WHAT DRIVES NEW PRODUCT SUCCESS?
AN INVESTIGATION ACROSS PRODUCTS AND COUNTRIES
Katrijn GIELENS
Jan-Benedict E. M. STEENKAMP
Katrijn Gielens is Associate Professor of Marketing, Erasmus University, P.O Box 1738, 3000
DR Rotterdam, The Netherlands; ph. + 31-10-4088635/fax: +31-10-4089011/e-mail:
K.Gielens@fbk.eur.nl. Jan-Benedict E. M. Steenkamp is CentER Research Professor of
Marketing and GfK Professor of International Marketing Research, Tilburg University, P.O Box
90153, 5000 LE Tilburg, The Netherlands; ph. + 31-13-4662916/fax: +31-13-4668354/e-mail:
J.B.Steenkamp@uvt.nl.
We gratefully acknowledge the support of AiMark, which provided the data on which this study
is based and the financial support of two U.S. CPG companies. The help of Peter Kempe (IRI)
and Alfred Dijs (Europanel) is especially acknowledged. The project also benefited from support
by the Flemish Science Foundation (F.W.O.) under grant No. G.0116.04. We thank Marnik
Dekimpe, Christophe Van den Bulte, Harald van Heerde, and Delaine Hampton, as well as
seminar participants at the 2003 MSI Conference on Global Marketing, the 2003 EMAC
Conference, the Catholic University of Leuven, and the Tuck Business School for constructive
comments.
1
WHAT DRIVES NEW PRODUCT SUCCESS?
AN INVESTIGATION ACROSS PRODUCTS AND COUNTRIES
ABSTRACT
The introduction of new products is widely recognized as one of the most important marketing
activities of companies. Nevertheless, at least two caveats to an intensive new product strategy
exist. First, it is a risky strategy, as many new products fail in the market place. Second, it is a costly
strategy as R&D expenditures are rising sharply. To recoup R&D investments and meet ROI
requirements, it is often no longer sufficient to sell the product in a single country only.
Increasingly, firms launch and sell new products into their international markets. General rules for
market response are therefore increasingly needed. To that extent, our primary objective is to
systematically examine the cross-national generalizability of the impact of key product, competitive
environment, and consumer drivers on consumers‟ first year purchase patterns of new product
across markets. Our data comprise the first year sales for 301 new consumer packaged goods
(CPGs) launched in the UK (74 CPG introductions), France (104), Germany (67), and Spain (56).
Individual-level purchases for each new product are obtained from the Europanel household panels
in each country, involving in total over 16,000 consumers. We derive cross-national empirical
generalizations, as well as differences regarding factors underlying new product success. We relate
the results to R&D recommendations, pan-European segmentation strategies, and local marketing
activities.
Keywords: New products, international generalizations, R&D, multilevel models
2
INTRODUCTION
The introduction of new products is one of the most important marketing activities of companies.
Firms like Procter & Gamble, Sony, Microsoft, and Gillette have made the frequent introduction
of new products an essential part of their marketing strategy. Successful new product
introductions contribute substantially to long-term financial success (Bayus, Erickson, and
Jacobson 2003), are an effective strategy to increase primary demand (Nijs et al. 2001) and to
keep store brands at bay (Ailawadi, Neslin, and Gedenk 2001), and strengthen the competitive
position of the company (Shankar, Carpenter, and Krishnamurthi 1998). Drucker (1999) argued
that only companies with a systematic policy of innovation are likely to succeed. Consequently,
it is not surprising that the Marketing Science Institute (2002) has named new products a top tier
priority topic.
However, there are at least two caveats to a strategy of relying on innovation to
strengthen the company‟s position. First, it is a very risky strategy, in that over 50% of new
products fail in the marketplace (Golder and Tellis 1993). Innovation is clearly not an isolated
activity. Rather it is interrelated with other business functions, especially marketing (Bayus,
Erickson, and Jacobson 2003). New products often fail because R&D has not yielded a product
that appeals to the marketplace, and/or because the marketing strategy associated with the new
product launch has been ineffective.
Second, it is a very costly strategy, and R&D expenditures are rising sharply. For
example, R&D for Gillette‟s Mach 3 razor blade exceeded $700 million, while R&D costs for
major new drugs are typically between 500 million and 1 billion dollars, and new car platforms
cost over one billion dollars. To meet ROI requirements, it is often no longer sufficient to sell the
product in a single country only (Golder 2000). Increasingly, firms launch and sell new products
3
into their international markets. General rules for market response are therefore increasingly
needed (Farley and Lehmann 1994). The challenge is to develop a new product strategy that is
sensitive to both supply side drivers (i.e., own company offering and resources and the
competitive setting) and demand drivers in an international context. Which factors have a similar
impact on new product success in different countries, and hence could be part of global new
product introduction strategies? Which ones work out differently in different countries, and
hence should be part of local adaptations to the introduction strategies? Does the context in
which the product is introduced have similar effects in different countries? An answer to these
questions requires detailed knowledge of the generalizability of factors underlying new product
success across countries.
Our study addresses these two issues. For a comprehensive set of key product,
competitive, and consumer factors we develop a systematic set of hypotheses as to their expected
effect on new product success. Collectively, these factors constitute our source model (Janssens,
Brett, and Smith 1995). We examine the cross-national generalizability of our source model in
four major European countries, viz., France, Germany, Spain, and the U.K.
The context of our study is the consumer packaged good (CPG) industry. It constitutes a
key industry, with consumer expenditure on packaged goods exceeding over 10% of total
consumer expenditure in most Western countries (Euromonitor 2003). The CPG industry is
characterized by heavy R&D spending. For example, L‟Oreal employs 2,800 researchers, has
registered 500 patents in 2002, and annually spends about $500 million on R&D. Unilever
spends over $1 billion each year on R&D and P&G over $1.5 billion.1 Over half of the global
sales of Gillette and Colgate Palmolive are generated by products that were not on the market
five years ago. Analysts have noted that the future health and growth of the CPG industry will
4
critically depend on its ability to expand sales through innovation and successful
commercialization of these innovations (Cook and Georgiadis 1997). However, it is worrisome
that new product failure is especially rampant in this industry with over 70% of new CPGs
failing within two years after introduction, with most failures occurring in the first year after
launch (Ernst&Young/ACNielsen 2000).
Our study can be positioned vis-à-vis previous research on new product success along
three dimensions: (1) the level of aggregation, namely market versus individual level, (2) the
sources of variation considered (product strategy, competitive environment, consumer, country),
and (3) the type of purchase behavior studied. Table 1 summarizes previous research on the
drivers of new product success along these three dimensions.2
---Insert Table 1 about here---
First, a large body of research at the aggregate (market) level has studied the diffusion of
new products (e.g., Gatignon, Eliashberg, and Robertson 1989) and success factors in the new
product diffusion development process (e.g. Calantone, Schmidt and Song 1996). Another
stream of research has examined new product success at the individual level (e.g.,
Chandrashekaran and Sinha 1995, Steenkamp and Gielens 2003).
Second, different sources of variation in new product success have been investigated.
Various product specific success drivers have been proposed mostly in connection to marketing
mix variables (e.g., Helsen and Schmittlein 1994, Steenkamp and Gielens 2003) and product
charcteristics (e.g., Calantone, Schmidt, and Song 1996). Individual-level studies have given
much attention to the role of consumer-related variables in new product success (e.g., Chatterjee
1
Information was obtained from official company reports, and refers to the year 2002.
2
Table 1 presents a number of key studies but due to space constraints, it does not provide an exhaustive overview
of the literature. Most notably, aggregate-level studies without an international component are not included. See
Mahajan, Muller, and Wind (2000) for an overview of that literature.
