Word of mouth (WOM), at one time viewed as a

Gangseog Ryu & Lawrence Feick A Penny for Your Thoughts: Referral Reward Programs and Referral Likelihood Because referral reward programs reward existing customers and build the customer base, firms use them to encourage customers to make recommendations to others. The authors report on four experiments in which they find that rewards increase referral likelihood. More specifically, they find that rewards are particularly effective in increasing referral to weak ties and for weaker brands. It is also important who receives the reward. Overall, for weak ties and weaker brands, giving a reward to the provider of the recommendation is important. For strong ties and stronger brands, providing at least some of the reward to the receiver of the referral seems to be more effective. The authors discuss the implications of the results for the design of reward programs. Gangseog Ryu is Associate Professor of Marketing, College of Business Administration, Korea University (e-mail: gryu@korea.ac.kr). Lawrence Feick is Professor of Business Administration, Katz Graduate School of Business, University of Pittsburgh (e-mail: feick@katz.pitt.edu). The authors thank the three anonymous JM reviewers for their guidance, Sity Norani Binte Rohani for her help in stimuli development and data collection, and Jeff Inman and the Consumer Behavior doctoral seminar participants at the University of Pittsburgh for their many helpful comments on a prior draft of this article. The data for Studies 1 and 3 were collected while the first author was with the National University of Singapore. The SK Award, given to the first author, provided partial support for this research. To read and contribute to reader and author dialogue on JM, visit http://www.marketingpower.com/jmblog. 2007, American Marketing Association ISSN: 0022-2429 (print), 1547-7185 (electronic) 84 Word of mouth (WOM), at one time viewed as a sociological phenomenon to be observed and described, is increasingly considered a marketing tool to be managed (Rosen 2000). In initial efforts to manage WOM, marketers focused on satisfying customers (so that they would generate positive rather than negative WOM) and on targeting influential consumers, such as opinion leaders. Only recently have firms introduced formal programs that are designed to encourage existing customers to make product recommendations. In these programs, firms offer various types of rewards (e.g., vouchers, gifts, free minutes, miles) when an existing customer attracts a new customer. Such programs have significant potential to affect firms performance. For example, consider customer relationship management (CRM), recently a central focus of marketers attention (Hogan, Lemon, and Libai 2003; Rust, Lemon, and Zeithaml 2004). A core idea in CRM is that firms need to invest in retaining existing customers not just in finding new ones. Thus, a referral reward program can be a key CRM tool because in addition to its potential to attract new customers, it can improve retention by rewarding existing customers. A review of Web search results suggests that the practice of rewarded referral is widespread. Referral reward programs exist for a wide variety of goods (e.g., contact lenses [Smart View Contacts], automobiles [Hanmar Motors], pet supplies [Neo-Paws]) and services (e.g., airlines [United Airlines], mobile phone service [Cingular]). They provide rewards that can be discounts on the product or service (e.g., discounted future hotel stays [Caesar s Pocono Resort], free perfume [Perfumeoutlet.net]) or cash and gifts unrelated to the product or service category being recommended (e.g., car dealers [#1 Cochran], real estate agencies [REMAX]). Researchers expect an increasing use of such programs because of their targetability and cost effectiveness compared with more traditional promotional tools (Mummert 2000). However, there is limited research on rewarded referral. Some scholars have examined the impact of various marketing activities on WOM. For example, Bolton, Kannan, and Bramlett (2000) show that offering a loyalty program has an indirect effect on customers repatronage behavior and on their WOM. Blodgett, Hill, and Tax (1997) find that the way customers are treated has a greater impact on complaining customers negative WOM intention than does offering discounts. Apart from these indirect approaches to studying the effects of offering rewards on WOM, two recent analytical studies offer guidance for developing optimal referral reward programs. First, on the basis of the premise that customers make recommendations when they are delighted, Biyalogorsky, Gerstner, and Libai (2000) identify conditions under which a referral reward program is more effective than a price reduction in enhancing the firm s profitability. Second, Chen and Shi (2001) use game theory to demonstrate that the optimal referral reward (cash versus free products) varies according to market structure (monopoly versus oligopoly). Overall, however, there has been almost no empirical work. This article reports the results of four laboratory experiments that investigate the impact of referral reward programs on referral likelihood. Across our studies, we examine the effect of the presence or absence of a reward, reward size, and reward recipient (i.e., does the existing customer, Journal of Marketing Vol. 71 (January 2007), 84 94

does the new customer, or do both get the reward?). We also examine the impact of the relationship between the recommender and the receiver of the recommendation (i.e., strong or weak ties) and of brand strength (i.e., stronger or weaker brands). Our results have implications for the design of reward programs and for WOM theory. Conceptual Background We adopt an exchange theory framework for examining consumers responses to referral reward programs. From this perspective, the customer s decision about whether to engage in WOM depends on the perceived costs and benefits of the exchange (Frenzen and Nakamoto 1993; Gatignon and Robertson 1986; Walster, Walster, and Berscheid 1978). Research on WOM identifies several (primarily psychological or social) benefits of or motivations for transmitting WOM (Arndt 1967; Dichter 1966; Gatignon and Robertson 1986). For example, consumers may use WOM in an attempt to reduce postpurchase anxiety or dissonance by talking about their product experiences. In addition, consumers may use WOM as a way to manage others impressions of them. Finally, WOM can be a means of expressing concern about others and helping them make better choices. Providing WOM also involves costs (Gatignon and Robertson 1986). The most obvious cost is the effort and time spent communicating. In addition, because of the norm of reciprocity, the recommender may feel obliged to be a good listener in future communication. Finally, there is the risk that if the receiver is dissatisfied with a purchase that results from the recommendation, the