Understanding Consumer Reactions to Assortment Unavailability

interaction effects between assortment structure and brand equity and between assortment
structure and (relative) assortment size. To do so, we estimate an additional model in which we
add the following interaction terms to Equation 1: STRi,p,r × BEi,b and STRi,p,r × ASi,p,r.
We measure SSI on a single five-point scale. Because this scale should be considered an
ordinal scale, we use an ordered probit model instead of the standard linear regression model to
estimate Equation 1 (Long 1997). In an ordered probit model, the observed response variable is
modeled on an underlying continuous variable yi * , which depends linearly on explanatory
variables. We estimate the model with maximum likelihood in E-Views 4.0. To estimate the
effect of our explanatory variables on assortment satisfaction and complaining behavior, we use
a standard linear regression model with ordinary least squares, because the summation of the
three CIs can be considered an interval scale.
Prior to estimating the model for Equation 1, we assess whether multicollinearity might
cause severe problems in our data by considering the correlation among the independent
variables (see Table 3.4). In general, the correlation among the independent variables is low. We
also compute the variance inflation factors and find that all are less than 2. Therefore, we
conclude that multicollinearity will not affect our estimation results (Hair et al. 1998; Leeflang et
al. 2000). We use White’s (1980) method to correct for potential heteroscedasticity in the errors
and variables.
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