The Role of Power and Incentives in Inducing Fake Reviews in the Tourism Industry

Abstract

As online reviews have become increasingly prevalent in recent years and their influence on consumers’ purchasing decisions has grown exponentially, some companies have begun to ask people to write fake reviews about their businesses or their competitors while offering compensation in return. This process has drawn the attention of regulators because it knowingly misleads consumers. This article reports on two studies that looked at the effect of two types of incentives (self-benefiting or charitable) on individuals’ intentions to write fake reviews and examined the moderating role of a person’s sense of power on his or her propensity to post a fake review. The study findings indicate that powerless individuals are more likely to post a fake review when presented with a monetary incentive rather than a charity incentive, while powerful individuals are not impacted by incentive type. Moreover, when asked to post negative fake reviews about competitors, such effects are mitigated.

Keywords

online review fake review unethical behaviors power incentives

Introduction

Word of mouth (WOM) has a huge impact on consumer behavior (Berger 2014; Chevalier and Mayzlin 2006; Trusov, Bucklin, and Pauwels 2009) and online reviews, a form of electronic word of mouth (eWOM), are widely recognized as the most impactful information source in consumers’ decision-making processes (Hennig-Thurau et al. 2004; Gruen, Osmonbekov, and Czaplewski 2006; Park and Lee 2009). Consumers trust other consumers’ recommendations of a product more than company-generated communications (Hennig-Thurau and Walsh 2003).

Hospitality and travel services tend to be intangible and experience-based and their attributes cannot be completely assessed until they have been purchased and consumed (Zeithaml, Bitner, and Gremler 2012). Consumers of such services tend to rely on recommendations from others in order to minimize uncertainty and perceived risk (Murray 1991) and the most recent and most widely used version of those recommendations is the online review (e.g., Ring, Tkaczynski, and Dolnicar 2016).

Previous research has examined the impact of online reviews on trip planning (Gretzel and Yoo 2008), hotel performance (Phillips et al. 2015; Ye, Law, and Gu 2009), hotels’ responses to online reviews (Sparks, So, and Bradley 2016; Wei, Miao, and Huang 2013), and consumers’ motivations to read or post online reviews (Bronner and de Hoog 2011; Kim, Mattila, and Baloglu 2011; Wu et al. 2016). More recently, there has been a focus on the effects of various central cues (Filieri and McLeay 2014) as well as peripheral cues in online reviews on consumers’ decision-making processes, such as review valence (Sparks and Browning 2011), reviewer’s expertise (Vermeulen and Seegers 2009; Zhang, Zhang, and Yang 2016), reviewer’s identity (Liu and Park 2015; Xie et al. 2011), and source credibility (Ayeh, Au, and Law 2013; Zhang, Wu, and Mattila 2014).

There is growing evidence to suggest that both businesses and consumers generate fake reviews, a practice that undermines the credibility of the process (Mayzlin, Dover, and Chevalier 2014; Simonson 2016). For instance, a hotel located nearby a competitor tends to have more fake, negative reviews than a hotel with no close competitors (Mayzlin, Dover, and Chevalier 2014). This phenomenon is frequently observed in the restaurant context as well (Luca and Zervas 2015).

The occurrence of fake online reviews has begun to receive attention, both from the media and state and federal regulators. The Federal Trade Commission (FTC) recently introduced endorsement guidelines, stating that “if there is a connection between an endorser and the marketer that consumers would not expect and it would affect how consumers evaluate the endorsement,” an endorser should disclose that connection clearly (FTC 2015, 2). Yet, while fake reviews are investigated at various levels, there is scant research on consumers’ motivation to engage in such reviews. To fill this gap, this study examines whether different types of incentives (i.e., self-benefiting vs. other-benefiting) influence consumers’ propensity to write fake reviews. Being compensated for writing a fake online review creates a moral dilemma. People can choose to be unethical and post a fake review in order to support a charity. Or, they can be unethical and post a fake review to receive some benefits for themselves. Finally, people might choose to be ethical and not post a fake review.

This study examines the role of a person’s sense of power in this dilemma and we propose that an individual’s sense of power, the capacity to control resources or outcomes in social relationships (Keltner, Gruenfeld, and Anderson 2003), influences a person’s response to an unethical request. Although common sense dictates that people can be motivated by something that benefits them personally, this study demonstrates that individuals are also motivated by incentives that benefit others, depending on their personal sense of power. Whereas powerless individuals tend to activate a concrete mindset and focus on self-interests, powerful individuals typically activate an abstract mindset and prioritize a greater social good (Rixom and Mishra 2014). Based on a review of the relevant literature on unethical behaviors, incentives, and sense of power, this study explores the ethical issues associated with posting fake online reviews. Specifically, we examine the joint effects of power and incentive type on consumers’ propensity to post either positive or negative fake reviews.

Literature Review

Unethical Behaviors and Fake Online Reviews

Writing a fake review is unethical and “illegal or morally unacceptable to the large community” (Jones 1991, 367). Research in social psychology and marketing has touched upon a variety of unethical behaviors, such as individuals’ propensity to engage in lying (Fischbacher and Föllmi-Heusi 2013), stealing and cheating (Yap et al. 2013), and other unethical behaviors (Vitell 2003). Yet, as consumer behavior is no longer confined to traditional personal interactions, researchers have begun to investigate unethical behaviors in online settings such as software piracy (Chiou, Wan, and Wan 2012) and retailers falsifying product information (Lu, Chang, and Yu 2013).

Hancock (2007, 290) describes “digital deception” as the “intentional control of information in a technologically mediated message to create a false belief in the receiver of the message.” He further states that digital deception must be (a) “intentional or deliberate” and (b) “designed to mislead or create a false belief in some target.” Based on this definition, fake online reviews fall into the category of digital deception.

Fake reviews are written to promote a business by unethical means and to deliberately mislead readers in their purchase decisions (Yoo and Gretzel 2009). For example, Harmon (2004) shows that many book reviews on Amazon were written by publishers and the authors themselves. Fake reviews are not only an issue in the retail industry but also in the travel industry. A hotel, for instance, might benefit from deceptively posting positive reviews about its own property and by posting negative reviews about competing properties on TripAdvisor.com (Mayzlin, Dover, and Chevalier 2014; Yoo and Gretzel 2009). However, when Mayzlin (2006) examined whether firms benefit from promotional reviews or chats in online communities, she found that it is not beneficial to produce a high volume of deceptive reviews, since creating and posting such reviews are costly. Moreover, she shows that eWOM remains persuasive despite misrepresentations in promotional reviews.

Previous research has explored the detection of deception in online communities, and studies in computer science and information technology have developed automated identifier systems to filter out fake reviews (Hu et al. 2012; Mukherjee, Liu, and Glance 2012). When comparing fake and actual reviews, Yoo and Gretzel (2009) and Ott et al. (2011) conclude that deceptive and actual, honest reviews are different in terms of their lexical complexity and the use of first-person pronouns. A recent study by Luca and Zervas (2015) uses the fraud filter on Yelp.com to detect fake reviews and found that promotional, fake reviews tend to be more extreme than other reviews.

