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

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

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

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

a b c d e f g h 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? n Ordered sample of things –Temporal orderliness among elements n Logically unified sequence –Succession of market-based decisions n Patterns in stream of behaviors n Coordinated series of actions n Actions in a sequential strategic thrust

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

Competing Forces for Strategic Change and Adaptation Timing Predictability Action Type(s) EnablingForces ConstrainingForces

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 Response Timing Duration

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

Sample and Data n Matched pairs: –Single-/Dominant-business firms (S.R. >.70) –U.S. market share leaders and challenger (No.2) – Cross-sectional time series panel n Actions: –News reports in F&S Predicasts, –Structured content analysis –Reliable set of key words

Action Sequence n Ordered sample of action events Time n 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

Sequence Structure n Elemental Complexity –Herfindahl Index of within-sequence action diversity –Low Scores: Complex sequence –High Scores: Simple sequence MKT PRICESIGMKTPRODPRICE Time

MKT PRICEMKTPRODPRICE Time MKT PRICESIGPRODPRICE Sequence 1 Sequence 2 MKT n Unpredictability (focal firm) n 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 PRICEMKTPRICE SVCPROD Rival Firm (a) (b) Time Focal Firm n Average Sequence Duration (a) –Greater No. days: Firm sustains attack n Average Sequence Response Lag (b) –Smaller No. days: Firm fast to respond/attack

TMT Heterogeneity Variables n Educational Background –Blau’s index of heterogeneity for degree types (BBA, BSME, JD, etc.) n Industry Tenure –Coefficient of variation of TMT members’ years spent in the focal industry Data Source: D&B Reference Book of Corporate Management,

Industry Variables n Industry Growth –Simple growth rate year t  year t+1 n Industry Concentration –Herfindahl index n Barriers to Entry –Sum of industry means for R&D, SG&A, and total assets Data Source: COMPUSTAT Industry Segment Files,

Influence of Firm and Industry Characteristics on Sequence Structure

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

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

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

Influence of Sequence Structure on Performance

Strategic Repertoire Complexity and Performance Performance SimpleComplex Extent of Elemental Complexity

Strategic Unpredictability and Performance Performance RoutineErratic Extent of Sequence Predictability

Strategic Pattern Differentiation and Performance Performance SimilarDifferent Extent of Sequence Differentiation

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

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

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

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