1 To see this algebraically, let
SB = Unit brand sales.
SC = Unit category sales.
MS = Market share of the brand.
NC = Number of households that buy the category.
NB = Number of households that buy the brand.
CC = Average category unit sales per household that buys the category.
CB = Average category unit sales per household that buys the brand.
Then:
SC = NC*CC
MS = SB/SC
PEN = NB/NC
SOR = SB/(NB*CB)
USE = CB/CC
11
(b) Effect of Advertising and Promotion: Our theoretical discussion suggests that both advertising
and promotion should increase PEN by encouraging more consumers to switch into the brand,
although previous empirical research suggests that the advertising effect is much weaker than the
promotion effect. Advertising should have a positive effect on SOR because it should enhance
repeat purchasing. Promotion could have a negative or a positive effect on SOR. Advertising
should have a positive effect on USE to the extent that it suggests new product uses. Promotion
could have a negative or positive effect, depending on whether it creates new usage occasions
and increases the consumption rate, or brings in consumers who purchase smaller quantities to
mitigate perceived risk.
(c) Moderators of Advertising and Promotion Effects: Consumer response elasticities differ
systematically from category to category and brand to brand. These cross-sectional differences
are not of direct interest for our research, but it is necessary to control for them in order to obtain
valid estimates on average. We allow market share position, stockpileability, purchase cycle,
deal intensity, and advertising intensity to moderate self- and cross-elasticities in the consumer
response model. While we do not have data on all possible moderators (e.g., advertising copy),
the research cited in section 2.1 suggests that the factors we include explain a significant portion
of cross-sectional variation in elasticities.
(d) Competitor Response: Competitor response also differs from category to category and brand
to brand. It is moderated by market share elasticities and the structural and firm-specific factors
suggested in the literature. Since market share elasticities are estimated in the consumer response
model, there is an important link between consumer response and competitor response. The
12
structural factors are market concentration, market share position, and multi-market contact.
Firm-specific factors over and above these are represented by dummy variables.2
3. Method
3.1 Data
We study changes in the market between 1990 and 1996. P&G introduced their value pricing
program in 1991 and implemented it over multiple years (Shapiro 1992; Kristofferson and Lal
1996a, b), and we look at the market before, during, and after implementation of the strategy.
Our data are primarily from IRI's annual Market Fact Book. We select 24 product categories in
which P&G participates, and compile data on price, promotion frequency and depth, as well as
market share, PEN, SOR, and USE for several brands in each category. Whenever possible, we
include P&G, three of its largest competitors, and at least one small competitor. The analysis is
at the level of a manufacturer within a product category. That is, for a manufacturer with more
than one brand within a product category, we combine the brands into one umbrella "brand".3
This results in data on 118 brands across the 24 product categories, although data for some
brands are missing for one or more of the seven years. The advertising data are compiled from
the Leading National Advertisers publication of annual media advertising. All the moderators in
the consumer and competitor response models are derived from these data, with the exception of
category stockpileability, which we obtain from Narasimhan, Neslin, and Sen (1996). Appendix
1 defines all the variables, and Appendix 2 lists the 24 product categories.
2 We do not include structural or firm-specific variables other than market share position as moderators in the
consumer response model because they are not relevant to consumers. For example, consumers would not be
expected to react differently to a given brand’s advertising because that brand competes with another brand in
multiple markets.
13
We note that our data reflect changes observed at the retail level, so we cannot separately
measure the change in P&G’s strategy towards the trade and the consequent change in strategy
of the trade. Also, these data represent activity only in US grocery stores and therefore do not
speak to changes in other countries or in other channels such as mass merchandisers. However,
the Market Fact Book covers a large number of packaged goods product categories and markets,
and has been used to gain important insights by researchers like Fader and Lodish (1990), and
Lal and Padmanabhan (1995). Our compilation is particularly valuable because we cover a
period of seven years, include most of the product categories that P&G plays a role in, and
augment the Market Fact Book data with media advertising data.
These data allow us to undertake a broad-based pooled time series, cross sectional analysis. This
is a well-established approach in the econometric literature (Hsiao 1986), that has produced
several important papers in the marketing literature (e.g., Jacobson and Aaker 1985; Hagerty,
Carman, and Russell 1988; Jacobson 1990; Boulding and Staelin 1990 and 1993; and Boulding,
Lee, and Staelin 1994). The advantage of this approach is that it permits broad and
generalizeable analyses that span several brands, categories, or industries. The challenge is to
control for cross-sectional differences so they are not confounded with longitudinal effects. We
model changes over time to control for cross-sectional main effects, and incorporate moderators
of both consumer and competitor response to control for cross-sectional interaction effects.
_____________________
3 This is consistent with the emphasis of packaged goods manufacturers on category management and with the
strategic emphasis of our research. It allows us to assess a firm's category performance as a function of its
advertising and promotion policy in that category.
