Forced brand marriages in broadcasting to fight competition. Happily ever after?

A study focused on the influence of level of brand concept consistency (BCC) and different types of BCC in the broadcasting industry on brand perceptions.

Student: Claudette van Schubert (10110992) First Supervisor: Drs. J. Labadie, MBM. Second Supervisor: Drs. R.E.W. Pruppers Version: Final version

Faculty of Economics and Business- Amsterdam Business School

Msc. in Business Adminstration – Marketing track

June 29, 2016 Statement of originality

This document is written by Student Claudette van Schubert 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.

Preface It is my pleasure to present to you ‘The End’ chapter of my student life: my Master thesis for the Msc. in Business Administration.

During this process I have learned a lot. I have learned a lot about conducting research and my interest in science is really fuelled. I became enthusiastic about statistics. Yes, I was the one liking a Facebook page during my very first year at the University of Amsterdam stating: ‘I hate SPSS’ and now I’m searching for one that states ‘I like SPSS’. But more importantly, I have learned a lot about myself. I have learned to balance things. A word I heard before but never really understood.

I am very grateful for the support that I have got during this process from my supervisors Jorge Labadie and Roger Pruppers. Jorge, thanks for being there in this huge learning process. Thanks for the motivational words, the advices and your patience. It means a lot to me. Roger, thanks for the helpful insights, your constructive feedback and your enthusiasm for academic research. Thanks to you both a lot of effort is not wasted. Thanks for showing this very critical person that this thesis is worth it and holding up the mirror!

I also want to thank my dad and Dettie, for the unconditional support, love and faith in me. And dad, your office is yours again! I am very glad that I do not have to spend days and nights there anymore. And last but not least, thanks for the pep talks and hugs Chantal, Samantha and Berna.

To ends and new beginnings!

Claudette van Schubert

Amsterdam, 29 th of June 2016.

Table of contents Statement of originality ...... Preface ...... Abstract ...... Chapter 1. Introduction ...... 1 1.1 Introduction ...... 2 1.2 Lack of knowledge ...... 3 1.3 Problem definition ...... 4 1.3.1 Problem statement ...... 4 1.3.2 Sub questions ...... 5 1.3.3 Delimitations of the study ...... 5 1.4 Contribution ...... 5 1.4.1 Theoretical contributions ...... 5 1.4.2 Managerial implications...... 6 1.5 Structure of the research ...... 6 Chapter 2. The associative network model in the broadcasting industry ...... 8 2.1 Customer-based brand equity ...... 8 2.2 The associative network model ...... 9 2.2.1 Brand salience ...... 10 2.2.2 Brand image ...... 10 2.2.3 Brand responses ...... 13 2.2.4 Brand resonance ...... 13 2.3 Customer-based brand equity for brands in broadcasting ...... 14 2.4 Brand architecture and strategies ...... 15 2.5 Brand architecture of the Dutch broadcasting brands ...... 16 2.5.1 Corporate brand ...... 17 2.5.2 Broadcasting channel ...... 17 2.5.3 Broadcasting networks ...... 17 2.5.4 Programs ...... 18 2.5.5 Presenters ...... 18 2.5.6 Example brand hierarchy ...... 18 Chapter 3. Brand alliances and consumer responses ...... 20 3.1 Image transfer ...... 20 3.2 Brand alliances ...... 20 3.3 The influence of brand alliances on consumer responses ...... 21 3.4 Categorization theory ...... 22 3.5 Schema theory ...... 24 3.6 Congruity theory ...... 25 3.7 Perceived level of fit ...... 25 3.8 Different types of brand concept consistency ...... 27 Chapter 4. Hypotheses development ...... 29 4.1 Perceived level of BCC ...... 29 4.2 Types of BCC ...... 33 4.3 Conceptual model ...... 35 Chapter 5. Exploratory study for stimuli development ...... 36 5.1 Research method ...... 36 5.1.1 Type of research ...... 36 5.1.2 Sample ...... 37 5.1.3 Procedure ...... 37 5.1.4 Data analysis ...... 37 5.2 Results: Categorization public broadcasters ...... 38 5.3 Results: Categorization of public broadcasters & commercial broadcasters ...... 41 Chapter 6. Methodology main study ...... 44 6.1 Research design ...... 44 6.2 Pre-testing ...... 44 6.2.1 Pre-test 1 ...... 44 6.2.2 Pre-test 2 ...... 46 6.3 Stimuli selection ...... 48 6.4 Sample ...... 51 6.5 Procedure ...... 51 6.6 Measures ...... 52 6.6.1 Independent variables ...... 52 6.6.2 Dependent variables ...... 53 6.6.3 Control variables ...... 56 6.6.4 Demographic variables ...... 57 Chapter 7. Results main study ...... 58 7.1 Respondent profile ...... 58 7.2 Data preparation ...... 60 7.2.1 Consistency and reliability checks ...... 60 7.2.2 Inter-rater-reliability checks...... 61 7.2.3 Control variables ...... 62 7.2.4 Manipulation checks ...... 66

7.3 Hypotheses testing ...... 70 7.3.1 Amount of brand associations ...... 71 7.3.2 Proportion of general brand associations ...... 74 7.3.3 Favorability brand associations ...... 77 7.3.4 Brand responses ...... 79 7.4 Overview of the hypotheses ...... 86 7.5 Additional insights ...... 87 7.5.1 Reasons for a misfit/fit ...... 87 7.5.2 Brand familiarity and type of misfit/fit ...... 88 7.5.3 The moderating influence of age ...... 90 Chapter 8. Discussion ...... 94 8.1 The role of level of BCC ...... 94 8.2 The role of types of BCC ...... 98 Chapter 9. Conclusion ...... 102 9.1 Suggestions for future research ...... 105 9.2 Theoretical contributions ...... 106 9.3 Managerial implications ...... 108 References ...... 112 Appendix 1. Exploratory study: Questionnaire ...... 126 Appendix 2. Exploratory study: Scree plots normalized raw stress ...... 130 Appendix 3. Pre-test 1: Questionnaire ...... 131 Appendix 4. Pre-test 2: Results ...... 138 Appendix 5. Main Study: Example of the stimuli ...... 140 Appendix 6. Main study: Questionnaire ...... 141 Appendix 7. Main study: Categorization key: type of BCC ...... 154 Appendix 8. Main study: Categorization key: type of brand associations ...... 157 Appendix 9. Additional analysis: results hierarchical regressions ...... 158

Abstract The broadcasting industry is characterized by fierce competition in a complex market. Due to technological shifts the number of content providers evolved (Ots, 2008). When preferences of consumers are changing rapidly and when competition is strong, brand loyalty is very important (Lowe & Palokangas, 2010). Dutch public broadcasting brands were forced to form an alliance due to the cuts in the media budget. When brands form an alliance, perceived fit seems to be widely accepted to be the key to success. However, it is yet unknown what the role of perceived fit is on brand perceptions for broadcasting brand alliances. Broadcasting brands do not have price as a point of and offer experience goods (Chan-Olmsted, 2006). Furthermore, moderating factors on the relationship between level of fit and brand responses are often neglected (Kim & John, 2008). Therefore this study implements a two-dimensional approach on perceived brand concept consistency (BCC). The role of the level of BCC as well as the moderating role of different types of BCC are examined for brand alliances in the broadcasting industry. First an exploratory study was conducted to find out how consumers categorize the Dutch broadcasting brands and if different levels of BCC and types of BCC could be identified. Followed up by a deductive approach: an experimental survey to test the hypotheses. Congruent with the expectations, the result indicate that a misfit based on BCC leads to a more negative brand response in terms of expected program quality, likeability of the programs and the brand attitude. However, a misfit based on BCC did not lead to less viewing intentions. Furthermore, the influence of level of BCC and types of BCC on the brand associations were examined. A fit on BCC did not lead to more brand associations or more favorable brand associations. However, a misfit on BCC did lead to a greater proportion of general brand associations, which can indicate that the image transfer process of the individual brand associations is distorted by the incongruence. No moderating effect of type of BCC was found on either the brand associations or the brand responses. The findings are very interesting for the broadcasting industry since the study gives an extensive insight in how brand alliances in broadcasting are evaluated by consumers. Additionally, the findings are also useful for researchers who are interested in exploring perceived fit beyond the more traditional dimension: level of fit. Forced brand marriages in broadcasting to fight competition. Happily ever after?

Chapter 1. Introduction 1.1 Introduction The last years major things changed in the public media landscape in the Netherlands. The role and core tasks of public broadcasting and the belonging broadcasting networks were extensively discussed. Recently the Dutch Senate accepted the new Media Act (Rijksoverheid, 2016). The Dutch public broadcasters lost a considerably great amount of viewers to one or more commercial broadcasters (Bakker & Scholten, 2003). This Media Act aims to strengthen the programming of the public broadcasting by making it more distinctive relative to their competitors (Rijksoverheid, 2016). Besides, the Dutch government decided that the public media budget in the Netherlands had to be reduced. The Dutch government mainly decreased the extra public media budget for public broadcasting (Rijksoverheid, n.d a). As a consequence some of the broadcasting networks were forced to merge (Rijksoverheid, n.d a). Broadcasting networks that all have a very different DNA. A remarkable merger is for example the one between the public broadcasting networks VARA and BNN. VARA is inspired by the principles and values of social democracy and humanism. Including the equality of people, the importance of social justice, protection of human dignity and the international solidarity of people (VARA, n.d). In contrast to VARA, BNN stands for humor, courage, quirkiness, cheekiness, daring and lust for life. BNN is the only Dutch broadcasting network focused on young people and they want to inform and entertain by experimenting while at the same time exploring boundaries (BNN, n.d). During the process of the brand mergers employees of both broadcasting networks were throwing mud to each other in the news. VARA employees called BNN employees unhygienic and on the other hand BNN employees who called VARA employees very bureaucratic. More importantly, both broadcasting networks did not hide the fact that they are absolutely not looking forward to work together (Nieuwe Revu, 2014). The combinations of brands and their existing brand associative networks will influence consumers’ judgments of the participating brands and the new product and/or brand (Besharat, 2010). In the case of a brand alliance each partner brand brings their own brand associations to the new relationship in order to form a new set of brand associations (James, 2005). When brands are combined the nature of the semantic relationship between

1 Forced brand marriages in broadcasting to fight competition. Happily ever after? the combined brands is important for the evaluation of the brand combinations (Zhang & Sood, 2002). Similarity between the brands or in other words the perceived ‘fit’ plays a crucial role for a positive evaluation of the combination. Völckner and Sattler (2006) have even identified perceived fit as the key driver of brand extension success. Not only product feature similarity between the brands is considered to be important but also a similar brand image (Park, Milberg & Lawson, 1991). Furthermore, similarity between specific brand associations seems important for the evaluation of a brand alliance (Broniarczyk & Alba, 1994). Brand alliances are often used as a technique to transfer positive associations from one brand to another and to build brand equity (Washburn, Till & Priluck, 2000). However, in the case of the Dutch public broadcasting networks the brand alliances were not initiated to increase brand equity but because of the cuts in the media budget. The broadcasting networks had no choice. The broadcasting industry is characterized by strong competition, advertising markets that are saturated and more importantly the enormous change in behavior of the viewers due to technological improvements (Evens, 2014). Consumers preferences shifted from traditional cable bundles to video on demand and streaming services (Matrix, 2014). When consumer preferences are so far from being static and when the competition is so fierce, creating brand loyalty seems to be a big challenge but yet very essential (Lowe & Palokangas, 2010). To build strong bonds with their audiences, to attract advertisers and to improve customer satisfaction and loyalty (Ots, 2008) broadcasters need strong brands. Brands with strong, favorable and unique associations that will lead to customer-based brand equity (Keller, 1993). In case of the Dutch public broadcasting networks it is the question if these forced marriages may cost more than it yields in terms of brand equity. Do the brand alliances in broadcasting have a disruptive effect on the brand equity and will these marriages instantly fail? Or do consumers not care at all? This research aims to provide an understanding of the role of fit in terms of brand concept consistency for brand alliances in broadcasting. The study provides an insight in what the influence of brand alliances is with different levels and different types of brand concept consistency on the perceptions of the consumers: the viewers.

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1.2 Lack of knowledge In order to exploit existing brand equity companies can adapt several branding strategies (Desai & Keller, 2002). By using these strategies, positive associations relating to brand quality, brand image or brand awareness can be transferred from one brand to the other (Simonin & Ruth, 1998; McCarthy & Norris, 1999). However, sometimes organizations with dissimilar brand images are forced to merge. In the case of the Dutch public broadcasting networks it is very likely that the brands have a perceived fit when the product feature similarity is considered (Park, Milberg & Lawson, 1991). They are all broadcasting networks making programs for television. Yet, it is very likely that all the brands have a very different brand image and thus differ based on brand concept consistency (BCC). These broadcasting brands were always competing on a dual market. With the commercial broadcasters for the highest audience ratings but also with each other in order to attract more members and a loyal audience to receive public funding and to get the popular primetime spots (Rijksoverheid, n.d b). After all, each broadcasting network always needed to differentiate in order to get a competitive advantage. Literature on brand alliances, the role of perceived fit and brand perceptions of consumers often examined product brands (Becker-Olsen & Hil, 2006). However, it is short sighted to assume that the role of perceived fit is the same for brand alliances that take place in broadcasting. There are some crucial differences between commercial product brands and media brands. Media brands offer experience goods (Chang & Chan- Olmsted, 2010) and they have a very different business model. Price is not a point of differentiation because consumers only invest time when consuming the product: in this case the programs (Chan-Olmsted, 2006). This study will therefore address this gap by examining the role of brand concept consistency for brand alliances in the broadcasting industry. Besides, there is an emerging stream of literature that is focused on identifying personal, cultural but also situational differences that could explain why consumers react differently to brand alliances (Kim & John, 2008). Perceived fit seems to be a concept that is so widely accepted that other factors that could have an influence on the established relationships are often neglected (Kim & John, 2008) or overshadowed. It seems that not only level of fit based on product feature similarity (PFS) and brand concept consistency (BCC) play a crucial role. The assumption that every consumer responds in the same way

3 Forced brand marriages in broadcasting to fight competition. Happily ever after? to brand alliances with different levels of PFS or BCC is an assumption that has to be challenged. Research namely shows that consumers can evaluate a fit based on two different features: ‘deep’ features (brand attributes) or ‘surface’ features (similarity visual cues) (Zhang & Sood, 2002). Meaning that there could also be different types of fit. A fit based on more ‘deep’ features such as brand mission and vision or a fit based on more ‘surface’ more visible features such as target audience and/or general brand concept. It is important to explore the undiscovered different factors that could influence the relationship between perceived brand fit and the evaluations of the brand alliances in order to clarify the influence of fit in a more extensive way. It is yet unknown if different types of BCC have a different influence on the evaluations of brand combinations. The Dutch broadcasting landscape offers a context to explore the concept of different types of BCC. In the 20 th century the Netherlands was divided in pillars, based on different religions and ideologies (Dekker & Ester, 1996). These pillars had their own institutions, their own education systems, their own newspapers and their own broadcasters. Some of the Dutch broadcasting networks are founded in that time based on a more ‘deep’ features: certain types of pillars. For example the broadcasting network KRO that was the broadcaster for Roman Catholics (KRO, n.d). At the same time the media landscape also offers broadcasting brands that are founded on a more ‘surface’ feature such as reaching a specific target audience or providing a certain type of content. An example is the broadcaster MAX, a broadcasting network that is focused on the elderly (Omroep MAX, n.d).

1.3 Problem definition 1.3.1 Problem statement To succeed and in order to exist, the public broadcasters must be popular and as Banerjee and Seneviratne (2006) argue “there is little point to public funding of merit goods if they are consumed by a few” (p.112). Strong brands are crucial to the broadcasters because they provide them with a means of distinguishing themselves from their competitors and to eventually attract a loyal audience (Ots, 2008) in a rapidly changing market. What the influence is of brand alliances in broadcasting on the brand perceptions and what the role of fit is, is yet unknown. A two-dimensional approach on BCC should be implemented to see if level of BCC and type of BCC have an influence on the brand perceptions of the

4 Forced brand marriages in broadcasting to fight competition. Happily ever after? consumers.

This leads to the following problem statement: What is the role of brand concept consistency for brand alliances in broadcasting on the brand perceptions of consumers?

1.3.2 Sub questions To answer this research question and to develop an understanding of the underlying concepts, several sub questions need to be addressed: * What are associative networks and how are these relevant in the broadcasting industry? * What are brand alliances and how can brand associations be transferred from one brand to another when brands are combined? * How does image transfer work between brands in the same product category? * What is the role of perceived fit?

1.3.3 Delimitations of the study This study focuses on brand alliances in Dutch broadcasting. This study will only consider the influence of the brand image of the brands and it will not consider the financial side of the brands. Simultaneously, this study will only look at the impact of brand alliances from a consumer perspective. In this study existing broadcasting brands will be used and some existing and fictitious brand alliances between these brands.

1.4 Contribution 1.4.1 Theoretical contributions This study will provide an insight into the meaning of brand alliances in broadcasting and therefore it will contribute to the body of literature about brands in the media. The real meaning of brands in a media context has only just begun to be explored and it is far from fully developed (Chan-Olmsted, 2006). So, extended knowledge in this area is needed. Additionally, this study will provide a deeper understanding of brand concept consistency. It will provide an insight in the level of BCC but more importantly also on the different types of BCC and if these different types relate to positive or negative outcomes in terms of brand evaluations. This study will therefore contribute to the emerging body of literature on the possible moderating factors that could influence the

5 Forced brand marriages in broadcasting to fight competition. Happily ever after? widely accepted relationship between perceived fit and brand evaluations (Kim & John, 2008). This study will especially focus on the mergers between the Dutch public broadcasting brands. According to Andrews (2008) empirical research on brand mergers in the marketing literature is very limited. This study will therefore also contribute to the little amount of marketing literature about mergers. More importantly it will provide a unique insight in realistic brand mergers that have a possible fit and misfit on different types of BCC and that try to co-exist by maintaining both brands.

1.4.2 Managerial implications The results of this study will be of particular interest to the management of the Dutch public broadcasting networks and especially for the management of the Nederlandse Publieke Omroep (NPO). The NPO is responsible for the cohesion between the national broadcasting networks and the public media supply (Rijksoverheid, n.d c. ). Additionally, the results could be of interest to the Dutch Ministry of Education, Culture and Science. The Dutch Ministry of Education, Culture and Science is responsible for the funding of the public broadcasting in the Netherlands. This study will provide a deeper understanding of the different associations that consumers have about combinations of broadcasting brands with different levels of BCC and different types of BCC. Furthermore, the influence on the brand responses will also be examined. Therefore the results of this study can be used to evaluate and it can give an insight in how the Dutch public broadcasters can build brand equity. Furthermore this knowledge could be very useful to managers in general because this study will give an insight in the effects of forced brand mergers with different levels and different types of BCC whereby two brands will co- exist. Apart from the fact that the results of this research are very useful in the media context, the results could thus also be useful for other organizations and/or brands that are in a similar position outside of the media context.

1.5 Structure of the research This research consists out of nine chapters. The theoretical part of this study is divided into four chapters. The second chapter gives a literature review on the associative networks of brands and how these are relevant in a broadcasting context. A brief literature

6 Forced brand marriages in broadcasting to fight competition. Happily ever after? review on brand image transfer, brand alliances and the role of perceived fit follows in chapter three. In the fourth chapter the hypotheses of this study are developed. First the findings of exploratory study will be discussed. Followed by methodology and findings of the main study, the online experiment. Chapter eight will discuss the results in light of the previous literature and finally the conclusion of this research will be given in chapter nine as well as suggestions for future research.

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Chapter 2. The associative network model in the broadcasting industry 2.1 Customer-based brand equity Creating and maintaining strong brands is of great importance to firms. Brands often provide the main point of difference for consumers: the reason to buy or use a certain product or service instead of others (Wood, 2000). Therefore brands and brand management can be critical for companies to succeed in a competitive market (Wood, 2000). Brands can even be considered as one of the most valuable assets a firm has (Keller, 2013, p.30). A brand is created when a product or service is identified and distinguished from other products or services on several brand elements (Keller, 2013, p.30). According to Keller (2013) these brand elements are: “trademarks that serve to identify and differentiate the brand” (p.142). Examples of these trademarks are brand names, logos, symbols, jingles, packages, spokespeople and signage (Keller, 2013, pp. 147-170). Branding is about differentiating and creating differences. Brands can differentiate themselves on tangible and intangible dimensions. Such as symbolic and emotional assets while satisfying the same need as competitors do (Keller, 2013, p.31). As mentioned before, brands can influence consumer preferences. According to Keller and Lehmann (2006) brands influence consumer preferences in that they indicate a certain quality level, reduce risks, can engender trust and therefore simplify choice. Creating a strong brand and therefore creating and/or maintaining brand equity is important. According to Keller (1993) brand equity occurs when certain outcomes result from the marketing of a product or service because of the brand name. Without that brand name the same results would not be achieved. Keller (2013, p.69) also explains customer- based brand equity (CBBE) and how CBBE can be build. Successful marketing is about understanding the needs and wants of consumers and satisfying their needs and wants by developing products or services (Keller, 2013, p.68). Therefore the CBBE takes the perspective of the consumer and is defined as “the differential effect that brand knowledge has on consumer response to the marketing of the brand”(Keller, 2013, p.69). CBBE is about what consumers know about the brand (Keller, 1993) and it occurs when the consumer is familiar with the brand and holds some favorable, strong, and unique brand associations (Keller, 1993). In the CBBE pyramid that Keller (2001) developed, it can be seen how CBBE can be created. The CBBE pyramid is portrayed on the next page in

8 Forced brand marriages in broadcasting to fight competition. Happily ever after? figure 1. In the next paragraphs the different blocks of the pyramid will be discussed.

Resonance

Judgments Feelings

Performance Imagery

Salience

Figure 1. CCBE model by Keller (2001, p.17)

2.2 The associative network model A strong brand holds the right type of associations and experiences in the memory of consumers (Keller, 2013, p.69). Brand associations can be seen as anything linked in memory to a brand (Aaker, 1991) and determining these associations is an important first step to understanding the brand preferences and choices of consumers (Henderson, Iacobucci & Calder, 1998). But how can strong brands be developed? How can the desired brand associations be linked to a brand? To answer these questions, first a deeper understanding of brand knowledge is needed. One way of defining brand knowledge that is often used in the literature is in terms of an associative network model (Keller, 1993). According to that model, memory and therefore knowledge can be seen as a network of nodes and links between those nodes (Keller, 2013, p.71). Information or concepts stored in memory are called ‘nodes’ and the strength of associations between these nodes are called ‘links’. Keller (1993) uses this model to give an insight in how brand knowledge exists in the memory. Keller (1993) states that brand knowledge can be seen as a brand node in the memory of consumers and therefore as a variety of associations linked to this brand node. Brand associations can be

9 Forced brand marriages in broadcasting to fight competition. Happily ever after? seen as all the informational nodes that are linked to the brand node in memory and contain the meaning of a brand to consumers (Keller, 2013, p.72). In order to achieve the top in the CBBE pyramid: brand resonance, first the bottom blocks should be fulfilled. Keller (1993) distinguishes two components of brand knowledge, namely brand salience (first block) and brand image (second block).

2.2.1 Brand salience The first block in CBBE pyramid refers to brand salience, which is related to brand awareness. According to Keller (1993) brand awareness is related to the strength of the brand node or trace in memory. In other words: can consumers’ recall and/or recognize the brand under several different conditions? There is a high brand salience when a consumer has breadth and depth brand awareness (Keller, 2001). According to Keller (2001) depth awareness refers to brand recall and brand recognition. Breadth awareness on the other hand, refers to thinking of the brand and the different situations in which the consumers think of the brand. Breadth awareness is related to the question: when, how often and where do consumers think about the brand?

2.2.2 Brand image Apart from managing the financial side of a brand, managing a positive brand image is very important (Timmerman, 2001). Keller (2013) defines brand image as “the perceptions of a brand as reflected by the brand associations held in consumer memory” (p.72). Creating a positive brand image takes marketing programs that link strong, favorable and unique associations to the brand (Keller, 1993). The second block which refers to the brand image is thus concerned with the perceptions of consumers of a brand and is reflected by the brand associations that consumer held in their memory (Keller, 2001). Brand associations can be seen as anything linked in the memory to a brand (Aaker, 1991). Meaning that brand associations can be seen as the things that come to mind when a consumer thinks about the brand (Keller, 1993). According to Keller (1993) brand associations contain the meaning of the brand for consumers. There are several ways of distinguishing several types of brand associations. Keller (1993) uses the level of abstraction to distinguish brand associations from each other. The brand associations are categorized by how much information the brand association contains. Associations can

10 Forced brand marriages in broadcasting to fight competition. Happily ever after? then be classified into three categories, namely: attributes, benefits and attitudes (Keller, 1993). Attributes are the descriptive features that are related to how a consumer sees a product. Attributes describe the more practical side of a brand. It relates to what the product or service is, what it can do and where or how it can be purchased (Keller, 1993). There are two types of attributes. First: product-related attributes which relate to the product or service itself and are therefore about the fundamental ingredients that are necessary for the product or service to perform. Such as: product reliability, efficiency and more aesthetic attributes: the style and the design. This are the ‘brand performance’ associations in the CBBE model (Keller, 2001). Second: non product-related attributes, which relate to the aspects connected to the purchase or consumption of the product or service. These attributes can be seen as the ‘external aspects’ of a product or service (Keller, 1993). These attributes are the more ‘abstract’ associations related to the personality of the brand, the users of a brand, the heritage of a brand and brand experiences (Keller, 2001). The second category Keller (1993) mentions are benefits. Benefits are the associations that are related to the personal value a product and/or service can provide for a consumer. Keller (1993) explains the three types of benefits that can be distinguished. First: functional benefits, which relate to the product-related advantages that come with using a product and/or service. Mostly these benefits relate to satisfying more basic needs. Second: experiential benefits. These benefits also relate to product-related attributes but the difference is that these benefits are relating to what if feels like to use the product and/or service. These benefits satisfy needs such as sensory pleasure and cognitive stimulation (Keller, 1993). Finally: the symbolic benefits. These benefits are more related to non product-related attributes and are the more extrinsic advantages of a product or a service. These attributes are more emotionally driven and they satisfy needs such as personal expression (Keller, 1993). The last category Keller (1993) mentions are the brand attitudes. Keller (1993) defines these as “consumers’ overall evaluations of a brand”. These brand attitudes often influence the behavior and preferences of consumers and can therefore be considered as very important. Brand attitudes are a combination of all the beliefs that a consumer has about the brand and the extent to which they evaluate these beliefs as something that is

11 Forced brand marriages in broadcasting to fight competition. Happily ever after? positive or negative (Keller, 1993). Brand attitudes can be formed by the beliefs about product-related attributes and symbolic benefits (Rossiter and Percy, 1987 in Keller, 1993). To sum up, the associated attributes (product-related or non product-related), the benefits (functional, experiential or symbolic) that are most important for a brand and the overall brand attitude (positive/negative), form the brand image and thus the second block in the CBBE pyramid.

Strong, favorable and unique brand associations Brand associations need to be strong, favorable and unique to create a positive brand image (Keller, 1993). According to Keller (2013, p.77) consumers differ in how they form attitudes and beliefs about products or services. That is exactly why Keller (2013, p.77) states that it is not really important what the source of the associations is and how they are formed but that it is important to look at how strong, favorable and unique these brand associations are. So, brand associations can vary in strength, favorability and uniqueness. First: brand associations can vary in the strength that they have. The strength of brand associations depends on the strength of the connection to the brand node. Meaning that the strength of the associations is dependent on how much people think about the information and how they process this information (Keller, 1993). It is important for brand associations to be strong because it makes information more accessible and the information can be easier recalled from memory (Keller, 1993). Second: brand associations can vary in how favorably they are evaluated. Is the association generating a positive, neutral or a negative response? This is called the favorability of the brand associations. When brand associations are evaluated as favorable, consumers believe that the brand has positive attributes and benefits for them that satisfy their needs (Keller, 1993). Apart from that, the uniqueness of associations is very important. The uniqueness helps consumers to choose between brands, it is the point of difference (Keller, 2013, p.77). A unique selling position gives the consumer a reason to buy that specific brand instead of the competing brands. Associations are unique when they are not shared with competing brands. However, not all associations can be unique because a brand will also share some associations with other brands in the same product category (Keller, 1993). A

12 Forced brand marriages in broadcasting to fight competition. Happily ever after? brand is linked to a product category and therefore these shared associations establish a category membership (Chakravati, MacInnis & Kent, 1990, as cited in Keller, 2013, p. 78). Category associations can be linked to the brand, either to the more specific beliefs about the brand or to the overall brand attitudes (Keller,1993). Creating strong, favorable and unique associations is essential for building CBBE and thus for moving up in the pyramid (Keller, 2001).

