An Action Sequencing-based View of Dynamic Competitive Interaction

WALTER J. FERRIERUniversity of Kentucky

November 1999

Firm A’sActions

Firm B’sActions

CompetitiveInteraction

CompetitiveOutcomes

IndustryCharacteristics

OrganizationalCharacteristics

EventDyad 1

EventDyad 2

EventDyad 3

EventDyad 4

Actor 1

Actor 2

Prior Studies: Action-Reaction Dyads

time

Action Char. Irreversibility Magnitude Radicality

Reaction Char. Likelihood Type Speed

Actor 1

Actor 2

Prior Studies: Action Repertoires

time

Firm Performance Profitability Sales growth Market share

Ye

ar-E

nd

Me

as

ure

s

Repertoire Char. Total actions Simplicity Avg. Timing

a b c d e f g h

8

7

6

5

4

3

2

1

Sequential Competitive Interaction ?

This Sequence:

Black: Knight b4

White: Pawn c3

Black: Bishop g4

White: Queen b5

Black: Pawn c5

Named Sequences:

Epaulette’s Mate

Sicilian Defense

Sequences in Strategy Research?

Ordered sample of things – Temporal orderliness among elements

Logically unified sequence– Succession of market-based decisions

Patterns in stream of behaviors Coordinated series of actions Actions in a sequential strategic thrust

Event Sequence 1

Event Sequence 2

Action Sequences

time

Sequence Structure

Predictability Complexity Timing Duration

Firm Performance

Profitability Sales growth Market share

Competing Forces for Strategic Change and Adaptation

Timing

Predictability

Action Type(s)

EnablingEnablingForcesForces

ConstrainingConstrainingForcesForces

Rival’s Actions

Industry Growth

Barriers to Entry

Rival’s Actions

Industry Growth

Barriers to Entry

Factors Influencing Sequence Structure

TMT Heterogeneity

Slack Awareness

Motivation

Ability

Complexity

Unpredictability

Differentiation

ResponseTiming

Duration

Firm Performance:

Sales Growth

Profitability

Sequence Structure and Performance

Sequence Structure:

Complexity

Unpredictability

Differentiation

Fast ResponseTiming

Long Duration

Sample and Data

Matched pairs:– Single-/Dominant-business firms (S.R. > .70)

– U.S. market share leaders and challenger (No.2)

– 1987-1993 Cross-sectional time series panel Actions:

– News reports in F&S Predicasts, 1987-93– Structured content analysis– Reliable set of key words

Action Sequence

Ordered sample of action events

Time

Competitive actions: – Externally-directed, specific, observable moves

• Smith, Grimm, Gannon & Chen, 1991• Miller & Chen, 1996• Hambrick, Cho & Chen, 1996• Young, Smith & Grimm, 1996• Ferrier, Smith & Grimm, 1999

Definitions of Action Types

Action Type

Keyword Example of News Headline

Pricing Price, rate, rebate discount

FedEx offers rate discount on 2nd-day service.

Marketing Ads, promote, spot, campaign

United ads to counter American’s campaign.

Product Introduce, launch, unveil, rolls out

Merck introduces Mevacor to cut cholesterol.

Capacity Raises, boosts, ups, increases

Mobil raises lube stock capacity 10%.

Service Service, warrantee, guarantee

Sears offers KidVantage frequent buyer warrantee program.

Signaling Vows, promises, aims, says, seeks

Reebok’s Fireman vows to retake #1 spot.

