Introduction

Model

Main results

WelfareExtensions

Conclusion

Softening Competition through
Unilateral Sharing of Customer Data
Chongwoo Choe (Monash)
Jiajia Cong (Fudan)
Chengsi Wang (Monash)

ISER, Osaka University, December 2022

C. Choe (Monash), J. Cong (Fudan), C. Wang (Monash)

Softening Competition through Unilateral Sharing of Customer DataIntroduction

Model

Main results

WelfareExtensions

Conclusion

Data is the new oil

C. Choe (Monash), J. Cong (Fudan), C. Wang (Monash)

Softening Competition through Unilateral Sharing of Customer DataIntroduction

Model

Main results

WelfareExtensions

Conclusion

Value of consumer data
1. Value of data for rmsData-enabled learning can lead to new and improved products, andimprovement of management practice.
More eective surplus extraction by price discrimination
Monetization through data-based services
Direct sales of data to third parties
2. The ip side
Privacy concerns: Privacy laws (GDPR, CCPA, etc) aim ataddressing this.
Potential adverse eects on competition

C. Choe (Monash), J. Cong (Fudan), C. Wang (Monash)

Softening Competition through Unilateral Sharing of Customer DataIntroduction

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Conclusion

Consumer data and competition
1. Data can harm competition in data-driven businesses.
Network eects and economies of scale and scope in data can leadto market tipping.
Data can be an entry barrier.
2. How about mandated data sharing?
Can dampen incentives for data collection, hence upfront
competition
Can create room for collusion
Can aggravate privacy concerns

C. Choe (Monash), J. Cong (Fudan), C. Wang (Monash)

Softening Competition through Unilateral Sharing of Customer DataIntroduction

Model

Main results

WelfareExtensions

Conclusion

Consumer data and competition
1. Data can harm competition in data-driven businesses.
Network eects and economies of scale and scope in data can leadto market tipping.
Data can be an entry barrier.
2. How about mandated data sharing?
Can dampen incentives for data collection, hence upfront
competition
Can create room for collusion
Can aggravate privacy concerns
3. Data can also intensify competition when competition is based on
price discrimination using ner levels of consumer data.

C. Choe (Monash), J. Cong (Fudan), C. Wang (Monash)

Softening Competition through Unilateral Sharing of Customer DataIntroduction

Model

Main results

WelfareExtensions

Conclusion

Consumer data and competition
1. Data can harm competition in data-driven businesses.
Network eects and economies of scale and scope in data can leadto market tipping.
Data can be an entry barrier.
2. How about mandated data sharing?
Can dampen incentives for data collection, hence upfront
competition
Can create room for collusion
Can aggravate privacy concerns
3. Data can also intensify competition when competition is based on
price discrimination using ner levels of consumer data.

C. Choe (Monash), J. Cong (Fudan), C. Wang (Monash)

Softening Competition through Unilateral Sharing of Customer DataIntroduction

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WelfareExtensions

Conclusion

Firms' incentives to share consumer data

1. Firms are generally averse to sharing consumer data if it can be used
for price discrimination.
2. Can a data-rich rm voluntarily share its consumer data with adata-poor competitor?
Yes, if it can charge for the data: data sharing can increase industry
prot, which the sharing rm can extract through the payment.
What if the sharing rm cannot charge for the data?
3. We show that unilateral data sharing, even without payment, canbenet both rms given the optimally chosen amount of shared data.

C. Choe (Monash), J. Cong (Fudan), C. Wang (Monash)

Softening Competition through Unilateral Sharing of Customer DataIntroduction

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Conclusion

Example: Amazon

Figure: Coupon targeting in Amazon.