2.2.3 Brand responses The next block in the CBBE pyramid refers to creating the preferred brand responses. Brand responses relate to what the consumers think about the brand (brand judgments) and to the feelings towards a brand (brand feelings) (Keller, 2001). To create a preferred brand response four brand judgments are important: brand quality, brand credibility (brand expertise, brand trustworthiness and brand likeability), brand consideration (do I seriously consider to purchase this brand?) and brand superiority (do I think the brand is unique and better than others?) (Keller, 2001). On the other hand Keller (2001) describes that it is not only about the hard judgments but also about the more affective responses towards a brand: the brand feelings. Brand feelings relate to the emotional responses and reactions that a brand creates towards consumers themselves but also towards the relationships they have with others. Keller (2001) describes six types of feelings towards a brand: warmth, fun, excitement, security, social approval and self-respect. Important for CCBE is that positive brand judgments and brand feelings are accessible and come to mind when consumers think about the brand (Keller, 2001).

2.2.4 Brand resonance The last block of the CBBE is related to brand resonance. It refers to the quality of the relationship that consumers have with the brand. Brand resonance refers to the: behavioral loyalty (how often and how much do consumers use/purchase the brand), attitudinal attachment (going beyond a positive attitude), sense of community (identification with other users, employees or representatives of the company) and active engagement (when consumers become brand ambassadors) (Keller, 2001). True brand resonance can only be reached when all other blocks in the bottom of the pyramid are fulfilling the consumers’ needs (Keller, 2001).

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2.3 Customer-based brand equity for brands in broadcasting Brands are crucial to companies because they provide them with a means of distinguishing themselves from their competitors (Keller, 2013). This is not any different for the broadcasting brands in the broadcasting industry. Different broadcasting networks are competing on a highly competitive market to attract loyal audiences and loyal advertisers (Ots, 2008). Media brands can also generate a wide spectrum of brand associations and related brand responses (Calder & Malthouse, 2005). However, there are still some differences between brands in media industries and brand in other industries that need to be addressed. The first difference is that the broadcasting networks offer experience goods. Experience goods are products and/or services whereby the quality and utility of the product and/or service cannot be (or hardly be) estimated before it is used (Chang & Chan-Olmsted, 2010). The second difference is that media firms have a unique position regarding to building and expanding brand equity because they own powerful mass- marketing tools (Ots, 2008). Media firms have the opportunity to reach enormous numbers of consumers every day. The third difference according to Ots (2008) is that media firms act on dual markets, they have to attract loyal audiences but they also need advertisers. McDowell (2006, as cited in Ots, 2008) furthermore states that another important difference between media industries and other industries can be found in the business model that they use. In media industries price is not a point of differentiation because media companies use an advertising-based business model. The audience only invests time and effort in the product, in this case in the programs that they are watching (Chan- Olmsted, 2006). The real costs for consumers are thus related to time and attention. Seeing that there is so much choice nowadays, Tungate (2004) argues that brand familiarity can be vital to consumers’ preferences, especially when the involvement of a consumer is low. Familiar brands produce stronger attitudes due to the extensive and established brand associations consumers have with them in their memories (Tungate, 2004). These established associative networks make the brand attitudes towards these brands more stable and less likely to change as new information is received (Campbell & Keller, 2003; Simonin & Ruth, 1998). Tungate (2004) also suggests that consumers will

14 Forced brand marriages in broadcasting to fight competition. Happily ever after? not be interested in searching for other brands or options but that they rely on the brands that they already know (Tungate, 2004). Technology has evolved and as a consequence the number of content providers grew (Ots, 2008). More and more media companies are seeking the attention and loyalty of audiences and advertisers (Ots, 2008). The introduction of subscription video on demand services such as Netflix but also online video platforms such as Youtube create a complex market environment. The technological shift in the market environment of the broadcasters has an impact on television program production decisions (Matrix, 2014). Consumer preferences shifted from the traditional cable bundles to streaming services and video on demand (such as Netflix) (Matrix, 2014). This consumer trend has a disturbing effect on traditional television and cable subscriptions. A larger share of the traditional TV audience nowadays consumes more via Netflix and other services on demand (Matrix, 2014). This shift causes that the traditional broadcasters now even face more competition. Therefore it is essential for the broadcasters to differentiate and to create strong brands. Strong brands eventually lead to loyal consumers who feel more involved with the brand and are less likely to switch to competitors (Keller, 2013, pp. 120-121). Building strong brands seems to be crucial for the broadcasters to make sure that they do not lose their audience to other broadcasters or to other services such as Netflix. Brand management is an important tool to build strong bonds with the audiences and to reach brand resonance. Customer satisfaction and loyalty can be improved and advertisers can be attracted (Ots, 2008).

2.4 Brand architecture and different branding strategies The brand architecture refers to a branding framework that explains the structure between the different brands within one organization (Aaker & Joachimsthaler, 2000). A branding architecture consists out of different levels, with the corporate brand in the top and the sub brands in the bottom. The brand architecture can be viewed according to five dimensions (Aaker & Joachimstahler, 2000). The brand portfolio (the number of brands) portfolio roles, the relationship between different brands in the portfolio, product market roles (structure for a specific market), portfolio structure (brand range) and portfolio graphics (color and size of logo). The linkages between brands and the drivers are crucial for the brand architecture.

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Keller (2002) therefore describes a four level brand hierarchy consisting out of: 1) the corporate brand, 2) family brands, 3) individual brands and 4) modifiers. Family brands are covering several product categories but cannot be seen as the corporate brand. Individual brands are brands that are restricted to one product class and modifiers modify a brand structure for a market segment. Several branding strategies can be used to structure a brands portfolio. The branding relationship spectrum of Aaker and Joachimsthaler (2000) describes the strategies that can be used based on the driver role of the brands. The four main strategies are: 1) a house of brands, 2) endorsed brands, 3) sub brands and 4) a branded house. In the house of brands strategy all brands operate individually and are in the eyes of the consumer not linked to the corporate brand. In this strategy the individual brands fulfil the driver role. The individual brands are the main reason the consumer purchases or uses the product and/or service. The endorsed brands strategy still has a focus on brands that operate individually. However, these individual brands are endorsed by the corporate brand. Meaning that there is a visible link between the corporate and individual brands. However, the driver role is still with the individual brands since the link is not very obviously. In the sub brand strategy, the driver role is with the individual brand as well as with the corporate brand. In this branding strategy individual (sub) brands are strongly linked to the corporate brands. The last branding strategy that Aaker and Joachimsthaler (2000) mention is the branded house strategy. The driver role moved from the individual brand (in house of brands) towards the corporate brand. The corporate brand is the umbrella of all individual brands and is strongly linked to all individual brands.

2.5 Brand architecture of the Dutch broadcasting brands The brand architecture of broadcasting brands in the Netherlands is extensive: consisting out of multiple brand levels. Five brand levels can be identified. A brand hierarchy will be portrayed for a Dutch public broadcaster: BNN in order to show the branding strategy that is used by presenting the brand elements in an explicit order (from the top to the bottom). But first the different brand levels will be explained.

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2.5.1 Corporate brand The corporate brand in the Dutch public broadcasting industry is the NPO (Stichting Nederlandse Publieke Omroep). The NPO is responsible for the cohesion between the national broadcasting networks but also for the content of the media supply, the distribution of the total media budget and for more practical issues such as: managing the distribution, carrying out research on the brand image and quality of radio, television and the internet and helping the broadcasting networks with subtitling and purchasing and selling programs (Rijksoverheid, n.d c).

2.5.2 Broadcasting channels The next brand level are the public broadcasting channels: Nederland 1, Nederland 2 and Nederland 3. Nederland 1 is profiled as a general network for everyone. Nederland 2 is more focused on providing critical and more in-depth content focused on education and culture. Finally, Nederland 3 is profiled as the channel for music and fiction and at the same this channel is addressing a younger audience (Rijksoverheid, 2014). Since August 2014 the NPO rebranded the channels in NPO1, NPO2 and NPO3 (Branding Source, 2014).

2.5.3 Broadcasting networks The broadcasting time on the three broadcasting channels is divided over the different broadcasting networks. As a result of the cuts in the media budget the Dutch government introduced the 3-3-2 model: three merging broadcasting networks, three independent broadcasting networks and 2 task-networks (Rijksoverheid, n.d b). All the broadcasting networks still belong to the corporate brand NPO (NPO, n.d). The following broadcasting networks were forced to merge: KRO (Catholic) with NCRV (Protestant), VARA (social democratic) with BNN (youth) and TROS (general/amusement) with AVRO (general) (Rijksoverheid, n.d d). From the three merging broadcasting networks first the brands AVRO and TROS merged in AVROTROS on brand level (“Fusieomroep AvroTros krijgt…”, 2013). They developed a shared identity in terms of the logo and a shared website. Followed by KRONCRV who also created a shared identity in terms of the logo. However, still

17 Forced brand marriages in broadcasting to fight competition. Happily ever after? separate websites for both brands exist. BNNVARA did not merge on brand level they merged as organizations but they kept their own brands (BNN, n.d). VARA and BNN did not create a shared identity (yet). The broadcasting networks EO (reformed), MAX (50+) and VPRO (socially critical) are the three independent broadcasting networks. The two- task networks are NOS (news and sport) and NTR (minorities, art, culture and education).

2.5.4 Programs The goods that broadcasting networks ‘sell’ are the programs that they produce and broadcast. As mentioned earlier each broadcasting network aims to reach a different target audience or has another mission. To reach the target audience and/or to fulfil their mission broadcasting networks each broadcast different kind of programs. The public broadcasting network NOS is for example responsible to provide programs that are related to the news, sports or events (NOS, n.d). On the other hand the public broadcasting network BNN provides programs that interest younger people since they aim to reach a younger audience (“BNN Merkboek”, n.d). On the contrary, broadcasting network MAX broadcasts programs that elderly people like since they aim to reach older people (Omroep MAX, n.d).

2.5.5 Presenters According to Uggla (2006) people may not literally be brands themselves but they can definitely possess brand equity. Persons can generate strong brand associations and brand recognition. In some cases persons are really strong related to a brand and thus very important. Persons can then fulfil the driver role and become a individual and/or subbrand in the brand hierarchy of the brand (Uggla, 2006). In the broadcasting industry there are also people that could be closely linked to the brands: the presenters.

2.5.6 Example brand hierarchy On the next page in figure 2 the example of the brand hierarchy of BNN and one of the programs can be seen. First in the brand hierarchy is the corporate brand which is NPO. Followed by the broadcasting channel: Nederland 3 (nowadays, NPO3). BNN is the broadcasting network and thus the third brand in the brand hierarchy. The program that is chosen for this example is ‘Je zal het maar hebben’ and is thus the next brand. Finally the

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last brand in this example is Valerio Zeno. Valerio Zeno is the presenter of this program.

Corporate brand - NPO

Channel – Nederland 3

Broadcasting network– BNN .…

Programs - JZMH ...... …

Presente r – Valerio Zeno

Figure 2. Brand hierarchy of one of the programs of broadcasting network BNN

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Chapter 3. Brand alliances and consumer responses Due to the cuts in the media budget for public broadcasting, different public broadcasting networks had to merge. The question remains what the influence of these brand mergers is on the perceptions of consumers. In this chapter the literature on the effects of brand alliances and the effects of different levels of perceived fit on the brand perceptions of consumers will be extensively discussed.

3.1 Image transfer Brands can be linked to other entities to leverage secondary brand associations. Brands can be linked to other knowledge structures in the mind of consumers (Keller, 1993). In that case the brand can leverages some brand associations of the other entity and can maybe even leverages the brand equity of the other entity. The brand can be linked to entities such as other brands, countries of origin, spokespersons, channels of distribution or even other organizations (Keller, 2013, p.261). In the case of linking brands, the brand image can then be transferred from one brand to another. The transfer of brand image is considered as the process in which associations from one entity become associated with another entity in the mind of consumers (Keller, 2003). How image transfer works will be explained in the next paragraphs.

3.2 Brand alliances One of the sources for leveraging secondary brand associations are brand alliances. Brand alliances are all the short and long term combinations between individual products, brands and/or other assets (Rao & Ruckert, 1994). A brand alliance includes brands that are perceived by consumers as linked or jointly branded. Multiple brands are integrated and are presented together to the consumer (Rao & Ruckert, 1994). There are different types of brand alliances. According to Simonin and Ruth (1998) products or brands can be combined and be presented to the consumer physically or symbolically. Physically in for example visual objects, such as bundled packaging. Or more symbolically by associating brand names or logos in marketing communication efforts. These brand combinations can vary in many forms (Simonin & Ruth, 1998). Owen James (2006) also classifies brand alliances according to the form they take. According to Owen James (2006) there is a distinction between physical and symbolic

20 Forced brand marriages in broadcasting to fight competition. Happily ever after? alliances. Physical alliances are related to the outcome product. Examples of physical alliances are: ingredient branding, composite brand extension, bundled products and product combinations where two brands are combined to produce a new product. A symbolic alliance on the other hand, refers to an effort that adds meaning to consumers by transferring images of the brands and the related brand associations. Examples are: joint advertising, co-packaging, joint-sales promotion and celebrity endorsement (Owen James, 2006).

3.3 The influence of brand alliances on consumer perceptions Linking a brand to another brand from the same or a different company may result in a new set of associations. Besides, the combination of brands may also affect existing associations (Keller, 2013, p.261). To transfer positive brand associations from one brand to another brand, marketers use brand alliances. Brand alliances offer possibilities to stimulate the transfer of brand associations (Washburn, Till & Priluck, 2000). When a brand is linked to another brand, the consumers must have some brand knowledge about the brands that are involved. Additionally, the brand alliance will be most successful when the consumers hold some strong, favorable and unique associations about the brands that will be combined. Besides, both brands should generate positive consumer judgments and feelings (Keller, 2013, p.271). A combination of brands results in new associations transferring from one brand to the other (Broniarczyk & Alba, 1994) or to the brand alliance itself (Rao & Ruekert, 1994). Certain associations can be owned by the brand. If some associations are very strong and typical for a brand it can be hard to leverage it to a new product category (James, 2005). It is therefore important to ensure the right kind of fit in values, capabilities and goals between the involved brands (Keller, 2013, p. 272) and to take the associations that both brands currently hold in consideration (James, 2005). The theories on brand extensions can explain why and when brand alliances are evaluated in a positive way. When there is a perceived fit between the brands than a positive spillover effect can take place because positive associations will be transferred (Simonin & Ruth, 1998). This can result in a change of the original brand attitude (Simonin & Ruth, 1998). However, combinations of brands do not always elicit positive responses from

21 Forced brand marriages in broadcasting to fight competition. Happily ever after? consumers. Instead, brand alliances can cause serious confusion, lost focus on target groups and brand image losses for both brands (Uggla & Åsberg, 2010). Brand alliances can result in brand dilution and it could lead to negative reciprocity effects (Park, McCarthy & Milberg, 1993). A negative reciprocity effect takes place when attitudes towards the involved brands are negatively changed due to the fact that the brand is combined or extended (Park, McCarthy & Milberg, 1993). A negative reciprocity effect is thus diluting original brand attitudes and beliefs due to the fact that the brand is combined. Furthermore, there is also the risk of losing control over the brand associations and that the brands that are combined become generic. Meaning that one of the brands can be overshadowed by the other one (Uggla & Åsberg, 2010). Uggla & Åsberg (2010) further mention that on first sight there may be a brand fit between the involved brands in the positioning process, but the attitudes and values of the brands that will form an alliance can differ so much from each other that this could cause friction . To understand how attitudes and evaluations about the brand alliances are formed, the categorization theory, the schema theory and the congruity theory will be explained in the next paragraphs.

3.4 Categorization theory The categorization theory states that people do not deliberately and individually evaluate each new object to which they are exposed (Keller, 2003, p.459). Instead, the categorization theory describes that objects will be classified at varying levels of specificity (Sujan & Dekleva, 1987). The classes in which objects can be placed range from super ordinate or product class categories (in this case ‘broadcasters’), to more product type categories (such as ‘religious broadcasters) to specific brand level categories (such as ‘Evangelische Omroep’) (Sujan & Dekleva, 1987). Categorical knowledge of brands and/or products influence the evaluation of the new objects by consumers (Keller, 2013, p.459). Consumers categorize this new information because they have to structure, simplify and interpret their marketing environment (Meyers-Levy & Tybout, 1989 as cited in Keller, 2013, p.459). The categorization process explains how (new) information is understood and how it is interpret by consumers (Cohen & Lefebvre, 2005).

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According to Park, Milberg and Lawson (1991) consumers judge new products in line with the categorization process. Consumers evaluate the new product and/or brand according to the suitability of its membership in a specific category. Consumers reactions to brand extensions thus appear to involve a categorization process (Park, Milberg & Lawson, 1991). Consumers categorize, label and store the brand associations based on previous experiences and knowledge with the brand or the category that the brand belongs in. Categories are developed through experiences and these experiences lead to a set of expectations that are related to that category (Lee, 1995). Simultaneously, they also develop an affective reaction towards the category to which an object belongs (Lee, 1995). Category members (such as the brands or products) are then also linked to these expectations and feelings that belong to that category (product category). The categorization process does not only explain how information is processed but it also seems to be related to the involvement and preferences of consumers (Nedungadi & Hutchinson, 1985). According to the categorization theory, consumers evaluate an object sometimes based on the feelings that are associated with the category (category-based processing) or based on individual attributes of the object (Lee, 1995). The latter is called piecemeal processing (Lee, 1995). By piecemeal processing the beliefs about the brand attributes and their importance are the key determinant for the evaluation of the object. The consumers’ evaluation is in that case based on putting together different pieces of separate information. By category-based processing on the other hand, consumers base their evaluations on the feelings that are associated with the category to which the object belongs (Lee, 1995). When there is a perceived “fit“ between the involved brands, the beliefs and affects that are associated with the brand category may transfer to the brand combination (Meyers-Levy & Tybout, 1989). With category-based processing, consumers will then transfer perceptions of the brand category to the new brand combination (Aaker and Keller, 1990). Additionally, these brand associations could then influence the brand evaluations (Sujan, 1985). However, when there is no fit between the brands and the brand category more elaboration will take place by using piecemeal processing (Meyers- Levy & Tybout, 1989).

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3.5 Schema theory The associative network theory defines the memory as a cognitive structure that consists out of nodes that are interconnected by links (Anderson, 1983). The spreading activation process refers to the fact that one certain set of nodes can cause that someone thinks about another set of nodes (Anderson, 1983). When two sets of nodes are closely linked in the mind of consumers it is more likely that spreading activation will take place. One set of nodes will then activate the other set of nodes and image transfer can take place from one brand to the other and vice versa (de Groot, 1989). The image transfer process and the importance of fit can be thus ne explained by using the associative network theory: when two objects have a lot in common more links are established between these two nodes and the nodes are closer to each other in the mind of consumers (Collins & Loftus, 1975). The similarity between the two nodes thus influences the potential transfer of brand associations. There is a greater potential for the transfer of brand associations when sets of nodes are closely linked (Fazio, 1989). Schema theory is based on the associative network theory and also explains why similarity between the nodes is so important for image transfer. Schema theory is founded on the belief that the memory of people is a mix of explicit memories and general abstractions about types of people, activities, events places and other objects (Bartlett, 1932 as cited in Gwinner and Eaton, 1999). The memory is not only based on past concrete experiences but on knowledge related to the general type of situations, persons, activities, events places or/and objects. These general types of associations are called schema’s. A schema is used to interpret the complex world. A schema can be described as a cognitive structure that consists out of all the knowledge of a stimulus (Barlett, 1932 as cited in Gwinner and Eaton, 1999). When information is presented that is incongruent with the current brand schema, the information will be filtered out and will not be encoded as congruent (Misra & Beatty, 1990). On the other hand, when presented with information that is congruent with current brand schemas the information will be more effectively encoded and will provide more meaning (Misra & Beatty, 1990). That incongruent information will be filtered out can be explained by the filtering model that Misra and Beatty (1990) describe. The filtering model determines which information will be encoded by structuring the information in an effective way (Taylor & Crocker, 1981as cited in

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Misra & Beatty, 1990). Schema theory argues that the level of similarity between the information about an object and the existing scheme of an object or related object will influence the transfer of brand associations (Fiske, 1982). When there is a fit, the image transfer will be more likely (Crocker, Fiske & Taylor, 1984 as cited in Gwinner and Eaton,1999). In terms of brand alliances: the potential that existing brand associations of the involved brands will be enhanced is greater when there is a perceived fit (Milberg, Park & McCarthy, 1997). When there is no fit, it is argued that there will be a change in existing brand associations (Weber & Crocker, 1983) since it does not fit with the existing ‘stereotype’ brand schema. However, when consumers are presented with information that is incongruent with the current schema, they rather make sure that the information will be distorted in order to ensure that the current schema does not have to be adjusted (Crocker, Fiske & Taylor, 1984 in Gwinner and Eaton, 1999) The similarity and dissimilarity between brands or in other words perceived fit, is therefore an important factor when it comes to brand image transfer. Simultaneously, perceived fit is also important for positive brand evaluations. The importance of perceived fit will be further examined in the next paragraphs.

3.6 Congruity theory As mentioned perceived fit is also important for a positive brand evaluation. The lack of fit can influence consumers’ evaluation of the brand alliance and this can be explained with the congruity theory. People seek to maintain and establish consistency among cognitive elements (Kamins & Gupta, 1994). The congruity theory describes that people like to avoid pressure and seek harmony when they make decisions (Osgood & Tannabaum, 1955). Research shows that the level of congruity between products and their associated product category schemas influence the evaluations of consumers (Meyers- Levy & Tybout, 1989). If incongruity or imbalance exists on either product level or brand image level, consumers will seek to resolve the imbalance, and attitude change is one way to achieve a balance state again (Osgood & Tannebaum, 1955).

3.7 Perceived level of fit There are different dimensions of fit. Aaker and Keller (1990) make a distinction between three measurements of fit. The first one is ‘complement’. Complementarity refers to the

25 Forced brand marriages in broadcasting to fight competition. Happily ever after? extent in which consumers’ think that both products can be consumed together while serving the same need. The second one is ‘substitutability’. This refers to the extent in which a product can replace the other. The last one is ‘transfer’. Transfer is related to the skills that are needed to manufacture the product. There is a high fit on ‘transfer’ when consumers’ think that the firm is able to make products in the other product class. (Aaker & Keller, 1990). Perceived level of fit is often measured as the notion of perceived similarity among products or product classes but fit does not have to be based on product feature similarity only (Park, Milberg & Lawson, 1991). Park et al., (1991) state that brands can also have a fit based on “brand concept consistency“ or in other words more abstract associations. Brand concept consistency is described as the similarity of the brand concepts of the two brands, in this case between the involved brands in a brand alliance. It is about the similarities between more abstract meanings and associations (Park et al., 1991). Park et al., (1991) concluded that brand concept consistency and product feature similarity moderate the evaluation of extension products. According to Keller (2013, p.460) any association about the brands that consumers hold in memory may serve as a potential basis for fit. To sum up, there are two clear identified types of fit ‘product feature similarity’ which is about product- related associations and ‘brand concept consistency’, which is about non-product related associations. Brand fit refers to how congruent two brands or a brand and a category are in the mind of the consumer (Uggla, 2004). Both types of fit are very important (Park, Milberg & Lawson, 1991). There are several authors who have concluded that fit is an important factor that influences the evaluations of brand combinations. Simonin and Ruth (1998) conclude that favorable co- branding evaluations can be achieved by ensuring that there is a fit between the product categories (PFS) but also when there is a fit based on brand concept consistency (BCC). Simultaneously, Venkatesh and Mahajan (1997) conclude that incongruity between objects that are combined may result in consumers switching away from the brand to competitors. Eventually this is harmful for the brand images of both brands. Also Aaker and Keller (1990) have looked at the fit between product classes and have examined how consumers form attitudes towards brand extensions. The attitude toward the extension was more positive when there was a fit between the product classes. More importantly, Aaker and Keller (1990) conclude that a poor fit could distort the transfer of positive brand

26 Forced brand marriages in broadcasting to fight competition. Happily ever after? associations but also that it could result in unwanted associations and beliefs. More recent research on fit showed that when brand associations are positive for the individual brands, this can change when an alliance is formed (James, 2005). Brand alliances that resulted in an unfavorable evaluation generated brand associations that were often linked to attributes of the original product category. On the other hand, the brand associations of brand alliances that generated a positive evaluation were linked to the fit between the involved brands (James, 2005). The basis for fit that is chosen for this study is based on brand concept consistency. It is argued that the broadcasting networks that have to merge all have a fit on product feature similarity. The broadcasters make programs for television. However, it could be argued that they do differ in terms of brand concept consistency.

3.8 Different types of brand concept consistency As discussed above, the level of perceived fit based on product feature similarity (PFS) but also based on brand concept consistency (BCC) has an influence on the evaluation of brand combinations and on the image transfer process. However, not only the level of fit seems to be important to take into consideration. There are some possible moderators that could have influence on how different brand alliances with different levels of fit are evaluated (Kim & John, 2008). It is even argued that researchers neglected the moderating factors that could have an influence (Kim & John, 2008). Previous research that tried to fill up this gap focused on the different types of consumers and how these individual differences could influence the evaluation and the importance of a perceived fit (Kim & John, 2008). Research shows that it matters how people construe their environments. Consumers who are more focused on abstract and generalized features evaluate high fit extensions far more positively than moderate fit extensions. However, consumers who are more focused on concrete and contextualized features evaluate moderate fit extensions as positive as high fit extensions (Kim & John, 2008). Zhang and Sood (2002) also conducted a research on the evaluations of brand extensions and the difference between using ‘deep’ and ‘surface’ cues. Zhang and Sood (2002) argued that the age of people plays an important role in how they evaluate and perceive a fit. The result show that children rely more on surface cues (such as similarities between the names or logos) while older people tend to rely on more deep cues (assessing the similarity between the brand extension and the category) when evaluating a brand

27 Forced brand marriages in broadcasting to fight competition. Happily ever after? extension. Children also evaluated the extensions based on ‘surface’ cues more favorable than extensions where no ‘surface’ cues where present (Zhang & Sood, 2002). The study of Zhang and Sood (2002) shows a different approach on perceived fit. The focus is not on the level of fit but on different types of cues where a fit can be based on. More importantly, this research sheds a light on that different cues that are used to evaluate an extension apparently have a different influence on brand evaluations. It seems like not only similarity/dissimilarity is used to categorize the brand alliance but also the features on which the brands are similar/dissimilar seems to have an influence on the positivity of the evaluation. The results of Zhang and Sood (2002) and the gap addressed by Kim and John (2008) form the fundament for the assumption that consumers may define different types of misfit/fit between brand alliances (based on deep or surface cues) which may result in different brand evaluations. In the Dutch broadcasting industry there are brands that are founded on more ‘deep’ underlying features such as religion or political views. An example is KRO which is founded on catholic beliefs (KRO, n.d) or VARA which is a left-oriented broadcasting network (VARA, n.d). These broadcasting networks are founded based on pillars (Dekker & Ester, 1996). The Dutch broadcasting industry also has brands that are founded on more ‘surface’ features such as the target audience they want to reach or the content that they provide. Examples of brands in Dutch broadcasting that are founded on more ‘surface’ features are BNN who tries to reach the young audience (BNN, n.d) and the opposite broadcasting network MAX who tries to reach the older audience (Omroep MAX, n.d), NOS that has the task to provide the news (NOS, n.d) and TROS that is pure focused on amusement (AvroTros, n.d). It is yet unknown if different types of fit in terms of ‘deep’ and ‘surface’ features have a different influence on the brand evaluations.

