To provide information on each firm’s allocation of advertising effort, each firm’s percent of advertising expenditure dedicated to television and internet advertising is
separately identified. The measure of print advertising is purposely omitted, as including all three media types results in errors related to collinearity of the data.
All innovative product introductions represent new products, but most new products are not truly innovative. The only criterion for a product to be considered “new” is that it
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simply offers a new variant of a product, such as a new flavor, variety, or even a new name. Therefore, only a small fraction of new product introductions are classified as innovative.
Innovations are measured by a count of the number of firm innovations introduced each year. Data on product innovations was gathered from Product Launch Analytics. Each innovative product is categorized as one or more of following innovation types: formulation, technology, packaging, merchandising, new markets, or positioning. Among all of the innovative CPG products assessed by Product Launch Analytics, formulation is the most frequently used innovation rating, as it often refers to first-ever flavors. Technology
innovation describes when a new manufacturing process is used that results in a product with breakthrough technology. Innovative packaging offers a new benefit through packaging design, and merchandising innovation involves marketing through an outlet that is unique to the category’s standard marketing technique. Instances of new market innovation, which requires opening up a completely new market, are extremely rare. Lastly, positioning innovation involves targeting a new group of users or positioning for a new usage.
Following the example of Gielens (2012), I classify the innovations related to formulation and technology as intrinsic innovations, packaging and merchandising as extrinsic
innovations, and new markets and positioning as usage innovations. The average number of annual innovations across all observations is 2.2, which represents a very small fraction of the annual new product introductions, of which the average is 44.3.
Interpurchase cycle data, which measures purchase frequency for the product category, was obtained for each firm using the ACSI survey data collection protocol, following the example of Morgan and Rego (2009). Personal care and cleaning products have an interpurchase cycle of three months, while all other categories in the data set (food,
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beverages, and pet food) have an interpurchase cycle of one month. A dummy variable was created that equals 0 when the interpurchase cycle is one month, and equals one when the interpurchase cycle is three months.
The Hirshman-Herfindahl index (HHI) is used as a measure of the degree of market concentration, which quantifies the extent to which the market is dominated by a few large firms. To determine the appropriate market for each firm, the firms were categorized based on the first four digits of their respective NAICS codes, provided by COMPUSTAT. There are 10 unique 4-digit codes represented in the data set. The HHI index values were then obtained for each of these 10 industries from the U.S. Census (http://www.census.gov). The U.S. Census reports the HHI6 for each market every five years, based on the market share of the top 50 firms in each industry.
To measure the scope of the firm, I use a count of the number of segments in which it is marketed. The number of segments is based on the North American Industry
Classification System (NAICS) market segments, and is a count of the number of NAICS operating codes in which each firm markets its brands. This data was obtained from the Hoover’s database. A few examples of market segments represented in the sample include breakfast cereal manufacturing, bread and bakery product manufacturing, and coffee and tea manufacturing. Kraft has the greatest number of segments, with 36, while Procter & Gamble dog food is only marketed in one segment. The average number of segments across firms is 11. To measure firm scale, or firm size, an annual count of the number of employees is used, as number of employees is a commonly used proxy (Shalit and Sankar 1977). The average
6
The HHI is calculated for the U.S. Census by summing the squares of the individual company percentages of market share for the largest 50 companies.
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number of employees across all observations in the data set is approximately 19,900. This information was obtained from COMPUSTAT.
112 Table 3.1
Data Operationalizations
Annual data from 1996-2010 Description and Source of Data
Annual customer loyalty scores Aggregated at the firm level (ACSI)
Advertising effort Advertising expenditure divided by the previous
year’s sales
(TNS Media and COMPUSTAT)
Promotion effort PSG&A = SG&A – advertising expenditure;
PSG&A is then divided by the previous year’s sales (TNS Media and COMPUSTAT)
New product introductions Number of unique product names listed in Product Launch Analytics; Corresponds to SKUs, less the SKUs for different product sizes
(Product Launch Analytics) Communication mix
(traditional versus nontraditional)
% of total annual advertising expenditures spent on TV and internet advertising, respectively
(TNS Media) Innovative new product mix
(Revolutionary, Incremental, and Usage)
Innovations are coded as Packaging,
Merchandising, Technology, Formulation, New Market, or New Positioning in Product Launch Analytics. The count of Packaging and
Merchandising are combined to form Incremental Innovations (Extrinsic), Technology and
Formulation are Revolutionary Innovations (Intrinsic), and New Market and New Positioning are Usage Innovations
(Product Launch Analytics)
Product interpurchase cycle Based on the ACSI survey data collection protocol (ACSI)
Market concentration Measured by the Hirshman-Herfindahl Index (HHI)
for each product category, as indicated by each firm’s four-digit NAICS code
(COMPUSTAT and U.S. Census)
Firm scope Number of segments per firm based on the number
of unique NAICS codes that a firm spans (Hoover’s)
Firm scale Number of employees per firm
(COMPUSTAT)
Firm sales Annual total revenue per firm
113 Step 2 Model
In a second step, a tobit model is used to regress the measures of loyalty capability on the percentage of advertising spent on internet advertising, the percentage of advertising spent on television advertising, revolutionary, incremental, and usage innovations, the degree of market concentration, the product interpurchase cycle, the firm’s scale and scope, and potential moderating effects of market concentration. The innovation variables are lagged for the same reasons that the new product introductions variable is lagged in the first step. Since the loyalty capability value is censored at 1, a tobit model is used.
Tobit model:
(5) log loyalty_capabilityi,t = β0 + β1 log revolutionaryi,t-1 + β2 log incrementali,t-1 +
β3 log usagei,t-1 + β4 log %interneti,t + β5 log %televisioni,t + β6 interpurchase_cyclei +
β7log market_concentrationi,t + β8 log firm_scopei,t + β9 log firm_scalei,t +
β10 (log mkt_conc.i,t x log revolutionaryi,t-1) +
β11 (log mkt_conc.i,t x log incrementali,t-1) + β12 (log mkt_conc.i,t x log usagei,t-1)+
β13 (log mkt_conc.i,t x log %interneti,t) + β14 (log mkt_conc.i,t x log %televisioni,t) +
β15 (log mkt_conc.i,t x log firm_scopei,t) + β16 (log mkt_conc.i,t x log firm_scalei,t) +
β17 (log mkt_conc.i,t x log interpurchase_cyclei) +eit
where revolutionary, incremental, and usage, respectively, refer to the type of product innovation.
3.3.4 Step 3: Relating Loyalty Capability to Firm Sales