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The impact of online reviews and samples: the

influence of actors on the effect of review valence

and sample presence in the terms of TV series

watching intention

Dániel Mester

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The impact of online reviews and samples: the

influence of actors on the effect of review valence

and sample presence in the terms of TV series

watching intention

Dániel Mester

Master Thesis

Marketing Department University of Groningen

23 June 2014

Address: Van Houtenlaan 27, 9722 GR, Groningen

Phone: +31-61-903-30-59

Student Number: 2533359

Email: daniel.mester.ofc@gmail.com

Supervisors: dr. Jenny van Doorn

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Management Summary

The developments in the world of Information Technology has fuelled the global interconnectedness of consumers which allowed them to share their opinions and thoughts on the World Wide Web. Moreover, it allowed for marketers to implicate the support of sampling in the online environment which traditionally required direct contact with customers. In the field of marketing there has been research on the impact of reviews and samples on consumer behaviour. Celebrity endorsements and in the case of motion pictures the influence of actors on consumer intentions and market performance has also been investigated, however most of these investigations have chosen stars based on awards and nominations not on awareness. Furthermore, the impact stars have on reviews and samples effect has been largely neglected.

Hence the aim of this investigation was to determine how the presence of a famous star influences the effect of reviews and samples on consumer intentions. Thus a 2 (review valence: positive and negative) x 2 (sample: presence or absence) x 2 (famous actor: presence or absence) between-subjects design was implemented. The online survey was distributed internationally and a total of 220 responses has been collected.

The results have supported previous research that both reviews’ valence, samples and celebrities have a significant and positive effect on customers’ consumption intentions. Additionally it was also discovered that the impact of reviews is really influential, hence managers should keep among their utmost priority to concentrate on avoiding the spreading of negative reviews and fostering the effect of positive ones. It was also found that trailers’ positive impact on consumption intentions is influenced by the presence of famous actors. The effect has found to be negative meaning that the joint presence of actors and trailers decreases their individual effect on consumption intentions. This suggest marketers to narrow their focus and try to avoid the implication of both elements at the same time, in order to effectively utilize their marketing budget and achieve the highest possible efficiency of their marketing actions. Contrary to the expectations the research has failed to show significant results of actors’ impact on reviews in consumption intentions.

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Preface

With my Master Thesis I am closing a really important chapter in my life. It does not only include the last couple of months I have spent with working on it, but all the years of my studies and work.

With this Thesis, I have gathered interesting insights of marketing, with special focus on the customer engagement behaviour. Nevertheless, these understandings that lead to the outcome of this thesis could not have been possible without the help of a handful of people. Therefore I would like to show my gratitude for their support during my thesis.

 dr. Jenny van Doorn for her supervision of my thesis. Her constructive feedbacks and assistance helped me developing my paper.

 Andreana Gosteva for supporting me in troubled times and for helping me in improving my research.

 Ilka Dickmann, Laura Sneeboer and Anton Pashuk for providing a warm and

welcoming feel for the brainstorming sessions during the thesis meetings.

Bloggers of the Sorozatjunkie.hu website, who contributed to my research a great deal by sharing my questionnaire on their Facebook page.

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Table of Contents

Management Summary

3

Preface

4

Table of Contents

5

List of tables and figures

7

1. Introduction

8

1.1 Problem Background

8

1.2 Problem Statement

10

1.3 Research Questions

11

1.4 Theoretical and Managerial Relevance

11

1.5 Structure of the Thesis

12

2. Literature Review

12

2.1 Customer Engagement Behaviour’s Effect on Brands

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2.2 Word-of-Mouth in the entertainment industry

13

2.3 Product Sampling in Case of Experience Goods

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2.4 Actors Effects in the Entertainment Industry

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2.5 Actors as Brands

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2.6 Brands’ effect on consumption intentions

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3. Conceptual Model

17

4. Hypotheses

18

4.1 The Impact of Trailers

18

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5. Methodology and Results

22

5.1 Pre-test

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5.1.1 Design of the Pre-Test

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5.1.2 Results of the Pre-test

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5.2 Design of the main survey

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5.2.1 The manipulations of reviews, trailers and actor presence 24

5.2.2 Built up of the main survey

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5.3 Data collection

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5.4 Sample Characteristics

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5.5 Reliability analysis

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5.6 Main results

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5.6.1 Manipulation check

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5.6.2 Testing the control variables

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5.6.3 Hypothesis testing

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5.6.4 Further analysis of the relationships

33

5.7 Discussion

35

6. Conclusion

37

6.1 Summary

37

6.2 Managerial Implications

38

6.3 Limitations and Further Research

39

References

41

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List of Tables and Figures

Table 1: The TV shows and actors of the pre-test

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Table 2:

Scales and Cronbach’s alpha scores of the pre-test

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Table 3: Mean scores of the pre-test

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Table 4: Overview of the conditions

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Table 5: Socidodemographic overview of the sample

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Table 6: Full trailer watching percentage

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Table 7: Overview of the reliability analysis

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Table 8: Overview of the manipulation check

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Table 9: Dummy variables of the sociodemographics

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Table 10: Overview of the control variable regression

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Table 11: Overview of the results

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Figure 1: The Conceptual Model

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Figure 2: Graphical representation of means 1.

34

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1. Introduction

Media systems and their relationships with its respective audiences have seen dramatic changes in the last decade due to increasing cultural globalization and digitalization. These developments created a trend of change in consumer behaviour from a passive observer into a highly involved active participant. This mostly affects younger generations who are more involved in the so called participatory culture, which includes social connections and engagement with others (Jenkins, 2006). Members of these generations communicate in numerous forms through media channels. Especially the so called social media (i.e. microblogs such as twitter or tumblr, forums, social networks like Facebook) is buzzing from consumers’ thoughts and opinions (Hennig-Thurau et al., 2010). Thus recent technological improvements in the field of information technology (IT) fuelled the opportunities for two-way interactions with customers and focused attention on the concept of the Customer Engagement Behaviour (CEB) (Brodie et al. 2013).

