Autos, Phases I and II." General Motors Electric Vehicle Project. (Associate)
December 1988 - June 1990 "Improved Methodologies to Measure Consumer Needs," Procter & Gamble Company. (Principal Investigator)
September 1981 - December 1985 "Prelaunch Forecasting System for New Consumer Durables and Its Applications to Auto Purchases," General Motors, Buick Division (co-Principal Investigator with Glen L. Urban).
January 1981 - May 1981 "Marketing Approaches in Travel Demand," United Parcel Service Grant (Faculty Advisor). January 1979 - August 1980 "Monitoring the Implementation of Innovative Public Transportation Services" from University Research Program of the Urban Mass Transportation Administration (Principal Investigator). July 1975 - September 1977 "Consumer-Oriented Transportation Service Planning." from the Program of University Research, U.S. Department of Transportation (Faculty Associate).
September 1977 - January 1978 "Consumer-oriented Transportation Service: Modification and Evaluation" from Program of University Research, USDOT (Faculty Associate).
May 1976 - September 1978 "Enhancement of Communications with a Small Scientific Community Using Slow-Scan Televideo Terminals and Voice-Grade Telephone Lines" from the National Science Foundation (Faculty Associate).
January 1976 - December 1976 "A Method for Assessing Pricing and Structural Changes on Transport Mode Use," U.S. Department of Transportation (Faculty Associate).
September 1976 - June 1977 "Prediction of Urban Recreational Demand" from the National Science Foundation (Faculty Consultant).
Invited Lectures (Outside the MIT Sloan School)
Carnegie Mellon University, April 8, 2016, “The Effect of Precision on Strategic Positioning.”
University of North Carolina, Kenan-Flagler Business School, Marketing Department. March 7, 2014. “Learning from Experience, Simply.”
Marketing Science Institute, November 2012, “Panel Discussion: Perspectives on Big Data from Marketing Scholars,” Cambridge, MA.
Wharton School, University of Pennsylvania, April 2009, “Website Morphing”
Max Planck Institute for Human Development, Center for Adaptive Behavior and Cognition, Summer Institute on Bounded Rationality in Psychology and Economics, August 2006, “Greedoid-Based Non-Compensatory Consider-then-Choice Inference.”
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Northwestern University, Evanston, IL, April 2006, “Greedoid-based Non-compensatory Inference.”
University of Michigan, Seminar Series, October 2004, “Table Stakes: Non-compensatory Consideration-then- Choice Inference.”
Management Roundtable Special Conference on “Taking the Voice of the Customer to the Next Level,” Boston, MA October 2004, “The Virtual Customer.”
Marketing Science Institute Research Generation Conference, Atlanta, GA, May 2004, “New Products/Innovation,” (with Gerry Tellis).
Marketing Science Institute Conference on Emerging Approaches for Successful Innovation, Chicago, IL, May 2003, "'Listening-In' to Find Unmet Customer Needs and Solutions."
University of California at Los Angeles, "Polyhedral CBC (and other fun stuff), February 2003
New York University, "Polyhedral Methods," March 2003.
Industrial Liaison Program – Research Directors' Conference, April 2002, "The Virtual Customer."
University of Maryland, "Polyhedral Methods for Conjoint Analysis," March 2002.
Marketing Science Institute Trustees Meeting on Marketing Outside the Silo, Boston, MA, April 2002, "Challenges and Visions for Marketing's Role in Product Development Processes."
Managing Corporate Innovation -- ILP Symposium celebrating ten years of Management of Technology Research at MIT. “Dealing with the Virtual Customer: Fast Web-based Customer Input.” April 2001
Epoch Foundation, Cambridge, MA, October 2000, “The Virtual Customer.”
Yale University Research Seminar in Marketing, New Haven, CN, March 2000, "Metrics Thermostat."
Analysis Group Economics Seminar, Boston, MA, December 1999, "The Use of Marketing Research in Litigation." Also New York, NY, March 2000 and Washington, D. C., March 2002.
Boston Chapter of the Society for Concurrent Engineering, Waltham, MA, October 1999, "Metrics Thermostat."
University of Michigan DuPont Distinguished Speakers’ Series, Ann Arbor, MI, March 1998, “New Product Metrics.”
Kirin Brewery Co. Limited, Tokyo, JAPAN, December 1998, “You Are What You Measure!” and “Scientific Studies of the Voice of the Customer.”
NEC Corporation, Tokyo, JAPA, December 1998, “Scientific Studies of the Voice of the Customer.”
University of California at Los Angeles, Los Angeles, CA, February 1997, “Research, Development, and Engineering Metrics”
Stanford University, Stanford, CA, December 1996, “Metrics to Value R,D&E”
University of California at Los Angeles, Los Angeles, CA, February 1997, “Research, Development, and Engineering Metrics”
Duke University, Durham, NC, "Internal Customers and Internal Suppliers," Nov. 1995.
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University of Minnesota, Minneapolis, MN, "Voice of the Customer," "Internal Customers and Captive Suppliers," May 1995.
Winter Retreat, University of Florida, Gainesville, FL, "Internal Customers and Captive Suppliers," December 1993.
Product Development Association - Boston, "Design and Marketing of New Products II: Advances in Product Development Management over the Last 13 Years," May 1993.
3M, Minneapolis, MN, "Incentives to Encourage a Long-term Perspective and a Customer Focus," Workshop on "Towards a World-class Research, Development, and Engineering Organization," November 1992.
Baxter Health Care, Orange County, CA, "The Voice of the Customer," August 1992.
TIMS College on the Practice of Management Science (New Directions in Management Science), Cambridge, MA: "The Voice of the Customer," October 1991.
IBM, Inc., Boca Raton, FL: "Voice of the Customer for Performance Graphics," May 1991.
Kirin Brewery Company, Ltd. Tokyo, JAPAN: "New Product Development" and "Customer Satisfaction and Customer Needs," April 1991.
American Iron and Steel Institute, Detroit, MI: "Satisfying the Customer -- Technical Issues," February 1991.
Warner Lambert, Inc., Mountain Laurel, PA: "Communication Among R&D and Marketing," October 1990.
Digital Equipment Corporation, Maynard, MA: "Voice of the Customer," May 1990.
Life Insurance Marketing and Research Association, Inc.: 31st Research Planning Conference, Boston, MA, "The House of Quality." June 1989.
University of Illinois: "Customer Driven Engineering." April, 1988.
Marketing Science Institute and IBM Thornwood Educational Facility: Quality through Customer Driven Engineering." April, 1988.
Harvard Business School: "Customer Driven Engineering: Integrating Marketing and Engineering." February, 1988.
Vanderbilt University: "Competitive Price and Advertising Strategies" and "Customer Driven Engineering." October, 1988.
Columbia University: "Price, Positioning, and Advertising Games: To Equilibrate of Not, Does it Pay to be Smart?" May, 1987.
New York Marketing Modelers' Club: "Would You Really Rather Have a Buick?: Prelaunch Forecasting of New Automobiles," May 1987.
M.I.T. Applied Economics: "Competitive Product Selection and Advertising Models." April, 1987.
Northwestern University: "Agendas and Consumer Choice," August, 1986.
AMA Faculty Consortium on Marketing Strategy at the University Tennessee, Knoxville. "Defender: Analyses for Competitive Strategy," July, 1986.
Ohio State University: "Defensive and Competitive Strategy." May, 1986.
Boston University: "Research in Competitive Strategy." November, 1985.
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Midwest Electronics Association, Minneapolis, MN: "New Products for High-Tech Firms." October, 1985.
University of Pennsylvania: "Agendas and Consumer Choice," August, 1985.
Herstein Institute, Vienna Austria: "Competitive Strategy," May, 1985.
Cadbury-Schweppes, Birmingham, England: "New Product Development and Defensive Strategy." May, 1985.
Rhone-Poulenc and Aluminum Pechiney, Paris, France: "New Product Development." April, 1985.
University of Michigan: "Defensive and Competitive Strategy." February, 1985.
Marketing Science Institute Special Mini-Conference: "Defensive Marketing Strategies for Consumer Firms." September 1983.
University of Chicago, Graduate School of Business, Chicago, IL. "Agendas and Consumer Choice," May 1984.
European Institute for Business Administration (INSEAD), Fontainebleau, FRANCE. "Agendas and Consumer Choice," June 1984.
University of Connecticut. "Defensive Marketing: Theory, Measurement, and Models," April, 1983.
University of Osaka, JAPAN "Defensive Marketing: Theory, Measurement, and Models," August, 1983.
Kao Soap, Ltd., Tokyo, JAPAN: "Defensive Marketing," August, 1983.
Johnson & Johnson, K. K., Tokyo, JAPAN: "Defensive Marketing," August, 1983.
Analog Devices, Inc., Norwood, MA. "New Product Development," May, 1982.
University of Rochester Research Seminar, "Prelaunch Forecasting of New Consumer Durables," April 1982.
Frito-Lay R & D Laboratory, Dallas, TX, "Marketing and R & D for New Products," October 1981.
University of California at Los Angeles Research Seminar, "Defensive Marketing Strategies," July, 1981.
Purdue University Research Seminar, "Product Realization," October 1979.
Stanford University Research Seminar, "Product Realization," October 1979.
Elrick and Lavidge, Inc., Chicago, Illinois, "Product Realization," October 1979.
Booz, Allen and Hamilton, Inc., Chicago, Illinois, "New Service Planning for Hospitals," April 1979.
Cornell University Research Seminar, "Intensity Measures of Consumer Preference," February 1979.
University of Rochester Research Seminar, "Product Realization: Synthesis of Marketing and Economic Theory," December 1978.
Region VI Center of Health Planning, New Orleans, LA, "Finding the Linkage Through Marketing,: August 1978.
Nebraska Hospital Association, Kearney, NE, "Hospital Marketing Surveys," May 1978.
Executive Development Group, Waterloo Management Education Centre, Toronto, Ontario, Canada, "Designing New Industrial Products," February 1978.
Academic Update, Xavier University Graduate Program in Hospital and Health Administration, Cincinnati, OH,
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"Designing Hospital Services: A Marketing Approach," October 1977.
The Hospital Marketing Workshop, Ireland Educational Corporation, Chicago, Illinois, "Analyzing the Hospital Markets," January 1977 and May 1977.
Association for College Unions - International, 1976 Fall Conference in Green Bay, WI, Keynote Speech - "Designing Successful Services: A Marketing Approach," October 1976.
University of Chicago, Graduate School of Business, Research Seminar, "Testing Probabilistic Models," April 1976.
Council for the Advancement and Support of Education, Conference on Marketing Alumni Program, New York, NY, Keynote Speech, February 1976.
Presentations at Professional Meetings (No published proceedings, some co-presented or presented by co-author[s]*)
New England Marketing Conference (NEMC),Cambridge, MA, October 11. 2019. “Issues In Ensuring That Marketing is a Viable Discipline Over the Next Decade.”
INFORMS Doctoral Consortium, Temple University, Philadelphia, PA. June 13, 2018. “Big Data and Machine Learning.”
INFORMS Marketing Science Conference, Temple University, Philadelphia, PA. June 14-16, 2018. John R. Hauser*, “Marketing Science’s Field Guide to Machine Learning and Algorithms.” Plenary Panel. John R. Hauser*, “Digital Marketing Applications of AI and Deep Learning ,” Panel Discussion Alex Burnap*, Artem Timoshenko, and John R. Hauser , “Deep Learning to Predict Consumer Aesthetic Preferences and Augment Product Designers” Artem Timoshenko* and John R. Hauser, “Combining Machine Learning and Human Judgment to Identify Customer Needs—New Tests and Applications” Gui Liberali* and John R Hauser, “Morphing Randomized Controlled Trials”
INFORMS Doctoral Consortium, University of Southern California, Los Angeles, CA. June 7, 2017. “Machine learning applications for customer-oriented recommendation systems and the voice of the customer.”
INFORMS Marketing Science Conference, University of Southern California, Los Angeles, CA. June 8-10, 2017. Daria Dzyabura and John R. Hauser*, “Recommending Products When Consumers Learn Their Preferences.” Felix Eggers* and John R. Hauser, “Precision Matters: How Craft in Conjoint Analysis Affects Price and Positioning Strategies.” Artem Timoshenko* and John R. Hauser, “Identifying Customer Needs from User Generated Content.”
Dies Natalis Academic Symposium, Erasmus University, Rotterdam, The Netherlands, November 8, 2016, “Recommending Products When Consumers Learn their Preferences.” Based on research with Daria Dzyabura.
Erasmus Centre for Marketing and Innovation, Econometric Workshop, Erasmus University, Rotterdam, The Netherlands, “Strategic Implications of Precision in Conjoint Analysis. Based on research with Felix Eggers.
2016 Paul D. Converse Symposium, University of Illinois, Champaign, IL, April 21-23, 2016, “Academic Achievements of Steven M. Shugan, Converse Winner.”
INFORMS Marketing Science Conference, Shanghai, China. June 16-18, 2016, Xinyu Cao*, T. Tony Ke, John R. Hauser, Juanjuan Zhang, “Competing for Limited Attention on Social Media.”
INFORMS Marketing Science Conference, Baltimore MD, June 2015. Songting Dong, John Hauser*, Min Ding, Lixin Huang, and Holger Dietrich, “The Sleuth Game: Predicting Consumer Response to as-yet-unspecified Product Features for Really New Products.”
AMA/Sheth Foundation Doctoral Consortium, Northwestern University, Evanston, IL, June 2014, “Bridging
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Empircs and Practice.”
INFORMS Marketing Science Consortium, Emory University, Atlanta GA, June 2014, “Learning from Experience Simply.”
AMA Summer Educators’ Conference, San Francisco, CA, August 1-3, 2014. Guilherme Liberali,* Hauser, John R., and Glen L. Urban “Recent Advances in Morphing Theory: Challenges and Opportunities for Research."
INFORMS Marketing Science Conference, Atlanta, GA, June 2014. Aliaa Atwi* and John R. Hauser, “Exploration vs. Exploitation in Rapid Coupon Personalization.”
AMA Sheth Foundation Doctoral Consortium 2013, University of Michigan, Ann Arbor, MI, June 6-9. “Managing Your Career (as a Marketing Academic).”
AMA Summer Educators’ Conference, Boston MA August 9-11, 2013. Panel on “Academic Integrity in the Publication Process” with Robert Meyer, Richard Lusch, John Hauser.*
10th Marketing Dynamics Conference, The University of North Carolina at Chapel Hill, May 30 – June 1, 2013. Song Lin*, Juanjuan Zhang, and John Hauser, “Learning from Experience, Simply.”
Joint Statistical Meetings 2013, Montreal, Ontario, August 2013. Song Lin*, Juanjuan Zhang, and John Hauser, “Learning from Experience, Simply.”
2012 AMA Sheth Foundation Doctoral Consortium, Foster School of Business, University of Washington, June 2012, Panel: 10 Steps to Successful Publishing.
INFORMS Marketing Science Conference, Boston, MA, June 2012. Song Lin*, Juanjuan Zhang, and John R. Hauser, “Learning from Experience, Simply.” Glen L. Urban, Guilherme Liberali, Erin MacDonald, Robert Bordley, and John R. Hauser*, “Morphing Banner Advertising” Matt Selove* and John R. Hauser, “The Strategic Importance of Accuracy in Conjoint Design.” Panel: Research Opportunities at the Marketing/Operations Interface
The 2012 Theory & Practice in Marketing (TPM) Conference on Marketing Strategy, Harvard University, Boston, MA. May 2-3, 2012. Glen L. Urban, Guilherme Liberali, Erin MacDonald, Robert Bordley, and John R. Hauser*, “Morphing Banner Advertising.”
New England Marketing Conference, Cambridge, MA, October 28, 2011. Gui Liberali, Glen L. Urban and John R. Hauser*, “ Providing Unbiased Competitive Information to Encourage Trust, Consideration, and Sales: Two Field Experiments.”
Yale School of Management, Center for Customer Insight, The Customer Insights Conference, New Haven, CT, May 12-14, 2011. John R. Hauser and Matthew Selove*, “The Strategic Importance of Accuracy in the Relative Quality of Conjoint Analysis.”
INFORMS Marketing Science Conference, Cologne, Germany, June 2010 (*indicates primary presenter if not me) Liberali, Guilherme*, John R. Hauser, and Glen L. Urban, “Optimal Time-to-Morph and Cognitive Costs of Morphing.” Liberali, Guilherme, Glen L. Urban, and John R. Hauser, “Do Competitive Test Drives and Product Brochures Improve Sales?” Urban, Glen L.*, Jong Moon Kim, Erin MacDonald, John R. Hauser and Daria Dzyabura, “Developing Consideration Rules for Durable Goods Markets.”
