Effectiveness and consumer preference of online advertising

EXECUTIONAL CUES, INTERACTIVITY, AND LEVEL OF INVOLVEMENT
IN BANNER ADVERTISEMENT:
AN EXPERIMENTAL APPROACH TO UNDERSTAND
ONLINE ADVERTISING EFFECTIVENESS

HUANG SHANSI
(B.A., FUDAN UNIVERSITY)

A THESIS SUBMITTED
FOR THE DEGREE OF MASTER OF ARTS
COMMUNICATIONS AND NEW MEDIA PROGRAMME

NATIONAL UNIVERSITY OF SINGAPORE
2007


ACKNOWLEDGEMENTS

I would like to gratefully express my sincere appreciation to all the people who in
some way contributed to the completion of this dissertation either with support and
encouragement, or with discussion and advice. First and foremost, I owe many thanks to
my supervisors Dr. Hichang Cho and Dr. Byungho Park, whose invaluable insight,
stimulating suggestions, and precious guidance helped me finally complete the long
journey. I am also deeply indebted to Dr. Siyoung Chung and Mr. Raaj Chandran for their
constant encouragement and crucial support during my experiment. I would like to
express my gratitude to the Communication and New Media Programme Head, Prof.
Millie Rivera for supporting me with a graduate scholarship for 2 years. I also sincerely
thank all the faculty members of CNM for their inspiring lectures and seminars.
I am thankful to all the fellow graduate students of CNM for valuable sharing and
help when I was in need. My gratitude also extends to the registered students of NM3215
“Advertising Strategy” and NM1101 “New Media and Society” in Semester I, 2006-2007

Academic Year for giving up their precious time in participating my experiment.
Special appreciation goes to my parents for their continued support all my life,
instilling in me their morals and values, and steering me in a lifetime quest for knowledge.
Last but not least, I am most thankful to my dear husband, Jinghao, who besides tolerating
my many moods and swings, had confidence and faith in me and assisted me throughout
all the difficulties.

i


Table of Contents

ACKNOWLEDGMENTS………………….……….…………………………….…i
TABLE OF CONTENTS…………………………………………………………….ii
ABSTRACT…………………………………………………………….....................iv
LISTS OF TABLES……………………………………………….............................v
LISTS OF FIGURES……………………………………………………………….vi
CHAPTER 1 INTRODCUTION……………. …………………………………….1
CHAPTER 2 LITERATURE REVIEW……………………………………………6
2.1

Online Advertising………………….…………………………….......................6

2.2

Conceptualization of Online Advertising Effectiveness…………………...........8
2.2.1 Criteria of Effectiveness…………………………………………………...8
2.2.2 Measures of Effectiveness of Online Advertising………………………..13

2.3

Executional Cues & Effectiveness……………………………………………..19

2.4

Involvement & Effectiveness…………………………………………………..26

2.5

Interactivity…………………………………………………………………….32

CHAPTER 3 METHODOLOGY…………………………………………….……39
3.1 Research Design………………………………………………………………..39
3.2

Participants……………………………………………………………………..40

3.3

Stimuli………………………………………………………………………….40

3.4

Pretest…………………………………………………………………………..45

3.5 Procedure……………………………………………………………………….46
3.6

Measures………………………………………………………………………..47
3.6.1 Involvement………………………………………………………………47

