Journal of Interactive Advertising, Volume 4, Number 2,
This study proposes a contingency framework on the role of emotions and incentives in affecting banner ads effectiveness. More specifically, how emotional appeals affect banner ad click-through rates in the presence or absence of incentives is explored. Data collected from nearly ten thousand real world banner ads is used to empirically test the moderating effect of ad-induced emotional appeals on the relationship between incentive offerings and banner ad effectiveness. The analysis concludes that providing incentives in banner ads is effective in soliciting click-through. When combined with emotional appeals, we found that positive emotions in banner ads enhance the effectiveness of incentives. However, ads with negative or no emotions seem to work better only when no incentives are offered.
Banner ads are simple advertisements that invite visitors to click them to be exposed to a target web page or web site. Banner ads serve functions of both direct response and image advertising (Li and Bukovac 1999). Also, banner ads are mostly two-dimensional, compared with 3-D advertising that promises more virtual experience and sense of presence (Li, Daugherty, and Biocca 2002).
The effectiveness of banner ads has been a central question ever since advertising on the WORLD WIDE WEB began in 1994 (Briggs and Hollis 1997). Banner ads have not been very effective in attracting respondents (Tuten, Bosnjak, and Bandilla 2000). Response to banner ads is typically measured by counting click-throughs, the process of a visitor clicking a web advertisement (banner) and going to that advertiser’s web site. Click-through rates overall are still low for banner ads and are less than 2% in most cases (Tuten, Bosnjak, and Bandilla 2000).
Most ads, including banner ads, can be classified into two categories based on content: thinking ads and feeling ads (Bagozzi, Gopinath, and Nyer 1999). Thinking ads focus on either factual information such as product attributes, or utilitarian consequences of product usage such as benefits obtained. Feeling ads, on the other hand, concentrate on the emotions consumers experience in using the advertised product (Bagozzi, Gopinath, and Nyer 1999). Emotions are ubiquitous throughout marketing as they influence information processing, mediate responses to persuasive appeals, and measure the effects of marketing stimuli (Bagozzi, Gopinath, and Nyer 1999). Affective responses, such as moods and feelings evoked by an advertisement are found to be antecedents of the attitude toward the ad (Batra and Ray 1986). It is widely accepted that emotions and moods trigger buying responses (Gardner 1985). How and to what extent emotional reactions to ads influence consumer decision-making has attracted attention from a number of researchers in recent years. Geuens and De Pelsmacker (1999) tested emotions and affect intensity on communication effects of different emotional (warm, humorous, and erotic) and non-emotional advertising appeals. They found that affect intensity seems to be mood specific, and the predicted effects of affect intensity seem to occur more in the case of warm and humorous appeals than erotic appeals.
At the same time, both offline and online, businesses are increasingly turning to discounts, free offers, rebates, coupons, and other incentives to attract customers. In prior years, toasters were used as incentives to lure customers to the banks. But over time, incentives to entice new customers have evolved into such things as SUVs filled with cash, trips to Paris, or a chance to walk the green with a golfing great (Dumont 2001).
Banner ads are more passive and less invasive, compared with pop-up ads, which may evoke irritating feelings and ad avoidance because of their intrusiveness (Edwards, Li, and Lee 2002). Animated banner ads draw quicker response and better recall than non-animated ones, and larger banner ads lead to better comprehension and more clicks than small ones (Li and Bukovac 1999).
Given the significance of emotions and incentives in influencing consumer responses, it is imperative that the effects of emotional appeals and incentive offerings on banner ad effectiveness be investigated in order to better understand the determinants that may make online advertising successful. How moods affect cognitive processes underlying ad-evoked attitude change and contingencies that might moderate this relationship is an under-researched area in marketing (Batra and Stayman 1990). This study fills that gap in consumer and advertising research and proposes a contingency framework on the roles of emotions and incentives in affecting banner ad effectiveness. We use data collected from nearly ten thousand real world banner ads and empirically test the moderating effect of ad-induced emotional appeals on the relationship between incentive offerings and banner ads effectiveness. Suggestions for future research in the area and implications for managers are also presented.
