International Relationship Marketing · 2020. 6. 9. · International Relationship Marketing ....
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“International Relationship Marketing” © 2013 Stephen A. Samaha, Joshua T. Beck, and Robert W. Palmatier; Report Summary © 2013 Marketing Science Institute MSI working papers are distributed for the benefit of MSI corporate and academic members and the general public. Reports are not to be reproduced or published in any form or by any means, electronic or mechanical, without written permission.
Marketing Science Institute Working Paper Series 2013 Report No. 13-117 International Relationship Marketing Stephen A. Samaha, Joshua T. Beck, and Robert W. Palmatier
Report Summary As trade across boarders expands, international relationships are increasingly critical to business performance. Yet despite a recent surge in international research on relationship marketing (RM), it is unclear whether or how RM should be adapted across cultures. To understand this, Stephen Samaha, Joshua Beck, and Robert Palmatier adopt Hofstede’s dimensions of culture to conduct a comprehensive, multivariate, meta-regression analysis of 42,378 relationships across 144 studies, 29 countries, and 6 continents. To guide future theory, they propose four tenets that capture the essence of culture’s effects on RM. Study 1 provides evidence in support of these tenets and shows that the importance of different cultural dimensions varies. For example, controlling for simultaneous effects, individualism–collectivism has a 114%–169% greater magnitude of effect on RM than other cultural dimensions, whereas masculinity–femininity has almost no effect. Study 2 adopts a country- and regional-level approach to reveal that RM’s impact on performance is much more effective outside the United States. For example, RM is 17%, 15%, 38%, and 55% more effective in Brazil, Russia, India, and China, respectively, suggesting a primary role for RM in the developing BRIC countries. Other findings underscore that designing effective strategies for building customer relationships requires cultural customization. For example, the authors’ models predict that dependence is 150% more effective for building relationships in Russia than the U.S., whereas relationship investments are 58% less effective in Russia than the U.S. Evidence from Study 2 also offers insight into a surprising finding: Culture has a greater influence on relationship construction than on relationship outcomes. Managers may evaluate the attractiveness of RM on the basis of objective performance outcomes in a country or region, but once determined, more specific attention should focus on the nuances of relationship-building strategies. To guide country-specific RM strategy development, the authors provide country-specific estimates of the effectiveness of different relationship-building strategies on customer relationship formation, and the effectiveness of customer relationships on seller performance. Ultimately, international marketing managers may use these estimates to optimize their allocation of resources aimed at building profitable customer relationships. Stephen A. Samaha is Assistant Professor of Marketing, California State University, Northridge. Joshua T. Beck is a Doctoral Candidate, Foster School of Business, University of Washington. Robert W. Palmatier is Professor of Marketing and John C. Narver Chair in Business Administration, Foster School of Business, University of Washington.
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Academics and practitioners maintain that relationship marketing enhances business
performance—a claim that is both empirically well documented (Swaminathan and Moorman
2009) and evident in the wisdom of managers who believe relationships are decisive for
achieving success (Würth-Group 2010). From a global perspective, international relationships
also are increasingly critical. International trade accounts for 20% of global gross domestic
product (GDP), and as trade expands rapidly across borders, firms and foreign customers grow
ever more interlinked (CIA 2010; World Trade Organization 2011). Among the S&P 500 firms
that report foreign sales, 46% of their total revenues in 2010 came from foreign markets
(Silverblatt and Guarino 2011). Despite this increase in international relationships, managers and
academics still can find little guidance regarding whether or how relationship marketing
strategies should be adapted in different countries, other than warnings that a “cross-national
generalization should not be assumed” (Steenkamp 2005, p. 6; see also Ghemawat 2011). Thus,
the goal of this research is to synthesize past theoretical and empirical research to provide
parsimonious guidance to researchers and managers seeking to understand international
relationship marketing.
Currently, a consensus relationship marketing (RM) framework generally gets applied across
different countries, with little consideration for how its effectiveness might depend on cultural
differences (Palmatier et al. 2006). At least three key limitations of prior research prevent
managers and researchers from developing a holistic understanding of international RM. First,
data restrictions have constrained RM research to studying one or at most a few countries at a
time, which impedes multicountry generalizations (De Wulf, Odekerken-Schröder, and Iacobucci
2001; Kumar, Scheer, and Steenkamp 1995). Second, RM research typically investigates the
impact of a single cultural dimension at a time (Aaker and Williams 1998; Ozdemir and Hewett
2010; Robinson, Irmak, and Jayachandran 2012), but because culture’s impact on RM
effectiveness is likely multidimensional, this approach undermines our ability to understand
culture’s “net effect” (Hofstede, Hofstede, and Minkov 2010). Third, little theoretical or
empirical research addresses how culture influences specific links in the RM framework, which
limits our ability to provide fine-grained guidance about the efficacy of specific RM strategies.
Thus, extant research is often globally incomplete, theoretically constrained, and too general to
provide clear and actionable insights into international relationship marketing.
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We attempt to overcome these limitations by performing a comprehensive meta-analysis of
RM research that synthesizes 42,378 dyadic relationships across 144 studies, 29 countries, and 6
continents. Our sample of 29 countries accounts for 82% of global GDP (United Nations
Database 2012). We investigate international RM in two complimentary studies. Our goal in
Study 1 is to provide a parsimonious theoretical foundation for culture’s influence on RM by
addressing two key research questions: How do RM linkages vary in a multidimensional cultural
framework? and What cultural dimensions are most critical in an RM context? Our goal in Study
2 is to provide managerially relevant, country-level RM guidance, because many firms
implement marketing strategies in accordance with their country-level or regional operations
(Johansson 2009). By applying our meta-analytic results from Study 1 to the 25 largest countries
and 7 geographic regions, we address two further research questions: What is the relative
effectiveness of RM across different countries/regions? and What specific RM strategies are
most effective for building customer relationships in different countries/regions?
As our theoretical basis for understanding how cultural differences affect RM, we adopt
Hofstede’s (1980) four primary dimensions of culture (individualism–collectivism, power
distance, uncertainty avoidance, masculinity–femininity), which have strong precedence in
marketing strategy (Deleersnyder et al. 2009; Erramilli and Rao 1993; Johnson and Tellis 2008;
Kirca, Jayachandran, and Bearden 2005). Culture refers to the pattern of values, norms, and
beliefs that affect the way people assess information; it leads to differential processing and
evaluations of environmental information (Hofstede 1991; Triandis 1989). Thus, culture should
influence how people interpret and respond to different RM activities. We examine
simultaneously the contingent effects of Hofstede’s four cultural dimensions on the classic RM
framework: antecedents → relational mediators (trust and commitment) → outcomes (Morgan
and Hunt 1994; Palmatier et al. 2006).
In turn, we make four contributions to extant RM literature. First, we find that culture is
critical to understanding RM. The effectiveness of RM strategies for building relationships and
then the subsequent effects of relationships on performance outcomes both depend on the
cultural context. To understand these contingent effects, we propose and find evidence in support
of four parsimonious tenets that capture the theoretical essence of how each cultural dimension
moderates specific linkages in the RM framework. For example, individualism–collectivism
primarily influences the effectiveness of RM activities that emphasize long-term, social bonding
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and dependence (e.g., communication, dependence), but power distance influences the
effectiveness of RM activities that emphasize the importance of status (e.g., word of mouth), and
uncertainty avoidance is most critical for RM activities that address risk and uncertainty (e.g.,
expertise). Thus, our results provide a concise theoretical explanation for when each cultural
dimension matters most and why.
Second, we find strong evidence that some cultural dimensions are more important than
others in an RM context. In particular, individualism–collectivism is the most important cultural
dimension, with effects on many RM linkages that tend to be 114% to 169% greater in
magnitude than the effects of the other cultural dimensions. In contrast, masculinity–femininity
emerges as the least important dimension. Other RM research notes the importance of this
cultural dimension (e.g., Beetles and Crane 2005; Fletcher and Fang 2006), but our results
suggest controlling for other cultural dimensions, before drawing conclusions about any other
single cultural dimension. For example, research that grants equal weight to the importance of
each cultural dimension by calculating the Euclidean distance across cultural factors may provide
misleading guidance (Johnson and Tellis 2008; Kogut and Singh 1988; Mitra and Golder 2002).