5
and Eliashberg 1990, Manning, Bearden, and Madden 1995). This source of variation has not
been considered in aggregate studies. The impact of several competitive environment variables
has been studied in a few studies (Dekimpe, Parker, and Sarvary 1998, Ganesh and Kumar 1996,
Steenkamp and Gielens 2003). Variation across countries has only been investigated in aggregate
studies (e.g., Mahajan and Muller 1994). Table 1 reveals that most studies on new product
success incorporate only a subset of these potential sources of variation. Specifically, none of the
aggregate studies incorporates consumer variation, while none of the individual studies considers
the country dimension. This may lead to invalid conclusions on the relative impact of the drivers
(Chandrashekaran and Sinha 1995).
Third, as observed by Chandrashekaran and Sinha (1995), new product research has
focused almost exclusively on the first purchase and ignores subsequent purchases. This
generates limited insights concerning factors underlying new product success, especially for
CPGs where trial purchases constitute only a modest portion of total purchase volume and
subsequent purchases are the key to enduring success (Urban and Hauser 1993). Moreover, the
operationalization of trial behavior in individual-level studies is often based on self-reports (e.g.,
Manning, Bearden, and Madden 1995, Steenkamp and Burgess 2002).
In this study, we hope to overcome some of the gaps in the literature by examining the
intensity and trend of all first year purchases of new CPGs at the level of the individual
consumer. To study consumers‟ first year purchase pattern, we trace how many items they
bought in each quarter of the first year. A multi-level Poisson regression model is used to model
differences in purchase intensity as well as differences in the purchase trend as a function of a
large set of product (marketing resources, roll-out strategy, brand reputation, product newness),
competitive environment (market concentration, price and non-price competition in the category,
6
market power of national brands vis-à-vis private labels), and consumer (dispositional
innovativeness and socio-demographics) variables. To the best of our knowledge, we are the first
to add a cross-national dimension in an individual-level study by explicitly establishing
communalities and differences in the effects of the different constructs across four countries.
Managers often focus too much on the means of key variables, which may differ more across
countries than do their effects on response. As such, they feed the myth that international
differences are both large and unpredictable (Farley and Lehmann 1994). In contrast, being able
to generalize internationally about factors affecting market response should provide insight in
what elements of a new product strategy can be standardized and which elements really have
different effects across different countries.
The remainder of the paper is organized as follows. In the next section, we develop
hypotheses concerning the likely effect of various drivers of new product success. Next, we
describe the data set and the methodology, and report the results. The final section summarizes
the findings, draws managerial implications, and provides suggestions for future research.
DRIVERS OF NEW CPG SUCCESS
Our focal measures of new CPG success are a consumer‟s purchase intensity and trend in
purchases in the first year after introduction. To gauge new product success, it is important to
both consider total purchases as well as the trend in purchases (cf. Gatignon and Robertson
1985). Industry studies (Ernst&Young/ACNielsen 2000) indicate that the first year is crucial for
the success of new CPGs. In this section, we develop hypotheses concerning the role of specific
product, competition, and consumer factors and their expected effects on consumers‟ first-year
purchase intensity and trend. These hypotheses are tested separately in four major European
7
countries to establish the extent to which the drivers of new product success are generalizable
across countries (Janssens, Brett, and Smith 1995).
Product Strategy Factors
Product strategy factors encompass both marketing resources available, as well as the strategic
factors associated with the new product introduction, including the international launch strategy
adopted for the product, the reputation of the brand, and the degree of newness of the product.
Marketing resources. A firm with larger marketing resources in a category is able to
provide more intensive marketing support (e.g., advertising, promotion) to back a new product
introduction (Calantone, Schmidt, and Song 1996) and to persuade retailers to carry the new product
and assign it the necessary shelf space (Rao and McLaughlin 1989). Intensity of marketing support
for the new product is expected to have a positive impact on a CPG‟s first-year success (i.e., on first
year intensity and trend in purchases).
International rollout strategy. Several rollout strategies can be distinguished. We focus on
the potential advantages derived from a sequential strategy (Golder 2000). In this case, the firm can
collect experience and market intelligence in countries in which the product has already been
introduced and share this intelligence with other markets. Spillover effects or goodwill from present
lead markets to new lagging markets may prevent the firm from making the same mistakes in new
markets (Golder 2000). We therefore posit that a CPG‟s first year success (i.e., intensity and trend in
purchases) will be greater if it has been introduced before in another country.
Brand reputation. A brand has a good reputation if consumers believe its products to be of
consistent high quality (Choi 1998, Shapiro 1983). When attributes of the new product are difficult
to observe prior to consumption, as is typically the case with CPGs (Moorthy and Zhao 2000), and
the high-reputation brand name is extended to a new product, consumers can plausibly believe that
8
the new product is also of high quality (Choi 1998). The incentive to cheat by extending the
reputable brand name to a low-quality product is prevented by the loss of repeat sales of the new
product (Shapiro 1983), the loss of repeat sales of established products (Wernerfelt 1988), and the
loss of future sales due to the reduced extension potential of the brand (Choi 1998). Hence, we
expect that new products introduced by reputable brands exhibit greater first year success.
Newness. We follow several studies that suggest a U-shaped relation between product
newness and various measures of market success such as market share and ROI for industrial
products (Kleinschmidt and Cooper 1991), firm value in the automobile industry (Pauwels et al.
2004), and trial rate for CPGs (Steenkamp and Gielens 2003). This U-shaped relation can be
explained in terms of the two underlying factors of complexity and relative advantage, both of
which increase with newness, albeit not in a linear fashion (Steenkamp and Gielens 2003). We
extend previous research by studying this relationship with respect to both purchase intensity and
trend, and by testing this relation in a cross-national context using a consistent data and
measurement scheme.
Moreover, if a sequential rollout strategy is used to launch the new product, potential
adopters in lagging countries can witness the success of the new product in lead countries (Ganesh,
Kumar, and Subramaniam 1997). They will be more knowledgeable about the new product, the
perceived complexity of new products high on newness will be lower, while the advantages will be
more salient. We therefore expect the sequential rollout strategy to reinforce the positive impact on
a CPG‟s first year success3 of products high in newness.
3
Here and elsewhere, we will focus on the effect of the interaction on purchase intensity. Although we expect a
similar effect on the trend, we will not pursue the impact on the trend because of multicollinearity problems.
9
Competitive Environment
The competitive context can act as a barrier to entry or can facilitate new entry. We examine the
role of the degree of concentration in the market, the extent of price and non-price competition, and
especially in the context of CPGs, the market power of national brands vis-à-vis private labels.
Concentration. A common hypothesis in industrial economics is that (tacit) collusion to
thwart new entrants is easier in markets characterized by high levels of concentration
(Lypczynski and Wilson 2001). As concentration increases, the importance of each brand to total
output will increase and firms are less likely to ignore the possible effect of any independent
action by a rival. Coordination of activities against new entrants is also easier in more
concentrated markets as the number of channels of coordination is smaller (Scherer and Ross
1990). Moreover, in concentrated markets, it is easier to monitor the competition. This makes it
more likely that new product introductions are noticed, which is a necessary requirement for
initiating a coordinated response (Chen, Smith, and Grimm 1992). We therefore expect the new
CPG‟s success to be lower in categories characterized by high levels of concentration.
Price competition. In the CPG industry, price competition between brands is largely
conducted using promotions. Promotions typically contain a pricing component (Fader and
Lodish 1990) and are present at the point of purchase. Intense competitive price promotions in
the category signal a high degree of commitment of the incumbents to the category. It may even
be a deliberate strategy used by incumbents to render it more difficult for others to enter the
market (Lal 1990). Hence, we propose a negative impact of price promotion intensity in the
category on the first year success of the new CPG.
However, the effectiveness of this barrier is usually assessed against rivals possessing
less “skills” than the incumbent (Han, Kim, and Kim 2001). If the new product is able to
10
differentiate itself from the existing offering on a non-price basis through innovation, tacit price
agreements will be hard to maintain (Lipczynski and Wilson 2001). We therefore expect the
newness of the new product to mitigate the negative effect of price promotion intensity.
Non-price competition. The two main forms of non-price competition are through new
product introductions and advertising (Lipczynski and Wilson 2001). Nijs et al. (2001) found that
new product introductions have an important primary demand effect, which in its turn may offer
better opportunities for subsequent new product introductions (Shankar, Carpenter, and
Krishnamurthi 1999). On the other hand, in categories characterized by frequent new product
introductions, most niches will be filled, so that a new product will find it more difficult to find
enough unmet demand (Schmalensee 1978). Hence, the effect of the extent of product-based
competition in a category on a new CPG‟s first year success is not clear, a priori.
If the new product is able to provide consumers with substantial added value, it can reshape
preferences within the category and differentiate itself from other products. Moreover, by offering
substantial added value over its incumbents, the threat of collusive behavior becomes less likely.
Consequently, we expect that the effect of category new product introduction intensity on new
product success will be positively affected (i.e., less negative or more positive) by the degree of
newness of the new product.
Heavy advertising is a powerful weapon to increase market power of the existing products
via differentiation and loyalty building (Lipczynski and Wilson (2001). These authors call it (p. 197)
“arguably the most common method of differentiating products.” Consistent with this view,
Boulding, Lee, and Staelin (1994) and Mela, Gupta, and Jedidi (1998) found that brands might be
able to use advertising to „insulate‟ themselves from direct competition. Heavy advertising by
incumbents will also increase the capital required to create awareness in the market (Robinson and
11
Fornell 1985). Hence, it will be more difficult for new products to gain a foothold. Consequently,
we expect a new CPG‟s success to be lower in categories characterized by intense advertising.
However, we expect that the negative effect of intense category advertising on a new product‟s
first year success is attenuated when the new product is introduced under a strong brand name as
it has awareness and brand associations to build upon (Comanor and Wilson 1967).
Market power of national brands vis-à-vis private labels. Following Scherer and Ross
(1990), we define market power as the degree to which brands are able to command prices above
those implied by competition. Much of today‟s power struggle – especially in CPG industry –
involves national brands versus private labels (Ailawadi, Neslin, and Gedenk 2001). Private
labels have increased their quality, prices, and market share in all Western countries to the extent
that in many categories, they have become a major threat to the market position of national
brands (Hoch 1996). However, the relative market power of national brands versus private labels
still varies considerably across categories. We expect that the success of a new CPGs introduced
by national brands will be higher the larger the market power of national brands vis-à-vis private
labels in the category.
Consumer Characteristics
Consumers‟ willingness to purchase the new product is affected by product and competitive
strategies, but also by their own personal characteristics. If a systematic, generalizable effect of
consumer factors on their first-year purchase pattern is found across countries, this offers a basis
for international market segmentation. We examine personality and sociodemographic variables.
In the context of the wide array of personality characteristics, we focus on dispositional
innovativeness.
12
Dispositional innovativeness. Dispositional innovativeness is defined as the predisposition
to buy new products and brands at an early stage, rather than to remain with previous choices and
consumption patterns across a variety of goods and services (Midgley and Dowling 1978,
Steenkamp and Gielens 2003). Steenkamp and Gielens (2003) reported a significant positive effect
of dispositional innovativeness on the trial rate of new CPGs. We extend this research by examining
its effect on consumers‟ first-year purchase intensity and trend. We propose a positive effect of
dispositional innovativeness on a consumer‟s first year purchase intensity. However, due to their
intrinsic need for change, consumers high on dispositional innovativeness have a decreased
tendency to stick to the same purchase response over time (Raju 1980). They tend to get bored more
easily with the new product and move forward to explore newer launches. Consequently, the effect
of innovativeness will diminish over time leading to a negative effect on the purchase trend.
Sociodemographics. Three sociodemographics– age, size of the household, and place of
residence - are included in this study. Younger people tend to be less risk averse, have a higher
optimal stimulation level than older people (Zuckerman 1994) and a lower stock of accumulated
experiences with the category (Assael 1995). Hence, younger consumers are more attracted to new
products but they will also switch more easily to new offerings. Thus, we expect that the first year
purchase intensity (trend) is negatively (positively) related to age.
In general, the larger the household, the higher the likelihood that significant within-
household preference heterogeneity exists, which can be addressed by purchasing multiple products
(Seetharaman and Chintagunta 1998). Moreover, larger households tend to be heavier users of the
category (through the sheer number of users). Hence, they have shorter interpurchase cycles and
more purchase occasions (Helsen and Schmittlein 1994). As such, we expect household size to be
positively associated with a new CPG‟s first year success.
13
Consumers living in the country‟s major metropolis(es) tend to be more cosmopolitan
(Hannerz 1990), and diffusion research has documented a positive relationship between
cosmopolitanism and the tendency to innovate (Gatignon et al. 1989). Metropolises also tend to
have a denser retail infrastructure, thus making it easier for consumers to acquire the new product.
Hence, we propose that the first year success of the new CPG is higher among consumers living in
metropolises. Table 2 gives an overview of our predictions.
--- Insert Table 2 about here ---
METHOD
Sample Description
Data are gathered in four major European countries, i.e. France, Germany, Spain, and the U.K.,
in which we trace the first year purchases of respectively 104, 67, 56, and 74 new CPGs
launched in 1998-1999. These product introductions covered a wide range of food and
beverages, personal care, and household care products in 49 categories. Our data set includes the
introduction of well-known new products such as Kraft Lunchables in the food category, the fruit
drink Sunny Delight, the fabric refresher Febreze, the shampoo Fructis, and the razor blade
Mach3, besides a varying set of (local) products. About 30% of these new products were
introduced in several countries, however, not necessarily at the same time. Febreze, for instance,
was introduced in Spain about a year after its introduction in the U.K. The Mach 3, on the other
hand, was introduced within approximately one month in all markets.
Consumer purchases for each of the new products were monitored in panels of
respectively 3,582, 4,531, 3,388, and 4,869 households during a period of 12 months after the
new product was introduced. Industry analysts consider the first 12 months after introduction
critical for success or failure in the CPG industry (Ernst&Young / ACNielsen 2000). For every
14
new product, the pan-European research agency Europanel delivered us the number of items
bought by each consumer in each quarter in the first year after introduction. The purchase
records for every consumer were provided by the pan-European market research agency
Europanel (GfK/Taylor Nelson Sofres).
The first year success of the new products in our data set varied considerably. Of the
Mach 3 razorblade 577 units were bought in the first year by the 4,869 consumers in the U.K.
panel, whereas the U.K. panel members only bought 210 units of the new Wilkinson razorblade,
which was introduced, in the same period. A similar pattern is found in France where 636 units
were purchased by the 3,582 consumers in the panel and only 164 units of the Wilkinson
razorblade. In contrast, the Dove bath cream, which was also was rated equally high on newness
in France and the U.K., performs substantially better in the U.K. where 1175 units were
purchased by the panel members of which 446 units in the first quarter. In France, however, only
487 units were bought in the first year of which only 48 units in the first quarter. Moreover,
purchases only picked up from the third quarter onwards. To explain this variation in both
purchase intensity and trend across products and countries the following measures are used.
Measures4
Product strategy factors. We used the country-specific market share of the firm in the
category in the year prior to introduction as proxy for the marketing resources the firm has at its
disposal to support the new product introduction. Marketing budgets are typically tied to market
share (e.g., Balasubramanian and Kumar 1990, 1997). To capture the effect of a sequential
launch strategy, we created a dummy, which equals one if the new product had been introduced
4
In 90% of all cases, the bivariate correlations between the different measures were below .35. The highest
correlation was recorded between advertising intensity and the market power of national brands vis-à-vis private
labels in France and amounted to .54.
15
in another country before5. If the dummy equals zero, no previous experience is available with
respect to the new product (cf. Golder 2000). Information on the reputation of the brand under
which the new product was introduced and the degree of newness of the new product were
provided by Europanel which collected this information among category management experts of
their local subsidiaries. Experts also have been used in other recent research for these purposes
(Gatignon and Xuereb 1997, Goldenberg, Lehmann, and Mazursky 2001, Pauwels et al. 2004,
Steenkamp and Gielens 2003). Each new product was rated independently by a varying group of
two to five experts. Brand reputation was measured by a three-point item pertaining to whether it
was a high quality brand (cf. Choi 1998). The degree of newness of a new product was measured
by a five-point item, referring to the extent to which the product was new and unique (Henard
and Szymanski 2001). Ratings for each item were discussed between Europanel experts until
consensus was obtained.
Competitive environment. Product categories were based on IRI‟s classification.
Assignment of new products was typically straightforward, but was discussed in detail with
managers of Europanel. Computation of all competitive environment variables was based on
information collected in the year prior to introduction. Market concentration was measured by
the combined market share of the top three brands in the category (Lipczynski and Wilson 2001).
The extent of price competition in the category is operationalized as the percentage of volume
sold on promotion in the category (Cotterill, Putsis, and Dhar 2000). The degree of non-price
competition through innovation and advertising is operationalized as the number of new SKUs
introduced into a category relative to the total number of SKUs in the year previous to new
5
We explicitly checked whether a product was launched in any other country in the world prior to its launch in
France Germany Spain or the U.K
16
product entry and the advertising-to-sales ratio (Lipczynski and Wilson 2001), respectively, both
measured at the category level.
The market power of national brands vis-à-vis private labels was operationalized using
the quasi-Lerner index (Connor and Peterson 1992), L = (PNB-PPL)/PNB where PNB (PPL) is the
market share weighted average price of national brands (private labels). It reflects national
brands‟ ability to raise prices above the prices of quality-equivalent private labels (Parker and
Kim 1997). A positive value of L indicates the presence of national-brand specific market power
versus private labels (Connor and Peterson 1992). In estimating the effect on first-year success of
the market power of national brands vis-à-vis private labels using the Lerner index, we control
for quality differences between national brands and private labels by adding the quality gap
between national brands and private labels in the category as a covariate6.
Consumer characteristics. Dispositional innovativeness was measured using an eight-
item instrument developed by Steenkamp and Gielens (2003). Items were rated on five-point
Likert scales. The items were administered to all 16,000 panel members (in France, Germany,
and Spain after back translation). Configural and metric invariance of the dispositional
innovativeness items across countries were supported.7 Thus, we can validly compare the effects
of dispositional innovativeness across countries (Steenkamp and Baumgartner 1998). Cronbach‟s
alpha was .81, .83, .75, and .80, respectively in France, Germany, Spain, and the U.K. A
6
Information on the quality gap was collected in consumer questionnaires (cf. Narasimhan, Neslin, and Sen 1996).
We administered two items: “In this category, the quality of brands is very high” and “In this category, the quality of
shops‟ own labels is very high,” to about 1,000 consumers in each country. The items were discussed with
Europanel experts and were pretested. Each category was evaluated, on average, by 106 (France) to 136 (U.K)
consumers. Respondents were users of the category. Item scores were averaged within categories, and the quality
gap was computed as the difference between the two average scores.
7
Configural invariance of the one-factor model was supported. Although the 2 is highly significant, which is not
unexpected given the large sample size (Anderson and Gerbing 1988), the other indices indicated good model fit:
2(76)=3530.87 (p .10; 101,Germany = .329, p .10). The impact on purchase trend was also
positive, but did only reach statistical significance in France and Germany (102,France = .048, p .10, 102,UK = .028, p > .10). These results
suggest that the impact of a sequential rollout strategy steadily grows over time in France and
Germany. For instance in Germany, in the first quarter the impact was about 21% below the
overall first-year average of 7% (= (exp(.102+.069*(-3))*100)-(exp(.102)*100)))9 and in the last
quarter 25% above the first-year average (= (exp(.102+.069*(3))*100)-(exp(.102)*100))).
Brand reputation had a positive impact on first year purchase intensity (003,France = .028, p .10).
Heavy competition using the price promotion weapon had its expected negative effect on
new product success in Germany (008,Germany = -.019, p .10)
and in Spain the effect was in the opposite direction (008,Spain = .007, p .10; 108 ,UK = -.001, p > .10).
In line with expectations, the effect of price promotion intensity in the category was
moderated by the newness of the new product as witnessed by the positive significant effect in
Germany, Spain, and the U.K. (009,Germany = .021, p .10;
24
1010,UK = -.103, p > .10), but the effect only reached significance in France and Germany. The
positive effect of new product introduction activity on purchase intensity was reinforced if the new
product scored high on newness (0011,France = .017, p .10; 1012,Germany = -.026, p .10;
1014,Spain = .039, p .10).
25
Consumer Characteristics
We found support for our hypothesis that consumers higher on dispositional innovativeness buy
more of the new product (010,France = .222, p .10). With respect to household size we found a consistent positive significant effect across
countries on a consumer‟s first year purchase intensity (030,France = .154, p .10; 140,Spain = .035, p < .01). In Germany and the U.K. a negative effect was
reported (140,Germany = -.022, p < .01; 040,UK = -.001, p < .01).
DISCUSSION
This paper investigates the effect of product, competitive environment, and consumer drivers on
market success of new CPGs in a cross-national context. We structure our main conclusions and
implications around the two caveats to a strategy of relying on innovation to strengthen the
company‟s position identified in the Introduction section: (i) it is a very risky strategy, in that the
overwhelming majority of new CPGs fails in the marketplace, requiring insight into the drivers
of new product success, and (ii) it is a very costly strategy, necessitating that firms increasingly
launch their products in international markets, which requires detailed knowledge of the extent of
generalizability of factors underlying new product success across countries.
Drivers of New Product Success
New products can fail because 1) R&D has not yielded a product that appeals to the marketplace
and/or because 2) the marketing strategy associated with the new product launch has been
ineffective (Cook and Georgiadis 1997). Concerning the first cause of new product failure, a key
parameter of the new product‟s attractiveness is its degree of newness. We find a U-shaped
relation between newness and market success. Products of either incremental or major newness
are more successful than products of intermediate newness. This effect increases over time.
Products of intermediate newness appear to be stuck in the middle: too high on complexity
compared to products of incremental newness and too low on relative advantage compared to
products of major newness. Products that rate intermediate on newness may be identified before
launch and subject to closer scrutiny to assess whether certain features can be changed to modify
its newness.
27
An attractive innovation strategy that combines both ends of the U is a pulse strategy in
which really new innovations are introduced from time to time, followed by incremental product
improvements and line extensions, to fine-tune the product based on market feedback and to fill
additional niches. Such a strategy is likely to be more successful than continuous intermediate-
level innovations. P&G‟s Swiffer cleaning system has followed this strategy to build a $1 billion
product in a relatively short time. The original Swiffer was a major innovation. Subsequent
incremental innovations introduced Swiffer Wet, Swiffer Dusters, Swiffer WetJet, Swiffer Mitts,
and Swiffer Max, new scents for the cloth, etc.
While incremental innovations are typically relatively easy to achieve in the R&D process,
this is less straightforward for major innovations. A study among 13 leading U.S. CPG companies
identified the generation of major new product ideas “as the critical bottleneck for growth” (Cook
and Georgiadis 1997, p. 96). It further found that consumers are the second most important source
of innovation (after competitors). However, not every consumer is equally useful in generating new
ideas and in evaluating really new products in the concept stage. Our work suggests that companies
might want to focus on the input of consumers that are relatively high on dispositional
innovativeness. These consumers have a higher tolerance for ambiguity, are more open to change,
curious, and creative, and have a lower need for clarity and structure (Foxall 1988). This personality
profile indicates that these people are less prone to reject really new ideas while being more likely to
come up with less conventional ideas themselves. Moreover, in this way, the company gets input
from those consumers who have a considerably higher purchase intensity with respect to the new
CPG in the crucial first year after launch. In sum, in order to increase the chances of coming up with
major new product ideas, we recommend that in the R&D process, companies listen selectively to
“the voice of the customer” and as such create a lead-user effect (cf. Morrison, Roberts, and von
28
Hippel 2000). One large U.S. CPG company has put this into practice, using a short-form of the
dispositional innovativeness scale, as screener for recruitment for their concept testing.
Concerning the second cause of new product failure identified by Cook and Georgiadis
(1997), even when the R&D process has produced a new CPG product that appeals to the
marketplace, it may still fail due to an ineffective marketing strategy. This is not unique to the
CPG industry. Indeed, there may be relatively few industries where Moore‟s (1995) contention
applies that “the appropriate marketing strategy is to supply, and not to court, the customers”
(Bayus, Erickson and Jacobson 2003, p. 209). We identify three product-related variables that
affect new product success, viz., marketing resources, the launch strategy, and its branding
strategy. New product success is greater when the product is supported by more marketing
resources, when the product has been launched previously in another country (with the exception
of the U.K.; see below) - and this effect is further strengthened in the case of truly new products -
and when it is marketed as a brand extension, using a reputable brand name. Successful product
introductions contribute to the power in the category and to brand reputation (Choi 1998), which
will contribute to the success of future new product introductions, creating a virtuous cycle of
innovation success. Finally, we also find that new product success is affected by the competitive
environment, albeit the results differ somewhat between countries (see below).
Cross-National Generalizations
Our source model was tested in four major European countries. To what extent are there general
rules concerning the firm‟s ability to expand sales through new product development and
marketing (Farley and Lehmann 1994)? Which factors have a similar impact on new product
success in different countries, and hence could be part of international new product introduction
29
strategies? Which ones work out differently in different countries, and hence should be part of
local adaptations of introduction strategies?
Many of our findings are consistent across countries. In all countries, the new product
profits from more intensive marketing support and the reputation of the brand. The U-shaped
relation between newness and sales is found in all countries. We consistently find that the
positive effects of really new products and brand reputation increase over time. The effect of the
competitive environment variables relative power of national brands versus private labels and
competition on new product introductions go in the same direction in all countries. In all four
countries, we find that product newness has a positive moderating effect on the effect of the
competitive environment variables category price promotion intensity and new product
introduction intensity. We also find in all four countries that brand reputation has a positive
moderating effect on the effect of the competitive environment category advertising intensity.
Perhaps the most important cross-national generalization is that the consumer variables work in the
same direction on purchase intensity in all four countries. Although the magnitude of the effects
differs somewhat across countries, in each country the first-year purchase intensity of new CPGs is
higher among consumers higher on dispositional innovativeness, larger households, younger
consumers, and consumers living in the country‟s metropolis. This implies that a cross-national
„ideal prospect‟ segment exists that offers a basis for pan-European (or global, if the segment is also
found in other parts of the world) marketing strategies. For illustrative purposes, we define the ideal
prospect segment as those consumers who are in the top 25% on dispositional innovativeness and
household size, the bottom 25% on age, and who live in a metropolis. Compared to the
unsegmented market, this ideal prospect scheme has, in the first year after launch, a purchase
intensity which is, an average, 80%, 94%, 28% and 32% higher in respectively France, Germany,
30
Spain, and the U.K. Note that this ideal prospect scheme can be easily applied and rates high on
actionability. Not only is socio-demographic information readily available, dispositional
innovativeness can be measured a priori rather than ex post. Thus, consumers can be classified
according to their score on the innovativeness instrument before product introduction. This offers
the firm the opportunity to develop targeted strategies beforehand rather than after the critical first
months after introduction. One CPG firm uses the dispositional innovativeness items on their direct
marketing databases in several European countries and the U.S., e.g., for targeting coupons at the
more innovative consumers. This involves segmenting millions of addresses so that they can target
appropriately. Another large CPG firm uses the items on simulated test markets and has started to
build up purchase intent benchmarks for consumers who rate high on dispositional innovativeness
to decide on new product launches.
Notwithstanding these cross-national communalities, a number of interesting differences
between countries can also be observed. We find that a sequential launch strategy, in which the
product has been introduced before in another country, has a significant, positive impact on first
year success in France, Germany, and Spain. No significant effect on either intensity or trend is
found in the U.K. The difference in effectiveness of a sequential rollout strategy between the
U.K. and the other three countries is even more pronounced in case the new product scores high
on newness. The findings are consistent with the game-theoretic predictions of Kalish, Mahajan,
and Muller (1995). These authors derived analytically that a sequential strategy is favored for
countries whose consumers are relatively lower on innovativeness. Our results indicate that the
segment of consumers relatively high on dispositional innovativeness is indeed much larger in
the U.K. than in the other three countries. We computed the median of the distribution of
dispositional innovativeness scores pooled across the total pan-European sample of 16,000
31
consumers, weighted for population size and identified how many consumers in each country
rated above the pan-European median. This reveals that in a European context, 70.1% of the
British consumers are relatively innovative (rate above the pan-European median dispositional
innovativeness score), versus 48.7% of the Germans, 44.1% of the French, and 46.7% of the
Spanish.
Second, there are differences across countries in the effect of several competitive
environment variables. Concentration works in the expected direction in all countries but
Germany. This may be due to a unique feature of the German CPG industry, viz., the strong
position of the hard discounter Aldi (Bachl 2003). Aldi carries no national brands and its market
share has grown dramatically over the last decade. Consequently, its private label is often one of
the largest in the category. In fact, the correlation between market concentration in the category
and Aldi‟s share in the category is .51. Since Aldi does not collude with national brands, this
implies that collusion opportunities may in fact be less in more concentrated markets.
In France, Germany, and the U.K. we find, as expected, that new product success is less
in heavily promoted categories. In Spain, the effect is less pronounced. The promotional
environment differs widely across Europe, due to different traditions and legal frameworks
specifying what types of promotion are allowed. Nevertheless, we find consistently that
relatively novel innovations suffer less from potential barriers erected by heavy price promoting.
Investing in newness thus helps to overcome competitive hurdles more easily.
Heavy advertising in the category acts as a barrier to entry in France, Spain, and the U.K.
In contrast, heavy category advertising seems to facilitate new product success in Germany
whereby we note that this positive effect decreases gradually over time. Scherer and Ross (1990,
p. 572) noted that advertising need not always act as barrier to entry and as weapon of “artificial”
32
product differentiation. They argued that “advertising can perfect competition by helping
consumers make better informed choices.” They posited that newspaper advertising is
“preponderantly informative” (p. 572). Informative advertising provides information about a
product‟s price and its qualities, which increases market transparency. This may explain the
German results, as the share of print advertising is considerably higher in Germany (70%)
compared to France (50%), Spain (47%), and the U.K. (58%) (Euromonitor 2003).
Third, apart from these cross-national differences in the effect of competitive
environment, the level of a specific competitive environment variable in a specific category may
differ between countries, giving rise to differences in success of any given new product across
countries. After all, companies face global as well as local competitors in each market, the power
of private labels in a given category can differ between countries, and even global companies can
use different intensity of instruments across countries. For example, market concentration in
ready-to-eat cereals is 78% in Spain versus 52% in the U.K. Market power of national brands
(using the Lerner index) in the yogurt market is .57 in Germany, but only .20 in France and .09
in the U.K. Advertising intensity in the bath and shower market is 13% in Spain versus 4% in the
U.K., while promotion intensity in the fabric detergents category is 42% in Germany versus 19%
in France. Hence, for any given product introduction, the influence of the competitive
environment can differ substantially between countries. This underlines the importance of local
implementation, even for global strategies.
Limitations
Our study has various limitations, which offer avenues for future research. First, the empirical
part of our study focused on new packaged goods in France, Germany, Spain, and the U.K. The
question remains to what extent our findings may be generalizable to other countries. Including
33
more countries within and outside Europe would allow us to extend the scope of our
recommendations from a pan-regional to global scale. Moreover, a fourth country-level could
thus be integrated in our model, which would allow us to formally test the impact of cultural and
economic factors that may give rise to country differences.
Second, the measurement of some of our constructs could be further refined. Our
dependent variable was provided at a 3-monthly temporal level of aggregation. Future research
might employ monthly or even weekly data to increase the power of the trend analysis.
Following Balasubramanian and Kumar (1990, 1997) market share in the category was used as a
proxy for the marketing resources available to support the new product introduction.
Nevertheless, a direct measure of marketing support given to the new product is to be preferred.
As no information was available on the exact order of launch in different markets, the impact of
the sequential rollout strategy was measured using a dummy variable indicating whether the
product was introduced before in any other country. Differences in the effects across earlier and
later lagging countries and between specific pairs of countries could thus not be established. Our
overall measure of product newness is commonly used in new product research (Henard and
Szymanski 2001), but could be refined. Gatignon et al. (2002) identified a set of measures to
evaluate a new product‟s locus, type and characteristics. Assessing the new product with greater
clarity on the units of analysis could lead to more insightful research on NPD.
Third, another source of variation that might be included in future research deals with the
store environment. Retailers are confronted with large numbers of CPG introductions in a wide
variety of categories. Desiraju (2001) reports that retailers have reacted to this onslaught of
introductions in variety of ways. Some retailers openly solicit new products indicating these new
items as the lifeblood of their business that have to be in their store before their competitors do.
34
Other retailers, in contrast, argue that introducing a new product is a service, which they provide to
the manufacturer. As a result, retailers have different attitudes towards new products. More
innovative retailers will provide a more nurturing environment for these new products, which will
positively impact the sales volume of these products. Future research could investigate the impact
and moderating effects of aspects of the retail environment such as retail pricing policy, private
label policy, etc. Further exploration of what aspects of the retail environment benefit the new
product in its infancy, may lead to improved predictions on what type of retail concepts may be
more interesting to build strategic relationships with and whether we can derive a general profile of
these „preferred‟ retailers across different countries.
35
REFERENCES
Assael, Henry (1995), Consumer Behavior and Marketing Action, Cincinnati, OH: South-
Western College Publications.
Ailawadi, Kusum L., Scott A. Neslin, and Karen Gedenk (2001), “Pursuing the Value-Conscious
Consumer: Store Brands Versus National Brand Promotions,” Journal of Marketing, 65
(January), 71-89.
Anderson, James C. and David W. Gerbing (1988), “Structural Equation Modeling in Practice: A
Review and Recommended Two-Step Approach,” Psychological Bulletin, 103 (3), 411-423.
Bachl, Thomas (2003), “The Hard Discounter Menace: Examples from Germany,” Presentation
given at the GfK/Europanel Seminar, March 27, Kronberg, Germany.
Balasubramanian, Siva K. and V. Kumar (1990), “Analyzing Variation in Advertising and
Promotional Expenditures: Key Correlates in Consumer, Industrial and Service Market,”
Journal of Marketing, 54 (April), 57-68.
Balasubramanian, Siva K. and V. Kumar (1997), “Explaining Variations in the Advertising and
Promotional Costs/Sales Ratio: A Reanalysis,” Journal of Marketing, 61 (January), 85-92.
Bayus, Barry L., Gary Erickson, and Robert Jacobson (2003), “The Financial Rewards of New
Product Introductions in the Personal Computer Industry,” Management Science, 49 (2), 197-
210.
Boulding, William, Eunkyu Lee, and Richard Staelin (1994), “Mastering the Mix: Do
Advertising, Promotion, and Salesforce Activities Lead to Differentiation?” Journal of
Marketing Research, 31 (May), 159-172.
Calantone, Roger J., Jeffrey B. Schmidt, and X. Michael Song (1996), “Controllable Factors of
New Product Success: A Cross-National Comparison,” Marketing Science 15 (4), 341-358.
36
Chandrashekaran Murali and Rajiv Sinha (1995), “Isolating The Determinants of Innovativeness:
A Split-Population Tobit (SPOT) Duration Model Of Timing and Volume of First and
Repeat Purchase,” Journal of Marketing Research, 32 (December), 444-456.
Chatterjee, Rabikar and Jehoshua Eliashberg (1990), “The Innovation Diffusion Process in a
Heterogeneous Population: A Micromodeling Approach,” Management Science, 36 (9),
1057-1074.
Chen, Ming-Jer, Ken G. Smith, and Curtis M. Grimm (1992), “Action Characteristics as
Predictors of Competitive Response,” Management Science, 38 (3), 439-455.
Choi, Jay P. (1998), “Brand Extension as Informational Leverage,” Review of Economic Studies,
65 (225), 655-669.
Comanor, William S. and Thomas A. Wilson (1967), “Advertising Market Structure and
Performance,” The Review of Economics and Statistics, 49 (4), 423-440.
Connor, John M. and Everett B. Peterson (1992), “Market-Structure Determinants of National
Brand-Private Label Price Differences of Manufactured Food Products,” The Journal of
Industrial Economics, 40 (2), 157-171.
Cook, John D. and Pantelis A. Georgiadis (1997), “Packaged Goods: It‟s Time to Focus on
Product Development,” The McKinsey Quarterly, 2, 91-99.
Cotterill, Ronald W., William P. Putsis, and Ravi Dhar, (2000), “Assessing the Competitive
Interaction btween Private Labels and National Brands,” Journal of Business, 73 (1), 109-
137.
Dekimpe, Marnik G., Miklos Sarvary, and Philip M. Parker (1998), “Staged Estimation of
International Dffusion Models: An Application to Global Cellular Telephone Adoption,”
Technological Forecasting and Social Change, 57, 105-132.
37
Dekimpe, Marnik G., Miklos Sarvary, and Philip M. Parker (2000), “Global Diffusion of
Technological Innovations: A Coupled-Hazard Approach,” Journal of Marketing Research,
37 (February), 47-59.
Desiraju, Ramarao (2001), “New Product Introductions, Slotting Allowances, and Retailer
Discretion,” Journal of Retailing, 77 (3), 335-358.
Drucker, Peter F. (1999), The Frontiers of Management: Where Tomorrow's Decisions Are
Being Shaped Today, New York, NY: Truman Talley Books/Plume.
Ernst&Young/ACNielsen (2000), New Product Introduction, Successful Innovation/Failure: A
Fragile Boundary, Paris: Ernst&Young Global Client Consulting.
Euromonitor (2003), Global Market Information Database, London.
Fader, Peter S. and Leonard M. Lodish (1990), “A Cross-Category Analysis of Category
Structure and Promotional Activity for Grocery Products,” Journal of Marketing, 54
(October), 52-65.
Farley, John U. and Donald R. Lehmann (1994), “Cross-National Laws and Differences in
Market Response,” Management Science 40 (1), 111-122.
Ferguson, George A. (1981), Statistical Analysis in Psychology and Education, New York, NY:
McGraw-Hill, 5th ed.
Foxall, Gordon R. (1988), “Consumer Innovativeness: Novelty Seeking, Creativity and Cognitive
Style,” in Research in Consumer Behavior, Vol. 3, Eds. Elisabeth C. Hirschman and Jagdish N.
Seth, Greenwich, CT: JAI, 79-113.
Ganesh, Jaishankar and V. Kumar (1996), “Capturing the Cross- National Learning Effect: An
Analysis of an Industrial Technology Diffusion,” Journal of the Academy of Marketing
Science, 24 (3), 328-337.
38
Ganesh, Jaishankar, V. Kumar, and Velavan Subramaniam (1997), “Learning Effect in
Multinational Diffusion of Consumer Durables: An Exploratory Investigation,” Journal of the
Academy of Marketing Science, 25 (3), 214-228.
Gatignon, Hubert, Jehosua Eliashberg, and Thomas S. Robertson (1989), “Modeling Multinational
Diffusion Patterns: An Efficient Methodology,” Marketing Science, 8 (3), 231-247.
Gatignon, Hubert and Thomas S. Robertson (1985), “A Propositional Inventory for New Diffusion
Research,” Journal of Consumer Research, 11 (March), 849-867.
Gatignon, Hubert, Michael L. Tushman, Wendy Smith, and Philip Anderson (2002), “A Structural
Approach to Assessing Innovation: Construct Development of Innovation Locus, Type and
Characteristics,” Management Science, 48 (9), 1103-1122.
Gatignon, Hubert and Jean-Marc Xuereb (1997), “Strategic Orientation of the Firm and New
Product Performance,” Journal of Marketing Research, 34 (February), 77-90.
Gauvin, Stephane and Rajiv K. Sinha (1997), “Innovativeness in Industrial Organizations: A Two-
Stage Model of Adoption,” International Journal of Research in Marketing, 10 (2), 165-183.
Goldenberg, Jacob, Donald R. Lehmann, and David Mazursky (2001), “The Idea Itself and the
Circumstances of Its Emergence as Predictors of New Product Success,” Management Science,
47 (1), 69-84.
Golder, Peter N. (2000), “Insights from Senior Executives about Innovation in International
Markets,” Journal of Product Innovation Management, 17 (5), 326-340.
Golder, Peter N. and Gerard J. Tellis, (1993), “Pioneer Advantage: Marketing Logic or Marketing
Legend?” Journal of Marketing Research, 30 (May), 158-170.
39
Han, Jin K., Namwoon Kim, and Hong-Bumm Kim (2001), “Entry Barriers: A Dull-, One-, Or
Two-Edged Sword For Incumbents? Unraveling The Paradox from a Contingency
Perspective,” Journal of Marketing, 65 (January), 1-13.
Hannerz, Ulf (1990), “Cosmopolitans and Locals in World Culture,” Theory, Culture & Society,
7 (2/3), 237-251.
Helsen, Kristiaan, Kamel Jedidi, and Wayne S. DeSarbo (1993), “A New Approach to Country
Segmentation Utilizing Multinational Diffusion Patterns,” Journal of Marketing, 57 (October),
60-71.
Helsen, Kristiaan and David C. Schmittlein (1994), “Understanding Price Effects for New
Nondurables: How Price Responsiveness Varies Across Depth-of-Repeat Classes and Types
of Consumers,” European Journal of Operational Research, 76, 359-374.
Henard, David H. and David M. Szymanski (2001), “Why Some New Products Are More
Successful Than Others,” Journal of Marketing Research, 38 (August), 362-375.
Hoch, Stephen J. (1996), “How should National Brands Think about Private Labels?” Sloan
Management Review, 37 (Winter), 89-102.
Im, Subin, Barry L. Bayus, and Charlotte H. Mason (2003), “An Empirical Study of Innate
Consumer Innovativeness, Personal Characteristics, and New-Product Adoption Behavior,”
Journal of the Academy of Marketing Science, 31 (1), 61-73.
Jaccard, James, Robert Turrisi, and Choi K. Wan (1990), Interaction Effects in Multiple
Regression, Newbury Park, CA: Sage.
Janssens, Maddy, Jeanne M. Brett, and Frank J. Smith (1995), “Confirmatory Cross-Cultural
Research: Testing the Viability of a Corporation-Wide Safety Policy,” Academy of
Management Journal, 38 (2), 364-382.
40
Kalish, Shlomo, Vijaj Mahajan, and Eitan Muller (1995), “Waterfall and Sprinkler New-Product
Strategies in Competitive Global Markets,” International Journal of Research in Marketing, 12
(2), 105-119.
Kleinschmidt, Elko J. and Robert G. Cooper (1991), “The Impact of Product Innovativeness on
Performance,” Journal of Product Innovation Management, 8 (4), 240-251.
Lal, Rajiv (1990), “Price Promotions: Limiting Competitive Encroachment,” Marketing Science, 9
(3), 247-262.
Lypczynski, John and John Wilson (2001), Industrial Organisation. An Analysis of Competitive
Markets, Harlow: Financial Times-Prentice Hall.
Mahajan, Vijay and Eitan Muller (1994), “Innovation Diffusion in a Borderless Global Market: Will
the 1992 Unification of the European Community Accelerate Diffusion of New Ideas, Products
and Technologies,” Technological Forecasting and Social Change, 45, 221-235.
Mahajan, Vijay, Eitan Muller, and Yoram Wind (2000), New-Product Diffusion Models, Norwell,
MA: Kluwer Academic Publishers.
Manning, Kenneth C., William O. Bearden, and Thomas J. Madden (1995), “Consumer
Innovativeness and the Adoption Process,” Journal of Consumer Psychology, 4 (4), 329-345.
Marketing Science Institute (2002), 2002-2003 Research Priorities, MA, Cambridge: Marketing
Science Institute.
Mela, Carl F., Sunil Gupta, and Kamel Jedidi (1998), “The Long-Term Impact of Promotions on
Consumer Stockpiling Behavior,” International Journal of Research in Marketing, 15 (2), 89-
107.
Midgley, David F. and Grahame R. Dowling (1978), “Innovativeness: The Concept and Its
Measurement,” Journal of Consumer Research, 4 (March), 229-242.
41
Moore, Geoffrey A. (1995), Inside the Tornado, New York, NY: Harper Business.
Moorthy, Sridhar and Hao Zhao (2000), “Advertising Spending and Perceived Quality,” Marketing
Letters, 11 (3), 221-233.
Morrison, Pamela D., John H. Roberts, and Eric von Hippel (2000), “Determinants of User
Innovation and Innovation Sharing in a Local Market,” Management Science, 46 (12), 1513-
1527.
Narasimhan, Chakravarthi, Scott A. Neslin, and Subrata K. Sen (1996), “Promotional Elasticities
and Category Characteristics,” Journal of Marketing, 60 (April), 17-30.
Nijs, Vincent, Marnik G. Dekimpe, Jan-Benedict E.M. Steenkamp, and Dominique M. Hanssens
(2001), “The Category Demand Effects of Price Promotions,” Marketing Science, 21 (1), 1-
22.
Parker, Philip and Namwoon Kim (1997), “National Brands Versus Private Labels: An Empirical
Study of Competition, Advertising and Collusion,” European Management Journal 15 (3),
220-235.
Pauwels, Koen, Jorge Silva-Risso, Shuba Srinivasan and Dominique M. Hanssens (2004), “New
Products, Sales Promotions and Firm Value, With Application to the Automobile Industry,”
Journal of Marketing (forthcoming).
Putsis, William P. Jr., Sridhar Balasubramanian, Edward H. Kaplan, and Subrata K. Sen (1997),
“Mixing Behavior in Cross-Country Diffusion,” Marketing Science, 16 (4), 354-369.
Raju, P. S. (1980), “Optimum Stimulation Level: Its Relationship to Personality, Demographics,
and Explanatory Behavior,” Journal of Consumer Research, 7 (December), 272-282.
Rao, Vithala R. and Edward W. McLaughlin (1989), “Modeling the Decision to Add New Products
by Channel Intermediaries,” Journal of Marketing, 53 (January), 80-88.
42
Raudenbush, Steve W. and Anthony S. Bryk (2002), Hierarchical Linear Models: Applications and
Data Analysis Methods, Second Edition. Newbury Park, CA: Sage
Raudenbush, Steve W., Anthony S. Bryk, and Richard Congdon (2000), HLM 5: Hierarchical
Linear and Nonlinear Modeling, Lincolnwood, IL: Scientific Software International.
Robinson, William T. and Claes Fornell (1985), “Sources of Pioneer Advantages in Consumer
Goods Industries,” Journal of Marketing Research, 22 (August), 305-317.
Schmalensee, Richard (1978), “Entry-Deterrence in the Ready to Eat Breakfast Cereal Industry,”
Bell Journal of Economics 9 (2), 305-327.
Scherer, Frederick M. and David Ross (1990), Industrial Market Structure and Economic
Performance, Boston, MA: Houghton Mifflin.
Seetharaman, P.B. and Pradeep Chintagunta (1998), “A Model of Inertia and Variety-Seeking with
Marketing Variables,” International Journal of Research in Marketing, 58 (1), 1-17.
Sinha, Rajiv K. and Murali Chandrashekaran (1992). “A Split Hazard Model for Analyzing the
Diffusion of Innovations,” Journal of Marketing Research, 29 (February), 116-127.
