This document provides an overview of the debate around "killer acquisitions" in the digital age. It outlines three hypotheses regarding killer acquisitions: 1) the target start-up may not have survived without acquisition, 2) the start-up may not have developed into a substantial competitor, and 3) a corporate investor would likely want the start-up to be complementary rather than competitive. The document argues the killer acquisition conjecture requires these hypotheses to be untrue. It provides context from literature and proposes examining evidence regarding target survivability, emergence as a competitor, and post-acquisition complementarity to evaluate merger cases.

1. pg. 1
Killer Acquisition Theory in the Digital
Age
Max Berre1
and Nicolas Petit2
ABSTRACT
This paper seeks to contribute to the growing literature on killer acquisitions and to the debate
contextualizing the emergence of the Big-Data industry, in order to enrich and inform the debate,
proposing threshold ideas for purposes of abuse of dominance and merger control. To that end, it
takes a different approach, deconstructing the killer acquisition narrative. Because killer
acquisitions are defensive in nature, serving to protect the market-share of incumbent firms.
Overall, the debate can be approached via the examination of the relative likelihoods of competing
acquisition objectives, effects, and contextual realities. Testing these may yield viable examination
tools which could be put to use in real-world policy, advisory, or litigation contexts. The killer
acquisition narrative is based on several conjectures that must be critically examined and
rigorously tested prior to undertaking policy reform. This paper’s contribution is to provide a
framework for said critical examination.
Keywords: FAANG, Killer Acquisition, CVC, Start-up, Merger, Big-Data, Digital Industry
1
Audencia Business School, Nantes, France and Université de Lyon, iaelyon, Magellan, Lyon, France mberre@audencia.com
2
European University Institute, Florence, Italy, and Brussels School of Competition, Brussels, Belgium.

2. pg. 2
Table of Contents
1: Introduction and Literature Review..........................................................................................................4
Key Literature...........................................................................................................................................5
2. Killer Acquisitions....................................................................................................................................6
Killer Acquisitions: Conjecture and Hypotheses......................................................................................6
Hypothesis 1: Start-up Survivability.....................................................................................................7
Hypothesis 2: Substantial Horizontal Competitor.................................................................................7
Hypothesis 3: Control and Complementarity........................................................................................7
3. Why Question the Killer Acquisition Conjecture? ...................................................................................8
Division of Labor in the Digital Marketplace...........................................................................................8
Logical reasoning underlines initial inconsistencies in conjecture...........................................................9
Survival to Maturity and Viable Horizontal Competitor Likelihood of Start-ups ................................9
Mergers Attract Start-ups......................................................................................................................9
FAANGS Grow and Diversify via Mergers..........................................................................................9
Most Acquisitions are Not Killer Mergers..........................................................................................10
4. Analysis ..................................................................................................................................................10
Approaching Start-up Survival: Is Start-up Survival Likelihood Influenced by Investment?................10
Testing and Applying H1: Is H1 More True than Untrue? .................................................................12
Approaching the Emergence of a Substantial Horizontal Competitor....................................................14
Testing and Applying H2: Is H2 More Likely than Unlikely? ...........................................................15
Approaching Internal Control and Complementarity .............................................................................16
Testing and Applying H3: Is H3 More True than Untrue? .................................................................18
Evidence to be Examined........................................................................................................................18
H1: Target’s Survivability Likelihood................................................................................................18
H2: Emergence of a Substantial Horizontal Competitor Likelihood ..................................................19
H3: Investor Control and Complementarity........................................................................................19
5. Cases: Google and Facebook Acquisitions..............................................................................................20
Google/Waze Merger .............................................................................................................................20
Anecdotal Media Coverage of Acquisition..........................................................................................20
H1: Had Waze Achieved Survivability? ...............................................................................................21
H2: Was Waze Likely to Develop into a Substantial Horizontal Competitor? ....................................21
H3: To What Degree is Post-Merger Waze Complementary with the Acquiror?...............................22
Facebook/Instagram Merger ..................................................................................................................22

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Anecdotal Media Coverage of Acquisition..........................................................................................23
H1: Had Instagram Achieved Survivability? ........................................................................................24
H2: Was Instagram Likely to Develop into a Horizontal Competitor? ................................................24
H3: To What Degree is Post-Merger Instagram Complementary with the Acquiror?........................24
6. Discussion and Conclusion.....................................................................................................................25
The Killer Acquisition Conjecture Revisited..........................................................................................25
Tests and Likelihood Thresholds............................................................................................................25
Possibilities for Future Research.............................................................................................................26
7. Bibliography ...........................................................................................................................................27

4. pg. 4
1: Introduction and Literature Review
The 21st
-century emergence of the fourth-industrial-revolution has given rise to new technological
and economic realities. The Big-Data and Internet of Things (IoT) industries in the digital
marketplace has given rise to heated and lively debate concerning market-structure and
competition-policy ramifications going forward as the 21st
century develops.
Because traditional measures and dynamics are fundamentally challenged by both the technology
and the associated economic dynamics of 21st
century digital markets, exploration of the market-
structure measures and dynamics of industries related to the fourth-industrial-revolution is
increasingly necessary as new market-realities evolve.
The past decade has seen an increase in articles discussing predatory M&A by large digital firms
like Google, Apple, Amazon and Microsoft. Going forward, it is likely that the digital marketplace
will feature large digital firms acquiring high-tech start-ups as they expand and diversify. Indeed,
the rise of the Big-Data and IoT industries has seen substantial cross-sector concentration in the
hands of the FAANG firms. Among the concerns that of competitive foreclosure by means of killer
acquisition of potential future competitors, whereby promising start-ups are acquired and
subsequently discontinued by dominant Big-Data firms as they develop. The process is described
in Gautier and Lamesch (2020).
Alternatively, the rise of the entrepreneurial start-up ecosystem surrounding the digital, Big-Data
and IoT industries can be seen and contextualized as an organically-arising ecosystem in which
start-ups intentionally feed into the venture-capital space, directly feeding the growth and
increasing concentration of the Big-Data industry, thereby organically giving rise to the so-called
FAANGs.
Mechanically, the expansion and concentration of FAANGs in the digital marketplace proceeds
via their entry into and subsequent expansion of the digital start-up ecosystem via use of corporate
venture capital (CVC) aimed at the acquisition of start-ups in related industries.
FAANGs are multi-sided platforms which create value for various user groups, giving rise to a
dynamic ecosystem featuring entrepreneurs in the various user-groups. By this process, the
FAANG platforms grow and diversify, while entrepreneurs and start-ups are attracted to the
ecosystem, in a context which bares resemblance to a digital, 21st
-century iteration of Porter’s
Diamond, as outlined in Porter (1990).
In principle, this means that there are several segments of operation in which FAANGs and other
Big-Data firms are active, and that Big-Data firms can grow by pursuing a strategy of synergy-
focused complementary and conglomerate mergers.
Alternately, it is also alleged that large established Big-Data firms engage in defensive acquisitions
of newly-entrant start-ups which carry the potential to develop into substantial future competitors.
Examples of literature that explore this are Gautier and Lamesch (2020) and Cunningham et al.
(2020).