C. Choe (Monash), J. Cong (Fudan), C. Wang (Monash)

Softening Competition through Unilateral Sharing of Customer DataIntroduction

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Example: Alibaba and JD.com

Chinese online platforms, Alibaba and JD.com, introduced A100 and Zu
Chongzhi programs, which provide individual level data to their
third-party sellers to improve their marketing strategies.
For example, Bestore Co Ltd, a Chinese snack food chain, links
customer data from its facial recognition technology with the data
shared by Alibaba, improving its targeting strategies.
At the same time, Alibaba and JD.com have invested heavily in theiroine stores to compete with these rms.

C. Choe (Monash), J. Cong (Fudan), C. Wang (Monash)

Softening Competition through Unilateral Sharing of Customer DataIntroduction

Model

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WelfareExtensions

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Research questions
1. Main research questions
Can unilateral sharing of consumer data benet both rms when thedata can be used for personalized pricing?
If yes, how to do it optimally?
Welfare implications of unilateral data sharing
2. Extensions
No search discrimination (making price discrimination less eective)
Data sharing for third-degree price discrimination
The implication for data as an entry barrier
Fee for sales of data

C. Choe (Monash), J. Cong (Fudan), C. Wang (Monash)

Softening Competition through Unilateral Sharing of Customer DataIntroduction

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Conclusion

Preview of results
1. There exists mutually benecial data sharing.
2. It is optimal for the data-rich rm to share data on consumers who are
more loyal to the data-poor competitor, but not share the data on thecompetitor's most loyal consumers.
3. The above data sharing softens competition for consumers whose data
is not shared, i.e., data sharing is an example of a fat-cat strategy.
4. Data sharing has two eects: surplus-extraction eect andquality-of-matching eect.
Surplus-extraction eect is always negative, hence consumers areworse o and rms are better o.
Quality-of-matching eect can be positive, which may increase total
welfare despite the lower consumer surplus.

C. Choe (Monash), J. Cong (Fudan), C. Wang (Monash)

Softening Competition through Unilateral Sharing of Customer DataIntroduction

Model

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Literature review
1. Consumer data sharing between rivals
Bilateral (mutual) data sharing: Chen et al. (2001), Shy andStenbacka (2013), Jentzsch et al. (2013), Choe et al. (2022)
Unilateral data sharing with transfer or data brokers: Chen et al.
(2001), Liu and Serfes (2006)
Data brokers: Montes et al. (2019), Bounie et al. (2021)
2. Competition based on personalized pricing
Static model: Thisse and Vives (1988), Rhodes and Zhou (2022)
Dynamic model: Zhang (2011), Fudenberg and Villas-Boas (2012),
Choe et al. (2018)

C. Choe (Monash), J. Cong (Fudan), C. Wang (Monash)

Softening Competition through Unilateral Sharing of Customer DataIntroduction

Model

Main results

WelfareExtensions

Conclusion

The model
1. Hotelling framework
A unit-length Hotelling line with rm 1 at x = 0 and rm 2 at
x = 1, cost of production normalized to zero
A unit mass of consumers distributed on the Hotelling line with CDF
F (x) and PDF f (x) satisfying the monotone hazard rate condition
A consumer's utility from buying from rm i is v − pi − di where pi
is the price paid, di is the distance traveled, and v ≥ 2.
2. Consumer data
Firm 1 is a data-rich: it is fully informed, i.e., knows eachconsumer's exact location.
Firm 2 is a data-poor: it has no information on any consumer's
location.
Note: Our results hold if rm 1 has data on [0, a] only where a islarger than a certain threshold and rm 2 has data on [b, 1] where b
is smaller than the threshold.
C. Choe (Monash), J. Cong (Fudan), C. Wang (Monash)

