The advent of the Internet has resulted in considerable shift in the asymmetrical informational relationship which existed previously between consumers and marketers (Urban 2005). Electronic word-of-mouth (eWOM)—any positive or negative statement made by potential, actual, or former customers about a product or company, which is made available to a multitude of people and institutions via the Internet (Hennig-Thurau et al. 2004)—provides a good illustration of the results of such structural shifts in the communication environment. By creating and distributing eWOM, consumers are now playing a major role in generating marketing information and can no longer be considered passive users of marketer-provided information (Berthon et al. 2008). In fact, the unique characteristics of the Internet as a media platform may expedite the motivational process of eWOM generation and encourage people to disseminate the kind of information that does not travel very well in traditional WOM (tWOM) contexts.

Although leading marketing scholars (Varadarajan and Yadav 2009) have emphasized the importance of understanding both generation and consumption of eWOM, majority of the studies have focused only on the consumption of consumer-generated information (Duan et al. 2008; Trusov et al. 2009). Furthermore, a handful of studies examining the generation of eWOM have limited their scope to motivational factors embedded in individual consumers such as self-enhancement or vengeance (e.g., Hennig-Thurau et al. 2004; Cheema and Kaikati 2010).

Also, relatively little attention has been paid to the influence of contextual factors in influencing consumer motivation to post eWOM. Extant research has asserted that consumption and communication contexts also play an important role in a consumer's motivational process (e.g., Albarracin et al. 2003), and it is quite plausible that contextual or environmental factors interact with individual factors to motivate e-WOM generation. Our basic premise is that online communication environments facilitate the influence of various motivational forces and generate eWOM patterns seemingly different from tWOM.

The purpose of this research is to enhance our understanding of the process of eWOM generation by investigating how two motivational factors, one internal and the other external to the consumer, interact with service consumption experience to influence consumers' intentions to post reviews in new media platforms. The internal motivational factor is regulatory focus, i.e., whether a person is promotion or prevention focused, and the external motivating factor is collective dissonance, a condition triggered by existing eWOM contents in a communication environment. To develop our hypotheses we focus on: (1) congruence between consumers' regulatory focus and service experience (H1 and H2 tested in studies 1A and 1B) and (2) inconsistency between the content of existing eWOM (i.e., collective dissonance) and the service experience (H3 tested in study 2).

1 tWOM, eWOM, and regulatory focus

tWOM communications involve face-to-face sharing of experiences about a product or a service with close others (e.g., Richins 1984). In such instances, consumers experience not only social benefits (e.g., improving social status when others accept the information) but also costs (e.g., the risk of providing inappropriate information) from sharing information (Cheema and Kaikati 2010). Because consumers usually evaluate negative information as more informative than positive information (Herr et al. 1991), the source of tWOM may enjoy higher benefits and lower costs when they provide negative information.

With the advent of the Internet, a less personal but more ubiquitous form of WOM, viz. eWOM consumer reviews, has come into vogue (Sen and Lerman 2007). In eWOM context, however, the importance of social benefits and costs diminishes because the relationship between the source and the receiver(s) is relatively weak (Chatterjee 2001). Consequently, the social motivational forces may not be strong enough to eclipse more personal motivation forces (e.g., a consumer's regulatory focus). We propose the absence of those social factors in online communication platforms will allow the effect of personal motivation to be more prominent for eWOM than tWOM and test our propositions using regulatory congruence hypotheses (Aaker and Lee 2001).

Regulatory focus theory (Higgins 1997) suggests that people strive to achieve their goals through two separate modes of the self-regulatory system—promotion or prevention focus. When people focus on their “ideal” goals (e.g., dreams, aspirations), they develop a promotion focus and rely on eagerness behavioral strategies to move closer to positive end states. On the other hand, when people focus on their “ought” goals (e.g., obligations, responsibilities), they develop a prevention focus and rely on vigilance strategies to stay away from negative end states.