5. pg. 5
What is called for in a practical sense, is an examination of the various ways in which start-up
acquisitions in the digital market-space can be examined, approached and weighed, for purposes
of ex-ante or export investigation of mergers, acquisitions, and abuse of dominance.
Key Literature
Gautier and Lamesch (2020) describes in detail the architecture and mechanical workings of a
FAANG firm with its relevant parts. This detailed explanation of the multi-sided markets in which
the FAANGs operate is a key contribution to understanding the sectoral context in which the killer
acquisitions debate is juxtaposed. FAANG structures are described as consisting of a core
platform, by which consumers, businesses, merchants, advertisers, and content editors interact
with each other. Moreover, Gautier and Lamesch (2020) describes each of these user-groups in
detail, cataloguing the extent to which the various FAANG platforms engage with the five user-
groups.
Additionally, Gautier and Lamesch (2020) explicitly describe the killer acquisition process, as
motivated by elimination of potential competitors. The process is described as one in which new
entrants are first acquired by FAANGS, and subsequently discontinued under its own brand name.
Gautier and Lamesch (2020) elaborate that while alternate reasons for post-acquisition
discontinuation exist, such as unsuccessful products and services, or acquisitions targeting
absorption of the entrant’s R&D, killer acquisition remains a viable explanation for the current
state of FAANG firms. Empirically, Gautier and Lamesch (2020) describe probability of
discontinuation decision as a function of age, user-group segment, and year of founding, indicating
that some FAANGs are protective of at least some of their user-groups.
Kamepalli et al. (2000) model the competitive marketplace dynamics of the digital and information
industries, as driven by incumbent firms, disruptive start-ups, and relative firm-level technological
quality. In particular, Kamepalli et al. (2000) model the disruptive potential of new entrants on the
basis of switching likelihood and network effects, driven by the entrant’s quality relative to the
incumbent, a concept which lends itself to the practical realities in a varied range of sectors and
industries, which may have divergent industry quality metrics.
Additionally, Kamepalli et al. (2000) sceptically examine the killer acquisition phenomenon,
claiming that the concept seems at odds with established economic thought, since it is unlikely that
acquisition at heft multiples would discourage entry.
Marx et al. (2014) explore the dynamic competition and cooperation relationship between
disruptive start-ups and established incumbent firms. This study contributes to the debate
surrounding the killer acquisition conjecture by outlining that start-up entrants with disruptive
technologies can be responded to by incumbents not only as competitors, but also in cooperative
terms. Marx et al. (2014) describe a dynamic strategy involving product market entry before
switching to a cooperative commercialization strategy. In principle, this provides a framework by
which potential reaction of market-incumbents can be understood. Using a sample of 579 firms,
concentrated in one technology-driven industry, Marx et al. (2014) found that roughly one-third
of entrants entered into cooperative technology commercialization relationships with incumbents.

6. pg. 6
The implications of Marx et al. (2014)’s contribution is that even considering very specific types
of entrant-incumbent cooperation, the narrative concerning market-entry into a technology-driven
competitive landscape is substantially challenged.
Damodaran (2009) describes and models both the valuation and the survival likelihood of start-
ups and growth companies, as well as the relationship between the two. On a conceptual level,
Damodaran (2009) suggests controlling valuation and discount rates for start-up failure likelihood,
using three approaches. These are the use of sectoral averages, use of probit functions, and use of
simulations involving specified probability distributions for revenues, margins and costs.
2. Killer Acquisitions
While Gautier and Lamesch (2020) outline that large Big-Data and digital industry incumbents
can have multiple motivations for start-up acquisition. First, dominant incumbents might be
interested in the products and services developed by the start-up. Second, the, dominant incumbent
might be interested in the start-up's assets and productive inputs (e.g., innovations, intellectual
property, human-resources, customer base, or other intangibles). Third, acquisition may be a way
of restricting competition and consolidating market-dominance, given that network effects serve
as an important source of firm-value in the digital economy.
At its most straightforward, killer acquisitions are described by Gautier and Lamesch (2020) as an
acquisition in which an incumbent acquires a target which develops a technology that can be used
to compete with its own products in the future and the acquisition kills the competitive threat.
Meanwhile, Cunningham et al. (2020) identify pharmaceutical-industry killer mergers in which
the acquiring-firm shuts down the target because it is directly competing with its own products or
R&D efforts.
In principle, killer acquisitions can lead to the absorption and subsequent discontinuation of
potentially competitive emergent start-ups, which can undermine welfare, via reduction of
consumer welfare, as well as reductions in both productive efficiency (efficient productive and
commercial practices) and dynamic efficiency (incentive for competitive innovation).
Killer Acquisitions: Conjecture and Hypotheses
According to Levitt (1922), while outcomes can be determined to be results of a given cause by
comparing with existing results of similar causes, natural cause can be determined by inspection
and comparison, and probable cause is determined by conjecture. Levitt (1922), describes that law
applies a “but for” conjecture, examining what, that is forbidden, has contributed to produce this
object or event, along the lines of "If A would not have come into being but for the existence of B,
then B is a cause of A. If A would not been hurt but for the act or omission of B, then B is a cause
of the hurt to A”.
Keeping this in mind, the killer acquisition conjecture contextualized in a “but for” structure, can
be stated as:

7. pg. 7
• If the acquisition-target start-up had not been acquired, it would have independently
developed into a horizontal competitor to the dominant incumbent.
Gautier and Lamesch (2000), describe that FAANG mergers are often characterized by the
discontinuation of the acquisition target’s operations under the target’s original brand name.
In principle, for the “but for” killer-acquisition conjecture to hold, several conditionalities would
need to hold true in any counterfactual scenario.
First, that scaling, development and survival-to-maturity of the target start-up would occur. Non-
survival probabilities for any given start-up are famously elevated vis-à-vis the surrounding
business environment. Damodaran (2009) makes clear that elevated discount-rates in the VC
industry are driven by both the perceived risk in the business and the likelihood that the start-up
will not survive.
Hypothesis 1: Start-up Survivability
With a small probability, the entrant start-up would survive to a sufficiently mature state such that
it may evolve into a high-impact horizontal competitor. Essentially, this is an iteration of the failing
firm argument, which Art. 90 of the Guidelines on the assessment of horizontal mergers under the
Council Regulation on the control of concentrations between undertakings describe as viable in
the TFEU 101(3) sense if three criteria are met. First, it would likely exit the market in the near
future. Second, there is no less anti-competitive alternative the start-up’s acquisition. Third, in the
absence of a merger, the assets of the start-up would exit the market. This leads to the hypothesis:
• H1: If the acquisition-target start-up had not been acquired, it may not have survived to
develop into a horizontal competitor to the dominant incumbent.
Hypothesis 2: Substantial Horizontal Competitor
Second, that the target start-up would ultimately develop into a horizontal competitor vis-à-vis the
would-be acquiror. Overall, there are numerous ways by which this could emerge. For starters, a
start-up may develop and mature into a viable horizontal competitor under its own direction and
resources, for example with the support of either a passive investor, such as return-oriented
independent or bank-related venture capitalists, or an IPO. Alternately, acquisition by a horizontal
competitor to the incumbent may lead the start-up into a horizontally-competitive relationship to
the incumbent. This leads to the hypothesis:
• H2: If the acquisition-target start-up had not been acquired, it may not have developed into
a substantial horizontal competitor to the dominant incumbent.
Hypothesis 3: Control and Complementarity
Third, that an acquiror would have insufficient control over the start-up in any counterfactual
scenario involving merger. In principle, if a corporate investor or CVC has control, the investor