2010 Advanced Research Techniques Forum, San Francisco, CA, June 6-9, 2010, “Unstructured Direct Elicitation of Non-compensatory and Compensatory Decision Rules,” with Min Ding, Songting Dong*, Daria Dzyabura (listed as Silinskaia), Zhilin Yang, Chenting Su, and Steven Gaskin.
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2009 AMA Sheth Foundation Doctoral Consortium, J. Mack Robinson College of Business, Georgia State University, June 2009. E-Commerce and Digital Marketing Topics.
INFORMS Marketing Science Conference, Ann Arbor, MI, June 2009 (* indicates primary presenter if not me) “An Empirical Test of Incentive-Compatible Direct Elicitation of Heuristic Decision Rules for Consideration and Choice,” with Min Ding, Songting Dong, Daria Dzyabura, Zhilin Yang, Chenting Su, and Steven Gaskin “Adaptive Profile Evaluation to Identify Heuristic Decision Rules in “Large” and Challenging Experimental Designs,” with Daria Dzyabura (formerly Silinskaia)* and Glen L. Urban.. “Morphing Websites in the Presence of Switching Costs,” with Guilherme Liberali* and Glen L. Urban. “Continuous-Time Markov-Process with Misclassification: Modeling and Application to Auto Marketing,” with Glen L. Urban* and Guilherme Liberali. “An Incentive-Aligned Sleuthing Game For Survey Research,” with Min Ding* “Would You Consider a Buick Even if It Were #1 in JD Power?” with Erin MacDonald* and Glen Urban “Cognitive Simplicity and Consideration Sets,” with Rene Befurt*, Daria Dzyabura, Olivier Toubia, and Theodoros Evgeniou “John D. C. Little, a Pioneer in Marketing Science (Festschrift paper),” with Glen L. Urban
INFORMS Marketing Science Conference, Vancouver, B.C., June 2008 (* indicates primary presenter if not me) “Cognitive Styles and Website Design,” with Michael Braun, Glen L. Urban, and Clarence Lee. Modeling Cognitive Complexity to Predict Consideration Sets,” with Daria Dzyabura (formerly Silinskaia)*, Theodoros Evgeniou, Olivier Toubia, and Rene Befurt. “Morphing Websites to Match Individual Cognitive Styles,” with Michael Braun*, Glen L. Urban, and Guilherme Liberali
Sawtooth Software Conference, Delray, FL, March 2009, “A Critical Review of Non-compensatory and Compensatory Models of Consideration-Set Decisions,” with Min Ding and Steven Gaskin
AMA Doctoral Consortium, Robert J. Trulaske, Sr. College of Business, University of Missouri, June 2007, “Looking Ahead: Directions for Scholarly Research in Marketing” and “Building Teaching Effectiveness: Stimulating Student Interest.”
Sawtooth Software Conference, Santa Rosa, CA, October 2007, “Two-Stage Models: Identifying Non- Compensatory Heuristics for the Consideration Set then Adaptive Polyhedral Methods Within the Consideration Set,” with Steven Gaskin, Theodoros Evgeniou, Daniel Bailiff.
AMA Advance Research Technologies Forum, Sante Fe, New Mexico, June 2007, “Two-Stage Models: Identifying Non-Compensatory Heuristics for the Consideration Set then Adaptive Polyhedral Methods Within the Consideration Set,” with Steven Gaskin, Theodoros Evgeniou, and Daniel Bailiff.
AMA Doctoral Consortium, W. P. Carey School of Business, Arizona State University, May 2007, “Consideration The New Battlefield in Product Development.”
Agent-based Models of Market Dynamics and Consumer Behaviour, University of Surrey, Guildford, UK, January 2006, “Co-opetition for the Diffusion of Resistant Innovations: A Case Study in the Global Wine Industry using an Agent-based Model.” with Rosanna Garcia. Also presented at the American Marketing Association’s Advanced Research Techniques (ART) Forum in June 2006 at Monterrey CA.
AMA Doctoral Consortium, University of Maryland, College Park, MD, July 2006, “Creating Value: Products and Brands.”
Marketing Science Conference, University of Pittsburgh, Pittsburgh, PA, June 2006, “A Truth-telling Sleuthing Game for Survey Research,” with Min Ding.
Marketing Science Conference, University of Pittsburgh, Pittsburgh, PA, June 2006, On Managerially Efficient Experimental Designs,: with Olivier Toubia.
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Sawtooth Software Conference on Conjoint Analysis, Delray Beach, FL, March 2006, “Must Have” Aspects vs. Tradeoff Aspects in Models of Customer Decisions,” with Michael Yee, James Orlin, Ely Dahan.
AMA Doctoral Consortium, University of Connecticut, Storrs CT, June 2005, “The Virtual Customer.”
Marketing Science Conference, Emory, Atlanta, GA, June 2005, “Direct, Nonparametric Product Optimization Using Interactive Genetic Algorithms,” with Kamal Malek and Kevin Karty.
Marketing Science Conference, Emory, Atlanta, GA, June 2005, “Non-Deterministic Polyhedral Methods for Adaptive Choice-Based Conjoint Analysis: Application to the Diffusion of the New Wine Cork,” with Olivier Toubia and Rosanna Garcia.
Marketing Science Conference, Emory, Atlanta, GA, June 2005, “Greedoid-Based Non-compensatory Two-Stage Consideration-then-Choice Inference,” with Michael Yee, Jim Orlin, and Ely Dahan.
Marketing Science Doctoral Consortium, Rotterdam, The Netherlands, June 2004, “Research that Has Impact.”
Marketing Science Conference, Rotterdam, The Netherlands, June 2004, “Improving Choice-Based Polyhedral Methods by Taking Response Error into Account,” with Olivier Toubia.
Marketing Science Conference, Rotterdam, The Netherlands, June 2004, “The Dream Versus Reality of CRM,” with Glen L. Urban, Eric Bradlow, and, Mahesh Kumar.
Marketing Science Conference, Rotterdam, The Netherlands, June 2004, “Non-compensatory Consideration-then- Choice Adaptive Conjoint Analysis,” with Michael Yee and James Orlin.
AMA Doctoral Consortium, Texas A&M University, College Station, TX, June 2004, "Virtual Customer Initiative."
AMA Advanced Research Techniques Forum, June 2004, “Conjoint Adaptive Ranking Database System (CARDS),” with Ely Dahan, James Orlin, and Michael Yee.
AMA Doctoral Consortium, University of Minnesota, Minneapolis, MN, June 2003, "The Review Process."
Marketing Science Doctoral Consortium, University of Maryland, June 2003, “Roots of Marketing Science Thought,” with John Little.
Marketing Science Conference, University of Maryland, June 12-15, 2003, "Individual-level Adaptation of Choice- Based Conjoint Questions: More Efficient Questions and More Accurate Estimation," (with Olivier Toubia and Duncan Simester).
Marketing Science Conference, University of Alberta, Canada, June 28, 2002, "Configurators, Utility Balance, and Managerial Use," (with Duncan Simester and Olivier Toubia).
Marketing Science Doctoral Consortium, University of Alberta, Canada, "Helping Managers Structure and Make Decisions," June 27, 2002. (Founding Consortium).
Marketing Science Conference, University of Alberta, Canada, June 28, 2002, "Adaptive Choice-Based Conjoint Analysis with Polyhedral Methods," (with Duncan Simester and Olivier Toubia*).
Advances in Marketing Research and Modeling: The Academic and Industry Impact of Paul E. Green, Wharton, Philadelphia, PA, May 2002, "New Methods of Data Collection and Estimation Using Polyhedral Estimation Techniques."
Production and Operations Management Society (POMS) Conference 2002 - High Tech POM, San Francisco, CA, April 2002, "The Virtual Customer," (with Ely Dahan*).
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Product Development Association (PDMA) International Research Conference, Santa Clara, CA, October 2001, "The Virtual Customer," (with Ely Dahan*).
New England Marketing Conference, Cambridge, MA, September 2002, "Fast Polyhedral Adaptive Conjoint Estimation," (with Ely Dahan, Duncan Simester, and Olivier Toubia).
Marketing Science Conference, Wiesbaden, Germany, July 2001, "Empirical Test of Web-based Conjoint Analysis Including ACA, Efficient Fixed Designs, Polyhedral Methods, and Hybrid Methods," (with Ely Dahan, Duncan Simester, and Olivier Toubia*)
Marketing Science Conference, Wiesbaden, Germany, July 2001, "Evaluation of Fast Polyhedral Adaptive Conjoint Estimation," (with Duncan Simester and Olivier Toubia).
The 12th Annual Advanced Research Techniques Forum, Amelia Island, Florida, June 2001, "The Virtual Customer: Communication, Conceptualization, and Computation," (with Ely Dahan*).
AMA Doctoral Consortium, University of Miami, June 2001, "Role of Technology in Marketing."
Marketing Science Conference, UCLA, June 2000, "Applications of the Metrics Thermostat."
Marketing Science Conference, UCLA, June 2000, "The Virtual Customer." (with Ely Dahan and Duncan Simester).
Marketing Science Institute Marketing Metrics Workshop, Washington, D.C. October 1999, "Metrics for New Product Development: Making Agency Theory Practical," Plenary Speaker.
Marketing Science Conference, Syracuse, NY, May 1999, “Balancing Customer Input, Speed to Market, and Reduced Cost in New Product Development: What is the Most Profitable Strategy”
ICRMOT Conference on Technology Alliances and New Product Development: A Cross-cultural Perspective, Mishima, JAPAN, December 1998, “You Are What You Measure!”
AMA Doctoral Consortium, Athens, Georgia, August 1998, “Quantitative Advances in Marketing Models.”
AMA Winter Educators’ Conference, Austin, TX, February 1998 (Plenary Speaker), “New Challenges in the Marketing-Product Development Interface.”
AMA Doctoral Consortium, Cincinnati OH, August 1997, "Working with Industry."
Marketing Science Conference, Berkeley CA, March 1997, “Cultivating Technological Managers for Customer Expertise.”
Marketing Science Institute Conference on Interfunctional Interfaces: The Management of Corporate Fault Zones, Palo Alto, CA, December 1996, “Multi-Stage Modeling of R&D/Marketing Interfaces in New Product Development.”
Marketing Science Conference, Berkeley CA, March 1997, “Cultivating Technological Managers for Customer Expertise.”
Envisioning the Future on Internet Marketing: Research and Strategy Implications, M.I.T., September 1996, “Agents and Intermediaries: Roles, Trust, and Value.”
"Can R&D be Evaluated on Market-Driven Criteria?," (with Florian Zettelmeyer). Marketing Science Conference, University of Florida, Gainesville, March 1996
"Information Acceleration," (with Glen Urban, William Qualls, Bruce Weinberg, Jon Bohlmann, and Roberta Chicos). Wharton Conference on Innovation in Product Development, Philadelphia, PA, May 1995.
"Metrics by Which Managers Evaluate R&D Groups," (with Florian Zettelmeyer). Association of Consumer
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Research, Boston, MA, October 1994.
"Satisfying the Internal Customer," (with Birger Wernerfelt and Duncan Simester) Marketing Science Conference, University of Arizona, Tucson, AZ, March 1994.
"Customer-Satisfaction Based Incentive Systems," AMA Educator's Conference, Boston, MA, August 1993.
"Marketing in the 1990s: Emerging Issues," AMA Doctoral Consortium, University of Illinois, August 1993.
"Quality Function Deployment and the Voice of the Customer," Pharmaceutical Management Science Association, Phoenix AZ, May 1993.
"In a World of Active Time-constrained Customers, How Can a Firm be the Great Communicator," (with Birger Wernerfelt), Marketing Science Conference, Washington University, St. Louis, MO, March 1993.
"Customer Needs, Customer Satisfaction, Sales, and Profit," (with Birger Wernerfelt, Ronit Bodner, and Duncan Simester), ORSA/TIMS Joint National Conference, San Francisco, CA, November 1992.
"Customer Satisfaction and Employee Rewards," (with Birger Wernerfelt, Ronit Bodner, and Duncan Semester), Marketing Science Conference, London, England, June 1992.
"Information Acceleration and Preproduction Forecasting of Electric Autos," (with Glen L. Urban and Bruce Weinberg), Marketing Science Conference, London, England, June 1992.
"The Voice of the Customer and Customer Satisfaction," ORSA/TIMS Joint National Meeting, Anaheim, CA, October 1991.
"Modeling Marketing Phenomena," AMA Doctoral Consortium, University of Southern Calif. August 1991.
"Relationship of Satisfaction to Customer Needs and to Market Share," 1st Congress on Customer Satisfaction and Market-Driven Quality, American Marketing Association, Orlando FL, May 1991.
"Time Flies When You're Having Fun: How Consumers Allocate Their Time When Evaluating Products" (with Bruce Weinberg, Glen Urban, and Miguel Villas-Boas), Marketing Science Conference, Wilmington, DL, March 1991.
"Information Acceleration and Preproduction Forecasting of New Autos," (with Glen Urban, and Bruce Weinberg), Marketing Science Conference, Wilmington, DL, March 1991.
"Beyond Quality Function Deployment," ORSA/TIMS Joint National Meeting, Philadelphia, PA October 1990. (Conference-wide Tutorial)
"Competitive Marketing Strategies," Operations Research 1990 (Osterreichische Gesellschaft fur Operations Research), Vienna, Austria, August 1990. (Invited Speaker)
"New Product Development: A Quantitative Analysis of Interfunctional Communication" (with Abbie Griffin), Marketing Science Conference, Urbana, IL, March 1990.
"Integrated Product Development: New Methodological Developments" (with Abbie Griffin), Marketing Science Conference, Durham, N.C., March 1989.
"Customer Driven Engineering" (with Gregory Cirmak and Robert Klein), ORSA/TIMS Joint National Meeting, Washington, D.C., April 1988.
"Competitive Advertising and Pricing in Duopolies" (with Birger Wernerfelt), Marketing Science Conference, Seattle, Washington, March 1988.
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"Customer Driven Engineering" (with Abbie Griffin), Marketing Science Conference, Seattle, Washington, March 1988.
"Customer Needs," Visions of Design Practices for the Future, Newton, MA, October 1987.
"Effective Strategies in Oligopoly" (with Peter Fader), ORSA/TIMS Joint National Meeting, Miami Beach, Florida, November 1986.
"Competitive Strategy Contest: Result and Analysis" (with Peter Fader), Marketing Science Conference, Dallas, TX, March 1986.
"The PC As a Tool to Teach Complex Marketing Science Concepts," Marketing Science Conference, Dallas, TX, March 1986.
"The Coming Revolution in Marketing Theory," Plenary Speaker, European Marketing Conference, Bielefeld, West Germany. April 1985.
"Defensive Strategy" Confer. on Economics of the Firm, Universite de Paris X, Nanterre, France, April 1985.
"Competitive Marketing Strategies" Marketing Science Conference, Nashville, Tennessee, March 1985.
"Developing New Product Management: Past Progress, Current Efforts, Current Needs" (Panel) Marketing Science Conference, Nashville, Tennessee, March 1985.
"Testing Competitive Marketing Structures: Theory and Applications" (with Glen Urban) ORSA/TIMS Joint National Meeting, Dallas, TX November 1984.
"Competitive Strategy," ORSA/TIMS Joint National Meeting, Dallas, Texas, November 1984.
"Forecasting Automobile Sales: An Application of a Value Priority Algorithm," (with Glen Urban), John Roberts and John Dabels), TIMS XXVI International Meeting, Copenhagen, Denmark, June 1984.
"Consumer Durables: The Actual Consumer Budgets Compared to the Value Priority Model," (with Glen Urban), Marketing Science Conference, Chicago, Illinois, March 1984.
"Defensive Strategy Models: Application and Predictive Text," (with Steven Gaskin, and Karl Irons) ORSA/TIMS Joint National Meeting, Orlando, Florida, November 1983.
"New Product Research: Focus on Defensive strategies," Roundtable Program, ORSA/TIMS Joint National Meeting, Orlando, FL, November 1983.
"Intensity of Preference," (with Steven Shugan) ORSA/TIMS Joint National meeting, San Diego, CA, October 1982.
"Measurement Error Theories for von Neumann-Morgenstern Utility Functions," (with Jehoshua Eliashberg) ORSA/TIMS Joint National Meeting, San Diego, CA, October 1982.