Third, by using multiple cultural dimensions to make country-level assessments in Study 2,
we demonstrate a large net effect of culture on the overall effectiveness of RM. For example, the
effect of relationships (trust and commitment) on objective performance in China is 55% larger
than in the parallel effect in the United States, whereas the effects in Belgium, Norway, and the
Netherlands are 10% to 12% less than the U.S.-related effects. Similarly, the influences of
relationship-building strategies on trust and commitment vary significantly across countries and
regions, such that building dependence is a more effective relationship building strategy in
Russia (r = .62, 150% larger than in the United States) than are relationship investments (r = .19,
58% smaller than in the United States). These country- and regional-level insights inform
managers about where RM leads to higher performance outcomes and which relationship-
building strategies are most effective in each country included in our study. Thus, we provide a
framework that supports international adaptations to RM.
Fourth, by examining the RM framework across countries, we find greater variation in the
relationship-building than in the performance outcome stages. For example, the effect of seller
expertise on trust and commitment ranges anywhere from .19 (Great Britain) to .84 (Russia),
suggesting a high degree of variability in its effectiveness across countries. Yet the effect of
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relationships on objective performance is more internationally similar, with the weakest effect in
the Netherlands (.35) and the strongest effect in China (.61). Thus, culture generally has a greater
influence on relationship construction than on relationship performance outcomes.
The Role of Culture in Relationship Marketing
A country’s culture is a key environmental force, shaping its people’s perceptions,
dispositions, and behaviors (Triandis 1989). Culture is defined as “the training or refining of
one’s mind from social environments in which one grew up” (Hofstede 1991, p. 4). Because RM
interactions are social exchanges, the norms, roles, and expectations of the relationships likely
are influenced by culture. Culture influences the types of socially engaging and disengaging
emotional processes that people experience (Kitayama, Mesquita, and Karasawa 2006), and
therefore, it should be critical for understanding international RM. The way social information is
encoded and exploited also differs across countries, due to differences in value systems. We aim
to evaluate how such ingrained cultural differences influence the effectiveness of RM strategies.
To do so, we synthesize results from cross-disciplinary research in marketing, psychology,
sociology, and management to formulate hypotheses regarding the predicted moderating effects
of Hofstede’s (1980) cultural dimensions on RM effectiveness, as we summarize in Table 1.
Consistent with prior research (Palmatier et al. 2006), we test the moderation effects of each
construct linked with trust and commitment separately, as well as in aggregate. To simplify our
terminology, when testing any hypotheses involving both trust and commitment, we use the
generic term “relational mediators.” Figure 1 illustrates the antecedents, relational mediators, and
outcomes in our conceptual model. Because we do not anticipate that every cultural dimension
matters equally for all constructs, we precede our hypotheses with a series of parsimonious
tenets, which capture the theoretical essence of how each cultural dimension should moderate the
RM framework. Thus, we offer one tenet for each cultural dimension, then propose hypotheses
tailored to testing the validity of each tenet. (Tables and figures follow References.)
Moderating role of individualism–collectivism in relationship marketing
We begin our discussion with individualism–collectivism, because it has received the most
attention in cross-cultural research (Allik and Realo 2004; Han and Shavitt 1994; Kitayama,
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Mesquita, and Karasawa 2006; Williams, Han, and Qualls 1998). The individualism–
collectivism cultural dimension captures the extent to which people are expected to be self-
reliant and distant from others (individualism) instead of mutually dependent and closely tied to
others (collectivism). Compared with individualistic cultures, collectivist cultures may respond
more positively to RM efforts, because they share substantial overlap with RM norms. In
collectivist cultures, reciprocity norms and mutual interdependence govern relationships
(Hofstede, Hofstede, and Minkov 2010; Morishima and Minami 1983). Collectivists are more
concerned with the collective well-being of their entire group, and members rely on and work
with one another to achieve mutually beneficial outcomes. In a collectivist society, a child learns
to refer to him- or herself as “we” versus “I” (Hofstede 1991). Collectivists also are more
receptive to social bonding than members of individualistic cultures and value long-term group
ties, similar to the ties binding extended families (Triandis 1995; Williams, Han, and Qualls
1998). Thus, collectivist norms emphasize long-term social bonding and dependence, which
emphasize familiarity, friendship, long-term ties, and close personal relationships (Williams,
Han, and Qualls 1998).
Compared with collectivists, individualists prefer arm’s-length relationships, in place for
self-serving (as opposed to mutually beneficial) reasons (Steensma et al. 2000). Because
individualists value individual goals over group goals, they likely build relationships only to the
extent that doing so is instrumental to their individual goal achievement (Triandis 1989, 1995).
Should a given relationship interfere with such pursuits, an individualist severs ties and forms
new relationships. All else being equal, we anticipate that as a culture becomes increasingly
individualistic, relationships based on long-term social bonding and dependence become harder
to form, and the benefits associated with having strong relationships decline. With this logic, we
propose the first of our four cultural–RM tenets:
Tenet 1: As cultural individualism increases, relationships based on long-term social
bonding and dependence become harder to form, and the beneficial effects of relationship-
based outcomes decline.
Because long-term social bonding and dependence are central in collectivist cultures, we
also anticipate that RM strategies and outcomes linked to long-term social bonding and
dependence grow stronger (positively moderated) in collectivist cultures but weaker (negatively
moderated) in individualistic cultures. Three relational antecedents appear in our framework,
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related to long-term social bonding and dependence: (1) communication, (2) dependence, and (3)
relationship duration. We anticipate that outcomes associated with having strong relationships
also get suppressed in individualistic cultures, because the effects of trust and commitment likely
flourish in collectivist cultures, which tend to be more relationally oriented. In Table 2 we list the
definitions, aliases, and representative studies for the constructs in our conceptual model. (Table
2 follows References.)
In particular, communication is critical in collectivist cultures. Collectivists rely on close
coordination and communication to enable them to act in unison and achieve shared goals.
Communicating and socially identifying with others also helps establish the primacy of group
goals over individual goals (Wagner 1995). Collectivist cultures feature more explicit norms and
expectations regarding appropriate communication behaviors than do individualistic cultures,
where communication rules generally are unstructured (Hofstede, Hofstede, and Minkov 2010).
The structured nature of collectivist communication also helps reinforce social bonding and
solidarity among group members. For example, collectivist cultures prioritize communication
intimacy more than do individualistic cultures, encouraging mutual sharing and increasing the
potential for stronger relationships (Gudykunst, Yoon, and Nishida 1987).
Dependence also plays a much more central role in collectivist than in individualistic
cultures (Morishima and Minami 1983). Collectivists are expected to contribute to the overall
well-being of their entire group, and in exchange for their contributions, members receive
protection and can expect to share in the group’s successes (Hofstede, Hofstede, and Minkov
2010). Mutual interdependence and reciprocity help guide member behaviors to ensure they
align with collective group goals. Conversely, individualistic cultures tend to be driven by their
own beliefs, values, and attitudes (Hofstede, Hofstede, and Minkov 2010), such that members are
expected to look after themselves and make decisions independently of others (Roth 1995). In
individualistic cultures, people attempt to depend neither practically nor psychologically on
others (Hofstede, Hofstede, and Minkov 2010).
Finally, relationship duration should be more critical in collectivist than in individualistic
cultures. Collectivists are more likely than individualists to partner with another with whom they
have shared prior close ties (Wuyts and Geyskens 2005). In collectivist cultures, firms rarely
conduct business with unfamiliar firms and rely instead on long-term relationships (Wuyts and
Geyskens 2005). Whereas individualists remain in a relationship for only as long as it is
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convenient, collectivists view relationships as long term in nature (Hofstede, Hofstede, and
Minkov 2010), so relationship length likely carries more weight in these cultures. Because
collectivists place greater emphasis on relationship duration than do individualists, there also
may be a greater window of opportunity for relationships to flourish and grow, such that
relationships in collectivist societies deepen even further.
H1: The positive effects of (a) communication, (b) dependence, and (c) relationship duration on relational mediators (trust and commitment) grow weaker as a culture’s individualism increases.