Prior research has shown that the congruence between consumers' regulatory focus and the valence of marketing information (i.e., positive-promotion and negative-prevention) can heighten their motivational state and generate positivity biases in evaluating the presented information (Zhang et al. 2010). Following the same line of reasoning, we propose that the consistency between service experience (satisfactory vs. unsatisfactory) and regulatory focus will motivate consumers to post eWOM describing their own experiences.

Consumers with promotion focus prefer behaviors that can generate positive outcomes. Thus, we posit that promotion-focused consumers would exhibit higher intentions to post eWOM when they experience a positive service. Conversely, since consumers with a prevention focus prefer behaviors that help avoid negative outcomes, they might disseminate negative consumption experiences through eWOM so that others can avoid the same negative experience. Therefore, we hypothesize:

  1. H1

    Promotion-focused consumers will have greater intentions to generate eWOM when they have positive compared to negative service experiences.

  2. H2

    Prevention-focused consumers will have greater intentions to generate eWOM when they have negative compared to positive service experiences.

Finally, while not offering a formal hypothesis, we expect to find “the negativity effect”—i.e., the psychological phenomenon that people tend to attach greater weight to negative information (Block and Keller 1995)—for tWOM. Specifically, consistent with prior research, we expect consumers with negative service experience to display higher intention to generate tWOM than consumers with positive experience.

2 Study 1A

2.1 Design

We tested H1 and H2 using a 2 (regulatory focus: promotion vs. prevention) × 2 (consumption experience: negative vs. positive) between-subject design. Following Molden and Higgins's (2004) approach, we manipulated regulatory focus by asking participants to write essays about hopes and ideals for the promotion manipulation and about duties and responsibilities for the prevention manipulation. We used two promotion items and two prevention items (Lockwood et al. 2002) to examine the effectiveness of the regulatory focus manipulation. Participants who wrote essays on hopes and ideals scored higher on the promotion scale (M = 5.16) than participants who wrote essays on duties and responsibilities (M = 4.44, t(71) = 3.11, p < .01). In contrast, participants who wrote essays on duties and responsibilities scored higher (M = 5.50) on the prevention scale than participants who wrote essays on hopes and ideals (M = 4.54, t(71) = 5.98, p < .01). We manipulated consumption experience by providing the following scenarios:

  • Positive experience

    Recently, you attended your friend's birthday party held in ABC restaurant. The restaurant has a nice atmosphere, and your waitress was very kind and nice enough to recommend awesome dishes. The food was very fresh and delicious. You have decided to visit this restaurant in the near future.

  • Negative experience

    Recently, you attended your friend's birthday party held in ABC restaurant. Although the restaurant was not crowded, you were seated after 10 min. Your waitress was not kind and did not know about the items in the menu. The food was served 30 min later and was not fresh at all. You have decided not to visit this restaurant again.

A pretest (N = 39) ensured that the consumption experience manipulation worked as intended. Participants assigned to the positive condition perceived the experience as more positive (M = 5.79) than those assigned to the negative condition (M = 1.55, t(37) = 11.15, p < .05).

2.2 Procedure

Undergraduate students (N = 73) from a mid-sized university participated in the study for class credit. Some 60.3 % were males, and the average age was 22 years.

First, we implemented the regulatory focus manipulation, where the writing task was described as part of a “separate” study. Upon completing their writings, participants were introduced to the “second” study by another researcher as follows: “ABC restaurant is a family restaurant serving casual lunch and dinner dishes such as steak, seafood, and pasta. ABC restaurant plans to launch its branch near our University next year, and the company wants to know more about potential customers like you.”

Participants next read the negative or positive scenario; following which, they were asked to visit a community website where they could write their opinions and read reviews of other customers who had already visited the restaurant. Four reviews (two positive and two negative) were already posted on the community site, and the contents of the reviews were all relevant for restaurant evaluation. After the participants read the reviews and browsed the website, we collected the dependent measure—intentions to post eWOM (α = .92), anchored by seven-point unlikely/likely, nonexistent/existent, and improbable/probable (Szymanski 2001) scales. For tWOM, participants responded to the same scales in response to their intentions to personally share their opinions with close others (tWOM, α = .96).

3 Results

Multivariate analysis of variance (MANOVA) on eWOM and tWOM produced a main effect of service experience (Wilks' lambda = .918, F (2, 68) = 3.020, p < .07) and an interaction effect (Wilks' lambda = .931, F (2, 68) = 2.519, p < .09). Regulatory focus did not show a significant main effect (Wilks' lambda = .972, F (2, 68) = .970, p > .10). These results reflect that eWOM and tWOM are likely to be differentially affected by regulatory focus and service experience. To identify the source of these effects and better understand the pattern of the interaction effect for eWOM and tWOM separately, we examined the univariate results for each dependent variable.

The univariate results indicate a significant interaction effect (F (1, 69) = 4.88, p < .05) on intentions to post eWOM. When the consumers were promotion focused (H1), they did not differ in terms of intent to post eWOM regardless of the nature of their consumption experience (M positive = 3.67, M negative = 3.53; t(33) = .24, p > .05) (see Fig. 1). Whereas, when consumers were prevention focused (H2), they had a greater intent post eWOM when the consumption experience was negative (M negative = 4.94, M positive = 3.35; t(36) = 2.95, p < .05). These results support a congruency effect for prevention-focused consumers (H2), but not for promotion-focused consumers (H1).

Fig. 1
figure 1

Service experience and regulatory focus (study 1A)

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For tWOM, the univariate results revealed a significant main effect of service experience (F (1, 69) = 6.57, p < .05), whereas the main effect of regulatory focus (F (1, 69) = .12, p > .10) and the interaction between regulatory focus and service experience (F (1, 69) = 1.55, p > .10) were not significant. Participants showed greater intentions to generate tWOM when they underwent negative service experiences (M negative = 5.75) than positive ones (M positive = 5.13). Overall, the univariate results from study 1A show that generation of eWOM was enhanced by regulatory fit, whereas tWOM was dominated by the “negativity effect” which overshadowed the motivational influence from the fit.

Interestingly, study 1A only showed a partial support for our predictions for eWOM—i.e., only the fit between prevention focus and negative experience generating a significant result. This asymmetrical effect of regulatory fit can be explained by Aaker and Lee's (2001) work on self-construal and regulatory focus. Aaker and Lee found that when a consumer sees herself as a part of a group (i.e., interdependent self-construal), she is more likely to activate prevention focus emphasizing duties and responsibilities. On the other hand, when a consumer sees herself as autonomous (i.e., independent self-construal), she is more likely to activate promotion focus highlighting hopes and ideals.

It is very likely that the collective nature of our setting for study 1A (i.e., posting experiences at a friend birthday party on an online community) made interdependent self-construal more salient and weakened the effect from the fit between promotion focus and positive experience. In study 1B, we show that change in communication context from a collective online community to an individual setting can influence how promotion fit impacts eWOM intentions.

4 Study 1B

4.1 Design and procedure

We devised a 2 (regulatory focus: promotion vs. prevention) × 2 (consumption experience: negative vs. positive) experiment using a Facebook-like personal blog as communication context. Seventy-six undergraduate business students participated in the study for course credit. Fifty-five percent of the participants were males, and the average age was 22.3 years.

We modified scenarios and settings used in study 1A to emphasize individualistic aspects in service experience and communication environment. In study 1A, participants assumed that they went to a family restaurant to dine as a group. In study 1B, the scenario described a more personal dining experience (i.e., going to a family restaurant with his/her close friend) where each participant was exposed to either a positive or negative experience. After reading the scenario, participants were presented with a fictitious blog where they could write their opinions about their restaurant experience. The participants were asked to think of the blog as personal. Finally, they were also asked about their intentions to post eWOM (α = .94), as well as to generate tWOM (α = .86).

