A note on conglomerate mergers: The Google/Fitbit caseAkihiko Nakagawa *(Graduate School of Law, Hokkaido University)
Noriaki Matsushima †(Institute of Social and Economic Research, Osaka University)

Abstract
We consider conglomerate mergers using the Google/Fitbit case as an example. First,
summarizing the importance of conglomerate merger control and the current
enforcement standards for such mergers by competition laws, we briefly describe areview of the Google/Fitbit merger by the Japan Fair Trade Commission. Next, we
explain the background of the merger and introduce Chen et al. (2022), whotheoretically discuss a cross-market merger by considering the Google/Fitbit merger.
Finally, we discuss the implications of Chen et al. (2022) for controlling
conglomerate mergers. Specifically, personalized pricing based on data analytics
can be a foreclosure device; in particular, merger-specific efficiencies can foster
market foreclosure.
Keywords: Conglomerate mergers, Google-Fitbit, Personalized pricing, Law enforcement
JEL codes: K40, L13, L44* Akihiko Nakagawa, Graduate School of Law, Hokkaido University, Kita 9 Nishi 7, Kita-ku, Sapporo, Hokkaido,
060-0808 Japan. E-mail: aki@juris.hokudai.ac.jp† Corresponding author: Noriaki Matsushima, Institute of Social and Economic Research, Osaka University, 6-1
Mihogaoka, Ibaraki, Osaka 567-0047, Japan. E-mail: nmatsush@iser.osaka-u.ac.jp

1. Introduction
Compared to horizontal mergers, conglomerate mergers have rarely been regulated
by competition laws. Conglomerate mergers are generally defined as mergers in which
the merging parties are neither competitors (horizontal) nor trading relationships(vertical). Competition laws generally prohibit conduct that restrains competition,
harming other trading parties who otherwise would benefit from competition in themarket. Since the merging parties to conglomerate mergers do not compete with eachother in the same market, the effects of conglomerate mergers on competition are notapparent in the merger itself. In recent years, however, we have witnessed increasing calls
for greater vigilance against acquisitions by digital platform companies, especially thosewith enormous market capitalization. As Bourreau and de Streel (2019) describe, “Oneof the main and most intriguing characteristics of the digital sector is the resurgence of
conglomeralism.” Among the policy proposals, there are calls for tighter control against
mergers that expand the scope of network effects and strengthen “the (conglomerate)ecosystem” (Crémer et al., 2019), updating Merger Guidelines for “Toning down theexisting text that suggests non-horizontal mergers will typically be benign,” (Furman etal., 2019) and introducing a presumption of illegality against startups’ acquisitions bydominant firms (Stigler Committee, 2019; Subcommittee, 2020). In addition to platforms,
an increasing number of businesses are collecting a variety of data on consumer behavior,
which has been newly available owing to technological advances and are using it forbusiness insights and marketing purposes. Firms that collect and use such consumer data
are generally able to sell goods and services directly to consumers; therefore, mergers inthis sector are likely to be both non-horizontal and horizontal.
1.1. Conglomerate control in practiceAt least four theories of competitive harm constitute the basis for prohibiting
conglomerate mergers:(1) The merged entity forecloses competitors in one or both markets by tying or bundlingits products. 1(2) The merged entity forecloses competitors from the market for related products bydeteriorating its product’s interoperability with competitors’ related products. 2
1

European Commission (2008, paras. 93, 95-97); ACCC (2008, para. 5.26); JFTC (2019, VI.2(1)A); DOJ (2020, §4.a,
Example 6); CMA (2021, para. 7.30). The 2020 Vertical Merger Guidelines were initially adopted by both the DOJ andthe Federal Trade Commission (FTC), but the FTC withdrew the Guidelines on September 15, 2021.
https://www.ftc.gov/news-events/news/press-releases/2021/09/federal-trade-commission-withdraws-vertical-mergerguidelines-commentary.
2 JFTC (2019, VI.2 n.15). Other jurisdictions treat this competitive harm as an input foreclosure: European
Commission (2008, para. 33); CMA (2021, para.7.11). The FTC has also addressed interoperability degrading as an
input foreclosure. See, e.g., In the Matter of Silicon Graphics, Inc., 120 F.T.C.928 (1995); In the Matter of Cadence2(3) By gaining access to competitors’ commercially sensitive information, the merged
entity reduces competitors’ competitive efforts. 3(4) Conglomerate mergers eliminate potential competition between the merging parties. 4
While this is not exhaustive of all the negative effects of such mergers oncompetition, 5 they have been relatively well analyzed. Because of rising concerns that
acquisitions of startups may be wiping out the last remaining sources of “future
disruption,” recent emphasis is put on the loss of “potential and dynamic competition,”as exemplified by the newly updated Competition and Markets Authority (CMA)’s
Merger Guidelines (CMA 2021). The Japan Fair Trade Commission (JFTC) updated its
Merger Guidelines in 2019. The JFTC emphasized that it will scrutinize the significanceof data that the merging parties have when addressing the loss of potential competition.
Control of conglomerate mergers has been a controversial area of competition law on
both sides of the Atlantic. 6 Among those who are skeptical about competitive harm from
conglomerate mergers, Robert Bork was the most critical and writes, “Basic analysis
shows that there is no threat to competition in any conglomerate merger...” 7 Phillip
Areeda and Donald Turner, who were among the most thought-out writers of antitrust,
were also critical of regulating tying in the context of merger control, insisting that “The
only plausible reason for worrying about mergers creating a tying potential is thedifficulty of detecting and controlling the more ‘subtle’ inducements by which thepurchaser of one product also buys more of a second product than he otherwise would.”
and that “the conditions necessary for a substantial foreclosure through ‘subtle’ tying are
relatively rare; the possibility of its occurring could wisely be ignored in appraisingconglomerate mergers.” 8 Although those who endorse a more active role inconglomerate merger control can counteract these passivists, there seems to be a tricky
obstacle in activating conglomerate merger control. This obstacle is our generalperception that conglomerate mergers are rarely regulated. Such a proposition appears to
be an innocuous statement, just describing an objective fact. However, once we accept
this proposition, competition agencies or courts can unconsciously believe that theyshould cautiously regulate conglomerate mergers. If enforcers or courts adopt thisapproach, fewer conglomerate cases will be challenged. As we see fewer cases ofenforcement actions, the general proposition is reinforced, combined with another
Design Systems, Inc. (1997).
3 ACCC (2008, para. 5.47); JFTC (2019, VI.2(1)B); DOJ (2020, §4.b); CMA (2021, para.7.3).
4 European Commission (2008, para. 7); JFTC (2019, VI.2(2)); DOJ (2020, §1.); CMA (2021, paras. 5.1-5.24).
5 Other types of harm to competition include facilitating coordinated interaction by multi-market contact and softening
competition. For the law and economics of conglomerate mergers, see Church (2004, 2008).
6 For detail, see Church (2008).
7 Bork (1978) at 246.
8 Areeda & Turner (1980) at 206-207 & 213. See also Areeda & Hovenkamp (2016) at 203.