Because collectivist cultures place a premium on the importance of relationships, they may
be able to leverage trust and commitment more effectively to drive word of mouth and objective
performance outcomes. Individualistic cultures are characterized by a loosely knit social
framework, which makes it more difficult for trust to transfer from one member to another
(Singh 1990; Ueno and Sekaran 1992). The reverse is true in collectivist cultures, which
facilitate the transference of trust among members and emphasize strong interpersonal ties (i.e.,
commitment). The “we” mentality associated with collectivist societies suggests that word of
mouth may spread and be accepted more readily than it might be in individualistic cultures that
lack such interpersonal ties (Doney, Cannon, and Mullen 1998). Finally, with regard to objective
performance, even if trust and commitment are high in individualistic cultures, individualists
generally are more difficult to work with than collectivists (Kirkman and Shapiro 2001), place
personal interests above shared group expectations (Wagner 1995), and make it more difficult for
firms to reap benefits from team-based structures (Kirkman and Shapiro 2001; Wagner 1995).
H2: The positive effects of relational mediators on (a) word of mouth and (b) objective performance grow weaker as a culture’s individualism increases.
Moderating role of power distance in relationship marketing
The power distance cultural dimension captures the extent to which inequalities between
more and less powerful members of society are considered acceptable (Hofstede 1991). In high
power distance cultures, an existing hierarchical system reinforces the inherent inequalities
among people. Thus organizations centralize power in as few hands as possible, and the system
emphasizes differences in power and status through prestige symbols (e.g., separate dining
rooms, parking places). In such cultures, people who hold power are entitled to exclusive
privileges and other symbolic behaviors that make them appear powerful (Hofstede, Hofstede,
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and Minkov 2010). Conversely, in low power distance cultures, inequality is considered
undesirable, and though it may be unavoidable, it should be minimized through legal means or
governmental intervention. Whereas privileges and status symbols are well accepted in high
power distance societies, they are generally frowned on in low power distance cultures.
Because status plays such a central role in high power distance cultures, relationship-
building strategies and outcomes linked to status seemingly should be strengthened (positively
moderated) in high power distance cultures but weakened in low power distance cultures. The
three relational constructs related to status in our conceptual framework are seller expertise, word
of mouth, and objective performance. Briefly, seller expertise conveys superior knowledge,
competency, and experience (Crosby, Evans, and Cowles 1990), which should be more highly
regarded in high power distance cultures. A key motivation for spreading word of mouth is to
enhance status, because it helps the person gain attention, show connoisseurship, and enhance his
or her reputation (Hennig-Thurau et al. 2004; Sundaram, Mitra, and Webster 1998). Similarly,
status is influenced by relative work outputs (performance), which should motivate employees to
work harder in cultures that emphasize status (Loch, Huberman, and Stout 2000). Such activities
should take on added importance and drive behavior more in high power distance cultures, which
place a premium on the importance of status. We therefore propose our second tenet:
Tenet 2: As cultural power distance increases, status-based relationships become easier to
form, and the beneficial effects of status-based outcomes increase.
In high-power distance cultures, inequalities are widely expected. This expectation
encourages the notion that information and knowledge sharing should be unequal too. People
with greater expertise and status maintain more information and therefore appear more credible
and trustworthy than those with less expertise. According to Hofstede, Hofstede, and Minkov
(2010), in decision settings, managers in high power distance cultures rely on their superiors
(i.e., perceived experts), whereas managers from low power distance cultures tend to rely on
their own experiences and subordinates (i.e., non-experts). All else being equal, expertise should
carry more weight and be more highly regarded in high versus low power distance cultures.
H3: The positive effects of seller expertise on relational mediators grow stronger as a culture’s power distance increases.
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A key motivation for engaging in word-of-mouth (WOM) behaviors and attaining greater
performance is self-enhancement and status seeking (Rose and Kim 2011; Sundaram, Mitra, and
Webster 1998). For example, providing WOM may allow a person to signal high status, project
him- or herself as an intelligent shopper, and enhance reputations (Hennig-Thurau et al. 2004;
Sundaram, Mitra, and Webster 1998). Similarly, attaining superior performance signals
competence and ability, and may motivate employees to work harder for the intrinsic status
benefits which accompany such performance (Huberman, Loch, and Önçüler 2004). Thus, strong
relationships should have a greater effect on WOM behaviors and performance-relevant
activities in high power distance cultures, due to the central role that relational status plays in
these societies.
H4: The positive effects of relational mediators on (a) word of mouth and (b) objective performance grow stronger as a culture’s power distance increases.
Moderating role of uncertainty avoidance in relationship marketing
Uncertainty avoidance is the extent to which the members of a culture feel threatened by
ambiguous or unknown situations (Hofstede, Hofstede, and Minkov 2010). In high uncertainty
avoidance cultures, the feeling that “what is different is dangerous” prevails (Hofstede, Hofstede,
and Minkov 2010, p. 203). Cultures with high uncertainty avoidance crave predictability and
shun ambiguity; those with low uncertainty avoidance accept uncertainty more readily, take
more risk, and value flexibility over the use of formal rules and explicit guidelines. Because
managing uncertainty plays a central role in high uncertainty avoidance cultures, we anticipate
that relationship-building strategies and outcomes linked to uncertainty reductions are stronger
(positively moderated) in high uncertainty avoidance cultures but weaker in low uncertainty
avoidance cultures. For example, seller expertise can help transform uncertainty into certainty
(Hofstede, Hofstede, and Minkov 2010) by demonstrating ability and competence. In addition,
relationship duration is important in this context, because relying on established, familiar
relationships helps confer predictability and may be perceived as less risky than new
relationships (Anderson and Weitz 1992; Doney and Cannon 1997). With this rationale, we
propose the third cultural–RM tenet:
Tenet 3: As cultural uncertainty avoidance increases, activities that reduce uncertainty make
relationships easier to form.
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In high uncertainty avoidance cultures, experts appear more credible than non-experts, and
this belief permeates many aspects of culture. For example, advertisements in high uncertainty
avoidance cultures often include doctors dressed in white coats, actively promoting products
(Hofstede, Hofstede, and Minkov 2010). In contrast, because low uncertainty avoidance cultures
cope more easily with uncertainty, they may rely less on the use of experts. Instead, common
sense and information obtained from generalists offer viable alternatives (Doney, Cannon, and
Mullen 1998; Hofstede, Hofstede, and Minkov 2010).
Similarly, relationship duration may become more important in high uncertainty avoidance
cultures, because they resist change and emphasize stability (Kale and Barnes 1992; Kale and
McIntyre 1991). In such cultures, people tend to rely on what is familiar, rather than what is new
or different. New relationships may be perceived as more risky than existing relationships, which
establishes expectations for future interactions (Doney and Cannon 1997). The longer a
relationship has survived, the more likely it is that the firms have also weathered a critical shake-
out period in their relationship, which further contributes to relationship stability and certainty
(Anderson and Weitz 1992; Dwyer, Schurr, and Oh 1987).
H5: The positive effects of (a) seller expertise and (b) relationship duration on relational mediators grow stronger as a culture’s uncertainty avoidance increases.
Moderating role of masculinity–femininity in relationship marketing
The masculinity–femininity cultural dimension captures the degree to which “tough”
(masculine) values prevail over “tender” (feminine) values in a society (Hofstede, Hofstede, and
Minkov 2010; see also Doney, Cannon, and Mullen 1998). In highly masculine cultures,
relationships appear less important, whereas values such as assertiveness, competitiveness, and
aggressiveness prevail. In more feminine cultures, relationships are more important, with an
emphasis on helping others, compromise, solidarity, and cooperation (Hofstede, Hofstede, and
Minkov 2010). This distinction is clear in the assertion that “Masculinity–femininity is about a
stress on ego versus a stress on relationship with others…. In a feminine society, the stress is
more on the importance of relationships with fellow humans” (Hofstede, Hofstede, and Minkov
2010, pp. 146, 177). Because relationships are less important in highly masculine cultures, we
anticipate that the relationship-based outcomes of WOM and objective performance are
weakened (negatively moderated) in masculine cultures but strengthened (positively moderated)
in feminine cultures. We thus propose our fourth and final cultural–RM tenet:
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Tenet 4: As a cultural masculinity increases, the beneficial effects of relationship-based
outcomes decline.
The core values of RM seem most closely aligned with femininity rather than with
masculinity. Feminine cultures not only emphasize relationships and collaboration but also are
associated with a higher level of benevolence. They also tend to view alliances as win–win
situations (Steensma et al. 2000). Conversely, masculine societies are competitive and
achievement oriented, with norms that prioritize striving to be the best (Kale and Barnes 1992).
Masculine cultures may discount RM’s core values of working together to achieve long-term
mutual success, because of their emphasis on excelling over others. In masculine cultures,
“Winning isn’t everything, it’s the only thing” (Hofstede, Hofstede, and Minkov 2010, p. 161).