"Consumer Preference Models: Axioms and Statistics," ORSA/TIMS Joint National Meeting, Houston, Texas, October 1981.
"Economic Models of Consumer Behavior," (panel discussion), ORSA/TIMS Joint National Meeting, Houston, Texas, October 1981.
"Defensive Marketing Strategies, Part II," (with Steven Shugan), ORSA/TIMS Joint National Meeting, Houston, Texas, October 1981.
"Agendas and Choice Probabilities," (with Amos Tversky), Association of Consumer Research, St. Louis, Missouri,
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October 1981, and Special Conference on Choice Theory, Durham, North Carolina , June 1981.
"Strategic Response to Competitive New Products," (with Steven Shugan), ORSA/TIMS Joint National Meeting, Toronto, Ontario, Canada, May 1981.
"Applications of a Dynamic Semi-Markov Model of Consumer Choice," (with Ken Wisniewski), ORSA/TIMS Joint National Meeting, Colorado Springs, Colorado, November 1980.
"Models of Consumer Behavior," (panel discussion), ORSA/TIMS joint National Meetings, Colorado Springs, Colorado, November 1980.
"Dynamic Semi-Markov Models of Consumer Behavior," (with Ken Wisniewski) TIMS International Conference on Marketing, Paris, June 1980.
"Profit Maximizing Perceptual Positioning," (with Patricia Simmie) TIMS International Conference on Marketing, Paris, June 1980.
"An Error Theory for von Neumann-Morgenstern Utility Assessment," (with Jehoshua Eliashberg), ORSA/TIMS Joint National Meeting, Washington, D.C., May 1980.
"Defender: Defensive Strategies Against New Products" (with Steven Shugan), ORSA/TIMS Second Special Interest Conference on Marketing Measurement and Analysis, Austin, Texas, March 1980.
"Adaptive Control of New Product Launches," (with Ken Wisniewski), ORSA/TIMS Joint National Meeting, Milwaukee, Wisconsin, October 1979.
"The Value of Up-front Research in New Products," (with Glen Urban), TIMS International Meeting, Honolulu, Hawaii, June 1979.
"Methods for Computing Probabilities of Choice," (with Steven Shugan), TIMS International Meeting, Honolulu, Hawaii, June 1979.
"Forecasting and Improving the Adoption of New High Technology Products," (with Pat Lyon), ORSA/TIMS Joint National Meeting, New Orleans, Louisiana, May 1979.
"A Methodology for Product Realization: Multi-method Procedures," (with Patricia Simmie), ORSA/TIMS Joint National Meeting, Los Angeles, California, November 1978.
"Searching for Marketing Segments" (with Ken Wisniewski), ORSA/TIMS Joint National Meeting, New York, New York, May 1978. "P.A.R.I.S.: An Interactive Market Research System," (with Steven Shugan), ORSA/TIMS Joint National Meeting, New York, New York, May 1978. "Extended Conjoint Analysis," (with Steven Shugan), ORSA/TIMS Joint National Meeting, Atlanta, Georgia, November 1977.
"Consumer Preference Functions: Theory, Measurement, Estimation , and Application," (with Steven Shugan), ORSA/TIMS Joint National Meeting, Atlanta, Georgia, November 1977.
"Measuring Consumer Preferences for Health Care Plans," (with Glen Urban), ORSA/TIMS Joint National Meeting, San Francisco, California, May 1977.
"Improved Transportation Design with Consumer Response Models: An AMTRAK Example" (with Frank Koppelman), ORSA/TIMS Joint National Meeting, Miami, Florida, November 1976.
"A Comparison of Statistical and Direct Multiattribute Utility Assessment Procedures," (with Glen Urban),
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ORSA/TIMS Joint National Meeting, Las Vegas, Nevada, November 1985.
"Measuring Consumer Preferences: An Axiomization for Describing Choice," ORSA/TIMS Joint National Meeting, Las Vegas, Nevada, November 1975.
"Modeling Consumer Response to Innovations," (1) Milwaukee Chapter of ORSA/TIMS, November 1985; (2) Chicago Chapter of ORSA/TIMS, December 1975.
"Modeling Decisions of Choice Among Finite Alternatives: Applications to Marketing and to Transportation Demand Theory," ORSA/TIMS Joint National Meeting, San Juan, Puerto, Rico, October 1974.
"An Efficient Model for Planning Bus Routes in Medium Sized Communities," ORSA/TIMS Joint National Meeting, San Diego, CA, November 1973.
Professional Affiliations
The Institute for Operations Research and Management Science (INFORMS)
INFORMS Society of Marketing Science (ISMS)
American Marketing Association
Product Development and Management Association, Certified New Product Development Professional
Professional Services
President, INFORMS Society of Marketing Science (January 2014 –December 2015). President-elect (a board position, January 2012 – December 2013). Past-President (a board position, January 2016 – December 2017).
Secretary, INFORMS Society of Marketing (January 2002 – December 2005). Founding Officer.
Advisory Council, INFORMS College of Marketing (1994 - 2002)
Council of The Institute of Management Sciences (TIMS, 1987 - 1989)
Associate Editor for Marketing, Management Science, (1980 - 1981)
Department Editor for Marketing, Management Science, (1982 - 1988)
Editor-in-Chief, Marketing Science, (1989 - 1994)
Editor, Special Issue on Big Data, Marketing Science, 2016. Senior Editor, Practice Papers, Marketing Science, 2016-2018. Associate Editor, Special Issue on the Theory and Practice of Marketing, Marketing Science, 2014.
Editorial Advisory Board, Sloan Management Review (2000-2002).
Associate Editor, Journal of Marketing Research (April 2006 – June 2009). First time in journal history that Associate Editors had been appointed.
Senior Advisory Board, Journal of Marketing Research (July 2009 – 2016). First time such an advisory board was formed.
Advisory Board, Marketing Science (2010 – 2018).
Advisory Board, Journal of Product Innovation Management (2011 – 2018)
Emeritus Editorial Board, Marketing Science (includes active reviewing of papers).
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Editorial Boards, Marketing Science, (1980 – 1988, Editor 1989-1995, 2003- 2008, including acting Area Editor), Journal of Product Innovation Management (1997 - 2010), Journal of Marketing (2005- 2008, outstanding reviewer 2006), European Management Journal (advisory, 1998 - 2002), International Journal for Research in Marketing (2007 – 2014).
Reviewer: Advances in Consumer Research, Applications in Management Science, European Journal of Research in Marketing, Journal of the Academy of Marketing Science, Journal of Consumer Research, Journal of Marketing, Journal of Marketing Research, Journal of Mathematical Psychology, Journal of Product Innovation Management, Management Science, Marketing Science, Proceedings of the National Academy of Sciences, Operations Research, Review of Marketing, Sloan Management Review, Transportation Research Record, Transportation Science, Journal of Business Research, AMA Dissertation Prize, AMA Educators' Conference, American Institute of Decision Sciences Dissertation Prize, Nicholson Dissertation Prize, Marketing Science Institute Dissertation Award, Product Development Management Association Dissertation Prize, Prentice-Hall Books, National Science Foundation.
Conference Chairman: Conference Chair, Profitable Customer-Driven Organizations: Developing the Blueprint, Management Roundtable, May 1994.
Segment Chairman: Yale School of Management, Center for Customer Insight, The Customer Insights Conference, New Haven, CT. May 12-14, 2011. New Product Innovations.
Non-traditional Models of Consumer Preference and Choice, Adaptive Preference and Estimation, Optimizing Product Design and Customer Targeting, Obtaining Information From or About Consumers (Atlanta, GA, 2005, co-chair four sessions)
TIMS International Meeting, Copenhagen, Denmark, June 1984 (two sessions).
TIMS College of Marketing, Houston, Texas, October 1981 (twelve sessions).
TIMS College of Marketing, Milwaukee, Wisconsin, October 1979 (five sessions).
American Marketing Association Educator's Conference, Chicago, Illinois, August 1978, (three sessions).
INFORMS Marketing Science Conference, Atlanta GA, June 2005 (four sessions)
Session Chairman: INFORMS (Previously named ORSA or TIMS)
Virtual Customer Initiative (Rotterdam, The Netherlands, 2004)
New Approaches to Mapping (University of Maryland, 2003)
The Virtual Customer (University of Alberta, Canada 2002)
The Virtual Customer (Wiesbaden, Germany 2001)
Building Competitive Advantage Through Product Quality and R&D (Gainesville, FL 1996)
Customer Satisfaction and Its Role in Global Competition (San Francisco, CA 1992)
Competitive R&D (Washington, D.C., April 1988)
Competitive Marketing Strategy, (St. Louis, Michigan, November 1987)
Competition in Multiattributed Spaces (Atlanta, Georgia, November 1985).
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Marketing: Consumer Measurement (Copenhagen, Denmark, June 1984)
Marketing: Dynamic Structures (Copenhagen, Denmark, June 1984)
Product Policy (Orlando, Florida, November 1983) Product Policy (San Diego, California, October 1982)
New Product Introduction and Defense in Competitive Environments, (Detroit, Michigan, April 1982) New Product and Product Policy Models, (Houston, Texas, October 1981)
New Product Models (Toronto, Ontario, Canada, May 1981)
Models of Consumer Behavior (Colorado Springs, Colorado, November 1980)
New Product Realization and Selection (Los Angeles, California, November 1978).
Session Chairman: Association of Consumer Research
Mathematical Theories of Consumer Behavior (St. Louis, Missouri, October 1981)
Committee Memberships
Editor Selection Committee, Marketing Science, INFORMS College of Marketing, 2001 (chair), 2004 (chair), 2007.
Editor Selection Committee, Journal of Marketing Research, American Marketing Association, 1999.
Conference Steering Committee, Duke Invitational Symposium on Choice Modeling and Behavior, June 1993.
Editor Selection Committee, Management Science, TIMS.
Founding Committee for Marketing Science, TIMS College of Marketing, (1979 - 1982).
Management Science Roundtable, TIMS, (1982 - 1988)
Marketing Strategy Steering Committee, Marketing Science Institute, (1983 - 1984).
Organizing Committee for Conference on Economics of the Firm, April 1985, Universite de Paris X Nanterre.
Organizing Committee for 1985 Conference in Bielefeld, West Germany, European Marketing Academy.
Publications Committee (1980 - 1982), Operations Society of America.
Scientific Committee for 1986 Conference in Helsinki, Finland.
Student Affairs Committee (1978 - 1979), Operations Society of America.
Litigation Consulting (on behalf of, *deposition testimony, †court, commission, or arbitration testimony)
ABC, Inc., American Broadcasting Company, Inc., and Disney Enterprises, Inc., Plaintiffs, v. Dish Network L.L.C. and Dish Network Corp., (Preliminary Injunction) Joseph Adinolfe, et al., v. United Technologies Corp., d/b/a Pratt & Whitney (class action, damages)* † Alcatel-Lucent USA Inc. v. Amazon.com, Inc. et al. (Patent Infringement)* † Allergan, Inc. Engagement. (Off-label Prescriptions)
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American Express Travel Related Services, Inc. v. Visa USA, Inc., et. al. (Evaluation of marketing research) * In Re American Express Anti-Steering Rules Antitrust Litigation (II) (Evaluation of marketing research)* American Multi-Cinema, Inc. v. American Movie Classics Company, Inc., et. al. (Confusion) Amway v. Procter & Gamble (Damages)* Garth A. Anderson, et al. v. American Family Insurance Company (Class Action) * Anoush Cab, Inc., et al. v. Uber Technologies, Inc., Rasier, LLC (damages) † Apple, Inc. v. Samsung Electronics Company, Ltd, et al. (Patent infringement, two cases) ** ††† Atlantic Recording Corporation, et. al. v. XM Satellite Radio, Inc. (Copyright infringement). Axcan Scandipharm, Inc. V. Global Pharmaceuticals And Impax Laboratories, Inc. (False Advertising) Avaya Inc. v. SNMP Research International, C.A. (Damages) * Berlex v. Biogen, Inc. (Damages)* Blue Mountain Arts, Susan Polis Schutz, and Stephen Schutz v. Hallmark Card, Inc. (Trade Dress) James And Lisa Camenson, et al.; v. Milgard Manufacturing Inc., et. al. (Class action) CBS Corporation, CBS Broadcasting Inc., CBS Studios Inc., and Survivor Productions, LLC. v. and DISH Network Corporation, DISH Network L.L.C. (damages). Clearchannel Communications, Inc. in the Webcasting IV. (Damages) *† Comm-Tract Corp. v. Northern Telecom, Inc. (Advice only) Comcast Cable Communications. LLC v. Sprint Communications Company (Patent Infringement)* Computer Aid, Inc. v. Hewlett Packard (damages)* Dayna Craft, et al. v. Philip Morris Companies, Inc. and Philip Morris Inc. (Class Action).* Creative Laboratories, Inc. v. Apple Computer, Inc. (Intellectual Property) CTC Communications Corporation v. Bell Atlantic Corporation (Damages) Eagle Harbor Holdings LLC, and Mediustech LLC, v. Ford Motor Company (Patent infringement). Anne Elkind And Sharon Rosen, et al. v. Revlon Consumer Products Corporation, Inc. (Class Action) EPD v. Curtis (Product Confusion)† FCA Canada Inc. and FCA US LLC, re Canadian Class Actions re Diesel Fuel Emissions, specifically, Shane Witham, et al. v. FCA Canada Inc., FCA US LLC, and FIAT Chrysler Automobiles N.V. (Class Action) † Fox Broadcasting Company, Inc., Twentieth Century Fox Film Corp., and Fox Television Holdings. Inc., Plaintiffs, v. Dish Network L.L.C. and Dish Network Corp., (Preliminary Injunction, Damages)* Stephen S. Gallagher, et. al. v. State Farm Mutual Automobile Insurance Company, et al. (Class Action) Geico v. Google and Overture Services (Yahoo), Inc. (Trademark Infringement) In Re: General Motors, LLC Ignition Switch Litigation (non-testifying expert) Gillette v. S. C. Johnson (Patent Infringement) Gyrodata, Inc. v. Atlantic Inertial Systems Inc (“AIS”), et al. (consulting expert) Heublein vs. Seagrams and Gallo (Liability) Hewlett-Packard, Inc. v. Factory Mutual Insurance Company (Insurance Coverage)* IMS Health Incorporated v. Symphony Health Solutions Corporation, Source Healthcare Analytics, LLC, and ImpactRx, Inc., C.A. No. 1:13-cv-2071-GMS (D. Del.). (Patent infringement, technical expert.)
