Humanization of webcare responses to PeWOM

The effects of message personification and message personalization of webcare responses to

PeWOM on perceived relationship investment

Nicolette Arkenbout ANR: 613072

Master thesis Communication and Information Sciences Specialization: Business Communication and Digital Media

Faculty: Tilburg School of Humanities Tilburg University, Tilburg

Supervisor: Dr. C.C. Liebrecht Second reader: Dr. M.M.H. Pollmann

January, 2018

Abstract

This study was conducted to investigate the influence of personification and personalization of webcare responses to PeWOM on the amount of perceived relationship investment and evaluation of this organizations‟ investment. Previous studies focused on either personification or personalization, two different ways of humanizing webcare responses to

PeWOM. In addition, it has not been investigated yet to what extent this influences perceived relationship investment and evaluation of this investment. In this study, the effect of personification and personalization was investigated separately and combined. An online experiment (N = 192) was conducted with a 3 (message personification: no vs. low level vs. high level) x 2 (message personalization: absence vs. presence) between-subject design. It was also investigated whether certain effects were mediated by perceived conversational human voice or invasion of customers‟ privacy. The results showed that personification and personalization have no effect on perceived relationship investment. However, the investment to use a low level of personification seems to be evaluated more positively than a high level of personification, which is not in line with prior expectations. Furthermore, this study shows that a high level of personification has a negative effect on perceived conversational human voice, but an increased perceived conversational human voice influences perceived relationship and its evaluation positively. Moreover, as expected, personalization seems to have a clear negative effect on evaluation of perceived relationship investment due to invasion of privacy. Therefore, organizations should not use personal customer information in their webcare responses.

2 Master thesis Nicolette Arkenbout Index

Introduction...... 5

Theoretical framework ...... 9

EWOM ...... 9

Webcare ...... 9

Perceived relationship investment ...... 11

Conversational human voice ...... 13

Personification ...... 14

Personalization ...... 17

Additional hypotheses...... 20

Method ...... 23

Design ...... 23

Participants...... 23

Stimuli ...... 24

Pretest ...... 27

Measures...... 31

Procedure...... 34

Results ...... 35

Demographic variables ...... 35

Consideration main analyses ...... 35

Assumptions...... 35

Main analyses ...... 36

Conclusion and discussion...... 41

Personification ...... 42

Personalization ...... 44

3 Master thesis Nicolette Arkenbout Limitations and suggestions for future research ...... 45

Theoretical and practical implications ...... 47

References ...... 49

Appendices ...... 54

Appendix A – Operationalization personification ...... 54

Appendix B – Pretest ...... 55

Appendix C – Materials ...... 63

Appendix D – Reliability of the scales...... 69

Appendix E – Experimental questionnaire ...... 70

Appendix F – Fillers ...... 74

Appendix G – Demographic variables...... 76

Appendix H – Normality checks...... 77

Appendix I – Mediation analyses ...... 78

4 Master thesis Nicolette Arkenbout Introduction

Nowadays, customers can easily express their positive feelings towards brands via social media. Brands can respond to these positive messages in different ways. For instance,

Coolblue, A Dutch online electronic company, responds to customers‟ messages using the official Coolblue account, but they also respond personally. For example, on Facebook,

Coolblue employee Wesley can respond with his own employee account: „Wesley from

Coolblue’ (Figure 1). This is a specific way to humanize webcare responses.

Figure 1. Example of profile picture of employee (left) and response message (right)

This study aims to gain more insights into this topic, by investigating humanization of webcare responses to positive online messages. Schamari and Schaefers (2015) and Demmers,

Van Dolen and Weltevreden (2014), also investigated this specific topic, but they each focused on a different way of humanizing webcare responses. Remarkably, in both studies, it was referred to as „(message) personalization‟. Message personalization can be defined as

“the degree to which a message can be made to address a specific individual” (Walther, 2011, p. 448). Both/either the company and/or the customer can be the subject of personalization

(Van Noort, Willemsen, Kerkhof, & Verhoeven, 2014). Schamari and Schaefers (2015) focused only on the company and Demmers et al. (2014) focused only on the customer, so it is not surprising that these study‟s results are not in line with each other.

A first way to humanize webcare is to humanize the company. In fact, Schamari and

Schaefers (2015) compared messages that were sent by an employee (Figure 1) with messages

5 Master thesis Nicolette Arkenbout that were sent by the company itself (corporate). Other previous studies also showed that using human representatives to send messages makes the message more personal (Kerkhof,

Beukeboom, Utz, & De Waard, 2010; Kwon & Sung, 2011; Park & Lee, 2013; Strauss &

Hill, 2001). Schamari and Schaefers (2015) have shown that messages sent by employees elicit more positive consumer engagement than messages sent by the brand, so organizations should actively humanize webcare responses this way. This effect was mediated by perceived conversational human voice (CHV). CHV can be seen as an engaging and natural style of organizational communication (Kelleher, 2009). When organizations use a CHV, customers perceive they are in a conversation with an actual person instead of a company (Park & Lee,

2013). Using human representatives to react on positive messages seems to increase CHV and

CHV seems to increase the willingness to perform positive customer engagement behaviour.

In contrast, Demmers et al. (2014) included personal customer information to humanize the webcare responses. Demmers et al. (2014) showed that responses without personal customer information (or even no responses) lead to more customer satisfaction than responses that contain personal customer information. This effect was mediated by invasion of privacy. In sum, it can be stated that, when responding to positive online messages, using customers‟ personal information is not beneficial, due to invasion of customers‟ privacy. On the contrary, using human representatives is beneficial, due to increased perceived CHV.

This study expands on these two studies by including both these types of humanizing webcare instead of only one. To be able to distinguish the two types, they will be referred to as „(message) personification‟ when the organization is subject of humanization and

„(message) personalization‟ when the customer is subject of humanization. Organizations can humanize their webcare responses in both these ways, but the effect of comparing and combining both types remains unclear. Furthermore, this study will measure personification more in depth and personalization will be measured differently than Demmers et al. (2014)

6 Master thesis Nicolette Arkenbout did, by using another type of personal customer information: information gathered via social media. In fact, these two ways of humanizing webcare responses can be seen as an (extra) investment in the customer-company relationship. This is one of the reasons why this study focuses on the effect of humanization on perceived relationship investment.

Perceived relationship investment (RI) can be briefly described as customers‟ perception of the extent to which companies make efforts to maintain relationships with customers (De Wulf, Odekerken-Schröder, & Iacobucci, 2001). Another reason to focus on perceived RI, is the fact that De Wulf et al. (2001) showed that interpersonal communication is the best predictor of perceived RI, so humanizing webcare might positively influence perceived RI. Moreover, perceived RI is a more approachable and accessible aspect than, for example, customer engagement behaviour (Schamari & Schaefers, 2015) (e.g. recommending a brand in an online community). Creating such brand-related content is the most extreme level of brand-related activeness (Muntinga, Moorman, & Smit, 2011). Perceived RI might be seen as a determinant, since perceived RI has a strong positive impact on relationship quality

(De Wulf et al., 2001; Rafiq, Fulford, & Lu, 2013). Besides, it could be concluded that a high amount of perceived RI is always favourable, but when personal customer information is present in responses, customers might feel their privacy is invaded and might not be satisfied with organizations‟ efforts. Therefore, perceived RI will be investigated more in depth by measuring amount and evaluation of perceived RI separately.

With more practical knowledge about personification and personalization on perceived

RI and evaluation of this investment, companies could improve their webcare services by responding to positive online messages properly and, hereby, increasing the positive effect of those messages. Therefore, this study will provide more in-depth information about who needs to be the sender of webcare responses and whether organizations should include personal information or not. Moreover, this study will gain more academic knowledge on the

7 Master thesis Nicolette Arkenbout influence of invasion of customers‟ privacy and perceived CHV. Specifically, this study will try to investigate whether the possible positive effect of personification, explained by CHV, or whether the possible negative effect of personalization, explained by invasion of privacy, is more influential with regards to perceived RI. In sum, the following research question will be answered in this study: “To what extent does personification and personalization of webcare responses to PeWOM affect perceived relationship investment?”

8 Master thesis Nicolette Arkenbout Theoretical framework

EWOM

Social media enables customers to create brand-related content and share their opinions about brands (eWOM). EWOM can be defined as: “any positive or negative statement made by potential, actual, or former customers about a product or company, which is made available to a multitude of people and institutions via the Internet” (Hennig-Thurau, Gwinner, Wals, &

Gremler, 2004, p. 39). Customers can share their positive attitude (PeWOM) and negative attitude (NeWOM) towards brands, but they can also ask certain questions or make neutral comments. Presumably, online complaints are more likely to lead to organizational crises than online compliments or recommendations, which might explain the fact that in research more attention has been paid to NeWOM than PeWOM. As a matter of fact, complaints can truly be a great threat for organizations, since it can have a harmful effect on the customers‟ decision making process (Grégoire, Salle, & Tripp, 2015; Van Noort & Willemsen, 2011). However,

East, Hammond and Wright (2007) showed that PeWOM occurs approximately three times as often as NeWOM, and Van Os, Hachmang, Derksen and Keuning (2016) showed that Dutch companies detect more PeWOM messages than NeWOM messages. Moreover, handling

PeWOM messages correctly can be an opportunity for organizations to increase customers‟ satisfaction with the brand, trust and improve organizations´ reputation (even more). In sum, although responding to NeWOM deserves attention, using webcare accurately in response to more occurring PeWOM messages is also of great importance.

Webcare

Webcare can be referred to as: “[t]he act of engaging in online interactions with

(complaining) consumers, by actively searching the web to address consumer feedback (e.g., questions, concerns and complaints)” (Van Noort & Willemsen, 2011, p. 133). Van Noort et

9 Master thesis Nicolette Arkenbout al. (2014) state that webcare can be seen as an integrative tool for customer care, reputation management and online marketing, so webcare can serve multiple goals, like increasing customer satisfaction, trust, reputation or purchase intention. There are various suggestions about how to use webcare in a NeWOM context and some regarding a PeWOM context.

Firstly, organizations need to decide whether they need to respond or not in particular situations. For NeWOM, previous studies have shown that customers are more satisfied when brands respond to their complaints (Van Noort et al., 2014; Van Noort & Willemsen, 2011).

Additionally, Demmers et al. (2014) have shown that responding to PeWOM leads to more customer satisfaction than not responding. This finding is in line with the Politeness Theory

(Brown & Levinson, 1987). When responding to PeWOM, positive face is maintained or enhanced by at least noticing the other person, the customer.

When responding to eWOM, organizations can respond to messages posted on different platforms: consumer-and brand-generated platforms. A consumer-generated platform is hosted by customers (e.g. a blog, a forum or a brand community) (Van Noort &

Willemsen, 2011; Lee, Kim, & Kim, 2011). A brand-generated platform is hosted by the brand itself (e.g. a brand‟s own Facebook page), so customers know the platform is monitored by the brand (Van Noort & Willemsen, 2011). Furthermore, when customers expect an answer to their messages from organizations, organizations can respond reactively to these messages on particular platforms. When customers do not expect an answer, organizations can respond pro-actively (Van Noort & Willemsen, 2011). It has been stated that customers do not prefer a pro-active response to their NeWOM message on a customer-generated platform, because it is perceived as an intrusion of the private online space (Fournier &

Avery, 2011; Van Noort & Willemsen, 2011). In contrast, Schamari and Schaefers (2015) showed that an unexpected response to a PeWOM message on a consumer-generated platform is perceived as a surprising reward that leads to positive engagement behaviour.

10 Master thesis Nicolette Arkenbout Another facet is the type of reader of webcare conversations. Two types can be distinguished: consumers who write the initial message and observing consumers who only see the conversation. Schamari and Schaefers (2015) only investigated observers and found a positive effect of personification on customer engagement. This finding is in line with the

Social Learning Theory (Bandura, 1977). This theory states that individuals not only learn from their own behaviour and experiences, but also by observing behaviour. In fact, Schamari and Schaefers (2015) showed that a webcare response can be seen as a reward for observers.

In sum, various facets could be taken into account in webcare. Organizations could also choose to humanize their webcare responses (by using personification and/or personalization), which will be thoroughly discussed in further sections of this chapter.

Eventually, when using webcare (and perhaps humanizing webcare) properly, it can be beneficial for customer care, reputation management and online marketing. In fact, organizations want to build a strong relationship with customers by using webcare. Perceived relationship investment can be a key element to these beneficial outcomes.

