Responding to illegitimate negative reviews: how defensive responses affect purchase intentions

Nearly 64% of customers consult Google reviews before visiting a business (ReviewTrackers, 2022), with over 90% reading at least one review before making a purchase (van Gelder, 2023). The public and permanent nature of online reviews presents a double-edged sword for service providers. Whereas positive reviews can enhance a service firm’s image and attract new customers, negative ones can undermine the company’s credibility and deter future customers (Ye et al., 2009). According to Hinckley (2015), one bad review drives 22% of customers away, with this number rising to 60% following three negative reviews.

A growing concern for businesses is the rise of illegitimate negative reviews – misleading or false feedback from individuals who never actually encountered a service failure. Illegitimate reviews can take various forms, including fake or intentionally misleading claims. While the exact proportion of illegitimate reviews in the real world is difficult to quantify, research suggests that 15%–30% of online reviews may be fake (Lappas et al., 2016; Luca and Zervas, 2016; Ubarall, 2021). Over eighty percent of consumers report encountering a fake review in the past year with more than a quarter admitting they have been misled by one (Paget, 2025; Frichou and Russell, 2021). Additionally, platforms such as Google, Yelp, TripAdvisor and Facebook allow reviews from unverified customers, further increasing the risk of inaccuracies or misrepresentations. Fake or misleading reviews can lead consumers to overpay by as much as 12% (Akesson et al., 2023) and a single false negative review can reduce purchase likelihood by over 40% (Chevalier and Mayzlin, 2006). In response to these fraudulent reviews, some businesses have pursued legal action to sue for damages resulting from false or misleading reviews. For example, Footprints Floors sued a couple in 2015 for a negative Yelp review alleged to have cost the company $625,000 in lost business (Hanley Law, 2024).

A negative review contains feedback that expresses dissatisfaction or criticizes a product or service, usually with unfavorable ratings or terminology. Traditionally, service providers have been advised to respond to negative reviews by admitting wrongdoing and making amends, regardless of the review’s legitimacy (Béal and Grégoire, 2022; Van Vaerenbergh et al., 2019; Kim and Baker, 2020). However, negative reviews can have detrimental impacts on a business’s image and bottom line. Thus, as awareness of customer fallibility grows, many service firms have adopted a more defensive approach by publicly challenging false claims. For example, a hotel responded to a guest’s complaint about not being placed in a ground-floor room, by stating, “We have NO ground floor rooms” (TripAdvisor, 2019). Similarly, a piercing studio owner went viral for publicly responding to a one-star review by explaining the situation and defending the studio’s protocols. The response resonated with online audiences who supported the firm’s defensive stance with comments such as “I actually kinda like this part […] where the business claps back […]” and “companies should be able to leave reviews for reviewers” (Damjan, 2022).

These examples underscore the tension businesses face in managing their brand online while navigating the complexities of illegitimate negative reviews. As consumer perception increasingly hinges on online feedback, understanding the implications of defensive response strategies is critical for businesses seeking to protect their credibility and financial well-being. Consequently, this research examines how defensive responses to illegitimate negative reviews influence consumer perceptions and purchase intentions. A defensive response strategy entails denying responsibility for a negative incident and attributing blame to another party (Chang et al., 2015; Lee and Song, 2010).

Although there are various types of defensive responses, such as justifications, excuses or counterattacks (Coombs, 2007), we concentrate on the “callout” strategy, where the service provider challenges illegitimate claims in a negative review. The growing prominence of these responses in public discourse and their appeal to outside observers, especially on social media and review sites, make our study timely and noteworthy. “Callouts” strike a balance between defending the service firm and upholding transparency by highlighting facts and correcting misinformation. Conversely, other defensive strategies like justifications or shifting blame to external factors may appear evasive and lack the clarity necessary to change perceptions of third-party observers.

Our study explores three key questions:

We argue that when a firm ignores the complaint or apologizes to the reviewer, readers perceive the complaint as legitimate. It is only when the firm demonstrates that the review is illegitimate that the reviewer’s credibility comes into question. Thus, by “calling out” the reviewer, the firm triggers an evaluative process that manifests in a shifting of blame, which influences credibility judgments and purchase intentions.

Grounded in attribution and appraisal frameworks, this research extends the discourse on online impression management. While prior studies primarily emphasize accommodative strategies, we highlight the effectiveness of defensive approaches in service recovery. This research makes a significant contribution to the field of service marketing by examining the issue of illegitimate negative reviews, which is a unique and often overlooked challenge. As online platforms continue to shape the service landscape, the credibility of user-generated content – and how companies respond to it – has become a vital factor for effective service management, building consumer trust and safeguarding a brand’s credibility. This paves the way for deeper insights into customer behaviors and the authenticity of firms. Our findings offer practical solutions for service firms to address illegitimate negative reviews, along with providing important theoretical implications.

Online reviews are strong indicators of both subjective (e.g., purchase intentions) and objective (e.g., sales) measures of service and firm performance (Bansal and Voyer, 2000; Chevalier and Mayzlin, 2006). Though many firms encourage customers to leave positive reviews and reward them for doing so (Poch and Martin, 2015; Zhang et al., 2023), it may be more important to avoid negative reviews due to their detrimental effects (Hinckley, 2015; Ye et al., 2009).

For service providers, negative reviews present a unique opportunity for service recovery. A timely and strategic response not only demonstrates a service firm’s commitment to customer satisfaction but also helps to minimize damage caused by unfavorable reviews (Azer and Alexander, 2020; Weitzl and Hutzinger, 2017). Additionally, effectively managing customer feedback requires distinguishing between legitimate and illegitimate complaints. Firms must monitor the validity of negative reviews to ensure that valuable resources are directed toward addressing genuine service issues rather than misleading or bogus claims (Noble et al., 2012).