relationship will suffer (Folkes 1984). With referral reward programs, exchange is more complex. As with natural WOM, there is the communication between the recommender and the receiver of a referral. If the referral successfully leads the receiver to purchase the product, another exchange will take place between the receiver and the company. Finally, the recommender receives a reward from the company in return for the referral. Because obtaining the reward is a result of the purchase, the receiver (new customer) provides a benefit (albeit indirectly) to the recommender (existing customer). We expect that this added exchange complexity affects how consumers perceive a referral s costs and benefits. The obvious additional benefit is the (economic) gain from the referral. On the cost side, if the receiver of the rewarded referral is dissatisfied with the product, there is increased (social) risk that the receiver might attribute his or her dissatisfaction to the recommender. Self-perception theory (Bem 1965, 1972) suggests that people try to understand the causes of their own behavior. If a referral is rewarded, consumers may perceive the referral as being driven by the reward rather than by intrinsic motivations. As a result, recommenders may feel as if they sold their recommendation, a perception unlikely to be consistent with their selfimage. For a firm to consider a referral reward program effective, the program should show results beyond what would occur naturally. In other words, the marginal gain from the reward program should be large enough to compensate for its cost. Thus, natural WOM is the appropriate comparison in the evaluation of the effects of referral reward programs. Study 1 In Study 1, we investigate whether the presence or absence of a reward and reward size influence satisfied customers referral likelihood. In addition, we examine the moderating effects of strong versus weak ties between the recommender and the receiver and of the strength of the brand offering the reward. Referral Rewards and Tie Strength Unlike more traditional sales promotion and customer loyalty programs that involve only the customer and company, referral reward programs also have implications for other consumers. Consumers consider the value of potential gains and costs for themselves and for the other consumer in rewarded referral. The nature of the recommender receiver relationship influences these perceptions of costs and benefits. Research shows that tie strength is an important property of relationships in determining how social context affects referral (Brown and Reingen 1987; Reingen and Kernan 1986). Tie strength varies from strong primary, such as spouse or close friends, to weak secondary, such as seldom-contacted acquaintances (Reingen and Kernan 1986). With strong ties, people tend to have communal relationships in which they feel general concern about the other person s welfare. They respond to the other s needs but do not expect anything in return (Clark 1984; Clark, Mills, and Powell 1986; Frenzen and Nakamoto 1993). Conversely, with weak ties, people typically have exchange relationships, driven primarily by self-interest. In such relationships, participants do not feel any special responsibility for the other person and try to maximize their own outcomes and minimize their costs. With weak ties, reciprocity is important; people expect to get back what they put in. People prefer an equitable (balanced) exchange, and if it is unbalanced, they feel distress and try to adjust. In such cases, they try to reduce what they give or increase what they receive to achieve equilibrium (Walster, Berscheid, and Walster 1973; Walster, Walster, and Berscheid 1978). Research on naturally occurring WOM finds that consumers are more likely to make a referral to a strong tie than to a weak tie (e.g., Brown and Reingen 1987; Frenzen and Nakamoto 1993), perhaps because their communal orientation toward strong ties motivates them to share the pleasure that they have received from using a product. Furthermore, people know much more about the needs and preferences of strong ties because they are in frequent contact with them (Granovetter 1973) and keep track of their needs (Clark, Mills, and Powell 1986). Greater knowledge about preferences is likely to make consumers feel more comfortable about sharing experiences and make the information more useful, especially for products from high-preferenceheterogeneity categories (Feick and Higie 1992). What changes are expected when a reward is offered for a referral? We consider strong ties. On the benefit side, a reward should have little additional impact. Consumers help Referral Reward Programs and Referral Likelihood / 85

without expecting a reward; indeed, helping is its own reward (Beach and Carter 1976; Clark, Mills, and Powell 1986). Frenzen and Nakamoto (1993) find that consumers are likely to share all types of information with strong ties (including both high- and low-value information). On the cost side, there is the potential social risk of negatively affecting a relationship if an economically driven referral does not work out. Thus, with strong ties, because the marginal benefit is small and because of potential (social) costs, we expect little impact of a reward on referral likelihood. In contrast, for weak ties, equity theory suggests that a recommender will regard a referral as a favor done for the receiver and/or the company. Thus, referrals yield inequity because an input is increased without a simultaneous increase in output (Walster, Berscheid, and Walster 1973; Walster, Walster, and Berscheid 1978). If the recommender receives a reward, the level of inequity is reduced, resulting in movement toward equilibrium. Furthermore, unless the economic value of the reward is large, it seems unlikely that a concern about being bought will be important to the recommender in interacting with a weak tie. Thus, with weak ties (in exchange relationships), we expect that consumers will be more influenced by economic motives and less concerned about the social or psychological risks of rewarded referral (Frenzen and Nakamoto 1993; Törnblom and Nilsson 1993). Thus: H 1 : The impact of offering a reward on referral likelihood depends on tie strength. The presence of a reward (compared with no reward) increases referral likelihood more for weak ties than for strong ties. Referral Rewards and Brand Strength Brand features also should moderate the effect of rewards on referral likelihood. We focus on brand strength. Following Keller s (1993) work, we conceptualize strong brands as enjoying high brand awareness and well-established brand associations. Research shows that consumers respond to stronger and weaker brands differently. For example, a given price reduction will have a greater sales impact when it is applied to a higher-quality (stronger) brand than when it is applied to a lower-quality (weaker) brand (e.g., Blattberg and Wisniewski 