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Intel v. Advanced Micro Devices (Damages)* J. B. D. L. Corp. d/b/a, Beckett Apothecary v. Wyeth-Ayerst Laboratories, Inc. and American Home Products Corporation, (Class Action) Jerry Jacobs, et. al. v. Osmose Inc., et. al. (Class Action)* Jay Kordich, et. al. v. Salton Maxim Housewares, Inc., et. al. (Trademark)† In RE J.P. Morgan Chase Cash Balance Litigation (Class Action)* Michael Kors, Inc. v. Costco Wholesale Corporation (False Advertising)* L.A. Taxi Cooperative, Inc. et al. v. Uber Technologies, Inc.; Rasier, LLC; and Rasier-CA, LLC. (False Advertising)*. Lending Tree, Inc. v. The Gator Corporation (Intellectual Property) Lotus v. Borland (Damages)* Louis Vuitton Malletier, S. A. v. Hyundai Motor America (Trademark Infringement)* Malden Transportation, Inc. et al. vs. Uber Technologies, Inc., Rasier, LLC*† (damages). See also Anoush. Marvin Lumber and Cedar Company v. PPG Industries, Inc., et. al. (Survey Design) MasterCard International, Inc. v. First National Bank of Omaha (Product Confusion)* Mayo Foundation v. Mayo Health Facilities (Product Confusion)† Mead Johnson Nutritionals v. unnamed party (False Advertising) Merck & Co. (Lanham Act Advice) Michael Kors (USA), Inc. and Michael Kors, L.L.C. v. Costco Wholesale Corporation, Civil Action No. 13-CV- 4832, the United States District Court Southern District of New York. (Damages)* In Re Microsoft Corporation Antitrust Litigation (Multi-district Litigation)* Millennium Laboratories, Inc. v. Ameritox, Ltd. (False Advertising) Scott Miller, et al. v. Fuhu, Inc. and Fuhu Holdings, Inc. (Class Certification)* MillerCoors, LLC v. Anheuser-Busch Companies, LLC. (False Advertising) * Pacific Bell Telephone Company in New Regulatory Framework Review of Customer Satisfaction before the California Public Utility Commission† Luciano F. Paone v. Microsoft Corporation (Patent Infringement)* Pfizer Consumer Healthcare (Lanham Act Advice) Playtex v. Procter & Gamble (Claims Substantiation)*† Procter & Gamble v. Amway (Liability and Damages)*† Procter & Gamble v. Haugan, et. al. (Liability and Damages)† Putnum Fund Trustees, (Investment Fraud, advice on market research) Ram Broadcasting, Inc. (Cellular Telephone Filings) RealPlayer, Inc. v. Microsoft Corporation (Anti-trust) Roberts et. al. v. Enterprise Rent-a-Car Company of Boston, Inc. (Class Action) The Republic of Columbia v. Diageo North America, et al. (Anti-trust). St. Clair Intellectual Property Consultants, Inc. v. Research in Motion, Ltd. and General Imaging Co. (Patent infringement)
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Curt Schlesinger and Peter Lore, on behalf themselves and the Certified Class, Plaintiffs, v. Ticketmaster (Class action, false advertising, confusion)* Barbara Schwab, et. al. v. Philip Morris, USA (Class Action)* SoundExhange, Inc. vs. Sirius Satellite Radio, Inc. and XM Satellite Radio, Inc.: In the Matter of Adjustment of Rates and Terms for Preexisting Subscription Services and Satellite Digital Radio Services. 2007*†. 2012*†. 2017*†. Sprint Communications Company L.P. et al. v. Comcast Cable Communications, LLC. et al. (Damages)* State of Colorado, et. al. v. Warner Chilcott Holdings Company III, Ltd., et. al. (Anti-trust)* † State of Florida and Plaintiff States Antitrust Litigation for Disposable Contact Lenses (Survey Analysis)† State of Washington v. Comcast, et al. (False Advertising)* † Stipic, et. al. v. Behr Process Corporation and Masco International (Class Action)* Straumann Company v. Lifecore Biomedical, Inc. (Product Confusion)* Sun Microsystems, Inc. v. Microsoft Corporation (Anti-trust). Symphony Health Solutions Corporation v. IMS Medical Radar (Technical Expert)*. Takada Pharmaceuticals USA, Inc. v. Par Pharmaceutical Companies, Inc. Par Pharmaceutical, Inc., Amneal Pharmaceuticals, LLC, Watson Laboratories, Inc. West-Ward Pharmaceutical Corp., Hikma Americas PLC. (Patent Infringement). Tivo, Inc. v. Echostar Communications Corporation, et. al* (Patent Infringement) Tropicana Products, Inc. v. Vero Beach Groves, Inc. (Lanham Act)† (Declaration accepted as court testimony.) United States of America Department of Justice v. AT&T Inc., DirecTV Group Holdings, LLC, And Time Warner Inc.* † Wal-Mart Stores, Inc (and other retailers) v. Mastercard International, Inc. (Liability and Damages, Anti-trust)* We Media, Inc. v. We: Women’s Entertainment, LLC. (Product Confusion)*. Yahoo Holdings, Inc., et al. v. Mozilla Corporation (customer satisfaction) * Olua Zakaria, et al. v. Gerber Products Co. d/b/a Nestle Nutrition, Nestle Infant and Nestle Nutrition North America (class action, damages)*.
Marketing, Marketing Research, and Product Development Consulting Not Otherwise Listed
American Home Foods, Inc.; American Airlines; American Hospital Supply Corporation; Analog Devices, Inc; Andersen Consulting, Inc. (Accenture), Applied Marketing Science, Inc.; A.T.&T.; Avon; Barton-Aschmann Associates; Baxter Cardiovascular Group, Booz Allen Hamilton, Inc., Cambridge Systematics, Inc.; Chrysler, LLC; Colgate-Palmolive; Costello Associates, Inc.; Economics’ Laboratories, Inc.; Elrick and Lavidge, Inc.; Evanston Hospital; Evanston, Illinois and Schaumburg, Illinois (Transportation Planning); Fiat Chrysler Automobiles, Fidelity Investments; Ford Motor Company; French's Inc., G.D. Searle, Inc.; General Foods, Inc.; General Motors, Inc., Buick Division, Chevrolet Division, Marketing and Product Planning; Gillette; IBM, Inc.; Information Resources, Inc.; Intel, Inc., Johnson & Johnson; Kodak; Macromedia, Inc., Management Decision Systems, Inc.; M/A/R/C, Inc.; Merck, Inc., Navistar International, Inc.; Pacific Gas and Electric Company, Pepsi-Cola, Inc.; Polaroid; Procter & Gamble Company; Product Genesis, Inc.; RAM Broadcasting, Inc.; Regional Transportation Authority; Richardson-
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Vicks, Inc.; Southern Company Services, Inc.; Time-Life Books; Volunteers in Technical Assistance, and Wyeth- Ayerst Laboratories, Inc. Co-founder, senior product development consultant, Applied Marketing Science, Inc., Advisory Board (former), Affinnova, Inc.
M.I.T. or MIT Sloan Committee Work
Associated Faculty Committee to Review the Organizational Learning Center (MIT Sloan), 1995.
Building Committee for the E51 Expansion, MIT Sloan, 1992, Ad Hoc.
Center for Innovation in Product Development
Leader, Virtual Customer Initiative, 2000 - 2006
Research Director, 1997 – 2000
Center for Transportation Studies, 1981 - 1982.
Master of Science in Transportation Committee.
Committee on the Masters in Analytics, 2014-2016.
Committee on the Undergraduate Program, 2003 – 2005.
Committee to Investigate Sloan-Logo Research Notes (MIT Sloan, chair), 2001-2002.
Dean’s Consultation Committee (MIT Sloan), 2008-2009.
Dean Search Committee (MIT Sloan), 1993.
Executive Educational Programs Committee (MIT Sloan), 1983 – 1985, 1998-1999, 2007.
Faculty Admissions Committee, 2004-2009.
Faculty Council (MIT Sloan), 1999.
International Center on Research for the Management of Technology (MIT Sloan).
Co-Director, (1993 - 2000).
Joint Steering Committee (1990 - 1993).
Management Science Area, MIT Sloan School of Management.
Area Head, (2005- 2009).
Chairman of Subcommittee on Peer Group Comparisons, (1981 - 1982).
Committee on Management Science Curriculum Redesign, (1982 - 1983).
Marketing Group Head (1986, 1988 – 2003, 2010-2011).
Marketing PhD Admissions, Head (2015, 2016)
Management of Technology Program Committee (MIT Sloan), (2001- 2003).
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Master's Program Committee, MIT Sloan, (1980 – 1987, 2007 – 2015).
Ad hoc committee to develop a Marketing, Operations and Strategy Track (2011-2012).
Ad hoc committee to understand gender issues in class participation (2015-2016)
Chairman: Subcommittee On Placement, (1981 - 1982).
Core Curriculum Implementation Committee (1992-1994).
Core Curriculum Reassessment Committee (1991-1992).
Subcommittee on Admissions, Special Consideration, (2007 – 2009).
Subcommittee on Course Ratings (2011).
Subcommittee on Entrepreneurship and Innovation Evaluation (Chair, 2008).
Subcommittee on Fellowship Awards (2014-2015)
Subcommittee on the Management Science Core, (1982 - 1983).
Subcommittee on Tracks (2008-2009).
Subcommittee on Strategy Curriculum (2009).
MIT Sloan Committee on Educational Technology, 2004 – 2006.
Operations Research Center
Admissions Committee, (1981 - 1982).
Associated Faculty (1980 – 2000).
Operations Research Committee (2001- 2003).
President's Committee (1984).
Organization Committee for the New MIT Sloan Building, E62, (2007- 2009).
Personnel and Policy Committee, MIT Sloan (Executive Committee, 2005 – 2009, 2013-2014).
Chair of ad hoc committees for reappointment, promotion, and tenure (1983 - 2014).
Member of ad hoc committees for reappointment, promotion, and tenure (1981 - 2014).
Sloan Appreciation Awards Committee (2013-2014)
Symposium Director, Marketing Center, MIT Sloan School, M.I.T., (1981 - 1982).
Zannetos Dissertation Award Committee, MIT Sloan, (1981-82, 1996-97, chair 1997-1998).
M.I.T. Subjects Taught (often multiple sections)
15.810, Marketing Management (Core) Spring 1990, 1991, 1992, 1993, 1994, 1995, 1997, 1998, 1999, 2001, 2004, 2005. 2006, 2018. Fall 1999, 2006, 2007, 2008, 2011, 2012,
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2013, 2014, 2015. (Teaching awards listed on page 2 of vita.). Retitled Marketing Innovation in 2018.
15.812, Marketing Management (UG) Fall 1981, 1982, 1984, 1985, 1986. Spring 1981, 1984, 2006, 2018. Retitled Marketing Innovation in 2018.
15.813, Marketing Management in Public Sector Fall 1980.
15.814, Marketing Innovation Spring 2019
15.8141, Marketing Innovation (UG) Spring 2019
15.814, Marketing Mgmt (Mgmt of Technology) Fall 1988, 1993, 1999, 2001.
15.820, Advanced Marketing Management Spring 1990
15.828, New Product Development Spring 1981, 1982, 1989; Fall 1982, 1984; 1985.
15.838, Ph.D. Seminar (Various Topics) Spring 1986, 1997, 2002, 2006, 2011, 2013, 2014, 2015, 2016.
15.839, Marketing and Statistics Workshop Spring 1982; Fall 1982, 1984.
15.TH4. Thesis Project on Competitive Strategy Spring 1985, 1986.
CS.113 A Core Ethics: Ethics in Marketing Fall 2014, 2015, 2016, 2017.
Summer Session, ILP, and External Executive
A.T.&T Course on New Product Development, 1986.
European Institute for Business Administration (INSEAD) European Marketing Programme, 1985.
Greater Boston Area Executive Program, 1982, 1983.
M.I.T. Civil Engineering, Demand Theory, 1980, 1981, and 1982.
M.I.T. ILP, Marketing Strategy and Models in the Information age, 1983.
M.I.T., Management of R&D, 1989, 1990, 1991, 1992, 1993, 1994. 1995, 1996, 1997, 1998, 1999.
M.I.T. Marketing Science Symposium, 1981, 1982, 1983, 1984, 1985, 1986, 1987, 1988.
M.I.T./M.I.P. Executive Program, 1992.
M.I.T. New Product Development, 1997.
Pedagogical Developments.
In 2017-209, I headed an effort to redesign the basic marketing course with further consideration of redesigning the entire marketing curriculum.
In 2012, I redesigned the core curriculum in marketing to reflect new developments in marketing analytics, big data, and new media.
In 1990 and 1991, Prof. John D. C. Little and I redesigned the core curriculum in Marketing Management and taught the course to the entire Master's class.
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In the 1991-1992 I was part of a committee of six faculty members that redesigned the core curriculum at the Sloan School. I supervised the voice-of-the-customer analyses of students and recruiters and encouraged the committee to design a program that these customers would find exciting. The new core was implemented in the 1993-1994 academic year. Student satisfaction increased significantly.
Teaching Notes
Note on Defensive Marketing Strategy (2005, for 15.810, Marketing Management)
Note on Product Development (2105, for 15.810, Marketing Management)
Note on the Voice of the Customer (2018 for 15.814, Marketing Innovation)
Note on Consumer Behavior (2015, for 15.810, Marketing Management)
Note on Life Cycle Diffusion Models (2005, for 15.810, Marketing Management)
Note on Engineering Product Design (2006, for 15.810, Marketing Management)
Note on Conjoint Analysis (2018, for 15.814, Marketing Innovation)
M.I.T. Thesis Supervision
(a) MIT Sloan School of Management, Master's Theses
Hafiz Adamjee (joint with John Scaife), "The Face of the Customer: The Use of Multimedia in Quality Function Deployment," - (1993). This product was subsequently commercialized and was a finalist for the New Media Invision 1994 Multimedia award at COMDEX/Spring '94.
Ramay Akras, "Competitive Strategy in the Marketing of Small DDP Computers: an Analysis of Emerging Price and Product Position Patterns," - (1986).
Frederic Amerson, "Strategic Marketing Simulation: Improvements to the Enterprise Integrating Exercise," - (1989).
Sébastien Andrivet (Sloan Fellows Program), “Customer research, customer-driven design, and business strategy in Massively Multiplayer Online Games,” – (2007)
Andrew Anagnos (joint with Karen Van Kirk), "A Framework for Analyzing Quality in the News Media," - (1991)
Allen Aerni, "Measurement of Customer Satisfaction," - (1994).
Joel Berez, "An Investigation of Decision Hierarchies" - (1981).
Harel Beit-on, "Competitive Strategy for Small Business Jet Aircraft," - (1985).
Willy Biberstein (SDM Program), "Framework for Customer Interaction Throughout the Automotive Product Development Process," (February 2002).
Andre Borschberg (joint with Webb Elkins), "Defensive Marketing Strategy: Its Application to a financial Decision Support System" - Reader (1983).
Philippe Bosquet, "European Airline Deregulation: Defining Air France's Strategy for the 1990's," - Reader (1989)
Jill A. Christians, (joint with Cheryl M. Duckworth), "Expectations and Customer Satisfaction: A Market Research Study for Plimoth Plantation," Reader (1994).
Poh-Kian Chua (MOT Program), “R,D&E Metrics: Shaping the Outcomes of Your R,D&E Investment,” – (1998).
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Leslie K. Cooper, "The Structure of Recruiter Needs at the Sloan School of Management: A Quantitative Assessment," - (1992).
Teruyuki Daino (Sloan Fellows Program), “How a Leading Company Can Overcome a Competitive Challenge: A Case Study of Anheuser-Busch Company.” – (1998).
Laura E. Donohue, "Software Product Development: An Application of the Integration of R&D and Marketing via Quality Function Deployment" - (1990)
Cheryl M. Duckworth (joint with Jill A. Christians), "Expectations and Customer Satisfaction: A Market Research Study for Plimoth Plantation," Reader (1994).
Webb Elkins (joint with Andre Borschberg), "Defensive Marketing Strategy: Its Application to a Financial Decision Support System" - Reader (1983).
Rasheed El-Moslimany (LFM Program), "Getting Value from the Value Chain: Comfort Choice," Co-Advisor. (June 2002)
Merve Ergez (Master of Science in Management Studies), Strategic Scent Selection: A Marketing Research Study for Olivita Brand,” (June 2014).
Julio Faura (MOT Program), "Contribution to Web-based Conjoint Analysis for Market Research," (2000).
Richard Feldman, "Decision Support Systems for Forecasting Communications in the Home," - Reader (1985).
Anders T. Fornander, "The Continuing Operating System Battle in the Personal Computer Industry," - Reader (1994).
Carl Frank (MOT Program), "Metrics Thermostat for Strategic Priorities in Military System Acquisition Projects," (2000).
Mihaela Fulga, "Competitive Pricing and Positioning Strategies in the Dating Service Market," - (1986).
Steven P. Gaskin, "Defender: Test and Application of a Defensive Marketing Model" - (1986). 1st Place, Brooks Award.
Peter N. Goettler, "A Pre-market Forecasting Model of New Consumer Durables: Development and Application," - Reader (1986).
Patti N. Goldberger, "Competitive Strategy in the Market for Running Shoes," - (1985).
Akhil Gupta, "The Personal Computer Industry: Economic and Market Influences on Product Positioning Strategies," - (1986).
Michael Halloran (joint with Marc Silver), "Defensive Marketing Strategy: Empirical Applications" - (1983).
Carla Heaton, "Competitive Strategy in the Facsimile Market," - (1985).
Judith Hee, "Determining Manufacturer's Coupon Strategies" - Reader (1981).
Jonathan E. Higginson, “Understanding Dependencies in Research and Development at the Charles Stark Draper Laboratory.” - (1997).
Scott D. Hill, "Correlation of Core Competencies with Market-Driven or Self-Guided Research," - (1995).
Dan Isaacs, "Competitive Pricing and Positioning Strategies in the Imported Beer Marketing," - (1986).
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Francois Jacques, "Marketing Strategies in Innovative Industries: The Case of Package/Document Delivery Services," - Co-Advisor (1985).
Lawrence Kahn, "Competitive Positioning: A Study of Recruiter's and Employer's Perceptions of the Sloan School of Management" - (1982). Honorable mention Brooke's Thesis Prize.
