Reaching across Disciplines for
Corporate Strategy Research
Jeffrey J. Reuer
Agenda

Two caveats
– No need to do cross-disciplinary research
– Many ways to build theory

Very brief introduction to research agenda

Inspiration for “reaching across disciplines”
– Why information economics as a theory?
– Why IPOs?

Illustrative paper as “raw data”

Group work and discussion
– How might one “reach across disciplines” in building theory?
– What are practical guidelines for building such a research agenda?
-2-
Research Interests
Key Phenomena
Key Theories
• Alliance governance
• Information economics
• Alliance dynamics
• Real options theory
-3-
Alliance Governance
Alliance Investment Decision
Alliance Type Decision
Alliance
Design
Decision
-4-
Economics of Alliances
Exchange
Hazards
Sources
Outcomes
Timing
Williamsonian TCE
“Distance”
Search
Costs
Asymmetric
Information
•Asset Specificity
•Uncertainty
•Etc.
Adverse
Selection
•Hold-Up
•Misappropriation
•Etc.
Ex Post Hazards
Ex Ante Hazards
-5-
Coping with Information Asymmetries
•The
problem of asymmetric information
– Markets for durable goods, labor, insurance, etc. (e.g., Akerlof, 1970; Spence, 1973;
Rothschild & Stiglitz, 1976)
– Markets for corporate exchange partners?
•Accumulating
evidence on solutions:
Ownership Solutions
•Strategic Alliances
Contractual Solutions
•Contingent Earnouts
-6-
Market Solutions
•IPOs: ‘Dual Tracking’
IPOs and the Corporate Strategy Research Agenda

Under traditional views, IPOs…
IPO
– are financing choices,
– are natural “end states” for successful
entrepreneurs, and
– relax owner-managers’ wealth
constraints.

Sequential
Strategic
Choices
Alliance
M&A
Emerging evidence
– Post-IPO M&A (Pagano et al., 1998; Brau &
IPO
Market
Kohers, 2005; Brau & Fawcett, 2006)
– Going public as “marketing” (Demers &
Lewellen, 2003)
Information
Spillovers
Market
for
Partners
-7-
Product
Market
The Choice Between Joint Ventures and Acquisitions:
Insights from Signaling Theory
Joint Ventures vs. Acquisitions for IPO Firms

When do firms partner instead of acquire?
– Infeasibility
– Inflexibility
– Indigestibility
– Information asymmetry
• Alternative remedies unexamined
• Little used, mixed evidence

The impact of IPOs
– Direct reduction of information asymmetries
– Reduction of the adverse effects of information asymmetries through signaling
(e.g., Welch, 1989; Riley, 2001)
Research question:
Do heterogeneous signals affect organizational governance
(i.e., JV vs. M&A) in deals involving IPO firms?
-9-
Theoretical Framework
Exchange Partners
in M&A Market
•Diversifying entrants versus
rivals
Signals on IPO Firms
•Investment bank reputation
•Venture capitalist backing
•Others
-
Organizational Governance
•Joint venture vs. acquisition
+ JV, - Acq.
+
Facilitation of Exchanges
•Joint venture or acquisition
vs. no transactions
- 10 -
Methodology

Sampling frame
– SDC modules on US firms’ IPOs and JVs and M&A
– Timeframe: IPOs during 1986-2001
– Exclusions: REITs, investment funds, equity carveouts, LBOs,
financial services firms
– Corporate transactions:
• JVs: Domestic, two-partner, no non-equity alliance deals
• M&A: Domestic, full acquisitions, no prior equity
– Time from IPO to JV or M&A: 5 years
- 11 -
Methodology

Specification and Measures
– Dependent variable:
• Governance structure: Joint venture = 1 if JV, 0 if M&A (with sample
selection)
• Level of commitment: 0 no transaction, 1 JV, 2 acquisition; or 0 no
transaction, 1 nonequity alliance, 2 JV, 3 acquisition
– Explanatory variables
• IB reputation: Index initially developed by Carter & Manaster (1990), using
Loughran & Ritter’s (2004) data (0-9)
• VC Backing: 0/1 variable from SDC
• Knowledge distance: Employment distributions across industries and
indicators for 3-digit SICs
– Controls
• Tobins’ Q of target, knowledge distance, target underpricing, lockup
provision, exchange partner firm alliance and acquisition experience, target
size and performance, sector fixed effects
- 12 -
Results