1.1 Problem Background

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9 TV series, similarly to the majority of the entertainment industry, are unique products, which can be labelled as experience goods. In such cases consumers have difficulties to observe product or service characteristics in advance, but these elements can be measured upon consumption (Nelson, 1970). The dominant attributes of experience goods are evaluated or compared more subjectively and with more difficulty compared to search goods (Huang et al., 2009). This constructs consumer perceived risk, but said consumers are apt to be risk averse on most occasions. Risk averse consumers feel vulnerable in a situation involving uncertain product evaluations. One of the main reason behind consumers’ information gathering actions, such as reading reviews, inspecting samples and relying on social guidelines, regardless the product category are to decrease perceived risk and to make suitable decisions easier (Dabholkar, 2006). Since consumers cannot evaluate TV shows without watching them, they turn to features (e.g., plot, genre, trailers, famous actors) or reviews for guidance.

One form of support customers rely on when searching for information are samples. Sampling supports customers by allowing them to picture the product and analyse the quality of it, therefore reducing perceived risk which can lead to increased consumption. For example, the ability to listen online short clips of a music CD allows customers to gather pre-purchase information and even attain a degree of “virtual experience” (Klein, 1998). In case of the motion picture industry trailers often serve the purpose of sampling. Trailers are unique elements with special importance as they function as a marketing tool due to their similarities to advertisements. They both contain messages that highlights features and unique characteristics, emphasize slogans and brands and they use the reputation of firms and people to increase attractiveness (Kernan, 2004). On the other hand samples are proven to more effective compared to traditional marketing tools such as advertising as they are a rapid and direct approach of information delivering to customers, hence their impact on sales is greater (McGuinnes and Mathew, 1992).

To the extent that trailers are insufficient, and audiences lack their own experience or knowledge to make profound judgments, they either turn to reviews or social guidelines (e.g. famous actors, high communal anticipation) to help them evaluate the programme (Mohr, 2007).

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10 have found to be really influential in guiding decisions regarding purchase and consumption by reducing the impact of uncertainty and stimulating interpersonal interactions (Kumar and Benbasat, 2006; Pavlou et al. 2007).

User reviews usually reflect user experience and consumer satisfaction, which are mainly viewed as a source of product information (Chen and Xie 2008; Li and Hitt 2008). Meanwhile other types of WOM, such as discussions in online community sites, reflect more about consumer expectation, which could be heavily influenced by social structure (Gopal et al. 2006; Liu, 2006).

In case of experience goods where the subjective nature of products makes evaluation challenging consumers have to rely on the limited information that is available. It has been found that if consumers are facing obstacles in measuring product quality of if judgemental criteria are vague, the value of available information for the purposes of analysis increases (Bone, 1995). Such available information besides samples and reviews can be the presence of a famous actor, which may influences the effects of the aforementioned features (i.e. plot, genre, trailer) and reviews on consumers’ judgements. Actors’ impact on consumer’s purchase intentions and purchase decisions has been analysed before (Basuroy et al., 2006; Litman, 1983; Ravid, 1999) but their power was always based on awards and nominations and not on awareness and associated fame. Hence it seems suitable to analyse whether the presence of a star has an impact on consumers’ TV series watching intention and how this influences Customer Engagement Behaviour in the case of reviews and trailers.

1.2 Problem Statement

From the illustrated problem background it can be concluded that both reviews and trailers are important factors of consumers’ information gathering and decision making process regardless the product category (Basuroy et al. 2003; Zhu, 2010). Consequently, their role is crucial in case of experience goods when product information is limited before consumption, hence the perceived risk of mentioned actions is relatively high (Pavlou et al, 2007).

So far theory and research show members of the popular culture (i.e. actors, celebrities) can increase attractiveness of and demands for products (Dean 1999, Elberse and Eliashberg, 2003; Levin et al. 1997, Till et. al 2008).

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11 whether actors’ presence have influence on the impact of review valence and sample presence on customers intentions.

For this research experience goods has been selected as the primary target of investigation, since evaluating product quality is generally not objective and such involves high perceived risks (Huang et al. 2009). Moreover the thesis concentrates on TV shows as experience and entertainment goods, of which quality is hard to evaluate before consumption. The research’s goal is to study how the valence of reviews and the availability of a sample enhances consumption intentions and how the presence of an actor alters the chances of consumption. The following problem statement can be formulated from the referred problems:

“Whether a famous actor’s presence influence the impact of review valence and trailer presence on consumption intentions in the TV series environment?”

1.3 Research Questions

In addition to the main research question a number of sub-questions can be formulated:

“Does the presence of a trailer increase the willingness to watch a TV show?”

“Does the presence of a famous actor in a TV series influence the impact of customer generated reviews on watching intentions?”

“Does the presence of a famous actor in a TV series effect the influence of the show’s

respective trailer on consumption intentions?

1.4 Theoretical and Managerial Relevance

For the time being there are no abundant research done on the topic of Customer Engagement Behaviour and its correlation with traditional marketing tools such as sampling or advertising. Furthermore there are not enough scientific evidence about the effect of engagement on costumer’s consumption intensions. Moreover previous research that aimed to investigate the effect of stars on consumption intentions in the entertainment industry approached star power not from the perspective of awareness or fame, but from professional recognition (awards and nominations).

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12 and customer loyalty. It may also contain relevant information for marketers in the entertainment industry, to unveil the importance of celebrities in their product’s marketing campaign and to what extent they should build the campaign on them. Therefore this thesis aims at discovering the settings when it is advantageous or not to rely on customer engagement or on traditional marketing tools in order to improve beneficially customers purchase intentions in case of experience goods in the online environment.

1.5 Structure of the Thesis

This thesis consists a number of chapters and has the following structure: In the upcoming chapter the main findings in the relevant literature with respect to this topic will be presented as part of the literature review to support the previously presented conceptual framework. Based on the abovementioned findings, a conceptual model and hypotheses will be created and to be tested later on. Furthermore, the research design and data collection method of the experiments will be provided along with the analysis of the first experiment. Then the results of the main experiment will be presented and discussed. At last, conclusions, limitations and recommendations regarding the previously elaborated topic will be delivered.

2. Literature Review

2.1 Customer Engagement Behaviour

Customer engagement is a lately arisen development in the area of customer management (Verhoef et al., 2010).

CEB has been defined as a phenomenon that goes beyond purchase and transactions and is a manifestation of brand or firm focused customer’s behaviour which results in motivational drivers (van Doorn et al., 2010). Van Doorn et al. (2010) establishes five core dimension of CEB: valence, nature of its impact, form or modality, scope and customer goals. The article also suggest the following factors regarding the impact of CEB: immediacy, intensity, breadth and longevity. According to the conceptual model founded by van can Doorn et al. (2010) antecedents of CEB are based on consumer, firm and contextual characteristics. This model also points out that reputation, trust and consumer satisfaction are among the key elements of CEB antecedents.

