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Influencer marketing: The effect of distrust issues on

consumer behaviour

by

Florentina Margaretha Dorothea Vasse

Dual Award Master of Science

Advanced International Business Management and Marketing

University of Groningen &

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Master dissertation:

Influencer marketing: The effect of distrust issues on

consumer behaviour

Dual Award Master of Science

Advanced International Business Management and Marketing

Supervisors:

University of Groningen: H.A. Ritsema Newcastle University Business School: A. Javornik

Student number:

University of Groningen: 2219123 Newcastle University Business School: 150688019

Florentina Margaretha Dorothea Vasse Heinsiusstraat 25

9716 AV Groningen, the Netherlands

+31 (0) 615582963

f.m.d.vasse@student.rug.nl F.Vasse2@newcastle.ac.uk

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Abstract

This master dissertation research aims to examine whether consumer behaviour towards a brand changes when consumers are being confronted with distrust issues involving online influencers. Brands started working together with influencers to promote their products and increase brand awareness. While several researchers focused on the identification of trusted influencers, it has not yet been researched what the influential power of an influencer is when there are distrust relationships. The focus of this research is specifically on the effects of distrust issues on consumer behaviour. Consumer behaviour was measured by means of the variables purchase intentions, brand loyalty, brand attitude and retransmission intentions. The influence of distrust issues on consumer behaviour was measured by means of an online questionnaire with a vignette study research design. A hypothetical scenario was shown to participants in the online questionnaire to see whether their behaviour towards the brand changed after reading the scenario. To investigate the differences between the consumer behaviour both before and after being confronted with the hypothetical scenario, paired samples t-tests and one-way repeated measures ANOVA tests were performed. The results show that distrust issues have a negative influence on purchase intentions, brand loyalty, brand attitude and retransmission intentions, and thus on consumer behaviour.

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Acknowledgements

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Table of contents

Abstract ... 3 Acknowledgements ... 4 Table of contents ... 5 List of tables... 7 List of figures ... 7 List of abbreviations ... 8 1. Introduction ... 9 1.1 Introduction ... 9 1.2 Research background ... 9

1.2 Research objectives and research question ... 11

1.3 Theoretical relevance ... 12

1.4 Managerial relevance ... 12

1.5 Dissertation structure ... 13

1.6 Conclusion ... 13

2. Literature review and research hypotheses ... 14

2.1 Introduction ... 14

2.2 Explanation of constructs ... 14

2.2.1 Influencer marketing ... 14

2.2.2 Trust and distrust as different concepts ... 15

2.2.3 Purchase intentions ... 17 2.2.4 Brand equity ... 18 2.2.4.1 Brand loyalty ... 19 2.2.5 Brand attitude ... 20 2.2.6 Retransmission intentions ... 21 2.3 Hypotheses development ... 22

2.3.1 Influence of distrust issues on purchase intentions ... 22

2.3.2 Influence of distrust issues on brand loyalty ... 23

2.3.3 Influence of distrust issues on brand attitude ... 24

2.3.4 Influence of distrust issues on retransmission intentions ... 25

2.4 Conceptual model ... 26

2.5 Conclusion ... 26

3. Methodology ... 27

3.1 Introduction ... 27

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3.3.3 Measurement and item specification ... 29 3.3.4 Survey development ... 34 3.4 Data collection ... 34 3.5 Data analysis ... 34 3.6 Ethical considerations ... 35 3.7 Conclusion ... 35 4. Results ... 36 4.1 Introduction ... 36

4.2 Preliminary data analyses ... 36

4.2.1 Sample characteristics ... 37

4.2.2 Descriptive results ... 38

4.2.3 Reliability analyses ... 40

4.3 Hypotheses testing ... 41

4.3.1 Correlations ... 43

4.3.2 Paired samples t-test and one-way ANOVA with repeated measures ... 44

4.5 Overview of findings ... 46

4.6 Conclusion ... 46

5. Discussion ... 47

5.1 Introduction ... 47

5.2 Distrust and purchase intentions ... 47

5.3 Distrust and brand loyalty ... 47

5.4 Distrust and brand attitude ... 48

5.5 Distrust and retransmission intentions ... 48

5.6 Distrust and consumer behaviour ... 49

5.7 Conclusion ... 49

6. Conclusion ... 50

6.1 Introduction ... 50

6.2 Contribution to literature ... 50

6.3 Managerial implications ... 50

6.4 Research limitations and future research ... 51

6.5 Conclusion ... 52

References ... 53

Appendices ... 66

Appendix A: Survey ... 66

Appendix B: Descriptive results ... 77

Appendix C: Output tables paired samples t-tests ... 81

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List of tables

Table 3.1 Overview of variables………... 30

Table 3.2 Measure and item specification………. 32

Table 4.1 Demographics sample profile………... 38

Table 4.2 Descriptive results sum variables………. 39

Table 4.3 Cronbach’s alpha for all constructs………... 40

Table 4.4 Pearson correlations………. 42

Table 4.5 Results of hypotheses testing………... 46

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List of abbreviations

ANOVA analysis of variance

BA brand attitude

BL brand loyalty

eWOM electronic word-of-mouth

M mean

OSN online social network

PI purchase intentions

RI retransmission intentions

SD standard deviation

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1. Introduction

1.1 Introduction

The fast growth of Internet-based social networking applications (such as Facebook and Instagram) and advanced information technologies (such as smart phones and personal computers) has brought with it a new type of communication which has the ability to connect with consumers in a more natural way – all the more important since consumers become increasingly turned off by pushing forms of advertising. This marketing concept has become known as influencer marketing (Liu et al., 2015; Rogers, 2016). This dissertation research investigates whether distrust issues towards online influencers have an effect on consumer behaviour. Purchase intentions, brand loyalty, brand attitude and retransmission intentions are studied in order to measure consumer behaviour. In this Introduction chapter the research background of this topic is first outlined. Subsequently, the research gap, research objectives and the research question are provided. After that, the theoretical and managerial relevance of this research are presented. Finally, this chapter ends by providing the structure of the remainder of this dissertation.

1.2 Research background

According to Kotler (1991, p. 443) a brand can be defined as “a name, term, sign, symbol, or design, or a combination of them which is intended to identify the goods and services of one seller or group of sellers and to differentiate them from those of competitors”. A brand can be seen as one of the most important competitive advantages for a company. Branding contributes to the success of a service or product sold by a company to a large extent, and this makes it an important activity (Phillips, 2006). By means of branding the goods of one company can be distinguished from those of another company (Keller, 2013). Goodson (2012) argued that brands are more important than ever before. Where products have a limited life, brands continue to exist. And thus, by building strong brands, large value can be created for companies.

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communication methods, marketers have a lot of options in reaching consumers (Newman, 2014; Rossiter and Percy, 2013). This results in companies being not focused on only one form of marketing anymore (Newman, 2014). Instead, companies are marketing their products and services via multiple channels. This is called “omni-channel marketing”.

It is important that marketers offer consumers an overall coherent experience via different devices or channels. There are different ways how consumers can engage with companies, for example a mobile application, social media (e.g. Facebook, Twitter, Instagram and YouTube), an online website or a physical store (Stocker, 2014). By means of social media, blogs, online communities and email people are enabled to interact with each other and share opinions together (Nowak and McGloin, 2014). Mangold and Faulds (2009) argue that social media needs to be seen as a new “hybrid” part of the promotion mix, because it allows the communication between companies and customers, as well as the communication between customers themselves. The traditional communication between consumers changed because of social media. By means of social media customers can have both a negative and a positive influence on the brand building of a firm because they have more power than before to contribute to the promotion and building of a brand (Zailskaite-Jakste and Kuvykaite, 2013).

Another trend is that brands also started working together with celebrities, bloggers and other influencers to increase brand awareness and promote their products. Influencer marketing seems to be a new concept that originated in the current social media and Internet era. However, it is mainly a form of word-of-mouth marketing and is therefore not a completely new phenomenon, like many people think. It is because of social media and Internet that a larger audience can be reached and it gets more attention because of this (Weiss, 2014). The advantage of influencer marketing is that many potential customers can be reached at a relatively low cost by means of only one influencer. An influencer can motivate its followers to try the products it is promoting (Waller, 2016).

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of peers play a big role in the decisions to purchase something nowadays. Much sales is generated by the earlier mentioned word-of-mouth marketing and it is considered as having a larger influence on consumers than any regular commercial (Harridge-March and Quinton, 2009; Weiss, 2014). Therefore, the importance of the influencer marketing concept is increasing and it plays an increasingly important role in business.

1.2 Research objectives and research question

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The following main research question can be formulated in order to be able to find answers to the above stated research objective:

What are the effects of distrust issues in influencer marketing on consumer behaviour in general, and on purchase intentions, brand loyalty, brand attitude and retransmission intentions in particular?

1.3 Theoretical relevance

Recently, challenges to the assumption that distrust and trust are two sides of the same coin have emerged. Several scholars have suggested in their studies that distrust and trust are two different constructs that differ from each other qualitatively (Lewicki, McAllister and Bies, 1998). Therefore, studies have started to investigate whether distrust and trust have different antecedents and how distrust can be diminished (McKnight, Kacmar and Choudhury, 2004). Nevertheless, not much research has focused on the possible consequences on consumer behaviour when distrust issues arise. The majority of researches on influencer marketing have focused on trust, and this research can enhance the understanding of consumer behaviour by focussing on the role that distrust plays in the effectiveness of influencer marketing. By incorporating distrust issues, the scope of the current influencer marketing literature will be expanded.

1.4 Managerial relevance

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possible when marketing products, and also be aware of possible counter effective results, for example reductions in purchase intentions, and how these can be dealt with or reduced.

1.5 Dissertation structure

In the remainder of this dissertation the structure will be as follows. In the second chapter

Literature review and research hypotheses, a review and analysis of the literature that is

relevant for this subject will be provided and afterwards hypotheses are formed based upon this literature. In the Methodology chapter, it is described what the methodology and design of the research will be and how the data will be collected. The outcomes and results of the research will be given in the Findings chapter. A discussion of the results and outcomes and an answer on the research question will be provided in the Discussion. Finally, in the Conclusion theoretical and managerial contributions will be given as well as limitations and directions for future research.

1.6 Conclusion

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2. Literature review and research hypotheses

2.1 Introduction

This part of the research exhibits the literature that is of relevance for this research. First, in

chapter 2.2 definitions and explanations of the concepts that are investigated in this research

will be discussed in order to have a good understanding of them. To begin with, influencer marketing is defined, after which the difference between the concepts of trust and distrust is being discussed. Subsequently, the variables that are used to measure consumer behaviour in this research are discussed, which are purchase intentions, brand loyalty, brand attitude and retransmission intentions. Thereafter, in chapter 2.3 a critical review of the ongoing research in this area is provided and hypotheses of the expected relations between the variables are developed. Subsequently, the concepts and the relationships between them make up the conceptual model presented in chapter 2.4 at the end of this chapter.

2.2 Explanation of constructs 2.2.1 Influencer marketing

In the current era of the Internet, many online social networks (OSNs) are created, where customers can communicate with each other and where they can find other persons with whom they share the same interests (Jiang et al., 2016). There are people in OSNs that have a high status online, and other consumers in these OSNs are searching for information from these people that is useful for them. These people that have a high online status can be called online influencers (Liu et al., 2015).

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opinion leaders have been defined by other researchers, namely as “novel information contributors who have the ability to affect the behaviour and attitudes of others”. While there are many celebrities that are influencers, it is important to note that anyone can become an influencer because the concept of word-of-mouth marketing is very popular (Weiss, 2014).

With the development of the Internet and social media channels, consumer influencers are getting a lot of power in the market, and they have a large influence on the brand and company perceptions due to this (Booth and Matic, 2011). Since influencers in OSNs communicate with other consumers, it is a valuable way of electronic word-of-mouth marketing for corporations. The reason for this is that consumers see information from peers as more credible and trustworthy than information that comes from advertisers and marketers from within the company itself (Liu et al., 2015). It is therefore of major importance for companies to identify the right influencers in order to increase the efficiency of marketing on social networks. The reason for this is that social networks, empowered and innovated by Internet-based social networking applications (such as Facebook and Twitter) and advanced information technologies (such as smart phones and personal computers), are the most important marketing channel for companies nowadays (Li et al., 2010).

2.2.2 Trust and distrust as different concepts

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Despite the recent attention to trust, there has been done little research on distrust as a distinct concept. This is partly because researchers conceptualized distrust as being at the lower end of the construct of trust for a long time (Mayer, Davis and Schoorman, 1995; Rotter, 1980). Recently however, researchers have rejected such conceptualisations and identified distrust as a construct that is related to trust, but qualitatively different from trust (Lewicki et al., 1998). Hardin (2004) argues that low trust does not necessarily mean that there is distrust. Therefore, distrust (which is also termed mistrust) can be seen as a concept in itself that is very distinct from and emerges from different beliefs and attitudes than trust (Lewicki et al., 1998; Sitkin and Roth, 1993). It is also argued that there are different determinants and characteristics for trust and distrust (Lewicki et al., 1998).