In addition, whereas feminine cultures emphasize mutual, long-term gains attained from
interfirm alliances, masculine cultures tend to evaluate alliance benefits in terms of unilateral,
short-term gains (Steensma et al. 2000). The beneficial effects of relationships on WOM and
objective performance therefore should decrease in masculine cultures, which devalue the
importance of relationships as means for achieving success.
H6: The positive effects of relational mediators on (a) word of mouth and (b) objective performance grow weaker as a culture’s masculinity increases.
Study 1: Meta-Analysis of Moderating Effects of Culture on Relationship Marketing
Study 1 advances extant theory by applying Hofstede’s (1980; Hofstede, Hofstede, and
Minkov 2010) four dimensions of culture in a relational context to test our hypotheses directly
and assess the related tenets indirectly, providing a parsimonious, theoretically based synthesis of
how culture affects relationship marketing. Contrary to most prior international RM research, we
can evaluate the effectiveness of each cultural dimension while controlling for the simultaneous
effects of the other dimensions, due to the relatively large size of our meta-analysis sample,
which provides a robust test of how culture affects RM.
Sample and analytic approach
To identify articles that featured empirical links among previously identified key RM
constructs (see Palmatier et al. 2006), we began by searching several databases, including
ABI/Inform, PsychINFO, ProQuest, Science Direct, and Business Source Complete. We also
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conducted a thorough search of the Social Sciences Citation Index to identify additional articles
in our research domain. Next, we conducted a manual shelf search of journals that contained
results relevant to our analysis.
Because the most common method to report relationships among variables of interest
involved correlation coefficients, we used them as our primary measure of effect size. Two
independent coders coded the studies and resolved any differences (overall agreement > 95%)
through discussion. We performed analyses and tested hypotheses only if we found at least ten
raw effects and six different countries associated with an effect. Our final sample thus includes
42,378 dyadic relationships collected across 144 studies, 29 countries, and 6 continents.
We corrected the correlations obtained in each study for measurement error by dividing each
correlation coefficient by the product of the square root of the respective reliabilities of the two
constructs (Hunter and Schmidt 2004). When a study did not report the reliability for a relevant
construct, we used the average reliability for that construct across all the studies we collected.
Consistent with prior research, we then transformed the reliability-corrected correlations into
Fisher’s z coefficients, weighted them by the estimated inverse of their variance (N – 3) to give
greater weight to more precise estimates, and then converted them back to correlation
coefficients (Kirca, Jayachandran, and Bearden 2005). Because the main effects of the
antecedents → relational mediators → outcomes relationship are replications of previous work,
we present these results in the Appendix. Except for the increase in variance across correlations
(due to the inclusion of more international studies in the sample), the replication results are
consistent with previous research (Palmatier et al. 2006).
To analyze the moderating effects of Hofstede’s cultural dimensions on construct
correlations, we used multivariate meta-regression (Brown, Homer, and Inman 1998; Kirca,
Jayachandran, and Bearden 2005). We followed the procedure outlined by Hedges and Olkin
(1985) and regressed the Fisher z-transformed, reliability-adjusted correlations on each of the
four Hofstedian variables, with the other variables included in the model as controls.1 The
weighted least squares technique weighted each observation by the inverse of its variance (N –
1 Our analyses include the simultaneous effects of all cultural variables, with the exception of individualism–
collectivism in the power distance model and power distance in all other models, due to the high multicollinearity between individualism–collectivism and power distance (Steensma et al. 2000). All other reported results indicate low multicollinearity (variance inflation factor < 3.0).
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3). For the country in which each study was conducted, we used the values of the four cultural
dimensions for that country reported by Hofstede, Hofstede, and Minkov (2010).
Results: Moderating effects of cultural dimensions on relationship marketing
We report the results for each model in Table 3. Consistent with precedent, we abbreviate
individualism–collectivism and masculinity–femininity as “individualism” and “masculinity,”
because high cultural scores are typically represented as more individualistic and more masculine
(Hofstede, Hofstede, and Minkov 2010). (Table 3 follows References.)
We find strong support for Tenet 1: As cultural individualism increases, relationships based
on long-term social bonding and dependence become harder to form, and the beneficial effects of
relationship-based outcomes decline. The effectiveness of communication (β = -.29, p < .01),
dependence (β = -.41, p < .05), and relationship duration (β = -.30, p < .05) on relational
mediators all fall as cultural individualism increases. Thus, we find support for H1a–c. We also
find support for H2b, because as a culture’s individualism increases, the impact of relational
mediators on objective performance gets suppressed (β = -.29, p < .01). However, we cannot
confirm our prediction in H2a that increases in individualism suppress effects of relational
mediators on word of mouth (β = .32, p = .84). That is, we find support for H2b but not H2a.
In line with Tenet 2, as cultural power distance increases, status-based relationships become
easier to form, and the beneficial effects of status-based outcomes increase. Specifically, we find
support for H3 (β = .48, p < .05), because as power distance increases, the impact of seller
expertise on relational mediators increases. Similarly, in support of H4a–b, as power distance
increases, the impact of relational mediators on both WOM (β = .41, p < .05) and performance (β
= .21, p < .05) become enhanced.
We find partial support for Tenet 3, in which we predicted that as cultural uncertainty
avoidance increases, activities that reduce uncertainty make relationships easier to form. In
support of H5a, as uncertainty avoidance increases, so does the impact of seller expertise on
relational mediators (β = .42, p < .05). However, in relation to H5b, the impact of relationship
duration on relational mediators does not increase with greater uncertainty avoidance (β = .14, p
= .20). Although not hypothesized, our results also show that the impact of relationship
investments on relational mediators diminishes as cultural uncertainty avoidance increases (β = -
Marketing Science Institute Working Paper Series 14
.49, p < .01). The reasons for this result are not totally clear, but a possible explanation relates to
the notion that cultures with high uncertainty avoidance prefer not to get locked into reciprocal
relationships. Thus, high uncertainty avoidance cultures may be more skeptical of relationship
investments and less bound by feelings of reciprocity.
Finally, we find partial support for Tenet 4: As cultural masculinity increases, the beneficial
effects of relationship-based outcomes decline. The impact of relational mediators on word of
mouth (β = -.62, p < .01) decreases as masculinity increases, in support of H6a. However, we do
not find support for H6b, because as masculinity increases, the impact of relational mediators on
objective performance does not decline (β = .11, p = .81).
Discussion
The results demonstrate that accounting for culture is critical for understanding the
effectiveness of international RM. In Table 4, we summarize the findings from Study 1 and the
overall level of support for the four proposed tenets, namely, strong support for Tenets 1 and 2
regarding the individualism and power distance cultural dimensions and partial support for
Tenets 3 and 4 related to the uncertainty avoidance and masculinity dimensions. Thus, we
provide parsimonious theoretical insights regarding when and how each cultural dimension
moderates specific linkages in the RM framework. Individualism emerges as the most important
cultural dimension, in that it suppresses the effectiveness of many relationship-building strategies
(communication, dependence, duration), as well as the effect of relationships on objective
performance. In addition, it exerts the largest absolute impact on RM, averaging a magnitude of
impact 114%, 116%, and 169% greater than those of power distance, uncertainty avoidance, and
masculinity, respectively. In contrast, masculinity appears to be the least important cultural
dimension, with little impact on the effectiveness of relationship-building strategies or the links
to objective performance. Our results suggest that masculinity’s only moderating role, across the
links tested in our model, is to suppress the effect of relationships on generating WOM
behaviors. Overall then, our findings suggest that the magnitude of cultural effects vary across
dimensions, which is noteworthy because prior research often assumes equal influences. For
example, measures of cultural similarity often calculate the Euclidean distance between cultural
factors, which implicitly assumes that each cultural factor takes the same weight (Johnson and
Tellis 2008; Kogut and Singh 1988; Mitra and Golder 2002). Our results suggest otherwise.
