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Finally, to gauge the profit implications of superstore competition, McConnell used a "dummy" (or binary) variable where S = 1 in each market in which Columbia faced superstore competition and S = 0 otherwise. The coefficient on this variable measures the average profit rate effect of superstore competition. Given the vigorous nature of superstore price competition, McConnell expects the superstore coefficient to be both negative and statistically significant, indicating a profit-limiting influence. The Columbia profit-margin data and related information used in McConnell's statistical analysis are given in the preceding table. Regression model estimates for the determinants of Columbia's profitability are as follows:

Finally, to gauge the profit implications of superstore competition, McConnell used a "dummy" (or binary) variable where S = 1 in each market in which Columbia faced superstore competition and S = 0 otherwise. The coefficient on this variable measures the average profit rate effect of superstore competition. Given the vigorous nature of superstore price competition, McConnell expects the superstore coefficient to be both negative and statistically significant, indicating a profit-limiting influence. The Columbia profit-margin data and related information used in McConnell's statistical analysis are given in the preceding table. Regression model estimates for the determinants of Columbia's profitability are as follows:

Determinants of Profitability for Columbia Drugstores, Inc.

Standard Error t Statistic

Variable Name Coefficient (1) of Coefficient (2) (3) = (1) ^ (1)

Intercept Market share Concentration

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