Take Care – Say ‘Sorry’?
The Effects of Webcare Strategies on Social Media and the Influence of Message Personalization and Message Authenticity
Master’s Thesis
Selina Peukert, Student ID: 10697012
Master’s Programme Communication Science
Persuasive Communication
Supervisor: Dr. Guda van Noort
Abstract
Organizations are increasingly experiencing customer complaints on social media, as the Web 2.0 has empowered consumers to voice their negative remarks about a company publicly with a huge audience witnessing. The practice of responding to these negative comments, also referred to as webcare, has gained importance as online complaints can negatively affect consumers’ brand responses and lead to organizational damage. This research examined how different webcare responses and their degree of personalization can influence the consumers’ brand re-sponses and whether the consumers’ perceived authenticity of these rere-sponses would mediate the effects. These aims were operationalized in a 3 (accommodative vs. defensive vs. no webcare) x 2 (personalized vs. corporate messages) experiment. The results show that an accommodative webcare response is the most suitable in evoking favourable brand responses. A direct effect of message personalization was found, as personalized webcare responses, regardless of them being accommodative or defensive, lead to more positive brand responses. However, the results
demonstrated that the webcare response types did not interact overall with message personaliza-tion, as only for the consumers’ positive word-of-mouth (PWOM) intention message personali-zation could significantly enhance the effectiveness of a defensive response. The effectiveness of accommodative webcare responses could not be improved by personalizing them. In addition, this research uncovered that the consumers’ perceived authenticity mediates the effects of the different webcare responses on the consumers’ brand responses. The findings are discussed tak-ing into consideration the challenges organizations face to find the right approach to deal with negative word-of-mouth (NWOM) on social media.
Keywords: Negative word-of-mouth, webcare, message personalization, authenticity of electronic word-of-mouth, complaint handling
“I am sick to my stomach after seeing the Kent State sweater. Absolutely disgusted with the UO [Urban Outfitters] company. Planning to never shop UO or its other companies, Anthro & Free People again”. “Airberlin, your customer service is horrendous”. “Two hours just to can-cel a line. AT&T you guys are insulting to every customer who does business with you.” These statements are just a few examples of consumers who use negative electronic word-of-mouth (hereafter: NWOM) on social media, to vent for instance their anger, dissatisfaction or negative experiences with companies. Social media depicts a double-edged sword for companies: Con-sumer empowering and interactive Web 2.0 applications do not only offer great new marketing potentials, but also allow consumers to use this two-way communication to distort and hijack brand messages, as well as to voice their complaints (Fournier & Avery, 2011; Hennig-Thurau et al., 2010; Xia, 2013). A study revealed that about 50% of the social media users voice their com-plaints or negative feedback regarding brands or services at least once a month (Nielsen, 2012). NWOM information has to be taken seriously, as it can have detrimental effects on the consum-ers’ brand responses (e.g., Davidow, 2003; Fournier & Avery, 2011; Lee & Song, 2010).
The complaint nature has undergone a fundamental change by evolving from a private conversation between the complainer and the company to being a public matter. By posting complaints visibly on social network sites, blogs, forums or brand communities, other consumers are able to witness the complaint situation (Constantinides & Fountain, 2008; Hennig-Thurau et al., 2010). The Web 2.0 enables complaints to spread easily, rapidly and widely and complaints therefore also depict a threat to the relationship a company has with the observing audience and endangers the brand responses of this audience, who might too engage in NWOM and hereby increase the range of organizational damage (Breitsohl, Khammash, & Griffiths 2010; Fournier & Avery, 2011). The negative impact of NWOM and its potential to be multiplied, demonstrate that companies need to engage in effective complaint handling, as their actions online can have harmful effects on multiple stakeholders. The necessity to find customer satisfying strategies to
address NWOM is furthermore emphasized by the fact that about half of the complaining con-sumers are dissatisfied with how companies handle their complaints (Estelami, 2000).
Webcare, “the act of engaging in online interactions with (complaining) consumers, by actively searching the web to address consumer feedback (e.g. questions, concerns and com-plaints)” (Van Noort & Willemsen, 2011, p. 133), has been found as such an effective strategy to counteract NWOM. Previous research on complaint handling and service failure recovery
demonstrated that effective corporate responses cannot only mitigate the effects of NWOM, but also lead to customer loyalty (Orsingher, Valentini, & de Angelis, 2010), positive word-of-mouth (hereafter: PWOM; e.g., Davidow, 2003; Maxham & Netemeyer, 2002), repurchase inten-tions (e.g., Davidow, 2003) and commitment and trust (Tax, Brown, & Chandrashekaran, 1998). As these outcomes are desirable for companies, the question arises as to what extent different webcare responses can contribute to reaching these goals.
Companies can respond to NWOM in several ways by for example apologizing, offering compensation or promise corrective actions (e.g., Lee, 2004). These accommodative webcare responses are oppositional to defensive webcare responses, which include denying the responsi-bility, attacking the accuser or shifting the blame to others (e.g., Davidow, 2003; Kerkhof, Beugels, Utz, & Beukeboom, 2011; Lee & Song, 2010). Although engaging in webcare depicts a company’s opportunity to demonstrate that they are open to address the consumers’ criticism and needs (Willemsen, 2013), not all webcare responses show equal effectiveness. Accommodative webcare responses have been found to result in positive brand evaluations (e.g., Lee & Song, 2010) and PWOM (Gelbrich & Roschk, 2011). Research revealed that defensive webcare re-sponses are not very well accepted by consumers, as they feel disappointed in the company’s complaint handling process and have the perception that the company is at fault (Gelbrich & Roschk, 2011; Lee & Song, 2010). Companies might also ignore NWOM altogether, which gives consumers the feeling that the company does not care about them or does not take their complaint seriously (e.g., Fournier & Avery, 2011; Lee & Song, 2010). Deriving from above
stated, the first research aim is to investigate which of these webcare strategies are suitable in evoking favourable marketing-related brand responses, such as brand attitude, purchase intention and PWOM intention. By concentrating on a marketing perspective, this study will extend previ-ous research, which mainly focussed on complaint handling from a PR perspective (e.g., Kerkhof et al., 2011), in connection with a crisis (e.g., Lee, 2004) or from a customer service perspective (e.g., Gelbrich & Roschk, 2011, Holloway & Beatty, 2003). Through taking into consideration the importance of the observing audience (e.g., Breitsohl et al., 2010), this study will not only provide managerial implications on how to integrate webcare in the marketing mix, but also state guidelines on what to respond to NWOM to have a positive effect on multiple stakeholders.
Asides the webcare response type being crucial at influencing the consumers’ brand re-sponses, it is also important how the response is conveyed, thus what kind of tone of voice is used (e.g., Park & Lee, 2013; Van Noort & Willemsen, 2011). Conversational human voice, which is “an engaging and natural style of organizational communication as perceived by an organization’s publics based on interactions between individuals in the organization and the in-dividuals in publics” (Kelleher, 2009, p. 177) has been found to be a valid predictor of the effec-tiveness of the different webcare responses (Van Noort, Willemsen, Kerkhof, & Verhoeven, forthcoming). Whereas past research concentrated on conversational human voice as a whole, this study will extend previous findings by breaking down the construct and examining one indi-vidual component, message personalization. It is assumed that message personalization, opera-tionalized through the company identifying who is responding on behalf of them and addressing the consumer by name along with using a multitude of personal pronouns, can improve the effec-tiveness of a message and evoke favourable consumer responses (Kwon & Sung, 2011; Park & Lee, 2013). The second aim of this thesis consists out of examining how message personalization can enhance the effectiveness of webcare responses and providing insights for marketers on how they can convey their webcare responses in a human and personal manner.