Marketing Science Institute Working Paper Series 15
Applying the tenets for each cultural dimension to specific RM strategies also provides
managerial insights into how the effectiveness of RM strategies may depend on each cultural
dimension. For example, power distance is most critical for RM activities that emphasize status,
because seller expertise is more effective at building relationships, and relationships have a
stronger effect on WOM behaviors in high power distance cultures. Extending this tenet to
brands suggests that emphasizing exclusivity or a premium brand positioning should be more
effective in high rather than low power distance cultures, consistent with extant research (Roth
1995). These results have clear implications for firms looking to enhance the productivity of
their RM programs. In particular, managers should recognize how each country’s cultural profile
will likely interact with RM strategies before making implementation decisions. For example,
managers seeking strong relationships with the highest payoff (for objective performance) should
focus on countries that are highly collectivist and rank high on power distance.
Study 1 emphasizes the contingent nature of international RM, and though understanding
how cultural dimensions influence RM is an important theoretical first step, the findings are not
directly applicable for managers for two key reasons. First, many managers adapt their marketing
strategy using country-level structures, so guidance based on theoretically relevant cultural
dimensions is not ideal (Johansson 2009). They would benefit more from county-level guidance.
Second, the effects of culture on RM are multidimensional, and some cultural dimensions have
countervailing effects (e.g., individualism and power distance’s moderating effect on the link
between relational mediators and performance). Thus, the net effect of culture on RM in any
particular country is unclear. To address these issues, we use our meta-analysis results from
Table 3 to model specific country-level RM effects in Study 2.
Study 2: Effects of Country and Regional Cultural Profiles on Relationship Marketing
In Study 2, we compliment Study 1’s theoretical insights into the effects of culture by taking
a managerial perspective at the country and regional levels to address two important questions.
First, in what countries and regions do relationships offer the highest payoff? Second, what
relationship-building strategies are most effective in such countries and regions? The country-
level analysis in Study 2 provides managers with answers to both questions, in a format aligned
with their needs. However, a critical challenge for any country-level analysis is capturing the
Marketing Science Institute Working Paper Series 16
simultaneous effects of all four cultural dimensions (individualism, power distance, uncertainty
avoidance, and masculinity) to model culture’s net effect on RM in a specific country or region.
Modeling the effectiveness of relationship marketing by country and region
We begin Study 2 by determining where relationships contribute most to objective
performance and thus provide managers with practical insights for selecting countries in which
to pursue RM. After understanding where relationships pay off most, we can determine the
country-level effectiveness of specific relationship-building strategies to help managers allocate
their RM budget across different RM programs. We therefore consider where RM best enhances
performance and how to build relationships across specific countries.
Our analysis includes the 25 largest countries in terms of GDP and seven geographic regions
across the world: Africa, Asia, Eastern Europe, Western Europe, Latin America, North America,
and the Middle East. The 25 selected countries collectively account for 82% of the world’s GDP
(United Nations Database 2011). In Table 5 we provide the cultural profiles that we use in our
analysis (Hofstede, Hofstede, and Minkov 2010); by combining these profiles with our results
from Study 1, we can model how the effectiveness of RM varies globally. Thus, our results are
not confined to countries or regions already studied by RM researchers.
We integrate the cultural profile for a specific country or region into our multivariate
regression model using the coefficients for each cultural dimension, determined from our meta-
analysis results of more than 42,000 relationships reported in extant research (Table 3; Bijmolt,
Van Heerde, and Pieters 2005). To increase confidence in our results, we only performed the
analysis for linkages for which at least 10 countries appeared in the meta-analysis.2
Results and discussion
Effect of relationships on performance by country and region. In Table 5, we report the
results of our analysis of the effect of relationships on objective performance, by country and
region, providing both absolute (correlation coefficients for each country and region) and relative
(ranking across countries/regions and in comparison with the United States) effects. Nearly half 2 As we noted previously, high multicollinearity between individualism–collectivism and power distance made it impossible to include both covariates in our model at the same time (Steensma et al. 2000). Instead, we ran two models: one with individualism–collectivism, uncertainty avoidance, and masculinity–femininity and another with power distance, uncertainty avoidance, and masculinity–femininity. We averaged the results from these two models to report correlations by country and region.
Marketing Science Institute Working Paper Series 17
(46%) of the studies in our data collection came from the United States, so this country offers a
useful benchmark for gauging the relative effectiveness of RM in other countries. Academics or
managers wishing to generalize to other countries and regions may benefit from a clearer
understanding of how much more or less effective RM is likely to be, relative to their U.S.
results. We rank the 25 countries and 7 regions by their correlation coefficients. (Table 5 follows
References.)
As Table 5 illustrates, the United States ranks 16 out of 25 countries in terms of the
effectiveness of market relationships for enhancing objective performance. With a correlation of
.39, it falls below the average correlation of .43 and instead is near the lowest reported
correlation in the entire sample, .35, for Belgium, the Netherlands, and Norway. The highest
correlation in our sample refers to China (.61), followed by Indonesia (.57), and India (.54). The
strong customer–seller relationships in these top three ranked countries result in predicted
objective performance outcomes that are 55%, 44%, and 38% higher, respectively, than in the
United States. On average, relationships drive objective performance more outside the United
States than in it, and these differences are often substantial.
Furthermore, with the exception of Western Europe, marketing relationships are generally
more effective at driving objective performance in other geographic regions. Perhaps most
notably, marketing relationships increase objective performance substantially in Asia, where
their impact on objective performance is calculated to be 38% higher than in the United States.
These results are consistent with Study 1. For example, compared with the United States, Asia is
more collectivist, whereas high individualism negatively moderates the impact of relationships
on performance (Table 2). These findings also are consistent with research that emphasizes the
central role of relationships in Asia for achieving business success (e.g., guanxi in China,
keiretsu in Japan; Lee and Dawes 2005; Sambharya and Banerji 2006).
Effects of relationship-building strategies by country and region. In Table 6, we report the
results of our analysis of the effects of the five relationship-building strategies (communication,
seller expertise, dependence, relationship investments, relationship duration) on relationships, by
country and region. Again, we report both the absolute effect (correlation coefficients) and the
relative effect (ranking and comparison) for each path in the model. The results suggest that
communication and seller expertise are the two most effective relationship-building strategies
across the entire sample, consistent with past research (Palmatier et al. 2006).
Marketing Science Institute Working Paper Series 18
The results in Table 6 also illustrate significant country and regional variations though.
Similar to our findings regarding the effect of relationships on performance, the United States
ranks toward the bottom of the list of countries in terms of the effectiveness of three RM
strategies for building relationships: seller expertise, dependence, and relationship duration.
Comparing overall country averages with U.S. averages, we find that seller expertise,
dependence, and relationship duration are, respectively, 76%, 78%, and 57% more effective in
other countries. Regarding communication, the U.S. ranking is average; the use of
communication to build relationships is a more effective RM strategy in Asia (18% above the
U.S.) but a less effective strategy in Western Europe (5% below the U.S.). Relationship
investments instead are 21% less effective in countries outside the United States—the only
relationship-building strategy in which the U.S. ranking is significantly above average (6 out of
25 countries). This result may be due to the relatively low level of uncertainty avoidance in the
United States compared to the other 24 countries, in that uncertainty avoidance suppresses the
beneficial effects of relationship investments on relational mediators.
Post hoc analyses
Magnitude of culture’s influence on relationship marketing. To gain more insights into the
magnitude and relevance of culture’s influences on RM, we compare the range (highest–lowest)
of country-level correlations for each link in Tables 5 and 6 against the unmoderated, sample-
weighted, reliability-adjusted correlations from Study 1 (as reported in the Appendix).
Significant variance in the correlations across countries calls for assessments of culture’s
influence on RM. That is, we observe moderate to large variations in the effectiveness of each
RM strategy, depending on the country. For example, the unmoderated correlation between seller
expertise and trust/commitment is .33, but country-level correlations range from .19 (Great
Britain) to .84 (Russia), a difference of .65, or nearly twice the unmoderated correlation.
Similarly, the correlations for the other RM strategies range from .50 to .76 for communication,
.22 to .62 for dependence, .18 to .59 for relationship investments, and .11 to .28 for relationship
duration. These ranges, compared with their unmoderated correlations (see the Appendix), vary
by 44% to 197% and thus are clearly managerially relevant.
Marketing Science Institute Working Paper Series 19
The unmoderated correlation between the relational mediators and objective performance is
.41, whereas the country-level correlations range from .35 to .61, a difference of .26, or 63% of
the unmoderated correlation. On average, we find greater variation across countries in terms of
building relationships (107%) rather than using relationships to drive performance (63%).