We measured consumers' regulatory focus using 18 items developed by Lockwood et al. (2002). Promotion (prevention) scores were created with the average of nine items measuring participants' chronic promotion (prevention) tendency. The difference between the two scores (i.e., promotion–prevention) was used as an indicator of participants' overall regulatory focus. Prevention and promotion groups were created by conducting a 35/65 percentile split on this indicator (Bao et al. 2011).

5 Results

Consistent with study 1A, MANOVA on eWOM and tWOM produced a significant main effect of service experience (Wilks' lambda = .842, F (2, 51) = 4.801, p < .05) as well as an interaction effect (Wilks' lambda = .907, F (2, 68) = 2.608, p < .09). Regulatory focus did not show a significant main effect (Wilks' lambda = .025, F (2, 51) = .639, p > .10).

The univariate results indicate only a significant interaction effect (F (1, 52) = 4.38, p < .05) on intentions to post eWOM. When consumers were promotion-focused (H1), they were more likely to post eWOM on their own blog when the consumption experience was positive (M positive = 5.13, M negative = 3.54; t(29) = 2.34, p < .05). However, prevention-focused consumers did not differ in terms of intent to post eWOM regardless of the nature of their consumption experience (M positive = 4.46, M negative = 4.99; t(25) = .70, p > .05) (see Fig. 2).

Fig. 2
figure 2

Service experience and regulatory focus (study 1B)

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Measures of tWOM displayed a pattern consistent with negativity effect. The main effect for consumption experience (F (1, 52) = 7.33, p < .01) was significant, whereas the main effect of regulatory focus (p > .10) and the interaction between regulatory focus and consumption experience (p > .10) were not significant. Participants showed greater intentions to generate tWOM when they underwent a negative service experience (M negative = 6.57 vs. M positive = 6.12).

6 Discussion

The results of studies 1A and 1B indicate that promotion-focused consumers were likely to spread eWOM on their own blog when they had positive service experience, whereas prevention-focused consumers had greater intention to post their reviews on community sites when they had negative experience. An important connotation of these results, therefore, is that regulatory focus is a key motivational factor affecting eWOM generation, but that such effects are likely to be a function of whether one's self-construal is independent or interdependent. Interestingly, we also found that regulatory focus did not play a significant role in tWOM generation, where negativity effect was dominant. We next examine how the external motivational factor, namely, collective dissonance, interacts with service consumption experience to influence consumers' intentions to post eWOM.

7 Collective dissonance and service experience

Emerging studies in social psychology have examined the impact of cognitive dissonance generated from disagreements among members of a social group (e.g., Glasford et al. 2009). Although traditional studies on individual-level cognitive dissonance separate the source of dissonance from personal strategies to reduce the psychological discomfort, collective dissonance studies treat a social group not only as a source of dissonance but also as a means of dissonance resolution (Matz and Wood 2005).

We adopt the concept of collective dissonance to explain how disagreeing opinions in online communities influence consumers' motivations to generate eWOM. When consumers observe eWOM contents different from their own experiences, they develop a sense of frustration from the inconsistency because they may believe that (1) their firsthand experience is a more valid source of information, (2) the people posting the review did not know the “true” nature of the service, and (3) the content in the reviews misinforms other community members (Dellarocas 2006). Thus, having different opinions from other community members who share the concept of “we”ness may create collective dissonance (Matz and Wood 2005), and a consumer would be highly motivated to reduce the psychological discomfort.

A viable behavioral strategy that consumers can use in such a situation is to inform other community members about their own experiences so that these members can evaluate the service based on more valid and reliable information, such that a right “consensus” among community members may be formed. This can eventually reduce consumers' psychological discomfort.

