Country-Level Performance of New
Experience Products in a Global
Rollout: The Moderating Effects of
Economic Wealth and National Culture
David A. Griffith, Goksel Yalcinkaya, and Gaia Rubera
ABSTRACT
International marketing manager decisions pertaining to a new experience product’s global rollout are critical to the
product’s country-level performance. Extending work on the lead–lag and success-breeds-success effects, the authors
examine how the country-specific factors of economic wealth and national culture influence the effects of a new experience product’s global rollout decisions (i.e., the time lag from initial lead country introduction to target country introduction and the number of countries in which the product was introduced before its introduction in the target country)
on the product’s country-level performance. The authors employ hierarchical linear modeling and, from an examination
of 259 unique movies gathered from 16 countries, corresponding to 2,523 total entries between 2006 and 2007, find
significant interaction effects between a country’s economic wealth and national culture and time lag and target country
position on the new experience product’s country-level performance. The authors conclude with a discussion of the
theoretical and practical implications.
Keywords: global rollout, experience products, national culture, hierarchical linear modeling, motion picture
lobal competition, driven in part by increased
cross-country communication, has created a
competitive environment in which managers are
increasingly challenged to consider cross-market effects
in their global product rollout decisions (Calantone and
Griffith 2007; Di Benedetto 1999; Rubera, Griffith, and
Yalcinkaya 2012; Tellefsen and Takada 1999). Of particular note, a firm must consider how both the product’s time lag to the target country market (i.e., the number of days between the date the product was first
introduced in the initial lead country and the date the
product is introduced in the target country) and the
G
David A. Griffith is Chairperson and Professor of Marketing, College
of Business and Economics, Lehigh University (e-mail: david.a.
[email protected]). Goksel Yalcinkaya is Associate Professor of
Marketing, Peter T. Paul College of Business and Economics, University of New Hampshire (e-mail: [email protected]). Gaia
Rubera is Associate Professor of Marketing, Department of Marketing, Bocconi University (e-mail: [email protected]). Bulent
Menguc served as associate editor for this article.
position of the target country market in the rollout (i.e.,
the number of countries in which the product was introduced before its introduction in the target country)
might influence the product’s country-level performance. This is especially true for experience products,
such as movies, music, concerts, sporting events, and
books, which are characterized by a short product life
cycle and a rapid decline in revenues after introduction
(Elberse and Eliashberg 2003; Krider and Weinberg
1998).
International marketing scholars have discussed the
global rollout decision as a strategic trade-off between a
simultaneous introduction (i.e., releasing the product
into all markets at the same time) and a sequential introduction (i.e., releasing the product into individual marJournal of International Marketing
©2014, American Marketing Association
Vol. 22, No. 4, 2014, pp. 1–20
ISSN 1069-0031X (print) 1547-7215 (electronic)
Country-Level Performance of New Experience Products 1
kets over time) (e.g., Ganesh 1998; Harvey and Griffith
2007; Kalish, Mahajan, and Muller 1995; Stremersch
and Tellis 2004). On the one hand, scholars contend
that while a simultaneous global product rollout allows
a firm to achieve first-mover advantages, it also
increases coordination complexity and overall costs
(e.g., Chryssochoidis and Wong 1998). On the other
hand, while a sequential global product rollout enables
the firm to spread product introduction costs over a
longer period and provides time for product modifications between market introductions, it can also decrease
a new product’s sales due to the introduction of
competitive offerings, gray market activity, or piracy
(e.g., Kalish, Mahajan, and Muller 1995; Stremersch
and Tellis 2004; Tellis, Stremersch, and Yin 2003).
While scholars continue to debate the costs and benefits
of each approach, in practice most global new product
introductions occur in a sequential manner of varying
lengths.
Despite the importance of global new product rollout,
and the widespread use of a sequential approach, limited empirical research has addressed this topic (Guiltinan 1999; Lee and Wong 2010). An examination of the
international marketing literature reveals several
notable shortcomings. First, the majority of prior
works examining global new product rollouts have
been conceptual, arguing that when firms engage in the
global rollout of new products, managers need to be
cognizant of coordination challenges (e.g., Guiltinan
1999; Vasilchenko and Morrish 2011). Second, the
empirical work related to this topic area focuses on
single-market product diffusion effects (e.g., Elberse
and Eliashberg 2003; Rubera, Griffith, and Yalcinkaya
2012; Stremersch and Tellis 2004; Tellis, Stremersch,
and Yin 2003). For example, Elberse and Eliashberg
(2003) find that a shorter time lag between domestic
and foreign market introduction positively influences
product performance in the lagged country. Third, with
limited exceptions (e.g., Elberse and Eliashberg 2003),
much of the diffusion literature has examined this issue
within the context of durable goods, leaving a lack of
clarity with respect to new experience products.
Fourth, research examining the timing of global launch
has primarily examined the delay between anticipated
and actual launch timing. For example, Chryssochoidis
and Wong (1998) assess international rollout timeliness
by examining the delay between scheduled and actual
rollout of new products across markets. As such, the
extant literature presents limitations in understanding
how global product rollout decisions influence countrylevel performance.
2 Journal of International Marketing
Previous research findings in the area of global rollout
and diffusion suggest a negative effect of time lag and a
positive effect of country position in the rollout on product performance (Rubera, Griffith, and Yalcinkaya
2012). However, of greater interest to those engaged in
the practice and study of international marketing, but so
far not empirically addressed within the context of new
experience products, is the question of when the time lag
and position effects on country-level product performance might be stronger and weaker. Providing insights
into this research question is the goal of this study, thus
contributing to the international marketing literature in
two ways. First, extending the literature on the lead–lag
(e.g., Ganesh and Kumar 1996; Kalish, Mahajan, and
Muller 1995; Kumar and Krishnan 2002) and successbreeds-success (e.g., Elberse and Eliashberg 2003; Hennig-Thurau, Houston, and Walsh 2006) effects, this
work outlines how economic wealth influences the effect
of the global rollout decisions of (1) time lag from the
lead market to the target country and (2) the number of
countries in which the product was introduced previously on a new experience product’s country-level performance. According to previous research, economic wealth
is a key influencer in new product acceptance (Chandrasekaran and Tellis 2008; Helsen, Jedidi, and DeSarbo
1993; Kumar 2014). By detailing how the economic
wealth of a country market influences the effectiveness of
specific global rollout decisions (i.e., time lag and position), this work extends the global rollout literature as
well as the international marketing literature related to
factors influencing product performance (e.g., Griffith
and Rubera 2014; Tellis, Stremersch, and Yin 2003).
Second, this study advances the international marketing
literature by demonstrating how national culture moderates the direct effects of time lag and position in a
global product rollout. Research has consistently
demonstrated the influence of national culture on new
product introduction and market entry (e.g., Chandrasekaran and Tellis 2008; Craig, Green, and Douglas
2005; Van Everdingen, Fok, and Stremersch 2009).
Extending this literature, we specify how the national
culture elements of individualism, power distance, masculinity, and uncertainty avoidance affect the influence
of global rollout decisions (i.e., time lag and position)
on country-level performance of a new experience product. In doing so, we contribute to the growing literature
on the influence of national culture, extend theory in the
international marketing domain related to global rollout, and assist international marketing managers in
more accurately estimating the effects on new experience product performance at the country level.
We begin by reviewing the lead–lag and success-breedssuccess effects as a theoretical foundation for understanding the influences of time lag and country position
in a global rollout on a new experience product’s
country-level performance. We then present a set of
moderation hypotheses that detail the effects of a country’s economic wealth and national culture on the influence of time lag and position in the global rollout on a
new product’s country-level performance. We present
the method and test the hypotheses using a data set of
259 unique movies gathered from 16 countries, corresponding to 2,523 total entries from 2006 to 2007.
Next, we discuss the results and their implications for
international marketing theory and practice. We conclude with the limitations of the study and future
research directions.
BACKGROUND LITERATURE AND
HYPOTHESES
Theoretical Foundation: Lead–Lag and
Success-Breeds-Success Effects
The theoretical foundation for understanding the global
rollout of a new experience product comes from the
innovation diffusion literature, which delineates the
lead–lag (e.g., Ganesh and Kumar 1996; Helsen, Jedidi,
and DeSarbo 1993; Kalish, Mahajan, and Muller 1995;
Krider et al. 2005; Kumar and Krishnan 2002; Takada
and Jain 1991) and success-breeds-success (e.g., Elberse
and Eliashberg 2003; Hennig-Thurau, Houston, and
Walsh 2006) effects. Taken together, these two effects
provide theoretical insight into timing issues (i.e., time
lag and position) related to the global rollout of new
products.
The lead–lag effect theorizes that sales in lead markets
influence demand in lag markets: Consumers in lag markets learn the benefits of a product from adopters in
lead markets, resulting in a faster diffusion rate in the
lag markets. Examining consumer durables, Takada and
Jain (1991) find that lagged adoption leads to faster diffusion. Consistent with Kalish, Mahajan, and Muller’s
(1995) explanation that the potential adopters in lag
markets closely watch the introduction and acceptance
of a new product in lead markets, this finding provides
the foundational argumentation for the importance of
momentum. That is, if the product is successful in the
lead market, diffusion of the product in the lag market
is likely to be faster because lag markets are aware of the
product’s prior success, thereby reducing the risk of
adoption associated with the product. Ganesh and
Kumar (1996) find that lag markets often have faster
diffusion rates than lead markets. Specifically, they find
that a “learning effect” exists across national borders,
preparing the lag market by communicating the benefits
of the innovation found in the lead market. Although no
specific theorization is available on unsuccessful products, extension of the lead–lag effect would suggest that
less successful products diffuse at a slower rate or fail to
diffuse to lag markets because of the cross-market learning effect.