Descriptive findings
– 15% JVs, 85% acquisitions
– 46% of the deals were inter-industry at 2-digit level (75% for JVs, 41%
for M&A)
– The likelihood of JV goes from 15 to 25 percent from smallest to
largest firm size quintiles
– The likelihood of JV is up to 3-4 times as large if a prominent I-bank is
absent
– Firms partner with VC-backed firms 8% of the time and partner with
non VC-backed firms 24% of the time
- 13 -
-0.35*
Venture capitalist (VC) backing
(0.15)
* Knowledge distance
IB reputation First-Stage
Results:
Selection Models
VC backing * Knowledge distance
-0.24*
(0.12)
-0.00
(0.07)
-0.31*
(0.12)
Selection equation variables (N=2171)
Intercept
-1.34***
(0.18)
-1.45***
(0.17)
-1.46***
(0.15)
IPO firm size
-0.05
(0.03)
-0.04
(0.03)
-0.02
(0.03)
0.18
(0.13)
0.14
(0.13)
0.07
(0.11)
-0.08
(0.07)
-0.10
(0.07)
-0.10
(0.07)
IPO firm Tobin's Q
0.00
(0.00)
0.00
(0.00)
0.01
(0.00)
Major exchange
0.28*
(0.13)
0.36**
(0.12)
0.34***
(0.10)
Pre-IPO alliances
0.08
(0.06)
0.09
(0.06)
0.07
(0.05)
-0.01
(0.05)
-0.02
(0.06)
0.04
(0.04)
Industry M&A volume
0.01
(0.04)
0.02
(0.04)
0.01
(0.05)
Industry JV volume
0.15***
(0.05)
0.14**
(0.05)
0.13***
(0.03)
IPO firm performance
Underpricing
Industry IPO volume
IB reputation
H1
0.25***
(0.06)
0.21**
(0.06)
0.20**
(0.06)
Venture capitalist (VC) backing
H3
0.18*
(0.08)
0.17*
(0.08)
0.19*
(0.07)
Model 2
103.96***
116.67***
130.68***
Wald test of independent equations (ρ=0)
0.78
5.04*
12.71***
- 14 -
Results: Second-Stage Entry Mode Models
III
II
I
Joint Venture vs. M&A choice model (N=343)
-1.93**
Intercept
(0.63)
Included
Sector fixed effects
-1.19***
Acquisition experience
0.71
(0.55)
Included
1.07***
(0.22)
Included
(0.26)
-0.71*
(0.28)
-0.47***
(0.09)
Alliance experience
0.13
(0.09)
0.07
(0.07)
0.08*
(0.04)
Target size
0.16*
(0.07)
0.13†
(0.08)
0.08†
(0.04)
Target performance
0.88†
(0.51)
0.43
(0.29)
0.37***
(0.09)
Lockup provision
0.37
(0.73)
0.29
(0.41)
0.23
(0.18)
-0.21
(0.27)
-0.04
(0.18)
-0.10
(0.09)
Underpricing
Target Tobin’s Q
0.07***
(0.02)
0.05*
(0.02)
0.03**
(0.01)
Knowledge distance
0.67***
(0.16)
0.43**
(0.16)
0.44***
(0.10)
Investment bank (IB) reputation
H2
-0.39**
(0.12)
-0.33***
(0.08)
Venture capitalist (VC) backing
-0.35*
(0.15)
-0.24*
(0.12)
IB reputation * Knowledge distance
H4
H5
-0.00
(0.07)
VC backing * Knowledge distance
H6
-0.31*
(0.12)
-1.46***
(0.15)
Selection equation variables (N=2171)
Intercept
-1.34*** - 15(0.18)
-1.45***
(0.17)
Results: Ordered Probit Models
Independent variables
I
II
DV: 0=no transaction
1=JV
2=acquisition
III
IV
DV: 0=no transaction
1=nonequity alliance
2=JV
3=acquisition
Controls and theoretical variables
Sector fixed effects
IPO firm performance
IPO firm Tobin’s Q
IPO firm size
Lockup provision
Underpricing
Included
Included
Included
Included
-0.08
(0.14)
0.01
(0.01)
0.04†
(0.03)
-2.08***
(0.13)
-0.07
(0.08)
0.11
(0.15)
0.01
(0.01)
-0.06
(0.04)
-2.08***
(0.13)
-0.15†
(0.08)
0.24***
(0.08)
0.47***
(0.09)
-0.17*
(0.08)
0.00
(0.00)
0.03
(0.02)
-1.69***
(0.07)
-0.04
(0.05)
-0.08
(0.08)
0.00
(0.00)
-0.02
(0.03)
-1.65***
(0.07)
-0.09
(0.05)
0.11*
(0.05)
0.35***
(0.06)
IB reputation
VC backing
- 16 -
Implications for Research
Search and
Discovery

