Employee mobility and acquisition targets

Transcription

Employee Mobility and Acquisition Targets
How Anticipated Employee Mobility
Affects Acquisition Likelihood:
Evidence from a Natural Experiment
Kenneth A. Younge
Leeds School of Business
The University of Colorado
Tony W. Tong
Leeds School of Business
The University of Colorado
Lee Fleming
Harvard Business School
Harvard University
March 2011
© Ken Younge, Tony Tong, Lee Fleming
11
Acquisitions can be a strategy to source
new knowledge and human talents
•
“Many mergers are driven by search for fresh talent.” (WSJ, 1997a)
•
“Why an acquisition? Often it‟s the people.” (WSJ, 1997b)
But there are challenges...
•
Retaining employees after an acquisition is a concern.
•
Human assets are inalienable & mobile.
•
For human capital-intensive companies, the most valuable assets
“walk out the door every night.” (LaVan, 2000)
2
The Literature
•
Acquisitions are disruptive; personnel problems well recognized
Jemison & Sitkin, 1986; Haspeslagh & Jemison, 1991
•
Most research focuses on post-acquisition mobility:
- The antecedents and consequences of turnover by acquired executives
Walsh, 1988, 1989; Hambrick & Cannella, 1993
-
The morale and productivity of employees who stay on after an acquisition
O‟Reilly & Pfeffer, 2000; Paruchuri et al., 2006
-
Incentives for retaining employees
O‟Reilly & Pfeffer, 2000; Ranft & Loft, 2000
3
The Gap
•
Little research on likelihood of becoming target: focuses on
financial drivers
Palepu, 1986; Song & Walkling, 1993, 2000; Field & Karpoff, 2002
•
No research studies on how anticipated employee mobility
affects the acquisition decision.
•
Extant research focuses almost entirely on realized deals.
-
Obvious potential for selection bias.
-
Current research sheds little light on the logic of acquisition decisions.
4
Research Question
•
How do firms‟ expectations about post-acquisition mobility
affect the selection of acquisition targets?
•
Assumptions:
•
-
Firms acquire resources based on expectations about the
future return of a strategy to use the resource (Barney,1986).
-
Employee departure from a target firm after an acquisition has,
on average, negative consequences for the acquirer.
-
Even if an acquirer aims to downsize the target or replace management, the
acquirer will always prefer to decide who will stay and who will go.
To pursue this question, we examine the full population of listed,
public firms that are „at risk‟ of becoming a target for acquisition.
5
Assumptions behind informal model
•
Knowledge is often tied to, or dependent upon, individuals.
- Loss of tacit knowledge Kogut & Zander, 1992
- Productivity losses when employees leave O‟Reilly & Pfeffer, 2000
- Knowledge can be transferred to competitors Stuart & Sorenson, 2003
•
Great uncertainty about turnover after an acquisition (Coff, 2002).
•
The uncertainty of ex post mobility affects ex ante valuation of the
target and the likelihood that acquirer will propose and strike a deal.
6
Hypothesis 1
•
NCAs constrain employee mobility
Marx, Strumsky, & Fleming, 2009; Garmaise, 2009; Fallick et al., 2006
•
Variation in the enforceability of NCAs is an observable proxy
for variation in expectations of post-acquisition mobility.
H1: An increase in the enforcement of non-compete agreements will
increase the likelihood that a firm will become an acquisition target.
7
Hypothesis 2
•
Knowledge workers have greater access to confidential
information and are more important to key capabilities Coff, 1997
•
Knowledge workers are more likely to depart after an acquisition
O‟Reilly & Pfeffer, 2000
•
Non-competes apply specifically to knowledge workers
Kaplan & Stromberg, 2001
H2: An increase in the enforcement of non-compete agreements