D. Darcy Kay, "Competitive Strategy for Anti-arthritic Drugs" - (1985).
Young Joo Kim (MOT Program), “R&D Management Applications of The Dynamic Metrics Framework” – (1998)
Priya Kher (Systems Design and Management Program), “Using Application Generated Data to Provide Personalized User Experience in Software Applications” – (2018)
Sidney A. Kriger, "The Effect of Quality Function Deployment on Communications of the New Product Development Teams," - (1989)
Yasuke Kume, "New Marketing Strategy of Telecommunications in Japan" - Reader (1981).
Elvind Lange, "Measuring Market Response to Marketing Mix Variables Using Dynamic Modeling and Its Implications for Brand Strategy" - Reader (1981).
Stephen P. Langhans, "Defensive Marketing Strategy: A Consumer Semi-Durable Case Example" - (1983).
In-Kyu Lee, "Evaluating System for the Upstream Center of R&D for being Market-Oriented in a Consumer Electronics Company," - (1995).
Michael Leslie (joint with Joel Wachtler), "A Methodology for Making International Marketing Mix Decisions," - Reader (1985).
Kit Mee Lim, "Competitive Strategy among Companies Offering Credit Cards," - Reader (1985).
James A. Lutz, "Competitive Marketing Strategy in the CAD Marketplace," - (1985).
Larry D. Lyons, "Forecasting the Impact of Competitive Entries on Sales of a New Consumer Durable" - Reader (1984).
Arpita Majundar (SDM Program), "Strategic Metrics for Product Development at Ford Motor Company," - (2000).
Catherine E. Manion, "A Survey of Customer Satisfaction Incentive Systems for Salespersons," - (1993).
Maureen E. Matamoros, "Information Overload," – Reader (1986).
Meghan McArdle (LFM Program), "Internet-based Rapid Customer Feedback for Design Feature Tradeoff Analysis," – co-Advisor (2000)
Fernando Motta, "Competitive Strategy Among Panamanian Banks," - (1985).
Neil Novich, "Price and Promotion Analysis Using Scanner Data" - Reader (1981).
Kenji Nozaki, "Marketing and Technology Strategy for the Japanese Architectural Design Company," - (1989).
Seiji Nozawa, “Voice of the Customer Analysis in the Japanese Beer Market.” - (1997).
Minho Park (MOT Program), “R&D Matrix at LG Electronics.” - (1997)
Stephen Pearse, "Production and Sales Forecasting: A Case Study and Analysis" - Reader (1982).
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Ning P. Peng, "An Exploration of the Impact and Success of Customer Satisfaction Programs," - (1994). Homer Pien (MOT Program), “Competitive Advantage through Successful Management of R&D.” - (1997) Susan B. Poulin, "Defensive Strategy in the Automatic Test Equipment Industry" (1984).
Jill W. Roberts, "MBA Recruiters' Needs: Voice of the Customer Analysis," - (1992).
Lisa Gayle Ross, "A Voice of the Customer Analysis of M.B.A. Schools: The Student Segment," - (1992). Lisa was a runner-up for the George Hay Brown Marketing Scholar of the Year in 1992.
Tamaki Sano, “Strategy for Kirin as a Global Brand” – (2009) Sloan Fellow.
John Scaife (joint with Hafiz Adamjee), "The Face of the Customer: The Use of Multimedia in Quality Function Deployment," - (1993). See award listed under Adamjee.
Paul E. Schoidtz, "Advertising, Price, and Positioning Equilibria," - (1986).
Hongmei Shang, "A Simulation Analysis of Optimal Task Assignment for Growing Managers from R&D Labs," – (February 2000).
Rosemarie Shield, "Competitive Pricing and Positioning Strategies in the Chromatographic Instruments Market," - , (1986).
Jon Silver (joint with John C. Thompson, Jr.), "Beta-binomial Analysis of Customer Needs -- Channels for Personal Computers," - (1991). 1st Prize, Brooks Award.
Marc Silver (joint with Michael Halloran), "Defensive Marketing Strategy: Empirical Applications" - (1983).
Lisa Silverman, "An Application of New Product Growth Modeling to Automobile Introductions" - (1982).
Sheryl Sligh, "An Assessment of the Analog Modem Market," - (1991).
Jamie Smith, "Industrial Buying Process of Pension Funds for Real Estate," - (1982).
Yoshihito Takahashi (MOT), "Analysis of Strategy in an Ethical Drug Industry," – Reader ( 2000).
Genevieve Tchang, "A Methodology for Planning and Evaluating External Relations at Business Schools" - Reader (1982).
John C. Thompson, Jr. (joint with Jon Silver), "Beta-binomial Analysis of Customer Needs -- Channels for Personal Computers," - (1991). 1st Place, Brooks Award.
V. Mullin Traynor, "The Dissemination and Adoption of New Technology: Control Data's Computer-Based Training System, Plato, and the Electric Utilities" - (1982).
Karen Van Kirk (joint with Andrew Anagnos), "A Framework for Analyzing Quality in the News Media," - (1991)
Joel Wachtler (joint with Michael Leslie), "A Methodology for Making International Marketing Mix Decisions," - Reader (1985).
Tamao Watanabe, "Customer Analysis of the U.S. Cardiovascular Drug Market: Focusing on Physician's Drug Choice" - (1991)
Stephen L. Weise, "Expert Decision Support Systems for Marketing Management," – Reader (1986).
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Nancy Werner, "Competitive Price and Positioning in the Integrated Office Automation Systems Market" - (1986).
Julie Wherry, “Pre-Test Marketing: Its Current State in the Consumer Goods Industry and Its Effect on Determining a Networked Good.” - (2006).
Ali Yalcin, "The Potentials and Limitations of Customer Satisfaction Indices in Captive Customer-Supplier Environments," - (1995)
Sandra Yie, "The Core Curriculum at Sloan: Establishing a Hierarchy of Needs," - (1992).
Judy Young, "Responsive Marketing Strategy at AT&T" - (1982).
(b) Aeronautics S.M. Theses
Keith Russell (LSI), "Reengineering Metrics Systems for Aircraft Sustainment Teams: A Metrics Thermostat for Use in Strategic Priority Management," (February 2001).
(c) Electrical Engineering, S.B. and M.Eng. Theses
Chan, Christine W. Y. (M. Eng), “Measuring Non-Monetary Incentives Using Conjoint Analysis,” Co-Advisor (1999).
Emily Hui (M.Eng.), "Application of Polyhedral Conjoint Analysis to the Design of Sloan's Executive Education Programs." June 2003.
Brian T. Miller (S. B.), "A Verification of Price Equilibria Based on Non-Zero Conjectural Variation," (1986).
(d) Mechanical Engineering, Master’s Theses
Burt D. LaFountain, “An Empirical Exploration of Metrics for Product Development Teams” – (1999)
Tina Savage, “The Virtual Customer: A Distributed Methodology for Linking Product Design and Customer Preferences.” Co-Advisor (1998).
(e) Operations Research Center, Master’s Theses
Jeffrey Moffit (ORC), " Applying the Metrics Thermostat to Naval Acquisitions for Improving the Total Ownership Cost – Effectiveness of New Systems," (2001)
Olivier Toubia (ORC), "Interior-point Methods Applied to Internet Conjoint Analysis," (February 2001), Co- Advisor.
(f) Urban Studies, Master's Theses
Marijoan Bull, "Affirmative Fair Housing Marketing" - Committee Member (1982).
Barry Cosgrove, "Marketing Analysis for the Brockton Area Transportation Authority" – Committee Member (1981).
(g) Sloan School of Management, Ph.D. Theses
Makoto Abe, "A Marketing Mix Model Developed from Single Source Data: A Semiparametric Approach." Committee member (August 1991). Abe is on the faculty at the University of Tokyo.
Cao, Xinyu, “Consumer Inattention, Uncertainty, and Marketing Strategy.” Committee member (June 2018). Cao is joining the faculty at New York University.
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Daria Dzyabura, “Essays on Machine Learning in Marketing (tentative title),” Chairman (June 2012). Dzyabura is on the faculty at the New Economic School in Russia.
Peter Fader, "Effective Strategies in Oligopolies," Chairman (February 1987). Sloan School of Management, Zannetos Prize, 1st Place. Fader is on the faculty at the University of Pennsylvania. Fred Feinberg, "Pulsing Policies for Aggregate Advertising Models" Committee Member (August 1988). Feinberg is on the faculty of the University of Michigan. Dave Godes, " Friend or Foe?: The Relationship Between Learning and Incentives and two additional essays in marketing," (June 2000), Committee Member. Primary advisor on listed essay. Zannetos Prize, 1st Place. Godes is on the faculty of the University of Maryland. Abbie Griffin, "Functionally Integrated New Product Development: Improving the Product Development Process Through Linking Marketing and Technology Development," Chairman. (June 1989). Griffin is on the faculty at the University of Utah and was editor of Journal of Product Innovation Management from 1997-2003 Frank Bass Dissertation Award (INFORMS).
Gurumurthy Kalyanaram, "Empirical Modeling of the Dynamics of the Order of Entry Effect on Market Share, Trial Penetration and Repeat Purchases for Frequently Purchased Consumer Goods," Committee Member (March 1989). G. K. was on the faculty at the University of Texas, Dallas.
Eriko Kitazawa, "Customer Satisfaction at Japanese Utility Franchises," Committee Member (1996).
Li, Xitong, “Using Web Data and Services: Technology, Theory, and Evidence,” Co-chairman (2014). Li is on the faculty at HEC Paris.
Eleanor (Nell) Putnam-Farr, “The Effects of Framing on Enrollment and Participation – Field Experiments Using Different Recruitment Language.” June 2015. Putnam-Farr joined Yale University as a post doctoral fellow. She is joining the faculty at Rice University.
John H. Roberts, "A Multiattributed Utility Diffusion Model: Theory and Application to the Prelaunch Forecasting of Autos". Committee Member (February 1984). Roberts is on the faculty at the London Business School and the Australian Graduate School of Management..
Matt Selove, “The Strategic Importance of Accuracy in Conjoint Design,” Committee Member (June 2010). Selove joined the faculty at the University of Southern California. He is now on the faculty at the University of Florida. John Howard Dissertation Award (AMA), 2010.
Duncan I. Simester, "Analytical Essays on Marketing," Committee Member, (June 1993). Sloan School of Management, Zannetos Prize, Honorable Mention. Simester is on the faculty of M.I.T.
Artem Timoshenko, "Essays on Machine Learning in Marketing (tentative ,June 2019),." Timoshenko is on the faculty of Northwestern University.
Olivier Toubia, “New Approaches to Idea Generation and Consumer Input in the Product Development Process,” (June 2004). Toubia is on the faculty of Columbia University. Frank M. Bass Dissertation Award (INFORMS), 2005, John Howard Dissertation Award (AMA), 2005. ISMS Long-term Impact Award 2016.
Miguel Villas-Boas, "On Promotions and Advertising Policies: A Strategic Approach." Committee member (February 1991). Villas-Boas is on the faculty at the University of California, Berkeley.
Bruce Weinberg, "An Information-Acceleration-Based Methodology for Developing Preproduction Forecasts for Durable Goods: Design, Development, and Initial Validation." Committee Member. (August 1992). Weinberg was on the faculty at Boston University.
Florian Zettelmeyer, “Three Essays on Strategic and Organizational Uses of Information in Marketing.” Committee Member. Zettelmeyer is on the faculty of Northwestern University.
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(h) Civil Engineering, Ph.D. Thesis
Karla Karash (Ph.D.), "An Application of the Lens Model in Measuring Retail Attractiveness and the Effects of Transportation Programs" - Committee Member (August 1983). Karash was at the MBTA.
(j) Mechanical Engineering, Ph.D. Thesis
Javier Gonzalez-Zugasti (Mechanical Engineering, Ph.D.), "Models for Product Family Design and Selection," (June 2000), Committee Member.
(k) Operations Research Center, Ph.D. Thesis
Yee, Michael (Operations Research, Ph.D.), “Inferring Non-Compensatory Choice Heuristics,” (June 2006), Co- Advisor. Yee is at MIT’s Lincoln Laboratories.
Northwestern University Ph.D. Thesis Supervision (1975 - 1980 Academic Years)
Steven M. Shugan, "A Descriptive Stochastic Preference Theory and Dynamic Optimization: Applications Toward Predicting Consumer Choice' Chairman (September 1977). Shugan is on the faculty at the University of Florida and was editor of Marketing Science for six years.
Patricia Simmie, "Product Realization: Theory, Models, and Application" - Chairman (June 1979), American Marketing Association Dissertation Prize, Honorable Mention. Simmie was at York University.
Ken J. Wisniewski, "A Semi-Markov Theory of Consumer Response: New Theoretical Properties, Simulation Testing, and Empirical Application" Chairman (June 1981). American Marketing Association Dissertation Prize, First Place. Wisniewski was on the University of Chicago.
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APPENDIX B
PUBLIC VERSION
John R. Hauser Prior Testimony 2014–2020
Thomas Allegra, et al. v. Luxottica Retail North America, Case No. 1:17-CV-05216-PKC-RLM, United States District Court, Eastern District of New York, Brooklyn Division. Deposition testimony, January 10, 2020.
Shane Witham and Robert Maginnis v. FCA Canada Inc.et al., Case No. CV-17-567691-00CP, Ontario Superior Court of Justice. Hearing testimony, December 6, 2019.
MillerCoors, LLC, v. Anheuser-Busch Companies, LLC, Case No. 19-CV-218, United States District Court for the District of Wisconsin. Deposition testimony, October 28, 2019.
Yahoo Holdings, Inc., et al. v. Mozilla Corporation, Case No. 17-CV-319921, Superior Court of the State of California, County of Santa Clara. Deposition testimony, September 13, 2019.
Malden Transportation, Inc., et al v. Uber Technologies, Inc., Rasier, LLC, Case No. 1:16-cv-12538- NMG, United States District Court, District of Massachusetts. Deposition testimony, January 30, 2019. Trial testimony, July 31 – August 1, 2019.
State of Washington v. Comcast Cable Communications Management, LLC; Comcast Cable Communications, LLC; and Comcast of Colorado/Florida/Michigan/New Mexico/Pennsylvania/Washington, LLC, Case No. 16-2-18224-1 SEA, State of Washington King County Superior Court. Deposition testimony, August 9, 2018.
United States of America v. AT&T Inc., DirecTV Group Holdings, LLC, and Time Warner Inc., Case No. 1:17-cv-02511, United States District Court for the District of Columbia. Deposition testimony, March 9, 2018. Trial testimony, March 29, 2018.
Joseph Adinolfe, et al., v. United Technologies Corp., d/b/a Pratt & Whitney, Case No. 10-80840- CIVKAM, In the United States District Court, Southern District of Florida, West Palm Beach Division. Deposition testimony, July 12, 2016. Class certification hearing testimony, January 9, 2018.
Garth Anderson, et al., v. American Family Insurance Company, Case No. 5:15-CV-475 (MTT), United States District Court for the Middle District of Georgia, Macon Division. Deposition testimony, November 14, 2017.
In the Matter of Determination of Royalty Rates and Terms for Transmission of Sound Recordings by Satellite Radio and “Preexisting” Subscription Services (SDARS III) before United States Copyright Royalty Judges, Library of Congress, Washington, DC, Docket No. 16-CRB-0001-SR/PSSR (2018- 2022). Deposition testimony, March 17, 2017. Trial testimony, May 9, 2017.
Oula Zakaria v. Gerber Products Co., a Corporation, d/b/a Nestle Nutrition, Nestle Infant Nutrition, and Nestle Nutrition North America, No. 2:15-cv- 0200-JAK, United States District Court, Central District of California. Deposition testimony, November 17, 2016.
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Sprint Communications Company L.P. et al. v. Comcast Cable Communications, LLC. et al., Case No. 2:12-cv-00859-JD, United States District Court for the Eastern District of Pennsylvania. Deposition testimony, April 5, 2016.
Scott Miller v. Fuhu, Inc. and Fuhu Holdings, Inc, Case No. 14-cv-6119 CAS-AS, United States District Court for the Central District of California, Western Division. Deposition testimony, October 20, 2015.
Symphony Health Solutions Corporation v. IMS Medical Radar, Case CBM2014-00188, United States Patent and Trademark Office. Deposition testimony, June 15, 2015.
In the Matter of Determination Of Rates And Terms For Digital Performance In Sound Recordings And Ephemeral Recordings (Web IV) before United States Copyright Royalty Judges, Library of Congress, Washington, DC, Docket No. 14-CRB-0001-WR. Deposition testimony, March 25, 2015. Trial testimony, May 22, 2015.
Fox Broadcasting Company, Inc. v. Dish Network LLC, Civil Action No. 12-04536-DMB-SHx, United States District Court for the Central District of California. Deposition testimony, December 15, 2014.
