The impact of context relevance and color on advertising effects
University of Groningen
Faculty of Economics and Business Specialization Marketing Management
Banner Advertising
The impact of context relevance and color on advertising effects
Master in Science of Business Administration
MARIEKE KRAMER
Student number: 1923897 Supervisor: Prof. Dr. J. C. Hoekstra Second supervisor: Dr. J.A. Voerman
Date: 27th March 2012
Stephensonstraat 26 // 9727 GN // Groningen (06) 28 13 67 34
Abstract
Love them or hate them, but banner advertisements are one of the dominant forms of online advertising. Internet advertising grows in importance, as part of the marketing communication mix. The purpose of this study is to identify the impact of context relevance and color of banners on participants emotional response and ultimately on their purchase intention, in an online setting. In this study, an experiment was conducted to test our hypotheses. Data was extracted from the results of an online questionnaire among 186 respondents. The experiment was a 2 (content: relevant/irrelevant) x 2 (color: red/blue) between subjects factorial design. The results indicated that context relevant banners have indeed an effect on the emotional state of the consumers. Those who saw a banner with context relevant that was within the web page, responded more positively than those who saw a content irrelevant banner. Color did not influence the emotional response or the purchase intent. The interaction between context relevance and color did not have an influence on the purchase intention of consumers. Emotional response is positively related to purchase intention.
Acknowledgements
After having finished my bachelor’s degree at the Hanzehogeschool Groningen, I missed a thorough theoretical approach. I believed at that point I was not ready to start my career yet. Therefore, I chose to follow an additional study to fulfill my needs in studying more about marketing. Now, after finishing my master’s program, and having fully enjoyed the student life, it is time for a new challenge, a new chapter; bringing my knowledge into practice.
I am proud of the report that is in front of you, I think that these results are valuable for online marketers, website providers and advertisers. Obviously, this thesis could not have been established without help and support from others. Therefore, I would like to take the opportunity to thank some people. First of all, my first supervisor, Prof. Dr. Janny Hoekstra, that gave me professional guidance, valuable feedback and non-stop encouragement throughout the whole process. I would like to thank her for her wonderful Argentina tea and our little Frisian small talks during our comfortable conversations. In addition, I would like to thank Dr. Liane Voerman for her constructive feedback as well. Furthermore I thank my loved ones for their support during the process of writing my thesis.
Marieke Kramer
Table of content
A
BSTRACT
... 2
A
CKNOWLEDGEMENTS
... 3
1.
I
NTRODUCTION
... 6
1.1 Background... 6 1.2 Problem statement ... 91.3 Academic and managerial contribution ... 9
1.4 Structure of the paper ... 10
2.
T
HEORETICAL FRAMEWORK
...11
2.1 Conceptual model ... 11 2.2 Banner advertisements ... 12 2.2.1 Click-through rate ...13 2.2.2 Advertising avoidance...13 2.3 Context relevance ... 14 2.4 Color ... 15 2.4.1 Characteristics of color ... 152.4.2 Culture differences regarding color ... 16
2.4.3 Effect of colors ... 17
2.4.4 Red versus blue ... 18
2.5 Interaction effects between contextual relevance and color ... 19
2.6 Emotional response ... 19
3.
M
ETHODOLOGY
... 22
3.1 Experimental research design ... 22
4.
R
ESULTS
... 34
4.1 Descriptive statistics ... 34
4.2 Analyisis ... 34
4.3 Regression results ... 35
4.4 Hypothesis evaluation ... 40
5.
C
ONCLUSION AND DISCUSSION
... 42
5.1 Conclusion ... 42
5.2 Limitations ... 43
5.3 Further research ... 43
R
EFERENCES
... 45
A
PPENDICES
... 50
Appendix 1: Online ad spending forecast ... 50
Appendix 2: Online advertising surpasses TV advertising ... 51
Appendix 3: Demographic profile ... 52
1. Introduction
In this chapter the topic of this thesis is introduced. In section 1.1 some background information is given. In section 1.2 the research questions are stated. In section 1.3 the academic and managerial contributions are described and in section 1.4 the structure of the thesis is stated.
1.1 BACKGROUND
The Internet is one of the most important innovations of the twentieth century. Internet usage is growing yearly, both the amount of the use of Internet and the amount of hours spent on the Internet in a certain period (Internet World Stats, 2011), see appendix 1 and 2. By 2000 the Internet became an information and communication medium that was integrated into our everyday lives. In March 2011 one third of the world population used the Internet daily, with a user growth (2000 – 2011) of 480,4%. The Internet has allowed consumers access to a variety of products and gave them freedom to engage in online activities at any chosen time of the day. Consumers are more and more eager to learn how to use the changing technology and their online behavior has responded on this. Online shopping behavior (also called online buying behavior and Internet shopping/buying behavior) refers to the process of purchasing products or services through the Internet (Alba et al., 1997). This type of shopping became popular from the mid-1990s on with the popularization of the World Wide Web (WWW). Buying goods online is nowadays more a habitual thing to do rather than an exception. The curiosity and ability to make use of online services influences how we make decisions in daily life.
intent of consumers. This research is inspired by the research of Zhang and Wedel (2009) in which they identified key factors affecting online (and offline) purchase decision-making processes. In this research, where we focus on banner advertisements, the effect of two factors on emotional response and purchase intention are researched in an online setting. First it is important to find out what affects online consumer’s product choice. Two factors that may have an effect on the consumer’s product choice are the content of a website and the design and structure of a website.