Recently, researchers have also examined the role of verified reviewers who actually purchased a product or experienced a service (Anderson and Simester 2014). Mayzlin, Dover, and Chevalier (2014) compare hotel ratings on TripAdvisor.com and Expedia.com. Whereas Expedia.com requires the customer posting a review to have had an actual reservation at the hotel, TripAdvisor.com does not, thus creating an environment that might be more conducive to fake reviews. Their study shows that reviews on TripAdvisor.com tend to be more extreme, thus potentially fake.

Whereas several studies have investigated various methods to detect deceptive reviews, to our knowledge, previous research has not examined the reviewer’s motivation to post fake reviews. In this study, we are primarily interested in fake reviews posted by consumers rather than by service providers. We define fake reviews as reviews written by consumers who did not purchase a product or a service and who still wrote a review about it. In the following section, we first discuss the role of incentive types followed by an individual’s sense of power in influencing their propensity to post fake reviews.

Incentives

In this study, we are interested in two types of incentives: self-benefiting (e.g., a discount in future purchases) and other-benefiting (e.g., contribution to charity).

A monetary reward is a powerful tool in motivating people to behave in certain ways. Previous research has demonstrated the importance of monetary (self-benefiting) incentives in enhancing employee motivation (Stajkovic and Luthans 2003), business unit outcomes (Peterson and Luthans 2006), and creative thinking (Eisenberger and Rhoades 2001). Moreover, research in marketing shows that monetary incentives are effective in generating positive WOM (Hennig-Thurau et al. 2004; Jin and Huang 2014; Wirtz and Chew 2002).

The other form of incentive, the charitable contribution, has received less attention. Yet, as corporate social responsibility (CSR) gains prominence in today’s corporate world, this kind of incentive has increasingly been used in cause-related marketing campaigns. For example, marketers often promise to donate a certain amount of an item’s purchase price to a charity. The effects of charity incentives depend on donation framing and on the price of the product (e.g., a bottle of shampoo vs. a color ink-jet printer) (Chang 2008). Strahilevitz and Myers (1998) demonstrate that, as compared to monetary incentives, charity incentives are more effective in promoting hedonic products rather than utilitarian products. Previous studies also suggest that the effect of charity incentives on product choice is moderated by the customers’ involvement in the cause and by customer–corporate identification (e.g., Nicole, Stefan, and Hoyer 2012).

The focus of this study is on examining if, and how, these two types of incentives motivate individuals to post fake reviews. Although monetary incentives can lead to socially responsible behaviors (e.g., Iyer and Kashyap 2007), they may backfire when used as justifications for unethical behaviors. Xie et al. (2014) suggest that when there is a monetary incentive to engage in a moral transgression, ethical dissonance (Barkan et al. 2012) is smaller, thereby enabling people to justify immoral behaviors. In other words, money seems to “share” some of the guilt, thereby diminishing the attribution of unethical behaviors to intrinsic motives (Barkan et al. 2012; Shalvi et al. 2015; Winterich, Mittal, and Morales 2014; Xie et al. 2014).

When charity incentives are used to persuade people to write fake reviews, there is an ethical dilemma: helping others by engaging in unethical behaviors. Such a situation is somewhat different from regular ethical dilemmas, which are defined as “situations in which no moral choice is without undesirable moral consequences” (Ditto and Liu 2012, 55). When a conflict exists between two ethical principles, people negotiate between potential outcomes and decide which one takes priority over the other, thereby influencing their behavior (Rixom and Mishra 2014). However, such prioritizing behaviors may vary depending on an individual’s sense of power (DeCelles et al. 2012; Kraus, Piff, and Keltner 2009), and therefore, we want to examine the moderating role of power in influencing consumers’ propensity to write fake reviews.

Sense of Power

Power refers to asymmetric control over resources or other people in social relationships (Keltner, Gruenfeld, and Anderson 2003). Such resources can be monetary, legitimate authority, or intellectual capital (French and Raven 1959). French and Raven (1959) demonstrate that power can arise from relationships based on five components: coercion, reward, legitimacy, reference, or expertise. Coercive power is the ability to let someone to do something forcibly. Reward power refers to the ability to retain or give something to someone. Legitimate power is the ability to administer to certain feeling of obligation. Finally, expert power stems from holding information that can be shared by others. Depending on the context, power can be generally described as rich vs. poor, boss vs. subordinate, or expert vs. novice. Accordingly, one of the frequently used power manipulations asks participants to imagine themselves as a boss or employee (Dubois, Rucker, and Galinsky 2010; Galinsky, Gruenfeld, and Magee 2003). However, it is important to note that resources are determined by an individuals’ subjective perception of such resources. Consistent with this perspective, previous marketing literature has defined power as perceived asymmetric control over resources in social relations (Rucker, Galinsky, and Dubois 2012) Thus, the present research adapts this notion of power.

The effects of power on human behavior have been extensively studied in the psychology and sociology literature (e.g., Anderson and Berdahl 2002; Galinsky, Gruenfeld, and Magee 2003). Similarly, the role of power on consumer behavior has been investigated in a variety of contexts: power shapes not only consumers’ information processing (e.g., Anderson and Galinsky 2006; Mourali and Nagpal 2013) but also their behaviors (e.g., Garbinsky, Klesse, and Aaker 2014; Rucker, Galinsky, and Dubois 2012).

Anderson and Galinsky (2006) show that high-power individuals are more likely to engage in risky behaviors because of enhanced optimism about risks (e.g., unprotected sex). Mourali and Nagpal (2013) conclude that high-power consumers tend to focus on positive product features and adopt a choosing strategy (i.e., select a preferred option), whereas low-power consumers focus on negative features and adopt a rejecting strategy (i.e., fail to purchase the product or service). Rucker and Galinsky (2009) demonstrate that low-power consumers are more likely to have a strong desire to acquire products (which are associated with status) to compensate for their lack of power, while high-power consumers are not heavily influenced by such a desire. Previous studies in the hospitality and travel literature have shown that power moderates the impact of relationship status (friends or strangers) on customer satisfaction when receiving unearned preferential treatment (Zhang and Hanks 2015), the impact of other customers’ dress styles on the focal customer’s approach behavior (Choi and Mattila 2016), and the impact of experience congruity with other customers on willingness to post online reviews (Wu et al. 2016).

Power, Incentives, and Unethical Behaviors Combined

In this article, we argue that individuals’ reactions to incentives that are related to writing fake reviews vary depending on their sense of power. Past research in social psychology has demonstrated the impact of social class and power on individuals’ propensity to engage in unethical behaviors. Social class and power are conceptually and empirically distinct. However, past research shows that people of higher social class tend to have greater resources, which in turn enhance their sense of power. Therefore, social class and power yield similar effects, such as neuroendocrine changes (e.g., Carney, Cuddy, and Yap 2010) and spending behavior (Piff et al. 2010; Rucker, Dubois, and Galinsky 2011). Scholars have suggested several reasons why high social class and power induce unethical behaviors. The general belief is that, if a person has control over resources (i.e., higher social class and power), she or he is less dependent on others. Thus, the individual feels less pressure to abide by social norms or to act prosocially (Lammers et al. 2015). There is further evidence to suggest people of higher social class engage in unethical behaviors because of greed (Piff et al. 2012), while individuals of lower social class engage in prosocial behaviors because of their concern and compassion for others (Piff et al. 2010). However, another stream of research argues that lower social class individuals are more likely to engage in unethical behaviors than higher social class individuals (e.g., Brush 2007).