1989; Heath et al. 2000). We also expect brand strength effects for rewarded referral. Consumers of stronger brands feel more brand commitment than consumers of weaker brands because their choices are affected more by preferences than by budget limits (Blattberg and Wisniewski 1989). This stronger commitment gives consumers of a stronger brand more confidence in making recommendations, thus increasing (unrewarded) referral likelihood and limiting the incremental impact of a reward. Furthermore, rewarding referral by consumers of a stronger brand may yield a perception that the reward compromises their commitment to and confidence in the brand (Bem 1965, 1972). In contrast, consumers of a weaker brand are likely to have greater residual desire or lower choice confidence (Heath et al. 2000; Simonson 1992) and, thus, less WOM motivation. For these consumers, a reward may compensate for this lower residual desire and increase their choice confidence. Furthermore, the two groups may perceive the value of a reward differently. If consumers of weaker brands put more weight on price than consumers of stronger brands (Kamakura and Russell 1989), they would perceive a higher value from the (economic) reward and be more likely to be attracted by the reward program. Thus: H 2 : The impact of offering a reward on referral likelihood depends on brand strength. The presence of a reward (compared with no reward) increases referral likelihood more for weaker brands than for stronger brands. Method Participants and design. Study 1 was a 3 2 2 between-subjects factorial experiment in which we varied the reward size (no reward, smaller, larger), the brand strength (weaker, stronger), and the tie strength (strong, weak). Two hundred seventy-five undergraduate students from a major university in Singapore were randomly assigned to the experimental conditions, except for brand strength, which we manipulated by having the respondents choose either a weaker or a stronger brand. Procedure. We used portable MP3 players as the product category for the study because of the relevance of this product to the student participants. Students were first asked to imagine being in the market for an MP3 player and then were asked to pick the brand they preferred from the two alternatives (i.e., the stronger and weaker brand). To avoid the influence of prior brand beliefs, we did not use actual brand names, instead labeling the brands A and B. We manipulated brand strength in two ways. First, a brief description of reputation and quality was presented for each brand. The stronger brand was described as one of the leading brands of electronic products, recognized for its high quality and reputation, and the weaker brand was described as a relatively less-well-known player in the electronic products market, known for its reasonable quality and reputation. Second, expert ratings on several dimensions of the brand were provided, in which the quality rating and price of the stronger brand were higher (four of five stars, S$549, or approximately US$350) than those of the weaker brand (three stars, S$399). A picture and detailed product specifications were also included. After making a choice, participants were asked to imagine that they had bought, used, and been very satisfied with the brand they had chosen. Product experience details were included to reinforce their satisfaction with the brand. The referral reward manipulation stated, You are reminded that when you made the purchase, the salesperson told you that if you recommend the product to someone who then purchases the same model, the manufacturer would give you a shopping voucher of (S$50 [40], S$100 [80]), which can be redeemed at a leading local department store. We did not include this information in the no-reward condition. Note that we used 10% and 20% of the product prices for the smaller and larger rewards, respectively. The use of a relative (rather than absolute) amount to determine reward size is consistent with the principle of relativity (Heath et al. 2000). We manipulated tie strength by asking participants to identify (using initials) either one of your closest friends 86 / Journal of Marketing, January 2007

for strong ties or a casual acquaintance someone you interact with from time to time, but someone not close enough to count as a friend (e.g., a classmate you have recently met) for weak ties (Frenzen and Nakamoto 1993). Next, participants indicated their referral likelihood on a scale anchored by 0% ( certain not to tell this person ) and 100% ( certain to tell this person ). Manipulation check and covariate measures included tie strength (a four-item scale that Frenzen and Davis [1990] developed) and perceived reward size (the average of two nine-point items: a very small amount/a very large amount and very unattractive/very attractive ). Then, participants were asked whether they could name the MP3 players used in the experiment. Finally, we included a nine-item, nine-point scale of product involvement (adapted from the work of Lichtenstein, Bloch, and Black [1988]) and the six-item market maven scale (Feick and Price 1987) to control for individual differences. Results Manipulation checks. Participants perceived the value of the larger reward as significantly greater than the smaller reward (mean smaller = 5.40, mean larger = 6.17; t(164) = 3.84, p <.01). Furthermore, mean tie strength ratings differed significantly (mean strong =.86, mean weak =.59; t(247) = 12.90, p <.01). Finally, 6.2% of the participants correctly identified at least one of the brands in the experiment and thus were dropped. Referral likelihood. We analyzed referral likelihood with an analysis of covariance (ANCOVA). Participants product involvement and market maven scores were covariates, and reward size, brand strength, and tie strength were between-subjects factors. The analysis yielded a significant main effect for market maven (F(1, 236) = 8.74, p <.01; β =.03). As market maven tendency increases, referral likelihood increases. This result is consistent with previous findings that indicate that market mavens exhibit a higher level of information provision than other consumers (Feick and Price 1987). Two main effects for experimental variables were significant: tie strength (F(1, 236) = 63.49, p <.01) and reward (F(2, 236) = 22.67, p <.01). Referral likelihood was greater with strong ties (88.1%) than with weak ties (71.3%), a pattern consistent with previous studies (e.g., Frenzen and Nakamoto 1993). In addition, offering a reward significantly increased referral likelihood (no reward = 69.7%, smaller reward = 84.7%, larger reward = 84.1%). Contrasts of means revealed a significant difference between the noreward and the smaller-reward conditions (t(168) = 4.89, p <.01) and between the no-reward and the larger-reward conditions (t(161) = 4.36, p <.01). The difference between the smaller- and larger-reward conditions was not significant (t(165) =.27, p =.79). The