The content of a website is an incredible important element for building and constructing websites because the fundamental goal of a website is to provide information (Stevenson, Bruner, and Kumar, 2000). When consumers are online, they experience the content of a web page, as well as the structure of it. The information can be commercial or noncommercial, depending on the function of the website. Also transaction and entertainment are two features that are part of the content of a website (Huizingh, 2000). To what extent does the consumer think or believe that the content of the website provides valuable additional information? This perception of the contextual relevance of a website is related to the level of involvement of the web visitors. Following the work of Zaichkowsky (1985) involvement is defined as the level of personal relevance that a product or purchase decision has for a consumer. It is stated that that people who are shopping for a product are more highly involved with the information in a banner advertisement for that product, than people who are shopping for anything else. When involvement is low, consumers may not be willing to process deeply. Consequently, these consumers are less likely to make the connection between the brand and their actual self and therefore are less likely to form an emotional attachment. In order to find out whether involvement has an effect on the emotional response of the consumer, this element will be taken into account in this research.
those are great opportunities, because too complex websites are experienced by consumers as more negative than positive (Stanaland and Tan, 2010). It is important to find a balance between complex versus not complex for web users to pursue the goal of having the website. Advertisements may have different goals, sizes and elements. This research focuses on banner advertisements.
Banner advertisements are horizontal, rectangular-shaped graphical elements, usually found at the top of web page (Moore, Stammerjohan and Coulter, 2005). There are generally 480 x 60 pixels in size and because of the acceptance from the consumers of this size, measuring the effectiveness of banner advertising is likely to be of considerable interest to both academics and practitioner. The main goal of banners is to inform users about the existence of particular websites and to persuade customers to visit the advertised sites and eventually increase the purchase intention. Manchanda et al. (2006) researched the effectiveness of banner advertising on Internet purchasing in the healthcare industry. By using a behavioral database that consists of customer purchases at a website along with individual advertising exposure, the authors found that the number of these exposures, websites and pages on which a customer is shown advertising all have a positive effect on repeat purchase probabilities. Jeong and King (2010) also did research on the online advertising environment. They suggest that a contextually relevant banner induced more favorable evaluation and a greater purchase intention towards advertised products than a contextually irrelevant counterpart. Next, a very recent research of Goldfarb and Tucker (2011) concludes that contextually targeted display advertisements are more effective in driving purchase intent. These findings are important to build further on in this research, since we focus on contextual relevance in an online setting.
Design features are one of the most executional variables of an advertisement which is important for the emotional state of the consumer after having seen the ad (Tanner Jr. and Raymond, 2006). It is therefore included in this research. Managers make decisions about which colors may have crucial consequences for the company, product or brand. In addition, color can be persuasive, both positively and negatively.
contributes to growing efforts to understand how consumers shape their emotional response and make purchase intentions.
1.2 PROBLEM STATEMENT
The main objective of this study is to examine the effect of the context relevance of banners together with design features of the banners on the participant’s emotional responses and the eventually subsequent purchase intention in an online setting. In addition, the effects of context relevance of the banner together with the color of the banner on the emotional response and purchase intention of the advertised product in the banner are researched .
During this study the following research questions will be analyzed:
1. To what extent does the context relevance of the banner on a webpage have an impact on the emotional response towards the banner ad?
2. To what extent does the context relevance of the banner on a webpage have an impact on the purchase intention?
3. To what extent does the color of banners have an impact on the emotional response towards the banner ad?
4. To what extent does the color of banners have an impact on the purchase intention? 5. To what extent does the context relevance of banners enhance the effect of emotional response towards the banner ad?
6. To what extent does the context relevance of banners enhance the effect of purchase intention?
1.3 ACADEMIC AND MANAGERIAL CONTRIBUTION
online banners. This research is one of the first in researching the effect of context relevance and design features on emotional response and purchase intention in online advertising, focused on the banner advertisements. Website designers can adjust the structure of their website in order to persuade consumers more than they do now. This study enables us to assess the emotional response of the consumer to a banner ad and show the resulting purchase intent of the consumer.
1.4 STRUCTURE OF THE PAPER
2. Theoretical framework
In this chapter relevant scientific literature is discussed. In section 2.1, the conceptual model is presented. Section 2.2 discusses the effectiveness of banner advertising in general. In section 2.3 we start focusing on the variables that are relevant in this study. Literature about the colors of banners is found in section 2.4. Section 2.5 discusses literature about the interaction between context relevance and color on emotional response and purchase intention, and section 2.6 describes literature about the effect of emotional response on purchase intention.