Building on this contradiction, Dubois, Rucker, and Galinsky (2015) suggest that the beneficiary of unethical acts influences people’s behaviors. According to the agentic–communal model (Bakan 1966), powerful people tend to foster an agentic orientation, which makes them focus on the self, while powerless people tend to foster a communal orientation, thus leading to focus on others (Rucker, Galinsky, and Dubois 2012). Based on the agentic–communal model of power, Dubois, Rucker, and Galinsky (2015) suggest that people of a higher social class or high power are more likely to engage in unethical behaviors when such an act helps themselves. Conversely, individuals of a lower social class or those who feel powerless are more likely to engage in unethical behaviors when the beneficiary is another person. However, we expect a different pattern of results based on the notion of power–mindset association (Smith and Trope 2006).

Power has also been linked to an individual’s mindset (Rucker, Galinsky, and Dubois 2012). Past research has shown that power might not directly influence an individual’s behavior, but might rather trigger an individual’s underlying traits or mindset (Chen, Lee-Chai, and Bargh 2001; DeCelles et al. 2012). Relying on the construal-level theory (Trope and Liberman 2003), Smith and Trope (2006) argue that any factors that influence an individual’s psychological distance from an object also affect his or her propensity to form an abstract or concrete representation of the object. As such, Smith and Trope (2006) show that high-power people tend to process information in an abstract manner because they are more independent of others, have a greater sense of distinctiveness, and feel more psychologically distant from others (Keltner, Gruenfeld, and Anderson 2003; Lee and Tiedens 2001). In contrast, powerless individuals process information in a concrete manner as they are dependent on others and feel psychologically proximal with others (Keltner, Gruenfeld, and Anderson 2003; Lee and Tiedens 2001).

Applying the notion of abstract and concrete mindsets to the context of ethicality, previous research has shown that ethical and moral principles are high-level constructs (Eyal and Liberman 2012; Eyal, Liberman, and Trope 2008) and that individuals with abstract mindsets are more likely to adhere to ethical decision making. Furthermore, Rixom and Mishra (2014) show that people with an abstract mindset tend to focus on the greater social good rather than on honesty. The authors explain that under an abstract mindset, the greater social good is seen as a superordinate concern that can justify the decision to violate other ethical principles in order to achieve a goal.

Conversely, individuals with a concrete mindset are less likely to prioritize ethical principles (Eyal and Liberman 2012; Eyal, Liberman, and Trope 2008) and, therefore, less likely to emphasize the greater social good. Rather, as self-interest is a more proximate concern (Kivetz and Tyler 2007), people with a concrete mindset tend to engage in behaviors with outcomes that will benefit the self (Rixom and Mishra 2014).

In sum, we propose that powerful individuals with an abstract mindset are willing to engage in unethical behaviors (i.e., posting a fake review) for a greater social good (i.e., donation to charity), while powerless individuals with a more concrete mindset are willing to do so for a personal gain (i.e., gift card). However, we further postulate that review valence is an important boundary condition for such effects.

The Boundary Effect of Review Valence

We argue that the interaction effect of power and incentive type only applies to situations in which individuals are asked to post positive fake reviews. Specifically, if asked to post negative fake reviews about a competitor, consumers are less likely to engage in unethical behaviors, regardless of their state of power or the incentive type. In other words, people are likely to perceive writing negative fake reviews to be more unethical and immoral than writing positive fake reviews because, when the moral dissonance increases, it is more difficult to justify unethical behaviors (Barkan et al. 2012; Xie et al. 2014).

Based on our conceptual framework shown in Figure 1, we put forth the following hypotheses:

Figure 1.

Conceptual model.

Hypothesis 1: Individuals will perceive posting a negative fake review about a competitor as more (a) unethical and (b) immoral than posting a positive fake review about the focal service provider.

Hypothesis 2: When asked to post positive fake reviews, powerful (vs. powerless) individuals will be more likely to post a fake review when the incentive is other-benefiting (vs. self-benefiting).

Hypothesis 3: When asked to post negative fake reviews, the interaction effect of power and incentive type on one’s likelihood of posting a fake review will be attenuated.

Research Design

To test our predictions, we conducted three studies. Study 1 was conducted to develop the stimuli and to verify that the two incentive types did not differ in terms of ethicality and morality ratings (hypothesis 1). The purpose of study 2 is to examine if powerful individuals are more inclined to post fake positive reviews when presented with charity incentives, while individuals who lack power tend to post fake reviews when presented with monetary incentives (hypothesis 2). Finally, study 3 investigated the proposed boundary condition of review valence (hypothesis 3).

Study 1

In study 1, several scenarios were tested using a 2 (review valence: positive vs. negative) × 2 (incentive type: monetary vs. charity) between-subjects design describing a situation in which a restaurant manager asked the participant to write a fake review while offering an incentive in return (see Appendix A for a full list of scenarios). In the positive fake review condition, the restaurant manager asked the participant to give the restaurant a five-star rating and write a positive review, while in the negative fake review condition, the manager asked the participant to give a competitor a one-star rating and to post a negative review. The incentive was either a personal gift card or a donation to a local charity.

After reading the scenario, participants rated the requested action by a four-item, 7-point semantic bipolar scale (ethical/unethical, moral/immoral, self-benefiting/other-benefiting, and selfish/altruistic) that was adapted from Dubois, Rucker, and Galinsky (2015).

Analyses and results

One hundred twenty-two participants (48 female; M_age = 33.25, SD = 11.71) recruited from Amazon’s Mechanical Turk were randomly assigned to one of the four conditions. Table 1 presents the means and standard deviations of study 1 results.

Table 1.

Means and Standard Deviations of Study 1.

Experimental Scenario		Moral/Immoral		Ethical/Unethical		Self-Benefiting/Other-Benefiting		Selfish/Altruistic
Valence	Incentive Type	Mean	SD	Mean	SD	Mean	SD	Mean	SD
Positive	Monetary	2.30	1.92	2.53	1.94	2.03	1.56	2.23	1.72
Positive	Charity	2.53	1.63	2.91	1.80	3.31	1.93	3.06	1.88
Negative	Monetary	1.53	1.24	1.63	1.16	1.47	1.02	1.44	1.01
Negative	Charity	2.14	1.80	2.04	1.73	3.43	1.93	3.32	2.04

Note: SD = standard deviation.

We conducted analyses of variance (ANOVAs) with incentive type as a factor and found that in the positive fake review condition, participants in both the monetary and charity incentive conditions perceived the scenario as equally unethical (F[1, 60] = 0.26, p > .60) and equally immoral (F[1, 60] = 0.62, p > .40). However, participants assigned to the monetary incentive condition perceived the scenario as more self-beneficial (F[1, 60] = 8.18, p < .01) and selfish (F[1, 60] = 3.27, p < .08) than those who were assigned to the charity incentive condition.