will increase the likelihood of acquisition to a greater extent for
firms with more knowledge workers.
8
Hypothesis 3
•
Employees are more likely to be aware of (and leave for)
external opportunities when there is more instate competition
Garmaise, 2009
•
Instate competitors are more likely to poach employees
Almeida & Kogut, 1999
•
Employees bargain more and extract more concessions when
there is more instate competition Coff, 1997
will increase the likelihood of acquisition to a greater extent for
firms with more instate competition.
9
Hypothesis 4
•
The effect of NCA enforcement depends on other available
mechanisms for mitigating the effects of mobility.
•
The enforcement of IP rights offers an alternative means for
protecting certain types of knowledge (i.e. patents) Teece, 1998
•
The effectiveness of IP protection, however, varies by
application and industry Cohen, Nelson & Walsh, 2000
will increase the likelihood of acquisition to a lesser extent for
firms protected by a stronger IP regime.
10
Main Hypothesis
H1 An increase in the enforcement of non-compete agreements
will increase the likelihood that a firm will become an acquisition
target.
Moderating Hypotheses
H2 ... to a greater extent for firms with more knowledge
workers.
H3 ... to a greater extent for firms with more instate
competition.
H4 ... to a lesser extent for firms protected by a stronger IP
regime.
11
Research Design
• Sample full population of public firms at risk of becoming an acquisition
target (all firms in Compustat for Michigan and comparison states).
• Use MARA and DID comparison to adjust for counterfactual trends over
time and identify a causal treatment effect.
• Use Coarsened Exact Matching (CEM) to balance on covariates between
our treated/untreated observations.
• Estimate logit models for the probability of becoming an acquisition target.
• Simulate the magnitude and significance of our non-linear interactions.
• Measures: knowledge workers/industry, proportion of firm‟s industry‟s sales
within region, Cohen, Nelson, and Walsh‟s survey of IP importance (2000)
12
Number of acquisitions in Michigan and the set of comparison states.
13
Transportation over-represented in MI
14
Acquired firms in Michigan 1982-1998
ALC COMMUNICATIONS INC
Transport, Comm.
FEDERAL SCREW WORKS
Metal Products
KELLOGG CO
Food & Tobacco
QUEST BIOTECHNOLOGY INC
Chemicals
ACME PRECISION PRODUCTS INC
Machinery, Computer Equip.
FEDERATED NATURAL RES LIQ TR
Agriculture, Mining
KELLY SERVICES INC -CL A
Business & Financial Svcs
REPUBLIC BANCORP INC
Banks
ACTION AUTO STORES INC
Retail
FIRST OF AMERICA BANK CORP
Banks
KELSEY HAYES CO
Transportation Equipment
RICH COAST INC
Utilities
AMERIWOOD INDS INTL CORP
Textiles, Wood, Furniture, Paper
FIRST FEDERAL BANCORP INC
Banks
KNAPE & VOGT MFG CO
SEMCO ENERGY INC
Utilities
ARBOR DRUGS INC
Retail
FIRST MICHIGAN BANK CORP
Banks
KNUSAGA CORP
SANDY CORPORATION
Professional Services
ARMADA CORP
Concrete, Metals, Stone, etc.
FIRST OF MICHIGAN CAPITAL CP
KYSOR INDUSTRIAL CORP
SCHERER (R P)/DE
Chemicals
AUTODIE CORP
FIRST NATL BANK CORP/DE
Banks
LA-Z-BOY INC
SECOM GENERAL CORP
BELL & HOWELL OPERATING CO
FIRSTFED MICH CORP
Banks
LARIZZA INDUSTRIES INC
SECURITY BANCORP INC/MI
Banks
BORMAN'S INC
Retail
FLAGSHIP EXPRESS INC
Transport, Comm.
LEAR HOLDINGS CORP
SECURITY SVGS BK FSB JKSN MI
Banks
BROADWAY HOLDINGS INC
Movies, Entertainment
FORD HOLDINGS INC
Banks
LEECO DIAGNOSTICS INC
Chemicals
SELIGMAN & ASSOCIATES
Construction
CMS ENERGY CORP
CADE INDUSTRIES INC
Utilities
FORD MOTOR CO
FORD MOTOR CREDIT CO LLC
Banks
MCN ENERGY GROUP INC
MANATRON INC
Utilities
SHELLER-GLOBE
SIMPSON INDUSTRIES
CENTRAL HOLDING CO
Banks
FRANKLIN BANCORP INC/MI
Banks
MANUFACTURERS NATIONAL CORP Banks
SPARTAN MOTORS INC
CENTREVEST CORP
CHAMPION ENTERPRISES INC
