The mediating effect of Consumer Engagement on the relationship between Brand Activation and Intended Brand Loyalty

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Master Thesis

The mediating effect of Consumer Engagement on the relationship between

Brand Activation and Intended Brand Loyalty

Student:

Melvin Kleinmeulman - Student ID: 9667261

Executive Programme Business Studies – Marketing Strategy

Amsterdam Business School - University of Amsterdam

Supervisor:

Dhr. prof. dr. E. Peelen

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Statement of Originality

This document is written by Melvin Kleinmeulman 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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ABSTRACT

Even though companies increasingly tend to engage their customers via Brand Activation in order to create relationships beyond the purchase context, little or no research has been published on brand activation. An accurate, scientific definition of the term brand activation is yet to be defined. The aim of this study was to examine the effect of brand activation on intended brand loyalty. As no previous study has tried to explain the relationship between these two variables in combination with the mediating effect of the third variable consumer engagement. Data was collected from 267 unique members of consumer-initiated brand communities. Respondents were questioned about two different types of brand activations and their engagement levels were assessed by five different dimensions of engagement: Attention, Interaction, Enthusiasm, Identification and Absorption. From the survey, we are able to infer that the hypothesis stating brand activation has a positive effect on intended brand loyalty is supported. Secondly, we infer that consumer-engagement has a positive effect on Intended Brand Loyalty and our main hypothesis, in which was proposed that consumer engagement has a positive mediating effect on the relationship between brand activation and intended brand loyalty, also turned out to be supported. Surprisingly, activating consumers offline leads to higher levels of engagement but this higher level of engagement does not transfer into higher levels of intended brand loyalty.

Keywords: consumer engagement, brand activation, intended brand loyalty, consumer-initiated brand community, brand engagement

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1

Introduction

It goes without saying that the Internet has changed the world. It has given consumers more control and (almost) limitless options to choose and buy products from merchants. The old (one directional) way of advertising has lost a lot of its effectiveness. Consumers do not solely rely on messages passed on to them through paid advertising. “The advent of the Internet has enlarged consumers’ options for collecting unbiased product information from other consumers and exchanging their own consumption-related advice by engaging in electronic word-of-mouth” (Hennig-Thurau, Gwinner, Walsh, & Gremler, 2004, p. 39). In order to keep up with the changed consumer attitudes and behaviors, brands have had to adapt their strategies and maintain connections beyond the service encounter to maintain (active) brand loyalty (So King and Sparks, 2012). Costly loyalty programs and discount programs have been set up but these programs are not sustainable due to their high costs (Kim, Jin-Sun, & Kim, 2008; So & King, 2010). It’s the two-way interaction between

consumers and the two-way interaction between a brand and consumers which enables a strong(er) relationship (Muniz, 2001). Engaging customers through brand-related activities seems to be the way advertisers are trying to connect or built relationships with their

customers. In 2016, brand activation marketing grew to $600 billion and is estimated to reach $740 billion in 2020. Brand activation marketing accounted for 59,8% of overall marketing expenditures in 2016 and is expected to have higher spending levels than advertising and trade shows for the next four years(chiefmarketer.com).This expected growth is supported by the fact that the number of media outlets has tripled, since the early seventies, to more than 200 options.

More than ever it important for brands to deliver compelling online experiences and engage consumers in positive brand-related activities. Online Brand communities, created/initiated by brands or consumers, help to facilitate these interactions (McAlexander, Schouten, & Koenig, 2002). Although more research is being carried out on brand communities and how they can possibly lead to more (or active) brand loyalty, little is known about how brands can ‘activate' consumers within consumer-initiated online brand communities and what the effects are on Intended Brand Loyalty. An accurate, scientific definition of the term Brand Activation is yet to be defined and there is insufficient insight into what it does for loyalty. In this study the

following research question is proposed; what effect does Brand Activation in a consumer-initiated online brand community has on Intended Brand Loyalty?

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The research is structured or split up into the following chapters. First, the relevant concepts are explained. The concepts are Brand Activation, Consumer Engagement and Intended Brand Loyalty. Next, the data collection method and description of the research method is outlined. The following chapter is an overview of the main results and conclusions. The last chapter details the managerial implications, limitations and future research suggestions.

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2 Theory and Hypotheses

In this chapter, the relevant concepts from current literature, from which the hypothesis will be derived, are discussed. The objective is to lay down the theoretical foundation for the key concepts consumer engagement, brand activation and intended brand loyalty. First, online brand communities are discussed to provide the reader the context in which the research is conducted. The conceptual model, which visually illustrates the formulated hypotheses, is to be found at the end of the chapter.

2.1 Online Brand Communities

An Online Brand Community (OBC) is a virtual community in which the interactions are mediated through the Internet (Füller, Jawecki, & Mühlbacher, 2007). It is “a specialized, non-geographically bound community, based on a structured set of social relations among admirers of a brand” (Muniz and O'Guinn (2001, p. 412). OBC’s differ from other

communities due to their focus on branded goods and services (Brogi, 2014). OBC’s are marked by the following factors: brand orientation, internet usage, funding and governance Wirtz (2013). Members join an online brand community because they share a common interest, love or admiration for a brand and like to share their knowledge and passion for the brand with other community members (McAlexander, Schouten, & Koenig, 2002). This shared feeling of belonging creates a differentiation and separation between users of their focal brand and users of other brands (Fournier, 1998; Muniz & O’Guinn, 2001; Bergami & Bagozzi, 2000). The number of OBC’s grew exponentially because of the introduction of Web 2.0. Web 2.0 helps to facilitate greater and easier collaboration between Internet users. It helps to accelerate the growth of online communities to a projected $1.2 billion by 2019 (Claveria, 2016). The University of Michigan released a study that if a customer joins a brand’s OBC on average the customer will spend up to 19% more after joining the company’s OBC (Claveria, 2016).

OBC’s can be set up in two ways: company- or consumer-initiated. In consumer-initiated OBC’s information and experiences are deemed to be more trustworthy because of its high level of perceived trustworthiness. Members tend to build stronger commitments to the community, possibly resulting active loyalty (Jang, 2007). The formation of OBC’s is important because they allow brands to enter long-term relationships with consumers, the more a brand is to reflect the personality of the members (perceived community brand similarity) or is to enhance their self-esteem or social status, the more likely it is that a long-term brand relationship is to develop (Wang, 2002). Community members can be classified

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as the lurker, the newbie, the regular, the leader, the elder and the elite (Bernard, 2015). The classification is based on how much effort a member puts into the online community.