The success-breeds-success effect theorizes that momentum generated by the success of the product in a lead
market may be quickly lost. The logic underlying this
effect is that the initial momentum gained creates shortterm awareness and a “learning effect” in cross-border
markets. However, the momentum a single product generates can quickly dissipate as consumers in lag markets
are exposed to information pertaining to competing
products. Researchers empirically examining the successbreeds-success effect have found that a longer time lag
between lead and lag market introductions results in a
weaker relationship between the product’s performance
in these two markets (e.g., Elberse and Eliashberg 2003;
Hennig-Thurau, Houston, and Walsh 2006). Empirical
support for the success-breeds-success effect has been
strongest for products with short product life cycles
(Elberse and Eliashberg 2003).
Global Rollout Decisions for New Experience
Products: Time Lag and Country Position
As we noted previously, when considering a global rollout, a firm must determine both the product’s time lag
to the target country market and the position of the target country market in the rollout. Regarding the time
lag of new experience products, particularly movies,
prior research indicates that the product’s previous
country success has a positive impact on consumers
(e.g., Elberse and Eliashberg 2003; Hennig-Thurau,
Houston, and Walsh 2006). That is, a successful movie
in one market fuels positive perceptions of moviegoers
in subsequent markets, and vice versa (i.e., a less successful movie in a lead market results in less positive perceptions in subsequent markets). In addition to improving perceptions, a product has the opportunity to set
patterns of consumer preferences in other markets and
thus influences diffusion (Johnson and Tellis 2008).
However, previous research also suggests that the
momentum generated in the home country dissipates
quickly (i.e., success-breeds-success), leaving little room
Country-Level Performance of New Experience Products 3
for movie studios to capitalize on the generated momentum (Elberse and Eliashberg 2003; Hennig-Thurau,
Houston, and Walsh 2006). Thus, to benefit from the
short-lived momentum generated in the lead market,
firms may implement a shorter release time for a product between the initial country and a subsequent country. Moreover, the availability of substitutable products
in the market—in our case, movies (one product category in the entertainment industry)—largely determines
the timing of product launch decisions (Calantone et al.
2010; Krider and Weinberg 1998).
In markets characterized by intensive competition, firms
tend to aggressively engage in rapid foreign market
entry to prevent competitive moves, thereby working to
maximize market performance (Stremersch and Tellis
2004). For example, Calantone and Griffith (2007)
argue that a rapid product rollout potentially restricts
other firms from producing imitative products and
reduces gray market activities. Moreover, because of the
short product life cycle of experience products, market
learning is limited, and the concentration of marketing
actions happens around the early part of the release,
necessitating a faster rollout across markets (Elberse and
Eliashberg 2003). Rapid product rollout also helps firms
recover quickly from high development costs (Golder
2000), which suggests minimization of the time lag to
enhance country-level performance.
Furthermore, we theorize that the position of a country
in a global rollout (i.e., the number of country market
introductions of the product before the target market)
influences the new experience product’s country-level
performance. Prior studies have found that preferences
in the lag market may be influenced by choices of users
in the lead market (Ganesh and Kumar 1996; Helsen,
Jedidi, and DeSarbo 1993; Kumar and Krishnan 2002;
Takada and Jain 1991). That is, the adoption of a new
product in a lead market may reduce uncertainty about
the benefits of the product in the lag market. Potential
adopters in a subsequent country may observe the success of the new product in the initial country, resulting
in a higher adoption rate in the lag market (or a lower
adoption rate in the lead market may result in a lower
adoption rate in the lag market). A growing number of
adopters in lead markets signal the credibility of a product (Erdem, Swait, and Valenzuela 2006) and reduce the
risk of adoption for potential customers in lag markets
(Sheth 1968). The need for quality signals is heightened
for new experience products because the quality of these
products is more difficult to judge before purchase than
that of nonexperience products. In line with this argu-
4 Journal of International Marketing
mentation, research in the movie industry indicates that
moviegoers are influenced by initial box-office information from previous countries, suggesting that they are
attracted to a movie after they become aware that a considerable number of others like it or are dissuaded from
a movie if it does poorly in a previous country (Elberse
and Eliashberg 2003; Litman and Ahn 1998; Neelamegham and Chintagunta 1999).
Taken together, the innovation diffusion literature
denotes the importance of building momentum in a
lead market that is carried over into new markets
(lead–lag) and the danger of allowing too long of a
period to expire before the introduction of a product
into a lag market (success-breeds-success). This suggests that country-level performance of a new experience product can be enhanced when there is a shorter
time lag between the introduction of the product in the
initial country market and in the target country market
and when the number of countries entered before the
target country is higher. In other words, we expect
(1) a negative relationship between time lag and countrylevel performance and (2) a positive relationship between
the number of previous countries and country-level
performance. These effects should be important to
international marketing managers, but of even greater
interest might be how specific country factors influence the product’s country-level performance in a
global rollout.
Extant literature (e.g., Elberse and Eliashberg 2003)
specifies the importance of analyzing specific country
factors to understand the introduction of new experience products into a global marketplace. Building on the
literature in the areas of global rollout, innovation diffusion, and international marketing, we examine the
effects of economic wealth and national culture as country factors. Table 1 provides the constructs, their definition, and the hypotheses.
Moderating Effect of Economic Wealth
Prior research maintains that a country market’s economic condition is highly influential when examining
new product introduction and adoption (Chandrasekaran and Tellis 2008; Golder and Tellis 2004;
Helsen, Jedidi, and DeSarbo 1993). Economic condition
is reflected in the economic wealth of a country and is
determined by the country’s gross domestic product
(GDP), which is the value of all the goods and services
produced in a country in a year (or another period). A
country’s GDP characterizes the standard of living of its
Table 1. Constructs, Their Definition, and Hypotheses
Construct
Definition
Hypothesis
Result
Economic
wealth
GDP as indicative of
country wealth
H1a: The economic wealth of a country positively moderates the
negative relationship between the time lag and the countrylevel performance of a new experience product.
Supported
Economic
wealth
Same as prior
H1b: The economic wealth of a country positively moderates the
positive relationship between the number of countries in
which a product was introduced before the target country and
the country-level performance of a new experience product.
Supported
Individualism
The tendency for people to
work alone and distance
themselves from the larger
social group to which they
belong
H2a: Individualism positively moderates the negative relationship
between time lag and country-level performance of a new
experience product.
Supported
Individualism
Same as prior
H2b: Individualism negatively moderates the positive relationship
between the previous number of countries in which a product
has been introduced before the target country and countrylevel performance of a new experience product.
Supported
Power
distance
The extent to which individuals accept an unequal
distribution of power
H3a: Power distance negatively moderates the negative relationship
between time lag and the country-level performance of a new
experience product.
Supported
Power
distance
Same as prior
H3b: Power distance negatively moderates the positive relationship
between the previous number of countries in which a product
has been introduced before the target country and countrylevel performance of a new experience product.
Not
supported
Masculinity
A country’s tendency to
value “masculine” goals
(e.g., recognition, achievement) over “feminine”
goals (e.g., social relationships, quality of life)
H4a: Masculinity positively moderates the negative relationship
between time lag and the country-level performance of a new
experience product.
Not
supported
Masculinity
Same as prior
H4b: Masculinity negatively moderates the positive relationship
between the previous number of countries in which a product
has been introduced before the target country and countrylevel performance of a new experience product.
Not
supported
Uncertainty
avoidance
A society’s tolerance for
uncertainty and ambiguity
H5a: Uncertainty avoidance negatively moderates the negative relationship between time lag and the country-level performance
of a new experience product.
Supported
Uncertainty
avoidance
Same as prior
H5b: Uncertainty avoidance positively moderates the positive relationship between the previous number of countries in which a
product has been introduced before the target country and
country-level performance of a new experience product.
Supported
citizens. Prior research suggests that the economic
wealth of a country, as captured by GDP, has a positive
effect on the diffusion of products in a market (Chandrasekaran and Tellis 2008; Golder and Tellis 2004).
The logic underlying this effect is that greater affordabil-
ity in countries with higher economic wealth decreases
the risk associated with new product adoption.
Building on this literature, we contend that in a country with greater economic wealth, the negative rela-
Country-Level Performance of New Experience Products 5
tionship between the time lag and a new experience
product’s target country-level performance will be
weaker. In general, consumers in wealthier countries
have greater disposable income than consumers in less
wealthy countries, which makes them less hesitant to
expend funds on newly introduced products (Van
Everdingen, Fok, and Stremersch 2009). When consumers have higher incomes and greater spending
power, they can better afford the risk of adopting
products whose performance is uncertain (Stremersch
and Tellis 2004). Furthermore, consumers in wealthier
countries are more connected with the global marketplace (e.g., through communication vehicles such as
the Internet) and, as such, are more likely to have the
opportunity to learn from those in other markets,
thereby reducing the risk and uncertainty associated
with new experience products. Thus, we theorize that
as country economic wealth increases, the negative
relationship between time lag and country-level performance will weaken. In other words, a country with
greater economic wealth acts as a buffer to the negative effect of time lag.