Therefore, the net effects of culture on RM appear to be more important in the relationship-
building stage of RM than in the performance driving stage. This difference might arise because
factors other than culture also affect a firm’s performance, beyond the influence of customer–
seller relationships. For example, pricing and competition have relatively large impacts on
performance, so the moderating role of culture on the relationship–performance link might
diminish.
Analysis of model robustness. To test the robustness of the country/region results from Study
2, we conducted a post hoc meta-analysis with subgroups, to compute the sample weighted,
reliability-adjusted correlations for any connection in the RM framework that appeared in at least
10 studies from a specific country or region. We compared these meta-analysis–derived
correlations for a specific country or region against the correlations we calculated with our
model, using cultural dimensions for that country or region (Study 2, Tables 5 and 6). We were
able to calculate 18 sample-weighted, reliability-adjusted correlations for different country and
region subgroups. The average of the absolute difference across all these correlations was only
.039. This result increased confidence in our country- and regional-level results from Study 2.
General Discussion and Implications
Relationship marketing is effective (Swaminathan and Moorman 2009). It thus has become
the focus of more international research. Whereas most research adopts and applies the logic of a
U.S.-based RM framework, we suggest the need to tailor this framework before applying it
outside the United States. Results from our two studies support our predictions, namely, that
dimensions of culture fundamentally alter the effectiveness of RM across countries. Thus we
extend RM theory by considering how it is shaped by culture. In doing so, we provide both
theoretical insight into how market relationships operate internationally and a tool for managers
evaluating and seeking to build RM strategies across countries.
Marketing Science Institute Working Paper Series 20
How culture shapes relationship marketing theory
To clarify how culture influences RM, we offer four tenets: (1) as cultural individualism
increases, relationships based on long-term social bonding and dependence become harder to
form, and the beneficial effects of relationship-based outcomes decline; (2) as cultural power
distance increases, status-based relationships become easier to form, and the beneficial effects of
status-based outcomes increase; (3) as cultural uncertainty avoidance increases, activities that
reduce uncertainty make relationships easier to form; and (4) as cultural masculinity increases,
the beneficial effects of relationship-based outcomes decline. Evidence from Study 1 (Table 4)
supports these tenets, and each can serve as a conceptual guide for further research and practice.
In addition, by accounting for the simultaneous effects of multiple dimensions, we find that
the moderating effects of cultural dimensions vary in their relevance. For example, individualism
is the most important cultural dimension, with effects on most RM linkages, as well as effects
that are 114% to 169% greater in magnitude than those of other cultural dimensions. Research
that weights cultural dimensions equally (Johnson and Tellis 2008; Kogut and Singh 1988; Mitra
and Golder 2002) thus may be overrepresenting some of the less consequential aspects of
culture. Constructing new cultural distance measures that account for differential effects across
cultural dimensions thus may yield surprising, novel insights for marketing theory and practice.
How managers should adapt their international relationship marketing strategies
Understanding the simultaneous, often countervailing effects of cultural dimensions within a
single country impedes strategy development, and we therefore extended our empirical model in
Study 2 to make predictions about the effectiveness of RM in specific countries and regions. In
turn, we identify the situations in which RM is most effective for driving performance, and we
explicate ways to tailor relationship-building strategies effectively. These results are striking.
The United States ranks only 16 (out of 25 countries) in terms of RM effectiveness for
performance. On average RM is more effective outside the United States. For example, it is 17%,
15%, 38%, and 55% more effective in Brazil, Russia, India, and China, respectively, suggesting
a primary role for RM in the developing BRIC countries. We also find that strategies for building
relationships must be tailored to specific countries. For example, Berlin is separated from
Moscow by just a brief 2.5-hour flight, but the countries are culturally very distant. Managers in
Russia seeking to build relationships can benefit from expertise- and dependence-based
Marketing Science Institute Working Paper Series 21
strategies, but in Germany, the two top strategies for building relationships are communication
and relationship investment. Extant research that has asserted that expertise and communication
are the sole best RM strategies ignores important country-specific clarifications; research
suggesting that “dependence is not an effective relationship-building strategy” (Palmatier et al.
2006, p. 150) also does not apply to countries such as Russia, where dependence is 150% more
effective than in the United States. The tables included in this article thus should serve as useful
tools for managers seeking an international RM perspective.
In Figure 2 we also offer a parsimonious graphical illustration of the most effective
international RM strategies for the largest economic regions and countries. This overlapping
diagram illustrates the heterogeneity across RM strategies (Study 2). Even if common themes
exist (e.g., overall effectiveness of communication and expertise for building relationships), a
disaggregation of strategies to account for regional and country-level differences can help
safeguard against the “failure to take cultural differences between countries into account [that]
has been the cause of many business failures” (Steenkamp 2001, p. 30). Evidence from Study 2
also offers insight into a surprising finding: Culture has a greater influence on relationship
construction than on relationship outcomes. Managers may evaluate the attractiveness of RM on
the basis of objective performance outcomes in a country or region (Table 5), but once
determined, more specific attention should focus on the nuances of relationship-building
strategies (Table 6), because each country is culturally unique. Ultimately, international
relationship marketing strategies succeed if they are well adapted to local cultural environments.
Limitations and Further Research
This research has some limitations that are typical of most meta-analyses. First, we
attempted to be comprehensive in our inclusion of RM constructs across publication outlets, but
we may have overlooked some studies. Second, because most research adopts a U.S.-based RM
framework, we are limited in the scope of available constructs. Our finding that culture has a
larger impact on relationship building than on relationship outcomes suggests a clear opportunity
for research that can identify the “unknown unknowns” of international RM.
Although culture usually is examined at the societal or national level (Hofstede, Hofstede,
and Minkov 2010), it is also relevant at the regional, organizational, and individual levels (Earley
Marketing Science Institute Working Paper Series 22
and Gibson 1998; Triandis 1989, 1995). Thus, further research should investigate how levels of
analysis for different cultural entities interact and influence RM. For example, a Japanese
organization with U.S. operations simultaneously manages employee cultures in two countries
with very different cultural profiles, which may be increasingly challenging in changing
relationship environments (Brown et al. 2005). The question of how cultural structures interact
with other marketing variables to influence the effectiveness of RM remains unanswered.
Finally, diasporas and immigrant cultural enclaves establish and operate in foreign countries with
great economic consequences (i.e., 215 million first-generation migrants globally; The
Economist 2011). Understanding how to implement culturally balanced RM strategies among
these populations requires additional research.
Marketing Science Institute Working Paper Series 23
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Wuyts, Stefan, and Inge Geyskens (2005), “The Formation of Buyer-Seller Relationships: Detailed Contract Drafting and Close Partner Selection,” Journal of Marketing, 69 (October) 103-117.
Marketing Science Institute Working Paper Series 28
Reference Key Constructs Key Findings
Individualism-Collectivism
Noesjirwan (1978); Gudykunst,
Yoon, and Nishida (1987)
Communication Collectivists are more likely to hide negative emotions
to preserve group harmony and to encourage greater
communication intimacy than individualists.
Morishima and Minami (1983);
Hofstede, Hofstede, and Minkov
(2010)
Dependence Interdependence and affiliation are more important for
collectivists than for individualists.
Wuyts and Geyskens (2005) Relationship
duration
Collectivist firms are more likely to select a close
partner with whom they have shared prior close ties.
Earley and Gibson (1998);
Kirkman (1996)
Objective
performance
Having a collectivistic orientation improves
performance on teams, while being an individualist
exerts a negative impact on performance. Individualism
lowers productivity on teams.
Money, Gilly, and Graham (1998) Word of mouth Japanese (collectivist) firms rely more on word-of-
mouth referrals than U.S. (individualistic) firms.
Power Distance
Pornpitakpan and Francis (2001) Seller expertise People from high power distance cultures are more
influenced by expertise than people from low power
distance cultures.
Lam, Lee, and Mizerski (2009) Word of mouth High power distance has a positive effect on in-group
word of mouth.
Uncertainty Avoidance
Hofstede (1980); Hofstede,
Hofstede, and Minkov (2010);
Pornpitakpan and Francis (2001)
Seller expertise High uncertainty avoidance cultures are more likely to
rely on experts than generalists. Non-experts are
perceived as less competent than experts in high
uncertainty avoidance cultures.
Kale and Barnes (1992); Kale and
McIntyre (1991)
Relationship
duration
Cultures high in uncertainty avoidance may exhibit a
stronger resistance to change because of the high
importance placed on stability.
