In an era of rapidly developing communication technology and increased consumer awareness, the formulation of successful electronic word-of-mouth strategies can help enterprises achieve the goal of sustainable operation. Hennig-Thurau et al. (2004) defined electronic word-of-mouth (eWOM) as a potential, actual, or previous consumer providing positive or negative opinions on relevant products or company information through an online platform for the greater knowledge of consumers or organizations. Berthon et al. (2008) stated that eWOM can be compared to prompt advertising created by consumers. Compared with conventional media advertising, eWOM is more likely to influence consumers’ purchase behavior, and has thus become popular within the industry and sparked researchers’ interest (Cheung & Thadani, 2012). However, Trusov et al. (2009) stated that although the influence of eWOM on consumer behavior has attracted scholarly attention, most studies have focused on consumer-generated information (e.g., Park et al., 2019; Wathen & Burkell, 2002), and few have further explored the internal factors of the message (e.g., message framing) or the characteristics of the consumers receiving the information (e.g., their regulatory focus). Thus, in this study we explored other dimensions to understand the full picture of the influence and persuasiveness of the message.

Shin et al. (2014) asserted that consumers are influenced by internal and external factors when processing electronic messages, and their regulatory focus is one of the crucial internal factors. Regulatory focus is a manifestation of long-term personality traits as well as temporary behavior triggered by situational factors (Higgins, 1998). It leads to varying information processing motivations and strategies (Wang & Lee, 2006), so that people deal with information in different ways according to their regulatory focus (Higgins, 2002).

The results of previous research on word-of-mouth (WOM) persuasiveness are contradictory: Some have shown that negative (vs. positive) WOM messages have a greater persuasive impact on consumers (J. Yang & Mai, 2010), whereas others found the opposite (Gershoff et al., 2003). As persuasion is related to consumers’ purchase decision making, Zhang et al. (2010) proposed that regulatory focus theory can be used to further explore the influence of eWOM messages.

When people face losses or gains, they employ one of two behavioral responses: risk seeking or risk aversion (Kahneman & Tversky, 2013), that is, through the constraints of the situation, they change their preferences. This is known as the framing effect on behavioral responses (Tversky & Kahneman, 1989). In addition, H.-C. Lee et al. (2018) found that consumers may make different purchase decisions according to the description of the products or services. Behavioral responses induced by the framing of positive and negative opinions occur in everyday life, and people have different attitudinal responses when faced with satisfaction and dissatisfaction situations (Vargo et al., 2007). We inferred that the framing effect of eWOM through positive and negative reviews would imperceptibly influence consumers’ attitudinal intention and purchase decisions. Thus, our three research objectives were to explore (a) the effect of consumers’ regulatory focus on their eWOM perceived credibility and purchase intention, (b) the effect of message framing on consumers’ eWOM perceived credibility and purchase intention, and (c) the effect of interaction between consumers’ regulatory focus and message framing on eWOM perceived credibility and purchase intention.

Literature Review and Hypothesis Development

Electronic Word-of-Mouth

Traditional WOM requires face-to-face interaction to convey information. However, since the development of information technology and the Internet, WOM has evolved to involve senders and receivers who may be unfamiliar with each other (Zhang et al, 2010). This WOM is known as viral marketing, e-mail marketing, Internet WOM, and eWOM, of which eWOM has become the most popular and widely used term (Eelen et al., 2017). In practice, eWOM involves experienced peer consumers giving positive and negative reviews of products or services (M. Lee et al., 2009).

Regulatory Focus

According to regulatory focus theory (Higgins, 1997), achievement motivation triggers people to exhibit one of two regulatory strategies when striving to achieve specific goals: promotion focus or prevention focus. Promotion focus is related to the strategy of approach to achieve a goal, whereas a prevention focus involves adopting an aversion strategy to avoid failure (Higgins, 1987). Higgins et al. (1994) found that promotion-focused people set hopes, desires, and progress as their goals and are sensitive to positive results, from which their happiness also stems. In contrast, prevention-focused people, who regard duties and obligations as goals and who feel happy when negative results disappear, are extremely sensitive to negative results. They regard failure as their responsibility and aim to avoid the wrong goal combinations (Higgins, 1998).

Consumers use various means to pursue specific goals according to their goal orientation, and when the means are consistent with their goals, this leads to a regulatory fit (Higgins, 2000). Researchers have demonstrated that consumers’ regulatory goal affects their product reviews and brand selection decisions (Higgins, 2002). A. Y. Lee and Aaker (2004) found that messages in which gains (vs. losses) are used for appeal framing are more convincing to promotion-focused (vs. prevention-focused) consumers. Haws et al. (2010) further indicated that the primary reason for differences in the regulatory focus types leading to different information responses is that promotion-focused people emphasize the ideal self as reflected in their hopes and aspirations; therefore, they adopt eagerness-oriented strategies. Conversely, prevention-focused people emphasize the ought self as reflected in their duties and obligations, so they adopt vigilance-oriented strategies.