8. pg. 8
has incentives towards pursuing the start-up’s development as a complement (rather than a
competitor) to the incumbent firm, or to the start-up’s operational absorption by the incumbent
firm. On the other hand, more passive investors, such as return-oriented independent or bank-
related venture capitalists as less likely to exert influence within the start-up directed at the start-
up’s relationship with the competitive market structure. This leads to the hypothesis:
• H3: If a corporate investor has control of an acquisition-target start-up, the investor may
opt for the start-up to develop into a complementary firm or a subsidiary of the incumbent,
rather than a horizontal competitor.
Theoretically, for the killer acquisition conjecture to hold, H1, H2, and H3 would each need to be
untrue. Empirically-speaking, H1, H2, and H3 would need to be more untrue than true. While in
principle the empirical validity of any of the hypotheses do not establish that any given merge, or
series of mergers is either socially-beneficial or welfare-maximizing in the microeconomic sense,
it would be indicative that the objective of the acquisition would be an objective other than to
eliminate the start-up as a potential competitor.
As a matter of context, Cunningham et al. (2020), a study that examines killer acquisitions in the
US pharmaceutical industry in terms of post-acquisition development likelihood, outlines that 5.3
% to 7.4 % of acquisitions in the study’s dataset classify as killer acquisitions.
3. Why Question the Killer Acquisition Conjecture?
Division of Labor in the Digital Marketplace
Abundant literature exists concerning competition and cooperation between large established firms
and smaller disruptive start-ups. This body of literature explicitly states that cooperation between
disruptive start-ups and established large firms creates substantial added value, as diversification
and outsourcing of R&D and innovation takes place within several high-tech industries.
For example, Marx et al. (2014) outlines the competition and cooperation dynamics of the
relationship between disruptive start-ups and incumbents. In principle, reasons for this innovation-
outsourcing may range from the need to diversify R&D and revenue streams, to the relative scaling
efficiencies.
Grey literature focusing on digital industries also points to competition and cooperation dynamics
between incumbents and disruptive start-ups. Examples of this include UBS (2016), as well as
MagnaCarta Communications (2017), which both examine the relationship between disruptive
fintech firms and established financial and banking-sector incumbents, finding that as fintech firms
emerge, relative advantages of financial-sector incumbents, who have extensive distribution
networks with considerable scope to fund new projects and fintech firms, who have structural
adaptability to react to changing market circumstances.

9. pg. 9
Logical reasoning underlines initial inconsistencies in conjecture
Survival to Maturity and Viable Horizontal Competitor Likelihood of Start-ups
Horizontally-positioned start-ups (i.e. start-ups in competition with or poised to be in competition
with the dominant incumbent), have access to fewer capabilities and operational resources. This
includes human resources such as engineers needed to undertake R&D, as well as infrastructure,
financial resources, and business relationships with suppliers and user-groups needed to expand
and diversify operations or adapt to changing market-circumstances.
Meanwhile, non-horizontally positioned start-ups might have unimpeded access to a more diverse
set of capabilities while also representing lower potential competitive challenge to the incumbent
FAANG, unless the start-up can diversify. In principle, this could occur either organically under
the start-ups own control, or with external backing. This external backing in turn could take the
form of either
Mergers Attract Start-ups
In principle, a market-economy, which is driven by profit-seeking entrepreneurs, tends to attract
entrepreneurs to sectors and industries in which pay-outs are the most dramatic. Kamepalli et al.
(2019) elaborates by pointing out that it is unlikely that the prospect of being acquired by FAANGs
at hefty multiples would discourage new entrepreneur entry.
Indeed, Berre and Le Pendeven (2020) point out that there were 45 unicorn companies (i.e., with
a valuation above $1 billion) in 2014, September 2016, there were 150. By January 2020, public
sources had tracked 558 unicorns with a combined valuation of $1.9 trillion. In a long-run sense,
the start-up market-place, among which FAANGS and other Big-Data firms mark their
acquisitions shows signs of acceleration rather than of slowing down.
In terms of EU regulatory language, the expectation is that entry is likely when sufficiently
profitable. The Guidelines on the assessment of horizontal mergers under the Council Regulation
on the control of concentrations between undertakings explicitly state that:
- For entry to be likely, it must be sufficiently profitable taking into account the price effects
of injecting additional output into the market and the potential responses of the incumbents.
(Art. 69 of Reg. 2004/C 31/03)
FAANGS Grow and Diversify via Mergers
As Gautier and Lamesch (2020) point out, a FAANG firm consists of multiple interdependent
segments, each of which engages with different user-groups in a multi-sided market. Historically,
the acquisition of start-ups that serve these segments and their associated user-groups has been one
of the primary ways in which both FAANGs and smaller Big-Data firms (from among which future
FAANGs are likely to emerge) have expanded and diversified a competitive and dynamic market-
space.

10. pg. 10
Most Acquisitions are Not Killer Mergers
Empirical studies that examine the killer merger phenomenon find that only a minority of
acquisitions lead to discontinuation, while an even smaller subset of these acquisitions might
hypothetically qualify as killer mergers.
Concrete examples include Cunningham et al. (2020), whose findings indicate that 5.3 % to 7.4 %
of acquisitions in the study’s dataset classify as killer acquisitions.
4. Analysis
Approaching Start-up Survival: Is Start-up Survival Likelihood Influenced by
Investment?
In order to approach H1, the question of start-up survival and start-up survivability needs to be
examined. After all, the killer acquisition conjecture depends on the counterfactual survival of the
potential acquisition target.
Damodaran (2009), makes clear that most young companies do not survive the test of commercial
trial by fire. Furthermore, Knaup and Piazza (2007) compute survival statistics across firms from
1998 to 2005 using data from the US Bureau of Labor Statistics Quarterly Census of Employment
and Wages (QCEW), and found that while survival rates varied by industry, only around one-third
of businesses founded in 1998 survived the 1998-2005 period. Information-industry firms founded
in 1998 in Knaup and Piazza dataset had a seven-year survival rate of 24.8%.
Overall, Damodaran (2009) advocates examining start-up survivability likelihood along one of
three possible approaches. This is either
1. As a matter of sectoral industry-averages. Knaup and Piazza (2007) provide year-to-year
survivability during the 1998-2005 period across several industries for US firms founded
in 1998. On the basis of this, five-year or seven-year survivability can be estimated on
sectoral industry-basis. Table 2 outlines the Knaup and Piazza sectoral industry survival
percentages for the 1998 to 2005 period.
Table 2: Knaup and Piazza year-to-year survival percentages 1998-2005
Year 1 Year 2 Year 3 Year 4 Year 5 Year 6 Year 7
Natural resources 82.33% 69.54% 59.41% 49.56% 43.43% 39.96% 36.68%
Construction 80.69% 65.73% 53.56% 42.59% 36.96% 33.36% 29.96%
Manufacturing 84.19% 68.67% 56.98% 47.41% 40.88% 37.03% 33.91%
Transportation 82.58% 66.82% 54.70% 44.68% 38.21% 34.12% 31.02%
Information 80.75% 62.85% 49.49% 37.70% 31.24% 28.29% 24.78%
Financial activities 84.09% 69.57% 58.56% 49.24% 43.93% 40.34% 36.90%
Business services 82.31% 66.82% 55.13% 44.28% 38.11% 34.46% 31.08%
Health services 85.59% 72.83% 63.73% 55.37% 50.09% 46.47% 43.71%
All firms 81.24% 65.77% 54.29% 44.36% 38.29% 34.44% 31.18%

