Same As it Ever Was: The Search for Hypercompetition

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BADM 551, MT1Law, Technology and Intellectual
Property
Paul M. Vaaler Associate Professor of
International Business Department of Business
Administration College of Business University of
Illinois at Urbana-Champaign
Session 12 Competition Policy and IPM
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Are Technology-Intensive Industries More
Dynamically Competitive? No and Yes
Paul M. Vaaler Associate Professor of
International Business College of
Business University of Illinois at
Urbana-Champaign, Illinios, USA pvaaler_at_uiuc.edu
Gerry McNamara Associate Professor of
Management Broad School of Management Michigan
State University, East Lansing, Michigan,
USA mcnamara.gerry_at_msu.edu
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Research Question Background

• Fundamental Strategy Question How Do We Explain
  Differences in Firm Performance?
• IO Economics Stable industry factors (Bain,
  1956 Porter, 1979)
• Corporate Strategy Stable corporate portfolio
  benefits and managerial actions (Chandler, 1962
  Montgomery, 1979)
• Business Strategy Stable, business-level
  idiosyncratic resources and positioning effects
  (Porter, 1980 Wernerfelt, 1984 Barney, 1991)
• Hypercompetitive Perspective Unstable markets,
  entrepreneurial advantage, adroit management of
  fluid, short-term factors in increasingly
  volatile markets (DAveni, 1994 Thomas, 1996
  Hamel, 2000)

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Increasingly Hypercompetitive Industries

• Driven by Exogenous and Endogenous Factors,
  Industries Have Become more Hypercompetitive
  (DAveni, 1994, 1995)
• Within These Industries, There Will Be
• Increased boldness in action, including attacks
  on industry leaders and the redefinition of
  markets and products
• More frequent and intense competitive
  interactions
• Increased emphasis on speed in strategic actions
• Focus on mobile and or substitutable resources
• Outcome Firms are Increasingly Less Able to
  Establish Sustainable Advantages. Instead, they
  Increasingly Act to Create Temporary Advantages
  and Erode the Advantages of Rivals

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Prior Findings

• Scant Broad-Based Evidence of Increasing
  Hypercompetition
• Supporting case study, specific industry, short
  time period research on dynamic industries
  (DAveni, 1994, 1995 Robins Wiersema, 2000
  Rindova Kotha, 2001)
• Less supporting evidence of any broader
  hypercompetitive shift. Some evidence
  suggesting shift in pattern of rivalry and
  profitability in select manufacturing industries
  (Thomas, 1996 Wiggins and Ruefli, 2005)
• Evidence of increasing dynamism not confirmed in
  a broad set of industries (Castrogiovanni, 2003
  McNamara, Vaaler, Devers, 2003)
• But What About the Possibility that Increasing
  Hypercompetition Is a More Limited Phenomenon?

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The Role of Technology and the Most Affected
Industries

• Researchers in Management, IO and Antitrust
  Economics Have Identified Technology as a Key
  Driver of Increased Dynamism in Markets
• New Competitive Landscape Driven by a
  Technological Revolution (Bettis Hitt, 1995)
• Technological change leading to a
  neo-Schumpeterian era where firms need to
  innovate continually (Garud Karaswarmy, 1995)
• Heightened turbulence in information,
  communications, and other technology-related
  industries (Chakravarthy, 1997)
• New processes for high-velocity,
  technology-driven industries (Brown Eisenhardt,
  1998)
• Industries experiencing rapid changes in
  contextual factors such as technology (Bogner
  Barr, 2000)

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The Role of Technology and the Most Affected
Industries