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13 generate positive CEB (de Matos and Rossi 2008; Keller 1998; Walsh et al. 2009). On the other hand, in case of not meeting consumer’s expectations, the extent of negativity may be bigger. As research pointed out, failure of brands with high reputation might lead to proportionally higher level of disappointment than brands with low reputation (Roehm and Brady, 2007).

One of the most common form of CEB are customer generated reviews. However one possible form of reviews, recommendations, are usually resulting positive influence, except when there is no or bad fit between the potential customer and the product/brand. Internet based CEB differ in two of the abovementioned factors compared to regular Word-of-Mouth: immediacy and longevity. Online reviews’ effect are immediate as their messages are quickly reachable for consumers and by their very nature reachable anytime and anywhere for long time periods. Hence it is very important to measure their effect as firms have limited time to react to consequences and as research has pointed out WOM can lead to financial gains for firms such as stock trading based on valence of chatter (Tirunillai and Tellis, 2012).

2.2 Word-of-Mouth in the entertainment industry

Researchers and practitioners have long recognized the importance of person-to-person WOM (e.g., Coleman 1966; Rosenzweig and Foster 1995), but the developments in the field of IT have immensely changed the way information is exchanged and have outgrown the traditional limitations of WOM (Laroche et al. 2005).

Since consumers can share their own thoughts and search for other fellow consumers views within the online environment marketers consider this activity as consumer-to-consumer marketing which is called word of mouth. WOM is greatly researched field of several sciences, in the marketing literature Liu (2006) defined it as “informal communication among consumers about products and services”, meanwhile Burton and Khammash (2010) further specified it: “WOM is any positive or negative statement made by potential, actual or former

consumers about a product or company, which is made available to a multitude of people and of people and institutions via the Internet”. WOM is perceived to be dependable and free from

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14 According to Liu (2006) correctly managed WOM should be considered a low-cost and efficient method of pre-release advertising, furthermore WOM increases visibility and is a low-risk way to create buzz around hype about products or services (Mohr, 2007).

The relationship between WOM valence and sales is often not clear, several studies reports mixed results. Chevalier and Mayzlin (2006) have found that an improvement in valence of book’s review leads to increased sales, however a similar investigation by Chen et al. (2004) found WOM valence is not connected to sales. Elberse and Eliashberg (2003) have found that WOM is a key predictor of movies’ box office revenue. Dellarocas et al (2007) studied the effect of online user reviews of forecasting box office revenues, and they have found that such metrics are significant signals of sales. On the other hand mixed effects in the relationship between WOM and generated revenue has also been found before. Neelamegham and Chintagunta (1999) failed to obtain any significant outcome and Liu’s (2006) results showed that volume and not valence of WOM correlates significantly to generated revenue.

2.3 Product Sampling in Case of Experience Goods

Sampling has been described and used as an effective way to introduce new and not ordinary products, changes in products, and support products in their earliest stages of the lifecycle, and generally just to create word-of-mouth (Freedman, 1986; Marks and Kamins, 1988). Also a recent study finds that the increased number of sampling is driven by companies who find this method cheaper and easier than other forms of advertisement (Biswas et al., 2014) and it can be a more effective way of marketing communication as well (McGuiness and Mathew, 1992). Sampling itself is perceived as a credible signal associated with better product quality and lower uncertainty (Hu et al., 2010). Moreover if consumers are offered a product sample the positive reinforcement can support and justify their believes, which may lead to attraction towards the product and can result in improved consumption and purchase intention (Motes and Woodside, 2001; Peter and Nord, 1982).

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15 information and experience (Klein, 1998) which given the products subjective nature it is challenging without samples.

As mentioned before trailers are similar to classical forms of advertisements (Kernan, 2004). Consumers’ exposure to trailers are limited compared to classical advertisement forms, and trailers are often made of upcoming movies and TV programmes. Advertisements’ effect on sales has been well-researched and the significance of the impact is important. Tellis et al. (2003) states that on a short-run, first exposure is the most impactful and advertisement of new products are more effective than old ones. This suggests that consumers exposed to a trailer of a TV show are more likely to be able to evaluate it and to have stronger opinion about the programme.

2.4 Actors Effects in the Entertainment Industry

The impact of stars in the entertainment industry has been analysed before. Research established that stars’ presence in movies has a significant effect on generated revenue (Litman and Khol, 1989; Sochay, 1994), and it also makes a demonstrable difference on market success of that film (Wallace et al., 1993). Scholars also established that demand for motion pictures moves accordingly with the reputation of the star appearing in it (Elberse and Eliashberg, 2003; Elberse, 2007). However Prag and Casavant (1994) only found this effect true in some cases of their samples, furthermore Ravid (1999) found no significant connection between stars and their movies market performance.

Moreover Levin et al. (1997) states that popular actors provide motivations to attend a film with stars significant enough to erase the effect of negative criticism, and that when a film receives positive remarks its need for additional buzz from the star is lower. Basuroy et al. (2003) also find that the presence of famous actors significantly reduces the impact of negative reviews but as near as makes no difference in case of positive ones.

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16 greater recall and awareness for both the advertisement and both for the product (Atkin and Block, 1983). Research also found that celebrity endorsement may affect perceived product quality (Dean, 1999).

2.5 Actors as Brands

Recently scholars have begun to argue that the definition of brand should be broadened to include anything that engages emotional relationships with consumers (Bayley, 2005) furthermore humans can also be perceived as brands (Hirschman, 1987) especially celebrities who, similarly to traditional brands, can be professionally managed since they have additional features and associations (Thomson, 2006). Moreover, prior research has examined stars as high-equity brands that benefit from high awareness and positive image (Levin et al., 1997) Following this logic, stars acting in TV shows can be perceived as brands themselves.

2.6 Brands’ effect on consumption intentions

Following the argumentation of scholars (Bayley, 2005; Hirschman, 1987) mentioned in the previous chapter, famous people and celebrities can be perceived as brands hence it is important to analyse brands effect on quality perceptions and consumption intentions. Researchers have argued that brand name is the most important element of brand awareness (Davis et al., 2008). It is also a well-researched fact that brand awareness and brand choice are highly correlated (e.g. Axelrod, 1968; Haley and Case, 1979). Furthermore brand awareness has an impact on purchase and consumption intention for multiple reasons. Consumers tend to favour brands with superior brand awareness or familiar brands in general (Keller, 1993). Moreover a brand with higher awareness is more recognizable in the category and also more likely to be get into the consideration set (Hoyer and Brown, 1990). Researchers also argued that brand awareness and perceived quality are related. All else being equal the higher the brand awareness, the higher the perceived quality is (Aaker, 1991; Dodds et al., 1991; Grewal et al., 1998).