Preceding research in the customer service context (Gruber, 2011) and the PR context (Kerkhof et al., 2011) found that the tone of voice of a message and its content interact with each other: It has been postulated that the effectiveness of accommodative responses can be enhanced if the responses are also personalized (Gruber, 2011), and research demonstrated that message personalization can compensate defensive responses, as consumers get the feeling that the com-pany wants to build a relationship with them (Kerkhof et al., 2011). Until now no research has tested the interaction between the different webcare response types and message personalization from a marketing perspective, in which the attainment of marketing-related goals is a central requirement of a company’s webcare efforts. Thus, the third aim of this study is to provide prac-tical value, as it is expected that consumers will react differently to the different webcare re-sponses when they get the feeling that they are dealing with a real person instead of an anony-mous organization (Park & Lee, 2013).
Although companies can determine the content of their response and decide which tone of voice they apply to it, consumers might perceive the message differently than intended by the company (Van Noort et al., forthcoming). For instance, saying ‘sorry’ is an apology, but to what extent it really portrays the company’s sincere regret, is up to the consumers to decide (Van Noort et al., forthcoming). Greyser (2009) postulated that corporate authenticity is central at all times, but especially in critical situations (e.g. consumer complaints), companies need to make authenticity an inalienable constituent of their communication. Authentic messages are success-ful at being accepted by the audience and lead to favourable brand responses (Huang, Cai, Tsang, & Zhou, 2011; Liao & Yang, 2012). Research found accommodative strategies to be ef-fective in eliciting high authenticity perceptions, as apologies evoke the consumers’ feeling that the company responds in a credible and genuine manner (Gelbrich & Roschk, 2011; Gruber, 2011; Liao & Yang, 2012). Additionally, it has been demonstrated that the perceived authenticity of a response can be enhanced when the response is conveyed with a personal tone of voice, as this increases the consumers’ perception of genuineness and sincerity (Bell & Zemke, 1987).
This points towards an interaction of webcare response type and message personalization on the consumers’ perceived authenticity, thus theoretical value can be found in uncovering the influ-ence of perceived authenticity as underlying mechanism to explain the varying effectiveness of the different webcare responses and their degree of personalization. As the above stated findings derived mainly from the service recovery context and crisis communication, the fourth research aim consists out of examining the role of authenticity from a marketing perspective in order to determine its importance for webcare.
Asides from providing theoretical value, this thesis will guide marketers in their use of webcare on social media by determining how effective complaint handling can be achieved through an adequate content and tone of voice of organizational messages. By doing so, this re-search will offer valuable insights into webcare’s potential to be a successful marketing tool.
Theoretical Framework
Online Complaint Handling as Marketing Practice
The characteristics of Web 2.0 applications have facilitated the creation and dissemina-tion of online complaints: Publicly accessible social media sites serve as popular platforms for consumers’ complaints, which can easily be shared with a multitude of other consumers without having financial or physical efforts attached to it (Fournier & Avery, 2010; Hennig-Thurau et al., 2010). Due to various consumer empowering tools to rate or rank companies, consumers have increasingly voiced their criticism of companies (Fournier & Avery, 2011). Fournier and Avery (2011) postulate that these developments led to an “age of criticism” (p. 200), in which effective complaint handling has become a full-time job. Consumers, who are networked together based on a positive ground, can be valuable allies, but if consumers unite based on their shared criti-cism of the brand, they can pose a great threat to companies (Fournier & Avery, 2011). That this is a serious matter, underlines the fact that 70% of social media users rely on the experiences and opinions of others when making decisions (Nielsen, 2012). Research on the acceptance of
elec-tronic word-of-mouth (hereafter: WOM) information has revealed that consumers believe and accept NWOM more than PWOM (Huang et al., 2011). The above stated illustrate the im-portance of webcare being an impression management tool for the observing audience, as the witnessing consumers play the decisive role in multiplying negative brand experiences online (Breitsohl et al., 2010).
Webcare can be studied from various theoretical perspectives, which differ in their con-sideration in which department of a company complaint handling is allocated and what organiza-tional goals should be reached with it (Van Noort et al., forthcoming). Whereas a vast amount of research examines complaint handling in connection to service failure recovery efforts and an-chors webcare in the customer care department of an organization (e.g. Holloway & Beatty, 2003; Maxham, 2001), or examines the role of complaint handling as crisis management tool (e.g., Lee, 2004), there also exists a research stream which emphasizes the marketing and PR potential of effective complaint handling (e.g. Kerkhof et al., 2011; Tax et al., 1998; Van Noort et al., forthcoming; Willemsen, Neijens, & Bronner, 2013). This study will specifically concen-trate on webcare as part of marketing, as this perspective challenges companies to embrace com-plaints in a way that they are the consumers’ attempts to strengthen their relationship with a company (Kim, Kim, & Kim, 2009; Shields, 2006; Willemsen et al., 2013). Any interaction with customers, even if they are of negative nature, can be the first step in fortifying the relationship with the customers, as effective complaint handling evokes a positive feeling, which can turn into trust and satisfaction (Kim et al., 2009). This perspective promotes the consideration that webcare should exceed being an ad-hoc strategy to mitigate the negative impact of complaints.
The Effects of Different Webcare Response Strategies
Although research on the effects of different webcare strategies is still to some extent limited, previous studies have found important contributions for when to offer webcare (Van Noort & Willemsen, 2011) or what to respond to customers (e.g., Gelbrich & Roschk, 2011; Lee
& Song, 2010). According to Gelbrich and Roschk (2011), organizational responses to com-plaints can be divided into compensation, favourable employee behaviour and organizational procedures. Whereas these different response types emerged out of their meta-analysis based on customer service literature, it provides valuable insights in regards to the corrective actions of a company: Apologies, compensation and attempts to redress are the most commonly used ac-commodative response strategies (e.g., Kerkhof et al., 2011; Lee, 2004; Lee & Song, 2010). The counterpart of accommodative strategies are defensive strategies, in which companies shift the blame to others, attack the accuser or deny their responsibility for the incident (e.g. Kerkhof et al., 2011; Lee, 2004; Lee & Song, 2010). Whereas these strategies have their origin in customer care literature (Gelbrich & Roschk, 2011), crisis communication (e.g., Lee, 2004) or in face-to-face complaint situations (Bell & Zemke, 1987), the differentiation based on the varying content and approach of the messages also applies to the social media context used in this study.