Similarly, in the negative fake review condition, participants in both the monetary and charity incentive conditions perceived the scenario as equally unethical (F[1, 58] = 2.39, p > .12) and equally immoral (F[1, 58] = 1.19, p > .27). Again, participants assigned to the monetary incentive condition perceived the scenario as more self-beneficial (F[1, 58] = 25.05, p = .000) and selfish (F[1, 58] = 21.35, p = .000) than those who were assigned to the charity incentive condition, verifying that the scenarios differed in terms of beneficiary but not in terms of morality and ethicality ratings.

To test hypothesis 1, we then assigned codes to the review valence (0 = negative, 1 = positive) and ran another one-way ANOVA. The results indicate that participants assigned to the negative fake review condition perceived the review request as more unethical (M_negative = 1.82 vs. M_positive = 2.42; F[1, 120] = 4.03, p < .05) and immoral (M_negative = 1.82 vs. M_positive = 2.73; F[1, 120] = 8.97, p < .01) than their counterparts in the positive fake review condition. These results lend support for hypothesis 1.

Study 2

Participants, procedures, and measures

One hundred nineteen participants were recruited (54 female; M_age = 34.13, SD = 11.18) from Amazon’s Mechanical Turk. The design was a 2 (power: high vs. low) × 2 (incentive type: monetary vs. charity) quasi-experiment. Participants read one of the hypothetical scenarios and then answered questions about their likelihood to post a fake review and about their personal demographics.

Study 2 included two independent variables: in order to manipulate incentive type, we presented each participant with one of the two scenarios (incentive type: monetary vs. charity) developed in study 1. The participants’ power was measured by two items adapted from previous research (Dubois, Rucker, and Galinsky 2010; Rucker and Galinsky 2008). Specifically, we asked participants to indicate the extent to which they felt powerful and in control in everyday life on a 7-point Likert-type scale (1 = powerless, lacking control; 7 = powerful, in control; r = .81, p = .000).

The dependent variable was likelihood of posting a fake review. Participants were asked to respond to three items to determine the extent to which they would engage in posting a fake review adapted from Karmarkar and Tormala (2010). Questions were “Please indicate how much you think you would like to write a review”; “Please indicate how interested you would be in writing a review” (1 = not at all, 9 = very much so); and “Please indicate the probability of writing a review” (1 = very low, 9 = very high) (α = .96).

We controlled for self-importance and dependence on others since previous research has shown that power is correlated with these two constructs (Rucker, Dubois, and Galinsky 2011). We assessed self-importance using two items adapted from Rucker, Dubois, and Galinsky (2011): “How important are you as an individual?” (1 = not important at all, 8 = very important) and “I am a person of worth” (1 = totally disagree, 8 = totally agree) (r = .69, p = .000). We measured dependence on others using two items: “When it comes to getting things done, do you depend more on yourself or others?” (1 = completely on myself, 8 = completely on others); and “How much do you value people’s opinions versus your own when making a decision?” (1 = my opinion matters most, 8 = others’ opinions matter most) (r = .51, p = .000). Moreover, we included a mood measure by asking participants how happy or sad they were feeling at the time of the experiment (1 = sad, 7 = happy). By doing so, we could rule out the alternative mechanism of the effect of mood on one’s intention to engage in unethical behaviors (Cialdini, Darby, and Vincent 1973; Dubois, Rucker, and Galinsky 2015).

Results

To assess each participant’s likelihood of posting a fake review, we measured one’s self-reported sense of power and ran a moderation analysis (Hayes 2013; Model 1) with incentive type as the independent variable, power as the moderator, intention to post a fake review as the dependent variable, and self-importance, dependence on others, and mood as covariates. The result shows a significant main effect for incentive type on posting a fake review (b = −5.67, t[112] = −3.70, p < .001), such that participants were more likely to post fake reviews when presented with monetary (vs. charity) incentives. The main effect for power was insignificant (b = −.27, t[112] = −1.14, p > .25). Yet the interaction effect between power and incentive type is significant (b = 1.04, t[112] = 3.40, p < .001) (see Table 2).

Table 2.

Result of Moderation Test for Likelihood of Posting a Fake Review Using PROCESS (Model 1).

Variable	Coefficient	SE	t	p
Constant	5.80	1.34	4.33	.000
Power	– 0.27	0.24	–1.14	.26
Incentive	–5.67	1.53	–3.70	.000
Incentive × power	1.04	0.31	3.40	.001
Self-importance	–0.36	0.18	–2.02	.05
Dependence on others	0.27	0.16	1.69	.09
Mood	0.29	0.12	2.36	.02

To decompose the interaction, we performed a floodlight analysis using the Johnson-Neyman technique. Floodlight analysis illuminates ranges of values of the continuous variable (X) where the simple effect is significant and where it is not (Spiller et al. 2013). Past research shows that performing a median split results in a substantial loss of statistical power from dichotomizing a continuous independent variable, which potentially leads to spurious results (Fitzsimons 2008; Irwin and McClelland 2001; Spiller et al. 2013). Our results indicate that there is a significant negative effect of incentive type on the likelihood of posting a fake review among participants with a sense of power lower than 4.52 (b_JN = –.95, SE = .48, p = .05), but not for individuals with power higher than 4.52. In other words, low-power individuals were more likely to post a fake review in the monetary incentive condition than in the charity incentive condition. Approximately 58% of participants fell into this category. This interaction is depicted in Figure 2.

Figure 2.

Likelihood of posting a fake review in study 2.

Overall, these results provide partial support for hypothesis 2. Consistent with our predictions, less powerful individuals were more likely to post a fake review when presented with a monetary incentive rather than a charity incentive. Unexpectedly, the incentive type had a minimal impact on powerful individuals’ likelihood to post fake reviews. We argue that this insignificant result can be explained by the fact that high-power individuals tend to have a relatively high propensity to engage in unethical behaviors (Detert, Treviño, and Sweitzer 2008; Piff et al. 2012). Accordingly, the likelihood of writing a fake review was uniformly high among our high-power participants.

Study 3

Participants, procedures, and measures

One hundred eighteen participants were recruited from Amazon’s Mechanical Turk and three individuals were excluded based on the instructional attendance check task (IMC; Oppenheimer, Meyvis, and Davidenko 2009; see Appendix D). The final sample was composed of 115 participants (54 female; M_age = 35.49, SD = 12.50), and they were randomly assigned to one of four conditions in a 2 (power: high vs. low) × 2 (incentive: monetary vs. charity) between-subjects experimental design.

We manipulated power by having participants complete a power recall task (Galinsky, Gruenfeld, and Magee 2003). In the high-power condition, participants were asked to recall and write about a time when they had power over others. In the low-power condition, they were asked to recall and write about a time when they lacked power (see Appendix C). We performed a manipulation check using a single bipolar item measured on a 9-point scale: “The event recall task made me feel powerful (vs.) powerless.” The manipulation for incentive type was identical to study 2, and we used the same dependent variable and control variables as in study 2.

