The effect of product placement on online purchase intention

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MSc Business Administration: Marketing Track

Master Thesis – Final version

Thesis Supervisor: Dr. Marco Mossinkoff

Student: Gabriele Belluzzi

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Abstract

As the modern technologies allow consumer to access millions of entertainment products,

such as films, TV series and music videos online, with a simple click, marketers get more

interested in the use of Product Placement, to promote brands in less prompting and more

effective way.

The potentiality of this marketing technique is enhanced by the spread and the acceptance of

online shopping worldwide, also for everyday product such as grocery goods.

The purpose of this paper is analyse the relationship between the use of Product Placement

and the Online Purchase Intention, and to shed new light into the marketing literature,

providing insights for marketers and scholars.

Statement of Originality

This document is written by Gabriele Belluzzi, who declares to take full responsibility for the contents of this document.

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

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

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1. Introduction

When in 1982 Reese’s Pieces candy sales increased by 65% after the placement in the movie

“E.T.” by Steven Spielberg, marketers and moviemakers started thinking about the big

opportunity given by this kind of collaboration.

Since then, the investment in product placement for movies and other entertainment sectors

(TV shows, music videos, etc.) grew year after year, and nowadays is considered an ordinary

marketing tool.

Product placement is defined as an advertising technique used by companies to subtly

promote their products through a non-traditional advertising technique, usually through

appearances in film, television, or other media. (Business Dictionary, 2017).

It is considered very effective because unlike traditional ads it appears more natural to the

consumers, which is already absorbed in the plot of the movie he chose to see, and he/she will

be more receptive to the brand communications (Panda, 2004).

The purpose of product placement is to enhance the brand awareness in consumers’ mind, and

to create positive association with the product. For example, after BMW partnership with

James Bond movie “GoldenEye” (1995), while the film was number one at the box office, the

German brand registered $ 240 million in sales for the BMW Z3 Roadster featured in the

movie. The entire 1996 BMW Z3 roadster production run, more than 15,000 roadsters, was

sold out by the time the car was introduced

But people habits are constantly changing, and so its marketing: in fact, in the past few years,

a new phenomenon appeared to open new scenarios: the video-consumption shifted more and

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5 YouTube or Netflix, and a whole world of new possibilities opened to companies, to better

target their marketing efforts.

Nowadays 78.4% of US internet users watch videos online, which led to an increase of the

spending for digital video ads from $7.21bn in 2015 to a $9.15bn forecast for 2017 (Statista,

2016), while TV ad revenue will decline by nearly 3% per year during the same time period.

Video consumption is not the only thing that shifted to the digital world: online shopping

retail sales grew steadily to $370 billion in 2017, up from $231 billion in 2012, and in 2016

about 42% of US internet users purchased online at least once in a month. (Adobe, 2016)

An interesting synergy about these two trends is given by the possibility to watch a

demonstrational video of the item you are willing to purchase: 90% of consumers stated that

this helped them making buying decisions; moreover video ads have an average click-through

rate of 1.84%, the highest rate of all digital ad formats. (Adobe, 2016)

With this research, my goal is to investigate the relationship between the use of product

placement for online videos and the online purchase intention for the product shown.

Understanding the dynamics behind this phenomenon could open new scenarios on the online

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2. Literature Review

2.1 Product Placement

Product placement as marketing technique is becoming more and more relevant for marketers. US product placement revenues raised of 12.8% up to $6.01 billion in 2014, fuelled by the

growing value of television, digital and music integrations, as well as massive DVR use

which allow consumers to skip the traditional advertising spots during television shows (PQ

Media, 2015)

Product Placement is a paid product message aimed at influencing movie (or television)

audiences via the planned and unobtrusive entry of a branded product into a movie (or

television program). (Balasubramian, 1994).

However, this definition can be applied also to any other kind of entertainment products, such

as music videos, novels, videogames, etc.

In general terms, the objective of product placement is to generate positive associations

toward the placed brand, resulting in a positive shift in brand attitude (Cowley, 2008).