3.6.2 Advertising Effectiveness………………………………………………...49
3.6.3 Other Covariates………………………………………………………….50

CHAPTER 4 DATA ANALYSIS AND RESULTS..……………………….……... 51
4.1

Sample Size and Composition…………………………………………………51

4.2

Descriptive Statistics & Scale Reliability……………………………………...52

ii


4.3

Executional Cues & Effectiveness……………………………………………..53

4.4

Level of Involvement & Effectiveness…………………………………………56

4.5

Interaction between Involvement & Executional Cues………………………...58

4.6

Interactivity & Effectiveness…………………………………………………...60

4.7

Interaction between Involvement & Interactivity.……………………………...61

4.8 Summaries of Findings…………………………………………………………63
CHAPTER 5 DISSUSTION, CONCLUSIONS, AND IMPLICATIONS……….66
5.1

The Impact of Executional Cues.………………………………………………66

5.2

The Impact of Interactivity……………………………………………………..68

5.3

The Impact of Involvement…………………………………………………….71

5.4

The Moderating Effects of Involvement……………………………………….73

5.5

Theoretical Implications……………………………………………………......77

5.6

Managerial Implications………………………………………………………..79

5.7

Limitations & Suggests of Future Study……………………………………….81

REFERENCES……………………………………………………………………...84
APPENDIX I TABLE OF MEASURES & QUESTIONS………………………..96
APPENDIX II EXPERIMENTAL BANNERS……………………………………98
APPENDIX III INDEX WEB PAGE……………………………………………..104
APPENDIX IV SAMPLE OF MAIN QUESTIONNAIRE……………………...105

iii


ABSTRACT

This study attempts to discover the source of effectiveness in banner
advertisements by exploring the effects of several potential factors such as
executional cues, level of involvement, and interactivity on advertising effectiveness.
This study employed the theoretical premise developed on the role of consumer’s
involvement on advertising by Richard E. Petty and John T. Cacioppo’s Elaboration
Likelihood Model (ELM). An experiment was conducted using custom-tailored
banner advertisements to facilitate either peripheral or central route of advertising
message processing. It was found that the level of advertising involvement had a
significantly positive relationship with the effectiveness of banner advertisement,
which supports the ELM in the context of online advertising generally. Unexpectedly,
it was also found that the banner advertisements presented in the format of peripheral
cues and higher interactivity did not yield the most desirable effects on advertising
effectiveness in generally; while only under low involved situation, banners that
employed peripheral cues and non-interactive features were more effective. The

findings suggest that advertisers need to take full advantage of the consumer
involvement to produce effective Web advertising. However, the enhanced
capabilities of the new medium have little effects on advertising effectiveness.

iv


List of Tables

Table 4.1

The Comparison of Four Experimental Groups............................................52

