An Action Sequencing-based View of Dynamic Competitive Interaction

1. An Action Sequencing-based View of Dynamic Competitive Interaction WALTER J. FERRIER University of Kentucky November 1999

2. Competitive Outcomes Competitive Interaction Firm A’s Actions Firm B’s Actions Organizational Characteristics Industry Characteristics

3. Action Char. Irreversibility Magnitude Radicality Reaction Char. Likelihood Type Speed Prior Studies: Action-Reaction Dyads Event Dyad 1 Event Dyad 2 Event Dyad 3 Event Dyad 4 Actor 1 Actor 2 time

4. Firm Performance Profitability Sales growth Market share Repertoire Char. Total actions Simplicity Avg. Timing Prior Studies: Action Repertoires Actor 1 Year-End Measures Actor 2 time

5. Named Sequences: Epaulette’s Mate Sicilian Defense Sequential Competitive Interaction ? 8 7 6 5 4 3 2 1 • This Sequence: • Black: Knight b4 • White: Pawn c3 • Black: Bishop g4 • White: Queen b5 • Black: Pawn c5 a b c d e f g h

6. 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

7. Action Sequences Event Sequence 1 Event Sequence 2 time • Sequence Structure • Predictability • Complexity • Timing • Duration • Firm Performance • Profitability • Sales growth • Market share

8. Competing Forces for Strategic Change and Adaptation Enabling Forces Timing Constraining Forces Action Type(s) Predictability

9. Factors Influencing Sequence Structure TMT Heterogeneity Slack Complexity Unpredictability Differentiation Response Timing Duration Awareness Motivation Ability Rival’s Actions Industry Growth Barriers to Entry

10. Sequence Structure and Performance Sequence Structure: Complexity Unpredictability Differentiation Fast Response Timing Long Duration Firm Performance: Sales Growth Profitability

11. 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 reportsin F&S Predicasts, 1987-93 • Structured content analysis • Reliable set of key words

12. 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

13. Definitions of Action Types

14. Sequence Structure Time • Elemental Complexity • Herfindahl Index of within-sequence action diversity • Low Scores: Complex sequence • High Scores: Simple sequence MKT MKT PRICE PROD SIG MKT PRICE

15. Inter-sequence Dissimilarity Time Sequence 1 • 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 MKT MKT PRICE PROD MKT MKT PRICE MKT PRICE PROD SIG PRICE MKT Sequence 2

16. Sequence Chronology 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 MKT MKT PRICE MKT PRICE (a) (a) (b) Rival Firm PROD SVC

17. 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

18. 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

19. Influence of Firm and Industry Characteristics on Sequence Structure

20. Rivalry and Sequence Structure Unpredictable Faster Timing Differentiated Similar Extent of Rivalrous Differentiation

21. TMT Heterogeneity and Sequence Structure Industry Heterogeneity Unpredictable Complexity Educational Heterogeneity Heterogeneous Homogeneous Extent of TMT Heterogeneity

22. Industry Context and Sequence Structure Unpredictable Low Growth Low Barriers High Growth High Barriers

23. Influence of Sequence Structure on Performance

24. Strategic Repertoire Complexity and Performance Performance Simple Complex Extent of Elemental Complexity

25. Strategic Unpredictability and Performance Performance Routine Erratic Extent of Sequence Predictability

26. Strategic Pattern Differentiation and Performance Performance Similar Different Extent of Sequence Differentiation

27. Duration of Strategic Attack and Performance Performance Sustained Short Extent of Subsequence Duration

28. Conclusions:Sequence Matters Focal Firm Rival Firm • Sequence Structure • Predictability • Complexity • Timing • Duration • Firm Performance • Profitability • Sales growth • Market share

29. Implications:Synthesized Perspectives Competitive Dynamics Action Sequences Learning & Change Upper Echelons

30. Sequence Applications... COMPUTER PROGRAM: data actions2; subj = _n_; do i = 1 to max; output = matrix; end; run; DNA: BOXING: Jab...Jab…Uppercut LANGUAGE: qcheaTiueissesne. hsiT si a cesneueq. This is a sequence. CAGTACATAGTACGATACGA MUSIC: