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Master Thesis

Name: Berna Cansu Yilmaz

Student Number: 10069364

Date: August 18th, 2016 Supervisor: Frank Slisser

Study: Master Business Administration

Track: Marketing

Institution: University of Amsterdam

Faculty: Faculty of Economics and Business

Version: Final draft

How does co-creation affect brand

engagement and how can the ELM help

understand the relationship?

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STATEMENT OF ORIGINALITY

This document is written by Berna Cansu Yilmaz, who declares to take full responsibility for the contents of this document.

I declare that the text and the work presented in this document is original and that no sources other than those mentioned in the text and its references have been used in creating it.

The Faculty of Economics and Business is responsible solely for the supervision of completion of the work, not for the contents.

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Delft, August 18th 2016.

This thesis is written as the final part of the Master in Business Administration at the University of Amsterdam. In this document, you will find a detailed report of how I conducted academic research on the effects of co-creation in advertising.

Nearly simultaneously with starting this master in September 2013, my personal life changed dramatically and I faced many difficult challenges. During this time, I have learned to deal with the wicked curve balls that life has in store and that not everything goes as planned. Now, after three years, it is greatly satisfying to see that I have finally reached my personal goal: I finished my thesis.

It is also important to note that I could not accomplish this alone. I would like to formally thank my supervisor for his guidance and providing me with the critical insights that eventually helped me reach my goal. Furthermore, I would like to thank all of my inspiring friends, who listened to all of my endless complaints, laughed with me when I needed it the most and had more faith in me than I did. Especially, I would like to acknowledge the patience of my father, brother and darling little sister. Even though I nearly neglected them while writing this thesis, their believe and support in me was endless.

Finally, I would like to dedicate this thesis in loving memory of my late mother Zübeyde, who passed away after a courageous battle during the time I was writing my thesis. No words can express how much I wish you could see me graduate.

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TABLE OF CONTENTS

PREFACE

... 5

ABSTRACT

... 8

CHAPTER 1. INTRODUCTION

... 8

1.1. Mobile applications and brand engagement... 9

1.2. Co-creation and content effects ... 10

1.3. Problem definition ... 12

1.4. Relevance ... 12

1.5. Structure ... 13

CHAPTER 2. THEORETICAL BACKGROUND

... 14

2.1. Brands ... 14

2.2. Brand engagement ... 15

2.3. Mobile advertising ... 17

2.4. Co-creation... 19

2.5. Motivation for information processing ... 21

2.6. Functional and symbolic brand messages ... 23

2.6.1. Functional and symbolic brand messages in mobile advertisements with co-creation ... 24

2.6.2. Functional and symbolic brand message in regular mobile advertising ... 25

2.7. Purchase intention ... 26 2.8. Conceptual model ... 26

CHAPTER 3. METHODOLOGY

... 27

3.1. Research type ... 27 3.2. Research method ... 27 3.3. Design ... 28 3.4. Pre-test ... 29 3.5. Sample ... 29 3.6. Procedure ... 30 3.7. Measures ... 32 3.7.1. Independent variable ... 32 3.7.2. Dependent variables ... 33 3.7.3. Control variables ... 34

CHAPTER 4. RESULTS

... 35

4.1. Manipulation checks ... 35

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4.2. Tests on randomization ... 36

4.3. Analyses on correlations ... 36

4.4. Hypotheses testing ... 36

4.4.1. Co-creation vs. no co-creation in mobile advertisements ... 37

4.4.2. Co-creation in mobile advertisements vs. type of brand message ... 38

4.4.3. Regular mobile advertisements vs. type of brand message ... 38

4.4.4. Brand engagement and purchase intention ... 39

4.5. Additional analysis ... 40

4.6. Overview of hypotheses ... 41

CHAPTER 5. DISCUSSION

... 42

5.1. Interpretation and value of the quantitative results ... 42

5.1.1. Co-creation vs. no co-creation in mobile advertisements. ... 42

5.1.2. Co-creation in mobile advertisements vs. type of brand message. ... 44

5.1.3. Regular mobile advertisements vs. type of brand message. ... 45

5.1.4. Brand engagement and purchase intention. ... 46

5.2. Theoretic implications ... 46

5.3. Managerial implications ... 47

5.4. Limitations ... 48

5.5 Recommendations for future research ... 50

CHAPTER 6. CONCLUSIONS

... 52

REFERENCES

... 54

APPENDICES

... 64

Appendix A: Sample ... 64

Appendix B: Complete Survey ... 66

Appendix C: Pre-test ... 70

Appendix D: Stimulus materials ... 71

Appendix E: Item generation ... 72

Appendix F: Correlations ... 74

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In a time where mobile devices and applications are unimaginable in people’s daily lives, brands are actively taking this opportunity to use these platforms for their persuasive communication efforts. Brands use these platforms to engage customers with their brands and a relatively new approach in this is a co-creation strategy. While this approach is gaining popularity, there is a substantial lack of insights and knowledge on how such a strategy can be shaped by businesses and how it affects customer brand engagement. The aim of this thesis was to empirically analyze how co-created advertisements, compared to regular advertisements on mobile applications, could affect customer brand engagement. Specifically, this study aimed to understand how people who co-create on an advertisement with a brand process different brand messages. The Elaboration Likelihood Model is applied to understand the processing. Apart from a literature review, this was analyzed by a so-called scenario experiment (N = 161). The main conclusions are that advertisements on mobile applications with co-creation generate higher brand engagement than regular mobile advertisements. Furthermore, the results showed that advertisements with co-creation are centrally processed and a functional brand message is more effective in increasing the customer brand engagement than a symbolic brand message. Conversely, a regular advertisement on a mobile application is peripherally processed and a symbolic brand message will affect customer brand engagement more favorably than a functional brand message. These results are interpreted on their theoretic and practical value and limitations and directions for future research are discussed and provided.

Keywords: co-creation, advertising, mobile marketing, mobile applications, social media applications, content effects, functional attributes, symbolic attributes, purchase intention, Elaboration Likelihood Model, Snapchat.

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CHAPTER 1. INTRODUCTION

Over the past decade, mobile devices such as smartphones and tablets have become such an essential part of people’s every day lives that most people could not imagine functioning without them (Kaplan, 2012). Along with the mobile market, the market for applications for these devices has exploded as well (Burchell, 2015). With an estimated 100.000 new mobile applications worldwide being uploaded every month, it becomes apparent that the mobile application market is also emerging (Westlund & Färdigh, 2015). While there is a broad array of categories of new applications, the few applications that are successful almost always belong in the category of social applications (Audestad, 2014). These new forms of messaging penetrate deep into the daily lives and routines of consumers in a way that desktop, television, radio and newspapers could never reach (Koivumaki, Ristola, & Kesti, 2008).