Softening Competition through Unilateral Sharing of Customer DataIntroduction

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WelfareExtensions

Conclusion

The model
1. Hotelling framework
A unit-length Hotelling line with rm 1 at x = 0 and rm 2 at
x = 1, cost of production normalized to zero
A unit mass of consumers distributed on the Hotelling line with CDF
F (x) and PDF f (x) satisfying the monotone hazard rate condition
A consumer's utility from buying from rm i is v − pi − di where pi
is the price paid, di is the distance traveled, and v ≥ 2.
2. Consumer data
Firm 1 is a data-rich: it is fully informed, i.e., knows eachconsumer's exact location.
Firm 2 is a data-poor: it has no information on any consumer's
location.
Note: Our results hold if rm 1 has data on [0, a] only where a islarger than a certain threshold and rm 2 has data on [b, 1] where b
is smaller than the threshold.
C. Choe (Monash), J. Cong (Fudan), C. Wang (Monash)

Softening Competition through Unilateral Sharing of Customer DataIntroduction

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Conclusion

Data sharing and pricing

1. Data sharing
Firm 1 can costlessly share a set S ⊆ [0, 1] of consumer data with
rm 2.
Data sharing does not involve any monetary transfer.
2. Pricing
Firm 1 charges personalized prices p1 (x) for any x ∈ [0, 1].

Firm 2 charges personalized prices p2 (x) for any x ∈ S, and uniform
price p2 for all x ∈/ S.

C. Choe (Monash), J. Cong (Fudan), C. Wang (Monash)

Softening Competition through Unilateral Sharing of Customer DataIntroduction

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Timing and equilibrium concept

1

Firm 1 makes a data sharing decision by choosing S.

2Firm 2 decides whether or not to accept the shared data.

3

Firm 2 chooses p2 .

4

Firm 1 chooses p1 (x) for all x ∈ [0, 1], and rm 2 chooses p2 (x) for
all x in S if it accepted data sharing in stage 2.

We solve for subgame perfect Nash equilibria.

C. Choe (Monash), J. Cong (Fudan), C. Wang (Monash)

Softening Competition through Unilateral Sharing of Customer DataIntroduction

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Benchmark without data sharing
Firm 2 sets uniform price p2 for all consumers.
Marginal consumer z is given by z + p1 (z) = 1 − z + p2 . But rm 1
can lower p1 (z) down to 0, so z = (1 + p2 )/2.
Firm 2 maximizes π2 = p2 (1 − F (z))

p2N :=

2
1
1, z N := +> 1/2.
Nh(z )2 h(z N )where h(z N ) = f (z N )/(1 − F (z N )) is the hazard rate at z N .

[z N , 1] is rm 2's customer base that rm 2 can serve even without
any data.
Firm 1 serves [0, z N ] by choosing p1N (x) = max{p2N + (1 − 2x), 0}
that makes all consumers on [0, z N ] indierent.

C. Choe (Monash), J. Cong (Fudan), C. Wang (Monash)

Softening Competition through Unilateral Sharing of Customer DataIntroduction

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Uniform example and the key intuition
Suppose F is a uniform distribution, F (x) = x .
Then h(x) = 1/(1 − x).
Thus, z N = 3/4, p2N = 1/2, and p1 (x) = p2N + (1 − 2x) = 3/2 − 2x
for all x ≤ 3/4 and p1 (x) = 0 for all x > 3/4.
R 3/4
π1N = 0 p1 (x)dx = 9/16, π2 = (1/2)(1 − 3/4) = 1/8.
Can rm 1 choose data sharing that makes both rms better o?

Observation 1: Data sharing can benet rm 2 by allowing it to use
personalized prices for consumers with shared data.
Observation 2: Firm 1's potential cost of data sharing is lost market
share.
Observation 3: Firm 1 can benet if data sharing induces rm 2 toincrease its uniform price. Recall p1 (x) = max{p2 + (1 − 2x), 0}.
So how?
C. Choe (Monash), J. Cong (Fudan), C. Wang (Monash)

Softening Competition through Unilateral Sharing of Customer DataIntroduction

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Uniform example and the key intuition
Suppose F is a uniform distribution, F (x) = x .
Then h(x) = 1/(1 − x).
Thus, z N = 3/4, p2N = 1/2, and p1 (x) = p2N + (1 − 2x) = 3/2 − 2x
for all x ≤ 3/4 and p1 (x) = 0 for all x > 3/4.
R 3/4
π1N = 0 p1 (x)dx = 9/16, π2 = (1/2)(1 − 3/4) = 1/8.
Can rm 1 choose data sharing that makes both rms better o?