2.1 CONCEPTUAL MODEL
FIGURE 1: Conceptual model
H2 H1 H5a H6 H5b H3 d H42.2 BANNER ADVERTISEMENTS
Internet advertising, and in particular banner effectiveness, in this relatively new medium, has received considerable attention from academics and practioners (Olney et al., 1991; Chang-Hoan and Cheon, 2004; Nager, 2009). The predominant form of WWW advertising is banner advertisements. These rectangular small advertisements (480 x 60 pixels) vary in appearance (design, animation, sound e.g.), but have a shared basic function: if you click on the banner, a new window will open the advertiser’s website. The goal of placing a banner on the web is an email registration or perhaps a purchase on the company’s website. In this manner, banner advertisements are used to attract prospective customers to a website, offering an automated link to the advertiser (Moore, Stammerjohan and Coulter, 2005).
Whether or not to include a banner on a company’s website is an important consideration, because it involves pros as well as cons (Newman, Stem Jr. and Sprott, 2004). The positive side is generating revenue in a relatively cheap and easy way by placing informative links on the ad. Negative effects are for example an unfavorable association with the brand that is advertised in the banner and incongruity with the website. Despite these negative effects, banner ads may provide advertisers with desirable outcomes, for instance increasing the brand awareness and purchase intention.
In the next part scientific literature about why consumers click on banners is discussed. After that, literature regarding the reasons why consumers avoid advertising, and in particular banners, is discussed.
2.2.1 Click-through rate
In web advertising, the banner advertisement click-through is believed to be the first gate to entering the world of interactivity (Cho, Lee and Tharp, 2001). Accordingly, measuring banner ad click-through rates has already become important both for the advertiser and the website. It is therefore important to investigate why consumers click on a banner. Robinson, Wysocka and Hand (2007) researched the effect of design on click-through rates. They found that animation, action phrase and showing the brand or company logo in banner advertisements were not effective in generating click-through rates. Dahlén (2001) revealed an impact and suggests that banners that do not show a brand, might stimulate curiosity, leading to click-through. Also Baltas (2003) and Chandon, Chotourou and Fortin (2003) confirm these results. Robinson, Wysocka and Hand (2007) also found that, contrary to their expectations, the largest banner advertisements were more effective in generating a higher click-through rate than smaller-sized banners. The latter is consistent with the findings of previous research. Lothia, Donthua and Hershberger (2003) found out that animation in banners decreased the click-through rates for business advertisements, but increased the click-through-rate (CTR) for business-to-consumer (B2C) advertisements. Also the presence of emotion increased the CTR for B2C ads. Therefore emotional response of consumers is taken into account for the current research.
2.2.2 Advertising avoidance
when consumers experienced goal impediment, through hindering consumers to browse web content (by a significant source of noise, which disrupt consumers web page viewing), intrude on their search for desired information. It is therefore important to find a way to advertise, but not intrude the web browsing or search for consumers or web users. In the advertising literature, this reaction is called ‘advertising avoidance’ and has been defined as all the actions that media users employ to reduce exposure to the content of the advertisement (Duff and Faber, 2011). In addition, banner ads failed in engaging consumers in interaction with advertising messages (Chang-Hoan, 2003). This is because consumers encounter considerable information related to brands, for example, when testing samples of products, when sensing advertising and seeing packages of products in their daily life. Once having an experience with the same brand, after having developed a brand scheme, again, the brand scheme that was developed during the first encounter is activated, and the information the consumers processed will set expectations of the brand. If information about a brand (advertising) is in accordance with the consumers’ expectations, the difference between processing new information and the existing brand schema is easier (Machleit, Allen and Madden 1993). For instance, an advertisement with a humorous message in it may be shown on a similar humorous context or in a contrasting context (De Pelsmacker, Geuens and Anckaert, 2002). On the contrary, when the expectations of the brand are not met (for example an ad of a PC is placed in a travel magazine), this may encourage people to pay attention and motivate them to think about it (Dahlén et al., 2008). The impact of the media context on advertising effectiveness has received considerable attention in the literature (Goodstein, 1993; Moore, Stammerjohan and Coulter, 2005; Dahlén et al., 2008). Previous studies have shown that ads which are incongruent with a brand schema, elicit more processing of information than ads which are brand schema congruent.
2.3 CONTENT RELEVANCE
indicated that the participants in the experiment produced more favorable attitudes towards the incongruent advertisement than the congruent condition. Goldfarb and Tucker (2011) researched what influences the effectiveness of online advertising. They found that consumers are willing to tolerate contextually targeted ads more than other ads because they potentially provide information. As mentioned before, providing information for the consumers created schemes, which may have an effect on the attitude towards the ad (and product).
Although previous research is not conclusive, it is expected that when a banner is congruent to a web page, it generates a more positive attitude towards the advertised product and a larger likelihood to purchase the advertised product, than when the banner is not relevant to the website. The following hypotheses are determined.
H₁: A banner ad with a relevant content will result in a more positive emotional response than a banner ad with low context relevance
H₂: A banner ad with a relevant content will result in a higher level of purchase intentions toward the banner ad than a banner ad with high context relevance.
2.4 COLOR
In this section relevant scientific literature about color is discussed. Subsection 2.3.1 describes literature about three characteristics of color: hue, chroma and value. Then the cultural interpretations and cultural differences of color are discussed. Subsection 2.3.3 discusses the effects of color on emotional response and product choice, and subsection 2.3.4 states literature about colors that are used in this research.
