Company Response to Negative Online Reviews: The Effects of Procedural Justice,Interactional Justice,and Social Presence

Abstract

This research investigates how potential customers evaluate a company response to negative online reviews. Integrating the literature on perceived justice in service recovery, social presence in online communications, and signaling in trust formation process, this research examines the effects of procedural justice, interactional justice, and social presence in the company’s response to negative online reviews on potential customers’ trust and purchase intentions toward a company. A 2 × 2 × 2 between-subject experimental design is utilized, and 410 participants are recruited through a consumer panels firm. Main results include the three-way interaction effect of procedural justice, interactional justice, and social presence on trust and the mediating effect of trust. Social presence exacerbates the negative effects on trust when both interactional justice and procedural justice are low in the company response. However, the social presence effect becomes small in increasing trust when both interactional justice and procedural justice are high in the company response. Trust mediates the relationship between customer perceptions of company response and purchase intentions. This research provides practical implications for hospitality companies on how to effectively respond to negative online reviews.

Keywords

negative online review company response justice social presence trust

Introduction

Third-party online review websites such as Yelp and TripAdvisor have become an important platform for consumers to share their purchase experiences with a vast number of other consumers (Y. Chen & Xie, 2008; Xiang & Gretzel, 2010). For example, TripAdvisor.com (2017), the largest travel review website in the world, has more than 435 million reviews of 6.8 million businesses. Customers often rely on online reviews to assess the quality of hospitality products before purchasing due to the intangible and experiential nature of services (Rose & Blodgett, 2016). Online reviews help potential customers make purchase decisions by providing a quick and convenient way to evaluate and compare hospitality products (Sparks et al., 2016). Although online reviews can be either positive or negative, the latter is particularly challenging because potential customers are likely to weigh negative information more heavily than positive information (Ahluwalia & Shiv, 1997; Sen & Lerman, 2007). The importance of online reviews has attracted significant attention from researchers, and an extensive amount of research has examined how online reviews left by past consumers influence future customers (e.g., Tsao et al., 2015; Vermeulen & Seegers, 2009); yet, the company’s involvement in the process has been largely overlooked.

Although dissatisfied customers who post negative online reviews may not expect a direct response from the company, research suggests that the company’s response to negative reviews affects potential customers’ perceptions of the company and their purchase decisions (Sparks & Bradley, 2014; Ye et al., 2008). Survey results report that four out of five potential customers have changed their purchasing decisions based on negative online reviews (Cone Communication, 2011). Yet, 85% to 87% of customers indicate that an appropriate managerial response to a negative review improves their impression of the hotel (Nerval Corp., 2015). The positive impact of company response is also found in the automotive company’s blog context (van Noort & Willemsen, 2012) and the online restaurant guide site (Pantelidis, 2010). Nevertheless, most hotel companies’ reviews of the responses are sporadic (S. Y. Park & Allen, 2013), suggesting there is a lack of strategies for companies to manage online reviews. It becomes clear that even though hospitality companies are increasingly becoming aware of the need for developing strategies to manage online customer reviews, many of them are unsure about how to respond to negative online reviews (Levy et al., 2013; S. Y. Park & Allen, 2013; Xie et al., 2014).

Realizing the importance of managing online reviews, a small stream of research has emerged recently to examine the effectiveness of company response (e.g., Min et al., 2014; Sparks & Bradley, 2014; Sparks et al., 2016). Although researchers encourage companies to respond to online reviews, there is still limited research for hospitality firms on how to effectively respond to negative reviews. More research has been called for examining such response strategies (Breitsohl et al., 2010; Min et al., 2014; S. Y. Park & Allen, 2013; Sparks et al., 2016). Furthermore, extant research findings on company response to negative online reviews are inconclusive in that some studies suggest positive outcomes (e.g., Breitsohl et al., 2010), whereas other studies report negative outcomes (e.g., Mauri & Minazzi, 2013). The inconsistency in the extant research might be due to the fact that the underlying mechanism explaining how company response relates to outcomes has not been established, theoretically and empirically. To fill these gaps, the current research is guided by three research questions:

Research Question 1: Does a company’s response to negative online reviews positively influence potential customers?

Research Question 2: If so, what elements should be used in the company’s response to address negative online reviews and thereby encourage patronage from potential customers?

Research Question 3: What are the underlying mechanisms that explain how a company’s response may influence potential customer behavioral intentions?

This research focuses on how potential customers evaluate a company response to negative online reviews. Drawing on perceived justice in service recovery literature (e.g., Tax et al., 1998), social presence in online communications literature (e.g., Gunawardena, 1995), and signaling in trust formation literature (e.g., Connelly et al., 2011), this research examines potential customers’ trust and purchasing (booking) intentions toward the company based on a company’s response to negative online reviews. Specifically, procedural justice and interactional justice are identified as key elements in understanding potential customers’ perceptions of the company response to negative online reviews. In addition, social presence in conjunction with procedural justice and interactional justice is expected to influence customer trust by providing a feeling of human contact and sensitivity in the online review management. Besides identifying the three key elements that should be considered in company response, this research demonstrates that trust plays an important mediating role between customer perceptions of company response and purchasing intentions.

This research advances our understanding of negative online review management by approaching the issue from a theoretically integrated perspective. Justice-based frameworks have often been used in investigating a company’s efforts toward complainers to restore their satisfaction in the face-to-face service recovery literature (e.g., Schoefer & Ennew, 2005; Sparks & McColl-Kennedy, 2001; Wirtz & Mattila, 2004). However, a company’s response to negative online reviews has two aims: addressing the complaint posted by a customer and managing potential customers’ perceptions of the company. Our research focuses on the latter, how potential customers perceive a company’s response to negative online reviews. Although previous research on service recovery models generally explains theoretical relationships of complainers’ justice perceptions, recovery satisfaction, and repeat intentions, our research model on online review management investigates theoretical relationships of potential customers’ justice perceptions, trust, and purchasing intentions. Furthermore, justice theory examinations in the extant service recovery literature suggest that distributive justice (e.g., compensation) is important in increasing recovery satisfaction (e.g., Tax et al., 1998). However, online review management mostly relies on written communication strategies where procedural justice and interactional justice are relevant but distributive justice is often not applicable in the online review management context. Thus, online review management strategies focus on increasing the effectiveness of company response communication to influence potential customers’ perceptions of the company and, consequently, their purchasing intentions. From a communications perspective, a notable difference between face-to-face and online contexts is the decreased presence of human and social elements in the online environment (Lu et al., 2016). To overcome such limitations, researchers in communications have emphasized social presence for enhancing the effectiveness of online communications (Gefen & Straub, 2004). Finally, a company’s response may serve as a signal for potential customers to make inferences about the trustworthiness of the company (Sparks et al., 2016) and thus help explain how potential customers’ purchase intentions are influenced by a company’s response to a negative online review. Integrating literature on perceived justice, social presence, and signaling theories, our research examines several key variables in the online review management context to explain how potential customers evaluate company responses to online complaints. Findings of this research provide recommendations in that hospitality companies do not only have to decide whether to respond to negative online reviews or not but they also have to decide upon a strategy for how to respond.