Observation 1: Data sharing can benet rm 2 by allowing it to use
personalized prices for consumers with shared data.
Observation 2: Firm 1's potential cost of data sharing is lost market
share.
Observation 3: Firm 1 can benet if data sharing induces rm 2 toincrease its uniform price. Recall p1 (x) = max{p2 + (1 − 2x), 0}.
So how?
C. Choe (Monash), J. Cong (Fudan), C. Wang (Monash)

Softening Competition through Unilateral Sharing of Customer DataIntroduction

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Interval sharing

Lemma

Firm 1 weakly prefers sharing data on a single interval [a, b] to sharing
data on disjoint intervals.
Sketch of proof: Firm 1 prefers sharing data on [a, b] to sharing data on[a, b] ∪ [a′ , b ′ ]. In the latter, data sharing on one of the two intervals
becomes redundant or prot-reducing for rm 1. Likewise, rm 1 prefers
sharing data on n intervals to sharing data on n + 1 intervals. By
induction, data sharing on a single interval is preferred to any other data
sharing.

C. Choe (Monash), J. Cong (Fudan), C. Wang (Monash)

Softening Competition through Unilateral Sharing of Customer DataIntroduction

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Interval sharing

In addition, it must be that b > z N and a ≥ 1/2
Choosing b ≤ z N intensies competition on [a, b] without raising p2
above p2N .
Sharing data on [a, b] with a < 1/2 is dominated by sharing data on[1/2, b].

C. Choe (Monash), J. Cong (Fudan), C. Wang (Monash)

Softening Competition through Unilateral Sharing of Customer DataIntroduction

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Firm 2's choice of uniform price
1. Data sharing on [a, b] allows rm 2 to delink its pricing decisions.
2. Firm 2 chooses personalized prices p2 (x) = 2x − 1 on [a, b].
3. For the rest of the market, rm 2 chooses a uniform price.
4. It can either set high p2 = 2b − 1 to serve [b, 1], and earn prot
π21 = p2 (1 − F (b)).

5. Or, it can set low p2′ = 2z ′ − 1 to serve [z ′ , a] ∪ [b, 1] for some z ′ < a,and earn prot π22 = p2′ (1 − F (b) + F (a) − F (z ′ )).

C. Choe (Monash), J. Cong (Fudan), C. Wang (Monash)

Softening Competition through Unilateral Sharing of Customer DataIntroduction

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Firm 2's choice of uniform priceLemma

For data sharing on [a, b] to be protable for rm 1, it should necessarily
induce rm 2 to choose its uniform price p2 = 2b − 1 to serve [b, 1] only.
Sketch of proof:

Given a ≥ 1/2, rm 1 loses entire [a, b] to rm 2.
The only way to prot from sharing data is to be able to set higher
p1 (x) to consumers on [0, a].
This can only happen if p2 > p2N , which is true for p2 = 2b − 1.
For p2′ , the monotone hazard rate condition implies z ′ < z N , which
in turn implies p2′ < p2N .

C. Choe (Monash), J. Cong (Fudan), C. Wang (Monash)

Softening Competition through Unilateral Sharing of Customer DataIntroduction

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Mutually benecial data sharing

Mutually benecial data sharing satises the following conditions.
(IC) rm 2 chooses high p2 = 2b − 1: π21 (b) ≥ π22 (a, b)(IR) rm 2 is better o by accepting the data:Rb
π2 (a, b) = a (2x − 1)dF (x) + π21 (b) ≥ π2N
Proposition

For any distribution F that satises the monotone hazard rate condition,
there exists b′ ∈ (z N , 1) such that sharing data on [z N , b′ ] makes bothrms better o compared to the benchmark without data sharing.