Regarding a country’s position in the global rollout, we
contend that the economic wealth of a country positively moderates the positive relationship between the
number of countries in which a product was introduced
before the target country and country-level performance. The logic underlying this expectation is that consumers with greater economic wealth are more connected with the global marketplace. Through this
connection, they learn about the introduction of the new
experience product and note the satisfaction of other
consumers more rapidly than those with less economic
wealth, resulting in higher levels of product adoption
(Stremersch and Tellis 2004). Learning effects are
heightened with new experience products. As such, we
contend that greater connectedness associated with
countries of higher economic wealth enhances the
success-breeds-success effect. More formally:
H1a: The economic wealth of a country positively
moderates the negative relationship between
the time lag and the country-level performance of a new experience product.
H1b: The economic wealth of a country positively
moderates the positive relationship between
the number of countries in which a product
was introduced before the target country and
the country-level performance of a new
experience product.
6 Journal of International Marketing
Moderating Effect of National Culture
National culture refers to the characteristics that create
a society’s profile, inclusive of norms, values, and institutions. Research consistently shows the influence of
national culture on new product introduction and market entry (Chandrasekaran and Tellis 2008; Dwyer,
Mesak, and Hsu 2005; Steenkamp, Ter Hofstede, and
Wedel 1999; Van den Bulte and Stremersch 2004; Van
Everdingen, Fok, and Stremersch 2009). To better
understand the effects of national culture, we employ
Hofstede’s (2001; see also Hofstede, Hofstede, and
Minkov 2010) cultural framework. We adopt this
framework for two reasons. First, Hofstede’s valuebased orientation characterizes the attitudes and behaviors influencing purchase decisions of new products.
Our arguments underscoring cross-market effects of
experience products directly pertain to Hofstede’s specific cultural dimensions (i.e., individualism, power distance, masculinity, and uncertainty avoidance). Second,
research has demonstrated that Hofstede’s value-based
framework provides a strong theoretical rationale for
national culture differences in the diffusion and adoption of new products (e.g., Chandrasekaran and Tellis
2008; Dwyer, Mesak, and Hsu 2005; Yalcinkaya 2008).
Consistent with Hofstede (2001), and in line with previous new product research (e.g., Chandrasekaran and
Tellis 2008; Dwyer, Mesak, and Hsu 2005; Griffith and
Rubera 2014; Rubera, Griffith, and Yalcinkaya 2012;
Stremersch and Lemmens 2009; Tellis, Stremersch, and
Yin 2003), we conceptualize national culture at the
nation-state level.
Hofstede (2001) and Hofstede, Hofstede, and Minkov
(2010) identify six different national cultural dimensions: individualism, power distance, masculinity, uncertainty avoidance, long-term orientation, and indulgence.
He states, however, that researchers should focus only
on the dimensions that are directly related to the phenomenon under study (Hofstede 1983). Thus, in line
with prior research in the field of international marketing (e.g., Engelen and Brettel 2011; Griffith and Rubera
2014; Özsomer 2012; Rubera, Griffith, and Yalcinkaya
2012; Tellis, Stremersch, and Yin 2003), we investigate
the national cultural values most theoretically relevant
to cross-market lead–lag and success-breeds-success
effects. As such, we investigate the effects of individualism, power distance, masculinity, and uncertainty avoidance. Although long-term orientation and indulgence
present additional cultural components (which can be
linked to aspects of innovation adoption, such as technological or design innovations; Griffith and Rubera
2014), we focus on Hofstede’s four original dimensions
because of the lack of a theoretical basis pertaining to
diffusion or cross-market effects and the limited data
availability for the countries investigated.
Individualism. Individualism refers to the tendency for
people to work alone and distance themselves from the
larger social group to which they belong (Hofstede
2001). Individualist cultures are characterized by loose
ties among societal members. Members of individualist
cultures value independence, self-sufficiency, and individual achievement. By contrast, members of collectivist
cultures are integrated into strong, cohesive groups that
focus on extended family and community. Individuals in
collectivist cultures value harmony and social cohesion.
We suggest that the negative relationship between time
lag and country-level performance will be weaker in
markets with higher degrees of individualism. The logic
underlying this expectation is that in more individualistic cultures, consumers use new products as a means to
establish independence and personal reward (Hofstede
2001; Rubera, Griffith, and Yalcinkaya 2012). Aaker
and Meheswaran (1997) indicate that new products
allow adopters to differentiate themselves from others
and that consumers in individualist cultures are more
likely to adopt new products because they value social
differentiation and uniqueness. Therefore, consumers in
individualistic societies are motivated to purchase new
products early, when greater emphasis is put on uniqueness and achievement. Consistent with this line of reasoning, prior research has found that consumers in individualistic cultures are more innovative than consumers
in collectivistic cultures (Steenkamp, Ter Hofstede, and
Wedel 1999), and thus acceptance of new products is
faster in individualistic cultures (Chandrasekaran and
Tellis 2008; Yeniyurt and Townsend 2003). Consumer
acceptance of new products should result in a weakening of the negative relationship between the time lag of
product introduction and a product’s country-level performance as individualism increases.
Regarding a country’s position in the global rollout, we
theorize that individualism mitigates the positive relationship between the number of previous countries in
which the product has been introduced and its countrylevel performance. The diffusion rate of a new experience product is largely dependent on communication
among consumers, captured in the lead–lag effect. Given
that consumers in individualist markets focus less on
others and value their freedom and independence (Hofstede 2001), they are less likely to be influenced by the
opinion of others. Therefore, the acceptance of a new
product by consumers in individualistic cultures is less
likely to have spillover effects leading to higher levels of
diffusion and adoption of the product by others (Dwyer,
Mesak, and Hsu 2005; Van den Bulte and Stremersch
2004). Because experience products need higher levels
of communication, given the inability of consumers to
judge quality on attributes alone, we contend that when
openness to communication of members of a higher
individualist culture is lower, the communication level
necessary for the lead–lag effect to be fully realized is
lower, thereby weakening the relationship between the
number of previous countries in which the new experience product was introduced before the target country
and country-level performance. More formally:
H2a: Individualism positively moderates the negative
relationship between time lag and country-level
performance of a new experience product.
H2b: Individualism negatively moderates the positive relationship between the previous number of countries in which a product has been
introduced before the target country and
country-level performance of a new experience product.
Power Distance. Power distance in a culture reflects the
acceptance of inequalities and is characterized by individual sensitivity to status differences and by how much
individuals are motivated by the need to conform to
those in their status group (Hofstede 2001). Countries
with high power distance traditionally have high
inequalities of power, which in turn translate into
inequalities in opportunity, status, and wealth (Hofstede
2001). Hofstede (2001) argues that individuals in societies
exhibiting a large degree of power distance accept a
hierarchical order in which everybody has a place and
that needs no further justification, whereas in societies
with low power distance, individuals strive to equalize
the distribution of power and demand justification for
inequalities of power.
We theorize that country-level power distance negatively moderates the negative relationship between time
lag and the country-level performance of a product. The
logic underlying this expectation is that better communication between different populations of the society
facilitates increased knowledge about the product, leading to lower adoption risk (Chandrasekaran and Tellis
2008). In high-power-distance societies, hierarchy and
its pervasiveness create distrust of others (Hofstede
Country-Level Performance of New Experience Products 7
2001) and inhibit fast and decisive decision making
(Dawar, Parker, and Price 1996). In high-power-distance
cultures, the adoption of a new experience product by
the powerful members of society influences the less
powerful members’ purchase decisions, given the
acceptance of hierarchical order. As such, less powerful
members of a society are likely to delay their purchase
decisions until the product is adopted by more powerful
members, leading to a slower adoption process for a
new experience product. Given the hierarchical order of
the society and the lack of communication between
those of different status, the negative relationship
between time lag and the country-level performance of
a new experience product is heightened as the countrylevel power distance increases.
Regarding a country’s position in the global rollout, we
argue that the positive effect of the introduction of a
product into a greater number of countries before the
target country on country-level performance will be
weaker as power distance increases. The underlying
logic derives from less information sharing among societal members due to hierarchical constraints. Social barriers in high-power-distance countries decrease communication and therefore increase the risk of product
adoption (Hofstede 2001). Furthermore, consumers in
high-power-distance cultures do not necessarily adopt
new experience products just because consumers in
other countries adopted them (diminishing the impact of
the lead–lag effect). Rather, consumers in these cultures
closely follow the adoption decision of more powerful
members in their country (Dwyer, Mesak, and Hsu
2005; Rubera, Griffith, and Yalcinkaya 2012). As consumers in a high-power-distance cultural look internally
rather than externally for information on product adoption, the effect of the success-breeds-success effect will
be weaker. More formally:
H3a: Power distance negatively moderates the
negative relationship between time lag and
the country-level performance of a new
experience product.
H3b: Power distance negatively moderates the
positive relationship between the previous
number of countries in which a product has
been introduced before the target country
and country-level performance of a new
experience product.
Masculinity. Masculinity refers to a country’s tendency
to value goals such as recognition, competition, and
8 Journal of International Marketing
individual achievement over goals such as harmonious
social relationships, consensus building, and quality of
life. In masculine countries, individuals make decisions
independently and admire strength and independence
(Hofstede 2001). Conversely, in feminine countries,
individuals prefer cooperation, modesty, caring for the
weak, and social welfare (Hofstede 2001).