In the context of marketing, companies use accommodative webcare strategies to show their efforts to restore the relationship with their customers. Given the positive approach of these responses and an organization’s intention to make it up to the customer, previous research found them to be more effective than no response to NWOM or defensive responses (e.g., Kerkhof et al., 2011; Lee & Song, 2010). Compensations lead to perceived distributive justice, meaning that customers are satisfied with the complaint outcome, which in turn leads to repurchase intentions and PWOM (Gelbrich & Roschk, 2011). Companies tend to avoid offering apologies in their responses, as they consider them to be an admission of guilt (Gelbrich & Roschk, 2011; Sparks & Bradley, 2014). Kerkhof et al. (2011) underline that apologies are superior to their denial counterparts, as they, although evoking the consumers’ feeling that the company is responsible for the incident, lead to higher credibility and a positive attitude towards the response. Bell and Zemke (1987) furthermore postulate that apologies, as “acknowledgement of error” (p. 33), are vital in terms of easing annoyed customers and Tax et al. (1998) explain that they are necessary to restore the emotional costs of consumers. A response, which contains a combination of an
apology and compensation leads to greater purchase intention, than a response only incorporat-ing compensation (Wirtz & Mattila, 2004). The same applies for apologies, as they also not lead to positive reactions if presented by themselves as webcare response strategy (Davidow, 2003), thus a connection of apologies and compensation is recommended in order to reach favourable brand responses.
Companies that react defensively to NWOM neglect to consider complaints as an oppor-tunity to fortify customer relationships. Lee (2004) found that consumers in the denial-of-crisis responsibility condition, in which the corporate answer consisted out of shifting the blame to others, minimizing the severity or not commenting, reported on more negative impressions of the company, ascribed the responsibility for the crisis more severely to the organization, were less sympathetic towards the company and mistrusted the organization more than the participants in the accommodative condition. Defensive webcare responses are not only ineffective at leading to favourable brand responses (Lee & Song, 2010), but they also do not evoke the consumers’ sym-pathy with the company (Kerkhof et al., 2011).
The above stated research findings differ in their perspective on complaint handling from this study, as many have their origin in customer service literature (e.g., Gelbrich & Roschk, 2011) or crisis communication (e.g., Lee, 2004), which is also reflected in the examined com-plaint outcomes. Whereas previous research focussed on comcom-plaint web sites (e.g., Lee & Song, 2010) or face-to-face situations (e.g., Bell & Zemke, 1987) as complaint environment, this study will examine the effectiveness of webcare response strategies in the social media context. Social media is not only a central vehicle for a company’s marketing activities, but also depicts an es-sential tool for a company’s webcare efforts since a lot of consumers use social media to engage with organizations (Nielsen, 2012). Hence, the first hypothesis reads as follows:
H1. An accommodative webcare response leads to more positive brand responses than a defen-sive webcare response and no response to NWOM.
Consumers resent being ignored when they take the effort to engage with companies by writing a complaint (Fournier & Avery, 2011), but there is still disagreement among researchers as to what extent reacting defensively can lead to higher brand responses than not providing a response to NWOM. Dekay (2012) found that not responding cannot count as acceptable
webcare strategy as it does not promote conversation and depicts a company’s missed out oppor-tunity to turn negative comments into valuable opportunities. Lee and Song (2010) demonstrated that participants in the defensive response condition reported on worse brand responses and higher blame attributions than consumers in the no response condition. Lee (2004) included the no response condition in the defensive webcare cluster, which calls for caution when interpreting her results as these two conditions will be treated separately in the present study. Nevertheless, the study by Lee (2004) offers a crucial insight: When independently comparing the no response condition with the ‘shifting the blame’ condition it was found that participants who did not re-ceive a corporate response attributed less responsibility to the company but had a greater nega-tive impression of the company than participants who were in the ‘shifting the blame’ condition (Lee, 2004). This is contrary to Lee and Song (2010) as they claim that defensive responses lead to greater blame attributions than not responding. Interestingly, Lee (2004) additionally demon-strated that participants who did not read a corporate response had more trust and sympathy to-wards the company than participants in the ‘shifting the blame’ condition. This is again in line with the study of Lee and Song (2010), in which participants in the no response condition rated the brand more positively than participants receiving a defensive response.
Lee (2004) investigated the effectiveness of the different response strategies in the con-text of crisis communication and Lee and Song (2010) looked at organizational responses on a complaint website, thus examining the effects of proactive webcare (Van Noort & Willemsen, 2011), but it is arguable that ignoring consumers or responding defensively is acceptable in terms of webcare being a tool to manage customer relationships and reach marketing-related goals. Thus, the following research question was formulated:
RQ1. To what extent does a defensive webcare response lead to more positive brand responses than no response to NWOM?
The Influence of Message Personalization
Applying a human presence to organizational communication on social media is vital as it serves as cue for consumers that they are communicating with real people (Rybalko & Seltzer, 2010). Although social media platforms were established to facilitate the interaction between users and not as a promotion tool for marketers, they enable organizations to get closer to their customers, interact and engage with them in a more informal way and manage customer relation-ships (Fournier & Avery, 2011; Hansson, Wrangmo, & Solberg Soilen, 2013; Kwon & Sung, 2011). In order to be successful on social media and not come across as intruders, companies have to adapt their communication to the particular social media platform (Becker, 2013; Grundmann, 2015).
Message personalization can be applied to webcare by the means of two strategies. First-ly, the organization can be personalized (Van Noort et al., forthcoming): Brand anthropomor-phism, in which human attributes are connected to non-human entities (Kwon & Sung, 2011), can be used to attach a human feel to the organization. Using first-person pronouns (“I”, “we”) and identifying the individual communicating on behalf of the organization by name or photo are effective personalization strategies (Kwon & Sung, 2011; Park & Lee, 2013). Secondly, webcare responses can be personalized through tailoring the message to the individual customer, thus personalizing the receiver. Companies can address the customer by name and use second-person pronouns (“you”, “yours”, “yourself”) (Kwon & Sung, 2011). As this study was conducted among German speaking participants, German informal and formal second-person pronouns were used to differentiate between personalized and corporate messages: “Du” (being the infor-mal translation of “you”) personalizes a company’s approach to the consumer and reflects the
informal communication style on social media (Grundmann, 2015). “Sie”, on the other hand, the formal translation of “you”, conveys a distance and is perceived as rigid (Grundmann, 2015).
A personal communication style is an opportunity to fortify customer relationships and allows companies to signalize closeness and their openness to communication (Grundmann, 2015; Kwon & Sung, 2011). Park and Lee (2013), who conducted a study on the effectiveness of attributing a human presence to a company’s Twitter communication, demonstrated personaliz-ing the company facilitates to minimize the consumers’ feelpersonaliz-ing that they are communicatpersonaliz-ing with an anonymous organization. Message personalization evokes favourable brand responses and has a positive effect for relationship marketing, as engaging in a more human and personal commu-nication style promotes the consumers’ PWOM intentions and enhances their favourable percep-tions of the relapercep-tionship with a company (Park & Lee, 2013). By using the informal personal-pronoun “du”, consumers get the feeling of a higher emotional bond with the company and a company can encourage communication (Grundmann, 2015). This is in according with Kwon and Sung (2011), who found that the use of second-person pronouns on Twitter stimulates con-versations with the company and is successful at decreasing the impersonality of online commu-nications. In addition, account personal pronouns and non-verbal cues, such as abbreviations and emoticons, positively for the consumers’ feeling that companies are actually listening to them (Kwon & Sung, 2011).
