d reizen jbem

Paper Submitted for the Journal of Broadcasting and Electronic Media

THE EFFECTIVENESS OF TELESCOPIC ADS DELIVERED VIA INTERACTIVE, DIGITAL

TV: THE IMPACT OF THE AMOUNT OF INFORMATION AND THE LEVEL OF

INTERACTIVITY ON BRAND RESPONSES

Verolien Cauberghe (Corresponding author)

University of Antwerp

Prinsstraat 13

2000 Antwerpen

Belgium

[email protected]

Tel: 0032 - 32755545

Fax: 0032 - 32755081

Patrick De Pelsmacker

University of Antwerp

Prinsstraat 13

2000 Antwerpen

Belgium

[email protected]

Tel: 0032 - 32755046

Fax: 0032 - 32755081

1

mailto:[email protected]

mailto:[email protected]





ABSTRACT

A telescopic ad on Interactive, Digital TV has a more positive influence on brand recall and

attitudes compared with a traditional 30 seconds TV ad. We further examined two aspects of the

complexity of the interactive ad more in depth; the impact of the amount of information and the

level of interactivity. The results demonstrate that the interactivity embedded in the telescopic TV

ad has a strong positive influence on brand recall and attitude, certainly when the amount of

information is low. The time spent in the telescopic ad, which is influenced by both the amount of

additional information and the embedded interactivity, has a positive influence on the development

of brand attitudes, but not on brand recall, and thus is a mediating variable for only some of the

brand responses. *

* This study was accomplished in cooperation with Paratel, VMMa, and InSites.

2





INTRODUCTION

The popularity and adoption of Interactive, digital TV (IDTV) and its related technologies such as

the Personal Video Recorder (PVR) are increasing in many Western countries (Levy & Nebenzahl,

2006), making the medium attractive for advertisers in terms of reach (Ducoffe, Sandler, &

Secunda, 1996). Yet, the medium has received little academic attention until now (Kim and

Sawhney, 2002; Kang, 2002). In a trend analysis of research studies about the Internet, Cho and

Chang (2006) observed a lack of research about the advanced applications of the Internet, such as

IDTV, which can be defined as the merging of the Internet and TV. Although the technology of

IDTV leads to threats for advertisers, e.g. in terms of an increase in ad avoidance behaviour due to

the PVR (Boddy, 2004; Thawani, Gopalan, & Sridhar, 2004), IDTV also offers a lot of new

advertising opportunities. One of the many new interactive TV advertising formats (for an overview

see Cauberghe & De Pelsmacker, 2006) is the Telescopic Advertisement (Reading, et al., 2006).

This format consists of a “30-second TV ad with a call-to-action button with clickable content or

‘micro sites’ featuring individual still screens providing additional information” (Bellman & Varan

2004, p.2). When the viewer clicks on the call-to-action, (s)he leaves the linear broadcast stream to

enter a Dedicated Advertising Location (DAL) where (s)he can navigate through the additional

information, which can be structured in different layers. The interactivity and additional information

are expected to increase the time actively spent in the DAL, and thus enlarge the cognitive

processing of the advertising message and as a result enhance the advertising effectiveness. In this

study we compare the impact of a traditional 30” ad versus a telescopic ad. Since the telescopic

advertisement can be characterized by the additional information and interactivity, we investigate

3


the impact of these two aspects that can have an influence on the complexity of the DAL (Geissler,

Zinkhan, & Watson, 2006). Both aspects, the amount of information and interactivity have been

studies in an internet environment, but the combined effects are rarely investigated in depth. Only a

few studies have tried to keep the amount of information constant when investigating the

effectiveness of interactivity (Martin, Sherrard and Wentzel 2005) or tried to manipulate to amount

of information in combination with interactivity. The first contribution of this study is the

investigation of the impact of a new advertising format, the telescopic ad exposed on a new medium

IDTV, in comparison to a traditional 30” TV ad. The second contribution is related to the

combined effects of the amount of information and the level interactivity in the DAL. Time spent in

the DAL will be investigated as a potential mediating variable.