We argue that masculinity positively moderates the
negative relationship between time lag and the countrylevel performance of a new experience product. The
underlying logic is that when a product is first introduced into the market, freedom to decide plays an
important role in the product’s acceptance because such
acceptance decisions require independent decision making (Tellis, Stremersch, and Yin 2003). Masculine societies
stress competition, ambition, wealth, and career advancement, while feminine societies put greater emphasis on
people, helping others, preserving the environment, and
equality (Van Everdingen and Waarts 2003). In masculine societies, individuals are more materialistic and
admire successful achievers (Hofstede 2001). A high
need for achievement necessitates having the latest and
most novel product, suggesting a link with the acceptance of new things in life (Hofstede 2001). Early purchase of new products is one way for people to assert
their status, showing wealth and success (Rogers 2003).
As such, those in highly masculine societies look externally for ways to achieve through new products, thus
weakening the negative influence of time lag on a new
experience product’s country-level performance.
Regarding a country’s position in the global rollout, we
theorize that masculinity weakens the positive effect of the
number of previous countries in which the product was
introduced before the target country on country-level performance. Masculine societies value independence, which
is related to new product acceptance. Individuals in masculine societies tend not to follow groups, particularly
people from other countries, preferring to make decisions
independent of others (Roth 1995). The lack of the need
to follow groups weakens the positive effect between the
previous number of countries in which a product has
been introduced before the target country and the product’s country-level performance. More formally:
H4a: Masculinity positively moderates the negative
relationship between time lag and the countrylevel performance of a new experience product.
H4b: Masculinity negatively moderates the positive relationship between the previous num-
ber of countries in which a product has been
introduced before the target country and
country-level performance of a new experience product.
Uncertainty Avoidance. Uncertainty avoidance refers to
a society’s tolerance for uncertainty and ambiguity
(Hostede 2001). Individuals in countries with low
uncertainty avoidance demonstrate a lower level of
information search, have greater tolerance of others’
opinions (Van Everdingen, Fok, and Stremersch 2009),
and are less resistant to change (Hofstede 2001). Hofstede (2001) argues that individuals in high-uncertaintyavoidance cultures maintain rigid codes of belief and
behavior and are less likely to take risks.
We theorize that uncertainty avoidance negatively moderates the negative relationship between time lag and the
country-level performance of a product. Compared with
products that have previously been introduced to and
used by consumers, new products are both unknown
and unproven, and thus their performance is more
ambiguous than established products (Dwyer, Mesak,
and Hsu 2005; Steenkamp, Ter Hofstede, and Wedel
1999). Ambiguity is high with experience products
because of the difficulty in assessing quality before consumption. Therefore, consumers in high-uncertaintyavoidance cultures are more resistant to purchasing new
experience products because the uncertainty surrounding their performance makes it difficult to judge the
risk–benefit trade-off. Conversely, consumers in lowuncertainty-avoidance cultures are more willing to
take risks and accept new concepts and ideas (Tellis,
Stremersch, and Yin 2003; Yeniyurt and Townsend
2003), and thus they are more willing to adopt new
experience products. Therefore, we theorize that the
negative influence of time lag on a product’s countrylevel performance will be heightened as uncertainty
avoidance increases.
Regarding a country’s position in the global rollout, we
theorize that uncertainty avoidance positively moderates
the relationship between the previous number of countries in which a product was introduced before the target
country and the new experience product’s country-level
performance. As more people adopt a new product, consumers in lag markets learn about potential benefits of
the product from adopters in lead markets (i.e., lead–lag
effect), resulting in a faster product acceptance rate in
lag markets. Research suggests that positive word of
mouth can reduce uncertainty and escalate the likelihood of adoption (e.g., Lam, Lee, and Mizerski 2009;
Schumann et al. 2010). As a new experience product is
released into a larger number of countries before the target country, product uncertainty declines, increasing
adoption. As such, we contend that the positive influence of the previous number of countries in which a
product is introduced before the target country on country-level performance of a new experience product is
heightened as uncertainty avoidance increases. More
formally:
H5a: Uncertainty avoidance negatively moderates
the negative relationship between time lag
and the country-level performance of a new
experience product.
H5b: Uncertainty avoidance positively moderates
the positive relationship between the previous number of countries in which a product
has been introduced before the target country
and country-level performance of a new
experience product.
METHOD
Sample
To test our hypotheses, we selected the movie industry.
Several characteristics make the movie industry an ideal
case for this research’s empirical application; movies have
a short product life cycle, can only be judged after consumption, and experience rapid decline after initial sale
(Elberse and Eliashberg 2003; Hadida 2009; HennigThurau, Houston, and Heitjans 2009).
We collected data for all movies released in the United
States (though the United States was not necessarily the
first country of introduction) during the 2006–2007
period. Data gathered for this study came from several
sources. We began data set construction by drawing
“movie-by-country” data from Box Office Mojo
(www.boxofficemojo.com). The data set was then complemented by data from The Numbers, IMDb,
IMDbPro, and Movie Insider. To ensure that global rollout was complete for our sample of movies, we limited
the sample to movies released in 2006 and 2007. We
selected 16 countries on the basis of data availability in
2006 and 2007: Argentina, Australia, Bulgaria, Czech
Republic, France, Germany, Hong Kong, Italy, Japan,
the Netherlands, New Zealand, Norway, Poland, Spain,
Sweden, and the United Kingdom. After we excluded
omissions and duplicates, the data set consisted of 259
unique movies, for a total of 2,523 entries. Of the 259
Country-Level Performance of New Experience Products 9
movies in the data set, 178 movies (68.73%) were first
introduced in the United States.
Measures
We captured new product country-level performance
with gross sales in the target country. For each of the 16
countries, gross sales figures came from Box Office
Mojo. We standardized movie sales by the country’s
population, to account for differences in the potential
market size across countries. We measured time lag as
the number of days between the dates in which the movie
was first released in the opening country and the date in
which the movie was introduced in the target country.
We captured previous number of countries by calculating
the number of countries in which the movie was introduced before being released in the target country. We
operationalized economic wealth as the country’s GDP,
drawn from the World Factbook (https://www.cia.gov/
library/publications/the-world-factbook/fields/2004.
html#85) and Euromonitor (http://www.euromonitor.
com/). We operationalized national culture using Hofstede’s (2001) value approach. Index scores for individualism, power distance, masculinity, and uncertainty
avoidance for each country came from Hofstede (2001).
Control Variables
To minimize spuriousness of the results, we included
several control variables identified in the literature (e.g.,
star power, director power, sequel, production budget,
genre, studio power, distribution intensity) in the study.
We used The Numbers as the primary source for star
power and director power, which we then complemented with data from IMDbPro. To operationalize star
and director power, we followed Hennig-Thurau, Houston, and Walsh’s (2006) suggested method. Similar to
their study, we used only actors/actresses and directors
listed on a movie’s theatrical poster. First, we drew the
average gross for each star and director from The Numbers and cross-checked the accuracy from IMDbPro.
For each movie, we only considered stars who received
first, second, or third billing. Second, when multiple
actor (or director) names were listed, we calculated an
overall star power (or director) index by weighting the
average gross value of the first name on the list by 1,
that of the second by .75, and that of the third by .50
and then summing the products and dividing it by three.
For movie sequels, we created a dummy variable (1 =
sequels, 0 = nonsequels). Sequels were gathered from
Movie Insider. Production budget came from The Numbers. Film MPAA rating came from The Numbers and
10 Journal of International Marketing
includes six possible rating categories: G (general audiences), PG (parental guidance suggested), PG-13 (possibly unsuitable for children younger than 13 years of
age), R (children not admitted unless accompanied by
an adult), NC-17 (no one under 17 admitted), and NR
(not rated). Film genre is a categorical variable classifying the film as action, comedy, drama, thriller, romance,
or animation. We obtained genre information for each
movie from The Numbers. For the few movies not listed
on The Numbers, we obtained genre from IMDb. We
used a dummy variable to measure studio power (i.e.,
1 = major studio, 0 = independent studio). Major studios included Warner Bros. Pictures, Paramount Pictures, 20th Century Fox, Walt Disney Pictures/Touchstone Pictures, Columbia Pictures, and Universal
Pictures. We collected distribution intensity—namely,
the number of theaters in the opening week for each
movie in each country—from Box Office Mojo and
IMDb. We also controlled for movie sales in the initial
countries before the introduction in the target country.
Analysis
We employ hierarchical linear modeling to account for
the lack of independence across cases (Raudenbusch and
Bryk 2002). This approach is consistent with similar
international marketing research (e.g., Ju et al. 2013;
Magnusson, Westjohn, and Boggs 2009; Walsh, Shiu,
and Hassan 2014). We adopt an incremental modelbuilding approach, which allows sequential model testing. To estimate our models, we used Proc Mixed in SAS
and employed a restricted maximum likelihood estimation method. We tested random or fixed effects by comparing the deviance (–2 log-likelihood criterion) between
two nested models. We included variables at two levels:
movie (i.e., time lag, previous number of countries, studio power, distribution intensity, star power, director
power, sequel, budget, sales in the previous countries in
which the movie was released, genre, and rating) and
country (i.e., economic wealth [EW], individualism
[IND], power distance [PD], masculinity [MASC], and
uncertainty avoidance [UA]), in addition to cross-level
interaction effects. We specify our model as follows:
(1) Country Performanceij = g00 +
15
∑ gk0MF + g01EW
k =1
+ g02INDj + g03PDj + g03MASCj + g04UAj
+ g11EW × Time lag + g12EW × Number previous
countries + g21IND × Time lag + g22IND
× Number previous countries + g31PD × Time lag
+ g22PD × Number previous countries
+ g41MASC × Time lag + g42MASC × Number
previous countries + g51UA × Time lag + g52UA
× Number previous countries + u0j + rij,
where MF refers to the movie-level factors as described
previously, u0j ~ N(0,t00) and rij ~ N(0,s2), t00 define
the variance in market share across countries, and s2
defines the variance in market share across movies
within countries. We also included dummy variables for
years (which turned out to be not significant).