• IO and Antitrust Economics and Increasing
  Dynamic Competition
• Schumpeterian dynamic competition (Schumpeter,
  1912 1942)
• Innovation-based competition threatening to sweep
  away leading firms, transforming industries and
  advancing national economic development
• Recent IO and antitrust views (Technology-based
  competition generating red queen effects
  (Khalil, 1997 Posner, 2000 Schmalansee, 2000
  Ahlborn, Evans, Podilla, 2001 Evans
  Schmalansee, 2001 Baumol, 1993 2002)
• Modern dynamic competition Technology-based
  competition for markets (rather than price and
  output-based competition within markets)
• Implications Knowledge-based competition
  battles over tech standards episodic winner
  take all or most battles for markets
  temporarily extremely profitable winners
  red-queen effects where firms have to innovate
  faster just to keep up
• Policy responses Less antitrust oversight
  certify industries as high-tech and have no
  antitrust oversight belief in the
  self-equilibrating market

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The Central Research Question

• Do We See Evidence of the Consequences of
  Increasing Hypercompetition in Technology-Intensiv
  e Industries (Dynamic Competition)?
• Evidence of increasing competitive dynamics over
  time (longitudinal evidence in TI industries)
• Evidence of higher competitive dynamics relative
  to other industries (cross-sectional evidence
  comparing TI to non-TI industries)

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Logical Consequences of Hypercompetition in TI
Industries

• Higher General Industry Dynamism
• Lower Persistence of Abnormal Performance
• Lower Persistence of Market Share Leadership
• Higher Mortality (Exit) Rates

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Increasing General Industry Dynamism

• Rapid Rise, Maturity, and Obsolescence of
  Technologies Leads to Greater Industry Dynamism
  (Chakravarthy, 2001)
• Rapid Role Out, Imitation, and Replacement of New
  Products and Services Results in Boom and Bust
  Cycles in Industries (Schumpeter, 1912 Agarwal
  Gort, 2001 McKnight, Vaaler, Katz, 2001)
• H1a TI industries will exhibit greater dynamism
  over time.
• H1b TI industries will exhibit greater dynamism
  than non-TI industries.

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Decreasing Persistence of Abnormal Performance

• Lower Barriers to Entry to and Imitability within
  Industries (DAveni, 1994)
• Deregulation
• Capital market changes
• Disintermediation due to technology advances
• Increased use of alliances
• Increase in Technological Change and Diffusion
  (Garud Karaswarmy, 1995)
• Shorter Product Life Cycles and Quicker Imitation
  (Agarwal Gort, 2001)
• Increasingly Frequent Winner Take Most Battles
  (Evans Schmalansee, 2001)
• H2a Abnormal business returns in TI industries
  will erode more quickly over time.
• H2b Abnormal business returns in TI industries
  will erode more quickly than for firms in non-TI
  industries.

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Decreasing Persistence of Market Share Leadership

• Lower Barriers to Entry to Industries (DAveni,
  1994)
• Shorter Product Life Cycles and Quicker Imitation
  of First Movers (Agarwal Gort, 2001)
• More Frequent and Bolder Attacks on Industry
  Leaders Requiring Response (or Leading to
  Dethronement) (DAveni, 1994 Ferrier et al.,
  1999)
• Increasingly Frequent Winner Take Most Battles
  (Evans Schmalansee, 2001)
• H3a The likelihood that market leading firms in
  TI industries are supplanted from one year to the
  next will increase over time.
• H3b The likelihood that market leading firms in
  TI industries are supplanted from one year to the
  next is higher than for leading firms in non-TI
  industries.

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Increasing Firm Mortality Rates

• Dramatic Environmental Changes Resulting in
  Sudden Obsolescence of a Firm Resources and
  Threatening Survival (Hannan Freeman, 1977,
  1984 Tushman Anderson, 1986)
• Technological Change Resulting in Industry
  Over-Supply and Increased Firm Mortality
  (Christensen, 1997)
• Winner Take Most Battles Resulting in Large
  Number of Distressed Firms (Posner, 2000, 2001)
• H4a Mortality rates for firms in TI industries
  will increase over time.
• H4b Mortality rates for firms in TI industries
  will be greater than for firms in non-TI
  industries.

