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Acquisition Performance:Acquisition Performance:Experience or Competence?Experience or Competence?

Steven E. PhelanSteven E. Phelan

Tomas ManteconTomas Mantecon

University of Nevada Las VegasUniversity of Nevada Las Vegas

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BackgroundBackground

• Phelan Research Questions

• Entrepreneurial competence• Alliances• Acquisitions

Methods• Agent-based models• Experimental game theory• Event studies

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Central Questions in StrategyCentral Questions in Strategy• Do some firms perform better than others?

Do some firms (consistently) create more shareholder value than others?

• Sustainable competitive advantage – the holy grail• There is a deeply held belief (bias?) that this is true

• Why do some firms perform better than others? Most research focuses on this question

• Can I make this specific firm perform better than others? Little on this

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Acquisition Research in Acquisition Research in StrategyStrategy

• Same questions Do some firms perform consistently better on

acquisitions than others? Why is this the case? What should a specific firm do to increase its

acquisition performance?

• General perception that… …acquirers (bidders) lose value in

acquisitions and that the targets capture most of the value created

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The Resource-Based View of StrategyThe Resource-Based View of Strategy

• A General Theory for Why Firm A Outperforms Firm B Firm A possesses a value-creating resource

(asset) that Firm B does not, or Firm A uses a resource in a way Firm B does not

(it possesses a competence or capability that Firm B finds difficult to imitate)

If Firm A can acquire its resources for a lower cost than Firm B (due to information asymmetry or luck) than they will also have a competitive advantage

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Resource-Based View of AcquisitionsResource-Based View of Acquisitions

• Firm can acquire valuable resources through acquisitions Emphasis on creating a synergy between old and new

resources (1+1=3)

• Porter has two tests: Is firm better off?

• Is additional value being created in the merger?

Cost of entry• Is the acquisition premium you are paying less than the value

created (and preferably much less)• Links to the synergy trap or winner’s curse

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Recent theoryRecent theory• Hitt, Hoskisson, and Ireland

Firms may develop a competency in identifying, negotiating, and/or integrating acquisitions that can lead to a competitive advantage

Classic examples: Cisco, GE – who make dozens of acquisitions each year

Not much empirical evidence for an acquisition competence

Those with an acquisition competence should have a higher performance

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The Role of ExperienceThe Role of Experience

• Simple enough The more acquisitions you do the better you

should get at acquisitions

• Easy to study Simply count how many acquisitions a firm

makes and see if performance increases with experience

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Measuring performanceMeasuring performance• Market efficiency

If you believe that markets are reasonably efficient then the deviation in a firm’s stock price following the acquisition announcement will reflect the market’s judgment on the wisdom of the acquisition (after adjusting for normal daily market movements)

• Window We use a 3-day day window that includes

movements one day before and after the announcement.

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Previous StudiesPrevious Studies• Kusewitt (1985)

Returns decline if firms do more than one acquisition per year

• 138 companies, 3500 events, 1967-76

• Fowler (1989), Bruton (1994) Small positive relationship between experience and

performance• Only 41 and 52 events respectively

• Lahey and Conn (1990) No difference in performance between firms making

single or multiple acquisitions in a six year window• 91 events over $10m

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Previous StudiesPrevious Studies• Haleblian & Finkelstein (1999)

Reported U-shaped relationship between experience and performance using 449 events >$10m

Convoluted logic to explain effect• Hayward (2002)

535 acquisitions by 100 firms No relationship between experience and performance Time between acquisitions was significant

• Inverted U-shape

• Zollo & Reuer (2003) 51 banks, 577 events No relationship between experience and performance

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Meta-AnalysisMeta-Analysis• King et al (2004) meta analysis

Compared 7 studies, 1300 events Different performance measures ranging from

days to months to years No relationship between experience and any

performance measure

• We hypothesize no relationship between experience and performance for our sample

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CompetenceCompetence• So what is making GE and Cisco so good

at acquisition if not experience? Perhaps raw experience is not a good proxy

for competence Chambliss (1999) found that Olympics

swimmers were qualitatively different from amateurs not just quantitatively different (they have differential technique)

• “superlative performance is really a confluence of dozens of small skills and activities, each one learned or stumbled upon”

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Differential LearningDifferential Learning There may also be an interaction between

experience and competence • competent companies may learn faster (perhaps

masking an experience main effect)

Hypotheses:• Qualitative competence will be associated with

performance• There will be an interaction between competence

and experience

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SampleSample• All reported acquisitions in SDC database

between 1991 and 2002 Dropped firms without CRSP data Dropped recaps, spinoffs, LBOs, contaminated events

(i.e. earnings announcement at same time) Dropped outliers (|CAR|>0.5) – only 50 cases Final sample 10,574 events

• 5734 private targets• 1465 public targets• 3375 subsidiary targets

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DesignDesign

• Sample was divided into 2 time periods 1991-1996 & 1997-2002

(although other divisions were tested)

• We operationalized ‘competence’ as the average (mean or median) performance in the first six years Two measures CAR and residual CAR Considered 1, 3, 5 qualifying events

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ResultsResults

• Controls: Event year, relative acquisition size, acquirer

performance, contested bids, business similarity, method of payment, use of advisor

• Raw correlations Positive correlation between competence and

performance, Negative correlation between experience and

performance

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ResultsResultsCompetence as… CAR Residual CAR