RESULTS
We present the descriptive statistics and correlation
matrix among the variables of interest in Table 2. We
tested for possible multicollinearity problems. Variance
inflation factors were well below 10, and the condition
number was below its critical value of 30 (Belsley 1991),
indicating that multicollinearity was not a serious problem. To facilitate interpretation of the results, we meancentered the movie-level variables around their country
mean (with the exclusion of dummy variables) and centered the country-level variables at the grand mean.
Table 3 reports the results. We included predictors in a
stepwise fashion, first introducing movie-level effects
(Models 2–3), then country-level effects (Model 4), and
finally cross-level effects (Model 5). In Model 1, we estimated the mean of country performance as the sum of a
fixed part, which contained the grand mean g00, and a
random part, which contained two random effects at the
movie and country levels:
Country performanceij = g00 + u0j + rij.
Model 1 indicated that countries differed in their average market share (t00 = 90.75, p < .05) and that there
was variation across movies within countries (s2 =
55.39, p < .01). The proportion of the total variance
occurring across countries was 62% (calculated as
t00/[t00 + s2]).
We added the movie-level factors in Model 2 and found
that star power (g20 = .18, p < .01), director power (g30 =
.57, p < .01), sequel (g40 = 8.17, p < .05), production
budget (g50 = .61, p < .01), distribution intensity (g60 = .32,
p < .01), and sales in the previous countries (g70 = .17, p <
.01) positively influenced country-level performance. Studio power, genre, and rating, however, did not have an
effect on the dependent variable. The inclusion of movielevel effects explained 15.8% more in the movie’s countrylevel performance variation within countries.
In Model 3, we added the time lag between the release
in the initial country and the release date in the target
country, as well as the number of countries in which the
movie was introduced before being released in the target
country. The results indicate that time lag (g14–0 = –.26,
p < .01) negatively influenced a movie’s country performance, whereas the number of previous countries
(g15–0 = .63, p < .01) positively influenced country performance. The inclusion of these two variables
explained an additional 11% of the movie’s countrylevel performance variation within countries and an
additional 9.2% of the variation across countries.
Next, we added country-level effects (Model 4). Economic wealth (g01 = 2.13, p < .01) was the only countrylevel variable to have a direct effect on a movie’s countrylevel performance. The inclusion of the set of countrylevel variables explained 35.3% of the performance
variance across countries.
We tested the cross-level interaction effects in Model 5.
This model explained 29.6% of the total variance in a
movie’s country-level performance. The predictors
explained 72.1% of the variance in country-level performance across countries and 29.4% of the variance in
country-level performance across movies. In support of
H1a and H1b, respectively, we found that economic
wealth of a country positively moderated the relationship between time lag and country-level performance
(g11 = .22, p < .01) and the relationship between number
of previous countries and country-level performance
(g12 = 1.12, p < .05). In support of H2a and H2b, respectively, the analysis revealed that individualism positively
moderated the relationship between time lag and country-level performance (g21 = .02, p < .01) but negatively
moderated the relationship between number of previous
countries and country-level performance (g22 = –.04, p <
.05). We also found that power distance negatively moderated the relationship between time lag and countrylevel performance (g31 = –.01, p < .01), in support of
H3a. However, power distance had no effect on the relationship between the number of previous countries and
country-level performance (g32 = –.01, p > .05). Thus,
H3b was not supported. H4a and H4b were also not supported; the interaction effect of masculinity between
time lag and country-level performance was not significant (g41 = .004, p > .05), nor was the interaction effect
of masculinity between the number of previous countries and country-level performance (g42 = –.007, p >
.05). Finally, in support of H5a and H5b, respectively, we
found that uncertainty avoidance negatively moderated
the relationship between time lag and country-level per-
Country-Level Performance of New Experience Products 11
12 Journal of International Marketing
.01
.34
.01
5. Sequel
18.44
33.85
60.56
50.73
49.41
68.43
12. Individualism
13. Power distance
14. Masculinity
15. Uncertainty
avoidance
745.41
9. Time lag
11. Economic wealth
199.84
8. Sales previous
countries
10. Previous number
of countries
153.60
7. Number of theaters
opening week
6. Budget
.67
.01
4. Director power
23.21
21.32
17.54
20.51
19.37
13.17
82.39
370.78
184.03
.01
.01
.01
.37
.82
3. Star power
3,502.52 8,423.82
SD
2. Studio power
1. Sales (000)
M
–.04*
.19*
–.05*
.16*
.10*
.10*
.05*
.55*
.68*
–.02
.16*
–.01
–.01
.12*
1.00
1
–.01
–.01
–.02
–.01
.01
.08*
–.03
.16*
.10*
.02
.11*
–.02
.01
1.00
2
Table 2. Descriptive Statistics and Correlation Matrix
.01
–.01
.03
–.05*
–.03
.04*
.01
–.01
–.03
.01
–.01
.62*
1.00
3
.01
.01
.03
–.06*
–.03*
.03
.04*
.01
–.06*
.02
.02
1.00
4
.01
–.01
.02
–.03
–.01
.11*
.02
.22*
.13*
–.02
1.00
5
–.01
.01
–.01
–.02
.01
–.01
.01
–.01
–.01
1.00
6
.12*
.31*
.01
.22*
.13*
.04*
–.01
.34*
1.00
7
–.12*
–.04*
–.11*
.10*
.13*
.14*
.05*
1.00
8
–.06*
–.03
.01
–.01
–.02
–.03
1.00
9
.11*
.04*
.06*
–.14*
–.01
1.00
10
–.47*
–.26*
–.62*
.61*
1.00
11
–.47*
.03
–.69*
1.00
12
.64*
.05*
1.00
13
0.26*
1.00
14
Table 3. Results of Hierarchical Logistic Regression
Fixed Effects
Intercept
Model 1
Model 2
Model 3
Model 4
Model 5
Null Model
Movie
Characteristics
Movie Rollout
Variables
Country-Level
Variables
Cross-Level
Effects
8.55*
Studio power
6.55
4.94
4.80
5.04
14.32
6.88
6.91
6.66
Star power
.18**
.16**
.16**
.17**
Director power
.57**
.51**
.51**
.50**
Sequel
8.17*
6.54
6.49
5.02
Budget
.61**
.66**
.67**
.61**
Number of theaters opening week
.32**
.38**
.43**
.37**
Sales previous countries
.17**
Time lag
Previous number of countries
.19**
.19**
.18**
–.26**
–.26**
–.33**
.63**
.74**
Economic wealth (EW)
.63**
2.13**
1.72**
Individualism (IND)
–.24
–.20
Power distance (PD)
.11
.08
Masculinity (MASC)
.01
.03
–.28
–.18
Uncertainty avoidance (UA)
EW × time lag
.22**
EW × number of countries before
1.12*
IND × time lag
.02**
IND × number of countries before
–.04*
PD × time lag
–.01**
PD × number of countries before
.004
MASC × time lag
–.007
MASC × number of countries before
.06
UA × time lag
–.28**
UA × number of countries before
.08**
Random Effects
Countries
90.75 (.04)
88.73 (.89)
80.6 (.96)
52.13 (.49)
25.42 (.30)
Residual
55.39 (21.3)**
46.65 (14.3)**
41.5 (12.1)**
41.6 (12.4)**
39.05 (10.3)**
15.7%
25.0%
24.9%
Total Proportion of Variance
Explained
29.6%
Movie variance
29.4%
Country variance
72.1%
Additional Proportion of Variance
Explained
Movie variance
Country variance
Incremental
c2(Dd.f.)
15.8%
11.0%
–.2%
6.1%
2.2%
9.2%
35.3%
51.2%
6.27 (2)*
59.38 (5)***
22.72 (10)*
1,575.91 (7)***
*p < .05.
**p < .01.
Notes: Genre and rating dummies are included but not reported here. They were not significant.
Country-Level Performance of New Experience Products 13
formance (g51 = .28, p < .01) and positively moderated
the relationship between number of previous countries
and country-level performance (g52 = .08, p < .01).
DISCUSSION
The goal of this study is to contribute to the international marketing literature by building on the findings
of previous research in the area of global rollout and diffusion to answer the following research question: When
might the time lag and position effects on a new experience product’s country-level performance be stronger
and weaker? To answer this question, we built on the
theoretical foundation of the lead–lag and successbreeds-success effects to theorize that country-level economic wealth and national culture would moderate the
influence of the global product rollout decisions about
time lag and country position on a new experience product’s country-level performance. The results provide
new insights for academics and practitioners into the
relationship between country-level factors and the country-level performance of a firm’s new experience product (i.e., movies).