Gupta & Lord (1998) established a framework to categorize the different Product-placement

strategies into three modes: (1) visual only (VIS); (2) audio only (AUD); and (3) combined

audio-visual (AV). The first mode (VIS) involves showing a product, logo, billboard or any

other visual brand identifier without naming explicitly the product name (e.g., Brad Pitt

drinking from a can of Pepsi in the movie “World War Z”). The second mode (AUD)

involves the mention of a brand name or a character referring to brand-related messages in

audio form, without showing directly the product, or its identifiers on the screen (e.g., Bryan

Cranston pronouncing “Would you really live in a world without Coca-Cola?” in an episode

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7 of a brand and at the same time an audio mention of the brand name or a brand-relevant

message in audio form (e.g. the characters of the movie “This Is Te End” arguing about who

has the right to eat the last Milky Way snack left).

The study of effectiveness of product placement inside entertainment product is not new:

studies have been made on the success of product placement on TV shows (Russel, 2002), on

movies (Gupta, Lord 1998) and also videogames (Glass 2007).

All these studies show that a relationship exists between the use of product placement and the

consumers’ attitude for the brand.

Two approaches have been used to explain a shift in brand attitude after exposure to a product

placement. In the first approach, exposure to a product placement increases implicit memory

(accessibility) for a brand without necessarily improving explicit memory. In this case, the

consumer misattributes the increase in accessibility for a brand as liking of the brand (Zajonc

1968). Therefore, the consumer will not explicitly remember seeing the brand as a placement,

but will report a more positive brand attitude as a result of the exposure.

In the second approach, exposure to a placement increases explicit memory for a brand.

(Russell, 2002) found both an increase in explicit recognition memory and a positive shift

in brand attitudes after exposure to audio placements that were high in plot connection.

However, this relationship sometimes can be negative, and lead to loss of credibility by the

brand. (Cowley, 2008).

This might happens if the consumer perceives the placement as not it line with the overall

experience of the product, or if the exposure to the brand is too high, overcoming the element

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2.2 Purchase Intentions and Online Shopping behaviour

Purchase intention is defined as a consumer’s willingness to buy a certain product in certain condition.. Purchase intention is a dependent variable that depends on several external and internal factors.

Wood and Scheer (1996), identified that purchase intention is related to the perceived value of

a product or service, which in turn is the results of the combination of the expected benefits

and costs incurred to obtain it. (Figure 1)

Figure 1 - General Model of Perceived Value and Purchase Intention

Mirabi et al. (2015) investigated the factors affecting consumers’ purchase intentions,

demonstrating that both brand name and product quality have a significant impact on it, as

well as product packaging, price and advertising.

Spears and Singh (2004) define Purchase Intention as an individual’s conscious plan to make

an effort to purchase a brand; in their studies they investigate the relationship between the

attitude that consumers have toward the brand, and their purchase intention.

They suggested that Brand attitude and Purchase intentions exist as separate but correlated

dimensions, and they develop measure scales to facilitate comparison and synthesis of finding

across studies.

With the number of online transactions raising year after year worldwide, scholars started

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9 integrate the element of trust into the e-commerce framework, stating that customer trust is a

primary reason for why customers return to an e-vendor.

One of the key features of e-commerce however, seems to be its role of facilitating

information search for consumers, and the width of product range availability, even if the

product category is a significant variable itself (Brown, Pope, Voges, 2003).

Another factor of online shopping which has been researched is related to the opportunity for

marketers to tailor customized advertising messages (Pappas, Kourouthanassis, Giannakos,

Chrissikopoulos, 2015), and the use or interactive tools such as a recommendation agent,

which allows consumers to more efficiently screen the set of alternatives available in the

online shopping environment (Haubl, Trifts, 2000).

2.3 Research question

Having explored the existent literature and spotted a gap which can be filled, the research

question is stated as follows:

What is the relationship between the use of product placement and online purchase intention?

The following sub-question will support answering the main question:

Does the mode of product placement strategy affect this relationship?

2.4 Theoretical relevance

In the last twenty researchers conducted many studies on the use of product placement as a

technique to boost sales; however, to my knowledge, nobody still investigated relationship

between this technique and online purchase intentions.