Distrust can be defined as “an actual expectation that another actor cannot be relied upon, and will engage in harmful behaviour” (Van de Walle and Six, 2014, p. 162). Similarly, a widely used definition of distrust is “a lack of confidence in the other, a concern that the other may act so as to harm one, that he does not care about one’s welfare or intends to act harmfully, or is hostile” (Govier, 1994, p. 240). According to Lewicki et al. (1998, p. 439) distrust includes “confident negative expectations regarding another’s conduct”. Distrust can be seen as the unwillingness of actors to be vulnerable, and it arises when the expectation of harm increases the vulnerability perceived to a point where persons are unwilling to accept it (Bijlsma-Frankema, Sitkin and Weibel, 2015). Specifically, distrust is a belief that a partner will exhibit irresponsible behaviour, will be incompetent, will not care about one’s welfare, violate obligations or even intend to act harmfully (Lewicki et al., 1998; Sitkin and Roth, 1993). When a distruster expects that the other party either cannot or will not perform the desired behaviour and is unwilling to cope with such outcomes, but might rather act in a negative manner toward the distruster, distrust is exhibited (McKnight and Chervany, 2001). Instead of being the absence of trust, distrust is the active expectation that another party will behave in a way that violates one’s security and welfare. High distrust is comprised of suspicion, fear, or cynicism. Therefore, distrust needs to be seen as distinct from trust.

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(Bijlsma-towards distrusted others (Chambers and Melnyk, 2006), avoidance of influence (Sheppard and Tuchinsky, 1996), lack of cooperation (Cho, 2006), and information distortion and disbelief (Kramer, 1994). Since researchers have started to investigate the causal dynamics and core constructs of distrust, this study will build on this new view towards distrust and focuses on the consequences of distrust relationships in influencer marketing next to the already existing literature about trust in influencer marketing.

2.2.3 Purchase intentions

According to Fishbein and Ajzen (2010), the best way to predict human behaviour is from the perspective of a person’s intentions. An intention can be seen as the decision to act in a certain way in the future (Ramayah, Lee and Mohamad, 2010). Furthermore, intentions represent motivational factors which in turn influence behaviour. Similarly, Howard and Seth (1969) argue that consumer behaviour towards a firm or brand partly consists of purchase intentions. When a person has the intention to perform a specific behaviour, the probability that this behaviour occurs is greater (Fishbein and Ajzen, 2010).

Based on the above assumption, purchase intentions can direct or predict future purchase performed by the customer (Ramayah et al., 2010). Purchase intentions can be defined as the likelihood that a customer will buy a certain product/service (Dodds, Monroe and Grewal, 1991). More specifically, purchase intentions in word-of-mouth communication can be defined as “the WOM recipient’s degree of motivation and willingness to eventually purchase the brand discussed in the WOM episode” (Baker, Donthu and Kumar, 2016, p. 226). Purchase intention can be seen as a good predictor for a consumer’s actual buying behaviour, and therefore it is important to understand the intentions of consumers to purchase (Bai, Law and Wen, 2008). Since consumers possibly make purchases not based on real preferences but on constraints, it can be more effective to use intentional measures rather than behavioural measures in understanding the mind of consumers (Day, 1969).

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are specific to a product class. Several brands that have the possibility to satisfy the buyer’s motives are the alternatives. Decision mediators are rules that the buyer uses and by which motives and alternatives are matched. Decision mediators are developed in the process where the buyer is learning about the buying situation and is influenced by the experience of purchase and consumption of the brand as well as by information that comes from the buyer’s environment (Howard and Seth, 1969).

2.2.4 Brand equity

Brand equity is a marketing outcome that is very important for marketers (Christodoulides and De Chernatony, 2010). Because of its importance it has extensively been researched in the marketing literature (e.g. Aaker, 1991; Bharadwaj, Varadarajan and Fahy, 1993; Christodoulides and De Chernatony, 2010; Keller, 2013; Taylor, Celuch and Goodwin, 2004). Brand equity building can therefore be seen as a key activity and marketing asset for companies (Christodoulides and De Chernatony, 2010). The definitions and conceptualizations of brand equity that are most often used are the ones of Aaker (1991) and Keller (1993). Aaker (1991, p. 15) defined brand equity as “the set of brand assets and liabilities linked to the brand – its name and symbols – that add value to, or subtract value from, a product or service. These assets include brand loyalty, name awareness, perceived quality and associations”. Keller (1993, p. 8) views brand equity as “the differential effect that brand knowledge has on consumer response to the marketing of that brand”. This definition views brand equity from the perspective of the individual consumer. By defining brand equity from this perspective, managers are enabled to examine how the brand value is improved by their marketing programs. Keller (1993) specified the concept of brand equity into several components, which are brand resonance, brand imagery, brand performance, brand salience, consumer feelings and consumer judgements.

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2.2.4.1 Brand loyalty

The focus in this research will be on one specific aspect of brand equity, namely brand loyalty. Brand loyalty is seen as a behavioural outcome of brand equity (Christodoulides and De Chernatony, 2010). Like brand equity, brand loyalty received much attention in the marketing research literature. According to Watson et al. (2015), obtaining loyalty among customers can be seen as a major goal of marketing. The relationship marketing theory shows that it is more profitable for a firm to develop and maintain long-lasting and close relationships with customers instead of focusing on short-term, discrete transactions (Kumar, Bohling and Ladda, 2003). Customers in long-lasting relationships are willing to pay more for the services and/or goods, they purchase more and become attached to the firm in an emotional sense. Furthermore, brand loyalty has a positive influence on the financial outcomes of a firm, an example of this is an increase in profitability (Bowen and Chen, 2001; Morgan and Rego, 2006). Reichheld and Sasser (1990) found for example that the profits of a company increase by 25 per cent to 125 per cent when it retains five per cent more of its customers and that loyal customers have a more positive attitude towards the brand than non-loyal customers. In addition, Lawrence (2012) argues that it’s easier to sell to existing customers instead of new customers. Besides this, Gallo (2014) mentions in his research that retaining a customer is five to 25 times less expensive than the acquisition of a new customer. Since brand loyalty is so valuable, loyalty can be seen as highly important for companies to focus on. However, it is challenging for companies to build customer loyalty and reap the benefits of it.

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services of a particular brand, and word-of-mouth recommendation for a specific brand. Behavioural loyalty can be defined as the intention of consumers to purchase products or services of a brand repeatedly over time (Bijmolt, Dorotic and Verhoef, 2011; Chaudhuri and Holbrook, 2001). Attitudinal loyalty contributes to the ability of companies to ask higher prices, whereas behavioural loyalty is important if the objective of the company is to increase profits or market share (Chaudhuri and Holbrook, 2001). Bloemer and Kasper (1995, p. 312) suggest that one should “explicitly take into account the degree of a consumer’s commitment to a brand when he/she repurchases a brand”. True loyalty means not just repurchase due to inertia but also commitment and a favourable attitude towards a brand. Therefore, both attitudinal and behavioural loyalty will be considered in this study in order to measure customer loyalty towards the brand.