2.2 Consumer Brand Engagement

In order for brands to elicit positive responses, from their constantly evolving consumers, brands need to constantly look for new ways to engage their consumers. Postmodern consumer behavior and decision-making processes are often driven by engagement and because of that reason valuable for marketers (Gambetti, 2010). The concept of Consumer Engagement (CE) is relatively new in marketing literature and is expected to help provide higher levels of predictive and explanatory powers to consumer behavior outcomes. In recent scientific publications CE has been addressed in a variety of perspectives and due to this reason, no consensus has been reached on how to define CE. In academic journals, CE has been reported as engagement, consumer engagement with a product and brand

engagement, which makes it relatively easy to get lost in all the different definitions for CE (Dessart et al, 2016). The red thread in the majority of publications is that the authors agree on the fact that in order for engagement to exist an actor or subject is needed. Considerable differences appear when the focus/foci of engagement/dimensions are defined. Nevertheless a trend towards multiple engagement foci instead of a single focus is to be observed. Vivek et al (2012) define CE by multiple engagement foci. CE is about how intense an individual partakes in activities or offerings from an organization/brand. Both the consumer as the organization can initiate this interaction. CE is considered to be an important component of relationship marketing. Vivek et al (2012) identified four dimensions; behavioral, cognitive, affective and social dimensions. This multidimensional approach makes the CE construct more comprehensive and improves the explanatory and predictive powers of the CE construct. Possible positive CE outcomes are brand community involvement, trust, word-of-mouth and (intended) brand loyalty.

Building on Vivek’s multidimensional approach So, King, & Sparks, (2012) defined CE as “a customers’ personal connection to a brand as manifested in cognitive, affective, and

behavioral actions outside of the purchase situation”. The dimensions of interest are,

Enthusiasm, Interaction, Identification and Attention and Absorption. The covariation among the five dimensions is what accounts for CE. The conceptual definitions of CE are:

• Enthusiasm: Level of excitement and interest in a brand (Vivek, 2009)

• Interaction: the different ways consumers participate in events (both online and

offline) or have contact with the brand organization or other customers outside of the

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• Identification: the level to which consumers perceive or feel the brand and they belong

to each other (Bhattacharya et al., 1995)

• Attention: the extent of attention, focus, and connection that a consumer has with the

brand (So, King, & Sparks, 2012, p. 311)

• Absorption: A pleasant state in which describes the customer as fully concentrated,

happy, and deeply immersed while playing the role as a consumer of the brand

(Patterson, et al., 2006)

2.3 Brand Activation

Brand activation (BA) is relatively new, so few publications were found on this subject and no single or encompassing definition was to be found. On the one hand, the majority of non-academic publications seem to agree on the fact that BA is about giving people an incentive or having them participate in events or activities, feeding into their passions with the aim to create engaging and memorable brand experiences which motivates them to take desired actions. On the other hand, BA professionals tend to dispute the term brand activation and some claim that it is the same concept as CE. CE/BA is to facilitate consumer/brand interactions which are to fill the brand loyalty funnel.Failing to constantly refuel the funnel will, in the mid or long run, lead to diminished interest, commitment or brand loyalty. When it came to classifying the different types of BA it was even more difficult to find a red thread in all the different forms of BA. In order to get a better grasp of the concept of BA, an initial explorative analysis of 50 different existing BA's was made. From this first analysis, it was obvious that there was a very broad range of types of BA. Some BA's were more focused on a (specific) community and others tend to focus more on the engagement of a less specified target group. BA's primarily focusing on a contest/challenge and BA's focused on one particular sense (taste) or multiple senses were found.

Looking at BA’s in this manner without a framework did not yield any more information besides confirming the fact that there is a broad range of BA’s. In order to be able to

compare the activations and look for commonalities/similarities the BA’s have been analyzed based on the following components/items:

• Objectives activation; whether this is trial, awareness, interest or loyalty? • Parties involved; who participates in the activation?

• Carriers of activation: which means help to communicate/transfer the message of the activation?

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As stated earlier, from the first analysis of the dataset patterns emerged through the use of open coding (Strauss and Corbin, 1990) but it was not until after the second sweep of data, using the framework discussed earlier when clearer patterns started to emerge. From these patterns, categories/labels were formed to describe the different BA's. The results of the executed analysis are to be found in Appendix 1 where the campaigns have been categorized under one of the following labels: demo (11), brand utility (22), digital (9), experiential (15), in-store (15), mobile (15), packaging (2), product (7), promo (9), PR-stunt (25), sampling (7), shopper (6) and social media (30). The numbers behind the categories indicate how many times they have been counted in the analysis of different BA's. From the executed analysis two types of BA’s were to be extracted. First, BA’s which were initiated and executed online or with an online follow-up (when it was an offline experience) were found. This type of BA can be among members within a specified brand community, among (potential) consumers outside of a brand community or among a combination of both groups. The participants are activated by inviting them to create their own content, further develop or provide feedback on the content given to them by the brand of interest. Furthermore,

participants were encouraged to share the results/objects of the activation with members and non-members of the brand community.

The other type of BA was that of a real-life (indoor or outdoor) experience(s), aimed at members and non-members of a brand community. The majority of these campaigns were about brand utility. In those campaigns, the objective was to have participants to experience the product attributes (tangible or intangible). Experiencing product attributes can cause consumers to start believing in the brand and what it stands for. Identification of the two types of BA’s made it possible to investigate the possible influence of BA on IBL. Both BA types used PR-stunts and social media as means to spread or transfer the BA and both had the brand as starting point. The previous steps led to the following definitions of the two types of BA used in this study:

• Activation type A (BAA): online contests (primarily) activating participants (with or without collaborators within a community) by means of user-generated content;

• Activation type B (BAB): an immersive and predominantly offline (live) experience, allowing participants to experience product attribute(s) intended to increase or strengthen brand connection;

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2.4 Loyalty

Oliver (1999) defines loyalty as “a consumer who rebuys or re-uses a product or service and has little to no interest in buying or using another offering”. The two important relationship dimensions are behavior (purchase/usage) and attitude (how a customer feels about a product). For any business to be sustainable it will need consumers to be satisfied with the product or service. And more important, consumers who are returning to repurchase the product or service. Reichheld (1996) argued that it is cheaper to retain consumers than to go out and find new consumers. Retaining customers helps reducing marketing costs, continues profit and provides a strategic advantage. Jacoby and Chestnut (1978) were the first ones to prove empirically that inferring loyalty or disloyalty only based on re-purchases from

consumers does not hold. Even though they are linked to each other, one does not automatically translate into another. Consumers can be loyal because of a lack of

alternatives or disloyal because they switch between a fixed set of small alternatives. Oliver’s (1999) approach is more holistic when it comes to loyalty. He identified four phases of

loyalty: cognitive, affective, intentional and action loyalty (commitment to act and overcome obstacles). Cognitive loyalty is labeled as the first level of loyalty. Consumers make a cost and benefits analysis for the brand of interest before purchase. The brand of interest is part of a set of different brands which are all suitable for satisfying the consumer's need. Affective loyalty is when consumers are emotionally attached to a brand. This emotional attachment does not automatically imply that they are fully committed to buying one brand (Sawmong &Omar, 2004). On the intentional level, the transfer from emotional attachment to

commitment is made. Intentional loyalty is when a consumer is willing to (re)purchase or recommend a brand (Vera, 2017). In this study ‘(brand) commitment’ is regarded as an antecedent of brand loyalty behavior (Knox and Walker, 2001). Action loyalty is when a customer repurchases services and products out of habit and a strong emotional link to the brand exists. Consumers who can be classified under action loyalty exhibit a high level of fortitude (personal determinism) and social support at a personal and institutional level (Oliver,1999).