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Research Methods

• Sample Drawn from Compustat Industry Segment
  Database 14,000 obs from 2800 BUs Operating in
  31 Industries with High RD Intensity Covering
  1978-1997 Period
• Hypotheses Evaluated Two Ways 1) TI Industries
  Alone (Longitudinal) and 2) TI Industries
  Compared to Non-TI industries (Cross-Sectional)
  
• Analytical Models Hypotheses Testing
  Predicted Trend
• OLS Regression General Industry
  Dynamism Positive
• Autoregressive Model Persistence of Abnormal
  Returns Negative
• Logistic Regression Persistence of Above
  Average Returns Negative
• Logistic Regression Persistence of Market
  Leadership Negative
• Hazard Rate Model Mortality (Industry Exit)
  Rate Positive

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Industry Dynamism Analysis

• Analytical Model Hypotheses Testing
  Predicted Trend
• OLS Regression General Industry
  Dynamism Positive
• Dependent Variable Variability in industry
  sales over a five-year window (longitudinal) or
  over the entire study period (cross-sectional)
  (Dess Beard, 1984)
• Control Variables Industry dummy variables
  (longitudinal analysis)
• Hypothesized Variables
• Time period dummy variables (longitudinal
  analysis)
• TI industry dummy variable (cross-sectional
  analysis)

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Industry Dynamism Results

• Results No significant positive time trend in
  TI industries, nor differences between TI and
  non-TI industries. But adding two additional
  controls (average industry sales, number of years
  reported in Compustat database) yields evidence
  of cross-sectional differences (TECHi 0.012 and
  t-value is 77.14).

Compared to Non-TI Industries
TI Industries Over Time
Variables
Time Period 1 (1978-1982) -0.0281
(0.0604) Time Period 2 (1983-1987)
0.0028 (0.0485) Time Period 3 (1988-1992)
0.0383 (0.0485) TI Industry (TECHi)
-0.0152 (0.0095)
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Autoregressive Analysis

• Analytical Model Hypotheses Testing Predicted
  Trend
• Autoregressive Model Persistence of Abnormal
  Returns Negative
• Dependent Variable ROA in year t (ROAjt)
• Control Variables ROA in year t-1 (ROAjt-1),
  industry structure (HHI), GDP growth, inflation,
  time counter, TI industry dummy (cross-sectional)
• Hypothesized Variables
• Interaction of year counter variable and lagged
  ROA (longitudinal analysis)
• Interaction of TI industry dummy variable and
  lagged ROA (cross-sectional analysis)

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Autoregressive Results
Results No evidence that abnormal returns are
less persistent in TI industry businesses over
time. Compared to non-TI industry businesses, TI
businesses have lower returns, but increasingly
more (positive) stable year-to-year performance.
TI Industries Over Time
Compared to Non-TI Industries
Variables
Year Interaction (ROAjt-1YEAR)
-0.0005 (0.0014) TI Industry Dummy
(TECHi) -0.0140 (0.0012) TI Industry
Interaction (ROAjt-1TECHi) 0.0524 (0.0
033)
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Performance Persistence Analysis

• Analytical Model Hypotheses Testing Predicted
  Trend
• Logistic Regression Persistence of High
  Returns Negative
• Dependent Variable Variable indicating whether
  or not a business sustained a certain performance
  level from one year to the next (Ruefli
  Wiggins, 2005)
• ROA above industry average
• ROA 1 standard deviation above industry average
• ROA 2 standard deviations above industry average
• ROA 3 standard deviations above industry average
• Control Variable Industry structure (HHI), GDP
  growth, inflation (as before)
• Hypothesized Variables
• Year counter variable (longitudinal analysis)
• TI industry dummy variable (cross-sectional
  analysis)

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Performance Persistence Results