Adding to the earlier mentioned branding literature, scholars has also established that consumers are often unable to distinguish among different brands when they cannot rely on branding elements (Allison and Uhl, 1964; Hoyer and Brown, 1990).

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17 it was still preferred by a relevant majority of the participants, even after sampling other brands.

3. Conceptual Model

For the further analysis of the thesis’ research topic, a conceptual model was created. The model is shown in Figure 1.

In order to analyse the effect a dependent variable had to be chosen. Purchase Intention is a well-researched notion and a significant relationship between intention and predicted behaviour has been found (Morwitz and Fitzsimons, 2004).

However due to the fact that most of the TV channels are utilising a business model which does not include payment upon consumption, and the newly established online companies and services are following the same way that does not require direct purchase, this has been modified to Consumption Intentions to better facilitate the aim of the research.

The two independent variable which effects will be analysed are the Valence of Reviews about and the Presence of a Trailer of the respective TV show.

Experts have long ago established the influence of both reviews (positive and negative) and general electronic Word of Mouth on sales and consumption dynamics among experience goods including e-books (Amblee and Bui, 2011), books (Chevalier and Mayzlin, 2006) and movies (Basuroy et al. 2003; Duan et al., 2008). In the field of Consumer Engagement Behaviour, valence is also treated as an important element and linked to the financial health of firms (van Doorn et al., 2010). It also has been established that the effect of eWOM is greater in case of experience goods compared to search goods (Park and Lee, 2009). Therefore this relationship is expected to be significant and strong, hence a hypothesis is not created to test this connection.

Regarding the other independent variable, which is the presence of trailers, the influence of samples on customers’ decisions in case of experience goods will be tested. Since samples are perceived as a credible signal of product quality and they generally reduce perceived risk of consumption (Hu et al. 2010) and as they serve as advertisements (Kernan, 2004) which are positively related to products’ market performance on the short run this relationship is expected to be positive (Tellis et al, 2003).

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18 People use several signals judge product quality (Spence, 1973) and they tend to only use the most accessible piece of available information (Feldman and Lynch, 1988). Thus it is expected that actors’ presence reduce the impact of trailers on consumption intentions, since their presence stands out from the available information the most. Additionally it is also expected that actor’s presence reduce the impact of reviews on consumption intentions.

In case of motion pictures scholars have researched the effects of actors on consumer behaviour and market performance (Basuroy et al., 2006; Elberse, 2007; Elberse and Eliashberg, 2003; Levin et al., 1997; Litman 1983; Litman and Khol, 1989; Ravid, 1999, Sochay, 1994). Thus this relationship is expected to be significant and impactful, hence a hypothesis is not created to test this connection.

Figure 1: The Conceptual Model

4. Hypotheses

4.1 The Impact of Trailers

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19 cannot evaluate outcomes of consumption they make efforts to ease up the risks connected to the uncertainty (Berger and Calabrese, 1975). This risk reduction can be achieved through direct and indirect information analysis. Online reviews count as an indirect way of gathering product information and product samples are a direct approach. As mentioned in the literature review part, attitudes formed through direct experience (e.g. samples, product trial) are tighter and more intense than attitudes created through indirect experience (Smith, 1993).

As stated previously experience goods are challenging to evaluate prior consumption (Nelson, 1970). In the online environment when costumers are faced with a new product they rely on quality signals. According to the signalling theory, first proposed by Michael Spence (1973), consumers use available signals to evaluate samples. These signals are not easy to attain, change or manipulate therefore are seen as a reliable piece of information and perceived as a good way of measuring quality. In the online world most notably reviews and samples serve as signals of product quality.

According to the analytical model proposed by Banker and Datar (1989) the relative weight consumers put on these signals are relative to the perceived precision and sensitivity of the signal. Precision measures the lack of noise in the signal while sensitivity means to what extent the signal changes due to an agent’s action. Samples compared to WOM and online reviews are suffer from less noise as they are really hard to be manipulated by the selling or producing companies. Furthermore even if marketers and companies can have some control over online reviews and product ratings consumers may be able to detect these modifications and filter them (Hu et al., 2010).

Thus considering those theoretical backgrounds and in order to analyse the impact of samples on consumption intentions the following hypothesis can be formulated:

H1: The presence of a trailer increases consumers’ intention to watch a TV series.

4.2 The Impact of Celebrities

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20 Consistent with Feldman and Lynch (1988) the probability of a piece of information’s usage as input for choice depends on three factors: the accessibility of the input, the accessibility of alternative inputs and finally the diagnosticity of the inputs. Factors increasing the accessibility of an input, are also increasing the possibility of that input’s role as a judgement criteria and reducing other inputs accessibility.

Olson (1973) argued that people use several cues to judge products quality. These cues can be extrinsic or intrinsic. Extrinsic cues are not connected directly to product performance, such as advertisement or brand name. Meanwhile intrinsic cues are directly related to the product therefore modifying them would change the product itself too, for example nutrition value of a vitamin drink or a storyline of a book or movie.

If intrinsic cues are not sufficient to base decisions on them consumers may turn to extrinsic cues to assume product quality (Zeithaml 1988). One possible extrinsic cue is brand name, which plays a crucial role in customers’ product quality perceptions and can represent information about a product (Richardson et al., 1994). This has been proven by several studies (e.g. Dodds et. al. 1991; Grewal et. al 1998), where support for the positive effect of brand name on customers quality perceptions have been found.

Brand names can also be used to eliminate alternatives as they often serve as enriched qualitative cues which are formed from a variety of associations and beliefs (Aaker, 1991; Keller, 1993).

In the world of entertainment these theories suggest that consumers rely on the most accessible and informative piece of information. In case of the entertainment industry this is the presence of celebrities or famous stars.

Due to this effect famous actors and celebrities can overshadow the impact of samples have on purchase intention.

According to the abovementioned the following hypothesis can be formulated:

H2:The presence of a famous actor decreases the impact of a trailer on consumption intentions of a TV show.