2.4.1 Characteristics of color
Color is one of the more striking executional variables under the control of the advertiser. In designing advertisements, a decision must be made about which color to use as a cue in the ad. Perceptually, to be able to analyze color, it is important to explain and understand these characteristics: hue, chroma, and value (Gorn, Chattopadhyay and Darren, 1997). Hue is the normal meaning or pigment of the color, for instance the color red, yellow and blue. Research in the field of psychophysiology found out that warm colors such as reds, oranges, and yellows, may have physiological effects opposite those of cooler colors, such as blues and whites (Chebat and Morrin, 2006). These colors are named as primary colors, also purple and green, among other colors, belong to this attributes. The second attribute, chroma, stands for the amount of light that is adjusted with white in order to be able to observe the perceived color for the consumer. Low chroma is perceived as dull, whereas high chroma colors are perceived as rich and deep. Value indicates the brightness that is used in color. It is the difference between light and dark (roughly perceived as the difference between black and white) that is perceived by the person.
In marketing, color is connected to the response of the consumer, to determine the consumer’s behavior (Gorn et al., 1997; Gorn et al., 2004). This link is measured through two dimensions; both are tied to chroma and value, namely boredom versus excitement and tension versus relaxation. We take the findings of these researches into consideration for choosing the colors for the current research.
2.4.2 Culture differences regarding color
color of wrapping paper, from green to pink (the latter color has a positive meaning in China), sales increased reasonably. This shows that color does play a considerable role in the sales process of products. Jacobs et al. (1991) gave a general advice of their research, stating that marketers need to be aware of all color implications and that the chosen hue may be perceived more negatively by the foreign market. Therefore, standardized marketing (when focusing on the colors of packaging products) may not always be effective. For academics as well as practioners, it is important to understand the meaning of colors for plotting a strategy in a certain country.
For the current research, the average Dutch color associations are taken into account, since the subjects of this research are all people that grew up with other Dutch people, are familiar with the Dutch color associations and use these associations as well in daily life. Color associations of other cultures are not taken into account.
2.4.3 Effect of colors
Gorn et al. (2004) investigated the link between the color of a web page’s background and the perceived quickness of the download of a webpage. Feeling and relaxation mediated this relationship. The authors researched differences in age, focusing on the effect of the perception of color. Gorn et al. (2004) stated that background screen colors may impact the younger generations, since they are more likely to use the Internet for assistance in developing their purchase behaviors.
2.4.4 Red versus blue
When consumers look at the colors red and blue, the physical state changes (Gorn et al. (1997). The authors stated in their research that red and blue are two colors that are least similar when taking into account the three characteristics of color, discussed in section 2.3.1. Chebat and Morrin (2006) referred to the research of Gerard (1957), in which he investigated the effect of color hues on the physical state of a person. Gerard (1957) found that a red light, compared to a blue light, increased blood pressure and the eye-blink frequency. Several studies manipulated the background color in several situations. Bellizzi and Hite (1992) confirm that red-colored backgrounds elicit greater feelings of arousal than blue-colored backgrounds, whereas products presented against blue-colored backgrounds are liked more than products presented against red-colored backgrounds. The attribute hue of color has been included into research, whereas chroma and value are not taken into account in the research.
Middlestadt (1990) concluded that the background color of an advertisement did have an effect on the attitude towards buying the product. Participants of the experiment with a blue condition had a more positive attitude towards buying the product that was advertised, compared with the red condition. The participants believed that blue showed more elegance and uniqueness, which resulted in a cognitive structure.
potency and activity. The color blue was most highly evaluated, whereas red came out most potent. Both red and blue were preferred hues, where blue was more liked than red. Although there are contradictory results from the literature, the following hypotheses are set up for the current research:
H₃: Blue has a more positive effect on the participants’ emotional response towards the ad than red in advertisements
H₄: Blue has a more positive effect on the likelihood to purchase the advertised product than red in advertisements
2.5 INTERACTION EFFECTS BETWEEN CONTEXTUAL RELEVANCE AND
COLOR
In addition to the two main variables, context relevance of the banner and color of the banner, that are hypothesized, also the interaction between context relevance and color of the banner are tested in this research. Moore, Stammerjohan and Coulter (2005) examined this earlier in a similar context. With regard to attitude toward the advertisement, the authors found a significant background color and congruency interaction. Web visitors reacted favorably to the congruent blue ad, as well as to the congruent and incongruent red ads: the incongruent blue ad was viewed least favorably. We add the interaction effect between color and contextual relevance on purchase intention in this research, in addition to the effect of the interaction on emotional response. Based on the literature, the following hypotheses are set up.
H₅a: Context relevance enhances the effect of color on emotional response. H₅b: Context relevance enhances the effect of color on purchase intention.
2.6 EMOTIONAL RESPONSE
Belch, 1986; Stevenson, Bruner II and Kumar, 2000). The majority of these studies have focused on the study of attitude toward the ad as a causal mediating variable in the process through which advertising influences brand attitudes and purchase intentions. ‘Attitude’ is one of the most frequently used variables in researching advertising effectiveness. It is important to understand how attitudes are formed, since this has an impact on purchase intention (Sicilia, Ruiz and Reynolds, 2006). Interest in the attitude toward the advertisement (Aad) has increased, because advertisers believe that a ‘likable’ ad can create a favorable consumer impression that may result in a long-term competitive advantage (Mitchell, 1986). Likeability is a component often used to measure attitude towards the advertisement (Brown and Stayman, 1992) and it is suggested that likeability influences advertising effectiveness. Thus, attitude towards the adhas been considered an efficient indicator for measuring the effects of advertising.