This kind of analysis could be relevant to understand how consumers’ mind react to this kind

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2.5 Managerial relevance

Considered that online video consumption and online shopping transactions are raising at

incredible speed, having a clear overview of the opportunity given by product placement

could improve the effectiveness of investment by the firms, and allow marketers to pick the

perfect strategy mix to promote their brand.

At the same time, it may improve the quality of the message within the movie, in order to

appear more natural and less obtrusive for the consumers.

2.6 Conceptual Model

With this research, my goal is to measure the impact of the product placement marketing

technique, on purchase intention in an online context.

More precisely, I will use the Gupta & Lord (1998) framework, to evaluate the three modes of

product placement strategies (Visual Only, Audio Only and combined audio-visual), and their

effect on online purchase intention, for the product placed.

H1

H2:

>

H1

AUDIO- VISUAL (AV)

H1

AUDIO ONLY (AUD) VISUAL ONLY

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H1: Product placement has a direct positive relationship on purchase intentions.

H2: Purchase intentions will be higher with the combined audio-visual mode, than with audio

only or visual only modes.

3. Data and Method

This research has an exploratory nature, in order to establish causal relationship between the

independent variable (use of product placement) and the dependent one (Purchase intention).

A survey, administrated through Qualtrics.com, has been used to collect cross-sectional data.

Four different surveys have been administered digitally, one for each of the three modes of

product placement categories, which represent the three levels of independent variable, and

one for the control group.

In the first section the computer randomly assigned the participants to one of the four groups,

and the relative video was shown to the them.

Then, participants were questioned about some general information, like where and how often

do they buy online, and how much time do they spend watching videos or movies online,

followed by some demographic questions. The main purpose of the section, besides collecting

consumer behaviour insights, was to disguise the real aim of the research, and to divert

respondent’s attention between the exposure to the brand and the measurement of purchase

intentions.

In fact, in the third section banner appeared, offering the participant the change to get a

coupon with a 10% to be used on Amazon.com for purchasing a selection of the brand placed

in the video they previously watched to be used within 24 hours: this limitations was intended

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12 Participants could choose between collect the coupon or not, and then the final section of the

survey appeared, asking to participant to evaluate their general attitude toward the brand,

through a bipolar Likert scale made up by 16 items. This items were previously used and

validated by Spears and Singh (2004) with a Cronbach’s Alpha of 0.97.

This section is aimed to measure Brand Attitude, which is a secondary (dependent) variable,

but won’t be part of the conceptual model as it has been already studied in its relationship

with product placement.

A pre-test was performed to a small group of twenty respondent, to gain feedback on the

structure of the survey itself and to obtain insights about audience concerns, beliefs, reactions,

and vocabulary, and small adjustments have been made accordingly.

3.1 Sample and distribution

Data was collected via convenience through the author’s personal social and professional

networks (Facebook, Linkedin) and through the Universiteit van Amsterdam mailing list.

Although nationality of the respondents was irrelevant, a basic knowledge of English was

required, in order to fully understand the questionnaire.

The link to the interview has been active for three weeks, and reached 191 people, even if

only 129 of them completed the whole questionnaire (and has been considered for data

analysis)

3.2 Measures

Each participant is assigned to one of the four groups. The video shown at the beginning of

the questionnaire is different for each group: the first video is a fragment from the movie

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13 second video is a clip from the series “Breaking Bad” and it contains an Audio Placement

(AUD) of the Coca-Cola brand. The third one, is taken from the movie “This Is The End”

and features an Audio-Visual placement of the snack “Milky Way”. The video for the control

group is from the movie “Pulp Fiction” and it doesn’t show any brand.

All the three videos last around one minute, and are in English.

In the third part, respondents’ Purchase Intention was measured, offering the choice of getting

a discount or not (in the control group a Coca-Cola banner was shown).

Their answer has been registered as a dichotomous nominal variable (YES, get the discount =

1; NO, thanks = 0)

Figure 2 - Examples for the banner (mobile and desktop versions)

In the last section of the survey, participants’ attitude towards the brand will be measured,

using an adapted version of a bipolar Likert scale made up by 16 items. These items were

previously used and validated by Spears and Singh (2004) with a Cronbach’s Alpha of 0.97.