1.1. Mobile applications and brand engagement

Mobile applications are powerful tools in reaching and engaging consumers; especially the younger generations (Gao, Rau & Salvendy, 2010; Mirbagheri & Hejazinia, 2010) and organizations are increasingly utilizing these new mobile media technologies as a means to enhance engagement with their audience (Kaplan, 2012; Yu, 2013). On the one hand, consumers have mastered these new platforms as tools to make their opinions and ideas heard and take part in the value creation process. On the other hand, as mobile platforms are gaining an undeniable place in our daily lives, advertisers and organizations are increasingly shifting their focus and persuasive communication efforts towards these devices and applications as well (Yu, 2013). These persuasive communication efforts are strategies through which marketers attempt to shape the beliefs or actions of customers (Hallahan, 2009). Companies are penetrating the online social networking scene and use these tools to promote brands, support the creation of brand communities and to engage customers (Kaplan & Haenlein, 2010).

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In general, engagement refers to an emotional commitment and motivational state of a person (Higgins, 2006). Brand engagement can be defined as the level of investment of a customer in an organization (Hollebeek, 2011) and is known to have a favorable impact on the profitability of the organization and customer-based brand equity (Cova & Pace, 2006; Porter & Donthu, 2008). Research states that social networking platforms are great tools for organizations to stimulate brand engagement, because these networks provide options for sharing, collaborating and contributing content (Porter & Donthu, 2008; Cvijikj & Michahelles, 2013; Burchell, 2015).

As consumers actively make use of such options on social networking platforms, they relate to the brand on a personal and social level (Jahn & Kunz, 2012). This is considered a natural way for organizations to positively influence the attitude of the consumer towards the brand and to build strong relationships, which eventually can lead to an increase of purchase intention (Men & Tsai, 2015). However, Fournier and Avery (2011) warn for the negative effect of advertising on social media, as consumers perceive the boundary to criticize and complain about brands to be lower on these platforms, which could lead to reputation damage. Even though mobile applications and social media are magnifying the impact that consumer-to-consumer conversations have in the marketplace, methods for shaping these conversations are yet to be tested extensively (Tuten & Solomon, 2013). Beuker and Abbing (2010) add that, considering that online interactions between brands and consumers can strengthen the market positioning of a brand, there has been little research on this topic.

1.2. Co-creation and content effects

An increasingly popular strategy that positively affects brand engagement is co-creation (Mangold & Faulds, 2009; Thompson & Malaviya, 2013; Bacile, Ye & Swilley, 2014). Co-creation is the process by which consumers and producers collaborate, participate and create value (Pongsakornrungsilp & Schroeder, 2011). As co-creation encourages consumers to actively and creatively contribute to the brand in some sort of way, consumers become more engaged with the brand (Thompson & Malaviya, 2013). Also, with a co-creation strategy, consumers gain an experience of value through their participation in the decision-making process of a brand (Ramaswamy, 2008). A more novel

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application of co-creation within businesses is creating advertisements together with consumers, which is gaining popularity (Thompson & Malaviya, 2013; Muñiz & Schau, 2007; Bacile, Ye & Swilley, 2014). It can be done by asking consumers for creative input, while the organization executes the idea or by providing consumers the opportunity to create the content for the organization.

Previous research on co-creation in advertising investigated the ways in which consumers are inspired to co-create (Muñiz & Schau, 2007). This research shows that co-creation reduces skepticism in advertisements (Thompson & Malaviya, 2013) and that co-created marketing strategies increase positive attitudes towards the brand (Bacile, Ye & Swilley, 2014). But previous research mainly focused on the effects of co-creation and not on the ways it can be shaped by businesses. No previous research has investigated content effects in co-created advertisements on any platform. Content effects relate to the ways of processing and reacting on a brand message, which can vary depending on the type of message (Belz & Dyllik, 1996). The content effects are important because organizations have lower control of an advertisement if it contains user-generated content (Story, 2007). A way for organizations to minimize such uncertainty is to carefully shape their persuasive messages.

In general, there are two types of content for a brand message: functional and symbolic. A functional brand message contains content related to the functional benefits of a product or service (e.g. descriptive content like characteristics, price or location) (de Chernatonay & Harris, 2000). A symbolic brand message has content related to the symbolic benefits for the consumer (e.g. good feeling, social status or prestige) (Sohier, 2009). Both are known to have a distinctive way of being processed by consumers, for example via the Elaboration Likelihood Model (ELM) (Petty, Cacioppo & Schumann, 1983). The ELM provides a model that helps one to understand how persuasive communication is processed and will be discussed in the next chapter. Regardless, no previous research has linked functional and symbolic brand message content to co-creation or brand engagement.

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1.3. Problem definition

Mobile advertising on social media platforms can indeed be beneficial for consumer brand engagement (Burchell, 2015; Jahn & Kunz, 2012), but the content is vulnerable for negative interpretations as well (Fournier & Avery, 2011). Research shows that co-created advertisements are a valuable content strategy for organizations as they positively influence customer’s attitude towards the brand and increase brand engagement (Bacile, Ye & Swilley, 2014; Thompson & Malaviya, 2013; Moskowitz, 2006). But there still is insufficient academic research on how managers should advertise on these platforms or how to shape co-creation (Pongsakornrungsilp & Schroeder, 2011). This is why this thesis will empirically investigate the effects of functional and symbolic brand messages in co-created advertisements. The goal of the current investigation is to gain insights on how co-co-created advertisements on mobile social applications affect brand engagement. Additionally, this research aims to determine the difference in effect between functional and symbolic content of the brand message on brand engagement. This leads to the following research question:

To what extent does co-creation in mobile advertising affect brand engagement and how does the content of the brand message (functional or symbolic) affect this relationship?

1.4. Relevance

This study contributes to both marketing literature and practice in several ways. The theoretical contribution of the current thesis is to extend the reach of brand engagement towards mobile communication platforms. Brand engagement affects core business goals, such as purchase intention, profits and brand image. For this reason, it is important to investigate under what circumstances it can be optimally leveraged. Mobile platforms are providing new ways for consumers and brands to engage more intimately, which make the organization more vulnerable than in the past. These technologies have transformed simple, one-way and organization-controlled communication into a two-way interaction where consumers have more say than ever (Yu, 2013).

Organizations could engage consumers by enabling the co-creation in advertising and learn under which circumstances it would work optimally (Bacile, Ye & Swilley, 2014). This unique perspective is not present within emerging mobile marketing models and should be explored

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thoroughly (Thompson & Malaviya, 2013; Etimur & Gilly, 2012; Mangold & Faulds, 2009). Organizations are in limited control of advertisements that are co-created, but do have some say in the way they communicate to consumers. If this small amount of control is executed effectively, it could limit negative response and positively influence brand engagement. By analyzing the content effects of co-creation in advertisements and differentiating for functional and symbolic brand messages, practitioners have more grip and guidelines while exploring co-creation in advertisements on mobile platforms. The empirical contribution of this research aims to add to the literature on brand engagement and provides insights into the ways co-creation in advertisements is processed.