Olney et al. (1991) researched the effects of ad content, emotions and the attitude towards the ad on viewing time. They found that emotional dimensions, attitudinal components, and viewing behavior, could be moderately well explained by various aspects of advertising content. Sherman et al. (1997) researched the consumer’s emotions as a mediating effect on consumer purchase behavior. They did a field study of a large sample of consumers. The authors investigated the potential influence of the store’s environment on the emotional states of the consumer and how these emotions may affect various aspects of purchase behavior and feelings toward the store. The results of Sherman et al. (1997) indicate that a consumer’s emotions can be a mediating factor in the purchase process. The emotional state (pleasure and arousal) of consumers may be an important determinant of their purchase behavior. Sherman et al. (1997) researched this in an offline shopping environment, in a retail store. It is an important result for this study, in which the emotional response is tested as an effect on purchase intention in the online environment.
towards the interactive digital television, rather than specified on the context or design attributes of the banners shown to the respondents. From the literature it seems that involvement is an element that has been taken into account very carefully during research. Consumer involvement has been shown to influence both the extent to which people process an advertisement and the type of information included Consumers that are high involved are motivated to gain (detailed) information, whereas less involved consumers are likely to apply simple heuristics that are easier to understand (Petty and Cacioppo, 1986).
Nager (2009) researched and compared the difference between advertisements through two different media; through the Internet and the television. Nager found out that the television advertisements helped in changing and maintaining attitudes towards the advertised products and services better than the advertisements through the web. However, the web is an efficient medium for conveying information. These findings are consistent with the research of Stevenson et al. (2000). Nager also implied that traditional media can be transferred to the dynamic environment of the web as well, which offers more opportunities for marketers in the online world. In comparing the relative importance given by users of the web and television, it is important take into account what consumers preference is of one medium of advertising over the other. Compared to traditional media, the Internet is believed to be a more goal and task-oriented medium (Yoo, 2009). Therefore, nowadays, research on the Internet could produce a better result and implications for further research than research in traditional media.
Morris et al. (2002) found as well that the emotional response of a consumer is a powerful predictor of behavioral intention. They measured emotional response by SAM pleasure, arousal and dominance, and had a stronger relationship to affective attitude than information-seeking variables knowledge and belief toward cognitive attitude. The effect of emotional response on the purchase intention of a product has been researched (Song and Zahedi, 2005), yet research lacks these findings in the online environment.
3. Methodology
To test the hypotheses, data are collected through an online survey. This chapter gives an overview of the research method used in this study; Section 3.1 outlines the choice of research and the type of experimental design. Section 3.2 describes how data is collected. Section 3.3 describes discusses the measurements of all variables which have been used. Section 3.4 states the plan of analysis, which includes a reliability analysis, manipulation check and an explanation of the relevant tests.
3.1 EXPERIMENTAL RESEARCH DESIGN
To be able to research two characteristics of banners, context relevance and color, we set up an experiment. This experiment employed a 2 x 2 design. The experiment is between-subjects, which are as follows: (1) context relevance of the banner (context relevance versus context irrelevance), and (2) color of the banner (red versus blue).
Figure 2: Smulweb design
The hue colors that were chosen for this research are red and blue. Red and blue are the least similar when taking into account the three characteristics of color, hue, chroma and value (Chebat and Morrin, 2006). Table 1 gives an overview of the experimental research design.
TABLE 1: Experimental research design
Context relevant Context irrelevant
Red banner www.smulweb.nl www.metro.nl
Blue banner www.smulweb.nl www.metro.nl
This research design results in the following four conditions: - Red banner and context relevant
- Red banner and context irrelevant - Blue banner and context relevant - Blue banner and context irrelevant
One banner is relevant in the context of the website and the other is irrelevant with the context of the website. The website of Smulweb is chosen, because this website is congruent with the banner. Both the banner and the website are related to cooking, recipes and the kitchen. The website of the (free) newspaper Metro is chosen, since the colors of the website are similar to www.smulweb.nl, but this website is incongruent to the banner ad for this research. By using two websites that show similar colors, bias can be avoided.
3.2 DATA COLLECTION
3.2.1 Pilot study
improvement was made based from the feedback of the subjects that participated in the pre-test. We changed the color of the banner into a brighter color, to mark this design element. Respondents participating in the pretest were excluded from participation in the main research.
3.2.2. Questionnaire
A questionnaire is used as a tool to gain quantitative data. First we ask questions about the main variable context relevance. Second, we find out the emotional response and the purchase intention of the participant. Third, we request to fill in the favorite color, followed by questions about the level of involvement with regard to the subject in the manipulation. Fourth, we examine the internet usage and we close the questionnaire with asking demographic information. Deutskens et al. (2004) researched the effect of the length, and presentation of the questionnaire on the response rate in an online experimental setting. We followed their results by creating a short questionnaire. In addition, we have chosen not to enhance the questionnaire with visual elements, since this seems to have a lower response rate according for Deutskens et al. (2004).