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proposition that conglomerate mergers rarely harm competition and become a selfperpetuating assumption. Such an assumption is difficult to revise, leading to status-quo
bias. If we want to change this mindset, competition agencies should actively challenge
conglomerate mergers 9 or propose a rule in court that conglomerate mergers presumably
harm competition in certain circumstances.
A noteworthy aspect of the Japanese Merger Guidelines is that concerns about
aggregate economic power across different lines of business have been in place since1980. Aggregate economic power, called "sogoteki jigyo noryoku" in Japanese legal
parlance, is enhanced by conglomerate mergers when the merged entity's buyer power,
technological competence, sales force, creditworthiness, brand power, or advertising
power is enhanced and makes competitors' competitive actions harder to be taken. For
example, the merged entity will utilize monopoly power to purchase or sell in one market
to advantage its position in another. The JFTC has examined whether a conglomeratemerger will enhance aggregate economic power in six merger cases, but remedies weresought to address this concern in only two of them, both of which are dated before 2000.
Although the 2019 update of the Guidelines replaced aggregate economic power theory
with bundling in conglomerate merger context, digital economy sheds new light on thistheory because aggregating personal data in different markets strengthens the merged
entity's competitive advantages, leading to digital market concentration. 10 As explained
below, the JFTC addressed this concern with respect to digital advertising market in
Google/Fitbit merger.
This study argues that conglomerate mergers involving consumer data and data
analytics will likely harm competition through personalized pricing. This new theory ofharm is uncommon in legal practice. We consider the Google/Fitbit merger as our
example of interest. Before discussing the details of this case, we provide a simple
nomenclature for non-horizontal mergers.
1.2. Vertical or conglomerate
Vertical and conglomerate mergers are often confused in practice. Indeed, it is often
difficult to decide whether the relevant merger is vertical or conglomerate with respect tospecific markets. As explained in 1.1., degradation of interoperability has been addressed
as either conglomerate or vertical, depending on jurisdiction. The CMA, while updating
its Merger Assessment Guidelines, made it clear that it adopts a wider concept of a verticalmerger: “The CMA may use the same framework in similar situations where the merged
910

For recent enforcement cases, see Witt (2022).
Stigler Committee (2019) at 37.

4

entity could use its presence in one market to directly harm the competitiveness of its
rivals in another, even if there is not a conventional supplier/customer relationship.” Theboundaries of the vertical and conglomerate are determined by how we define verticalmergers. If vertical mergers are narrowly defined as those between parties in a suppliercustomer relationship, the rest are conglomerate mergers, and, therefore, the sphere of theconglomerate is large, and vice versa. We adopt a narrow definition of vertical mergers
because it matches the legal definition of a relevant market in which buyers and sellers
meet to buy and sell specific products or services in a specific geographic area. We do notargue that our definition is better because legal categorization should not determinatively
change the ultimate competitive analysis. We intend to provide only one perspective,
which might alleviate the confusing aspects of the residual concept.
We propose to judge vertical or conglomerate this way:
(1) Specify two or more products (including services) of interest (e.g., products A andB).
(2) Identify direct customers for each product.
(3) Check whether the direct customers of each product are the same.
(a) If the direct customers of each product are different, and one product (e.g., A) is
necessary for the supply of the other product (B), it is a vertical merger.
(b) If the direct customers of each product are different and one product (e.g., A) is notnecessary for the supply of the other product (B), it is a conglomerate merger.
(c) If the direct customers of each product are the same, this is a conglomerate merger.
The above method is akin to the explanation that “the main difference between the two
types of mergers is that in the case of vertically related goods, it is the downstream firmthat combines the two products, whereas, in a complementary relationship, the integrationof the products is left to the consumers.” 11In the Google/Fitbit merger, the European Commission addressed the concern thatwrist-worn wearable suppliers competing with Fitbit would be foreclosed from access toGoogle Play after the merger (Case No COMP/M.9660). The Commission examined thisas input foreclosure theory. More specifically, the Commission examined the possibility
that Google treats competing wearable devices unfavorably in the app store by lowering
the rating of rivals’ companion apps required for competing wearable devices to connect
to smartphones or by delaying the approval of rivals’ updates of companion apps. The appstore is an upstream market, and if app developers who develop companion apps forcompeting wearable devices are treated unfavorably, competing wearable-device vendors
11

Bishop et al. (2005, para. 2.1).