To better understand how firm response strategies have been categorized, we examined service recovery typologies, particularly those related to online reviews (see Supplementary Material 1 for a glossary of terms and definitions). The literature identifies three primary response strategies: accommodative, defensive and passive. An accommodative response involves acknowledging the problem and accepting responsibility, often through an apology (Coombs, 1998; Weitzl, 2019). In contrast, a defensive response denies responsibility for the issue and shifts blame to the complainant or external factors (Coombs, 1998; Lee and Cranage, 2014; Weitzl, 2019). A passive response entails minimal engagement, such as ignoring the complaint or providing a generic acknowledging without taking corrective actions (Lee and Song, 2010; Weitzl and Hutzinger, 2017).

In the present research, we focus on a specific subset of company response strategies: no response (i.e., a passive approach), apology (i.e., an accommodative approach) and “callout” (i.e., a defensive approach). The concept of defensive responses has evolved significantly within the marketing and crisis communication literature. Coombs (2006, 2007) laid the foundation by introducing a framework that includes denial of responsibility (i.e., denial), direct confrontation (i.e., attacking the accuser) and shifting blame (i.e., scapegoating), as well as diminishing responses such as claiming limited control over the incident (i.e., excuse) or minimizing the perceived harm (i.e., justification). More recent research has consolidated these tactics under the broader term “defensive responses,” which have been defined in various ways, including: “Denying responsibility for the negative event, taking an attack on the accuser, and shifting blame to others” (Lee and Song, 2010, p. 1076); “Insisting there is no problem, claiming that the company has no responsibility for a problem, accusing the complainer, and even shifting the blame to others” (Chang et al., 2015, p. 49); “Reject responsibility and include indicators such as denial, doubts, excuses, trivializing, or accusations” (Johnen and Schnittka, 2019, p. 858); and “Denial of the company’s responsibility, an attack on the complainant, or a shift of blame to the complainant or third parties” (Weitzl and Hutzinger, 2017, p. 165).

In our study, we specifically examine the “callout” strategy, a direct and transparent form of defensive response that actively refutes false information while addressing the reviewer’s claims, making it a particularly relevant tactic for firms navigating illegitimate negative reviews on online platforms. We investigate the callout strategy as it reasserts control over the narrative while simultaneously protecting the firm’s image. When the validity of the review itself is questioned, other defensive responses like vague denials or justifications may lack the clarity and assertiveness needed to regain the trust of third-party observers (Coombs, 2007). By pointing out false statements, service firms can initiate the process of assigning blame and evaluating credibility – two processes that are essential to how third-party observers form judgment about the reviewer and the service firm.

The situational crisis communication literature provides a valuable framework for understanding how firms should respond to service failures in terms of perceived responsibility (Coombs, 2006). This framework suggests that greater perceived responsibility of a firm elicits more negative customer reactions (Coombs and Holladay, 2008). However, firms can mitigate these reactions by strategically managing their level of accountability (Racine et al., 2020).

Traditionally, the service failure and recovery literature has emphasized accommodative responses, reflecting the long-standing “customer is king” mindset, which assumes customers can do no wrong. However, as consumers become more aware of situations where service providers and employees face unfair treatment from customers, this perspective has evolved (Kim and Baker, 2020). Growing recognition that customers are not infallible suggests that service providers must reconsider taking the accommodative route, particularly in cases where a negative review is illegitimate. Therefore, this paper focuses on the effectiveness of a defensive response strategy, specifically the practice of “calling out” illegitimacies in negative reviews.

ReviewTrackers (2022) reports that more than 50% of consumers expect businesses to address negative reviews within a week, with 33% anticipating an even swifter response. Remarkably, 96% of consumers read firm responses to online reviews (Murphy, 2020) and companies are judged more favorably when they respond (Sparks et al., 2016). Therefore, it is critical for service firms to adopt an effective response strategy to address negative reviews posted online. However, companies must consider their level of liability when responding (Coombs, 2007; Einwiller and Steilen, 2015).

An accommodative response (e.g., an apology) is appropriate when the firm is responsible and is willing to accept blame for the adverse event (Kim et al., 2006; Lee and Cranage, 2014; Luong et al., 2021). Yet, in situations where an individual has not actually encountered a service failure as claimed, using an accommodative strategy may (incorrectly) reinforce that the firm is to blame, possibly harming the firm. In such cases, an alternative strategy – what we refer to as a “callout” – may be more effective. A callout is a type of defensive response in which the firm refutes the complaint and provides clarifying evidence that contradicts the reviewer’s claim. In other words, this type of response clarifies that the firm is not at fault for the negative incident described by the reviewer. Nevertheless, executing a successful defensive strategy that alters perceptions of blame can be challenging.

The impact of service recovery extends beyond the focal customer to include observers of the service encounter, including those in virtual settings (Hogreve et al., 2019). Prior research has found that bystanders (i.e., third-party observers) may experience anger when they see other customers being treated unfairly (Mulcahy et al., 2023). Thus, a firm response that corrects an illegitimate negative review has the potential to affect observers of the service encounter (Hogreve et al., 2019). Despite the growing prevalence of online reviews and firm responses, little is known about how these communications shape third-party observer perceptions. In this paper, we examine the perceptions of third-party observers, particularly the readers of reviews who are considering patronizing a company.

Unlike accommodative strategies that prioritize the complainant’s interests, defensive strategies prioritize the service provider’s interests (Lee and Song, 2010). Though the effectiveness of defensive strategies is mixed (see Table 1), research has generally found them to be detrimental to firms (see Chang et al., 2015; Einwiller and Steilen, 2015; Lee and Song, 2010). However, several studies challenge this contention. For instance, Lopes et al. (2024) found that a defensive strategy increased hotel bookings and Lee and Cranage (2014) found defensive responses yield better outcomes when a negative review is baseless. Similarly, Li et al. (2018) found that defensive responses are more effective following a generic negative review than one citing a product failure and Johnen and Schnittka (2019) found that a defensive response works well when the complaint lacks reasoning. These studies suggest that defensive strategies can be effective and warrant further investigation.