3.2.3 Procedure
answer the questions pertaining to the webpage including ads that followed. After they were asked to carefully look at the webpage, questions were asked about one specific ad, namely the ad about the Thai kitchen. In the end, participants answered some questions related to demographic background. The experiment took the participants around five minutes to complete.
3.2.4 Sample
To measure the effect of context relevance and color on emotional response and purchase intentions we concentrate only on Dutch native speakers. The target population is all people between 18 and 65 years old that are not color blind. For data collection, friends, family, and colleagues are contacted via e-mail to participate in the experiment. We make use of the nonprobability sampling technique where the respondents are selected, because they happen to be in the right place at the right time. This convenience sample is not representative for the population. The snowball system was activated, which asked the respondents to forward the link of the questionnaire to their acquaintances. The sample that filled in the questionnaire consisted of adults only, where both men and women were aged at least 18 years. To create a reliable comparison between the four groups of people, we stated a minimum of forty respondents per group (Malhotra, 2010). According to Malhotra, forty respondents per group is a sufficient number to perform an experiment. In the introduction mail, it is requested that respondents that are color blind are excluded from the research.
3.3 MEASUREMENTS
TABLE 2: Constructs
Constructs Source
Context relevance
How relevant is the product in the banner advertisement to the content of the website?
How appropriate is the product in the banner advertisement to the content of the website?
Miniard et al. (1991)
Emotional response
I experienced:
- Pleasure when seeing the ad on the web page - Enthusiasm when seeing the ad on the web page - Fascination when seeing the ad on the web page - Satisfaction when seeing the ad on the web page - Attraction when seeing the ad on the web page - Amusement when seeing the ad on the web page
Mehrabian and Russell’s (1974)
Purchase intention
It is likely that you will buy the product in the ad. It is probable that you will buy the product in the ad. It is possible that you will buy the product in the ad.
MacKenzie et al. (1986)
Attitude towards the ad
I like the ad
I find the ad positive The advertisement is good The ad gives me a good feeling
Holbrook and Batra (1987) Mitchell and Olson (1981) Gardner (1985) Involvement
In general I have a strong interest in cooking Cooking is very important to me
Cooking means a lot to me
I get bored when other people talk about cooking
Beatty and Talpade (1994)
Internet usage
How often have you used the Internet the last months? How much time do you spend online on an average day? I use the Internet to search for information
I use the Internet to communicate with other people I use the Internet to get free access to information/music I use the Internet to sell products
I use the Internet to consult websites I use the Internet to apply for jobs
Context relevance. The context relevance of a banner (CONR) on the website was measured by using the scales of Miniard, Bhatla et al. (1991). They used a two item seven-point Likert scale, using the following questions: (1) How relevant is the product in the banner advertisement to the content of the website? and (2) How appropriate is the product in the banner advertisement to the content of the website?
Emotional response. We used Mehrabian and Russell’s (1974) twelve-item semantic differential scale (PAD-model) modified for online shopping to measure participants’ emotional response (EM). We included the following question in the questionnaire: To what extent did you experience [emotion] when seeing the advertisement on the web page? Six item pairs were used to measure the arousal dimension of emotions: happy– unhappy, pleased– annoyed, satisfied–unsatisfied, contented–melancholic, hopeful– despairing, and relax–bored. The other six items dealt with the pleasure dimensions: stimulated–relaxed, excited–calm, frenzied–sluggish, jittery–dull, wide awake–sleepy, and aroused–unaroused. The remaining six items represented dominance, but, these showed no important effects and will therefore not be pursued further in the present research. In addition to these measurements, following Holbrook and Batra (1987), attitude towards the advertisement (Aad) was measured by the mean of four seven-point scales anchored by the adjectives: I dislike–like the ad, I react unfavorably–favorably to the ad, I feel negative– positive to the ad, and the ad is bad–good. These scales represent a combination of measures used in previous Aad research as well (Mitchell and Olson, 1981; Gardner, 1985).
1. It is likely that you will buy the product in the ad. 2. It is probable that you will buy the product in the ad. 3. It is possible that you will buy the product in the ad
Control variables. Halfway the questionnaire, we asked what the respondent’s favorite color was. We only stated the colors that were used in the webpage stimuli that they saw already when the favorite color was asked, and included an option ‘other color’ as well. The subjects might be influenced by their favorite color before filling in the questionnaire. Also involvement is tested as a control variable. We followed Beatty, Sharon et al. (1994) when measuring involvement: (1) In general I have a strong interest in cooking/ trying out recipes, (2) Cooking/trying out recipes is very important to me, (3) Cooking/ trying out recipes matters a lot to me, and (4) I get bored when other people talk to me about cooking/trying out recipes.
Moderator. We asked questions about the internet usage of the respondents, to get a clear view of the subjects of the research. To find out the frequency of Internet usage, daily Internet usage and the diversity of Internet usage, we used the questions of Teo and Lim (1999). To be able to measure the diversity of Internet usage, this section contained seven sub questions.