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2.5 Conceptual

model

Figure 1 Research model

In the previous chapter, the variables of this study have been discussed. Bringing all the variables together yields the conceptual framework as displayed in figure 1. This model shows the earlier proposed positive effect of Brand Activation (BA) on Intended Brand Loyalty (IBL) visually. This effect is in later analysis referred to as the direct effect. The effect BA has on Consumer Engagement (CE) and CE’s effect on IBL is referred to as the indirect effect. CE is split up into 5 different dimensions. Brand activation (in the context of the thesis) was limited to two types of activation. The individual effects of the different types of BA’s (and for all the following hypotheses) are reported in the results/conclusion section (chapter 6). The main hypothesis for which support was to be found was:

H1: Brand Activation within a consumer-initiated brand community has a positive effect on Intended Brand Loyalty.

The second hypothesis was formulated to find support for the effects BA has on CE. As stated earlier, the CE construct used in this study consists of five different dimensions on which BA can have an effect. Individual effects of the different types of BA’s on the individual dimensions of CE are reported in the results/conclusion section. (chapter 6)

H2: Brand Activation within a consumer-initiated brand community has a positive effect on Consumer Engagement.

Brand Activation

Interaction

Intended Brand Loyalty

H2 H5

Identification

Absorption

Enthusiasm

Attention

H3a H3b H3c H3d H3e Consumer Engagement H1 H4a H4b H4c H4d H4e

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As we know little of BA and its effect on CE, the following hypotheses are about investigating the relationship between BA and the individual dimensions of Consumer Engagement:

H3a: Brand Activation within a consumer-initiated brand community has a positive effect on Consumer Engagement dimension Identification.

H3b: Brand Activation within a consumer-initiated brand community has a positive effect on Consumer Engagement dimension Absorption.

H3c: Brand Activation within a consumer-initiated brand community has a positive effect on Consumer Engagement dimension Enthusiasm.

H3d: Brand Activation within a consumer-initiated brand community has a positive effect on Consumer Engagement dimension Attention.

H3e: Brand Activation within a consumer-initiated brand community has a positive effect on Consumer Engagement dimension Interaction.

The next set of hypotheses are about testing the relationship between the individual CE dimensions and IBL. From So, King, & Sparks, (2012) we know that CE can enhance brand loyalty. Their study was conducted in the tourist industry, here the effects are measured in two different contexts.

H4a: Consumer Engagement dimension Identification has a positive effect on positive effect on Intended Brand Loyalty within a consumer-initiated brand community.

H4b: Consumer Engagement dimension Absorption has a positive effect on positive effect on Intended Brand Loyalty within a consumer-initiated brand community.

H4c: Consumer Engagement dimension Enthusiasm has a positive effect on positive effect on Intended Brand Loyalty within a consumer-initiated brand community.

H4d: Consumer Engagement dimension Attention has a positive effect on positive effect on Intended Brand Loyalty within a consumer-initiated brand community.

H4e: Consumer Engagement dimension Interaction has a positive effect on positive effect on Intended Brand Loyalty within a consumer-initiated brand community.

The last hypothesis to be tested is:

H5: The 5 Consumer Engagement dimensions combined have a positive on Intended Brand Loyalty within a consumer-initiated brand community

As we did not know much about the different Brand Activation types beforehand and

no existing academic literature to point in a specific direction (positive or negative

effect) no specific hypotheses were formulated on the Brand Activation types. In the

results section of this study the effects of the types on CE and IBL will be

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3

METHODS

3.1 Research Design

The methodological choice for this research was that of a multi-method quantitative study. A quantitative research design fits best with the deductive research approach because the research was conducted to explain the relationship between brand activation and brand loyalty numerically (Saunders, 2016). In order to be able to test the hypotheses, quantitative data was collected through the use of a survey. The used method of data gathering was convenience sampling. The data was collected from adult English-speaking members of consumer-initiated brand communities. An example of a consumer-initiated brand community would be the KitchenAid Kreations and Community page on Facebook where fans of Kitchen Aid products share pictures of bought products and share recipes made with KitchenAid appliances. The research was executed on research platform Qualtrics. Respondents were able to complete the survey by using a desktop computer or by using a mobile phone. Data generation was done by presenting respondents two different types of brand activation. Their responses were recorded by using Likert scales because a Likert scale yields ordinal data which can be analyzed using descriptive statistics. Screening questions were used to check whether the right respondents were selected. When respondents showed little or no interest in the first brand activation, the second brand activation type was presented to them. If the respondent, again, showed little or no interest in the activation the respondent was routed to the demographics part of the survey, which consisted of two questions and these were the last questions of the survey. Before the survey was distributed there was a soft-launch to test the survey. The soft-launch was executed to ensure the outcome would meet the objectives of the survey. Question comprehension, typos and routing issues arose from the soft-launch and were tackled as a result of the test. The time horizon was cross-sectional as the survey was conducted from November 20, 2017, until December 5, 2017. In that time frame, 297 respondents started the survey and 267 unique respondents completed the survey (response rate 89%). The response rate is high due to the fact that 130 respondents were bought from Qualtrics and these respondents received a financial incentive when they completed the survey. Repeated follow-up messages were sent to the other (non-Qualtrics) respondents who had not completed the survey. 48,9% of the respondents were male and 50,2% was female. The remaining 0,9% stated that they were transgender. The majority of the respondents (62%) were in the age bracket 25 – 44 years.

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3.2 Measurement of variables

3.2.1 Consumer Engagement

In order to be able to measure Consumer Engagement, the scales developed by So, King, & Sparks (2013) were utilized. According to these authors who, similar to Vivek, approach CE multi-dimensionally, CE consists of five different dimensions. The dimensions of interest are, Enthusiasm, Interaction, Identification Attention and Absorption. As a result, their

measurement tool consists of 5 x 5 items scales, using five-point Likert scales enabling to gain insight in CE. The range of the scale items went from strongly agree to strongly disagree. Minor adjustments to the scales were made to fit the context of the survey. For example, instead of using the Identification scale item; “When someone criticizes my brand, it feels like a personal insult”. An adjustment was made into; When someone criticizes my brand of interest, after the online contest, it feels like a personal insult. The Cronbach’s α for all the dimensions combined of CE = .93. The Cronbach’s α for the individual scale item can be found in table 2.