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in the downstream market will be foreclosed. This vertical concern can also be seen as aconglomerate concern because the focus is on deteriorating the interoperability between
smartphones running on Android OS and competing wearables. In markets wherevertically integrated firms (e.g., Apple) and vertically separate firms (e.g., Google andFitbit) compete, focusing on the markets from the competitors’ perspectives might bejustified. That is, from Apple’s perspective, smartphones and wrist-worn wearable
devices are relevant markets. Indeed, the Commission examined a larger market ofsmartphones, noting “degradation strategy would have no impact on the wearable OEMs’sales prospect with iPhone users.”
1.3. The JFTC’s Google/Fitbit merger review
The JFTC released an outline of the Google/Fitbit merger review on January 14,
2021. 12 The JFTC approved the merger subject to Google’s remedies. Competitive
concerns in three relevant markets were examined: wrist-worn wearable devices, mobile
apps, and digital advertising businesses.
Figure 1 below shows the four theories of harm the JFTC examined:

Figure 1(1) Competition concerns in the market for wrist-worn wearable devices.
Fitbit was the third-largest supplier of wrist-worn wearable devices in Japan, with a
10 percent market share. Fitbit owns its proprietary wearable OS. Two larger suppliers ofwrist-worn wearable devices, with 55 percent and 20 percent market share, licensed

12

https://www.jftc.go.jp/en/pressreleases/yearly-2021/January/210114r.pdf

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wearable OS for free (Results of Review, p.19). 13 The JFTC examined whether Google
would refuse to supply its wearable OS, which is an indispensable input for wrist-wornwearable devices, to wrist-worn wearable suppliers competing with Fitbit, thereby
foreclosing them from the wrist-worn wearable devices market (input foreclosure, see (1)in Fig. 1). Noting that two larger suppliers license wearable OSs for free, the JFTC
concluded that even if Google refused to license its own Wear OS, competing wrist-wornwearable device suppliers would have other sources of wearable OSs; therefore, input
foreclosure is unlikely. The JFTC also examined whether Fitbit would refuse to purchasewearable OSs supplied by Google’s competitors (customer foreclosure). Because Fitbit
does not purchase a wearable OS, this concern is unlikely (Results of Review, pp.19-20).
The second concern was that Google would degrade the interoperability between the
Android OS for smartphones and competitors’ wrist-worn wearable devices after themerger, thereby foreclosing them from the wrist-worn wearable devices market (see (2)in Fig. 1) (Results of Review, p.21). Such degradation can be achieved by refusing accessto the Android API, which enables the Android OS to connect to and synchronize withwrist-worn wearable devices, or by offering poor technical support. On the other hand,
Google submitted a vertical arithmetic analysis that compares gains and losses fromforeclosure to support the view that Google has no incentive to degrade interoperability.
However, the JFTC criticized this analysis, noting that the critical switching threshold isarbitrarily small and that some worldwide data differ significantly from those of Japan(Results of Review, pp.22-23). The JFTC approved the remedy proposed by Google,
which makes Android APIs available without charge for access and on a
nondiscriminatory basis (Results of Review, p.23-24).
(2) Competition concerns in health-related app markets.
Both Google and Fitbit provide access to their health-related databases through the
Web API, and each of them also provides health-related apps for wrist-worn wearable
devices and smartphones. Competing health-related app providers can access the healthrelated databases owned by Google and Fitbit through the Web API. The JFTC wasconcerned that the merged entity would treat competing health-related app suppliers
unfavorably, thereby foreclosing them from the markets (see (3) in Fig.1) (Results ofReview, p.25). Such treatments could include refusing access to health-related databases
through the Web API or setting disadvantageous access charges. The JFTC approved theremedy proposed by Google, which makes access to the health-related database available
without charge for ten years.
13 Results of review on the Proposed Acquisition of Fitbit, Inc. by Google LLC.
https://www.jftc.go.jp/en/pressreleases/yearly-2021/January/210114r.pdf

7

(3) Competition concerns in the market for digital advertising businesses.
Google has a leading position in the digital advertising market. Google and Fitbit
provide access to their health-related databases through the Web API; however, they
currently do not provide digital ad businesses with the data. Since the health-related
database can be a useful input for digital advertising, the JFTC was concerned that after
the merger, Google could aggregate health-related data from the merging parties andwould thereby strengthen its position in the digital ad business market (Results of Review,p.27). Particularly, Google could combine its health-related data with those provided by
Fitbit and improve the precision of targeting, which would further enhance Google’s
position. In response, remedies were submitted that Google would not use certain healthrelated data for the digital ad business and that Google would maintain separation ofhealth-related data from other datasets. The JFTC accepted these remedies as being
appropriate for addressing competitive concerns (Results of Review, p.28).
Although the JFTC’s review seems reasonable, one might argue that competitive
concerns related to data aggregation could arise in health-related markets other than thedigital ad business market. Based on the theoretical analysis of Chen et al. (2022), we
explore another theory of competitive harm that could arise when a firm that collects data
merges with a firm that provides data-application services.

2. The business domain affected by the Google-Fitbit merger
The JFTC approved the merger remedy proposed by the constituent firm in the merger
review: it promises not to apply health data to digital advertisement businesses (p. 28).
This remedy does not seem to restrict data usage by the firm to other business domains,
as in the EU case. 14 However, Bourreau et al. (2020) express concern over the possibility
that the merged entity will exert monopoly power in the business domains of life scienceand healthcare in the near future. In addition, using a simple model, Chen et al. (2022)
theorize their concerns. 15 Given these facts, we briefly summarize Google's entry into
the health industry and then graphically explain Chen et al. (2022), who theoreticallyconsider the cross-market effects of data-driven mergers by considering the Google Fitbit
merger. Finally, using these summaries, Section 3 investigates the implications of Chenet al. (2022) on Japanese competition law.
2.1 Google’s entry into the health industry

14 The merger review in the EU prohibits the usage of health data to any online advertising (Case No. COMP/M.9600
Google/Fitbit [2020], para 966(c)).
15 Considering the concern, Regibeau (2021) explains the plausibility of the merger review in the case.

