acquisition performance: experience or competence?
DESCRIPTION
Acquisition Performance: Experience or Competence?. Steven E. Phelan Tomas Mantecon University of Nevada Las Vegas. Background. Phelan Research Questions Entrepreneurial competence Alliances Acquisitions Methods Agent-based models Experimental game theory Event studies. - PowerPoint PPT PresentationTRANSCRIPT
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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