Emotions are kinds of mental feelings, which together with moods and attitudes form the umbrella concept of affect (Bagozzi, Gopinath, and Nyer 1999). More specifically, emotion has been defined as a "mental state of readiness that arises from cognitive appraisals of events or thoughts, has a phenomenological tone, often expressed physically, accompanied by physiological processes, and may result in specific actions to affirm or cope with the emotions" (Bagozzi, Gopinath, and Nyer 1999). Holbrook and Batra (1987) called for a broadening of the unidimensional view of affect to encompass the full gamut of emotions, and these emotional reactions include not only liking and disliking, but also love, hate, fear, anger, joy, sadness, and so on.It is somewhat difficult to differentiate between emotion and mood (Bagozzi, Gopinath, and Nyer 1999). But by convention, several criteria could be used to distinguish the two – from their duration, intensity, intention, and action tendencies (see Table 1).
Table 1 Differences between emotion and mood
(based on Bagozzi, Gopinath, and Nyer 1999)
Many scholars in the field argue that emotions are in the final analysis bipolar states or processes, happy or sad, pleasant or unpleasant (Bagozzi, Gopinath, and Nyer 1999). Westbrook (1987) found emotional items to load on two factors: positive affect and negative affect. Not all researchers adopt this dichotomous categorization however. Edell and Burke (1987) identified three factors of emotions: upbeat feelings, negative feelings, and warm feelings. Holbrook and Batra (1987) described three other factors: pleasure, arousal, and domination. While it is not always easy to predict the positive and negative effects (Bagozzi and Moore 1994), experiential emotional responses have been found to be related positively to more positive attitudes toward an ad (Stout and Leckenby 1986).Emotions have been measured in a number of ways, such as evaluative appraisals, subjective feelings, body posture and gestures, facial expressions, physiological responses, action tendencies, and overt actions (Bagozzi, Gopinath, and Nyer 1999). Most marketers have relied on self-reports in measuring emotion (Bagozzi, Gopinath, and Nyer 1999). Izard’s (1977) taxonomy of affective experiences identified ten fundamental affects, such as interest, joy, anger, disgust, contempt, fear, and shame, but these could mostly be categorized under the valence of either positive or negative. The only exception Izard (1977) identified was surprise, which was considered by her as "neutral". Further elaboration on surprise would probably reveal that there might exist two kinds of surprises – positive and negative (good surprises and not good surprises), just like any other kind of emotion. In this study, we considered this dichotomous analysis: "positive emotion" as one of the two factors, and "negative or no emotion" as the other.
The Internet has long been considered a marketplace for bargains. Online incentive programs offer advantages of instant tracking, instant updating, cost reduction in printing and mailing, quick feedback and program modification, and the ability to get the information to participants (James 2000). Incentive offering in the online environment is more cost efficient than its offline counterpart. An outsourcing offline incentive program can cost anywhere from $20,000 to $500,000 where an automated online program starts at only $2000 (James 2000). Increasingly, voucher providers are turning to the Internet to deliver rewards ("Internet is Primed" 2001).For an incentive program to work effectively, it must be perceived as credible, tangible, and valuable (Baird 2001). Six types of incentives are commonly used in marketing practice – merchandise premiums, information premiums, the product itself, price-related incentives (discounts, rebates, or offerings such as free shipping and handling), mystery gifts, and point programs to facilitate repurchase or loyalty (Baird 2001). Banner ads that rely on incentives and other extrinsic cues are based on the assumption that they may be more effective than central cues and web visitors exposed to such ads lack the motivation to respond. Therefore, extrinsic cues may be appropriate tools for persuasion (Tuten, Bosnjak, and Bandilla 2000).