8

Alphabet, Google’s parent company, has invested a lot of money in life sciences andhealthcare. We introduce Google’s strong interest in entering these fields by borrowing
the Appendix in the preliminary version of Chen et al. (2022) (Chen et al., 2021).
Alphabet established two independent subsidiaries in these fields. Verily and Calico,established in 2015 and 2013, respectively, focus on life science research and health,welfare, and longevity. A corporate venture capital arm of Alphabet, GV (the former
Google Venture), invested 36% of its funds in health management and life sciences in
2014. 16 Although Google Health was reestablished in 2018 and closed again in 2021,
Google revealed that it still has a strong interest in health cases. 17
Given its strong interest in health, it is natural that Google acquired Fitbit for $2.1
billion. Mr. Sundar Pichai, the CEO of Alphabet and Google, says that “health care offers
the biggest potential over the next five to ten years for using artificial intelligence toimprove outcomes” (CNBC, 2020). 18
Project Nightingale, established in 2018 by Ascension, one of the largest private
healthcare system companies in the US, and Google Cloud, is a project to establish abridgehead to enter the healthcare market. Ascension and Google Cloud followed the
Health Insurance Portability and Accountability Act (HIPPA) and transferred the patient
data from Ascension to Google Cloud under the agreement that Google uses it only forservices offered to Ascension; however, this causes ethical issues regarding the mannerof treating patient data. 19 In 2019, Google signed a 10-year contract with Mayo Clinic, ageneral hospital in the US, regarding information management on genetic, medical, andfinancial records. 20 Although Google also proposed a storage service for a huge amountof health data to Cerner Corporation (currently Oracle Cerner), the matter ended with
Cerner choosing Amazon’s AWS. Moreover, according to the Wall Street Journal (2020),
Google signed alliance contracts with several major companies that managed devices for
hospitals and advanced healthcare services, and Google was able to see and analyze
information on more than 10 million patients. 21
Verily launched Project Baseline in 2017 to conduct comprehensive research on healthproblems worldwide. Along with the project, it produced its smartwatch, Study Watch, totrack participants’ health information. The project’s purpose is to “create Google Maps
for health care,” according to an interview with Jessica Mega, Verily’s chief medical
16

https://money.cnn.com/2014/12/16/smallbusiness/google-ventures-funding/index.html
https://www.cnbc.com/2021/10/21/google-is-all-in-on-health-care-again.html
18 https://www.cnbc.com/2020/01/22/google-ceo-eyes-major-opportunity-in-health-care-says-it-will-protectprivacy.html
19 Following the issues, Schnebel et al. (2020) suggest about ethical issues in the treatment of patient information.
20 https://www.wsj.com/articles/google-s-secret-project-nightingale-gathers-personal-health-data-on-millions-ofamericans-11573496790
21 https://www.wsj.com/articles/paging-dr-google-how-the-tech-giant-is-laying-claim-to-health-data-11578719700
17

9

officer, by CNBC (2017). 22 In addition, Verily has alliances with various healthcareorganizations (e.g., Atrius Health, Blue Cross Blue Shield Association, and Veterans
Affairs Palo Alto Health Care System) to conduct data-oriented prescriptions byanalyzing health information. It also started an alliance with John Hancock, a healthinsurance company, to suggest health insurance to customers and conduct information
technology-based illness management (e.g., diabetes). 23 Verily and Swiss Re Corporate
Solutions, an Swiss Re Group insurance department, performed similar challenges in
2020. In an interview with CNBC (2020), Verily’s President of Health Platforms said:“We’re hoping to be more personalized in the way we offer health solutions.” 24
While Google has been interested in the health industry, it bought Fitbit in 2021. The
competition authorities reviewed the Google Fitbit case in many countries and regions.
The authorities in the EU and Japan approved the merger with the remedy of therestriction on the usage of health data for advertisements and securing access to the web
API of Fitbit and the Android API. However, Google completed its merger process
without approval from the Australian Competition and Consumer Commission (ACCC)
and the Department of Justice (DOJ) in the US (the two authorities continued theirinvestigations at least until the end of 2021).
Such divergent treatments reflect competition agencies' experience in vertical andconglomerate merger reviews. The European Commission has led the modernization of
conglomerate merger review, which has been closely patterned by the JFTC. The UnitedStates is the most reluctant to condemn vertical and conglomerate mergers, as reflectedin the different approaches between the FTC and the DOJ. The ACCC was particularly
concerned with the effectiveness of behavioral remedies in "such a complex and dynamic
industry" (ACCC, 2020). 25
2.2 Data-driven mergers: A theory by Chen et al. (2022)
We introduce Chen et al. (2022), who propose a theoretical model to consider the
Google/Fitbit case. They argue for the impact of a data-driven cross-market merger on
profits and welfare.
The outline of the model is as follows. Market A, a digital health market, consists of
two firms, 𝐴𝐴1 and 𝐴𝐴2 , which supply horizontally differentiated products for this market.
Market B, a wearable market, consists of two firms, 𝐵𝐵1 and 𝐵𝐵2 , which supply
22

https://www.cnbc.com/2017/04/18/alphabet-verily-project-baseline-longitudinal-health-study.html
https://www.fiercehealthcare.com/payer/alphabet-s-verily-breaks-into-stop-loss-health-insurance-market-backedby-swiss-re
24 https://www.cnbc.com/2020/08/25/alphabet-verily-enters-stop-loss-insurance-market.html
25 See Vande Walle (2021) and Richter (2023) for discussion of appropriate remedies.
23

10

horizontally differentiated products for this market. If firms 𝐴𝐴1 and 𝐵𝐵1 merge, turning
to firm 𝐶𝐶, it can acquire customer information in market B and use it in market A. Eachconsumer in the market purchases a unit of products supplied in the two markets.
Consumer preferences in the two markets are perfectly correlated. Note that the perfectcorrelation assumption is not essential in their study (see Section 6 in Chen et al. (2022)).
We explain the structures of the two markets. Each market consists of a line segmentof length one (see Figure 2). The distribution of consumers in the line segment in eachmarket is uniform, with a density of 1. 26 Firms
𝐴𝐴1 and 𝐴𝐴2 are at the edges of the line segmentof market A, and firms 𝐵𝐵1 and 𝐵𝐵2 are at theedges of the line segment of market B. Eachconsumer purchases one unit of a product in eachmarket, and the intrinsic utility of each product issufficiently large. As a result, each consumerpurchases from one firm in each market.
Figure 2: Market structure