C. Choe (Monash), J. Cong (Fudan), C. Wang (Monash)

Softening Competition through Unilateral Sharing of Customer DataIntroduction

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Mutually benecial data sharing: intuition

Sharing data on [z N , b ′ ] does not cost rm 1 any market sharebecause it is a subset of rm 2's customer base.
Firm 1 keeps data on consumers who have high loyalty to rm 2,
i.e., [b, 1]. This softens competition as rm 2 chooses a highuniform price for them.
This allows rm 1 to raise its own personalized prices.
Firm 1 benets from data sharing through higher personalized prices
but at no cost of reduced market share.
Firm 2 also benets from such data sharing because it serves thesame set of consumers but at higher prices.

C. Choe (Monash), J. Cong (Fudan), C. Wang (Monash)

Softening Competition through Unilateral Sharing of Customer DataIntroduction

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Optimal data sharing

1. The previous data-sharing strategy [z N , b ′ ], although mutuallybenecial, may or may not be rm 1's optimal data-sharing strategy.
2. Firm 1's optimal data sharing problem solves
Z amax π1 (a, b) =(p2 + (1 − 2x))dF (x)
(a,b)

0

s.t. (IC) and (IR)C. Choe (Monash), J. Cong (Fudan), C. Wang (Monash)

Softening Competition through Unilateral Sharing of Customer DataIntroduction

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Optimal data sharing with x ∼ U[0, 1]
Proposition

If x ∼ U[0, 1], then [a∗ , b∗ ] ≈ [0.71, 0.97].
Firm 1 serves consumers on [0, a∗ ] with personalized pricep1∗ (x) = 2b ∗ − 2x and earns prot π1∗ ≈ 0.87 > 9/16 = π1N .
Firm 2 serves consumers on [a∗ , b∗ ] with personalized pricep2∗ (x) = 2x − 1, consumers on [b ∗ , 1] with uniform pricep2∗ = 2b ∗ − 1, and earns prot π2∗ ≈ 0.21 > 1/8 = π2N .
1. Recall z N = 3/4 and p2N = 1/2. Note that a∗ < z N !
2. The key is how to satisfy rm 2's (IC).
3. If F is left-skewed around z N > 1/2, i.e., a fat right tail, thenchoosing a > z N and large b can satisfy (IC).
4. If F is right-skewed around z N (including the symmetric case sincez N > 1/2), then choosing a < z N and small b can satisfy (IC).
C. Choe (Monash), J. Cong (Fudan), C. Wang (Monash)

Softening Competition through Unilateral Sharing of Customer DataIntroduction

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Optimal data sharing: numerical results for x ∼ Beta(α, β)

PDF(α, β)zN[a∗ , b ∗ ]CS ∗ -CS N

TS ∗ -TS N

unimodalU-shapeddecreasing
increasing
uniform(2, 4)(0.9, 0.9)
(0.9, 2)(5, 1)(1, 1)

0.61
0.76
0.67
0.81
0.75

[0.50, 0.98][0.72, 0.97][0.50, 0.99][0.83, 0.96][0.71, 0.97]







+
+
+

+

All satisfy π1∗ > π1N and π2∗ > π2N . Except for the case with increasing
density, we have a∗ < z N .