main effect of reward was moderated by two significant two-way interactions (see Figure 1, Panels A and B). As H 1 proposed, there was a significant interaction between reward and tie strength (F(2, 236) = 22.65, p <.01). With strong ties, the presence of a reward did not affect referral likelihood (no reward = 87.2%, smaller FIGURE 1 Study 1 Results A: The Effect of Reward Size and Tie Strength on Referral Likelihood B: The Effect of Reward Size and Brand Strength on Referral Likelihood reward = 89.7%, larger reward = 87.3%; F(2, 114) =.19, p =.83). In contrast, with weak ties, offering a reward increased consumers referral likelihood (no reward = 52.6%, smaller reward = 79.8%, larger reward = 81.1%; F(2, 120) = 35.42, p <.01). As H 2 proposed, there was a significant interaction between reward and brand strength (F(2, 236) = 5.28, p <.01). Offering a reward increased referral likelihood by more than 20 percentage points for the weaker brand but by less than 10 percentage points for the stronger brand (weaker brand: no reward = 63.7%, smaller reward = 86%, larger reward = 85.9%; F(2, 118) = 20.28, p <.001; stronger brand: no reward = 75.1%, smaller reward = 83.1%, larger reward = 82.6%; F(2, 126) = 2.52, p <.10). The effect is driven by the no-reward condition in which referral likelihood for the stronger brand is significantly higher than for the weaker brand (75.1% versus 63.7%; t(81) = 2.08, p <.05). To gain insight into the mechanism underlying the effects of brand strength, we compared participants who chose the stronger (51.6%) and weaker (48.4%) brands. Participants evaluated both brands after their choice, and we computed the difference between the evaluation of the brands chosen and those not chosen. This difference was Referral Reward Programs and Referral Likelihood / 87

significantly larger for participants who chose the stronger brand than for those who chose the weaker brand (1.71 versus.53; t(248) = 6.64, p <.01). In addition, participants relative ratings of the importance of price and quality in evaluating and choosing an MP3 player differed significantly (t(247) = 9.82, p <.01). Those who chose the stronger brand gave larger weights to quality than did those who chose the weaker brand (61.2/100 versus 46.5/100, respectively). Discussion Compared with offering no reward, offering a reward increased the likelihood of referral. Thus, the results suggest that referral reward programs can be effective. However, at least with the reward sizes we used, size does not matter. An increase in reward size did not increase referral likelihood. There are several possible explanations for this result. There may simply be a ceiling effect; that is, although the participants perceived the reward sizes as significantly different (based on the manipulation check), the smaller reward may have been large enough to generate the same effect as the larger reward. In addition, and more substantively, it may be that increases in reward size (which increase benefits of referral) also increase psychological and social costs by creating feelings of guilt about the inequity of the exchange (Austin and Walster 1974; Smith, Bolton, and Wagner 1999). Weaker brands benefited more from offering a reward than did stronger brands. This result may be due to consumers of weaker brands having a lower level of commitment to or confidence in their brand and price being more important to them. Our results suggest the usefulness of referral reward programs for weaker brands. Finally, consumers behaved differently when a reward was offered only with weak ties. With strong ties, there was no increase in referral likelihood with a reward. This point is critical in thinking about the marginal impact of referral reward programs. Programs need to be carefully crafted to achieve results greater than those that would have occurred in due course through naturally occurring WOM. Study 2 Study 1 results are consistent with exchange theory, but we designed Study 2 to gain greater insight into the mechanism underlying the effects. With strong ties, we expect consumers to place greater weight on the sociopsychological costs and benefits of making a referral. If they are rewarded, they will produce thoughts related to these costs and benefits. With weak ties, we expect consumers to give less weight to (and produce fewer thoughts about) sociopsychological costs and benefits but to give more consideration to the economic benefits of the interaction. Method Study 2 was a 2 2 between-subjects design in which we manipulated the presence of a reward (no, small) and tie strength (strong, weak). Eighty-one Singaporean students were randomly assigned to the experimental conditions. Study 2 differed from Study 1 in that participants did not make a product choice but rather were asked to imagine that they had bought an MP3 player and were very satisfied with it. Furthermore, we provided a few detailed experiences with the product to simulate usage. In addition to Study 1 measures, in Study 2, we collected written thoughts about making a referral after collecting referral likelihood. We also measured perceptions of a referral s benefits and costs, using items developed from existing WOM research (Arndt 1967; Dichter 1966; Gatignon and Robertson 1986): For social benefits (α =.89), we measured others perceptions of showing genuine concern, helping others make the best choice, and developing (maintaining) a good relationship with others, and for psychological costs (r =.86), we measured feeling of being selfish and feeling of being motivated by money. Each item was evaluated on an 11-point ( 5 to +5) scale, indicating how good or bad the consequence would be. More extreme ratings indicate higher weights. Results Perception ratings. Referral likelihood results replicate Study 1, and thus we do not describe them. To examine the mechanism, we ran 2 2 analyses of variance on the perceived social and psychological costs and benefits of referral. Tie strength (F(1, 77) = 20.4, p <.01) and reward (F(1, 77) = 4.60, p <.05) had significant main effects on social benefits. There are greater perceived social benefits with referral to a strong (3.14) than to a weak (1.59) tie and for no reward than for a reward (no reward = 2.74, reward = 1.95). The interaction between reward and tie strength was significant (F(1, 77) = 3.86, p <.05). With strong ties, there was little difference in the evaluation of social benefits, regardless of whether a reward was offered (no reward = 3.17, reward = 3.11; t(39) =.148, p >.85). With weak ties, less social benefit was perceived with a reward (.90) than without (2.30; t(40) = 2.61, p <.01). Tie strength yielded a significant main effect on psychological costs (F(1, 77) = 11.70, p <.01). Perceived costs were greater for referral to a strong ( 3.35) than to a weak ( 1.73) tie. A reward also resulted in a significant main effect (F(1, 77) = 19.66, p <.01). Participants evaluated perceived costs less negatively when there was a reward than when there was no reward (no reward = 3.56, reward = 1.48). In addition, the interaction between reward and tie strength was significant (F(1, 77) = 4.35, p <.05). There was a greater difference between no reward and reward with weak ties than with strong ties (weak tie: no reward = 3.25, reward =.29; strong tie: no reward = 3.86, reward = 2.79). Thought listings. We developed three categories of thought types: social benefits, social costs, and psychological costs. Two independent judges who were blind to the study s purpose coded the data. Agreement between the judges was high (92.5%); disagreements were resolved by discussion. We ran separate 2 2 analyses of variance on the number of thoughts within each of the three categories. For social benefits, there was only a significant main effect of tie strength (F(1, 77) = 14.57, p <.01). There were more thoughts about social benefits of a referral for strong ties 88 / Journal of Marketing, January 2007