1.5. Structure

This thesis is structured as follows. In the second chapter, the theoretical background of the research question is further analyzed. The proposed relationship between co-creation and brand engagement is examined by means of an experiment, of which the methodology is presented in the third chapter. The fourth chapter contains the results. In the fifth and final chapter the discussion and conclusions are provided.

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CHAPTER 2. THEORETICAL BACKGROUND

In this chapter the theoretical foundations behind the research question are discussed and linked to one another in order to provide justification for the current empirical research based on existing academic literature.

2.1. Brands

In consequence of the rapidly increasing and tight competition within the global economy, brands are seeking for ways to conquer and maintain market share. Competing on price can be non-profitable on the long term, as it is not a unique distinction from competitors and easily imitable (Nandan, 2005). Thus, brands are looking for ways to create sustainable competitive advantage through improving and stimulating branding (Ramaswamy, 2008), specifically by targeting brand equity (Keller, 1993). De Chernatony and Dall’Olmo (1997) conducted an exploration research on the meaning of a brand and concluded that there are a dozen varying meanings for the term. Their research shows that brands can be viewed as an image, a value system, a logo, a company, a legal instrument, a risk reducer, an identity system, a personality, a relationship, an added value or an involving entity. Another research focused on the definition of brand showed that the different definitions of a brand should be divided into metamorphic, literal and integrative interpretations (Stern, 2006). From a metamorphic interpretation, a brand is seen as the image of a certain product or organization through the eyes of the outside world. The literal interpretation of the word focuses on the varying assets of a brand. The integrative meaning relates to the identity of a brand. In branding, the metaphorical meaning is the most relevant (Stern, 2006). Kotler (1991) provides a definition that suits the metaphorical interpretation of a brand and which is used in this thesis. According to him, a brand is “a name, term, sign, symbol, or design, or 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 (p. 442)”. Branding helps customers reduce risk by providing a certain level of product quality and specific attributes (Keller, Apéria & Georgson, 2008).

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Organizations aim to provide a clear brand identity to differentiate themselves from global competitors (Neumeier, 2006). A way to do this is by creating brand equity, which is defined as a unique attribute belonging to an organization and is seen as a tool to accomplish differentiation from competitors (Keller, 1993). Brand equity provides a sustainable and competitive advantage as it allows the organization to compete based on brand value rather than offering a lower price (Broyles, Schumann & Leingpibul, 2009). Keller (2013) describes brand equity from the perspective of consumer’s perspective, customer-based brand equity (CBBE), and defines the concept as the differential effect that brand knowledge, or more specifically the associative network on a brand, has on the response of consumers to marketing activities of a certain brand. The highest level of CBBE is brand resonance, which encompasses a customer’s loyalty and attachment to a brand. The general notion of CBBE is that the strength of a brand is determined by customer response, as it is formed by the (in)-direct experiences consumers have with a specific brand (Keller, 2013).

The associative network model views a person’s memory as a network of nodes and interconnecting links. Each node stores information on specific concepts and the connection, also known as links, between the nodes differ in strength (Keller, 2013). Organizations try to influence, create and/or strengthen the associations that people have by using branding techniques and different marketing efforts (Nandan, 2005). The goal is to create strong, favorable and unique associations in the minds of consumers in order to realize sustainable competitive advantage (Keller, 1993). Brand equity is linked to a higher profitability of the organization, higher levels of customer retention, a higher customer lifetime value, more forgiving response in times of organizational crisis and overall higher brand equity (Fishbein & Ajzen, 1975; Porter & Donthu, 2008). A common and successful way to create brand loyalty is by stimulating engagement between customers and a brand (Yu, 2013).

2.2. Brand engagement

Although customer brand engagement is a relatively recent development in marketing practice and literature (Bowden, 2009), it is already seen as a driver of the consumer decision-making process (Hollebeek, 2011) and brand equity (Schultz & Block, 2011). Customer brand engagement is valued as a strategic asset that helps businesses to create and maintain a sustainable competitive advantage

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(Jakste & Kuvykaite, 2012). Customer brand engagement can be defined as “the level of an individual customer’s motivational, brand-related and context-dependent state of mind characterized by specific levels of cognitive, emotional and behavioral activity in direct brand interactions” (Hollebeek, 2011, p. 21). It is an ongoing interaction between a brand and consumers that can help to gain a greater likability for a brand because of the continuous communication (Kapferer, 2001) and to strengthen brand equity dimensions: brand awareness, brand associations and brand loyalty (Aaker, 1996).

A customer is engaged with a brand when that person is motivated by the brand to get involved, encouraged by other customers or when the customer receives certain benefits (Jakste & Kuvykaite, 2012). Discussing consumer brand engagement, the terms engagement and involvement are both often used. The term involvement is perceived as part of the broader concept engagement, as engagement includes customer‘s experience as well as interactive relationship between a brand and a customer (Mollen & Wilson, 2010; Brodie, Ilic, Hollebeek & Juric, 2011). Involvement is generally perceived as a more complex expression of customer attitude and intensity of feelings for a brand, reflecting the positive customer assertion of priority for a brand against others (Morris & Martin, 2000). Involvement is an internal psychological process with emotional ties, whereas engagement is more concerned with the actual experience of interacting with a brand (Brodie et al., 2011). Engagement is also seen as a motivational state, which is used to understand customer attitudes towards products or brands (Guthrie & Kim, 2009).

Research shows that customer brand engagement functions as a construct that enforces a strong and lasting bond between a brand and its customers, which is achieved when customers continuously interact with the brand, share common values with the brand and experience contents of the brand (Schultz, 2006). Furthermore, Wang (2006) states that customer brand engagement affects the effectiveness of advertising processing; his research showed that more engagement leads to better recall of the advertisement, more involvement in the brand message, a higher credibility of the advertisement and a more favorable attitude towards the message.

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2.3. Mobile advertising

Organizations perceive the widespread adoption of mobile phones as an opportunity to reach and serve their customers at any given time and place (Grant & O’Donohoe, 2007; Roach, 2009; Barutcu, 2007). Advertising on mobile devices started with SMS marketing almost a decade ago (Mirbagheri & Hejazinia, 2010). Since, it has become increasingly popular with organizations (Koivumaki, Ristola, & Kesti, 2008). Marketing via mobile devices is different than traditional mass media marketing, mostly because mobile marketing is generally perceived as a more personalized form of advertising (Kaplan, 2012). Previous research investigated the general attitudes towards mobile advertising and showed that mobile advertising is generally accepted better than traditional advertising, especially with the younger generations (Roach, 2009; Bauer, Reichardt, Barnes & Neumann, 2005; Megdadi & Nusair, 2011). Previous research on mobile marketing and what the motives for use are, showed that mobile devices are commonly used for entertainment purposes and basic communication (Hanley & Becker, 2008). This allows mobile devices to become platforms where commercial advertising blends with regular communication (Gao, Rau & Salvendy, 2010; Kaplan, 2012).