Perceived relationship investment

When companies put more time and effort in webcare, they try to invest in the customer- company relationships. However, customers need to acknowledge and appreciate these efforts. Therefore, this study takes amount of perceived relationship investment and evaluation of this investment into account. Perceived RI can be defined as: “a consumer‟s perception of the extent to which a retailer devotes resources, efforts and attention aimed at maintaining or enhancing relationships with regular customers” (De Wulf et al., 2001, p. 36).

In comparison to Schamari and Schaefers (2015), who investigated the effect of webcare humanization on customer engagement, perceived RI is a concept that might come earlier in the customer-company relationship building process. To get more insights in this process,

11 Master thesis Nicolette Arkenbout perceived RI seems to be a suitable concept to investigate. However, perceived RI has not been investigated yet in a webcare context. In an offline environment, perceived RI has a positive effect on relationship quality, and this increased relationship quality leads to customer loyalty (De Wulf et al., 2001; Rafiq et al., 2013). Therefore, it can be suggested that perceived RI is an important determinant for a positive customer-company relationship. In an online context, strengthening a customer-company relationship can be linked to more customer care and more reputation management, the main goals of webcare.

Moreover, De Wulf et al. (2001) have shown that real-life interpersonal communication strongly affects perceived relationship investment (RI) positively. As a matter of fact, interpersonal communication seemed to be the best predictor of perceived RI. In an offline environment, De Wulf et al. (2001) explained interpersonal communication as the extent to which a customer perceives the retailer as interacting with customers in a warm and personal way. However, it remains unclear if this specific effect is present on social media. In general, it can be concluded that brands should be active on social media, since it enhances perceived RI (Clark & Melancon, 2013; Park & Kim, 2014). This study focuses on this social media context by investigating the effect of humanizing webcare on perceived RI.

In addition, this study also includes evaluation of perceived RI. De Wulf et al. (2001) used the concept perceived RI and it only covered the amount of effort companies make (e.g.

“This store makes various efforts to improve its tie with regular customers”). It is also important to investigate how companies‟ efforts are perceived by customers. Customers should, namely, be satisfied with the investments of the company to improve the relationship.

As a result, two different concepts can be distinguished: the amount of perceived relationship investment and the evaluation of this investment.

Specifically, this study tries to give more insights in the effect of humanizing webcare on perceived RI and evaluation of perceived RI. An important aspect of humanizing webcare

12 Master thesis Nicolette Arkenbout is creating a conversational human voice (Van Noort et al., 2014), which will be discussed in the next section. In addition, it is worth noting that, for example, Van Noort et al. (2014) refer to humanization as personalization. In order to avoid any confusion with terminology, it must be noted that this study refers to overall personalization (not specifying whether personification or personalization is used) as humanization.

Conversational Human Voice

A conversational human voice (CHV) can be defined as „„an engaging and natural style of organizational communication as perceived by an organization‟s publics based on interactions between individuals in the organization and individuals in publics‟‟ (Kelleher, 2009, p. 177).

Kelleher and Miller (2006) showed that perceived CHV can improve relationships between customers and organizations. In addition, Dijkmans, Kerkhof, Buyukcan-Tetik and

Beukeboom (2015) showed that CHV mediates the positive effect between exposure to companies‟ social media activities and an increased company reputation. Next to that,

Kerkhof et al. (2010), Park and Lee (2013) and Schamari and Schaefers (2015) showed that personification significantly leads to increased perceived CHV.

In these prior studies, the scale of Kelleher and Meller (2006) was used to measure

CHV, but a variety of samples of the items was used in these studies. This might be due to the subjectivity of the concept CHV. In fact, Huibers and Verhoeven (2014) suggested that CHV is an undefined concept. The concept consists of multiple, diverse indicators (11 items proposed by Kelleher and Miller, 2006). Likewise, Gretry, Horváth, Belei and Van Riel

(2017) stated that the concept CHV lacks clarity and that there are no precise operational guidelines for brands to make use of CHV. However, this study includes this slightly undefined concept, CHV, because it is closely related to humanization. In fact, using webcare humanization is a sufficient tactic to enhance CHV (Koot, 2013; Van Noort et al., 2014). In

13 Master thesis Nicolette Arkenbout addition, this study takes two specific ways into account to humanize webcare responses:

„(message) personification‟ and „(message) personalization‟.

Personification

Personification, when the company is subject of humanization, is about a specific employee communicating with customers instead of a corporate company. In fact, Kwon and Sung

(2011) employed a content analysis to indicate how organizations try to make webcare responses more personal, in other words, how to humanize their brand. Half of the analyzed organizations used human representatives, so personification seems to be frequently used by organizations. In addition, multiple studies investigated the effect of personification in different contexts. Thus, both in practice and in research, personification has gained attention.

In previous studies, personification was operationalized in different ways, because human representatives can be mentioned through text or be made visible through images/photos. Multiple studies focused on text. Firstly, Strauss and Hill (2001) showed that signing emails with an employee‟s name (an employee signature) leads to increased consumer satisfaction, since it is perceived as more personal. Besides, Kerkhof et al. (2010) investigated personification by comparing messages sent by a global company (signature: KPN) with an employee of KPN (signature: Thomas de Vries, employee Webservice Team KPN). Among other things, they found that when responding to NeWOM, a personalized response (in comparison to a non-personalized response) elicits more positive attitudes towards the company. Thus, these studies suggest that using human representatives leads to more positive outcomes than communicating as a brand.

The mentioned previous studies‟ findings are in line with the Social Presence Theory

(Short, Williams, & Christie, 1976). This theory is based on the extent to which the other person in the interaction is perceived as a „real person‟ (Gunawardena, 1995). During an

14 Master thesis Nicolette Arkenbout interaction, contact can be acoustic, visual and physical. Undoubtedly, a face-to-face conversation is a conversation with the highest degree of social presence. The higher the social presence, the more impact individuals have on each other‟s knowledge, attitude and behaviour (Kaplan & Haenlein, 2010). The mentioned studies that focused on personification have shown that higher degree of online social presence leads to satisfaction and other positive attitudes towards the brand.

Additionally, to create even more social presence on the visual level and to make the conversation more humanly, organizations could also use nonverbal cues, images/photos or avatars of the human beings. Park and Lee (2013) investigated the effect of using human representatives by using avatars. They made the employee highly visible for customers by adding avatars and the names of the employees. They showed that this way of using human representatives improves customer-company relationships and promotes PeWOM. Besides,

Schamari and Schaefers (2015) also included the signature of the employee at the end of the response and a real profile picture of the employee in the personalized condition. This can be seen as high online social presence and it increased positive customer engagement.

Based on this Social Presence Theory (Short et al., 1976), it might be assumed that customers acknowledge companies‟ efforts more easily when the degree of social presence is high. Moreover, interpersonal communication seems to be the best predictor of perceived RI

(De Wulf et al., 2001). In an online environment, when an employee is the sender of the webcare response, a real person is talking to the customer instead of a faceless company. One could interpret this as online interpersonal communication. Therefore, it can be expected that personification positively affects perceived RI.

Besides, it might be expected that perceived CHV plays a role in this possible effect.

Schamari and Schaefers, (2015), Kerkhof et al. (2010) and Park and Lee (2013) showed that personification significantly leads to increased perceived CHV. Thus, personification can

15 Master thesis Nicolette Arkenbout often cause a more “engaging and natural style of communication” (Kelleher, 2009). Since organizations make an effort to improve the relationship by humanizing the brand (increasing perceived CHV) via message personification, so the effect might be explained by CHV.

H1a. Personification of webcare responses to PeWOM has a positive effect on perceived RI.

H1b. Webcare responses to PeWOM with a high level of personification increase perceived

RI in comparison to webcare responses with a low level personification. The latter increases perceived RI in comparison to no personification.

H1c. The positive effect of message personification on perceived RI is mediated by perceived

CHV.

Moreover, it might be expected that personification will also positively influence evaluation of perceived RI, because using an employee as sender instead of the brand also leads to a positive attitude towards the brand (Kerkhof et al., 2010), trust, control mutuality, commitment, satisfaction (Park & Lee, 2013) and positive engagement (Schamari &

Schaefers, 2015). Moreover, companies are evaluated more positively when they use interpersonal approaches on social media (Sung & Kim, 2014). Besides, a high degree of social presence leads to more impact on customers‟ attitude (Kaplan & Haenlein, 2010).

In addition, this predicted positive effect of personification on evaluation of perceived

RI might be explained by CHV. In particular, Dijkmans et al. (2015) have shown that being active on social media leads to a better corporate reputation, through CHV. Besides, Kelleher and Miller (2006) have shown that perceived CHV also positively correlates with relational outcomes, like satisfaction. Customers could be satisfied with the amount of effort (the company‟s employees will make effort to send messages via their own account). Moreover,

16 Master thesis Nicolette Arkenbout the positive influence of CHV can be confirmed in terms of personification, because the effect of personification on engagement can be explained by CHV (Schamari & Schaefers, 2015).

H2a. Personification of webcare responses to PeWOM has a positive effect on evaluation of perceived RI.

H2b. Webcare responses to PeWOM with a high level of personification increase evaluation of perceived RI in comparison to webcare responses with a low level personification. The latter increases evaluation of perceived RI in comparison to no personification.

H2c. The positive effect of message personification on evaluation of perceived RI is mediated by perceived CHV.

Personalization

Another way to humanize webcare responses is using „personalization‟. The customer is, hereby, point of attention. Dijkstra (2008) describes personalization as including

“recognizable aspects of a person in content information” (p. 768). It is about personal information that refers to the customer. In fact, Demmers et al. (2014) focused on personal customer information gathered via companies‟ databases (e.g. information about customers‟ orders). Dijkstra (2008) suggested that personal information in a message leads to increased involvement, since the message seems personally relevant, and leads to more central processing of the other information in the message In addition, Vlasic and Kesic (2007) interpret personalization as a way of making the content unique and relevant for each customer individually. Vlasic and Kesic (2007) focused on personalization and its effects on the customer-company relationship. They showed that customers only prefer personalized messages from companies they can trust, so trustworthiness seems to be a determining factor.

17 Master thesis Nicolette Arkenbout Arora et al. (2008) and Chellappa and Sin (2005) confirm this by linking online personalization to invasion of privacy.

In particular, personalized webcare messages can be perceived as too personal, which can result in invasion of customers‟ privacy (Demmers et al., 2014). When customers‟ desired level of control is higher than the experienced level of control, privacy is invaded (Goodwin,

1991). In particular, when customers notice they are not in control of companies‟ behaviour towards collecting and sharing personal information, invasion of privacy occurs (Demmers et al., 2014). As a consequence, online privacy invasion has a negative impact on customers‟ attitude and behaviour towards the company (Awad & Krishnan, 2006; Demmers et al.,

2014).

In this study, personal customer information gathered via social media will be taken into account. Also in a social media context, invasion of privacy can easily occur (Zhang,

Wang & Xu, 2011). The information that is collected via social media can be seen as private information although it is publically available online. Companies could put time and effort in looking for this information, but it could increase invasion of customers‟ privacy, just as seems to be the case with „database information‟ (Demmers et al., 2014).

As a result, expectations can be made about personalization and perceived RI and evaluation of this investment. Firstly, since collecting and including personal information will cost the company time and effort, it might be expected that customers recognize these efforts and perceived RI will increase. Furthermore, Dijkstra (2008) suggested that personal items in a message lead to increased involvement. It might be assumed that the personalized webcare responses make a greater impression on the customer and, therefore, customers recognize the efforts the company makes. Moreover, De Wulf et al. (2001) mentioned that interpersonal communication needs a personal touch. On social media one could ensure this personal aspect in communication by including personal customer information. Besides, although Demmers et

18 Master thesis Nicolette Arkenbout al. (2014) did not investigate the effect of perceived CHV, personalization might be linked to

(the items of) CHV (Kelleher & Miller, 2006). In fact, when including personal customer information, an organization uses „conversation-style communication‟. Therefore, CHV might explain the expected positive effect of personalization on perceived RI.

H3a. Highly personalized webcare responses to PeWOM increase perceived RI in comparison to non-personalized webcare responses.

H3b. The positive effect of message personalization on perceived RI is mediated by perceived

CHV.

Secondly, it can be expected that customers might negatively evaluate a high amount of perceived RI when webcare responses contain too much personal information, because customers are not in control and feel their privacy is invaded (Demmers et al., 2014).