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21 available signals to evaluate products (Spence, 1973), especially in case of the subjective experience goods. These signals are not easy to attain, change or manipulate therefore are seen as a reliable piece of information and perceived as a good way of measuring quality. As the earlier mentioned accessibility-diagnosticity theory (Feldman and Lynch, 1988) states, information is used to judge product quality if it seems the most diagnostic an accessible piece of information. This suggest that stars can serve as a quality signal that is one of the most accessible and diagnosable piece of information for consumers. Their presence can narrow down consumers’ focus which results less attention on indirect information such as reviews. In relation to the uncertainty reduction theory, when consumers have no adequate knowledge of products or cannot estimate outcomes of consumption they make efforts to ease up the risks connected to the uncertainty (Berger and Calabrese, 1975). Famous actors of whom consumers are not only aware of but have previous knowledge of, hence they can connect them to certain level of quality or performance, may serve as a factor which reduces perceived uncertainty regarding product quality.

In addition higher levels of brand awareness and brand familiarity are associated with a well-developed knowledge structure about the brand and its attributes (Alba and Hutchinson, 1987). Consumers are less likely to change their attitudes towards a well-known brand (Hoyer and MacInnis, 1997) which according to scholars’ recent arguments can be a celebrity (Hirschamn 1987), hence either positive or negative WOM is not probable to change significantly the pre-existing evaluations (Sundaram and Webster, 1999). On the other hand, brands with less familiarity are usually associated with less developed brand knowledge structures, therefore their brand evaluations are more likely to change after exposure to any new brand related communications, including electronic word-of-mouth (eWOM). In case of less familiar brands, consumers tend to rely on new brand-related informations when judging the respective brand (Sundaram and Webster, 1999). Therefore the presence of a famous actor can reduce the impact of reviews.

Having in mind the cited theories and the relevant literature and with the aim of analysing the impact of actors’ presence have on valence of reviews the following hypotheses can be formulated:

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5. Methodology and Results

To display the effect of the presence of a sample and the valence of reviews have on people’s consumption intention and to determine whether this effect varies by the presence of a famous actor two studies were conducted. The first was a pre-test to find a combination of a barely known TV show of a really famous actor for the purpose of the main research. The second was an online questionnaire based on the findings of the first investigation.

5.1 Pre-test

In order to conduct the main research, a suitable combination of a TV show and an actor or actress was necessary. Thus a pre-test was run to investigate which actor and show fits best the main test’s goal. The actors had to be internationally known and the show had to be in English to facilitate the international respondent base. For the purpose of getting unbiased answers regarding the consumption intentions a programme with significantly below average awareness and familiarity was necessary to find. Moreover another goal of the pre-test was to find an actor who is familiar and considered as really famous by the majority of the possible respondents, hence to make sure that the manipulation check regarding the actor presence is apparent.

5.1.1 Design of the Pre-Test

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23 Table 1: The TV Shows and Actors of the pre-test

For the purpose of testing reliability Cronbach’s alphas were calculated. The according values range from .905 to .981 which are above the .60 level of acceptance (Malhotra and Birks, 2008), thus the scales represent satisfactory reliability. The used scales with the Cronbach’s alpha scores of the reliability test is provide below in table 2.

Table 2: Scales and Cronbach’s alpha scores of the pre-test

5.1.2 Results of the Pre-test

Table 3: Mean scores of the pre-test

Actor/Actress

TV Show

Amy Poehler Welcome To Sweden

Charlie Sheen Anger Management

Matt LeBlanc Episodes

Matthew McConaughey Woody Harrelson

Matthew Perry Go On

True Detective

Scale Name Authors Items Cronbach's Alpha Mean SD

I am aware of this actor/actress 5.5833 1.67624

I can recognize this actor/actress 5.6667 1.42318 Some characteristics of the actor come to my mind quickly 5.4923 1.78921

I am aware of this TV show 3.2545 2.21933

I can recognize this TV show 3.6818 2.07622

Some characteristics of the characters come to my mind quickly 3.2182 2.00175 If I was planning to watch a TV series of this type, I would choose this one 2.8526 2.03150

I would watch the TV show 3.1789 2.24546

If a friend were looking for a show of this type, I would advise him/her to watch the TV show 2.7368 1.94176

Attitude towards the act of purchase

Berens, Riel and Bruggen (2005) .905 Yoo and Donthu (2000) .981 Awareness Yoo and Donthu (2000) Awareness .912

Mean

SD

Mean

SD

Mean

SD

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24

After the successful reliability analysis the mean scores were calculated. Matthew Perry scored the highest points on awareness (6.3), while Amy Poehler achieved the lowest awareness scores (3.72). Respondents were the most familiar with Woody Harrelson and Matthew McConaughey’s show (4.27) and they were also given the highest watching willingness score (3.79). Keeping in mind the main purpose of the pre-test it became clear that Matthew Perry and his show, Go On, suits best the goals of the main investigation. Due to the lead actor’s above average scores on the awareness scale, his show’s low awareness scores and it has also achieved the second best position on the watching willingness scale (3).

5.2 Design of the main survey

With the purpose of analysing the problem statement “What is the degree of the altering

effect a famous actor’s presence have on the link between valence of reviews and trailer presence on consumption probability in the TV series environment?” a 2 (negative or positive

review) x 2 (trailer presence or absence) x 2 (actor presence or absence) between-subjects set up was established. Due to its simplicity and manageability an online survey was chosen for the main research method. Respondents were to indicate their answers on 5 or 7 point Likert scales. The advantages of this survey method include simplicity and convenience for the participants. The real goal of the research was not shared with respondents to make sure the answers are not biased in any way. Instead subjects were only informed that they are about to provide insights for a master thesis on the field of customer engagement behaviour.

5.2.1 The manipulations of reviews, trailers and actor presence

With the intention of keeping the research as close to a real situation as possible, the IMDB.com website was chosen as a platform for the reviews. The reason behind this selection is that IMDB is the biggest and most visited online database in relation to the world of TV shows. According to the web traffic analysis company Alexa.com, it is among the top 50 most visited sites in the world, which is significantly better than comparable pages such as tvguide.com or boxofficemojo.com (Alexa.com, 2014).

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25 keeping the content of the reviews as close to each other as possible, by only changing the adjectives in the sentences.

Regarding the sample controlling, the official trailer of the TV show was edited accordingly to fit into the scenarios, by either including or leaving out Matthew Perry from the videos. Moreover a timer was embedded before the video to measure how long people watch the videos.