Consumers on the line segment recognize their location 𝑥𝑥 ∈ [0,1] as the degree oftaste mismatch for the products in the line segment. Concretely, consumers at point 𝑥𝑥 ∈[0,1] in market 𝑀𝑀 (𝑀𝑀 = 𝐴𝐴, 𝐵𝐵) consider the degrees of taste mismatches for firms 𝑀𝑀1
and 𝑀𝑀2 are respectively 𝑥𝑥 and 1 − 𝑥𝑥, and the utility levels for the products decreaseby degrees.
As explained earlier, if firms 𝐴𝐴1 and 𝐵𝐵1 merge, they become a merged firm 𝐶𝐶. The
merger allows firm 𝐶𝐶 to do the following. First, by using the data collected in market B,
firm 𝐶𝐶 can offer personalized products in market A to consumers who purchase fromfirm 𝐶𝐶 in market B. These personalized products eliminate those consumers’ taste
mismatches for firm 𝐶𝐶’s product and provide additional personalized benefits to those
consumers. They assume that these personalized benefits are sufficiently large such thatfirm 𝐴𝐴2 in market A cannot supply to consumers who purchase from firm 𝐶𝐶 in market
B in equilibrium. 27 Second, firm 𝐶𝐶 can supply personalized products in market A to its
customers purchasing from firm 𝐶𝐶 in market B under personalized prices. The
personalized prices discussed here are for personalized products, which depend on
consumer preferences, and we should distinguish those prices from those for a
26

Several papers on health markets also adopt the model formulation (e.g., Biglaiser and Ma, 2003; Olivella and VeraHernández, 2007; Katz, 2011).
27 Chapter 3 by Chen et al. (2022) investigates the relationship between personalized products with personalized prices
and competition in market A under the no-merger case by assuming that the benefits of personalized products and therange of firm 𝐴𝐴1 's customer base in market A are exogenous. We omit this argument here.

11

standardized product or service. We believe that consumers’ complaints about
personalized pricing (e.g., unfairness) are weaker if products and services are consumerspecific. Of course, it is natural to question the feasibility of offering personalized prices
due to consumers’ fairness concerns for pricing; for instance, Li and Jain (2016)
theoretically investigate price discrimination by incorporating consumers' fairness
concerns for the discriminatory pricing of a standardized product.
When firms 𝐴𝐴1 and 𝐵𝐵1 merge, the game proceeds as follows: In the first stage, firms
𝐶𝐶 and 𝐵𝐵2 compete in uniform price in market B. We explain it later. In the second stage,
based on the outcome in market B, firms 𝐶𝐶 and 𝐴𝐴2 compete in price in market A, andfirm 𝐶𝐶 can supply personalized products at personalized prices in market A to customers
who purchase from firm 𝐶𝐶 in market B.
Figure 3 shows the competition modes of the two segments in market A. The segment
lengths depend on the outcome in which firm 𝐶𝐶 supplies consumers in segment [0, 𝑥𝑥𝐵𝐵∗ ]in market B. In segment [0, 𝑥𝑥𝐵𝐵∗ ] in market A, firm 𝐶𝐶 can supply personalized products,
whose qualities are higher than in the nomerger case, under personalized pricing
to consumers on [0, 𝑥𝑥𝐵𝐵∗ ] . In segment[𝑥𝑥𝐵𝐵∗ , 1] in market A, firms 𝐶𝐶 and 𝐴𝐴2
supply consumers at uniform prices. As

firm 𝐴𝐴2 is closer to consumers in thesegment, it has a competitive advantage
over firm 𝐶𝐶.

Figure 3: The relationship between markets B and A

The resulting outcomes in the two segments of market A are as follows. In segment[0, 𝑥𝑥𝐵𝐵∗ ] in market A, firm 𝐶𝐶 monopolizes the segment owing to higher-quality
personalized products under personalized prices, which are useful for maintaining

consumer demand. In segment [𝑥𝑥𝐵𝐵∗ , 1] of market A, firm 𝐴𝐴2 has a competitive
advantage mentioned above.
Specifically, there are three types of outcomes in market A, which depend on theoutcome in market B. First, as shown in Figure 3, firm 𝐶𝐶 monopolizes [0, 𝑥𝑥𝐵𝐵∗ ], and firms
𝐶𝐶 and 𝐴𝐴2 compete in uniform pricing in segment [𝑥𝑥𝐵𝐵∗ , 1]. In the latter segment, owing
to its disadvantage, firm 𝐶𝐶 sets a low uniform price, inducing firm 𝐴𝐴2 to set a low
uniform price. The low price of firm 𝐴𝐴2 forces firm 𝐶𝐶 to set low personalized prices insegment [0, 𝑥𝑥𝐵𝐵∗ ] . The competitive disadvantage of firm 𝐶𝐶 worsens as 𝑥𝑥𝐵𝐵∗ increases,
leading to lower personalized prices in segment [0, 𝑥𝑥𝐵𝐵∗ ].
In the first type, an increase in 𝑥𝑥𝐵𝐵∗ has a trade-off between (i) expanding the segment
12

to which firm 𝐶𝐶 offers personalized prices and (ii) decreasing personalized prices at eachpoint. The former gain dominates the latter if and only if 𝑥𝑥𝐵𝐵∗ is smaller than a thresholdvalue. However, the outcome in segment [𝑥𝑥𝐵𝐵∗ , 1] changes when 𝑥𝑥𝐵𝐵∗ exceeds a thresholdvalue (which is different from the threshold value mentioned right before).
Second, as in Figure 4, firm 𝐴𝐴2 monopolizes segment [𝑥𝑥𝐵𝐵∗ , 1] when 𝑥𝑥𝐵𝐵∗ is higher
than the threshold value mentioned right before.
In this case, an increase in 𝑥𝑥𝐵𝐵∗ increases theprice of firm 𝐴𝐴2 because the distance between
firm 𝐴𝐴2 and consumers 𝑥𝑥𝐵𝐵∗ becomes smaller.
The price increase allows firm 𝐶𝐶 to offer
higher personalized prices to consumers insegment [0, 𝑥𝑥𝐵𝐵∗ ].