Partner
Selection
Deal
Structuring
Deal
Implementation
Information costs need to be studied to:
– complement TCE to attend to ex ante exchange hazards
– address pre-formation processes (e.g., search, negotiations, etc.) prior to the
contracting stage

Information costs are closely tied to other transaction costs
– Search might be endogenous to transaction-specific investment
– Information asymmetries might lead to post-merger integration challenges
– Problems due to hidden information (i.e., adverse selection) and hidden action
(i.e., moral hazard) often go hand-in-hand
- 17 -
Group Discussion
How can one “reach across disciplines” in management
research?
What are some good (or bad) ways of doing so?
What are some practical tips for developing a research
agenda?
Any Q&A
How Can One Reach Across Disciplines
and Build a Research Agenda?
•
Two problems in grad school…
• “Reading SMJ to write for SMJ”
• “Integration”
•
Inspiration through importation
• You can use stepping stones (e.g., corporate finance)…
• Read the giants in the core discipline (e.g., economics) (see next
slide)
• Concrete puzzles and business problems (e.g., “putting a company on
the tee”)
•
Analogical reasoning (e.g., used car market)
•
Turn the tables on yourself (e.g., boundary conditions for the theory,
drawbacks, etc.)
•
The need for contextualization of the theory
- 19 -
Contextualizing the Theory
•
The opportunism assumption
– resource misrepresentation versus ex post hazards
– due to incentives created by terminal transactions
•
Transactions are embedded in different contexts (e.g.,
nations, cultures, relationships, etc.)
•
Contexts as a source of information asymmetry (e.g.,
Deloitte study of M&A in emerging markets)
•
Contexts as a locus of remedies to information asymmetry
(e.g., asocial (e.g., contracts) or social (e.g., interpersonal
networks, trust, endorsements, etc.)
- 20 -
Relationship between Information Economics and TCE
•
Occasional reviewer comments:
– This is not theory
– This is just TCE
•
What would Williamson say?
– Williamson (1975), Markets and Hierarchies: “information impactedness”
appears on 41 pages (vs. 57 for “opportunism”)
– Williamson (1985), The Economic Institutions of Capitalism: “information
asymmetry” on 11 pages
– Williamson (2005, footnote 4): “[t]he economics of information also deals with
contractual hazards, but mainly of a different kind than those dealt with [in
TCE]. Thus, where insurance is the paradigm problem for the economics of
information, vertical integration is the paradigm problem for [the] governance
[branch].”
– Williamson (2002: 178): “Because transactions in intermediate product markets
avoid some of the more serious conditions of asymmetry – of information,
burden, legal talent, risk aversion and the like – that beset some transactions in
final product markets, I examine the ‘make
or buy’ decision.”
- 21 -
Contextualizing the Theory
•
New predictions for JV (+) vs. M&A (-): Variables “claimed”
by TCE and IE
Illustrative
Variable
TCE
IE
Technological
overlap
-
-
Prior ties
+
-
Geographic
clusters
+
-
- 22 -
How Can One Reach Across Disciplines
and Build a Research Agenda?
•
Practical hints
• Think about where you will get inspiration in concrete terms
• Focus: Research as making toast
• “Sharpen the saw”
• Who is the reader? The conversation has to be a management
conversation
Darkness
time
- 23 -