Advertising effectiveness and mediating factors are a central and important topic in advertising research (Bhargava, Donthu, and Caron 1994). It is widely perceived that persuasion does not rest within advertising messages per se, it depends on certain mental processes that an ad recipient invokes (Meyers-Levy and Malaviya 1999). It has been found that argument-based appeals, expert sources and negatively framed messages are more effective in new markets; while emotion-based appeals and positively-framed messages are more effective in old markets (Chandy et al. 2001).Banner ad effectiveness is usually measured with click-through rates. Click-through rate as a measure of advertising response on the web has the advantage that it is a behavioral response and easy to observe, and it indicates an immediate interest in the brand being advertised (Briggs and Hollis 1997). Click-through rates for most banner ads are in the single digits (Mand 1998). When an interactive element is added, the click-through rate is greatly increased and could even be doubled (Mand 1998). Following the widely used practice in banner ad research, click-through rates in this study are calculated by dividing the number of clicks over the total number of exposures (impressions) of each ad. Click-through rates for ads are preferred over the sheer number of clicks because the former takes into consideration the differences in banner ad impression rates due to differences in exposure by the web pages/sites that carry the ads.
Advertising research provides evidence that feelings are elicited by ads (Edell and Burke 1987), and positive moods evoked by ads facilitate brand-attitude change (Batra and Stayman 1990). Both the ad’s characteristics and feeling-based responses, which are more susceptible to change over time, account for variances in attitudes toward the ad (Edell and Burke 1987; Olney, Holbrook, and Batra 1991). Sometimes, emotions spur an individual onto action, and at other times emotions may inhibit or constrain action (Bagozzi, Gopinath, and Nyer 1999).
Empirical evidence shows that feelings matter in assessing the effectiveness of advertising (Edell and Burke 1987). There is an asymmetric effect of mood on memory, i.e., positive memories and mood maintenance are highly interconnected (Bagozzi, Gopinath, and Nyer 1999). As to the rationale of the effect of positive and negative emotions, it is argued that positive affect usually indicates a favorable environment that does not require any action, and negative affective states act as information signaling that the environment poses an uncertainty and may motivate people to engage in systematic processing (Bagozzi, Gopinath, and Nyer 1999). In their experiments investigating the advertising attitude effects of feelings of warmth generated by commercials, Aaker, Stayman, and Hagerty (1986) found that warmth, a volatile feeling, is related positively to liking for an advertisement and purchase intentions. It has been found that people in positive mood/emotion states, compared with those in neutral or negative mood/emotion states, tend to be better at integrating information, finding relationships among stimuli, and at finding creative solutions (Bagozzi, Gopinath, and Nyer 1999). Also, individuals in positive-mood/emotion states have been shown to evaluate stimuli more positively than individuals in neutral- or negative-mood/emotion states (Bagozzi, Gopinath, and Nyer 1999).
Similarly, Wegener, Petty, and Smith (1995) argue that happy (versus sad) moods lead to the processing of more arguments in a message when a "pro-attitudinal or uplifting" position is taken, but lead to less processing when "counter-attitudinal or depression" position is taken. They suggest that when in happy moods, people tend to maintain that mood and thus process less of the counter-attitudinal or depression content in the ad (Wegener, Petty, and Smith 1995). In addition, positive emotions are associated with attainment of goals, and usually lead to a decision to continue with the plan; while negative emotions are a result of problems with on-going plans and failures to achieve certain goals (Bagozzi, Gopinath, and Nyer 1999). Laboratory tests showed that subjects whose brand preferences were influenced by positive affect during ad exposure were more able to feel positive when the brand name was used later as a retrieval cue than subjects without positive affect at exposure (Stayman and Batra 1991).
In a like manner, in an online advertising environment, positive ad-induced emotions are expected to lead to a tendency to evaluate the advertised content more favorably and continue with click-through that may subsequently continue and maintain that positive emotional state. Therefore, we hypothesize that:
H1: Banner ads with positive induced emotions will result in higher click-through rates than ads with negative or no emotions.As indicated earlier, banner ads relying on incentives and other extrinsic cues are based on the assumption that they may be more effective than central cues and web visitors exposed to such ads lack motivation to respond, and therefore, extrinsic cues may be appropriate tools for persuasion (Tuten, Bosnjak, and Bandilla 2000). Incentive offerings have proven effective in offline advertisements and are widely used in sales and promotional activities throughout the world. The ease of obtaining offered products, samples, or services in an online environment (with a few mouse clicks and the filling of correspondence information) should make it even more attractive to online consumers. Therefore, click-through rates for banners with incentives should be higher than those without incentive offerings:H2: Banner ads with incentive offerings will result in higher click-through rates than ads without incentive offerings.