Table 4.2

Descriptive statistics for scales used in the experiment……………………53

Table 4.3

Results of Advertising Exposure for Three Product Categories……………55

Table 4.4

T-test Results for Effects of Execustional Cues…………………………….56

Table 4.5

Correlations between Involvement & Effectiveness……………………….57

Table 4.6

Low Involvement: T-test Results of Effects of Executional Cues………….59

Table 4.7

High Involvement: T-test Results of Effects of Executional Cues…………60

Table 4.8

T-test Results for Effects of Interactive Features…………………………...61

Table 4.9

High Involvement: T-test Results of Effects of Interactive Features……….62

Table 4.10

Low Involvement: T-test Results of Effects of Interactive Features………63

Table 4.11 Summaries of Findings…………………………………………………….65
Table 5.1

Means Comparison Between Type Peripheral & Central…………………..75

Table 5.2

Means Comparison Between Type Interactive & Non-interactive…………75

v

List of Figures

Figure 2.1

The Traditional “Hierarchy of Effects” CAB Model………………………9

Figure 2.2

The FCB Grid Model……………………………………………………...12

Figure 2.3

The Venn Diagram of Contemporary CAB Criteria……………………...13

Figure 3.1

Research Design for Banner Type Manipulation…………………………42

Figure 3.2

Experimental Stimuli for Each Experimental Group……………………..43

Figure 3.3

Sample Web Page and Banner Ad………………………………………..44

Figure 3.4

Presentation Orders of Experimental Banners……………………………45

Figure 3.5

Experiment Slots and Participants Details………………………………..46

Figure 4.1

Illustration of Banner Regrouping………………………………………..54

vi


Chapter 1 Introduction

Within less than twenty years, the Internet has fundamentally transformed the
landscape of traditional communication and business. It has not only facilitated global
sharing of information and resources, but also provided potential efficient channels for
advertising, marketing, and even direct distribution of certain goods and information
services (Hoffman, Novak & Chatterjee, 1995). These unique capabilities of the Internet
have contributed to the spectacular diffusion of the Web as a new commercial media in
the last several years.
The world also witnessed an astonishing expansion in the popularity of Internet
users, which has reached 1.08 billion in 2005 (Nielsen//NetRatings, 2006). Internet users
have been revealed to own higher incomes and have better education than the general
population (PEW Internet, 2006). The trend of significant migration from TV and print
consumption to Internet usage has also been confirmed, which was up to fifty percent, in
the number of users as well as the amount of time spent (Gluck, 2000).
In order to cater this promising new market, advertisers show great enthusiasm for
expanding their horizons to encompass online advertising. Since the first banner
advertisement appeared on the online magazine Hotwired Website in 1994 (Adams,

1995), the growth of online advertising has been exponential. The revenue of online
advertising was only $267 million in 1996; it ascended to a historical peak of $8087
million in 2000 (IAB & PricewaterhouseCoopers, 2003). Recently a new record of $3.9
billion for the first quarter of 2006 was announced, marking the highest quarter ever
reported (IAB & PricewaterhouseCoopers, 2006).

1


The rapid increment of annual revenues shows the vitality of the burgeoning
advertising, as well as the confidence of committing huge funds. This gravity was driven
by the continual optimistic reports of the industry. Therefore many companies have been
agitated for putting up their online advertisements by indiscriminately applying some
online advertising approaches, such as large sizes, animations and 3-D, to each single
product/brand, without clear goals for their online advertising presence, or even without
the means of measuring whether they are getting a return on their investment. Differences
between the new medium and the traditional media were also disregarded. The traditional
advertising approaches have been adopted without any reformation, even though
researchers have already raised the pressing necessity to refine both of the general
principles and measures of traditional advertising to meet the need of new environment.
The risks of advertising in the new medium are increased as research into online
advertising is still in its infancy. A lot of debates have not been settled in respect of the
effectiveness of online advertising. Notwithstanding compelling evidence to prove that
online advertising is an effective tool for promoting products (Briggs, 2001; Dreze &
Hussherr, 2003; Wakeling & Murphy, 2002), it is not yet clear, however, how to
successfully gauge and achieve advertising effectiveness online.
The question of online advertising effectiveness becomes especially pertinent in
light of the deteriorated click-through rates, less than 2% in most cases (Tuten, Bosnjak
& Bandilla, 2000), and the inflated advertising expenses. In 2000, the average CPM
(Cost-Per-Thousand impressions), which is the dominant approach to online advertising

pricing, is around $34 (Adknowledge, 2000). By contrast, CPMs range from $6-$14 for
national television advertising, $8-$20 for magazines advertising, and $18-$20 for

2


newspaper advertising (The Economist, 2006).
Obviously, advertisers are struggling to justify online advertising expenditures for
one of the largest line items in their marketing budget. In order to be more strategic and
precise in planning and optimizing online campaigns, they starve for detailed guidelines
of effectively adopting the relevant characteristics of online advertising. This paper
attempts to address this unmet need in online advertising effectiveness by exploring the
potential influential factors and their respective impacts on online advertising.
As one of the outstanding characteristics of online advertising, effects of
executional cues have received considerable attention. Executional cues include central
cues and peripheral cues. It has been suggested that some executional cues play important
role in enhancing awareness, eliciting positive attitudes and engendering purchase
intention. As an equally consumer-controlled media, the Internet presents a vast array of
possibilities when it comes to the creative execution of these advertising cues, which,
nevertheless, might differ from traditional media. In order to further branch the research
of executional cues into the new media, this paper focuses on investigating the
application of different executional cues for banner advertisement and the impact on
advertising effectiveness in the context of online advertising.
The literature also suggested the impact of advertising on consumer be predicted
and moderated by product involvement, which is perfectly interpreted by Elaboration
Likelihood Model (ELM) (Petty & Cacioppo, 1981). Elaboration Likelihood Model
postulates two divergent paths of information processing, central route vs. peripheral
route, contingently upon consumers' level of involvement and information-processing
ability. According to ELM, when people are highly involved, they are motivated to have

