Event Count Analysis and Strategic Management

  • Jean-Luc Arregle
  • Terry L. Amburgey
  • Tina Dacin


The development of strategic management research has brought about an increasing emphasis on longitudinal research. Concurrently, there is a long-standing interest in the ‘actions’ of organizations (mergers, alliances, technical innovations, et cetera) which typically involve relatively discrete events rather than changes in the level of a continuous variable. Thus research on organizational actions results in the analysis of discrete events over time. A number of empirical studies of this type have been published in the strategic management literature, and the number is likely to increase over time Event history analysis is the preferable method for this type of research. Unfortunately, in many instances complete information on the type and timing of organizational actions is not available; many secondary sources provide only the number of events occurring during some period of time. In that case, event count analysis can provide meaningful inferences about factors influencing the rate of occurrence of strategic events. In this chapter we review two stochastic models (Poisson and Negative Binomial) appropriate for event count analysis. We begin with a brief description of the relationship between event histories and event counts. We then discuss specific issues involved in conducting event count analyses. For purposes of illustration, we provide the results of an analysis of mergers among French firms. The chapter ends with a summary discussion of the limitations and advantages of event count modeling.


Poisson Model Interarrival Time Negative Binomial Model Event Count Event History Analysis 
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Copyright information

© Springer Science+Business Media Dordrecht 1997

Authors and Affiliations

  • Jean-Luc Arregle
    • 1
  • Terry L. Amburgey
    • 2
  • Tina Dacin
    • 3
  1. 1.EDHEC School of ManagementUSA
  2. 2.University of KentuckyUSA
  3. 3.Texas A&M UniversityUSA

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