Figure 4: Monopolization in the segments (market A)

In the second type, an increase in 𝑥𝑥𝐵𝐵∗ generates two gains from expanding the segment

to which firm 𝐶𝐶 offers personalized prices and increases personalized prices at eachpoint, benefiting firm 𝐶𝐶.
Third, 𝑥𝑥𝐵𝐵∗ = 1 and firm 𝐶𝐶 offers personalized products with personalized pricing to
all consumers in market A. Firms 𝐴𝐴2 and 𝐵𝐵2 are excluded from the market.
In this case, firm 𝐶𝐶 can exploit the gains from personalized products throughpersonalized pricing, thereby deteriorating consumer welfare in market A.
Considering the above three outcomes in market A, we discuss the competition inmarket B. Firm 𝐶𝐶 competes with firm 𝐵𝐵2 and anticipates high profits in market A,
inducing firm 𝐶𝐶 to set a low-cost price in market B. There are three types of equilibriumoutcomes in market B that correspond to the three types in market A. The key factor
influencing the outcomes in market B is the (common) additional benefits of personalized
products. If the additional benefit of each personalized product is small, the outcome in
Figure 3 appears; if the benefit is large, the outcome in Figure 4 appears; and if the benefit
is large enough, monopolization by firm 𝐶𝐶 appears.
We explain pricing in market B for the three types of equilibrium outcomes. Under the
first-type outcome (Figure 3), the profitability of personalized pricing is not sufficiently
high, weakening firm 𝐶𝐶’s incentive to acquire demand in market B. Then, firm 𝐶𝐶 needs
to consider the trade-off of increasing 𝑥𝑥𝐵𝐵∗ mentioned above, and as a result, the realized
value of 𝑥𝑥𝐵𝐵∗ is small. Under the second type of outcome (Figure 4), an increase in 𝑥𝑥𝐵𝐵∗
from the threshold value has two gains from segment expansion and increments inpersonalized prices. Whether firm 𝐶𝐶 monopolizes the market depends on the gain frompersonalized prices in market A and the loss from below-cost pricing in market B. If the13

additional benefit of personalized products is sufficiently large, firm 𝐶𝐶 monopolizes themarket; otherwise, it does not.
From the discussion, we find that, as the additional benefit of personalized products
increases, monopolization is more likely to appear because of the higher profitability of
personalized pricing. Additionally, because firm 𝐶𝐶 exploits the gross surplus from theadditional benefit through personalized pricing, the merger reduces the total consumer
surplus. Contrary to monopolization, if the additional benefit of personalized products is
not large, leading to an outcome in Figure 3, then a low price for firm 𝐶𝐶 in market B andlow prices through uniform price competition in market A benefit consumers.
The implication of Chen et al. (2022) is that competition authority should be more
likely to carefully inspect a merger with consumption synergies under market
environments in which personalized pricing is acceptable, contrasting to the following
tendency of merger reviews. When a merger has social benefits from synergies, thecompetition authority tends to approve such a merger.
Chen et al. (2022) also consider the following three merger remedies.
First, Chen et al. (2022) discuss the following data-sharing remedy: Firm 𝐶𝐶 shares
firm 𝐶𝐶’s customer information acquired in market B with firm 𝐴𝐴2 , allowing firm 𝐴𝐴2 tooffer personalized prices in segment [0, 𝑥𝑥𝐵𝐵∗ ]. Data sharing captures Firm 𝐶𝐶’s opening of
API access to its database for firm 𝐴𝐴2 , making it possible to offer personalized prices.
Because firm 𝐶𝐶 is closer to segment [0, 𝑥𝑥𝐵𝐵∗ ] and has the advantage of offering
personalized products, firm 𝐴𝐴2 ’s ability to offer personalized prices creates competitive
pressure on firm 𝐶𝐶 , reducing the profitability of firm 𝐶𝐶 . The data-sharing remedy
dampens the incentive of firm 𝐶𝐶 to acquire customer information in market B, mitigatingcompetition in market B. Mitigation of competition benefits firm 𝐵𝐵2 but harms
consumers in market B. However, the outcome in Figure 3 is more likely to appear,
meaning that consumer welfare in market A improves. We must compare the loss inmarket B with the gain in market A. If the market share of firm 𝐶𝐶 is higher under nomerger remedy, the data-sharing remedy helps maintain price competition, as in Figure 3,
or changes the equilibrium outcome from Figure 4 to Figure 3, diminishing personalized
prices. Thus, a data-sharing remedy can improve consumer welfare.
Second, Chen et al. (2022) discuss the effect of banning below-cost pricing on welfare
in market B. The ban vanishes monopolization and mitigates competition in market B.
However, the outcome in Figure 4 is less likely to appear, thus benefitting consumers inmarket A. The ban has a positive effect on welfare through a vanishing monopolization.
Third, Chen et al. (2022) consider the prohibition of firm 𝐶𝐶’s personalized pricing. The
prohibition increases the profits of firm 𝐶𝐶’s rivals and consumer welfare in market A but
14

decreases consumer welfare in market B. The effect of the prohibition was similar to thatof the first remedy, and the effective situation was similar to that of the first remedy.
However, the effect of monopolization prevention on welfare is weaker than that of thefirst remedy. In the first remedy, firm 𝐴𝐴2 can offer personalized prices in segment[0, 𝑥𝑥𝐵𝐵∗ ] that are independent of the uniform price in segment [𝑥𝑥𝐵𝐵∗ , 1], inducing firm 𝐴𝐴2
to set the lowest feasible prices in segment [0, 𝑥𝑥𝐵𝐵∗ ], diminishing the incentive of firm C
to acquire consumers in market B. In the third remedy, firm 𝐴𝐴2 sets a uniform price inall segments of market A, allowing firm 𝐶𝐶 to offer personalized products with a slightly
high uniform price in segment [0, 𝑥𝑥𝐵𝐵∗ ] (of course, the high uniform price is lower thanpersonalized prices without remedies).
In addition to these three remedies, Chen et al. (2022) consider no merger approval. If
we use consumer welfare as the standard to evaluate mergers, we must consider rejecting
the merger when we expect the strong additional benefits of personalized products more
likely to result in monopolization.
We briefly refer to related studies. The results of Chen et al. (2022) contrast with thoseof Choe et al. (2018) and Garella et al. (2021), in which personalized pricing accelerates
competition in symmetric duopoly models but is similar to that in Chen et al. (2020), in
which firms can achieve perfect price discrimination when each firm has customer
information that does not mutually overlap with that of the rival firm. 28