Results

A two-tailed t test on the power manipulation check revealed that high-power participants reported feeling more powerful than low-power participants (M_high-power = 5.78 vs. M_low-power = 4.33; t[113] = −4.33, p = .000). We examined the effect of primed power and incentive type on participants’ intentions to post fake reviews. The results of a two-way ANCOVA showed no main effect of power (F[1, 108] < 1) and incentive type (F[1, 108] < 1). Moreover, the interaction effect of power and incentive type was not significant (F[1, 108] = 1.50, p = .22). The effects of self-importance, dependence on others, and mood were also statistically insignificant (F[1, 108] = 0.04, p = .84; F[1, 108] = 2.71, p = .10; and F[1, 108] = 0.03, p = .87, respectively).

These results support hypothesis 3. Notably, the propensity to post fake reviews among both high- and low-power individuals remained low (i.e., mean scores less than 3.0) across the two incentive conditions. This finding is consistent with study 1 results showing that participants considered writing a negative fake review of a competitor to be more unethical and immoral than writing a positive fake review for the focal service provider.

General Discussion

The main purpose of this research is to identify the effect of incentive type (i.e., self-benefiting vs. other-benefiting) on consumers’ intention to post fake reviews and to determine whether an individual’s sense of power plays a moderating role in that association. The results of study 2 show that powerless individuals are more likely to write fake reviews when presented with monetary (i.e., self-benefiting) incentives than when presented with charity (i.e., other-benefiting) incentives. However, powerful consumers are not influenced by the incentive type and consequently, hypothesis 2 is only partially supported. The results for the powerless are consistent with previous social psychology research stating that individuals with a low sense of power desire to acquire personal benefits (Rixom and Mishra 2014).

The findings of study 3 support hypothesis 3: when asked to post negative fake reviews about a competitor, the joint impact of power and incentive type on an individual’s intention was attenuated. This result is congruent with previous research on WOM and self-enhancement. Previous research has shown that individuals want to be perceived as a “good person,” and therefore, they tend to share things that make them look good (Berger 2014). This evidence suggests that negative fake reviews on third-party platforms are likely to be written by jealous competitors rather than by real customers.

This study makes two theoretical contributions: first, despite the fact that about 25% of reviews posted on Yelp are suspicious (Roberts 2013), the tourism literature is silent on fake reviews. Previous empirical research on the topic is limited to the domain of computer science with a focus on pattern detection (e.g., Ott et al. 2011). However, there is a lack of understanding on what motivates consumers (as opposed to companies) to post fake reviews. We show that monetary (self-benefiting) and charity (other-benefiting) incentives—two prevalent marketing practices—are the main drivers of consumer participation in writing fake reviews.

Second, the study findings reveal that one’s sense of power plays an important role in moderating the relationship between incentive type and consumers’ propensity to post fake reviews. Specifically, powerless individuals are more likely to engage in such unethical behaviors when presented with self-benefiting (vs. other-benefiting) incentives. This finding is incongruent with Dubois, Rucker, and Galinsky’s (2015) results. Focusing on the modality of power (i.e., agentic vs. communal), Dubois, Rucker, and Galinsky (2015) find that high-power individuals tend to engage in unethical behaviors when the behaviors benefit the self, whereas low-power individuals tend to engage in unethical behaviors when the behaviors benefit others. However, their study does not examine situations in which two conflicting ethical principles are involved. In such cases, as in our study, the fundamental modalities are not necessarily applicable. Instead, abstract and concrete mindsets activated by power play a substantial role in an individual’s decision-making processes. Specifically, less powerful people with a concrete mindset focus on helping themselves with a monetary gain, thus justifying their decision to violate an ethical principle.

By examining consumer motivations to post fake reviews, the present study delivers an important message to hospitality and tourism practitioners. It is noteworthy that fake online reviews not only undermine credibility of reviews but also affect consumer choices (Munzel 2016). In turn, these reviews can directly influence business performance (Chevalier and Mayzlin 2006). Hence, it is critical to understand reviewers’ motivation to eradicate fake reviews from online platforms. As such, this research has several practical implications. First, many third-party firms offer reputation management services for hotels and restaurants. Their strategy is to assist their clients by collecting feedback from customers and posting such feedback on online review forums, such as Yelp.com and TripAdvisor.com. A classic way to motivate customers to write reviews is to distribute emails that include monetary incentives, such as gift cards or discount coupons. Although their goal is to obtain genuine evaluations from customers, our findings suggest that this method can unintentionally motivate individuals (especially powerless consumers) to write fake reviews. Furthermore, when a consumer responds to an email request and writes a review, TripAdvisor.com adds the sentence: “Review collected in partnership with this restaurant.”¹ However, such a cue may backfire, because consumers might infer that the review is fake.

Second, as others have suggested (Anderson and Simester 2014; Mayzlin, Dover, and Chevalier 2014), online review forum practitioners might want to follow Expedia.com’s example and allow only verified purchasers to post a review. However, this strategy may lead to inadvertent consequences of reducing the number of reviews (Mayzlin, Dover, and Chevalier 2014).

Finally, even after Amazon’s lawsuit against Fiverr.com, an outsourcing site, there are still some websites with users who advertise “review services” for $5. Our findings suggest that adopting a different incentive method, such as a charity appeal, might prevent users to engage in fake reviews.

Limitations and Future Research

As with any research, the present study is not without limitations. First, it was based on self-reported data, which may or may not accurately describe how individuals act in real-life situations. Thus, future research should develop methods that reflect more realistic situations, for instance, by sending fake review requests to a random sample of participants and recording their responses. Second, past research found that the valence of fake reviews depends on the market situation of a hotel and restaurant. For example, a hotel tends to have more negative fake reviews when located near competitors (Mayzlin, Dover, and Chevalier 2014), and a restaurant whose reputation is less established tends to have more positive fake reviews (Luca and Zervas 2015). However, in our two experiments, such information was missing. Therefore, future research should specify the market situation of a property in a hypothetical scenario. Third, we did not examine linguistic characteristics in fake reviews, which can be an interesting way to detect fake reviews. Thus, future research should investigate the effect of power and incentive type on reviewers’ writing styles in fake reviews.

Footnotes

Appendix A

Appendix B

Appendix C

Appendix D

Declaration of Conflicting Interests

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: The authors thank the Marriott Foundation for the funding of this research.

1.

For details, see TripAdvisor’s official press release, available at .

Author Biographies

Sungwoo Choi is a graduate student at the School of Hospitality management at the Pennsylvania State University. He received his M.S. at the School of Hospitality management at the Pennsylvania State University. His primary research interests focus on social influence and consumer behavior in the hospitality and tourism industry.

Anna S. Mattila, is the Marriott Professor of Lodging Management at the School of Hospitality management at the Pennsylvania State University. She holds a Ph.D. in services marketing from Cornell University. Her research interests focus on service encounters with a particular interest in service recovery, corporate social responsibility, social media and cross-cultural research.

Hubert B. Van Hoof, is a Professor at the Penn State School of Hospitality Management. He holds a Ph.D. in Public Administration with a focus on Tourism Policy Analysis from Arizona State University. His primary areas of research and teaching interest are strategic management and issues in international higher education.