5.2.2 Built up of the main survey

After a short welcoming message, participants had to read the provided review and if they were in a scenario with a trailer they had to watch the video, subsequently they were to mark their opinion about the provided elements. Overall review impression by Goldsmith et al. (2000) was used to measure respondents’ perception of the reviews. Afterwards the trailer perception was assessed on the scale of interest in something just viewed by Bello et al. (1983). To measure the effect on the dependent variable the scale of Berens, Riel and Bruggen (2005) called attitude towards the act of purchase was utilized. To determine the respondents’ perception of the actor Wells’ (1964) emotional quotient scale was adopted.

Respondents were also asked to fill in questions regarding their sociodemographic situation, namely: gender, age, education level, marital status and nationality.

The questionnaire is provided in appendix 3.

5.3 Data collection

The survey was distributed among friends, family members and classmates and one of the Hungarian TV series blogs, sorozatjunkie.hu, was contacted to post the questionnaire’s link on their Facebook page. Participants were randomly assigned to the scenarios by following the provided link. In order to overcome the issue of mistakenly skipped questions, all of them were made mandatory to fill before proceeding further, and the first 30 seconds of the provided video was also compulsory to watch.

5.4 Sample Characteristics

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26 has at least 21 responses and according to Malhotra and Birks (2008) it is not mandatory to have equal number of subjects for each condition. Table 4 highlights the number of participants and the combinations of the tested variables in the scenarios.

Table 4: Overview of the conditions

Table 5: Sociodemographic overview of the sample

As it is presented in table 5, more women (57.4%) than men (42.6%) took part in the research. Two of the most populous age categories are the groups between 19- 25 (42.2%) and 26-30 (35.5%) The highest completed education level was a Bachelor degree (40.8%) followed by a Master degree (29.8%) and a High School diploma (16%). Regarding the marital status it can be retrieved that almost half of the sample size is single (49.3%), respondents in relationship also make a populous group (35%) and luckily none of the subjects is widowed (0%). Although contestants are from 28 different nationalities, most of their country of origin is Hungary (39.7%) and a little bit less than one third of the participants (27.7%) are Bulgarian.

Table 6: Full trailer watching percentage

Scenario Actor Presence Review Valence Trailer Presence Participants

1 Actor Positive Trailer 28

2 Actor Negative Trailer 33

3 No Actor Negative No trailer 37

4 No Actor Positive No trailer 37

5 No Actor Positive Trailer 21

6 No Actor negative Trailer 22

7 Actor Positive No Trailer 21

8 Actor Negative No Trailer 21

Under 18 2.8% High school d. 16% Single 49.3%

19-25 42.2% Bachelor d. 40.8% Relationship 35% HUN 39.7% Male 42.6% 26-30 35.5% Master d. 29.8% Married 7.3% BUL 27.7% Female 57.4% 31-35 11.3% Phd 1.8% Married w. Child 7.7% NED 10.6% 36-40 3.5% Professional d. 6.4% Separated 0.5% Other 22%

Over 40 4.6% Other 5.3% Widowed 0%

Nationality Gender Age Groups Education Marital Status

Actor Video 88.5% No Actor Video 90.7%

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27 As mentioned previously the time respondents spent watching the video was measured. The trailers length are approximately 58 and 73 seconds, the latter includes the scenes with Matthew Perry. Table 6 highlights what percentage of respondents have watched the whole video. 88.5% of the participants in the conditions with actor presence have watched the full video provided in the research. 90.7% of subjects in the no actor scenarios have watched the trailer in the questionnaire.

5.5 Reliability analysis

For the purpose of testing reliability of multi item scales, Cronbach’s alphas were calculated.

Table 7: Overview of the reliability analysis

As table 7 highlights it, Cornbach’s alphas for the scales are ranging from .902 to .970 which are significantly above the 0.60 level of acceptance (Malhotra and Birks, 2008), therefore the scales represent satisfactory reliability. Furthermore correlation tests were run between the items in the respective scales, which found positive and significant correlations. Hence summated scales could be computed in SPSS. Please refer to the appendix 4 for the correlation tables of the scales.

Scale Name Authors Items Cronbach's

Alpha Mean SD

I have the impression that the reviewer is satisfied with the TV show 2.9045 1.62598

The reviewer finds the TV show to be good 2.9227 1.59578

The reviewer has a positive opinion about the show 2.9682 1.60305

The reviewer does not recommend the TV show to tohers 2.9636 1.66855

I believe the trailer was Eyecathcing 3.57 1.519

I believe the trailer was Attention-getting 3.38 1.521

I believe the trailer was Memorable 3.95 1.657

I believe the trailer was Interesting 3.46 1.487

If I was planning to watch a TV series of this type, I would choose this one 4.23 1.481

I would watch the TV show 4.23 1.539

If a friend were looking for a show of this type, I would advise him/her to watch the TV show 4.00 1.485

This actor is very appealing to me 3.7282 0.93089

I would probably skip his work if I saw it on TV 3.9320 0.85477

This actor has little interest for me 3.6796 1.03102

I dislike his work 4.0971 0.76073

This actor makes me feel good 3.6796 0.87687

This is a wonderful actor 3.5534 0.87142

This is the kind of actor you forget easily 3.8447 0.9777

This is a fascinating actor 3.4175 0.84626

I am tired of this kind of actors 3.8252 1.00418

This actor leaves me cold 3.8447 1.10929

Goldsmith et al. (2000) Overall review Impression 0.970 Bello et al. (1983) Interest in something just viewed 0.949 Attitude towards the act of purchase Berens, Riel and Bruggen (2005) 0.902 Emotional

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28

5.6 Main results

The next part of the thesis handles the evaluation of the described hypotheses and research questions. Regression was used to analyse the relationship review valence and the presence of a trailer has on TV show consumption probability, and whether a famous actor’s presence has a significant effect on these realtionships. Regression analysis was chosen as it is a powerful and flexible procedure to investigate whether relationships between the dependent and independent variables exist, and how much variance in the dependent can be explained by the independents (Malhotra and Birks, 2008).

5.6.1 Manipulation check

Before executing the analysis of the research and the hypotheses, the manipulation of the reviews had to be checked. Consequently, independent samples t-test was executed to compare mean scores of the two different review conditions.

Goldsmith et al. (2000) overall review impression scale was used to check for the manipulation. Respondents were to mark their answers on a 5 point scale, where the higher the number the more positive the review’s perception is.