The effects of message personalization can be explained with assumptions from infor-mation processing theories: The Elaboration-Likelihood-Model (ELM) suggests that individuals will be more motivated to process information centrally and elaborate, if the information is per-sonally relevant to them (Petty & Cacioppo, 1986). The ELM furthermore states that an in-creased elaboration leads to consumers devoting more effort on assessing the quality of the mes-sage characteristics (Petty & Cacioppo, 1986). Thus, consumers concentrate more on the argu-ments made in the message rather than relying on simple and easy-accessible heuristic cues, which consumers do when processing messages peripherally (Petty & Cacioppo, 1986). In the
context of webcare, personalized webcare responses provoke the consumers’ feeling that the message is highly relevant for them, which will promote their thoughtful processing of a compa-ny’s response. It has been proven that health care material is more successful when it is personal-ized (Kreuter, Bull, Clark, & Oswald, 1999), but previous research also found that message per-sonalization increases the effectiveness of marketing messages, as personalized messages lead to greater attention and heightened elaboration, as well as better information recall and higher per-ceived usefulness (Tam & Ho, 2005, 2006).
Whereas previous studies investigated the effects of message personalization on Twitter (e.g., Kwon & Sung, 2011; Park & Lee, 2013), being a platform with very specific communica-tion boundaries, this research will concentrate on the effects of personalized webcare messages on Facebook. This study will add to the scope of past research, which solely concentrated on message personalization operationalized through personalizing the company (e.g., Park & Lee, 2013) or giving a descriptive overview of how companies use brand anthropomorphism elements in their online communication (e.g., Kwon & Sung, 2011). In the present research, message per-sonalization will be applied using two dimensions, perper-sonalization of the company and the re-ceiver, and it will be examined how this can lead to favourable brand responses. Based on the above stated, the second hypothesis reads as follows:
H2. There is a direct effect of message personalization on consumers’ brand responses, such that personalized webcare responses lead to better brand responses than corporate webcare responses.
When in fact a personalized approach accounts positively for the consumers’ increased attention on the message, Kerkhof et al. (2011) argue that the tone of voice of a message can also interact with the content of a message: A personalized denial response leads to a greater percep-tion of the communicated relapercep-tional commitment of a company than a corporate denial response (Kerkhof et al., 2011). Gruber (2011) supports the assumption of an interaction effect, as he ex-plains that complaining customers wished for a personalized approach in connection with an
apology. Based on the findings of information processing theories, it is therefore expected that message personalization will increase the consumers’ attention on the message characteristics, which in turn will enhance the positive effects of accommodative webcare responses, as con-sumers devote more thoughts on the company offering them an apology and signalizing their efforts to make it up to them. Nevertheless, it is also expected that defensive webcare responses will lead to more positive brand responses if they are personalized (vs. corporate), as consumers value the customer-centralized approach and feel taken seriously (Kwon & Sung, 2011). Addi-tionally, it can be assumed that the positive effect of message personalization will make up for the negative nature of defensive webcare responses. Following this line of argument, the third hypothesis reads as follows:
H3a-b. The effects of the different webcare responses on brand responses are moderated by mes-sage personalization, such that a) the positive effect of an accommodative webcare response on brand responses will be increased by message personalization, and b) message personalization will improve the effectiveness of a defensive webcare response in evoking more positive brand responses.
The Role of Perceived Authenticity of Webcare Responses
With the content of a webcare response and the tone of voice applied to that response, companies try to determine how their response is perceived by the consumers. Nevertheless, a well thought out and communicated response might still be off target, because consumers per-ceive it differently than intended (Van Noort et al., forthcoming). This discrepancy between what is being communicated and how consumers understand it can lead to a failure of a webcare re-sponse (Van Noort et al., forthcoming).
An explanation why webcare responses can be ineffective is found when considering the consumers’ perceived authenticity of these responses. Authenticity constitutes a central charac-teristic of WOM information and authentic information consists, according to Huang et al.
(2011), of three concepts: Credibility, trustworthiness and reliability. Huang et al. (2011) adapted this understanding from Rieh’s (2002) explanation of information authority, which is important for the judgement of web information. The standard of authenticity, and especially its compo-nents credibility and trustworthiness, is used to evaluate the content and the tone of voice of a message (Huang et al., 2011). The notion of authenticity being a multi-dimensional construct is also shared by Greyser (2009) as he argues that corporate authenticity consists of four parts: Companies have to talk authentically, be authentic (the core values and previous behaviour have to be in accordance), stay authentic (stand by core values), and defend their authenticity in times of crisis. The first constitute is in line with Mitra and Watts (2002), who point out that an authen-tic voice has to speak genuinely and ethically. For the context of this study authenauthen-tic communi-cation is the key, as the consumers’ perception of a webcare response’s authenticity is merely based on the content of the response and how it is framed.
Authenticity is central for the effectiveness of a company’s webcare message, as per-ceived authenticity serves as a valid predictor of the consumers’ acceptance of WOM infor-mation (Huang et al., 2011; Liao & Yang, 2012). This is supported by Sparks and Bradley (2014), who examined the effectiveness of organizational responses to negative online hotel re-views, as they explain that an authentic organizational response which is perceived as honest, thorough and adequate, leads to positive customer evaluations. These positive evaluations also translate to favourable behavioural intentions, as high message authenticity accounts for the con-sumers’ intention to resend that information (Huang et al., 2011). Research has furthermore demonstrated that authentic and credible WOM information can lead to purchase intention (Liao & Yang, 2012). In the context of customer care, authentic employee behaviour depicts the most important requirement for customer satisfaction (Gruber, 2011), which again is central for posi-tive brand responses (e.g., Gelbrich & Roschk, 2011; Orsingher et al., 2009; Tax et al., 1998).
Whereas the above stated findings underline that authenticity can lead to favourable brand responses (e.g., Huang et al., 2011; Liao & Yang, 2012), it remains questionable how
dif-ferent webcare responses and their degree of personalization can influence the consumers’ au-thenticity perceptions. Past research did not examine the auau-thenticity of webcare responses in particular, but rather concentrated on authentic customer service employee behaviour (e.g., Bell & Zemke, 1987; Gruber, 2011) or the role of authenticity in crisis communication (e.g., Greyser, 2009). Nevertheless, these results hint towards an interaction between the variables webcare re-sponse type, their degree of personalization and authenticity: An apology and a personal ap-proach are antecedents for the consumers’ feeling of distributive justice (Gelbrich & Roschk, 2011). The justice dimension is a requirement for the consumers’ feeling that the company will solve their problems. However, the expectation that the company will provide a solution is also closely linked to the consumers’ feeling of being taken seriously, which again can only originate if a company’s complaint handling is perceived as authentic (Gruber, 2011; Min, Lim, & Magni-ni, 2014). In order to be perceived as authentic, companies need to convey their messages with a personal tone of voice, as this promotes the consumers’ feeling that the company is sincere and credible (Bell & Zemke, 1987).
So far, no research has tested the role of authenticity as underlying mechanism of the ef-fectiveness of the different webcare responses, but above stated does suggest that there is an in-teraction ofthe different webcare responses and their degree of personalization on the perceived authenticity of these responses, which in turn influence the consumers’ brand responses. Since previous research points to a positive effect of accommodative webcare responses on the per-ceived authenticity of these responses (e.g., Gelbrich & Roschk, 2011; Gruber, 2011; Min et al., 2014), and also points to a positive effect of personalized messages on the consumers’ perceived authenticity (e.g., Bell & Zemke, 1987), it is expected that a response that is both accommoda-tive and personalized will have the most posiaccommoda-tive effect on the consumers’ perceived authentici-ty, which will have the most positive effect on consumers’ brand responses. Nevertheless, it is also expected that a personalized defensive response, in comparison to a corporate defensive response, will lead to a higher authenticity perception, as will targeting the message to the
indi-vidual customer and personalizing the organization account positively for the messages’ credibil-ity, being a necessary premise for authenticity. To explore above stated, the final hypothesis reads as follows:
H4a-b. There is a mediated interaction effect of webcare responses and message personalization on brand responses through perceived authenticity, such that a) the positive effect of an accom-modative webcare response (vs. a defensive response) on perceived authenticity is stronger when the message is also personalized (vs. corporate); and b) consequently this positive effect on per-ceived authenticity results in more positive brand responses.
