1. 1 Acquisition Performance: Experience or Competence? Steven E. Phelan Tomas Mantecon University of Nevada Las Vegas

2. 2 Background Phelan  Research Questions Entrepreneurial competence Alliances Acquisitions  Methods Agent-based models Experimental game theory Event studies

3. 3 Central 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

4. 4 Acquisition Research in Strategy 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

5. 5 The 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

6. 6 Resource-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

7. 7 Recent 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

8. 8 The 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

9. 9 Measuring 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.

10. 10 Previous 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

11. 11 Previous 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

12. 12 Meta-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

13. 13 Competence 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”

14. 14 Differential 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

15. 15 Sample 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

16. 16 Design 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

17. 17 Results 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

18. 18 Results Competence as…CARResidual CAR Model 1Model 2Model 3Model 4 MeanMedianMeanMedian Firm Performance 1.741.681.941.9 Cash 0.490.530.830.8 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 experience 2 0.931.000.970.90 Acquisition competence 52.22**50.83**43.64*43.24* Competence * Experience -29.43-7.6817.1037.81 R2R2 0.035 0.036

19. 19 Results by Target Status Model 1Model 2Model 3 PrivatePublicSubsidiary Firm Performance-0.226.39*1.83 Cash-3.1220.51*-11.78* Stock-0.67-11.88-22.8* Contested Bid-0.17-6.8524.11 Business Similarity1.12-4.26-9.49* Relative Acquisition Size9.21***-1.5411.68** Use of Advisor9.98*-15.53*5.5 Bidder size-2.14*-1.86-3.72** Past experience (log)-7.49-9.855.29 Experience squared0.872.45-0.31 Acquisition competence72.62**-33.6856.49* Competence * Experience-34.87-99.82-4.12 R2R2 0.0430.0640.058

20. 20 Discussion 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

21. 21 Discussion 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

22. 22 Extension I. Firm Effects VariableDFSSMSFp Firm Size10.16698 46.79<.0001 Relative Acq Size10.00057 0.160.6894 Year110.045530.004141.160.3109 Target Status20.115610.0578116.2<.0001 Target Industry580.359040.006191.730.0007 Cash10.00246 0.690.4065 Stock17.5E-05 0.020.8848 Contested10.00869 2.440.1189 Similarity10.00177 0.50.4815 Advisor10.00234 0.660.4178 Firm1490.849420.00571.6<.0001 Firm*Year7383.135110.004251.190.0037 N=2224

23. 23 Extension II. Cross Border Acquisitions VariableDFSSFp Year190.0571.0190.4345 Target Status50.0322.1940.0522 Bidder Size10.0072.4660.1164 Competing Bids10.0000.0790.7781 Relative Acq Size10.0289.4090.0022 Prior Holdings10.0072.4630.1166 Advisors10.0010.3380.5612 Industry640.1870.9920.4952 Business Similarity10.0113.6160.0573 Cash10.04816.235<.0001 Cultural Distance10.03411.4140.0007 R 2 =0.035 N=4682

24. 24 Extension III. Recursive Partitioning Analysis R 2 =.198