Donna Quadri-Felitti is the Marvin Ashner Director and Associate Professor in the Penn State School of Hospitality Management. She holds a PhD. in Hospitality Management from Iowa State University. Her areas of research interest are consumer experiences in hospitality and destination and digital marketing.

References

Anderson

Berdahl

J. L.

2002. “The Experience of Power: Examining the Effects of Power on Approach and Inhibition Tendencies.” Journal of Personality and Social Psychology 83 (6): 1362–77.

Anderson

Galinsky

A. D.

2006. “Power, Optimism, and Risk-taking.” European Journal of Social Psychology 36:511–36.

Anderson

E. T.

Simester

D. I.

2014. “Reviews without a Purchase: Low Ratings, Loyal Customers, and Deception.” Journal of Marketing Research 51 (3): 249–69.

Ayeh

J. K.

Law

2013. “‘Do We Believe in TripAdvisor?’ Examining Credibility Perceptions and Online Travelers’ Attitude toward Using User-Generated Content.” Journal of Travel Research 52 (4): 437–52.

Bakan

1966. The Duality of Human Existence: Isolation and Communion in Western Man. Boston, MA: Beacon Press.

Barkan

Ayal

Gino

Ariely

2012. “The Pot Calling the Kettle Black: Distancing Response to Ethical Dissonance.” Journal of Experimental Psychology: General 141 (4): 757–73.

Berger

2014. “Word of Mouth and Interpersonal Communication: A Review and Directions for Future Research.” Journal of Consumer Psychology 24 (4): 586–607.

Bronner

de Hoog

2010. “Vacationers and eWOM: Who Posts, and Why, Where, and What?” Journal of Travel Research 50 (1): 15–26.

Brush

Jesse

. 2007. “Does Income Inequality Lead to More Crime? A Comparison of Cross-sectional and Time-Series Analyses of United States Counties.” Economics Letters 96 (2): 264–68.

10.

Carney

D. R.

Cuddy

A. J.

Yap

A. J.

2010. “Power Posing Brief Nonverbal Displays Affect Neuroendocrine Levels and Risk Tolerance.” Psychological Science 21 (10): 1363–68.

11.

Chang

C. T.

2008. “To Donate or Not to Donate? Product Characteristics and Framing Effects of Cause-Related Marketing on Consumer Purchase Behavior.” Psychology and Marketing 25 (12): 1089–1110.

12.

Chen

Lee-Chai

A. Y.

Bargh

J. A.

2001. “Relationship Orientation as a Moderator of the Effects of Social Power.” Journal of Personality and Social Psychology 80 (2): 173–87.

13.

Chevalier

Mayzlin

2006. “The Effect of Word of Mouth on Sales: Online Book Reviews.” Journal of Marketing Research 43 (3): 345–54.

14.

Chiou

W. B.

Wan

P. H.

Wan

C. S.

2012. “A New Look at Software Piracy: Soft Lifting Primes an Inauthentic Sense of Self, Prompting Further Unethical Behavior.” International Journal of Human-Computer Studies 70 (2): 107–15.

15.

Choi

Mattila

A. S.

2016. “The Effects of Other Customers’ Dress Style on Customers’ Approach Behaviors: The Moderating Role of Sense of Power.” Cornell Hospitality Quarterly 57 (2): 211–18.

16.

Cialdini

R. B.

Darby

B. L.

Vincent

J. E.

1973. “Transgression and Altruism: A Case for Hedonism.” Journal of Experimental Social Psychology 9 (6): 502–16.

17.

DeCelles

K. A.

DeRue

D. S.

Margolis

J. D.

Ceranic

T. L.

2012. “Does Power Corrupt or Enable? When and Why Power Facilitates Self-Interested Behavior.” Journal of Applied Psychology 97 (3): 681–89.

18.

Detert

J. R.

Treviño

L. K.

Sweitzer

V. L.

2008. “Moral Disengagement in Ethical Decision Making: A Study of Antecedents and Outcomes.” Journal of Applied Psychology 93 (2): 374–91.

19.

Ditto

P. H.

Liu

2011. “Deontological Dissonance and the Consequentialist Crutch.” In The Social Psychology of Morality: Exploring the Causes of Good and Evil, edited by Mikulincer

Shaver

P. R.

, 51–70. Washington, DC: American Psychological Association.

20.

Dubois

Rucker

D. D.

Galinsky

A. D.

2010. “The Accentuation Bias: Money Literally Looms Larger (and Sometimes Smaller) to the Powerless.” Social Psychological and Personality Science 1 (3): 199–205.

21.

Dubois

Rucker

D. D.

Galinsky

A. D.

2015. “Social Class, Power, and Selfishness: When and Why Upper and Lower Class Individuals Behave Unethically.” Journal of Personality and Social Psychology 108 (3): 436–49.

22.

Eisenberger

Rhoades

2001. “Incremental Effects of Reward on Creativity.” Journal of Personality and Social Psychology 81 (4): 728–41.

23.

Eyal

Tal

Liberman

Nira

. 2012. “Morality and Psychological Distance: A Construal Level Theory Perspective.” In The Social Psychology of Morality: Exploring the Causes of Good and Evil, edited by Mikulincer

Shaver

P. R.

, 185–202. Washington, DC: American Psychological Association.

24.

Eyal

Liberman

Trope

2008. “Judging Near and Distant Virtue and Vice.” Journal of Experimental Social Psychology 44 (4): 1204–9.

25.

Federal Trade Commission. 2015. “The FTC’s Endorsement Guides: What People Are Asking.” https://www.ftc.gov/tips-advice/business-center/guidance/ftcs-endorsement-guides-what-people-are-asking (accessed December 13, 2015).

26.

Filieri

McLeay

2014. “E-WOM and Accommodation: An Analysis of the Factors That Influence Travelers’ Adoption of Information from Online Reviews.” Journal of Travel Research 53 (1): 44–57.

27.

Fischbacher

Föllmi-Heusi

2013. “Lies in Disguise—An Experimental Study on Cheating.” Journal of the European Economic Association 11 (3): 525–47.

28.

Fitzsimons

G. J.

2008. “Editorial: Death to Dichotomizing.” Journal of Consumer Research 35 (1): 5–8.

29.

French

J. R.

Raven

1959. “The Bases of Social Power.” In Studies in Social Power, edited by Cartwright

, 150–67. Ann Arbor: University of Michigan Press.

30.

Galinsky

A. D.

Gruenfeld

D. H.

Magee

J. C.

2003. “From Power to Action.” Journal of Personality and Social Psychology 85 (3): 453–66.

31.

Garbinsky

E. N.

Klesse

A. K.

Aaker

2014. “Money in the Bank: Feeling Powerful Increases Saving.” Journal of Consumer Research 41 (3): 610–23.

32.

Gretzel

Yoo

K. H.

2008. “Use and Impact of Online Travel Reviews.” In Information and Communication Technologies in Tourism, edited by O’Connor

Hopken

Gretzel

, 35–46. Vienna: Springer.