The original pool of items consisted of 31 items, but 15 of them has been removed because

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14 A reliability test for the new items has been executed resulting in a new Cronbach’s Alpha of

0.937.

Table 1 Reliability test for the brand attitude items

4. Results

This chapter illustrates the finding of the survey administered through Qualtrics.com

4.1 Descriptive data of sample

The questionnaire has been taken by 191 respondents, but 62 of them did not complete it

resulting in 129 valuable surveys: the gender distribution is almost identical: 62 males (48%)

and 67 females (52%).

The average age of the respondents were almost 25 years (24.91), with the prominent

representation of the so called millennials (aged 18-35), which represent the 95 of the sample.

The overrepresentation of this particular group is a consequence of the self-selective nature of

data collection, and of the distribution channel used for the survey (Facebook and University

mailing list): this is also relevant from a managerial perspective, because this consumer

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15 Table 2 Descriptive data of sample (N=129)

Freq. %

Gender Male 62 48

Female 67 52

Age (in years) M=24.9, SD=6,22, Min 14, Max 56

<18 1 0.8

18-35 123 95.3

>35 5 3.9

For what concerns video consumption, the average time per day that people spent watching

online videos in the last two months was 80 minutes, with a significant variance of 77.

58% of the respondents watches at least one hour of online videos per day.

Table 3 - Time spent watching online videos (on average per day)

> 120' 60'-120' 10'-60' < 10'

TV Series is the most watched category of videos watched (65% of the respondents) followed

by movies (60%) and music videos (45%). Only 29% watches TV programs online.

Regarding online shopping, 87.6 % of the people interviewed completed a purchase in the last

two months, with an average of 5,20 purchases completed.

10%

29% 32%

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16 Amazon is the most used channel (60%) followed by comparable online retailer such as

bol.com and aliexpress.com. 33% of respondent made a purchase from a fashion retailer

platform (zalando, asos, et al) in the last two months.

4.2 Variables and measurement

The core of the questionnaire was whether to collect or not the discount to be used on

Amazon.com within 24 hours.

41 of the total respondents (31.8%) chose to get it.

The computer assigned the respondents randomly, with a self-weighting criteria, to guarantee

an equal distribution within the groups.

When it comes to the analysis of the responses of the different groups, the results are as

follows:

In the three group with a brand placement, the percentage of people who chose to collect the

coupon is 28.6; respectively 27.3% for the VISUAL category, 32.4% for the AUDIO

category, and 25.9% for AUDIO-VISUAL category.

In the control group, where no brands were placed in the video, 45.8% of the respondents

decided to get the discount. (See appendix for the detailed results)

A correlation analysis has been run, using the IBM’s software SPSS, between the dummy

variable measuring Purchase Intentions (1= get the discount; 0= don’t take it), and

dichotomized independent variable resulting from presence of a brand placement in the video

shown (1= presence of placement, 0= no brands placed)

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17 Figure 4 – Correlation analysis between product placement and Purchase Intention

Correlations

Purchase Int. ProdPlace

Purchase Int. Pearson Correlation 1 -.144

Sig. (2-tailed) .103

N 129 129

ProdPlace Pearson Correlation -.144 1

N 129 129

4.3 Secondary variables: Brand Attitude

The last section of the questionnaire asked the participants to evaluate the brand appeared in

the banner.

The results explain the respondent’s general attitude towards the brand, in order to see if there

is a correlation between the latter and the intention to purchase dummy variable from the

results of the previous part of the survey.

A Pearson’s correlation analysis has been executed, using as independent variable the average

of the value assigned to every item of the Likert scale first, and then repeated for every item

alone.

The calculation shows that a slight but significance positive correlation elapses between the

average attitude and the purchase intention:

Figure 5 – Correlation analysis between Purchase Intention and Brand attitude

Correlations

Purchase Int. Attitude

Purchase Int. Pearson Correlation 1 .184*

N 129 120

Attitude Pearson Correlation .184* 1

N 120 120

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18 And between three of the items considered singularly and purchase intention. (See appendix

for further details).