TELESCOPIC VERSUS TRADITIONAL ADVERTISEMENTS

The merging of TV and the Internet is remarkably noticeable when looking at the appearance of

telescopic advertisements. This new format is promising, given earlier empirical studies that show

that the synergy of a TV ad and the exposure to a website results in better advertising effects than

repetition of the TV ad (Chang & Thorson, 2004). The study of Bellman and Varan (2004)

demonstrated that one exposure to an interactive advertisement with additional information is equal

to the effectiveness of the exposure to three traditional 30” ads in terms of brand recall and attitude,

and behavioural intentions. Also the recent study of Reading et al. (2006) provides evidence of the

positive impact of telescopic advertisements on advertisement and brand attitudes, compared to a

traditional 30” advertisement and a long infomercial. This superior effect of telescopic TV ads can

be explained based on three independent, but interrelated, mechanisms: the message length effect,

the amount of information about the product, and the interactivity embedded in the persuasive

content. The latter two are assumed to have an influence on the time spent in the DAL. Research on

the message length effect has demonstrated that longer ads have more opportunities to provide extra

4


product arguments (Agee & Martin, 2001; Stanton & Burke, 1998) and to repeat key points of the

message. This leads to an increase in attention to the information (MacKenzie, 1986), and thus to a

better message comprehension and information processing (MacInnis & Jaworski, 1989). From the

extensive literature about the advertising effects of the amount of product and consumer

information (e.g., Jacoby, Speller, & Kohn, 1974; Malhotra, 1982), the basic conclusion is that too

much product information leads to an information overload and negatively impacts choice

behaviour, and thus also advertising effects. Later, Keller and Staelin (1987) nuanced these results

and found that an increase in the quality of the additional information, defined as “the information’s

inherent usefulness to consumers” (p.200) could lead to a positive effect on advertising credibility,

and thus to more positive advertising effects. Given that the information in a DAL adds information

of qualitative value compared to the information in the 30” ad, a positive effect of the amount of

information on advertising effects can be expected. As far as the advertising effects of interactivity

are concerned, internet research found that interactivity can increase attention to the persuasive

content, and make it a pleasurable experience, through the development of feelings of flow, “an

intrinsically motivated optimal enjoyable mental state” (Csikszentmihalyi & Lefevre, 1989). This

mental state increases the cognitive involvement with the interactive content (Liu & Shrum, 2002).

The intrinsically motivated joy will be transferred to the persuasive content, leading to positive

advertising outcomes (Chung & Zhao, 2004; Macias, 2003). Given these positive effects of the

additional information and interactivity, in combination with the increase in time exposed to the

persuasive message, the following can be expected:

H1: “An interactive advertisement will lead to higher brand recall, and a more positive brand

attitude than a traditional advertisement.”

5


ADVERTISEMENT COMPLEXITY INDUCED BY THE AMOUNT OF INFORMATION AND

THE LEVEL OF INTERACTIVITY

A challenge of telescopic ads is to keep the consumer’s interest focused on the persuasive message

(Reading et al 2006). To achieve this Putrevu, Tan and Lord (2004) argue that an appropriate level

of complexity is recommended. Early theorization of Berlyne (1958) postulated that individuals,

who are confronted with complex stimuli, will be more aroused, and will try to reduce this arousal

by exploring the source of the complexity, therefore increasing the elaboration. However,

Sanbonmatsu and Kardes (1998) and Shapiro, Park and McInnes (2002) found that too high levels

of physiological arousal reduce the amount of processing capacity available for elaborating on the

persuasive message. From their qualitative research, Geissler, Zinkham and Watson (2006) could

identify 5 important factors that affect the perceptions of the complexity of a homepage. Both the

amount of information (length of the homepage) and interactivity (number of links) were included.

In their subsequent empirical study they found that a moderate level of complexity compared to a

low and high level, facilitated communication effectiveness most optimal. Martin, Sherrard and

Wentzel (2005) investigated the advertising impact of the verbal complexity of a website by

manipulating the amount of information presented on each webpage, keeping the total amount of

information constant. Their results revealed that subjects prefer Web sites of medium level of

complexity, rather than high (little clicks) or low complexity (a lot of clicks). These latter authors

explained their results by referring to the Cognitive Resource Matching Theory, which states that a

balance between the available cognitive resources and required resources to accomplish the task is

necessary for an optimal persuasion (Peracchio & Meyers-Levy, 1997).

6


Amount of Information

The telescopic nature of the interactive advertisement makes it possible to provide extra product

information. In contrast with the choice behaviour research stream, the impact of the amount of

information on the evaluation (instead of choice behaviour) of one single brand (instead of multiple

alternatives) is investigated in this study. In the DAL, the quantity of information is manipulated by

keeping the quality constant. Therefore, referring to the work of Keller and Staelin (1987) and in

line with the Limited Capacity Theory (Lang, 2000) the following can be expected:

H2: “A high amount of information will lead to lower brand recall, and a less positive brand

attitude than a low amount of information.”