Message Framing

The message-framing effect comprises the framing effect and message framing. The framing effect refers to decision making between two essentially identical options, where difference in the descriptions leads people to respond differently (Jacobson et al., 2019). Researchers have found that the degree of positivity or negativity of a message has a significant effect on consumers’ purchase intention (H. C. Lee et al., 2018). As a positive message elicits more favorable reviews and advertising preferences (Levin & Gaeth, 1988), it yields a stronger persuasive effect (Smith & Petty, 1996). Soliha and Dharmmesta (2012) showed that consumers handle a message more cautiously when they expect negative message framing. Smith and Petty (1996) found that negative (vs. positive) message framing attracts attention more easily, and necessitates consumers exerting additional psychological effort to process the message. Pratto and John (1991) explained this by stating that people always think that pleasure is less urgent than pain. Thus, people’s impulse and reaction to avert danger in the face of negative events outperform those in the face of positive events. Additionally, Wong and McMurray (2002) stated that a negative message (e.g., health risk) would render their deeper involvement in the message and a greater influence of negative message framing.

From the risky decision perspective, when consumers are making decisions that involve high risk without a clear message, they become highly involved in the message and think it over carefully; conversely, if consumers receive a clear message, they use the message directly as the basis for decision making, which inevitably leads to a lower degree of involvement (Soliha & Widyasari, 2018). When people process in-depth thinking, negative message frames are more persuasive than positive ones; in contrast, positive and negative message frames are equally persuasive if people are certain that the message will lead to the desired outcome (Block & Keller, 1995). In sum, researchers differ in their conclusions on the message-framing effect. We postulated that the crucial point for the message-framing effect is if the message is related to personal concerns, which would lead consumers to evaluate if that message needs to be further processed.

In the context of eWOM, credibility is the level of trust that receivers place in a message. Receivers first determine the credibility of a message according to its content and quality, and then decide whether to accept it (Wathen & Burkell, 2002). K. T. Lee and Koo (2012) stated that eWOM researchers have extensively examined the effect of message credibility and acceptance, of which the influencing factors of review valence (i.e., positive and negative reviews) are most often used. Park et al. (2019) pointed out that consumers are more likely to trust two-sided reviews (positive and negative) than they are to trust one-sided reviews. Although consumers less commonly post negative (vs. positive) reviews, the negative reviews often have more influence (Xue & Zhou, 2010) because most consumers believe that negative (vs. positive) product information has greater diagnostic value (Herr et al., 1991).

Researchers have stated that negative WOM is more influential than positive WOM, and attracts public attention more easily (Wilson et al., 2017). Psychologists have termed this negative attitudinal tendency negativity bias (Soroka et al., 2019) or negativity effect (L. Yang & Unnava, 2016). Chiou and Cheng (2003) further explained that negative responses gain more traction among online reviews than positive responses do, mainly because negative messages are scarce. Although negative eWOM attracts consumer attention more easily, from the viewpoint of consumers’ purchase decisions, positive (vs. negative) eWOM is more capable of overcoming consumers’ psychological barriers, and thus gives consumers more confidence to purchase the product being reviewed (Gershoff et al., 2003). In addition, Kudeshia and Kumar (2017) found that positive eWOM had a positive influence on consumers’ brand attitude and purchase intention. Therefore, we proposed the following hypotheses:
Hypothesis 1: Prevention-focused (vs. promotion-focused) consumers will perceive greater credibility of electronic word-of-mouth when presented with negative (vs. positive) message framing.
Hypothesis 2: Negative (vs. positive) message framing will result in greater perceived credibility of electronic word-of-mouth among prevention-focused consumers.
Hypothesis 3: Promotion-focused (vs. prevention-focused) consumers will exhibit stronger purchase intention when presented with positive (vs. negative) message framing.
Hypothesis 4: Promotion-focused consumers will have a stronger purchase intention when presented with positive (vs. negative) message framing.

Method

Participants

Participants were adults in Taiwan aged between 20 and 60 years. We used a purposive sampling method outside a restaurant to find customers who had finished eating their meal as experimental participants. We distributed 400 surveys and collected 344 valid completed responses (response rate = 86%). Participants provided informed consent and agreed to take part in the experiment (see Table 1 for demographic characteristics).

Procedure

Ethical approval for the study was obtained from the Center for Research Ethics at National Taiwan Normal University. We adopted a 2 × 2 between-subjects design to manipulate the two independent variables of regulatory focus (promotion focused and prevention focused) and message framing (positive and negative) to evaluate their effects on participants’ eWOM perceived credibility and purchase intention. The overall conceptual framework is shown in Figure 1.