2.2.5 Brand attitude

Brand attitude is a combination of what people learn and know about a brand and the feelings they associate with a brand (Percy and Elliott, 2012). It is important that consumers have a favourable attitude towards a brand, in order for purchases to occur. Therefore, creating and sustaining a positive attitude towards a brand can be seen as an important marketing goal. Brand attitude can be defined as “the buyer’s overall evaluation of a brand with respect to its perceived ability to meet a currently relevant motivation” (Rossiter and Percy, 1992, p. 266). Similarly, Spears and Singh (2004, p. 55) define attitude towards a brand as “a relatively enduring, unidimensional summary evaluation of the brand that presumably energizes behaviour”. Brand attitude can be seen as a phenomenon that is relatively stable, contrary to brand feelings, which is something that is more transitory. Therefore, attitudes can be seen as a useful predictor of consumers’ behaviour towards a service or product. Brand attitudes show the extent of unlikeability or likeability of a brand and whether consumers have an unfavourable or favourable view towards the brand (De Pelsmacker, Geuens and Van den Bergh, 2007). Brand attitudes can change over time, although they are relatively stable. In fact, changing brand attitudes or reinforcing them toward a company’s favourable direction is one of the most important marketing communication activities (De Pelsmacker et al., 2007).

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motivation of the buyer changes. Second, brand attitude consists of an affective as well as cognitive component. The affective component energizes the behaviour whereas the cognitive component guides behaviour. Thirdly, the cognitive component consists of a set of specific benefit beliefs that are the reasons for a specific brand attitude. Finally, brand attitude is a construct that is relative. Consumers are looking for the brand that meets their underlying motivations better than other alternative brands in almost every product category (Percy and Rossiter, 1992). Despite the difficulty of the construct, brand attitude is critical for the understanding of effective marketing strategies.

2.2.6 Retransmission intentions

When influencers successfully pitch stories, this can generate conversations among the word-of-mouth receivers (Weiss, 2014). In turn, the receivers can diffuse the information they received from the influencers when they have the desire to retransmit the information. Retransmission intentions among receivers of word-of-mouth are largely important, since users must be inclined to actively retransmit content, in order for content to spread (Luarn and Chiu, 2016). Like purchase intentions, WOM retransmission intentions deal with the future behavioural actions of consumers towards a brand. Retransmission intentions can be defined as “the WOM recipient’s degree of motivation and willingness to eventually pass along the content of the WOM communication about the brand to another person” (Baker et al., 2016, p. 226). Similarly, WOM is defined by Harrison-Walker (2001, p. 63) as “informal, person-to-person communication between a perceived non-commercial communicator and a receiver regarding a brand, a product, an organization, or a service”. The underlying idea of WOM is that information about services, products, companies, stores, and so on can spread from one individual to another. This transfer of information from an individual to another can happen either via some communication medium or in person (Brown et al., 2005). Like already mentioned, the focus in this research is the transfer of information via online communication media, like social networks. Furthermore, WOM can both be negative and positive. Since marketers’ interest naturally lies in promoting positive WOM (Brown et al., 2005), such as recommendations to others, that will be the focus of this research.

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very powerful for companies since the purchase-decision making processes of consumers tend to be highly influenced by others opinions. Until recently, there have been several researches that focused on predictors of the intention of consumers to pass along information in an online setting (Kim et al., 2016). There has however been done little research on examining how the attitudes of consumers towards social media messages influence their participation intentions in eWOM communication, and in particular their intentions to recommend the brand to others.

2.3 Hypotheses development

2.3.1 Influence of distrust issues on purchase intentions

Lewicki et al. (1998) highlight the importance of knowing the negative expectation (distrust) intrinsic to commercial interactions or relationships, next to knowing the positive expectation (trust). Companies should not only try to encourage customer’s trust, but should also minimize and manage the impact of distrust (Riquelme and Román, 2014). Distrust seems to play a more critical role than trust in for example transactions, since the negative experience or information tends to predominate over the positive experience or information in the decision-making process of the customer (Singh and Sirdeshmukh, 2000; Ou and Sia, 2010). Distrust leads to pervasive negative expectations and perceptions (Cho, 2006; Lewicki et al., 1998). The relations between negative perceptions and negative behaviours are two-fold: negative behaviours are justified by and a result from negative expectations and perceptions. Perceived risk in a relationship is increased by distrust, which will in the end lead to smaller commitment to the relationship (Chang and Fang, 2013).

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2.3.2 Influence of distrust issues on brand loyalty

Morgan and Hunt (1994) regard trust as the key factor of any relationship. It is likely that a person will develop some form of behavioural intention towards the other party if he/she trusts another party (Lau and Lee, 1999). Brand loyalty can be seen as an important outcome of trust in a brand, either as an actual pattern of purchase behaviour or as a behavioural intention towards the brand, or both. According to Chaudhuri and Holbrook (2001) brand trust has among other factors a strong impact on both behavioural and attitudinal loyalty. The reason that brand trust leads to higher levels of loyalty is that trust creates highly valued exchange relationships (Morgan and Hunt, 1994). When consumers have a more positive mood and affect towards a brand, brand loyalty should be higher. When brands make consumers “affectionate”, “joyful” or “happy” this elicits more attitudinal and behavioural loyalty, and thus together brand loyalty. All in all, one could conclude that in the case of trust, a consumer has positive expectations of the behaviour or the intentions of another. Therefore, trusted influencers can potentially lead consumers to accept recommendations, make purchase decisions, and select transaction partners in e-commerce (Zhang and Yu, 2012).

Contrary, in the case of distrust, it involves negative expectations and perceptions of the other (Cho, 2006; Kramer, 1994). These negative attributions towards others will have an influence on distrust. Whereas high trust is characterised by faith, hope, or assurance, high distrust is comprised of cynicism, fear, or suspicion. When brand loyalty is evoked by happy, joyful, or affectionate consumers, one could assume that the negative feelings associated with high distrust will have a negative effect on the loyalty of consumers towards a brand. Thus, when a consumer experiences high distrust towards an online influencer, it could be expected that this has a negative influence on customer brand loyalty. This leads to the second hypothesis:

Hypothesis 2: The higher the distrust that a consumer experiences towards an online

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2.3.3 Influence of distrust issues on brand attitude

Despite the fact that brand attitudes are relatively stable, they can change over time. In fact, changing or reinforcing brand attitudes towards a beneficial direction to the company’s brand is one of the most important marketing communication activities objectives (De Pelsmacker et

al., 2007). According to previous literature, social media has a significant effect on attitudes of

customers towards brands. Communications of users, which are in this case users with a high online status called influencers, can influence the attitudes of consumers towards a particular brand (Abzari, Ghassemi and Vosta, 2014). One of the factors that is seen as a strong predictor of favourable brand-related outcomes like brand attitude, is trust. Therefore, trust in an influencer is important, since consumers tend to purchase and like products from trustworthy persons. Trust is considered to be the perceived reliability of the target of trust (Morgan and Hunt, 1994). When people trust others they have the expectation that an exchange partner represents honesty, reliability, and integrity (Morgan and Hunt, 1994). In the relationship literature the role of trust has been investigated, and it has been concluded that it is strongly predicting favourable brand-related outcomes (Garbarino and Johnson, 1999; Macintosh and Lockshin, 1997). In this stream of research, it has been noted that when trust is established, this can improve one’s attitude towards a brand.