3.2.2 Intended Brand Loyalty

Oliver’s definition of loyalty contained two elements: attitude and behavior (repurchase). In this study, only half of this definition is investigated. The main aim is to research what the effects of CE and BA are on consumer’s loyalty attitude; especially future loyalty intentions are of main interest. IBL was measured by two five-point item scales utilized by Vera (2017). The scale items helped to measure a consumer’s willingness to (re)purchase or recommend a brand. The items were slightly adjusted to fit the context of the questions in the survey. An example of an adjustment is: “Next time I'm going to buy this brand again”, was changed into “After participating in a brand activation activity at my supermarket, I will continue to buy from them again” (Cronbach  = .95). The scales had to be recoded because the way the scales were set up led to a counter-intuitive interpretation of the results. Initially the scale items went from extremely likely to extremely unlikely, meaning that higher scores would lead to a

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3.2.3 Brand Activation

Brand Activation is when a brand is giving its customers an incentive or has them to

participate in events or activities, feeding into their passions with the aim to create engaging and memorable brand experiences, which motivates them to take desired actions. These activities can take the form of a gift-wrapped billboard that gets your attention at a shopping center, the side-stage at a music festival you are attending, a TV-show-themed amusement park or an online interview, using questions from the audience which are answered on Twitter. BA was measured by measuring the respondent’s reactions to two different case studies, representing the main categories of BA. After identifying the different types of BA, a first draft of the BA descriptions was made and tested on a small sample of respondents. The objective of this test was to discover whether the descriptions were easy to comprehend and were written in such a manner that they would elicit workable associations across different OBC’s (as the survey was to be distributed in a wide variety of OBC’s). In this study, BA was split up into two types: Activation type A (BAA) which were online contests (primarily)

activating participants (with or without collaborators within a community) by means of user-generated content. The second type was Activation type B (BAB) which was an immersive and predominantly offline (live) experience, allowing participants to experience product attribute(s) intended to increase or strengthen the brand connection. The two activation types were a result of the analysis described in paragraph 2.3. Deciding on how to test the different BA’s a choice was made to present written BA’s instead of BA’s with pictures because in the latter case the ‘creative execution’ possibly could influence the respondents (Holland, Jane, et al, 2015). It would be easier to create associations for an offline BA than for an online BA, differences in the outcomes would then largely be explained by this fact. Giving descriptions of the BA’s would diminish the changes from this to happen. The descriptions were tested on a small sample of (potential) respondents and the feedback was used to improve the

descriptions.

In the final survey BAA respondents were presented the following: A member of your Facebook group, centered around your brand of interest, asks all members of the group to participate in a two-part contest. The first part is that you are asked to come up with creative content related to your brand of interest. Creative content in this context would be, taking brand-related selfies, building a lookbook, drawing or painting visuals, writing a story/essay, creating memes etc. In return, you are eligible for winning a redeemable coupon for a product or service of your brand of interest. The second part of the online Facebook group contest is that you are asked to vote for your favorite, creative content submission, among

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world. In the survey, these two parts of BA were asked in two different questions. The questions contained the important elements of BAA, it being an online contest and making use of user-generated content.

For BAB, respondents were presented the following: You and your friend are invited to participate in a cooking event at your local supermarket, at which a well-known chef will help you to create a unique dish. The dish will exclusively consist of products sold at the local supermarket and/or bearing the local supermarket’s name. After the event, you will get a book signed by the well-known chef and/or you upload photos or videos on a social media platform. This question also contained the important elements. BAB is offline and allows participants to experience the brand with an emphasis on brand/product attributes in order to increase brand connection. The choice for a supermarket was deliberate because in order for respondents to be able to imagine BAB an activity should be chosen all the respondents at least could imagine themselves doing (due to the fact that there were no pictures).

In the survey respondents were asked if they had participated in an online or offline BA. If they had never engaged in such an activity then they were asked how likely it would be for them to engage in online or predominantly offline BA’s. The five-point scale items of the construct differed when respondents were asked about if they had ever engaged in a BA. In those cases, scale items would range from a great deal to not at all. When a respondent’s willingness to engage was measured the scale items would range from a great deal to not at all. The measured Cronbach  = .923

3.2.4 Control variables

The control variables for this study were gender and age. These items were included in the last part of the survey.

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4

RESULTS

4.1 Preliminary checks

At first, a data-ordening procedure was executed. For every analysis executed the underlying assumptions were tested and where necessary adjusted. For instance, when the normality distribution assumption for both BA’s was violated, two answer categories were combined to meet the test of normality.

The total number of unique respondents for the data set used was 267 respondents. The majority of respondents completed the survey for both activation types. Due to the routing of the questionnaire it was possible for respondents to provide their opinions on one or two different BA’s types or state that they were not interested in BA at all. So that’s why a total number of 420 BA’s was recorded. The difference, between the total number of BA’s (420) vs 384 recorded BA’s, is due to the fact that the responses of 36 respondents could not be classified as BA type A (BAA) or BA type B (BAB) respondents. Three dummy variables were created to split up the respondents for the different activation types for further analysis. BA type A was recoded to 1, BA type B was recoded to 2 and No BA was coded to 0.

Table 1 Distribution of Brand Activations

Types of Brand Activation Frequency Percent Valid Percent Cumulative Percent

No Brand Activation 36 8,6 8,6 8,6

Brand Activation A 188 44,8 44,8 53,3

Brand Activation B 196 46,7 46,7 100

Total 420 100 100

Secondly, the Cronbach Alpha’s were computed to measure the internal consistency of the scales used. The Alpha’s scores were computed for all the variables of interest combining both activation types (A and B). BA consisted of 4 scale items (α = .86) The CE construct consisted of 5 different dimensions and on average 5 different subscales (46 items; α = .93).

The Alpha’s scores for the subscales were: Attention (α = .89), Identification (α = .89),

Absorption (α = .88), Enthusiasm (α = .90), Interaction (α = .90). IBL consisted of 6 items (α

= .86). All variables (listed in table 3) scored above the rule of thumb limit of .70.

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As stated before the respondents were split up into two BA type groups. An independent samples t-test was executed in order to compare IBL in BAA and BAB type conditions.

Table 2 Overview of Independent sample t-test

Brand

Activation A Activation B

Variable

M

SD

M

SD

t-test p

Attention_

3.98 0.78 3.79 0.87 1.91 .057

Identification

3.66 0.86 3.35 1.06 3.18 .002*

Absorption

3.61 0.88 3.09 1.15 4.90 .000*

Enthusiasm

3.90 0.83 3.56 0.95 3.58 .001*

Interaction

3.86 0.90 3.56 1.03 2.95 .003*

Engagement 5 dimensions 3.77 0.77 3.39 0.93 4.32 .000*

Intended Brand Loyalty

2.09 0.79 2.05 0.78 0.43 .666

N (BAA)= 188, N(BAB)= 196 , * p < .05, SD = standard deviation

BAA scored higher on absorption with the brand of interest (M= 3.61, SD= .88) than BAB (M= 3.09, SD= 1.15), meaning that BAA has a bigger effect on mediating variable absorption. The difference, .52, CI (0,307040, 0,717966), was significant t(381) = 4.90, p < .001. This was the only t-test where the effect-size was strong (d = .83).

A medium effect size (d=.45) was found for BAA and. On average BAA scored higher on the five dimensions of CE (M= 3.77, SD= 0.77) BAB (M= 3.39, SD = 0.93). The difference, .38, CI (0,205318, 0,547398) was significant t(379) = 4.32, p < .001.

The independent t-test for Attention and Loyalty produced different results. On a first glance BAA seemed to score higher on CE dimension Attention and dependent variable IBL. For BAA the Attention scores were (M=3.98, SD= 0.78) which were higher than BAB (M= 3.79, SD= 0.87). The difference, 0.19, CI (.1197, .5064), was not significant t(263) = 1.91, p = .057. The same conclusion can be drawn for BAA in relation to IBL. Again, BAA scored higher on IBL (M= 2.09, SD= .79) than BAB (M= 2.05, SD= .78). The difference, .04, CI

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(-0,124997, 0,195466), was also not significant t(367) = 0.43, p = .666. For both tests the effect size was small (Attention (d =.23)) or very small (Loyalty (d =.05)).