5. Discussion

The aim of this research was to investigate the relationship between the use of product

placement and the purchase intentions in online shopping.

The hypothesis, based on the insight from the existing literature were formulated as follows:

H1 Product placement has a direct positive relationship on purchase intentions. Rejected

H2 Purchase intentions will be higher with the combined audio-visual mode,

than with audio only or visual only modes.

Rejected

The following section will elaborate on the interpretation of the statistical and qualitative

outcomes and compare the results with the literature on which the hypotheses were based.

H1: The results show that there is no significant correlation between the exposition to a brand

in a video and the intention to purchase it in a short term perspective.

Conversely, the findings suggest that people is more willing to accept the discount for the

product when it doesn’t appear in the video, leading to a slight but not significant negative

relationship.

There are several factors which help explaining this phenomenon.

First, when responding to academic surveys, people is not necessary in a shopping mood,

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19 Second, the video clip shown to the respondent was extrapolated by the context of the

movie/series, resulting in a less smooth effect of the placement. People might perceive it as

intrusive, and that could affect their purchase intentions.

Despite the fact that this hypothesis has been rejected, it prove once again that consumers are

becoming more and more resilient to what they consider a traditional advertising message,

and the less invasive it is the more effective it will be.

H2: Also in this case the hypothesis is not supported: the percentage of respondent who chose

to collect the discount after being exposed to the video containing audio-visual product

placement is the lowest compared to the other groups. This might be related to the same

reasons as before, considering that in this case the brand placement was even stronger and

much more intrusive.

There no reason to believe that the presence of a brand instead of another affected the results,

because the consumers’ attitude resulted to be almost identical for every brand:

Brand placed: Coca-Cola Pepsi Milky Way

Average attitude: 4.201 4.220 4.203

However, the results show that there is a positive significant correlation between personal

brand attitude and purchase intention.

That means that people’s decision might be affected by the feeling toward the brand,

regardless the exposition to the video containing the placement, in particular outside a

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5.1 Theoretical implications

This thesis sought to provide new insights to the marketing literature, combining the existing

literature on the use Product placement technique, with the online purchase intentions, in a

way that, to my knowledge, has not been investigated so far.

As explained in the previous sections of the paper, product placement has been explored

many times relatively to its relationship with brand awareness and brand attitude.

Hopefully this paper will contribute to shift the focus of further research on the relationship

between product placement and online shopping behaviour.

5.2 Managerial implications

Although the initial hypothesis has not been confirmed, the results provide useful insights for

marketers, in particular for what concerns the consumers’ reaction to a invasive use of product

placement, proving once again that the strength of this technique is given by the fact that

people is more willing to accept the presence of a brand when is more integrated to the

context and the plot of the video.

6. Conclusions

The aim of this study was to investigate the new marketing opportunities given by linking

product placement to e-commerce, a strategy that in the next future could be relevant for

marketers, thanks to the digitalization of both video consumption and shopping habits.

Unfortunately my hypothesis have not been supported by the findings, but some interesting

insight emerged from the analysis, and new material will contribute to the academic literature

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6.1 Limitations and Further Research

As an individual Master Thesis, this project incurred in some constraints in terms of time and

availability of respondents that could have limited the accountability of the study.

The final sample is composed by 129 valid responses, which is a number large enough to be

statistically relevant, but considering the presence of different sub-groups inside the survey, a

larger size would have been more representative.

Another limitation, as explained in the results section, is due to the fact the in this particular

survey, the video containing the product placement is just a clip extracted from a movie or a

TV series, during more or less one minute. This imply that the viewers were not absorbed in

the plot of the movie/series, which is one of the main strength of the product placement

effectiveness.

Finally, another frequent limitation of a self-conducted survey is linked to the possibility to

incur into common method bias, given by the limited reach of the survey within the author’s

network, or by the unfamiliarity of some respondent with an electronic survey interface.

I tried to reduce these risks by asking people to share the link to the survey, emphasizing the

need for honesty, and guaranteeing participants’ anonymity.