Shankar, Venkatesh, Gregory Carpenter, and Lakshman Krishnamurthi (1998), “Late Mover
Advantage: How Innovative Late Entrants Outsell Pioneers,” Journal of Marketing Research,
35 (February), 54-70.
Shapiro, Carl (1983), “Premiums for High Quality Products as Returns to Reputation,” Quarterly
Journal of Economics, 98 (4), 659-680.
Steenkamp, Jan-Benedict E.M. and Hans Baumgartner (1998), “Assessing Measurement Invariance
in Cross-National Research,” Journal of Consumer Research, 25 (June), 78-90.
43
Steenkamp, Jan-Benedict E.M. and Steven M. Burgess (2002), “Optimum Stimulation Level and
Exploratory Consumer Behavior in an Emerging Market,” International Journal of Research in
Marketing, 19 (2), 131-150.
Steenkamp, Jan-Benedict E.M. and Katrijn Gielens (2003), “Consumer and Market Drivers of the
Trial Probability of New Consumer Packaged Goods,” Journal of Consumer Research, 29 (4)
(December), 368-384.
Stoolmiller, Mike (1995), “Using Latent Growth Curve Models to Study Developmental
Processes,” in Analysis of Developmental Change. Ed. J.M. Gottman, Mahwah, NJ:
Lawrence Erlbaum Associates, Inc, 103-138.
Takada, Hirokazu and Dipak Jain (1991), “A Cross-Nation Analysis of Consumer Durables in
Pacific Rim Countries,” Journal of Marketing, 55 (April), 48-56.
Talukdar, Debabrata, K. Sudhir, and Andrew Ainslie (2002), “Investigating New Product
Diffusion Across Products and Countries,” Marketing Science, 21 (1), 97-116.
Tellis, Gerard J., Stefan Stremersch, and Eden Yin (2003), “The International Takeoff of New
Products: The Role of Economics, Culture, and Country Innovativeness,” Marketing Science,
22 (2), 188-208.
Urban, Glen L. and John R. Hauser (1993), Design and Marketing of New Products, Englewood
Cliffs, NJ: Prentice-Hall, 2nd ed.
Wernerfelt, Birger (1988), “Umbrella Branding as a Signal of New Product Quality: An Example of
Signaling by Posting a Bond,” Rand Journal of Economics, 19 (3), 458-466.
Zuckerman, Marvin, D. (1994), Behavioral Expressions and Biosocial Bases of Sensation
Seeking, New York, NY: Cambridge University Press.
44
Table 1:Overview Literature
Sources of difference Dependent variable
Level First year
Authors Comp.
Empirical basis
aggregation Product Consumer Country Trial purchases
setting
Intensity Trend
Calantone et al. 1996 2 countries, 142 products
Dekimpe et al. 1998 74 countries, 1 D1
Dekimpe et al. 2000 160 countries, 1 D
Ganesh and Kumar 1996 10 countries, 1 ind. product
Ganesh et al. 1997 16 countries, 4 Ds
Market Gatignon et al. 1989 14 countries, 6 Ds
level Helsen et al. 1993 12 countries, 3 Ds
Mahajan and Muller 1994 16 countries, 1 Ds
Putsis et al. 1997 10 countries, 4 Ds
Takada and Jain 1991 4 countries, 8 Ds
Talukdar et al. 2002 31 countries, 6 Ds
Tellis et al. 2003 16 countries, 137 Ds
Chandrashekaran and Sinha 1995 3 1 country, 1 CPG2, 3236 cons.
Chatterjee and Eliashberg 1990 1 country, 65 consumers
Gauvin and Sinha 1997 1 country, 9742 consumers, 8 Ds
Helsen and Schmittlein 1994 3 1 country, 4 CPG, 2261 cons.
Im et al. 2003 1 country, 10CD, 296 cons.
Individual
level Manning et al. 1995 1 country, 74 consumers
Sinha and Chandrashekaran 1992 1 country, 3689 consumers, 1 D
Steenkamp and Burgess 2002 1 country, 3328 cons.
Steenkamp and Gielens 2003 1 country, 239 CPGs, 3658 cons.
4 countries, 301 CPGs, 16370
This study
consumers
Remarks: 1: D refers to durable; 2: CPG refers to consumer packaged good; 3: These studies look at the timing of repeat purchases rather than a trend.
Table 2: Overview Expected Effects of Key Determinants of First Year New Product Success
First year First year
Drivers of CPG success
purchase intensity purchase trend
Product strategy factors
Marketing resources + +
Sequential rollout strategy + +
Brand reputation + +
Product newness
* Sequential rollout strategy +
Competitive environment
Concentration - -
Price competition
Price promotion intensity - -
* Product newness +
Non-price competition
New product introduction intensity ? ?
* Product newness +
Advertising intensity - -
* Brand reputation +
Market power national brands viz. private labels + +
Consumer characteristics
Dispositional innovativeness + -
Age - +
Size household + +
Living in a country‟s metropolis + +
Table 3: Results
Expectation France Germany Spain U.K.
int. trend intensity trend intensity trend intensity trend intensity trend
Coef
Coef. t Coef. t Coef. t Coef. t t Coef. t Coef. t Coef. t
.
Product factors
Mark. resources (001, 101 ) + + .081 1.65 .019 .273 .143 2.02 .329 3.71 .120 2.05 .438 4.07 .469 1.58 .197 1.91
Sequential rollout (002, 102) + + .143 1.63 .048 3.64 .102 1.65 .069 2.32 .411 2.31 .016 .060 .063 1.15 .028 1.02
Brand reputation (003, 103) + + .028 1.70 .008 1.80 .369 4.47 .067 2.62 .142 1.96 .034 1.69 .510 2.09 .041 2.34
Newness (004, 104) -.041 3.28 -.006 2.67 -.101 3.24 .013 2.67 -.048 -1.88 -.022 3.05 -.103 1.72 -.019 2.58
Newness2 (005, 105) + + .080 3.68 .011 2.19 .205 5.00 .011 3.96 .075 1.79 .035 2.71 .253 1.98 .026 2.04
*Rollout (006, 106) + .181 2.66 .491 5.88 .092 1.73 -.060 2.31
Competitive environment
Concentration (007, 107) - - -.032 1.79 -.007 1.33 .025 7.04 -.004 .068 -.049 1.81 -.013 2.23 -.012 1.58 -.021 1.81
Price competition
Price prom. Int. (008, 108) - - -.008 .59 -.003 6.32 -.019 3.03 -.006 5.14 .007 1.74 -.001 1.01 -.025 1.53 -.001 .812
* Newness (009) + .009 .21 .021 4.15 .045 5.63 .086 1.40
Non price competition
NP intensity (0010, 1010) ? ? .169 3.15 -.007 8.51 .075 1.81 -.070 1.71 .044 2.38 -.024 1.31 .068 1.92 -.103 1.39
* Newness (0011) + .017 4.65 .022 3.37 .045 3.92 .075 2.75
Adv. Intensity (0012, 1012) - - -.079 1.43 -.001 .99 .060 2.49 -.026 1.99 -.100 2.03 -.102 1.73 -.060 1.48 -.062 1.84
* Brand reputation (0013) + .014 2.32 .052 2.24 .012 1.48 .074 1.67
Power NB (0014, 1014) + + .073 2.14 .095 2.47 .048 1.99 .020 .291 .061 1.67 .039 3.56 .058 1.83 .046 .354
Consumer
Dis. innovativ. (010, 110) + - .222 20.38 -.022 8.12 .276 21.36 -.019 4.62 .129 7.39 -.022 3.58 .089 8.32 -.013 10.10
Age (020, 120) - + -.007 4.43 .001 1.56 -.015 10.17 .001 2.95 -.017 13.07 -.000 .117 -.007 -4.18 .001 6.11
Size household (030, 130) + + .154 17.82 .006 3.45 .183 19.29 .006 3.95 .047 5.25 .009 4.35 .068 6.11 .019 11.97
Metropolis (040, 140) + + .151 5.18 .003 .059 .216 6.20 -.022 2.59 .291 7.04 .035 3.47 .019 2.61 -.001 3.48