All the expected relationships can be seen in figure 1.
Figure 1. Conceptual model
Method
Participants and Design
To test the hypotheses and research question, an online experiment with a 3 (Webcare re-sponse: accommodative vs. defensive vs. no response) x 2 (Message personalization: personal-ized vs. corporate) between-subjects design was conducted. In total 196 participants (67.9% fe-male) participated in this experiment (Mage = 30.82, SD = 12.36). 59.2% of the participants
indi-cated that their highest level of education was a University degree (Bachelor or Master). Almost half of the participants were students (49%) and the second largest group (31.6%) indicated to be working.
Stimulus Materials
The experimental material consisted out of a fictitious complaint posted on Lufthansa’s Facebook page and was designed in resemblance to real complaints on social networks in terms of content and tone of voice. Facebook was chosen as a platform for the complaint interaction as it is not only a very popular social network, but also has the most users across all social media platforms (Nielsen, 2012). Furthermore, 47% of social media users engage in social care, being customer care over a social network and consumers are most likely to do that on Facebook (Niel-sen, 2012).
The fictitious customer, Anna Langer, indicated to be very unhappy with Lufthansa as her flight to New York got cancelled short notice, which forced her to wait a great amount of time at the airport in London. She pointed out that she was promised some sort of compensation but did not receive anything until now. The customer declared her disappointment with Lufthansa, de-manded an immediate solution and doubted if she would ever fly with the airline again.
It was opted to use a real brand, as this contributes positively to the external validity of the study. Willemsen, Neijens, Bronner and De Ridder (2011) postulate that NWOM has an es-pecially big influence on experience products, which can only be evaluated after the purchase, as negative reviews are only perceived as useful when they are written for experience products (vs. search products). Flights are considered to be such products, as their quality cannot be assessed prior to the purchase. Moreover, it can be assumed that consumers are highly involved in Lufthansa’s products, as flights are often quite costly and booked with a lot of consideration (in regards to different prices, dates, etc.).
Depending on the webcare response condition, Lufthansa reacted with an accommodative response, a defensive response or no response at all. Additionally, the messages were manipulat-ed in regards to their tone of voice (personalizmanipulat-ed vs. corporate). Each participant saw only one of the five responses (see figures 3, 4, 5, 6 and 7 in Appendix A).
Webcare response. For the manipulation of the webcare response, the complaint was followed by either no response (the screenshot contained a statement informing the participants that Lufthansa did not respond to the complaint), or a response which was accommodative or defensive. In the accommodative webcare condition, Lufthansa apologized and offered compen-sation for the negative experience in form of a voucher. In the defensive response condition, Lufthansa denied its responsibility and shifted the blame to the customer by stating that accord-ing to their general terms and conditions, short term cancellations are not applicable for the re-ceipt of equalization benefits. Lufthansa further refused to help the customer and indicated that the customer will have to contact customer care for further questions.
Message personalization. The manipulation of message personalization was two-fold in this study: In the personalized condition, the message to the receiver was altered by using many second-person pronouns, “you”, and directly addressing the customer with her name (“Dear An-na”). These alterations of the message are along the conceptualization of Kwon and Sung (2011). As the questionnaire was translated to German, “you” was translated to “du”, the German infor-mal personal pronoun. To further emphasize the personal tone of the personalized responses, “Du” was written with a capital letter, which reduces the distance between the speakers by sug-gesting that they are acquainted with each other. Secondly, the organization was personalized by using an individual Lufthansaemployee, Max, who spoke using the first person for Lufthansa: In the beginning of the response Max introduced himself as a Lufthansa Team member and ex-plained that he will take care of the request. The personalized messages were signed with
“/Max”. The use of identification by name is adopted from Park and Lee (2013). In the corporate response condition, there was no information on who is responding on behalf of Lufthansa, as
few personal pronouns as possible were used and if they were used, the formal and distant “Sie” was used. The customer was not addressed by name and the message was signed with “Kind regards, Lufthansa”.
Pretest
A pretest consisting of a 2 x 2 within subjects design was conducted among 22 partici-pants (72,7% female, Mage = 25.50, SD = 2.69) to check whether the manipulations of the
webcare response types and message personalization were successful. Participants were random-ly assigned to one of the four conditions. The no response condition was excluded as participants only saw the complaint but no manipulated response. The participants were exposed to the Lufthansa’s Facebook page, on which they saw the complaint and one of the four responses. Subsequently, participants received questions concerning the tone of voice manipulation (per-sonalized vs. corporate) and the type of webcare manipulation (accommodative vs. defensive).
The first questions regarding the manipulation of webcare response type was ‘Lufthansa is apologizing and tries to make it up to the customer’. Participants had to indicate their opinion on a 7-point Likert scale (1= “Completely disagree”, 7= “Completely agree”). As intended, there was a significant difference between respondents who saw an accommodative response and respondents who saw a defensive response by Lufthansa (t(20) = 3,61, p < .01; Maccommodative =
5.45, SD = 1.44; Mdefensive = 2.73, SD = 2.05). The second statement, ‘Lufthansa refuses to help
the customer and declares that the problem lies outside of its responsibility’, disclosed again a significant difference between respondents who saw the defensive response and respondents who saw the accommodative response (t(20) = -6.02, p < .001): The statement was agreed upon more by participants in the defensive condition (M = 5.73, SD = 1.62) than by participants in the ac-commodative condition (M = 2.00; SD = 1.27). Therefore it can be said that the manipulation of webcare response type into accommodative and defensive was successful and no adaptations needed to be made for the main study.
To test the manipulation of message personalization participants were asked to rate four statements on 7-point Likert scales (1= “Completely disagree”, 7= “Completely agree”). The first statement, ‘Lufthansa responded in an impersonal manner’, revealed that there was a significant difference between the personalized and corporate webcare response condition (t(20) = -4.12; p < .01). However, the mean value of 4.73 of participants in the corporate condition (see table 1) suggests that the corporate messages were considered to be quite neutral in terms of their degree of personalization as the mean value manifested a great proximity to the midpoint of the scale. The second statement, ‘Lufthansa responded with a formal tone of voice’, disclosed anoth-er significant diffanoth-erence between the two groups (t(20) = -3.18, p = .01). Again, the mean value of the personalized condition indicated a small distance to the midpoint of the 7-point scale. In order to achieve a more distinctive differentiation, the corporate messages in the final stimulus material were slightly adjusted to emphasize the impersonal, distant and formal tone of voice. The third statement, ‘Lufthansa identifies who is responding on behalf of them’, exposed again a significant difference between respondents in the corporate and the personalized condition (t(20) = 5.62, p < .001). Finally, there was a significant difference between the two groups on
‘Lufthansa responded in a personalized and individualized manner’ (t(20) = 6.07, p < .001). All the mean scores regarding the manipulation of message personalization can be found in table 1.