To assess regulatory focus, we used Lockwood et al.’s (2002) 18-item Regulatory Focus Scale, in which nine items are promotion-focused and nine items are prevention-focused (see Table 2). Items are rated on a 5-point Likert scale (1 = never, 5 = always). After participants had completed the scale, we calculated their total scores for the promotion-focused and prevention-focused items. If participants’ promotion-focused item scores were higher, their regulatory focus was classified as being promotion-focused, and vice versa.

Analysis of responses indicated that 167 participants (48.55%) were prevention-focused, scoring between 21 and 45 points (M_{prevention-focused} = 32.92, SD = 5.59), and 177 participants (51.45%) were promotion-focused, scoring between 23 and 45 points (M_{promotion-focused} = 34.15, SD = 5.33).

Stimuli

The experimental stimulus was provided in five steps: (a) we created a virtual Japanese cuisine restaurant (Ritaotang; see Figure 2); (b) from a popular Taiwanese food blog (iFoodie.tw), we collected 20 reviews (10 positive and 10 negative, encompassing, e.g., service quality, meal quality, and prices) from customers of restaurants serving Japanese cuisine; (c) the content of each customer’s review was modified to between 52 and 54 Chinese words to attain consistent review quality; (d) three experts who each had 6 years of advertising and marketing experience selected six positive and six negative reviews based on the restaurant attributes; and (e) four (vs. two) positive and two (vs. four) negative reviews were adopted in the positive (vs. negative) message-framing stimulus. The order of presentation of the positive and negative reviews was counterbalanced in each message-framing stimulus.

Measures

Electronic Word-of-Mouth Perceived Credibility
To measure eWOM perceived credibility, we consulted Hussain et al. (2017) and Newell and Goldsmith (2001), and devised a survey with four items rated on a 5-point Likert scale (1 = strongly disagree, 5 = strongly agree). The items are “The message in these electronic reviews is correct,” “The message in these electronic reviews is fair,” “The message in these electronic reviews is truthful,” and “The message in these electronic reviews is unbiased.”

Purchase Intention
To measure purchase intention, we consulted Bataineh (2015) and Jalilvand and Samiei (2012), and devised a four-item survey that was rated on a 5-point Likert scale (1 = strongly disagree, 5 = strongly agree). The items are “I am willing to try the meals at this restaurant,” “I may order meals from this restaurant,” “I will actively search for information related to this restaurant,” and “I may recommend others to try this restaurant.”

To evaluate data reliability, we calculated Cronbach’s alphas, which were .88 and .86 for eWOM perceived credibility and purchase intention, respectively, indicating that both had high reliability as they exceeded the recommended threshold of .70.

Results

Two-Way Analyses of Variance

We performed a two-way analysis of variance (ANOVA) of the interaction effects of regulatory focus and message framing on eWOM perceived credibility and purchase intention data. Results show that the interaction effects of regulatory focus and message framing on eWOM perceived credibility and purchase intention were both significant (see Table 3).

Analysis of Simple Main Effects

Owing to the significant observed interaction effect, we further conducted a simple main effects analysis. The results in Table 4 and interaction plot in Figure 3 indicate that when presented with negative message framing, the prevention-focused group (M = 3.45, SD = 0.07) had greater eWOM perceived credibility than did the promotion-focused group (M = 2.99, SD = 0.07). In addition, for the prevention-focused group, eWOM perceived credibility of negative message framing (M = 3.45, SD = 0.07) was significantly higher than that of positive message framing (M = 2.99, SD = 0.07).

The results in Table 5 and Figure 4, which show significant differences in positive message framing, reveal that the promotion-focused group (M = 3.55, SD = 0.08) had stronger purchase intention than did the prevention-focused group (M = 3.16, SD = 0.08). Further, the purchase intention for positive (vs. negative) message framing was stronger in both the prevention-focused and promotion-focused groups.

Interactive Effects Between Regulatory Focus and Message Framing

The two independent variables—regulatory focus and message framing—interacted with each other in their effect on eWOM perceived credibility and purchase intention. Thus, Hypotheses 1, 2, and 3 were supported. Because both promotion-focused and prevention-focused participants exhibited stronger purchase intention for positive (vs. negative) message framing, Hypothesis 4 was partially supported.

