international relationship marketing · 2020. 6. 9. · international relationship marketing ....

“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.

Marketing Science Institute Working Paper Series 1

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.


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


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


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,


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,


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


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,


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.


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.


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:


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


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).


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 = -


.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.


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


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.


(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).


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.


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.


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


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


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.


References

Aaker, Jennifer L., and Patti Williams (1998), “Empathy versus Pride: The Influence of

Emotional Appeals across Cultures,” Journal of Consumer Research, 25 (3), 241-261.

Allik, Jüri and Anu Realo (2004), "Individualism-Collectivism and Social Capital," Journal of

Cross-Cultural Psychology, 35 (1), 29-49.

Anderson, Erin, and Barton Weitz (1992), “The Use of Pledges to Build and Sustain Commitment in Distribution Channels,” Journal of Marketing Research, 29 (February), 18-34.

Beetles, Andrea and Andrew Crane (2005), "Mapping Out the Field of Gender and Buyer-Seller Relationships: Developing a New Perspective," Journal of Marketing Management, 21, 231-50.

Bijmolt, Tammo H.A., Harald J. Van Heerde, and Rik G.M. Pieters (2005), "New Empirical Generalizations on the Determinants of Price Elasticity," Journal of Marketing Research, 42 (May), 141-156.

Brown, Steven P., Kenneth R. Evans, Murali K. Mantrala, and Goutam Challagalla (2005), "Adapting Motivation, Control, and Compensation Research to a New Environment," Journal of Personal Selling and Sales Management, 25 (2), 155-67.

———, Pamela M. Homer, and J. Jeffrey Inman (1998), "A Meta-Analysis of Relationships between Ad-Evoked Feelings and Advertising Responses," Journal of Marketing Research, 35 (1), 114-26.

CIA (2010), The World Factbook. Washington, DC: Central Intelligence Agency

Crosby, Lawrence A., Kenneth R. Evans, and Deborah Cowles (1990), "Relationship Quality in Services Selling: An Interpersonal Influence Perspective," Journal of Marketing, 54 (3), 68-81.

De Wulf, Kristof, Gaby Odekerken-Schroder, and Dawn Iacobucci (2001), "Investments in Consumer Relationships: A Cross-Country and Cross-Industry Exploration," Journal of

Marketing, 65 (4), 33-50.

Deleersnyder, Barbara, Marnik G. Dekimpe, Jan-Benedict E.M. Steenkamp, and Peter S.H. Leeflang (2009), "The Role of National Culture in Advertising's Sensitivity to Business Cycles: An Investigation Across Continents," Journal of Marketing Research, 46 (5), 623-36.

Doney, Patricia M., and Joseph Cannon (1997), “An Examination of the Nature of Trust in Buyer-Seller Relationships,” Journal of Marketing, 61 (April), 35-51.

———, ———, and Michael R. Mullen (1998), "Understanding the Influence of National Culture on the Development of Trust," Academy of Management Review, 23 (3), 601-20.


Dwyer, Robert F., Paul H. Schurr, and Sejo Oh (1987), "Developing Buyer-Seller Relationships," Journal of Marketing, 51 (2), 11-27.

Earley, P. Christopher, and Cristina B. Gibson (1998), “Taking Stock in Our Progress on Individualism-Collectivism: 100 Years of Solidarity and Community,” Journal of

Management, 24 (3), 265-304.

Erramilli, M. Krishna and C. P. Rao (1993), "Service Firms' International Entry-Mode Choice: A Modified Transaction-Cost Analysis Approach," Journal of Marketing, 57 (3), 19.

Fletcher, Richard and Tony Fang (2006), "Assessing the Impact of Culture on Relationship Creation and Network Formation in Emerging Asian Markets," European Journal of

Marketing, 40 (3-4), 430-46.

Ghemawat, Pankaj (2011), "The Cosmopolitan Corporation," Harvard Business Review (May), 1-9.

Gudykunst, William B., Young-Chul Yoon, and Tsukasa Nishida (1987), "The Influence of Individualism-Collectivism on Perceptions of Communication Ingroup and Outgroup Relationships," Communication Monographs, 54 (3), 295.

Han, Sang-Pil, and Sharon Shavitt (1994), “Persuasion and Culture: Advertising Appeals in Individualistic and Collectivistic Societies,” Journal of Experimental Social Psychology, 30, 326-350.

Hedges, Larry V. and Ingram Olkin (1985), Statistical Methods for Meta-Analysis. Orlando, FL: Academic Press.