C. Choe (Monash), J. Cong (Fudan), C. Wang (Monash)

Softening Competition through Unilateral Sharing of Customer DataIntroduction

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Optimal data sharing: numerical results for x ∼ Beta(α, β)
=1
0.95

b*

0.90
0.85

a*

0.80

zN

0.75
0.70

1.0

1.5

2.0

2.5

3.0

3.5

4.0

1. For all α = β , i.e., F is symmetric around 1/2, we have a∗ < z N .
2. F becomes more left-skewed as α increases, holding β xed. Thus, a∗monotonically increases in α, holding β xed.
C. Choe (Monash), J. Cong (Fudan), C. Wang (Monash)

Softening Competition through Unilateral Sharing of Customer DataIntroduction

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Consumer surplus
Proposition

For any distribution F that satises the monotone hazard rate condition,
data sharing on [a∗ , b∗ ] decreases consumer surplus unambiguously.
1. Consumers who do not switch rms are all worse o because they pay
higher prices after data sharing (negative surplus extraction eect).
2. For consumers who switch rms,
If z N < a∗ , all consumers on [z N , a∗ ] are worse o (negative
quality-of-matching eect).
If a∗ < z N , all consumers on [a∗ , z N ] are better o (positive
quality-of-matching eect). But the gain is oset by the loss on
non-switching consumers, hence total consumer surplus is lower.

C. Choe (Monash), J. Cong (Fudan), C. Wang (Monash)

Softening Competition through Unilateral Sharing of Customer DataIntroduction

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Total surplus

1. Because the market is fully covered (due to v ≥ 2), total surplus canbe proxied by the average distance travelled by a consumer, which isminimized when the marginal consumer is at 1/2.
2. Since z N > 1/2, total surplus increases if and only if a∗ < z N .
In the example with beta distributions, total surplus increases in allcases except for the case with increasing density.

C. Choe (Monash), J. Cong (Fudan), C. Wang (Monash)

Softening Competition through Unilateral Sharing of Customer DataIntroduction

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No search discrimination

1. No search discrimination: rm 2 cannot prevent a consumer who isoered its personalized price from choosing its uniform price.
2. Without search discrimination, (IC) is automatically satised.
Consumer x ∈ [a, b] chooses min{p2 (x), p2 }.
Firm 2 never wants to serve consumers on [z ′ , a] with p2 = 2z ′ − 1because, then, all consumers on [a, b] will choose p2 .
Firm 2 sets p2 (x) = 2x − 1 to serve all x ∈ [a, b] and p2 = 2b − 1 toserve all x ∈ [b, 1].
3. Because rm 1 benets from high p2 , it sets b as high as possible
while choosing a to make (IR) binding.

C. Choe (Monash), J. Cong (Fudan), C. Wang (Monash)

Softening Competition through Unilateral Sharing of Customer DataIntroduction

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No search discrimination
Proposition

Suppose rm 2 cannot engage in search discrimination.
Firm 1's optimal data sharing is given by [â, 1] where â solves
R1(2x − 1)dF (x) = π2N , and â > max{z N , a∗ }.
âFirm 1 serves consumers on [0, â] with personalized pricesp̂1 (x) = p̂2 + (1 − 2x) ≥ 2 − 2x and earns prot strictly higher thanthe case with search discrimination, where p̂2 ≥ 1 is rm 2's(o-the-path) uniform price.
Firm 2 serves consumers on [â, 1] with personalized pricesp̂2 (x) = 2x − 1, and earns the same prot as in the benchmark
without data sharing.
Both consumer surplus and total surplus are lower compared to thecase without data sharing, as well as the case with data sharing andsearch discrimination.
C. Choe (Monash), J. Cong (Fudan), C. Wang (Monash)

Softening Competition through Unilateral Sharing of Customer DataIntroduction

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Third-degree price discrimination
1. Firm 2 may not have capabilities such as data analytics necessary toprocess the shared data for personalized pricing.
2. It instead exercises third-degree price discrimination (3DPD): a
uniform price p2l for [a, b], and another uniform price p2h for the rest.
3. Compared to the case where data is used for personalized pricing, if(IR) holds under [a∗ , b ∗ ],
rm 1's optimal data sharing does not change;rm 1's prot under optimal data sharing does not change but rm
2's prot decreases (3DPD is a less eective tool for rm 2 toextract surplus);
total surplus does not change but consumer surplus increases.