Masculinity-Femininity
Steensma et al. (2000); Kale and
Barnes (1992); Hofstede,
Hofstede, and Minkov (2010)
Objective
performance
Whereas feminine cultures generally emphasize
relationships and collaboration for achieving success,
masculine cultures emphasize the importance of
competitiveness and winning.
TABLE 1
Selected Literature on the Role of Culture in Relationship Marketing
Marketing Science Institute Working Paper Series 29
Definitions Common Aliases Representative Studies
Relational MediatorsTrust Confidence in an exchange partner’s
reliability, integrity, and
forthrightness
Trustworthiness, credibility,
benevolence, and honesty
Doney and Cannon (1997);
Morgan and Hunt (1994)
Commitment An enduring desire to maintain a
valued relationship
Affective, behavioral, obligation,
and normative commitment
Anderson and Weitz (1992);
Morgan and Hunt (1994)
Antecedents
Relationship
investments
Seller’s investment of time, effort,
spending, and resources focused on
building a stronger relationship
Support, gifts, resources,
investments, and loyalty
programs
De Wulf, Odekerken-Schröder,
and Iacobucci (2001);
Palmatier Gopalalkrishna, and
Houston (2006)
Communication Amount, frequency, and quality of
information shared between
exchange partners
Bilateral or collaborative
communication, information
exchange, and sharing
Anderson and Weitz (1992);
Morgan and Hunt (1994)
Dependence on
seller
Customer’s evaluation of the value
of seller-provided resources for
which few alternatives are
available from other sellers
Relative and asymmetric
dependence, switching costs,
and imbalance of power
Morgan and Hunt (1994);
Palmatier et al. (2006)
Seller expertise Knowledge, experience, and overall
competency of seller
Competence, skill, knowledge,
and ability
Crosby, Evans, and Cowles
(1990)
Relationship
duration
Length of time that the relationship
between exchange partners has
existed
Relationship age or length,
continuity, and duration with
firm or salesperson
Anderson and Weitz (1989);
Doney and Cannon (1997)
OutcomesWord of mouth Likelihood of a customer
positively referring the seller to
another potential customer
Referrals and customer referrals Hennig-Thurau, Gwinner, and
Gremler (2002); Palmatier et
al. (2006)
Seller objective
performance
Actual seller performance
enhancements including sales,
share of wallet, profit performance,
and other measurable changes to
the seller’s business
Sales, share, sales effectiveness,
profit, and sales performance
Johnson and Tellis (2008);
Palmatier, Gopalalkrishna, and
Houston (2006)
Note: Adapted from Palmatier et al. 2006.
Constructs
TABLE 2Construct Definitions, Aliases, and Representative Studies
Marketing Science Institute Working Paper Series 30
Number
of Raw
Effects
Number
of
Countries
AntecedentsRelationship investments → Commitment 11 5 — — — —Relationship investments → Trust 17 9 .02 - .20 - .36 - .06Relationship investments → Relational mediators 28 10 - .15 .02 - .49*** .19
Communication → Commitment 38 15 - .24* .14 - .41** .29*Communication → Trust 46 17 - .33** .19 - .07 .08Communication → Relational mediators 84 19 - .29*** .16 - .19* .15
Dependence on seller → Commitment 21 9 - .37 .21 .07 - .07Dependence on seller → Trust 30 10 - .50** .23 - .16 - .16Dependence on seller → Relational mediators 51 11 - .41** .20 - .05 - .09
Seller expertise → Commitment 6 6 — — — —Seller expertise → Trust 25 12 - .15 .56*** .46** - .02Seller expertise → Relational mediators 31 13 - .01 .48** .42** - .16
Relationship duration → Commitment 19 8 - .31 .16 .16 .09Relationship duration → Trust 22 7 - .26 .22 .08 .08Relationship duration → All mediators 41 10 - .30** .19 .14 .10
OutomesCommitment → Word of mouth 14 3 — — — —Trust → Word of mouth 9 5 — — — —Relational mediators → Word of mouth 23 6 .32 .41** .44 - .62***
Commitment → Objective performance 31 13 - .44** .29* .00 .21Trust → Objective performance 42 14 - .07 .04 - .24 - .18Relational mediators → Objective performance 73 18 - .29*** .21** - .12 .11
***p < .01. **p < .05. *p < .10.
Notes: Operationally, we attempted calculations only when there were a minimum of ten raw effects and six countries associated with a relationship. A dash
(―) indicates when this condition was not met. Standardized estimates of the regression analyses are reported for each cultural dimension.
TABLE 3
Study 1 Results: Influence of Cultural Moderators on Relationship Marketing Framework
Proposed Relationships IndividualismPower
Distance
Uncertainty
AvoidanceMasculinity
Marketing Science Institute Working Paper Series 31
H1a Communication → Relational mediators Individualism ‒ decreased Supported
H1b Dependence on Seller → Relational mediators Individualism ‒ decreased Supported
H1c Relationship duration → Relational mediators Individualism ‒ decreased Supported
H2a Relational mediators → Word of mouth Individualism ‒ decreased Not supported
H2b Relational mediators → Objective performance Individualism ‒ decreased Supported
H3 Seller expertise → Relational mediators Power Distance + increased Supported
H4a Relational mediators → Word of mouth Power Distance + increased Supported
H4b Relational mediators → Objective performance Power Distance + increased Supported
H5a Seller expertise → Relational mediators Uncertainty Avoidance + increased Supported
H5b Relationship duration → Relational mediators Uncertainty Avoidance + increased Not supported
H6a Relational mediators → Word of mouth Masculinity ‒ decreased Supported
H6b Relational mediators → Objective performance Masculinity ‒ decreased Not supported
TABLE 4
Study 1: Summary of Support for Tenets and Hypotheses
Tenet 3
Tenet 1
Tenet 2
Hypotheses Supported?
As cultural individualism increases, relationships based on long-term social bonding and dependence become harder to form, and the beneficial
effects of relationship-based outcomes decline.
As cultural power distance increases, status-based relationships become easier to form, and the beneficial effects of status-based outcomes
increase.
As a cultural masculinity increases, the beneficial effects of relationship-based outcomes decline.
As cultural uncertainty avoidance increases, activities that reduce uncertainty make relationships easier to form.
Tenet 4
Hypothesized Path Cultural ModeratorTenet /
Hypothesis
Hypothesized
Moderating Effect
Marketing Science Institute Working Paper Series 32
Est. Rank Relative Power UncertaintyEffect Order to U.S. Distance Avoidance
Country
Australia .37 22 -5% 90 36 51 61
Belgium .35 23 -10% 75 65 94 54
Brazil .46 6 17% 38 69 76 49
Canada .39 14 0% 80 39 48 52
China .61 1 55% 20 80 30 66
France .37 21 -5% 71 68 86 43
Great Britain .41 11 5% 89 35 35 66
Germany .37 20 -5% 67 35 65 66
Indonesia .57 2 44% 14 78 48 46
India .54 3 38% 48 77 40 56
Iran .46 5 18% 41 58 59 43
Italy .38 19 -4% 76 50 75 70
Japan .41 12 5% 46 54 92 95
South Korea .44 9 12% 18 60 85 39
Mexico .50 4 27% 30 81 82 69
Netherlands .35 25 -12% 80 38 53 14
Norway .35 24 -11% 69 31 50 08
Poland .39 13 1% 60 68 93 64
Russia .45 7 15% 39 93 95 36
Saudi Arabia .45 8 15% 43 61 68 49
Spain .38 18 -3% 51 57 86 42
Sweden .39 15 0% 71 31 29 05
Switzerland .39 17 0% 68 34 58 70
Turkey .43 10 9% 37 66 85 45
USA .39 16 0% 91 40 46 62
Country Averages .43 9% 55 57 66 50
Region
Africa .48 2 22% 36 67 65 49
Asia .54 1 38% 24 73 50 53
Eastern Europe .44 6 12% 46 66 74 47
Latin America .46 3 17% 23 71 86 47
North America .45 4 16% 54 49 51 55
Middle East .46 5 17% 38 65 71 47
Western Europe .38 7 -3% 63 46 69 48
Regional Averages .46 17% 41 62 67 50
Notes: The country averages exclude the United States. "Est. Effect" represents the model estimated effect of relational
mediators on outcomes in countries and regions listed.1 Cultural scores reproduced from Hofstede, Hofstede, and Minkov (2010).