Our research builds on these findings by exploring the specific mechanisms through which defensive responses influence the perceptions of third-party observers, namely, the appraisal of blame. We examine how a defensive response, particularly one that calls out an illegitimate review, impacts evaluations of blame and its downstream effects on consumer perceptions and intentions. We explore conditions under which defensive strategies benefit firms (Lopes et al., 2023) by focusing on how shifting blame from the service firm to the reviewer impacts the legitimacy of the review. Additionally, we examine the effects of verbal aggression in a firm’s defensive response, a factor that has received limited attention. Our findings shed light on the conflicting results in prior research and contribute to the literature by examining the role of blame in the review evaluation process from the perspective of the reader. Finally, we extend the work of Johnen and Schnittka (2019) and others by examining:

• how a firm’s response to an illegitimate negative review affects a potential customer’s blame appraisals;

• how these appraisals affect attitudes and intentions; and

• how service firms can strategically respond to illegitimate negative reviews to shift blame, leading to increased purchase intentions.

The conceptual model that guides our research is presented in Figure 1.

Consumer reactions to online reviews are heavily influenced by how companies choose to respond. When businesses opt for a defensive approach – like contesting misleading or outright false reviews – they are not only safeguarding their brand image but are also shaping how third-party observers perceive their trustworthiness and responsibility (Sparks and Bradley, 2017; Weiner, 2000). In contrast to more passive methods, such as ignoring the complaint or providing a generic apology, addressing an illegitimate negative review directly acts as a strong rebuttal against misinformation and emphasizes the firm’s commitment to fairness and transparency. Previous studies indicate that assertive, yet fair responses can lessen damage to a company’s image by demonstrating that the business is unwilling to sit back and accept unfair criticism (Einwiller and Steilen, 2015). Through a callout strategy, firms can refute illegitimate claims, reassign blame and position themselves as transparent and credible, leading to a higher likelihood of purchases among third-party observers.

Cognitive appraisal and attribution theories emphasize the processes involved in interpreting and responding to events. Together, these theories provide insights into how individuals make sense of their experiences and make decisions based on their interpretations of events. In service contexts, cognitive appraisal theory posits that customers assess various elements of their service experience leading to satisfaction or dissatisfaction (Dalakas, 2006). When expectations are unmet, a service failure occurs (Hoffman and Bateson, 1997). In such cases, customers engage in a sensemaking process to determine the cause and the likelihood of reoccurrence (Van Vaerenbergh et al., 2014). This process is not limited to direct service encounters but extends to indirect evaluations such as online reviews where customers assess feedback to inform their purchase decisions (Folkman et al., 1986).

If a negative review is deemed credible, customers are likely to form unfavorable perceptions of the service provider. A firm’s response to such a review can either reinforce or challenge these perceptions (Lee and Cranage, 2014). A lack of response may signal avoidance and reinforce this negative perception (Coombs, 1995) while an apology may cement the assigned fault (Kim et al., 2006). A defensive response, on the other hand, can provide additional context to reshape the review reader’s perception and redirect blame to the reviewer.

In summary, when service providers face allegations of wrongdoing, their subsequent actions are scrutinized by external audiences who attempt to make sense of the situation (Roulet and Pichler, 2020). This attention provides firms with an opportunity to strategically address and clarify any attributional ambiguity, defending themselves against illegitimate accusations. We argue that third-party observers play a critical role in this process because they are active evaluators who use firm responses as cues to infer blame and credibility. Thus, we propose that a defensive response strategy will yield more favorable third-party purchase intentions (i.e., that of the reader of the review) than an accommodative or passive response. More formally:

According to attribution theory (Weiner, 2000), third-party observers assess blame based on the response provided by a firm, with stronger, more assertive responses deflecting blame away from the firm and toward the reviewer (Lee and Song, 2010). A blame game often arises when firms are accused of wrongdoing, prompting external audiences to evaluate responsibility (Roulet and Pichler, 2020). The assignment of blame is shaped by the discourse that follows. In the context of negative reviews, firms can strategically respond to the complaint to influence the readers’ perception. Passive responses, such as ignoring complaints, are generally viewed unfavorably as they signal a lack of empathy and imply the firm does not take the concern seriously (Lee and Cranage, 2014; Lee and Song, 2010; Li et al., 2018). Hence, we argue that passive responses (e.g., ignoring the complaint) create an ambiguous situation, causing readers to side with the reviewer and blame the firm.

Conversely, accommodative responses, like apologies, reduce ambiguity by acknowledging fault, which can enhance the credibility of the review and foster favorable perceptions of the reviewer. However, when firms adopt a defensive response, such as a callout, they present evidence that shifts blame from the service firm to the reviewer. This reassignment of blame can improve third-party observers’ perception of the service provider and increase their purchase intentions.

Blame plays a crucial role in the evaluation of online reviews and can affect downstream cognitions and behaviors. Credibility, defined as the degree to which someone or something is considered trustworthy or believable, is a critical factor when evaluating a review (Weitzl and Hutzinger, 2017). Indeed, reviewer credibility influences an observer’s trust in a review (Chang et al., 2015) and is a strong driver of attitudinal changes (Yusuf et al., 2018; Weitzl and Hutzinger, 2017). Credibility has been shown to increase consumer trust and suppress skepticism regarding online complaints (Kim and Song, 2016). Past research indicates that standing up to an unfair critic can increase the perceived credibility of the firm by demonstrating transparency and equity (Davidow, 2003; Sparks and Bradley, 2017). Further, credibility has been shown to directly impact purchase intentions (Allard et al., 2020; Mannan et al., 2019).