11. pg. 11
2. On a probability model basis. A sophisticated way to estimate probability of failure is to
look at firms that have succeeded and failed over a time period (ie, five years, ten years,
etc.), modelling the failure likelihood as a probit model, which can predict the probability
of a firm failing as a function of investor participation and investor coaching, as well as
firm characteristics, such as assets, age, sector, profitability measures and debt levels.
Formally, a probit model would adopt the functional form:
EQ 1:
𝑝(1 = 𝑠𝑢𝑟𝑣𝑖𝑣𝑎𝑙|𝑖𝑛𝑣, 𝑐𝑜𝑎𝑐ℎ𝑖𝑛𝑔, 𝑠𝑒𝑐𝑡𝑜𝑟, 𝑎𝑠𝑠𝑒𝑡𝑠, 𝑎𝑔𝑒) = Φ( ∑ 𝛽𝑖(𝑖𝑛𝑣 𝑐𝑜𝑎𝑐ℎ𝑖𝑛𝑔, 𝑝𝑟𝑜𝑓𝑖𝑡, 𝑠𝑒𝑐𝑡𝑜𝑟, 𝑎𝑠𝑠𝑒𝑡𝑠, 𝑎𝑔𝑒,
𝑖=1…𝑛
))
In a probit model, which captures the factors driving the probability of a binary outcome,
Φ (.) captures the standard normal cumulative distribution function, while βi represents the
coefficients applied to the impact of investor participation, as well as, each of the firm
characteristics on a start-ups survival likelihood. Examples of such models include
Bernhardsen (2001), which uses a probit model to predict firm-bankruptcy on the basis of
firm-level profitability, asset-adjusted performance, age and firm-level liquidity, in
addition to sectoral industry-averages for firm-performance.
3. On a composite scenario basis. In principle, scenarios are used in financial contexts for
stress-testing. Because start-up entrepreneurship is characterized by both uncertainty and
market-risk, simulations can be used to gauge survivability.
One common approach is a Ribonato-style Bayesian network approach used by Ribonato
(2017), or Hoefman and Berre (2011), whereby scenario results are networks of stepwise
dependent probabilities, driven interactions of influencing factors. Bayesian networks
orders the events in a parent-child relationship, as outlined in Figure 2:
Figure 2: Bayesian Web Scenario used in Bayesian Bank Stress Testing
Formally, Ribonato (2017), refers to the Master Theorem for Bayesian Nets, which says
that the joint probabilities among n variables are given by the product of the conditional
probabilities, conditioned on their parents only, as follows:
Event A Event B
Event C
Event D Event E
Event F

12. pg. 12
EQ 2:
𝑝(𝐸𝑣𝑒𝑛𝑡 1, … . 𝐸𝑣𝑒𝑛𝑡 𝑛) = ∏ 𝑝 (𝑥𝑖|𝑝𝑎𝑟[𝐸𝑣𝑒𝑛𝑡𝑖])
𝑖=1,𝑛
In this model, par[Event i] denotes the parents of variable Event I, and the conditional
probability of the root (i.e., of the variable that has no parents) coincides with its marginal.
In such a model-structure, non-acquisition can be placed in one of the parent nodes in order
to model the likelihood of start-up failure in a non-acquisition counterfactual scenario.
While future debates on whether the likelihood of killer acquisitions is impacted by the
incumbent’s acquisition and participation as an investor, are likely to be examined using each of
these three approaches, and the specifics of the context may demand, given the situation, the
acquisition target’s firm characteristics, and nature of the relationship between the target and the
incumbent.
Testing and Applying H1: Is H1 More True than Untrue?
Probit-Based Approach
In principle, whether the emergent start-up’s survival likelihood is impacted by the incumbent’s
acquisition and participation as an investor, if examined via the probit model approach, should
control for sectoral industry, as well as relevant firm characteristics, and should subsequently
examine the impact of investor participation on start-up survival in a counterfactual scenario by
asking:
• In which industry sectors is the acquisition target active in? What are the industry-level 5-
year, 7-year, and 10-year survival rates for start-ups?
• Did the acquisition target have access to external financing, coaching, and supply chains?
• What was the acquisition target’s stage of development? Firm age? Product development
stage?
• What was the acquisition target’s performance? Asset-weighted performance? Cost or
Investment-weighted performance? Risk-weighted performance?
Functionally, any of these factors – or combinations thereof –can serve as input factors to a probit
model along the lines of EQ1.
Scenario-Based Approach
Overall, the scenario-based approach demands the establishment of realistic likely firm-outcomes
given a series of input factors. A key feature which makes the scenario approach unique is that it
is a multi-stage approach, which each stage consisting of several possibility nodes, each of which
can have revenues, product development stages, and risk of failure associated with it.

13. pg. 13
As an example, a four-step Bayesian start-up survivability scenario for start-ups in an industry
with a 50/50 probability of becoming a high-growth industry would have the following nodes:
- A-Nodes: State of the industry. Hypothetically, an industry could become a high-growth
industry, as measured by its revenue growth-rate relative to macroeconomic indicators,
either globally or in a given market.
- B-Nodes: Outside investors decide whether to select a given start-up for acquisition or not.
Selection is assumed to only be made in high-growth industries.
- C-Nodes: Re-investment rates, which in discounted cash-flow models of valuation, directly
affect firm-valuation. Damodaran (2009) defines as Retained Earnings/ Current Earnings.
Growth rate defined by Damodaran (2009) as g = ROE * Re-investment Rate
- D-Nodes: Outcomes. The start-up might end-up bankrupt, a moderately-successful minor
market-actor, or a major digital firm.
A Bayesian scenario, subject to probabilistic viability checks (also called “sanity checks”), such
that the probability of any given outcome, or sum thereof is not larger than 1.00, would force
regulators and investigators to argue the following question:
- How far apart is P(D3|B2), (i.e., the probability of start-up bankruptcy if NOT selected for
acquisition) from P(D1|B1) and P(D2|B2) (i.e. the probability of becoming either a major
or minor digital firm if selected for acquisition)?
Figure 3: Start-up survival likelihood scenario
In principle, if an acquisition target can be determined to have had low survival likelihood using
either the probit approach or the scenario approach, the killer acquisition conjecture is undermined,
given that this would be indicative that the start-up had low survival probability, and that the