Table 1
Mean scores regarding tone of voice manipulation (pretest) Condition
Personalized Corporate
Characteristic M SD M SD
Impersonal manner 2.09 1.14 4.73 1.79
Formal tone 3.45 1.53 5.55 1.51
Personalization of the company 5.91 1.14 2.45 1.70 Personalization of the receiver 5.91 1.04 2.54 1.57 Note. N = 22
Procedure
Participants living in Germany and German-speaking participants living in the Nether-lands were approached by email, through the social network Facebook and via online forums with the request to participate in a study on ‘consumer-related issues and complaints’. The re-quest contained the link to the online experiment. An online experiment was suitable in this con-text, as it allowed the stimulus materials to look as true to real Facebook brand pages as possible. Firstly, participants read an introduction, which informed them that all their answers were treated anonymously and that they could cease their participation at any time. Participants were then told that they are about to see a corporate Facebook page and asked to look at it carefully, as ques-tions regarding that page would follow. In the next step, participants were randomly assigned to one of the five conditions. After the exposure to the stimulus materials, respondents were asked questions about the authenticity of Lufthansa’s reaction on the complaint and about their brand responses. Next, participants had to answer questions regarding several covariates, such as pre-vious experience with Lufthansa and prepre-vious experience with writing online complaints. Lastly, a manipulation check was performed to test whether the stimulus materials were effective and participants were asked to provide some demographic data before being debriefed and thanked.
Measures
Perceived authenticity. To assess the participants’ perception of the responses’ authen-ticity, the authenticity scale of Huang et al. (2011) was used. Participants were asked to indicate on a 7-point scale (1= “Completely disagree”; 7= “Completely agree”) whether they perceived the reaction of Lufthansa to be credible, trustworthy and reliable. All the items loaded on one factor (EV = 2.4; R² = .80), proved to constitute a reliable scale and were averaged to form a composite score (M = 3.53, SD = 1.49, α = .87).
Brand responses. The measurement of the consumers’ brand responses was multi-dimensional and included the assessment of their brand attitude, their purchase intention and their PWOM intention. It was opted to measure brand responses in three dimensions, as purchase intention and brand attitude have proven to be reliable measurements to assess the participants’ overall brand responses (Raney, Arpen, Pashupati, & Brill, 2003). As this study concentrates on the marketing perspective, it is also valuable to measure the participants’ PWOM intention as it significantly contributes to the success of online marketing activities (Huang et al., 2011).
Brand attitude. As a real brand was used in this study, it was important to ensure that participants indicated their brand attitude in relation to how Lufthansa handled the complaint in this specific situation and not how they perceive Lufthansa in general. Based on Lufthansa’s re-action, participants were asked to indicate their brand attitude with the means of six items on a 7-point Likert-scale (1= “Completely disagree”; 7= “Completely agree”): The company is good, interesting, appealing, pleasant, of high quality and likable (Mitchell & Olson, 1981; Voorveld, Neijens & Smit, 2011). The scale items loaded all on one factor (EV = 4.02; R² = .67) and as in previous research, the scale proved to be reliable and the items were averaged to form a compo-site score (M = 4.14, SD = 1.73, α = .86).
Purchase intention. The participants’ purchase intention was assessed with the means of three items on a 7-point Likert scale (1= “Completely disagree; 7= “Completely agree”). The first two items, which were adopted from the purchase intention scale from Coyle and Thorson (2001), were supplemented by a third, self-created, item: ‘It’s very likely that I will fly Lufthansa, ‘I will use Lufthansa the next time I need to book a flight’ and ‘I’m very likely to choose
Lufthansa over a different airline company for my next flight’. The three items all loaded on one factor (EV = 2.00; R² = .67) and proved to form a reliable scale (M = 3.59, SD = 1.35, α = .74).
PWOM intention. The participants’ PWOM intention was assessed by the means of a single-item measure on a 7-point Likert-scale (1= “Very unlikely”; 7= “Very likely”): ‘How like-ly are you to recommend Lufthansa to friends or familike-ly?’ The item was taken from Boulding,
Kalra, Staelin and Zeithaml (1993). Rossiter (2002) argues that single-item measures provide valid measurements if the construct is clear and unambiguous. He furthermore explains that a multiple item measure is only necessary if a construct contains many abstract attributes (Rossit-er, 2002), which is not the applicable for PWOM intention.
Control Variables
To rule out alternative explanations and test the impact of cofounding variables on per-ceived authenticity, brand attitude, purchase intention and PWOM intention, the following varia-bles were included: Previous experience with Lufthansa, the valence of this experience and the frequency and experience with writing online complaints as well as the participants’ satisfaction with previous complaint handling.
The participants’ previous experience with Lufthansa was measured by asking them if they ever flew with Lufthansa (dummy-coded, 0 = no, 1 = yes; 76.5% said ‘yes’). Participants, who indicated that they flew with Lufthansa before, were directed to a second question asking them how they perceive their experience with Lufthansa (assessed on a 7-point bipolar scale: 1= “Predominantly negative”; 7= “Predominantly positive”; M = 5.91, SD = 1.15).
In order to assess the participants’ experience with writing an online complaint, they were asked if they had ever written an online complaint (dummy-coded: 0 = no, 1 = yes; 19.4% said ‘yes’) and participants who answered with ‘yes’ received a follow-up question about the fre-quency and how the companies resolved their complaint: ‘How many online complaints have you written in the past year’ (1-2 (84.2%), 3-4 (10.5%), 5-6 (2.6%), more than 6 (2.6%)) and ‘How did the companies resolve your complaint(s)?’ (Assessed on a 7-point bipolar scale: 1= “Pre-dominantly unsatisfactory”; 7= “Pre“Pre-dominantly satisfactory”; M = 4.05, SD = 2.17).
Results
Manipulation and Confound Checks
Manipulation checks similar to those applied in the pretest were used to ensure that the experimental materials had the intended effects. Respondents, who saw the accommodative re-sponse agreed significantly more (M = 5.63, SD = 1.36) with the statement postulating that Lufthansa apologises and tries to make it up to the customer, than respondents who saw the de-fensive response (M = 2.00, SD = 1.30; t(160) = 17.34, p < .001). Likewise, respondents in the defensive response condition also perceived Lufthansa’s response to be more defensive than re-spondents in the accommodative condition (Mdefensive = 5.20, SD = 1.84; Maccommodative = 1.75, SD
= 1.35; t(160) = -13.69, p < .001).
Regarding the manipulation of message personalization and the question if Lufthansa re-sponded in an impersonal manner, there was a significant difference between respondents in the personalized response condition and respondents in the corporate response condition (t(160) = -5.94, p < .001). Furthermore, respondents in the corporate condition indicated significantly more strongly that they perceived Lufthansa’s response to be formal than respondents in the personal-ized condition (t(160) = -7.57, p < .001). In regards to the personalization of the company, par-ticipants in the personalized condition agreed significantly more with the statement that
Lufthansa identified who is responding on behalf of them than participants in the corporate con-dition (t(160) = 8.72, p < .001). Lastly, the manipulation check revealed that there was again a significant difference between the two groups (t(160) = 7.04, p < .001) on the statement that Lufthansa personalizes the approach to the receiver. All the mean scores for the manipulation of tone of voice can be seen in table 2.