  Model 1 Model 2 Model 3 Model 4

  Mean Median Mean Median

Firm Performance 1.74 1.68 1.94 1.9

Cash 0.49 0.53 0.83 0.8

Stock -9.58** -9.72** -9.64** -9.86**

Contested Bid -15.49 -15.33 -15.51 -15.14

Business Similarity -6.2* -6.14* -6.1* -5.83*

Relative Acquisition Size 4.53* 4.51* 4.48* 4.35*

Use of Advisor -5.13* -5.01* -4.67 -4.5

Bidder size -2.98*** -2.93*** -3.37*** -3.53***

Past experience (log) -4.73 -5.18 -5.26 -5.1

Past experience2 0.93 1.00 0.97 0.90

Acquisition competence 52.22** 50.83** 43.64* 43.24*

Competence * Experience -29.43 -7.68 17.10 37.81

R2 0.035 0.035 0.035 0.036

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Results by Target StatusResults by Target Status  Model 1 Model 2 Model 3

  Private Public Subsidiary

Firm Performance -0.22 6.39* 1.83

Cash -3.12 20.51* -11.78*

Stock -0.67 -11.88 -22.8*

Contested Bid -0.17 -6.85 24.11

Business Similarity 1.12 -4.26 -9.49*

Relative Acquisition Size 9.21*** -1.54 11.68**

Use of Advisor 9.98* -15.53* 5.5

Bidder size -2.14* -1.86 -3.72**

Past experience (log) -7.49 -9.85 5.29

Experience squared 0.87 2.45 -0.31

Acquisition competence 72.62** -33.68 56.49*

Competence * Experience -34.87 -99.82 -4.12

R2 0.043 0.064 0.058

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DiscussionDiscussion• Experience has no relationship with

performance Confirms meta-study We also found no U-shaped relationship on

normalized data• Artifact of extreme measures?

• Past performance predicts future performance Arguably an unobserved competence

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DiscussionDiscussion• Competence relationship:

Strongly significant for private firms Marginally significant for subsidiaries Not significant for public acquisitions

• Suggests an informational component Private market is less competitive than public market Perhaps, competent firms have lower search costs

• No interaction between experience and competence Competent firms did not leverage experience better

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Extension I. Firm EffectsExtension I. Firm EffectsVariable DF SS MS F p

Firm Size 1 0.16698 0.16698 46.79 <.0001

Relative Acq Size 1 0.00057 0.00057 0.16 0.6894

Year 11 0.04553 0.00414 1.16 0.3109

Target Status 2 0.11561 0.05781 16.2 <.0001

Target Industry 58 0.35904 0.00619 1.73 0.0007

Cash 1 0.00246 0.00246 0.69 0.4065

Stock 1 7.5E-05 7.5E-05 0.02 0.8848

Contested 1 0.00869 0.00869 2.44 0.1189

Similarity 1 0.00177 0.00177 0.5 0.4815

Advisor 1 0.00234 0.00234 0.66 0.4178

Firm 149 0.84942 0.0057 1.6 <.0001

Firm*Year 738 3.13511 0.00425 1.19 0.0037

N=2224

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Extension II. Cross Border Extension II. Cross Border AcquisitionsAcquisitions

Variable DF SS F p

Year 19 0.057 1.019 0.4345

Target Status 5 0.032 2.194 0.0522

Bidder Size 1 0.007 2.466 0.1164

Competing Bids 1 0.000 0.079 0.7781

Relative Acq Size 1 0.028 9.409 0.0022

Prior Holdings 1 0.007 2.463 0.1166

Advisors 1 0.001 0.338 0.5612

Industry 64 0.187 0.992 0.4952

Business Similarity 1 0.011 3.616 0.0573

Cash 1 0.048 16.235 <.0001

Cultural Distance 1 0.034 11.414 0.0007

R2=0.035N=4682

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Extension III. Recursive Partitioning Extension III. Recursive Partitioning AnalysisAnalysis

Count

Mean

Std Dev

59456

0.0049712

0.0561442

All Rows

Count

Mean

Std Dev

39483

-0.009572

0.0467052

Log Rel Acq Size<2.60667683

Count

Mean

Std Dev

22648

-0.01961

0.0397567

Cash?(No)

Count

Mean

Std Dev

20979

-0.020158

0.0391379

Advisors?(No)

Count

Mean

Std Dev

1669

-0.012723

0.0463063

Advisors?(Yes)

Count

Mean

Std Dev

16835

0.0039322

0.0516895

Cash?(Yes)

Count

Mean

Std Dev

19973

0.0337201

0.0618611

Log Rel Acq Size>=2.60667683

Count

Mean

Std Dev

2682

-0.004401

0.0735244

T_Status(Public)

Count

Mean

Std Dev

1811

-0.015257

0.0753235

Advisors?(Yes)

Count

Mean

Std Dev

871

0.0181717

0.064027

Advisors?(No)

Count

Mean

Std Dev

17291

0.039633

0.057635

T_Status(Govt.,J.V.,Mutual,Sub.,Priv.,Unk.)

Count

Mean

Std Dev

4937

0.0244832

0.0737465

Cash?(Yes)

Count

Mean

Std Dev

12354

0.0456873

0.0484547

Cash?(No)

R2=.198