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Chapter 4. Hypotheses development In the previous chapters the importance of strong brands in the broadcasting industry in terms of customer-based brand equity and the influence of brand alliances on consumer perceptions and image transfer have been discussed. The previous chapters have introduced the associative network theory, the categorization theory, the schema theory and the congruity theory. Based on these theories and the other literature that has been discussed the hypotheses about brand alliances in broadcasting and the role of level of BCC and the role of type of BCC are developed in this section. A strong brand holds the right type of associations (Keller, 2013, p.69). Brand associations need to be strong, favorable and unique to create a positive brand image (Keller, 1993). As the CBBE model shows the brand image is formed by brand associations. In this study the influence of level of BCC and the role of type BCC on the brand associations will be explored. This study will also look at the brand responses, another level in the CBBE pyramid. How do the consumers judge the brand combinations? Will they seriously consider watching programs of this alliance? Do they think that they will like the programs? First the hypotheses will be discussed, followed by the conceptual model of this study.

4.1 Perceived level of BCC Drawing on the schema theory it can be argued that congruent information in terms of a fit based on BCC will be effectively processed and incongruent information will be filtered out (Misra & Beatty, 1990). Incongruent information does not fit in the current brand schema. One of the most important tools for people to interpret the world around them is to use a schema. When new information is available a person tries to fit the new information into a pattern and thus a schema that is used before (Axelrod, 1973). In case of a misfit between brands it is hard to fit the information into a schema because the information is very likely not perceived as congruent. First of all it is thus expected that brand alliances in broadcasting with a fit on BCC will generate more brand associations than brand alliances in broadcasting with a misfit on BCC. A misfit causes incongruence and it is expected that this incongruence puts pressure on the information processing.

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Consequently, the current associative network model of the two brands cannot be enhanced because the information about the alliance does not fit in the current brand schema’s. It is expected that brand associations cannot be retrieved from current established brand schema’s and that these brand associations will thus be ‘lost’ and cannot be transferred to the new associative network model of the alliance. It is expected that a misfit will result in less brand associations. Additionally it is expected that when consumers are presented with information that is congruent with current brand schemas, that the information will be more effectively encoded. Congruent information will be processed (Misra & Beatty, 1990). In case of a fit between the brands, the new information can be processed and the current brand schema’s with their brand associations can be enhanced and transferred. This leads to the following hypothesis:

H1: Brand alliances in broadcasting that have a fit on brand concept consistency (BCC) will generate more brand associations than brand alliances in broadcasting that have a misfit on BCC.

Simultaneously, the schema theory argues that the level of similarity between the information about an entity and the existing scheme of an entity will influence the transfer of specific brand associations (Fiske, 1982). As discussed in the previous chapters an important factor that determines the transfer of brand associations is the perceived fit. When there is a fit, the image transfer of the separate brands will be more likely (Fiske, 1982). The potential that existing brand associations will be enhanced is greater (Milberg, Park & McCarthy, 1997). When there is no fit between brands, it is argued that the brand associations that the separate brands generate cannot spillover. Image transfer or in other words the ‘transfer of meaning’ is taking place when associations of the separate brands (attributes, benefits, attitudes) are transferred to the associations of the brand alliance (McCracken, 1989). As described in hypothesis 1 congruent information is encoded and incongruent information is filtered out (Misra & Beatty, 1990). When brands that are involved in an alliance have a fit and are thus considered as similar, encoding the information and linking the associations is easier. This results in more image transfer of the two brands towards the brand alliance. In case of a misfit, the opposite is expected.

30 Forced brand marriages in broadcasting to fight competition. Happily ever after?

The information is filtered out and encoding and linking associations of both brands is much harder. It is therefore expected that consumers will mention more general brand associations (referring to the product category and referring to the brand alliance itself) when they are faced with a brand alliance that has a misfit. The transfer of specific brand associations is in the case of a misfit distorted by the incongruence. This leads to the following hypothesis:

H2: For brand alliances in broadcasting with a fit on BCC the proportion of general brand associations will be smaller than for brand alliances in broadcasting with a misfit on BCC.

There are several authors who have concluded that perceived fit is also an important factor that influences the evaluation of brand evaluations. Simonin and Ruth (1998) concluded that PFS and the degree of consistency between the images of the participating brands (BCC) influence the evaluations of co-branding. Research shows that it is important that brand alliances do not only have a fit based on concrete dimensions such as product categories but that they also have a fit based on more abstract dimensions (James, Lyman & Foreman, 2006). Völckner and Sattler (2006) even described perceived fit as the most important factor that determines the success of a brand extension. According to the congruity theory people like to establish consistency among cognitive elements and a lack of similarity puts pressure on this consistency (Osgood & Tannebaum, 1955). If people experience imbalance or incongruity due to the lack of fit on either product or brand image level, they will try to balance the situation by for example changing their attitudes towards the new brand combination (Osgood & Tannebaum, 1955). It is expected that brand alliances with a misfit based on BCC will result in such an unbalanced situation. People do not like it when there inconsistency among certain elements (Osgood & Tannebaum, 1955). It is therefore expected that the unbalanced situation will result in a negative state of mind and that this will lead to less favorable brand associations. This leads to the following hypothesis:

H3: For brand alliances in broadcasting with a fit on BCC the favorability of the brand associations will be higher than for brand alliances in broadcasting with a misfit on BCC.

31 Forced brand marriages in broadcasting to fight competition. Happily ever after?

Another important block in the CBBE pyramid are the brand responses (Keller, 2001). Brand quality, brand likeability and brand consideration are one of the important judgments to establish a preferred brand response (Keller, 2001). It is expected that a more negative brand image due to a lack of fit also results in less positive brand responses. For broadcasting networks price is not a point of differentiation. Consumers only have to invest time and effort in the products of the broadcasting networks (Chan- Olmsted, 2006; McDowell, 2006, as cited in Ots, 2008). Brand responses that are relevant for the broadcasting networks are related to the products, the programs that they broadcast and very concrete: the viewing intentions. Broadcasting brands offer experience goods. Since it are experience goods, the quality of the programs is hard to estimate before the consumption (Chang & Chan- Olmsted, 2010). Consumers thus seeks for signals of quality (Reinstein & Snyder, 2005). Consumers seek information that includes cues that help to estimate the quality of the product/service (Roggeveen, Grewal & Gotlieb, 2006). Research shows that perceived fit is considered as an important cue for consumers that reduces purchase risks (Campbell & Goodstein 2001). When a clear misfit is perceived by consumers it is expected that consumers will be confused about the incongruence and that a misfit is not working as a signal of quality. It is expected that the brand alliance with a perceived misfit on BCC will therefore result in more negative brand responses. It is expected that a brand alliance with a misfit on BCC leads to more negative brand attitudes towards the brand alliance and lower quality perceptions with respect to the programs. Furthermore, it also expected that consumers tend to dislike the programs of the brand alliances in broadcasting with a misfit. Finally, it is expected that level of BCC will also have an influence on the more behavioral response: the viewing intentions. It expected that the viewing intentions will be lower for a brand alliance in broadcasting with a misfit on BCC. For brand alliances in broadcasting that have a fit on BCC it is expected that this will result in signaling more quality. Synergy can take place and the brands can strengthen each other. It is also expected that this will result in a more positive brand attitude, higher expected program quality, higher likeability of the programs and higher viewing intentions than towards the brand alliance with a misfit on BCC. The perceived fit on

32 Forced brand marriages in broadcasting to fight competition. Happily ever after?

BCC is thus functioning as a cue that signals quality. H4: For brand alliances in broadcasting with a fit on BCC the brand responses: (a) brand attitudes, (b) expected program quality, (c) likeability of the programs (d) viewing intentions will be more positive than for brand alliances in broadcasting with a misfit on BCC.

4.2 Types of BCC As mentioned before a two-dimensional approach on BCC will be implemented in this study. A lot of attention in the literature is focused on the level of BCC and not on possible moderators (Kim & John, 2008). However, research showed that people use different cues on which they evaluate and judge a brand extension (Zhang & Sood, 2002). Consumers judge the fit on ‘deep’ features such as brand attributes and/or on more ‘surface’ features such as similarity in visual cues. Interesting about the research of Zhang and Sood (200) is that is shows that perceived fit is not only judged on whether or not the brands are similar or dissimilar based on PFS or BCC but that the fit can be judged based on different dimensions. On deep or surface features, or in other words: different types of fit. It could be suggested that one brand combination fits based on ‘deep’ features while other combinations have a fit based on more ‘surface’ features such as that they aim to reach the same target audience. What can be argued is that a fit or misfit based on ‘deep’ features is less easy accessible than a fit based on ‘surface’ features. Zhang and Sood (2002) also conclude that children often use ‘surface’ features to judge a brand extension while older people use a ‘deep’ feature to judge the same extension. Perhaps this is the case because ‘surface’ features are easier to process. What Zhang & Sood (2002) also found is that the preferred fit for children: a brand extension with a fit based on ‘surface’ cues led to a more positive brand evaluation. The findings suggest that a fit based on ‘deep’ cues is maybe more difficult to establish for children. In the context of the Dutch public broadcasters it can be argued that broadcasting brands that are founded based on a pillar such as religion or political preferences have a more ‘deep’ (internal) underlying feature when it comes to a fit or misfit. The feature is less visible. On the other hand, there are brands that are founded on less deep (more external) features such as reaching a specific target audience or providing a certain type of

33 Forced brand marriages in broadcasting to fight competition. Happily ever after? content. These features are more visible and therefore it is stated that these features can be considered as more ‘surface’. When brands are combined that are founded on a ‘surface’ feature, the fit or misfit is more remarkable because it is more visible and not that profound. It is argued that the scores will be extremer for these types of fit and misfit in comparison with the ‘deep’ feature fits. It is expected that consumers experience more incongruence with the ‘surface’ brand misfits/fits because these features are more visible and cause a greater incongruence. Based on this reasoning an interaction effect of type of BCC is expected on the relationships that were defined in hypothesis 1 till 4. This leads to the following hypotheses:

H5: The effect of level of BCC on the amount of the brand associations (H1) will be stronger for the brand alliances in broadcasting that have a misfit/fit on ‘surface’ features than for the brand alliances in broadcasting that have a misfit/fit on ‘deep’ features .

H6: The effect of level of BCC on the proportion of general brand associations (H2) will be stronger for the brand alliances in broadcasting that have a misfit/fit on ‘surface’ features than for the brand alliances in broadcasting that have a misfit/fit on ‘deep’ features.

H7: The effect of level of BCC on the favorability of the brand associations (H3) will be stronger for the brand alliances in broadcasting that have a misfit/fit on ‘surface’ features than for the brand alliances that have a misfit/fit on ‘deep’ features.

H8: The effect of level of BCC on the brand responses (a) brand attitudes, (b) expected program quality, (c) likeability of the programs (d) viewing intentions (H4) will be stronger for brand alliances in broadcasting that have a misfit/fit based on ‘surface’ features than for brand alliances in broadcasting that have a misfit/fit based on ‘deep’ features’.

34 Forced brand marriages in broadcasting to fight competition. Happily ever after?

4.3 Conceptual model In figure 3 the conceptual model with an overview of the hypotheses and the expected relationships between the variables can be seen.

Type of BCC Deep

Surface

H5 H6 Total amount of + H1 H7 + + brand assocations H8 + Level of BCC + H2 Proportion of general Misfit on BCC - brand associations

Fit on BCC + H3 Favorability of brand assocations

+ H4 Brand responses

a) Brand attitude

b) Program quality

c) Likeability programs

d) Viewing intentions

Figure 3. Conceptual model

35 Forced brand marriages in broadcasting to fight competition. Happily ever after?

Chapter 5. Exploratory study for stimuli development 5.1 Research method 5.1.1 Type of research Given the relatively little prior empirical research on types of BCC and brands in broadcasting first an exploratory study is conducted. This study is conducted to identify different levels of BCC and types of BCC in the Dutch broadcasting industry. Using a qualitative approach to study a phenomena of which little is known is preferred by a growing body of research (Starr, 2014). Especially mixed-method research combining quantitative and qualitative approaches are becoming more popular (Starr, 2014). To investigate if there are different types of fit in the Dutch broadcasting industry perceptual mapping is used to get insight in if and how the broadcasting networks are related. By using Multidimensional Scaling in SPSS perceptual representations can be created so that a clear image comes forward in how the broadcasters are related to each other on the basis of perceived fit. Multidimensional scaling is a technique that represents the distances between the objects based on similarity or dissimilarity (Kruskal, 1964). The aim of the exploratory study is to find out how consumers categorize the Dutch broadcasting networks based on shared brand associations. The results of this study will be used to conduct the stimuli for the second research part based on a deductive approach. The hypotheses will be tested by using an experimental survey in the main study. The main study will be presented in chapter six and seven. In order to find out how consumers will categorize the Dutch broadcasting networks based on shared associations a ‘basket study’ was conducted. In this study the assignment is to put a bunch of broadcasters in baskets, based on whether the respondents feel that they fit together. The only criterion is that the respondents put the broadcasters together in a basket if they think that they somehow belong together. Besides that, the respondents are also asked to label the baskets that they have filled. These labels are based on the questions: why are these broadcasters in the same basket? Or/and what do they have in common? Two different version were conducted. One version with all the Dutch public broadcasters and a second version with all of the Dutch public broadcasters and a bunch of commercial broadcasters. The original questionnaire and an example can be found in Appendix 1.

36 Forced brand marriages in broadcasting to fight competition. Happily ever after?

5.1.2 Sample Respondents were invited through private mail and an announcement was placed on a platform for students of a branding course (BlackBoard). Since this study wanted to include respondents from multiple age groups, both versions of the basket study were disseminated under students and ‘older’ respondents aged 40-70. In total 80 respondents participated in this exploratory study.

5.1.3 Procedure The respondents had to fill in the basket study by using the program PowerPoint. In the first slide of the PowerPoint file the introduction was given. In the introduction it was explained that the broadcasters could be found in the middle of the slides and that the broadcasters could be dragged in one of 9 baskets that were placed on the bottom. Not all baskets had to be filled: filling only 1, 2 or 3 baskets was totally fine. It was also explained that broadcasting brands could be copied, so that they could place the broadcasting brands in multiple baskets. Furthermore if they did not know the broadcasting brands they were asked to leave the broadcaster in the middle. Finally, the respondents were asked to label the baskets that they had filled based on the question: what do these brands have in common? To illustrate the assignment an example was given on the second slide. In the third slide the baskets could be filled with the broadcasters. In the last slide the respondents had to fill in their age, nationality and they had to fill in how familiar they were with the broadcasting brands that were used in this study. Finally the respondents were asked to save the file and send it back to the researcher via e-mail or to upload the PowerPoint file on BlackBoard.

5.1.4 Data analysis Multidimensional scaling was used to determine which broadcasting brands fit well together and which broadcasting brands do not fit together. The objects are geographically mapped based on points (Kruskal 1964). Points were given when broadcasting brands were put together in a basket. The distance between the broadcasting brands in the perceptual maps refers to how similar the broadcasting brands are based on any shared association.

37 Forced brand marriages in broadcasting to fight competition. Happily ever after?

5.2 Results: categorization public broadcasters The procedure started with a 12-dimensional solution since there were 13 broadcasting brands. The analysis showed that a 2-dimensional solution fits the best. The scree plot indicated that the ‘stress’ improved from dimension 1 to 2 but that the ‘stress’ did not improve from dimension 2 to 3. Therefore a two-dimensional solution is chosen. A scree test is a procedure to determine how many dimensions (factors) are needed to interpret the data (Cattell, 1966). The ‘stress’ is plotted against the total amount of possible dimensions (Kruskal & Wish, 1978) . In this case: 12. In figure 1 in Appendix 2 the scree plot on the raw normalized stress and the amount of dimensions can be found. The orientation of the two axes in multidimensional scaling are free for interpretation. No definite axes are given. According to these perceptual maps four kind of fits can be identified. As the model shows in figure 4 the purple circle stands for the broadcasting brands that all have a religious approach. They are close together in the perceptual map which indicates that these brands have been combined very often. Examples of labels that were given by the respondents are: ‘religion’, ‘conservative and religious’ and ‘Christianity’. The blue circle stands for the brands that could have a fit on the general brand concept and/or the content they provide. Labels that were given are: ‘entertainment’, ‘Dutch family programs’, ‘family feeling’ and ‘focused on the middle class’. The orange circle for brands that could have a fit based on ‘target audience’. Labels that were given for the combinations BNN and PowNed were related to ‘young’, ‘more for the young people’ and ‘puberal’. The last circle is the pink one with the VPRO and VARA. These broadcasting brands are closely linked in the first perceptual map. However, in figure 6 it can be seen that the in particular the older respondents think that the VARA and VPRO are very similar. The VARA and VPRO are in the perceptual map of the old respondents very closely linked. Labels that were given by these combinations are: ‘liberal’ and ‘progressive’. It can be argued that these brands have a fit based on their political view and that this “fit” is especially perceived by elderly people.

38 Forced brand marriages in broadcasting to fight competition. Happily ever after?

1 WNL

MAX

0,5 EO

NTR NOS KRO

0 NCRV

VPRO TROS BNN AVRO PowNed -0,5 VARA

-1 -1 -0,5 0 0,5 1 Figure 4. The perceptual map of younger (18-30) and older (40+) respondents (N = 42)

Differences based on age As can be seen in figure 5 and 6 on the next page there is a difference in how old and young participants categorize the public broadcasters. The elderly make a clearer distinction between certain groups of public broadcasters. This can be seen because the distances between most of the brands that are clustered are smaller (figure 6). The distances between the brands in the perceptual map of the young people are greater (figure 5). Besides, the clusters of the elderly people are more dispersed. The explanation could be that the elderly do perceive a fit between certain broadcasters sooner because they have more brand knowledge. Another remarkable finding is that younger people see the perceived fit between the relative ‘new’ broadcasting brands PowNed and BNN maybe sooner than the elderly. Overall it can be concluded that the four clusters based on the identified dimensions of fit can be seen by the younger and older respondents. The only big difference is that the political fit (pink circle) is less perceived by the younger respondents. The results indicate that young respondents think that these political oriented brands could also fit with the TROS or AVRO.

39 Forced brand marriages in broadcasting to fight competition. Happily ever after?

1

MAX WNL

0,5 NOS TROS NTR VPRO VARA 0 AVRO

NCRV BNN PowNed -0,5 KRO

EO

-1 -1 -0,5 0 0,5 1 Figure 5 . The perceptual map of younger (18-30) respondents (N = 27)

1

WNL AVRO 0,5 TROS MAX

EO NCRV NOS NTR 0 KRO

-0,5 VARA VPRO BNN PowNed

-1 -1 -0,5 0 0,5 1 Figure 6. Perceptual map of the older (40+) respondents (N = 15)

40 Forced brand marriages in broadcasting to fight competition. Happily ever after?

5.3 Results: categorization public broadcasters and commercial broadcasters The procedure started with a 21-dimensional solution since there were 22 broadcasting brands. The analysis showed that a 2-dimensional solution fits the best. The scree plot again indicated that the ‘stress’ improved from dimension 1 to 2. After dimension 2 the ‘stress’ is not improved. A two-dimensional solution is thus chosen. In figure 2 in Appendix 2 the scree plot on the normalized raw stress and the different dimensions can be found. The results show that even when commercial broadcasters come in, the four types of fit are still visible. As can be seen in figure 7 on the next page the religious broadcasting brands: EO, KRO and NCRV are still clustered together (purple circle). Labels for these brands do refer to the religious approach that all broadcaster have. Besides, TROS and AVRO are still perceived as similar (blue circle). Examples of labels that were given are ‘entertaining programs’, ‘mostly entertainment’ and ‘fun’. The labels are related to the content that TROS and AVRO provide, more ‘surface’ features. As can be seen BNN and PowNed (orange circle) are also still clustered together based on the more ‘surface’ features according to the labels that were given, for example: ‘young audience’, ‘focused on a young public’ and ‘popular broadcasters for younger people’. VPRO and VARA the broadcasting brands that fit well together based on political views, are also still closely linked (pink circle). There is a clear distinction made by the participants between the public and commercial broadcasters as can be seen due to the fact that almost all public broadcasters are left centered and the commercial ones are right centered. What is very interesting is that two public broadcasters: BNN and PowNed are closely linked to two commercial broadcasters: MTV and Comedy Central (yellow circle). Based on the labels given by the participants BNN and MTV and Comedy Central fit well together because they stand for : ‘fun’ ‘nice comedy’ and ‘easy to watch tv’. For BNN and MTV respondents mentioned that they are both ‘young’ broadcasters focused on a ‘young target audience’. It can be argued that there can be a fit based on a more ‘surface’ feature namely: the target audience that both broadcasting brands aim to reach. It can be seen that the clear border between the public broadcasters and commercial broadcasters blurs there. The public broadcaster BNN is closer to the right side of the commercial broadcasters than towards the left side: the public broadcasters. BNN and MTV and/or Comedy Central do have a fit according to

41 Forced brand marriages in broadcasting to fight competition. Happily ever after? the respondents despite the fact that it is a public versus a commercial broadcaster.Therefore the pre-study for the main study will also include commercial broadcasters that fit well with public broadcasters.

1 WNL PowNed MTV NOS BNN Comedy 0,5 MAX Central NTR TLC

0 EO KRO Veronica NCRV TROS Net 5 VPRO AVRO SBS 6 VARA RTL 5 -0,5 RTL 7 RTL 4

-1 -1,0 -0,5 0,0 0,5 1,0

Figure 7. Perceptual map of the younger (18-30) and older (40+) respondents (N = 38)

Differences based on age The results also indicate that there is a difference in how younger and older people categorize the public broadcasters (blue symbols) and commercial broadcasters (purple symbols). The differences are portrayed in figure 8 and figure 9 on the next page. What is remarkable is that younger people see less disimilarities between the public broadcasting brands than older people. An explanation for this can be that older people know more about the roots of the public broadcasting brands and that this brand knowledge could result in pronouning the dissimalarities more than younger people. The exact opposite is going on for the older people and the commercial broadcasters. According to the results older people see more similairities between the commercial broadcasters than younger people. Furthermore, the older people tend to see more dissimilarities between the public broadcasters even when commercial broadcasters come in. The axes are free for interpretation with multidimensional scaling but what can be seen is that for the younger people public broadcasters are left centered and the commercial ones are right centered while for the elderly the exact opposite is true. The x-

42 Forced brand marriages in broadcasting to fight competition. Happily ever after? as could stand for the brand familairity or brand knowledge. This would mean that elderly are more familair with public broadcasters and less familair with commercial broadcasters in comparison with the younger people.

1 Comedy WNL PowNed Central MAX MTV 0,5 BNN NOS NTR EO TLC 0 KRO NCRV Veronica Net 5 AVRO TROS VPRO VARA SBS 6 -0,5 RTL 4 RTL 5 RTL 7

-1 -1 -0,5 0 0,5 1

Figure 8 . The perceptual map of younger (18-30) respondents (N = 26)

1 PowNed WNL NOS MTV BNN 0,5 NTR Comedy TLC Central KRO 0 NCRV EO Veronica RTL 7 RTL 5 Net 5 VPRO RTL 4 AVRO VARA -0,5 SBS 6 MAX TROS

-1 -1,0 -0,5 0,0 0,5 1,0

Figure 9. Perceptual map of the older (40+) respondents (N = 12)

43 Forced brand marriages in broadcasting to fight competition. Happily ever after?

Chapter 6. Methodology main study 6.1 Research design In the main study there are two independent variables: the level of BCC and the type of BCC. The hypothesis will be tested by using a 2 x 4 experimental between-subjects design: level of BCC (misfit vs. fit) x type of BCC (political, religion, target audience vs. program content). Eight combinations of broadcasting brands that each have a different type of BCC and a different level of BCC will be tested. A quantitative approach is the most appropriate in order to test the causal relationships. An online experiment is chosen that is conducted in Qualtrics. A between subjects design is chosen to limit the chance of a carrying over effects that repeated measurements can cause. Randomization is used to reduce the chance that the differences between the tested groups are having an influence on the relationships that will be tested. Different scenarios are developed in which different broadcasting brands that have a fit or misfit on one of the dimensions will have to merge. Different types of BCC and levels of BCC between the broadcasting brands will be employed, in order to test what the effect is of these manipulations on the perceptions of consumers. In the next paragraphs the pre-tests that are conducted to select the stimuli that are used in this experiment will be discussed.

6.2 Pre-testing To ensure that the manipulations will work out two pre-tests are conducted. Brand combinations are selected based on the outcomes of the exploratory study. Public broadcasters and commercial broadcasters were included since the results of the pre-study showed that some of the public broadcasters do fit well with commercial ones. The goal of the pre-tests was to examine which broadcasting brand combinations have the highest and lowest level of BCC and also to test if the broadcasting brands are familiar. The original questionnaire that is used for this pre-test can be found in Appendix 3.

6.2.1 Pre-test 1 A within-subjects design is used where 34 respondents (varying in age) rated the level of BCC of 12 broadcasting brand combinations that were selected based on the results of the

44 Forced brand marriages in broadcasting to fight competition. Happily ever after? exploratory study. The brand concept consistency was measured by one statement measured on7-point Likert scale adapted from the scale of Bhat & Reddy (2001), namely: “I think brand A fits well with the brand image of brand B” . A bunch of brand combinations that were similar and/or dissimilar according to the results of the exploratory study were used for in the pre-study. First of all the pre-study showed that the respondents were quite familiar with all of the broadcasting brands that were tested. The brand familiarity with the broadcasting brands can be seen in table 1.

Table 1. Mean scores and Std. deviations on the variable brand familiarity

Brand familiarity Mean SD BNN 5.71 1.64 EO 4.47 2.06 KRO 5.03 1.71 PowNed 4.68 1.95 MAX 4.18 1.83 NOS 6.35 1.23 VARA 5.74 1.36 VPRO 4.65 1.81 Comedy Central 5.18 2.08 MTV 5.65 1.74

A repeated measurement ANOVA shows that the combination with a misfit based on religion (EOPowNed) scored significantly lower on level of BCC ( M = 1.14, SD = 0.36) than the fit based on religion (EOKRO) ( M = 5.14, SD = 1.56), p < 0.00 . The results also show that the misfit based on target audience (BNNMAX) has a significantly lower level of BCC ( M= 1.48, SD = 0.93) than the fit based on target audience (BNNMTV) ( M = 5.24, SD = 1.52), p < 0.00. BNNComedyCentral also seems to have a fit ( M = 5.27 , SD = 1.43 ). However the brand familiarity of Comedy Central is lower than for MTV. That is why BNNMTV is a better option. BNN and MTV are quite similar in brand familiarity. Furthermore the results show that VARA fits very well with VPRO ( M = 5.52, SD

45 Forced brand marriages in broadcasting to fight competition. Happily ever after?

= 1.17). However the VARA combined with (NOS) ( M = 2.48, SD = 1.37) and PowNed (M = 2.76, SD = 1.22) does not lead to a misfit. It’s more a low fit and not a misfit. Therefore in the main study another brand is chosen to combine with VARA, namely WNL. This brand is chosen because it is a right-oriented brand and VARA can be seen as a left-oriented brand together with VPRO. The exploratory study already showed this. There are only two brand combinations that scored below a 2 on the BCC scale: EOPowNed and BNNMTV. That is why these brand combinations are selected for the misfits. Three brand combinations with a clear fit that are selected are: VARAVPRO, BNNMTV and EOKRO. These brand combinations all scored above the 5 on the BCC scale. Looking again at the results of the exploratory study another type of BCC can be identified. A misfit/fit based on content. NOS is a task-broadcaster focused on the news and sports. TROS on the other hand is a brand that is the first broadcaster that was founded on amusement. According to the exploratory study TROS fits with AVRO and the reason could be that is because they focus on the same content: mainly amusement.