Although customers may be in control of their (non-)available personal information on social media, they cannot control to what extent companies search for it and decide to incorporate it in their public webcare responses. As a result, customers will not be satisfied with the amount of effort the company made to collect and share the information. Thus, perceived RI may be negatively evaluated when messages are highly personalized.

H4a. Highly personalized webcare responses to PeWOM negatively affect evaluation of RI evaluation in comparison to non-personalized webcare responses.

H4b. This negative effect of message personalization on evaluation of perceived RI is mediated by invasion of privacy.

19 Master thesis Nicolette Arkenbout Additional hypotheses

This study also investigates the effect of using both personification and personalization. Since both types separately can be linked to the positive effect of interpersonal communication on perceived RI showed by De Wulf et al. (2001), it can be expected that combining the types leads to more aspects of „real‟ interpersonal communication. Furthermore, the company makes various efforts by using message personification and personalization and the customer might acknowledge these efforts. Besides, when using both ways of humanization, it is likely that (more) aspects of perceived CHV are integrated more strongly. Next to that, when using both ways, there is a higher degree of social presence, so there is more impact on individuals‟ knowledge, attitude and behaviour (Kaplan & Haenlein, 2010). Customers might perceive webcare conversations as more real-life face-to-face conversations.

As a consequence, it can be expected that combining personification and personalization leads to more perceived RI via increased CHV than using only personalization

(H5a) and using only personification (H5b). These additive hypotheses are formulated based on prior hypotheses in this study. H1 and H3 are formulated to investigate whether personalization and personification affect amount of perceived RI separately. H5a and H5b are focused on the same effects, but for specific subsamples. For instance, H5a is formulated to investigate the effect of personification (H1), but only for webcare responses that are highly personalized (contain personal customer information).

H5a1. Highly personalized webcare responses to PeWOM with a high level of personification increase perceived RI in comparison to highly personalized webcare responses with a low level personification. The latter increases perceived RI in comparison to no personification.

H5a2. The positive effect of combining message personalization and personification on perceived RI is mediated by perceived CHV.

20 Master thesis Nicolette Arkenbout H5b1. Highly personalized webcare responses to PeWOM with a high level of personification increase perceived RI in comparison to non-personalized webcare responses with a high level of personification.

H5b2. The positive effect of combining message personification and personalization on perceived RI is mediated by perceived CHV.

Lastly, if previously formulated hypotheses 2 and 4 can be supported, this study can also provide knowledge about how customers evaluate companies‟ efforts when both personification and personalization are used. Although previous knowledge is missing, information is needed about whether putting effort in the customer-company relationship by combining message personification and personalization is beneficial (positive customers‟ evaluation) or not (negative customers‟ evaluation). In addition, it can be investigated whether

CHV or invasion of privacy has a greater impact on evaluation of perceived RI. As a result, the following exploratory sub-question is formulated: “To what extent does the combination of personification and personalization of webcare responses to PeWOM positively affect evaluation of perceived RI (due to perceived CHV) or negatively affect evaluation of perceived RI (due to invasion of privacy?)”

An overview of this study, the conceptual models, can be found in Figure 2a for perceived RI and in Figure 2b for evaluation of perceived RI.

21 Master thesis Nicolette Arkenbout

Figure 2a. Conceptual model (perceived RI)

Figure 2b. Conceptual model (evaluation of perceived RI)

22 Master thesis Nicolette Arkenbout Method

Design

To test the hypotheses, an online experiment was conducted with a 3 (message personification: no vs. low level vs. high level) x 2 (message personalization: absence vs. presence) between-subject design, see Table 1. Participants were randomly assigned to one of these six conditions. The dependent variables were perceived RI and evaluation of perceived

RI with mediators perceived CHV and invasion of privacy.

Table 1. Clarification of the conditions (number of participants in parentheses)

Condition Personification Personalization

1 (N = 31) No (Company account + Company signature) No personal information

2 (N = 34) Low (Company account + Employee signature) No personal information

3 (N = 32) High (Employee account + Employee signature) No personal information

4 (N = 32) No (Company account + Company signature) Personal information

5 (N = 32) Low (Company account + Employee signature) Personal information

6 (N = 31) High (Employee account + Employee signature) Personal information

Participants

The experimental questionnaire was written in Dutch and distributed among 237 Dutch potential participants of whom 197 filled in the complete questionnaire. Participants needed to be familiar with the social media platform used in this study. On average, Dutch customers are mostly active on Facebook (Marketingfacts, 2017), so Facebook was used as social media platform in this study. As expected, most of this study‟s participants used Facebook on a daily basis (N = 155), and most participants were, at least to a great extent, familiar with the fact that companies can be active on Facebook (N = 177). Participants who never used Facebook 23 Master thesis Nicolette Arkenbout (N = 3) and participants who were completely unfamiliar with the fact that companies can be active on Facebook (N = 2) were excluded from further analyses. As a result, 192 participants

(129 women and 63 men) with a mean age of 23.93 (SD = 5.67) (ages ranging from 14 to 69 years) remained. The majority of these participants (93%) was highly educated (N = 178). In addition, 71 participants (37%) indicated that they have had a conversation with a company via Facebook in the past.

The participants were distributed almost equally over the six conditions. Per condition, at least 31 participants filled in the experimental questionnaire. No significant differences were present between the six participant groups regarding participants‟ age, F(5, 186) = 0.43, p = .825, gender, χ2(5) = 9.24, p = .100, and education level, χ2(25) = 14.54, p = .952.

Furthermore, no significant differences were signalled between participants in the different conditions regarding how often participants used Facebook, χ2(15) = 9.82, p = .831, participants‟ familiarity with the fact that companies can be active on Facebook, F(5, 85.14) =

2.00 p = .093, and whether participants had an online conversation with a company before,

χ2(5) = 5.00, p = .416.

Stimuli

Participants were exposed to fictive webcare conversations between different customers and the company IKEA. IKEA was used as the conversing company, because its reputation is generally good (e.g. trustworthy and successful) (Fonk, 2015). Besides, Gretry et al. (2017) showed that unfamiliar brands are not allowed to be more informal due to inappropriateness, which might also be (partly) true for using humanization. Since IKEA is a well-known, familiar, brand, they might be allowed to be more personal than unfamiliar brands. Therefore, based on reputation and familiarity, IKEA was included in the stimuli for this study.

24 Master thesis Nicolette Arkenbout Two factors were included in this study: personification and personalization. The first factor, personification, was operationalized by the extent to which a specific person

(employee) sends the webcare response instead of a faceless company. Participants were exposed to webcare responses with no personification (1), a low level of personification (2) or a high level of personification (3). Specifically, webcare responses were either sent by the

IKEA team via the IKEA account (1), an employee named Yannick of the IKEA team via the same IKEA account (2) or an employee named Yannick of the IKEA team via his/her employee account (3). An example is illustrated in Figure 3. The operationalization for no personification and a high level of personification were based on how Schamari and Schaefers

(2015) operationalized personification. The comparable operationalizations of both studies can be found in Appendix A.

Hi! It’s great that you enjoy it so much! Kind regards, the IKEA team. 1.

Hi! It’s great that you enjoy it so much! Kind regards, the IKEA team. 2.

Hi! It’s great that you enjoy it so much! Kind regards, Yannick of the IKEA team. 3.

Figure 3. Example of no personification (1), low level of personification (2), high level of personification (3)

25 Master thesis Nicolette Arkenbout The second factor, personalization, was operationalized by the absence or presence of personal customer information. Demmers et al. (2014) gathered personal information via the company‟s database (e.g. information about the customer‟s order). In this study, personal information was gathered via customers‟ Facebook profile pages (e.g. recently posted events).

This study‟s results could perhaps contribute to more external validity, because another type of personal information was used. Besides, in this particular case, IKEA is not allowed to publicly share „database information‟, gathered via IKEA FAMILY accounts, due to specific terms and conditions. However, IKEA is allowed to search for personal „Facebook information’, since users can decide for themselves whether to share this information publicly or only with friends. Also in the stimuli, it was mentioned that IKEA retrieved the personal information from customers‟ Facebook pages. An example is illustrated in Figure 4.

In addition, a pretest was conducted to check what kind of Facebook information would be realistic and truly personal, and whether the manipulation of personification was successful (see Pretest and Appendix B). It is also worth noting that Figure 3 and 4 show the two factors separately. In the materials the factors are combined (Appendix C).

Hi! How nice to read that! It’s good to hear that you’re so happy with your new closet. Kind regards, the IKEA team. 1.

Hi! How nice to read that! It’s good to hear that you’re so happy with your new closet. This could be really useful, since you’re having new-born twins. What a nice picture on Facebook! Congratulations! Kind regards, the 2. IKEA team.

Figure 4. Example of no personalization (1), personalization (2)

26 Master thesis Nicolette Arkenbout Multiple other aspects were important to consider when creating the stimuli. Firstly, the customers‟ PeWOM messages were not posted on a completely brand-generated platform

(brand‟s Facebook page), because the positive effect of personification does not seem to be present on a brand-generated platform. Schamari and Schaefers (2015) used an online forum as a customer-generated platform. However, it seemed unlikely that this study‟s participants visit online forums regularly. It was assumed that participants were more familiar with

Facebook, so Facebook messages that were posted on customers‟ own publicly visible profile page were used in the materials. Next to that, in this study, the participants were observers.

Based on the Social Learning Theory (Bandura, 1977), it was shown that also observers can see a webcare response as a social reward and are willing to perform positive customer engagement behaviour (Schamari & Schaefers, 2015). Although Demmers et al. (2014) tried to let participants imagine they were initial customers that wrote the PeWOM message, invasion of customers‟ privacy might also be experienced by observers. Moreover, since

Schamari and Schaefers (2015) showed that pro-active, unexpected, responses are beneficial in PeWOM context, a pro-active response was included in the materials. In addition, recommendations were used as PeWOM messages. Lastly, to avoid gender effects, only gender-neutral names were used in the stimuli.

Pretest

A pretest was conducted to ensure the brand IKEA was suitable for this study, to ensure the manipulation of personification was successful and to choose which personalized responses were appropriate for the experimental questionnaire. The pretest (Dutch version) can be found in Appendix B. In total, 20 individuals (4 male and 16 female participants) with a mean age of

25.30 years (SD = 7.19) participated. All participants filled in all three parts of the pretest.

The first part concerned the brand IKEA, the second part concerned the manipulation of

27 Master thesis Nicolette Arkenbout personification, and the third part concerned personalization. The three parts and their results are discussed separately in this section.

Firstly, participants were exposed to the part regarding IKEA. Participants were asked to denote their initial attitude towards IKEA (not based on any stimuli) regarding perceived

RI and evaluation of perceived RI to check for floor or ceiling effects. The specific measurements of these two concepts can be found in the paragraph concerning Measures, because these 7-point scales were also used in the main experiment of this study. The results of this part of the pretest showed no extreme floor or ceiling effect for perceived RI (M =

5.08, SD = 0.66) and evaluation of perceived RI regarding IKEA (M = 4.88, SD = 0.77).

Secondly, the personification manipulation was checked. Pretest participants needed to confirm there was a difference between the IKEA team sending a message (stimuli with no personification) versus an employee named Yannick of the IKEA team sending the same message with the same IKEA account (stimuli with a low level of personification), so only the signature (name) was different. Only if they saw a difference, they were sent to a survey page with a text block and they were asked to denote what the difference was. All pretest participants (N = 20) recognized the difference between the messages and described the difference properly.

Thirdly, personalization was brought up, which was the biggest part of the pretest.

Because the final webcare responses in the experimental questionnaire needed to be perceived as responses that contained personal customer information and needed to be realistic, this part of the pretest was of great importance. Specifically, this part was needed to choose the most realistic responses that were perceived as containing personal customer information out of multiple optional responses.

The procedure of this last part regarding personalization was as follows. All pretest participants were exposed to two different webcare conversations, one conversation with

28 Master thesis Nicolette Arkenbout customer Marijn and one conversation with customer Jamy. It was clearly stated that the conversations were fictive. Per conversation, all pretest participants saw four different responses. In fact, they saw one non-personalized response and three personalized responses

(in Appendix B and in this section‟s Tables called: P1, P2, P3). These personalized responses contained diverse types of „Facebook information‟ (e.g. a remark about the place of residence, friends/family, recently posted events or posted pictures). All conversations with the different responses were shown on separate pages, so participants could not directly compare the responses. Per response, participants had to denote if the company, IKEA, could respond in this particular way in reality. This was measured with two items on a 7-point Likert scale (1 = strongly disagree, 7 = strongly agree) (e.g. “IKEA could have posted this response for real”).