Hennig-Thurau, Thorsten, Kevin P. Gwinner, and Dwayne D. Gremler (2002), "Understanding Relationship Marketing Outcomes: An Integration of Relational Benefits and Relationship Quality," Journal of Service Research, 4 (3), 230-47.

———, ———, Gianfranco Walsh, and Dwayne D. Gremler (2004), “Electronic Word-of-Mouth Via Consumer-Opinion Platforms: What Motivates Consumers to Articulate Themselves on the Internet?” Journal of Interactive Marketing, 18 (1), 38-52.

Hofstede, Geert H. (1980), Culture's Consequences: International Differences in Work-Related

Values. Beverly Hills, CA: Sage Publications.

——— (1991), Cultures and Organizations: Software of the Mind. London; New York: McGraw-Hill.

———, Gert Jan Hofstede, and Michael Minkov (2010), Cultures and Organizations: Software

of the Mind, Intercultural Cooperation and Its Importance for Survival. New York: McGraw-Hill.

Huberman, Bernardo A., Christoph H. Loch, and Ayse Önçüler (2004), “Status As a Valued Resource,” Social Psychology Quarterly, 67 (1), 103-114.


Hunter, John E. and Frank L. Schmidt (2004), Methods of Meta-Analysis: Correcting Error and

Bias in Research Findings, 2d ed. Thousand Oaks, CA: Sage Publications.

Johansson, Johny K. (2006), Global Marketing: Foreign Entry, Local Marketing & Global

Management. Boston: McGraw-Hill Irwin.

Johnson, Joseph, and Gerard J. Tellis (2008), “Drivers of Success for Market Entry into China and India,” Journal of Marketing, 72 (May), 1-13.

Kale, Sudhir H. and John W. Barnes (1992), "Understanding the Domain of Cross-National Buyer-Seller Interactions," Journal of International Business Studies, 23 (1), 101-32.

——— and Roger P. McIntyre (1991), "Distribution Channel Relationships in Diverse Cultures," International Marketing Review, 8 (3), 31-45.

Kirca, Ahmet H., Satish Jayachandran, and William O. Bearden (2005), "Market Orientation: A Meta-Analytic Review and Assessment of Its Antecedents and Impact on Performance," Journal of Marketing, 69 (2), 24-41.

Kirkman, Bradley L. and Debra L. Shapiro (2001), "The Impact of Cultural Values on Job Satisfaction and Organizational Commitment in Self-Managing Work Teams: The Mediating Role of Employee Resistance," Academy of Management Journal, 44 (3), 557-69.

Kitayama, Shinobu, Batja Mesquita, and Mayumi Karasawa (2006), "Cultural Affordances and Emotional Experience: Socially Engaging and Disengaging Emotions in Japan and the United States," Journal of Personality and Social Psychology, 91 (5), 890-903.

Kogut, Bruce and Harbir Singh (1988), "The Effect of National Culture on the Choice of Entry Mode," Journal of International Business Studies, 19 (3), 411-432.

Kumar, Nirmalya, Lisa K. Scheer, and Jan-Benedict E. M. Steenkamp (1995), "The Effects of Perceived Interdependence on Dealer Attitudes," Journal of Marketing Research, 32, 348-56.

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, Don Y. and Philip L. Dawes (2005), "Guanxi, Trust, and Long-Term Orientation in Chinese Business Markets," Journal of International Marketing, 13 (2), 28-56.

Loch, Christoph H., Bernardo A. Huberman, and Suzanne Stout (2000), “Status Competition and Performance in Work Groups,” Journal of Economic Behavior & Organization, 43, 35-55.

Mitra, Debanjan and Peter N. Golder (2002), "Whose Culture Matters? Near-Market Knowledge and Its Impact on Foreign Market Entry Timing," Journal of Marketing Research, 39 (3), 350-65.


Money, Bruce R., Mary C. Gilly, and John L. Graham (1998), “Explorations of National Culture and Word-of-Mouth Referral Behavior in the Purchase of Industrial Services in the United States and Japan,” Journal of Marketing, 62 (October), 76-87.

Morgan, Robert M., and Shelby D. Hunt (1994), “The Commitment-Trust Theory of Relationship Marketing,” Journal of Marketing, 58 (July), 20-38.

Morishima, M. and T. Minami (1983), "Task Interdependence and Internal Motivation: Application of Job Characteristics Model to Collectivist Cultures," Tetsugaku, 77, 133-47.

Noesjirwan, Jennifer (1978), "A Rule-Based Analysis of Cultural Differences in Social Behaviour: Indonesia and Australia," International Journal of Psychology, 13 (4), 305.