Batra and Stephens (1994) explored the moderating role of motivation in shaping the attitudinal effects of ad-evoked moods and emotions on brand attitudes. Emotions have been found to serve as moderators in their impact on attitudes toward the brand (Ab) (Bagozzi, Gopinath, and Nyer 1999). Batra and Stayman (1990) found that positive moods moderate the relationship between cognitive processes and attitudes toward the brand in print ads. They also found that mood and motivation interact to affect attitudes toward ads when consumers watch television ads and further argue that this is because positive mood and low motivation suppress counter-argumentation. Additionally, interaction of emotions sometimes occurs with other variables such as motivational or ability factors (Bagozzi, Gopinath, and Nyer 1999).
Coping with a potentially emotion-laden choice trade-off is one factor influencing consumer choice strategies; avoiding or otherwise coping with negative emotion is an important goal that guides decision behavior (Luce, Payne, and Bettman 1999). People in a positive-mood state tend to believe that systematic processing of a message would help maintain their mood, and therefore may engage in more detailed processing (Bagozzi, Gopinath, and Nyer 1999). Consequently, people are more likely to pay attention, appreciate, and commit actions to take advantage of incentive offerings presented in banner ads under positive emotional states. Thus, click-through rates are expected to be higher when incentive offerings are present in banner ads, especially when people are under positive ad-induced emotions:H3: Banner ads with positive induced emotions will result in higher click-through rates than ads with negative or no emotions, especially in the presence of incentive offerings.In order to conceptualize the overall connections, Figure 1 depicts the relationship between the variables.
Figure 1. Hypothesized relationship between incentives,
emotional appeals, and effectiveness
The empirical study was conducted at the individual banner ad level. The banner ads used for this study came from the inventory of actual banner ads that were produced and broadcast over the Internet by an Internet ad agency in the United States. A systems administrator, who was not aware of the research project, randomly assigned 10,000 ads from the inventory into a secured server for our data collection panel to code. The banner ads represented a wide variety of products and services. Five independent judges remotely coded these ads. The judges were marketing doctoral candidates who completed a joint training session where they were familiarized with the coding scheme. An online coding tool was developed and each coder had a unique password to the web site where the banners could be viewed and coded.
To ascertain inter-judge reliability, all judges coded a sub-sample of 100 randomly selected ads. For all independent variables, we estimated the inter-judge reliability coefficient using Rust and Cooil’s (1994) proportional reduction in loss (PRL) reliability measure, which can be evaluated using the same criteria as evaluating Cronbach’s alpha — i.e., 0.70 is acceptable, 0.90 is desirable. All reliabilities were high and in the desirable range (mean = 0.94).
The actual click-through rate (CTR) for each banner ad was provided by the online advertising firm, however not all ads had click data. Those ads without click data were eliminated from the data.
We measured incentives by evaluating the banner ads for the presence or absence of incentives to click. The literature has conceptualized emotion in different ways (Batra and Ray 1986; Chandy et al. 2001), either treating each emotion as a construct itself, or treating all emotions as a scale from negative through neutral to positive (Bagozzi and Moore 1994). In this research, we followed the latter route. We assessed banner ads’ use of emotional appeals by capturing a range of positive and negative emotions. Some ads used no emotional appeal at all. Since less than one percent of the ads used negative emotions, we defined emotion as a binary variable to capture the use of positive emotions and negative or no emotions.
Analysis of variance (ANOVA) was used to test the moderating effect of ad context. The results of this analysis are discussed in the following section.
Of the 10,000 banner ads coded, 8,098 had data on all the independent variables and the dependent variable (click-through rates) and were used in the analysis.
Both emotional appeals and incentive offerings were binary coded ("1" for positive emotion and presence of incentives and "0" for negative or no emotion and absence of incentives). Incentives offered included free offers and discounts explicitly presented in the banner ad itself. Of the 8,098 banner ads used in this study, 1,893 of them offered some kind of incentive, while 6,205 of them offered no incentives; 1,167 of them had positive induced emotions, and 6,931 of them had negative or no induced emotions. Click-through rates (CTR, or click percentage) were calculated by dividing the number of clicks over the total number of exposures (impressions) for each ad.