6.2.2 Pre-test 2 Since the combinations NOSTROS, TROSAVRO and VARAWNL were not tested in the first pre-study, a small second pre-study was conducted ( N = 15). In this study a free association procedure was used. The respondents were asked to write down anything they think about when they think about this brand combination. They were exposed to all three combinations. Randomization was used for the order of the brand combinations. A free association task was chosen because it is a common procedure to elicit responses that are representative for the knowledge that people have and their structures of the content (Deese, 1966). Free-association tasks have a long history in social and behavioural sciences (Stone, 1983 as cited in Wyer & Srull, 2014, p.88). In Appendix 4 the wordclouds of the brand associations that each of the combination generated can be found. Furthermore, the brand associations were categorized. The categorization table of the brand associations can also be found in Appendix 4.

46 Forced brand marriages in broadcasting to fight competition. Happily ever after?

NOSTROS- misfit based on content The results show that especially the brand combination NOSTROS leads to confusion. Examples of associations that were mentioned are: ‘clash’, ‘no-way’, ‘strange’ and ‘cannot be combined’. These associations clearly relate to the fact that there is a misfit between those brands. This combination generated 59 brand associations in total. Of these brand associations 27.12% refers to a misfit. Furthermore, a lot of people refer to amusement vs. news/journal, serious vs. simple entertainment. These associations refer to the content the broadcasters produce and also refer to the differences in the content. Of all the brand associations 47.46% refers to something that is related to the content that the broadcasters provide. Besides that, also negative attitude associations are generated such as: ‘degradation’, ‘less quality’, ‘cannot be trusted’ and ‘stupid’. Since the small survey indicates that people indeed refer to a clear misfit and also refer a lot towards the misfit based on content, NOSTROS is selected as a brand that has a misfit based on content.

TROSAVRO – fit based on content This combination generated 50 brand associations in total. A lot of associations (48%) refer to specific content such as programs (‘Wie is de mol’, ‘Buitenhof’, ‘Eenvandaag’, ‘Lingo’) but also to presenters/spokespersons that belong to one of the broadcasters (‘Jan- Smit’, ‘Lucile Werner’, ‘Art Rooijakkers’). Furthermore there are associations referring to the fact that they have something in common ‘both generic’ and ‘both folksy’. None of the associations was referring to the misfit between the broadcasters. Of all brand associations 27.12% referred to a fit. Examples are: ‘both focused on entertainment’, ‘better together’. Building on the results of the exploratory study in which TROSAVRO were also considered as similar and the results of this free-association task, the brand combination TROSAVRO is also implemented in the study as a fit based on a more surface feature: a fit based on the content they provide.

VARAWNL – misfit based on political views VARAWNL is the third combination that was tested. This combination generated less brand associations namely: 44. What the results indicate is that there are indeed associations that refer to the difference between the broadcasters based on political views (20.45% of the total brand associations). Such as: ‘left oriented broadcaster’,

47 Forced brand marriages in broadcasting to fight competition. Happily ever after?

‘progressive’, ‘liberal’, ‘red’ and ‘left vs. right’ and even a specific Dutch political party was mentioned: ‘pvda’. There also associations that refer to the fact that they do not fit together like: ‘that cannot be good’, ‘weird’ and ‘does not fit’ (18.18%). A point of caution is that some associations also refer to the content (specific programs: ‘DWDD’ and ‘pauw & witteman’). Two respondents referred to the unfamiliarity with WNL (‘don’t know WNL’). However, since most of the respondents are apparently familiar with WNL and brand associations do relate to the political differences (left and right oriented) the combination is included in the main study as a misfit based on political views. A point of caution will be the brand familiarity. Brand familiarity is added as a control variable in the main study.

6.3 Stimuli selection The brands and the combinations that are selected for the second part of the research are based on the results of the exploratory study and the pre-tests. The independent variables are manipulated but in a real-life setting. Also, real broadcasting brands rather than fictitious ones, are used in this study so that real brand associations can be triggered by the brand alliances. Broadcasting brands are selected based on the identified prototypes of the type of BCC (religion, political, target audience and program content). The prototype brands are combined with brands that have a misfit based on that type of BCC or a fit based on that type of BCC. In the perceptual maps it can be seen that EO (evangelical public broadcaster) fits with the KRO (Catholic public broadcaster) but does not fit at all with PowNed. PowNed is also a public broadcasters who claims to serve the network generation and argues heavily against baby boomers and a lot of other things (PowNed, n.d). Therefore EO is selected as prototype for religious type of fit and has a fit with KRO and a misfit with PowNed. Furthermore, it can be seen that VARA (left oriented view) fits with VPRO (left oriented view) but not with WNL (right oriented view). VARA is therefore selected as the prototype for political type of BCC. An interesting finding is also that one public broadcaster seems to fit very well with some of the commercial broadcasters. This public broadcasting network is BNN (focused on the target group: youth and young adults between 15 and 35 year) (BNN, n.d). BNN is therefore selected as prototype on the target audience type of BCC. As can be

48 Forced brand marriages in broadcasting to fight competition. Happily ever after? seen BNN fits very well with the commercial broadcaster MTV (current target audience is teenagers and young adults) (“MTV”, n.d). BNN has a clear misfit with MAX (focus on target audience: 50 years and older) (MAX, n.d). The last type of BCC is about the content that the public broadcasters provide. The public broadcasting system in the Netherlands provides the public with information, entertainment, culture and education. One of the broadcasters that is clearly focused on entertainment is TROS (AvroTros, n.d). It was the first public broadcaster that was founded on the belief that people needed programs that were fun. As can be seen in the perceptual map TROS clearly does not fit with the public broadcaster NOS. NOS provides news, sports and the broadcast important events (NOS, n.d). NOS and TROS clearly differ in the type of programs that they offer. On the other hand TROS and AVRO fit together. These two public broadcasters are closely related in the perceptual maps. AVRO is also a broadcaster without a religious background or political preference (AvroTros, n.d). Based on the results of the exploratory study TROS is selected as prototype brand based on program content BCC. In figure 10 the stimuli selection is visually portrayed according to the results of the exploratory study. In table 2 on the next page an overview of the selected stimuli can be found.

1

WNL PowNed BNN MTV 0,5 NOS Comedy MAX Central NTR TLC

0 EO KRO Veronica NCRV TROS Net 5 VPRO AVRO SBS 6 VARA RTL 5 -0,5 RTL 7 RTL 4

-1 -1,0 -0,5 0,0 0,5 1,0 Figure 10. Prototypes (blue squares) combined with misfit on BCC (pink arrow) and fit on BCC (green circle)

49 Forced brand marriages in broadcasting to fight competition. Happily ever after?

Table 2. Research design with the selected stimuli IV: Level of BCC IV: Type of BCC Specific Prototype brand Misfit Fit Deep Religion EO PowNed KRO Political VARA WNL VPRO Surface Target audience BNN MAX MTV Content TROS NOS AVRO

The eight brand alliances in broadcasting that are chosen for this study were incorporated in a news article of NU.nl. NU.nl is the largest online news brand in the Netherlands with 2.5 million unique daily visitors (Sanoma, n.d). NU.nl produces 300 items a day focused on national and international news. Since the reach of NU.nl is so enormous it is expected that all the respondents will recognize the format. This format was chosen because the forced mergers in broadcasting were a ‘hot’ topic in the Dutch news. A news article seemed appropriate in terms of realism. The news articles were exactly the same. There was only variation in the different brand combinations, in terms of the logo’s and the brand names. An example of the stimuli can be found in Appendix 5. The article stated that the broadcasting brands had to merge due to the recent cuts in the media. A bit of background information on the recent media cuts was given. Furthermore the article informed the readers that probably soon people would watch and listen to programs made by BRAND-A/BRAND-B. It was stated that the broadcasters do not only want to merge on organization level but also on brand level: so a shared logo and programs from one merged brand. A quote of one of the directors of the broadcasting networks was given to make it even more realistic. The researcher showed two examples of the stimuli materials (one brand combination with a fit and one brand combination with a misfit) to ten people that were not familiar with the research project and asked to rate the stimuli on credibility (1 “Not credible at all” till 7 “Very credible”) and realism (1 “Not realistic at all” till 7 “Very realistic”. Furthermore the respondents were asked how familiar they were with the website NU.nl (1 “Not familiar at all” till 7 “ Very familiar”). Randomization was used

50 Forced brand marriages in broadcasting to fight competition. Happily ever after? for providing the stimuli. So five people judged the news article about a brand combination with a fit and five people judged the news article about a brand combination with a misfit. The results show that the stimuli materials can be considered as credible ( M = 6.20, SD = 0.79) and realistic ( M = 5.80, SD = 1.03). Furthermore the respondents are familiar with the news website NU.nl ( M = 6.50, SD = 0.71).

6.4 Sample The online survey was disseminated under students and acquaintances via social media and email. A snowball sampling method is used because it was less easy to get acquire people above the age of 40. Snowball sampling is created through referrals of the respondents that were already recruited (Berg, 1988). Respondents were thus asked to also spread the survey in their personal networks. People that were approached for the exploratory study were not approached again for the main study. Also the respondents that were approached for one of the pre-studies were not approached again.

6.5 Procedure The experiment that is conducted is an online experimental survey. The experiment is conducted in Qualtrics. Qualtrics is an online computer program, which allows the participants to fill in the survey in their own environment. An online survey is conducted because this method offers the most efficient way of gathering a lot of data which is necessary to test the hypotheses. It was important that the participants were Dutch since it is about Dutch public broadcasting brands. Eight different surveys were developed for the eight different brand combinations that need to be tested. In Qualtrics all respondents are randomly assigned to one of the eight conditions. In the survey flow the age of the respondents was taken into account so that there would be a more equal distribution between older (> 40 years old) and younger people (< 40 years old) across the eight conditions.

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6.6 Measures In the following paragraphs the different measures that are used in the main study will be explained. In Appendix 6 one of the original questionnaires of the main study can be found.

6.6.1.Independent variables Level of BCC The first independent variable in this research is the perceived level of brand concept consistency. To control if the manipulations in the stimuli worked for perceived level of BCC a scale is derived from from Bhat & Reddy (2001). This scale is developed for measuring brand concept consistency. The scale is concerned with the similarity between broadcasters’ brand images. Questions will be related to if respondents think that the brands in the combination portray similar images and whether they convey the same impressions. Seven-point scales will be used with 1 as “Strongly Disagree” and 7 as “Strongly Agree”.

Type of BCC The second independent variable in this research is the perceived type of BCC. This variable consists out of a religion misfit/fit, political misfit/fit, target audience misfit/fit and program content misfit/fit. To control if the manipulations for type of BCC succeeded a qualitative question is asked about the type of BCC. Namely: “For this study is important to know why you think BRAND A and BRAND B fit or do not fit together. Give a brief description based on the questions: What have BRAND A and BRAND B in common or what have they not in common? And why do you think BRAND A and BRAND B fit or do not fit together?” A qualitative approach is chosen because little is known about different types of fit and how people judge a brand fit in broadcasting. The answers are coded and to check whether the developed categorization key is reliable, the inter-rater reliability is checked by using three different coders that each coded 50 items. The results on the inter-rater reliability can be found in chapter 7. When a certain type of BCC is mentioned this will be coded according to the categorization key. When an answer relates to multiple types of fit (for example target audience as well as program content) the first mentioned type of fit

52 Forced brand marriages in broadcasting to fight competition. Happily ever after? will be taken into account. The categorization key that is used can be found in Appendix 7. Since the brand associations were given in Dutch, the categorization key is also in Dutch. There are six main categories: 0) unknown, 1) general misfit/fit 2) misfit/fit based on political views, 3) misfit/fit based on religion, 4) misfit/fit based on target audience, 5) misfit/fit based on content and 6) remaining. For illustration purposes an example can be found in table 3.

Table 3. Two categorization examples of type of BCC

Answer of the respondent: Category? Reason? “BNN and MAX do absolutely not fit Category 4: It is about the elderly vs. younger together. What should the elderly think of Target audience cheeky brats. The answer refers to those cheeky young brats? And vice versa.” a misfit based on target audience.

"Live news from the music square? This Category 5: The respondents clearly refers to a must be a joke. NOS provides high-quality Content misfit by stating that it can never programs with a focus on news and sports. work out. The respondent also TROS, is simple and banal entertainment. clearly gives a reason for the That can never work out”. misfit based on the content that the broadcasters provide. News and sports vs. banal entertainment.

6.6.2 Dependent variables Amount of brand associations The strength of an associative network is dependent on the strength of the brand nodes in the memory and thus to brand awareness (Rossiter & Percy, 1987 in Keller, 1993). Strength is a function of both the amount and quality of the nodes. In this study the strength of the network will be measured by the quantity, namely the amount of brand associations. A free association procedure will be used. This is a technique of mapping associations among concepts. Respondents are asked to write down everything that comes to mind when they think about a certain concept (Nelson, McEvoy & Schreiber, 2004). The respondents will be asked to write down any association they have when they think of the broadcasting alliance (positive and/or negative associations).. For every association a new line has to be used. Respondents can fill in 10 lines with associations.

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Proportion of general brand associations The dependent variable proportion of general brand associations will be determined by coding the brand associations that the respondents gave for the brand combinations. A small pre-test ( N = 15) was conducted to test which associations belong to the category ‘broadcasters’ and can thus be seen as general brand associations that belong the product category. Examples are: ‘Nederland, 1, 2, 3’, ‘zendtijd’, ‘tv kijken’, ‘presentatoren’, ‘televisie’, ‘NPO’, ‘radio’, ‘uitzendiggemist’ and ‘groot verdieners’. Based on the results of this small study the categorization key is developed. Brand associations were coded according to the developed categorization key. The categories are: 0) Unknown, 1) General/Shared/Category associations, 2) Associations referring to the alliance itself and 3) Remaining. The categorization key can be found in Appendix 8. The proportion of general brand associations consist out of the general brand associations: referring to the product category (according to the results of the pre-study) + brand associations relating to the brand alliance itself. The percentage of these general brand associations of the total amount of brand associations is considered as the proportion of general brand associations. To check the reliability of the categorization key, the inter-rater reliability is checked by using three different coders that each coded the brand associations of 50 respondents according to the developed categorization key. In chapter 7 the inter-rater- reliability will be tested by conducting Fleiss’ kappa. For illustration purposes a small part of the categorization key of the brand associations is portrayed in table 4 on the next page.

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Table 4. A small part of the categorization key Category Examples brand associations Reason?

0. Unknown Geen idee, weet niet, onbekend Any association that refers to nescience

1. General/ Shared/Category Ned 1, 2 en 3, Hilversum, NPO, According to the pre-study this omroepen, series, landelijke associations belongs to the product omroepen, tv-gids, verzuiling, category and can be considered as traditioneel, uitzendinggemist ‘general’.

2. To the alliance itself Fusie, samen gaan, moeten Associations that specifically refer to samen, bezuinigingen, the merger and/or alliance itself gedwongen samen

3. Remaining Jan Smit, journal, I don’t like it, If an association does not belong in Lucille Werner, Quiz, category 0,1 or 2. Associations that conservatief, comedy refer to specific presenters, specific programs, attitudes, feelings

Favorability of the brand associations Subsequently, the respondents will be asked to indicate for each of the brands associations they came up with if these associations are negative, neutral or positive. The favorability is measured on a 7-point Likert scale with 1 as “Very negative” and 7 as “Very positive”. For the analysis the mean score on the favorability of the brand associations will be calculated.

Brand responses: a) brand attitude, b) expected quality of the programs, c) expected likeability of the programs and d) viewing intentions Brand responses refer to creating the preferred responses in terms of brand judgments and brand feelings. The overall brand response is also taken into account. Brand attitude refers to a consumers’ overall evaluation of a brand (Keller, 1993). Brand attitudes can be seen as “the overall evaluations of the brand in terms of its quality and the satisfaction it generates” (Ambler, Bhattacharya, Edell, Keller, Lemon & Mittal, 2002, p.15). The scale that will be used is developed by Osgood, Suci and Tannenbaum (1957) and Simonin and Ruth (1998). Statements will be related to the feelings that the respondents have towards the broadcasting brand alliance in terms of good/bad and negative/positive. Seven-point

55 Forced brand marriages in broadcasting to fight competition. Happily ever after? scales will be used with the descriptors very good–very bad and very positive–very negative. Based on the scale of Washburn, Till and Priluck (2004) the expected quality of the programs will be measured by two items. “I expect that the quality of the programs of BRAND A – BRAND B will be high” and “The quality of the programs that BRAND A- BRAND B will offer must be very good” . For the expected likeability of the programs an attitude measure is used inspired on the scale of Osgood, Suci and Tannebaum (1957). Statements will be related to the feelings that the respondents have towards the programs that the new broadcasting brand alliance will offer. Seven-point scales will be used with the descriptors very good–very bad, very unattractive – very attractive and very stupid – very nice. To measure viewing intentions one item is adopted from a scale of Keller and Aaker (1992) that originally measured purchase intentions. A seven-point scale will be used with 1 as “Strongly Disagree” and 7 as “Strongly Agree”. The following statement measures the viewing intentions: “It is likely that I will watch programs of BRAND A- BRAND B” .

6.6.3 Control variables In order to clarify the relationships between the variables in this study a few control variables must be considered. The first control variable that is important to take into account is the age of the respondents. The exploratory study namely shows that older people categorize the public broadcasting networks but also the commercial broadcasting networks differently than younger people. Another important control variable is familiarity with the broadcasting networks. If the respondents is not familiar with one of the broadcasters, this could have an influence on the image transfer and also on how the BCC is perceived in terms of level of BCC but also in terms of type of BCC. To check whether the respondents are familiar with the brands, the respondents will be asked for each broadcasting brand that is involved, if they know the brand or not. Seven-point scales will be used with 1 as “Strongly Disagree” and 7 as “Strongly Agree”. Other variables that could have an influence on the relationships between the variables in this study are the pre-existing attitudes towards the broadcasting networks, the

56 Forced brand marriages in broadcasting to fight competition. Happily ever after? pre-existing quality assumptions towards the programs and the attitude towards the Dutch public broadcasting system. Attitude towards the Dutch public broadcasting system will be measured by the following items: “I have a positive attitude towards the Nederlandse Publieke Omroep” , “I think the quality of the Nederlandse Publieke Omroep is high” , “I would not mind if the Nederlandse Publieke Omroep would disappear” , “I would not miss the programs of the Nederlandse Publieke Omroep” . All statements can be answered with a seven-point scale with 1 as “Strongly Disagree” and 7 as “Strongly Agree”. Pre-existing quality assumptions about the programs will be measured for the separate brands before the respondents are exposed to the manipulations. Based on the scale of Washburn, Till and Priluck (2004) the quality of the broadcasting network will be measured by one item:“I think that the quality of the programs of brand A (B) is high”. Pre-existing attitudes will also be measured for the separate brands before the respondents are exposed to the manipulations with the statement: “I have a positive attitude towards brand A (B)” . Both items can be answered with a seven-point Likert scale with 1 as “Strongly Disagree” and 7 as “Strongly Agree”.

6.6.4 Demographic variables To get a good insight in the respondents’ profiles gender, education level and nationality will also be measured.

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Chapter 7. Results main study In this chapter the results of the main study will be presented. SPSS Statistics 22 from IBM is used to analyze the data. First an overview of the respondents profile will be given. Then the data preparation will be described. The reliability analysis, the inter-rater reliability checks, the manipulation checks and the tests with the control variables will be presented. Followed by the hypotheses testing and additional insights.

7.1 Respondent profile In total 258 respondents started the online experiment. However, 69 respondents did not finish the whole questionnaire. In total 189 respondents finished the experiment and are taken into account for the analysis. A reason for this high drop-out is that the survey maybe took too long to finish. Since a free association procedure was used more cognitive effort is needed. All respondents are randomly assigned to one of the eight conditions. In the survey flow the age of the respondents was taken into account so that there would be a more equal distribution between older (> 40 years old) and younger people (< 40 years old) across the eight conditions. The number of respondents differs across the conditions because there was a drop-out of respondents. However, the numbers are still very close to each other so this will not form a problem for the analysis. In table 5 the distribution of the respondents across the eight conditions can be found.

Table 5. Distribution of respondents across conditions Type of BCC Level of BCC Low High Political 20 21 Religious 28 23 Target audience 23 22 Content 28 24

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The major part of the respondents is female (63.0%). Unfortunately this is not an optimal reflection of society. However it is expected that this will not be very problematic for the results since randomization is used and thus gender varies across the conditions. More importantly, the age of the respondents is more equally distributed. The major part (40.2%) of the respondents is young (18-25 years old). With 23.3% belonging in the age category 26-40 years old and 37% belonging in the age category 41-71. Younger people are thus a bit overrepresented. However, there was an equal distribution across the categories based on age, with an overrepresentation of young people in every condition. The level of education is not quite equally divided. Most of the respondents have a high education degree (HBO 34.4%) or have a University degree (42.9%). Unfortunately this is not an optimal reflection of the Dutch society. MBO is underrepresented with 10.1% and HBO and University are overrepresented. Of the Dutch people more than 30% has a degree in MBO and only 28.8% has a degree higher than HBO (CBS, 2014). In figure 11 the total distribution of the level of education can be seen.

Education level

2.1% 3.2%

6.9% High school 10.1% VMBO 42.9% HAVO VWO MBO 34.4% HBO University

Figure 11. Distribution of the level of education of the respondents.

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7.2 Data preparation 7.2.1 Consistency and reliability checks There are multiple constructs that are measured with multiple items. To check if these constructs have a high internal consistency a principal component factor analysis (PCA) will be conducted. In order to test the reliability of these constructs the Cronbach’s Alpha will be reported. Cronbach’s Alpha needs to be greater than .70 to confirm that the construct is reliable (Field, 2009). For the following variables a PCA and Cronbach’s Alpha will be reported: brand attitude, expected program quality, brand concept consistency and the attitude towards the NPO (corporate brand).

Brand attitude The items that measure the dependent variable: brand attitude indeed measure one construct. The PCA shows that the two items measuring brand attitude form an one dimensional scale: only one component has an initial eigenvalue of 1.92. Both items correlate positively with this first component. Both items have a high consistency (component load is 0.98) . These items explain 96.21% of the total variance in this construct. The two items form a very reliable scale. The Cronbach’s Alpha is 0.96.

Expected program quality The PCA shows that the two items form a one dimensional scale that measures the dependent variable: expected program quality. Only one component has an initial eigenvalue above 1. The eigenvalue is 1.81 and the items explain 90.25% of the total variance in this construct. Again both items correlate positively with this component. The component loads are 0.95. The scale is also reliable with a Cronbach’s Alpha of 0.89.

Likeability programs Three items measure the dependent variable: likeability of the programs. The PCA shows that the three items form a one dimensional scale. One component has a initial eigenvalue of 2.57. The three items together explain 85.55% of the total variance in this construct. All items correlate positively with this component. All components loadings are above 0.91. The reliability of the scale is also very high and can therefore be considered as internal consistent. The Cronbach’s Alpha is 0.91.

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Brand concept-consistency The items that measure the BCC form a one dimensional construct. One component has a eigenvalue of 1.74 and explains 86.80% of the total variance in this component. The two items both correlate positively with this component (component load is 0.93).The scale is also internally consistent. The Cronbach’s Alpha is 0.85.

Attitude towards the NPO (corporate brand) The four items that measure the control variable: general attitude towards the NPO, form a one dimensional scale according to the PCA. One component has an initial eigenvalue of 2.78. The four items explain 69.40% of the total variance in this construct. All items correlate positively with this construct. All components loadings are above 0.81. Furthermore the scale is also very reliable. The Cronbach’s Alpha is 0.84 and could not be improved if an item is deleted.

7.2.2 Inter-rater reliability checks Some of the variables used in this research are measured based on open-answers rather than on established scales. Assessing inter-rater reliability is an important method for ensuring reliability and validity of these constructs (Armstrong, Gosling, Weinman, Marteau, 1997). Inter-rater reliability is a measure that is used to examine the agreement between different coders on a variable. For the following variables the inter-rater reliability has to be measured: the independent variable: type of BCC and the dependent variable: proportion of general associations. Fleiss’s Kappa will be conducted for type of BCC since there are more than two coders. Cohen (1960) made his Kohen’s Kappa only suitable for two coders. Fleiss (1971) provides a formula that is suitable for multiple coders. SPSS cannot be used because there is not a standard procedure for Fleiss’ Kappa. The Fleiss’s Kappa formula is used to calculate the inter-rater reliability for type of BCC since this variable is measured on a nominal scale based on categories. However, the proportion of general brand associations is a ratio variable. Fleiss’s Kappa cannot be calculated then. To estimate the inter-rater reliability a Pearson correlation will be used as an estimator.

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Inter-reliability type of BCC First the proportion of agreement on each item is calculated. Fifty items are included to calculate the Fleiss’s Kappa. Then the proportion of agreements on the different categories of the variable will be calculated. Type of BCC had six categories as can be seen in the categorization key (Appendix 7). If Fleiss’s Kappa is above 0.75 the strength of agreement is very good (Fleiss, Levin & Paik 2003). The agreement on the independent variable type of BCC is high. The resulting Fleiss’s Kappa is strong namely: 0.80.

Inter-reliability proportion of general brand associations Since there are three coders the Pearson correlation coefficient is calculated for coder 1 & coder 2, for coder 2 & coder 3 and for coder 1 & 3. The category that is important is the category referring to general brand associations and brand associations that are related to the brand alliance. These brand associations form the proportion of general brand associations. Three coders coded 50 cases according to the categorization key. The Pearson correlation coefficient shows that there is a significant correlation between coder 1 and coder 2. There is a strong, positive correlation between the coding of the proportion of general brand associations by coder 1 and coder 2, r (50)= 0.87, p < 0.00. There is also a strong, positive relation between coder 2 and coder 3, r (50)= 0.72, p < 0.00. However, the correlation is less stronger than between coder 1 and coder 2. Finally, coder 1 and coder 3 also seems to agree on the categorization key in terms of the proportion of general brand associations, r (50)= 0.84 p < 0.00. The inter reliability between the three coders based on the proportion of general brand associations can thus be considered as moderately high.

7.3 Control variables Brand familiarity One of the important control variables in this research is the familiarity with the broadcasting brands that are used. Brand familiarity has an influence on information processing and brand evaluations (Alba & Hutchinson, 1987). Brand familiarity is measured on a seven-point bipolar scale. To test whether this variable could have an influence on the relationships that are tested in the hypotheses a One-way ANOVA is

62 Forced brand marriages in broadcasting to fight competition. Happily ever after? conducted. The differences in the means on the brand familiarity scale in all different conditions is examined. Levene’s Test of Equality of Variances has been violated. Levene’s test is significant F (7, 181) = 2.43, p = 0.02. Meaning that there are unequal variances across the conditions. The conditions can therefore not be treated as equal. First a Welch’s correction should be applied and a Games-Howell post-hoc test designed for unequal variances, should be examined. After the Welch’s correction the means on brand familiarity still significantly differ across the conditions, F (7, 75) = 4.93, p < 0.00. Games-Howell post-hoc test shows that the brand familiarity with the misfit based on political views (VARAWNL) ( M = 4.25, SD = 1.71) is significantly lower than the brand familiarity with the misfit based on content (TROSNOS) ( M = 6.03, SD = 0.91), p = 0.01. The high brand familiarity of the misfit based on content (TROSNOS) also differs significantly with the less familiar combinations: EOPowNed (misfit based on religion) (M = 4.70, SD =1.21), p = 0.00 and BNNMAX (fit based on target audience) ( M = 4.80, SD = 1.30). The rest of the combinations do not differ significantly based on brand familiarity. Based on these findings it can be suggested that the control variable brand familiarity could have an influence on the relationships that will be tested. Therefore brand familiarity will be taken into account by the hypotheses testing.

Pre-existing attitudes A One-way ANOVA is conducted to see if the mean differences on the pre-existing attitudes could have an influence on the results. Again, Levene’s Test of Equality of Variances has been violated. Levene’s test is significant F (7, 181) = 2.48, p = 0.02. A Welch’s correction should be applied and a Games-Howell post-hoc test designed for unequal variances, should be examined. There are significant differences in the pre-existing attitudes across the conditions, F (7, 75) = 10.79, p < 0.00. Games-Howell post-hoc test shows that the pre-existing attitudes towards EOPowNed ( M = 3.34, SD = 1.16) are significantly more negative than towards VARAVPRO ( M = 5.02, SD = 1.21), p < 0.00, EOKRO ( M = 4.43, SD = 1.01), p = 0.02, BNNMAX ( M = 5.16, SD = 0.97), p < 0.00, TROSNOS ( M = 5.36, SD = 0.70), p < 0.00 and TROSAVRO ( M = 4.36, SD = 1.11), p = 0.04.