Michael Kors, Inc. v. Costco Wholesale Corporation, Civil Action No. 13-CV-4832, United States District Court for the Southern District of New York. Deposition testimony, June 9, 2014.
Apple Inc. v. Samsung Electronics Co. Ltd. et al., Case No. 12-CV-00630, United States District Court for the Northern District of California San Jose Division. Deposition testimony, September 27, 2013. Trial testimony, April 8, 2014.
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APPENDIX C
PUBLIC VERSION
Materials Relied Upon
Expert Reports
Written Direct Testimony of Professor John R. Hauser, September 20, 2019, and backup materials.
Written Direct Testimony of Gal Zauberman, September 20, 2019, and backup materials, including survey data, analysis code, and documents relied upon.
Written Direct Testimony of Dominique M. Hanssens, September 23, 2019, and backup materials, including survey data, survey start data, analysis code, and documents considered.
Books
Aaker, David A., V. Kumar, and George S. Day, Marketing Research, Fifth Edition, John Wiley & Sons, Inc., 1995.
Diamond, Shari S., “Reference Guide on Survey Research,” in Reference Manual on Scientific Evidence, Third Edition, Washington, D.C.: Federal Judicial Center and National Research Council of the National Academies, 2011, pp. 359–423, available at https://www.fjc.gov/content/reference-guide-survey-research-2.
Krosnick, Jon A. and Stanley Presser, “Question and Questionnaire Design,” in Handbook of Survey Research, Second Edition, Bingley, U.K.: Emerald Group Publishing Limited, 2010, pp. 263–313.
Payne, Stanley L.B., “Isn’t that Loaded?” in The Art of Asking Questions, Princeton, NJ: Princeton University Press, 1980, pp. 177–202.
Tourangeau, Roger, Lance J. Rips, and Kenneth Rasinski, The Psychology of Survey Response, Tenth Edition, New York, NY: Cambridge University Press, 2009.
Academic Articles
Bradburn, Norman M., Lance J. Rips, and Steven K. Shevell, “Answering Autobiographical Questions: The Impact of Memory and Inference on Surveys,” Science 236, 4798, 1987, pp. 157–161.
Buchanan, Tony W., “Retrieval of Emotional Memories,” Psychological Bulletin Journal 133, 5, 2007, pp. 761–779.
Fieller, E.C., H.O. Hartley, and E.S. Pearson, “Tests for Rank Correlation Coefficients. I.,” Biometrika 44, 3/4, 1957, pp. 470–481.
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Sawyer, Alan G., “Demand Artifacts in Laboratory Experiments in Consumer Research,” Journal of Consumer Research 1, 4, 1975, pp. 20–30.
Shimp, Terence A., Eva M. Hyatt, and David J. Snyder, “A Critical Appraisal of Demand Artifacts in Consumer Research,” Journal of Consumer Research 18, 3, 1991, pp. 273–283.
Internet Sources
Andrea Zarczynski, “Record High 34.9 Million Paid Subscribers Marks SiriusXM Milestone Year,” Forbes, January 7, 2020, available at https://www.forbes.com/sites/andreazarczynski/2020/01/07/record-high-349-million- paid-subscribers-marks-siriusxm-milestone-year/#695fe3283787.
“Choose How You Want to Listen,” Pandora, available at https://www.pandora.com/.
“Recommendations and Personalization on Pandora,” Pandora Help, available at https://help.pandora.com/s/article/000001078?language=en_US.
“SiriusXM’s Huge Library of On Demand Content - Featuring Howard Stern and Much More - Now Available on Amazon Alexa and Echo Devices,” SiriusXM, November 19, 2019, available at http://investor.siriusxm.com/investor- overview/press-releases/press-release-details/2019/SiriusXMs-Huge-Library-of-On- Demand-Content---Featuring-Howard-Stern-and-Much-More---Now-Available-on- Amazon-Alexa-and-Echo-Devices/default.aspx.
“Skips and Replays,” Pandora Help, available at https://help.pandora.com/s/article/Skips-1519949305278?language=en_US.
“U.S. Sales Database,” Recording Industry Association of America, available at https://www.riaa.com/u-s-sales-database/.
Industry Reports
Morgan Stanley, “5th Annual Music & Radio Survey,” January 10, 2019 (SXMWEBV_00005137).
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APPENDIX D
PUBLIC VERSION
Ways Survey Respondents Listened To Music Hauser Survey QS10 and Zauberman Survey Q1[1]
Hauser QS10 Zauberman Q1 Response Last 3 Days[2] Last 30 Days[3]
AM/FM Radio on a Receiver[4] 75.9% 77.9%
Free On-Demand Streaming Service[5] 44.9% 67.6%
CDs, Vinyl Records, or MP3 Files[6] 35.7% 52.4%
Free Streaming Radio Service[7] 32.5% 65.6%
Paid On-Demand Streaming Service[8] 23.5% 39.5%
SiriusXM Satellite Radio Service[9] 19.5% 28.8%
Paid Streaming Radio Service[10] 7.0% 20.8%
Number of Respondents 3,889 6,146
Average Number of Responses per Respondent[11] 2.4 3.5
Source: Written Direct Testimony of Professor John R. Hauser; Hauser Survey Data; Written Direct Testimony of Gal Zauberman
Note: [1] The percentages represent the share of respondents selecting the corresponding music-listening options that are common between the two surveys. 10.9 percent of respondents selected the Hauser Survey QS10 response “I listened to music channels through a cable or satellite television subscription (e.g., Music Choice),” which is not an available option in Zauberman Survey Q1. [2] The Hauser Survey QS10 screening question asks: “You mentioned that you listened to music or non-music content in the last three days. In which, if any, of the following ways did you listen to that content? (Select all that apply).” This tabulation is limited to respondents who selected “I listened to music (e.g., pop, country, rock)” over the last three days in Hauser Survey QS9.
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[3] The Zauberman Survey Q1 question asks: “In the past 30 days, which of the following music-listening options have you used to listen to music?” [4] AM/FM Radio on a Receiver corresponds to: the Zauberman Survey Q1 response “AM/FM radio on a traditional radio receiver. (Please do not select this option if you only listen to AM/FM radio streamed over the internet or on a phone)”; the Hauser Survey QS10 response “I listened to live AM/FM radio broadcasts through a radio.” [5] Free On-Demand Streaming Service corresponds to: the Zauberman Survey Q1 response “A FREE on-demand streaming service, such as free Spotify and free YouTube, where you can choose the specific songs you want to hear on-demand and/or listen to playlists, but must listen to advertisements”; the Hauser Survey QS10 responses “I listened to on-demand music streaming service(s) that have ads and that I do not need to pay for (e.g., ad-supported Spotify)” and “I listened to music on video site(s) that have ads and that I do not need to pay for (e.g., ad-supported YouTube).” The calculated percentage for Hauser Survey QS10 represents the percentage of respondents who selected at least one of these responses. [6] CDs, Vinyl Records, or MP3 Files corresponds to: the Zauberman Survey Q1 response “CDs, Vinyl Records, or MP3 Files that you own”; the Hauser Survey QS10 responses “I listened to digital music files or CDs” and “I listened to music obtained through peer-to-peer file sharing or free download sites.” The calculated percentage for Hauser Survey QS10 represents the percentage of respondents who selected at least one of these responses. [7] Free Streaming Radio Service corresponds to: the Zauberman Survey Q1 response “A FREE streaming radio service, such as personalized radio services like free Pandora and free iHeart Radio, and online streams of AM/FM radio stations, where you cannot choose a specific song, and must listen to advertisements”; the Hauser Survey QS10 responses “I listened to not-on-demand music streaming service(s) that have ads and that I do not need to pay for (e.g., ad-supported Pandora)” and “I listened to live AM/FM radio broadcasts over the Internet.” The calculated percentage for Hauser Survey QS10 represents the percentage of respondents who selected at least one of these responses. [8] Paid On-Demand Streaming Service corresponds to: the Zauberman Survey Q1 response “A PAID on-demand streaming service, such as Spotify Premium, Apple Music, YouTube Premium, and Amazon Music, where you can choose the specific songs you want to hear on-demand and/or listen to playlists, all commercial free, at a price of approximately $9.99 per month”; the Hauser Survey QS10 response “I listened to on-demand music streaming service(s) through paid subscription(s) (e.g., Apple Music, Spotify Premium, Google Play Music).” [9] SiriusXM Satellite Radio Service corresponds to: the Zauberman Survey Q1 response “Sirius XM satellite radio on a satellite receiver in your car, home or somewhere else, at a price of approximately $10.99 to $20.99 per month. (Please do not select this option if you only stream Sirius XM over the internet or on a phone)”; the Hauser Survey QS10 response “I listened to satellite radio through a paid subscription (SiriusXM).” [10] Paid Streaming Radio Service corresponds to: the Zauberman Survey Q1 response “A PAID streaming radio service, such as Pandora Plus, iHeart Radio Premium, and Rhapsody unRadio, where you can listen to customized radio stations commercial free, but cannot choose a specific song, at a price of approximately $4.99 per month. (Please also select this option if you stream Sirius XM over the internet or on a phone, but not on a satellite receiver)”; the Hauser Survey QS10 response “I listened to not-on-demand music streaming services(s) through paid subscription(s) (e.g., Pandora Plus).” [11] The average number of responses per respondent for each survey is calculated as the sum of the percentages divided by 100 percent. The Hauser Survey QS10 responses “I listened to non-music digital content (e.g., podcasts, audiobooks),” “I listened to music channels through a cable or satellite television subscription (e.g., Music Choice),” “Other. (Please specify, if not already selected in the list above),” and “Don’t know/Unsure” are not available options in Zauberman Survey Q1, and thus are excluded from this table.
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APPENDIX E
PUBLIC VERSION Approximate Survey Response Comparison Hauser Survey Q5 and Zauberman Survey Q2 Free Hypothetical
Hauser Zauberman Q5 Figure 8 (Percent of Q5 (Percent of Figure 8 Response Respondents) (Normalized)[1] Respondents) (Normalized)[2]
Paid On-Demand Streaming Service[3] 8.8% 10.5% 38.7% 10.1% Free On-Demand Streaming Service[4] 9.6% 11.4% 79.9% 20.8% Paid Streaming Radio Service[5] 4.4% 5.2% 33.4% 8.7% Free Streaming Radio Service[6] 10.0% – – – SiriusXM Satellite Radio Service[7] 8.4% 10.0% 30.9% 8.0% AM/FM Radio on a Receiver[8] 28.9% 34.4% 84.6% 22.0% CDs, Vinyl Records, or MP3 Files[9] 8.4% 10.0% 69.2% 18.0% Do Something Other than Listen to Music[10] 15.6% 18.5% 48.2% 12.5% Other (not listed above)[11] 6.0% – – –
Total (Percentage) 100% 100% 385% 100%
Source: Written Direct Testimony of Professor John R. Hauser; Hauser Survey Data; Written Direct Testimony of Gal Zauberman
Note: [1] In Q5 of the Hauser Survey, 84.0 percent of respondents selected a response option that is not classified as free streaming radio or “other (not listed above),” which is composed of options not available to respondents in the Zauberman Survey. After I matched response options from the Hauser Survey to the corresponding response options from the Zauberman Survey, I rescaled the matched results to this question by dividing all percentages by 0.84. [2] In Q2 of the Zauberman Survey, on average, respondents selected “yes” to 3.85 response options. I rescaled the results to this question by dividing all reported percentages by 3.85. [3] Paid On-Demand Streaming Service corresponds to: the Zauberman Survey Q2 response “Paid On-Demand Streaming Service”; the aggregation of the Hauser Survey Q5 choices “I would listen to on-demand music streaming service(s) through the paid subscriptions I already have (e.g., Apple Music, Spotify Premium, Google Play Music)” and “I would purchase new paid subscription(s) to on-demand music streaming service(s) that I don’t currently subscribe to (e.g. an individual subscription to Apple Music, Spotify Premium, or Google Play Music at $9.99 per month or $119.88 per year).” [4] Free On-Demand Streaming Service corresponds to: the Zauberman Survey Q2 response “Free On-Demand Streaming Service”; the aggregation of the Hauser Survey Q5 choices “I would listen to on-demand music streaming service(s) that have ads and that I do not need to pay for (e.g. ad-supported Spotify)” and “I would listen to music on video site(s) that have ads and that I do not need to pay for (e.g. ad-supported YouTube).” [5] Paid Streaming Radio Service corresponds to: the Zauberman Survey Q2 response “Paid Streaming Radio Service”; the aggregation of the Hauser Survey Q5 choices “I would listen to not-on-demand music streaming service(s) through the paid subscription(s) I already have (e.g., Pandora Plus)” and “I would purchase a new paid subscription(s) to not-on-demand music streaming service(s) that I don’t currently subscribe to (e.g., an individual subscription to Pandora Plus at $4.99 per month or $59.88 per year).” E-1 NAB Written Rebuttal Statement Dkt. No. 19-CRB-0005-WR (2021-25) PUBLIC VERSION
[6] Free Streaming Radio Service corresponds to: the Zauberman Survey Q2 response “Free Streaming Radio Service”; the aggregation of the Hauser Survey Q5 choices “I would listen to not-on-demand music streaming service(s) that have ads and that I do not need to pay for (e.g., ad-supported Pandora)” and “I would listen to live AM/FM radio broadcasts from not-for-profit radio stations (e.g., NPR, college radio stations) over the Internet.” [7] SiriusXM Satellite Radio Service on a Receiver corresponds to: the Zauberman Survey Q2 response “Sirius XM Satellite Radio Service on a Receiver”; the aggregation of the Hauser Survey Q5 choices “I would listen to satellite radio through the paid subscription I already have (SiriusXM)” and “I would purchase a new paid subscription to the satellite radio that I don’t currently subscribe to (e.g., a SiriusXM subscription at $10.99 per month or $131.88 per year for ad-free music, $15.99 per month or $191.88 per year for ad-free music, news, traffic, weather, and other content).” [8] AM/FM Radio on a Receiver corresponds to: the Zauberman Survey Q2 response “AM/FM Radio on a Receiver”; the aggregation of the Hauser Survey Q5 choices “I would listen to live AM/FM radio broadcasts from commercial radio stations through a radio” and “I would listen to live AM/FM radio broadcasts from not-for-profit radio stations (e.g., NPR, college radio stations) through a radio.” [9] CDs, Vinyl Records, or MP3 Files corresponds to: the Zauberman Survey Q2 response “CDs, Vinyl Records, or MP3 Files”; the aggregation of the Hauser Survey Q5 choices “I would listen to digital music files or CDs that I already purchased,” “I would purchase and listen to digital music files or CDs that I don’t currently own,” and “I would listen to music obtained through peer-to-peer file sharing or free download sites.” [10] Do Something Other than Listen to Music corresponds to: the Zauberman Survey Q2 response “Do Something Other than Listen to Music”; the aggregation of the Hauser Survey Q5 choices “I would listen to non-music digital content that I already purchased or downloaded (e.g., podcasts, audiobooks),” “I would purchase or download and listen to non-music digital content that I don’t currently own (e.g., podcasts, audiobooks),” “I would watch video content that I already purchased, subscribe to, or have access to (e.g., movies, cable television, Hulu, Netflix),” “I would purchase or subscribe to video content that I don’t currently own or subscribe to (e.g., movies, cable television, a Hulu subscription at $5.99 per month or $71.88 per year, a Netflix subscription at $8.99 per month or $107.88 per year),” “I would read print or online content that I already purchased, subscribe to, or have access to (e.g., books, newspapers, magazines),” and “I would purchase or subscribe to print or online content that I don’t currently own or subscribe to (e.g., books, newspapers, magazines).” [11] Other (not listed above) corresponds to: the aggregation of the Hauser Survey Q5 choices “I would listen to music channels through my existing cable or satellite television subscription (e.g., Music Choice),” “Other,” “Don’t Know/Unsure,” and “Blank responses,” which includes the three respondents who did not select “Would consider” for any options in Hauser Survey Q4, and thus were not directed to Hauser Survey Q5.
E-2 NAB Written Rebuttal Statement Dkt. No. 19-CRB-0005-WR (2021-25) PUBLIC VERSION PUBLIC VERSION
7$% ( PUBLIC VERSION
Before the UNITED STATES COPYRIGHT ROYALTY BOARD LIBRARY OF CONGRESS Washington, D.C.