For CE, dimensions Identification, Interaction BAA scored higher than BAB. All the

differences proved to be significant p < .001 but the effects were either small or very small. The results from table 2 also seem to indicate that BAB scores higher on engagement but does not lead to higher engagement.

Thirdly, the means, standard deviations and correlations were computed for both types of activation and listed in the table below. A Pearson test correlation coefficient was computed to assess the relationship between BA, CE and IBL. This was computed for all the variables of interest. From table 3 we are able to conclude that CE dimension Interaction is related the strongest to value IBL. The correlation coefficient is r = .646 and p < 0.001, indicating a strong positive relationship, meaning an increase in interaction was correlated with an increase in IBL. All other items were positively related to each other, especially the CE dimensions amongst each other. The weakest relation is between BA and IBL r = .323 and p < 0.001.

Table 3: Means, Standard Deviations, Correlations

Variables M SD 1 2 3 4 5 6 7 1. Brand Activation 1.84 .95 (.923) 2. Attention 3.98 .78 .232** (.892) 3. Identification 3.66 .86 .287** .783** (.888) 4. Absorption 3.61 .89 .182** .719** .795** (0.883) 5. Enthusiasm 3.90 .83 .258** .763** .732** .742** (.904) 6. Interaction 3.86 .90 .258** .680** .697** .719** .733** (.896) 7. Intended Brand Loyalty 2.01 0.79 .323** .547** .503** .444** .586** .646** (.958) Note: Reliabilities are reported across the diagonal

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4.2 Mediation Analysis

The mediation analysis was executed to investigate the hypothesis that Consumer

Engagement mediates the effect of brand activation on intended brand loyalty. In line with the conceptual model, model 4 from the SPSS macro of Hayes (2012) was selected.

First, a mediation analysis was carried out for the combined BA (n=369). From this analysis, we were able to conclude that there was a significant direct effect of BA on IBL through CE,

b= .38, p < .001. R2 _{= .155, meaning that the model explains 15,5% of the variances in IBL.}

Both the indirect effect of BA on CE (b = .16, p <.0004) and the indirect effect of CE on IBL were significant (b = .45, p <.001). The total effect of BA on IBL was c = .382 p <.001, while the direct effect was c’ =0.16, p <.001. The fact that the direct effect was significant indicates that there is no complete mediation of CE. Partial mediation was significant judging from the Sobel-test z = 7.17, p < .001. From this, we are able to conclude that CE is a mediator in the relationship between BA and IBL. These results support the mediational hypothesis. The total effect of BA on IBL was .382 p<.001, which indicates that there is no full mediation. Partial mediation was significant judging from the z-score= 7.17, p<.001. Figure 2 shows the effects visually, when values are followed by an asterisk this means the effects are significant at p<.05

Figure 2 Effects of brand activation (combined) and consumer engagement on intentional brand loyalty

The next step in the analysis was to look at the individual brand activations. For BAA (=174) there was a significant direct effect of BAA on IBL through CE, b = .43, p <.001. R2 _=.17,

meaning that the model explains 17% of the variances in IBL. This is slightly higher than in our previous analysis (R2 _{=.155). The indirect effect of BA on CE (b =.51, p <.001) and the}

indirect effect of CE on IBL were significant (b = .61, p < .001). The total effect of BA on IBL was c = .43 p < .001, while the direct effect was c’ = 0.12, p > .08. The fact that the direct effect was not significant (after adding CE) indicates that there is complete mediation of CE. The Sobel-test z = 7.17, p < .001 was significant. CE is to influence IBL and if BA is to have an effect on IBL this is through CE. Figure 3 shows the effects visually, when values are followed by an asterisk this means the effects are significant at p<.05.

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Figure 3 Effects of brand activation (type A) and consumer engagement on intentional brand loyalty

For BAB (n=195) there was a significant direct effect of BAB on IBL through CE, b = .43,

p <.001. R2_{= .14 meaning that the model explains 14% of the variances in IBL. The indirect}

effect of BA on CE (b = .50, p <.001) and the indirect effect of CE on IBL were significant (b = .42, p < .001).The total effect of BA on IBL was c = .35, p <.001, while the direct effect was c’ = 0.14, p < .02. The fact that the direct effect was significant indicates that there is partial mediation of CE. Partial mediation was significant judging from the Sobel-test z= 5.23, p<.001. From this, we are able to conclude that CE is a mediator in the relationship between BA and IBL. Partial mediation was significant judging from the z-score= 5.23, p<.001. BAB has an effect on IBL but the effect is mediated by CE. In figure 4 the effects are again shown visually; significant values have an asterisk at p<.05

Figure 4 Effects of brand activation (type B) and consumer engagement on intentional brand loyalty

Next, an analysis on the individual level of dimensions was conducted, again we used PROCESS model 4, which allows us to use five mediators, in this case, the five mediators are the five dimensions of CE.

For BAA the indirect effect of BA on the individual CE dimensions Attention, Enthusiasm, Absorption, Interaction and Identification were significant. For CE on IBL only Interaction turned out to have a significant effect. All the other dimensions were not significant (see table 8). The direct effect c’ = .09, p > .235 which makes the effect non-significant and we should speak of full mediation. Attention, Enthusiasm and Interaction have an effect on IBL and BAA

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Judging from the Sobel-test Attention (z = 2.32, p <.02), Enthusiasm (z = 2.12, p < .03) and

Interaction (z = 2.73, p < .01) were significant mediators. Significant effects (at p<.05 ) can

be found in figure 6 with an asterisk behind the value.

Figure 5 Effects of brand activation (type A) on Intended Brand Loyalty through individual dimensions of Consumer Engagement

BAB did have a significant effect on the individual CE dimensions: Attention, Identification, Absorption, Enthusiasm and Interaction. For BAB, the only significant mediator on IBL was CE dimension Interaction (b =.52, p < 001.) All the other dimensions seem to have a higher p-value >.05.The total effect of BA on IBL was c = .39, p <.001, while the direct effect was c’ = 0.18, p < .0082. The fact that the direct effect was significant indicates that there is partial mediation effect of CE. Judging from the Sobel-test partial mediation was only significant for Interaction (z = 4.63, p< .0001). Significant effects (at p<.05 ) can be found in figure 6 with an asterisk behind the value.

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The indirect effects of BA (combined) on the individual CE dimensions is significant

for Attention (b =.43, p< .001), Identification (b =.41, p< .001), Absorption (b =.34, p< .001), Enthusiasm (b =.41, p< .001) and Interaction (b =.41, p< .001). BA combined on IBL also was significant (b =.18, p< .0003). CE dimension Interaction (b =.43, p< .001) and Absorption (b =-.17, p< .02) were the only mediators to have a significant effect on IBL. The total effect of BA on IBL was c = .43, p <.001, while the direct effect was c’ = 0.18, p < .0003. The fact that the direct effect was significant indicates that there is partial mediation of CE. Judging from the Sobel-test partial mediation was significant for Absorption (z = -2.08, p< .04) and Interaction (z = 4.63, p< .0001). Significant effects (at p<.05) can be found in figure 7 with an asterisk behind the value.