Contrary, in the case of distrust one could expect that this will deteriorate the attitude of consumers towards a brand. According to Teng, Laroche and Zhu (2007), both positive or negative affective reactions to marketing activities are transferred to the brand by customers. Negative thoughts about marketing activities lead to less favourable brand attitudes. All in all, it can be concluded that negative associations influence brand attitude negatively. In the case of distrust in an online influencer, negative feelings like fear, cynicism, or suspicion are associated with the influencer and in turn, transferred to a less favourable brand attitude. Therefore, it can be hypothesised that:

Hypothesis 3: The higher the distrust that a consumer experiences towards an online

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2.3.4 Influence of distrust issues on retransmission intentions

Several studies have researched the reasons why consumers engage in eWOM behaviour. According to previous research, the intention of a consumer to pass along information in an online setting is significantly predicted by community- and brand-related variables. One of the variables that is an antecedent of eWOM behaviour in social networking sites is trust (Chu and Kim, 2011). Similarly, regarding WOM retransmission intentions, both the “strength of strong ties” perspective and the self-enhancement perspective suggest that WOM will be more frequently retransmitted when it comes from strong ties. This is because consumers associated relatively less risk with retransmitting the informational content that they received from a well-known source, since strong social ties are seen as more reliable, relevant, credible, and trustworthy (Baker et al., 2016).

In contrast, when there is distrust in an online influencer, consumers may associate relatively more risk with retransmitting the informational content that they received from this influencer. Due to feelings of distrust towards the online influencer there will be weak ties between the influencer and the consumers. Therefore, the intention of a consumer to pass along information in an online setting is assumed to be relatively low when there is distrust present compared to when trust is present. Therefore, the fourth and final hypothesis can be formulated as follows:

Hypothesis 4: The higher the distrust that a consumer experiences towards an online

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2.4 Conceptual model

The concepts and relationships between the concepts discussed in this chapter can be summarised into the following conceptual model:

Figure 2.1 Conceptual model

2.5 Conclusion

A review of the literature is provided in the second chapter. Based on this literature review, hypotheses are developed and a conceptual model is provided.

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3. Methodology

3.1 Introduction

In the following chapter, the appropriate research design to test the hypotheses and ultimately find answers to the research question will be developed. First, the research paradigm will be defined. Thereafter, a clarification of the research design is provided wherein it will be explained how the data for this study will be collected. At the end of the chapter, the ethical considerations that need to be considered will be outlined.

3.2 Research paradigm

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3.3 Research Design

In this research, it will be investigated whether distrust issues in influencer marketing have an effect on consumer behaviour related variables. This dissertation uses a vignette study research design, within a quantitative paradigm. The vignette technique is a research method that can elicit attitudes, opinions, beliefs and perceptions from comments or responses to stories depicting situations and scenarios. A vignette (within a quantitative paradigm) can be described as “short stories about hypothetical characters in specified circumstances, to whose situation the interviewee is invited to respond” (Finch, 1987, p. 105).

3.3.1 Survey structure

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intentions, brand attitude, brand loyalty and retransmission intentions towards the brand (Nike) again. By doing so, their purchase intentions, brand attitude, brand loyalty, and retransmission intentions towards the brand Nike after reading the story could be measured in order to see whether the effect measurement differs from the baseline measurement. At the end of the questionnaire, several general questions about sociodemographic factors were asked to participants in order to gain more information about the investigated sample. The complete questionnaire is included in Appendix A.

3.3.2 Brand selection

In the hypothetical scenario described in this questionnaire, a real brand was used and linked to the hypothetical characters in order to be able to measure all variables included in this research. The hypothetical scenario described in the questionnaire was based on a real story that recently took place in the Netherlands. The brand selected to be linked to the hypothetical characters in the scenario in the questionnaire is the sports brand Nike. Nike is the world’s largest and most valuable sports brand. The value of the brand Nike has increased from $7.5 billion to $26 billion since the year 2007 (Ozanian, 2015), and is therefore a growing sports brand. This year (2016), Nike employs approximately 70 thousand employees worldwide (CNN Money, 2016). Nike operates in the Americas, Europe, the Middle East, Asia and Africa. The main competitors of Nike are Adidas-Reebok, Puma and Fila (Mahdi et al., 2015). Furthermore, Nike also needs to be aware of new competitors in the sports brands market, such as Under Armour. Although Nike is currently the global market leader, it faces increasing competition from other sports brands both in Europe and China (Forbes, 2014). Overall, the athletic apparel, footwear, and equipment industry is highly competitive worldwide. The brand Nike is chosen to be used in the questionnaire for this dissertation because it is not only a popular brand among consumers, but also because it makes a lot of use of social media for customer retention (Huang et al., 2014).

3.3.3 Measurement and item specification

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Table 3.1 Overview of variables

Type of variable Variable

Independent Distrust

Dependent Purchase Intentions (PI)

Dependent Brand Loyalty (BL)

Dependent Brand Attitude (BA)

Dependent Retransmission Intentions (RI)

In order to be able to measure the perceptions and beliefs of respondents towards the brand and their attitudes towards the bloggers described in the situational scenario, scale questions were used in the online questionnaire. Scale questions are often used by researchers in order to measure beliefs, attitudes and perceptions of participants (Saunders, Lewis and Thornhill, 2012). One of the scale questions was measured by a five-point Likert scale, ranging from

strongly disagree = 1 to strongly agree = 5. The rest of the scale questions was measured by a

seven-point Likert scale of which some of the items were ranging from very unlikely = 1 to

very likely = 7 and most items were ranging from strongly disagree = 1 to strongly agree = 7.

Because of the use of odd scales in all scale questions, participants had the option to respond with neutral or neither agree nor disagree to a statement (Malhotra and Birks, 2007). For the questions regarding brand attitude of the participants towards the brand a seven-point semantic differential format was used. All measurement instruments of this research were based on measurement instruments used in the existing literature. The reason that existing measurement instruments are used in this dissertation is because they are already tested and used in other studies, and are therefore seen as valid and reliable. Below it will be explained which measurement instruments were used for the different items and variables in this dissertation.

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The dependent variables in this dissertation are purchase intentions, brand loyalty, brand attitude and retransmission intentions. A six-item measurement instrument was used for measuring the variable purchase intentions. Purchase intentions were measured with three items of the research of Grewal et al. (1998), whereas the other three items were taken from the research of Abzari et al. (2014). Two of the items of Grewal et al. (1998), and all three items of Abzari et al. (2014) were measured based on the rating of participants on a seven-point Likert scale ranging from strongly disagree = 1 to strongly agree = 7. One of the items taken from Grewal et al. (1998) was measured on a seven-point Likert scale ranging from very unlikely = 1 to very likely = 7.