Theoretical Implications
The findings reveal substantive country-level (i.e., economic wealth and national culture) moderating effects
of the decisions of time lag and country position in a
global rollout on new experience product country-level
performance outcomes. For example, consistent with
prior work (e.g., Stremersch and Tellis 2004; Talukdar,
Sudhir, and Ainslie 2002), the results indicate that
greater country economic wealth weakens the negative
relationship between time lag and country-level performance. This demonstrates that in wealthier countries,
consumers are better able to afford the product, thus
permitting a longer time lag between a home and a foreign country introduction. Furthermore, the results
show that greater economic wealth strengthens the relationship between previous number of country introductions and a new experience product’s country-level performance. This suggests that a new experience product’s
momentum from previous country markets combines
with a country’s greater economic wealth to synergistically fuel acceptability and enhance its country-level performance. Thus, our results extend research on singlemarket effects (e.g., Elberse and Eliashberg 2003;
Rubera, Griffith, and Yalcinkaya 2012; Stremersch and
Tellis 2004; Tellis, Stremersch, and Yin 2003) by
demonstrating carryover of the lead–lag effect in a
14 Journal of International Marketing
cumulative manner. These findings also extend the literature, which, overall, has ignored the previous number of country effects in a product’s global rollout, suggesting the importance of considering both the
economic wealth of a country and the country position
in the global rollout of the product. By incorporating
economic wealth as a factor in the theorization of the
global rollout for a new experience product, scholars
can gain a more nuanced understanding of the global
product rollout effects.
Beyond economic wealth, national culture is also a significant factor to consider in a global rollout. The findings underscore the important role of national cultural
in explaining systematic differences in the effects of
global rollout decisions on a new experience product’s
country-level performance. Specifically, the empirical
findings show that elements of national culture influence the effects of time lag and country position on a
new experience product’s country-level performance. By
combining time lag, country position, and national culture in an integrated model, we shed more light on product acceptance by consumers across markets, extending
research that has focused on single-market effects (e.g.,
Elberse and Eliashberg 2003; Rubera, Griffith, and Yalcinkaya 2012; Stremersch and Tellis 2004; Tellis,
Stremersch, and Yin 2003). For example, the findings
show that individualism positively moderates the negative relationship between time lag and country performance but negatively moderates the positive relationship between country position in the global rollout and
country performance. These finding indicate that
greater independence and freedom in individualist countries weaken normative pressures on consumers, resulting in a greater likelihood of adopting new experience
products. Moreover, because individuals in these cultures are loosely coupled and have little interactions
with others, momentum plays less of a role than it
would otherwise, implying that firms may not be able to
capitalizing on previous momentum. These findings
extend understanding of the lead–lag and successbreeds-success effects when considering global rollout
decisions in a culturally diverse marketplace.
Furthermore, the empirical findings indicate that power
distance negatively moderates the negative relationship
between time lag and a new experience product’s countrylevel performance. This finding indicates that lower barriers to information exchange among members in cultures with lower power distance enhance communication
among consumers. This finding is particularly important
because it extends the literature to new experience prod-
ucts. In contrast, Chandrasekaran and Tellis (2008)
focus primarily on durables (e.g., microwave ovens,
freezers, washing machines, CD players, cellular phones,
personal computers), which are easier to judge before
consumption than experience products. The findings
suggest that as power distance increases, greater crossmarket communication facilitates increased product
knowledge, leading to lower risk and quicker product
adoption in lag markets.
The results pertaining to masculinity as a moderator are
surprising. While prior work suggests that masculinity
can play an important role in adoption decisions, the
findings of this study imply neither direct nor moderation effects. One reason for the lack of significant effects
could be that we examined a new experience product
and, more so, an experience product with limited visibility. Individuals in masculine societies focus on materialism and achievement (Hofstede 2001), both of which
tend to lead to the early purchase of new products to
assert status of wealth and success (Rogers 2003). While
this rationale may apply to tangible goods, experience
products do not necessarily allow for the public consumption aspect that allows for status visibility. Furthermore, the specific product explored in this study,
movies, is a low-cost experience product, which does
not provide the exclusivity necessary for the assertion of
status. As such, the findings suggest caution when generalizing theoretically from credence goods to experience goods.
Regarding uncertainty avoidance, the findings indicate a
heightened effect for both time lag and previous number
of countries. Individuals in low-uncertainty-avoidance
countries are more willing to take risks and therefore
accept new concepts more readily (Tellis, Stremersch,
and Yin 2003; Yeniyurt and Townsend 2003). As uncertainty avoidance increases, timing effects become more
troublesome (heightening the success-breeds-success
effect). Furthermore, as the number of previous countries in which a product has been introduced increases,
the amount of information available to consumers
about the new experience product increases. As such,
there is a greater need to build momentum from previous markets when introducing a new experience product into a market high in uncertainty avoidance, to
improve the product’s country-level performance.
Although not specifically tested, the results suggest that
consideration of the cultural dimension of uncertainty
avoidance would also be indicative of the specific position of countries in the rollout; for example, placing
high-uncertainty-avoidance countries later in the global
product rollout would help increase the amount of
information available to consumers in such markets,
thereby enhancing country-level performance.
In addition, the model controlled for a significant number of variables that previous single-country effect
works have deemed important (e.g., Elberse and Eliashberg 2003; Hennig-Thurau, Houston, and Walsh 2006).
The unique product (i.e., movies) in this study necessitated accounting for these product- and industryspecific elements in our model. The strength of the
model findings in terms of the direct and moderator
effects, even when we accounted for theoretically meaningful, product-related control variables, demonstrates
the theoretical and empirical importance of economic
wealth and national culture elements. Taken together,
the results present a more comprehensive theoretical
and empirical understanding of the effects of time lag
and the position of a country in the firm’s global rollout
strategy for new experience products on country-level
economic and national cultural factors.
Managerial Implications
Managers assessing the country-level performance
impact of their efforts in the global rollout of new
experience products must recognize the factors that
could influence performance effects. The findings of this
study show that country-level product performance is
determined not only by time lag and country position in
a global product rollout but also by a country’s economic wealth and national culture. That is, the results
suggest that though there is a direct relationship
between time lag and country position and new experience product country-level performance, the effect is
contingent on the economic wealth and the national culture elements of a country.
First, while international marketers typically treat economic wealth as a predictor of a product’s market
potential, the findings of this study provide a more
nuanced picture of the effect of economic wealth.
Specifically, economic wealth not only influences the
country-level performance of a new experience product
(as illustrated by the strong direct effect in the model)
but also weakens the effect of time lag and strengthens
the effect of a country’s position in the global rollout on
a product’s country-level performance. In particular, the
results imply that when consumers have higher incomes
and greater spending power, they can better afford the
risk of adopting products when performance is uncertain. As such, as country economic wealth increases, the
Country-Level Performance of New Experience Products 15
negative relationship between time lag and country-level
performance is suppressed; this suggests that managers
can leverage learning across markets (inherent in the
lead–lag effect) to enhance a new experience product’s
country-level performance. In addition, consumers with
greater economic wealth tend to learn about the introduction of the product and witness the satisfaction of
other consumers with the product more rapidly than
those with less economic wealth. These factors result in
higher levels of adoption of the new experience product,
thus suggesting that managers can enhance countrylevel performance when economic wealth and a greater
number of previous country introductions are engaged
jointly.
Second, despite its diversity, national culture still plays a
critical role in product acceptance. The findings indicate
that compared with launching new experience products
in more collectivist countries (e.g., Mexico, South
Korea, India), firms launching these products in more
individualist countries, such as the United States, can
take advantage of the freedom of expression in such
countries to offset the loss of momentum. Furthermore,
the findings suggest that it is to firms’ advantage to
introduce new experience products rapidly in lowpower-distance cultures (e.g., Sweden, Norway, Austria)
than in high-power-distance cultures (e.g., Malaysia,
Brazil, France), to gain the greatest advantage and minimize the inherent rapid decline associated with short life
cycles characteristic of new experience products. In
addition, the findings indicate that uncertainty avoidance negatively moderates the relationship between time
lag and country-level performance but positively moderates the relationship between country position in the
global rollout and a new experience product’s countrylevel performance, thus necessitating different strategies
when entering high-uncertainty-avoidance markets (e.g.,
Portugal, Argentina, Spain, Greece) rather than lowuncertainty-avoidance markets (e.g., Sweden, the United
States, Great Britain).
Taken together, the results offer international marketing
managers a more nuanced understanding of the country
market conditions that affect their global rollout decisions regarding timing and the number of countries in
which the product is introduced before the target country. Specifically, the findings shed light on how economic
wealth and specific elements of national culture
strengthen or weaken the relationship between time lag
and country position in the global rollout and a new
experience product’s country-level performance. This
can aid managers in reducing the uncertainty about for-
16 Journal of International Marketing
eignness and in increasing the ability to improve the
forecasting of demand for the product.
LIMITATIONS AND FURTHER RESEARCH
Although the study lends new insights to the international marketing literature, it has several limitations
that should be considered when interpreting the findings. First, although this work provides insight into the
effects of timing, country position in a global rollout,
and country-specific factors on a new product’s countrylevel performance, it fails to provide greater insight into
the factors determining issues such as the speed of
global rollout (i.e., the antecedent factors determining
the time lag from entry into the first country market to
entry into the last country market). For example, significant work has been conducted in the area of firm innovativeness and its drivers, demonstrating significant
influence on new product introductions (e.g., Boso et al.
2013; Sun and Lee 2013; Yalcinkaya, Calantone, and
Griffith 2007). Similar to previous research, we theorize
that the resource-based view of the firm (Yalcinkaya,
Calantone, and Griffith 2007) and organizational ecology (Li, Qian, and Qian 2014) may provide a fertile
theoretical foundation for specifying product- and firmrelated factors that could help understand speed of a
global product rollout.