Conceptual Framework and Hypotheses

Company Response to Negative Online Reviews

The impact of online consumer reviews on potential consumers’ attitudinal and behavioral outcomes has been examined extensively, and the extant literature generally is in consensus that positive (negative) reviews increase (decrease) consumer perceptions of the company and purchasing intentions (Chatterjee, 2001; Tsao et al., 2015; Vermeulen & Seegers, 2009). Negative reviews are found to be more persuasive and influential in consumers’ buying decision process than positive ones (Ahluwalia & Shiv, 1997; Chevalier & Mayzlin, 2006; M. Lee et al., 2009; S. Park & Nicolau, 2015), and the impact of negative reviews is stronger for intangible services than tangible goods (Christodoulides et al., 2012). As customer buying decisions are greatly affected by negative online reviews, hospitality companies that sell intangible service products face a challenge to deal with them effectively to minimize damaging impact on potential customers.

In managing customer dissatisfaction, service recovery literature suggests that responding to customer complaints is not just desirable but necessary because the appropriate handling of a complaint leads to trust and commitment toward a company (Strauss & Hill, 2001; Tax et al., 1998). Researchers further note that service failures themselves do not automatically result in customer dissatisfaction, but the service provider’s improper or lack of a response is most likely to lead to dissatisfaction (del Río-Lanza et al., 2009; Smith et al., 1999). Previous studies in face-to-face service recovery strongly advise a company to respond to those customers who express dissatisfaction. Thus, the same notion applies to dissatisfaction expressed on online review sites; however, companies’ responsiveness to negative online reviews still remains low. For example, Xie et al.’s (2017) analysis of management response to online reviews on TripAdvisor shows that hotel managers echo positive reviews but are less responsive to negative reviews as 69.6% of the management responses were provided for the four- and five-star reviews as opposed to only 11.6% for the two- and one-star reviews. Some companies may be hesitant to respond to negative consumer reviews because their response may cause more harm than good by highlighting or escalating the issue.

Although company response to negative online reviews is suggested by many researchers (e.g., Levy et al., 2013; Min et al., 2014; S. Y. Park & Allen, 2013; Sparks & Bradley, 2014), research findings are mixed with inconsistent results. Some studies show that company involvement on online review sites can lead to skepticism toward the company and amplification of negative effects (Deighton & Kornfeld, 2009; Dellarocas, 2006; Kniesel et al., 2016). Consumers may view company responses as being similar to advertising and consider them disingenuous and self-serving (Buttle, 1998). Similarly, Mauri and Minazzi (2013) found that hotel managers’ responses to online reviews lowered purchasing intentions of potential customers. On the contrary, other studies report that a company response results in more favorable outcomes, such as higher credibility and trust, compared with no response (Breitsohl et al., 2010; Kniesel et al., 2016). Recent research findings tend to support the positive effects of company response (e.g., Liu et al., 2015; Min et al., 2014; Rose & Blodgett, 2016; Sparks et al., 2016), suggesting that potential customers are more willing to engage in business with the company that responds to negative reviews. Company response, however, may not always be better than no response. According to Y. L. Lee and Song’s (2010) findings, no response to the negative online review has a more favorable outcome than a company response with a defensive response strategy.

Thus far, the effectiveness of company response to negative online reviews is not fully determined. These inconclusive results in extant literature raise the question of whether mediating variables may account for the mixed findings in the previous research about company response and outcomes, therefore requiring further investigations into how potential customers evaluate company’s response to negative online reviews. Although previous research findings are varied and even contradicting, both the negative outcomes led by skepticism (e.g., Mauri & Minazzi, 2013) and the positive outcomes including credibility (e.g., Breitsohl et al., 2010) seem to imply that trust is important in understanding the customer evaluation of company response to negative online reviews.

Trust

Trust refers to consumers’ willingness to rely on a service provider with confidence (Moorman et al., 1992) based on the expectation that the service provider will provide a solution to service failure (Söderlund & Julander, 2003). In the online environment, the importance of trust is emphasized due to the complexity in online interactions and the possibility of insincere and unpredictable behaviors (Gefen & Straub, 2004). Online reviews influence customers’ trust toward a company, brand awareness, and product acceptance (Cantallops & Salvi, 2014), and potential customers use online reviews to reduce risk and uncertainty in the purchase situation (Wang & Emurian, 2005). Recently, several studies have examined the impact of company response on trust in online review contexts. For example, Wei et al. (2013) compared general and specific responses and found positive effects of specific responses on perceptions of trust and communication quality. In addition, Sparks et al. (2016) found higher trust when a human voice was characterized in a managerial response versus a corporate voice.

Signaling theory (Connelly et al., 2011) offers an explanatory mechanism for the way in which company response can work to affirm the credibility of a company’s service commitment and, in so doing, improve customer’s purchase intentions. Customers without prior experience with a company draw inferences about the trustworthiness of a company based on informational cues or signals (Urban et al., 2000) and responses posted by the company serve as such informational cues (Sparks et al., 2016). Customers are more willing to engage in business with a company if the company can be relied upon (Sichtmann, 2007). By responding to negative reviews, a company signals that it cares about its customers and will continue to do so in the future (Li et al., 2017). This effort enhances trust toward the firm (Rose & Blodgett, 2016) and influences potential customers’ purchasing intentions (Weisberg et al., 2011). In essence, we contend that potential customers perceive the company response to a negative online review as a manifestation of its service quality commitment that not only enhances trust but also reduces perceived risk and uncertainty in a purchasing situation. In this process, a company response that fails to signal trust in potential customers’ minds will not lead to purchase intentions. We believe that trust not only allows us to have a better understanding of the relationship between the company response and purchase intentions but may also help explain some of the mixed findings that have been reported so far.