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5 DISCUSSION / CONCLUSION

5.1 Main findings

A

cross-sectional study, using the non-probability sampling method

convenience-sampling,

has been conducted among 267 unique members of Online Brand Communities (OBC’s).

Building on So, King and Sparks (2012) the objective of

this study

was to contribute to existing studies by not only looking at Consumer Engagement’s (CE) effect on Intended Brand Loyalty (IBL) but also to investigate the effect Brand Activation (BA) has on CE and CE’s mediating effect. Like many other authors in this field, the importance of engaging customers beyond the purchase was acknowledged, purchase-related antecedents like service or satisfaction were not taken into account to measure intended brand loyalty. The findings of this study suggest that BA within an OBC has a positive effect on intended brand loyalty and that this effect is mediated by Consumer Engagement. When brand activation is divided into two categories (offline vs online) the results for each activation type were different. BAA (online activation) scored higher than BAB (offline activation) on CE.

Surprisingly, the results of the survey indicated that there is a difference in the level of effect on CE but there is no difference between BAA and BAB when it comes to IBL. The same level of IBL can be achieved through offline or online activation. In the following paragraphs, possible justifications of the results presented/found will be explored.

Until this study, no academic paper has focused on the relationship between BA and IBL and especially CE’s role in that relationship. A great number of studies can be found on CE focusing on defining (or exploring) the concept of CE without empirical testing (Hollebeek, 2011). So, King and Sparks’ (2012) study helped to extend the theoretical understanding of how CE is to affect IBL beyond the purchase situation and it was the first study in which the CE construct was tested empirically. As useful as this study proved to be, it could only imply an association between CE and IBL and not a causal relationship. More important So, King and Sparks did not investigate the effects of BA on CE.

As simple as it was to find relevant academic literature on CE, as difficult it turned out to be to find academic literature on BA. Even when BA’s share in advertising spending has been growing exponentially the last few years. It was difficult to find one encompassing definition of BA or its effect loyalty, trust or satisfaction. Available literature is non-academic and focuses on the tactical aspects of BA rather than on the added value of BA for the overall brand management strategy of an organization. Information on BA is scarce and fragmented

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so it is safe to say that the BA concept is heavily underdeveloped. The few authors writing about the subject do not seem to agree on the term because BA is also listed as brand engagement or marketing activation. Before being able to test the different hypotheses, a working definition had to be formulated, which is an interpretation of definitions currently being used by BA professionals and by authors in non-academic publications. After the definition, an analysis was made of different kinds of BA’s from which two BA types were selected. One was a BA type which primarily activated participants online, making use of the content participants created. The other type was that of an immersive offline experience enabling participants to experience the brand.

When looking at the differences between the two different BA types, BAA seemed to score higher than BAB on all the different dimensions of CE (including the whole CE construct), meaning that BAA has a higher effect on CE than BAB. When it came to IBL, BAA also scored higher on IBL than BAB but this difference was not significant. From this outcome, we are able to conclude that it does not make a difference which type of BA a brand manager is to choose because the outcome on IBL would be the same. The managerial implication of this finding is that managers could reach the same levels of IBL with more reach and at a lower cost. On the flip side managers should be aware of the fact that the level of

engagement will be lower.

The direct relationship between BA and IBL was investigated in which BA was not split up into different types but the two different kinds of brand activations that were defined were combined. The results showed the mediating effect of CE (as a whole construct) between BA and IBL. So, King and Sparks’ (2012) conclusion that CE beyond purchase has a positive effect on intended brand loyalty was supported. Evidence was found that CE’s effect on IBL was not only valid in a tourism industry context but also in other contexts (in this study a supermarket and an online consumer-initiated Facebook brand group).

Secondly, the relationship between the two different BA’s and CE was investigated. The second hypotheses in which we proposed that BAA would have a positive effect on CE was supported. No support was found for BAA’s effect on IBL. In this case, a full mediating effect of CE on IBL was found. BA was not of any significant influence on IBL. Consumers’ brand loyalty intentions do no tend to go up because of the activation but through the level of engagement triggered by the activation. BAB’s positive effect on CE was supported and also evidence was found for its positive relationship with IBL. The justification for this can be

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more immersive and engaging activity, and in that case increased loyalty intentions are to be expected.

The analysis for the different types of BA’s on the individual CE dimensions yielded the following results: BAA only seem to have a significant effect on CE dimension Interaction but the direct effect of BA on IBL was insignificant. This was to be expected because of the way the BA was presented to the respondents. Respondents were asked if they would

participate/vote in a contest within their OBC, which is intended to trigger the interaction. Again, for BAA the effect of BA on IBL was fully mediated by CE. We should be careful to label this as a full mediation because the full mediation consisted of 3 different mediators (Attention, Enthusiasm and Interaction) which had a significant effect. The effect of BAB on IBL was significant and Interaction turned out to be the most significant factor. The results seem to suggest that human interaction is the most powerful factor in engaging customers with the brand. In order for brand managers to activate consumers the element of (human) interaction is of crucial importance, whether these interactions are with the brand itself or among consumers. This is in line with Algesheimer et al (2004) who argue that active engagement in OBC’s in the form of participation, sharing or giving recommendations translates into brand loyalty.

5.2 Limitations and Future Research

After evaluating the findings and research process a couple of limitations need to be brought to the attention of the reader. A limitation of the study is the way the variable Brand Activation was operationalized. Brand Activation ranges a broad spectrum of activities, the used binary division in activities (online vs offline) may seem to be too broad. The scale proposed in this research does not measure real behavior, but rather the consumer’s perception of his own repeat purchasing behavior. Loyalty intentions do not always transform into actual

repurchasing behavior. Also, the non-probability sampling method, convenience sampling, is due to its nature prone to bias (being based on availability). For future research, it is

recommended that first a comprehensive definition of BA is formulated. Second, an

extensive categorization of BA activities would make it possible to gain more insight on the effects BA has on the mediating effect of CE on IBL. It would give managers an overview of (extra) tools to engage their customers.

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6 REFERENCES

• Algesheimer, R., Dholakia, U. M., & Hermann, A. (2004). Interplay between

Brand and Brand Community: Evidence from European Car Clubs. SSRN

Electronic Journal. doi:10.2139/ssrn.534542

• Belleghem, S. V. (2012). The Conversation Company: Boost Your Business

Through Culture, People and Social Media. Kogan Page.

• Belleghem, S. V. (2015). Marketing: de nieuwe principes. Leuven:

LannooCampus.

• Bergami M. & Bagozzi R.P. (2000). Self categoritazion, affective commitment

and group self-esteem as distinct aspects of social identity in the organization,

British Journal of Social Psychology, 39, 555-577.

• Bernard, H. R. (2015). Handbook of methods in cultural anthropology.

Lanham, Md.: Rowman & Littlefield.