In the Matter of:
Determination of Rates and Terms for Digital Performance of Sound Recordings Docket No. 19-CRB-0005-WR and Making of Ephemeral Copies to (2021-2025) Facilitate those Performances (Web V)
WRITTEN REBUTTAL TESTIMONY OF JOSEPH RITZ (On Behalf of iHeartMedia, Inc., a National Association of Broadcasters Member Company)
1. I am Vice President, Finance, Digital Networks at iHeartMedia, Inc. (“iHeart” or
“the company”). I submit this statement in support of the National Association of Broadcasters’
(“NAB”) written rebuttal case in the above-captioned proceeding.
BACKGROUND AND QUALIFICATIONS
2. I have worked on the finance team at iHeart since June 2015. My first role was
Finance Manager. In that role, I was responsible for working with iHeart’s national programming group to financially plan our larger national events — known as “tent pole” events — including the iHeart Music Festival and Jingle Ball. In October 2016, I became Director, Corporate Financial
Planning & Analysis. In that role, I similarly worked on financially planning iHeart’s large sponsorship deals and events. In September 2017, I took on my current role of Vice President,
Finance, Digital Networks. In this role, I oversee all digital revenue and expenses for iHeart, including expenses related to sound recording royalties. My team manages the tracking and payment of sound recording royalties both to SoundExchange and our direct deal partners. I am familiar with, and frequently directly involved in, the process by which iHeart responds to 1 NAB Written Rebuttal Statement Dkt. No. 19-CRB-0005-WR (2021-25)
PUBLIC VERSION
information requests from auditors. While much of the work on SoundExchange’s 2011-2013
audit of iHeart was done before I joined the company, I am generally familiar with that audit,
which has been ongoing for the last five years. In addition to audits by SoundExchange, I
understand that iHeart is subject to audits from the performing rights organizations (“PROs”).
PROs like ASCAP, BMI, SESAC, and GMR have the ability to audit iHeart. I further understand
that, since the summer of 2018, ASCAP, BMI, and SESAC have all conducted audits of iHeart’s books and records.
3. Prior to joining iHeart, I held finance roles at LiveStyle, Inc. (“LiveStyle”).
LiveStyle is one of the world’s largest music event producers. I worked in Mergers & Acquisitions
from 2013 to 2014 and served as Finance Lead, North American Live from 2014 to 2015.
4. Prior to joining LiveStyle, I worked at some of the world’s largest accounting organizations. Specifically, I was Transaction Advisory Manager at Ernst & Young from 2011 to
2013 and Senior Associate at KPMG from 2006 to 2011. In my role at KPMG, I worked on audits for a number of Fortune 500 consumer products companies. Based on this experience, I am familiar with standard audit procedures, extrapolations, and other general assessments made within the scope of a professional audit.
5. I have a bachelor’s degree in accounting from Quinnipiac University (2006) and a master’s degree in accounting from Fairleigh Dickinson University (2008).
IHEART’S INCENTIVES TO PAY FOR THE USE OF SOUND RECORDINGS
6. I understand that SoundExchange has taken the position that licensees have a
“strong incentive to underpay statutory royalties.” Bender WDT ¶ 90. At iHeart, nothing could be further from the truth. In fact, we have strong business incentives to ensure our royalty payments are timely and accurate.
2 NAB Written Rebuttal Statement Dkt. No. 19-CRB-0005-WR (2021-25)
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team, and legal team. These internal reviews are necessary before providing raw data to ensure
iHeart is providing exactly what the auditors are requesting while not jeopardizing our proprietary
data and systems. Moreover, it is especially time-consuming to prepare and produce the requested
data when a licensor waits a substantial period of time after the close of a fiscal year to initiate an
audit. In those cases, the iHeart personnel responsible for maintaining the relevant performance
data and payments may have left the company, and the data systems we use to maintain the
requested information may have changed in ways that make old information difficult to both obtain
and merge with existing data and systems.
12. Second, iHeart does not have a dedicated team that responds to audits. Rather, our royalty finance, data management and reporting, engineering, and legal personnel must take time away from their already demanding workloads to search for information, create documents, and sign off on production. I estimate that more than ten iHeart personnel are typically involved in the search for, creation, and production of information for an audit.
13. Third, iHeart typically has little or no notice when an auditor will serve requests for
information during the course of an audit. If the company is in the midst of its budget season or a
new product launch or significant upgrade, it can be extremely difficult for iHeart personnel to
dedicate any substantial amount of time to responding to auditor requests.
14. Fourth, as with most audits, the auditor determines the accuracy of several months
of payments and then extrapolates to reach a figure for the entire relevant period. That
extrapolation involves a number of assumptions (e.g., that a particular month is representative of
the entire period) that iHeart finance and legal personnel must examine and potentially challenge
in a time-consuming back-and-forth with the auditor. This process is rarely simple and
straightforward.
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SOUNDEXCHANGE’S 2011-2013 AUDIT OF IHEART
15. I understand that, in late December 2014, SoundExchange noticed an audit of iHeart’s royalty payments for 2011-2013. That audit is ongoing today. In my view, iHeart has worked hard to provide the extensive information requested, and delays on the part of the auditors have contributed substantially to the fact that the audit remains open.
16. I understand that the Royalty Review Council (“RRC”), a specialized royalty consulting firm, and accounting firm Dawson & Associates (“Dawson”) were initially engaged to conduct the 2011-2013 audit. I understand that the RRC initiated the first round of questions and data requests. It is my understanding that these initial requests were burdensome in several respects. Most importantly, they involved data and related questions going back to the beginning of iHeart’s music service and therefore required iHeart’s engineers to retrace steps and systems created and maintained by other engineers no longer at the company. Although the RRC’s initial requests imposed a substantial burden on iHeart, the company worked to gather and provide the requested information, ultimately tasking (to the best of my knowledge) about four data engineers, two business managers, inside and outside counsel, and two other iHeart executives with taking time away from their jobs to create and review responsive information.
17. It is my understanding, based on my conversations with iHeart employees who worked with the RRC and Dawson, that the original requests from the RRC and Dawson were very detailed and contained several sub-requests. The requests sought detailed information related to iHeart’s systems, performance data, and logs, as well as data only attainable from third parties. I further understand that iHeart did its best to gather and provide data, despite the considerable volume of data sought and the difficulties associated with pulling and merging data that was several years old.
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18. It is my understanding that iHeart initially objected to RRC’s involvement in the
SoundExchange audit. However, I understand that iHeart ultimately accepted RRC’s consulting role so long as it was clear that Dawson would be in charge of the audit. Then, over a year into the audit, the auditor changed from Dawson to Armanino LLP (“Armanino”). iHeart was not informed of the reason for this change, and had no opportunity to object. Naturally,
SoundExchange’s decision to transition to a new auditor slowed the process down.
19. iHeart worked diligently to prepare, deliver, and redeliver responsive documents to
(and answer follow-up questions from) the new Armanino audit team. While some of Armanino’s follow-up questions could be answered within minutes, other requests required additional time- consuming data pulls and extensive internal review. We provided the requested data and responded to all of Armanino’s questions as soon as possible.
20. A series of logistical obstacles on Armanino’s end further delayed and complicated
the audit. Several months into Armanino’s audit work, the RRC was removed from the
SoundExchange audit. Then, a month later, Armanino removed its lead auditor and team from the
engagement. At that time, it is my understanding that Armanino deleted files iHeart had provided
from its systems. These unanticipated personnel changes and data deletions led to more delays
and logistical headaches.
21. After Armanino introduced a new lead auditor, iHeart redelivered files provided to date to Armanino, despite the fact that those files were still accessible (as they had been since July
2016) at the shared file transfer location. Several months after the redelivery, Armanino issued additional follow-up questions. iHeart responded to Armanino and continued to work with the audit team at a reasonable pace. A few months later, Armanino again asked for redelivery of the data files. iHeart reminded the audit team of the original file transfer drop location.
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22. iHeart engaged in back-and-forth with Armanino for several months, hoping to
finalize the audit as soon as possible. In early 2018, iHeart provided yet more data in response to
Armanino’s requests and offered to answer any additional questions. We then heard nothing from
Armanino for 15 months. We had no idea of the status of the audit until we received a draft audit report from Armanino in July 2019.
23. Following receipt of the draft report, iHeart requested a call with Armanino to object to various provisions in the draft that did not follow logically from the data presented and to extrapolations that were both based upon limited data and inconsistent application of use of sample data. Misunderstandings on the part of the auditors—and this late in the audit process— have required additional follow-up that will now further delay the process.
24. Since then, the audit has been at somewhat of a standstill due to Armanino’s request for additional data (albeit at iHeart’s urging) that is not readily available to iHeart. In October
2019, Armanino requested data for six additional months from the audit period after having initially requested data for only three months. Because iHeart’s limited technical support staff spent much of Q4 2019 preparing for other time-sensitive projects, we are only now able to divert resources to responding to these additional data requests. The primary issue with Armanino’s additional data requests is that some of the data sought is nine years old at this point. In order to collect it, we need to pull from outdated systems and piece together information from different platforms, which is made even more difficult by the fact that many of the engineers who created and maintained these systems are no longer with iHeart. The longer an audit is delayed, the more burdensome it becomes to collect the relevant data, which is certainly the case with the present
SoundExchange audit.
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25. I understand that SoundExchange has claimed that the 2011-2013 audit has been delayed due to [
]. In my view, none of these issues resulted in a more significant delay than the delays caused by the auditors and SoundExchange. For
example, none of the aforementioned factors caused the delay between iHeart’s delivery of
information in April 2018 and Armanino’s delivery of the draft audit report in July 2019, a period
of over 15 months. Moreover, business issues such as [
] are exactly the reason
that putting strict time limits on licensees’ responses to auditor requests is unreasonable and
impractical.
26. In sum, providing information in connection with the 2011-2013 audit has been particularly burdensome for iHeart. When SoundExchange initiated the audit in late December
2014, all of the relevant information was between one and four years old. Much of the data sought
is now nine years old. When an audit involves data from almost a decade prior, the systems and
technology quickly become outdated and difficult to translate to new and updated systems. At the beginning of the SoundExchange audit, much of iHeart’s files were stored in a warehouse; today,
all of the data is in the cloud. The level of quality control and review necessary to ensure the
requested files are complete and exactly what SoundExchange’s auditors are looking for is difficult
and takes time. Additionally, the turnover in our engineering department over the past nine years
(a variable outside our control) substantially complicates data collection and review. Despite these
obstacles, iHeart has done its best to close out what feels like a never-ending process.
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SOUNDEXCHANGE’S AUDIT-RELATED PROPOSALS
27. I understand that SoundExchange has proposed several changes to the audit-related
terms of the statutory license. I do not believe these changes are warranted, reasonable, or feasible.
A. Multiple Audits Per Year
28. I understand that SoundExchange has proposed that it be permitted to conduct
audits of multiple time periods in the same year. This proposal would impose even greater burdens
on iHeart than the current audit process already does, and thus slow down a process
SoundExchange claims it wants to speed up.
29. Requiring iHeart to provide information related to more than one audit in a given
year would substantially increase the burdens I describe in paragraphs 10-14 above. It would mean
a second set of auditors—or even a third or fourth, since SoundExchange’s proposal puts no limit
on the number of audits it may conduct at once as long as they cover different time periods—with
an entirely different set of ad hoc data requests. It would mean double (or triple, or more) the work
for the iHeart finance, data management and reporting, engineering, and legal personnel who must pull, prepare, and review responsive information. It would potentially mean additional problems
associated with gathering and manipulating old data. And it would make it more likely that auditor
requests would come in while iHeart personnel were focused on new product launches, significant
upgrades, or other important business decisions and events. SoundExchange’s proposal that the
licensees be required to do even more work in a single year will only slow the audit process down.
30. In addition, it is important to keep in mind that SoundExchange is not the only
rightsholder representative that has the ability to audit iHeart. In addition to the audit rights in
direct label deals discussed above, the PROs (i.e., ASCAP, BMI, SESAC, and GMR) have the
right to audit iHeart. It is my understanding that these PRO audits have occurred simultaneously
10 NAB Written Rebuttal Statement Dkt. No. 19-CRB-0005-WR (2021-25)
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33. What strikes me most about SoundExchange’s proposal is that it imposes deadlines
only on the licensee, not the auditor. In my experience, it is frequently the auditor that causes significant delays in the audit process. While there are instances where a licensee like iHeart may take substantial time to respond to a request for certain data, these delays are largely the result of limited resources. Imposing hard deadlines, as SoundExchange proposes, will only lead to more problems for both iHeart and SoundExchange. In my experience, under the time constraints proposed by SoundExchange, there is no guarantee that companies could provide complete, accurate, or vetted data. Instead, it is possible that companies would provide data in whatever form to avoid missing a punitive deadline. SoundExchange’s proposed deadlines are just repackaging and kicking the same problem down the road, albeit in incremental steps. I believe this will inevitably lead to more requests (albeit on a shorter timeframe). SoundExchange’s proposal does nothing to solve that problem. It will only lead to more follow-up questions and
requests while imposing unreasonable deadlines on just one party in the process—the licensee.
34. More specifically, imposing a bright-line 60-day deadline for fieldwork
appointments and responses to information requests is simply not reasonable or practical. There
are certainly instances in which iHeart could (and in fact has) provided information to an auditor
in far less than 60 days. A request regarding the meaning of a character string in a data file, for
example, is something that could be responded to in a matter of hours. But many requests are far
more complicated, involving a huge range and volume of data. If the auditor wants hundreds of
deliverables containing data within specific parameters, 60 days is not a reasonable period of time
in which to respond. There cannot be a one-size-fits-all response deadline, when information
requests vary so significantly.
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35. The same is true of a deadline for commenting on tentative findings. In some cases,
iHeart might be able to provide comments on a draft report within 60 days, such as where the report reflects comprehensive findings that have been vetted by both sides and do not involve complicated extrapolations. But in the case of a report that makes questionable assumptions, is poorly drafted and fails to make connections between assumptions and conclusions, or raises a dispute regarding whether there are over- or underpayments, the report would take far longer to analyze and respond to. Often auditor extrapolations do not take into account categories of overpayments made by iHeart, which can involve significant back and forth between the auditor and iHeart, additional review of the source data from which the extrapolations are made, and even more internal review from multiple departments. A 60-day deadline to comment on a draft report is simply not feasible in all cases.
36. Finally, I note that none of iHeart’s direct license agreements with independent labels [
], and I am not aware of any marketplace agreements that impose such deadlines.
C. SoundExchange’s Participation in the Audit
37. I understand that SoundExchange has proposed that the auditor be allowed to consult with SoundExchange, including to advise SoundExchange of the status of the audit, request information from SoundExchange relevant to the audit, and request SoundExchange’s views regarding tentative findings and other issues. I believe that audits should remain independent, which is how they are conducted pursuant to agreements reached in the free market.
38. In iHeart’s direct license agreements with independent labels, the audit provisions
allow for an
13 NAB Written Rebuttal Statement Dkt. No. 19-CRB-0005-WR (2021-25)
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]. See, e.g., NAB Ex. 40, § 5(b); NAB Ex. 41, § 5(b); NAB Ex. 42, § 5(b); NAB Ex. 54
§ 5(b). There is no provision in these agreements allowing the auditor to request information
relevant to the audit from the label or to request the label’s views regarding tentative findings or
any other issues.
39. Further, it is my understanding that there are often significant unresolved issues to be worked through between the auditor and iHeart, as the target of the audit, which, if disclosed to
SoundExchange, could prejudice iHeart in any discussions with SoundExchange following the
delivery of the final audit report. Based on my experience, it seems counterproductive, and
contrary to the purpose of an independent audit, to have SoundExchange participate in an audit
when the auditor is being hired for their professional skill, expertise, and objectivity.
40. Finally, if SoundExchange were permitted to participate in the audit, iHeart would
feel compelled to hire an auditor that is actually independent, in order to verify the results of
SoundExchange’s auditor. That would further complicate and delay the audit process.
D. Interest Rate for Underpayment
41. I understand that the statutory license currently provides for an 18% annual interest rate on underpayments. I further understand that NAB has proposed amending that rate to the federal post-judgment rate in 28 U.S.C. § 1961 (consistent with the interest rate recently adopted by the Copyright Royalty Judges in the SDARS III proceeding), and that SoundExchange proposes maintaining the current rate. I believe NAB’s proposal makes more sense.