3


a deep examination and a diligent consideration of the product-related messages based on
past experience or knowledge. The peripheral route portrays the situation when people
are low involved with the product. They will pay attention to non-product related stimuli
such as advert model, background music or graphics. This study tries to examine how
consumer involvement interacts with executional cues in the new environment of online
advertising.
Interactivity is a unique feature only endowed by the new medium Internet. Owing
to its new emergence and complexity, very few researches have touched upon this issue
and its impact on advertising effectiveness was far from comprehension. However, there
is a conventional belief that interactivity positively boosts advertising effectiveness. This
study is designed to determine how interactivity affects effectiveness of online
advertising. The interaction between involvement and levels of interaction will also be
examined.
In sum, the purpose of this study is to examine whether traditional principles of
mass media advertising apply in this new commercial environment; whether several
acknowledged important characteristics of online advertising can produce short-term
effects on each dimension of effectiveness among proficient Internet users. This research
aims to answer the following questions:
RQ1. Do executional cues, interactivity and involvement have an impact on online
advertising effectiveness?
RQ2. How does the interaction of involvement with executional cues and
interactivity affect online advertising effectiveness?
RQ3. How can we manipulate different executional cues or different level of

4

interactivity to enhance the effectiveness of online advertising?
This dissertation contributes in several ways to the growing body of advertising
knowledge about the Internet medium. First, this study employed Petty and Cacioppo’s
Elaboration Likelihood Model as the conceptual framework and empirically examined
the model in the context of online advertising. Second, this paper explored the role of
customer’s involvement on the effectiveness of online advertising, which has important
implications for advertisers to optimize their online campaigns. Third, this study
investigated the function and impact of executional cues of banner advertisement. The
findings help to provide insights on the value of different executional features and reveal
more practical routes of achieving online effectiveness. As such, this study answers the
recall by advertising practitioners for furnishing a set of guidelines for online advertising.
Finally, this study enriches the literature in interactivity of online advertising, especially
indicating potential factors affecting the impacts of interactivity, which may serve as a
foundation or a springboard for continuing research in effective interactivity on online
advertising persuasiveness.

5


Chapter 2 Theoretical Background

2.1 Online Advertising
Online advertising generally follows the same principles as traditional advertising.
Nevertheless, the Internet as a unique medium has led to huge differences between online
and traditional advertising. Firstly, owing to the digital Web, online advertising is
interaction-orientated. Online ads can be directly activated, which is a form of interaction,
a kind of user response that provides evidence for the novel role of addressees. Beyond
that, different types of online ads also allow different degrees of interactivity (Janoschka,
2004). For example, interactive online game has higher level of interactivity compared to
non- synchronous e-mail feedback. Moreover, online advertising is generally considered

to be less intrusive since the Web is a pull, not a push medium. That is, advertising
message is available to consumers who are willing to reach for and pull it out (Sterne,
1999), while traditional advertising is usually embedded within the program content. By
displaying online, it can also be accessed on demand 24 hours a day, seven day a week
regardless of geographic location. Furthermore, the multimedia nature of the Web lends
full support for multimedia applications of online advertising, which allows it to
optionally package the capabilities similar to those of newspaper (text, graphics), radio
(audio) and TV (video) (Ainscough & Luckett, 1996; Breitenach & Van Doren, 1998). In
addition, online advertising offers advertisers the opportunity of precisely targeting an
audience and measuring responses instantly (Zeff & Aronson, 1997) with the help of
technologies such as cookies—programs that unobtrusively keep track of a visitor's
previous activities on a site.