FRANKS NURSERY & CRAFTS INC
FRETTER INC
Retail
Retail
MARGATE INDUSTRIES INC
MASCO CORP
STANDARD FEDL BANCORP INC
STANDARD PRODUCTS CO
Banks
CHEMICAL FINANCIAL CORP
Banks
GMAC INC
Banks
MAXCO INC
STRYKER CORP
Instruments
CHRYSLER CORP
CHRYSLER FINANCIAL CORP
Banks
GELMAN SCIENCES INC
GENERAL ENER RESOURCE & TECH
Instruments
Agriculture, Mining
MAXAXAM CORP
MCCLAIN INDUSTRIES INC
SUNSHINE-FIFTY INC
TECHTEAM GLOBAL INC
CITIZENS REPUBLIC BANCORP
Banks
GENERAL METAL & ABRASIVES CO
MCLAREN PERFORMANCE TECH INC Transportation Equipment
TECUMSEH PRODUCTS CO -CL A
CLARK EQUIPMENT CREDIT CORP
CODE-ALARM INC
Banks
Electrical Equipment
GENERAL REAL ESTATE SHARES
GENTEX CORP
MEDSTAT GROUP INC
MERITAGE HOSPITALITY GROUP
Retail
TELECAST INC
THETFORD CORP
Transport, Comm.
Petroleum, Rubber, Leather
COMSHARE INC
GERBER PRODUCTS CO
Food & Tobacco
MICHIGAN BELL TELEPHONE CO
Transport, Comm.
THORN APPLE VALLEY INC
Food & Tobacco
CONSUMERS ENERGY CO
Utilities
GREAT DANE HOLDINGS INC
MICHIGAN CONSOLIDATED GAS CO Utilities
TRANS-INDUSTRIES INC
Other Manufacturing
CORE INDUSTRIES INC
CROSS & TRECKER CORP
Metal Products
GREAT LAKES BANCORP
GUARDSMAN PRODUCTS INC
Banks
Chemicals
MICHIGAN ENERGY RESOURCES CO Utilities
MICHIGAN FINANCIAL CORP
Banks
TRIMAS CORP
TUBBY'S INC
Wholesale
CROWLEY MILNER & CO
Retail
HANDLEMAN CO
MICHIGAN NATIONAL CORP
Banks
2B SYSTEM INC
D & N FINANCIAL CORP
D O C OPTICS CORP
Banks
Retail
HASTINGS MANUFACTURING CO
HIGHLAND SUPERSTORES INC
Retail
MICHIGAN POWER CO
MICHIGAN RIVET CORP
Utilities
Metal Products
USL CAPITAL CORP
UNITED SATELLITE AMER INC
Banks
Transport, Comm.
DTE ENERGY CO
Utilities
HOWELL INDUSTRIES INC
Metal Products
MILLER (HERMAN) INC
UNIVERSITY BANCORP INC
Banks
DETREX CORP
DETROIT & CANADA TUNNEL CORP
Transport, Comm.
INACOMP COMPUTER CENTERS INC Retail
INDEPENDENT BANK CORP/MI
Banks
MOTOR WHEEL CORP
MOTORS LIQUIDATION CO
UPPER PENINSULA ENERGY CORP Utilities
VSI HOLDINGS INC
DETROIT EDISON CO
Utilities
INTEGRAL VISION INC
Instruments
NETI TECHNOLOGIES INC
VOTRAX INC
DIAMOND CRYSTAL SALT CO
Food & Tobacco
INTER ACTIVE SERVICES INC
NATIONAL-STANDARD CO
VOPLEX CORP
DONNELLY CORP
DOUGLAS & LOMASON CO
INTERFACE SYSTEMS INC
INTERMET CORP
NEWCOR INC
OIS OPTICAL IMAGING SYSTEMS
WALBRO CORP
WAVEMAT INC
DOW CHEMICAL
Chemicals
INTL RESEARCH & DEV CORP
NUVISION INC
Retail
WHIRLPOOL CORP
DOW CORNING CORP
DURAKON INDS INC
Chemicals
IRWIN MAGNETIC SYSTEMS INC
J P INDUSTRIES INC
OLD KENT FINANCIAL CORP
ONCOLOGIX TECH INC
Banks
WOLOHAN LUMBER CO
WOLVERINE TECHNOLOGIES INC
Retail
ESELCO INC
Utilities
JACOBSON STORES
Retail
OXFORD ENERGY CO
Utilities
WOLVERINE WORLD WIDE
ENERGY CONVERSION DEV
ENTERTAINMENT PUBLISHING CP
Other Manufacturing
K-H CORP
KMS INDUSTRIES INC
PERRY DRUG STORES
WICKLUND HOLDING CO
Retail
Agriculture, Mining
X-RITE INC
ZONDERVAN CORP
Instruments
Other Manufacturing
F&M DISTRIBUTORS INC
Retail
KAUFMAN HW FINANCIAL GROUP
PRAB INC
FEDERAL-MOGUL CORP
KAYDON CORP
PULTEGROUP INC
Construction
Metal Products
Metal Products
Metal Products
15
Descriptive Statistics
16
Correlations
17
Descriptive Difference-in-Differences
Full models need longer windows for significant 3 way interactions; basic
MIxMARA always significant.
18
19
Coarsened Exact Matching (CEM)
• Improves covariate balance in the sample Blackwell, Iacus, King, & Porro, 2009;
Iacus, King, & Porro, 2010. For a recent example, see Azoulay et al., 2010 in QJE.
• As a result of better covariate balance, CEM generates a better
counterfactual comparison and reduces causal estimation error Iacus, King, &
Porro, 2009.
- Much less vulnerable to model mis-specification
• CEM circumvents potential problems of covariate imbalance in alternative
methods such as Propensity Score Matching Deheja, 2005; Smith & Todd, 2005.