3. Legal perspective
Chen et al. (2022) show two related points that have significant implications forcompetition policy. First, they show that in a B2C conglomerate merger context,
personalized pricing, a kind of price discrimination, could be a foreclosure device,depriving competitors of revenues and deterring entry of new firms. Second, they showthat although aggregating data and data analytics could enable the merged entity toprovide additional benefits to consumers, those benefits could be exploited by the merged
entity. The latter point means that merger-specific efficiencies could be used to fuelforeclosure: when the additional benefits are large, both markets are monopolized. Since
this theory is novel and has not been discussed in the literature on conglomerate mergers,
28

In Chen et al. (2020), not only monopolistic data held by each firm but also consumers' abilities to actively escapepersonalized prices are important factors in deriving the perfect price discrimination. Intuitively, such consumers’abilities seem to benefit consumers owing to escaping high personalized prices, improving consumer welfare. However,Chen et al. (2020) show the opposite result. When a firm offers a low uniform price to consumers who are notrecognized by it, its targeted customers respond to the low price, making profitable personalized prices for thosetargeted customers ineffective. When each firm anticipates the ineffectiveness of personalized pricing because of alower uniform price, it abandons offering such a uniform price to its untargeted consumers and focuses on its targetedcustomers by offering personalized prices that are indifferent to no purchase. As a result, each firm successfully exploits
consumer surplus through personalized pricing.

15

we first discuss the important assumptions of Chen et al. (2022) from a legal perspective
in Section 3.1. We then ask whether such a theory of competitive harm is recognizable incompetition laws (3.2). Section 3.3 discusses the policy implications and limitations ofChen et al. (2022) when applying theory in practice.
3.1 Data analytics and competition
In their model, there are two relevant markets: Product A (digital health market) and
Product B (wearable market). Consumer data are collected in market B, and utilizing thedata collected, suppliers of product A can provide individualized/personalized productsthat better match each consumer’s taste. Data analytics affect the merged entity’s conductin market A in three ways. First, by accessing the data collected in market B, the merged
entity C has a better knowledge of consumers’ tastes in market A compared to 𝐴𝐴2 . This
enables C to provide personalized products. Although C can charge a higher price due topersonalized offerings, the market price does not necessarily increase because 𝐴𝐴2 will
price aggressively. Second, they assume that consumers who buy both products from themerger entity can obtain additional benefits (consumption synergy). C, therefore, canincrease its price in market A. Thirdly, C can charge a different price to each consumer inmarket A based on data on consumers’ tastes.
The additional benefits consumers obtain when they purchase both products from C
correspond to the merger-specific efficiencies recognized in the merger review. Mergerspecific efficiencies must be those benefits to customers that would not be brought about
by other means, such as a licensing agreement. 29 Since Chen et al. (2022) assume that𝐴𝐴2 can also offer personalized products if it obtains consumer data from C in theextension of the main model (Data sharing, Section 5), personalized offerings are notrecognized as merger-specific, in contrast to the additional benefits.
3.2 Personalized pricing and competition law
As mentioned in the Introduction, competition laws generally prohibit conduct thatharms competition. Because conglomerate mergers do not restrain competition between
the merging parties (except in the case of potential competition), conglomerate mergers
are prohibited when the merger entity engages in certain conduct that restrainscompetition after the merger. 30 We must determine whether personalized pricing in Chen
29

European Commission (2008, para. 53); Dep't of Justice & FTC, Horizontal Merger Guidelines (2010, §10); JFTC
(2019, IV.2.(7)); CMA (2021, paras. 8.16-8.19).
30 Some jurisdictions might go further than this and prohibit price discrimination as a practice that facilitates theexercise of market power or as an abuse of a dominant market position. However, since the Japanese Antimonopoly
Law prohibits mergers that would significantly restrain competition in the market, we confine our analysis to the casein which price discrimination harms competition.

16

et al. (2022) restrains competition in the market. According to their analysis, the merging
entity’s personalized pricing reduces competitors’ profits in both markets A and B. Morespecifically, in two equilibria with the duopoly, the profits of competitors (𝐴𝐴2 and 𝐵𝐵2 )will decrease after the merger compared to those before the merger. In a monopoly
equilibrium, both markets are dominated by the merged entity. Therefore, competitors’
access to customers is foreclosed, and their profits are reduced, which has the same impact
on competitors as observed in other foreclosure theories of harm in conglomerate mergers.
Merged entity C does not sell below the cost in market A, but its competitor 𝐴𝐴2 faces
reduced profits even though it reduces its price after the merger, which increases the costsof 𝐴𝐴2 to act competitively. If competitors face fewer customers, they might increase theirprices to maintain their business scale. They may also reduce their investments ininnovation. These impacts on competitors may be called raising rivals’ costs, and because
they reduce competitive pressure on the merged entity, conduct with such impacts can besaid to restrain competition. Chen et al. (2022) note that, depending on the size of fixed
costs for entry, a new entry would be deterred because personalized pricing makes thosecompetitors, which otherwise would have been viable, harder to compete; such practiceafter the merger should be prohibited as a practice that would significantly restrain
competition. In market B, the merged entity prices below its cost in both equilibria. Thisis made possible by personalized pricing in market A. If personalized pricing in market A
is prohibited, below-cost pricing in market B will cease.
3.3 Implementing the theory in practice
If competition authorities accept the theory of Chen et al. (2022), how should they
analyze personalized pricing concerns in conglomerate mergers, and what should be
adequate remedies? In turn, we discuss these issues.
In Europe, the competitive effects of non-horizontal mergers have been analyzed byfocusing on the merged entity’s (i) ability, (ii) incentive, and (iii) impact/effect. 31 We
applied this approach to personalized pricing.
In “ability,” competition authorities would ask whether the merged entity could use
personalized pricing and whether competitors could take counter-strategies. Personalized
pricing is possible when the merged entity knows each consumer’s taste by analyzing thedata collected in market B, when it can personalize the products to each consumer basedon their taste, and when it can charge a personalized price to each consumer. These three
conditions are cumulative, and all must be satisfied. Each merging party must not have
all the necessary data analytics and personalization skills. It is sufficient that the merged
31

As to tying and bundling concerns, see European Commission (2008, paras. 99-118); CMA (2021, paras. 7.33-7.37).