Level of Interactivity

Most internet studies find positive advertising effects of interactivity (e.g., Sicilia, Ruiz, & Munera,

2006). Although Geissler, Zinkhan and Watson (2006) found that interactivity (amount of links) can

increase the complexity of a website, a reasonable amount of links should not cause the website to

exceed a moderate level of complexity, which has been found to be to most optimal in terms of

advertising effects (e.g. Martin, Sherrard, & Wentzel, 2005). Therefore, consumers will still have

the ability to focus their attention on the interactive content. This attention is a prerequisite for the

cognitive processing to occur (Lang, 2000). The positive mood evoked by the interactivity, induced

by the experience of flow, may increase the cognitive elaboration of individuals (Lee & Sternthal,

1999). The next can be hypothesized:

H3: “A high level of interactivity will lead to higher brand recall, and a more positive brand

attitude than a low level of interactivity.”

7


The interaction effect of interactivity and information

Despite the positive effect of interactivity, some authors however detected no or even a negative

impact of interactive advertisements (e.g., Bezijan-Avery, Calder, & Iacobucci, 1998; Eveland &

Dunwoody, 2001). The Cognitive Load Theory (CLT, van Merriënboer & Sweller, 2005) can be

used to explain the combined cognitive impact of the amount of information and interactivity

(Eveland & Dunwoody, 2001). The CLT assumes that the human working memory is limited in

processing novel information (Cf. also the Limited Capacity Theory, Lang, 2000). There are

broadly two types of cognitive loads that can affect the working memory (e.g., Bodemer & Faust,

2006): intrinsic cognitive load, which is related to the intrinsic nature of the information, and the

extraneous cognitive load, which corresponds to the mental effort imposed by the way the

information is presented (in this study related to the interactivity). Information processing only

occurs when the respondent is motivated to process the information and when he/she has the

cognitive ability to do so. Depending on the strength of the internal load, the extraneous load can

stimulate the cognitive processing, or can lead to a limited cognitive capacity, and thus inhibit the

information processing due to feelings of disorientation and being lost. Interactive media impose

more cognitive extraneous load than traditional, linear media (e.g., Conklin, 1987). But, on the

other hand, interactivity can increase the involvement with the content (Liu & Shrum, 2002).

According to the ELM (Petty & Cacioppo, 1981) involvement has an influence on the motivation to

process information more intensively, if the individual has the cognitive ability to do so.

Concluding, interactivity demands a certain cognitive load but also influences the motivation to

process the information positively. Referring to the Cognitive Load Theory this leads to the

following reasoning. When the intrinsic cognitive load (the amount of information) is high, the

extraneous load (interactivity) can increase the motivation but also the cognitive load, leading to

less profound processing of the information due to limited cognitive capacity. However, when the

extraneous load is low, the individual may have more ability to process the information, but will be

less motivated to do so. When the intrinsic cognitive load (the amount of information) is low and

8


the extraneous load (interactivity) is high, the individual will have both the motivation and ability to

process the information. When the extraneous load is low, the respondent has the ability to process

information, but will only have a low motivation to do so. The following can be expected:

H4: “In case of a low amount information, a high level of interactivity will lead to higher

brand recall, and a more positive brand attitude than a low level of interactivity. In case of a

high amount of information, a high level of interactivity will lead to lower brand recall, and

a less positive brand attitude than a low level of interactivity.”

TIME SPENT IN THE ADDITIONAL INFORMATION

Research about the effect of advertising exposure length has found that the longer the consumer is

exposed to the stimulus the more (s)he can remember of it (Krugman, Cameron, & White, 1995).

Earlier research also shows that longer advertisements generate more positive advertising results

than their shorter equivalents (e.g., Singh & Cole, 1993; Pieters & Bijmont, 1997). In an internet

context, the time spent and amount of clicks in a website are often used as dependent variables to

measure the effectiveness of website design (Drèze and Zufdreyden 1997). The role of time spent

with a website can be emphasized by the study of Danaher and Mullarkey (2003) who found that

the longer a person is exposed to a web page containing a banner ad, the more likely they remember

that banner advertisement. The following can be expected:

H5: Time spent in the DAL has a positive influence on brand recall and brand attitude.

Morrison and Dainoff (1972) investigated the effect of advertisement complexity on viewing time.

They found that the visual complexity of print ads was positively related with viewing time. Given

9


that both the amount of information and interactivity are assumed to increase the level of

complexity, the following can be expected:

H6: The amount of information and the level of interactivity have a positive effect on the

time spent in the DAL.