Conceptual Framework

There is substantial evidence that the company response affects potential customers’ perceptions of the company (Rose & Blodgett, 2016; Sparks et al., 2016). Despite this evidence, researchers still do not identify the key elements of the company response to effectively address negative online reviews, nor do they adequately understand the mechanism through which company response affects potential customers (Sparks & Bradley, 2017). Although recent research within online review management is suggestive, it does not yet offer a complete picture of the negative online review management process. In this research, we conceptualize two justice dimensions and social presence as the key elements of company response to negative online reviews. From a potential customer’s perspective, a company response to negative online reviews can be seen as company-initiated service recovery efforts expressed via a written message in the online communications context. Also, the effectiveness of the company response that is mostly relying on text type of message in online communications can be enhanced by increasing the social aspect of the communicator (company). The way in which the negative online review is managed works as a signal for potential customers because they use it to form inferences about the trustworthiness of the company and consequently determines purchase intentions. Taken together, the conceptual framework of this study is proposed to explain potential customers’ evaluations of negative online review management (see Figure 1). In the model, two justice dimensions (procedural justice and interactional justice) as well as social presence represent the key elements of company response to online reviews and influence trust through a signaling process. Furthermore, trust mediates the relationship between the company response and purchasing intentions. The following sections will discuss the variables used in the model and their relationships to explain the negative online review management process from a potential customer perspective.

Figure 1.

Conceptual Framework.

Justice

The conceptual framework most often used to explain customers’ evaluation of service recovery process is justice theory. Justice theory has its foundations in social psychology and has been widely used to explain individuals’ reactions to a conflict situation (Blodgett et al., 1997). In the service failure and recovery literature, perceived justice is shown to influence customers’ postrecovery satisfaction (Smith et al., 1999; Tax et al., 1998) and consequently leads to behavioral intentions such as repurchase and negative word of mouth (Wirtz & Mattila, 2004). Although previous studies have demonstrated that perceived justice has both psychological (e.g., satisfaction) and behavioral outcomes (e.g., repurchase intentions) in the service recovery context, our research applies justice theory to the online review management context to understand the dynamics between potential customers and a company by examining their psychological (e.g., trust) and behavioral outcomes (e.g., purchasing/booking intentions) based on the company response to negative online reviews.

Justice-based models, which include three distinct but related dimensions (i.e., distributive, procedural, and interactional), are commonly used to explain how customers evaluate a company’s service recovery (e.g., Chebat & Slusarczyk, 2005; Kuo & Wu, 2012; McColl-Kennedy & Sparks, 2003). Although distributive justice has shown to influence customer perceptions of service recovery in the face-to-face context (e.g., Blodgett et al., 1997; Wirtz & Mattila, 2004), it is not a common practice for companies to offer traditional forms of distributive justice, such as a refund or compensation, in a written response on online review sites due to some practical reasons. Because online reviews can be posted by anyone, the credibility of the complaints may be questionable because of reviewer anonymity (Schindler & Bickart, 2005), and companies are often unable to verify whether the complaint on a third-party review site is real. In addition, providing or promising monetary compensation on online review sites may generate unintended side effects, such as “copycat” posters that replicate complaints for unjust financial gain. Furthermore, the findings of an empirical research confirm that the merit of distributive justice is insignificant in managing negative online reviews (Cheng & Loi, 2014). This research, therefore, focuses on procedural justice and interactional justice to examine the impact of company response to negative online reviews on potential customers.

Procedural justice refers to the perceived fairness of the policies and procedures used by the company in customer complaint management (Blodgett et al., 1997). The structural considerations and the speed of a company’s intervention are critical determinants of perceptions of procedural justice in service recovery (Tax et al., 1998; Wirtz & Mattila, 2004). In the online review management context, procedural justice involves the company’s online review management process such as a response time and a company’s monitoring system. However, interactional justice refers to the customer’s evaluation of the manner in which a company responds to customer complaints, and it usually includes an apology, explanation, and other interpersonal elements, such as courtesy, empathy, concern, and effort (Blodgett et al., 1997; Smith et al., 1999; Wirtz & Mattila, 2004). In the online review management context, interactional justice involves the content of company’s response including apology and an explanation for the service failure.

Service recovery literature suggests that perceived justice influences trust. For example, DeWitt et al. (2008) found a positive relationship between justice perceptions and trust in the hospitality industry. In a study of airline delays, Wen and Chi (2013) found support for a positive relationship between procedural and interactional justice and customer trust of the service firm. When a company responds to negative online reviews, it can be considered that the company initiates service recovery that acknowledges the failures and attempts to make right with the customer who had a negative experience. This responsiveness of the company can be perceived positively by potential customers who read online reviews during their information search process. A company that has a monitoring process in place to address consumer concerns on online review sites and responds to them in a timely manner is likely to be perceived as being trustworthy by a potential customer. Also, a company that responds to negative reviews in an appropriate manner with an apology and explanation can increase trust for potential customers. Accordingly, we posit that procedural justice (monitoring and timing) and interactional justice (apology and explanation) in the company’s response positively influence potential customers’ perceptions of the company (trust).

Hypothesis 1 (H1): A company’s response with high procedural justice leads to higher trust toward a company than a company’s response with low procedural justice.

Hypothesis 2 (H2): A company’s response with high interactional justice leads to higher trust toward a company than a company’s response with low interactional justice.

Social Presence

The concept of social presence is grounded in social presence theory that elaborates the ability of a communication medium to transmit social cues (Short et al., 1976). Social presence refers to the degree to which a person is perceived as being real in communication (Gunawardena, 1995), and it is also described via social warmth that increases a feeling of human contact and sensitivity in the online communication context (Gefen & Straub, 2004; Hess et al., 2009; Yoo & Alavi, 2001). Social presence is formed based on not just the words used in communication but other elements such as verbal and nonverbal cues and the communication context (Rice, 1993). In other words, consumers perceive social presence if they sense a form, behavior, or sensory experience that indicates the presence of another (Biocca et al., 2003). Unlike face-to-face interactions, online interactions have occurrence across different times and locations, less control over data, unknown relationships with others, lower barriers to entry and exit, the absence of a physical environment, and fewer human or social elements (Hassanein & Head, 2007). As communications in the online environment increase, researchers suggest that trust can be enhanced through social cues in the online environment (Cyr et al., 2007; Gefen & Straub, 2004; Hassanein & Head, 2007; Racherla et al., 2012; Weisberg et al., 2011).

Communication is considered to have a high social presence if it conveys a feeling of human contact and sensitivity (Yoo & Alavi, 2001). Sparks et al. (2016) found that a conversational human voice results in more positive trust inference about the hotel than a professional corporate voice. Similarly, a personalized organizational response to a consumer comment on an organizational crisis message post positively affects organizational reputation through higher perceptions of conversational human voice (Crijns et al., 2017). In addition, self-disclosing information enhances intimacy with others in online environment by increasing social presence of the communicator (Shen & Khalifa, 2009) and results in high credibility of the reviewer (Munzel, 2016). Also, Forman et al. (2008) suggest that consumers rate product reviews containing identity descriptive information more positively than those that lack in the e-commerce context. These findings suggest that a company response including social presence cues, such as direct contact information and photo of the manager, can enhance trust from potential customers in the online communication context. Therefore, we hypothesize the following:

Hypothesis 3 (H3): A company response with high social presence leads to higher trust toward a company than a company response with low social presence.