Discussion

Consumers share their personal consumption experience and product evaluation on electronic platforms through eWOM. This information propagation power between consumers is sometimes comparable to that of companies’ costly marketing promotions. In addition, with the emergence of e-commerce as the main business operations model (Zhu & Zhang, 2010), consumers’ online consumption evaluation and feedback play an even more dominant role. To achieve the goal of sustainable development for the enterprise, managers must consider the influence of eWOM. The planning of well-structured eWOM management strategies is crucial to companies’ sustainable operations; however, managers should bear in mind that consumers’ psychological traits affect eWOM message reception and interpretation. Thus, company marketing staff should manage and respond to consumer opinions seriously because these new types of consumption characteristics and purchase decision behavior may affect the future sustainable development of the company. Managers must carefully assess the emerging trends of consumer behavior.

In our study the first analysis was from the eWOM perceived credibility perspective. According to Higgins (1997), prevention-focused people are more sensitive to negative (vs. positive) messages and adopt prudent measures to avoid adverse outcomes. Therefore, when prevention-focused consumers are satisfied with the message content and quality in eWOM with negative message framing, they believe the eWOM to be trustworthy, with the result being that their purchase intention declines.

Further, when eWOM was presented with positive message framing, this exerted a positive effect on the purchase intention of both prevention- and promotion-focused participants. According to Bickart and Schindler (2001), the information search levels and content acceptance of consumers of online product reviews are significantly greater than the search and acceptance of conventional advertising and marketing sources. The primary reason for this is that both sender and receiver are consumers; thus, they are less likely to associate product interests with message manipulation. Therefore, despite eWOM with negative message framing eliciting greater eWOM perceived credibility among prevention-focused consumers than positive message framing did, positive message framing nonetheless aids consumers in deciding their purchase strategies, regardless of whether they are prevention- or promotion-focused. Specifically, as promotion-focused people have the risk-seeking psychological trait, eWOM with positive message framing can be expected to increase their purchase intention. However, as prevention-focused people have a latent failure-aversion psychological trait, eWOM with negative message framing may cause them to generate greater eWOM perceived credibility. Nonetheless, for actual purchase decision making, eWOM with positive message framing exerts a positive effect owing to consumers’ individual regulatory fit.

Our four major findings can help managers understand the correlations among eWOM, consumption psychology, and message type: (a) prevention-focused (vs. promotion-focused) consumers had greater eWOM perceived credibility when presented with negative message framing, (b) prevention-focused consumers exhibited greater eWOM perceived credibility for negative (vs. positive) message framing, (c) promotion-focused (vs. prevention-focused) consumers had stronger purchase intention when presented with positive message framing, and (d) both prevention- and promotion-focused consumers exhibited stronger purchase intention for positive (vs. negative) message framing. Many companies have overlooked the influence of eWOM and consumers’ evaluation and user feedback regarding products, and managers have failed to improve the products, resulting in losses for the organization (Zinko et al., 2021). Hence, our findings may provide a reference for establishing a set of comprehensive eWOM marketing strategies so that the company can earn more profit. Managers of companies must seriously consider the effect of both positive and negative eWOM.

Moreover, eWOM not only allows customers to exchange consumer experience and product knowledge without hindrance, but is also directly related to customer loyalty and purchase intention. This relationship indirectly affects the overall image of the value provided by the company. Park et al. (2019) regard eWOM as a spontaneous consumer advertisement and the message of the eWOM to be more influential than conventional mass media. Regardless of whether WOM is positive or negative, it imperceptibly influences consumers’ purchase motivation and decisions. Thus, we suggest that vendors should be cautious in handling eWOM, value each consumer’s message on products or postsale services, and provide professional and objective feedback through full-time professional staff to eliminate consumers’ doubts or express gratitude to them for their affirmation. Thus, eWOM can generate communication capability.

Finally, consumers have different regulatory focus tendencies and decision-making approaches for messages. These latent influential factors may vary according to consumers’ situation and how the problems are described, leading to different decision choices. We suggest that when operating online message platforms, vendors should incorporate the characteristic differences of how users process information, distinguish between the review pages of novices and experts, and provide consumers with suitable content and presentation. Vendors can then more precisely target consumers with appropriate reviews, so that the consumers can choose the type of reviews they wish to read, thereby avoiding the effect of negative reviews attributable to differences in consumers’ purchase habits. Irreparable harm to vendors’ reputation caused by irrational reviews from prevention-focused consumers can thus be minimized. To experience increased popularity and enhanced consumer loyalty, positive eWOM must be used efficiently and marketing staff and managers must better understand consumer preferences to improve products in a timely manner.

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https://doi.org/10.3390/jtaer16060109

This study was funded by the Ministry of Science and Technology in Taiwan (108-2410-H-131-001

109-2410-H-131-001

109-2410-H-141-003)

by Ming Chi University of Technology

and by National Taipei University of Business.

The authors wish to thank all the study participants.

Chao-Ming Yang, Department of Visual Communication Design, Ming Chi University of Technology, 84 Gungjuan Road, Taishan, New Taipei 243303, Taiwan. Email: [email protected]