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Furthermore the pre-existing attitudes towards VARAWNL ( M = 4.23, SD = 0.93) also differ significantly from BNNMAX ( M = 5.15, SD = 0.97), p = 0.05 and TROSNOS (M = 5.36, SD = 0.70), p < 0.00. Finally, the pre-existing attitudes towards TROSNOS ( M = 5.36, SD = 0.70) also differ significantly from EOKRO ( M = 4.43, SD = 1.01), p = 0.01 and TROSAVRO ( M = 4.36, SD = 1.11), p = 0.01. In table 6 an overview can be seen of the combinations and the scores on the pre-existing attitudes. The variable pre-existing attitude will definitely be included in the further analysis since there are significant differences across several conditions.

Table 6. Mean scores and Std. deviations on the variable pre-existing attitudes across conditions Type of Category Level of Combinations Mean SD BCC BCC Deep Political Misfit VARAWNL 4.23 0.92 Deep Political Fit VARAVPRO 5.02 1.22 Deep Religion Misfit EOPOWNED 3.34 1.16 Deep Religion Fit EOKRO 4.43 1.01 Surface Target audience Misfit BNNMAX 5.15 0.97 Surface Target audience Fit BNNMTV 4.48 1.36 Surface Content Misfit TROSNOS 5.36 0.69 Surface Content Fit TROSAVRO 4.38 1.11

Pre-existing quality assumptions Another important control variable is the pre-existing quality assumptions about the broadcasting brands that are used in the brand combinations. A One-way ANOVA is conducted to see if there are significant differences on this variable across the different conditions. The results indicate that there are significant differences in the pre-existing quality assumptions across the conditions, F (7, 181) = 8.07, p < 0.00. Post-hoc test Tukey shows that the pre-quality assumptions towards the fit based on religion (EOKRO, M = 4.71, SD

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= 0.99) and misfit based on religion (EOPowNed) are significantly higher ( M = 3.55, SD = 1.12, p = 0.01). There are also significant ( p = 0.04) differences in the pre-existing quality assumptions of the fit based on target audience (BNNMTV, M = 3.75, SD = 1.32) and the misfit based on target audience ( M = 4.74, SD = 0.98). Furthermore, significant ( p = 0.01) differences are found between the fit based on content (TROSAVRO, M = 4.00, SD = 1.04) and the misfit based on content (TROSNOS, M = 5.07, SD = 0.75) in terms of pre-existing quality assumptions. Finally, no significant differences ( p = 0.07) are found between the fit based on political views (VARAPRO, M = 5.04, SD = 1.22) and the misfit based on political views (VARAWNL, M = 4.10, SD = 0.79). These significant differences could distort the possible effects. The control variable pre-existing quality assumptions will thus also be included in the further analysis.

Attitude towards the NPO (corporate brand) To see if the attitude towards the NPO could distort the possible relationships between the variables in the hypotheses a One-way ANOVA is conducted. The equality assumption is violated. Levene’s test is significant F (7, 181) = 2.59, p = 0.01. After the Welch’s correction there are no significant differences in the attitude towards the NPO between the different conditions, F (7, 77) = 0.53, p = 0.81. Therefore this control variable does not have to be taken into consideration in further analysis.

Age The last control variable is the age of the respondents. The exploratory study showed that there are differences in how older and younger people categorize the different broadcasting networks. To see if there are significant differences based on age between the different conditions a One-way ANOVA is conducted. Levene’s test is not significant, F (7, 181) = 1.52, p = 0.53. Furthermore there are no significant differences in age between the different conditions, F (7, 181) = 0.91, p = 0.50. This control variable does not distort the possible findings that may be found in this research. The control variable age will therefore not be taken into account in the further analysis.

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7.2.4 Manipulation checks Level of BCC The level of BCC is one of the variables that has been manipulated in this experiment. To check if the manipulations in terms of misfit and fit on BCC actually worked out a One- way ANOVA has been conducted. The outcome variable (BCC-scale) is measured on a seven-point Likert scale and thus measured on interval level and the independent variable is categorical. Levene’s Test of Equality of Variances is significant F (7, 181) = 4.61, p < 0.00. There are unequal variances and therefore the Welch F-ratio is reported .There are significant differences between the conditions based on the level of brand concept consistency, F (7, 75) = 11.36, p < 0.00. The degrees of freedom had to be adjusted because Levene’s test was significant. Planned contrasts shows that the manipulations for level of BCC unfortunately only partially worked out. The fit based on religion (EOKRO) is indeed perceived as a combination that has a higher brand concept consistency ( M = 3.35, SD = 1.64) than the misfit based on religion (EOPowNed) ( M = 1.52, SD = 0.88), t (32) = 4.82, p < 0.00. The fit based on target audience (MTVBNN) is also perceived as a combination that has a significantly higher brand concept consistency ( M = 3.45, SD = 1.18) than the misfit based on target audience (BNNMAX) ( M = 2.02, SD = 1.22), t (43) = 4.00, p < 0.00. The combination that has a fit based on content (TROSAVRO) scores higher on the brand concept consistency scale ( M = 3.58, SD = 1.53) than the combination with a misfit based on content (TROSNOS) ( M =2.59, SD = 1.26), t (41) = 2.33, p < 0.03. However, the fit based on political views (VARAVPRO) is not perceived as a combination that has a significantly higher brand concept consistency ( M = 3.45, SD = 1.66) than the misfit based on political views (VARAWNL) ( M = 3.28, SD = 1.18) t (43) = 4.00, p = 0.69. Therefore the manipulations unfortunately failed for this combination. Ideally the three fit conditions and the three misfit conditions that are selected for the further analysis do not differ significantly from each other. Planned contrasts shows that the misfit based on religion (M = 1.52, SD = 0.88) does not differ significantly from the misfit based on target audience ( M = 2.02, SD = 1.22), t (39) = - 1.66, p = 0.11. However, the misfit based on content ( M = 2.59, SD = 1.26) scores significantly higher on brand concept consistency than the misfit based on religion, t (48)

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= -3.69, p = 0.00 and the misfit based on target audience, t (48) = -13.22, p < 0.00. It seems like the misfit based on content is more considered as a ‘moderately’ misfit on brand concept consistency. Additionally, planned contrasts show that there are no significant differences in brand concept consistency between the fit based on religion ( M = 3.35, SD = 1.66) and the fit based on target audience ( M = 3.45, SD = 1.18), t (40) = 0.25, p = 0.80. There are also no significant differences between the fit based on religion and the fit based on content ( M = 3.58, SD = 1.73), t (45) = 0.48, p = 0.64. Simultaneously, there is no significant difference on brand concept consistency between the fit based on content and the fit based on target audience, t (41) = -0.30, p = 0.77. A remarkable finding is that the misfit on content (TROSNOS) scores significantly higher on the brand concept consistency scale than the other misfits (religion and target audience). Consequently, for the analysis based on the level of BCC only the four combinations by which the manipulations did succeed will be taken into account. The misfit and fit based on religion and target audience. The misfit and fit based on political views and the misfit and fit based on content will not be taken into account. The misfit based on content (is more a moderate misfit) and differs significantly from the other misfits and the misfit and fit based on political views do not differ at all based on the brand concept consistency. As can be seen, the brand combinations that were supposed to have a fit on BCC score moderately on the brand concept consistency scale (between 3 and 4). However, the brand combinations with a fit do score significantly higher than the brand combinations with a misfit (between 1.5 and 2). In table 7 on the next page an overview of the different combinations and the scores on the BCC scale can be found.

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Table 7. Mean scores and Std. deviations on the brand concept consistency scale

Type of BCC Category Level of BCC Combinations Mean SD Deep Political Misfit VARAWNL 3.28 1.18 Deep Political Fit VARAVPRO 3.45 1.66 Deep Religion Misfit EOPOWNED 1.52 0.88 Deep Religion Fit EOKRO 3.35 1.64 Surface Target audience Misfit BNNMAX 2.02 1.22 Surface Target audience Fit BNNMTV 3.45 1.64 Surface Content Misfit TROSNOS 2.59 1.26 Surface Content Fit TROSAVRO 3.58 1.53

Type of BCC The manipulation of type of BCC is checked by asking the respondents an open question. Namely: “Give a brief description based on the questions: What have brand A and brand B in common or what is it that they don’t have in common? And why do you think brand A and brand B fit or do not fit together?”. The qualitative answers are coded. The categorization key can be found in Appendix 7. For this manipulation check it was important to know if people referred to the correct feature of the fit or misfit (political, religion, target audience or content). A lot of the respondents mentioned multiple reasons for a fit or misfit. Therefore the coders also coded the most dominant argument. For this manipulation check the most dominant argument is the one that is mentioned first. A Chi-Square will be conducted for all types of BCC because the outcome variable is a dichotomous one (type of BCC: mentioned or not mentioned) and the independent one is also a categorical variable.

Type of mis(fit) based on political views Since there are two cells that have an expected count less than 5, the Fisher’s Exact test will be reported because the Chi-square is then less accurate. The Fisher’s exact is not significant (1, N = 41) = 2.21, p = 0.18. This means that the manipulation for political type of fit and misfit failed. In only five cases the political background of the broadcasters

68 Forced brand marriages in broadcasting to fight competition. Happily ever after? was mentioned as a reason for the fit or misfit.

Type of (mis)fit based on religion The Chi-Square shows that there is a significant association between a fit/misfit based on religion and mentioning that the main reason for a fit or misfit is based on religion, χ2 (1, N = 51) = 12.13, p < 0.00. In 24 cases the main reason for a fit or misfit was based on religion. However in 27 cases it was based on something else. In the fit condition the fit was mainly based on religion ( N = 17) and not on other reasons ( N = 6). In the misfit condition however, the misfit was mostly based on something else ( N = 21) and not on religion ( N = 7). This means that the manipulation for type of fit and misfit based on religion only partially succeeded. Only the manipulation in the fit condition was very clear.

Type of (mis)fit based on target audience The Chi-Square shows that there is a significant associations between a fit/misfit based on target audience and mentioning that the main reason for a fit or misfit is based on target audience, χ2 (1, N = 45) = 3.79, p = 0.05. In 27 cases the main reason for a fit or misfit was based on target audience in 18 other cases another reason was more dominant. The manipulations for type of misfit based on target audience succeeded. Especially the misfit based on target audience was clear of the 23 cases 17 cases referred to target as the main reason for the misfit.

Type of (mis)fit based on content The Chi-Square shows that there is a significant associations between a fit/misfit based on content and mentioning that the main reason for a fit or misfit is NOT based on the content that the broadcasters provide, χ2 (1, N = 52) = 14.44, p < 0.00. This is exactly the opposite of what was expected. In total 10 people referred to the content as a main reason for a fit or misfit. Unfortunately 42 cases referred to something else as the main reason for the fit or misfit for the combinations. The manipulations for type of BCC based on content thus failed. To sum up, the manipulations for type of BCC did only partially succeed. It seems like people judge a fit based on multiple features of a misfit/fit. The analysis considering

69 Forced brand marriages in broadcasting to fight competition. Happily ever after? type of BCC can thus only be partially preformed on the types of misfit/fit based on religion and target audience. For the misfit/fit based on surface features the brand combination based on target audience are selected (MTVBNN and BNNMAX). The manipulations for these brand combinations succeeded. For the ‘deep’ fit/misfit the brand combinations based on religious misfit/fit are selected (EOKRO and EOPowNed). However, the results should be interpret with caution because the misfit based on religion seems to be a bit unclear for the respondents. In the additional analysis more information will be provided on how the respondents evaluated the different types of fits and misfits.

7.3 Hypotheses testing The first four hypothesis are all related to the influence of the level of BCC. The last four hypothesis are all related to the moderating effect of type of BCC on the relationship between level of BCC and all the outcome variables. As the manipulations only succeed for four combinations based on two types of BCC (religion and content) with two levels of BCC (misfit and fit) only these combinations will be used to test the hypotheses. Meaning that a 2 x 2 between-subjects design: level of BCC (misfit vs. fit) x type of BCC (surface-target audience vs. deep-religion ) remained. The previous analyses with the control variables (brand familiarity, pre-existing attitudes and pre-existing quality assumptions) showed that these variables may distort the results. The variables do systematically vary within the conditions. To eliminate the effects of the possible confound variables Two-way Analyses of Covariance (ANCOVA’s) and a Two-way Multiple Analysis of Covariance (MANCOVA) will be conducted. In the following paragraphs the results will be presented in order of the models that are used per outcome variable. So first the Two-way ANCOVA to test the main effect of level of BCC (H1) and the moderating effect of type of BCC (H5) on the total amount of brand associations will be presented. Followed by another Two-way ANCOVA that tests the main effect of level of BCC (H2) and the moderating effect of type of BCC (H6) on the proportion of general brand associations. Finally, the last Two-way ANCOVA that examines the main effect of level of BCC (H3) and the moderating effect of type of BCC (H7) on the favorability of the brand associations. The main effect of level of BCC (H4) and type of BCC (H8) on the brand responses will be tested by conducting a MANCOVA.

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The results of the MANCOVA will be presented in the last paragraph.

7.3.1 The amount of brand associations: the main effect of level of BCC and moderating effect of type of BCC Hypothesis 1 of this study suggests that brand alliances in broadcasting that have a fit on BCC generate more brand associations than brand alliances in broadcasting that have a misfit on BCC. Hypothesis 5 suggests that this relationship is moderated by type of BCC. It is expected that the effect of level of BCC on the amount of brand associations is stronger for brand alliances in broadcasting that have a misfit/fit based on ‘surface’ features than for brand alliances in broadcasting have a misfit/fit based on ‘deep’ features. Both hypotheses relate to the same outcome variable, namely: the amount of brand associations. The outcome variable: the amount of brand associations is measured on an interval level (0 till 10). The two independent variables are categorical namely: 1) the level of BCC with two levels: misfit and fit and 2) the type of BCC. This variable also has two levels namely: misfit/fit based on religion (deep feature) and misfit/fit based on target audience (surface feature). A 2 by 2 between-groups ANCOVA is conducted since this test offers the opportunity to test the main effect of level of BCC (H1) and the moderating effect of type of BCC (H5) in one model while controlling for the effect of the possible confound variables: brand familiarity, pre-existing quality and pre-existing attitudes.

Assumption testing ANCOVA When running an ANCOVA it is important to check if the assumption of independence of the covariates and treatment effect are not violated. The values of the covariates brand familiarity, pre-existing attitudes and pre-existing quality assumptions cannot vary (too much) across the different levels of the independent variable(s): in this case the level of BCC and type of BCC. Two-way ANOVA’s are conducted to check if this assumption is not violated for each of the covariates. First a Two-way ANOVA is conducted for brand familiarity. The results indicate that there is no statistical difference between the different levels of BCC as measured by the variable brand familiarity, F (1, 93) = 2.73, p = 0.10. Additionally, no statistical significant difference between the different types of BCC as measured by brand familiarity was found, F (1, 93) = 0.22, p = 0.88. For brand familiarity the assumption of

71 Forced brand marriages in broadcasting to fight competition. Happily ever after? independence is thus met. For the other covariate: pre-existing quality assumptions the assumption of independence is also not violated. The Two-way ANOVA shows that there are no significant differences in the pre-existing quality assumptions between the different conditions of level of BCC, F (1,93) = 0.35, p = 0.55. There is also no statistical significant difference between the different types of BCC in the pre-existing quality assumptions, F (1,93) = 0.47, p = 0.50. The Two-way ANOVA shows that there is no significant difference between the level of BCC as measured by the last covariate: pre-existing brand attitudes, F (1,93) = 1.11, p = 0.30. However, there are significant different between the type of BCC as measured by the variable pre-existing brand attitudes, F (1, 93) = 15.50, p < 0.00. The pre-existing attitudes towards the misfit/fit based on religion ( M = 3.83, SD = 1.22) are significantly more negative than towards the misfit/fit based on target audience ( M = 4.82, SD = 1.21). There are two options: either removing the covariate in the ANCOVA so that the assumption is not violated or retain the covariate in the model. The covariate pre-existing attitudes is measured before the experimental treatment so it can be assumed that the experimental treatment did not influence the covariate. As Keppel (1991) mentioned: “The analysis of covariance is based on the assumption that the covariate is independent of the experimental treatment” (as cited in Grace- Martin, n.d). In this experiment the pre- existing attitudes are measured before the respondents were exposed to the stimuli. Therefore the appropriate solution is keeping the covariate in the analysis. If the covariate will be removed from the model a less accurate examination of the real relationship will be provided and possible effects will be overestimated (Grace- Martin, n.d). The second assumption for an ANCOVA is that the homogeneity of regression slopes is not violated. There may be no interaction between the covariates and the independent variables. A Two-way ANOVA is conducted to examine the interaction effects between the independent variables and the covariates on the amount of brand associations. The results indicate that there is no interaction effect of the covariate brand familiarity and level of BCC, F (1, 84) = 0.10, p = 0.75. There is also no significant interaction between type of BCC and brand familiarity, F (1, 84) = 0.88, p = 0.35. The results also show that there is no significant interaction effect of the covariate pre-existing attitudes and the different conditions of level of BCC, F (1, 84) = 0.44, p =

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0.51, and also not on the different conditions of type of BCC, F (1, 84) = 0.47, p = 0.47. Finally, the results show that there is no significant interaction between the pre-existing quality assumptions and the different levels of BCC, F (1, 84) = 0.21, p = 0.65, and the different types of BCC, F (1, 84) = 1.05, p = 0.31. The assumptions of the homogeneity of regression slopes is for all covariates is not violated, no significant interactions were found.

Results ANCOVA Main effect of level of BCC The results of the Two-way ANCOVA show that there is no significant main effect of level of BCC on the amount the amount of brand associations that are generated, F (1, 89) = 0.02, p = 0.88. A fit based on BCC does not generate more brand associations ( M = 5.71, SD = 2.70) than a misfit based on BCC ( M = 5.67, SD = 2.44). No support was found for hypothesis 1: “Brand alliances in broadcasting that have a fit on brand concept consistency (BCC) will generate more brand associations than brand alliances in broadcasting that have a misfit on BCC” .

Interaction effect of type of BCC Additionally, no significant main effect was found for type of BCC, F (1, 89) = 0.01, p = 0.93. Consequently, there was no significant interaction effect of type of BCC on the expected relationship between level of BCC and the amount of brand associations, F (1, 89) = 0.05, p = 0.83. Hypothesis 5 is not supported: “The effect of level of BCC on the amount of the brand associations (H1) will be stronger for the brand alliances in broadcasting that have a misfit/fit on ‘surface’ features than for the brand alliances in broadcasting that have a misfit/fit on ‘deep’ features” .

Effects of the added covariates Furthermore no main effects of the added covariates were found on the amount of brand associations. Brand familiarity ( F (1, 89) = 0.99, p = 0.32) the pre-existing attitudes ( F (1, 89) = 0.00, p = 0.97) and the pre-existing quality assumptions ( F (1, 89) = 0.69, p = 0.41) are not related to the amount of brand associations.

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7.3.2 Proportion of general brand associations: the main effect of level of BCC and moderating effect of type of BCC Hypothesis 2 of this study suggest that the proportion of general brand associations will be smaller for brand alliances in broadcasting that have a fit on BCC than for brand alliances in broadcasting that have a misfit on BCC. Additionally hypothesis 6 suggest that the effect of level of BCC on the proportion of general brand associations will be stronger for brand alliances in broadcasting with a misfit/fit on ‘surface’ features than for brand alliances in broadcasting with a misfit/fit on ‘deep’ features. The proportion of general brand associations is continuous and measured on interval level (0% till 100%). The independent variables level of BCC and type of BCC are categorical and since the covariates (brand familiarity, pre-existing attitudes and pre- existing quality assumption) have to be included a 2 by 2 between-groups ANCOVA was conducted. In this ANCOVA the main effect of level of BCC and the interaction effect of type of BCC on the dependent variable: the proportion of general brand associations will be tested. Brand familiarity, pre-existing attitudes and pre-existing quality assumptions were added as covariates.

Assumption testing ANCOVA The first assumption for the ANCOVA: the assumption of independence of the covariates was already tested in the previous paragraph The same covariates are added in this analysis. However, the second assumption: the homogeneity of regression slopes has to be examined again. Two-way ANOVA’s are conducted with the three covariates, the dependent variable and the independent variables: level of BCC and type of BCC to check if there are any interaction effects. The results indicate that there is no significant interaction effect of the covariate brand familiarity and level of BCC, F (1, 84) = 0.03, p = 0.86 and type of BCC, F (1, 84) = 0.53, p = 0.47. The assumption is also not violated for pre-existing attitudes. No interaction effects were found for pre-existing attitudes and level of BCC, F (1, 84) = 0.71, p = 0.40, and type of BCC, F (1, 84) = 0.91, p = 0.34. Finally, the results indicate that the there is also no significant interaction between the covariate pre-existing quality assumptions and level of BCC, F (1, 84) = 0.00, p = 0.96, and type of BCC, F (1, 84) = 0.18, p = 0.67. The assumptions for running an ANCOVA are thus not violated.

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Results ANCOVA Main effect of level of BCC The results indicate a significant main effect of level of BCC on the amount of general brand associations when controlled for brand familiarity, pre-existing attitudes and pre- existing quality assumptions, F (1, 89) = 7.12, p = 0.01, ηp2 = 0.08. A brand alliance in broadcasting with a misfit on BCC generates a larger proportion of general brand associations ( M = 0.29, SD = 0.31) than a brand alliance in broadcasting with a fit on BCC (M = 0.14, SD = 0.24). The effect of level of BCC on the amount of general brand associations can be considered as medium ( ηp2 = 0.08) (Cohen, 1988). There is support for hypothesis 2 : “For brand alliances in broadcasting with a fit on BCC the proportion of general brand associations will be smaller than for brand alliances in broadcasting with a misfit on BCC” .

Interaction effect of type of BCC The results also indicate that there is a significant main effect for type of BCC on the proportion of general brand associations when controlled for the covariates, F (1, 89) = 8.39, p = 0.01, ηp2 = 0.09. The effect of type of BCC on the proportion of general brand associations is a bit stronger in comparison with the effect of level of BCC but it still has to be considered as a medium effect (Cohen, 1988). The interaction effect of level of BCC and type of BCC is marginally significant when controlled for the covariates, F (1, 89) = 3.58, p = 0.06, ηp2 = 0.04 .The interaction effect is small since the ηp2 is smaller than 0.06 (Cohen, 1988). The main effects of level of BCC and type of BCC and are portrayed in figure 12.

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Figure 12. Overview of the significant influence of level of BCC and type of BCC on the proportion of general brand associations when controlled for brand familiarity, pre-existing attitudes and pre-existing quality assumptions

The results indicate that the misfit/fit based on religion ( M = 0.29, SD = 0.32) generates a larger proportion of general associations than the misfit/fit based on target audience ( M = 0.14, SD = 0.22). The misfit based on religion results in the largest proportion of general associations ( M = 0.38, SD = 0.36), while the fit based on target audience results in smallest proportion of general brand associations (M = 0.10, SD = 0.20). The results are the opposite of what was expected, namely that the difference between the proportion of general associations would be larger for a misfit/fit based on surface features (target audience). As the graph shows the difference seems to be larger between the misfit/fit based on a deep feature (religion). Besides, the interaction effect is marginally significant (p = 0.06). The statistical significance to claim a significant finding is p < 0.05. Hypothesis 6 is not supported : “The effect of level of BCC on the proportion of general brand associations (H2) will be stronger for the brand alliances in broadcasting that have a misfit/fit on ‘surface’ features than for the brand alliances in broadcasting that have a misfit/fit on ‘deep’ features” .

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Effects of the added covariates No significant main effects were found for brand familiarity ( F (1, 89) = 0.94, p = 0.34) the pre-existing attitudes ( F (1, 89) = 2.26, p = 0.14) and the pre-existing quality assumptions ( F (1, 89) = 0.01, p = 0.93). None of the covariates is thus related to the proportion of general brand associations.

7.3.3 Favorability of the brand associations: the main effect of level of BCC and moderating effect of type of BCC The third hypothesis in this study suggests that for a brand alliance in broadcasting with a misfit on BCC the favorability of the brand associations will be lower than for the brand alliance in broadcasting with a fit based on BCC. Furthermore, hypothesis 7 suggests that the effect of level of BCC on the favorability of the brand associations (H3) will be stronger for brand alliances in broadcasting that have a misfit/fit based on ‘surface’ features than for brand alliances with a misfit/fit based on ‘deep’ features. To test these hypotheses the mean scores on the favorability of the brand associations were calculated. The dependent variable is measured on interval level and the identified covariates need to be added in the model. To test the hypotheses a 2 by 2 ANCOVA is conducted with the independent variables: level of BCC and type of BCC, and the mean scores on the favorability of the brand associations as dependent variable. The three covariates: brand familiarity, pre-existing attitudes and pre-existing quality assumptions are again added in the model.

Assumption testing ANCOVA The first assumption for the ANCOVA: the independence of the covariates was not violated, as it was already tested. The second assumption of the ANCOVA: the homogeneity of regression slopes, is also not violated for any of three covariates. There was no significant interaction effect between brand familiarity and level of BCC, F (1, 84) = 0.02, p = 0.88, and type of BCC, F (1, 84) = 0.06, p = 0.81. Furthermore no interaction effects were found for the second covariate: pre-existing attitudes and level of BCC, F (1, 84) = 0.77, p = 0.38, and type of BCC, F (1, 84) = 0.00, p = 0.96. Finally, there is no interaction effect between pre-existing quality assumptions and level of BCC, F (1, 84) = 0.06, p = 0.80, and type of BCC, F (1, 84) = 0.04, p = 0.85.

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Results ANCOVA Main effect of level of BCC There is no significant main effect of level of BCC on the favorability of the brand associations, F (1, 89) = 0.11, p = 0.74. The mean favorability of the brand associations of a brand alliance in broadcasting with a fit on BCC is not significantly higher ( M = 5.26, SD = 4.74) than for a brand alliance in broadcasting with a misfit on BCC ( M = 5.12, SD = 4.96). Hypothesis 3 is therefore not supported : “For brand alliances in broadcasting with a fit on BCC the favorability of the brand associations will be higher than for brand alliances in broadcasting with a misfit on BCC”.

Interaction effect of type of BCC Additionally, the results indicate that there is no main effect of type of BCC on the favorability of the brand associations, F (1, 89) = 0.29, p = 0.59. Furthermore no interaction effect of type of BCC and level of BCC on the favorability of the brand associations was found, F (1, 89) = 1.23, p = 0.27. Hypothesis 7 is also not supported : “The effect of level of BCC on the favorability of the brand associations (H3) will be stronger for the brand alliances in broadcasting that have a misfit/fit on ‘surface’ features than for the brand alliances in broadcasting that have a misfit/fit on ‘deep’ features”.

Effects of the added covariates The results show that there is no significant relationship between the covariates and the favorability of the brand associations. No main effects were found for brand familiarity ( F (1, 89) = 3.16, p = 0.08) the pre-existing attitudes ( F (1, 89) = 0.25, p = 0.62) and the pre-existing quality assumptions ( F (1, 89) = 0.04, p = 0.85).

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7.3.4 The brand responses: the main effect of level of BCC and moderating effect of type of BCC Hypothesis 4 suggests that for a brand alliance in broadcasting with a fit on BCC the brand responses will be more positive than for a brand alliance with a misfit on BCC. Brand responses consists out of four variables that are expected to be related to each other: a) brand attitudes, b) expected program quality, c) likeability of the programs and the more behavioural response: d) the viewing intentions. Additionally, hypothesis 8 suggests that this effect of level of BCC on the brand responses will be stronger for brand alliances in broadcasting with a misfit/fit based on ‘surface’ features than for brand alliances in broadcasting with a misfit/fit based on ‘deep’ features. A Two-way MANCOVA is in this case the best choice because there are several dependent variables that need to be tested and the model needs to be extended with the possible confounds. It is expected that it is likely that the dependent variables correlate with each other, multiple ANCOVA’s can then result in a greater chance of type I error. Besides, a MANCOVA can detect the underlying relationships between the dependent variables (Fields, 2009, p.585). That makes the MANCOVA the preferable test for these hypotheses. To investigate if the level of BCC has an influence on the brand responses and if this is effect is moderated by type of BCC, a MANCOVA has been conducted. The brand attitude, expected program quality, likeability of the programs and the viewing intentions are added as the dependent variables and the level of BCC and type of BCC as the independent variables. The possible confounds: brand familiarity, pre-existing attitudes and pre-existing quality assumptions are also included in the model.