As our conceptual framework posits that three elements of company response (procedural justice, interactional justice, and social presence) increase trust, we also expect a combined effect. There is substantial evidence that suggests interaction effects among the justice dimensions in service recovery literature (e.g., Blodgett et al., 1997; Tax et al., 1998; Wirtz & Mattila, 2004). Also, Aurier and Siadou-Martin (2007) have found a joint effect of procedural justice and interactional justice on the perception of interactional quality between customer and service personnel in the restaurant context. Although there is no study that has directly examined the interaction effect between justice dimensions and social presence, several studies suggest that “human,” rather than “corporate,” communication style is associated with greater perceived effectiveness of the communication (Weinberg & Pehlivan, 2011; Yang et al., 2010) and increases trust (Kelleher, 2009) in the social media context. In sum, the extant literature seems to suggest that the attributes of company response to a complaint cannot be examined in isolation but should be considered in conjunction with each other (Wirtz & Mattila, 2004). Along the same lines, we expect that the three elements of the company response may not act in isolation but interact with one another. Thus, when a company quickly responds to negative reviews through a monitoring system in an appropriate manner with an apology and explanation and includes social presence cues that increase human connection in the online environment, a potential customer’s trust toward the company will increase further beyond each element’s additive effect. Taken together, we propose that procedural justice, interactional justice, and social presence have an amplifying positive joint effect on trust.

Hypothesis 4 (H4): There is a positive three-way interaction effect of procedural justice, interactional justice, and social presence on trust toward a company.

Relating to our earlier discussions on trust in the online review context, we also posit that potential customers’ behavioral intentions are affected by trust that they have formed based on the company response. Service recovery studies have shown that trust mediates service recovery satisfaction and word of mouth/revisit intention in the hotel setting (e.g., Kim et al., 2009), and other studies have suggested that trust mediates the relationship between justice and behavioral loyalty (e.g., DeWitt et al., 2008). In the online shopping context, Hassanein and Head (2007) show that trust mediates the relationship between social presence and attitude. Trust is also found to mediate social presence and purchase intentions in e-commerce (Lu et al., 2016). These previous studies in service recovery and social presence have demonstrated that trust mediates the attributes of company/seller and behavioral intentions. We argue that potential customers’ purchasing intentions may not be simply based on whether a company responded to the negative review or not, as evidenced with mixed results documented in the previous research (e.g., Mauri & Minazzi, 2013; Rose & Blodgett, 2016) but are determined by the effectiveness of company response and how trust can explain the mechanism. In other words, even though a company responds but fails to form trust in potential customers’ minds, the company response will not lead to positive outcomes. Accordingly, we hypothesize a mediating role of trust between company response (procedural justice, interactional justice, and social presence) and customer purchase (booking) intentions.

Hypothesis 5 (H5): Trust mediates the relationship between a company response and purchase intentions.

To establish empirical evidence of the proposed model, we conducted two experiments. The preliminary study aimed to verify whether a company’s response to a negative online review positively influences potential customers’ behavioral intentions in a restaurant online review context. Then, the main study tested the proposed model by examining potential customers’ perceptions of a manager’s response to negative reviews in terms of the three elements (procedural justice, interactional justice, and social presence) in a hotel online review context.

Preliminary Study

Research Design

The research design was a single-factor between-subject experiment that manipulated a restaurant manager’s response to a negative online review through written scenarios. The restaurant context is chosen considering the familiarity level of student subjects in the preliminary study. To increase realism, an actual online review and manager’s response from the restaurant industry were selected from Tripadvisor.com and modified for the preliminary study. To determine the effectiveness of manipulations, participants were asked to indicate their agreement levels on dissatisfaction in regard to the negative online review (“The customer experienced a dissatisfying experience”) and company responsiveness (e.g., “This restaurant is always ready to respond to customers’ requests”) on a 5-point Likert-type scale (1 = strongly disagree, 5 = strongly agree). Also, they were asked to rate the scenario realism (“how realistic was the scenario?”) on a 5-point scale (1 = highly unrealistic, 5 = highly realistic).

For this preliminary study, 115 undergraduate students from a university in the southeastern United States participated. Three participants were excluded due to the respondent not answering “yes” to the qualification question, “In the last six months, have you read an online review about a hospitality service, such as a review about a restaurant, bar, lounge, or hotel from an online review website like Tripadvisor.com, Yelp.com, or GooglePlus.com?” and one participant was dropped due to excessive missing values, resulting in 111 usable surveys. The sample was mostly female (66%), the average age was 22 years old, and respondents dined out an average of 3.7 times per week. Participants were randomly assigned to one of two scenarios (manager response: yes vs. no) and asked to imagine that they were planning to dine out and searching for a restaurant based on online reviews. Data analyses were conducted with IBM Statistical Package for the Social Sciences (SPSS) Version 25.

Measurement of Research Variables

The dependent variable, behavioral intentions, was measured by a four-item scale, “I would dine at this restaurant in the future”; “There is a likelihood that I would dine at this restaurant in the future”; “I will recommend this restaurant to my friends, family, or others”; “I will say positive things about this restaurant to others” (Cronbach’s α = .935) from Han and Jeong (2013). In addition, two covariates, task involvement and attitude toward online reviews, were considered in the study and assessed by multi-item scales adapted from J. Lee et al. (2008). All items were measured on a 5-point Likert-type scale (1 = strongly disagree, 5 = strongly agree).

Results

Participants indicated that the customer who posted a negative review had a dissatisfying experience (M = 4.60), and there was no difference in perceived dissatisfaction between whether or not the manager responded to the complaint (t = −0.173, p = .250). Next, for the responsiveness manipulation, there was a difference between two conditions (t = −8.070, p < .001). As expected, respondents who read a response from the manager had indicated that the restaurant was more responsive (M = 3.29) compared with those who read the negative review only without the manager’s response (M = 1.94). In addition, the participants indicated that the scenario was realistic (M = 4.01). Taken together, these results indicate that the manipulation was successful.

An analysis of covariance (ANCOVA) was used to examine the effect of the manager’s response to the negative online review on behavioral intentions after accounting for task involvement and attitude toward online reviews. As expected, respondents reported higher behavioral intentions toward the restaurant when a manager response was included (M = 2.48) compared with no manager response (M = 1.67; F = 26.188, p < .001). Although task involvement and attitude toward online reviews were included as covariates, neither of them was significant.