Table 2
Mean scores regarding tone of voice manipulation (main study) Condition
Personalized Corporate
Characteristic M SD M SD
Impersonal manner 2.67 1.77 4.43 1.99
Formal tone 3.24 1.80 5.28 1.61
Personalization of the company 5.02 1.84 2.55 1.77 Personalization of the receiver 5.41 1.74 3.33 2.03 Note. N = 160
Confound checks revealed that the participants’ previous experience with Lufthansa (rs = -.24, p < .001) and the valence of this experience (r = .34, p < .001) were significantly related to one variable, purchase intention. The participants’ previous experience with writing online com-plaints and its frequency were not related to perceived authenticity, purchase intention, PWOM intention or brand attitude and were therefore dropped as covariates. Confound checks addition-ally revealed that the participants’ satisfaction with how companies resolved their previous online complaints was also significantly related to purchase intention (r= .32, p = .05).1
To test the hypothesis and the research question, several statistical analyses were con-ducted. H1 and RQ1 were tested with a Multivariate Analysis of Variance (MANOVA), in which the webcare response type was the independent variable with three conditions (accommo-dative vs. defensive vs. no response), and brand attitude, purchase intention and PWOM inten-tion were used as dependent variables. Because H1 and RQ1 also investigated the effects of the no response condition, they were tested together in one MANOVA. A second MANOVA was conducted to test H2 and H3a-b, in which the independent variable, webcare response type only included the accommodative and defensive condition, as the no response condition was not per-sonalized. Next to the webcare response type, message personalization was added as a second independent variable in the MANOVA, whereas the dependent variables stayed the same. Lastly,
to test H4a-b, three bootstrapping analyses were conducted (for each dependent variable) to test whether perceived authenticity was an underlying mechanism for the effects.
Effectiveness of Webcare Response Type
In H1 it was hypothesized that an accommodative webcare response leads to better brand responses than a defensive response and no response on the consumer’s complaint, whereas RQ1 dealt with the question whether a defensive webcare response leads to more positive brand re-sponses than no webcare response. To test H1 and answer RQ1, a MANOVA was performed with webcare type as the independent variable, and brand attitude, PWOM intention and pur-chase intention as dependent variables. Using the Wilks’ Lambda, there was a significant differ-ence in the effects of the different webcare response types on the consumers’ brand attitude, their purchase intention and their PWOM intention (λ = .65, F(6,382) = 15.21, p < .001, pη² = .19). When the results for the dependent variables were considered separately, all three dependent variables reached statistical significance: Brand attitude (F(2,193) = 44.33, p < .001, pη² = .32), purchase intention (F(2,193) = 4.91, p = .01, pη² = .05) and PWOM intention (F(2,193) = 8.72, p < .001, pη² = .08). Post hoc analysis was conducted in order to examine which of the three condi-tions significantly differed from each other: The Games-Howell test revealed that the accommo-dative condition significantly differed from the defensive condition and the no response condi-tion. An exception was found for the participants’ purchase intention, where the results only dis-closed a significant difference between the means of the accommodative condition and the de-fensive condition. However, regarding RQ1, the differences between the means of the partici-pants in the defensive condition and the participartici-pants in the no response condition did not reach statistical significance (see mean differences in table 3 in Appendix B).2 As predicted by H1, the participants in the accommodative condition reported on the most positive brand attitude (M ac-commodative = 4.79, SD = .97; Mdefensive = 3.34, SD = 1.04; Mno response = 3.12, SD = 1.57), the highest
SD = 1.55) and highest PWOM intention (Maccommodative = 3.69, SD = 1.40; Mdefensive = 2.96, SD =
1.28; Mno response = 2.71, SD = 1.47). H1 could therefore be supported as accommodative webcare
responses lead to the most positive brand responses. Regarding RQ1, the post hoc tests revealed that it cannot be concluded that one of the two strategies is superior to the other, as there was no significant difference between respondents in the defensive webcare condition and respondents in the no response condition.
Effect of Message Personalization on Brand Responses
H2 stated that personalized webcare responses would lead to more positive brand re-sponses than corporate webcare rere-sponses. To test the direct effect of the moderator, a second MANOVA including message personalization (dummy-coded: 1 = personalized, 2 = corporate) and webcare response type (dummy-coded: 1 = accommodative, 2 = defensive) as independent variables and brand attitude, purchase intention and PWOM intention as dependent variables, was conducted. Yet, for this hypothesis was only the direct effect of interest, thus the interaction effect will be explained in the next section.
Although, the p value of the Wilks’ Lambda statistics of .07 showed that the difference between participants receiving personalized webcare responses and corporate webcare responses did not reach significance, the results demonstrated that there is a visible trend towards a differ-ence between these two groups. When considering the values for each dependent variable sepa-rately, significant effects could be reported: Message personalization had a significant effect on the participants’ brand attitude (F(1,158) = 4.23, p = .04, pη²= .03) and their PWOM intention (F(1,158) = 5.66, p = .02, pη² = .04), but it did not significantly influence the participants’ pur-chase intention (F(1,158) = .51, p = .48, pη² = .00). Participants, who were exposed to a person-alized webcare response indicated to have a higher PWOM intention (Mpersonalized = 3.55, SD =
1.33; Mcorporate = 3.11, SD= 1.41) and a better brand attitude (Mpersonalized = 4.20, SD = 1.24; M cor-porate = 3.96, SD = 1.24) than participants in the corporate condition. These results only partly
supported H2, as personalized messages lead to a more positive brand attitude and a higher PWOM intention, but the participants’ purchase intention was not significantly affected.
Interaction Effect between Webcare Response Type and Message Personalization
H3a-b postulated that the effects of the different webcare responses on brand responses are moderated by message personalization, such that a) the positive effect of an accommodative webcare response on brand responses will be increased by message personalization, and b) mes-sage personalization will improve the effectiveness of a defensive webcare response in evoking more positive brand responses. The MANOVA which was conducted for H2, was used to exam-ine how the two variables, webcare response type and message personalization, interact with each other on the consumers’ brand responses. The results revealed that there was no significant interaction effect of the different webcare responses and message personalization on the con-sumers’ brand responses (λ = .96, F(3,156) = 2.06, p = .11, pη² = .04). Follow-up analysis re-vealed that when considering the interaction of webcare response type and message personaliza-tion separately on the three dependent variables, there was no significant interacpersonaliza-tion effect on brand attitude (F(1,158) = 2.59, p =.11, pη² = .02) or purchase intention (F(1,158) = 1.68, p = .20, pη² = .01), but the results revealed a significant interaction effect on the consumers’ PWOM intention (F(1,158) = 6.19, p = .01, pη² = .04).
However, contrary to the expectations, the results revealed that personalized accommoda-tive responses did not lead to higher PWOM intentions, as participants in the corporate accom-modative response condition reported on a slightly higher PWOM intention (Mpersonalized accommoda-tive = 3.68, SD = 1.44; Mcorporate accommodative = 3.70, SD = 1.37). H3a could therefore not be
sup-ported, as there was no significant interaction effect on the participants’ brand attitude and pur-chase intention, and the significant interaction on PWOM intention was oppositional to what was expected for accommodative responses. Nevertheless, H3b can be partly supported as the hy-pothesized interaction effect of a defensive webcare response and message personalization was
significant for the participants’ PWOM intention: The personalized defensive response (M = 3.43, SD = 1.21) scored significantly higher on the participants’ PWOM intention than the cor-porate defensive response (M = 2.43, SD = 1.43). The interaction effect of the webcare response type and message personalization on PWOM intention can be seen in figure 2.