Ozdemir, V. Emre and Kelly Hewett (2010), "The Effect of Collectivism on the Importance of Relationship Quality and Service Quality for Behavioral Intentions: A Cross-National and Cross-Contextual Analysis," Journal of International Marketing, 18 (1), 41-62.

Palmatier, Robert W., Rajiv Dant, Dhruv Grewal, and Kenneth R. Evans (2006), "Factors Influencing the Effectiveness of Relationship Marketing: A Meta-Analysis," Journal of

Marketing, 70 (3), 136-53.

———, Srinath Gopalakrishna, and Mark B. Houston (2006), "Returns on Business-to-Business Relationship Marketing Investments: Strategies for Leveraging Profits," Marketing Science, 25 (5), 477-93.

Pornpitakpan, Chanthika, and June N. Francis (2001), “The Effect of Cultural Differences, Source Expertise, and Argument Strength on Persuasion: An Experiment with Canadians and Thais,” Journal of International Consumer Marketing, 13 (1), 77-101.

Robinson, Stefanie Rosen, Caglar Irmak, and Satish Jayachandran (2012), “Choice of Cause in Cause-Related Marketing,” Journal of Marketing, 76 (July), 126-139.

Rose, Paul and Jong Han Kim (2011), "Self-Monitoring, Opinion Leadership and Opinion Seeking: A Sociomotivational Approach," Current Psychology, 30 (3), 203-14.

Roth, Martin S. (1995), "The Effects of Culture and Socioeconomics on the Performance of Global Brand Image Strategies," Journal of Marketing Research, 32 (2), 163-75.

Sambharya, Rakesh B. and Kunal Banerji (2006), "The Effect of Keiretsu Affiliation and Resource Dependencies on Supplier Firm Performance in the Japanese Automobile Industry," Management International Review, 46 (1), 7-37.

Silverblatt, Howard and Dave Guarino (2011), "S&P 500: 2010 Global Sales," in S&P Indices. New York: Standard & Poor's.


Singh, Joginder P. (1990), “Managerial Culture and Work-Related Values in India,” Organization Studies, 11, 75-101.

Steenkamp, Jan-Benedict E. M. (2001), "The Role of National Culture in International Marketing Research," International Marketing Review, 18 (1), 30.

——— (2005), "Moving Out of the U.S. Silo: A Call to Arms for Conducting International Marketing Research," Journal of Marketing, 69 (October), 6-8.

Steensma, H. Kevin, Louis Marino, K. Mark Weaver, and Pat H. Dickson (2000), “The Influence of National Culture on the Formation of Technology Alliances by Entrepreneurial Firms,” Academy of Management Journal, 43 (5), 951-973.

Sundaram, D. S., Kaushik Mitra, and Cynthia Webster (1998), "Word-of-Mouth Communications: A Motivational Analysis," Advances in Consumer Research, 25 (1), 527-31.

Swaminathan, Vanitha and Christine Moorman (2009), "Marketing Alliances, Firm Networks, and Firm Value Creation," Journal of Marketing, 73 (5), 52-69.

The Economist (2011), "The Magic of Diasporas," 400 (8760), 13.

Triandis, Harry C. (1989), "The Self and Social Behavior in Differing Cultural Contexts," Psychological Review, 96 (3), 506-20.

——— (1995), Individualism and Collectivism. Boulder, CO: Westview Press.

Ueno, Susumu, and Uma Sekaran (1992), “The Influence of Culture on Budget Control Practices in the USA and Japan: An Empirical Study,” Journal of International Business Studies, 23, 659-674.

United Nations Database (2012), “GDP and its Breakdown at Current Prices in US Dollars,” (accessed January 15, 2013), [available at http://unstats.un.org/unsd/snaama/dnllist.asp].

Wagner, John A. III (1995), “Studies of Individualism-Collectivism: Effects on Cooperation in Groups,” Academy of Management Journal, 38, 152-172.

Williams, Jerome D., Sang-Lin Han, and William J. Qualls (1998), “A Conceptual Model and Study of Cross-Cultural Business Relationships,” Journal of Business Research, 42, 135-143.

World Trade Organization, (2011), International Trade Statistics. Geneva, Switzerland: World Trade Organization

Würth-Group (2010), Annual Report of the Würth Group. Künzelsau, Germany.

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.


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


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);


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



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


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


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


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


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


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.


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


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


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)


international relationship marketing · 2020. 6. 9. · international relationship marketing ....

Documents