Discussion

The results from the preliminary study confirm that a company response to negative online reviews has a positive impact on behavioral intentions. This result supports the recent research findings that company response to negative online reviews positively affects the company by mitigating uncertainty about a firm’s capability (M. J. Chen et al., 2007) and reducing the likelihood of potential customers drawing their own negative inferences (e.g., Y. L. Lee & Song, 2010; Sparks & Bradley, 2014; Sparks et al., 2016). Our results suggest that company response can be considered as a company-initiated service recovery, and this responsiveness of the company is perceived favorably by potential customers who read online reviews during their information search process and influence their behavioral intentions positively. Because we have confirmed the positive effect of company response to a negative online review, we proceed to the main experiment to examine the effectiveness of the three key elements in the company response and the underlying mechanism of the relationship between company response and customer purchase intentions.

Main Study

Research Design

The main experiment was a 2 (procedural justice: high vs. low) × 2 (interactional justice: high vs. low) × 2 (social presence: high vs. low) between-subject full factorial design. We developed an online questionnaire with eight conditions, each condition consisting of the negative customer review pertaining to outdated décor and a Wi-Fi issue as complaints along with one of the eight managers’ responses. The examples of the customer negative review and manager’s responses can be found in Appendix A. Similar to the preliminary study, the customer’s negative review and the hotel company’s response were adapted from TripAdvisor to increase realism and were modified for the manipulated variables accordingly. To reduce the possibility of confounds, such as brand effect, a fictitious hotel name was used. Participants were randomly assigned to one of eight conditions and asked to role-play a potential customer reading the negative customer review and the hotel manager’s response on a third-party online review site. Prior to the main study, we conducted two pretests with consumer panel samples (n = 101 for the first pilot study and n = 99 for the second pilot study) to polish the questionnaire, check the manipulations, and assess the realism of the research design. Based on these results, some refinements were made relating to wordings and manipulations.

Manipulated Variables

In the manager response, procedural justice was manipulated by response time and online review monitoring (high: quick response time and regular monitoring vs. low: slow response time and no regular monitoring). The manipulation of procedural justice was assessed by five items (e.g., “The hotel has good policies and practices for dealing with complaints”); four items were adapted from Gursoy et al. (2007) and DeWitt et al. (2008), and one new item (“The manager routinely monitors online reviews for feedback”) was added. Interactional justice was manipulated by the manner of manager’s response to the complaint (high: apology and explanation vs. low: no apology and no explanation). The manipulation of interactional justice was assessed by two items of apology scale (e.g., “The response included a genuine apology”) and two items of explanation scale (e.g., “The response provided an explanation of why the problem occurred”) adapted from Gursoy et al. (2007). Social presence was manipulated by social cues (high: direct contact information and photograph of the manager vs. low: generic contact information and no photograph) in the manager response. The manipulation of social presence was assessed by six items: Five items (e.g., “There is a sense of human contact in the response”) were adapted from Gefen and Straub (2004) with minor wording modification to reflect the online review management context, and one new item (“There is a real person in the response”) was added. All manipulation check items were measured on a 7-point Likert-type scale (1 = strongly disagree, 7 = strongly agree). The measurement items used for manipulation checks are shown in Appendix B. Finally, scenario realism and the role-playing effectiveness were assessed by asking participants, “How realistic was this scenario to you?” (1 = highly unrealistic, 7 = highly realistic) and “How easy/difficult to imagine yourself as a viewer reading these messages online? (1 = very difficult, 7 = very easy).

Measurement of Research Variables

Trust was measured by three items: two items (e.g., “I feel that this hotel is trustworthy”) adapted from Sparks and Browning (2011) and one new item (“I feel that this company has the ability to provide good service”) was added. Purchasing intentions was measured by three items (e.g., “I would stay at this hotel in the future”) adapted from Han and Jeong (2013) and Chiang and Jang (2006). All items were measured on a 7-point Likert-type scale (1 = strongly disagree, 7 = strongly agree). The scales used in the main study are shown in Appendix B.

To ensure scale reliability and validity of the three manipulated and two dependent variables used in the study, the items were tested and refined through two pretests before the main study. Also, in the main study, confirmatory factor analysis was conducted to examine the psychometric properties by estimating a measurement model containing procedural justice, interactional justice, social presence, trust, and behavioral intentions. Results indicate the model is an adequate to fit to the data (χ² = 646.161, df = 178, p < .001, goodness-of-fit index [GFI] = 0.868, comparative fit index [CFI] = 0.963, normed index [NI] = 0.950, and root mean square error of approximation [RMSEA] = 0.079). The average variance extracted (AVE) for each variable is above 0.5, and all AVE estimates are greater than the corresponding squared correlation estimates. The reliability coefficient alphas were ranged from .93 to .98. Table 1 includes means, standard deviations, correlations, squared correlations, AVEs, and reliability coefficients of all manipulated variables and dependent variables.¹

Table 1.

Descriptive Statistics, Correlations, AVE, and Reliability Coefficients α.

Constructs	M	SD	PJ	IJ	SP	Trust	PI	Cronbach’s α
PJ	4.02	1.98	.78	.40*	.50*	.57*	.53*	.95
IJ	3.67	2.14	.02	.83	.83*	.68*	.65*	.96
SP	4.05	1.93	.25	.69	.88	.75*	.69*	.98
Trust	4.23	1.51	.32	.46	.56	.83	.86*	.93
PI	3.62	1.63	.28	.42	.48	.74	.80	.97

Note. Squared correlations appear below the diagonal and correlations appear above the diagonal; the AVE for each construction is shown in bold along the diagonal. AVE = average variance extracted; PJ = procedural justice; IJ = interactional justice; SP = social presence; PI = purchase intentions.

p < .01.

Participants

An online questionnaire was distributed to the consumer panel samples recruited by an online marketing research firm that provided a service to collect data for the researchers. A total of 449 respondents participated in the study by meeting the qualifying question, “In the last 6 months, have you read an online review from a hospitality product review website like Tripadvisor.com, Yelp.com, or GooglePlus.com?” Then, 39 respondents were excluded due to an attention filter question, a trick filter question embedded in the questionnaire to identify respondents who may not read the questionnaire carefully, resulting in 410 usable respondents.

The participants were mostly female (63.5%), White/Caucasian (81.9%), married (55.9%), and the average age was 31.4 years. Most respondents indicated having a college degree (37%) or college credits (28.2%), followed by high school degree (20.3%), graduate school (12.7%), and some high school (1.7%). For income level, 41.1% had a household income of US$40,000 to US$79,999, followed by US$39,999 or less (32.1%) and US$80,000 or more (26.7%). Most participants (90.7%) stayed in a hotel in the last year, and about half of the respondents (52.9%) stated that they had stayed in a hotel five or more nights in the last year. All respondents indicated that they use the internet daily; 52.4% of them replied that they are on the internet more than 5 hr a day. In addition to high internet usage rates, respondents appear to be users of online review websites, with all the respondents reporting that they had spent time on an online review website in the previous week. Thus, the respondents are deemed suitable to the task.