• Berry, L. L. (1995). Relationship Marketing of Services: Growing Interest,

Emerging Perspectives. Journal of the Academy of Marketing Science, 23(4),

236-245. doi:10.4135/9781452231310.n6

• Brodie, R. J., Ilic, A., Juric, B., & Hollebeek, L. (2013). Consumer engagement

in a virtual brand community: An exploratory analysis. Journal of Business

Research,66(1), 105-114. doi:10.1016/j.jbusres.2011.07.029

• Brogi, S. (2014). Online Brand Communities: A Literature Review. Procedia -

Social and Behavioral Sciences, 109, 385-389.

doi:10.1016/j.sbspro.2013.12.477

• Chan, K. W., & Li, S. Y. (2010). Understanding consumer-to-consumer

interactions in virtual communities: The salience of reciprocity. Journal of

Business Research, 63(9-10), 1033-1040. doi:10.1016/j.jbusres.2008.08.009

• Claveria, K. (2016, Sept. & oct.). 13 stunning stats on the ROI and growth of

online communities. Retrieved December 22, 2017, from

http://www.customerexperienceupdate.com/

• Dessart, Laurence, et al. “Capturing consumer engagement: duality,

dimensionality and measurement.” Journal of Marketing Management, vol. 32,

no. 5-6, 2016, pp. 399–426., doi:10.1080/0267257x.2015.1130738.

• Fuller, J., Jawecki, G., & Muhlbacher, H., 2007. Innovation creation by online

basket- ball communities. Journal of Business Research, 60 (1), 60–71.

• Hansen., Amanda, and Amanda Hansen Amanda Hansen Is Senior

VP-marketing at MMI Agency in Houston. Follow View All Articles by This Author.

"How to Create Brand Activation that Fosters Engagement." Ad Age. N.p., 24

June 2015. Web. 28 June 2017.

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

Electronic word-of-mouth via consumer-opinion platforms: What motivates

consumers to articulate themselves on the Internet? Journal of Interactive

Marketing, 18(1), 38-52. doi:10.1002/dir.10073

• Holland, Jane, et al. “Is a picture worth a thousand words: an analysis of the

difficulty and discrimination parameters of illustrated vs. text-Alone vignettes in

histology multiple choice questions.” BMC Medical Education, vol. 15, no. 1,

2015, doi:10.1186/s12909-015-0452-9.

(29)

Validation. Journal of Interactive Marketing,28(2), 149-165.

doi:10.1016/j.intmar.2013.12.002

• Jacoby, J., & Kyner, D. B. (1973). Brand Loyalty vs. Repeat Purchasing

Behavior. Journal of Marketing Research, 10(1), 1. doi:10.2307/3149402

• Jang, H., Ko, I., & Koh, J. (2007). The Influence of Online Brand Community

Characteristics on Community Commitment and Brand Loyalty. 2007 40th

Annual Hawaii International Conference on System Sciences (HICSS07).

doi:10.1109/hicss.2007.544

• Jang, H., Ko, I., & Koh, J. (2007). The Influence of Online Brand Community

Characteristics on Community Commitment and Brand Loyalty. 2007 40th

Annual Hawaii International Conference on System Sciences (HICSS07).

doi:10.1109/hicss.2007.544

• So, K. K. F., C. King, and B. Sparks. "Customer Engagement With Tourism

Brands: Scale Development and Validation." Journal of Hospitality & Tourism

Research 38.3 (2012): 304-29. Web.

• Kozinets, R. V. (1999). E-tribalized marketing?: the strategic implications of

virtual communities of consumption. European Management Journal, 17(3),

252-264. doi:10.1016/s0263-2373(99)00004-3

• McAlexander, J., Schouten, J., & Koenig, H. F. (2002). Building Brand

Community. Journal of Marketing, 66, 38-54. doi:DOI:

10.1509/jmkg.66.1.38.18451

• Mikulincer, M. (1998). Attachment working models and the sense of trust: An

exploration of interaction goals and affect regulation. Journal of Personality

and Social Psychology, 74(5), 1209-1224. doi:10.1037//0022-3514.74.5.1209

• Muniz,, A. M., & O'Guinn, T. C. (2001). Brand Community. Journal of

consumer research, 27(4), 412-432. doi: https://doi.org/10.1086/319618

• Oliver, R. L. (1999). Whence Consumer Loyalty? Journal of Marketing, 63, 33.

doi:10.2307/1252099

• Park, C. W., Macinnis, D. J., Priester, J., Eisingerich, A. B., & Iacobucci, D.

(2010). Brand Attachment and Brand Attitude Strength: Conceptual and

Empirical Differentiation of Two Critical Brand Equity Drivers. Journal of

Marketing, 74(6), 1-17. doi:10.1509/jmkg.74.6.1

• Strauss, A., & Corbin, J. (1990). Basics of qualitative research: Grounded

theory procedures and techniques. Newbury Park, CA: Sage.

• Vera, J., & Trujillo, A. (2017). Searching most influential variables to brand

loyalty measurements: An exploratory study. Contaduría y

Administración,62(2), 600-624. doi:10.1016/j.cya.2016.04.007

• Qualtrics, Online Survey Software with Ultimate Flexibility. (n.d.). Retrieved

June 29, 2017, from https://www.qualtrics.com/research-core/

• Zhou, Z., Zhang, Q., Su, C., & Zhou, N. (2012). How do brand communities

generate brand relationships? Intermediate mechanisms. Journal of Business

Research, 65(7), 890-895. doi:10.1016/j.jbusres.2011.06.034

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7

Appendix

7.1 Overview Brand Activations

Campaign Demo Brand Utility Digital Experiental Instore Mobile Packaging Product Promo PR Stunt Sampling Shopper Social Media

Toblerone x x

Data Dollar Store x x x

Bentley Burial x

Samsung - Dream to Reality x x x

Safety bags x x x x

Unlimited Stadium x x

Unusual Football Field Project x

True Wetsuits x x x x

Motor Dreams x x

I wish I had a Samsonite x x x x x x

Muscdrome x x

In-A-Snap x x x

Behind the Leather x x x x

One-Drop Bottle x x x x x

The Gig App x x x x

Mall Surprise x x

DILL x x x x x

Live Test Series x x x

Seat Taxi Fare x x x

IKEA sleep over x x x x

Sorry about the Twigs x x x x

Adoptable Trends x x x x

Magenta Unleashed x x x x x

The Social Dishwashing x x

2016 Wrapped x x x x x

Green Light Run x x x x x

Payphone Bank x x x x

Boost Your Voice x x

ReApply Reminder x x

Safety Truck x x

S-Drive x x x x

Refresh Cap x x

Musical Earmuff x x

Cook This Page x x

Future Fries x x x x x

The Talking Fridge

x x

Small big idea x x x

Food slot x x x

Bitcoin Rain x x

A small demonstration x x x

Climb and Jump x x

The Bitter Voucher x

Sugar Detox x x

The 6 Second Sale x x

URXXL x x x

Snaplications x x x

The Human Catalog x x x x

ToolPool x x x x

AiMEN x x

Google Home of the Whopper x x x x x

I Will What I Want x

Fairy Fair x x x

Not Coming Soon x x

Straight Outta x x Cheesy Hits x x Dated Pillows x x x StackeRTweet x x x x Miele Powerwash x x x Totals 11 22 9 15 15 15 2 7 9 25 7 6 30