42. The interest rate is not iHeart’s only incentive to ensure its payments are accurate and timely. As I have explained, iHeart takes its obligation to pay artists for use of their sound recordings very seriously, as failure to do so could harm its relationships with artists and direct deal partners. See supra ¶¶ 6-9. Any underpayments uncovered during an audit may simply reflect
14 NAB Written Rebuttal Statement Dkt. No. 19-CRB-0005-WR (2021-25)
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good faith errors or reasonable disagreements between the parties about the proper interpretation of the statutory license. The 18% interest rate is therefore inappropriate, especially because
SoundExchange may conduct an audit for any of the prior three calendar years.
15 NAB Written Rebuttal Statement Dkt. No. 19-CRB-0005-WR (2021-25)
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7$% ) PUBLIC VERSION
Before the UNITED STATES COPYRIGHT ROYALTY BOARD LIBRARY OF CONGRESS Washington, D.C.
In the Matter of:
Determination of Rates and Terms for Docket No. 19-CRB-0005-WR Digital Performance of Sound Recordings (2021-2025) and Making of Ephemeral Copies to Facilitate those Performances (Web V)
DECLARATION AND CERTIFICATION OF SARANG VIJAY DAMLE ON BEHALF OF THE NATIONAL ASSOCIATION OF BROADCASTERS
1. I am counsel for the National Association of Broadcasters (“NAB”) in this proceeding.
2. On June 24, 2019, the Copyright Royalty Board (“CRB”) entered a protective order that limits the disclosure of “confidential information” to outside counsel of record and their staff, personnel supplied by any independent contractor with whom such attorneys work, and any outside independent consultant or expert who is assisting a participant to this proceeding (“Protective
Order”). See Dkt. No. 4012. The participants agreed that in this proceeding, “confidential information” protectable under the Protective Order (hereinafter referred to as “Restricted material”) “shall consist of commercial or financial information disclosed by any means
(including, but not limited to, through documents, testimony, or argument), by a Participant
(Producing Participant) to another Participant or other Participants, that the Producing Participant has reasonably determined in good faith would, if disclosed, either (1) result in a competitive disadvantage to the Producing Participant, (2) provide a competitive advantage to another
Participant or entity, or (3) interfere with the ability of the Producing Participant to obtain like information from other Participants or entities in the future.” Id. § III. Prior to the production of 1 NAB Written Rebuttal Statement Dkt. No. 19-CRB-0005-WR (2021-25) PUBLIC VERSION
Restricted materials, participants must (1) mark these materials “with a conspicuous label of
‘RESTRICTED – Subject to Protective Order in Docket No. 19-CRB-0005-WR (2021-25)’”;
(2) mark these materials “with highlights or brackets”; and (3) “deliver with all Restricted materials an affidavit or declaration signed under penalty of perjury listing a description of all materials marked with the ‘Restricted’ stamp and the basis for the designation.” Id. § IV.A.
3. Pursuant to the Protective Order, I submit this declaration in support of NAB’s designation of certain rebuttal testimony as “Restricted.”
4. I have reviewed NAB’s rebuttal introductory memorandum and rebuttal witness testimony. After consultation with my client and with the witnesses who submitted rebuttal testimony in support of NAB’s rebuttal case, I have determined to the best of my knowledge, information, and belief that portions of NAB’s rebuttal introductory memorandum and rebuttal witness testimony contain non-public Restricted material protected under the Protective Order.
Restricted material is redacted in the public copies of NAB’s filing, highlighted in gray and bracketed in the restricted copies of NAB’s filing, and described in more detail below.
5. The Restricted materials include, but are not limited to, testimony involving:
(a) contracts, contractual terms, and contract strategy that are proprietary, not available to the public, competitively sensitive, and often subject to express confidentiality provisions with third parties; (b) confidential internal business information, financial data, and competitive strategy that are proprietary, not available to the public, and commercially sensitive; (c) communications between NAB’s member station groups and content providers concerning activities that, if disclosed, would disrupt ongoing partnerships and collaborations, and interfere with future partnerships and collaborations; and (d) various matters that SoundExchange has designated as confidential.
2 NAB Written Rebuttal Statement Dkt. No. 19-CRB-0005-WR (2021-25) PUBLIC VERSION
6. If Restricted materials of the NAB and NAB member stations were to become public, it would place NAB and its member stations at a commercial and competitive disadvantage, unfairly advantage other parties to the detriment of NAB and its member stations, and jeopardize
NAB and its member station’s business interests. Information related to NAB member stations’ confidential contracts and their relationships with content providers could be used by their competitors, or by other content providers, to formulate rival bids, bid up NAB member station payments, or otherwise unfairly jeopardize NAB member stations’ commercial and competitive interests.
7. The Written Rebuttal Testimony of NAB’s economic expert, Dr. Gregory K.
Leonard, and the accompanying appendices contain material non-public information concerning
(among other things) the particular terms agreed to by specific NAB member stations in direct licenses; NAB member stations’ sensitive communications with content providers; and various matters that SoundExchange has designated as confidential or that NAB understands
SoundExchange would wish to keep under seal. None of this information is publicly known or available. Disclosure of such information belonging to NAB member stations would put the stations at a competitive disadvantage.
8. The Written Rebuttal Testimony of Joseph Ritz, Vice President, Finance, Digital
Networks, iHeartMedia, Inc. (“iHeart”), contains non-public information concerning the particular terms agreed to by iHeart in license agreements with record labels for sound recording public performance rights. Disclosure of this information would, for the reasons discussed above, competitively disadvantage iHeart.
9. The contractual and commercial information described in the paragraphs above must be treated as restricted confidential information in order to prevent business and competitive
3 NAB Written Rebuttal Statement Dkt. No. 19-CRB-0005-WR (2021-25) PUBLIC VERSION
harm that would result from the disclosure of such information while, at the same time, enabling
NAB to provide the Judges with the most complete record possible on which to base their determination in this proceeding.
I declare under penalty of perjury that the foregoing is true and correct, and that I executed this Declaration on January 10, 2020 in Washington, D.C.
Sarang Vijay Damle
4 NAB Written Rebuttal Statement Dkt. No. 19-CRB-0005-WR (2021-25) PUBLIC VERSION
TAB G
PUBLIC VERSION
Before the UNITED STATES COPYRIGHT ROYALTY BOARD LIBRARY OF CONGRESS Washington, D.C.
In the Matter of: Docket No. 19-CRB-0005-WR Determination of Rates and Terms for (2021-2025) Digital Performance of Sound Recordings and Making of Ephemeral Copies to CERTIFICATE OF SERVICE Facilitate those Performances (Web V)
CERTIFICATE OF SERVICE Dkt. No. 19-CRB-0005-WR (2021-25)
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CERTIFICATE OF SERVICE
I am employed in Washington, D.C. I am over the age of 18 years and not a party to this action. My business address is Latham & Watkins LLP, 555 Eleventh Street, NW, Suite 1000,
Washington, D.C. 20004.
I hereby certify that on January 10, 2020, I caused a copy of the foregoing Written
Rebuttal Statement of the National Association of Broadcasters to be served via electronic mail delivery to the people set forth below, who have consented to electronic mail service.
David Handzo Alex S. Trepp Devi M. Rao Emily Chapuis James Dawson Jennifer J. Yun Loreal R . Rock Previn Warren Steven R. Englund Andrew B. Cherry Jenner & Block LLP 1099 New York Ave., NW, Suite 900 Washington, D.C. 20001 Tel: (202) 639-6000 Fax: (202) 639-6066 Email: [email protected] Email: [email protected] Email: [email protected] Email: [email protected] Email: [email protected] Email: [email protected] Email: [email protected] Email: [email protected] Email: [email protected] Email: [email protected]
Counsel for The American Association of Independent Music; The American Federation of Musicians of the United States and Canada; Jagjaguwar, Inc.; SAG-AFTRA; Sony Music Entertainment; SoundExchange, Inc.; UMG Recordings, Inc.; and Warner Music Group Corp.
David Golden Constantine Cannon, LLP
2 CERTIFICATE OF SERVICE Dkt. No. 19-CRB-0005-WR (2021-25) PUBLIC VERSION
1001 Pennsylvania Ave., NW, Suite 1300N Washington, D.C. 20004 Tel: (202) 204-3500 Fax: (202) 204-3501 Email: [email protected]
Counsel for College Broadcasters, Inc.
David Oxenford Jennifer Tatel Wilkinson, Barker, Knauer, LLP 1800 M. Street, NW, Suite 800N Washington, D.C. 20036 Tel: (202) 783-4141 Fax: (202) 783-5851 Email: [email protected] Email: [email protected]
Counsel for Educational Media Foundation and Radio Paradise Inc.
Kenneth L. Steinthal Lida Ramsey King & Spalding LLP 101 Second Street Suite 2300 San Francisco, CA 94105 Tel: (415) 318-1211 Email: [email protected] Email: [email protected] Email: [email protected]
David P. Mattern King & Spalding LLP 1700 Pennsylvania Ave, NW, Suite 200 Washington, D.C. 20006 Email: [email protected]
Jason B. Cunningham King & Spalding LLP 401 Congress Ave. Austin, TX 78701 Tel: (512) 457-2023 Email: [email protected]
Counsel for Google Inc. and National Public Radio, Inc.
3 CERTIFICATE OF SERVICE Dkt. No. 19-CRB-0005-WR (2021-25) PUBLIC VERSION
Karyn K. Ablin Elizabeth Craig Fletcher, Heald & Hildreth, P.L.C. 1300 N. 17th St., 11th Floor Arlington, VA 22209 Tel: (703) 812-0443 Fax: (703) 812-0486 Email: [email protected] Email: [email protected] Email: [email protected]
Counsel for National Religious Broadcasters Noncommercial Music License Committee
Benjamin E. Marks Todd Larson Jeremy C. Cain Jeremy P. Auster Jessica L. Falk Lucas F. Tesoriero Reed L. Collins Weil, Gotshal & Manges LLP 767 Fifth Avenue New York, NY 10153 Tel: (212) 310-8000 Fax: (212) 310-8007 Email: [email protected] Email: [email protected] Email: [email protected] Email: [email protected] Email: [email protected] Email: [email protected] Email: [email protected]
Counsel for Pandora Media, LLC and Sirius XM Radio Inc.
I declare under penalty of perjury that the foregoing is true and correct, and that I executed this Declaration on January 10, 2020 in Washington, D.C.
Sarang Vijay Damle 4 CERTIFICATE OF SERVICE Dkt. No. 19-CRB-0005-WR (2021-25) Before the UNITED STATES COPYRIGHT ROYALTY BOARD LIBRARY OF CONGRESS Washington, D.C.
In the Matter of: Docket No. 19-CRB-0005-WR Determination of Rates and Terms for (2021-2025) Digital Performance of Sound Recordings and Making of Ephemeral Copies to CERTIFICATE OF SERVICE Facilitate those Performances (Web V)
CERTIFICATE OF SERVICE Dkt. No. 19-CRB-0005-WR (2021-25)
CERTIFICATE OF SERVICE
I am employed in Washington, D.C. I am over the age of 18 years and not a party to this action. My business address is Latham & Watkins LLP, 555 Eleventh Street, NW, Suite 1000,
Washington, D.C. 20004.
I hereby certify that on January 14, 2020, I caused a copy of the foregoing Public Version of the Written Rebuttal Statement of the National Association of Broadcasters to be served via electronic mail delivery to the people set forth below, who have consented to electronic mail service.
David Handzo Alex S. Trepp Devi M. Rao Emily Chapuis James Dawson Jennifer J. Yun Loreal R . Rock Previn Warren Steven R. Englund Andrew B. Cherry Jenner & Block LLP 1099 New York Ave., NW, Suite 900 Washington, D.C. 20001 Tel: (202) 639-6000 Fax: (202) 639-6066 Email: [email protected] Email: [email protected] Email: [email protected] Email: [email protected] Email: [email protected] Email: [email protected] Email: [email protected] Email: [email protected] Email: [email protected] Email: [email protected]
Counsel for The American Association of Independent Music; The American Federation of Musicians of the United States and Canada; Jagjaguwar, Inc.; SAG-AFTRA; Sony Music Entertainment; SoundExchange, Inc.; UMG Recordings, Inc.; and Warner Music Group Corp.
2 CERTIFICATE OF SERVICE Dkt. No. 19-CRB-0005-WR (2021-25) David Golden Constantine Cannon, LLP 1001 Pennsylvania Ave., NW, Suite 1300N Washington, D.C. 20004 Tel: (202) 204-3500 Fax: (202) 204-3501 Email: [email protected]
Counsel for College Broadcasters, Inc.
David Oxenford Jennifer Tatel Wilkinson, Barker, Knauer, LLP 1800 M. Street, NW, Suite 800N Washington, D.C. 20036 Tel: (202) 783-4141 Fax: (202) 783-5851 Email: [email protected] Email: [email protected]
Counsel for Educational Media Foundation and Radio Paradise Inc.
Kenneth L. Steinthal Lida Ramsey King & Spalding LLP 101 Second Street Suite 2300 San Francisco, CA 94105 Tel: (415) 318-1211 Email: [email protected] Email: [email protected] Email: [email protected]
David P. Mattern King & Spalding LLP 1700 Pennsylvania Ave, NW, Suite 200 Washington, D.C. 20006 Email: [email protected]
Jason B. Cunningham King & Spalding LLP 401 Congress Ave. Austin, TX 78701 Tel: (512) 457-2023 Email: [email protected]
Counsel for Google Inc. and National Public Radio, Inc.
3 CERTIFICATE OF SERVICE Dkt. No. 19-CRB-0005-WR (2021-25)
Karyn K. Ablin Elizabeth Craig Fletcher, Heald & Hildreth, P.L.C. 1300 N. 17th St., 11th Floor Arlington, VA 22209 Tel: (703) 812-0443 Fax: (703) 812-0486 Email: [email protected] Email: [email protected] Email: [email protected]
Counsel for National Religious Broadcasters Noncommercial Music License Committee
Benjamin E. Marks Todd Larson Jeremy C. Cain Jeremy P. Auster Jessica L. Falk Lucas F. Tesoriero Reed L. Collins Weil, Gotshal & Manges LLP 767 Fifth Avenue New York, NY 10153 Tel: (212) 310-8000 Fax: (212) 310-8007 Email: [email protected] Email: [email protected] Email: [email protected] Email: [email protected] Email: [email protected] Email: [email protected] Email: [email protected]
Counsel for Pandora Media, LLC and Sirius XM Radio Inc.
I declare under penalty of perjury that the foregoing is true and correct, and that I executed this Declaration on January 14, 2020 in Washington, D.C.
Sarang Vijay Damle 4 CERTIFICATE OF SERVICE Dkt. No. 19-CRB-0005-WR (2021-25) Proof of Delivery
I hereby certify that on Tuesday, January 14, 2020, I provided a true and correct copy of the Written Rebuttal Statement of The National Association of Broadcasters [Public Version] to the following:
Jagjaguwar Inc., represented by Steven R. Englund, served via Electronic Service at [email protected]
American Association of Independent Music ("A2IM"), The, represented by Steven R. Englund, served via Electronic Service at [email protected]
Pandora Media, LLC, represented by Reed L Collins, served via Electronic Service at [email protected]
National Religious Broadcasters Noncommercial Music License Committee, represented by Karyn K Ablin, served via Electronic Service at [email protected]
Google Inc., represented by Kenneth L Steinthal, served via Electronic Service at [email protected]
Radio Paradise Inc., represented by David Oxenford, served via Electronic Service at [email protected]
Sirius XM Radio Inc., represented by Reed L Collins, served via Electronic Service at [email protected]
American Federation of Musicians of the United States and Canada, The, represented by Steven R. Englund, served via Electronic Service at [email protected]
National Public Radio, Inc., represented by Kenneth L Steinthal, served via Electronic Service at [email protected]
SoundExchange, Inc., represented by Steven R. Englund, served via Electronic Service at [email protected]
Warner Music Group Corp., represented by Steven R. Englund, served via Electronic Service at [email protected] circle god network inc d/b/a david powell, represented by david powell, served via Electronic Service at [email protected]
Corporation for Public Broadcasting, represented by Kenneth L Steinthal, served via Electronic Service at [email protected]
Educational Media Foundation, represented by Jennifer Tatel, served via Electronic Service at [email protected]
Sony Music Entertainment, represented by Steven R. Englund, served via Electronic Service at [email protected]
College Broadcasters, Inc., represented by David D Golden, served via Electronic Service at [email protected]
UMG Recordings, Inc., represented by Steven R. Englund, served via Electronic Service at [email protected]
SAG-AFTRA, represented by Steven R. Englund, served via Electronic Service at [email protected]
iHeartMedia, Inc., represented by John Thorne, served via Electronic Service at [email protected]
Signed: /s/ Sarang V Damle