17

entity will acquire these skills through the merger. Examining counter-strategies would
be similar, asking whether competitors in both markets can combine their skills to use
strategies that make the merged entity’s personalized pricing ineffective. Another point tonote with respect to ability is the merging parties’ market positions before the merger. A
typical scenario of anticompetitive conglomerate mergers is that a firm with market power
in one market will leverage its power in another market. However, personalized pricing
might be of concern with a lower degree of market position. In Chen et al. (2022), themarket share of 𝐵𝐵1 was 18/43 in value; thus, the competitor of the merging parties waslarger before the merger.
In “incentive,” competition authorities examine the gains and losses (benefits andcosts) of personalized pricing for the merged entity. Gains would include increased sales
from the enlarged customer base of both markets A and B. Losses would include lost sales
from customers in market A who dislike personalized pricing and switch away from C’s
product (𝐴𝐴1 ) to the product of 𝐴𝐴2 . In Chen et al. (2022), some consumers could buy 𝐵𝐵1
and 𝐴𝐴2 ; thus, lost sales are at least partially examined. Moreover, lost sales might belimited because the additional benefits belong to those consumers who buy both products
from the merged entity.
The “impact/effect” prong examines the overall competitive effect on the market.
Competition authorities examine whether the merged entity creates or strengthens market
power through foreclosure and whether merger-specific efficiencies counterbalance thenegative effects. We have already confirmed in Section 3.2 that personalized pricing after
the merger can reduce competitors’ profits and significantly restrain competition. One of
the most frequently cited efficiencies of conglomerate mergers is the Cournot effect:
compared to the situation in which two complementary products are supplied by different
firms, the merged entity would, considering that the price of one product influences thedemand of the other, reduce the aggregate price and supply more. 32 It is unclear whether
the Cournot effect is also observed when personalized pricing is possible; this is left for
future research. Personalized pricing could also increase overall output in the market, butbalancing these efficiencies would be difficult.
Regarding merger remedies, if the expected anticompetitive conduct after the merger
is personalized pricing, it is natural for competition authorities to prohibit personalized
pricing as a remedy. That said, the remedy should not be too broad to prevent competitive
price discrimination. Prohibiting overly detailed personalized pricing is sufficient.
Remedies prohibiting below-cost pricing are practically difficult because agreeing on therelevant cost benchmark and estimating the relevant costs take time in a limited merger
32

See European Commission (2008, para. 117) and DOJ (2020, §6).

18

control timetable. Chen et al. (2022) discuss data sharing as a merger remedy and showthat monopolization equilibrium is more often deterred by data sharing than by theprohibition of personalized pricing itself. Data sharing underpins competitors’ growth. It
may be wise to maintain data sharing in stock as an alternative remedy.
3.4 Industrial policy and competition policy
We briefly discuss the possible tension between competition policy/law and industrial
policy. In general, competition policy promotes competition and could limit innovation
activities, including cooperative R&D (Shapiro, 2002), although industrial policy seeks
to boost innovation in selected firms (Tirole, 2022). However, in Japan, the Ministry of
Economy, Trade, and Industry, which mainly deals in industrial policy, and the Japan Fair
Trade Commission, which deals in competition policy, have jointly developed a policy
for the digital economy, resulting in the Act on Improving Transparency and Fairness ofDigital Platforms (TFDPA). 33 The Act orders digital platform firms designated as"specified digital platform providers" to report their activities in order to maintain healthy
competition in the digital economy. 34 As per such an act, industrial strategies, which
intend to avoid monopolization ex-ante, are necessary, along with competition policy thatcan fix abuse of dominance ex-post. 35 That is, industrial strategies and competition policy
are complements (Bianchi and Labory, 2022). The ex-ante regulatory regime is similar to
the EU's Digital Markets Act (DMA).

4. Conclusion
This article discusses competitive concerns related to data aggregation and data
analytics in merger control. Based on the case of the Google/Fitbit merger, we showedthat personalized pricing after the conglomerate merger could be a powerful foreclosure
device, where the merged entity would absorb even merger-specific benefits. We
examined how competition agencies should apply this theory of harm in practice andargued that prohibiting personalized pricing or requiring data sharing would be thepreferred remedy.
Acknowledgments: We have benefited from many constructive comments from the
Editor and an anonymous referee. We acknowledge Masaki Kakimoto and Kenta Suzuki
for their valuable advice on JFTC’s review of the Google/Fitbit case. We gratefully
33

https://www.meti.go.jp/english/policy/mono_info_service/information_economy/digital_platforms/index.html
For instance, in the app store markets, App Store by Apple and Google Play Store by Google are designated as
specified digital platform providers. https://www.meti.go.jp/english/press/2022/1222_003.html
35 The terminology of industrial strategy follows that in Cowling (1982) and related articles (e.g., Bianchi and Labory,2022).
34

19

acknowledge financial support from the Japan Society for the Promotion of Science(JSPS), KAKENHI Grant Numbers JP19H01483, JP20H05631, JP20K01323,
JP21H00702, JP21K01452, and JP21K18430. Although Matsushima serves as a memberof the Competition Policy Research Center (CPRC) at the Japan Fair Trade Commission(JFTC), the views expressed in this paper are solely our own and should not be attributed
to the JFTC. The usual disclaimer applies.

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