We expect that when blame is assigned to the service firm, the reviewer will be viewed as more credible. Conversely, reviewer credibility should be lower when more blame is assigned to the reviewer. Furthermore, we propose that the effect of firm response strategies on third-party purchase intentions will be mediated by blame and credibility:

A company’s online communication style and tone of voice have a significant impact on consumer perceptions of a brand (Barcelos et al., 2018). Within communication, social exchange theory posits that people must abide by rules that ultimately shape the exchange process (Cropanzano and Mitchell, 2005). Social norms are a collective understanding of acceptable behaviors within a group or society that guide interactions within various social settings (Melnyk et al., 2022). In service encounters, these norms establish expectations for both customers and service providers regarding appropriate conduct (Wan et al., 2011). When these norms are violated, behavior is deemed inappropriate, resulting in negative evaluations (Clark and Waddell, 1985; Hair and Ozcan, 2018). While we hypothesize that a defensive firm response (i.e., a callout) will positively impact third-party purchase intentions, firms must carefully consider how they deliver these responses.

Although defensive responses can address illegitimate complaints effectively, service firms must implement these responses appropriately. As noted previously, a passive response can be detrimental because it lacks empathy and devalues the customer’s concern. Similarly, a defensive response that violates a third-party observer’s standards for interpersonal treatment can also have negative consequences. Prior research suggests that fair interpersonal treatment is a key driver of postcomplaint satisfaction and loyalty, often outweighing the actual service outcome (Blodgett et al., 1997). For example, aggressive responses have been found to undermine the credibility of the messenger and are ultimately less persuasive (Jensen et al., 2013). Accordingly, Li et al. (2018) caution against using inappropriate tone or language in responses as it could trigger a “double deviation” where the reader’s initial negative reactions become even more negative due to the inappropriate response.

Conversely, gentler responses lead to more positive outcomes, such as improved brand image (Shin and Larson, 2020). Thus, a more subdued response can demonstrate professionalism and a willingness to engage with feedback constructively, creating goodwill and building customer trust. We argue that it is beneficial for firms to defend themselves against illegitimate negative reviews; however, it is crucial to do so in an appropriate manner to avoid undesirable outcomes. Even during conflicts, individuals expect behaviors to adhere to social norms (Brew et al., 2011). In other words, consumers may tolerate a firm-centric response that corrects an illegitimate review, but not at the expense of decorum (Béal and Grégoire, 2022). Moreover, research indicates that the inappropriate language used in online reviews can diminish the credibility of the source (Hair and Ozcan, 2018; Jensen et al., 2013). Consequently, a high level of aggression in a service firm’s response will lessen its credibility and decrease purchase intentions:

To test our hypotheses, we conducted three studies. Studies 1 and 2 examine H1. Study 2 also tests H2, which predicts mediation. Study 3 tests both H3 and H4. In all studies, participants read a series of online reviews. To enhance realism, the reviews were adapted from actual reviews published online. To avoid potential biases, the reviewers and companies were given fictitious names. Additionally, to ensure results were not influenced by viewing a single negative review in isolation, we pretested both positive and negative reviews and created three sets of reviews, each comprised of four individual reviews: three positive (five-star) and one negative (one-star) review, which were randomly selected. Examples of the reviews and manipulations are provided in Supplementary Material 2.

We also assessed the valence and aggressiveness of the language used in the reviews using a four-item, seven-point semantic differential scale (α = 0.880) where participants rated whether the reviews were bad (good), unfavorable (favorable), negative (positive) and unpleasant (pleasant). The nine positive reviews used in our experiment did not significantly differ from each other in terms of valence. Similarly, the two negative reviews were not significantly different in terms of valence. As expected, there was a significant difference in valence between the groups such that the nine positive reviews were more positive than the two negative reviews (see Supplementary Materials 6 and 7).

Aggressiveness of the language used in the reviews was also measured with a four-item, seven-point semantic differential scale (α = 0.906). Participants rated how supportive (condescending), respectful (disrespectful), polite (rude) and nice (mean) the reviews were, with higher scores indicating higher levels of aggression. All reviews, whether positive or negative, were rated similarly in terms of aggressiveness (see Supplementary Materials 6 and 7).

We operationalize our variable of interest, a “callout,” as a dichotomous action to align with our study objectives wherein a callout is present or absent. This allows for experimental control to capture the main effect of a defensive response. After completing our pretests and confirming the validity of our reviews, we programmed Qualtrics to randomly select three positive and one negative review without replacement to ensure that no review was presented more than once per participant. Additionally, both the order in which the positive and negative reviews were presented and the manipulation of firm responses (i.e., no response, apology and callout) were randomized to prevent biases (Ruiz-Mafe et al., 2020). All reviews were presented in English to the US-based consumers.

In Study 1, we explore the “callout” phenomenon by examining a consumer’s monetary allocation decisions. By investigating the distribution of financial resources among competing companies, Study 1 aims to provide insights into the impact of firm response strategies on consumer decisions.

Students from a Midwestern university in the USA took part in Study 1, which was a monetary allocation experiment. Participants were randomly assigned to one of two conditions and read reviews for two dining vendors. After reading the reviews, they were instructed to allocate funds among potential on-campus dining options. Participants were given a total budget of $100 and could allocate between $0 and $50 to each vendor. They also had the option to leave some funds unallocated and were instructed that the unallocated funds could be used at “any location where campus dining cards are accepted” so participants did not feel obligated to allot the full $50 to the companies in question. In the first condition, the callout was compared to no response. In the second condition, the callout was compared to the apology. The order in which the companies and reviews were presented was randomized. Additionally, demographic data were collected including age and gender. Two respondents incorrectly answered both attention check questions and were removed from the analysis, resulting in a final sample size of 98 (54.1% female; M_Age = 22.8).