After these items a filler item was included to keep the participants focused (“IKEA is being unfriendly”). Secondly, participants needed to indicate, per individual response, if the response contained personal customer information. Two items were used to measure this on a

7-point Likert scale (1 = strongly disagree, 7 = strongly agree) (e.g. “This response contains personal customer information”).

This last part of the pretest showed the following results. Per conversation, the most realistic responses that were perceived as containing personal customer information needed to be chosen. The results of the first conversation can be found in Table 2 and the results of the second conversation in Table 3. Firstly, in terms of realism, not all responses were perceived as sufficiently realistic (average scores were ranging from M = 2.90 to M = 4.70). It makes sense that several responses containing personal customer information gathered via Facebook are not all realistic, since it might already elicit a feeling of invasion of privacy. Participants might think IKEA will probably not want to elicit this feeling and, therefore, not post a certain response in real-life. However, for the first conversation, item P2 (a response about new born twins of a customer) was perceived as moderately realistic (Table 2). For the second

29 Master thesis Nicolette Arkenbout conversation, item P1 (a response that contained the place of customer‟s residence:

Leeuwarden) was perceived as moderately realistic (Table 3).

In addition, all responses with personal information were perceived as responses containing personal information (M‟s > 6.70), so also the most realistic responses. However, it had to be checked whether the (most realistic) personalized responses differed significantly, in terms of perceived personal information, from the non-personalized responses. Per conversation, a repeated measures ANOVA was performed. The two most realistic personalized responses (Conversation 1: P2, Conversation 2: P1) differed significantly in terms of perceived personal information from the non-personalized responses (Table 2 and 3).

As a result, these two responses were used in the materials.

Table 2. Mean scores, standard deviations (in parentheses) and difference mean scores (and p- values in parentheses) of a non-personalized response and three personalized responses of conversation 1 regarding the perceived realism of the responses and perceived presence of personal customer information (both assessed on a 7-point scale)

Difference non- personalized and Non-personalized response Personalized responses personalized Realism 5.90 (1.90) P1: 3.45 (2.21) P2: 4.20 (2.35) P3: 3.68 (2.43) Personal 2.05 (1.39) P1: 6.85 (0.46) -4.80 (< .001) P2: 6.70 (0.92) -4.65 (< .001) P3: 6.70 (0.55) -4.65 (< .001) Note: difference scores are only applicable to perceived presence of personal information

30 Master thesis Nicolette Arkenbout Table 3. Mean scores, standard deviations (in parentheses) and difference mean scores (and p- values in parentheses) of a non-personalized response and three personalized responses of conversation 2 regarding the perceived realism of the responses and perceived presence of personal customer information (both assessed on a 7-point scale)

Difference non- personalized and Non-personalized response Personalized responses personalized Realism 6.18 (1.73) P1: 4.70 (2.09) P2: 3.43 (2.10) P3: 2.90 (2.26) Personal 1.23 (0.44) P1: 6.78 (0.41) -5.55 (< .001) P2: 6.80 (0.59) -5.58 (< .001) P3: 6.93 (0.25) -5.70 (< .001) Note: difference scores are only applicable to perceived presence of personal information

In sum, IKEA could be seen as an applicable brand for this study, the personification manipulation was checked and recognized properly, and, per conversation, the most appropriate personalized response was chosen. All final materials (per condition) can be found in Appendix C.

Measures

In the experimental questionnaire, perceived CHV was measured on a 7-point Likert scale, using 4 items that were adopted from the CHV-scale of Kelleher and Miller (2006). The original scale consisted of 11 items. Four items that matched personalization and personification best were chosen to incorporate in this study. Three (out of four) items were also used by Schamari and Schaefers (2015) to measure CHV: “Is open to dialogue”, “Uses conversation-style communication”, “Treats the customer and others as human”. The last item that was inserted was: “Tries to communicate in a human voice”. Since „tries to‟ is

31 Master thesis Nicolette Arkenbout slightly vague in this context, this item was slightly reformulated: “Communicates in a human voice”. Together, the items formed a reliable scale (α = .86).

To measure invasion of privacy, the scale of Demmers et al. (2014) was used for input. Demmers et al. (2014) used 3 items for measuring invasion of privacy: “I think the amount of personal information used by… is inappropriate”, “… knows more about me than I would prefer”, and “… is on my online private territory”. The first item was used in this study, after this item was slightly re-formulated. The second item was also re-formulated, because measuring what the company knows about the customer does not take in account that

IKEA actually used that amount of personal information in a webcare response. The third item was mostly based on type of platform. In this study, „Facebook information‟ has been taken into account, so platform type was also of great importance here. Nevertheless, it was even more important to focus on companies‟ searching behaviour regarding this platform.

Therefore, two items that included the fact that companies need to search for personal customer information on this platform, were added to the scale. In sum, the following 4 items were used to measure invasion of privacy on a 7-point Likert scale (1 = strongly disagree, 7 = strongly agree): “IKEA’s response contains more personal customer information than preferred”, “The amount of personal customer information used by IKEA is appropriate”

(reverse coding), “IKEA intrudes into private lives by searching for this personal customer information” and “IKEA’s search behaviour towards this personal customer information is improper”. This scale was highly reliable (α = .92).

Perceived relationship investment (RI) was measured using 3 items on a 7-point Likert scale (1 = strongly disagree, 7 = strongly agree) that were also used by De Wulf et al. (2001) for measuring perceived RI. To ensure the statements were understandable and fitted the context of the study, the items were re-formulated. In addition, after analysing the pretest results, these items did not prove to be sufficiently reliable due to the third item (α = .68).

32 Master thesis Nicolette Arkenbout Therefore, the third item (“IKEA really cares about keeping customers”) of the scale was re- formulated once more. Eventually, the following items are used: “IKEA makes effort to increase customers´ loyalty”, “IKEA makes various efforts to improve its tie with customers” and “IKEA strives to keep customers”. In the experimental questionnaire, these items proved to be a reliable scale (α = .86).

Lastly, to measure how customers evaluated perceived RI and whether they were satisfied with the perceived RI, semantic differential items were included. The items are comparable to the items of Crosby, Evans and Cowles (1990): “satisfied/dissatisfied”,

“pleased/displeased”, and “favourable/unfavourable”. These three items were used in different studies about satisfaction (Jones & Suh, 2000; Rafiq et al., 2013; Szymanski & Hise,

2000). Demmers et al. (2014) included the first item as well and replaced the other items with comparable items. The items used by Demmers et al. (2014) seemed most suitable for this study: “dissatisfied/satisfied”, “bad/good” and “positive/negative” (reverse coding), because these items were used to measure satisfaction, but there is a focus on valence

(positive/negative). This latter aspect was important for measuring evaluation of perceived RI.

The first item was shown with the following question: “How satisfied are you with IKEA’s efforts to improve its tie with customers?” The second and third item were shown with: “How would you evaluate IKEA’s efforts to improve its tie with customers?” The items were measured on a 7-point semantic differential scale, which proved to be reliable (α = .91).

It is worth noting that reliability of all scales was retrieved by calculating the

Cronbach‟s alpha of the combined items in all conditions at once, with the two webcare conversations combined. Values of Cronbach‟s alpha per conversation (which were also sufficient) can be found in Appendix D. All Dutch translations of the items can be found in the Dutch experimental questionnaire in Appendix E.

33 Master thesis Nicolette Arkenbout Procedure

First, the participants were gathered through personal network and snowball sampling

(Treadwell, 2013). They received an anonymous online link to an online Qualtrics questionnaire. First, an introduction text about this webcare study was shown. It was clearly stated that participants stayed anonymous and that they were allowed to stop participation at any time. Then, the participants were randomly assigned to one of the six conditions. They were exposed to four fictive webcare conversations between a customer and IKEA: (1) a filler conversation, (2) the first experimental conversation, (3) a filler conversation, (4) the second experimental conversation. The filler conversations were added to distract the participant. The fillers were neutral eWOM messages that contained questions. IKEA responded to the questions as short and concise as possible. All filler conversations were the same in each condition. However, the account that the messages were sent by (either IKEA or Yannick from IKEA) was in line with the particular condition, to ensure the participants did not recognize the difference in senders immediately. Otherwise, when using another IKEA account in the fillers, the difference between an employee account (a real person) and the

IKEA filler account would immediately be bigger than the difference between the corporate

IKEA account and the IKEA filler account. The fillers can be found in Appendix F.

Per conversation, participants were asked to denote to what extend they agreed with the statements regarding CHV, invasion of privacy, perceived RI and evaluation of perceived

RI. After all conversations, the participants were asked to indicate how often they used

Facebook, if they were familiar with the fact that companies are active on Facebook, and if they ever had a Facebook conversation with a company. Next, they were asked to share their demographic information (gender, age and education level). Lastly, it was mentioned that the shown conversations between customers and IKEA were fictive and they were thanked for their cooperation. It took the participants 8 to 10 minutes to complete the questionnaire.

34 Master thesis Nicolette Arkenbout Results

Demographic variables

Before conducting main analyses, it was checked whether the demographic variables affected the dependent variables. All results concerning demographic variables can be found in

Appendix G. Participants‟ age, gender, education level, and whether participants had a

Facebook conversation with a company before, did not have an effect on the dependent variables. However, participants‟ familiarity with the fact that companies can be active on

Facebook correlated positively with one of the dependent variables, perceived RI (r = .25, p <

.001). Also how often participants used Facebook slightly correlated with perceived RI (rs =

.142, p = .050). Although this last effect was small, because the p-value did not indicate a strong significant effect, it was decided to control for both these variables in the main analyses. If the demographic variables did not affect perceived RI, one two-way MANOVA test could have been performed, since the dependent variables correlated at a low level (r =

.38, p = < .001), so they were considered as separate dependent variables. However, due to the influence of the demographic variables on only one dependent variable, a two-way ANCOVA test for perceived RI and one two-way ANOVA for evaluation on RI seemed the most appropriate statistical tests.

Assumptions

To perform a two-way ANCOVA and a two-way ANOVA test, several assumptions were checked. First, to check whether the data were normally distributed, a normality check was performed. The results can be found in Appendix H. Five Z-scores exceed the values of -1.96 and 1.96 and the Kolmogorov-Smirnov test showed significant differences from a normal distribution. Thus, the assumption of normality was not met. Nevertheless, a two-way

35 Master thesis Nicolette Arkenbout ANOVA does not provide an alternative or corrective option, so one should interpret the results of these statistical tests with caution.

Furthermore, the assumption of homogeneity and the assumption of independent observations were checked. For perceived RI, the assumption of homogeneity of variances was met, because Levene‟s test of equality of error variances was not significant (F(5, 186) =

1.49, p = .196. Also for evaluation of perceived RI, the assumption of homogeneity of variances was met, since Levene‟s test of equality of error variances was not significant, F(5,

186) = 1.96 , p = .086. Next to that, the assumption of independent observations was met, because participants were asked to participate by filling in the experimental questionnaire on their own device at any time they preferred.

Main analyses

Firstly, to investigate the effects of personification and personalization on perceived RI, a two-way ANCOVA test was performed with participants‟ familiarity with the fact that companies can be active on Facebook and how often participants used Facebook as covariates. All mean scores were rather high, as can be seen in Table 4. The two-way

ANCOVA showed no significant main effect of personification on perceived RI, F(2, 184) =

1.00, p = .370, and no significant main effect of personalization on perceived RI, F(1, 184) =

0.09, p = .758. In addition, no interaction effect was found, F(2, 184) = 1.12, p = .329. 1

1 The statistical test was also performed without taking covariates into account. The values did not change to a great extent. Similar to the two-way ANCOVA, a two-way ANOVA showed no significant effects. 36 Master thesis Nicolette Arkenbout Table 4. Mean scores and standard deviations (in parentheses) of personification and personalization regarding perceived RI (assessed on a 7-point scale)

No personalization Personalization Total

No personification 5.54 (0.75) 5.83 (0.68) 5.69 (0.73)

Personification (low) 5.92 (0.76) 5.82 (0.95) 5.87 (0.85)

Personification (high) 5.71 (0.53) 5.72 (0.80) 5.71 (0.67)

Total 5.73 (0.70) 5.79 (0.81)

Secondly, to investigate the effects of personification and personalization on evaluation of perceived of RI, the two-way ANOVA test was performed. The mean scores can be found in Table 5. Overall, the two-way ANOVA showed a small positive main effect of personification, F(2, 186) = 3.26, p = .041, ղ2 = .034. However, the contrasts showed that when an employee sends the webcare response with the IKEA account (M = 5.15, SD = 1.09) company‟s investment in the customer-company relationship was evaluated more positively than when an employee sends the webcare response with an employee account (M = 4.66, SD

= 1.34), p = .012. In other words, a low level of personification is evaluated more positively than a high level of personification. The contrasts showed no significant differences between no personification and a low level of personification (p = .147) and no personification and a high level of personification (p =.285). In addition, the ANOVA showed a significant main effect of personalization on evaluation of perceived RI, F(1, 186) = 62.35, p < .001, ղ2 = .251.