Subsequently, the seven-items measurement scales used for brand loyalty were based on the measurement items that were used in the researches of Spry, Pappu and Cornwell (2011) and Chaudhuri and Holbrook (2001). Three of the items came from the research of Spry et al. (2011), whereas the other four items came from the research of Chaudhuri and Holbrook (2001). All seven items were measured based on the participants rating on a seven-point Likert scale ranging from strongly disagree = 1 to strongly agree = 7.

In the same way, the five measurement scale items for brand attitude are taken from Spears and Singh (2004). Participants were asked about their overall feelings about the brand both before and after reading the hypothetical scenario. The participants had to indicate whether their overall feelings towards the brand were unappealing/appealing, bad/good, unpleasant/pleasant, unfavourable/favourable and unlikable/likable. In these measurement scales a seven-point semantic differential format was used. The items measure an “individual’s internal evaluation of the brand” and are generalizable to a wide range of services and products.

Finally, the two-items measurement scale for retransmission intentions are taken from Brown

et al. (2005). Both items were measured using a seven-point Likert scale ranging from very unlikely = 1 to very likely = 7.

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Table 3.2 Measure and item specification

Constructs Items

Distrust

Cho (2006) - This (person) will exploit customers’ vulnerability given the chance

- This (person) will engage in damaging and harmful behaviour to customers to pursue its own interest

- The way this (person) operates its business will be irresponsible and unreliable

- This (person) will perform its business with customers in a deceptive and fraudulent way

Purchase Intentions

Grewal et al. (1998) - I would purchase products from this (brand)

- I would consider buying products from this (brand)

- The probability that I would consider buying products from this (brand) is Abzari et al. (2014) - I would buy this (product/brand) rather than any other brands available

- I am willing to recommend others to buy this (product/brand) - I intend to purchase this (product/brand) in the future

Brand Loyalty

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- I would not buy another brand of (product category) if (brand) was available at the store

Chaudhuri and Holbrook (2001) - I will buy this (brand) the next time I buy (product category) - I intend to keep purchasing this (brand)

- I am committed to this (brand)

- I would be willing to pay a higher price for this (brand) over other brands Brand Attitude

Spears and Singh (2004) - Unappealing/Appealing

- Bad/Good

- Unpleasant/Pleasant - Unfavourable/Favourable - Unlikable/Likable

Retransmission Intentions

Brown et al. (2005) - If a friend were shopping for (product category), how likely is it that you would recommend (brand)

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3.3.4 Survey development

After developing the questionnaire by including the measurement scales for all variables and making the scenario, a group of N = 7 persons was asked to pre-test the questionnaire. These participants were asked whether they thought the questionnaire could be improved and if so, on which points. They were asked whether all measurement scale items and the hypothetical scenario in the questionnaire were understandable. Furthermore, it has been asked to the participants whether the explanations and instructions given in the survey were clear and understandable. Based on the comments and feedback from the persons that participated in the pre-test, the survey was slightly adapted, for example some of the measurement scale items statements were rephrased. Like already mentioned, the final version of the survey can be found in Appendix A.

3.4 Data collection

In this dissertation a non-probability sampling strategy will be used. Self-selection and snowball sampling techniques were used for the sample included in this research (Stevens, 2012). By means of social media and email, people from the researcher’s personal network were invited to take part in the research. Several of the participants out of the personal network of the researcher spread the questionnaire among their personal networks, and by doing so a larger sample group could be build up. The survey was distributed online by means of the online survey tool Qualtrics. One of the advantages of an online survey is that data can be collected very fast and in an efficient way (Birnkrant and Callahan, 2002). The result of the data collection was a raw data set of N = 198 participants.

3.5 Data analysis

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3.6 Ethical considerations

As already mentioned, for this research the data will be collected by means of an online survey. Distributing an online questionnaire involves some possible ethical issues that need to be considered and taken into account when distributing the questionnaire, in order to make sure that this dissertation does not conflict with any ethical standards. Nowadays, Internet research protocols that involve Web or online surveys are the most often reviewed types (94% of respondents). Therefore, this methodology for academic research has a growing prevalence (Buchanan and Hvizdak, 2009). Respondents indicated that the online and electronic nature of these survey data challenges traditional research ethics principles such as risk, consent, anonymity, privacy, autonomy, and confidentiality, and adds new methodological complexities surrounding survey design, sampling, security and data storage (Buchanan and Hvizdak, 2009). In order to make sure that this research would not conflict with any ethical standards, at the beginning of the online questionnaire participants were informed about the content and nature of the research. Participants of the survey were made aware that participating in the questionnaire and research is voluntary and that they may decide to withdraw at all times from the research. Furthermore, it is stated on the first page that the answers will be dealt with in a confidential and anonymous way. By continuing to the next page, participants agreed with these terms and conditions, and by doing so they gave their informed consent. In addition to this, the email-address of the researcher was provided both at the beginning as well as the end of the questionnaire. Participants were able to contact the researcher via the provided email-address when there were any remarks or questions regarding the research.

3.7 Conclusion

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4. Results

4.1 Introduction

The appropriate research design that was outlined in the previous chapter Methodology will be used in this chapter Results to analyse the data and test the hypotheses. Before analysing the collected data, the data set will first be screened and responses that are incomplete will be deleted. Thereafter, descriptive statistics of the research sample are provided. Subsequently, the reliability of the constructs will be analysed and the hypotheses will be tested.

4.2 Preliminary data analyses

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4.2.1 Sample characteristics

Like already mentioned, the final valid analytic data set used for this research is comprised of

N = 145 respondents. In the online questionnaire, there were several general questions about

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Table 4.1 Demographics sample profile

Demographic variables Complete sample

N % Sample 145 100 Gender Male Female 68 77 46.9 53.1

Age 25 years or less

26 to 35 years 36 to 45 years 46 to 65 years 65 years or older 99 24 15 7 0 68.3 16.6 10.3 4.8 0 Country of origin Australia

Austria Belgium Bulgaria Denmark Finland France Germany Indonesia Italy Mexico Netherlands United Kingdom 2 1 7 1 1 1 1 8 2 1 1 115 4 1.4 0.7 4.8 0.7 0.7 0.7 0.7 5.5 1.4 0.7 0.7 79.3 2.8 Highest obtained degree Primary school

High school Vocational school University 0 17 27 101 0 11.7 18.6 69.7 4.2.2 Descriptive results

The descriptive results of the measurement scale items presented in Table 3.2 are shown in

Appendix B. The mean (M), standard deviation (SD), Skewness and Kurtosis are given for all