33.

Gruen

T. W.

Osmonbekov

Czaplewski

A. J.

2006. “eWOM: The Impact of Customer-to-Customer Online Know-How Exchange on Customer Value and Loyalty.” Journal of Business Research 59 (4): 449–56.

34.

Hancock

2007. “Digital Deception.” In Oxford Handbook of Internet Psychology, edited by Joinson

Adam

McKenna

Katelyn

Postmes

Tom

, 289–301. Oxford: Oxford University Press.

35.

Harmon

2004. “Amazon Glitch Unmasks War of Reviewers.” The New York Times, February 14. http://www.nytimes.com/2004/02/14/us/amazon-glitch-unmasks-war-of-reviewers.html?_r=0.

36.

Hayes

A.F.

2013. Introduction to mediation, moderation, and conditional process analysis: A regression-based approach. Guilford Press.

37.

Hennig-Thurau

Walsh

2003. “Electronic Word-of-Mouth: Motives for and Consequences of Reading Customer Articulations on the Internet.” International Journal of Electronic Commerce 8:51–74.

38.

Hennig-Thurau

Gwinner

K. P.

Walsh

Gremler

D. D.

2004. “Electronic Word-of-Mouth via Consumer Opinion Platforms: What Motivates Consumers to Articulate Themselves on the Internet?” Journal of Interactive Marketing 18:38–52.

39.

Bose

Koh

N. S.

Liu

2012. “Manipulation of Online Reviews: An Analysis of Ratings, Readability, and Sentiments.” Decision Support Systems 52 (3): 674–84.

40.

Irwin

J. R.

McClelland

G. H.

2001. “Misleading Heuristics and Moderated Multiple Regression Models.” Journal of Marketing Research 38 (1): 100–9.

41.

Iyer

E. S.

Kashyap

R. K.

2007. “Consumer Recycling: Role of Incentives, Information, and Social Class.” Journal of Consumer Behaviour 6 (1): 32–47.

42.

Jin

Huang

2014. “When Giving Money Does Not Work: The Differential Effects of Monetary versus In-kind Rewards in Referral Reward Programs.” International Journal of Research in Marketing 31 (1): 107–16.

43.

Jones

T. M.

1991. “Ethical Decision Making by Individuals in Organizations: An Issue-Contingent Model.” Academy of Management Review 16 (2): 366–95.

44.

Karmarkar

U. R.

Tormala

Z. L.

2010. “Believe Me, I Have No Idea What I’m Talking About: The Effects of Source Certainty on Consumer Involvement and Persuasion.” Journal of Consumer Research 36 (6): 1033–49.

45.

Keltner

Gruenfeld

D. H.

Anderson

2003. “Power, Approach, and Inhibition.” Psychological Review 110 (2): 265–84.

46.

Kim

E. E. K.

Mattila

A. S.

Baloglu

2011. “Effects of Gender and Expertise on Consumers’ Motivation to Read Online Hotel Reviews.” Cornell Hospitality Quarterly 52 (4): 399–406.

47.

Kivetz

Tyler

T. R.

2007. “Tomorrow I’ll Be Me: The Effect of Time Perspective on the Activation of Idealistic versus Pragmatic Selves.” Organizational Behavior and Human Decision Processes 102 (2): 193–211.

48.

Kraus

M. W.

Piff

P. K.

Keltner

2009. “Social Class, Sense of Control, and Social Explanation.” Journal of Personality and Social Psychology 97 (6): 992–1004.

49.

Lammers

Galinsky

A. D.

Dubois

Rucker

D. D.

2015. “Power and Morality.” Current Opinion in Psychology 6:15–19.

50.

Lee

Tiedens

L. Z.

2001. “Is It Lonely at the Top? The Independence and Interdependence of Power Holders.” Research in Organizational Behavior 23:43–91.

51.

Liu

Park

2015. “What Makes a Useful Online Review? Implication for Travel Product Websites.” Tourism Management 47:140–51.

52.

L. C.

Chang

H. H.

S. T.

2013. “Online Shoppers’ Perceptions of E-retailers’ Ethics, Cultural Orientation, and Loyalty.” Internet Research 23 (1): 47–68.

53.

Luca

Michael

Zervas

Georgios

. 2015. “Fake It till You Make It: Reputation, Competition, and Yelp Review Fraud.” Harvard Business School NOM Unit Working Paper 14-006.

54.

Mayzlin

2006. “Promotional Chat on the Internet.” Marketing Science 25 (2): 155–63.

55.

Mayzlin

Dover

Chevalier

2014. “Promotional Reviews: An Empirical Investigation of Online Review Manipulation.” American Economic Review 104 (8): 2421–55.

56.

Mourali

Nagpal

2013. “The Powerful Select, the Powerless Reject: Power’s Influence in Decision Strategies.” Journal of Business Research 66 (7): 874–80.

57.

Mukherjee

Arjun

Liu

Bing

Glance

Natalie

. 2012. “Spotting Fake Reviewer Groups in Consumer Reviews.” In Proceedings of the 21st international Conference on World Wide Web, 191–200. ACM.

58.

Munzel

2016. “Assisting Consumers in Detecting Fake Reviews: The Role of Identity Information Disclosure and Consensus.” Journal of Retailing and Consumer Services 32:96–108.

59.

Murray

K. B.

1991. “A Test of Services Marketing Theory: Consumer Information Acquisition Activities.” Journal of Marketing 55:10–25.

60.

Nicole

K. F.

Stefan

I. V.

Hoyer

W. D.

2012. “Willingness to Pay for Cause-Related Marketing: The Impact of Donation Amount and Moderating Effects.” Journal of Marketing Research 49 (6): 910–27.

61.

Oppenheimer

D. M.

Meyvis

Davidenko

2009. “Instructional Manipulation Checks: Detecting Satisficing to Increase Statistical Power.” Journal of Experimental Social Psychology 45 (4): 867–72.

62.

Ott

Choi

Cardie

Hancock

J. T.

2011. “Finding Deceptive Opinion Spam by any Stretch of the Imagination.” In Proceedings of the 49th Annual Meeting of the Association for Computational Linguistics: Human Language Technologies, Vol. 1, Long Papers, 309–19. Stroudsburg, PA: Association for Computational Linguistics.

63.

Park

Lee

T. M.

2009. “Information Direction, Website Reputation and eWOM Effect: A Moderating Role of Product Type.” Journal of Business Research 62 (1): 61–67.

64.

Peterson

S. J.

Luthans

2006. “The Impact of Financial and Nonfinancial Incentives on Business-Unit Outcomes over Time.” Journal of Applied Psychology 91 (1): 156–65.

65.

Phillips

Zigan

Silva

M. M. S.

Schegg

2015. “The Interactive Effects of Online Reviews on the Determinants of Swiss Hotel Performance: A Neural Network Analysis.” Tourism Management 50:130–41.

66.

Piff

P. K.

Kraus

M. W.

Côté

Cheng

B. H.

Keltner

2010. “Having Less, Giving More: The Influence of Social Class on Prosocial Behavior.” Journal of Personality and Social Psychology 99 (5): 771–84.