Examples of banner ads with each type of emotional appeal and the presence or absence of incentives are given in the Appendix. The first example represents an ad with no emotional appeal and no incentive offering. Example 2 represents an ad with a negative emotional appeal (fear appeal) and no incentive offering. Example 3 is an ad with positive emotional appeal and no incentive offering. Finally, example 4 is one with an incentive offering but no emotional appeal.
There are many advantages to using real world banner ads as the data source in this study. First, the click-through rates represent real actions of consumers toward the ads and not just intentions, as is the case in most lab experimental settings. Second, the incentive offerings and emotion-inducements are designed and used by practitioners/advertisers that reflect true competitive forces that influence online business today. Thirdly, the large sample size enabled the researchers to have adequate quantity of ads of different incentive-emotion categories for use in the analysis.
ANOVA was used to test for between-subjects main effects of emotions and incentives on banner ad effectiveness (click-through rates) as well as the interaction between the two (see Table 2).
Table 2 ANOVA – Between Subjects Effects Tests (N=8,098)
The main effect of ad-induced emotional appeals on click-through rates is significant (F=2.85) at the 0.1 level, marginally supporting H1. The main effect of incentives on click-through rates was significant (F=9.85), strongly supporting H2 which implied that banners ads with incentive offerings have mean click-through rates significantly higher than banner ads without incentives. The interaction between incentive offerings and emotional states is significant (F=6.70), strongly supporting H3. Figure 2 graphically illustrates this result.
Figure 2 Interaction of emotion and incentive on click-through rates
Banner ads with incentive offerings and positive emotional appeals have a mean click-through rate of 2.89%, whereas banner ads with no incentive offerings and positive emotional appeals have a mean click-through rate of 1.01%. On the other hand, ads with negative or no emotional appeal in the presence of incentive offerings averaged a click-through rate of 1.28%, whereas ads with negative or no emotional appeal in the absence of incentive offerings averaged a click-through rate of 2.23%. The next section discusses these results and draws implications for managers and researchers.
Our data supports the commonly held belief and the resulting widely adopted practice that banner ad effectiveness is affected by incentive offerings in the ads. The existence of incentives of any kind, be it discounts, free offers, free shipping and handling, or free samples, tends to attract more online users to the banner ads and thereafter the company/product web sites. We found that ad-induced emotional states are only marginally significant in affecting click-through rates by themselves. In general, ads with positive emotional appeals are slightly better in attracting consumers than ads with negative or no emotional appeals. This result seems to be in line with some previous research in that, under some conditions, attitude towards ad (Aad) does not totally mediate the effect of feeling responses, especially at relatively low levels of exposure (Stayman and Aaker 1988). This could be particularly true in the case of banner ads where exposure levels are relatively low.
However, what this study contributes the most to our understanding of online advertising is the finding that the effect of incentive offerings on click-through rates is moderated by emotional appeals in the ads. Even though emotional appeals alone may not have a very significant impact on banner ads effectiveness, they may make a difference when used in conjunction with incentive programs. When incentives are present, positive emotional appeals are more effective in generating click-through than negative or no emotional appeal ads. For managerial considerations, positive emotional appeals are effective only when there are incentives. Consumers seem to perceive, appreciate, and respond to banner ads more enthusiastically when they are in a positive mood that is evoked by the ad and when they can benefit from the incentive offerings at the same time. To put it simply, this suggests to the managers that if you are going to give your customers something for free, better do it while making them happy.
On the other hand, negative or no emotional appeals are more effective than positive appeals when there are no incentive offerings. When incentives are present, negative or no emotional appeals are not as effective as positive appeals. The use of fear tactics such as those used in insurance ads or no emotional appeals are likely to be effective when they are not used concurrently with incentive offerings. This seems to suggest to managers that induced negative feelings (such as fear) or neutral feelings are not very compatible with more positive feeling inducing incentive offerings and the two should not be used concurrently in the same ads. This may imply that if you are not offering your customers anything free of charge, then, and only then use scare tactics or neutral ads.