The contrast showed that when no personal information was added (M = 5.49, SD = 0.95) company‟s investment in the customer-company relationship was evaluated more positively than when personal information was added (M = 4.28, SD = 1.19). Besides, there was no interaction effect, F(2, 186) = 0.56, p = .575.

37 Master thesis Nicolette Arkenbout Table 5. Mean scores and standard deviations (in parentheses) of personification and personalization regarding evaluation of perceived RI (assessed on a 7-point scale)

No personalization Personalization Total

No personification 5.57 (0.79) 4.15 (1.16) 4.85 (1.22)

Personification (low) 5.65 (0.94) 4.61 (0.99) 5.15 (1.09)**

Personification (high) 5.25 (1.07) 4.06 (1.35) 4.66 (1.34)**

Total 5.49 (0.95)* 4.28 (1.19)*

Note: significant difference between values in same row with * and significant difference between values in same column with **

Since two webcare conversations were used in the experiment, an additional mixed repeated measures ANOVA test was conducted to check whether the conversations‟ results differed. Specifically, the conversation between Marijn en IKEA (conversation 1) and the conversation between Jamy and IKEA (conversation 2) could have led to different results.

The ANOVA showed that the results of the conversations regarding perceived RI and evaluation of perceived RI differed significantly on one aspect. As a matter of fact, the test revealed a significant main effect between conversation and personalization regarding perceived RI, F(1, 186) = 3.78, p = .053, 2 = .020, and evaluation of perceived RI, F(1, 186)

= 4.91, p = .028, 2 = .026. When only conversation 1 or 2 was used for the main analyses, the results still showed no significant main effect of personalization on perceived RI and still showed a significant main effect of personalization on evaluation of perceived RI. It can be concluded that, although there was a difference between the two conversations in terms of personalization and perceived RI and evaluation of perceived RI, it did not lead to significantly different results.

38 Master thesis Nicolette Arkenbout Furthermore, to investigate whether perceived CHV and invasion of privacy had an influence, several mediation analyses were performed using the mediation model (model 4) of

PROCESS in SPSS (Hayes, 2013). Since main effects were only found on evaluation of perceived RI, the mediation analyses regarding this dependent variable are discussed first.

Firstly, a mediation analysis was performed to test if the effect of personalization on evaluation of perceived RI could be explained by invasion of privacy (Figure 5). The analysis showed the already found main effect, the total effect. When taking invasion of privacy into account as a mediator, it showed that personalization positively affects invasion of privacy, and invasion of privacy negatively affects evaluation of perceived RI. The indirect effect, that measures mediation, was significant. After controlling for the mediator, the direct effect was not significant, so only when the mediator was taken into account, an effect was found. It can be stated that invasion of privacy mediated the negative effect of personalization on evaluation of perceived RI.

Figure 5. Mediation analysis (personalization on evaluation of perceived RI)

Secondly, two mediation analyses were performed to test whether the main effect of personification on evaluation of perceived RI could be explained by CHV. Two analyses were

39 Master thesis Nicolette Arkenbout needed due to the fact that the categorical variable personification had to be transformed to 2 dummy variables. The first analysis (Appendix I, Figure 6) (low level vs. no and high level) showed the already found main effect, the total effect (b = 0.39, SE = 0.19 p = .036, 95% CI

[0.03, 0.76]). No significant direct or indirect effect was shown. The next analysis (Appendix

I, Figure 7) (high level vs. no and low level) did not show the main effect (b = -0.34, SE =

0.18 p = .076, 95% CI [-0.71, 0.04]). Thus, the ANOVA showed a significant difference between a low level and a high level of personification, but apparently mostly the low level ensured the main effect. Surprisingly, the latter mediation analysis showed a significant indirect effect (b = -0.14, SE = 0.07, 95% CI [-0.31, -0.03]), although no main effect was found. A high level of personification negatively affected perceived CHV and CHV positively affected evaluation of perceived RI, but the total indirect effect was negative, meaning that a high level of personification negatively affected evaluation of perceived RI via CHV.

In addition, the mediation analysis regarding a high level of personification and the other dependent variable, perceived RI, showed a similar outcome (Appendix I, Figure 10).

Although there was no main effect, a similar significant indirect effect was shown (b = -0.15,

SE = 0.07, 95% CI [-0.29, -0.03]). Again, a high level of personification negatively affected perceived CHV and CHV positively affected perceived RI, but the overall indirect effect was negative, meaning that a high level negatively affected perceived RI via CHV. Thus, both mediation analyses showed that a high level of personification has a negative effect on CHV.

However, CHV had a positive influence on both perceived RI and evaluation of perceived RI.

Next to that, five other mediation analyses were performed to further investigate CHV.

All results of these analyses can be found in Appendix I. All mediation analyses showed significant positive effects between perceived CHV and perceived RI and between perceived

CHV and evaluation of perceived RI (b ranging from 0.47 to 0.54, all accompanied with p <

.001). No other effects were found.

40 Master thesis Nicolette Arkenbout Conclusion and discussion

The purpose of this study was to answer the following research question: “To what extent does personification and personalization of webcare responses to PeWOM affect perceived relationship investment?”

First of all, no effect of personification was found regarding perceived RI. Since no differences were found between the different levels of personification, hypotheses 1 can be rejected. It can be concluded that using personification does not influence the perceived amount of effort the company makes to maintain or enhance the customer-company relationship. However, personification did have an effect on evaluation of perceived RI.

Although a small positive main effect was found, a low level of personification was evaluated more positively than a high level of personification, which was not expected. Therefore, hypothesis 2 cannot be fully supported. It can be concluded that when an employee sends a webcare response via the company‟s account, so only the employee‟s signature is present, individuals evaluate this more positively than when an employee sends a webcare response via an employee social media account.

Furthermore, in terms of personalization, no effect was found between personalization and perceived RI. No differences were found between the absence and presence of personal information in webcare responses, so hypothesis 3 can be rejected. Individuals do not acknowledge the extra effort of adding personal customer information. In addition, as predicted, individuals evaluated company‟s efforts to add personal information to webcare messages more negatively than when no personal information was added, due to invasion of privacy. Thus, hypothesis 4 can be supported.

Some other conclusions can be drawn. Firstly, additional hypothesis 5 can be rejected, since it was based on hypotheses 1 and 3 (which are rejected). Secondly, regarding perceived conversational human voice (CHV), it can be concluded that a high level of personification

41 Master thesis Nicolette Arkenbout negatively affects CHV. However, CHV has a positive effect on both perceived RI and evaluation of perceived RI.

Personification

The predictions regarding the effect of personification on perceived RI and evaluation of perceived RI were not accurate. In this section, this study‟s results and previous literature will be discussed to find possible explanations for the results.

For perceived RI, it was expected that using human representatives to send webcare responses would increase perceived RI. De Wulf et al. (2001) stated that interpersonal communication was the most prominent predictor of perceived RI. In this study, customers in a high level condition were exposed to a human representative of a company, a person who was visible through a profile picture. This would mean the degree of social presence was higher than in other conditions and the influence on knowledge would be greater (Kaplan &

Haenlein, 2010). However, no effect was found. In terms of the Social Presence Theory

(Short et al., 1976), perhaps the presence of an employee account was not perceived as social presence. It might be the case that the theory cannot completely be applied to social media accounts. Nevertheless, Schamari and Schaefers (2015) found a positive effect of employee accounts, although the materials of Schamari and Schaefers (2015) can be assumed to be similar to this study‟s materials (Appendix A). Perhaps type of platform explains the different results. In this study, a semi consumer-generated platform was used, namely statuses on customers‟ own Facebook pages. Perhaps only a true consumer-generated platform, like a forum, elicits a certain positive effect like in the study of Schamari and Schaefers (2015).

Next to that, remarkably, a high level of personification negatively affected perceived

CHV, which is also conflicting with the results of Schamari and Schaefers (2015). Perhaps, when an employee‟s account was used, participants did not perceive the employee as being

42 Master thesis Nicolette Arkenbout „IKEA‟ and perceived CHV was measured with items like “IKEA communicates in a human voice”. It might not have been completely clear that the employee represents the brand. Apart from perceived CHV, another reason could be that an employee‟s account is perceived as someone‟s account who is unfamiliar and, therefore, perceived as a stranger. An official company‟s account is perhaps more familiar and, therefore, more trustworthy (Gretry et al.,

2017). Perhaps the advantages of using human representatives are only present when representatives are trustworthy enough.

Overall, it is remarkable that, on average, individuals perceived all webcare responses

(all three levels of personification) as a sign of the company making an effort to improve the relationship. It is assumable that when a company pro-actively responds to PeWOM, it is perceived as a high amount of investment, as the customer does not expect a response.

For evaluation of perceived RI, the results were not in line with the hypotheses and previous literature. Employees were visible through a profile picture. This would mean the degree of social presence was higher than in other conditions and the influence would be greater (Kaplan & Haenlein, 2010). In fact, personification should lead to various positive relational outcomes (Kerkhof et al., 2010; Park & Lee, 2013; Schamari & Schaefers, 2015).

However, in this study, personification did not have a truly positive effect although the small main effect was positive. Because there was no significant difference between no personification and a low or high level of personification, one cannot clearly conclude whether personification is preferable or not. A message that was sent with only a signature of an employee was perceived as more positive than when this message was sent via an employee‟s account. This finding is not in line with the Social Presence Theory (Short et al.,

1976). In addition, previous literature about human representatives does not provide a clear theoretical explanation for this finding. Moreover, it has been found, just as for perceived RI, that a high level of personification negatively affected perceived CHV.

43 Master thesis Nicolette Arkenbout Since most hypotheses regarding evaluation of perceived RI were not supported, the overall exploratory question was not applicable anymore. However, based on this study, one could conclude that it is better to avoid invasion of customers‟ privacy by not adding personal

Facebook information. In contrast, it is preferable to ensure a conversational human voice, since it has a positive effect on both perceived RI and evaluation of perceived RI. This study can give no concrete insights into how to increase CHV through personification or personalization, but, overall, using a conversational human voice is preferable. These findings are in line with Kelleher and Miller (2006) and Dijkmans et al. (2015) that showed that perceived CHV leads to several positive outcomes.

Personalization

The predictions regarding the effect of personalization on perceived RI and evaluation of perceived RI were not all accurate. In this section, this study‟s results and previous literature will be discussed to find possible explanations for the results.

For perceived RI, it was expected that adding personal information would increase perceived RI, but no effect was found. Although Dijkstra (2008) suggested that personal items in a message lead to increased involvement and De Wulf et al. (2001) showed that interpersonal communication (with a personal touch) is the best predictor of perceived RI, individuals did not perceive it as an extra investment of the company in this study. It might be the case that observing audience did not experience the personal items as personally relevant, so a message that is not directed at themselves might not lead to more involvement and awareness of the company‟s investment. However, that would not be in line with the Social

Learning Theory (Bandura, 1977). Next to that, perhaps including personal Facebook information in the response was not seen as an extra effort, because Facebook information could be perceived as relatively easily accessible.

44 Master thesis Nicolette Arkenbout Overall, just as for personification, on average, individuals perceived all webcare responses (with and without personal information) as a sign of the company making an effort to improve the relationship. This strengthens the assumption that when a company pro- actively responds to PeWOM, it can be perceived as a high amount of investment.

It was also found that personalization did not affect perceived CHV. Since CHV can be described as an “engaging and natural style” (Kelleher, 2009), perhaps adding that type and amount of personal information cannot be seen as more „engaging‟ or „natural‟

“conversation-style communication”. In fact, according to the pretest, it is only moderately realistic to use this particular type of information in webcare, so perhaps „Facebook information‟ cannot be linked to a truly realistic CHV. Overall, since no previous studies, like

Demmers et al. (2014), focused on this particular topic, it is hard to explain this finding.