Assumption testing MANCOVA The assumption for the MANCOVA: the homogeneity of regression slopes is not violated for brand familiarity and level of BCC. Using Pillai’s trace there is no significant interaction effect for level of BCC and brand familiarity, F (4, 81) = 1.60, p = 0.18. There is also no significant effect for type of BCC and brand familiarity, F (4, 81) = 1.44, p = 0.23. For the covariate pre-existing attitudes and level of BCC the assumption of homogeneity of regression slopes is also not violated, Using Pillai’s trace there is no significant interaction effect, F (4, 81) = 1.06, p = 0.38. There is also no significant

79 Forced brand marriages in broadcasting to fight competition. Happily ever after? interaction effect of type of BCC and the covariate pre-existing attitudes, F (4, 81) = 0.33, p = 0.86. Finally, for the last covariate: pre-existing quality assumptions, the assumption is also not violated. No interaction effect between level of BCC and the pre-existing quality assumptions is detected, F (4, 81) = 1.44, p = 0.23. Furthermore, no interaction effect between type of BCC and the pre-existing quality assumptions is found, F (4, 81) = 0.04, p = 0.99.

Results MANCOVA Main effect of level of BCC and interaction effect of type of BCC Mauchly’s test is not significant ( p = 0.12), meaning that the assumption of sphericity has not been violated. Furthermore the MANCOVA using Pillai’s Trace shows that there is a significant effect of level of BCC on the brand responses when controlled for the covariates, F (4, 86) = 3.97, p = 0.01, ηp2 = 0.15. There is a strong effect (Cohen, 1988) of level of BCC on the combination of the dependent variables. The MANCOVA using Pillai’s Trace indicates that there is not a significant effect of type of BCC on the brand responses, F (4, 86) = 0.99, p = 0.42. Furthermore, the MANCOVA using Pillai’s Trace shows that there is no significant interaction effect of level of BCC and type of BCC on the brand responses, F (4, 86) = 1.36, p = 0.26. The main effect of level of BCC on each of the dependent variables that belong to the general brand responses will be examined in the next paragraphs. The results of the seperate ANCOVA’s also indicate significant differences of level of BCC on several dependent variables that were added in the model. The assumption of homogeneity is not violated since Levene’s test is not significant for any of the ANCOVA’s. The results of the separate ANCOVA’s will be discussed on the next pages.

80 Forced brand marriages in broadcasting to fight competition. Happily ever after? a) brand attitude The results show that the brand attitudes towards brand alliances in broadcasting with a misfit on BCC are significantly more negative ( M = 2.85, SD = 0.20) than towards brand alliances in broadcasting with a fit on BCC (M = 3.80 , SD = 0.21), F (1, 86) = 11.72, p = 0.00, ηp2 = 0.12. Even when controlled for the three covariates: brand familiarity, pre- existing attitudes and pre-existing quality assumptions a significant main effect of level of fit appears. In figure 13 it can clearly be seen that a misfit based on BCC leads to a less positive brand attitude than a fit based on BCC. It can also be seen that there is indeed no interaction effect of type of BCC.

Figure 13. Overview of the significant influence of level of BCC on the brand attitudes when controlled for brand familiarity, pre existing attitudes and pre-existing quality assumptions

81 Forced brand marriages in broadcasting to fight competition. Happily ever after? b) expected program quality Furthermore, the expected quality of programs is significantly lower for brand alliances in broadcasting with a misfit on BCC (M = 3.23, SD = 0.21) than for brand alliances in broadcasting with a fit on BCC (M = 4.04, SD = 0.22), F (1, 86) = 8.65, p = 0.00, ηp2 = 0.09. In figure 14 it can be seen that a brand alliance with a fit on BCC generates higher quality assumptions of the programs in comparison with the brand alliances that have a misfit on BCC. In the graph it can be seen that there is also no significant main effect of type of BCC and no significant interaction effect.

Figure 14. Overview of the significant influence of level of BCC on expected program quality when controlled for brand familiarity, pre-existing attitudes and pre- existing quality assumptions

82 Forced brand marriages in broadcasting to fight competition. Happily ever after? c) likeability of the programs Finally, the likeability of the programs is also significantly lower for the brand alliances in broadcasting with a misfit on BCC (M = 3.38, SD = 0.19) than towards brand alliances in broadcasting with a fit on BCC (M = 4.13, SD = 0.20) even when controlled for the covariates, F (1, 86) = 7.47, p = 0.01, ηp2 = 0.08. However, again no significant interaction effect of type of BCC was found, which can be clearly seen in figure 15.

Figure 15. Overview of the significant influence of level of BCC on the likeability of the programs when controlled for brand familiarity, pre-existing attitudes and pre-existing quality assumptions

83 Forced brand marriages in broadcasting to fight competition. Happily ever after? d) viewing intentions The separate ANCOVA for the effect of level of BCC on viewing intentions is not significant, F (1, 86) = 2.38, p = 0.26. The viewing intentions towards a brand alliance in broadcasting with a fit on BCC ( M = 3.71, SD = 1.79) are not significantly higher than towards a brand alliance in broadcasting with a misfit on BCC ( M = 3.18, SD = 1.71)

In table 8 an overview of the separate ANCOVA’s on the significant main effect of level of BCC on the outcome variables that measure brand responses, can be found.

Table 8. Overview of the separate ANCOVA’s with the independent variable: level of BCC, the dependent variables: brand attitude, quality programs, likeability programs and viewing intentions and the covariates: brand familiarity and pre-existing attitudes

DV F p ηp2 Brand attitude 11.72 0.00 0.12 Quality programs 8.64 0.01 0.09 Likeability programs 7.49 0.01 0.08 Viewing intentions 2.38 0.26 0.01

Based on the results that are discussed above hypothesis 4 is partially supported : “ For brand alliances in broadcasting with a fit on BCC the brand responses: (a) brand attitudes, (b) expected program quality, (c) likeability of the programs (d) viewing intentions will be more positive than for brand alliances in broadcasting with a misfit on BCC”. A main effect of level of BCC was found on (a) the brand attitudes, (b) expected program quality and (c) likeability of the programs. The effect of level of BCC on the brand attitudes is the strongest ( ηp2 = 0.12), followed by a strong effect on the expected quality of the programs ( ηp2 = 0.09). Finally, a smaller but still a strong effect of level of BCC on the likeability of the programs was found ( ηp2 = 0.08). A remarkable finding is that there is not a significant effect of level of BCC on the more behavioural response: the viewing intentions. Therefore hypothesis 4 is partially

84 Forced brand marriages in broadcasting to fight competition. Happily ever after? supported. Furthermore, hypothesis 8 is not supported : “The effect of level of BCC on the brand responses (a) brand attitudes, (b) expected program quality, (c) likeability of the programs (d) viewing intentions (H4) will be stronger for brand alliances in broadcasting that have a misfit/fit based on ‘surface’ features than for brand alliances in broadcasting that have a misfit/fit based on ‘deep’ features’. The results of the Two-way ANCOVA showed that no interaction effects of type of BCC and level of BCC were found on any of the brand responses.

Effects of the added covariates Furthermore the MANCOVA using Pillai’s Trace shows that there is a significant effect of one of the covariates on the brand responses. Pre-existing quality assumptions seems to have a significant relationship with the brand responses, F (4, 86) = 3.97, p = 0.01, ηp2 = 0.15. Pre-existing attitudes ( F (4, 86) = 2.21, p = 0.08) and brand familiarity ( F (4, 86) = 1.80, p = 0.14) do not have a significant effect on the outcome variables. In table 9 an overview of the separate ANCOVA’s of expected program quality and the dependent variables can be seen. A remarkable finding is that the pre-existing quality assumptions have a medium and significant effect on viewing intentions (ηp2 = 0.07). The results also indicate that there is a strong effect of pre-existing quality assumptions on the expected quality of the programs (ηp2 = 0.18) and likeability of the programs (ηp2 = 0.13). The results indicate that a spillover effect maybe took place, pre-quality assumptions that spilled over to the post brand responses.

Table 9. Overview of the separate ANCOVA’s of the covariate pre-existing quality on the dependent variables DV F p ηp2 Brand attitude 4.94 0.03 0.05 Quality programs 19.02 0.00 0.18 Likeability programs 13.70 0.00 0.13 Viewing intentions 6.58 0.01 0.07

85 Forced brand marriages in broadcasting to fight competition. Happily ever after?

7.4 Overview of the hypotheses

Hypotheses Findings H1: Brand alliances in broadcasting that have a fit on brand concept Not consistency (BCC) will generate more brand associations than brand supported alliances in broadcasting that have a misfit on BCC.

H2: For brand alliances in broadcasting with a fit on BCC the proportion of Supported general brand associations will be smaller than for brand alliances in broadcasting with a misfit on BCC” .

H3: For brand alliances in broadcasting with a fit on BCC the favorability Not of the brand associations will be higher than for brand alliances in supported broadcasting with a misfit on BCC.

H4: For brand alliances in broadcasting with a fit on BCC the brand Partially responses: (a)brand attitudes, (b) expected program quality, (c) likeability of supported the programs (d) viewing intentions will be more positive than for brand alliances in broadcasting with a misfit on BCC” H5: The effect of level of BCC on the amount of the brand associations (H1) Not will be stronger for the brand alliances in broadcasting that have a misfit/fit supported on ‘surface’ features than for the brand alliances in broadcasting that have a misfit/fit on ‘deep’ features” .

H6: The effect of level of BCC on the proportion of general brand Not associations (H2) will be stronger for the brand alliances in broadcasting supported, that have a misfit/fit on ‘surface’ features than for the brand alliances in but a main broadcasting that have a misfit/fit on ‘deep’ features” effect of type of fit was found H7: The effect of level of BCC on the favorability of the brand associations Not (H3) will be stronger for the brand alliances in broadcasting that have a supported misfit/fit on ‘surface’ features than for the brand alliances in broadcasting that have a misfit/fit on ‘deep’ features” H8: The effect of level of BCC on the brand responses (a) brand attitudes, Not (b) expected program quality, (c) likeability of the programs (d) viewing supported intentions (H4) will be stronger for brand alliances in broadcasting that have a misfit/fit based on ‘surface’ features than for brand alliances in broadcasting that have a misfit/fit based on ‘deep’ features’.

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7.5 Additional insights In this paragraph some additional analysis will be performed on the data in order to clarify some of the results.

7.5.1 Reasons for a misfit/fit The manipulation checks for type of BCC partially failed. A clear pattern came forward in the exploratory study, when the respondents were asked to categorize all the broadcasters based on shared associations. However when respondents were asked to evaluate the type of misfit/fit in an isolated context in the main study, it seemed like other types of misfits/fits were seen. The additional analysis indicate that the reasons for a misfit/fit were mostly based on target audience (23.3%) and content (31.2%). The more ‘surface’ features. Followed by a general brand fit/misfit (when no specific reason was given) (16.9%) and a fit/misfit based on religion (12.7%). A political fit/misfit was only mentioned in 3.7% of the cases. In figure 16 an overview of the different types of misfit and fit that were mentioned in the main study can be seen.

Reasons for misfit/fit

2.6%

9.5% Unknown General 31.2% 16.9% Political views Religion 3.7% Target audience 12.7% Content 23.3% Remaining

Figure 16. Overview of the reasons for a misfit/fit ( N = 189).

87 Forced brand marriages in broadcasting to fight competition. Happily ever after?

7.5.2 Brand familiarity One of the reasons that especially ‘surface’ reasons like target audience and content were mentioned for a misfit/fit could be due to the fact that more brand knowledge is needed to give a reason based on deep features. Unknown brands need to build brand knowledge to become established in the mind of the consumers (Campbell & Keller, 2003). Consumers already have existing cognitive structures for a familiar brand based on brand knowledge and brand experiences (Bettman & Sujan 1987). For (relatively) unfamiliar brands this is different, there are no cognitive structures yet, or they are weak in terms of strength and accessibility (Fazio, 1989). When consumers are not familiar with a brand it is harder to judge if there is a misfit/fit based on BCC or not. It becomes even more harder to judge where that misfit/fit is based on. Consumers do not have an existing network of brand associations (yet) on which they can base their fit judgment when brands are unfamiliar. There is no associative network to base the judgment on (Simonin & Ruth, 1998). One of the reasons that the manipulations partially failed for level of BCC and type of BCC could thus be related to the brand familiarity of the broadcasting brands. Pre-test 1 showed that the brand familiarity was moderately high for all broadcasting brands that were used in this study (except for WNL, which was only included in pre-study 2). However, the results of the main study show that there are significant differences in the brand familiarity of the separate brands. The One-way ANOVA with brand familiarity of the separate brands as dependent variable and the different brands as independent variable indicates that there are significant differences, F (11, 124) = 8.01, p < 0.00. A Welch correction had to implemented because Levene’s test was significant, F (11, 366) = 2.80, p = 0.00. The Games-Howell post-hoc test for unequal variances shows significant differences. The brand familiarity of WNL is significantly lower ( M = 3.10, SD = 1.94) than the brand familiarity of VARA ( p = 0.01), EO ( p = 0.01), BNN ( p = 0.02), MTV ( p = 0.00), KRO ( p = 0.02) , NOS ( p < 0.00) and AVRO ( p = 0.03). On the other hand the brand familiarity of NOS is significantly higher ( M = 6.36, SD = 0.78) than the brand familiarity of EO ( p < 0.00), TROS ( p = 0.02), PowNed ( p = 0.00), MAX ( p = 0.00), AVRO ( p = 0.05), KRO ( p = 0.04) and BNN ( p = 0.03). All the other brands do not significantly differ from each other in terms of brand

88 Forced brand marriages in broadcasting to fight competition. Happily ever after? familiarity. In table 10 mean scores and standard deviations on brand familiarity for the separate broadcasting brands can be seen.

Table 10. Overview of the mean scores and standard deviations of the broadcasting brands on brand familiarity. Type of BCC Level of BCC Brand Mean Std. deviation Political Prototype VARA 5.34 1.78 Fit VPRO 5.14 1.80 Misfit WNL* 3.10 1.94 Religion Prototype EO 5.12 1.35 Fit KRO 5.13 1.49 Misfit PowNed 4.43 1.83 Target audience Prototype BNN 5.04 1.78 Fit MTV 5.55 1.50 Misfit MAX 4.35 1.72 Content Prototype TROS 5.44 1.41 Fit AVRO 5.13 1.57 Misfit NOS* 6.36 0.78 Differs significantly from other broadcasting brands on brand familiarity: *. p < 0.05:

The manipulation checks of level of BCC and type of BCC failed for the political misfit and fit. The fit based on political views (VARAVPRO) (M = 3.45, SD = 1.66) did not score significantly higher on BCC than the misfit based on political views (VARAWNL) (M= 3.28, SD = 1.18). As can be seen the brand familiarity for WNL is low ( M = 3.10, SD = 1.94). The unfamiliarity with WNL could be the reason for the fact that the respondents judged the political misfit combination as a ‘moderate’ fit and that also the manipulation check for type of BCC failed. When consumers are not familiar (enough) with the brand it is hard to judge why the brands would fit together or why the brands would not fit together. Furthermore the manipulation checks of type of BCC and level of BCC also failed for the misfit and fit based on content. First of all, the results of the manipulation checks indicated that the misfit based on content (TROSNOS) scored significantly higher on the

89 Forced brand marriages in broadcasting to fight competition. Happily ever after? brand concept consistency scale than the rest of the misfits. This is remarkable because all the scores on brand familiarity are high (except WNL), with NOS even having the highest score on brand familiarity ( M = 6.23, p = 0.78). A logical consequence would be that due to the high score on brand familiarity people would see the differences that NOS and TROS have based on BCC. The combination that has a fit based on target audience (TROSAVRO) scores only a bit higher on the brand concept consistency scale ( M = 3.58, SD = 1.53) than the combination with a misfit based on content (TROSNOS) ( M = 2.59, SD = 1.26). Unfortunately, the analysis on the brand familiarity do not give a clear explanation on why the manipulations on level of BCC for content did not fully worked out. That the misfit/fit based on political views failed can be explained by the fact that the respondents were not familiar enough with WNL.

8.4.3 The moderating influence of age The results of the exploratory study indicated that older and younger people tend to categorize the public broadcasters differently. This could be explained by the fact that older people grew up with the pillars. As explained, some of the broadcasters are founded on these pillars. It could be suggested that the associative networks that older people have about the broadcasting brands are more resistant to change, since they are more familiar with them. Pre-existing attitudes and cognitive structures are already formed and strong in terms of strength and accessibility when people are very familiar with a brand (Fazio, 1989). Age could thus have an influence on the previous tested relationship in that it could moderate the relationships between level of BCC and type of BCC and the outcome variables. This could also be the reason that none of the hypothesis for type of BCC were supported. Younger people may not know how to judge the brands because they lack knowledge about the roots of the broadcasting brands that have a misfit/fit based on ‘deep’ features (religion and political views). Knowledge that elderly may have because they know more about the pillarization and thus also about the broadcasting brands that were founded on these pillars. It is therefore important to take age into account in the additional analysis to check if the results of the main study can be explained. After all the results of the exploratory study showed a different pattern for older and younger people.

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A multiple hierarchical regression analysis will be conducted with type of BCC and level of BCC as independent variables and age as a moderating variable. Because age is an quantitative variable a regression analysis is the best choice. The moderation effect of age will be tested by including the variable as a second step in the hierarchical regressions. In Appendix 9 the results of the hierarchical regressions analyses with a significant main effects and/or moderating effects are portrayed.

Age- amount of associations The hierarchical regression with level of BCC is not significant, F (1,94) = 0.00, p = 0.94. The model is not able to explain any of the variance in the dependent variable amount of brand associations. When age is added in the model there is only an increase of the R2 of 0.006. This increase is also not significant F (1,93) = 0.26, p = 0.47. The results of the hierarchical regression with type of BCC is not significant, F (1,94) = 0.05, p = 0.82. Adding age as a moderating variable only leads to an increase of 0.006 in the explanation of the variance in the dependent variable. This is not a significant increase F (1,93) = 0.29, p = 0.75.

Age- proportion general brand associations The hierarchical regression with level of BCC is significant, F (1,94) = 7.51, p = 0.01. The model is able to explain 7.4% of the total variance in the proportion of general brand associations. However when age is added in the model there is only an increase of the R2 of 0.001. This increase is not significant F (1,93) = 3.76, p = 0.77. The hierarchical regression with type of BCC is also significant, F (1,93) = 6.13, p = 0.02. The model is able to explain 6.1% of the total variance in the proportion of general brand associations. When age is added in the model there is only an increase of the R2 of 0.001. This increase is again not significant F (1,93) = 3.09, p = 0.76. The relationship of level of BCC and type of BCC on the proportion of general brand associations is not moderated by age. In table 1 and 2 in Appendix 9 the results of this hierarchical regression analysis are portrayed.

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Age- favorability of the brand associations The hierarchical regression with level of BCC and the favorability of the brand associations is not significant, F (1,94) = 0.02, p = 0.89. The model is not able to explain any of the variance in the dependent variable ( R2 = 0.00). When age is added in the model as a moderator there an increase of the R2 = 0.02. This increase is not significant F (1,93) = 9.94, p = 0.18. For type of fit there are also no significant results, F (1,94) = 0.06, p = 0.80. Adding age as a moderating variable only leads to an increase of R2 = 0.02 in the explanation of the variance in the favorability of brand associations. This increase is again not significant, F (1,93) = 0.94, p = 0.39.

Age- brand response The dependent variable brand response consists out of multiple dependent variables namely: a) brand attitude, b) quality of the programs, c) likeability of the programs and d) viewing intentions. Again, hierarchical regressions will be conducted to see if there is any moderating relationship of age on these dependent variables. a) Brand attitude The hierarchical regression for level of BCC and the brand attitude is significant, F (1,94) = 10.48, p = 0.02. Level of BCC explains 10% of the variance in the dependent variable brand attitude. However, when age is added in the model it can be seen that the explained variance is not increasing enough. The R2 change is only 0.004. This means that age has not a significant moderating effect on brand attitude, F (1,93) = 5.44, p = 0.50. In table 3 in Appendix 9 the results are portrayed. For type of BCC no significant effect was found on brand attitude, F (1,94) = 3.03, p = 0.08. Adding age as a moderator leads only to an increase of the R2 of 0.005. This is not a significant increase, F (1,93) = 1.73, p = 0.50. b) Program quality The hierarchical regression for level of BCC and the program quality is significant, F (1,94) = 7.16, p = 0.01. Level of BCC explains 7.1% of the variance in the dependent variable program quality. The results show that when age is added in the model, it only increases the R2 with 0.03. Again, age has no moderating effect since the increase is not

92 Forced brand marriages in broadcasting to fight competition. Happily ever after? significant, F (1,93) = 4.99, p = 0.10. In table 4 in Appendix 9 the results are portrayed. The hierarchical regression for type of BCC and program quality is not significant, F (1,94) = 0.45, p = 0.50. The moderating effect of age is also here not significant, F (1,93) = 1.56, p = 0.21. c) Likeability of the programs The hierarchical regression for level of BCC and likability of the programs is significant, F (1,94) = 7.59, p = 0.01. Level of BCC explains 6.5% of the variance in the dependent variable likeability of the programs. The results show that when age is added in the model, it does not increases the R2 = 0.00. Age has no moderating effect, F (1,93) = 3.77, p = 0.88. In table 5 in Appendix 9 the results are portrayed. The hierarchical regression with type of BCC is also significant, F (1,94) = 4.23, p = 0.04. Type of BCC can explain 4.3% of the variance in the likeability of the programs. When age is added as a moderating variable it can be seen that there no change in the R2. Meaning that age has no moderating effect on the effect of type of fit on the likeability of the programs, F (1,93) = 2.10, p = 0.88. The results of the analysis can be found in table 6 in Appendix 9. d) Viewing intentions The hierarchical regression for level of BCC and viewing intentions is not significant, F (1,94) = 2.24, p = 0.14. The results show that when age is added in the model, it does not significantly increases the R2 (0.014). Age has no moderating effect, F (1,93) = 1.81, p = 0.17. The hierarchical regression for type of BCC and program quality is not significant, F (1,94) = 0.45, p = 0.50. The moderating effect of age is also here not significant, F (1,93) = 1.56, p = 0.21.The results of this hierarchical regression analysis are portrayed in table 7 in Appendix 9. The hierarchical regression with type of fit is significant, F (1,94) = 4.44, p = 0.04. Type of fit can explain 4.5% of the variance in the viewing intentions. When age is added as a moderating variable it can be seen that there is almost no change in the R2 = 0.013. Meaning that age has no moderating effect on the effect of type of fit on the likeability of the programs, F (1,93) = 2.88, p = 0.25.

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8. Discussion This study investigated the effect of level of BCC and (potential) types of BCC of brand alliances in the Dutch broadcasting industry on the brand perceptions of consumers. This study wanted to provide a deeper meaning of fit and in particular of brand concept consistency in the broadcasting industry. A two-dimensional approach on brand concept consistency was implemented. Not only the level of BCC was taken into consideration but also the influence of (potential) different types of BCC. In this chapter the results of this research will be discussed in light of the previous literature. Furthermore, the research design will be discussed and the possible limitations of the design that is used in this study.

8.1 The role of level of BCC The exploratory study showed that broadcasting networks are distinguished in the eyes of consumers based on different kind of categories. Even when consumers are asked to categorize public and commercial broadcasters a clear difference between the public broadcasters came forward. Simultaneously, this resulted in broadcasting networks that are quite similar and fit together and broadcasting networks that are not similar and do not fit together. This is in line with the arguments that a fit or misfit goes beyond product feature similarity (Park, Milberg & Lawson, 1991). A misfit/fit between broadcasters can be based on brand concept consistency (BCC) or in other words: how similar are the brand images that the broadcasters portray? The question still remained if these variety in levels of BCC between broadcasting brands would also have an influence on the customer-based brand equity.

The effect of level of BCC on the brand associations The main study tries to answer that question. Brand alliances with a low or high fit form a new associative network (James, 2005). This associative network can consist out of enhanced brand schema(’s) of the separate brand(s). In that case original brand associations were transferred (James, 2005). On the other the hand, brand associations can also only relate to the brand alliance itself (Rao & Ruekert, 1994). Congruent with previous findings on brand image transfer and the role of similarity between brands and/or objects, this study finds that a brand alliance with a misfit on BCC results in a greater proportion of general brand associations. On the other hand, a brand alliance with a fit

94 Forced brand marriages in broadcasting to fight competition. Happily ever after? based on BCC results in a smaller proportion of general brand associations. This study thus founds support that the brand image transfer process is influenced by level of BCC. In a way that a misfit on BCC could result in incongruence which makes the transfer of specific brand associations less easy. Therefore a larger proportion of the brand association are generic. This is in line with the schema theory. This theory is based on the fact that incongruent information is filtered out because it does not fit in a current schema. Consequently, this is resulting in less image transfer (Misra & Beatty, 1990). The potential that existing brand associations can be transferred and enhanced is less likely when there is no similarity (Milberg, Park & McCarthy, 1997). The only existing schema that can be used in case of incongruence is the schema referring to the product category, in this case the broadcasting industry or to the brand alliance itself. Building on the same theoretical background it was also expected that the quantity of the brand associations would be effected by the level of BCC. It was expected that a misfit on BCC puts pressure on the information processing due to the incongruence. Resulting in less brand associations since brand association of the separate brands would be ‘lost’ and could not be transferred. However, no support was found in this study for the effect of level of BCC on the amount of brand associations. An explanation for this could be that it was easy for respondents to come up with a lot of other associations, which are maybe lower in quality but not in terms of quantity. A larger proportion of generic associations was the result of exposure to a broadcasting alliance with a misfit on BCC, however a misfit on BCC does thus not lead to less brand associations. Another reason that an effect for the amount of brand associations is not found could be caused by the experimental setting of this study. Respondents were asked to come up with associations and they had to continue until nothing came up anymore. This could have caused that respondent maybe felt too much pressure to come up with as many associations as they could, also in the case of a misfit. Building on the congruity theory it was expected that a misfit on BCC puts pressure on the consistency that people like to experience (Osgood & Tannebaum, 1955). People prefer harmony or consistency in their mind. When incongruity is perceived, people will be motivated to change their thoughts to seek congruity again (Osgood & Tannebaum, 1955). However, incongruent with this line of thought, this study does not find support for the fact the brand associations towards a brand alliance with a fit on BCC

95 Forced brand marriages in broadcasting to fight competition. Happily ever after? are more positive than towards a brand alliance with a misfit on BCC. An explanation for this can be that the alliance between the broadcasting brands was presented as a forced brand merger. Some authors argue that consumer responses towards a brand alliance in general elicits a positive response of consumers but that this is different for mergers (Andrews, 2008; Jaju, Joiner & Reddy, 2006). Often the reasons behind a merger are reducing costs by integrating similar departments and functions (Howell, 1970; Rappaport 1987 as cited in Andrews, 2008, p.4). Mostly the brand mergers are driven by short-term goals which leads to mistrust and failure (Basu, 2006). During the merging process managers unfortunately do not have much attention for customers since managers are very strongly internally oriented (Hitt, Hokisson & Ireland, 1990). When firms or brands merge there is chance that customers will feel insecure about their relationship with the merging firms (Andrews, 2008). The strong internal focus and the lost focus on consumers could cause that customers switch away from the newly merged company to another company (Morrall, 1996 in Andrews, 2008, p.6). In the main study the stimuli was relating to the fact that the brand mergers had to take place due to cuts in the media budget. In the stimuli it was also stated that the broadcasting networks were willing to merge into one brand. However, this was maybe not enough to elicit positive responses. Another reason that no differences were found in the favorability of the brand associations could be that the difference between the misfit and fit on level of BCC was not large enough. The results of the pre-test indicated that the selected combinations with a fit indeed scored high on the BCC scale. However, in the main study the brand alliances with a fit on BCC scored more moderately than high on BCC. A reason for this could be that in the pre-study people judged multiple brand combinations with a misfit and fit based on BCC. In that situation the fits and misfits can be clearly seen by the respondents because the context offers possibilities to compare multiple brands and their different brand schema’s. A repeated measurements design can also cause a carrying over effect. When respondents judged a clear misfit in the pre-study, the effect could carry over to evaluation of the next brand combination: in that the clear misfit of the previous brand combination underscored the high fit of the next combination. In the main study only one brand combination was judged.