14. pg. 14
incumbent’s motivation for the acquisition is likely to have been driven by motivations other than
competitive market-structure. Alternate motivations might include acquisition of human resources,
intellectual property, developed products, business relationships, intangibles, or other assets.
Overall, estimation of survival likelihood can be approached using the acquisition target’s
performance disclosures, assets, and market risks, information about the target’s strategic
commercial relationships, and information about the acquisition target’s stage of development.
Applying H1 in a merger control context can also be undertaken, it would require informed
deliberation concerning industry and context-specific survival likelihood to be deliberated, which
would be no easy task given the subjectiveness and intangibility of survival likelihood. That being
said, regulatory authorities could approach the question via a series of proxies and thresholds, such
as industry-related start-up survivability metrics, funding costs and availability tests, coaching and
supply-chain availability tests.
Considering the questions and implications raised by H1, what competition authorities could take
into consideration when considering whether to approve a FAANG-related merger, is the survival-
to-maturity likelihood of the target firm, given its age, state of product-development, access to
outside investment, coaching, and supply-chain relationships. For the purposes of economic
modelling survival likelihood models can be established using some, or all of these factors, as
independent and direct relationships, or as inter-related factors.
Approaching the Emergence of a Substantial Horizontal Competitor
Given that a start-up survives to maturity, there are several ways that a start-up can evolve into a
horizontal competitor to an incumbent dominant firm.
This implies therefore, that the likelihood that an emerging start-up will develop into a horizontal
competitor to an incumbent dominant firm is driven by the likelihood of emerging as a substantial
industry player, as well as by the likelihood of the start-up’s different possible paths to emerging
as a horizontal competitor.
First, Kamepalli et al. (2020) describe both general welfare and consumer switching likelihood is
driven by relative quality of the entrant’s technology vis-à-vis that of the incumbent dominant
firm. Furthermore, for the start-up to emerge as a viable horizontal competitor, one of three types
of events must be likely:
a) The start-up can organically grow into a substantial horizontal competitor under its own
control. In principle, a start-up growing to maturity under its own control would imply that
the start-up would ultimately terminate its emergent stage with an initial public offering
(IPO), thereby becoming its own mature firm.
b) The start-up can be acquired by an existing or aspiring horizontal competitor. In principle,
rather than a killer acquisition, this would be an acquisition made for purposes of acquiring
the start-up’s resources, developed products, or established business relationships, and
their subsequent competitive deployment into the market in competition with the

15. pg. 15
incumbent dominant firm. This would resemble the cooperative relationship adopted by
disruptive firms described in Marx et al. (2014), whereby development of the start-up’s
commercial strategy proceeds via pursuit of joint venture or technology-licencing.
Concrete examples of such cooperation in a disruptive technology context are described in
the fintech industry by UBS (2016) and Berre and Aguirre (2018).
c) The start-up can be invested in by passive investors, such as financially-affiliated VCs or
independent, non-affiliated VCs (IVCs). According to Chemmanur et al. (2014), CVC-
backed firms are more innovative, as measured by their patenting outcome, although they
are younger, riskier, and less profitable than IVC-backed firms, a divergence owed to the
incumbent’s industry knowledge, as well as the technological fit with start-up firms. While
the involvement of IVCs might ultimately also lead to and IPO as it exits its emergent
stage, an IVC-backed start-up may also generally posses the resources to scale itself into
the position of substantial competitive market-actor during its emergent stages. Concrete
examples of this include start-ups backed by Softbank, such as WeWork.
Formally, H2 can be approached as a probability-summation function, whereby the likelihood of
the emergent start-up growing into a substantial horizontal competitor to the dominant incumbent
firm consists of a summation of the likelihood of organic growth-to-maturity, of acquisition by
horizontal competitors, and of passive IVC-backing, modified by quality-increment relative to the
incumbent, as modelled in Kamepalli et al. (2020). The substantial horizontal competitor
likelihood can be expressed as:
EQ 3:
𝑝(𝐻𝑜𝑟𝑖𝑧𝑜𝑛𝑡𝑎𝑙 |𝑂𝐺, 𝐶𝐴, 𝐼𝑉𝐶) = 𝜃 ∑ 𝛽𝑖(𝑝(𝑂𝑟𝑔𝑎𝑛𝑖𝑐 𝑔𝑟𝑜𝑤𝑡ℎ), 𝑝(𝐶𝑜𝑚𝑝𝑒𝑡𝑖𝑡𝑜𝑟 𝑎𝑐𝑞𝑢𝑖𝑠𝑖𝑡𝑖𝑜𝑛), 𝑝( 𝐼𝑉𝐶))
𝑖=1…𝑛
In this model, likelihood of development is modified Kamepalli’s θ, which captures the relative
quality of the start-up’s technology and services (hence its disruption potential), and is calibrated
such that at θ = 0, the start-up is of equal quality to the dominant incumbent. The coefficient βi
captures the impact of the likelihood of factor i on total substantial horizontal competitor
likelihood. Given that factor-overlap, factor-proxy overlap, and factor-interactive effects may be
present, βi may become a dynamic element of the substantial horizontal competitor likelihood
model.
Testing and Applying H2: Is H2 More Likely than Unlikely?
Essentially, H2, which captures whether a start-up is likely to grow into a substantial horizontal
competitor, can be applied to counterfactual analyses or to merger control deliberations. The fact
that H2 is driven by factors which are both uncertain and subjective will make H2 somewhat
difficult to apply in a regulatory context.

16. pg. 16
For starters, it will be necessary to develop thresholds for “substantial”, by applying existing
market-share thresholds. Next, thresholds for Kamepalli’s θ need to be developed based on
substantiability thresholds.
Lastly, because H2 is being approached via a likelihood function, deliberations on whether H2
undermines the killer acquisition conjecture in either counterfactual scenario analysis or in merger
control deliberations would lead to the emergence and application of likelihood thresholds.
In principle, a dominant incumbent’s acquisition of targets, whose relative quality is negative, or
whose substantial horizontal competitor factor likelihoods are demonstrably unlikely can
generally be considered not be killer acquisitions.
Approaching Internal Control and Complementarity
In general, a corporate investor in a post-acquisition scenario has at least some measure of control
of an acquisition-target start-up. This control can be exercised via board seats, voting rights, voting
power, liquidation rights, or milestone clauses in the start-up’s shareholder agreement.
This implies therefore, that in a post-acquisition scenario the incumbent investor has incentive to
use its control to influence the target start-up’s development towards a developing into
complement or subsidiary, rather than towards dissolution of the start-up.
As Gautier and Lamesch (2020) explain, while horizontal and vertical mergers raise competitive
concerns as they reduce market competition or create a risk of vertical foreclosure respectively,
conglomerate mergers raise somewhat concern.
In principle, this leads to the emergence of two key questions:
• To which degree does the CVC or incumbent-investor hold control and liquidation rights
within the target start-up?
• Does the CVC or incumbent-investor have the incentive and opportunity to influence the
target start-up’s development towards a developing into complement or subsidiary?
These questions are especially pertinent, given the findings of Kaplan and Stromberg (2003),
which outline that control rights must be paid for, a cost typically paid under uncertainty. Empirical
evidence demonstrated however, that these questions may influence CVC behavior in opposite
directions. Both Masulis and Nahata (2009), and Rohm et al. (2018) find empirically that corporate
investors pay more to acquire a potential horizontal competitor than they do to acquire a
complementary firm.
Formally, we can suppose that if the degree of investor-control in a start-up influences
complementary between the start-up at either the firm-level, or in a given industry, it might be
indicative that corporate investors are use their control to influence complementarity. Because
complementary can be measured via the cross-elasticity of demand:
EQ 4:

