Analysis of Sales Promotion Effects on Household Purchase Behavior

The variables size, age, and cycle are related by definition. Household cycle is a
composite variable consisting <strong>of</strong> both age and size <strong>of</strong> the household. Potential estimation
problems can be prevented by incorporating cycle in the analysis as a nominal, categorical
variable and at the same time incorporating age and size in the analysis as variables having
a linear relationship with promotion response. But because this approach does not provide
us with the detailed insights about the effect <strong>of</strong> age and size per se, additional analyses are
carried out excluding cycle and incorporating age and size as categorical variables. These
analyses are not restricted to a linear relationship between these two variables and
promotion response.
Another potential variable that could bring estimation problems about is
education. Numbers are assigned to education and social class so that both variables can be
dealt with as interval variables (see Table A7.1). Education has a very strong relationship
with social class (0.76, 0.00, 156). This is expected, because social class is defined based
on education and occupation (see TableA3.1). Social class is a frequently used
segmentation variable in marketing studies, which underlines the importance <strong>of</strong>
incorporating this variable in this research. However, education is also <strong>of</strong> interest, and the
correspondence between social class and education is not one-to-one. Excluding education
would mean that the hypothesis regarding the relationship between education and
promotion response could not be tested in an empirical setting. This problem is solved as
follows. The nominal, categorical variable education has four levels. For this variable, four
dummies are defined. Each <strong>of</strong> these dummies is logistically regressed on social class
(which, in turn, is transformed into dummy variables for each specific level <strong>of</strong> social class).
Four columns <strong>of</strong> error terms, one for each <strong>of</strong> the education levels, result. The variables are
named EDUCRES_STANDARD (standard level), EDUCRES_LOWER (lower level),
EDUCRES_MIDDLE (middle level), and EDUCRES_HIGH (high level). Three out <strong>of</strong>
these four error terms, which add up to zero, are incorporated in the binary logistic
regression analysis (leaving out EDUCRES_HIGH). They are uncorrelated with social
class, and indicate the stand-alone effect <strong>of</strong> education on promotion response, relative to
the highest level <strong>of</strong> education.
Two measures <strong>of</strong> store loyalty (STORLOY1 and STORLOY2, being the share <strong>of</strong>
the primary store in total FMCG expenditures in quantity and money, respectively, see
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