New mobile devices (e.g. smartphones) are developed with functionalities that benefit both consumers and organizations, such as applications (Persaud & Azhar, 2012). Consumers install these applications to personalize their mobile device to meet all their needs (Roach, 2009). With the rise in popularity of mobile devices and their increasing influence on people’s daily lives, numerous social networking platforms (e.g. Facebook) developed mobile applications. Kaplan (2012) provides a definition of mobile social media and states that they are “a group of mobile marketing applications that allow the creation and exchange of user-generated content” (p. 131). Social media applications, which can be blogs, content communities, social networking sites and virtual gaming worlds, have become a generally accepted means of communication for both consumers as organizations (Murdough, 2009). Social media provide opportunities for businesses to reach consumers through active communication and constantly updated content to successfully engage them (Jakste & Kuvykaite, 2012).

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customer relationship management (CRM), customer service, lead generation, sales promotion delivery channel, paid advertising channel and branding (Schmitt, 2012). It allows brands to communicate better with their target audience and intensifies their associations with them (Sheehan & Morrison, 2009). Also, organizations increasingly utilize these new mobile media technologies as a means to enhance engagement with their audience (Yu, 2013). Kaplan (2012) states that the best way to create customer brand engagement is by utilizing social mobile applications as a platform for advertising, as customers spent lots of time on these applications. Campbell, Pitt, Parent and Berthon (2011) show that advertisements on social applications create a greater sense of engagement with a brand than advertisements on traditional mass media. In social media, engaged customers participate and share. Participation may be passive, involving simply consuming the social content, or active, including such behaviors as submitting consumer-generated stories (Hutton & Fosdick, 2011).

When organizations target their branding efforts to engage customers with their brand, it does not immediately imply that engaging a customer is actually accomplished (Gambetti, Graffigna, & Biraghi, 2012). In general, advertisements are sensitive to advertising avoidance, which means that a customer has been exposed to too many advertisements and may avoid an advertisement instead of processing it (Yaakop, Anuar & Omar, 2013). This is also known as an excess of advertisement clutter, a term that is used when consumers believe that there is an excess of advertising within a given medium at a given time (Cho & Cheon, 2004). If this is experienced, consumers have the ability to avoid an advertisement by cognitive, behavioral and mechanical means such as ignoring the advertisement, switching to another medium or blocking the advertiser (Yaakop, Anuar & Omar, 2013). Research by Stelzner (2013) contributes that branded content on social media should be interactive and experiential to ensure engagement of users. Furthermore, Persaud and Azhar (2010) found that successful engagement of consumers on mobile devices requires that strategies center around value creation together with consumers, so consumers get engaged with a brand in an authentic way, which means that such a strategy should be creative.

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2.4. Co-creation

Historically, advertising is defined as “communication and information flows originating within firms or their designated advertisement agencies, which create advertisements and pay to transmit them in broadcast or print media with reasonably clear intentions: to inform, persuade, or remind present and potential customers of their offerings or of the organization itself” (Barton, 1950, p. 928). In this sense, the public was perceived as passive recipient of persuasive messages, reacting to these either by becoming attentive or by being able to recall them (Campbell, Pitt, Parent & Berthon, 2011). Now more than ever, consumers are no longer passive recipients of persuasive communication offered by organizations, as they are informed, connected, networked, and empowered thanks to online platforms such as social media (Etimur & Gilly, 2012). This shift is backed by an often cited theoretical framework relating to the media consumption of people: the Uses and Gratifications theory. It questions how people use media and what motivates them (Katz, Gurevitch, & Haas, 1973; Katz, Blumer, & Gurevitch, 1974). According to this theory, users are active and conscious while choosing and using media and one should look at what users do with them, rather than looking at the influence of the media on users (Katz et al., 1974).

Organizations see this shift as an opportunity and respond with co-creation efforts between their brand and customers (Ramaswamy, 2008). Co-creation is the process by which customers and producers collaborate and participate and create value (Pongsakornrungsilp & Schroeder, 2011). Co-creation helps organizations acquire valuable customer insights, incorporate authentic and user-generated content and increase customers’ engagement with the brand (Moskowitz, 2006). In co-creation, user-generated content (UGC) is central. UGC is an important manner through which consumers express themselves and communicate with others online; it is what is produced at the moment of being social, as well as the object around which sociality occurs (Boyd & Ellison, 2008). It may be individually or collaboratively produced, modified, shared and consumed, and “can be seen as the sum of all ways in which people make use of social media” (Kaplan & Haenlein, 2010, p. 61). UGC across various (social) media platforms (i.e. review websites) can be brand-related and has the potential to shape consumer brand perceptions. In an effort to gain more control over UGC, organizations have learned to incorporate user-generated content in their advertisements, making the

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advertisements co-created (Campbell, Pitt, Parent & Berthon, 2011).

Co-creation in organizations is defined as consumers whom are collaborating with the organization in at least one interactive manner (Etgar, 2008; Grönroos, 2006). It involves enabling some form of interaction so that individuals can have meaningful, engaged and compelling experiences (Ramaswamy, 2008). Co-creation with customers includes that a customer decides at least one or multiple of the following advertising characteristics for an organization: message's delivery time, frequency, recipient, subject, format, preferred media channel or any other message characteristic prior to receiving a marketing communication (Berthon, Pitt, & Campbell, 2008; Bacile, Ye & Swilley, 2014). Where mass media actually limit consumers in actively participating, personal media, like social media and mobile applications, do enable active participation and co-creation (Campbell, Pitt, Parent & Berthon, 2011). Customers’ willingness to co-create content with an organization is influenced by benefits a customer expects to receive such as psychological benefits like feeling important and relevant (Etgar, 2008). Co-creation encourages consumers to actively and creatively contribute to the brand, which is why customers become more engaged with the brand (Thompson & Malaviya, 2013). Also, with a co-creation approach, customers gain an experience of value through their participation in the decision-making process of a brand (Ramaswamy, 2008). Customers are willing to co-create as they acquire these benefits in the process. In this way, customers are in a motivated and active state when they co-create. Organizations incorporate co-creation through mobile applications in several aspects of their business, one of them being in advertisements (Thompson & Malaviya, 2013).

Advertisements that do not incorporate co-creation, which can also be seen as regular advertisements, are generally targeted to be visible to customers and create exposure for a brand regardless of the platform (Yaakop, Anuar & Omar, 2013). Such advertisements do have the advantages to create engagement to a certain degree (e.g. linking, sharing and commenting), but lack aspects that promote active participation that a co-creation strategy has (Etgar, 2008). Mobile devices already prove to be platforms where brand engagement can be easily created (Campell, Pitt, Parent & Berthon, 2011) and co-creation as an advertising strategy has a favorable influence on brand engagement (Moskowitz, 2006); thus advertisements with co-creation on mobile platforms are

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expected to influence brand engagement positively than regular mobile advertisements. However, there is an essential step between co-creation and brand engagement: the motivation of a person to process the persuasive communication and information (e.g. the advertisement), which will be discussed next.