However, based on the Cognitive Load Theory, a high intrinsic load in combination with a high

extraneous load can lead to feelings of distraction and being lost in the information. The respondent

will be quickly diverted and not motivated to spend a long time looking at the DAL. Contrary, when

the intrinsic load is low, a high extraneous load may motivate the respondent more to process the

information, and thus is expected to be more willing to spend more time to process the information.

This leads to the following hypothesis:

H7: “In case of a low amount of information, a high level of interactivity will lead to a

longer time spent in the DAL than a low level of interactivity. In case of a high amount of

information, a high level of interactivity will lead to a shorter time spent in the DAL than a

low level of interactivity.”

METHOD

Stimuli

To investigate our research questions a Telescopic Ad was developed, consisting out of a 30” TV

ad, a call-to-action and an interactive DAL. To avoid language and other confounding effects, an

advertisement of The Netherlands, for a brand unknown to Belgians is used. Given that product

involvement has an influence on information processing (Cf. ELM), a product category with an

average involvement was selected through the use of a pre-test. The involvement with 12 product

10


categories was measured with 39 respondents using the ten item five-point scale of Zaichkowsky

(1994). The travel agency was selected with an average product involvement rate (M = 2.80). The

attitude toward the 30” advertisement was controlled to be positive to avoid feelings of irritation.

This was important given the procedure in which the respondents were requested to click on the

additional information in the DAL. Therefore, a second pretest was conducted in which we

measured the advertisement attitude of six 30” ads of travel agencies with 19 respondents. We

selected the advertisement of “D-reizen”, which had the highest score (M = 4.21) on the 4 item 5-

point scale of Holbrook and Batra (1986). The hypotheses regarding the effects of the complexity of

the DAL were tested using a 2x2 between-subjects factorial design. The amount of information was

manipulated by the quantity of the information (e.g., information about 106 hotels versus 22 hotels).

The set size (the number of attributes) and the quality of the information were kept constant.

Interactivity was manipulated by the amount of hyperlinks (12 versus 92), the availability of a

navigation bar, and the possibility of two-way communication (e.g., search an address). The

advertisement was preceded by a programme context of average involvement and induced feeling,

trying to control pre-existing mood effects.

Participants

Out of a data base, a gross sample of 521 Flemish respondents was randomly selected based on a

spread in age, gender and education. Past research has shown that Internet use has an impact on

perceived interactivity (e.g. Sohn and Leckenby 2001; Jee and Lee 2002), and was therefore also

used as selection criterium, to make sure all respondents had some experience with media

interactivity (e.g. Tremayne and Dunwoody 2001). Finally, a nett sample of 282 respondents

participated in the study, retaining a sample of respondents with an average age of 38 years old

(range 21-56 years old, 50% between 21-40 years old), 61.8% males versus 38.2% females and

44.7% of the respondents holding a diploma of secondary high school versus 55.3% finished a

higher education level. The average internet use was 17 hours a week. The respondents were

11


randomly divided into 5 groups (4 groups for the varying complexity of the DAL and one group for

the traditional ad).

Procedure

The respondents were individually invited to an experimental “living room” setting. They were

requested to try out all the interactive possibilities they could notice on screen. After the briefing,

the respondents watched the 6 minutes during mood neutral excerpt of a TV programme, followed

by the advertisement. At the end of the 30” ad, a red call-to-action button appeared in the right

upper corner of the screen, in combination with a voice-over that invited the respondent to press the

red button to receive more product information. From the moment the respondents entered the

DAL, their time was recorded. Afterwards, the respondents entered a computer assisted

questionnaire containing the brand attitude measurement (7-point 4 item scale based on existing

scales of MacKenzie, Lutz and Belch 1986; good-bad, lovable-not lovable, desired- not desired,

positive – negative; alpha = .87), and the unaided brand recall. Attitude toward the 30” ad was

measured as a covariate through the scale of Holbrook and Batra (1986) (Alpha = .946). At the end

of the questionnaire the respondent was thanked for his/her cooperation. Each respondent received

an incentive of 25 euro. The experiment lasted 40 minutes in total.

RESULTS

Telescopic ad versus traditional 30” ad

To compare the advertising effects of the telescopic Ad (traditional 30” ad and DAL) with the

traditional 30” ad, the manipulated conditions of interactivity and information were combined, to

compare them with the group of respondents that viewed only the traditional 30” ad. The results

indicate that the telescopic ad resulted in better brand recall (56.9% versus 36.1%, chi² = 5.474, p

12


= .019) and a more positive brand attitude (M = 4.32 versus M = 2.97, t = -8.134, p < .001) than the

30” ad. H1 is accepted.