Data were analyzed using a paired samples t-test in SPSS. As depicted in Table 2, the funds allocated to the service provider that called out the negative reviewer ($32.63) did not significantly differ from the amount allocated to the firm that did not respond ($33.45, t = −0.380, p = 0.353, d = –0.053). Therefore, H1 is not supported. However, a significantly larger sum was allocated to the firm that used a callout response ($33.15) compared to the firm that offered an apology ($27.83, t = 2.387, p = 0.011, d = 0.348), providing support for H2.

Findings from Study 1 underscore the impact of firm responses to illegitimate negative reviews on monetary allocation decisions. More particularly, our results reveal that when presented with online reviews and prompted to allocate funds between competing companies, participants favored the service provider that “called out” the illegitimate negative review over the firm that offered an apology. In the context of this research, an illegitimate negative review refers to misleading or false feedback from individuals who never actually encountered a service failure. In the scenario presented, while the reviewer claims they were told the service provider was “too busy” to complete a request, this claim is later challenged as a misrepresentation when the company uses a defensive response. The significant difference in monetary allocation between the firm that used a callout response and the one that apologized suggests that consumers are more inclined to support companies that defend themselves against inaccurate claims rather than apologizing. Notably, customers in the callout condition were likely to spend over 20% more on a service than those in the apology condition. These findings align with previous research highlighting the importance of proactive engagement in managing online brand image and consumer perceptions (Barhorst et al., 2020; Johnen and Schnittka, 2019; Lee and Cranage, 2014; Li et al., 2018).

The disparity in monetary allocation between the callout response and the apology response further emphasizes the effectiveness of defensive approaches in mitigating the impact of illegitimate negative reviews. While offering apologies may demonstrate a degree of accountability and willingness to rectify grievances (Li et al., 2018), our results suggest that a “callout” has a strong impact on a consumer’s willingness to spend after reading an illegitimate negative review. In the following study, we examine the underlying mechanisms of this effect.

Building upon the findings of the previous study, which highlights the effectiveness of defensive firm responses in managing online brand image, Study 2 aims to uncover the mechanisms driving this effect. Specifically, we focus on third-party evaluations of the reviewer and their conduct and examine the mediating effects of blame and credibility.

Using a between-subjects design, participants were exposed to a set of reviews for a fictional catering service provider. Participants were recruited via CloudResearch’s Connect panel. After reading the reviews, participants were exposed to one of the three firm response manipulations: no response, apology or callout. Following this, participants answered questions relating to our key variables. The primary focus of this study was third-party observers’ (i.e., readers’) purchase intentions assessed through the mediating effects of blame and reviewer credibility. Variables were presented in random order. Participants also responded to two attention check questions and provided their age and gender. Measurement items and their psychometric properties are shown in Supplementary Material 3.

To ensure data quality, responses were screened and removed based on criteria outlined by Aguinis et al. (2013), which included the detection of straight-line (Meade and Craig, 2012) and random responding methods (Huang et al., 2012; Johnson, 2005). Additionally, participants who incorrectly answered both attention check questions were excluded from the analysis. A total of 15 responses (approximately 5%) were removed. Of the 287 participants included in the final sample (52.3% female; M_Age = 38.5), 85% remembered the service provider’s name (χ² = 403.9, df = 6, p < 0.001) and 99% identified the correct firm response in their scenario (χ² = 269.4, df = 2, p < 0.001), indicating that participants were engaged in the study.

Test of main effects: To test the main effects predicted by H1 and H2, we compared third-party purchase intentions (α = 0.958) across firm response conditions. As predicted, third-party purchase intentions were higher when the service provider called out the reviewer (M = 5.34, SD = 1.15) compared to when the firm did not respond [M = 4.91, SD = 1.95, t (1,192) = 2.596, p = 0.01, d = 0.373] or apologized [M = 4.76, SD = 1.26, t (1,192) = 3.352, p < 0.001, d = 0.482]. Therefore, both H1 and H2 are supported.

Measurement model: We conducted a confirmatory factor analysis (CFA) to evaluate our measures. Based on several indices (χ² = 83.41, df = 51; CFI = 0.993; TLI = 0.991; SRMR = 0.024; RMSEA = 0.047) model fit is good (Browne and Cudeck, 1993; Hu and Bentler, 1995). All factor loadings are significant (p < 0.001) and above 0.847, providing evidence of convergent validity (Anderson and Gerbing, 1988). Following the recommendations of Fornell and Larcker (1981), the average variance extracted (AVE) for each factor exceeds the squared correlations between factors and is above 0.50, providing evidence of discriminant validity. Factor loadings means and AVE can be seen in Supplementary Material 3. Factor correlations can be seen in Supplementary Material 5.

Structural model: To test the hypothesized model, we used structural equation modeling (SEM) in Mplus. Dummy coding was used where the no response and apology conditions were the reference groups. Specifically, the first dummy coded variable compares the no response condition (coded as a 0) to the callout condition (coded as a 1) and the second compares the apology condition (coded as a 0) to the callout condition (coded as a 1). Model results are shown in Figure 2. Model fit is acceptable (χ² = 193.41, df = 75; CFI = 0.976; TFI = 0.971; SRMR = 0.150; RMSEA = 0.074).

Mediation testing: Bias-corrected bootstrapping with 5,000 samples (MacKinnon, 2008; Preacher and Hayes, 2008) was used to test the mediating effects predicted by H3. Results are detailed in Table 3. For the dummy variable comparing the no response condition to the callout condition (D_NoResponse), the indirect effect via blame and reviewer credibility was significant (β = 0.141; 95% CI [0.189, 0.589]). Likewise, the dummy variable comparing the apology to the callout (D_Apology), had a significant indirect effect on purchase intentions via blame and reviewer credibility (β = 0.142; 95% CI [0.188, 0.595]). These results provide initial support for H3.