(1.58) than for weak ties (.68). For social costs, the main effects of reward and tie strength were both significant (F(1, 77) = 5.60 and 7.37, p <.05 and p <.01, respectively). There were more thoughts about social costs with a reward (.55) than without (.24) and when the referral was to a strong (.58) than to a weak (.22) tie. Moreover, the interaction between reward and tie strength was significant (F(1, 77) = 4.36, p <.05). With weak ties, participants showed little difference in their thoughts about social costs, regardless of whether a reward was offered (no reward =.20, reward =.24; t(40) =.25, p =.80). With strong ties, however, there were more thoughts about social costs with a reward (.89) than without (.29; t(39) = 2.65, p <.01). For psychological costs, there was a significant main effect of reward and tie strength (F(1, 77) = 52.04 and 4.31, p <.01 and p <.05, respectively). Participants generated more thoughts about the costs of making a referral when a reward was offered (.73) than when it was not (.00) and to strong (.45) than to weak (.29) ties. In addition, the interaction between reward and tie strength was significant (F(1, 77) = 4.31, p <.05). A reward yielded a greater increase in thoughts about psychological costs with strong ties than with weak ties (weak tie: no reward =.00, reward =.52; strong tie: no reward =.00, reward =.95). Discussion Study 2 provides direct support for our exchange theory argument. In general, the scales we used to measure costs and benefits and the thought listings were consistent and suggest that consumers evaluate the social and psychological costs and benefits of a referral differently when a reward is involved. The potential social benefits of a referral are perceived as lower and the social and psychological costs are perceived as higher when a reward is offered than when one is not. Tie strength also matters. Consumers perceive greater potential social and psychological costs and benefits when the referral is to strong ties in the presence of rewards. In contrast, consumers tend to discount the importance of social and psychological costs and benefits and are more likely to recognize economic benefits when the referral is to weak ties. Study 3 Studies 1 and 2 suggest that rewards matter and that their impact depends on tie strength and brand strength. What cannot be determined from these studies is whether it matters to whom the reward is given. Referral Reward Schemes Sales promotion benefits typically are provided only to the customer who makes use of the promotion. However, in customer referral programs, because there is an existing customer who makes a recommendation and a new customer who receives the referral, there could be three reward schemes. The first is Reward Me, in which the recommender (the existing customer) receives the reward. This scheme is the focus in Studies 1 and 2 and, seemingly, the most typical in practice. In addition, however, there could be a scheme called Reward You, in which the receiver of the recommendation (the new customer) receives the reward. Finally, there could be a blend of the two scenarios, or Reward Both. Costs and benefits vary depending on the scheme. The personal economic benefit that accrues to the existing customer is affected. He or she receives the full benefit for Reward Me, partial benefit for Reward Both, and nothing for Reward You, but the potential social and psychological costs decrease in the same order. The offsetting of economic gains by psychological/social costs makes it difficult to predict a main effect of reward scheme. We propose tie strength as a moderator. We expect that consumers will weight benefits and costs differently and will be governed by different rules of exchange depending on the receiver of the recommendation. In recommending to weak ties, consumers are motivated more by self-interest and are less concerned about psychosocial dimensions. Thus, with weak ties, we expect the lowest referral likelihood for Reward You. Our weak ties prediction is also based on an equity argument; specifically, people expect to receive resources (e.g., rewards) in exchange for resources (e.g., referral) they provide (Walster, Berscheid, and Walster 1973; Walster, Walster, and Berscheid 1978). With Reward You, inequity exists because the consumer receives nothing in return for a referral. Conversely, with Reward Me, the recommender is rewarded, and balance is achieved, increasing referral likelihood. Reward Both should be in between. With strong ties, consumers attempt to maximize mutual benefits for the relationship as a whole, regardless of which member receives the greater individual reward (Kelly 1979; Kelly and Thibaut 1978). Furthermore, consumers are likely to help strong ties without expecting any economic return and enjoy psychological and/or social benefits by helping a strong tie obtain a reward. This logic implies an ordering for referral likelihood that is the opposite of that for weak ties. Thus: H 3 : The impact of reward allocation scheme on referral likelihood depends on tie strength. With weak ties, consumers are most likely to make a referral in the Reward Me condition, followed by Reward Both and Reward You. With strong ties, consumers are most likely to make a referral in the Reward You condition, followed by Reward Both and Reward Me. Method One hundred thirty-six undergraduate students from a Singaporean university participated in a 3 2 between-subjects factorial experiment in which we varied the scheme of the reward distribution (Reward Me, Reward You, Reward Both) and tie strength (strong, weak). The experimental procedure of Study 3 was identical to Study 2 except for the reward scheme. We manipulated scheme by varying who received the referral reward (a shopping voucher): the recommender, the receiver of the recommendation, or both. Results Manipulation checks. Manipulations of reward scheme and tie strength were successful. Participants perceived reward value similarly across reward schemes (Reward Me = 6.29, Reward You = 5.95, Reward Both = 5.83; Referral Reward Programs and Referral Likelihood / 89