6


In general, online advertisements can be classified as passive ads and active ads
based on the amount of control exercised by the consumer over their exposure (Hoffman
& Novak, 1998). Usually, active ads consist of one or more Web pages that are totally
dedicated to advertising contents. They customarily locate in the advertisers’ or
publishers’ servers and can only be reached by clicking the hyperlinks on related passive
ads. Thus, most of the online advertisements now under discussion are considered to be
passive ads, which are forcefully exposed to consumers and act as a “gateway” by
providing hyperlinks to those active ads, typically in form of banners. Banners are small
text and graphic-based billboards that spread across the Web page, primarily aiming at
informing users about the existence of certain Web sites or Web pages and persuading
them to visit them via clicking. In a sense, the banners are hyperlinks that enable
activation through their users.
According to annual reports of Interactive Advertising Bureau, banners have been
one of the most common formats of online advertising all along since 1999, accounting

for over half of the online advertising dollars spent. Thus, this paper focuses on
measuring the effectiveness of online advertising in form of banners since the consensus
supports the banner advertisements as the dominant and most prevalent form of online
advertising.

7


2.2. Conceptualization of Online Advertising Effectiveness
2.2.1 Criteria of Effectiveness
Despite its expanded functions, the issue of criteria of online advertising
effectiveness is still part of the broader question of advertising effectiveness in general.
Thus, the effectiveness of online advertising should be examined in a similar way as that
of traditional advertising (Li & Leckenby, 2004; Pavlou & Stewart, 2000).
Researchers and advertising practitioners have long sought to understand how
advertising works. A number of measures have been proposed to empirically evaluate
advertising effectiveness. Some contend that advertising is effective only when it sells
(Little, 1979). Others argue that there is a series of stages between the point of
unawareness of a product and/or brand and the ultimate purchase/sale of a particular
brand, that is, the hierarchy of effects (Colley, 1961; Schultz, 1990). As literature
indicates that the direct shot-term sales effect of advertising is, in general, quite low
(Aaker & Carman, 1982; Assmus, Farley & Lehmann, 1984; Tellis, 1988), this study thus
adopts the latter view of accessing the impact of advertising.
The model of hierarchy of effects was initially developed by attitude researchers in
acknowledgement that individuals engender a series of responses in a certain order as
effectively exposed to the advertising. This model started as early as in 1898, from
“Attention- Interest- Desire- Action” (AIDA) model advanced by Elmo St. Lewis (Barry,
1987). Through AIDA model, Elmo St. Lewis proposed a systematic way of discussing
criteria of effectiveness for the first time. It hypothesizes that attention, interest, desire,
and action are the most important responses consumers might make to advertising with

attention being the initial response and action being the last.

8


Many works had been endeavored to develop AIDA model. But most of them
involved modifying the conceptual outlines or frameworks in a small way, based on
intuition and logic. Not until 1961 had significant progress been made by Lavidge and
Steiner to furnish the main body of modern hierarchy of effects literature (Barry, 1987).
Lavidge and Steiner (1961) made the first attempt to identify advertising impact in terms
of cognitive, affective, and conative categories of responses. Enclosed within those
categories was a six-stage hierarchy that includes awareness, knowledge, liking,
preference, conviction, intention, and purchase. As illustrated in Figure 2.1, Lavidge and
Steiner (1961) postulated that cognition generally leads to affection which, in turn, leads
to conation; consumers would inevitably go through a series of steps to that threshold of
purchase. It was the first time that the criteria of effectiveness were linked to the areas of
interest in the field of social psychology, thereby leading the literature in that large field
to the issue of criteria in advertising and related field (Li & Leckenby, 2004; Weilbacher,
2001).