Results

Manipulation and realism checks

For the procedural justice manipulation, there was a significant difference between high procedural justice (M = 5.48) and low procedural justice (M = 2.60), t = 21.503, p < .001. For the interactional justice manipulation, there was a significant difference between high interactional justice (M = 5.35) and the low interactional justice (M = 1.94), t = 26.571, p < .001. For the social presence justice manipulation, there was a significant difference between high social presence (M = 4.39) and low social presence (M = 3.69), t = 3.739, p < .001. Regarding realism, the respondents rated the description of the online review and the manager’s response (M = 5.23) and indicated that they could easily imagine themselves as a viewer reading the messages online (M = 6.18). Taken together, these results indicate that the manipulation was successful.

Hypothesis testing

The analysis of variance (ANOVA) examined the main effects and interactions between the three independent variables (procedural justice, interactional justice, and social presence) on trust. The effect of procedural justice was significant (F = 44.248, p < .001), and customers indicated higher trust with high procedural justice (M = 4.64) than with low procedural justice (M = 3.80), supporting H1. Similarly, higher trust was found with high interactional justice (M = 4.91) compared with low interactional justice (M = 3.54) as the interactional justice effect was significant (F = 118.772, p < .001), supporting H2. The social presence main effect was not significant (F = 0.769, p = .381); thus, H3 was not supported. Most important, however, there was a significant three-way interaction effect of procedural justice, interactional justice, and social presence (F = 7.084, p < .01), supporting H4. Table 2 provides the summary of ANOVA results.

Table 2.

ANOVA Results.

Dependent Variable: Trust
Source	SS	df	MS	F	Significance	Partial η²
Corrected model	278.228^a	7	39.747	24.600	.000	.300
Intercept	7,277.290	1	7,277.290	4,504.076	.000	.918
Procedural justice	71.492	1	71.492	44.248	.000	.099
Interactional justice	191.901	1	191.901	118.772	.000	.228
Social presence	1.242	1	1.242	0.769	.381	.002
Procedural justice × Interactional justice	0.116	1	0.116	0.072	.789	.000
Procedural justice × Social presence	2.723	1	2.723	1.686	.195	.004
Interactional justice × Social presence	3.488	1	3.488	2.159	.143	.005
Procedural justice × Interactional justice × Social presence	11.446	1	11.446	7.084	.008	.017
Error	649.516	402	1.616
Total	8,278.222	410
Corrected total	927.744	409

Note. SS = sum of squares; MS = mean square.

R² = .300 (adjusted R² = .288).

The lowest trust (M = 2.85) was found when both procedural and interactional justice are low but social presence is high, and the highest trust (M = 5.40) was found when all three elements are high (see Table 3 for cell means). Although there were no two-way interactions between any pairs of three elements, the significant three-way interaction showed that the effects of procedural justice and interactional justice were different at the social presence level (see Figure 2 for interaction plots). In particular, when both interactional justice and social presence were low, procedural justice did not make much difference on trust (M = 3.42 vs. M = 3.72). However, when interactional justice was low but social presence was high, the procedural justice effect changed drastically by polarizing its effect (M = 2.85 vs. M = 4.12). In fact, the cell means and interaction patterns show that when both interactional and procedural justice were low, high social presence lowered trust (M = 2.85) resulting in the lowest trust, which is lower than when all three elements were low (M = 3.42). However, when both interactional justice and procedural justice were high, social presence did not make much difference (M = 5.28 vs. M = 5.40). However, social presence helped in increasing trust (M = 4.70 vs. M = 4.24) when procedural justice was low but interactional justice was high.

Table 3.

Cell Means.

Procedural Justice	Interactional Justice	Social Presence	n	Trust
Low	Low	Low	54	3.42 (1.44)
Low	Low	High	48	2.85 (1.21)
Low	High	Low	52	4.24 (1.25)
Low	High	High	54	4.70 (1.24)
High	Low	Low	46	3.72 (1.25)
High	Low	High	54	4.12 (1.44)
High	High	Low	49	5.28 (1.18)
High	High	High	53	5.40 (1.09)

Note. Standard deviations are shown in parentheses. All scores are based on a 7-point Likert-type scale (1 = strongly disagree, 7 = strongly agree).

Figure 2.

Interaction Plots.

Mediation analysis

We examined a mediation analysis using the bootstrapping approach (Hayes, 2017) to examine the psychological mechanisms underlying our model’s effects. In the model, the three-way interaction was entered as the independent variable, trust was entered as the mediation variable, and behavioral intentions was entered as the dependent variable. Bootstrapping results stated a significant mediation process effect (5,000 samples, indirect effect = −1.234, 95% confidence interval [CI] = [0.923, 1.548]). Thus, H5 is supported, and Table 4 provides mediation results.

Table 4.

Mediation Results Summary.

Dependent Variable	Trust			Behavioral Intentions
Dependent Variable	B	SE	p	B	SE	p
Constant	4.061	0.076	.000	−0.308	0.126	.015
PJ × IJ × SP	1.342	0.212	.000
Trust				0.920	0.029	.000
R		.299			.860
R ²		.090			.739
F		40.136			576.578
df		1, 408			2, 407
p		.000			.000
Direct and Indirect Effects	Effect	SE	t	p	LLCI	ULCI
Direct effect of PJ × IJ × SP on behavioral intentions	1.459	0.231	6.326	.000	1.006	1.913
Indirect effect of PJ × IJ × SP	1.234	0.158			0.923	1.548

Note. PJ = procedural justice; IJ = interactional justice; SP = social presence; LLCI = lower limit of the confidence interval; ULCI = upper limit of the confidence interval.

Discussion

Overall, the main study results present strong evidence in support of the proposed conceptual framework for understanding potential customers’ evaluation of a company’s response to negative online reviews. In terms of “what” to include in the company’s response, this research suggests that both perceived justice and social presence perspectives in a combined manner are helpful in identifying the three key elements of the company response to address negative online reviews effectively. In terms of “how” potential customers evaluate the company’s response to a negative online review, this research demonstrates the underlying mechanism that a company response to a negative online review serves as a signal that implies a service quality commitment; potential customers use it to form inferences about the trustworthiness of the company, and it consequently influences purchase intentions.

Although most of our hypotheses are supported, except for H3, the most important findings would be the three-way interaction effect of procedural justice, interactional justice, and social presence on trust and the mediating effect of trust. Interestingly, trust was lowest when social presence was high but both procedural justice and interactional justice were low, and it was lower than when all three elements were low, which is when it is expected that the lowest trust may be found. These findings suggest that social presence magnifies the negative effects of low justice in company response. In other words, when the manager responds slowly without apology/explanation, social presence backfires and potential customers have more negative perceptions about the manager’s response when it is accompanied with manager’s photo and direct contact information. It can be understood that when justice is not restored, its negative effect on trust is highlighted by having a sense of someone in the response. Customers may raise expectations by sensing someone in the communication but perceiving low justice as incompetence at the same time. However, social presence helps increasing trust whenever it is accompanied by either interactional justice or procedural justice. Although the most effective way to increase trust was when all three elements were present in the manager’s response, the results reveal that when both interactional and procedural justice are included in the manager’s response, high trust was achieved regardless of social presence. This means that as long as justice is restored, social presence has a minimal incremental effect.