• Results Mixed. Above average business returns
  more persistent in TI Industries, but the
  sustainability of very high business returns
  lower in TI Industries and over time.
• Above-Average
• Variables Performance 1 STD 2 STD
  3 STD
• TI Industries over time
• Year Counter (YEARt ) 0.0452 0.0145
  -0.0744
• (0.0083) (0.0147) (0.0379)
• Compared to Non-TI Industries
• TI Industry (TECHi) 0.1082 -0.0514
  -0.2684 -0.8635
• (0.0341) (0.0596) (0.1450)
  (0.3123)

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Persistence of High Performance of TI Firms
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Market Leader Persistence Analysis

• Analytical Model Hypotheses Testing
  Predicted Trend
• Logistic Regression Persistence of Market
  Leadership Negative
• Dependent Variable Variable indicating whether
  or not business with the largest industry sales
  base in one year sustained it in the next year
• Control Variable Industry concentration (HHI)
• Hypothesized Variables
• Year counter variable (longitudinal analysis)
• TI industry dummy variable (cross-sectional
  analysis)

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Market Leader Persistence Results

• Results No significant negative time trend.
  Also, no evidence that market share leadership is
  more difficult to sustain in TI industries
  compare to other industries.

Compared to Non-TI Industries
TI Industries Over Time
Variables
Year Counter (YEARt) -0.0083 (0.0204) TI
Industry (TECHi) -0.0782 (0.1079)
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Market Leader Persistence Over Time
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Mortality Analysis

• Analytical Model Hypotheses Testing Predicted
  Trend
• Hazard Rate Model Mortality (Industry Exit)
  Rate Positive
• Dependent Variable Variable indicating whether
  or not business in existence in one year remained
  in existence in the following year
• Control Variables Industry density, Density2,
  Value of MA activity in year t
• Hypothesized Variables
• Year counter variable (longitudinal analysis)
• TI industry dummy variable (cross-sectional
  analysis)

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Mortality Results

• Results No significant positive time trend.
  Also, no evidence that mortality is greater in TI
  industries compare to other industries.

Compared to Non-TI Industries
TI Industries Over Time
Variables
Year Counter (YEARt) -0.0035 (0.0023) TI
Industry (TECHi) -0.0075 (0.0095)
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Mortality Rate Over Time
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Research Conclusions and Implications

• Is Dynamic Competition Greater in TI Industries?
  No (and maybe) Yes.
• No Support for the Assertion of Broadly
  Increasing Hypercompetition within TI Industries
• Some Support for the Assertion that TI Industries
  Are Significantly More Hypercompetitive than
  Non-TI Industries
• Some (a Little) Support for Assertion of
  Increasing Hypercompetition within TI Industries,
  but Only in a Narrow Strata of Very hHigh (But
  Not High or Highest) Performing TI Industries
• A fringe theory to explain increasingly
  challenging conditions for winning firms in TI
  industries?
• We should know better

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Limitations and Future Research

• If Only We Had Done Another Test
• If Only We Had Done the Same Tests in Another
  (More Recent) Time Period Or With The Right
  Sample
• If Only We Had Thought About Dynamic
  Capabilities
• For the Future Closer Look At Causal Chains
  linking industry conditions, firm actions, and
  performance consequences for top performing firms
• Moving in and out of periods of heightened
  competitive dynamics
• Causes of differential impact at varying
  performance levels
• For the Future The Role of Cognition in the
  Dynamics of Industries
• Managerial perceptions
• Perceptions of other stakeholders (e.g.,
  investors and analysts)

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Are Technology-Intensive Industries More
Dynamically Competitive? No and Yes
Thank You!
Paul M. Vaaler Associate Professor of
International Business College of
Business University of Illinois at
Urbana-Champaign, Illinios, USA pvaaler_at_uiuc.edu
Gerry McNamara Associate Professor of
Management Broad School of Management Michigan
State University, East Lansing, Michigan,
USA mcnamara.gerry_at_msu.edu