For evaluation of perceived RI, the results were in line with the hypotheses and previous literature. Customers were not in control of companies‟ behaviour towards collecting personal information, so invasion of privacy occurred (Demmers et al., 2014). In general, the desired level of control was higher than the experienced level of control (Goodwin, 1991).

This invasion of privacy explained the negative effect between personalization and evaluation of perceived RI.

Limitations and suggestions for future research

One of the limitations of this study was the optional influence of fillers. All filler conversations were the same in each condition. However, the account that the messages were sent by (either the company or the employee) was in line with the particular condition, to ensure the participants did not recognize the difference in senders immediately. However, this might have influenced the effect of the employee account or just decreased the awareness of

45 Master thesis Nicolette Arkenbout the employee account. When a control question was used to check whether all participants really noticed the employee account, this optional influence would have been clearer.

Another possible limitation could be the fact that a semi consumer-generated platform was used. Further research could focus on the possible effect of semi consumer-generated platforms, like consumers‟ Facebook pages, and truly consumer-generated platforms, like a fan forum, and perhaps compare it to brand-generated platforms to investigate the influence of type of platform more thoroughly.

Based on several other (possible) limitations and the results of this study, more suggestions can be made for further research. First, further research could focus more on personification. This study found that adding the signature of an employee is more preferable than using an employee account with a profile picture. However, these results needed to be interpreted with caution and Schamari and Schaefers (2015) showed that using an employee account with a profile picture leads to more customer engagement. Therefore, further research should focus on the effect of personification by visualizing (or mentioning) employees in multiple ways to see to what extent or in what context personification can be beneficial (e.g. signature/no signature, profile picture/no profile picture). Perhaps following studies can also measure the perceived degree of social presence and provide more information about which way(s) of personification lead to more online social presence. Moreover, personification did not seem to have a positive effect on CHV in this study, but Schamari and Schaefers found a positive effect of personification on CHV. Therefore, more research is needed about in which circumstances personification can increase perceived CHV.

Furthermore, regarding personalization, it could be interesting to investigate to what extent adding personal information to webcare responses to PeWOM is perceived as positive.

It could be investigated what amount or type of personal customer information does not elicit invasion of customers‟ privacy, but leads to personal relevant messages and increased

46 Master thesis Nicolette Arkenbout involvement, as Dijkstra (2008) suggested. Just as in this study, Demmers et al. (2014) only focused on adding highly personal items. Perhaps using only customers‟ first names in webcare responses could lead to more personal relevance and positive outcomes. Besides,

CHV could be incorporated in further research regarding personalization, since other types of personal information than „Facebook information‟ might have an effect on CHV.

Next to that, it might be interesting to compare pro-active and reactive webcare responses to PeWOM. Van Noort & Willemsen (2011) stated that pro-active responses to

NeWOM is only preferable on brand-generated platforms, but Schamari and Schaefers (2015) suggested that pro-active responses to PeWOM on consumer-generated platforms leads to positive customer engagement, since it can be seen as a surprising reward. Further studies could include several types of platforms, also customers‟ personal Facebook pages that were used in this study, and use both pro-active and reactive responses to PeWOM to investigate how the type of response and type of platform might interact.

Theoretical and practical implications

This study contributes to the current knowledge on humanization of webcare in response to

PeWOM on multiple levels. First of all, personification and personalization does not affect perceived RI, although a positive effect could be expected, since offline interpersonal communication affects perceived RI. Besides, Demmers et al. (2014) showed that „database information‟ leaded to invasion of customers‟ privacy. This study expanded on this topic by taking personal „Facebook information‟ into account. Also this latter type of personal customer information seems to have a negative effect explained by invasion of customers‟ privacy. Moreover, this study added some knowledge on perceived CHV. Kelleher and Miller

(2006) already have shown that perceived CHV positively correlates with relational outcomes: trust, satisfaction, control mutuality and commitment. Based on this study, one

47 Master thesis Nicolette Arkenbout could also state that perceived CHV positively affects perceived RI and evaluation of perceived RI in a webcare context.

Based on this study, also several practical implications can be made. First of all, it can be truly recommended that companies should not use personal Facebook information in webcare responses to PeWOM, since it increases invasion of customers‟ privacy and leads to less positive evaluation of the efforts made by the company. Furthermore, this study implies that companies should prefer letting an employee send webcare responses with only a signature at the end of the message instead of creating employee accounts with profile pictures. However, this implication should be not be taken by heart, since the statistical test needed to be interpreted with caution and because Schamari and Schaefers (2015) found other effects of using employees. On the contrary, it can be truly recommended that companies should communicate with a conversational human voice instead of a corporate human voice, since CHV increases perceived RI and results in positive evaluations of these efforts. This particular study cannot give recommendations on how to establish this, but the importance of communicating with a more CHV has been made clear. In sum, adding personal Facebook customer information to webcare responses can be discouraged and it is highly recommended to incorporate a more conversational human voice. Hence, organizations can let go of using a corporate voice and truly focus on enhancing an engaging and natural communication style.

48 Master thesis Nicolette Arkenbout References

Arora, N., Dreze, X., Ghose, A., Hess, J., & Iyengar, R. (2008). Putting one-to-one marketing

to work: Personalization, customization, and choice. Marketing Letters, 19(3), 305-

321.

Awad, N., & Krishnan, M. (2006). The personalization privacy paradox: An empirical

evaluation of information transparency and the willingness to be profiled online for

personalization. MIS Quarterly, 30(1), 13-28.

Bandura, A. (1977). Social learning theory. Englewood Cliffs: Prentice-Hall.

Brown, P., & Levinson, S. C. (1987). Politeness: Some universals in language usage (Vol. 4).

Cambridge: Cambridge University press.

Chellappa, R. K., & Sin, R. G. (2005). Personalization versus privacy: An empirical

examination of the online consumer‟s dilemma. Information Technology and

Management, 6(2), 181-202.

Clark, M., & Melancon, J. (2013). The influence of social media investment on relational

outcomes: A relationship marketing perspective. International Journal of Marketing

Studies, 5(4), 132.

Crosby, L. A., Evans, K. R., & Cowles, D. (1990). Relationship quality in services

selling: An interpersonal influence perspective. Journal of Marketing, 54(3), 68-81.

De Wulf, K., Odekerken-Schröder, G., & Iacobucci, D. (2001). Investments in consumer

relationships: A cross-country and cross-industry exploration. Journal of

Marketing, 65(4), 33-50.

Demmers, J., Van Dolen, W. M., & Weltevreden, J. W. J. (2014). 4.“Bedankt voor het

compliment!” Het effect van bedrijfsreacties op positieve online word-of-mouth.

Ontwikkelingen in het marktonderzoek, 39e jaarboek MarktOnderzoekAssociatie, 55-

70.

49 Master thesis Nicolette Arkenbout Dijkmans, C., Kerkhof, P., Buyukcan-Tetik, A., & Beukeboom, C. (2015). Online

conversation and corporate reputation: a two-wave longitudinal study on the effects of

exposure to the social media activities of a highly interactive company. Journal of

Computer-Mediated Communication, 20(6), 632-648.

Dijkstra, A. (2008). The psychology of tailoring‐ingredients in computer‐tailored

persuasion. Social and Personality Psychology Compass, 2(2), 765-784.

East, R., Hammond, K., & Wright, M. (2007). The relative incidence of positive and negative

word of mouth: A multi-category study. International Journal of Research in

Marketing, 24(2), 175-184.

Fonk. (2015). Incompany 500: IKEA is merk met beste reputatie. Retrieved from:

https://fonkonline.nl/artikelen/prijzen/incompany-500-ikea-is-merk-met-beste-

reputatie-31637.html

Fournier, S., & Avery, J. (2011). The Uninvited Brand. Business Horizons, 54(3), 193-207.

Goodwin, C. (1991). Privacy: Recognition of a consumer right. Journal of Public Policy &

Marketing, 10(1), 149-166.

Grégoire, Y., Salle, A., & Tripp, T.M. (2015). Managing social media crises with your

customers: the good, the bad, and the ugly. Business Horizons, 58(2), 173-182.

Gretry, A., Horváth, C., Belei, N., & Van Riel, A.C.R. (2017). “Don‟t pretend to be my

friend!” When an informal brand communication style backfires on social media.

Journal of Business Research, 74, 77-89.

Gunawardena, C. N. (1995). Social presence theory and implications for interaction and

collaborative learning in computer conferences. International Journal of Educational

Telecommunications, 1(2), 147-166.

Hayes, A.F. (2013). PROCESS [Computer software].

Hennig-Thurau, T., Gwinner, K. P., Walsh, G., & Gremler, D. D. (2004). Electronic word-of

50 Master thesis Nicolette Arkenbout mouth via consumer-opinion platforms: what motivates consumers to articulate

themselves on the internet? Journal of Interactive Marketing, 18(1), 38-52.

Huibers, J., & Verhoeven, J. (2014). Webcare als online reputatiemanagement. Tijdschrift

voor Communicatiewetenschap, 42(2), 165-189.

Jones, M., & Suh, J. (2000). Transaction-specific satisfaction and overall satisfaction: An

empirical analysis. Journal of Services Marketing, 14(2), 147-159.

Kaplan, A. M., & Haenlein, M. (2010). Users of the world, unite! The challenges and

opportunities of Social Media. Business Horizons, 53(1), 59-68.

Kelleher, T. (2009). Conversational voice, communicated commitment, and public relations

outcomes in interactive online communication. Journal of Communication, 59(1), 172-

188.

Kelleher, T., & Miller, B.M. (2006). Organizational blogs and the human voice: relational

strategies and relational outcomes. Journal of Computer-Mediated Communication,

11(2), 395-414.

Kerkhof, P. Beukeboom, C. J., Utz, S., & De Waard, J. (2010, February). Het vermenselijken

van een bedrijf: Effecten van persoonlijke vs. onpersoonlijke bedrijfsreacties op online

klachten van consumenten. [Humanizing an organization: effects of personal and

impersonal reactions on negative consumer reviews]. Paper presented at the 9th

Etmaal van de Communicatiewetenschap, Ghent, Belgium.

Koot, F. (2013). Organizations with a Human Voice: Antecedents and Consequences of a

Conversational Human Voice in the Webcare Responses of

Organizations. Unpublished Master‟s thesis (UVA Amsterdam).

Kwon, E. S., & Sung, Y. (2011). Follow me! Global marketers‟ Twitter use. Journal of

Interactive Advertising, 12(1), 4-16.

51 Master thesis Nicolette Arkenbout Lee, D., Kim, H. S., & Kim, J. K. (2011). The impact of online brand community type on

consumer's community engagement behaviors: Consumer-created vs. marketer-created

online brand community in online social-networking web sites. Cyberpsychology,

Behavior, and Social Networking, 14(1-2), 59-63.

Marketingfacts. (2017). Social media in Nederland 2017: Instagram & Snapchat favoriet

onder jongeren. Retrieved from:

https://www.marketingfacts.nl/berichten/nationale-social-media-onderzoek-2017

Muntinga, D.G., Moorman, M., & Smit, E.G. (2011). Introducing COBRAs: Exploring

motivations for brand-related social media use. International Journal of Advertising,

30(1), 30-46.

Park, H., & Kim, Y. K. (2014). The role of social network websites in the consumer–brand

relationship. Journal of Retailing and Consumer Services, 21(4), 460-467.

Park, H., & Lee, H. (2013). Show us you are real: The effect of human-versus-organizational

presence on online relationship building through social networking sites.

Cyberpsychology, Behavior, and Social Networking, 16(4), 265-271.

Rafiq, M., Fulford, H., & Lu, X. (2013). Building customer loyalty in online retailing: The

role of relationship quality. Journal of Marketing Management, 29(3-4), 494-517.

Schamari, J., & Schaefers, T. (2015). Leaving the home turf: how brands can use webcare

on consumer-generated platforms to increase positive consumer engagement. Journal

of Interactive Marketing, 30, 20-33.

Short, J., Williams, E., & Christie, B. (1976). The social psychology

of telecommunications. London: John Wiley & Sons.

Sung, K. H., & Kim, S. (2014). I want to be your friend: The effects of organizations‟

interpersonal approaches on social networking sites. Journal of Public Relations

Research, 26(3), 235-255.