2.5. Motivation for information processing

Roloff and Miller (1980) define persuasive communication as “any message that is intended to shape, reinforce, or change the responses of another or others” (p. 14). This definition limits the scope of persuasive communication to intentional behavior, which is important as it implies that not all communication is persuasive in nature (Bolatito, 2012). Woodward and Denton (1992) view persuasive communication as a process that encompasses ‘preparing and delivering verbal and nonverbal messages to individuals in order to alter or strengthen their attitudes, beliefs, and behaviors" (p. 21). Thus, persuasive communication can be viewed as both a process and a conscious attempt of an organization to change and shape attitudes, beliefs and behaviors individuals or groups by the transmission of a message (Bettinghaus & Cody, 1994; Bolatito, 2012).

The Elaboration Likelihood Model of persuasion (ELM) is a conceptual framework that is used for understanding the basic processes underlying the effectiveness of persuasive communication (Petty & Cacioppo, 1986). The model, which can be viewed in figure 1, is perceived as one of the most useful models in persuasion theory and practice and is the most commonly used model to understand processing of persuasive content (Bitner & Obermiller, 1985; Lien, 2001). The ELM assumes that variations of persuasive content affect the likelihood that receivers will engage in elaboration of the information in the communication (Petty & Cacioppo, 1986) and measures attitudinal change and formation (Liu & Shrum, 2009).

The model features two routes of persuasion, the central route and the peripheral route, and perceives motivation as a determinant for message elaboration and attitudinal change. The central route of the ELM is concerned with a high level of message elaboration in which the customer receiving the message generates a great amount of cognition about the arguments, for example the degree to which the message is based on facts (Petty, Briñol & Priester, 2009). When a person is

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motivated to process the information, the processing will occur via the central route of persuasion. The attitudinal change will be relatively resistant, enduring and predictive of future consumer behavior (Liu & Shrum, 2009). If a person has little motivation to process the persuasive information, persuasion is processed via the so-called peripheral route. The processing occurs via peripheral cues, such as an expert opinion or the amount of arguments provided and can influence and changes in attitudes. Research shows that an attitudinal change via peripheral cues are generally only effective on short-term and are less enduring than attitude change via the central route (Petty, Briñol & Priester, 2009).

Figure 1 Conceptual representation of the Elaboration Likelihood Model (Petty, Briñol & Priester, 2009).

In general, the goal of a brand is to change attitudes of customers favorably with their persuasive communication. Customer attitudes are associated with their beliefs and behaviors towards a brand or product. These attitudes are not stable but can change over time as they are context-dependent and can be influenced by the communication of others. Attitudes are processed and occur on an affective and cognitive level. Within the ELM, processing through the central route leads to a more lasting attitudinal change. This is more desirable for organizations, as a lasting attitudinal change affects the behavioral dimension positively and is also more resistant towards counter persuasion (Petty & Cacioppo, 1986).

The degree that a customer is engaged with the brand is an attitudinal association with the brand, as brand engagement is defined as “the level of an individual customer’s motivational, brand-related and context-dependent state of mind characterized by specific levels of cognitive, emotional

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and behavioral activity in direct brand interactions” (Hollebeek, 2011, p. 21). Thus, when attitudinal change such as a higher degree of engagement in the brand is desired by an organization, there needs to be a high level of motivation to process the message. Jakste and Kuvykaite (2012) back this, as they state that customer brand engagement depends on how brands motivate customers to participate. An effective way to stimulate this motivation is by incorporating co-creation in advertisements but also by advertising on mobile social applications. As customers actively participate to co-create with an organization, they are expected to be more motivated as they satisfy their need of feeling important and relevant and gain an experience of value (Etgar, 2008; Ramaswamy, 2008). Furthermore, when people consciously use their phone and browse social mobile applications willingly, they are already in an active and motivated state (Teng, Khong & Goh, 2014). This leads to the first hypothesis:

H1: When exposed to a mobile advertisement with co-creation, a person will have a higher motivation for information processing and a higher degree of brand engagement, than when a person is exposed to a regular mobile advertisement

2.6. Functional and symbolic brand messages

A basic and well grounded assumption in branding literature is that people have both functional and symbolic associations with brands, which can be strengthened and brought on top of mind by creating and using respectively functional and symbolic benefits in an advertisements brand message (Keller, 1993; Merrilees, 2005). The brand message, also known as a slogan, is generally a short tagline that informs customers about the benefits of the brand, product or service and captures the identity of an organization (Keller, 1993). On the one hand, there are functional attributes that are related to a brand and describe a product or service in terms of its physical and tangible attributes (Bhat & Reddy, 1998). A functional brand message, thus, is focused on utility, facts and rationally assessed statements related to the brand, for example product features (e.g. best camera quality) or business performance (e.g. most used product world wide) (de Chernatony & Harris, 2000). The success of a branding strategy with exclusively functional attributes can be limited, as the message does not deliver individual benefits to consumers (Belz & Dyllik, 1996). Furthermore, competitors easily imitate brand messages with functional attributes as a focus, which does not help with differentiation. On the other

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hand, there are symbolic attributes that are related to a brand. They correspond to non-product related attributes, specifically user imaginary and sentiment (Bhat & Reddy, 1998). Symbolic brand messages describe the brand in term of subjective, abstract and intangible attributes and target consumers’ beliefs, culture and values, for example their relationships with loved ones or their consciousness to evoke emotion (Merrilees, 2005).

De Chernatony and Harris (2000) state that in general, symbolic values are more sustainable in differentiating a brand than functional attributes. While symbolic values in brand messages are generally perceived as more appealing, it is important for a brand to select their brand message as fitting as possible to their branding strategy, to ensure that consumers process their message effectively (Liu & Shrum, 2009). When consumers are involved by creating an advertisement and active participation, cognitive and functional persuasion is more effective (Cope & Winward, 1991; Swenson & Wells, 1997; Fuller, 1999).