C. Choe (Monash), J. Cong (Fudan), C. Wang (Monash)

Softening Competition through Unilateral Sharing of Customer DataIntroduction

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Data as an entry barrier
1. Customer data is often an important input in digital markets and,
therefore, can act as a barrier to entry. Assume uniform F .
Firm 1 is an incumbent and rm 2 needs to incur E to enter.
If rm 1 does not have data, each rm makes a post-entry prot 1/2.
If rm 1 has data but does not share, rm 2 makes a post-entry
prot 1/8.
Then, does data works as an entry barrier when E ∈ [1/8, 1/2]?
2. The above argument ignores the possibility of post-entry data sharing.
Firm 2's post-entry prot is 1/8 without data sharing and 0.21 with
optimal data sharing.
Firm 1 can then deter entry by committing not to share data whenE ∈ [1/8, 0.21], although such a commitment is not credible.
The possibility of data sharing mitigates the role of data as an entry
barrier.
C. Choe (Monash), J. Cong (Fudan), C. Wang (Monash)

Softening Competition through Unilateral Sharing of Customer DataIntroduction

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Conclusion

Data as an entry barrier
1. Customer data is often an important input in digital markets and,
therefore, can act as a barrier to entry. Assume uniform F .
Firm 1 is an incumbent and rm 2 needs to incur E to enter.
If rm 1 does not have data, each rm makes a post-entry prot 1/2.
If rm 1 has data but does not share, rm 2 makes a post-entry
prot 1/8.
Then, does data works as an entry barrier when E ∈ [1/8, 1/2]?
2. The above argument ignores the possibility of post-entry data sharing.
Firm 2's post-entry prot is 1/8 without data sharing and 0.21 with
optimal data sharing.
Firm 1 can then deter entry by committing not to share data whenE ∈ [1/8, 0.21], although such a commitment is not credible.
The possibility of data sharing mitigates the role of data as an entry
barrier.
C. Choe (Monash), J. Cong (Fudan), C. Wang (Monash)

Softening Competition through Unilateral Sharing of Customer DataIntroduction

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Data as an entry barrier

Proposition

Suppose rm 1 makes a data sharing decision before rm 2 makes anentry decision, and rm 2's entry cost is E .
If E < 1/8, then rm 1 shares data on [0.71, 0.97] and rm 2 enters.
If E ∈ (1/8, 0.21], then rm 1 commits not to share customer data,
which deters rm 2's entry; if instead rm 2 makes an entry decisionrst, then rm 2 enters and rm 1 shares data on [0.71, 0.97].
If E > 0.21, then rm 2 does not enter the market regardless of rm
1's data sharing decision.

C. Choe (Monash), J. Cong (Fudan), C. Wang (Monash)

Softening Competition through Unilateral Sharing of Customer DataIntroduction

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Conclusion

Fee for sales
1. Many hybrid platforms (Amazon, Alibaba, etc) sell rst-party goods indirect competition with third-party sellers on their platforms.
2. Suppose rm 1 charges rm 2 a xed per-unit sales fee k (proportional
fee is harder to analyze).
3. Firm 1 can serve consumer x for prot p1 (x) or concede consumer x
to rm 2 and earn k instead.
4. For consumers more loyal to rm 2, rm 1 prefers earning k instead ofchoosing zero personalized price.
5. The sales fee softens competition.
Firm 2 shifts k entirely onto its customers by raising its prices.
Firm 1 can raise its personalized prices by k .
Firm 1 collects k from each consumer, either through higher
personalized prices or through k collected from rm 2.
C. Choe (Monash), J. Cong (Fudan), C. Wang (Monash)

Softening Competition through Unilateral Sharing of Customer DataIntroduction

Model

Main results

WelfareExtensions

Conclusion

Fee for sales

Proposition

Suppose rm 1 charges rm 2 a per-unit fee for sales k ≥ 0.
In the equilibrium with or without data sharing, each rm's market
share and rm 2's prot are the same as those without the sales fee,but all prices and rm 1's prot increase by k .
Firm 1's optimal data sharing is the same with or without the sales
fee.

