# Presentation: 863369

## 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

## Overview

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

## 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

## 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 1980’s, there has been a tremendous growth in strategic alliances and a corresponding increase in research interest

## 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

## 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 SA’s in 2001 (Schifrin 2001)

## 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?

## 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

## Cardiology VCC’s in 1999

## 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

## Conceptual Framework

## Benefits

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

## 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

## 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)

## 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

## 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

## 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.*

## Competition

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

## 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.

## 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)

## 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

## Empirical Study

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

## 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)

## 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

## 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

## 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

## 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

## Model Formulation

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

## 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

## Overall Model Results

- Model fit v. null
- Χ2=1781.85, d.f.=5, p<0.001
- Errors in choice and commitment models were significantly correlated
- ρ=0.51, Χ2=239.53, d.f.=1, p<0.001

## Estimation Results

| Model | Variable | Coefficient | p | Expected Sign |
| --- | --- | --- | --- | --- |
|  |  |  |  |  |
|    Choicepqt | Social capital | 7.1e-07 | 0.05 | + (H1) |
|   | Past experience | 3.16 | 0.001 | + (H3) |
|  | Opportunity costs | -0.01 | 0.001 | - (H5) |
|   | Presence of Competitor | 0.02 | 0.502 | - (H7) |
|   | Attraction of Competitors | 0.01 | 0.001 | + (H9) |
|   | 
Constant  | -1.60 | 0.001 |  |
|  |  |  |  |  |
|   Commitmentpqt | Social capital | 2.9e-05 | 0.001 | + (H2) |
|   | Past commitment | 0.71 | 0.001 | + (H4) |
|   | Opportunity costs | -0.01 | 0.001 | - (H6) |
|  | Competitor Commitment  | 0.06 | 0.001 | + (H8) |
|   | Attraction of Competitors | 0.01 | 0.078 | + (H10) |
|   | Constant | 0.52 | 0.001 |  |

## 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

## 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

## 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

## 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

## Attraction to Competitors

- Distance to nearest competitor has marginally negative (p < 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

## 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

## Alternative positioning 

- Inwoo’s 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

## 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

## Choice Model

-   if

-    if

*Z**pqt **  *= 1, if firm *p* forms a strategic alliance with a partner *q* at time t
-         = 0, otherwise.

## Commitment Model

*Y**pqt*  = level of commitment from firm *p* to a partner *q* at time *t*

- if   *Z**pqt *= 1

- not observed  if *Z**pqt *= 0

## Key estimation issue