2.6.1. Functional and symbolic brand messages in mobile advertisements with co-creation

As mentioned before, within a co-creation advertising strategy, consumers participate in a creative process of value creation with the organization and are more likely to process via the central route of the ELM. According to the ELM, the brand message should be concrete and factual, as the central route of processing makes customers focus on the quality and relevance of the message (Teng, Khong & Goh, 2014). In this case, in advertisement with co-creation, a brand message with functional attributes will improve attitudinal change such as higher brand engagement. Conversely, a co-created advertisement with a brand message that has symbolic attributes is expected to be less effective an attitudinal change in brand engagement. This expectation is based on the fact that when a customer is centrally processing persuasive communication, symbolic brand messages could seem irrelevant and unrelated to the core-business of the organization, and thus not improve an attitudinal change such as more engagement with the brand (Liu & Shrum, 2009; Lien, 2001). Based on this, the following hypothesis is formulated:

H2: When exposed to a co-created mobile advertisement with a functional brand message, a person will have a higher motivation for information processing and a higher degree of brand

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engagement, than when a person is exposed to a co-created mobile advertisement with a symbolic brand message

2.6.2. Functional and symbolic brand message in regular mobile advertising

Conversely, if mobile advertisements do not incorporate co-creation, also known as regular mobile advertisements, the role of the brand message can be different. As regular mobile advertisements do not require participation of the customer, the customers are simply only exposed to them. Mobile platforms are generally used for both communication and entertainment purposes (Gao, Rau & Salvendy, 2010; Kaplan, 2012) and customers generally have a better attitude towards advertisements on mobile platforms than advertisements on traditional platforms (Roach, 2009; Bauer, Reichardt, Barnes & Neumann, 2005; Megdadi & Nusair, 2011).

However, when a customer is exposed to an advertisement while browsing a mobile application, the person is focused on the initial intended task (e.g. sending a message to a friend or scrolling down a social feed) and not on an advertisement. The person is not initially motivated to process the advertisement and might process the advertisement via the peripheral route of persuasion of the ELM. In this route, customers are focused on basic cues of the advertisement, such as the tone of voice and amount of arguments provided, and form an attitude about the persuasive message based on surface-level characteristics, such as sentiment of the advertisement (Petty & Cacioppo, 1986). Functional and factual information is generally rejected or ignored when processing occurs via the peripheral route of persuasion, and thus, is not expected to be successful (Liu & Shrum, 2009). Based on this, the following hypothesis is formulated:

H3: When exposed to a regular mobile advertisement with a symbolic brand message, a person will have a lower motivation for information processing and a higher degree of brand engagement, than wen a person is exposed to a regular advertisement with a functional brand message

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2.7. Purchase intention

The best indicator or predictor of a customer’s future behavior is their intentions. The intentions of a person can be described as cognitive representations of one's willingness to perform certain behavior (Fishbein & Ajzen, 1975). As previously discussed, brands are looking for new ways to create a sustainable competitive advantage and are using branding to reach this goal (Ramaswamy, 2008). By stimulating brand engagement, the goal is to increase customer-based brand equity (Schultz & Block, 2011). However, brands are not solely looking for likability and brand equity, performance is also highly important for brands, as their main objective is to become profitable (Keller, 2013). Brand engagement is known to positively influence demand creation, brand choice and an increased purchase intention (Jahn & Kunz, 2012). Research shows that the more engaged the viewer, the more responsive they are towards an advertisement (Calder, Malthouse & Schaedel, 2009). Based on the above, the following and final hypothesis is formulated:

H4: High levels of brand engagement will lead to high levels of purchase intention

2.8. Conceptual model

To conclude, the aforementioned hypotheses can all be found in figure 2, which is a conceptual representation of the concepts and relations that are discussed in this chapter.

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CHAPTER 3. METHODOLOGY

Apart from the literature review, the research question will be analyzed by means of a scenario experiment. This will be discussed in this chapter.

3.1. Research type

In general, there are two different approaches to conducting scientific research, which are an inductive approach and a deductive approach (Saunders, Lewis & Thornhill, 2009). An inductive approach of conducting research is concerned with building a complete new theory. In contrast, a deductive approach of conducting research is concerned with building theory that is based on existing academic literature (Field, 2009). In such studies, hypotheses are formulated to test if the knowledge and theory derived from existing literature are supported. The current study uses a deductive approach of conducting research, as existing literature is used to form several hypotheses to expand the theory on co-creation and brand engagement. Furthermore, a quantitative data collection approach is selected for this study, which is a common approach for deductive research (Saunders et al., 2009).

3.2. Research method

In this study, a scenario experiment will be conducted to test the hypotheses. A scenario experiment entails that participants are presented different hypothetical scenarios instead of real-life scenarios (Kim & Jang, 2014). In general, an experiment is seen as the best research method to study causal links between variables, while controlling for external factors (Saunders & Lewis, 2014; Boeije, ‘t Hart & Hox, 2009). Specifically, a scenario experiment offers a high amount of internal validity by manipulating and controlling variables (Kim & Jang, 2014). Also, scenario experiments avoid some ethical concerns, such as actual disappointment of failures that real life true experiments can have (Bitner, 1990). A scenario experiment in the form of a survey allows the researcher the opportunity to spread the experiment within a larger sample, which positively affects generalizability, while simultaneously providing the means to explore a causal relationship (‘t Hart, Boeije and Hox, 2009),

In scientific research, it is important to ensure that the results of an experiment actually measure the intended constructs and relationships as proposed in the literature review. This is also

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known as the validity of a research, which is defined by Saunders, Lewis and Thornhill (2009) as the extent “to which data collection method or methods accurately measure what they were intended to measure” (p. 603). Thus, the concept entails the degree to which the results actually reflect the theoretical concepts. The validity of results consists of internal and external validity. Internal validity, as defined by Bryman (2008), is concerned with “whether a conclusion that incorporates a causal relationship between two or more variables holds water” (p. 32). External validity, as defined by Saunders et al. (2009), is concerned with “the extent to which the results of a study can be generalized to other situations and to other people” (p. 592). Aside from the validity of a research, it is important that the results of a scientific investigation are reliable. This means that the results should be generalizable to the general population and can be recreated at a different time and place (Bryman, 2008). If researchers want to protect the reliability of their investigations, it is recommended that a standardized research method such as an experiment should be used (Saunders et al., 2009).

3.3. Design

The experimental design of this study is a 2x2 factorial, between-subjects design. The experiment consists of four experimental conditions, which also represent the independent variables. This experiment has two independent variables, which are type of mobile advertisement and the type of brand message. The experimental design is shown in figure 3. In this experimental research, the dependent variables are motivation for information processing, brand engagement and purchase intention.

The first experimental condition concerns a scenario with a co-created advertisement on a mobile device with a functional brand message. The second experimental condition concerns a scenario with a co-created advertisement on a mobile device with a symbolic brand message. The third experimental condition concerns a regular mobile advertisement without co-creation and a functional brand message. The final and fourth experimental condition concerns a regular mobile advertisement without co-creation and a symbolic brand message.

The selected mobile application within this research is Snapchat. It is an application that facilitates advertising in the form of both co-creation and regular advertisements. Snapchat is a social

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mobile application and is characterized by ephemerality and disappearing posts. With more than 100 million active monthly users and nearly 4 billion daily video views worldwide, the app is now the single most popular social medium among teenagers (Sashittal, Demar, & Jassawalla, 2016). Snapchat offers co-created advertising in the form of branded Geofilters; these are special overlays for Snaps, which can be created and sponsored by companies (Snapchat, 2016).

Figure 3 Experimental design.