According with this thought, further research, aimed to explore effectiveness of product

placement in an online shopping context, are suggested.

In particular, a replication of a similar study involving the exposition to a full movie/series’

episode, administrated through the main streaming platforms, would lead to more accurate

results.

Moreover, it could be interesting to replicate a similar experiment using a positive brand

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22 the purchase intention, and it could help obtaining more precise data about the real

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7. References

• Aaker, D.A., 2009. Managing brand equity. Simon and Schuster.

• Balasubramanian, S.K. (1994) Beyond Advertising and Publicity: Hybrid Messages and Public Policy Issues. Journal of Advertising, Vol. 23, No. 4 (Dec., 1994), pp. 29- 46

• Brown, M., Pope, N. and Voges, K., 2003. Buying or browsing? An exploration of shopping orientations and online purchase intention. European Journal of

Marketing, 37(11/12), pp.1666-1684.

• Cowley, E.; Barron, C. (2008) When Product Placement Goes Wrong: The Effects of Program Liking and Placement Prominence. Journal of Advertising, Vol. 37, No. 1 pp. 89-98

• Gefen, D., Karahanna, E. and Straub, D.W., 2003. Trust and TAM in online shopping: an integrated model. MIS quarterly, 27(1), pp.51-90.

• Glass, Z. (2007). The effectiveness of product placement in video games. Journal of

Interactive Advertising, Vol. 8, No. 1, pp. 23-32.

• Gupta, P.B.; Lord K.L. (1998) Product Placement in Movies: The Effect of Prominence and Mode on Audience Recall, Journal of Current Issues & Research in

Advertising, Vol 20 No.1, pp. 47-59

• Häubl, G. and Trifts, V., 2000. Consumer decision making in online shopping environments: The effects of interactive decision aids. Marketing science, 19(1), pp.4- 21.

• Heath, T. P. M., & Heath, M. (2008). (Mis) trust in marketing: a reflection on consumers' attitudes and perceptions. Journal of Marketing Management, 24(9-10), 1025-1039.

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24 • Keller, K.L. Conceptualizing, Measuring, and Managing Customer-Based Brand

Equity. Journal of Marketing. Vol. 57, No. 1 (Jan., 1993), pp. 1-22

• Keller, K.L., Parameswaran, M.G. and Jacob, I., 2011. Strategic brand management:

Building, measuring, and managing brand equity. Pearson Education India.

• Mirabi, V., Akbariyeh, H. & Tahmasebifard, H. 2015, "A Study Of Factors Affecting on Customers Purchase Intention", Journal of Multidisciplinary Engineering Science

and Technology (JMEST), vol. 2, no. 1.

• Panda, T.K., 2004. Consumer response to brand placements in films role of brand congruity and modality of presentation in bringing attitudinal change among consumers with special reference to brand placements in Hindi films. South Asian

Journal of Management, 11(4), p.7.

• Pappas, I.O., Kourouthanassis, P.E., Giannakos, M.N. and Chrissikopoulos, V., 2016. Explaining online shopping behavior with fsQCA: The role of cognitive and affective perceptions. Journal of Business Research, 69(2), pp.794-803.

• Percy, L. & Rossiter, J.R. 1992, "A model of brand awareness and brand attitude advertising strategies", Psychology & Marketing, vol. 9, no. 4, pp. 263-274.

• Russell, C.A. (2002) Investigating the Effectiveness of Product Placements in Television Shows: The Role of Modality and Plot Connection Congruence on Brand Memory and Attitude. Journal of Consumer Research. Vol. 29, No. 3 (December 2002), pp. 306-318

• Schimdt, B.H. & Simonson, A. 1997, Marketing aesthetics: the strategic management

of brands, identity, and image, The Free Press, New York, NY.

• Spears, N. and Singh, S.N., 2004. Measuring attitude toward the brand and purchase intentions. Journal of Current Issues & Research in Advertising, 26(2), pp.53-66.