Figure 2.1 The Traditional “Hierarchy of Effects” CAB Model
Behavior

Affection

Cognition

9

In their work, “Cognition” represents the intellectual, mental or rational state,
concerning the process or faculty of becoming specifically aware of a solution to fit one’s
need, relating to the process of encoding, storing, processing, and retrieving information.
It includes steps of perception, memory, thinking and understanding. More precisely,
perceives stimuli (signals) is sensed by human beings and transformed into data in
working memory, which will be compared with long term memory and manipulated by
reasoning processes such as problem solving, planning, judgments until reaching a
decision and executing a response (Toth, 2004). “Affection” refers to feeling or emotional
states, for example, liking or disliking. “Conation” refers to the striving or behavioral
states, meaning the aspect of mental processes or behavior directed toward action or
change. It is closely associated with the concept of volition, defined as the use of will, or
the freedom to make choices about what to do.
The basic principles of the hierarchy went unchallenged until Palda (1966) posed
his concerns over the lack of support of experimental evidences, which stirred a new
developmental phase in the theory. This challenge was strongly reinforced by Ray's
insightful suggestion that perhaps there were alternate orders to the hierarchy of effects
(Ray, Sawyer, Rothschild, Heeler, Strong & Reed, 1973). Ray et al.’s research indicated
that advertising did not always lead or cause people to change their attitudes and behavior
towards a product; there is no specified sequence of stages which must occur as in
Lavidge and Steiner’s (1961) view. Consumers may make decisions in a “non-rational”
manner and could possibly “skip” stages. The process of consumer decision will not
necessarily be linear or one-dimensional. As a result, the model should be provided
feedback loops. Further, he proposed three orders of hierarchy of effects as a refinement

10


of the traditional model: the traditional or learning hierarchy (cognition-affect-conation),
the dissonance-attribution hierarchy (conation-affect- cognition), and the low
involvement hierarchy (conation-cognition-affect). He suggested that consumers might

respond differently to advertising messages under certain circumstances. Audiences may
follow the Learning Hierarchy model that they think and perceive, then feel or develop
attitudes and then behave as the traditional CAB model describes. Consumers could also
first behave, then develop attitudes and feelings as a result of that behavior, and then
learn or process information that supports the earlier behavior, which is the Dissonance
Hierarchy, the total reverse of the Learning Hierarchy. At the same time, the Low
Involvement Hierarchy maintains that consumers behave, then learn as a result of that
behavior and then develop attitudes as a result of the behavior and the learning. Ray et al.
(1973) emphasized that all three orders of hierarchies are feasible and can be correct.
Subsequent research on advertising effects led to the inception of integrative
models. Vaughn’s (1980) FCB grid illustrated the adaptive nature of advertising effects.
As shown in Figure 2.2, the grid features four effects sequences that vary according to
level of involvement (high/low) and type of inclination (rational/emotional) of the
consumer towards a product category. The FCB grid’s sequences are: cognition-affectconation (informative), affect-cognition-conation (affective), conation-cognition-affect
(habitual), and conation-affect-cognition (satisfaction). Vaughn (1980) suggests that
advertisers should use the grid as a guide in shaping advertising messages to ensure that a
product’s advertising is based on the right tactic and appeal to an audience.

11


Figure 2.2 The FCB Grid Model

Smith and Swinyard’s (1982) developed Information Integration Response Model
(IIRM), with its major contribution to introduce belief type (higher and lower order
beliefs) to the literature of advertising effects. Their findings suggest that in lower order
belief product purchases (where trial is cheap and easy) advertising works by increasing
consumer awareness and reinforcing previous consumer experiences with a product,
whereas in higher belief order situations (where trial is costly and risky) advertising
works simply as a source of information for the consumer. Similarly, in Deighton’s twostage model (1984) advertising effects adapt to different consumer and product contexts.

Kreshel further (1984) contended that an emotional response to a stimulus such as an
advertisement might consist of a physiological, affective and cognitive response
occurring simultaneously.

12


Based on the earlier works, Li and leckenby (2004) suggest a Venn diagram, shown
in Figure 2.3, to illustrate the non-linear and overlapping nature of the three criteria of the
effectiveness. The new diagram expresses the mutually non-exclusive nature of the three
criteria, in which there is no pre-determined starting point or ending stage. In addition, it
is possible to have more than one criterion developing at the same time. Thus, a full view
of the effectiveness of the advertising message requires being measured on all three
dimensions.

Figure 2.3 The Venn Diagram of Contemporary CAB Criteria

Behavior

Cognition

Affection

2.2.2 Measures of Effectiveness of Online Advertising
At present, the measures of online advertising effectiveness have not reached
consensus. The question of what constitute the appropriate measures of effectiveness
remains highly debatable (Wright-Isak, Fable & Horner, 1996). Quite a number of
measures have been proposed to empirically evaluate advertising effectiveness, which
generally fall into two categories: actual response and impressions (Danaher & Mullarkey,
2003).