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the five-point Likert scale item the mean (M) ranges from 3.21 to 3.53, whereas the lowest and highest standard deviation (SD) are .98 and 1.04 respectively. Skewness and Kurtosis are measures that are used to examine whether data is normally distributed. Skewness is a tool that measures the symmetry of the distribution, whereas Kurtosis is a tool that measures whether the data are flat or peaked relative to a normal distribution. When the values for Skewness and Kurtosis are between ± 2 they are considered acceptable in order to be interpreted as normally distributed (Field, 2009; Gravetter and Wallnau, 2014). Most of the measurement items in this research have values between ± 2 and are therefore normally distributed, as can be seen in

Appendix B. However, for some of the measurement items the value for Kurtosis lies outside

the acceptable range. This is the case for PI1 and PI2 in the baseline measurement, as well as for BA1, BA2, BA3 and BA5 in the baseline measurement. The Kurtosis values for PI1 and PI2 are 2.61 and 3.56 respectively. For BA1, BA2, BA3 and BA5 the Kurtosis values are 2.56, 4.01, 2.43 and 2.47. Since these values of Kurtosis are not exceptionally higher than the acceptable range of ± 2, no problems are expected with the analyses that are used for hypotheses testing. In Table 4.2 the mean (M), standard deviation (SD), Skewness and Kurtosis are given for the combined items of the variables included in this research. In the table the baseline measurement of the items is designated by means of the word “pre” placed before the item (e.g. pre-purchase intentions), whereas the effect measurement is designated by means of the word “post” (e.g. post-purchase intentions).

Table 4.2 Descriptive results sum variables

Item Mean SD Skewness Kurtosis

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4.2.3 Reliability analyses

One of the most widely used measures of internal consistency reliability is the Cronbach’s alpha reliability (Bonett and Wright, 2015). The Cronbach’s alpha measures the reliability of the internal consistency when multiple questionnaire items are represented by measurements. Therefore, Cronbach’s alpha reliability tests were conducted to find out whether the items for each construct show internal consistency. The coefficients of the Cronbach’s alpha should be above the value of .7 for each scale (DeVellis, 2003). If this is the case, there are no problems concerning the internal consistency of the measures. The Cronbach’s alpha coefficients are the results of the reliability tests and can be found in Table 4.3. For all constructs the Cronbach’s alpha coefficients are above the threshold value of .7. Therefore, it can be concluded that the internal consistency of the items is relatively high and there are no problems with regards to further analysis.

Table 4.3 Cronbach’s alpha for all constructs

Construct Number of items Cronbach’s alpha

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4.3 Hypotheses testing

This research has the goal to investigate whether consumer behaviour towards a brand changes after being confronted with an influencer towards whom people have feelings of distrust. Therefore, it needs to be analysed whether consumers perceived the brand Nike significantly different before and after being confronted with the bloggers in the hypothetical scenario. To test the hypotheses, a one-way ANOVA with repeated measures is performed. This test is used because the participants in this research are measured multiple times, both before and after being confronted with the hypothetical scenario. This has been done in order to see whether being confronted with the story changes their behaviour towards the brand.

Before conducting the one-way ANOVA with repeated measures test, Pearson correlations tests were conducted to see whether the variables in this dissertation research are interrelated. The outcomes of the correlations tests can show whether there is an association between pairs of variables, and if so, how strongly they are related (Pallant, 2010). The values of Pearson correlation coefficients (r) range from -1 to +1. It is indicated by the sign out the front whether there is a negative or a positive correlation. An indication of the strength of the relationship is given by the size of the absolute value. A correlation of 1 or -1 is a perfect correlation and indicates that the value of one variable can be exactly determined by knowing the other variable’s value, whereas no relationship between two variables is indicated by a correlation of 0 (Pallant, 2010). However, despite that correlation gives an indication of whether there is a relationship between two variables, it does not indicate that one variable is being caused by the other or that it causes the other. Therefore, other additional tests are needed. The correlations between study constructs as a result of the Pearson correlations tests can be found in Table 4.4 on the next page.

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Table 4.4 Pearson correlations

Variables 1 2 3 4 5 6 7 8 9 10 11 12

1. Gender -

2. Age .02 -

3. Highest obtained degree .03 -.31* -

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4.3.1 Correlations

As mentioned above, before testing the four hypotheses by means of paired samples t-tests and one-way ANOVAs with repeated measures, it first will be looked at whether the variables included in this research are related with each other, and if so, how strongly they are related. While the correlations between all variables can be found in Table 4.4 on the previous page, the most important relations between the variables are discussed below.

The variable pre-purchase intentions correlates positively with post-purchase intentions, and this correlation was statistically significant (r = .761, n = 145, p = .000). Furthermore, it is shown that there is a negative correlation between distrust and post-purchase intentions, which was not statistically significant (r = -.148, n = 145, p = .075), with high levels of distrust associated with lower levels of purchase intentions.

There was a strong positive correlation between pre- and post-brand loyalty, which was statistically significant (r = .823, n = 145, p = .000). In addition, the results of the conducted tests show that there was a small positive correlation between the distrust and post-brand loyalty, which was not statistically significant (r = .014, n = 145, p = .863). This means that higher levels of distrust are associated with higher levels of brand loyalty, which is not the relationship we expected, as discussed in the second chapter of this dissertation.

The relationship between pre- and post-brand attitude was also determined. There was a strong and positive correlation between pre- and post-brand attitude, which was also statistically significant (r = .783, n = 145, p = .000). There was a small negative correlation between distrust and post-brand attitude, which was not statistically significant (r = -.148, n = 145, p = .076). This means that high levels of distrust are associated with lower levels of purchase intentions, although this is only a small relationship.

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4.3.2 Paired samples t-test and one-way ANOVA with repeated measures

The first paired samples t-test and one-way ANOVA with repeated measures were conducted to test whether there was a significant difference between pre- and post-purchase intentions and whether this difference is being caused by the variable distrust (H1). By means of conducting a paired samples t-test it could be evaluated what impact the intervention by means of the hypothetical scenario had on purchase intentions towards the brand Nike. There was a statistically significant decrease in purchase intentions from the pre-intervention (M = 5.36, SD = 1.16) to post-intervention measurement (M = 4.72, SD = 1.24), t (144) = 9.188, p = .000. From this test it can be concluded that participants had lower purchase intentions towards the brand after reading the story than they had before doing so, since the mean decreases. In order to see whether the decrease in mean from pre- to post-purchase intentions is being caused by the variable distrust, a one-way repeated measures ANOVA test was conducted. Since the repeated-measures variable has only two levels, sphericity is met. The assumption of sphericity is met for all four one-way repeated measures ANOVA tests, and therefore for all hypotheses the test with sphericity assumed can be used. The one-way repeated measures ANOVA test with sphericity assumed determined that the difference in pre- and post-purchase intentions was not statistically significant (F (1, 143) = 18.797, p = .074). Subsequently, it should be investigated whether the change in purchase intentions is being caused by distrust. There was a significant effect for distrust on the change in purchase intentions (F (1, 143) = 18.797, p = .000). Therefore, it can be concluded that distrust elicits a statistically significant reduction in purchase intentions, which means that the first hypothesis is supported.