To further assess H3 we examined the direct effects of the model. As indicated in Table 3, the effect of firm response on blame is negative and significant in both conditions (β_NoResponse = −0.583, p < 0.001; β_Apology = –0.589, p < 0.001) indicating that the callout effectively reduces blame attributed to the firm. Additionally, blame has a significant positive effect on reviewer credibility (β = 0.779, p < 0.001), indicating that as blame toward the firm increases, the reviewer’s credibility also increases. Finally, we found that reviewer credibility negatively affects purchase intentions (β = −0.310, p < 0.001). These findings fully support H3.

Findings from Study 2 underscore the effectiveness of calling out reviewers who post illegitimate negative reviews as a strategy to increase third-party purchase intentions. When companies call out reviewers who post illegitimate negative reviews, blame shifts from the service provider to the reviewer. As blame shifts away from the firm (and toward the reviewer), the service firm’s credibility is diminished and purchase intentions increase. These findings suggest that companies take the brunt of the blame when an illegitimate negative review is posted. Only after making it clear that the review is misleading do third-party observers (i.e., readers) reassign blame from the service provider to the reviewer, leading to higher third-party purchase intentions.

To explore this phenomenon further, a post hoc ANOVA was conducted (refer to Figure 3). Results show that when the firm either provides no response or apologizes, roughly 70% of the blame is attributed to the firm. However, when the firm “calls out” the reviewer, there is an extreme shift in blame with the reviewer assuming most of the responsibility.

Study 2 illuminates the mechanisms driving the “callout” phenomenon; however, it is important to acknowledge that consumer evaluations are not only shaped by what is said, but how it is said (Béal and Grégoire, 2022; Liebrecht et al., 2021; Olson and Ro, 2020). Thus, in Study 3 we manipulate the amount of verbal aggression in a firm’s response to examine its impact on purchase intentions.

Study 2 highlights that a defensive firm response can influence third-party purchase intentions through blame and credibility judgments. Study 3 builds on these findings by examining the potential pitfalls of overly aggressive or inappropriate defensive responses. Study 3 also focuses on firm-oriented evaluations (i.e., perceptions of the service firm’s credibility) and illustrates how the “callout” strategy can backfire if not implemented correctly.

In Study 3, a between-subjects design was used to manipulate the aggressiveness of the firm “callout” (low vs high). Participants were recruited from Prolific. Consistent with our previous studies, they read reviews while being exposed to one of the two callouts. After the manipulation, participants completed the same measures and attention checks used in Study 2 and responded to a question about service firm credibility. After cleaning the data using the same procedures reported in Study 2, 8 responses were removed (about 2%). Of the 396 subjects included in the final sample (54.8% male; M_Age = 40.5), 77% correctly recalled the service provider (χ² = 476.2, df = 6, p < 0.001) and 97% correctly indicated that the firm responded to the negative review, suggesting that participants were attentive.

Manipulation checks: Before completing the full study, we conducted a brief pretest to assess the aggressiveness of the firm’s callout using the same four items used to measure the aggressiveness of the reviews (α = 0.946). Participants rated the more aggressive callout (M = 3.99, SD = 1.77) as significantly more hostile than the less aggressive callout [M = 2.88, SD = 1.38, t (46) = 2.40, p = 0.010] (see Supplementary Materials 6 and 7). Thus, the aggressiveness manipulation was successful.

Test of main effects: To test the prediction that aggressiveness will decrease third-party purchase intentions (H4), we compared the mean difference between conditions. Aggression was operationalized as a categorical variable (low vs high). Results indicate that purchase intentions (α = 0.969) are significantly higher when aggression is low (M = 5.53, SD = 1.12) than when aggression is high [M = 4.94, SD = 1.47, t (1, 394) = 4.543, p < 0.001, d = 0.457]. Thus, H4 is supported.

Measurement and structural models: Results of a CFA indicate good model fit (χ² = 233.15, df = 98; CFI = 0.983; TLI = 0.979; SRMR = 0.021; RMSEA = 0.059). As shown in Supplementary Material 4, all factor loadings are significant (p < 0.001) and above 0.879, providing evidence of convergent validity. In all cases, the AVE for each factor was above 0.50 and exceeded the squared correlations between factors demonstrating discriminant validity. We then used SEM with bias-corrected bootstrapping with 5,000 samples to test our proposed model shown in Figure 4. The predicted model fit the data well (χ² = 267.79, df = 114; CFI = 0.981; TLI = 0.977; SRMR = 0.040; RMSEA = 0.059).

Mediation testing: Like Study 2, we tested H5 by examining the model’s indirect effects which are shown in Table 4. We also assessed the direct effects to determine if they were of the predicted valence. As expected, the indirect effect of callout aggressiveness on third-party purchase intentions through blame and reviewer credibility is negative and significant (β = –0.008, 95% CI [−0.025, −0.002]). Additionally, the indirect effect of callout aggressiveness on purchase intentions through blame and service firm credibility is negative and significant (β = −0.050, 95% CI [−0.113, −0.024]). Each direct effect is significant (all p’s < 0.001) and of the expected valence; therefore, H5 is fully supported.

Study 3 builds on our earlier findings by demonstrating that a poorly executed callout can backfire. Even when addressing illegitimate negative reviews, service firms must remain tactful and professional to avoid reducing third-party purchase intentions. Our results also reveal a notable sequence: readers attribute blame based on the perceived aggressiveness of the firm’s response. Overly aggressive responses shift blame from the reviewer to the firm, lowering the service firm’s credibility and ultimately decreasing third-party purchase intentions. Conversely, less aggressive responses enhance the service firm’s credibility, reduce the reviewer’s credibility and increase third-party purchase intentions. These findings underscore the importance of appropriately responding to illegitimate negative reviews to maintain credibility and drive purchase intentions.