Figure 2. Interactionplot for PWOM intention
Interaction Effect between Webcare Response Type and Message Personalization on Brand Responses explained by Perceived Authenticity
In H4a-b it was hypothesized that there is a mediated moderation effect of webcare re-sponse type and message personalization on brand rere-sponses through perceived authenticity, such that a) the positive effect of an accommodative response (vs. a defensive response) on per-ceived authenticity is stronger when the message is also personalized (vs. corporate); and b) con-sequently this positive effect on perceived authenticity results in more positive brand responses. To investigate the effects, Preacher and Hayes’ (2008) bootstrapping method was used. In total, three bootstrapping analyses were run in the Model 8 of Hayes’ PROCESS macro (2013), in which webcare response type was the independent variable, perceived authenticity the mediator, message personalization the moderator and either brand attitude, purchase intention or PWOM intention the dependent variable. With 1,000 bootstrapping samples (N = 160) to estimate the
bias corrected and accelerated confidence intervals (BCACI), the results disclosed that the webcare response type has a direct effect on perceived authenticity (b = -.95, SE = .21, p < .001, 95% BCACI [-1.37, -.53]). Yet, the direct effect of message personalization on perceived au-thenticity (b = -.02, SE = .21, p = .94, 95% BCACI [-.44, .41]) and the interaction of webcare response type and message personalization on perceived authenticity (b = -.45, SE = .43, p = .29, 95% BCACI [-1.30, .39]) was not significant. The findings support that the consumers’ per-ceived authenticity influences their brand responses (H4b), as authenticity has a positive effect on the participants’ brand attitude (b = .45, SE = .06, p < .001, 95% BCACI [.34, .56]), their purchase intention (b = .38, SE = .08, p < .001, 95% BCACI [.22, .56]) and their PWOM inten-tion (b = .48, SE = .07, p < .001, 95% BCACI [.36, .61]). However, the findings reveal that the indirect effect of webcare response strategies moderated by message personalization on brand responses through perceived authenticity was not significantly different from zero, as the 95% bootstrap confidence interval included zero for all dependent variables (Brand attitude: indirect effect = -.10, SE = .10, 95% BCACI [-.31, .08]; purchase intention: indirect effect = -.17, SE = .17, 95% BCACI .55, .11]; PWOM intention: indirect effect = -.22, SE = .21, 95% BCACI [-.69, .14]). Thus mediated moderation did not take place and H4a-b has to be rejected.
Notwithstanding, the analysis disclosed some unexpected results. As established above, there was a significant effect of the webcare response type on the participants’ perceived authen-ticity, which significantly affected the participants’ brand responses. To test whether perceived authenticity indeed mediated the effects of the different webcare response types on the consum-ers’ brand responses, additional bootstrapping analyses (Model 4 in PROCESS; Hayes, 2013) for each dependent variable were conducted. The webcare response type was the independent varia-ble, perceived authenticity was used as mediator and brand attitude, purchase intention or
PWOM intention was used as dependent variables. The bootstrap procedures (1000 samples, N = 160) revealed that there was indeed a mediated path from webcare response type to the partici-pants’ brand attitude (b = -.43, SE = .09, p < .001, 95% BCACI [-.68, -.24]), their purchase
inten-tion (b = -.37, SE = .12, p < .001, 95% BCACI [-.65, -.18]) and their PWOM inteninten-tion (b = -.47, SE = .18, p < .001, 95% BCACI [-.77, -.24]). The direct effects of the webcare response type on the participants’ purchase intention and their PWOM intention become insignificant after per-ceived authenticity has been controlled for, thus complete mediation takes place and c’ becomes zero (Purchase intention: b = -.25, p = .20, 95% BCACI [-.64, .13]; PWOM intention: b = -.26, p = .17, 95% BCACI [-.64, .12]). The direct effects of the webcare response type on the partici-pants’ brand attitude stay significant when authenticity is added to the model, thus partial media-tion is existent (b = -1.01, p < .001, 95% BCACI [-1.27, -.74]).3
Conclusion and Discussion
Companies have come to realize that it is necessary for the means of successful impres-sion management and effective complaint handling, to find appropriate ways to address NWOM on social media (e.g., Fournier & Avery, 2011, Kerkhof et al., 2011). This study investigated the effectiveness of different webcare strategies in evoking favourable brand responses and exam-ined how these responses need to be conveyed in order to maximize their positive effects. In ad-dition, it was researched whether the consumers’ perceived authenticity mediates these effects. By doing so, this thesis aimed at providing guidelines for marketers on how to use webcare as a marketing tool and deal successfully with NWOM on social media.
This was executed in an experimental study, in which respondents were randomly as-signed to one of the five experimental groups. The experimental groups differed in the type of Lufthansa’s webcare response (accommodative, defensive or no response) and the degree of per-sonalization of that response (personalized or corporate). After being exposed to Lufthansa’s Facebook page with the complaint interaction, participants had to indicate their perceived au-thenticity of Lufthansa’s reaction and their brand responses.
The results revealed four interesting findings. First, in support of H1, this study builds on the results of previous research (e.g., Kerkhof et al., 2011; Lee & Song, 2010) postulating that
accommodative webcare responses lead to the most positive brand responses among the three different webcare response types in this study (accommodative, defensive and no response). This study extends the scope of previous studies, which concentrated on the effects of organizational responses on customer care outcomes (e.g. satisfaction; Gelbrich & Roschk, 2011) or crisis communication outcomes (e.g. trust, responsibility for crisis; Lee, 2004); by showing that ac-commodative webcare leads to the attainment of favourable marketing-related brand responses. This study therefore sheds light on the notion of Fournier and Avery (2010), who postulate that brand managers are unsure about what to respond to complaining customers. Furthermore, a re-search question was formulated as previous studies (e.g., Lee, 2004; Lee & Song, 2010) reported mixed results regarding the effectiveness of defensive webcare responses versus no response of the company. Contrary to previous research (e.g., Lee & Song, 2010), the results disclosed that the means of the two conditions did not significantly differ from each other. These findings em-phasize that both response strategies are not effective in evoking favourable brand responses, thus defensive responses and no response to NWOM can therefore not be considered as webcare, since companies using these approaches pass on their opportunity to improve customer relation-ships and neglect to turn negative experiences into positive ones (Dekay, 2012). Whereas previ-ous research (Lee, 2004; Lee & Song, 2010) disagreed on defensive responses or no response leading to higher blame attributions, companies using webcare as marketing tool should have the goal to solve complaints regardless of whose responsibility the issue is. Thus the question “Who is to blame for the incident?” becomes irrelevant and blame attributions are not an insightful out-come variable when taking a marketing perspective on webcare.
Second, the findings from this research revealed that there was a significant effect of message personalization on the participants’ brand responses (H2), but only on their PWOM intention and brand attitude, and not on their purchase intention. It is assumed that there is no direct effect on the participants’ purchase intention, as the purchase of flights is connected to great financial investments and consumers are hesitant to form behavioural intentions about that.