However, consumers will not experience dissonance when they encounter online reviews that agree with their own service experiences. Also, writing a review reflecting their own (similar) service experience will not provide any sense of contribution to the community (e.g., Park et al. 2009). Therefore, consumers will be less motivated to write a review because they perceive such behavior as redundant. Thus, we hypothesize:

  1. H3

    Consumers who encounter an inconsistency between their own experience and others' reviews will have greater intentions to post eWOM. Specifically:

  2. 1.

    When consumers read all positive reviews, those who had a negative experience will have greater intentions to post eWOM than those who had a positive experience.

  3. 2.

    When consumers read all negative reviews, those who had a positive experience will have greater intentions to post eWOM than those who had a negative experience.

8 Study 2

8.1 Design

A 2 (others' reviews: all positive vs. all negative) × 2 (consumption experience: negative vs. positive) between-subject design was used to test H3. We used the same positive and negative restaurant consumption scenarios as in study 1A. We manipulated existing reviews on a community website by presenting either four positive or four negative reviews about the restaurant.Footnote 1

We conducted a pretest (N = 20) to ensure the valence of the reviews in the two conditions. Participants in the all positive (negative) review conditions rated the reviews as significantly higher (lower) than the midpoint of the scale (M positive = 6.40; t(9) = 17.76; p < .01; M negative = 1.30; t(9) = −14.40; p < .01).

8.2 Procedure

One hundred forty-nine undergraduates enrolled in marketing courses participated in the experiment for extra credit. Sixty-nine percent were males, and the average age was 22.1 years. Participants read the negative or positive scenario used in study 1A. Next, participants were guided to visit the community website where half of them were either exposed to all four positive reviews or to all four negative reviews. After the participants read the reviews and browsed the community website, we measured their intentions to post eWOM (α = .96).

9 Results

The ANOVA results indicate a significant interaction effect (F (1, 145) = 9.40, p < .05) on intentions to post eWOM. As expected, when consumers read all positive reviews on the community website, those who had a negative experience (i.e., inconsistent condition) were more likely to post eWOM (M = 4.30) than those who had a positive experience (i.e., consistent condition) (M = 3.41; t(75) = 2.05, p < .05) (see Fig. 3). Also, when consumers read all negative reviews, those who had a positive experience had greater intentions to post eWOM (M = 3.88) than those who had a negative experience (M = 2.83; t(70) = 2.28, p < .05). Therefore, H3a and H3b were supported.

Fig. 3
figure 3

Service experience and collective dissonance (study 2)

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10 Overall discussion

10.1 Theoretical implications

Our studies make incremental contribution to an emergent research area on new media and eWOM. First, we applied regulatory focus theory in the context of eWOM creation. Previous studies have explored the effect of regulatory focus on message efficacy (Aaker and Lee 2001; Keller 2006), investment decisions (Zhou and Pham 2004), behavioral patterns (Chernev 2004), and brand extension (Yeo and Park 2006). However, we believe that this study is the first application of the theory to examine the motivational process of eWOM creation (cf. Cheema and Kaikati 2010 Footnote 2), and our results indicate the usefulness of the theory for understanding marketing communication in the area of new media and technology.

Second, our study extends the theory to a post-consumption behavior (i.e., eWOM generation) and examines the transfer of the motivational force generated from consumption experience to post-consumption behaviors using a slight modification of regulatory fit hypothesis. Our findings suggest that regulatory focus generates a more lasting effect on consumers' post-consumption behaviors in online communications than in traditional consumer to consumer communications. Third, we adopted collective dissonance theory to explain the role of social context (i.e., other community members' reviews and opinions) in the motivational process of posting eWOM. Our results highlight the importance of social contexts in consuming and generating eWOM.

Finally, we demonstrate that regulatory focus does not play a significant role in tWOM generation, where negativity effect is dominant. This results in the generation of negative tWOM when consumers experience a negative service or product experience regardless of their motivational state. We believe that regulatory focus probably operates in tWOM contexts, but its effect is overshadowed by other motivational factors (e.g., benefits and costs) generated from a strong social tie between the source and the receiver(s).