Main effects of amount of information and level of interactivity

The amount of information in the DAL did not have any effect on brand recall (52.1% versus 47.9%,

chi² = .845, p = .358) nor on attitude (M = 4.77 versus M = 5.45, F = .039, p = .843), which was

analyzed using an ANCOVA. H2 is not supported. The main effect of interactivity revealed a

positive effect on brand recall and attitude. A high level of interactivity increased brand recall from

43.6% to 56.4% (chi² = 5.371, p = .020). This effect was also noticeable for Ab (M = 4.19 versus M

= 4.46, F = 9.502, p = .002). H3 is accepted.

Interaction effect amount of information and level of interactivity

The interaction effect of the amount of information and interactivity on brand recall showed that for

the low amount of information, a high level of interactivity increases the brand recall from 41.1% to

58.9% (Chi² = 4.753, p = .029). For a high amount of information, this effect of interactivity

becomes insignificant (chi² = 1.201, p = .273), but not negative as expected (46.3% versus 53.7%).

For the brand attitude the same trend occurs. Given that the interaction effect of the amount of

information and the level of interactivity on Ab was not significant (p = .508) in the ANCOVA, the

mean values were further analyzed by using a t-test, which revealed that for the low information

condition, interactivity does have a significant positive effect (M = 4.09 versus M = 4.46, F = -2.027,

p = .045) on Ab, but for the high information condition, the effect is not significant (M = 4.28 versus

M = 4.45, F = -1.023, p = .308) (Fig.1). Therefore, H4 can only partly be accepted. The results of the

ANCOVA also show that attitude toward the 30” advertisement was a significant covariate that was

positively related to brand attitude (p < .001).

13


__

________________________________________________________________________________Place Figure 1 about here

__________________________________________________________________________________

__

________________________________________________________________________________Place Figure 2 about here

__________________________________________________________________________________

Time spent in the DAL

The average time spent in the DAL across the experimental conditions was 5.26 minutes. Looking at

the brand recall results in relation to the time spent (median split), the timing does not have a

significant impact on brand recall (47.5% versus 52.5%, chi² = 1.108, p = .293). Investigating the

effect of timing on brand attitudes, the regression results provide evidence for a significant positive

effect of the time spent in the DAL on Ab (Beta = .139, t value = 2.186, p = .030). Therefore H5 is

partly accepted. The ANOVA results indicate that both the amount of information (p = .020) and the

level of interactivity (p < .01) have a significant, positive main effect on the time spent in the DAL.

H6 is accepted. The interaction effect of both variables on timing is also significant (p = .025), but

only partly in line with our expectations. For the low level of information, the increase of

interactivity leads to a high increase in time spent in the DAL (3.39 min. versus 6.08 min.). In case

of a high level of information, there appeared no the negative effect of the level of interactivity on

the time spent in the DAL (5.29 min. versus 6.22 min.). Instead the results showed that the increase

in time was higher for the low information level compared to the high information level. H7 is partly

accepted.

14


DISCUSSION, IMPLICATIONS AND FUTURE RESEARCH

In line with previous studies (Bellman & Varan, 2004; Reading, et al., 2006), a telescopic ad that

offers more information to the consumer and makes interactivity possible, thereby increasing the

time spent with the persuasive content, performed notably better in terms of brand recall and

attitude, compared to a traditional advertisement. Contrary to our expectations, the amount of

information did not have an effect on brand recall nor on brand attitudes. However, the level of

interactivity had a positive effect on both brand recall and attitude. The cognitive involvement and

the intrinsic enjoyable experience evoked by the interactivity may explain these results, which are

in line with earlier internet studies (e.g., Sicilia, Ruiz & Munera, 2006). Previous ad complexity

studies found that too much information, graphics or links cause the respondent to feel lost or

overwhelmed, which may lead them to lose focus and interest rapidly. On the other hand, too little

complexity may induce a feeling of boredom. The Cognitive Load Theory states that there are four

possible situations (the combined effects of intrinsic load (amount of information) and extraneous

load (level of interactivity)). This study could partly confirm the expectations based on the CLT.