Other variables. We also asked the subjects to indicate their gender, age in years, nationality, and their educational background. The questionnaire can be found in appendix 4.
3.4 PLAN OF ANALYSIS
3.4.1 Reliability analysis
First, to measure the reliability of the scales we performed Cronbach’s analyses. All items were included in this research, because they all had a Cronbach’s Alpha of 0,7 or higher (Nunnally, 1978). All constructs, including the source of the constructs and Cronbach’s alpha can be found in table 3.
TABLE 3: Items, sources and internal consistency
Constructs Source Cronbach’s
Alpha Context relevance Miniard et al. (1991) α = 0,953
Emotional response Mehrabian and Russell’s (1974) α = 0,946 Purchase intention
MacKenzie et al. (1986) α = 0,924
Attitude towards the ad Holbrook and Batra (1987) Mitchell and Olson (1981) Gardner (1985)
α = 0,917
Involvement Beatty and Talpade (1994) α = 0,871
Internet usage Teo and Lim (1999) α = 0,725
3.4.2 Manipulation check
TABLE 5: Means of the manipulation check for EM and PI
Relevance N Mean Standard
deviation T-value P-value Context relevance Context relevant 103 4,5146 1,72419 28,486 ,000 Content irrelevant 83 2,8855 1,49455
3.4.3 Multiple regression
The data will be analyzed using the computer program Statistical Package for the Social Sciences (SPSS) statistics version 18.0. To be able to test the differences in means of emotional response and purchase intention between the levels of both context relevance and color, we performed an ANOVA. In order to test the hypotheses, we performed several multiple regressions. In doing so, we tested if there is a relationship between the main variables (context relevance and color) and emotional response as well as purchase intention. The following equations are estimated, in order to test all effects of the conceptual model, including main effects, control variables, moderators and interaction effects. The six models of emotional response and the four models of purchase intention create a clear overview of the strengths of effects of this research.
Purchase intention
(2.1) (2.2)
(2.3) (2.4)
Explanation of the abbreviations in the formulas: CR= Context relevance
CO = Color of the banner EM = Emotional response I = Involvement FC = Favorite color IU = Internet usage PI = Purchase intention Multicollinearity
Table 4: VIF values
Construct Emotional Response Purchase intention
Context relevance 50,051 10,073
Color 9,528 9,488
Involvement 1,067 1,110
Favorite color 1,011 1,031
Internet usage 18,341 -
Interaction (Int. usage * CR) 42,418 -
Interaction (Color * CR) 2,278 18,285
4. Results
In this chapter the results of the research are presented and analyzed. In section 4.1, the demographic profile of our sample is described. Section 4.2 states the results of the ANOVA. Section 4.3 gives the results of the regressions and section 4.4 evaluates the hypotheses testing.
4.1 DESCRIPTIVE STATISTICS
A total of 190 respondents participated in the research. Four cases were deleted, due to incompleteness of the answers, resulting in 186 respondents that were included for further analysis. A small majority of the sample was female (57%). The subjects have an average age of 33 years (SD= 13,35). Also the average age and distribution of men and women in each group is equally divided (see Table 6). In addition, 98,4% of the sample is Dutch. More demographic characteristics of the sample are given in appendix 3.
TABLE 6: Demographic profile of the sample
Group 1*: N = 53 Group 3*: N = 43
Gender Age Gender Age
Men N = 23 Women N = 29 M = 31,59 SD = 13,03 Men N = 19 Women N = 24 M = 34,42 SD = 14,17 Group 2*: N = 50 Group 4*: N = 40
Gender Age Gender Age
Men N = 23 Women N = 27 M = 33,02 SD = 13,92 Men N = 14 Women N = 26 M = 33,28 SD = 13,49
*1 = Context relevance with red banner *3 = Content irrelevance with red banner *2 = Context relevance with blue banner *4 = Content irrelevance with blue banner
4.2 ANALYSIS
TABLE 7: Descriptive statistics
Purchase intention Emotional response
M SD N M SD N Significant
difference Group 1: Content relevance
with red banner
3,11 1,27 53 4,03 1,23 43 P = 0,650
Group 2: Content relevance with blue banner
3,28 1,41 50 4,15 1,34 40 P = 0,530
Group 3: Content irrelevance with red banner
2,38 1,23 43 3,03 1,40 43 P = 0,286
Group 4: Content irrelevance with blue banner
2,57 1,35 40 3,37 1,37 40 P = 0,506
We performed an ANOVA to determine whether there are significant effects between the four groups. We tested these both on emotional response and purchase intention (see table 8). The ANOVA proved that there are significant differences between the four groups for both emotional response (P = .000) and purchase intention (P = .003).
TABLE 8: ANOVA on emotional response and purchase intention
df F-value P-value
Purchase intention Between groups 3 4,950 0,003
Total 185
Emotional response Between groups 3 7,439 0,000
Total 185
4.3 HYPOTHESIS TESTING
Table 9 shows the results of the two-way ANOVA as shown above. This is tested on the dependent variable emotional response. We first look at the color*relevance interaction as this is the most important result we are after. We see that the p-value is .590, which indicates there is no statistically significant interaction between context relevance and color. There is also no significant difference in color on emotional response (P = .261), but there are significant differences between the context relevance (P = .000).