There are limitations to this study. It has been found that good and bad feelings are nearly independent of each other, i.e., an ad may generate both positive and negative feelings at the same time, and that consumers may be aware of and able to articulate both (Edell and Burke 1987). In our study, even though we excluded banner ads with multiple emotional appeals (less than 0.3 percent of the ads), we had no control to ensure that, in other ads, one and only one emotional state was evoked. In addition, click-through rate is used as a measure of banner ad effectiveness in this study, and this measure may not be totally appropriate for advertisements that do not evoke immediate behavior response.
Researchers studying mood effects have generally used mood manipulations to induce a "positive" or "negative" affective state in experimental subjects (Hill and Ward 1989). But these mood manipulations may influence more than the subjects’ moods and thus confound studies, that is, efforts to put consumers into good moods could have other effects that help or hinder selling efforts (Hill and Ward 1989). While we did not manipulate mood states in this study, we have no assurance of ruling out confounding inducements in the ads.
Tuten, Bosnjak, and Bandilla (2000) compared intrinsic-appeal and extrinsic-appeal banner ads in generating click-through and found that those banner ads with intrinsic appeals (i.e. with cues through ad content), generated more click-through than ads with extrinsic appeals (those with cues such as prizes, color, and sound). This indicates that while emotion-inducing mechanisms and incentives are important, the content of the ad itself that brings about intrinsic appeals is probably more important and should not be neglected. Superior content should be used first, and then in combination with other tools, such as emotion inducement and incentive offerings to achieve superior return on advertising investment.
Finally, notice that even though people can experience emotions privately, emotions are most often interpersonal or group-based responses, especially in a marketing context (Bagozzi, Gopinath, and Nyer 1999). This aspect of ad-induced emotions is, certainly, not captured in this study, and is subject to future research in the area. It has to be pointed out that, while feelings appear to be properties of the individual, the judgments of the ad’s characteristics appear to be properties of the ad (Edell and Burke 1987). Therefore, any attempt to associate an individual’s feelings evoked by the ad and subsequent behavior responses needs to proceed very cautiously.
Aaker, David A., Douglas M. Stayman, and Michael R. Hagerty (1986), "Warmth in Advertising: Measurement, Impact, and Sequence Effects," Journal of Consumer Research, 12 (4), 365-381.
Bagozzi, Richard P., Mahesh Gopinath, and Prashanth U. Nyer (1999), "The Role of Emotions in Marketing," Journal of the Academy of Marketing Science, 27 (2), 184-206.
Bagozzi, Richard P. and David J. Moore (1994), "Public Service Advertisements: Emotions and Empathy Guide Prosocial Behavior," Journal of Marketing, 58 (January), 56-70.
Baird, Bill (2001), "Incentives," TM (July), 14.
Batra, Rajeev and Michael L. Ray (1986), "Affective Responses Mediating Acceptance of Advertising," Journal of Consumer Research, 13 (September), 234-248.
Batra, Rajeev and Douglas M. Stayman (1990), "The Role of Mood in Advertising Effectiveness," Journal of Consumer Research, 17, 203-214.
Batra, Rajeev and Debra Stephens (1994), "Attitudinal Effects of Ad-Evoked Moods and Emotions: The Moderating Role of Motivation," Psychology and Marketing, 11, 199-215.
Bhargava, Mukesh, Naveen Donthu, and Rosanne Caron (1994), "Improving the Effectiveness of Outdoor Advertising: Lessons from a Study of 282 Campaigns," Journal of Advertising Research, 34 (2), 46-55.
Briggs, Rex and Nigel Hollis (1997), "Advertising on the Web: Is There Response before Click-Through?" Journal of Advertising Research, March-April, 33-45.
Chandy, Rajesh K., Gerard J. Tellis, Deborah J. Macinnis, and Pattana Thaivanich (2001), "What to Say When: Advertising Appeals in Evolving Markets," Journal of Marketing Research, 38 (November), 399-414.
Dumont, Elinor (2001), "Today’s Version of Toaster Giveaway," ABA Bank Marketing (September), 12-14.
Edell, Julie A. and Marian Chapman Burke (1987), "The Power of Feelings in Understanding Advertising Effects," Journal of Consumer Research, 14 (December), 421-433.