Table 8: Overview of the manipulation check

The independent samples t-test was significant (p=.000). Table 7 highlights that in the scenarios with the positive review subjects judged the text positively (M=4.25, SD=0.87) compared to the negative review scenarios (M=1.70, SD=0.90).

This means that the manipulation of the reviews was achieved, respondents have perceived the positive scenarios as positive and the negative ones as negative. Please refer to appendix 5 for the output table on the t test.

Pariticipants Mean SD Positive conditions 107 4.2523 0.86772

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29

5.6.2 Testing the control variables

In order to test whether the control variables (sociodemographics) have an influence on the dependent variable (consumer’s willingness to watch a TV show) a linear regression was executed where all the according variables were regressed on the dependent variable. In order to run the analysis it was necessary to dummy code the variables. Consequently they were coded into one less variable than the number of their categories where the reference categories. The following dummy variables were made:

Table 9: Dummy variables of the sociodemographics

Variable Name Coding

Male 1=male, 1=female

HUN 1=hungarian, 0=other BLG 1=bulgarian, 0=other

NED 1=dutch, 0=other

High Scool 1=high scool diploma, 0=other Master's 1=Master's degree, 0=other

PHD 1=PhD, 0=other

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30 Before starting the analysis the following regression formula was developed:

Yi= α0 + β1ai + β2b1i + β3b2i + β4b3i + β5c1i + β6c2i + β7c3i + β8c4i + β9c5i + β10d1i + β11d2i +

β12d3i + β13d4i + β14e1i + β15e2i + β16e3i + β17e4i + β18e5i +

ε

i

Y = Customers’ willingness to watch the TV show α0 = Intercept

a = Male

b1 = Hungarian, b2 = Bulgarian, b3 = Dutch

c1 = High School diploma, c2 = Master’s degree, c3 = Phd, c4 = Professional degree, c5 =

Other

d1 = In relationship, d2 = Married, d3 = Married w. Children, d4 = Separated

e1 = Under 18, e2 = Between 26-30, e3 = Between 31-35, e4 = Between 36-40, e5 = Over 40

ε = Error term i = Respondents

Table 10 present the main results of the regression analysis which was run to determinate the relationships between the sociodemogprahic variables (gender, nationality, level of education, marital status and age) and the dependent variable (watching intention).

Table 10: Overview of the control variables regression

Variable B Std. Error p VIF

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31 The regression analysis was not significant R2=.095, F=1.166, p=.293. The variance inflation factor (VIF) levels are not exceeding 2.060, which is lower than the cut off point of 10 (Myers, 1990), hence all VIF scores show low levels of multicollinearity, it should not be an issue. Furthermore as it is highlighted in table 1, the lowest p value is .144, thus none of the dummy variables have significant explanatory power. Therefore none of the sociodemographic variables influence respondents’ willingness to watch the TV series. Please refer to appendix 6 to the exact output tables of the analysis.

5.6.3 Hypothesis testing

This section describes the outcomes of the hypotheses test. For further convenience the hypotheses are reiterated below.

H1: The presence of a trailer increases consumers’ intention to watch a TV series.

H2: The presence of a famous actor decreases the impact of a trailer on consumption intentions of a TV show.

H3a: The presence of a famous actor decreases the impact of negative reviews. H3b: The presence of a famous actor decreases the impact of positive reviews.

In order to analyse the hypotheses it was required to dummy code the variables as there were 2 settings for each variable, positive and negative reviews, actor presence or absence and trailer presence or absence. Consequently the following dummy variables were made:

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32 Before starting the analysis the following regression formula was developed:

Yi = α0 + β1

x

i + β2

y

i + β3

z

i+ β4

x

i *

z

i + β5

y

i *Zi +

ε

i

Y = Customers’ willingness to watch the TV show α0 = Intercept

x = Review valence dummy y = Trailer presence dummy z = Actor presence dummy ε = Error term

i = Respondents

Table 11 presents the main results of the regression analysis which was run to determinate the relationships between the independent variables (review valence, trailer presence) and the dependent variable (watching intention) as well as whether a moderation effect of the actor presence occurs in the relationship.

Table 11: Overview of the results

The regression analysis was significant R2=0.229, F=12.696, p=.00. The variance inflation factor (VIF) levels are not exceeding 3.397, which is lower than the cut off point of 10 (Myers, 1990), hence all VIF scores show low levels of multicollinearity, it should not be an issue. Please refer to appendix 7 for the exact output tables of the regression.

As it can be seen in Table 11 positive review has a significant (p= .000) and positive (B= 1.173) impact on consumer’s willingness to watch the tested TV show. This means that people’s intentions of watching the TV show moves accordingly to the review’s valence they

Variable Beta Std. Error p VIF scores

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33 read. Furthermore table 11 also highlights that actor’s presence has a significant (p= .008) and positive influence on consumer’s willingness to watch the TV show. This means that people’s attention to watch the programme is higher whenever a famous actor takes part in the show.

In H1 it was hypothesized that the presence of a trailer positively influences consumer’s intention to watch a TV series. Table 10 highlights that Trailer Presence has a significant (p= .018) and positive (B= .558) effect on consumer’s willingness to watch the tested TV show. This means whenever consumers sample a TV show by watching its respective trailer their willingness to watch the entire programme is higher compared to people who have not sampled it. This result meets the previous expectations of H1, therefore the hypothesis is supported.

H2 theorized that famous actors decrease the trailers effect on consumption intentions. It can be extracted from table 10 that the interaction effect of Trailer Presence and Actor Presence is marginally significant (p=.097) and has a negative effect (B= -.565) on consumer’s willingness to watch the TV show. This means whenever consumers sample a show of a famous actor they are aware of the joint presence of a trailer and a famous actor decreases each other’s influence. These findings conclude that H2 is supported by the research and therefore it is accepted.

Both hypotheses H3a and H3b theorized a relationship between reviews’ valence and a famous actor’s presence. However contrary to the expectations, the research has failed to show significant results (p=.868). This means that, based on this investigation, both H3a and H3b cannot be supported and have to be discarded.

5.6.4 Further analysis of the relationships

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34 Figure 2: Graphical representation of means 1

H1 hypothesized a positive effect of a trailer on consumer’s watching intentions. As Figure 2 highlights it, the means of watching willingness are in line with this finding, the presence of a trailer increases people’s intention to watch the TV show. This supports the outcome of the regression analysis and H1.