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7.2 Tables

7.2.1 Table 4 Indirect effects of brand activation (combined) and consumer

engagement on intentional brand loyalty

*significant p < .05

7.2.2 Table 5 Indirect effects of brand activation (type A) and consumer engagement

on intentional brand loyalty

7.2.3 Table 6 Indirect effects of brand activation (type B) and consumer engagement

on intentional brand loyalty

Brand Activation combined N=369

Y (Intended Brand Loyalty)

Coeff. SE p Coeff. SE p X (brand activation) a1 0,482 0,051 ,000* a2 c' 0,162 0,045 ,000* M1 Engagement b1 0,458 0,041 ,000* Constant iM1 2,650 0,108 ,000* iM2 iy 0,105 0,139 ,451 R2=0.366 F(2,366)=24.146, p<.000 M1(Engagement) R2=0.1963 F(1,367)=89.631, p<.000 Brand Activation A N= 174

Coeff. SE p Coeff. SE p X (brand activation) a1 0,513 0,065 ,000* a2 c' 0,124 0,071 ,085 M1 Engagement b1 0,606 0,072 ,000* Constant iM1 2,848 0,133 ,000 iM2 iy -0,462 0,240 ,056 R2=0.4157 F(1,171)=60.830, p<.000 F(1,172)=62.180, p<.000 M1(Engagement) R2=0.2655 Brand Activation B N= 195

Coeff. SE p Coeff. SE p X (brand activation) a1 0,504 0,071 0,000* a2 c' 0,140 0,600 ,021* M1 Engagement b1 0,424 0,054 ,000* Constant iM1 2,379 0,156 0,000* iM2 iy 0,329 0,175 ,061 R2=0.3524 F(2,192)=52.231, p<.000 M1(Engagement) R2=0.2077 F(1,193)=50.581, p<.000*

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7.2.4 Table 7 Indirect effects of brand activation (type A) on Intended Brand Loyalty

through individual dimensions of Consumer Engagement

7.2.5 Table 8 Indirect effects of brand activation (type B) on Intended Brand Loyalty

through individual dimensions of Consumer Engagement

Coeff. SE p Coeff. SE p Coeff. SE p

X (brand activation) a1 0,548 0,075 ,000* a2 0,644 0,800 ,000* a3 0,495 0,087 ,000* M1 (attention) M2 (Identification) M3 (abso) M4 (enth) M5 (int) Constant iM1 2,906 0,158 ,000 iM2 2,724 0,168 ,000 iM3 2,780 0,183 ,000 F(1,135)=53.180, p<.000 F(1,135)=48.189, p<.000 F(1,135)=32.101, p<.000 M3 (Absorption) R2=.2826 R2=0.2549 R2=0.1921 M1(Attention) M2 (Identification)

Coeff. SE p Coeff. SE p Coeff. SE p p

X (brand activation) a4 0,514 0,080 ,000* a5 0,471 0,084 ,000* c' 0,091 0,660 ,008* ,000* M1 (attention) b1 0,256 0,103 ,014* ,057 M2 (Identification) b2 0,080 0,108 ,459 ,603 M3 (abso) b3 _-0,175 _0,100 _,082 _,019* M4 (enth) b4 _0,261 _0,115 _,025* _,129 M5 (int) b5 0,302 0,095 ,002* ,000* Constant iM4 2,987 0,168 ,000 iM5 3,084 0,177 ,000 iy -1,008 0,270 ,000* ,056 R2 =0.5271 F(6,130)=24.146, p<.000 M4 (Enthusiasm) M5 (Interaction) R2 =0.2342 R2 =0.1879 F(1,135)=41.2882, p<.000 F(1,135)=31.233, p<.000

X (brand activation) a1 0,381 0,089 ,000* a2 0,342 0,095 ,001* a3 0,258 0,106 ,016* M1 (attention) M2 (Identification) M3 (abso) M4 (enth) M5 (int) Constant iM1 2,943 0,210 ,000 iM2 2,911 0,224 ,000 iM3 2,919 0,251 ,000 M2 (Identification) M1(Attention) F(1,119)=18.452, p<.001 F(1,119)=12.987 , p<.001 F(1,119)=5.921, p<.016 R2 =0.0474 R2 =0.0984 R2 =0.1342 M3 (Absorption) Y (Leerprestaties)

X (brand activation) a1 0,377 0,095 ,000* a5 0,396 0,087 ,000* c' 0,177 0,660 ,008* M1 (attention) b1 0,061 0,111 ,587 M2 (Identification) b2 0,035 0,125 ,777 M3 (abso) b3 -0,120 0,099 ,229 M4 (enth) b4 0,010 0,113 ,929 M5 (int) b5 0,524 0,096 ,000* Constant iM1 2,950 0,226 ,000 iM5 3,053 0,206 ,000 iy -0,211 0,248 ,397 R2 =0.4922 F(6,114)=18.417, p<.001 F(1,119)=15.2675 p<.0001 F(1,119)=20.810, p<.000 M5 (Interaction) R2 =0.1164 R2 =0.1488 M4 (Enthusiasm)

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7.2.5.1 Table 9 Indirect effects of brand activation combined on IBL through individual

dimensions of CE

X (brand activation) a1 0,429 0,059 ,000* a2 0,415 0,062 ,000* a3 0,336 0,069 ,000* M1 (attention) M2 (Identification) M3 (abso) M4 (enth) M5 (int) Constant iM1 3,006 0,131 ,000 iM2 2,869 0,138 ,000 iM3 2,928 0,154 ,000 R2 =0.1732 R2 =0.1500 R2 =0.0848 F(1,256)=53.628, p<.000 F(1,256)=45.183 , p<.000 F(1,256)=23.719, p<.000

M1(Attention) M2 (Identification) M3 (Absorption)

Y (Leerprestaties)

X (brand activation) a1 a4 0,411 0,062 ,000* a5 0,414 0,060 ,000* c' 0,178 0,049 ,000* M1 (attention) b1 0,144 0,076 ,057 M2 (Identification) b2 0,043 0,082 ,603 M3 (abso) b3 -0,166 0,071 ,019* M4 (enth) b4 0,124 0,081 ,129 M5 (int) b5 0,427 0,068 ,000* Constant iM1 iM4 3,042 0,139 ,000 iM5 3,111 0,134 ,000 iy -0,512 0,183 ,056 R2_=0.1450 _R2_=0.1571 _R2_=0.4872 F(1,256)=43.407 p<.000 F(1,256)=47.708 p<.000 F(6,251)=39.739 , p<.000 M4 (Enthusiasm) M5 (Interaction)

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7.3 Survey

Question 1

Question 2

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Question 4

Question 5

Question 6

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Question 7

Question 8

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Question 10

Question 11

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Question 13

Question 14

(39)

Question 16

Question 17

(40)

Question19

Question 20

(41)

The mediating effect of Consumer Engagement on the relationship between Brand Activation and Intended Brand Loyalty

Master Thesis