13


Click-through rate was once the most widely and exclusively used measure for
online advertising effectiveness (Forrester, 2002 & 2001), which is the percentage of the
total number of ad exposures that induce a surfer to actually click on a banner in response
to an advertised message (Novak & Hoffman, 1997). As a measure of actual response,
Click-through rate has the advantage of a behavioral response that is easy to observe, and
indicates an immediate interest in the brand being advertised (Berthon, Pitt &Watson,
1996; Briggs & Hollis, 1997). However, merely click-through fails to quantify the impact
of advertising exposure on a consumer’s cognition and affection (Briggs & Hollis, 1997).
Drèze and Hussherr (2000) also argued click-through rates not capture the full extent of
an advertisement's effectiveness, as pre-attentive processing does not lead to immediate
action. Furthermore, response measures are not objective as the outcome can depend on
the advertising copy strategy (Danaher & Mullarkey, 2003). In sum, emphasizing clickthrough rates only will predicatively lead to the overlook of effects that occur before or
after the clicking action (Chtourou & Chandon, 2000). Meanwhile, it is acknowledged
that click-through rate has declined steadily from 5% in 1998 and seems to have
stabilized at 0.5% (Doubleclick, 2003a). In response to these situations, other measures of
online advertising effectiveness should be adopted.
In academic research, the currently favored measures to assess changes of
impressions, include awareness, Attitude towards the ad (Aad), Attitude towards the
brand (Abrand), and purchase intention (PI) (Li & Leckenby, 2004; Wu, 1999).
Methodologically, the vast majority of communication effects research in the past few
decades has relied on these measures to examine the persuasive impact of advertisement
exposure.

14

Awareness

Awareness is one of the traditional measures on advertising

effectiveness, which means consumers recognize the existence of a brand, service or idea.
Awareness has been claimed to be the first step to assess the impact of advertising in
many hierarchy of effects models. For example, as discussed in the previous session,
AIDA model, suggests that awareness is affirmatively the initial response when
consumers react to advertising. Colley (1961) also claimed that awareness represents the
minimal level advertisers seek for advertising goals.
Awareness includes advertising awareness and brand awareness. Advertising
awareness refers to the recall or recognition of a specific advertisement. Research has
provided evidence that there is relationship between advertising awareness and short-term
sales (Hollis, 1994). Brand awareness is defined as a pyramid level of knowledge
involving recognition, recall and top-of-mind awareness of the brand (Hoyer & Brown,
1990). Brand awareness has long been recognized as essential prerequisite for
establishing brand images (Engel, Blackwell & Miniard, 1995) and the gateway leading
to consumers’ purchase intention.
Attitude towards ad (Aad) & Attitude towards brand (Abrand) Attitude is the
most common measure in the hierarchy of effect. Engel et al. (1995) justified it to be
simply an overall evaluation.

As proposed by traditional hierarchy views, such as

Lavidge and Steiner’s CAB model in 1961, attitude is deemed as linear sequences from
cognition to affection and conation. A more contemporary perspective argued that attitude
can be formed by either cognitive, and/or affective and/or cognitive dimensions, with
conation being either a determinant or an outcome of attitude (Eagly & Chaiken, 1993; Li
& Lekenby, 2004; Ray, 1973)