Online reviews wield significant influence over third-party observers’ attitudes and behaviors. Research indicates that 94% of consumers have avoided a business due to a negative review, and four out of five customers have reconsidered a purchase after reading one (ReviewTrackers, 2022). Given the power held by customers, it is imperative for service organizations to understand how to address illegitimate negative reviews. The literature on firm responses to negative online reviews is extensive; however, nearly all focus on situations where the firm is at fault. Consequently, the academic literature typically advises service firms to use accommodative strategies where the firm accepts responsibility (Chang et al., 2015; Lee and Song, 2010). Industry experts echo this advice, recommending that companies avoid defensive responses and provide redress for dissatisfied customers (Podolsky, 2024).

However, these dynamics shift when the review is falsified or inaccurate (Roeloffs, 2023). In such cases, accommodative strategies may validate illegitimate complaints and cause undeserved harm to the service firm. We emphasize the dual nature of defensive reactions, illustrating how they can shape third-party perceptions both positively and negatively, depending on the tone of the response.

Study 1 demonstrates that when implemented correctly, defensive response strategies can improve brand outcomes in service contexts. Specifically, our findings contribute to the literature on decision-making in online service environments by showing that firm responses to illegitimate negative reviews influence consumers’ monetary allocation decisions. In Study 2, we find that compared to a passive (i.e., no response) or accommodative response (i.e., an apology), a defensive response (i.e., a callout) shifts blame to the reviewer. This shift decreases the reviewer’s credibility and increases third-party purchase intentions. Additionally, the domain lacks clarity on how response characteristics affect observer evaluations. Study 3 addresses this gap by examining verbal aggression, demonstrating that overly aggressive responses diminish a service firm’s credibility, ultimately lowering purchase intentions.

Nowadays, consumers are increasingly savvy and value fairness over the outdated notion that “the customer is always right” (Kim and Baker, 2020); therefore, it is essential for service firms to have an effective strategy to address illegitimate negative reviews. A well-executed callout allows firms to refute false claims, reassert control over the narrative and protect their brand amongst third-party observers (i.e., potential customers reading reviews).

This research demonstrates that third-party observers engage in blame attributions and credibility assessments when evaluating a service firm’s response to a review. A well-crafted callout can shift blame away from the company and toward the reviewer, especially when the firm’s response is factual and respectful in tone. Ignoring or apologizing to the reviewer when their negative feedback is illegitimate can be seen as passive or weak, confirming that the blame should lie with the service firm. However, firms must tread carefully as an overly aggressive response can backfire. An effective callout strikes the right balance – assertive yet respectful, defending the brand while maintaining professionalism.

The following sections explore the theoretical and managerial implications of our findings, acknowledge some limitations of our research and provide avenues for future research.

Our findings contribute to the service recovery and complaint management literature by integrating appraisal and attribution theory (Lazarus and Folkman, 1986; Weiner, 1985) to explain how blame and credibility judgments mediate the effects of firm response strategies on purchase intentions when reviews are illegitimate. We demonstrate how consumers assign responsibility for negative incidents based on a firm’s public response to online complaints and ultimately reveal that blame can be shifted with a defensive response strategy. These theoretical perspectives help clarify the psychological mechanisms through which defensive response strategies influence third-party observers’ (i.e., readers’) evaluations.

First, we advance the literature by demonstrating that a defensive response can shift the blame from the firm to the reviewer, thereby mitigating credibility damage and restoring purchase intentions among third-party observers. When negative reviews have merit, past research has found that an accommodative response is not only warranted but constructive (Lee and Song, 2010). In such cases, an accommodative response appropriately accepts blame on behalf of the company and initiates the service recovery process through redress (Xia, 2013). Weitzl and Hutzinger (2017) found that apologies elicit favorable reactions by increasing perceptions of empathy and sincerity. However, contrary to these findings, the present research reveals that in the case of an illegitimate review, an apology can be perceived as an admission of guilt, rendering the review legitimate. This study offers fresh perspectives on managing illegitimate reviews, thereby enhancing theories related to service recovery, customer relationship management, and online impression management. By building on prior literature and integrating appraisal and attribution theoretical perspectives, our work provides significant insights into the strategic benefits of using a defensive response to illegitimate negative online reviews.

Second, we delve deeper into the nuances of how “perceived credibility seems to explain variations in bystander reactions” with respect to online reviews (Weitzl and Hutzinger, 2017, p. 168). Grounded in appraisal theory, we tested and confirmed that credibility judgments play a large role in third-party observer purchase intentions. One factor impacting these judgments is the aggressiveness of the firm’s response. We apply social exchange theory to explore how aggressive firm responses to illegitimate reviews violate the norm of reciprocity, damaging the firm’s image and customer relations. By applying social exchange theory to digital contexts, we continue to develop a deeper understanding of online customer-firm exchanges. Results of Study 3 reveal that firm credibility (β = 0.78) has a much stronger positive effect on third-party purchase intentions when compared to the negative effect of reviewer credibility (β = −0.11). Even though discrediting the reviewer is effective (as revealed in Study 2), it is crucial that a firm does not deviate from acceptable social norms in professional discourse, as this can undermine the firm’s own credibility, rendering the “callout” ineffective. We find that verbal aggression in defensive responses can be detrimental to the beneficial outcomes of a defensive response. This supports the crucial role of tone in consumer-brand communication.

Third, when a firm addresses an illegitimate negative review, it enables third-party observers to reevaluate the situation and blame assignment based on the new information presented in the response. This suggests that evaluations of online reviews are cognitively complex and context-dependent, which challenges the assumption that consumer judgments are fixed after the initial exposure to a review. Overall, our study underscores the impact of defensive responses on third-party perceptions, which can be positive or negative depending on factors like blame, credibility and verbal aggression. This research deepens our theoretical understanding of the complexities involved in firms defending themselves on public mediums.