• Till, B.D. & Busler, M. 2000, "The match-up hypothesis: Physical attractiveness, expertise, and the role of fit on brand attitude, purchase intent and brand beliefs", Journal of advertising, vol. 29, no. 3, pp. 1-13

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25 • Wood, C.M. & Scheer, L.K. 1996, "Incorporating perceived risk into models of consumer deal assessment and purchase intent", NA-Advances in Consumer Research

Volume 23, .

• Zajonc, R. (1968), Attitudinal Effects of Mere Exposure, Journal of Personality and

social Psychology Monographs, Vol. 9, No. 2, pp. 1–27

7.1 Online sources

o “15 Mind-Blowing Stats About Digital Video”, Adobe Digital Insights, Retrieved from: http://www.cmo.com/features/articles/2016/1/6/15-mind-blowing-stats-about-digital- video.html#gs.V0ajEmo

o “15 Mind-Blowing Stats About Online Shopping”, Adobe Digital Insights, Retrieved from: http://www.cmo.com/features/articles/2014/5/6/Mind_Blowing_Stats_Online_Shoppi ng.html#gs.6Wx7qqU

o Business Dictionary, Product placement definition. Retrieved from: http://www.businessdictionary.com/definition/product-placement.html

o PQ Media Global Branded Entertainment Marketing Forecast 2015-2019. Retrieved from: http://www.pqmedia.com/gbemf-2015-2019.html

o Purchase intention definition. Retrieved from: http://www.mbaskool.com/business- concepts/marketing-and-strategy-terms/10976-purchase-intention.html

o “Statistics and facts about online video usage”, Statista, Retrieved from: https://www.statista.com/topics/1137/online-video/

7.2 Audio-visual material

All the audio-visual material featured on the Qualtrics’ Survey has an academic purpose only,

the ownership of that material belong exclusively to the original authors.

 Breaking Bad (2008-2013), season 5, episode 7 (2013), television series, Sony

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26  Pulp Fiction (1994), motion picture, Miramax Film Corp, Retrieved: 21/07/1995  This Is The End (2013), motion picture, Sony Pictures Releasing, Retrieved:

12/06/2013

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8. Appendix

8.1 Survey

Part 1 - Introduction

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28 Figure 3 - Screenshot from the movie ‘’World War Z’’

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29 Figure 5 Screenshot from the movie "This Is The End"

Figure 6 - Screenshot from the movie ''Pulp Fiction''

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Part 5 – Brand evaluation

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8.2 Report of the results

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8.3 Data analysis

Correlation analysis between Purchase Intention and exposure to product placement

Correlations

Purchase Int. ProdPlace

Purchase Int. Pearson Correlation 1 -.144

N 129 129

ProdPlace Pearson Correlation -.144 1

Sig. (2-tailed) .103 N 129 129 Descriptive Statistics Mean Std. Deviation N Purchase Int. .3125 .46533 129 Attitude 4.2141 1.18507 120

Likert scale reliability:

Case Processing Summary

N %

Cases Valid 109 84.5

Excludeda 20 15.5

Total 129 100.0

a. Listwise deletion based on all variables in the procedure. Reliability Statistics Cronbach's Alpha Cronbach's Alpha Based on Standardized Items N of Items .937 .935 16 Item Statistics

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38 Mean Std. Deviation N Item1 4.4404 1.64672 109 Item2 4.1193 1.56184 109 item3 4.3578 1.38459 109 item4 4.2202 1.58907 109 item5 4.6147 1.55699 109 item6 4.3211 1.58044 109 item7 4.2385 1.47760 109 item8 4.5780 1.71212 109 item9 3.6606 1.62857 109 item10 4.4587 1.37795 109 item11 4.5138 1.55525 109 item12 4.0917 1.46907 109 item13 4.3211 1.51462 109 item14 4.2752 1.56271 109 item15 4.0000 1.37437 109 item16 4.6422 1.52463 109