This three-way interaction effect is noteworthy because previous studies have not found interaction effects of elements in company response. Sparks et al. (2016) examined the effects of hotel manager’s response via source of response, speed of response, voice of responder, and action frame on trustworthiness, however did not find any interaction effect, and concluded that the four elements of company response may work independently. Similarly, Min et al. (2014) examined the effects of manager’s response via emphatic statement, paraphrasing statement, and speed of response on satisfaction with response; yet, none of interaction effects were significant in their results. On the contrary, our research found a three-way interaction effect of procedural justice, interactional justice, and social presence on trust. Overall, social presence exacerbates the negative effects on trust when both interactional justice and procedural justice were not presented appropriately in the company’s response. However, when both interactional justice and procedural justice were high, the social presence effect became small in increasing trust. Based on these results, we encourage further investigations on interaction effects of elements in managerial response to negative online reviews.

This study also provides some useful insights by examining the full mediation effect of trust on a company response to negative online reviews and potential customers’ behavioral intentions. Although previous research findings on company response to negative online reviews are mixed with positive results (e.g., Breitsohl et al., 2010) and negative results (e.g., Mauri & Minazzi, 2013), both the negative outcomes led by skepticism and the positive outcomes including credibility directed us to test the role of trust in customer evaluation of company response to negative online reviews. Potential customers’ purchasing intentions are not just simply based on whether a company responded to the negative review or not, but rely on whether a company response is effective in increasing trust in potential customers’ minds. Demonstrating the full mediating role of trust between the company response and customer behavioral intentions, our research not only clarifies the mixed results of previous studies but also allows a better understanding of customer perceptions of company response to negative online reviews. This finding is consistent with previous studies examining trust as a mediating variable in service recovery studies (e.g., DeWitt et al., 2008), suggesting that trust is important in understanding how potential customers evaluate company’s response to negative online reviews and determining their purchasing decisions.

Theoretical Implications

Integrating literature on perceived justice, social presence theory, and signaling theories, our research develops a model to explain how potential customers evaluate company responses to online complaints. In particular, this research contributes to the emerging literature of company response to online reviews in three theoretical aspects. First, this study relates to the justice theory in online review management and service recovery literature and extends it to online review management context. Although previous studies examine the company response effectiveness via attributes-based approach, for example, paraphrasing, empathy, and speed in Min et al. (2014) and source, voice, action frame, and speed in Sparks et al. (2016), this research examines the company response effectiveness via theory-based approach. Furthermore, most justice-based frameworks applied in service failure literature have focused on face-to-face complaints and recovery; our research extends it to the online review management context by examining how viewers evaluate company responses to online complaints. A company’s response to negative online reviews can be viewed as company-initiated service recovery in the online context; procedural justice and interactional justice are identified as key elements in understanding how viewers interpret the exchange between a manager response and a review in the online context. Furthermore, Min et al. (2014) emphasize that companies should respond to negative online reviews by following the same principles as in face-to-face service recovery. Our research confirms that procedural justice (e.g., monitoring, response time) and interactional justice (e.g., apology, explanation) are useful in the online review context to understand how potential customers perceive company’s response to negative reviews.

Second, this study suggests social presence as an important element to influence the effectiveness of managers’ responses in online review management. Although face-to-face complaints are managed through service recovery, negative reviews on third-party review websites present challenges for companies to respond to them effectively. Social cues normally available in face-to-face communication (e.g., voice quality, appearance, movements, and facial expressions) are often absent in online communications (Cui et al., 2010; Walther et al., 2005). Consequently, online communications tend to be more detached and automated than those in traditional face-to-face interactions, resulting in perceptions of lacking human warmth and sociability (Hassanein & Head, 2007). Although social presence has been studied in communication and e-commerce research that focuses on a website design to increase trust among users (e.g., Gefen & Straub, 2004; Hassanein & Head, 2007), this research incorporates it in the company’s negative online review management context. Furthermore, unlike previous studies (e.g., Min et al., 2014; Sparks et al., 2016), this research reports the three-way interaction effect of the response elements. This research demonstrates that social presence conveyed through a company’s response on an online review site can affect potential customers’ perception of trust toward the company; yet, its effect depends on the justice elements in the company response. High social presence helps increase trust when both procedural justice and interactional justice are presented strongly in the company’s response. However, high social presence has a reverse effect by decreasing trust when two justice dimensions are poorly presented in the company response. Potential customers may consider high social presence as a “sham” when a company response does not appropriately address justice. This is meaningful not only in finding that elements of online response are not simply additive in their effects but also in providing a possibility to future researchers to uncover more interaction effects of company response elements.

Third, this study contributes to emerging literature on company response to online reviews by documenting the role of trust. Although some literature on the company response to online reviews has emerged recently (e.g., Y. L. Lee & Song, 2010; Mauri & Minazzi, 2013; S. Y. Park & Allen, 2013; Sparks et al., 2016), the results are inconclusive with mixed outcomes. Although there is increasing evidence that company response to negative online reviews may be beneficial, few scholars have examined the underlying mechanism of how do company’s response strategies affect potential customers. Furthermore, although potential customers consider that online reviews provide a reliable basis upon which to make future purchase decisions (Flanagin & Metzger, 2013), the process of how company response to online reviews affects potential customers’ behavioral intentions has not been clear. For example, Sparks and Browning (2011) show that potential customers’ perception of trust and booking intentions are influenced by review valence and framing. However, they did not examine company response to online reviews in their examination of trust and booking intentions. Also, trust and booking intentions are examined separately without considering the role of trust between customer perceptions of online review and booking intentions. Later, Sparks et al. (2016) suggest that a company’s online response increases potential customers’ inferences of trust and concern about the company; yet, the role of trust in predicting purchase intentions is not examined. Bridging the gap in the previous studies, this research demonstrates that trust plays an important mediating role between customers’ evaluations of a company response to negative online reviews and their purchase intentions.