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The third paired samples t-test and one-way ANOVA with repeated measures were conducted to test whether there was a significant difference between pre- and post-brand attitude and whether this difference is being caused by the variable distrust (H3). The results of the paired samples t-test show that there is a statistically significant difference between the pre-intervention (M = 5.60, SD = 1.15) and post-pre-intervention (M = 5.11, SD = 1.19) measurements of brand attitude, t (144) = 7.531, p = .000. This means that the brand attitude towards the brand was less favourable after participants were being confronted with the scenario than it was beforehand. Furthermore, out of the one-way repeated measures ANOVA with sphericity assumed it can be concluded that the difference in pre- and post-brand attitude is significant (F (1, 143) = 4.298, p = .028). In addition, the results also show that there was a significant effect of distrust on the reduction in brand attitude (F (1, 143) = 18.765, p = .000), which results in the acceptance of the third hypothesis.

The final paired samples t-test and one-way ANOVA with repeated measures were conducted to test whether there was a significant difference between pre- and post-retransmission intentions and whether this difference is being caused by the variable distrust (H4). The results of the paired-samples t-test indicate that there is a statistically significant decrease in retransmission intentions from the pre-intervention (M = 4.63, SD = 1.39) to the post-intervention measurement (M = 4.26, SD = 1.39), t (144) = 4.795, p = .000. Subsequently, the performed one-way ANOVA with repeated measures determines that the difference between pre- and post-retransmission intentions is statistically significant (F (1, 143) = 10.495, p = .001). The results also show that there was a significant effect of distrust on the decrease in retransmission intentions (F (1, 143) = 21.601, p = .000). Therefore, the fourth and final hypothesis is also supported by the data gathered for this research.

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4.5 Overview of findings

An overview of all four hypotheses and the results of hypotheses testing, whether they are either supported or not supported, is provided in Table 4.5.

Table 4.5 Results of hypotheses testing

Hypotheses Explanations Results

H1 The higher the distrust that a consumer experiences towards an online influencer, the lower the purchase intentions towards the products of the brand.

Supported

H2 The higher the distrust that a consumer experiences towards an online influencer, the lower the brand loyalty towards the brand the influencer is promoting.

Supported

H3 The higher the distrust that a consumer experiences towards an online influencer, the less favourable the attitude towards that brand.

Supported

H4 The higher the distrust that a consumer experiences towards an online influencer, the lower the retransmission intentions.

Supported

4.6 Conclusion

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5. Discussion

5.1 Introduction

The implications of the results of the statistical analyses used for hypotheses testing will be discussed in this chapter Discussion. For every hypothesis included in this research the statistical results will be discussed in this chapter. At the end of the chapter, an overall discussion about distrust issues and consumer behaviour will be provided.

5.2 Distrust and purchase intentions

The aim of this research was to investigate the influence of distrust issues on consumer behaviour. One of the variables that was included in the measurement of consumer behaviour was purchase intentions. The results of this research show that distrust issues in an online influencer have a negative effect on purchase intentions and therefore support the first hypothesis which stated that: The higher the distrust that a consumer experiences towards an

online influencer, the lower the purchase intentions towards the products of the brand. The

results of this research that support the first hypothesis are in line with literature (Chang and Fang, 2013; Cho, 2006; Lewicki et al., 1998) expecting that distrust will influence purchase intentions negatively, since distrust will lead to negative perceptions, which will in turn lead to negative behaviours and smaller commitment to the relationship. The expectation of negative consequences will accordingly lead to behaviour which is intended to reduce those consequences (Deutsch, 1958). Therefore, consumers purchase intentions are inhibited by distrust (Ou and Sia, 2010).

5.3 Distrust and brand loyalty

The second hypothesis discusses the effect of distrust issues on brand loyalty. The second hypothesis was stated as follows: The higher the distrust that a consumer experiences towards

an online influencer, the lower the brand loyalty towards the brand the influencer is promoting.

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and perceptions associated with high distrust (Cho, 2006; Kramer, 1994) will affect consumers’ brand loyalty negatively. Thus, when a consumer experiences high distrust towards an online influencer, this has a negative influence on customer brand loyalty.

5.4 Distrust and brand attitude

The third hypothesis is about distrust and its effect on brand attitude. More specifically, the third hypothesis was formulated as follows: The higher the distrust that a consumer experiences

towards an online influencer, the less favourable the attitude towards that brand. The results

of the online questionnaire show that there was a negative relationship between distrust and attitude towards the brand. This outcome was in line with the reasoning behind the third hypothesis. It has been argued that communications of users in social media have a large influence of consumers’ attitudes towards a brand (Abzari et al., 2014). Within this, trust can be seen as a strong predictor of brand-related outcomes like a favourable brand attitude (Garbarino and Johnson, 1999; Macintosh and Lockshin, 1997). It can be expected that both positive and negative affective thoughts and reactions to marketing activities are influencing brand attitudes. When distrust issues are present, the negative feelings associated with distrust will be transferred to a less favourable attitude towards the brand. The reason for this is that a failure to produce favourable and strong brand associations will lead to a less favourable brand attitude.

5.5 Distrust and retransmission intentions

The fourth and final hypothesis is about the relationship between distrust and retransmission intentions, and was stated as follows: The higher the distrust that a consumer experiences

towards an online influencer, the lower the retransmission intentions. This hypothesis was, like

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relatively low with distrust issues being present. This is in line with the statistical tests performed in this dissertation research, and the fourth and final hypothesis is therefore supported.

5.6 Distrust and consumer behaviour

The purpose of this dissertation research was to find an answer on the main research question, which was stated as follows: ‘What are the effects of distrust issues in influencer marketing on

consumer behaviour in general, and on purchase intentions, brand loyalty, brand attitude and retransmission intentions in particular?’ The results of the statistical analyses show that all

variables measuring consumer behaviour changed significantly after participants were being confronted with the hypothetical scenario. In addition, the results of this study also showed that distrust issues had a significant influence on these changes in consumer behaviour. Thus, purchase intentions, brand loyalty, brand attitude and retransmission intentions are negatively influenced when consumers are being confronted with distrust issues towards online influencers. This means that consumers have less favourable behaviour towards a brand cooperating with distrusted influencers. Therefore, it is important that companies take this into account when they consider to cooperate with online influencers. Identifying trusted online influencers could help companies improve their online marketing strategies, since they have more influential power compared to distrusted online influencers (Li et al., 2010).

5.7 Conclusion

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