52 Master thesis Nicolette Arkenbout Strauss, J., & Hill, D. J. (2001). Consumer complaints by e-mail: an exploratory investigation

of corporate responses and customer reactions. Journal of Interactive Marketing,

15(1), 63-73.

Szymanski, D. M., & Hise, R. T. (2000). E-satisfaction: an initial examination. Journal of

Retailing, 76(3), 309-322.

Treadwell, D. (2013). Introducing communication research: Paths of inquiry. SAGE

Publications.

Van Noort, G. & Willemsen, L. M. (2011). Online Damage Control: The Effects of Proactive

Versus Reactive Webcare Interventions in Consumer-generated and Brand-generated

Platforms. Journal of Interactive Marketing, 26(3), 131-140.

Van Noort, G., Willemsen, L. M., Kerkhof, P., & Verhoeven, J. W. (2014). Webcare as an

Integrative tool for customer care, reputation management, and online marketing: a

literature review. Integrated Communications in the Post-Modern Erea, 1(1), 77-99.

Van Os, R., Hachmang, D., Derksen, M., & Keuning, A. (2016). Stand van webcare 2016:

Hoe doen Nederlandse organisaties webcare anno 2016? Retrieved from:

http://www.marketingfacts.nl/images/research/Whitepaper-Stand-van-Webcare-NL-

2016.pdf

Vlasic, G., & Kesic, T. (2007). Analysis of consumers' attitudes toward interactivity and

relationship personalization as contemporary developments in interactive marketing

communication. Journal of Marketing Communications, 13(2), 109-129.

Walther, J. B. (2011). Theories of computer-mediated communication and interpersonal

relations. The Handbook of Interpersonal Communication, 4, 443-479.

Zhang, N., Wang, C., & Xu, Y. (2011).Privacy in online social networks. In D. Galletta and

T. Liang (Eds.), Proceedings of the 32th International Conference on Information

Systems held in Shanghai 2011. Atlanta: Association for Information Systems.

53 Master thesis Nicolette Arkenbout Appendices

Appendix A – Operationalization personification

Figure. No personification, operationalization by Schamari and Schaefers (2015)

Figure. Personification, operationalization by Schamari and Schaefers (2015)

Figure. No personification, this study‟s operationalization

Figure. High level of personification, this study‟s operationalization

54 Master thesis Nicolette Arkenbout Appendix B – Pretest

Introductie

Beste deelnemer,

Voor mijn masterscriptie ga ik het effect van personalisatie in webcare nader bestuderen. Hierbij kunt u bijvoorbeeld denken aan het effect van een gepersonaliseerde (in vergelijking met een niet-gepersonaliseerde) Facebook-reactie van een bedrijf op een Facebook-bericht van een klant. In een later stadium zal ik een enquête verspreiden om meer inzicht te krijgen in dit effect. Voor die uiteindelijke enquête is materiaal nodig dat voldoet aan bepaalde criteria.

Vandaar dat in deze enquête verschillende materialen zullen worden getoond die door u en andere deelnemers zullen worden beoordeeld. Uw mening is dus enorm van belang. Graag wil ik benadrukken dat het om uw eigen mening gaat. Er zijn dan ook geen goede of foute antwoorden.

Uw antwoorden zullen uitsluitend gebruikt worden om het materiaal voor de uiteindelijke enquête te optimaliseren.

Het invullen van deze enquête duurt circa 20 minuten. Bij voorbaat hartelijk dank voor uw deelname.

Voor eventuele vragen en/of opmerkingen over deze enquête, kunt u contact met mij opnemen door te mailen naar

Met vriendelijke groet, Nicolette Arkenbout

Volgend tekstblok (start deel 1)

Het materiaal zal gebaseerd zijn op een bepaalde organisatie, namelijk IKEA. Eerst wordt gevraagd naar uw eigen mening over IKEA zelf. U wordt niet blootgesteld aan materiaal, dus u kunt uw mening over IKEA baseren op eigen (online en/of offline) ervaringen. Er zijn geen goede of foute antwoorden.

Geef aan in hoeverre u het eens bent met de volgende stellingen.

55 Master thesis Nicolette Arkenbout 1. IKEA doet moeite om klanten aan zich te binden.

O O O O O O O Volledig Grotendeels Enigszins Niet mee Engiszins Grotendeels Volledig mee oneens mee oneens mee oneens oneens/niet mee eens mee eens mee eens mee eens

2. IKEA doet pogingen om de relatie met te klant te versterken.

O O O O O O O Volledig Grotendeels Enigszins Niet mee Engiszins Grotendeels Volledig mee oneens mee oneens mee oneens oneens/niet mee eens mee eens mee eens mee eens

3. IKEA hecht waarde aan het behouden van klanten.

O O O O O O O Volledig Grotendeels Enigszins Niet mee Engiszins Grotendeels Volledig mee oneens mee oneens mee oneens oneens/niet mee eens mee eens mee eens mee eens

4. Hoe tevreden bent u met de moeite die IKEA doet om de relatie met de klant te verbeteren?

Ontevreden O O O O O O O Tevreden

5. Hoe zou u IKEA‟s pogingen om de relatie met de klant te verbeteren beoordelen?

Slecht O O O O O O O Goed Negatief O O O O O O O Positief

Volgend tekstblok (start deel 2)

56 Master thesis Nicolette Arkenbout Is er een verschil tussen deze twee berichten?

O Ja (als participant “Ja” kiest, wordt participant geleid naar volgend tekstblok) O Nee (als participant “Nee” kiest, wordt participant geleid naar daaropvolgend tekstblok)

Volgend tekstblok

Wat is het verschil tussen de twee berichten?

(Tekstvak om antwoord te noteren)

Volgend tekstblok (start deel 3)

U krijgt nu verschillende versies van online conversaties te zien die op social media platform Facebook zijn gevoerd. Een conversatie houdt in dat een klant een Facebook-bericht op zijn/haar tijdlijn plaatst en dat hij/zij in dit bericht zijn/haar mening over IKEA deelt. IKEA plaatst een reactie onder dit bericht.

In de komende fictieve conversaties zal het Facebook-bericht van de klant hetzelfde blijven, maar de reactie van IKEA zal anders zijn. U wordt gevraagd uw mening te geven over deze reacties.

Volgend tekstblok (non-personalized)

(Afbeelding in Facebook lay-out met het volgende gesprek:)

Marijn Dirksen: Erg tevreden met mijn nieuwe IKEA kast! Hij is groot genoeg voor al m‟n spullen en de kast is alles behalve duur. Eerst keek ik naar die kasten in de exclusievere meubelzaken, maar het is het niet waard om zo ontzettend veel geld aan een simpele kast uit te geven. Dus… Niet twijfelen, gewoon naar IKEA gaan!

IKEA: Hi! Wat is dat leuk om te lezen! Goed om te horen dat je zo blij bent met de nieuwe kast. Vriendelijke groet van het IKEA-team.

Geef aan in hoeverre u het eens bent met de volgende stellingen.

1. IKEA zou deze reactie ook in het echt geplaatst kunnen hebben.

O O O O O O O Volledig Grotendeels Enigszins Niet mee Engiszins Grotendeels Volledig mee oneens mee oneens mee oneens oneens/niet mee eens mee eens mee eens mee eens 57 Master thesis Nicolette Arkenbout 2. De reactie van IKEA is realistisch.

O O O O O O O Volledig Grotendeels Enigszins Niet mee Engiszins Grotendeels Volledig mee oneens mee oneens mee oneens oneens/niet mee eens mee eens mee eens mee eens

3. IKEA maakt een onvriendelijke indruk.

O O O O O O O Volledig Grotendeels Enigszins Niet mee Engiszins Grotendeels Volledig mee oneens mee oneens mee oneens oneens/niet mee eens mee eens mee eens mee eens

4. De reactie van IKEA bevat persoonlijke informatie van de klant.

O O O O O O O Volledig Grotendeels Enigszins Niet mee Engiszins Grotendeels Volledig mee oneens mee oneens mee oneens oneens/niet mee eens mee eens mee eens mee eens

5. IKEA heeft zich verdiept in de klant om persoonlijke informatie te achterhalen.

O O O O O O O Volledig Grotendeels Enigszins Niet mee Engiszins Grotendeels Volledig mee oneens mee oneens mee oneens oneens/niet mee eens mee eens mee eens mee eens

Volgend tekstblok (P1)

(Afbeelding in Facebook lay-out met het volgende gesprek:)

Marijn Dirksen: Erg tevreden met mijn nieuwe IKEA kast! Hij is groot genoeg voor al m‟n spullen en de kast is alles behalve duur. Eerst keek ik naar die kasten in de exclusievere meubelzaken, maar het is het niet waard om zo ontzettend veel geld aan een simpele kast uit te geven. Dus… Niet twijfelen, gewoon naar IKEA gaan!

IKEA: Hi! Wat is dat leuk om te lezen! Goed om te horen dat je zo blij bent met de nieuwe kast. Ook je partner Renee heeft iets leuks op Facebook geplaatst over jullie nieuwe kast. Leuk om te zien dat jullie er zo blij mee zijn! Vriendelijke groet van het IKEA- team.

58 Master thesis Nicolette Arkenbout (Participant geeft aan in hoeverre hij/zij het eens is met de 5 stellingen, zoals bij eerste webcare conversatie)

Volgend tekstblok (P2)

(Afbeelding in Facebook lay-out met het volgende gesprek:)

Marijn Dirksen: Erg tevreden met mijn nieuwe IKEA kast! Hij is groot genoeg voor al m‟n spullen en de kast is alles behalve duur. Eerst keek ik naar die kasten in de exclusievere meubelzaken, maar het is het niet waard om zo ontzettend veel geld aan een simpele kast uit te geven. Dus… Niet twijfelen, gewoon naar IKEA gaan!

IKEA: Hi! Wat is dat leuk om te lezen! Goed om te horen dat je zo blij bent met de nieuwe kast. Zeker met de pasgeboren tweeling kan die extra opbergruimte heel handig zijn. Leuke foto op Facebook! Nog gefeliciteerd! Vriendelijke groet van het IKEA-team.

(Participant geeft aan in hoeverre hij/zij het eens is met de 5 stellingen, zoals bij eerste webcare conversatie)

Volgend tekstblok (P3)

(Afbeelding in Facebook lay-out met het volgende gesprek:)

Marijn Dirksen: Erg tevreden met mijn nieuwe IKEA kast! Hij is groot genoeg voor al m‟n spullen en de kast is alles behalve duur. Eerst keek ik naar die kasten in de exclusievere meubelzaken, maar het is het niet waard om zo ontzettend veel geld aan een simpele kast uit te geven. Dus… Niet twijfelen, gewoon naar IKEA gaan!

IKEA: Hi! Wat is dat leuk om te lezen! Goed om te horen dat je zo blij bent met de nieuwe kast. We bladerden even door je Facebookfoto‟s en we spotten toevallig veel IKEA- spullen. Wat leuk! Vriendelijke groet van het IKEA-team.

(Participant geeft aan in hoeverre hij/zij het eens is met de 5 stellingen, zoals bij eerste webcare conversatie)

Volgend tekstblok

Dit waren de vragen over de fictieve conversaties tussen Marijn en IKEA. De komende fictieve conversaties zullen tussen een andere klant en IKEA plaatsvinden.

59 Master thesis Nicolette Arkenbout In de komende fictieve conversaties zal het Facebook-bericht van de klant wederom hetzelfde blijven. De reactie van IKEA zal wederom anders zijn.

Volgend tekstblok (non-personalized)

(Afbeelding in Facebook lay-out met het volgende gesprek:)

Jamy de Vonk: Die Zweedse balletjes van IKEA zijn zo lekkerrrr! Ik raad ze iedereen aan!

IKEA: Hi! Fijn dat je er zo van geniet! Vriendelijke groet van het IKEA-team.

Geef aan in hoeverre u het eens bent met de volgende stellingen.

(Participant geeft aan in hoeverre hij/zij het eens is met de 5 stellingen, zoals bij eerste webcare conversatie)

Volgend tekstblok (P1)

(Afbeelding in Facebook lay-out met het volgende gesprek:)

Jamy de Vonk: Die Zweedse balletjes van IKEA zijn zo lekkerrrr! Ik raad ze iedereen aan!