Our research provides several actionable insights for practitioners managing online complaints, particularly in handling illegitimate negative reviews. By considering blame attributions and credibility, service firms can more effectively respond to negative reviews, which not only protect but also enhance their bottom line by positively influencing third-party observer purchase intentions.

First, we offer firms strategy for retaking control of the narrative in online reviews through alternating blame and credibility evaluations. Our findings show that purchase intentions are heavily influenced by how third-party observers assign blame. We offer firms strategies to shift blame effectively through defensive callouts against illegitimate negative reviews. This allows service providers to address the power imbalance created by public consumer reviews. Without a proper response, observers may wrongly assume a review is legitimate. By challenging false claims, firms can reduce undeserved blame and improve consumer evaluations.

Ignoring or apologizing for illegitimate reviews led to similar outcomes, with consumers assigning fault to the firm. However, challenging illegitimate claims significantly decreased blame on the firm, resulting in more favorable consumer reactions. This highlights the importance of proactive online brand management as strategic responses can redirect blame and mitigate brand harm. In Study 1, participants allocated more funds to service providers that called out illegitimate negative reviewers compared to those that apologized. In Study 2, third-party purchase intentions were highest when firms used the “callout” strategy, showing that addressing illegitimate negative reviews can positively influence potential customers’ attitudes and behaviors. In Studies 2 and 3, we show that credibility evaluations impact observers’ purchase intentions. Prior literature has explored important factors in online reviews and discourse such as the role of firm reputation, perceived threat and frustration sensation (Barhorst et al., 2020; Kim and Lee, 2023; Tuzovic, 2010) – we recommend future research explore other key mediating variables to guide practice.

Second, we offer firms nonmonetary service recovery options for handling illegitimate negative reviews. Past research has emphasized the need to compensate and offer redress in response to negative reviews, which can be costly and, more importantly, unnecessary for baseless reviews. We suggest offering nonmonetary service recovery through a defensive response, which preserves the purchase intentions of a third-party observer. In doing so, this research offers strategies for public-facing service recovery efforts, moving beyond traditional one-to-one recovery transactions. Effectively addressing a negative review can offer reassurance to potential customers. For illegitimate negative reviews, we provide firms with strategies that can salvage third-party observers’ purchase intentions at no direct cost to the company by shifting the blame from the company to the reviewer. This approach ensures that firms do not inadvertently reinforce undesirable behavior and helps avoid unnecessarily eroding their bottom line.

Third, we highlight that even in digitally mediated forums, social norms shape consumer expectations of how firms should respond to complaints. Our results demonstrate that a well-structured “callout” – one that adheres to the norms of professionalism and fairness – can lead to positive outcomes. However, in Study 3 we find that excessive verbal aggression decreases third-party purchase intentions by enhancing the reviewer’s credibility while undermining the firm’s credibility, ultimately reducing purchase intentions. A response perceived as too aggressive could trigger a “double deviation,” where the reader’s initial negative reactions become even more negative due to the inappropriate response (Li et al., 2018).

Furthermore, overlooking aggression in a firm’s response may account for the negative reception of defensive strategies observed in past research. This finding contributes to research on online service interactions by reinforcing the dual role of credibility assessments (i.e., of both the firm and the reviewer) when shaping consumer responses to digital complaints. Thus, this research advises that companies should avoid verbal aggression when responding to illegitimate negative reviews to protect their credibility and maintain positive perceptions among third-party observers, which can enhance purchase intentions. To maximize the effectiveness of a defensive strategy, such as a “callout,” service managers should train employees to craft responses that are defensive yet professional. A well-executed “callout” can enhance brand perceptions; however, the opposite holds true if it is poorly executed.

We find strong support for our models; however, results may not apply to all contexts. For example, factors like review length, quantity and valence influence perceptions of the review (Purnawirawan et al., 2015; Schindler and Bickart, 2012). Similarly, textual elements such as spelling errors and the use of slang or profanity affect the trustworthiness and usefulness of online reviews (Cox et al., 2017; Hair and Ozcan, 2018; Schindler and Bickart, 2012). Our study focused primarily on firm response strategies, not on review characteristics; however, future research should explore how such factors impact customer evaluations. Furthermore, service failure elements like the type and severity of the failure can affect service quality perceptions and future behaviors (Lewis and McCann, 2004). Thus, future studies could build on our findings by examining how these elements interact with firm responses.

Additionally, research has shown that consensus among online reviews affects evaluations of firm responses (Lee and Cranage, 2014). Our results might differ if there were fewer positive or more negative reviews in the stimuli (Bradley et al., 2016; Casado-Díaz et al., 2020; Dens et al., 2015). We also investigated a defensive strategy following a single negative review, but it is possible that its effectiveness diminishes if overused. If a firm repeatedly defends itself, it may lose its “victim” status and the blame-shifting effect that is so vital to improving purchase intentions may not occur. Future research should examine such scenarios to identify boundary conditions and enhance the applicability of our models.

Moreover, there may be limitations in using a binary classification for negative reviews. Websites often solicit feedback across multiple dimensions, resulting in reviews that contain both positive and negative sentiments. Therefore, we recommend exploring a more complex continuum or multidimensional feedback system. Furthermore, quantifying the number of company callouts that occur on online review platforms could yield valuable insights. Therefore, we encourage future research to explore this direction further, potentially leveraging web scraping and other field data collection techniques. Finally, we recognize the limitations of laboratory-based experiments in generalizing our findings. Nevertheless, we believe our controlled setting offers a robust foundation for addressing our research questions. Future studies conducting field tests will be essential to validate and extend our findings in real-world conditions.

In sum, our findings provide valuable insights for service providers managing their online brand image. By strategically “calling out” negative reviews, businesses can lessen brand damage and build trust and loyalty in an ever-competitive digital servicescape. However, companies must be cautious and professional in their approach to avoid potential backlash.

The supplementary material for this article can be found online.