17. pg. 17
𝐸 𝑥𝑦 = ∑ (𝛽𝑖 𝜓𝑖 )
𝑖=1…𝑛
In this model, Exy is the cross-elasticity between firm x (the incumbent) and firm y (the acquisition
target). Because many products and services of FAANG firms and their horizonal competitors do
not charge prices to end-users, cross-elasticity can also be measured as the relationship between
y-quantities and x-revenues. Meanwhile, ψ captures the degree of investor control, ranging from
0 (no investor control) to 1 (total investor control). The model is structured in such a way that
investor control can be captured by either one parameter, or by multiple parameters (for example,
voting rights, board seats, board powers, milestone clauses, dissolution rights, exit rights). This is
multiplied by
Other, more sophisticated measures of complementarity and substitution can also serve as the basis
of an investor-control and complementarity model as well. Examples of this would include
Elasticity of Substitution functions which explicitly include investor control, whereby the investor
control drives elasticity of substitution. For example, a Constant Elasticity of Substitution
approach, would take the form:
EQ 5:
𝑆𝑒𝑐𝑡𝑜𝑟𝑎𝑙 𝑂𝑢𝑡𝑝𝑢𝑡 = 𝛽[𝐴𝑥 𝜌
+ 𝐵𝑦 𝜌
]1/𝜌
while 𝜎 =
1
1−𝜌
and 𝜌 ∝ µ (𝑖𝑛𝑣𝑒𝑠𝑡𝑜𝑟 𝑐𝑜𝑛𝑡𝑟𝑜𝑙)
In this model approach, x and y denote the output levels or revenues of incumbent and the
acquisition target respectively, while A and B are coefficients representing respective share-
parameters (i.e. market-shares). The elasticity of substitution, denoted by σ, otherwise stated as 1
/ 1-ρ, and is proportional to investor control, subject to coefficient µ. That is, as investor control
increases, ρ increases and σ decreases leading to an increasingly-perfect complementary
relationship between the incumbent and the acquisition target.
Investor control can be gathered from the start-up’s internal documents, by noting or constructing
an index quantifying and weighting investor’s vote concentration, board concentration, and
presence of any clauses granting veto power, milestones, or special decision rights.
In absence thereof, attempt can be made to proxy the level of control by estimating the share of
CVC investment as a share of the acquisition target’s total valuation.
EQ 6:
𝐷𝑒𝑔𝑟𝑒𝑒 𝑜𝑓 𝑐𝑜𝑛𝑡𝑟𝑜𝑙 𝑝𝑟𝑜𝑥𝑦 =
𝐴𝑚𝑜𝑢𝑛𝑡 𝐼𝑛𝑣𝑒𝑠𝑡𝑒𝑑 𝑏𝑦 𝐴𝑐𝑞𝑢𝑖𝑟𝑜𝑟
𝑇𝑜𝑡𝑎𝑙 𝑆𝑡𝑎𝑟𝑡 − 𝑢𝑝 𝑉𝑎𝑙𝑢𝑎𝑡𝑖𝑜𝑛
This approach may however, require tracking multiple rounds of investment, for start-ups that have
experienced successive rounds of investment by the same investor.

18. pg. 18
Testing and Applying H3: Is H3 More True than Untrue?
Essentially, in the case of a cross-elasticity approach as per EQ4, H3 captures whether investor
control drives cross-elasticity between the incumbent and the acquisition target. A positive
relationship between the two (i.e., a positive Exy) may indicate a complementary relationship,
while a negative Exy may indicate economic substitutes (i.e. a competitive relationship). judging
whether H3 is more true or untrue would require establishment of a cross-elasticity of demand
threshold, based on the revenue and business activities of the incumbent and the acquisition target.
In the case of an elasticity-function approach as per EQ5, where investor control drives elasticity
of substitution, judging whether H3 is more true or untrue would require establishment of an
elasticity of substitution threshold, given sectoral-level output, as per the established market-
definition.
A third way would be the establishment of H3 on the basis of share of CVC investment as a share
of the acquisition target’s total valuation. While this approach would grant informative insight if
used on sectoral or industry level analysis, the approach may be difficult to use as a viable proxy
in specific individual cases because of the possibility of special voting rights, as well as second
and third degree ownership.
In principle, if the buyer has very little control over the target start-up, the killer acquisition
conjecture is undermined, while the role of the corporate-investor within the start-up comes to
resemble that of a passive investor.
If on the other hand, a corporate investor has control of an acquisition-target start-up, the investor
may opt for the start-up to develop into a complementary firm or a subsidiary of the incumbent,
rather than a horizontal competitor. This would also undermine the killer acquisition conjecture.
Evidence to be Examined
In principle, each of these hypotheses can be both examined empirically and be tested for the
purposes of merger control and abuse of dominance investigation on either and ex-ante basis, an
ex-post basis, or both.
H1: Target’s Survivability Likelihood
While there are several ways to establish a start-up acquisition-target’s survivability, analysis of
this would almost certainly be sector-specific. A probit model approach, as per EQ 1 would
measure a start-up’s 5-year or 7-year survival likelihood as a function of the firm’s age,
development level, and performance measures, as well as industry-level standards for growth,
profitability, and risk. In principle, these can be a collection of one-dimensional measures drawn
from a firm’s income statement and balance sheet, such as revenues, assets, profit margins,
userbase, customer-base, we all as the growth thereof. Foulquier et al. (2019) outline however that
these can also take the form of two-dimensional measures which capture both performance and
scale of resources employed such as ROA, or ROCE, as well as three-dimensional measures which
additionally capture risks involved such as market-risk-adjusted returns or RAROC.

19. pg. 19
Approaching start-up survivability via the construction of stress-testing or survival-scenarios
would be a multi-step scenario which would also require the use of firm-level performance metrics.
These would these be subjected to a series of market-level or industry-level stress factors, which
may be employed as a single-step or multi-step analysis.
In all cases, examination of survivability requires firm-level data gathered from the start-up’s
accounting figures, as well as sector-level economic data.
H2: Emergence of a Substantial Horizontal Competitor Likelihood
Approaching the question of horizontal competitor emergence can be segmented into two parts.
First, the likelihood that the start-up is or will become a viable horizontal competitor. As per EQ
3, the likelihood that a start-up will become a viable competitor. There are several ways a start-up
can develop into a viable horizontal competitor. In terms of market-data indicators, this essentially
boils down to sources of external financing, support, coaching, and/or complementary business
relationships.
Second, the likelihood that the start-up is or will become a substantial horizontal competitor can
be tied to Kamepalli et al. (2020)’s θ, which tracks the start-up’s quality relative to the incumbent.
In practical terms, θ serves as a proxy for issues ranging from technological development, to
service quality, to business practices, all of which are likely to be industry or sector-specific, or
even product-specific.
That being said, θ can be proxied via market-share for the purposes of ex-post analysis, or θ can
be modelled for the purposes of ex-ante analysis (for example for merger-control). Model-factors
which would impact θ could include growth-rate, start-up R&D expenditures, intellectual property,
or other intangible assets. All of these factors would be modulated by one or multiple sectoral
coefficients.
H3: Investor Control and Complementarity
In order to gather sufficient information concerning the relationship between investor control and
complementarity, it would be necessary to gather both internal evidence and market data.
Principally, the degree of investor control can be gathered from the acquisition target’s formal
documentation. Because corporate governance legislation in many jurisdictions does not outline
specific details of corporate governance for SMEs and start-ups, they are often outlined in
shareholder agreements, firm bylaws, and general assembly resolutions. These documents would
allow for the collection of specific details of an investor’s vote concentration, board concentration,
and presence of any clauses granting veto power, milestones, or special decision rights.
In absence thereof, attempt can be made to proxy the level of control by estimating the share of
CVC investment as a share of the acquisition target’s total valuation.
Complementarity meanwhile, can be inferred from either internal firm-level data or from market
data. As per EQ4, cross-elasticity can be determined from positive empirical association between