Managerial Implications

Hospitality companies should understand how online reviews and company response affect potential customer’s perceptions of their firm. Researchers suggest that the widespread use of online reviews can be an opportunity rather than a threat for hospitality companies (e.g., Litvin et al., 2008); yet, managers have struggled with how to respond to online reviews, especially negative ones that damage a company’s image and sales. Our preliminary study suggests that potential customers have higher behavioral intentions toward a restaurant that responds to negative online reviews than a company that does not respond. Our main study further suggests not just a response but an effective response considering justice and social presence elements in the hotel context. Hospitality firms should recognize the importance of reaching out to customers who express dissatisfaction on online review sites by establishing a response system to deal with negative reviews across various online platforms. S. Y. Park and Allen (2013) suggest that hotel managers should consider their overall approach to utilizing online review information in their operations. It is recommended that hotel companies set and create a system and guidelines for responding to online reviews and allocate the technology, support, personnel, and training to manage online reviews effectively. For example, hotels should address specific operational processes such as who will respond to the negative review, how fast the review should be responded to, and the content of the response.

Although many online review sites, such as Tripadvisor.com, provide some tips for responding to reviews, our findings shed light on response strategies to enhance trust in the online environment by utilizing three key elements, procedural justice, interactional justice, and social presence. Hotel company response should communicate that the company monitors online reviews and has a process in place, be immediate, and state that the firm is equitable, fair, and consistent. A quick and timely response is important on many online review websites because a timestamp is often included in the manager’s response to online complaints. This is especially important because online reviews can occur across time zones. Because interactional justice refers to the way people are treated in service recovery, hotel managers can show empathy, dignity, and respect in their response. Y. Chen and Xie (2008) stress that company response should avoid standardized and defensive strategies. To showcase interactional justice, a hotel company’s response should validate the complaining customer’s response, provide an apology for the dissatisfying experience, and reserve judgment.

Social presence cues (e.g., a manager’s direct contact information and a photograph) alone do not increase trust. However, when social presence is accompanied with procedural justice (quick response time and regular monitoring) and interactional justice (apology and explanation), higher trust can be achieved. Currently, most online review response strategies used by hotel companies are limited to utilizing text in their response, and increasing social presence on the review sites is challenging. Many retail websites have been successful at incorporating tactics of social presence (e.g., webchat, avatar), and online review websites should explore some tactics that could be used for online review websites, giving hotel managers more options for incorporating real or imagined elements of social presence in company response. Imaginary interactions include socially rich picture content (Cyr et al., 2007), socially rich text content (Gefen & Straub, 2004), human audio (Lombard & Ditton, 1997), human video (Kumar & Benbasat, 2006), and photographs (Gefen & Straub, 2004). In addition, people also express their emotions through computer networks by using emoticons that use typographic symbols to resemble facial expressions (Walther & D’Addario, 2001). Hotel managers should consider incorporating various social presence cues in their responses to negative online reviews by appropriately restoring justice.

Limitations and Future Studies

There are several limitations of this study that warrant attention and provide suggestions for future studies. First, our experimental design involved one negative review and one manager response to examine potential customers’ reactions to such interactions in an online review site context. However, potential customers are often exposed to multiple positive and negative reviews that may or may not have company’s response. As C. H. Lee and Cranage (2014) suggest that the effect of organizational response is stronger when there is high consensus presented in a set of consumer reviews, future studies should consider various conditions, such as mixed reviews and a company response to a negative review only, mixed reviews and company responses to both positive and negative reviews, and multiple negative reviews and multiple company responses. In addition, this study focused on negative reviews. Although previous studies have shown that customers are more reactionary to negative reviews (e.g., M. Lee et al., 2009), it is not currently understood how a manager response to positive or neutral reviews affects potential customers. Thus, future studies are encouraged to examine potential customers’ trust and behavioral intentions based on manager responses to positive and neutral reviews.

Second, this research focuses on procedural justice and interactional justice to examine the impact of company response to negative online reviews on potential customers. Although it is neither practical nor common for companies to promise or provide distributive justice (e.g., compensation) on online review sites and researchers suggest that distributive justice is ineffective in increasing trust and purchase intentions (Cheng & Loi, 2014), future studies may explore the ways to incorporate distributive justice in the company response to online review context effectively.

Third, this study focused on how potential customers perceive company response to negative online reviews in the hotel context. Although we believe that our theoretical model is applicable to negative online review management in other hospitality contexts, additional research is required to test the applicability of the model and increase generalizability of the current research findings. Furthermore, we encourage future research to extend the findings of this research to different hospitality contexts considering potential moderators. For example, Airbnb is an emerging segment in the hospitality industry, and potential customers use online reviews to aid their purchasing decisions (Fradkin et al., 2015). Because Airbnb is a customer-to-customer business that is different from most business-to-customer hospitality products (Zervas et al., 2017) and an owner’s response to customer reviews may have a stronger impact on potential customers’ perception of the product than other business-to-customer hospitality products. Also, some researchers suggest that customer confidence influences how online reviews are perceived (H. H. Lee & Ma, 2012). Future research may examine how different levels of customer confidence (e.g., expert and novice) perceive online reviews and company responses in different business model contexts (e.g., business-to-customer and customer-to-customer).

Finally, this research examined social presence as a way to increase trust toward a company; yet, further research is suggested to explore how a company should reply to online reviews to be perceived as genuine and credible. Building on studies on different communication strategies and styles, for example, defensive versus accommodative strategy (Marcus & Goodman, 1991) and company-focused versus customer-focused communication style (Bonfanti et al., 2016), future research is suggested into ways in which to best respond to online reviews.

Footnotes

Appendix A

Appendix B

Main Study Measurement Items.

Variable	Items
Procedural justice	It took the hotel a reasonable time to react to the complaint. The hotel was very prompt in responding to the complaint. The complaint was taken care of as quickly as it could have been. The hotel has good policies and practices for dealing with complaints. The manager routinely monitors online reviews for feedback.^a
Interactional justice	The response included a genuine apology. The customer received a sincere “I am sorry” from the manager. The response provided an explanation of why the problem occurred. The explanation of the problems in the response was convincing.
Social presence	There is a sense of human contact in the response. There is a sense of personalness in the response. There is a sense of sociability in the response. There is a sense of human warmth in the response. There is a sense of human sensitivity in the response. There is a real person in the response.^a
Trust	I feel that this hotel is trustworthy. I have confidence in the services of this hotel. I feel that this company has the ability to provide good services.^a
Purchase intentions	I would stay at this hotel in the future. The likelihood of booking this hotel is very high. The probability that I would consider booking this hotel is very high.

Additional new items.

Declaration of Conflicting Interests

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

Funding

The author(s) received no financial support for the research, authorship, or publication of this article.

ORCID iD

Eric D. Olson

Notes

Author Biographies

Eric D. Olson is currently an Assistant Professor in the Department of Apparel, Events, and Hospitality Management at Iowa State University. His research interests are in LGBT events and tourism.

Heejung Ro’s research focuses on the evaluation of service encounters that involves customer behavior and front-line employee interactions with customers. She also conducts research on LGBT customers’ perceptions of hospitality services from a social justice perspective.

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