Second, this work investigates the position of a country
in a firm’s global rollout within the context of experience products by measuring country position as the total
number of previous countries entered. Although the
findings indicate that country position is important, this
is likely only the starting point for greater theory development and empirical research. Specifically, the lead–lag
and success-breeds-success effects function on the
underlying topic of momentum. Thus, more may be
learned by drawing from alternative theories, such as
inertia, or developing organic theories that may help
provide a more nuanced understanding of country position by focusing on the specific sequencing of countries
in a global rollout (i.e., for a new experience product,
which specific countries should a firm enter first, second, third, and so on). An alternative approach to
theory development in this area would be empirically
modeling sequencing in terms of country-level product
performance, thereby working toward empirical generalizations as the foundation for theory development.
Third, although this work focused on new experience
products, the use of a single product category (i.e.,
movies) limits the generalizability of the findings. Thus,
the examination of a broader set of product categories
would be helpful in extending this research. For example, Chandrasekaran and Tellis (2008) show that
although a simultaneous strategy (e.g., a shorter time
lag) might be a better fit for a “fun” product because of
its universal appeal, a sequential strategy (e.g., a longer
time lag) might be more desirable for a “work” product
because of its culturally bounded nature. Similarly,
Rubera, Griffith, and Yalcinkaya (2012) find that the
type of innovation, whether technological innovations
(i.e., advances in the functioning of a product) or design
innovations (i.e., advances in the stylistic features of a
product), also plays an increasingly important role in
determining a firm’s rollout strategy. They indicate that
a longer time lag is a more effective strategy for technological innovations while a shorter time lag is a more
effective strategy for design innovations. As such, more
work across product categories is warranted to advance
understanding of global product rollout.
Fourth, although this work presented the firm decision
criteria, the model is not complete because it fails to
capture consumer aspects. Research has demonstrated
significant effects of innovativeness across countries
(e.g., Kumar 2014; Nijssen and Douglas 2011; Steenkamp, Ter Hofstede, and Wedel 1999; Tellis, Yin, and Bell
2009). For example, Tellis, Yin, and Bell (2009) show differential cross-industry and cross-country effects in relation to consumer innovativeness. The incorporation of
consumer innovativeness into the model would not only
extend the literature but also help complement existing
work to provide a more holistic understanding for international marketing academics and practitioners. Similarly, the incorporation of aspects such as consumer animosity (e.g., Alden et al. 2013) and country-specific
associations (e.g., Herz and Diamantopoulos 2013) may
be beneficial to advancing the area.
Finally, there has been growing debate on whether Hofstede’s (2001) culture typology is appropriate in all contexts and whether other typologies or frameworks
should be used. Although Hofstede’s study was one of
the first systematic works on cross-cultural research in
the business domain and is widely used in international
marketing research (e.g., Ashraf, Thongpapanl, and
Auh 2014; Lund, Scheer, and Kozlenkova 2013; Madden, Roth, and Dillon 2012; Walsh, Shiu, and Hassan
2014; Yalcinkaya 2008), it is by no means the only
approach. Indeed, researchers should consider employing other cultural frameworks to create a more holistic
understanding of the effect of culture on international
marketing research. For example, Rubera, Ordanini,
and Griffith (2011) show the value of alternative frameworks for understanding cross-national consumption
behavior by employing Schwartz’s (1994, 1999) value
framework to understand the perception of new creative
products. We recommend that further research carefully
consider the cultural framework being applied, working
to employ the one that is most theoretically meaningful
to the topic under study.
REFERENCES
Aaker, Jennifer L. and Durairaj Maheswaran (1997), “The
Effect of Cultural Orientation on Persuasion,” Journal of
Consumer Research, 24 (3), 315–28.
Alden, Dana L., James B. Kelley, Petra Riefler, Julie A. Lee, and
Geoffrey N. Soutar (2013), “The Effect of Global Company
Animosity on Global Brand Attitudes in Emerging and Developed Markets: Does Perceived Value Matter?” Journal of
International Marketing, 21 (2), 17–38.
Ashraf, Abdul R., Narongsak (Tek) Thongpapanl, and Seigyoung Auh (2014), “The Application of the Technology
Acceptance Model under Different Cultural Contexts: The
Case of Online Shopping Adoption,” Journal of International
Marketing, 22 (3), 68–93.
Belsley, David A. (1991), Conditioning Diagnostics: Collinearity
and Weak Data in Regression. New York: John Wiley & Sons.
Boso, Nathaniel, Vicky M. Story, John W. Cadogan, Milena
Micevski, and Selma Kadi-Maglajli (2013), “Firm Innovativeness and Export Performance: Environmental, Networking, and Structural Contingencies,” Journal of International
Marketing, 21 (4), 62–87.
Calantone, Roger J. and David A. Griffith (2007), “Challenges
and Opportunities in the Field of Global Product Launch,”
Journal of Product Innovation Management, 24 (5), 414–18.
———, Sengun Yeniyurt, Janell D. Townsend, and Jeffrey B.
Schmidt (2010), “The Effects of Competition in Short Product
Life-Cycle Markets: The Case of Motion Pictures,” Journal of
Product Innovation Management, 27 (3), 349–61.
Chandrasekaran, Deepa and Gerard J. Tellis (2008), “Global
Takeoff of New Products: Culture, Wealth or Vanishing Differences,” Marketing Science, 27 (5), 844–60.
Chryssochoidis, George M. and Veronica Wong (1998),
“Rolling Out New Products Across Country Markets: An
Empirical Study of Causes of Delays,” Journal Product Innovation Management, 15 (1) 16–41.
Craig, C. Samuel, William H. Greene, and Susan P. Douglas
(2005), “Culture Matters: Consumer Acceptance of U.S.
Country-Level Performance of New Experience Products 17
Films in Foreign Markets,” Journal of International Marketing, 13 (4), 80–103.
Dawar, Niraj, Philip Parker, and Lydia M. Price (1996), “A CrossCultural Study of Interpersonal Information Exchange,” Journal of International Business Studies, 27 (3), 497–517
Di Benedetto, C. Anthony (1999), “Identifying the Key Success
Factors in New Product Launch,” Journal of Product Innovation Management, 16 (6), 530–44.
Dwyer, Sean, Hani Mesak, and Maxwell Hsu (2005), “An
Exploratory Examination of the Influence of National Culture
on Cross-National Product Diffusion,” Journal of International Marketing, 13 (2), 1–27.
Elberse, Anita and Jehoshua Eliashberg (2003), “Demand and
Supply Dynamics for Sequentially Released Products in International Markets: The Case of Motion Pictures,” Marketing
Science, 22 (3), 329–54.
Engelen, Andreas and Malte Brettel (2011), “A Cross-Cultural
Perspective of Marketing Departments’ Influence Tactics,”
Journal of International Marketing, 19 (2), 73–94.
Erdem, Tülin, Joffre Swait, and Ana Valenzuela (2006), “The
Cross-Cultural Aspects of Brands as Signals,” Journal of Marketing, 41 (January), 86–100.
Ganesh, Jainshankar (1998), “Converging Trends Within the
European Union: Insights from an Analysis of Diffusion Patterns,” Journal of International Marketing, 6 (4), 32–48.
——— 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 (4),
328–37.
Golder, Peter N. (2000), “Insights from Senior Executives
About Innovation in International Markets,” Journal of Product Innovation Management, 17 (5), 326–40.
——— and Gerard J. Tellis (2004), “Growing, Growing, Gone:
Cascades, Diffusion and Turning Points in the Product Life
Cycle,” Marketing Science, 23 (2), 207–218.
Griffith, David A. and Gaia Rubera (2014), “A Cross-Cultural
Investigation of New Product Strategies for Technological and
Design Innovations,” Journal of International Marketing, 22
(1), 5–20.
Guiltinan, Joseph P. (1999), “Launch Strategy, Launch Tactics,
and Demand Outcomes,” Journal of Product Innovation
Management, 16 (6), 509–529.
Hadida, Allègre L. (2009), “Motion Picture Performance: A
Review and Research Agenda,” International Journal of Management Reviews, 11 (3), 297–335.
18 Journal of International Marketing
Harvey, Michael G. and David A. Griffith (2007), “The Role of
Globalization, Time Acceleration and Virtual Global Teams in
Fostering Successful Global Product Launches,” Journal of
Product Innovation Management, 24 (5), 486–501.
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.
Hennig-Thurau, Thorsten, Mark B. Houston, and Torsten Heitjans (2009), “Conceptualizing and Measuring the Monetary
Value of Brand Extensions: The Case of Motion Pictures,”
Journal of Marketing, 73 (November), 167–83.
———, ———, and Gianfranco Walsh (2006), “The Differing
Roles of Success Drivers Across Sequential Channels: An
Application to the Motion Picture Industry,” Journal of the
Academy of Marketing Science, 34 (4), 559–75.
Herz, Marc Florian and Adamantios Diamantopoulos (2013),
“Country-Specific Associations Made by Consumers: A DualCoding Theory Perspective,” Journal of International Marketing, 21 (3), 95–121.
Hofstede, Geert (1983), “Dimensions of National Cultures in
Fifty Countries and Three Regions,” in Expiscations in CrossCultural Psychology, J.B. Deregowksi, S. Dziurawiec, and
R.C. Annis, eds. Lisse, the Netherlands: Swets & Zeitlinger,
335–55.