20. pg. 20
the acquisition target’s output level or revenues, and those of the acquiror. Meanwhile, as per EQ5,
elasticity of substitution can be inferred from the relationship between output level or revenues of
both firms and the industry’s output as a whole.
5. Cases: Google and Facebook Acquisitions
Google/Waze Merger
In 2013, Waze, an Israel-based crowdsourced GPS navigation and mapping start-up founded in
2006 was acquired by Google for $966 million, and was US Federal Trade Commission, the UK
Office of Fair Trading, and the Israeli Competition Authority, all of whom cleared the merger.
Waze’s product viability depends on a sizable userbase for scale and network effect.
While Waze can be used anywhere in the world but requires enough initial users to create the maps
and continuously update data to make it useful. Currently, only 13 countries have a full base map;
the others are incompletely mapped, requiring users to record roads and edit maps.
Nevertheless, Argentesi et al. (2019) outline that even in the years after the merger, Waze and
Apple Maps constituted the primary alternatives to Google Maps for turn-by-turn digital
navigation services.
In 2018 and 2019, Waze announced successively increasing levels of integration with other Google
services, such as Android Auto, YouTube Music, and Google Assistant, broadly cementing
Waze’s complementarity with Google’s other services and products.
Anecdotal Media Coverage of Acquisition
Digital industry press covering the acquisition characterized the acquisition as a conglomerate
merger. TechCrunch describes the merger as complementary in nature, coming in the aftermath of
failed acquisition negotiations by Apple and Facebook, rival FAANG platforms to Google.3
Meanwhile, Wired’s coverage of the acquisition points out that while direct competitor status vis-
à-vis Google Maps is limited and indirect. According to ex-post coverage by Wired however,
Alphabet has a history of “acquihires”, whereby Google’s parent company plans its acquisitions
with expansion of human resource and R&D capabilities in mind.4
Business-focused press also mentions the competitive-market context in which the acquisition took
place. Financial Times’ coverage of the merger points out that the Waze acquisition served to
prevent Facebook and Apple from catching-up with Google’s market-position.5
Forbes’ coverage
3
Google Bought Waze For $1.1B, Giving A Social Data Boost To Its Mapping Business. TechCrunch. June 11,
2013
4
If you can't build it, buy it: Google's biggest acquisitions mapped. Wired. November 25, 2017
5
Google buys mapping app for $1bn. Financial Times. June 11, 2013.

21. pg. 21
of the merger also cites interest from Facebook and Apple as a motivating factor in Google’s
acquisition bid.6
H1: Had Waze Achieved Survivability?
Waze’s viability was driven by network effects. According to Argentesi et al. (2019), effects
stemmed from the fact that Waze used a community-based application to develop its maps, but
that UK authorities concluded that the scale achieved by Waze in the UK was insufficient for Waze
to benefit from significant network effects, in terms of its product.
In terms of revenue, pre-merger Waze introduced advertising in 2012, running search ads, pop-up
ads, nearby store-arrows, and branded pins. Argentesi et al. (2019), outline explicitly this is an
approach that is also used by Google. The implication is that Waze was a smaller competitor, with
a similar business model to Google, and therefore did not face much non-survival risk had the
merger not occurred.
H2: Was Waze Likely to Develop into a Substantial Horizontal Competitor?
While media coverage of the Waze acquisition (most notably, that of TechCrunch) characterized
Waze as only a vague substitute for Google Maps7
, Argentesi et al. (2019) outline that by the time
of the merger, Waze had already developed into a horizontal competitor to Google Maps, a free
navigational service. Certainly, Argentesi et al. (2019) outline that Google and Waze overlapped
in the supply of turn-by-turn navigation applications for mobile devices.
According to Argentesi et al. (2019), Waze was a smaller competitor, with a similar business model
to Google. Furthermore, Waze and Apple Maps constituted the primary competition to Google
Maps for turn-by-turn digital navigation services. This means that Waze was viable horizontal
competitor.
Nevertheless, as a substantial horizontal competitor, Google Maps faced a stronger competitive
threat from Apple Maps, a FAANG-supported competitor whose parent-company also supplies
mobile devices. Corroborating this, Figure 4 displays the Argentesi et al. (2019) market-share
figures for 2015, two-years post-merger. In both cases, Waze occupied a market-share of less than
5%.
That being said, it should also be noted that media coverage of the Waze acquisition explicitly
state Google’s concern about Waze’s potential acquisition by rival FAANG firms Apple and
Facebook, who both entered merger negotiations with Waze. This means in principle, that the
likelihood that Waze may have developed into a substantial horizontal competitor might have
depended on likelihood of acquisition by Google’s existing horizontal competitors.
6
Four Reasons Google Bought Waze. Forbes. June 11, 2013.
7
Google Bought Waze For $1.1B, Giving A Social Data Boost To Its Mapping Business. TechCrunch. June 11,
2013

22. pg. 22
Figure 4: 2015 Market-shares of Waze and Google Maps: Of all turn-by-turn navigation apps, and of Android devices
H3: To What Degree is Post-Merger Waze Complementary with the Acquiror?
Overall, the post-merger trajectory and development of Waze has seen the start-up develop into an
integrated complement to Google’s other services, products, and subsidiaries. This is indicative of
Waze’s complementarity with Google’s other services. Media coverage of the Waze merger
corroborates this is a Google growth strategy, applying the term “Acquihire”.8
Announcements in 2018 and 2019, revealed Waze to be on a path of increasing integration with
Google’s mobile products and services in particular. These include as Android Auto, YouTube
Music, and Google Assistant.
Facebook/Instagram Merger
Instagram is perhaps one of the 2010s’ most prominent FAANG acquisition deals, wherein the
acquisition target continues operations. Instagram, a US-based photo and video sharing social
platform launched in 2010, saw initial rapid userbase growth while receiving extensive media
fanfare, and was acquired Facebook in 2012. Ultimately, the merger was cleared by the both the
US Federal Trade Commission and the UK Office of Fair Trading in 2012.
Figure 4, drawn from Argentesi et al. (2019), demonstrates Instagram’s launch, acquisition by
Facebook and post-merger timeline, including its extensive post-acquisition development as a
product, whose viability as a substantial horizontal competitor grew noticeably during the post-
acquisition period.
8
If you can't build it, buy it: Google's biggest acquisitions mapped. Wired. November 25, 2017

23. pg. 23
Figure 4: Argentesi et al. (2019) Instagram Acquisition Timeline
Seen from an ex-post perspective, the continued independent existence, revenue growth and capacity
development of Instagram demonstrates that Facebook’s acquisition of Instagram did not constitute a killer
acquisition.
Anecdotal Media Coverage of Acquisition
Digital industry press at the time were clear both about Instagram’s status as a horizontal competitor and
about Facebook’s plan to continue operating and expanding Instagram under its existing brand name. In
2012, Tech crunch reported that merger would turn its “budding rival” into a standalone photo app, who
would remain both separate and independently-branded, but whose services will increase its ties to those
of Facebook.9
Business-focused press meanwhile, characterized Instagram and the qualitatively-superior platform. For
example, Business Insider’s coverage of the acquisition explicitly described the Instagram app as being
9
Facebook Buys Instagram For $1 Billion, Turns Budding Rival Into Its Standalone Photo App. TechCrunch, April
09, 2012