TABLE 5
Study 2: Effects of Relational Mediators on Performance and Cultural Scores by Country
Objective Performance
Individualism Masculinity
Cultural Dimension Scores1
Marketing Science Institute Working Paper Series 33
Est. Rank Relative Est. Rank Relative Est. Rank Relative Est. Rank Relative Est. Rank RelativeEffect Order to U.S. Effect Order to U.S. Effect Order to U.S. Effect Order to U.S. Effect Order to U.S.
CountryAustralia .57 17 -3% .32 23 -1% .24 24 -2% .42 8 -6% .13 21 0%Belgium .51 23 -13% .73 3 128% .41 17 66% .18 25 -59% .20 14 57%Brazil .62 9 4% .70 8 119% .53 6 114% .32 17 -29% .24 8 90%Canada .58 14 -1% .37 20 15% .31 18 28% .43 7 -4% .14 19 8%China .76 1 29% .47 18 47% .53 5 117% .59 1 32% .26 5 102%France .53 22 -11% .74 2 132% .46 14 88% .21 23 -52% .20 15 56%Great Britain .62 7 5% .19 25 -41% .22 25 -12% .51 3 14% .12 24 -6%Germany .58 16 -2% .36 21 14% .29 21 16% .37 11 -16% .17 17 33%Indonesia .71 2 21% .62 11 94% .60 2 145% .48 4 8% .26 3 108%India .70 3 19% .54 13 70% .50 9 102% .51 2 14% .22 11 71%Iran .63 5 6% .59 12 86% .51 8 106% .39 10 -11% .21 13 68%Italy .57 18 -3% .52 16 63% .30 20 21% .32 16 -28% .18 16 41%Japan .62 6 5% .53 14 68% .30 19 23% .30 18 -33% .25 6 93%South Korea .59 11 0% .72 6 125% .58 3 135% .26 19 -41% .26 4 103%Mexico .66 4 12% .72 5 125% .52 7 110% .33 15 -26% .28 1 117%Netherlands .50 25 -16% .53 15 68% .45 15 82% .34 14 -25% .12 23 -4%Norway .50 24 -15% .49 17 54% .48 13 93% .35 13 -21% .13 22 -2%Poland .57 19 -4% .71 7 125% .42 16 72% .22 22 -50% .23 9 79%Russia .58 15 -2% .84 1 165% .62 1 150% .19 24 -58% .27 2 111%Saudi Arabia .62 8 5% .63 10 97% .49 10 100% .36 12 -20% .22 10 74%Spain .54 21 -8% .69 9 118% .49 11 98% .23 21 -48% .21 12 68%Sweden .55 20 -7% .39 19 24% .48 12 94% .45 5 2% .11 25 -15%Switzerland .60 10 2% .30 24 -6% .26 22 6% .42 9 -6% .16 18 29%Turkey .59 13 -1% .73 4 128% .54 4 118% .26 20 -42% .24 7 91%USA .59 12 0% .32 22 0% .25 23 0% .44 6 0% .13 20 0%
Country Averages .60 1% .56 76% .44 78% .35 -21% .20 57%
RegionAfrica .64 2 9% .65 4 103% .52 3 113% .38 3 -15% .24 3 85%Asia .70 1 18% .59 5 85% .55 2 123% .47 1 6% .25 2 96%Eastern Europe .60 6 2% .68 2 114% .50 5 105% .31 6 -29% .23 5 77%
Latin America .61 5 4% .74 1 133% .57 1 132% .27 7 -39% .27 1 110%Middle East .62 4 5% .66 3 109% .52 4 111% .34 4 -23% .23 4 83%North America .63 3 7% .45 7 41% .41 6 65% .44 2 0% .19 6 47%Western Europe .56 7 -5% .54 6 70% .40 7 63% .33 5 -26% .18 7 40%Regional Averages .62 6% .62 94% .50 102% .36 -18% .23 77%
Notes: The country averages exclude the United States. "Est. Effect" represents the model estimated effect of antecedents on relational mediators in countries and
regions listed.
TABLE 6
Study 2: Effects of Antecedents on Relational Mediators Across Countries
Communication Seller Expertise Dependence Relationship Invest. Relationship Dur.
Marketing Science Institute Working Paper Series 34
FIGURE 1International Relationship Marketing Framework
Relationship investments
Relational Mediators
Cultural Moderators
Communication
Dependence on seller
Seller expertiseObjective performance
Word of mouth
Individualism-collectivism
Power distance
Uncertainty avoidance
Masculinity-femininity
Relationship duration
Relational Antecedents
Performance Outcomes
Trust
Commitment
Marketing Science Institute Working Paper Series 35
FIGURE 2
Study 2: Effectiveness of Antecedents → Relational Mediators → Performance Across Top Four Economies
Notes: Axes represent effect of relationship-building strategy on relational mediators or effect of relational mediators on objective performance. Lines
closer to scale endpoints represent stronger effects within region or country.
Performance
Communication
Expertise
Dependence
Investments
Duration
-
0.40
North America
Western Europe
Asia
Latin America
-
0.40
USA
China
Japan
Germany
Performance
Communication
Expertise
Dependence
Relationshipinvestments
Duration
Performance
Communication
Expertise
Dependence
Relationship investments
Duration
Top Four Economic Regions
Top Four Economies
Marketing Science Institute Working Paper Series 36
Lower
Bound
Upper
Bound
Antecedents
Relationship investments → Commitment 11 2,927 0.39 0.46 0.42 0.39 0.45 1,776 184.72 (10)
Relationship investments → Trust 17 3,998 0.36 0.44 0.36 0.33 0.39 2,675 244.42 (16)
Relationship investments → Relational mediators 28 6,925 0.37 0.45 0.39 0.37 0.41 8,836 439.08 (27)
Communication → Commitment 38 8,240 0.48 0.58 0.58 0.56 0.59 33,060 591.74 (37)
Communication → Trust 46 11,144 0.49 0.61 0.60 0.59 0.61 60,787 1,939.02 (45)
Communication → Relational mediators 84 19,384 0.49 0.60 0.59 0.58 0.60 183,590 2537.07 (83)
Dependence on seller → Commitment 21 5,632 0.37 0.45 0.40 0.37 0.42 5,831 620.84 (20)
Dependence on seller → Trust 30 6,838 0.17 0.20 0.23 0.20 0.25 2,341 501.48 (29)
Dependence on seller → Relational mediators 51 12,470 0.26 0.31 0.31 0.29 0.32 15,621 1232.63 (50)
Seller expertise → Commitment 6 1,544 0.31 0.39 0.32 0.28 0.37 322 266.34 (5)
Seller expertise → Trust 25 10,402 0.42 0.54 0.33 0.31 0.35 12,084 1,576.48 (24)
Seller expertise → Relational mediators 31 11,946 0.40 0.51 0.33 0.31 0.34 16,390 1842.85 (30)
Relationship duration → Commitment 19 8,056 0.12 0.14 0.15 0.13 0.17 718 276.93 (18)
Relationship duration → Trust 22 8,479 0.12 0.13 0.15 0.12 0.17 766 76.32 (21)
Relationship duration → Relational mediators 41 16,535 0.12 0.13 0.15 0.13 0.16 3,006 353.30 (40)
Outcomes
Commitment → Word of mouth 14 3,686 0.66 0.72 0.69 0.67 0.71 9,932 337.36 (13)
Trust → Word of mouth 9 2,688 0.59 0.70 0.64 0.61 0.66 3,912 383.06 (8)
Relational mediators → Word of mouth 23 6,374 0.64 0.71 0.67 0.65 0.68 26,332 734.25 (22)
Commitment → Objective performance 31 8,061 0.34 0.41 0.35 0.33 0.37 9,463 599.04 (30)
Trust → Objective performance 42 9,628 0.34 0.42 0.46 0.45 0.48 21,607 1,361.55 (41)
Relational mediators → Objective performance 73 17,689 0.34 0.42 0.41 0.40 0.43 59,742 2,033.29 (72)
Study 1 Results: Relationship Marketing Framework Without Cultural ModerationAPPENDIX
Q-Statistic for
Homogeneity
Test (df)
Proposed Relationships
Number
of Raw
Effects
Total N
Simple
Average
r
Average r
Adjusted for
Reliability
Sample Weighted
Reliability Adjusted
Average r
95% Confidence
IntervalFile Drawer
N (using two-
tailed test)
Marketing Science Institute Working Paper Series 37