1 To see this algebraically, let
SB = Unit brand sales.
SC = Unit category sales.
MS = Market share of the brand.
NC = Number of households that buy the category.
NB = Number of households that buy the brand.
CC = Average category unit sales per household that buys the category.
CB = Average category unit sales per household that buys the brand.
Then:
SC = NC*CC
MS = SB/SC
PEN = NB/NC
SOR = SB/(NB*CB)
USE = CB/CC
11
(b) Effect of Advertising and Promotion: Our theoretical discussion suggests that both advertising
and promotion should increase PEN by encouraging more consumers to switch into the brand,
although previous empirical research suggests that the advertising effect is much weaker than the
promotion effect. Advertising should have a positive effect on SOR because it should enhance
repeat purchasing. Promotion could have a negative or a positive effect on SOR. Advertising
should have a positive effect on USE to the extent that it suggests new product uses. Promotion
could have a negative or positive effect, depending on whether it creates new usage occasions
and increases the consumption rate, or brings in consumers who purchase smaller quantities to
mitigate perceived risk.
(c) Moderators of Advertising and Promotion Effects: Consumer response elasticities differ
systematically from category to category and brand to brand. These cross-sectional differences
are not of direct interest for our research, but it is necessary to control for them in order to obtain
valid estimates on average. We allow market share position, stockpileability, purchase cycle,
deal intensity, and advertising intensity to moderate self- and cross-elasticities in the consumer
response model. While we do not have data on all possible moderators (e.g., advertising copy),
the research cited in section 2.1 suggests that the factors we include explain a significant portion
of cross-sectional variation in elasticities.
(d) Competitor Response: Competitor response also differs from category to category and brand
to brand. It is moderated by market share elasticities and the structural and firm-specific factors
suggested in the literature. Since market share elasticities are estimated in the consumer response
model, there is an important link between consumer response and competitor response. The
12
structural factors are market concentration, market share position, and multi-market contact.
Firm-specific factors over and above these are represented by dummy variables.2
3. Method
3.1 Data
We study changes in the market between 1990 and 1996. P&G introduced their value pricing
program in 1991 and implemented it over multiple years (Shapiro 1992; Kristofferson and Lal
1996a, b), and we look at the market before, during, and after implementation of the strategy.
Our data are primarily from IRI's annual Market Fact Book. We select 24 product categories in
which P&G participates, and compile data on price, promotion frequency and depth, as well as
market share, PEN, SOR, and USE for several brands in each category. Whenever possible, we
include P&G, three of its largest competitors, and at least one small competitor. The analysis is
at the level of a manufacturer within a product category. That is, for a manufacturer with more
than one brand within a product category, we combine the brands into one umbrella "brand".3
This results in data on 118 brands across the 24 product categories, although data for some
brands are missing for one or more of the seven years. The advertising data are compiled from
the Leading National Advertisers publication of annual media advertising. All the moderators in
the consumer and competitor response models are derived from these data, with the exception of
category stockpileability, which we obtain from Narasimhan, Neslin, and Sen (1996). Appendix
1 defines all the variables, and Appendix 2 lists the 24 product categories.
2 We do not include structural or firm-specific variables other than market share position as moderators in the
consumer response model because they are not relevant to consumers. For example, consumers would not be
expected to react differently to a given brand’s advertising because that brand competes with another brand in
multiple markets.
13
We note that our data reflect changes observed at the retail level, so we cannot separately
measure the change in P&G’s strategy towards the trade and the consequent change in strategy
of the trade. Also, these data represent activity only in US grocery stores and therefore do not
speak to changes in other countries or in other channels such as mass merchandisers. However,
the Market Fact Book covers a large number of packaged goods product categories and markets,
and has been used to gain important insights by researchers like Fader and Lodish (1990), and
Lal and Padmanabhan (1995). Our compilation is particularly valuable because we cover a
period of seven years, include most of the product categories that P&G plays a role in, and
augment the Market Fact Book data with media advertising data.
These data allow us to undertake a broad-based pooled time series, cross sectional analysis. This
is a well-established approach in the econometric literature (Hsiao 1986), that has produced
several important papers in the marketing literature (e.g., Jacobson and Aaker 1985; Hagerty,
Carman, and Russell 1988; Jacobson 1990; Boulding and Staelin 1990 and 1993; and Boulding,
Lee, and Staelin 1994). The advantage of this approach is that it permits broad and
generalizeable analyses that span several brands, categories, or industries. The challenge is to
control for cross-sectional differences so they are not confounded with longitudinal effects. We
model changes over time to control for cross-sectional main effects, and incorporate moderators
of both consumer and competitor response to control for cross-sectional interaction effects.
_____________________
3 This is consistent with the emphasis of packaged goods manufacturers on category management and with the
strategic emphasis of our research. It allows us to assess a firm's category performance as a function of its
advertising and promotion policy in that category.
การแปล กรุณารอสักครู่..