TABLE 9: Emotional response
Source F-value df P-value
Color 1,269 1 ,261
Relevance 20,650 1 ,000
Color * relevance ,291 1 ,590
Table 10 shows the results of the two-way ANOVA with the dependent variable purchase intention. First we look at the interaction color*context relevance. The result is not significant (P-value = .959). Therefore we conclude that there is no significant interaction between color and context relevance. Furthermore, we look at the independent variables. There is also no significant difference in color on purchase intention (P = .362), but there are significant differences between the context relevance (P = .000).
TABLE 10: Purchase intention
Source F-value df P-value
Color ,834 1 ,362
Relevance 13,963 1 ,000
Color * relevance ,003 1 ,959
TABLE 11: Regression analysis results
TABLE 12: Regression analysis results
Regression results (standardized coefficients) for Purchase intention Hypothesis (effect) Model 2.1 Model 2.2 Model 2.3 Model 2.4 Main variables Context relevance Color Emotional response 2 (+) 4 6 (+) 0,104 -0,027 0,510* 0,106 -0,027 0,501* 0,106 -0,027 0,501* 0,063 -0,069 0,502* Control variables Involvement Favorite color 0,030 0,030 0,001 0,029 0,002 Interaction effect Context relevance*color 5 (-) -0,062 R2 (Adjusted R2) 0,308 (0,296) 0,308 (0,293) 0,308 (0,289) 0,309 (0,285) R2 change F-value 26,946* 0,000 20,174* 0,000 16,051* 0,001 13,314* *= P-value <.01 **=P-value <.05
4.4 HYPOTHESES EVALUTION
TABLE 13: Summary of the results
Hypotheses Result
H₁: A banner ad with a relevant content will result in a more positive emotional response than a banner ad with low context relevance
Supported
H₂: A banner ad with a relevant content will result in a higher level of purchase intentions toward the banner ad than a banner ad with high context relevance.
Not supported
H₃: Blue has a more positive effect on the participants’ emotional response towards the ad than red in advertisements
Not supported H₄: Blue has a more positive effect on the likelihood to purchase the
advertised product than red in advertisements
Not supported H₅a: Context relevance enhances the effect of color on emotional response. Not
supported H₅b: Context relevance enhances the effect of color on purchase intention. Not
5. Conclusion and discussion
In section 5.1 the conclusion of this paper is given. Section 5.2 determines the limitations. Section 5.3 states recommendations for further research.
5.1 CONCLUSION
The main objective of this study was to examine the effect of context relevance of banners together with design attributes of the banners on the participant’s emotional responses and the eventually subsequent purchase intention in an online setting. Data was extracted from the results of an online questionnaire among 186 respondents. This research finds that context relevant banners on web pages have a significant effect on the emotional state of web users. Our results indicate that when banner advertisements are shown on a web page that is relevant to the banner, the emotional state of the consumer is more positive, than when the banner is not relevant to the web page. For context relevance positive coefficients could be seen. Color did nothing for both emotional response and purchase intention. There was no causation shown between color and emotional response based on the current research. This was contrary with the expectations.. In addition to the dependent variable emotional response, a second dependent variable was taken into account in this research, purchase intention. Based on the regression analysis it can be concluded that only the independent variable emotional response was positively related to purchase intention. This conclusion fits perfectly within the supported hypothesis in the previous regression analysis, in which the emotional state of consumers was positively influenced by context relevant banners. Based on these results we can conclude that emotional response positively relates purchase intention of the advertised product in the banner. This result was expected from the theoretical framework (Sherman et al., 1997; Morris et al., 2002).
well experienced with the internet, are more sensitive for context relevant banner advertisements.
The favorite color of the consumers did nothing for the effect of the independent variables on emotional response or purchase intention. Thus, it does not matter whether your favorite color is red, green, or blue, the consumers are not influenced by that when seeing a banner in their favorite color.
For the practioner, the study’s findings have implications for the design of the website. Based on the results of this research, we can conclude and recommend that banners should be placed on websites which are relevant to the content of the banner, in order to stimulate more positive emotional response towards the banner advertisement. Also, because emotional response relates positively to purchase intention, this might stimulate purchase intention in the long run.
5.2 LIMITATIONS
As with any empirical research work, this paper has a number of limitations that present opportunities for future research. Firstly, we rely on stated expressions of purchase intention, and not the actual purchase data. The type of advertising used in this research may have a different effect in real life, where the actual purchases are made. A second limitation of this study is that it examines only one brand (imaginary) with only two different websites and two different colors. The two websites were chosen to prevent bias error, in which two websites with green elements and pictures were created. Future research may focus on extending this study by using other websites in different industries (besides cooking/recipes) and more different colors to weaken this limitation. Also, the data that was collected, consists of Dutch consumers. It is therefore not possible to generalize the results across other countries.
5.3 FURTHER RESEARCH
be placed on web pages that are relevant to the banner in order to stimulate emotional response.
Another recommendation for future research lies in the generalizability of the model. The conceptual model can be made more generalizable through including data from actual data from consumers, or companies. In the same vein, the model can be generalized if it is tested in more than one industry, and add data from more countries than just The Netherlands.
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