15


A great number of empirical studies have documented attitudinal shifts resulting
from advertising exposure (e.g., Batra & Ray, 1986; Cacioppo & Petty, 1985; Ha, 1998;
Kim, Jang & Lim, 2000; Lutz et al., 1983). Thus, the attitude towards the ad (Aad) is
conceptualized as “a predisposition to respond in a favorable or unfavorable manner to a
particular advertising stimulus during a particular exposure occasion” (MacKenzie, Lutz,
& Belch, 1986, p. 130). That is, Aad represents an individual’s evaluation of the overall
advertising stimulus. Some researchers (Batra & Ahtola, 1991; Olney, Holbrook & Batra,
1991) argued that the measure of attitude toward the ad should be considered multidimensionally with hedonism, utilitarianism and interestingness as Aad’s attitudinal
components. Here, hedonism refers to the evaluation of entertainment value of the ad;
utilitarianism refers to the evaluation of usefulness of the ad, and interestingness is
viewed as an evaluation of curiosity.
The attitude towards the ad (Abrand) measures the extent to which respondents
have a positive or favorable opinion of the brand. Researchers and practitioners have
been using multi-attribute models to study consumer attitude towards brand for two
decades (Trout, 2005), which propose that individuals perceive brands as possessing a
number of attributes that provide the basis on which consumers form their attitudes.
Using this approach, an individual's overall attitude toward the brand is determined by a
consumer's evaluative response or attitude toward brand attributes and a subjective
estimation of the probability that the brand actually has the attribute (Pechmann &
Stewart, 1989). Belch and Belch (2006) represented the attitude towards the brand as
being influenced by consumers’ beliefs about specific brand attributes and different levels
of importance attached to these attributes.

16


Purchase Intention Purchase intention (PI) is the most immediate step preceding

actual behavior. It tends to measure the likelihood of respondents to taking a purchase
action in the future (indicate will buy, or test-drive, for example). Many studies have
reported Aad as a mediator of advertising effects on brand attitude and purchase intention
(Aaker, Stayman & Hagerty, 1986; Lutz, 1985; MacKenzie, Lutz & Belch, 1986).
According to MacKenzie et al. (1986), there can be a one-way or two-way flow between
Aad and Abrand owing to different situations; both Aad and Abrand are independent
determinants of purchase intention.
As discussed above, the effectiveness of online advertising should be addressed in
general context of the criteria of cognition, affection and behavior by measuring changes
in awareness, brand perceptions, attitudes, and purchase intention. However, online
advertising differs from traditional advertising with expanded capabilities. One
significant aspect is that online advertising is endowed with the capability of interactive
communication, which attributes more power to the users over controlling the
communication processes that the users can not only be actively involved in, but also
have a wide range of freedom and opportunities. In this sense, user’s control should be
considered as an outstanding issue with respect to online advertising effectiveness. In
response to that, some researchers suggested online advertising employ new measures
with respect to user’s control. According to the Interactive Advertising Model (IAM)
proposed by Rodger and Thorson (2000), items such as Internet uses, information
processes, and the responses that result from the encounter of this processing were
clarified as the new measures for consumer’s control. Li and Leckenby (2004) further
modified the traditional measures by suggesting and specifying a list of measures that

17


might be under the control of either the user or the advertiser. The measures under control
of advertiser are largely the standard measures, such as attention, attitude and intention;
while the newly suggested measures are grouped under user’s control, include consumer
goals, consumer expertise, consumer ideals, personalization effects, quality of decision,

trust, internet motivation, and active participation.
Notwithstanding the necessity of refinement of the general measures to meet the
need of contemporary environment, the new measures with respect to user’s control will
not be adopted in this study. Firstly, as for the current status, it is presumable that the new
measures are put forward on the basis of taking into consideration of active online ads. As
discussed above, active ads can only be reached by clicking the passive ads, which
requires the actual responses from consumers. However, under the circumstance of the
low 0.5% click-through rate, most banner ads on the Web are acknowledged as the
passive form of non-interactive advertising. Thus, it is not appropriate to apply new
measures of active ads to the current passive ads. Secondly, very few studies have
suggested or applied new schemes for accessing online advertising effectiveness till now.
As pioneer, the new measures are still in the immature stage and need more empirical
validation. As such, these new measures will not be employed as criteria of online
advertising effectiveness in this study. However, some items from new measures, such as
consumer expertise and active participant, were practically measured in this study as
controvertible factors for their potential effects on advertising effectiveness.
To summarize, there is no one best way to measure online advertising effectiveness.
Multiple measures should be employed to obtain more insight. Advertising awareness,
attitude towards ad, attitude toward brand, and purchase intention are the most commonly

18