3.4. Pre-test

To ensure that the experimental conditions optimally represent the researcher’s objectives, a pre-test was performed to select the experimental stimuli. In this pre-test, the brand message used in both the co-creation and no co-creation condition were tested. In total, two brand messages needed to be selected, namely one functional and one symbolic brand message. Three different versions of both types were formulated for this pre-test. These stimuli were presented to a sample of 19 respondents who rated all six messages with an 8-item scale to rate the brand message on functional and symbolic content, which will be further described in section 3.7. Based on this, the item that scored the highest on the intended dimension (either functional or symbolic) was selected for use in the main experiment. The results can be viewed in appendix C and the final experimental stimuli can be found in appendix D.

3.5. Sample

In general, literature shows that younger and higher educated people are the most internet-savvy; they have a high usage rate and a tendency to try new technologies (Grant & O’Donohoe, 2007; Barutcu,

Type of Brand Message

Functional Symbolic

Type of Mobile Advertisement

Co-creation Condition 1 Condition 2

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2007). This study focuses on younger consumers, aged 18-34, as the people in this age category use interactive media intensively and are the most likely to use their mobile phones for social networking (Moore, 2012). Heinonen and Strandvik (2007) found that younger consumers are more responsive to digital media, which is why organizations target them online. Furthermore, worldwide 41% users of the selected mobile application Snapchat are between 18 and 34 years old (Snapchat, 2016).

In order to gather the data and information required to meet the goals of this study, a convenience sample was taken. An experimental survey was launched on July 28th 2016 until August 5th 2016. In these nine days, 185 participants started the experiment. However, only 161 finished the survey, which means that 24 participants started but did not finish the survey. The dropout rate was then 12,9%. A common reason for the dropout rate can be assigned to the freedom and distractions in the natural environment of the participants. As there is no researcher present to oversee the procedure, participant can suddenly stop participating because of a distraction or forget to complete the survey (Field, 2009). The final sample of 161 participants consists of 73 male (45,3%) and 88 female (54,7%) participants. The mean age of the participants was 23,47 years old (SD = 3,69). The youngest participant was 16 and the oldest participant was 34 years old, showing that the target sample was reached. The educational level of the participants was for 56,6% university level or higher. Of the 161 participants, 83,3% was familiar with Snapchat. The most used functions in Snapchat were sending Snaps to friends (42,5%), looking at Snaps from friends (32,7%) and using filters over Snaps (25,8%). The least used function was looking at the section where brand advertise called Discover (5,7%). A complete overview of the socio-demographic data can be found in appendix A.

3.6. Procedure

This experiment was presented in the online program Qualtrics. Participants were invited to join the experiment via e-mail or social media and could complete the experiment in their natural habitat. The advantage of completing a questionnaire in one’s own environment is that there is no pressure from a researcher, which reduces the amount of socially desirable answers (Boeije, ‘t Hart & Hox, 2009). However, one must keep in mind that online questionnaires have a lack of control because there is no

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social pressure to be honest (Thompson & Malaviya, 2003). The only requirement for participating in the experiment was the ability to read and understand the Dutch language.

Upon starting the survey, participants first read a short introduction about the subject of the thesis and information about the anonymous processing of their answers. The first questions that participants were asked to answer were related to their familiarity with Snapchat and their use of Snapchat. After these questions, a short description of Snapchat was provided along with an explanation that participants were about to be exposed to a screenshot on the next page.

Next, the participants were randomly exposed to one of the four experimental stimuli. The participants who were exposed to the conditions with co-creation were explained what Geofilters are and how they can be used. These participants received further instructions to imagine that they were able to actually use the provided geofilters in any way they wished to. In the conditions without creation, participants were exposed to an advertisement that was identical to the geofilter in the co-creation condition. Participants in these conditions were explained that the advertisement could come up randomly in their Snapchat and were asked to imagine that this would happen to them, as they would use the app. In both the co-creation and no co-creation condition, participants could only proceed further after 20 seconds to provide enough time to read the instruction and to process the advertisements. The advertisement could not be revisited to mimic real life advertising on Snapchat.

After being exposed to either one of the experimental conditions, all participants were asked to answer two questions relating to the manipulation check. These questions relate to the degree to which participants thought they were creating something of value with the brand and a set of questions on how they rated the brand message. These questions are relevant as they check if the intended manipulation has succeeded with the participants.

Next, regardless of which condition they were assigned to, all participants were asked the following questions. First, they were asked about the way they processed the stimuli they were exposed to. This question was necessary to determine their motivation for information processing. Then, sets of questions relating to the degree of brand engagement and purchase intention were asked. The aforementioned questions will be discussed in detail below. Finally, questions that measure

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demographic data regarding gender, age and educational level were asked. After filling out the survey, the participants were thanked formally and their response was recorded.

3.7. Measures

In this section, it is explained in depth how the constructs that are used in the experiment are measured. The language of the experimental survey was Dutch. All of the constructs and items were converted to Dutch using the back translation approach (McGorry, 2000). The questions were translated independently to Dutch and then back to English by two different graduate degree university students. If the questions were translated back in an understandable and similar manner, the translation was successful. The complete experimental survey can be found in appendix B.

3.7.1. Independent variable

In this experiment the independent variables are the type of mobile advertisement (co-creation/regular) and the content of the brand message (functional/symbolic), which also represent the experimental stimuli. Four different advertisements were created especially for the four experimental conditions in this experiment. These were created and designed to resemble actual advertisements of Dunkin’ Donuts, as the brand already advertises on Snapchat in the United States.

The stimuli contain advertisements on Snapchat of the brand Dunkin’ Donuts, which has nearly 12.000 restaurants in 43 countries (Blonk, 2016). If participants have too strong associations based on prior knowledge and experiences with a brand, the outcome of an experiment might be biased and negatively affect the validity of the results (Keller, 1993; Field, 2009). However, using a fictional brand does not recreate a real life scenario and can also negatively affect the validity of the results. To seek a balance, Dunkin’ Donuts was chosen because, while the brand has no actual stores in The Netherlands, it does have a high degree of recognition with the target audience (Karamshuk, Noulas, Scellato, Nicosia & Mascolo, 2014; Sashittal, Demar, & Jassawalla, 2016). Furthermore, it is a low investment brand, as it mostly sells coffee and baked goods, which are more affordable for most people than, for example, expensive products of a software company (Lewis, 2016). In this way, the brand selection does not exclude people who cannot afford the products or services.

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The independent variable is controlled by means of two questions. The first question relates to the co-creation dimension. Participants were asked to what extend they thought they felt like they were creating something of value with the brand. This question is based on the description of co-creation provided by Pongsakornrungsilp and Schroeder (2011). The second question relates to the functional and symbolic brand message content. This was controlled by presenting participants with 8 questions relating to both function and symbolic attributes of a brand message. These questions are based on the description of both concepts by Cable and Graham (2000), Lievens and Highhouse, (2003), De Chernatony and Harris (2000), Bhat and Reddy (1998) and can be rated on a scale of one (strongly disagree) through seven (strongly agree). These can be viewed in appendix E.