F(2, 133) = 1.84, p =.16), and tie strength was significantly greater with strong ties (.85) than with weak ties (.55; t(135) = 12.21, p <.01). Referral likelihood. We ran an ANCOVA on referral likelihood with reward scheme and tie strength as betweensubjects factors and product involvement and market maven as covariates. As in Study 1, the market maven covariate was significant (F(1, 128) = 8.86, p <.01), and there was a significant main effect of tie strength (strong ties = 86.5%, weak ties = 68.7%; F(1, 128) = 42.53, p <.01). As H 3 predicted, there was a significant interaction between reward scheme and tie strength (F(2, 128) = 4.54, p <.01; see Figure 2). With strong ties, differences among reward schemes were not significant, though they were directionally consistent with our prediction (F(2, 62) =.98, p =.38; Reward You = 90.1%, Reward Both = 86.7%, and Reward Me = 82.8%). Conversely, with weak ties, differences were significant (F(2, 64) = 4.37, p <.05) and in the predicted order (Reward You = 58.3%, Reward Both = 70.4%, and Reward Me 75.8%). Reward You is marginally lower than Reward Both (t(42) = 1.90, p =.06) and is lower than Reward Me (t(44) = 3.15, p <.01), but the latter two are not significantly different from each other (t(46) = 1.21, p =.23). Discussion Study 3 illustrates the importance of considering the target of the reward when designing referral reward programs. The reward s distribution between the existing and the new customer had different effects on consumers likelihood of making a referral, depending on the relationship between the recommender and the receiver of the recommendation. Study 3 showed that varying the recipient of the reward has little effect on referral likelihood when the recipient is a strong tie, though the direction favors rewarding the new customer (or both). With weak ties, a reward for the recommender (existing customer) seemed to work best. The results are consistent with the framework we proposed; that is, psychological and social benefits and costs are more important with strong ties, and economic benefits and costs are more important with weak ties. FIGURE 2 Study 3: The Effect of Reward Scheme and Tie Strength on Referral Likelihood Study 4 In Studies 1 3, we used student participants who reacted to a scenario about MP3 players. We designed Study 4 to examine the generalizability of these findings using adult consumers actual experiences with mobile phone service. Method Design. Study 4 was a 3 2 2 between-subjects factorial experiment in which we varied reward scheme (No Reward, Reward Me, Reward Both), brand strength (weaker, stronger), and tie strength (weak, strong). Participants were randomly assigned to the experimental conditions, except in the case of brand strength, which we measured. Participants. Two hundred ninety-eight adult consumers were recruited from executive programs at a South Korean university. The participants, 61% of whom were men, were employed and had a median age of 36 at the time of the study. Stimuli and manipulations. We chose mobile phone service because it differs in important ways from MP3 players. It is a service (not a good), it has several intangible features, and some of the critical attributes are based on experience (not search) characteristics. In addition, high consumer involvement and long market availability are likely to make WOM important, influential, and prevalent for mobile phones. Finally, mobile service is familiar and relevant to our respondents and is not gender specific. In Study 4, participants responded on the basis of their own experience with their current mobile phone service. In Korea, there are three major mobile service providers, and at the time of the study, the leading brand had a 53% market share, the longest presence in the market, and a reputation for high quality and high price. The two follower brands had 31.5% and 15.5% market shares, respectively, with a reasonable or low quality and price image. Customers of the leading brand were assigned to the stronger brand condition, and customers of the two follower brands were assigned to the weaker brand condition. We use manipulation checks to confirm our expectations about brand perceptions. To manipulate reward scheme, we included No Reward, Reward Me, and Reward Both conditions. We excluded the Reward You condition to simplify the study because it is much less common in practice. The reward was 60,000 Korean won in free calls (about $50 at the time of the study) in the Reward Me condition or 30,000 won in free calls each in the Reward Both condition. We manipulated tie strength as previously. Procedure. After answering basic questions about their mobile phone service, participants responded to the tie strength manipulation. Next, they were told that their current mobile phone service provider was beginning a referral reward program. This part was not presented in the No Reward condition. Then, they read a mobile phone related WOM scenario in which they were asked to imagine discovering that the individual described previously was considering a new or changed mobile phone service. 90 / Journal of Marketing, January 2007

Measures. Because participants had real brand experience, we needed a referral likelihood measure that included valence and extremity. We used two nine-point items ( strongly recommend that they not subscribe to the service/strongly recommend that they subscribe to the service and sure to tell the friend [acquaintance] not to join the service/sure to tell the friend [acquaintance] to join the service ) to measure referral likelihood (Blodgett, Hill, and Tax 1997). We used the same manipulation checks for tie strength and perceived value of rewards as in Studies 1 and 3. We also measured (on seven-point scales) perceived reputation, quality, and price of the participants brands. Again, we included product involvement and market maven scales as covariates. In addition, we included three seven-point items that measured brand satisfaction ( dissatisfied/satisfied, displeased/pleased, and unfavorable/favorable ; Crosby and Stephens 1987). Results Manipulation checks. Of the participants, 56% were customers of the leading brand, and 44% were customers of one or the other of the followers. Perceived brand reputation, quality, and price of the stronger brand were significantly higher than those of the weaker brands (reputation: 5.18 versus 4.79; t(292) = 2.25, p <.05; quality: 5.09 versus 4.35; t(292) = 5.47, p <.01; price: 3.92 versus 3.43; t(292) = 3.40, p <.01). Mean tie strength ratings also differed significantly (.88 for strong ties and.66 for weak ties; t(292) = 11.45, p <.01). Participants perceived the reward as being of the same value in the two reward conditions (Reward Me = 5.01, Reward Both = 5.18; t(197) =.62, p >.50). Referral