IKEA: Hi! Fijn dat je er zo van geniet! We zien via Facebook dat je in Leeuwarden woont. Je kunt ook zakken Zweedse gehaktballetjes aanschaffen om thuis op te bakken en er ook thuis vaker van genieten! Vriendelijke groet van het IKEA-team.

(Participant geeft aan in hoeverre hij/zij het eens is met de 5 stellingen, zoals bij eerste webcare conversatie)

Volgend tekstblok (P2)

(Afbeelding in Facebook lay-out met het volgende gesprek:)

Jamy de Vonk: Die Zweedse balletjes van IKEA zijn zo lekkerrrr! Ik raad ze iedereen aan!

IKEA: Hi! Fijn dat je er zo van geniet! Ook je moeder en zusje zijn zojuist ingecheckt op onze locatie via Facebook. Vinden zij de Zweedse balletjes ook lekker? Vriendelijke groet van het IKEA-team. 60 Master thesis Nicolette Arkenbout (Participant geeft aan in hoeverre hij/zij het eens is met de 5 stellingen, zoals bij eerste webcare conversatie)

Volgend tekstblok (P3)

(Afbeelding in Facebook lay-out met het volgende gesprek:)

Jamy de Vonk: Die Zweedse balletjes van IKEA zijn zo lekkerrrr! Ik raad ze iedereen aan!

IKEA: Hi! Fijn dat je er zo van geniet! We zien via Facebook dat je sinds vorige week dinsdag een relatie hebt met Maxim. Neem je Maxim een keer mee op date om Zweedse balletjes te komen eten? Vriendelijke groet van het IKEA-team.

(Participant geeft aan in hoeverre hij/zij het eens is met de 5 stellingen, zoals bij eerste webcare conversatie)

Volgend tekstblok

Dit waren de stellingen over de online conversaties. Tot slot volgen er nog drie korte vragen.

Volgend tekstblok

1. Wat is uw geslacht?

O Man O Vrouw

2. Wat is uw leeftijd? (Noteer uw leeftijd in jaren)

…

3. Wat is uw huidige of hoogst genoten opleidingsniveau?

O Vmbo O Havo O Vwo O Mbo O Hbo O Wo

61 Master thesis Nicolette Arkenbout Volgend tekstblok

Mocht u nog specifieke opmerkingen hebben over het getoonde materiaal in deze enquête, dan kunt u deze hieronder noteren:

(Tekstvak om antwoord te noteren)

62 Master thesis Nicolette Arkenbout Appendix C – Materials

Condition 1 (1x1) (Conversation 2 and 4):

63 Master thesis Nicolette Arkenbout Condition 2 (1x2) (Conversation 2 and 4):

64 Master thesis Nicolette Arkenbout Condition 3 (1x3) (Conversation 2 and 4):

65 Master thesis Nicolette Arkenbout Condition 4 (2x1) (Conversation 2 and 4):

66 Master thesis Nicolette Arkenbout Condition 5 (2x2) (Conversation 2 and 4):

67 Master thesis Nicolette Arkenbout Condition 6 (2x3) (Conversation 2 and 4):

68 Master thesis Nicolette Arkenbout Appendix D – Reliability of the scales

Table. Reliability of the scales per conversation

Measures Conversation Reliability (Cronbach‟s alpha) CHV 1 α = .86 2 α = .85 Both α = .86 Invasion of privacy 1 α = .87 2 α = .87 Both α = .92 Perceived RI 1 α = .85 2 α = .89 Both α = .86 Evaluation of perceived RI 1 α = .89 2 α = .89 Both α = .91

69 Master thesis Nicolette Arkenbout Appendix E – Experimental Questionnaire

Introductie

Beste deelnemer,

Voor mijn masterscriptie focus ik me op het effect van „webcare‟. Hierbij kunt u denken aan een online conversatie (bijvoorbeeld op social media platform Facebook) tussen een bedrijf en een klant.

Om meer inzicht te krijgen in het effect van webcare, heb ik uw input nodig. Graag wil ik benadrukken dat het om uw eigen mening gaat. Er zijn dan ook geen goede of foute antwoorden.

Uw gegeven antwoorden zullen uitsluitend gebruikt worden voor deze specifieke masterscriptie. Daarnaast zullen uw antwoorden vertrouwelijk behandeld worden en zullen de antwoorden niet naar u als persoon te herleiden zijn. U kunt, indien gewenst, te allen tijde de enquête stoppen. Ook kunt u ervoor kiezen de enquête tijdelijk af te breken en op een later tijdstip de enquête verder invullen.

Het invullen van deze enquête duurt circa 8 minuten. Bij voorbaat hartelijk dank voor uw deelname.

Door op onderstaande blauwe knop te klikken, start u de enquête en neemt u deel aan dit onderzoek.

Voor eventuele vragen en/of opmerkingen over deze enquête, kunt u contact met mij opnemen door te mailen naar [email protected].

Met vriendelijke groet, Nicolette Arkenbout

Volgend tekstblok

In deze enquête krijgt u 4 verschillende online conversaties te zien. Deze conversaties vinden plaats tussen verschillende klanten en het bedrijf IKEA.

Een online conversatie houdt concreet in dat een klant een Facebook bericht op zijn of haar eigen tijdlijn plaatst en IKEA hierin benoemt. IKEA plaatst een reactie onder dit bericht. Na het zien van een dergelijke conversatie, wordt u gevraagd aan te geven in hoeverre u het eens bent met verschillende stellingen. Wanneer u op onderstaande blauwe knop klikt, zal de eerste conversatie te zien zijn.

70 Master thesis Nicolette Arkenbout Volgend tekstblok

Participant wordt geplaatst in één van de zes condities en ziet in totaal vier conversaties. Per conversatie worden verschillende vragen gesteld. Alle vragen, behalve de laatste twee, gaan gepaard met de volgende antwoordmogelijkheden op een 7-punts Likertschaal:

O O O O O O O Volledig Grotendeels Enigszins Neutraal Engiszins Grotendeels Volledig mee oneens mee oneens mee oneens mee eens mee eens mee eens

Geef aan, op basis van deze specifieke conversatie, in hoeverre u het eens bent met de volgende stellingen.

(1 = volledig mee oneens, 7 = volledig mee eens) 1. IKEA staat open voor een gesprek 2. IKEA gebruikt een communicatiestijl die ook in een normaal face-to-face gesprek zou kunnen worden gebruikt. 3. IKEA behandelt de klant op een menselijke manier. 4. IKEA communiceert met een menselijke toon.

(1 = volledig mee oneens, 7 = volledig mee eens) 1. IKEA‟s reactie bevat meer persoonlijke informatie van de klant dan gewenst. 2. De hoeveelheid persoonlijke klantinformatie die IKEA gebruikt, is gepast. (reverse coding) 3. IKEA maakt inbreuk op de persoonlijke levenssfeer door naar deze persoonlijke klantinformatie te zoeken. 4. IKEA‟s zoekgedrag naar deze persoonlijke klantinformatie is onfatsoenlijk.

(1 = volledig mee oneens, 7 = volledig mee eens) 1. IKEA doet moeite om klanten aan zich te binden. 2. IKEA doet pogingen om de relatie met te klant te versterken. 3. IKEA streeft ernaar klanten te behouden.

1. Hoe tevreden bent u met de moeite die IKEA doet om de relatie met de klant te verbeteren?

Ontevreden O O O O O O O Tevreden

2. Hoe zou u IKEA‟s pogingen om de relatie met de klant te verbeteren beoordelen?

Slecht O O O O O O O Goed Positief O O O O O O O Negatief (reverse coding)

71 Master thesis Nicolette Arkenbout Volgend tekstblok

Nu volgen er enkele vragen met betrekking tot uw Facebook gebruik.

1. Hoe vaak gebruikt u Facebook?

O Nooit O Minder dan één keer per maand O Maandelijks O Wekelijks O Dagelijks

2. In hoeverre bent u bekend met het feit dat bedrijven actief kunnen zijn op Facebook?

O O O O O O O Volledig Grotendeels Enigszins Neutraal Engiszins Grotendeels Volledig onbekend onbekend onbekend bekend bekend bekend

3. Heeft u wel eens een conversatie gevoerd met een bedrijf via Facebook?

O Ja O Nee

Volgend tekstblok

Tot slot volgen er 3 korte vragen.

1. Wat is uw geslacht?

O Man O Vrouw

2. Wat is uw leeftijd? (Noteer uw leeftijd in jaren. Voorbeeld: 25)

…

72 Master thesis Nicolette Arkenbout 3. Wat is uw huidige of hoogst genoten opleidingsniveau? (Indien u momenteel studeert, kies uw huidige opleidingsniveau)

O Vmbo O Havo O Vwo O Mbo O Hbo O Wo

Volgend tekstblok

U heeft voor dit onderzoek vragen beantwoord over online conversaties tussen IKEA en bepaalde klanten. Ik wil benadrukken dat de zojuist getoonde online conversaties fictief zijn. De klanten en IKEA hebben deze conversaties dus nooit daadwerkelijk gevoerd. De conversaties zijn gemaakt en gebruikt voor dit specifieke experiment.

Door op onderstaande blauwe knop te klikken, worden al uw antwoorden geregistreerd.

73 Master thesis Nicolette Arkenbout Appendix F – Fillers

Conditions 1, 2, 4 and 5 (Conversation 1 and 3):

74 Master thesis Nicolette Arkenbout Conditions 3 and 6 (Conversation 1 and 3):

75 Master thesis Nicolette Arkenbout Appendix G – Demographic variables

To check whether the demographic variables influenced the dependent variables, several tests were conducted. First, age did not correlated with perceived RI (r = -.03, p = .733) or evaluation of perceived RI (r = .00, p = .996). Also gender did not influence perceived RI,

Mdif = -0.05, t(190) = -0.39, p = .699, or evaluation of perceived RI, Mdif = -0.14, t(190) = -

0.71, p = .476, according to an independent t-test. Next, an one-way ANOVA was performed that showed that education level did not affect perceived RI, F(5, 186) = 0.86, p = .507, or evaluation of perceived RI, F(5, 186) = 0.17, p = .975. In addition, participants‟ familiarity with the fact that companies can be active on Facebook correlated positively with perceived

RI (r = .25, p < .001), but not with evaluation of perceived RI (r = .03, p = .638). Also the

extent to which participants used Facebook slightly correlated with perceived RI (rs = .142, p

= .050), but not with evaluation of perceived RI (rs = .052, p = .473). Lastly, an independent t- test was performed and showed that whether participants had an online conversation with a company before did not influence perceived RI, Mdif = 0.13, t(190) = 1.16, p = .247, or evaluation of perceived RI, Mdif = 0.10, t(190) = 0.55, p = .587.

76 Master thesis Nicolette Arkenbout Appendix H – Normality checks

Table. Z-scores and Kolmogorov-Smirnov tests of combinations of the predictor variables on perceived RI with the values of Skewness; Kurtosis; Kolmogorov-Smirnov (sig.)

No personalization Personalization

No personification -1.68; 0.94; .13 (.200) -1.48; -0.01; .10 (.200)

Personification (low) -3.21; 2.98; .17 (.020) -1.93; 1.34; .12 (.200)

Personification (high) 0.40; 0.90;.14 (.127) 0.36; -0.69; .17 (.027)

Note: Z-scores indicating a non-normal distribution (< -1.96, > 1.96) and significant K-S values are in boldface

Table. Z-scores and Kolmogorov-Smirnov tests of predictor variables on evaluation of perceived RI with the values of Skewness; Kurtosis; Kolmogorov-Smirnov (sig.)

No personalization Personalization

No personification -1.25; 0.02; .13 (.200) 0.69; -0.25; .10 (.200)

Personification (low) -1.88; 0.15; .19 (.005) 1.42; -0.16; .14 (.095)

Personification (high) -1.46; -0.05;.13 (.200) -1.23; 0.90; .12 (.200)

Note: Z-scores indicating a non-normal distribution (< -1.96, > 1.96) and significant K-S values are in boldface

77 Master thesis Nicolette Arkenbout Appendix I – Mediation analyses

Figure 6. Mediation analysis (low level of personification on evaluation of perceived RI)

Figure 7. Mediation analysis (high level of personification on evaluation of perceived RI)

78 Master thesis Nicolette Arkenbout

Figure 8. Mediation analysis (personalization on perceived RI)

Figure 9. Mediation analysis (low level of personification on perceived RI)

79 Master thesis Nicolette Arkenbout

Figure 10. Mediation analysis (high level of personification on perceived RI)

80 Master thesis Nicolette Arkenbout