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The effect of level of BCC on the brand responses Congruent with previous literature on the role of level of BCC, this study supports that brand responses are more positive towards brand alliances with a fit on BCC than towards brand alliances with a misfit on BCC. The brand responses are of a higher order in the CBBE pyramid than the brand image (measured by brand associations). In the end, positive brand judgments and feelings are needed to reach the top in terms of brand resonance (Keller, 2001). However, a logical assumption is that favorable brand associations are needed to move up in the CBBE pyramid to eventually get a positive brand response. That being said, the brand responses towards the brand alliances with a fit on BCC were less negative than towards the brand alliances with a misfit on BCC. The brand attitudes towards both brand alliances with a fit and a misfit on BCC were below a 4. Or in other words below neutral and more negative than positive. The same effect was found for the quality of the programs and the likeability of the programs. It can be concluded that a brand alliance in broadcasting with a fit on BCC leads to less negative brand responses that a brand alliance in broadcasting with a misfit on BCC, even when controlled for pre-existing brand attitudes, pre-existing quality assumptions and brand familiarity. It could be stated that a brand alliance in broadcasting with a fit on BCC is less destructive than a brand alliance in broadcasting with a misfit on BCC. It cannot be concluded that the brand alliances in broadcasting have a very positive effect on the brand responses. Finally, no effect of the level of BCC of the broadcasting alliances was found on the viewing intentions. An explanation for this is that a misfit may arouse curiosity by consumers and that this triggers the viewing intentions. The clear incongruence then triggers this curiosity. Curiosity can be seen as a powerful driver and motivator for behavior (Van den Driessche, Vermeir & Pandelaere, 2013). Curiosity leads to exploring and resolving the uncertainty by making the unknown, known (Van den Driessche, et al., 2013). As mentioned before, price is not a point of difference in the traditional broadcasting industry. Consumers only have to invest their time and some effort in their products by viewing the programs. The costs of shifting are thus very low (Chan-Olmsted, 2006). When curiosity is triggered by a misfit, so is exploring that misfit because it can be considered as ‘unusual’. When exploring is ‘free’ and only costs time this could cause that the viewing intentions are not lower for brand alliances with a misfit on BCC.

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8.2 The role of types of BCC Inspired by Zhang and Sood (2002) who found that consumers evaluate a fit between brands based on different cues that can be ‘deep’ or ‘surface’, this study also approached perceived fit between brands from another perspective. In this study the types of misfit and fit between broadcasting networks based on BCC were explored. The results of the exploratory study showed different clusters of broadcasting brands based on shared associations. The results indicated a clear pattern in the perceptual maps of the Dutch broadcasting industry. Since labels were given based on shared associations, the different types of misft/fit came forward. As extensively discussed some broadcasting brands in the Dutch broadcasting industry were categorized based on ‘deep’ features such as religion or political views. Other broadcasting brands were categorized based on the fact that they aim to reach a specific target audience (young and/or older people) or provide a specific type of content: the more ‘surface’ features. However, in the main study the brand combinations that were selected based on different types of BCC seemed to be evaluated on multiple (or other) dimensions instead of the dimension of misfit/fit that was prospected. An explanation for this could be that different types of misfit/fit are more visible when consumers are faced with multiple brands and have more opportunities to identify multiple types of misfit/fit. Following the associative network theory: there are more triggers to activate certain nodes and links. Brand salience is the driver for quantity of brand associations (Rossiter & Percy, 1987 in Keller 1993). It is expected that more sets of nodes in the brain will be activated by exposure to multiple brands. When less brands and thus less “context” is presented, less sets of nodes will be activated. In the main study only two brands were presented in isolation of all the other broadcasting brands, which makes it harder to see all the different types of misfit/fit that exist. Consequently, it makes it harder to estimate which type of misfit/fit ‘fits’ the best by the brand combination because the types of misfit/fits cannot be compared due to the lack of the activation of multiple sets of nodes. That could be the reason why most people referred to ‘target audience’ or ‘content’ as a reason for misfit/fit. This could be the type of fit that comes to mind first when thinking of any broadcasting combination. In the main study consumers were not forced to think more deeply about why certain broadcasting brands fit together or why they do not fit together. In the exploratory study they were

98 Forced brand marriages in broadcasting to fight competition. Happily ever after? forced to process the information more thoughtfully since multiple brands and multiple opportunities to categorize them were offered. All the broadcasting brands were put together in the exploratory study and respondents had to put the broadcasters in baskets based on shared associations. The context was present while in the main study a lot of that context was missing. Imagine that you were asked what a cow and a fish have in common. A shared associations that probably comes to mind pretty fast is: animals. A fish and a cow are animals. Imagine now that you were asked to categorize the following words based on shared associations: beans, apples, rice, grains, milk, bananas, bread, pineapple, broccoli, eggs, fish and cow. Now it could be that other types of fit are more prominent and that a fish and a cow fit together because ‘vegetarians do not eat fish and cow’. The other words placed in the context (in the exploratory study the other broadcasting brands) activate other sets of nodes (such as vegetables, fruits, healthy etc. ) which makes it possible to see other similarities/dissimilarities that would not be easily seen without the context. There are more ‘schema’s that can be compared based on similarity with each other. All the similarities/dissimilarities between the other concepts (bananas + pineapple + apples = fruit & broccoli + beans = vegetables.) could then in turn influence the categorization process for the specific concepts (fish + cow = non vegetarian). This could be the reason that the manipulation checks for the types of misfit and fit partially failed in the main study. Meyers, Goldsmith and Dhar (2012) also highlight the importance of the consumers’ decision making environment. When brand extensions are presented with visual cues or with comparative brands the preferences of consumers seem to shift from low quality brands with a high fit to high quality brands with a low fit. These results also indicate that the environment of consumers can play a crucial role in brand evaluations and maybe even brand preferences. Correspondingly, assuming that the context can play a role in the categorization process of consumers does make sense and is something that should be explored in future studies. It could thus be argued that evaluating a fit based on surface or deep features is not only influenced by age (Zhang & Sood, 2002) but potentially also by the (complexity) of the context that is provided (multiple brands). If the context is more complex and/or offers multiple objects it could be that the evaluation

99 Forced brand marriages in broadcasting to fight competition. Happily ever after? of a misfit/fit is based on more deep features. Due to the fact that more sets of nodes are activated in the brain and as explained: certain sets of nodes can cause that someone thinks about other sets of nodes. At the same time, when consumers are faced with a more simple context without multiple objects, a brand evaluation could be based on more ‘surface’ features. In a simple context less sets of nodes are activated which results in a more ‘simple’ evaluation. In the example this simple evaluation would be referring to the shared association ‘animals’ for cow and fish. A more difficult ‘deep’ one, caused by a more complex context is then the shared association ‘not suitable for vegetarians’. Now that the concept type of BCC is more explained in light of the results of this study the hypotheses that were based on the interaction effects of type of BCC will be discussed. The hypotheses were tested since not all manipulation checks failed. As mentioned, the results still have to be interpret with caution because the manipulation checks did not fully succeed. It was expected that the perceived misfit and fit would be more visible for the ‘surface’ types of misfit/fit and less visible for the ‘deep’ types of misfit/fit. It was expected that this would in turn result in more positive evaluations (in case of a fit) or more negative evaluations (in case of a misfit) for the brand combinations with a misfit/fit based on surface features. However, no interaction effect of type of fit was found. An explanation for this could be that the manipulations partially failed and that type of fit is hard to isolate and very difficult to manipulate. Type of BCC is a construct that seems to be very ambiguous because multiple types of misfits and fits can be seen by somebody. Another unexpected result that was found en that needs to be discussed is the main effect for type of BCC that was found on the proportion of general brand associations. A misfit/fit based on a more ‘deep’ feature (religion) resulted in more general brand associations than a misfit/fit based on a more ‘surface’ feature (target audience). An explanation for this could be that people use a more ‘surface’ ways of evaluating the misfit/fit between broadcasting brands, as was shown in the additional analysis. Most people gave a ‘surface’ reason (content and target audience) for the misfit/fit between the broadcasting brands. When people are faced with a misfit/fit that is based on a ‘surface’ feature, people can simply mention more about that because they use a more ‘surface’ way of evaluating. When people are faced with a misfit/fit based on a ‘deep’ feature and

100 Forced brand marriages in broadcasting to fight competition. Happily ever after? still use a ‘surface’ way of evaluating (looking at target audience and/or content) it is harder to come up with brand specific associations. A ‘deep’ fit needs a more ‘deep’ way of evaluating.

No moderating influence of age The last thing that needs to be discussed is the influence of age on perceiving a misfit/fit on BCC in the Dutch broadcasting industry. The results of the exploratory study clearly showed that young people do categorize the public and commercial broadcasters differently than the elderly. Elderly make a clear distinction between the kind of public broadcasters based on shared associations while younger people tend to make a more clear distinction between the commercial broadcasters. It was argued that this result could be explained by the fact that older people have more knowledge about the public broadcasters and their roots. The pillarization is not such an obscure event for the elderly since they grew up with it or their parents grew up with it. Young people on the other hand did not grew up with pillars and a clear deviation in society based on these pillars. Around 1960 the pillarization gradually disappeared in the Netherlands (“Verzuiling En Ontzuiling…”, n.d). An additional analysis was performed to check if age could have a moderating effect on any of the relationships. However, no moderating effect of age was found. Based on these results it could be argued that the effect of level of BCC between Dutch broadcasting brands on the brand perceptions is the same for older and younger people. Furthermore, this also the case for the main effect that was found of type of BCC on the general brand associations.

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Chapter 9. Conclusion The main objective of this study was to investigate the role of level of BCC and different types of BCC for brand alliances in broadcasting on the perceptions of consumers: the viewers. A consumer perspective was taken by examining the effects of different levels of BCC and types of BCC on the brand associations and brand responses. A qualitative and a quantitative approach were used to explore the concept of BCC in this specific industry: the broadcasting industry. An industry that was traditionally characterized by competition from other broadcasters but since the technological shifts they also face fierce competition from other relatively ‘new’ platforms such as Netflix (Matrix, 2014). The traditional TV audience is now also watching series and films on services like Netflix. In this complex and highly dynamic market, a strong brand is needed to make sure that consumers do not switch to the competitors. Reaching the top of the CBBE pyramid in terms of brand resonance seems more than ever crucial. Brand alliances have an influence on the brand perceptions of consumers and thus also on the strength of the brands. The real meaning of media brands if far from fully developed (Chan-Olmsted, 2006, in Ots, 2008, p.1) and so is the real meaning of brand alliances in the media. Inspired by the real brand mergers that took place in Dutch public broadcasting and the lack of knowledge in this area, the following research question was formulated:

“What is the role of brand concept consistency for brand alliances in broadcasting on the brand perceptions of consumers? “

First an extensive literature review was given on customer-based brand equity. The relevance of brand equity in Dutch broadcasting was extensively discussed. Followed by a literature review on the effects of brand alliances on consumer perceptions. Drawing on the brand alliance literature, the associative network theory, schema theory, congruity theory and the categorization theory multiple hypotheses were formulated. A two- dimensional approach on BCC was implemented by exploring the influence of level of BCC but also the influence of a less traditional concept: type of BCC. It was expected that brand alliances with a misfit on BCC would result in more negative outcomes in terms of the associative network model: less brand associations, less

102 Forced brand marriages in broadcasting to fight competition. Happily ever after? favorable brand associations and a larger proportion of general brand associations. Furthermore it was expected that a misfit on BCC would lead to more negative brand responses in terms of: the brand attitude, the program quality, the likeability of the programs and the more behavioral response: the viewing intentions. Additionally, the hypotheses stated that different types of misfit and fits would have a different effect on the outcome variables. It was expected that misfits based on more ‘surface’ features (such as target audience and content) would lead to more negative responses than a misfit based on more ‘deep’ features (religion or political views). Simultaneously, it was expected that the reverse was true for brands combinations with a fit based on ‘surface’ and ‘deep’ features. It was expected that a fit based on surface features would elicit more favorable responses than a fit based on deep features. An exploratory study and an online experiment were conducted to explore the role of BCC in the broadcasting industry. First an exploratory study was conducted because of the relatively little empirical research on types of BCC and the meaning of brands in broadcasting. The aim of the exploratory study was to investigate how broadcasting networks are categorized and if different levels and types of BCC could be identified. Based on the results of the exploratory study the brand combinations with different types of BCC and levels of BCC were selected for the main study. The main study had a deductive approach and was conducted to test the hypotheses. An online experiment was conducted in which eight different broadcasting brand combinations, varying on level of BCC and type of BCC were tested. In this online experiment 189 respondents participated. The results of the exploratory study indicated that different levels of similarity were indeed perceived by the respondents. Based on the categorization labels and the perceptual clusters of broadcasting brands different types of misfit and fits were identified. Two more ‘surface’ types of BCC: target audience and content and two more ‘deep’ types of BCC: political views and religion. However, the results of the main study show that types of BCC and maybe even level of BCC are not ‘simple’ constructs but rather very complex ones. The failure with respect to the manipulations in the main study gave relevant new insights on this construct: type of BCC. The results of the additional analysis indicated that when broadcasting brands are isolated another type of misfit/fit is seen. It is argued that this could be caused by the fact that the activation of other sets of

103 Forced brand marriages in broadcasting to fight competition. Happily ever after? nodes is less likely (due to the absence of a context) and that this is the reason why defining the ‘correct’ type of misfit/fit more complicated. It is argued that people then use a more ‘simple’ way of evaluating the misfit/fit based on more surface features (such as target audience and content). The additional analysis indicates such a pattern because the reasons mentioned for a misfit/fit were overall mostly based on target audience (23.3%) and content (31.2%). Consequently, this causes unexpected results when it comes to the successful manipulations of type of BCC in the main study. In line with previous literature support was found for some of the hypotheses relating to the level of BCC. The results indicate that brand alliances in broadcasting with a misfit on BCC generate larger proportions of general brand associations and more negative brand responses in terms of brand attitudes, expected program quality and expected likability of the programs. However, no effect of level of BCC was found on a more behavioral response namely: the viewing intentions. This could be caused by the fact that a misfit based on BCC results in curiosity, which reduces the expected negative effect of the misfit on the viewing intentions. So what is the role of brand concept consistency for brand alliances in broadcasting on the perception of consumers? First of all, the research question can only partially be answered. The role of type of BCC was hard to determine since the results of the main study indicate that it is not a holistic concept. What can be concluded is that level of BCC for brand alliances in broadcasting does have an influence on the brand perceptions. Whereby a brand combination with a fit on BCC leads to more positive brand responses than a brand combination with a misfit on BCC. However, a remarkable finding is that the brand responses towards a brand alliance in broadcasting with a fit on BCC did not result in positive responses but more positive responses in comparison with the misfit on BCC. An explanation for this is that brand mergers in general elicit less positive responses then brand alliances. If this is the case: ‘framing’ the brand merger as a voluntary brand alliance could be crucial in terms of maintaining or strengthening the customer-based brand equity.

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9.1 Suggestions future research Some suggestions for future research have already been discussed in the previous paragraphs. However, some suggestions still have to be highlighted and have to be explained in more detail. The results of this study show that there was no differential effect of level of BCC on the viewing intentions of consumers. Other results were maybe found if the consumers were asked if they would pay for the programs of those broadcasting networks. In that case it is not only the time and effort that consumers have to ‘pay’ but also money. This is very interesting for future research since there is an important trend going on in the media use of today. The market environment of the traditional broadcasters is changing rapidly. Consumers prefer streaming services and video on demand over traditional cable television providers (Matrix, 2014) and more importantly they are willing to pay for those services. Traditional broadcasters nowadays also face competition of platforms such as Youtube but also a lot of competition of video on demand services such as Netflix. Traditional broadcasters launched their own streaming services to keep up with their competitors (Waterman, Sherman & Ji, 2013). In the Netherlands, NPO launched NPO Plus. A paid subscription streaming service of the Dutch public broadcasters that provides programs in high quality, without advertisements (NPO, n.d b). RTL did the same and launched RTLXL, a streaming service where all programs can be watched on demand, in exchange for a monthly subscription. NPO president Henk Hagoort and Managing Director Digital Media at RTL Arno Otto both refer to the fact that the business model of broadcasters (mostly advertisement based) is changing and that it is very likely that in the future consumer will pay more directly for certain programs (“Digitiale Strategie van…”, 2016).Traditional broadcasters have to look beyond the advertisement based business model. Revenues from TV-advertising in Europe dropped significantly and broadcasters have to search for new ways of getting a steady income (De Prato, Sanz & Simon, 2014). However, the question remains if consumers are willing to pay for that service coming from traditional broadcasting networks that use to broadcast their programs for “free”. Especially for the Dutch public broadcasters the question is if consumers feel that it is justified that public broadcasting will charge an extra amount of money for that service. After all, consumers already paid via taxes for public broadcasting. Broadcasting networks should thus also explore the willingness to pay concept and how a strong brand

105 Forced brand marriages in broadcasting to fight competition. Happily ever after? can influence this. Maybe even more importantly: how can the broadcasters create brand resonance so that consumers are willing to pay for their programs? In the future the business model of traditional broadcasters could very likely change from only attracting viewers to attracting ‘buyers’ of the programs that they produce. Customer-based brand- equity then even plays a bigger role for traditional broadcasting networks since the effort of the consumers increases then. It is not only time and effort that has to be invested then. The role of perceived BCC between brand alliances in broadcasting becomes even more important in that case and it is very likely that a misfit between brand alliances in broadcasting then will have an influence on the viewing intentions. Furthermore it is interesting for future research to build on the results of this research and explore different types of misfit/fit. More importantly, to identify types of BCC that could have a differential effect on the outcome variables. Furthermore, another identified relationship should be further investigated: the relationship between the context and the evaluation of a misfit/fit. It seems like a given context in terms of competitive brands, can be crucial for how people categorize certain objects. If certain contexts/situations can be defined and indentified in more detail, the context could be manipulated to generate a more preferable brand response towards a brand alliance. Finally, it could be interesting for future research to explore the role of perceived product feature similarity for media brands. This study indicates that perceived brand concept consistency plays a role for brand alliances in broadcasting. However, what would happen when a broadcasting network decides to produce a weekly magazine and forms an alliance with a magazine brand? Or what happens when a media brand extends to other non media related product-categories?

9.2 Theoretical contributions The existing literature on the meaning of brands in the media is scarce (Ots, 2008). Despite the similarities between media brands and product brands there are also some crucial differences. The main differences are that media brands offer experience goods and price is not a point of differentiation (Chang & Chan-Olmsted, 2010; Chan-Olmsted, 2006). When brands form an alliance, brand associations from one brand to another can be transferred or a new associative network can be formed (James, 2005). This can either

106 Forced brand marriages in broadcasting to fight competition. Happily ever after? have a positive or a negative effect. One of the most important determinants of success is perceived fit (Völckner and Sattler, 2006). However, a lot of literature on the role of perceived is focused on product brands (Becker-Olsen & Hil, 2006). What the influence of brand alliances in broadcasting is on the perceptions of consumers was unknown. This research thus contributes to the literature on the effect of brands alliances in the media. The study focused on brand concept consistency (BCC) and the results indicate that perceived level of BCC is an important factor for the evaluations of the brand alliances in broadcasting. A misfit leads to less positive evaluations than a fit based on BCC. As previously explained a remarkable finding was that a misfit on BCC did not lead to less viewing intentions (the more behavioral brand response). This indicates an important difference between media brands and product brands. For consumers’ the only costs to ‘use’ broadcasting brands is some time and attention. For product brands the costs are larger, they also include paying money for using the product. Perceived BCC could in the case of ‘willingness to pay’ play a more destructive role. Furthermore, this study adds knowledge to the body of literature that is focused on one of the most important drivers of brand alliance success: perceived level of fit and in particular perceived level of brand concept consistency (BCC). Research has examined the differential effects of PFS (product feature similairity) (Aaker & Keller; Simonin & Ruth) and BCC (Park, Milberg). Most of the literature on perceived fit assumes that all consumers’ respond in the same way to different levels of fit (Kim & John, 2008). It is assumed that a low fit results in more negative evaluations than a fit. However, a more recent stream of research is focused on identifying possible moderators on the relationship between perceived fit and brand evaluations. Kim & John (2008) conclude that the construal level of consumers moderates the importance of perceived fit. Zhang & Sood (2002) concluded that age has an influence on how the fit is evaluated. This research is a contribution to the emerging literature that contemplate perceived fit on more than just one traditional dimension: level of fit. Despite the fact that the manipulations of type of BCC did not succeed completely this research provided a relevant insight in how the misfit/fits between the broadcasting brands were evaluated. Finally, this research gave an indication about how the categorization process may be influenced by the consumers’ decision environment (the context). Adding competitive brands and providing a more realistic decision environment could have an influence on

107 Forced brand marriages in broadcasting to fight competition. Happily ever after? the possibilities to identify different types of misfit/fit. The additional insights showed a pattern that when broadcasting brands are evaluated in isolation of competitive brands a more ‘surface’ feature is used to evaluate the fit. However, research is needed to test if a context can indeed influence the evaluations of different types of misfit/fit. The results of this study hopefully raises the interest of other researchers in a less traditional dimension fit: different types of misfit/fit and the possible effects of different types of misfit/fit.

9.3 Managerial implications Important insights can be provided to managers based on this research. First of all, level of BCC has an influence the proportion of general brand associations and several important brand responses. For brand alliances in broadcasting it is thus important that the level of BCC between the involved brands is taken into consideration. Another important note to managers is related to the framing of the brand alliance in for example press releases. In this study the brand alliance was framed as ‘forced’ because it was explained why the brands had to merge (due to cuts in the media budget). In general the brand combinations with a brand fit on BCC did also not elicit very positive responses. The brand attitudes, expected program quality and expected likeability of the programs all scored under a 4 on a scale of 1 till 7.Meaning that the brand responses of a brand alliance with a fit on BCC were also more negative than positive. When a brand merger is framed as a brand alliance, where the benefits of the consumers are more highlighted, it could be that the brand alliance with a fit on BCC will than elicit positive brand responses. The result show that a merger between broadcasting brands does not lead to a very positive evaluation despite the fit. However, a combination that has a misfit on BCC scores more negative than the combination that has a fit on BCC. This is something managers in general should take into account. In the Dutch broadcasting context the management team of BNN and VARA, the broadcasting networks that were openly discussing their sour marriage (Nieuwe Revu, 2014), were better off if they made sure that employees were at least pretending to be enthusiastic. Emphasizing on how the two broadcasting brands could strengthen each other instead of emphasizing how they do not fit together and how awful it is. An involuntary merger is never fun for involved brands and/or organizations, however it seems best for both brands and their brand equity to take

108 Forced brand marriages in broadcasting to fight competition. Happily ever after? a consumer perspective and try to hide the discontentment. For management teams of broadcasting networks and especially for the NPO it is useful to know that broadcasting brands and the misfit/fit between broadcasting brands is mostly evaluated based on the content they produce or the target audience they try to reach. The perceived fit is evaluated based on more ‘surface’ features. This could mean that when broadcasting brands do not fit very well based on more deep features (such as religion or political background) they could still form a brand alliance that elicits positive responses if the programs that they offer or the target audience they aim for are considered as similar. When the broadcasting industry is reforming again this is an important issue to take into consideration. Repositioning could then maybe take place based on content and/or the different target groups in society that they want to reach. Another interesting result is that some of the public broadcasting brands fit with some of the commercial broadcasting brands. According to the exploratory study the public broadcasters: BNN and PowNed fit well with the commercial broadcasters: MTV and Comedy Central. In the main study BNN and MTV were also presented as a brand alliance and elicited more positive responses than the misfit BNN and MAX. Even though the latter ones are two public broadcasters. The fit and misfit is judged differently when the whole competitive field is taken into account. This is especially for the NPO an interesting insight. The NPO is after all responsible for the general positioning of public broadcasting. To justify the existence of public broadcasters they have to be distinctive from their competitors: the commercial broadcasters and nowadays also from competitive services such as Netflix. If they are not different, a distorted market is created which drives unfair competition (Hafkamp, 2013). A fact is that the budget of the NPO is much greater than for the commercial broadcasters. In 2014 the NPO received 635 million euro’s only for the programs. That is without the costs for the organization NPO (Takken & Benjamin, 2016). In comparison, RTL Netherlands had a turnover of 457 million that year and SBS had a turnover of 264 million (Takken & Benjamin, 2016). The Dutch Council for Culture also accentuated that the public broadcasters have to define their distinctiveness again (Raad voor Cultuur, 2014). The Dutch council for Culture is the legal adviser of the government in the field of arts, culture and the media (Raad voor Cultuur, n.d). Clear choices and a sharper focus on specific themes and reaching specific target groups is necessary. The council mentioned: journalism, programs

109 Forced brand marriages in broadcasting to fight competition. Happily ever after? for children, culture, knowledge and informing about events as themes in which the public broadcasters can distinct themselves from commercial broadcasting (Raad voor Cultuur, 2014). Entertainment and commercial sport events did not really prove their added value in terms of distinctiveness according to the Council. It is a challenge for public broadcasters to offer programs that are distinctive from their commercial competitors. However, a sharp focus is needed (Raad voor Cultuur, 2014) to avoid unfair competition (Hafkamp, 2013). It could therefore be argued that broadcasters that are more focused on entertainment should distinguish themselves more from their commercial competitors. The exploratory study showed at least two public broadcasting brands that could fit with commercial ones namely: BNN and PowNed. Simultaneously the main study showed that BNN fits with MTV (a commercial broadcaster) and generates more positive responses than the combination BNN and MAX (both public broadcasters). BNN could maybe focus more on the ‘knowledge’ theme for youth without losing their ‘fun’ image and distinguish in that way from MTV/ Comedy Central. The result of the exploratory study indicate that when a more complete consumer environment is taken into consideration that the categorization of the public broadcasters also changes. Especially younger people (18-30 years) tend to see less dissimilarities between the Dutch public broadcasters when commercial broadcasters come in. So when more competitive brands are added in the consumer decision environment the categorization process of the consumers change. This is an important finding for the broadcasting industry in general. It shows that not only their own market (for example only public broadcasters) should be taken into consideration when brand alliances are initiated but the complete consumer decision environment (commercial broadcasters but also services on demand such as Netflix). Taking a consumer perspective seems crucial when redeveloping the media landscape to fight the fierce competition in the broadcasting industry. Of course all the separate Dutch public broadcasting networks want to survive but do they add significant value to the brand equity of Dutch public broadcasting? And if not, how can the brand hierarchy of the NPO be reorganized? Which brands can form a strong brand alliance so that the overall brand equity of Dutch public broadcasting will get a boost? That seems to be a crucial question that has to be answered in order to overcome the fierce competition

110 Forced brand marriages in broadcasting to fight competition. Happily ever after? in a dynamic and rapidly changing market. The results of this research provide a good starting point to answer that question.

111 Forced brand marriages in broadcasting to fight competition. Happily ever after?

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125 Forced brand marriages in broadcasting to fight competition. Happily ever after?