likelihood. The two items measuring referral likelihood were highly correlated (r =.93), and we averaged them. We analyzed referral likelihood with an ANCOVA. Participants product involvement, market maven, and satisfaction scores were covariates, and reward scheme, brand strength, and tie strength were between-subject factors. The analysis yielded a significant main effect for all three covariates (F(1, 275) = 10.01 to 14.85, all ps <.01). Increases in market maven (β =.27), involvement (β =.27), and satisfaction (β =.18) yielded increases in referral likelihood. Main effects for tie strength (F(1, 275) = 16.77, p <.01) and reward scheme (F(2, 275) = 10.66, p <.01) were significant. Again, there was greater referral likelihood with strong ties (6.37) than with weak ties (5.67). In addition, referral likelihood was greatest when both customers were rewarded and lowest when neither was (Reward Both = 6.51, Reward Me = 6.12, and No Reward = 5.43). The differences between No Reward and Reward Me (t(195) = 3.08, p <.01) and between No Reward and Reward Both (t(195) = 4.37, p <.01) were significant, but the difference between Reward Me and Reward Both was not. There was a significant interaction between reward scheme and tie strength (F(2, 275) = 5.19, p <.01; see Figure 3). In the strong tie condition, referral likelihood for Reward Both (6.79) was marginally greater than Reward Me (6.17; t(103) = 1.89, p =.06) and greater than No Reward (6.13; t(101) = 2.49, p <.05). Reward Me and No Reward were not different from each other (t(100) =.82, p =.42). Conversely, with weak ties, referral likelihood was greater for both Reward Me (6.08) and Reward Both (6.19) than for No Reward (4.72; t(93) = 3.66, p <.01; t(92) = 3.80, p <.01; respectively). The difference between Reward Me and Reward Both was not significant. In addition, the interaction between reward scheme and brand strength was significant (F(2, 275) = 3.35, p <.05). For the stronger brand, referral likelihood was greater for Reward Both (6.90) than for No Reward (5.80; t(107) = 3.90, p <.01). Reward Me (5.90) was not different from No Reward (t(109) =.83, p =.41), but it was different from Reward Both (t(114) = 3.32, p <.01). For the weaker brands, referral likelihood was greater for both Reward Me (6.41) and Reward Both (6.02) than for No Reward (5.01; t(84) = 3.55, p <.01; t(86) = 2.37, p <.05; respectively). The difference between Reward Me and Reward Both was not significant (t(84) = 1.08, p =.28). Discussion Study 4 replicated the moderating effects of both tie strength and brand strength on referral likelihood that we FIGURE 3 Study 4 Results A: The Effect of Reward Scheme and Tie Strength on Referral Likelihood B: The Effect of Reward Scheme and Brand Strength on Referral Likelihood Referral Reward Programs and Referral Likelihood / 91

found in Studies 1 and 2. A reward offered to an existing customer who makes a referral (i.e., Reward Me) increased referral likelihood to weak ties but not to strong ties (H 1 ). We also found that referral likelihood was greater when the reward was offered by a weaker brand (H 2 ). Furthermore, Study 4 results were similar to those of Study 3 for the interaction of tie strength with reward scheme. There was little difference between Reward Both and Reward Me with weak ties. With strong ties, referral likelihood was greater with Reward Both than with Reward Me (H 3 ). In Study 4, we also found an interaction between brand strength and scheme. For the stronger brand, Reward Both performed significantly better than Reward Me, whereas for the weaker brand, Reward Me fared slightly (albeit not significantly) better than Reward Both. This result has direct implications for the design of reward programs. Furthermore, this interaction is similar to the one between tie strength and scheme, perhaps for similar reasons. It is possible that for consumers of a stronger brand, Reward Me induces negative self-perceptions because of their high level of commitment to the brand and strong intrinsic motivation for referral. Conversely, Reward Both may reduce such psychological costs. In addition, the incremental economic gain of Reward Me over Reward Both is likely to be perceived as less important by consumers of a stronger brand, because they tend to be less price sensitive. General Discussion Contributions to Theory This article makes several contributions to the literature on WOM and exchange theory. First and at the most basic level, our work broadens the scope of exchange theory from a focus on exchange between two parties (for a discussion of types of exchange, see Ekeh 1974) to the examination of a more complex relationship among an existing customer, a new customer, and a brand. Furthermore, although exchange theory has been used to examine a wide range of behaviors, scholars have rarely approached WOM from this perspective (an exception is Gatignon and Robertson s [1986] conceptual study). We believe that our findings show the utility of applying exchange theory to understanding WOM. In the equity view of exchange, people prefer an equitable or balanced exchange, and in the presence of an inequitable or unbalanced exchange, they feel distress and try to remedy the situation by either reducing their input or increasing their output to achieve equilibrium (Walster, Berscheid, and Walster 1973; Walster, Walster, and Berscheid 1978). Our finding that rewards increase people s referral likelihood supports the exchange theory explanation. That is, making a referral without any extrinsic reward may create feelings of inequity for a customer; the referral is an unreciprocated favor done for the other consumer and the company. In this framework, rewards for referral work because they reduce the level of inequity and create movement toward equilibrium. The lack of difference in referral likelihood between smaller and larger rewards can be interpreted in the same light; that is, the larger reward may have been perceived as too much compensation for a referral (Austin and Walster 1974; Smith, Bolton, and Wagner 1999). We expected that equity concerns would dominate in casual relationships but not in close relationships. In close relationships, people respond to the other person s needs, and we linked our prediction for these relationships to the concept of strong ties (Clark 1984; Clark, Mills, and Powell 1986; Granovetter 1973). The prediction for close relationships was supported; the presence or amount of reward did not affect referral likelihood. Our research also increases the understanding of the operation of norms or rules of exchange by examining how reward allocation influences referral likelihood. Because the recommender receives the full economic benefit with Reward Me, partial benefit for Reward Both, and nothing for Reward You, the level of equity in exchange is in the same order (i.e., the greatest inequity is with Reward You). For weak ties, referral likelihood is directly linked to the amount