Inter-Item Correlation Matrix

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 1 1.00 .69 .74 .76 .82 .68 .53 .47 .33 -.04 .55 .65 .67 .71 .52 .66 2 .69 1.00 .70 .70 .66 .61 .44 .35 .52 -.03 .46 .42 .63 .56 .57 .53 3 .74 .70 1.00 .75 .73 .58 .37 .41 .37 .00 .48 .50 .56 .57 .43 .56 4 .76 .70 .75 1.00 .81 .67 .52 .49 .41 .02 .53 .63 .65 .65 .56 .61 5 .82 .66 .73 .81 1.00 .77 .54 .58 .38 -.09 .55 .65 .78 .74 .55 .73 6 .68 .61 .58 .67 .77 1.00 .51 .45 .42 .00 .50 .53 .72 .67 .51 .60 7 .53 .44 .37 .52 .54 .51 1.00 .55 .23 -.06 .40 .57 .47 .60 .42 .47 8 .47 .35 .41 .49 .58 .45 .55 1.00 .29 .05 .40 .55 .52 .57 .35 .53 9 .33 .52 .37 .41 .38 .42 .23 .29 1.00 .08 .20 .30 .43 .30 .43 .36 10 -.04 -.03 .00 .02 -.09 .00 -.06 .05 .08 1.00 .26 -.12 -.05 -.15 -.19 -.02 11 .55 .46 .48 .53 .55 .50 .40 .40 .20 .26 1.00 .45 .43 .47 .39 .49 12 .65 .42 .50 .63 .65 .53 .57 .55 .30 -.12 .45 1.00 .59 .66 .52 .62 13 .67 .63 .56 .65 .78 .72 .47 .52 .43 -.05 .43 .59 1.00 .76 .61 .68 14 .71 .56 .57 .65 .74 .67 .60 .57 .30 -.15 .47 .66 .76 1.00 .63 .68 15 .52 .57 .43 .56 .55 .51 .42 .35 .43 -.19 .39 .52 .61 .63 1.00 .53 16 .66 .53 .56 .61 .73 .60 .47 .53 .36 -.02 .49 .62 .68 .68 .53 1.00

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39 Item-Total Statistics Scale Mean if Item Deleted Scale Variance if Item Deleted Corrected Item- Total Correlation Squared Multiple Correlation Cronbach's Alpha if Item Deleted Item1 64.4128 262.356 .828 .775 .929 Item2 64.7339 269.234 .733 .694 .931 item3 64.4954 273.863 .730 .686 .931 item4 64.6330 263.957 .828 .765 .929 item5 64.2385 262.535 .877 .861 .927 item6 64.5321 266.659 .776 .673 .930 item7 64.6147 276.924 .612 .507 .934 item8 64.2752 271.961 .608 .497 .934 item9 65.1927 281.398 .461 .394 .938 item10 64.3945 308.667 -.028 .301 .947 item11 64.3394 275.430 .608 .486 .934 item12 64.7615 272.887 .704 .616 .932 item13 64.5321 267.362 .799 .747 .930 item14 64.5780 266.265 .794 .746 .930 item15 64.8532 278.145 .637 .545 .933 item16 64.2110 269.131 .755 .618 .931

Correlation analysis between Brand Attitude and Purchase Intention

Descriptive Statistics Mean Std. Deviation N purchase .3178 .46745 129 attitude 4.2141 1.18507 120 Correlations purchase attitude

purchase Pearson Correlation 1 .184*

N 129 120

attitude Pearson Correlation .184* 1

N 120 120

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The effect of product placement on online purchase intention

Abstract

Statement of Originality

Table of Contents

1. Introduction

2.

Literature Review

2.1 Product Placement

2.2 Purchase Intentions and Online Shopping behaviour

2.3 Research question

2.4 Theoretical relevance

2.5 Managerial relevance

2.6 Conceptual Model

H1

H2:

H1

H1

3. Data and Method

3.1 Sample and distribution

3.2 Measures

4. Results

4.1 Descriptive data of sample

4.2 Variables and measurement

4.3 Secondary variables: Brand Attitude

5. Discussion

5.1 Theoretical implications

5.2 Managerial implications

6. Conclusions

6.1 Limitations and Further Research

7. References

7.1 Online sources

7.2 Audio-visual material

8. Appendix

8.1 Survey

8.2 Report of the results

8.3 Data analysis