Benefits, Costs and Competition: Determinants of Strategic Alliance Partner Selection

1
Benefits, Costs and Competition Determinants of
Strategic Alliance Partner Selection Commitment
Decisions

• Inwoo Nam
• Nanyang Business SchoolThomas S. Gruca
• Tippie College of Business
• Roger Tracy
• Office of Statewide Clinical Education
  ProgramsRoy J. and Lucille A. Carver College of
  Medicine
• CHPR-CRIISP Seminar Series
• November 4th 2005

2
Overview

• Background
• Conceptual Framework
• Hypotheses
• Empirical Study
• Setting
• Measures
• Model
• Results
• Conclusions

3
Background

• Visiting Consulting Clinics
• Specialist physician travel to rural hospitals to
  meet with patients and consult with local
  physicians
• Data collected by Office of Statewide Clinical
  Education Programs
• Collected continuously since 1988
• Phone survey of hospitals every year
• Covers multiple specialties
• Track origin city, specialty practice and
  specific doctors
• Only data set of its kind
• Previously described in two articles in Health
  and Hospital Administration
• Tracy, et al. 1996
• Wakefield, et al. 1997

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Strategic Alliances

• relatively enduring inter-firm cooperative
  arrangements, involving flows and linkages that
  use resources and/or governance structures from
  autonomous organizations, for joint
  accomplishment of individual goals linked to the
  corporate mission of each sponsoring firm."
  (Parke 1993)
• Since the 1980s, there has been a tremendous
  growth in strategic alliances and a corresponding
  increase in research interest

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Strategic Alliance Characteristics

• Narrow range of organizations and settings
• Purpose organizational learning or provide
  access to markets
• Ownership equity v. non-equity
• Industry manufacturing v. services
• Study scope cross-sectional v. longitudinal

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Strategic Alliance Research

• Two major areas
• Who enters into these arrangements
• Perceptions of performance
• Only 4 studies look at partner selection
• Two are studies of hypothetical choices
• Commitment is seen to be key to SA success
• Studies on commitment perceptions or intentions
• Organizations have multiple SA partners
• Firms with sales over 2 billion had an average
  of 138 SAs in 2001 (Schifrin 2001)

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Primary Research Questions

• How do firms choose their strategic alliance
  partners?
• Only study (Guliati 1995) was limited to largest
  firms in the industry
• How do firms determine their level of commitment
  across multiple SA partners?

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Our study setting Visiting Consulting Clinics
(VCC)

• Participants
• Specialist physicians from urban areas
• Hospitals in rural areas
• Urban specialists travel on a set schedule to a
  rural hospital
• Provide limited range of on-site diagnostic and
  treatment services
• Consult with local doctors
• More complex cases are treated at urban hospital
• Much more detail in Tracy, et al. 1996

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Cardiology VCCs in 1999
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VCC as a Strategic Alliance

• Non-equity agreement that is reviewed by both
  parties every year.
• Urban specialists may have VCC arrangements with
  multiple rural hospitals
• Rural hospitals may have VCC arrangements with
  multiple urban practices in the same specialty
• Multiple VCC arrangements introduces competition
  into decisions

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Conceptual Framework
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Benefits

• In learning SAs, the benefits depend on your
  partners social capital linkages to other
  firms
• For market access SAs, social capital of
  interest is partners linkages with its customers
• SA leverages those relationships
• More extensive networks of customers are more
  attractive

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Hypotheses 1 2

• H1 A firm is more likely to form a strategic
  alliance with a partner that has higher levels of
  social capital.
• H2 Given that a firm has chosen its strategic
  alliance partners, the firm will commit more of
  its resources to a partner that has higher social
  capital.
• Cost benefit analysis balancing potential returns
  and current commitment costs

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Stability

• Organizations are interested in stable flows of
  resources (Pfeffer and Salancik 1978)
• Continued interaction increases trust (Gulati
  1995) and reduces opportunistic behaviors (Parkhe
  1993)

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Hypotheses 3 4

• H3 A firm is more likely to form a strategic
  alliance with a partner with which it had a
  strategic alliance in the past.
• H4 Given that a firm has chosen its partners,
  the current level of commitment is positively
  related to the level of commitment in the past.
• Invest in the relationship in order to signal
  intent to continue in the SA

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Costs

• Opportunity costs
• First type is associated with benefits from
  partnering with another
• Second type involves resources dedicated to a
  given SA relationship
• Resources could be used for another purpose
• Risk aversion suggests choosing partners with
  lower opportunity costs

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Hypotheses 5 6

• H5 A firm is more likely to form a strategic
  alliance with a partner with lower opportunity
  costs.
• H6 Given that a firm has chosen its partners,
  the firm will commit more to a partner with lower
  opportunity costs.

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Competition

• Not addressed in previous research
• Firms prefer to not share a partners resources
  with another firm
• If a potential SA partners is already in an
  arrangement with a competitor, it will be less
  attractive.

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Hypotheses 7 8

• H7 A firm is less likely to form a strategic
  alliance with a partner which has already formed
  strategic alliances with competitors.
• H8 Given that a firm has chosen its partners,
  the firm commits more to a partner to whom the
  competitors committed more in the past.
• Partner plays off one competitor against another
  in attracting resources.