of equity. For strong ties, in which equity should not matter, we found that the link between equity and referral likelihood was broken. Implications for Managers In general, our results show that offering a reward increases referral likelihood but that there was no difference in effect between smaller and larger rewards. These results suggest that firms need to calibrate reward size carefully by computing the revenue impact of the size of a reward on marginal referral likelihood and then comparing that with the cost of alternative reward programs. Studies 1 and 2 found that with strong ties, rewarding the existing customer (Reward Me) did not increase referral likelihood. For marketing managers, the results create a challenge. Referral reward programs tend to target strong ties explicitly (e.g., cell phone family-and-friends programs) or end up with strong ties (because people interact most frequently with strong ties, these ties are more likely to receive recommendations). A solution may be the allocation scheme. The results of Studies 3 and 4 suggest that rewarding either the new customer or both the new and the existing customer can increase referral likelihood with strong ties (though not by much). In addition, our study examined only referral likelihood. Rewards may have other effects on strong ties; perhaps they serve as a reminder to talk about the brand, even to friends. Conversely, rewards are important for increasing referral likelihood to weak ties. Frenzen and Nakamoto (1993) find that weak ties are not as effective as strong ties in the flow of certain types of information, though they play a critical role in bridging the gap between different groups (Granovetter 1973). Although our results show that information transmission through weak ties can be improved with incentives, the managerial issue is how to devise programs that target weak ties. The first referrals from a customer will probably be family or close friends for whom the recommendation is likely to have occurred anyway. It is probably subsequent referrals, presumably to weaker ties, that need encouragement. An option would be to increase the reward as the number of referrals increases. This segmentation approach would pay the least for referrals that are most likely to occur naturally (i.e., strong ties) and the most for referrals that are least likely to occur naturally (i.e., weak ties). 92 / Journal of Marketing, January 2007

Furthermore, the results in Studies 3 and 4 show that with weak ties, the recommender needs to receive something in return for the recommendation. The reward scheme could be calibrated to reflect this result by tilting the payoff toward the recommender for the subsequent referrals. Our results in Study 4 support this notion; the referral levels with strong ties drop off as the reward switches from Reward Both to Reward Me. Thus, tilting the rewards toward the recommender should naturally switch the emphasis to weak ties. In Study 1, we also found that the impact of reward programs on referral likelihood varied by brand strength. The increase in referral likelihood with a reward compared with no reward was much greater for the consumers of the weaker brand than for the consumers of the stronger brand. These results imply that referral reward programs may be particularly important for brands that are perceived as weaker. Even if the focus is on increasing brand strength in the long run, in the short run, weaker brands can use a reward program to increase referrals and, perhaps, product trial. As we noted in Study 4, our results provide managers with guidance in the choice of scheme by brand strength; specifically, they should use Reward Me for weaker brands and Reward Both for stronger brands. Limitations and Further Research We concentrated on the recommender s referral likelihood, but for a referral program to be effective, there must be referrals combined with receiver receptivity. Receivers may form different perceptions of the recommender and evaluate the brand differently if a referral arises from a reward program rather than from naturally occurring WOM (for a related idea, see Wiener and Mowen 1986). Thus, further research should more explicitly focus on the dyad, examining reward program conditions under which both referral likelihood and receiver receptivity are high. In addition, because it is possible that referral likelihood does not always lead to actual referrals (Mittal and Kamakura 2001), further research should collect behavioral data to complement and validate our findings. Kivetz and Simonson (2002) show that as consumers invest more effort to obtain a reward in a frequency program, their preference moves more toward luxury rewards. This result may have implications for ours. If referral requires relatively high levels of recommender effort, our use of more utilitarian/functional rewards might have underestimated the potential effects of referral programs. It seems worthwhile to consider different types of rewards in further research. In general, communicating an opinion makes the communicator s attitude more extreme, even when the opinion is not the communicator s own (Higgins and Rholes 1978). In addition, self-perception theory argues that a behavior induced by or associated with a large extrinsic incentive is likely to lead to overjustification and thus affect the person s attitudes negatively (Bem 1972; Festinger 1957). The results of this work indicate that though engaging in natural WOM may reinforce recommenders satisfaction with the brand, making rewarded referrals may undermine it. In examining rewarded referral, further research should examine other downstream variables (e.g., brand attitude, satisfaction, brand loyalty) in the recommender. Our research designs assumed that consumers learn about the referral reward program after product purchase. However, consumers can also learn about such programs before purchase. If so, the program could affect brand choice positively if it is perceived as an added value of the brand. Offering a reward might also activate persuasion knowledge for some consumers, leading them to make negative inferences about the firm s motives and perhaps leading them to less favorable responses toward the brand (Freistad and Wright 1994). Further research should examine the impact of pre- versus postpurchase knowledge of the reward program. Finally, the role of cultural differences should be considered. All our participants were from Asia. Asians are more likely to have an interdependent self-construal, whereas Westerners are more likely to be independent (Aaker and Lee 2001). Because self-construal affects a person s assessment of the importance of the self versus the group, the (presumed) interdependent self of our participants may have exerted systematic effects on their referral likelihood in interacting with strong versus weak ties. There are two possible effects. 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