——— (2001), Culture’s Consequences: Comparing Values,
Behaviors, Institutions, and Organizations Across Nations.
Thousand Oaks, CA: Sage Publications.
———, Gert Jan Hofstede, and Minkov, Michael (2010), Cultures and Organizations: Software of the Mind. New York:
McGraw-Hill.
Ju, Min, Kevin Zheng Zhou, Gerald Yong Gao, and Jiangyong
Lu (2013), “Technological Capability Growth and Performance Outcome: Foreign Versus Local Firms in China,” Journal of International Marketing, 21 (2), 1–16.
Kalish, Shlomo, Vijay 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.
Krider, Robert E., Tieshan Li, Yong Liu, and Charles B. Weinberg (2005), “The Lead–Lag Puzzle of Demand and Distribution: A Graphical Method Applied to Movies,” Marketing
Science, 24 (4), 635–45.
——— and Charles B. Weinberg (1998), “Competitive Dynamics and the Introduction of New Products: The Motion Picture
Timing Game,” Journal of Marketing Research, 35 (February), 1–15.
Kumar, V. (2014), “Understanding Cultural Differences in Innovation: A Conceptual Framework and Future Research Directions,” Journal of International Marketing, 22 (3), 1–29.
——— and Trichy Krishnan (2002), “Multinational Diffusion
Models: An Alternative Framework,” Marketing Science, 21
(3), 318–30.
Johnson, Joseph and Gerard J. Tellis (2008), “Drivers of Success
for Market Entry into China and India,” Journal of Marketing, 72 (May) 1–13.
Lam, Desmond, Alvin Lee, and Richard Mizerski (2009), “The
Effects of Cultural Values in Word-of-Mouth Communication,” Journal of International Marketing, 17 (3), 55–70.
Lee, Keon B. and Veronica Wong (2010), “New Product Development Proficiency and Multi-Country Product Rollout
Timeliness,” International Marketing Review, 27 (1), 28–54.
Li, Lee, Gongming Qian, and Zhengming Qian (2014), “Inconsistencies in International Product Strategies and Performance
of High-Tech Firms,” Journal of International Marketing, 22
(3), 94–113.
Litman, Barry R. and Hoekyun Ahn (1998), “Predicting Financial Success of Motion Pictures,” in The Motion Picture
Mega-Industry, Barry R. Litman, ed. Needham Heights, MA:
Allyn & Bacon, 172–97.
Lund, Donald J., Lisa K. Scheer, and Irina V. Kozlenkova
(2013), “Culture’s Impact on the Importance of Fairness in
Interorganizational Relationships,” Journal of International
Marketing, 21 (4), 21–40.
Madden, Thomas J., Martin S. Roth, and William R. Dillon
(2012), “Global Product Quality and Corporate Social
Responsibility Perceptions: A Cross-National Study of Halo
Effects,” Journal of International Marketing, 20 (1), 42–57.
Magnusson, Peter, Stanford A. Westjohn, and David J. Boggs
(2009), “Order-of-Entry Effects for Service Firms in Developing Markets: An Examination of Multinational Advertising Agencies,” Journal of International Marketing, 17 (2),
23–41.
Neelamegham, Ramya and Pradeep Chintagunta (1999), “A
Bayesian Model to Forecast New Product Performance in
Domestic and International Markets,” Marketing Science, 18
(2), 115–36.
Nijssen, Edwin J. and Susan P. Douglas (2011), “Consumer
World-Mindedness and Attitudes Toward Product Positioning
in Advertising: An Examination of Global Versus Foreign Versus Local Positioning,” Journal of International Marketing,
19 (3), 113–33.
Özsomer, Ayşegül (2012), “The Interplay Between Global and
Local Brands: A Closer Look at Perceived Brand Globalness
and Local Iconness,” Journal of International Marketing, 20
(1), 71–94.
Raudenbush, Stephen W. and Anthony S. Bryk (2002), Hierarchical Linear Models. Thousand Oaks, CA: Sage Publications.
Rogers, Everett M. (2003), Diffusion of Innovations, 5th ed.
New York: The Free Press.
Roth, Martin S. (1995), “The Effects of Culture and Socioeconomics on the Performance of Global Brand Image Strategies,” Journal of Marketing Research, 32 (May), 163–75.
Rubera, Gaia, David A. Griffith, and Goksel Yalcinkaya (2012),
“Technological and Design Innovation Effects in Regional
New Product Rollouts: A European Illustration,” Journal of
Product Innovation Management, 29 (6), 1047–60.
———, Andrea Ordanini, and David A. Griffith (2011), “Incorporating Cultural Values for Understanding the Influence of
Perceived Product Creativity on Intention to Buy: An Examination in Italy and the U.S.,” Journal of International Business
Studies, 42 (4), 459–76.
Schumann, Jan H., Florian v. Wangenheim, Anne Stringfellow,
Zhilin Yang, Vera Blazevic, Sandra Praxmarer, et al. (2010),
“Cross-Cultural Differences in the Effect of Received Wordof-Mouth Referral in Relational Service Exchange,” Journal
of International Marketing, 18 (3), 61–80.
Schwartz, Shalom H. (1994), “Beyond Individualism/
Collectivism: New Cultural Dimensions of Values,” in Individualism and Collectivism: Theory, Methods, and Applications,
U. Kim, H.C. Triandis, C. Kagitcibasi, S.C. Choi, and G. Yoon,
eds. Thousand Oaks, CA: Sage Publications, 85–119.
——— (1999), “A Theory of Cultural Values and Some Implications for Work,” Applied Psychology: An International
Review, 48 (1), 12–47.
Sheth, Jagdish N. (1968), “A Factor Analytic Model of Brand
Loyalty,” Journal of Marketing Research, 5 (November),
395–404.
Steenkamp, Jan-Benedict E.M., Frenkel ter Hofstede, and
Michel Wedel (1999), “A Cross-National Investigation into
the Individual and Cultural Antecedents of Consumer Innovativeness,” Journal of Marketing, 63 (April), 55–69.
Stremersch, Stefan and Aurélie Lemmens (2009), “Sales Growth
of New Pharmaceuticals Across the Globe: The Role of Regulatory Regimes,” Marketing Science, 28 (4), 690–708.
——— and Gerard J. Tellis (2004), “Understanding and Managing International Growth of New Products,” International
Journal of Research in Marketing, 21 (4), 421–38.
Sun, Sunny Li and Ruby P. Lee (2013), “Enhancing Innovation
Through International Joint Venture Portfolios: From the
Country-Level Performance of New Experience Products 19
Emerging Firm Perspective,” Journal of International Marketing, 21 (3), 1–21.
off,” Journal of Marketing Research, 46 (October), 637–
52.
Takada, Hirokazu and Dipak Jain (1991), “Cross-National
Analysis of Diffusion of Consumer Durable Goods in Pacific
Rim Countries,” Journal of Marketing, 55 (April), 48–54.
——— and Eric Waarts (2003), “The Effect of National Culture
on the Adoption of Innovations,” Marketing Letters, 14 (13),
217–32.
Talukdar, Debabrata, K. Sudhir, and Andrew Ainslie (2002),
“Investigating New Product Diffusion Across Products and
Countries,” Marketing Science, 21 (1), 97–114.
Vasilchenko, Elena and Sussie Morrish (2011), “The Role of
Entrepreneurial Networks in the Exploration and Exploitation of Internationalization Opportunities by Information and
Communication Technology Firms,” Journal of International
Marketing, 19 (4) 88–105.
Tellefsen, Thomas and Hirokazu Takada (1999), “The Relationship Between Mass Media Availability and the Multicountry Diffusion of Consumer Products,” Journal of International
Marketing, 7 (1), 77–96.
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.
———, Eden Yin, and Simon Bell (2009), “Global Consumer
Innovativeness: Cross-Country Differences and Demographic
Commonalities,” Journal of International Marketing, 17 (2),
1–22.
Van den Bulte, Christophe and Stefan Stremersch (2004),
“Social Contagion and Income Heterogeneity in New Product
Diffusion: A Meta-Analytic Test,” Marketing Science, 23 (4),
530–44.
Van Everdingen, Yvonne, Dennis Fok, and Stefan Stremersch
(2009), “Modeling Global Spillover of New Product Take-
20 Journal of International Marketing
Walsh, Gianfranco, Edward Shiu, and Louise M. Hassan
(2014), “Cross-National Advertising and Behavioral Intentions: A Multi-Level Analysis,” Journal of International Marketing, 22 (1), 77–98.
Yalcinkaya, Goksel (2008), “A Culture-Based Approach to
Understanding the Adoption and Diffusion of New Products
Across Countries,” International Marketing Review, 25 (2),
202–214.
———, Roger J. Calantone, and David A. Griffith (2007), “An
Examination of Exploration and Exploitation Capabilities:
Implications for Product Innovation and Market Performance,” Journal of International Marketing, 15 (4), 63–93.
Yeniyurt, Sengun and Janell D. Townsend (2003), “Does Culture Explain Acceptance of New Products in a Country? An
Empirical Investigation,” International Marketing Review, 20
(4), 377–96.
Copyright of Journal of International Marketing is the property of American Marketing
Association and its content may not be copied or emailed to multiple sites or posted to a
listserv without the copyright holder's express written permission. However, users may print,
download, or email articles for individual use.