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Attractiveness of Competitors

• Partners have a choice in forming the SA
• If a competitor is more attractive, the partner
  may terminate SA (or form additional SA)

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Hypotheses 9 10

• H9 When strategic alliances can be easily formed
  and terminated, a firm is less likely to form a
  strategic alliance with a partner that is highly
  attracted to a competitor.
• H10 Given that a firm has chosen its partners,
  the firm commits less to partner that is highly
  attracted to a competitor.
• Uncertainty about future reduces current
  commitments

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Empirical Study

• Setting Iowa 1989-2001
• Cardiology specialty practices in 18 urban areas
  in Iowa
• More than 100 rural hospitals
• Rapid growth
• 1990 82 VCCs in 66 communities
• 2001 159 VCCs in 98 communities
• Visits per year grew from 1518 to 5300

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Overview

• Model choice and commitment decisions for Iowa
  based cardiology practices from 1990-2001
• Choice f(social capital, past experience,
  opportunity costs, presence of competitors and
  attraction to competitors)
• Commitment f(social capital, past commitments,
  opportunity costs, commitments by competitors and
  attraction to competitors)

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Dependent Variables

• Choice (yearly)
• Presence of a VCC arrangement between a given
  urban specialty practice and a rural hospital
• Commitment (yearly)
• Number of visits by urban practice to rural
  hospital per month
• Total of 1484 VCC arrangements during that time
  period

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Independent Variables Benefits

• Social capital
• Rural hospital patient base
• County population as a proxy
• Past experience commitment
• From prior year
• Arrangements are reviewed often
• Some last only one year, some for many years
• 30 last five years or more

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Independent Variables Costs

• Opportunity costs
• Specialty physician services are an inseparable
  service
• Opportunity costs depend on time spent traveling
  to rural hospital
• Used Euclidean distance as a proxy

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Independent Variables Competition

• Presence of competitor
• Indicator of VCC arrangement between rural
  hospital and competitor in prior year
• Competitor commitment
• Sum of all visits to rural hospital from
  competing urban practices in prior year
• Attraction to competitors
• Distance to nearest competitor

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Model Formulation

• Key issue Commitment is observed only when
  Choice 1
• Affects estimation of coefficients of Commitment
  model.
• Used generalized Tobit model
• Amemiya, 1984

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Sampling

• Restricted set of possible partners (rural
  hospitals) to 100 mile radius
• Average round trip is 2 hours
• Wakefield, et al. 1997
• Compared to synthetic retrospective sampling
• Found comparable results

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Overall Model Results

• Model fit v. null
• ?21781.85, d.f.5, plt0.001
• Errors in choice and commitment models were
  significantly correlated
• ?0.51, ?2239.53, d.f.1, plt0.001

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Estimation Results
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Social Capital Past Experience

• Social capital has a significant positive
  influence on choice and commitment
• Support for Hypotheses 1 2
• Significantly more likely to choose partner that
  you had chosen in the past
• Support for Hypothesis 3

33
Past commitment level

• Past commitment are positively related to current
  commitment level
• Compared number of visits year over year
• Significantly higher (paired t 7.1)
• Same or higher year over year in 80 of cases
• Support for Hypothesis 4

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Opportunity Costs Presence of Competitors

• Choice likelihood and commitment are negatively
  affected by opportunity costs
• Support for Hypotheses 5 6
• Presence of competitors does not affect
  likelihood of choice
• Do not support Hypothesis 7

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Competitor Commitment

• Competitor commitment has a positive influence on
  commitment decisions
• Rural hospitals with multiple cardiology VCC
  arrangements have significantly higher number of
  visits (6.4 vs. 2.86, t 5.4)
• Support for Hypothesis 8
• Leverage the competition between cardiology
  practices

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Attraction to Competitors

• Distance to nearest competitor has marginally
  negative (p lt 0.078) influence on choice
  likelihood
• Could be institutional pressure to avoid direct
  competition
• Limited support for Hypothesis 9
• Negative effect on commitment
• Past commitments time sunk costs
• Less attractive partner
• Support for Hypothesis 10

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Conclusions

• Benefits and costs are key to SA decisions
• Cannot tease out which is more important
• Better understanding of choice commitment
  decisions
• Competition
• Missing piece Performance

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Alternative positioning

• Inwoos approach in thesis
• Spatial diffusion of professional services
• Reach and frequency are the dependent variables
• Hierarchical vs. neighborhood diffusion
• Competitive effects due to multiple origination
  points

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What else have we learned?

• Can take a lot of time and effort to get data
  into format suitable for analysis
• Original VCC data was in print form
• Health care is not motivation for the study
• Theory / findings should generalize to other
  types of organizations
• Look for leverage points of data
• Know who was and was not chosen
• Longitudinal

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Choice Model
Zpqt 1, if firm p forms a strategic alliance
with a partner q at time t 0,
otherwise.

if
if
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Commitment Model
Ypqt level of commitment from firm p to a
partner q at time t

if Zpqt 1
not observed if Zpqt 0
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Key estimation issue