10.2 Managerial implications

Marketers need to understand how to manage both negative and positive eWOM, as well as how individual consumer's regulatory focus can be modified to effectively control and influence eWOM. First, there are certain product types (e.g., antivirus software, car insurance) or contexts (e.g., message frames, advertising appeals) that might independently stimulate prevention-focused goals (Zhou and Pham 2004). For example, when purchasing car insurance, a consumer is more likely to frame the consumption goal as a preventive one (e.g., protect assets when an accident occurs). Also, when marketers communicate with consumers, the use of fear appeal ads or negatively framed messages could stimulate consumers to develop a prevention focus. Either way, our research implies that consumers' negative experiences with “preventive” products could be shared easily over new media platforms.

Our findings also have implications for service failure situations. Since it is easy for consumers to post negative reviews through online communities, blog, companies' websites, etc., it is even more important for marketers to deal effectively with service failure situations. Marketers should monitor postings on their website or other new media platforms and respond immediately to the negative comments. For example, a local BMW dealership found the following negative comment in August last year: “The entire process felt rushed and I left with an awkward feeling—just wanted to take my car elsewhere—even though I am a regular at ‘….’ after 5 years of coming here—thinking of not returning with my car.” The management, though after a 7-day delay, responded in the following manner: “Let us start by apologizing for your most recent experience and thank you for the feedback and previous business. Our service manager will be reaching out directly and as always we will certainly do our best to alleviate any concerns.”

Marketers can also ask a consumer who has had a negative experience to rationally explain why she thinks the negative event occurred. If the consumer rationally “explains” her experience, then not only the valence of her feelings related to the negative experience is likely to become less negative, she is also less likely to repeat the story to others (Moore 2012).

Finally, marketers could use promotion-oriented actions when responding to service failure to minimize the likelihood of negative eWOM. An interesting implication of regulatory focus theory is that a person's regulatory focus can shift depending on contextual characteristics (Higgins 1997), so appropriate methods of addressing failures in service could modify contexts to induce such changes. Creating a promotion focus in a consumer's mind, such as providing free coupons redeemable for the next maintenance service or for special food and events at the restaurant, might be an effective way of managing service failure in addition to focusing on preventive communication such as apologizing to customers for any negative events.

We also found that positive eWOM is more likely to be generated on (individual) new media platforms when consumers are promotion focused. A marketer might want to remain alert to this possibility and respond to the positive posting, thereby reinforcing the observation of the customer and potentially increasing the likelihood of repeat positive posts by the same customer. Again, the BMW dealership noted above responded to the following positive comment on their website: “No BMW dealer in America has a better service department than ‘…,’ no one” by responding “All we can say is WOW. Thank you!”

Finally, our findings regarding the role of collective dissonance may increase managers' understanding of the role of existing reviews in creating and managing positive eWOM. Our results show that consumers are more likely to share their positive experiences when there are inconsistent reviews posted on a community site. Thus, service providers and community managers need not fear or degrade negative reviews of their products or services. In contrast, managers should be careful in manipulating or encouraging positive reviews. Marketers often hire professional reviewers or provide incentives to consumers to encourage positive eWOM for their products or services. Our study shows that many positive reviews could encourage consumers with negative experiences to share negative eWOM.

10.3 Limitations and future research

There are limitations of our research. We considered eWOM in a limited setting. Future research should examine the effect of regulatory fit in other user-generated contents, such as digital videos, blogs, and multimedia. We also tested our hypotheses in one service category. Although we did not find the expected differences in intention to post eWOM among promotion-focused consumers when the experience was positive in a group consumption situation, it is possible that other promotion-oriented product categories, such as traveling packages, would provide different results. Nevertheless, this study serves as a first step toward understanding the area of development and management of new media and their impact on consumer behavior.