For a low amount of information, a high level of interactivity leads to more positive results, whereas

when the individual is exposed to a of lot information, the effect of interactivity becomes

insignificant (both for recall and attitude), but not negative as expected. In line with the main effect

of the amount of information on Ab and Brand recall, this interaction effect did not signal an

information overload phenomenon as a combined effect of a high amount of information and a high

level of interactivity. There are two explanations for not finding this effect. First, the traditional

information processing approach found that a consumer “can” experience information overload in

decision making processing, but they “will” not necessary do so (Jacoby, 1984). Maybe in this

study the information overload, and thus the negative advertising results, did not occur because the

individuals did not allow it to happen, and only processed the amount of information that (s)he

desired. Given that, in contradiction to traditional media, the viewer controls the information, this

15


effect may even be larger for IDTV formats, given that the consumer can be even more selective in

the exposure to the information that he/she likes. Bezjian-Avery, Calder and Iabucci (1998)

concluded from their study that clicking and interactivity may lead to less intensive processing of

the intrinsic information, and may therefore not lead to limited cognitive ability. A second

explanation can be found on the basis of the study of Danaher and Mullarkey (2003). They found

(in an internet context) that the exposure time to the persuasive information (banner) captured most

of the variance of brand attitude, leading to an insignificant effect of the amount of information.

Investigating the interaction effect of the amount of information and the level of interactivity on the

time spent in the DAL in this study, it was clear that for the high information condition, a high level

of interactivity, leads to the longest average time spent in the DAL, hereby decreasing the

likelihood of the information overload phenomenon to occur. Besides this dependent relation of

time spent in function of the amount of information and the level of interactivity, the time spent in

the DAL did have a positive main influence on the brand attitude, confirming earlier studies.

However, the timing had no impact on the brand recall. This Time spent in the DAL has a

mediating role for the effect of information and interactivity on brand attitude, but not for brand

recall. This can be explained by the fact that both in conditions of short and long exposure time, the

amount of minutes spent was high (minimum 1min 45) compared to other studies (e.g. Bezjian-

Avery, Calder, & Iabucci, 1998). The results lead to implications for advertising professionals.

First, the telescopic ads generate more positive advertising effects compared to the traditional TV

ads. Secondly, the positive effect of interactivity in the DAL is remarkable noticeable on both brand

recall and attitude, and is even more positive when the respondent is exposed to a low amount of

information. Next, given that the amount of information did not have a negative effect in any way,

advertisers can never give enough information to consumers. High amounts of information will

increase the time spent in the DAL, and will therefore even have a positive effect on brand attitude

and recall. The limitations of this study provide some directions for future research. First, our

results are only pertinent when the respondent reacts to the call-for-action, and uses the interactive

16


possibilities. Given the experimental setting of this study, little can be said about the more

externally valid real-life click-trough rate of this new advertising format. Secondly, the time that

consumer could spend processing the DAL was unlimited. Restricting the time is called for in

further research to more validly discover an information overload phenomenon (Davis and Davis,

1996). Thirdly, only two dimensions of the DAL’s complexity were manipulated. Other aspects

such as vividness and the occurrence of a simultaneous media context could also be investigated.

REFERENCES

Agee, T., & Martin, B.S. (2001). Planned or Impulse Purchases? How to Create Effective

Infomercials. Journal of Advertising Research, 41 (6), 35-42.

Bellman, S., & Varan D. (2004). The impact of adding additional information to television

advertising on elaboration, recall, persuasion. Paper presented at the ANZMAC Conference,

Wellingthon.

Bezjian-Avery, A., Calder, B., & Iacobucci, D. (1998). New Media Interactive versus Traditional

Advertising. Journal of Advertising Research, 38 (4), 23-32.

Bruner, G.C., & Kumar A. (2000). Web Commercials and Advertising Hierarchy-of-Effects.

Journal of Advertising Research, 40 (1), 35-42.

Bodemer, D., & Faust, U. (2006). External and mental referencing of multiple representations.

Computers in Human Behavior, 22, 27-42.

Boddy, W. (2004). New Media and Popular Imagination,” Oxford, Oxford University Press.

Bezjian-Avery, A., Calder, B., & Iacobucci, D. (1998). New Media Interactive versus Traditional


Cauberghe, V., & De Pelsmacker, P. (2006). Opportunities and Thresholds for advertising

17


on Interactive, Digital TV: A view from Advertising Professionals. Journal of Interactive

Advertising, Fall 2006, retrieved at http://www.jiad.org/vol7/no1/cauberghe/index.htm (accessed

on 25th November 2006).

Chang, Y., & Thorson, E. (2004). Television and Web Advertising Synergies. Journal of

Advertising, 33 (2), 75-84.