67.

Piff

P. K.

Stancato

D. M.

Cote

Mendoza-Denton

Keltner

2012. “Higher Social Class Predicts Increased Unethical Behavior.” Proceedings of National Academy of Sciences 109 (11): 4086–91.

68.

Ring

Tkaczynski

Dolnicar

2016. “Word-of-Mouth Segments Online, Offline, Visual or Verbal?” Journal of Travel Research 55 (4): 481–92.

69.

Rixom

Mishra

2014. “Ethical Ends: Effect of Abstract Mindsets in Ethical Decisions for the Greater Social Good.” Organizational Behavior and Human Decision Processes 124 (2): 110–21.

70.

Roberts

2013. “Yelp’s Fake Review Problem.” Fortune, September 26. http://tech.fortune.cnn.com/2013/09/26/yelps-fake-review-problem/.

71.

Rucker

D. D.

Dubois

Galinsky

A. D.

2011. “Generous Paupers and Stingy Princes: Power Drives Consumer Spending on Self versus Others.” Journal of Consumer Research 37 (6): 1015–29.

72.

Rucker

D. D.

Galinsky

A. D.

2008. “Desire to Acquire: Powerlessness and Compensatory Consumption.” Journal of Consumer Research 35 (2): 257–67.

73.

Rucker

D. D.

Galinsky

A. D.

2009. “Conspicuous Consumption versus Utilitarian Ideals: How Different Levels of Power Shape Consumer Behavior.” Journal of Experimental Social Psychology 45 (3): 549–55.

74.

Rucker

D. D.

Galinsky

A. D.

Dubois

2012. “Power and Consumer Behavior: How Power Shapes Who and What Consumers Value.” Journal of Consumer Psychology 22 (3): 352–68.

75.

Shalvi

Gino

Barkan

Ayal

2015. “Self-Serving Justifications: Doing Wrong and Feeling Moral.” Current Directions in Psychological Science 24 (2): 125–30.

76.

Simonson

2016. “Imperfect Progress: An Objective Quality Assessment of the Role of User Reviews in Consumer Decision Making, A Commentary on de Langhe, Fernbach, and Lichtenstein.” Journal of Consumer Research 42 (6): 840–45.

77.

Smith

P. K.

Trope

2006. “You Focus on the Forest When You’re in Charge of the Trees: Power Priming and Abstract Information Processing.” Journal of Personality and Social Psychology 90 (4): 578–96.

78.

Sparks

B. A.

Browning

2011. “The Impact of Online Reviews on Hotel Booking Intentions and Perception of Trust.” Tourism Management 32 (6): 1310–23.

79.

Sparks

B. A.

K. K. F.

Bradley

G. L.

2016. “Responding to Negative Online Reviews: The Effects of Hotel Responses on Customer Inferences of Trust and Concern.” Tourism Management 53:74–85.

80.

Spiller

S. A.

Fitzsimons

G. J.

Lynch

J. G.

Jr. McClelland

G. H.

2013. “Spotlights, Floodlights, and the Magic Number Zero: Simple Effects Tests in Moderated Regression.” Journal of Marketing Research 50 (2): 277–88.

81.

Stajkovic

A. D.

Luthans

2003. “Behavioral Management and Task Performance in Organizations: Conceptual Background, Meta-Analysis, and Test of Alternative Models.” Personnel Psychology 56 (1): 155–94.

82.

Strahilevitz

Myers

J. G.

1998. “Donation to Charity as Purchase Incentives: How Well They Work May Depend on What You Are Trying to Sell.” Journal of Consumer Research 24:434–47.

83.

Trope

Liberman

2003. “Temporal Construal.” Psychological Review 110 (3): 403–21.

84.

Trusov

Bucklin

R. E.

Pauwels

2009. “Effects of Word-of-Mouth versus Traditional Marketing: Findings from an Internet Social Networking Site.” Journal of Marketing 73:90–102.

85.

Vermeulen

I. E.

Seegers

2009. “Tried and Tested: The Impact of Online Hotel Reviews on Consumer Consideration.” Tourism Management 30 (1): 123–27.

86.

Vitell

S. J.

2003. “Consumer Ethics Research: Review, Synthesis and Suggestions for the Future.” Journal of Business Ethics 43:33–47.

87.

Wei

Miao

Huang

Z. J.

2013. “Customer Engagement Behaviors and Hotel Responses.” International Journal of Hospitality Management 33:316–30.

88.

Winterich

K. P.

Mittal

Morales

A. C.

2014. “Protect Thyself: How Affective Self-Protection Increases Self-Interested, Unethical Behavior.” Organizational Behavior and Human Decision Processes 125 (2): 151–61.

89.

Wirtz

Chew

2002. “The Effects of Incentives, Deal Proneness, Satisfaction and Tie Strength on Word-of-Mouth Behaviour.” International Journal of Service Industry Management 13 (2): 141–62.

90.

Mattila

A. S.

Wang

C. Y.

Hanks

2016. “The Impact of Power on Service Customers’ Willingness to Post Online Reviews.” Journal of Service Research 19 (2): 224–38.

91.

Xie

H. J.

Miao

Kuo

P. J.

Lee

B. Y.

2011. “Consumers’ Responses to Ambivalent Online Hotel Reviews: The Role of Perceived Source Credibility and Pre-decisional Disposition.” International Journal of Hospitality Management 30 (1): 178–83.

92.

Xie

Zhou

Sedikides

Vohs

K. D.

2014. “Money, Moral Transgressions, and Blame.” Journal of Consumer Psychology 24 (3): 299–306.

93.

Yap

A. J.

Wazlawek

A. S.

Lucas

B. J.

Cuddy

A. J. C.

Carney

D. R.

2013. “The Ergonomics of Dishonesty: The Effect of Incidental Posture on Stealing, Cheating, and Traffic Violations.” Psychological Science 24 (11): 2281–89.

94.

Law

2009. “The Impact of Online User Reviews on Hotel Room Sales.” International Journal of Hospitality Management 28 (1): 180–82.

95.

Yoo

K. H.

Gretzel

2009. “Comparison of Deceptive and Truthful Travel Reviews.” In: Information and Communication Technologies in Tourism 2009: Proceedings of the International Conference in Amsterdam, The Netherlands, 2009, edited by Höpken

Wolfram

Gretzel

Ulrike

Law

Rob

, 37–47. Vienna: Springer.

96.

Zeithaml

V. A.

Bitner

B. J.

Gremler

D. D.

2012. Services Marketing: Integrating Customer Focus across the Firm, 6th ed. New York: McGraw-Hill.

97.

Zhang

Hanks

2015. “Unearned Preferential Treatment: The Moderating Role of Power.” Cornell Hospitality Quarterly 56 (3): 309–19.

98.

Zhang

Mattila

A. S.

2014. “Online Reviews: The Role of Information Load and Peripheral Factors.” Journal of Travel Research 55 (3): 299–310.

99.

Zhang

Yang

2016. “The Power of Expert Identity: How Website-Recognized Expert Reviews Influence Travelers’ Online Rating Behavior.” Tourism Management 55:15–24.