• CEM discards observations and can result in the loss of statistical power.
• Matched on assets, liquidity, and return on assets.
20
Robustness Checks
Consistent Result: High Performing Targets
•
Acquirers sometimes target poor performers specifically to
replace management Walsh & Kosnik, 1993
•
Acquirers therefore may be:
- Less concerned about retaining employees for poor performing targets.
- More concerned about retaining employees for high performing targets.
-----------------------------------------------------------------------------|
Robust
acquired |
Coef.
Std. Err.
z
P>|z|
[95% Conf. Interval]
-------------+---------------------------------------------------------------tXa |
.8407934
.3244132
2.59
0.010
.2049553
1.476631
tXaXprf |
3.312442
1.639902
2.02
0.043
.0982929
6.526591
tXaXiss |
4.185143
1.775637
2.36
0.018
.7049586
7.665327
tXaXipp | -1.556446
.7684213
-2.03
0.043
-3.062524
-.0503681
tXaXroa |
1.36282
.6287118
2.17
0.030
.1305671
2.595072
Note: The full model specification is included in the regression, even though it is not shown here....
22
23
Non-linear interactions
•
Interpreting non-linear interactions is a current area of controversy.
Ai & Norton, 2003; Hoetker, 2007; Greene, 2010.
•
Following King et al. (2000) and Zelner (2009), we interpret our
triple-interactions based on simulated & predicted probabilities.
- Run model
- Draw sample from distribution of each coefficient estimate
- Calculate dependent variable at points of interest
- Repeat 1,000 times
- Plot histogram of outcomes and see what portion above/below 0
24
Results: Michigan * After * Knowledge Workers (H2)
The predicted probability of acquisition in Michigan by level of Knowledge Workers
−1 Std. Dev.
+1 Std. Dev.
27
The predicted diff-in-diff change in the probability of acquisition in Michigan by level of Knowledge Workers
−1 Std. Dev.
+1 Std. Dev.
28
The predicted triple-difference between the +/- 1 SD levels of Knowledge Workers
29
Results: Michigan * After * Instate Competition (H3)
The predicted diff-in-diff change in the probability of acquisition in Michigan by level of Instate Competition
30
Results: Michigan * After * Instate Competition (H3)
The predicted triple-difference between the +/- 1 SD levels of Instate Competition
31
Results: Michigan * After * IP Protection (H4)
The predicted diff-in-diff change in the probability of acquisition in Michigan by level of IP Protection
32
Results: Michigan * After * IP Protection (H4)
The predicted triple-difference between the +/- 1 SD levels of IP Protection
33
Limitations
• Anti-trust reform influences acquisitions directly.
- Null results for placebo states that implemented same reforms
• We assigned firms to treatment vs. control based on HQ state.
-
Not completely accurate, though DID measures the relative effect and results
should be conservative
• “Target-side” model prevents examination of acquirer and
transaction factors such as capabilities, learning, etc.
34
Conclusions and future work
• Noncompetes influence firm strategy.
- Particularly for human capital intensive acquisitions
• Are startups in enforcing regions less likely to grow or have IPO?
• Up next: do noncompetes influence pricing of acquisitions?
35

Employee mobility and acquisition targets

Transcription

Similar documents

REGISTRO ANTE LA FDA 2015 Bionatur Invernaderos Biologicos

ExhibitorPre-Show Sponsorship Program

announcements store promotions and events

Perform acquires Turkish digital sports media co Mackolik

AroFlo Windshield

Daleco Resources Corp.

Indonesian Diaspora Network Southern California

Beverly Hills Sheet Official Website

Trusted Specialists in Aerial Survey and Digital Mapping

Webinar presentations - National Center for Mobility Management