Edwards, Steven M., Hairong Li, and Joo-Hyun Lee (2002), "Forced Exposure and Psychological Reactance: Antecedents and Consequences of the Perceived Intrusiveness of Pop-up Ads," Journal of Advertising, 31 (3), 83-95.
Gardner, Meryl Paula (1985), "Mood States and Consumer Behavior: A Critical Review," Journal of Consumer Research, 12 (December), 281-300.
Geuens, Maggie D. and Patrick De Pelsmacker (1999), "Affect Intensity Revisited: Individual Differences and the Communication Effects of Emotional Stimuli," Psychology and Marketing, 16 (3), 195-209.
Hill, Ronald P. and James C. Ward (1989), "Mood Manipulation in Marketing Research: An Examination of Potential Confounding Effects," Journal of Marketing Research, 26 (February), 97-104.
Holbrook, Morris B. and Rajeev Batra (1987), "Assessing the Role of Emotions as Mediators of Consumer Responses to Advertising," Journal of Consumer Research, 14 (December), 404-420.
"Internet is Primed to Deliver Rewards, Vouchers and Incentives," (2001), Marketing (April), 33-34.
Izard, Carroll E. (1977), Human Emotion, New York: Plenum Press.
James, Dana. (2000), "Incentive Programs Move to Cyberspace," Marketing News, (December 4), 4.
Li, Hairong and Janice L. Bukovac (1999), "Cognitive Impact of Banner Ad Characteristics: An Experimental Study," Journalism & Mass Communication Quarterly, 76 (Summer), 341-353.
Li, Hairong, Terry Daugherty, and Frank Biocca (2002), "Impact of 3-D Advertising on Product Knowledge, Brand Attitude, and Purchase Intention: The Mediating Role of Presence," Journal of Advertising, 31 (3), 43-57.
Luce, Mary Frances, John W. Payne and James R. Bettman (1999), "Emotional Trade-Off Difficulty and Choice," Journal of Marketing Research, 36 (May), 143-159.
Mand, Adrienne (1998), "There’s Gold in Them Banners!" Adweek, 39 (17), 28-29.
Meyers-Levy, Joan and Prashant Malaviya (1999), "Consumers’ Processing of Persuasive Advertisements: An Integrative Framework of Persuasion Theories," Journal of Marketing, 63 (Special Issue), 45-60.
Olney, Thomas J., Morris B. Holbrook, and Rajeev Batra (1991), "Consumer Responses to Advertising: The Effects of Ad Content, Emotions, and Attitude toward the Ad on Viewing Time," Journal of Consumer Research, 17 (March), 440-453.
Rust, Roland T. and Bruce Cooil (1994), "Reliability Measures for Qualitative Data: Theory and Implications," Journal of Marketing Research, 31 (February), 1-14.
Stayman, Douglas M. and David A. Aaker (1988), "Are All the Effects of Ad-Induced Feelings Mediated by Aad?" Journal of Consumer Research, 15 (December), 368-373.
Stayman, Douglas M. and Rajeev Batra (1991), "Encoding and Retrieval of Ad Affect in Memory" Journal of Marketing Research, 28 (May), 232-239.
Stout, Patricia A. and John D. Leckenby (1986), "Measuring Emotional Response to Advertising," Journal of Advertising, 15 (4), 35-43.
Tuten, Tracy L., Michael Bosnjak, and Wolfgang Bandilla (2000), "Banner-Advertised Web Surveys," Marketing Research, Winter 1999/Spring 2000, 17-21.
Wegener, Duane T., Richard E. Petty, and Stephen M. Smith (1995), "Positive Mood Can Increase or Decrease Message Scrutiny: The Hedonic Contingency View of Mood and Message Processing," Journal of Personality and Social Psychology, 69 (1), 5-15.
Westbrook, Robert A. (1987), "Product/Consumption-Based Affective Responses and Postpurchase Processes," Journal of Marketing Research, 24 (August), 258-70.
Ad example 1 (no emotional appeal and no incentive offering)
Ad example 2 (negative emotional appeal and no incentive offering)
Ad example 3 (positive emotional appeal and no incentive offering)
Ad example 4 (incentive offering and no emotional appeal)
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