3.7.2. Dependent variables

This experiment contains one mediating variable and two dependent variables. Each variable is measured by a set of items, on which the participant can rate the construct. How the variables are constructed and the items are generated is explained below and presented in appendix E. Furthermore, the variables are tested on their reliability by calculating the Cronbach’s alpha and conducting a factor analysis. A Cronbach’s alpha score that is higher than 0,60 proves that a scale is reliable; a score of 0,80 indicates that scale is very reliable (Boeije, ‘t Hart & Hox, 2009). A factor analysis tests if the items of a scale measure one and the same dimension. If there is one dimension with an Eigenvalue higher than 1, the scale is reliable (Field, 2009).

Motivation for information processing. This variable is both a dependent and mediating variable between exposure to the experimental conditions and brand engagement. The motivation for information processing is measured with a six-item scale, with three questions about the central route (e.g. ‘the information given in the advertisement is useful to me’) and three about the peripheral route of the ELM (e.g. ‘I found the advertisement enjoyable’). Participants can rate the items on a 7-point Likert scale from one (strongly disagree) through seven (strongly agree). Maclnnis, Moorman & Jaworski (1991) developed the scale that was based on Petty, Cacioppo and Schumann (1983). The motivation for information processing scale was internally consistent and proved to be a reliable scale (α = 0,898). The items together have an Eigenvalue of 4,01 and explain 66,87% of the variance.

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Brand engagement. Brand engagement is a variable that is operationalized by Hollebeek (2011), who created a scale of 10 items that measures brand engagement. Participants can rate the items on a 7-point Likert scale ranging from one (strongly disagree) through seven (strongly agree). The brand engagement scale was internally consistent and proved to be a very reliable scale (α = 0,919). The items together have an Eigenvalue of 3,97 and explain 79,06% of the variance.

Purchase intention. This variable is measured on a three-item scale based on previous research (Dodds, Monroe & Grewal, 1991; Sweeney, Soutar & Johnson, 1999). The items (e.g. I will purchase from the shown brand) were measured on a seven-point Likert scale, ranging from one (strongly disagree) through seven (strongly agree). The three-item purchase intention scale was internally consistent and proved to be a reliable scale (α = 0,946). The items together have an Eigenvalue of 2,44 and explain 81,35% of the variance.

3.7.3. Control variables

In this experiment, demographical data was measured to get a complete profile on the participants in this experiment. Age, gender and educational level were measured. These measures were also considered as control variables in the experiment. It is argued hat age might distort the results of the proposed relationships, as mostly younger people use Snapchat (Snapchat, 2016). Also, research showed that in general males have a higher sense of engagement with brands than females (Goldsmith, Flynn & Clark, 2011; Yang & Lester, 2005). Furthermore educational level was considered because research shows that higher educated people are more critical towards advertising (Maringe & Gibbs, 2008) and this should be controlled for. Finally, familiarity with Snapchat was considered as a control variable, as unfamiliarity with the medium might distract from the purpose of the experiment (Park & Sheth, 1975). The familiarity with Snapchat was considered as a possible control variable in the experiment. It was measured with a one-item scale based on the familiarity-index scale by Lanseng and Olson (2012). The participants can answer the question ‘to what extend are you familiar with Snapchat’ on a 7-point Likert scale from one (strongly disagree) through seven (strongly agree).

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CHAPTER 4. RESULTS

The results of the experiment are presented in this chapter. First, several tests on manipulation, randomization and correlation are performed to determine if the data meets the assumptions for the main analysis that test hypotheses.

4.1. Manipulation checks

In order to test if the different experimental manipulations were successful, two ANOVA analyses were conducted to see if the experimental conditions differed significantly on the manipulations. The first ANOVA was used to determine if respondents in the co-creation condition indeed felt that they were creating value with the brand and if those in the non co-creation condition did not feel that way. Levene’s test for equal variances proved to be not significant (F (3, 157) = 2,07; p = 0,106), which indicated that the ANOVA could be performed. The ANOVA shows that the conditions with co-creation differ significantly from the conditions with regular mobile advertisements on the manipulation question (F (3, 157) = 88,773; p = 0,000). A Bonferonni post-hoc test shows that conditions 1 and 2 significantly differ from conditions 3 and 4 (Mdifference = 3,650; SD = 0,294; p =

0,000; Mdifference = 3,410; SD = 0,272; p = 0,000). Thus, the results indicate that the manipulation was

successful.

Next, another ANOVA was performed to check the manipulation of the second independent variable, namely the type of brand message. Again, Levene’s test for equal variances was not significant (F (3, 157) = 0,988; p = 0,400), which indicated that the ANOVA could be performed. Results indicate that there was a significant difference between the conditions and the type of brand message (F (3, 157) = 34,77; p = 0,000). A closer look with a Bonferonni post-hoc analysis shows that the differences between conditions 1 and 3 with a functional brand message differ significantly from conditions 2 and 4 with a symbolic brand message (Mdifference = 2,22; SD = 0,223; p = 0,000;

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4.2. Tests on randomization

To determine if the randomization to the experimental conditions was successful, the distribution of the control variables gender, age, educational level and familiarity with Snapchat over the conditions was checked. The experimental conditions were tested with the numeric control variables age and familiarity with Snapchat by means of a MANOVA. Levene’s test for equal variances proved to be not significant (F (3, 157) = 0,853; p = 0,467), thus the MANOVA could be conducted. Results show that there was no significant influence of the experimental conditions on age (F (3,159) = 0,62, p= 0,600) and familiarity with Snapchat (F (3,159) = 0,87, p= 0,454).

For the categorical control variables gender and educational level Chi-square tests were performed to analyze the distribution over the conditions. Again, results show that there was no significant difference between the conditions for gender (χ2 (3, N= 161)= 2,75, p= 0,432) and educational level (χ2 (12, N= 161)= 2,98, p= 0,996. These analyses prove that randomization was successful.

4.3. Analyses on correlations

To determine whether the control variables were randomly distributed over the dependent variables and moderating variable, several analyses were conducted that depend on the measurement level of the variables. For the categorical control variables Chi-square tests were conducted; for numeric variables Pearson’s correlation analyses were conducted. The results of these analyses also determine whether the control variables have to be included in the main analyses as covariates.

The results of these correlation analyses indicate that randomization was once again successful. Furthermore, the results show that the control variables do not need to be included in the main analyses as covariates. The results for the correlations can be found in appendix F.

4.4. Hypotheses testing

In this section, the hypotheses are tested. Hypotheses 1, 2, and 3 all contain a mediator, namely the motivation for information processing. In a mediation analysis, the relation between the dependent and the independent variable is explained by the mediating variable (Field, 2009). To test if there was indeed mediation, the Preacher and Hayes (2004) method was applied, which is also known as the

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