Sequence Structure

Elemental Complexity– Herfindahl Index of within-sequence action

diversity– Low Scores: Complex sequence– High Scores: Simple sequence

MKT MKTPRICE SIGMKT PROD PRICE

Time

MKT MKTPRICEMKT PROD PRICE

Time

MKT MKTPRICE SIGPROD PRICE

Sequence 1

Sequence 2

MKT

Unpredictability (focal firm) Differentiated (vis-à-vis rival firm)

– Optimal Matching: Index of resemblance of two sequences, INDEL costs

– High scores: Sequences are different– Low scores: Sequences are similar

Inter-sequence Dissimilarity

Sequence Chronology

MKT MKTPRICEMKT PRICE

SVCPRODRival Firm

(a) (a)

(b)

Time

Focal Firm

Average Sequence Duration (a)– Greater No. days: Firm sustains attack

Average Sequence Response Lag (b)– Smaller No. days: Firm fast to respond/attack

TMT Heterogeneity Variables

Educational Background– Blau’s index of heterogeneity for degree types

(BBA, BSME, JD, etc.)

Industry Tenure – Coefficient of variation of TMT members’ years

spent in the focal industry

Data Source: D&B Reference Book of Corporate Management, 1987-93

Industry Variables

Industry Growth– Simple growth rate yeart yeart+1

Industry Concentration– Herfindahl index

Barriers to Entry– Sum of industry means for R&D, SG&A, and total

assets

Data Source: COMPUSTAT Industry Segment Files, 1987-93

Influence of Firm and Industry Characteristics on Sequence Structure

UnpredictabilityElemental

ComplexitySequence

DurationSequence

Response Lag

Rivalrous Differentiation .1005 † .0033 .0561 -.0901 †

Educational Hetero. -.1859 ** -.1054 † -.0047 -.3268 ***

Industry Tenure Hetero. .0919 .1854 ** -.1177 † -.0305

Slack .0325 -.3179 *** .1877 * .2177 **

Barriers to Entry -.1523 * .0510 .0884 .0045

Industry growth -.2302 ** -.0514 -.0111 .0130

R-square = .096 .142 .049 .163

F = 2.792 ** 4.324 *** 1.363 5.077 ***

Rivalry and Sequence Structure

Similar Differentiated

Extent of Rivalrous Differentiation

UnpredictableFaster Timing

TMT Heterogeneity and Sequence Structure

Homogeneous Heterogeneous

Extent of TMT Heterogeneity

UnpredictableComplexity

Industry Heterogeneity

Educational Heterogeneity

Industry Context and Sequence Structure

Low GrowthLow Barriers

Unpredictable

High GrowthHigh Barriers

Influence of Sequence Structure on Performance

ROSModel 1

ROSModel 2

SalesGrowthModel 3

SalesGrowthModel 4

Unpredictability .0089 .8322 *** .0702 † .2042

Unpredictability Squared -.8495 *** -.1324

Differentiation .1345 * -.1459 .0274 -.4856 *

Differentiation Sq. .2818 .5296 *

Elemental Complexity .0705 .6303 ** .1780 ** .2922 †

Elemental Complexity Sq. -.5644 * -.1501

Sequence Response Lag -.0493 -.0748 .0636 .0604

Sequence Duration .0877 † .0593 .0108 .0081

Adjusted R-square = .013 .074 .222 .227

F = 1.318 2.413 ** 7.620 *** 6.231 ***

Strategic Repertoire Complexity and Performance

Performance

Simple Complex

Extent of Elemental Complexity

Strategic Unpredictability and Performance

Performance

Routine Erratic

Extent of Sequence Predictability

Strategic Pattern Differentiation and Performance

Performance

Similar Different

Extent of Sequence Differentiation

Duration of Strategic Attack and Performance

Performance

Short Sustained

Extent of Subsequence Duration

FocalFirm

Rival Firm

Conclusions:Sequence Matters

Sequence Structure

Predictability Complexity Timing Duration

Firm Performance

Profitability Sales growth Market share

UpperEchelons

Learning& Change

CompetitiveDynamics

ActionSequences

Implications:Synthesized Perspectives

Sequence Applications...

LANGUAGE:

BOXING: DNA:

qcheaTiueissesne. hsiT si a cesneueq.

This is a sequence.

Jab...Jab…Uppercut

CA

GT

AC

AT

AG

TA

CG

AT

AC

GA

MUSIC:

COMPUTER PROGRAM:

data actions2; subj = _n_; do i = 1 to max; output = matrix; end;run;