C. Choe (Monash), J. Cong (Fudan), C. Wang (Monash)

Softening Competition through Unilateral Sharing of Customer DataIntroduction

Model

Main results

WelfareExtensions

Conclusion

Additional discussions
1. Data sharing with side payment
Suppose rm 1 can charge Φ to rm 2 for data sharing.
Firm 1 can choose [a, b] to maximize industry prot, and set Φ tomake rm 2's (IR) binding.
Firm 1 shares more data and earns a larger prot.
2. When rm 1 cannot price discriminate
Firm 1's benet from data sharing hinges on rm 2's ability to pricediscriminate and increase its uniform price.
It does not depend on rm 1's ability to price discriminate. Our
results continue to hold in this case.

C. Choe (Monash), J. Cong (Fudan), C. Wang (Monash)

Softening Competition through Unilateral Sharing of Customer DataIntroduction

Model

Main results

WelfareExtensions

Conclusion

Additional discussions
1. Data sharing with side payment
Suppose rm 1 can charge Φ to rm 2 for data sharing.
Firm 1 can choose [a, b] to maximize industry prot, and set Φ tomake rm 2's (IR) binding.
Firm 1 shares more data and earns a larger prot.
2. When rm 1 cannot price discriminate
Firm 1's benet from data sharing hinges on rm 2's ability to pricediscriminate and increase its uniform price.
It does not depend on rm 1's ability to price discriminate. Our
results continue to hold in this case.
3. Partially covered markets
Suppose v < z N so that [v , z N ] is not served without data sharing.
The segment [v , z N ] separates the two rms, making each rm a
local monopoly, and prices are no longer strategic complements.
There does not exist mutually benecial data sharing, although data
sharing can benet rm 2 and increase total surplus.
C. Choe (Monash), J. Cong (Fudan), C. Wang (Monash)

Softening Competition through Unilateral Sharing of Customer DataIntroduction

Model

Main results

WelfareExtensions

Conclusion

Additional discussions
1. Data sharing with side payment
Suppose rm 1 can charge Φ to rm 2 for data sharing.
Firm 1 can choose [a, b] to maximize industry prot, and set Φ tomake rm 2's (IR) binding.
Firm 1 shares more data and earns a larger prot.
2. When rm 1 cannot price discriminate
Firm 1's benet from data sharing hinges on rm 2's ability to pricediscriminate and increase its uniform price.
It does not depend on rm 1's ability to price discriminate. Our
results continue to hold in this case.
3. Partially covered markets
Suppose v < z N so that [v , z N ] is not served without data sharing.
The segment [v , z N ] separates the two rms, making each rm a
local monopoly, and prices are no longer strategic complements.
There does not exist mutually benecial data sharing, although data
sharing can benet rm 2 and increase total surplus.
C. Choe (Monash), J. Cong (Fudan), C. Wang (Monash)

Softening Competition through Unilateral Sharing of Customer DataIntroduction

Model

Main results

WelfareExtensions

Conclusion

Conclusion
1. A data-rich rm can soften competition by strategically choosing theamount of data to share with its data-poor competitor.
2. Share data on consumers who are more loyal to the competitor, but
withhold the data on the competitor's most loyal consumers. (Release
the hostage except the most important one).
3. Such data sharing, while reducing consumer surplus, can increase total
surplus if the quality-of-matching eect is signicant. So, there is no
prima facie case against such data sharing.
4. Future research:More general use of data including that for product improvement
General platform fee as an additional revenue source
Platforms' data collection from third-party sellers
Consumers' privacy choice and opt-in decisions

C. Choe (Monash), J. Cong (Fudan), C. Wang (Monash)

Softening Competition through Unilateral Sharing of Customer Data