Appendix 1. Exploratory study: Questionnaire

Slide 1 introduction (all):

Slide 2 an example (all):

126 Forced brand marriages in broadcasting to fight competition. Happily ever after?

Version 1: public broadcasters- starting point:

Version 1: example categorization process of a respondent

127 Forced brand marriages in broadcasting to fight competition. Happily ever after?

Version 2: commercial broadcasters – starting point:

Version 2: example cateorization process of a respondent

128 Forced brand marriages in broadcasting to fight competition. Happily ever after?

Slide 4 (all):

129 Forced brand marriages in broadcasting to fight competition. Happily ever after?

Appendix 2. Exploratory study: Scree plots on the raw normalized stress and the dimensions

Figure 1. Normalized raw stress version 1 (public broadcasters)

Figure 2. Normalized raw stress version 2 (public & commercial broadcasters)

130 Forced brand marriages in broadcasting to fight competition. Happily ever after?

Appendix 3. Pre-test 1: Questionnaire

Beste deelnemer,

Bedankt dat u wil deelnemen aan deze voorstudie voor mijn masterscriptie! Deze vragenlijst is een onderdeel van mijn masterscriptie aan de Universiteit van Amsterdam. Dit onderzoek is opgezet omdat ik graag uw mening wil horen over bepaalde combinaties van omroepen die gebruikt zullen worden in het hoofdonderzoek van mijn scriptie.

Het invullen van de vragenlijst zal ongeveer 10 minuten duren. Bij het invullen van de vragen zijn er geen goede of foute antwoorden, het gaat om uw mening.

Deelname aan dit onderzoek is geheel anoniem. De door u verstrekte informatie en gegevens worden vertrouwelijk behandeld en zijn voor academische doeleinden.

Voor meer informatie, vragen of opmerkingen kunt u contact met mij opnemen via: … Lees alstublieft de instructies goed door.

Nogmaals hartelijk dank voor uw tijd en deelname!

Met vriendelijke groet,

Claudette van Schubert

131 Forced brand marriages in broadcasting to fight competition. Happily ever after?

Q1: Het is de bedoeling dat u uw mening zo goed mogelijk weergeeft op een schaal die loopt van 1 tot en met 7. Vul alleen een 1 in als u echt nog nooit van een omroep heeft gehoord. Hoe bekend bent u met de volgende omroepen

Helemaal onbekend Heel bekend 1 2 3 4 5 6 7

BNN

EO

KRO

PowNed

MAX

NOS

VARA

VPRO

Comedy






Central

MTV

132 Forced brand marriages in broadcasting to fight competition. Happily ever after?

Nu is het tijd om merkcombinaties te beoordelen! Geef uw mening aan op een schaal van 1 tot 7. Waarbij 1 staat voor helemaal mee oneens en 7 voor helemaal mee eens.

Combination 1:

Helemaal mee oneens Helemaal mee eens 1 2 3 4 5 6 7 Ik vind dat de KRO & EO bij elkaar passen qua






imago

Combination 2:

Helemaal mee oneens Helemaal mee eens 1 2 3 4 5 6 7 Ik vind dat de EO & PowNed bij elkaar passen






qua imago

Combination 3:

Helemaal mee oneens Helemaal mee eens 1 2 3 4 5 6 7 Ik vind dat de BNN & NOS bij elkaar passen qua






imago

133 Forced brand marriages in broadcasting to fight competition. Happily ever after?

Combination 4:

Helemaal mee oneens Helemaal mee eens 1 2 3 4 5 6 7 Ik vind dat de BNN & Comedy Central bij elkaar






passen qua imago

Combination 5:

Helemaal mee oneens Helemaal mee eens 1 2 3 4 5 6 7 Ik vind dat de NOS & VARA bij elkaar passen






qua imago

Combination 6:

Helemaal mee oneens Helemaal mee eens 1 2 3 4 5 6 7 Ik vind dat de BNN & MAX bij elkaar passen qua






imago

134 Forced brand marriages in broadcasting to fight competition. Happily ever after?

Combination 7:

Helemaal mee oneens Helemaal mee eens 1 2 3 4 5 6 7 Ik vind dat de KRO & PowNed bij elkaar passen






qua imago

Combination 8:

Helemaal mee oneens Helemaal mee eens 1 2 3 4 5 6 7 Ik vind dat de VPRO & VARA bij elkaar passen






qua imago

Combination 9:

Helemaal mee oneens Helemaal mee eens 1 2 3 4 5 6 7 Ik vind dat de MAX & PowNed bij elkaar passen






qua imago

135 Forced brand marriages in broadcasting to fight competition. Happily ever after?

Combination 10:

Helemaal mee oneens Helemaal mee eens 1 2 3 4 5 6 7 Ik vind dat de BNN & PowNed bij elkaar passen






qua imago

Combination 11:

Helemaal mee oneens Helemaal mee eens 1 2 3 4 5 6 7 Ik vind dat de BNN & MTV bij elkaar passen qua






imago

Combination 12:

Helemaal mee oneens Helemaal mee eens 1 2 3 4 5 6 7 Ik vind dat de VARA & PowNed bij elkaar passen






qua imago

136 Forced brand marriages in broadcasting to fight competition. Happily ever after?

Tot slot nog een aantal algemene vragen.

Wat is uw geslacht?
Man
Vrouw

Wat is uw nationaliteit?

TEXT ENTRY…

Wat is uw leeftijd?

137 Forced brand marriages in broadcasting to fight competition. Happily ever after?

Appendix 4. Pre-test 2: Results

Table 1. Coded brand associations pre-study 2.

Combination Total brand Content Politics Refers Refers to a Unknown associations /program/presenter to a fit misfit s NOSTROS 59 28 / 47.46% 0 0 16 / 0 (N=15) 27.12% TROSAVRO 50 24 / 48% 0 6 / 0 0 (N=15) 12% VARAWNL 44 10 / 22.73% 9 0 8 /18.18% 0 (N=15) /20.45%

Figure 1. Wordcloud for the combination NOSTROS (N=15)

Figure 2. Wordcloud for the combination TROSAVRO (N=15)

138 Forced brand marriages in broadcasting to fight competition. Happily ever after?

Figure 3. Wordcloud for the combination VARAWNL (N=15)

139 Forced brand marriages in broadcasting to fight competition. Happily ever after?

Appendix 5. Main study: Example of the stimuli

140 Forced brand marriages in broadcasting to fight competition. Happily ever after?

Appendix 6. Main study: Example of the Questionnaire

Beste deelnemer,

Bedankt dat u wil deelnemen aan dit onderzoek! Dit onderzoek is een onderdeel van mijn Masterscriptie voor de opleiding Business Studies aan de Universiteit van Amsterdam en het gaat over de merkbeleving van verschillende omroepen.

Het invullen van de vragenlijst zal ongeveer 10 minuten duren. Bij het invullen van de vragen zijn er geen goede of foute antwoorden, het gaat om uw mening. Neem alstublieft de tijd om de instructies goed te lezen.

Deelname aan dit onderzoek is geheel anoniem. De door u verstrekte informatie en gegevens worden vertrouwelijk behandeld en zijn voor academische doeleinden. Voor meer informatie, vragen of opmerkingen kunt u contact met mij opnemen via: …..

Nogmaals hartelijk dank voor uw tijd en deelname!

Met vriendelijke groet,

Claudette van Schubert

141 Forced brand marriages in broadcasting to fight competition. Happily ever after?

Wat is uw leeftijd?

Dit onderzoek zal gaan over de omroepen EO en PowNed . Het is de bedoeling dat u uw mening zo goed mogelijk weergeeft op een schaal die loopt van 1 tot en met 7. Geef een 1 als u deze omroep echt niet kent. Geef een 7 als u heel bekend bent met de omroep.

Q1:Geef aan in hoeverre u bekend bent met deze omroepen:

Heel erg onbekend Heel erg bekend 1 2 3 4 5 6 7

EO:

PowNed:

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De volgende stellingen zullen gaan over uw houding ten opzichte van de EO.

Q2:Geef aan in hoeverre u het eens bent met de volgende stellingen:

Helemaal mee oneens Helemaal mee eens 1 2 3 4 5 6 7 Ik heb een positieve houding ten op zichtte van






EO

Ik vind dat de kwaliteit van de






programma's van EO hoog is

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De volgende stellingen zullen gaan over uw houding ten opzichte van de EO.

Q3:Geef aan in hoeverre u het eens bent met de volgende stellingen:

Helemaal mee oneens Helemaal mee eens 1 2 3 4 5 6 7 Ik heb een positieve houding ten op zichtte van






PowNed

Ik vind dat de kwaliteit van de






programma's van PowNed hoog is

Lees onderstaande instructie voor de volgende opdracht alstublieft GOED door.

- Straks ga ik u vragen welke ASSOCIATIES een bepaalde omroep bij u oproept, dus waar u zoal aan denkt als u de naam van die omroep hoort.

- Associaties kunnen zowel positieve als negatieve dingen zijn, die bij u opkomen als u aan die omroep denkt. U kunt straks alles (ja echt alles!) opschrijven wat er in u opkomt.

- Vervolgens zal u nog gevraagd worden om voor elke associatie te noteren of deze positief, neutraal of negatief is

Ter illustratie zal er nu eens voorbeeld worden gegeven van hoe het zou kunnen werken. Klik op de pijltjes rechtsonder om door te gaan.

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1. Opschrijven van al uw associaties De eerste stap is het opschrijven van alle gedachtes die er in u opkomen wanneer u aan de Amsterdam Arena denkt.

U denkt daarbij bijvoorbeeld aan:

1) Ajax 2) Een slechte grasmat 3) Popconcerten 4) Slechte stoeltjes 5) Elektrisch dak 6) Suarez topscorer Eredivisie 7) Ben er nog nooit geweest 8) Bonnetjes rotsysteem 9) ... etc. etc.

Associaties zijn dus echt alle gedachtes die er bij u opkomen wanneer u in dit geval aan de Amsterdam Arena denkt.

2. Positief, neutraal of negatief? Daarna moet u voor elke associatie aangeven of deze positief, neutraal of negatief is.

Indien u zelf een fan bent van Ajax dan is de associatie ‘Ajax’ een positief kenmerk. Bent u juist geen fan van Ajax, dan is het een negatief kenmerk. En heeft u eigenlijk helemaal niets met voetbal, dan is het misschien meer een neutraal kenmerk.

Succes!

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Lees nu alstublieft eerst het artikel dat op www.nu.nl is geplaatst. Lees vooral de eerste alinea en de laatste alinea onder het kopje: 'Eén omroep, één merk: EO-PowNed' aandachtig door.

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LET OP: Zoals u heeft gelezen zijn er een aantal ontwikkelingen in de politiek waardoor publieke omroepen moeten fuseren. In dit onderzoek gaat het verder niet over uw mening over deze politieke ontwikkelingen en de fusies. Daarnaast gaat het ook niet om uw mening ten opzichte van de algehele Nederlandse Publieke Omroep. Het gaat puur over merkbeleving en hoe u naar de nieuwe omroep EO-PowNed kijkt en wat u van deze nieuwe omroep vindt.

Q4: Schrijf al uw associaties op

Schrijf alstublieft alles op wat er in u opkomt als u denkt aan de nieuwe omroep EO-PowNed.

Neem zoveel tijd als u nodig hebt en ga net zo lang door totdat er geen associaties/gedachtes meer in u opkomen. Gebruik voor elke associatie een aparte regel.

*Associaties kunnen zowel positieve als negatieve dingen zijn, die bij u opkomen als u aan EO- PowNed denkt. U kunt alles (ja echt alles!) opschrijven wat er in u opkomt.

1.

2.

3.

4.

5.

6.

7.

8.

9.

10.

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Q5: Positief, neutraal of negatief?

Geef voor elke associatie die u hebt opgeschreven aan in hoeverre deze positief, neutraal of negatief voor u is.

Laat de rijen zonder een associatie leeg. Heel negatief Heel positief 1 2 3 4 5 6 7

TEXT Associatie 1

TEXT Associatie 2

TEXT Associatie 3

TEXT Associatie 4

TEXT Associatie 5

TEXT Associatie 6

TEXT Associatie 7

TEXT Associatie 8

TEXT Associatie 9

TEXT Associatie 10

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Er zullen nu nog een aantal stellingen volgen die gaan over de nieuwe omroep EO-PowNed en uw houding ten opzichte van deze nieuwe omroep.

Q6: Geef aan wat uw gevoelens zijn ten opzichte van de nieuwe omroep: EO-PowNed

1 2 3 4 5 6 7 Zeer slecht






Zeer goed Zeer Negatief






Zeer Positief

De volgende stellingen gaan over de programma’s die EO-PowNed zal maken en uw houding ten opzichte van deze programma’s

Q7: Naar mijn mening kan de nieuwe omroep EO-PowNed programma’s aanbieden die ik zou beoordelen als:

1 2 3 4 5 6 7 Zeer slecht






Zeer goed Zeer onaantrekkelijk






Zeer aantrekkelijk Zeer stom






Zeer leuk

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Q8:Geef aan in hoeverre u het eens bent met de volgende stellingen:

Helemaal mee oneens Helemaal mee eens 1 2 3 4 5 6 7 Ik verwacht dat de kwaliteit van de programma's van






EO-PowNed hoog zal zijn De kwaliteit van de programma's die EO-PowNed gaat






maken moet wel heel goed zijn Ik heb een positieve attitude ten op






zichte van EO- PowNed Het is aannemelijk dat ik programma’s ga kijken die






gemaakt worden door EO-PowNed

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Q9:Geef aan in hoeverre u het eens bent met de volgende stellingen:

Helemaal mee oneens Helemaal mee eens

1 2 3 4 5 6 7 EO past goed bij de ideeën en het imago






van PowNed Ik denk dat EO hetzelfde imago






uitstraalt als PowNed

Het is belangrijk voor dit onderzoek om te weten waarom u EO en PowNed wel of niet bij elkaar vindt passen.

Q10: Geef een korte beschrijving gebaseerd op de vragen: ‘Wat hebben de EO en

PowNed gemeen of juist helemaal niet? En waarom vindt u dat de EO en PowNed wel of niet bij elkaar passen?

TEXT ENTRY..

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Tot slot nog een aantal algemene vragen. U bent bijna klaar! Q11: Hoeveel uur per dag kijkt u naar televisie? Probeer een schatting te maken en vul het aantal uren in getallen in.

TEXT ENTRY…

Q12:Geef aan in hoeverre u het eens bent met de volgende stellingen:

Helemaal mee oneens Helemaal mee eens 1 2 3 4 5 6 7 Ik heb een positieve houding ten op zichtte van de






algehele Nederlandse Publieke Omroep Ik vind dat de kwaliteit van de algehele Nederlandse






Publieke Omroep hoog is Ik zou het niet erg vinden als Nederlandse Publieke






Omroep zou verdwijnen Ik zou de programma's van de






Nederlandse Publieke Omroep niet missen

Q13: Bent u lid van een publieke omroep?

Ja
Nee

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Only showed when Q13 is answered with ‘Ja’. U hebt aangegeven lid te zijn van een publieke omroep. Schrijf hieronder de omroep op waarvan u lid bent.

TEXT ENTRY..

Q14: Wat is uw geslacht?
Man
Vrouw

Q15: Wat is uw hoogst genoten opleiding?
Lager onderwijs
VMBO
HAVO
VWO
MBO
HBO
Universiteit Q16: Wat is uw nationaliteit?

TEXT ENTRY…

Q17: Mijn allerlaatste vraag is of u alle gedachtes die nu in u opkomen of tijdens het invullen van het onderzoek in u opkwamen wil opschrijven:

TEXT ENTRY..

Hartelijk dank voor uw deelname aan dit onderzoek! U heeft mij op weg geholpen om de eindstreep te halen!

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Appendix 7. Main study: Categorization key independent variable: type of BCC. Hoofdcat Label Subcat Label Examples 0 Onbekend 1 Onbekend- Respondent heeft absoluut geen enkel idee waar het geen reden over gaat: Weet niet, geen idee, ik zou het niet weten 2 Onbekend Respondent is onbekend met de omroep(en): met ik ken ze (of één omroep) niet goed genoeg, ik kan het omroep zelf niet beoordelen omdat ik niet genoeg kennis heb, ben onbekend met de omroep(en) 1 Algemene 3 Algemene Respondent benoemt NIET specifiek wat er precies fit/misfit misfit verschillend is en wat zorgt voor de misfit: imago ‘Ze passen gewoon niet bij elkaar’. ‘Ze lijken niet op elkaar’. 4 Algemene Respondent benoemt NIET specifiek wat er precies fit imago hetzelfde is en wat zorgt voor de fit op basis van imago: ‘Ze passen wel bij elkaar’. ‘Ze lijken niet op elkaar’. 5 Algemene Respondent benoemt NIET specifiek waarom misfit kernwaarden/visie verschillen: visie/kernw ‘Hebben een verschillende visie’. ‘Waarden zijn te verschillend/niet gelijk’. aarden 6 Algemene Respondent benoemt NIET specifiek wat er dan fit hetzelfde is in die visie kernwaarden: visie/kernw ‘Hebben dezelfde visie’. ‘Waarden zijn te hetzelfde/gelijk’. aarden 2 Political 7 Politieke Respondent verwijst naar de politieke verschillen view misfit (stroming of politici): de een liberaal de ander rechts, verschillende politieke visie, verschillende politieke voorkeur, verschillende politieke gedachtegang, niet dezelfde politieke stroming, links, rechts, groen, rood.

8 Politieke fit Respondent verwijst naar de politieke overeenkomsten (stroming of politici): Beide liberaal/beide rechts/beide links/ beide groen/beide rood, zelfde politieke visie, zelfde politieke voorkeur, zelfde politieke gedachtegang, zelfde politieke stroming 3 Religion 9 Religion Respondent verwijst naar de verschillen op basis van misfit religie/geloofsachtergrond: Verschillende religie/verschillende geloofsachtergrond, één christelijk/katholiek/evangelisch, ander atheïstisch, één gelovig ander niet gelovig. Ook redenen die refereren naar : ‘grevo’, ‘god’ en een misfit benadrukken.

10 Religion fit Respondent verwijst naar de overeenkomsten op basis van religie/geloofsachtergrond: Beide christelijk/evangelisch/katholiek/gelovig/, atheïstisch/grevo/ beide niet gelovig/ beide te maken met god, zelfde religie, zelfde geloofachtergrond, zelfde geloofsovertuiging

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4 Target 11 Target Respondent verwijst naar de verschillen in de audience misfit doelgroep (kijkers) op basis van verschillende kenmerken; geslacht, leeftijd, klasse etc. niet dezelfde doelgroep, jongeren vs. ouderen, bejaarden, niet dezelfde kijkers, verschillende doelgroep, ander publiek 12 Target fit Respondent verwijst naar de overeenkomsten in de doelgroep (kijkers) op basis van verschillende kenmerken; geslacht, leeftijd, klasse etc. Dezelfde doelgroep, beide jongeren/beide ouderen/beide volks, focussen op dezelfde kijkers/viewers, zelfde publiek. 5 Content 13 Content Respondent verwijst naar de verschillen in de misfit programma’s (programma-inhoud) of het genre dat de omroep aanbiedt: verschillende programma's, kwaliteit/nieuws vs. Amusement, informatief/serieus vs. amusement/vermaak, taak omroep vs. amusement omroep / cultuur vs. Nieuws en sport, ander programma inhoud, ander genre 14 Content fit Respondent verwijst naar de gelijkenissen in de programma’s (programma-inhoud) of het genre die de omroep aanbiedt: dezelfde programma's, kwaliteit/nieuws/amusement/informatief/serieus/c ultuur/beide vermaak/ beide programma’s voor fun/ zelfde programma inhoud, passen bij elkaar qua genre 6 Overig 15 Country of Alles wat refereert naar: origin misfit Nationaal vs. internationaal. Amerikaans vs. Nederlands 16 Country of Alles wat refereert naar: origin fit Beide Nederlands/ Beide Hollands/ Beide nationaal 17 Publiek Alles wat refereert naar: commercie Publiek vs. Commercieel el misfit 18 Publiek fit Alles wat refereert naar: Beide publieke omroepen/ beide betaald door belastingbetalers

Explanation: Aan de hand van de kwalitatieve antwoorden vaststellen waarom er een fit of misfit is volgens de respondent. Graag de antwoorden coderen aan de hand van de subcategorieën. Per respondent maximaal 3 redenen noteren, waarbij de eerste reden het eerste argument is dat wordt genoemd. Gebruik de cijfers onder hoofdcategorie voor het argument dat het eerste wordt genoemd en dus het meest dominant is. Wanneer er maar één reden wordt genoemd voor type fit/misfit, uiteraard één reden noteren. Hieronder volgen een paar voorbeelden ter illustratie.

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Voorbeeld 1: “BNN en MAX passen absoluut niet bij elkaar. Wat moeten die ouderen wel niet van die brutale jonge snotapen denken.” Stap 1: Hoofdcategorie = 4. Het gaat immers alleen maar over ouderen vs. Jongeren (of te wel target audience). Dit is dan ook het dominante argument. Stap 2: Subcategorie = 11. De respondent refereert duidelijk naar dat ze niet passen qua doelgroep.

Voorbeeld 2: “De EO en KRO hebben beide een gelovige achtergrond, ik denk dat ze daarom wel mooie programma’s kunnen maken samen.” Stap 1: Hoofdcategorie = 3. Hier wordt ook gerefereerd naar de programma’s die ze kunnen maken (in de toekomst) echter gaat dat niet over wat ze NU gemeen hebben, dat is namelijk volgens de respondent het geloof. Stap 2: Subcategorie = 9. De respondent refereert duidelijk naar de gelijkenis door ‘beide’ te noemen in het antwoord.

Voorbeeld 3: “Nieuws vanaf het muziekplein? Dit moet wel een grap zijn. NOS maakt kwalitatief hoogstaande programma’s met een focus op nieuws en sport. TROS is simpel en plat vermaak. Dat kan nooit goed gaan” Stap 1: Hoofdcategorie = 5. De respondent verwijst naar de programmainhoud van NOS (nieuws en sport) en naar die van TROS (simpel en plat vermaak). Stap 2: Subcategorie = 13. De respondent refereert duidelijk naar dat er een misfit is door ‘dit moet wel een grap zijn’ en ‘dat kan nooit goed gaan’.

Voorbeeld 4: “MTV en BNN zijn beide meer voor de jeugd. Ik denk dat het wel goed zou zijn als deze twee samen gaan. Ze kunnen dan een grotere doelgroep bereiken (vooral BNN). Het enige dat denk ik lastig wordt is dat de één publiek is en de ander commercieel” Stap 1: Hoofdcategorie = 4. Deze is lastiger, de respondent wijst eigenlijk naar een reden voor fit (zelfde doelgroep) en een reden voor een misfit (publiek vs. Commercieel). Zoals hier boven uitgelegd geldt dan het eerste argument als meest dominante argument. Stap 2: Subcategorie = 12. Er is dus een fit op basis van de doelgroep. En als tweede reden nummer 15 (misfit publiek & commercieel).

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Appendix 8. Main study: Categorization key proportion of general brand associations

(category 1 + 2 = general brand associations) Hoofdcat Label Subcat Label Examples 0 Onbekend 1 Onbekend Associatie refereert naar onbekendheid: Weet niet, geen idee, ik zou het niet weten, geen kennis, onbekend, ken de omroep(en) niet, ‘?’ 1 General / 2 Generieke Al de volgende associaties (enkelvoud en meervouden): shared associaties die bij - over omroepen: Omroepen, commerciële omroepen, category beide omroepen publieke omroepen, Nederlandse publieke omroep, passen en refereren naar de nationaal, vermindering aantal omroepen, ned 1,2,3. product Hilversum, Nederlandse omroepen, Nederlands, toegankelijk categorie: in dit voor iedereen, geldzuigers, NPO, belasting, geval de belastingbetalers, series, films, documentaires, subsidie, omroepwereld. gesubsidieerd, regionale omroepen, landelijke omroepen, tv-gids, ouderwets, kosten teveel, zendtijd, verzuiling, traditioneel, vroeger, old school, uitzendinggemist, npo+, terugkijken

- over televisie/radio: televisie, radio, tv kijken, kijken, luisteren, tijdverdrijf, luid, zenders, net, televisiewereld, programma’s, presentatoren, presenteren, old- school tv kijken, kijkers, programma genre’s, traditioneel voor de buis, tv bingen,

-overig: doelgroepen, geld, crisis, veel groot verdieners, staatssecretaris Dekker, concurrentie van Netflix, HBO, concurrerend met nieuwe tv kijken 2 Fusie/ brand 3 Associaties die Associaties die naar de fusie verwijzen denk aan: alliance specifiek - algemener: samenklontering omroepen, fusie, samengaan, refereren naar de moeten samen fusie

-maar ook associaties die specifiek wijzen naar de fusie in stimuli: deze fusie klopt wel/niet, deze merken moeten samen door bezuinigingen, rare/aparte/leuke combinatie, 3 Overig 3 Passen de  Dan label 3 geven. associaties niet in Associaties die bijvoorbeeld specifiek naar een presentator categorie 0,1, en wijzen: ‘Jan Smit’, ‘Lucille Werner’, of een programma: 2? ‘Spuiten en Slikken’, ‘Wie is de Mol’ of naar één van de merken: jonge doelgroep, journaal, nieuws, plat vermaak. Associaties die verwijzen naar attitudes: avro vind ik stom, ik vind PowNed brutaal, BNN is voor baby’s, Mathijs is niet leuk etc.

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Appendix 9 Additional study: Results of the hierarchical regressions

Age- proportion general brand associations – level of BCC Table 1. Analysis of the moderating effect of age with IV: level of BCC and DV: proportion of general brand associations

R R² R² B SE β t p Change Model 1 Level of BCC 0.272 0.074 0.074 -0.156 0.278 -0.272 -2.740 0.01 Model 2 0.274 0.075 0.001 Level of BCC -0.156 0.279 -0.0273 -2.734 0.01 Age -0.001 0.002 -0.030 -0.297 0.77

Age- proportion general brand associations – Type of BCC Table 2. Analysis of the moderating effect of age with IV: type of BCC and DV: proportion of general brand associations

R R² R² B SE β t p Change Model 1 Type of BCC 0.248 0.061 0.051 -0.142 0.280 -0.248 -2.477 0.02 Model 2 0.249 0.062 0.042 Type of BCC -0.142 0.280 -0.249 -2.475 0.02 Age -0.001 0.281 -0.030 -0.312 0.76

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Age- brand attitude– level of BCC Table 3. Analysis of the moderating effect of age with IV: level of BCC and DV: brand attitude

R R² R² B SE β t p Change Model 1 Level of BCC 0.317 0.100 0.100 0.942 1.430 0.317 3.237 0.00 Model 2 0.324 0.105 0.004 Level of BCC 0.942 1.430 -0.315 3.208 0.02 Age -0.007 1.435 -0.066 -0.673 0.50

Age- program quality– level of BCC Table 4. Analysis of the moderating effect of age with IV: level of BCC and DV: program quality

R R² R² B SE β t p Change Model 1 Level of BCC 0.266 0.071 0.071 0.819 1.496 0.266 2.675 0.01 Model 2 0.311 0.097 0.026 Level of BCC 0.805 1.496 0.262 2.654 0.02 Age -0.018 1.483 -0.162 -1.644 0.10

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Age- likeability of the programs– level of BCC Table 5. Analysis of the moderating effect of age with IV: level of BCC and DV: program quality

R R² R² B SE β t p Change Model 1 Level of BCC 0.273 0.065 0.075 0.754 1.339 0.273 2.754 0.01 Model 2 0.274 0.055 0.000 Level of BCC 0.753 1.339 0.273 2.735 0.01

Age- likeability of the programs– type of BCC Table 6. Analysis of the moderating effect of age with IV: type of BCC and DV: likeability of the programs

R R² R² B SE β t p Change Model 1 Type of BCC 0.208 0.043 0.043 0.573 1.361 0.208 2.057 0.04 Model 2 0.208 0.043 0.000 Type of BCC 0.571 1.361 0.207 2.040 0.04 Age -0.002 1.368 -0.015 -0.149 0.88

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Age- Viewing intentions– type of BCC

Table 7. Analysis of the moderating effect of age with IV: type of of BCC and DV: viewing intentions

R R² R² B SE β t p Change Model 1 Type of BCC 0.212 0.045 0.045 0.744 1.727 0.212 2.106 0.04 Model 2 0.242 0.058 0.013 Type of BCC 0.729 1.727 0.208 2.067 0.04 Age -0.015 1.724 -0.116 -1.147 0.25

161