Event Count Analysis and Strategic Management
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.
KeywordsPoisson Model Interarrival Time Negative Binomial Model Event Count Event History Analysis
Unable to display preview. Download preview PDF.
- Amburgey, Terry L. and Dacin, Tina. (1994), “As the Left Foot Follows the Right? The Dynamics ofGoogle Scholar
- Strategic and Structural Change“. Academy of Management Journal,37, pp 1427–1452.Google Scholar
- Cox, D. R. and Lewis, P.A.W. (1966), Statistical Analysis of Series of Events. New York: Wiley.Google Scholar
- Daley, D. J. and Vere-Jones, D. (1972), “A Summary of the Theory of Point Processes”, in Stochastic Point Processes: Statistical Analysis, Theory, and Applications, ( P. A. W. Lewis, Ed.), pp 299–383. New York: Wiley.Google Scholar
- Kim, Yong-Duck, Anderson, Dan.R., Amburgey, Terry.L. and Hickman, James.C. (1995), “The Use of Event History Analysis to Examine Insurer Insolvencies. The Journal of Risk and Insurance, 62, pp 94–110.Google Scholar
- Nelson, Ralph. (1959), Merger Movements in American Industry, 1895–1956. Princeton: Princeton University Press.Google Scholar
- Neyman, J. and Scott, E.L. (1972), “Processes of Clustering and Applications”, in Stochastic Point Processes: Statistical Analysis, Theory, and Applications, ( P. A. W. Lewis, Ed.), pp 646–681. New York: Wiley.Google Scholar