Cho, C.H., & Khang, H.K. (2006). The state of Internet-related Research in Communications,

Marketing and Advertising: 1994-2003. Journal of Advertising, 35 (3), 143-163.

Chung, H., & Zhao, X. (2004). Effects of Perceived Interactivity on Web Site Preference and

Memory: Role of Personal Motivation. Journal of Computer-Mediated Communication, 10 (1)

retrieved at http://jcmc.indiana.edu/ (accessed on 29 January 2007).

Conklin, J. (1987). Hypertext, An introduction & Survey. IEEE Computer, 20 (9), 17-41.

Csikszentmihalyi, M., & Lefevre, J. (1989). Optimal experience in Work and Leisure. Journal of

Personality and Social Psychology, 56 (6), 815-822.

Danaher, P., & Mullarkey, G. (2003). Factors Affecting Online Advertising Recall: A study of

Students. Journal of Advertising Research, sept, 252-267.

Davis, C.E., & Davis, E.B. (1996). Information Load and Consistency of Decisions. Psychological

Reports, 79, 279-288.

Drèze, X., & Zufryden, F. (1997). Testing Web Site Design and Promotional Content. Journal of

Advertising Research, 37(2), 77-92.

Ducoffe, R.H., Sandler, D., & Secunda, E. (1996). A Survey of Senior Agency, Advertiser, and

Media Executives on the Future of Advertising. Journal of Current Issues and Research in

Advertising, 18(1), 1-19.

Eveland, W.P., & Dunwoody, S. (2001). User control and Structural Isomorphism or Disorientation

and Cognitive Load. Communication Research, 28 (1), 48-78.

Geissler, G.L., Zinkhan, G.M., & Watson, R.T. (2006). The influence of Home Page Complexity on

Consumer Attention, Attitudes and Purchase Intent. Journal of Advertising, 35, 69-80.

18

http://jcmc.indiana.edu/

http://www.jiad.org/vol7/no1/cauberghe/index.htm


Holbrook, M.B., & Batra, R. (1987). Assessing the role of emotions as mediators of consumer

responses to advertising. Journal of Consumer Research, 14, 404-420.

Jacoby, J. (1984). Perspectives on Information Overload. Journal of Consumer Research, 10, 432-

435.

___________, Speller, D.E., & Kohn, C.A. (1974). Brand Choice Behaviour as a Function of

Information Overload. Journal of Marketing Research, 11 (feb), 63-69.

Jensen, J.F., & Toscan, C. (1999). Interactive TV. TV of the future or future of TV? Media and

cultural studies 1. Denmark, Aalborg University Press.

Kang, M.H. (2002). Interactivity in TV: Use and impact of an Interactive Program Guide. Journal

of Broadcasting & Electronic Media, 46(3), 330-345.

Keller, D.K., & Staelin, R. (1987). Effects of Quality and Quantity of Information on Decision

Effectiveness. Journal of Consumer Research, 14, 200.

Kim, P., & Sawhney, H. (2002). Machine-like new medium - theoretical examination of ITV. New

Media & Society, 47(2), 217-233.

Kitchen, P. (2003). Future of Marketing. New York, Pallgrave McMillan.

Korgaonkar, P.K., Karson, E.J., & Akaah, I. (1997). Direct Marketing Advertising: The Assents,

the Dissents, and the Ambivalents. Journal of Advertising Research, 37(5), 41-55.

Krugman, D.M., Cameron, G.T., & McKearney, C. (1995). Visual attention to programming and

Commercials. Journal of Advertising, 24(1), 1-12.

Lang, A. (2000). The limited capacity model of mediated message processing. Journal of

Communication, 50 (1), 46-70.

Lee, A.Y., & Sternthal, B. (1999). The Effects of Positive Mood on Memory. Journal of Consumer

Research, 26, sept., 115-127.

Levy, S., & Nebenzahl, I.D. (2006). Programme Involvement and Interactive Behaviour in

Interactive Television. International Journal of Advertising, 25(3), 309-322.

19


Liu, Y., & Shrum, L.J. (2002). What is Interactivity and is it Always Such a Good Thing?

Implications of Definition, Person and Situation for the Influence of Interactivity on Advertising

Effectiveness. Journal of Advertising, 21 (4), 53-64.

Lowrey, T. (1998). The Effects of Syntactic Complexity on Advertising Persuasiveness. Journal of

Consumer Psychology, 7(2), 187-206.

Macias, W. (2003). A Beginning Look at the Effects of Interactivity, Product Involvement and

Web Experience on Comprehension: Brand Websites as Interactive Advertising. Journal of

Current Issues and Research in Advertising, 25 (2), 31-44.