24. pg. 24
much faster than that of Facebook.10
Wall Street Journal’s coverage also mentioned Instagram’s status as
a viable horizontal competitor.11
It was only in 2019 that media reports surfaced of future Facebook plans to partially integrate the
messengers services associated with Facebook’s various platforms.12
H1: Had Instagram Achieved Survivability?
While Instagram acquired 1 million users within a year of its launch and was acquired by Facebook two
years after its launch, UK regulatory sources describe Instagram as establishing its economic success in the
UK after the merger. Argentesi et al. (2019) outline that while Instagram started to monetize in the UK in
2015, and subsequently saw its revenues increase and user-base significantly vis-à-vis revenue increases
experienced by other social platforms. Figure 3, which outlines Instagram’s acquisition timeline
corroborates this, with monetization beginning in 2015.
That being said, Instagram experienced two rounds of venture capital funding prior to its acquisition by
Facebook, raising $7 million in 2011, and $50 million in early 2012, a fact which likely led to Instagram’s
trade-sale to a FAANG.
H2: Was Instagram Likely to Develop into a Horizontal Competitor?
Given Instagram’s userbase growth within its first year, as well as its initial focus on smartphone users, pre-
acquisition Instagram was likely to develop into a horizontal competitor. Considering the likelihood factors
outlined in EQ4, the presence of numerous business angel and IVCs, such as Benchmark Capital and Thrive
Capital served as a source of resources allowing Instagram to develop as a horizontal competitor.
Instagram is considered a competing platform to its acquiror even post-acquisition. Argentesi et al. (2019)
describe Instagram’s market-share in terms of number of monthly unique users on social networks, share
of monthly time spent on social network, and social network advertising revenue. In all of these, Instagram
is compared its acquirer Facebook, as well as other social media platforms, most of which, Instagram
outperforms.
H3: To What Degree is Post-Merger Instagram Complementary with the Acquiror?
In order to gather sufficient information concerning the relationship between investor control and
complementarity, it would be necessary to gather both internal evidence and market data.
Principally, the degree of investor control can be gathered from the acquisition target’s formal
documentation. Because corporate governance legislation in many jurisdictions does not outline specific
details of corporate governance for SMEs and start-ups, they are often outlined in shareholder agreements,
firm bylaws, and general assembly resolutions. These documents would allow for the collection of specific
details of an investor’s vote concentration, board concentration, and presence of any clauses granting veto
power, milestones, or special decision rights.
10
Facebook Buys Instagram For $1 Billion. Business Insider, April 09, 2012
11
Insta-Rich: $1 Billion for Instagram Facebook Inks Its Biggest Deal Ever; Neutralizes Threat from a Hot Photo
Start-Up. Wall Street Journal. April 10, 2012
12
Facebook looks to integrate WhatsApp, Instagram and Messenger. Financial Times. January 25, 2019.

25. pg. 25
In absence thereof, attempt can be made to proxy the level of control by estimating the share of CVC
investment as a share of the acquisition target’s total valuation.
Complementarity meanwhile, can be inferred from either internal firm-level data or from market data. As
per EQ4, cross-elasticity can be determined from positive empirical association between the acquisition
target’s output level or revenues, and those of the acquiror. Meanwhile, as per EQ5, elasticity of substitution
can be inferred from the relationship between output level or revenues of both firms and the industry’s
output as a whole.
6. Discussion and Conclusion
The Killer Acquisition Conjecture Revisited
According to Levitt (1922), while outcomes can be determined to be results of a given cause by
comparing with existing results of similar causes, natural cause can be determined by inspection
and comparison, and probable cause is determined by conjecture.
In this study, we have established that in order for the killer acquisition conjecture to be more true
than not true, it would necessarily require for Hypotheses H1, H2, and H3, concerning the target’s
survivability likelihood, substantial horizontal competitor emergence, and investor control to be
unlikely.
In a practical sense, this means that whether for competition policy purposes or for purposes of
investigation of abuse of dominance and merger control, it should be taken into consideration that
the realities of the 21st
century digital marketplace demonstrate that while Big-Data industry firms
are large, have diverse operations, and frequently acquire start-ups, there are strategic motivations
for doing so, and of acquisitions can also be complementary in nature, or are of firms that might
not have otherwise not survived.
While killer acquisitions on the other hand, being acquisitions to discontinue potential current or
future competing start-ups aimed at protecting market share rather than the growth and
diversification of the acquirer, might not have any further strategic meaning for the acquirer, the
Big-Data & Analytics industry has seen several high-profile acquisitions, whose result was either
the continuation of the target start-up, or the complementary integration of the acquirer’s wider-
range of products and services.
Tests and Likelihood Thresholds
In principle, the validity of survivability-likelihood tests, substantial horizontal competitor
emergence likelihood tests, and control-complementarity tests serves to challenge the likelihood
of any given individual merger to be a killer-acquisition and to establish the merger as a legally-
legitimate pro-competitive merger, with the potential to contribute to improving the production or
distribution of goods or contribute to promoting technical or economic progress, as per TEFU
101(3).

26. pg. 26
The application of thresholds can serve to determine and establish the competitive-market
legitimacy of digital industry start-up acquisitions. This includes tests and thresholds for:
- survivability metrics
- funding costs
- availability of coaching
- supply-chain availability
- organic growth likelihood
- competitor acquisition likelihood
- cross-elasticity of demand
- elasticity of substitution
Possibilities for Future Research
Going forward, the nascent and emerging digital, Big-Data and IoT industries have led and are
leading to reform and disruption in in markets, in terms of both technological development and
market-structure.
Consequently, this gives rise to several avenues of possibility for future research in the field of
competition policy in the digital age. This extends across both theoretical and empirical research,
as well as with focuses which can be both general or industry-specific.
In terms of theoretical research, more research needs to be carried out into the specific elaboration
and description of threshold-measures in general, as well as on an industry-specific basis for
industries related to the fourth-industrial-revolution, such as Big-Data, IoT, and digital industries.
Furthermore, because FAANGs
Additionally, further research needs to be undertaken into the exploration of the market-structure
measures and dynamics of industries related to the fourth-industrial-revolution, since traditional
measures and dynamics are fundamentally challenged by both the technology and the associated
economic dynamics of 21st
century digital markets.
In terms of empirical research, the empirical relationship between investor control and investor-
complementarity has not heretofore been investigated in peer-review literature. Given that
shareholder agreements and investor relationships can given rise to different investor-control
mechanisms, this may be a source of multiple empirical law and finance studies.
While Damodaran (2009) outlines that start-up survivability can be estimated based on sectoral
averages, probit functions, or scenarios, empirical studies on start-up survivability have
concentrated on probit functions, while use of scenarios to examine survivability has generally
been limited to macroeconomic or banking-industry studies, rather that start-up or venture capital
studies.
Legal studies on the viability of survivability thresholds, or substantial horizontal competitor
likelihood thresholds are also heretofore yet to emerge in peer-review literature.

27. pg. 27
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