Figure 3: Graphical representation of means 2

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35 same results, therefore the plotted means support the regressions analysis’ outcome and further supports H2.

5.7 Discussion

This thesis aim was to answer the research question: “Whether a famous actor’s presence

influence the impact of review valence and trailer presence on consumption intentions in the TV series environment?” After examining the results in the previous chapter, one can

conclude that actors’ presence does impact the influence of trailers on consumption intentions, by reducing their main effect.

Impact of reviews

The study has supported the results of previous investigations (e.g. Basuroy et al. 2003; Duan et al. 2008) about the influence of review’s valence on consumption intentions. An explanation for this impact is that reviews are important elements in guiding customers’ decisions by reducing the effect of uncertainty (Pavlou 2007). A reason for the relatively big influence of reviews is that in case of experience goods reviews effect is bigger than in case of search goods (Park and Lee, 2009).

Impact of actors

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36 Impact of trailers

This study confirmed the results of previous researches about the impact of samples on consumption intentions. The finding of trailers positive influence on consumers’ willingness to watch a TV show is also in line with the uncertainty reduction theory (Berger and Calabrese, 1975) which states that by exposure to direct information about the show, such as the trailer, the risk respondents associate with the consumption is decreased. Consequently this result supports the findings of Motes and Woodside (2001) and Peter and Nord (1982) who stated that samples are seen as a credible signal associated with better product quality and lower uncertainty which in turn lead to attraction towards the product which results in improved purchase intentions. However the impact of trailers on consumption intentions was relatively small (B= .558). On possible explanation for this reason might be the low scores (M=3.5, SD=1.37, on a 7 point scale) for the trailer’s quality, which might have resulted in an overall smaller impact of the trailer on perceived quality. Since attitudes formed through direct experiences are tight and intense (Smith, 1993) and as samples serve as signals of product quality, therefore a trailer which hasn’t been perceived as an exquisite quality sample, cannot influence consumer’s perceived quality that well.

Impact of celebrities on trailers’ effect

Through the analysis of the impact of trailers on consumptions intentions it has been found that the presence of a famous actor also plays a significant role. It has been discovered that the impact of trailers on consumption intentions decreases by the presence of a star in the TV show. This is in line with the accessibility-diagnosticity theory (Feldman and Lynch, 1988) which states that accessible information is not used as a judgement and choice criteria when a more diagnostic information is available. Since the presence of the famous star is both accessible and highly diagnostic, compared to the trailer, it increased the chance of using it as the main judgemental criteria and reduced the trailer’s accessibility hence its role in the decision making process.

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37 awareness the higher the perceived quality is (Aaker, 1991 Dodds et al., 1991, Grewal et al., 1998).

Impact of celebrities on reviews’ effect

The investigation has failed to show significant results in the relationship between review’s impact and the effect of actors’ presence in a TV show on customers’ consumption intentions. An explanation for this is that reviews are really influential elements in guiding customers’ decision making process (Pavlou, 2007) and their impact in case of experience goods are bigger than in case of search goods (Park and Lee, 2009). Therefore the weight consumers’ associate to valence of reviews is really big, which is contrary to the expectations based on Zeithaml’s (1988) argument about people associating smaller weight to extrinsic cues compared to intrinsic cues. Moreover it could also mean that reviews are perceived as a more credible signal of quality than famous actor are

Another explanation for the not significant relationship is the moderate mean score of Matthew Perry among the respondents (M=3.76, SD=.744), which may have resulted in a smaller impact of actor’s presence both on consumption intentions and on the influence of reviews.

6. Conclusion

6.1 Summary

Due to technological developments customer engagement becomes more and more apparent in this social networking society, and allowed companies to utilize sampling experience goods in the online environment too. Therefore this study sought evidence for user generated reviews and trailers effects and the influence famous actors have on these impacts on consumptions intentions in the world of the entertainment industry. The interest for conducting this investigation emerged from the subjective nature of experience goods and the high level of interconnectedness of customers on social networks.

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38 Secondly the impact of a famous actor’s presence on sample’s influence on consumption intentions was assessed. The findings has supported theoretical and empirical results by showing that a famous actor’s presence decreases the effect of a trailer on consumption intentions.

Lastly, this research attempted to investigate the relationship between review’s valence and actor’s presence on consumers’ willingness to watch a TV series, however the investigation has failed to show significant results in this matter.

6.2 Managerial Implications

The previously elaborated findings have some managerial implications.

Reviews’ valence have shown to be the very impactful in the research, and since the likelihood of negative WOM leading to lower purchase and continuous consumption intention is really high (Gupta and Zeithaml 2006), it is recommendable for marketers and brand managers to try to handle and minimalize the impact of negativism or even make a step further and try to prevent negative WOM. This could be achieved by concentrating on market research and monitoring the main platforms on which the quickly spreading eWOM can appear and have the most influence in a short time. However marketers ought not to discard the option of commenting or allowing users and consumer’s to express their complaints and negative attitude about their brand or product. It allows for marketers to collect feedback from consumers which could be utilized in improving their offerings or in new product developments and the embracement of criticism expresses to both current and future consumers that the company cares about its customers’ opinion.

On the contrary, decision makers should invest in generating positive eWOM about their products and services. Managers could utilize the help of reward systems or create some creative way to motivate users in writing reviews and comments on websites about their products and services in order to maximize the impact.

As it was shown the impact of stars presence positively influenced customers’ watching intentions towards the TV show. This suggest to marketers and managers that they should try to connect their product and services to favourable stars via celebrity endorsements to benefit from this positive effect. In the world of entertainment industry this would mean to persuade stars or celebrities to take part in the productions.

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39 customers to sample or try their product for a limited time period. This would reduce the perceived risk people associate with purchase, and could lead to favourable intentions regarding the product which could lead to enhanced market performance.

Although motion pictures are unique products in the sense that unlike endorsements, celebrities are undividable part of the product, it can be suggested from the results that marketers should narrow down their focus by either concentrating on celebrity endorsements, or focusing on sampling as it has been shown that their joint presence have reduced their efficiency. Furthermore the separate utilization of sampling and celebrities could also result in cost reduction or the allowance of money reallocation for the issue of managing the ever-changing eWOM, which was shown to be very impactful.

6.3 Limitations and Further Research

Despite containing relevant theoretical and managerial implications, the present results have some limitations that should be acknowledged and should be taken into account and considered in future research efforts.

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