MacKenzie, S. B. (1986). The role of Attention in Mediating the Effect of Advertising on Attribute

Importance. Journal of Consumer Research, 55 (Oct.), 174-195.

_________________., Richard, L.J., & Belch, G.J. (1986). The role of attitude toward the Ad as

mediator of advertising effectiveness: A test of competing explanation. Journal of Marketing

Research, 23 (May), 130-143.

MacInnis, D.J., & Jaworski, B.J. (1989). Information Processing of Advertisements; Towards an

Integrated Framework. Journal of Marketing (Oct), 1-23.

Maddox, L.W, & Mehta, D. (1997). The role and effect of web addresses in advertising. Journal of

Advertising Research, 37(2), 47-60.

Malhotra, N. K. (1982). Information Load and Consumer Decision Making. Journal of Consumer

Research, 8 (March), 419-430.

Martin, B.A., Sherrard, M.J., & Wentzel, D. (2005). The Role of Sensation Seeking and Need for

Cognition on Web-Site Evaluations: A Resource-Matching Perspective. Psychology & Marketing,

22(2), 109-126.

Morrison, B.J., & Dainoff, M.J. (1972). Advertisement Complexity and Looking Time. Journal of

Marketing Research, 9 (nov), 396-400.

Petty, R.E., & Cacioppo J.T. (1981). Attitudes and Persuasion: Classic and Contemporary

Approaches, Dubuque, IA: William C. Brown.

20


Peracchio, L.A., & Meyers-Levy, J. (1997). Evaluating Persuasion enhancing Techniques from a

resource-matching perspective. Journal of Consumer Research, 24, 178-191.

Pieters, R., & Bijmont, T. (1997). Consumer Memory for TV Advertising: A Field Study of

Duration, Serial Position and Competition Effects. Journal of Marketing Research, 23 (4), 362-377.

Putrevu, S., Tan, J., & Lord, K.R. (2004). Consumer Responses to Complex Advertisements: The

Moderating Role of Need for Cognition, Knowledge and Gender. Journal of Current Issues and

Research in Advertising, 26 (1), 9-24.

Reading, N., Bellman, S., Varan, D., & Winzar, H. (2006). Effectiveness of Telescopic

Advertisements Delivered by Personal Video Recorders. Journal of Advertising Research, June,

217- 227.

Sanbonmatsu, D. M., Kardes, F.R., Houghton, D.C., Ho, H.A., & Posavac, S.S. (2003).

Overestimating The Importance of the Given Information in Multiattribute Consumer Judgment.

Journal of Consumer Psychology, 13(3), 289-300.

Shrum, L.J. (ed) (2004). The Psychology of Entertainment Media; Blurring the lines Between

Entertainment and Persuasion, Mahwah: Lawrence Erlbaum Associates.

Sicilia, M., Ruiz, S., & Munera, J.L. (2005). Effects of Interactivity in a Website. Journal of

Advertising, 34 (3), 31-45.

Singh, S., & Cole, C.A. (1993). The Effects of Length, Content and Repetition on Television

Commercial Effectiveness. Journal of Marketing Research, 30 (1), 91-104.

Stanton, J.L., & Burke, J. (1998). Comparative Effectiveness of Executional Elements in TV


Stevenson, J.S., Bruner, G.C., & Krumar, A. (2000). Webpage background and Viewer Attitudes.

Journal of Advertising Research, 40 (1), 29-34.

Thawani, A., Gopalan, S., & Sridhar, V. (2004). Context aware personalized Ad insertion in an

interactive TV environment, Presented at the workshop of Personalization in Future TV, The

Netherlands, Eindhoven.

21


Van Merriënboer, J., & Sweller, J. (2005). Cognitive Load Theory and Complex Learning: Recent

Developments and Future Directions. Educational Psychological Review, 17 (2), 147-177.

Zaichkowsky, J.L. (1994). The personal Involvement Inventory: Reduction, Revision and

Application to Advertising. Journal of Advertising, 23 (4), 59-70.

22


TABLES AND FIGURES

Figure 1: Interaction effect of amount of information and level of interactivity on brand attitude

A lotFewInformation

4,60

4,40

4,20

A lot

Low

Interactivity Means of Ab

23


Figure 2: Interaction effect of amount of information and level of interactivity on time spent in the

DAL

A lotLittle

Information

6,50

6,00

5,50

5,00

4,50

4,00

3,50

3,00

A Lot

Low

InteractivityMeans of timing

24