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thesis entitled
CONSUMER LEARNING AND 3-D ECOMMERCE: THE EFFECTS OF

SEQUENTIAL EXPOSURE OF A VIRTUAL EXPERIENCE RELATIVE TO
INDIRECT AND DIRECT PRODUCT EXPERIENCE ON PRODUCT KNOWLEDGE,
BRAND ATTITUDE AND PURCHASE INTENTION

presented by

Terry M. Daugherty

has been accepted towards fulﬁllment
of the requirements for

Ph.D degree in M388 Media

 

 

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CONSUMER LEARNING AND 3-D ECOMMERCE: THE EFFECTS OF
SEQUENTIAL EXPOSURE OF A VIRTUAL EXPERIENCE RELATIVE TO
INDIRECT AND DIRECT PRODUCT EXPERIENCE ON PRODUCT KNOWLEDGE,
BRAND ATTITUDE AND PURCHASE INTENTION
By

Terry M. Daugherty

AN ABSTRACT OF A DISSERTATION
Submitted to

Michigan State University

in partial fulﬁllment of the requirements
for the degree of
DOCTOR OF PHILOSOPHY
Mass Media Ph.D. Program
200i

Dr. Bonnie Reece

ABSTRACT
CONSUMER LEARNING AND 3-D ECOMMERCE: THE EFFECTS OF
SEQUENTIAL EXPOSURE OF A VIRTUAL EXPERIENCE RELATIVE To
INDIRECT AND DIRECT PRODUCT EXPERIENCE ON PRODUCT KNOWLEDGE,
BRAND ATTITUDE AND PURCHASE INTENTION
By

Terry M. Daugherty

The Internet has the ability to serve as a more poweriultnedium because
consumers are able to interact with products in 3-D multimedia environments thus
simulating a new form of experience — a virtual experience. However, very little research
has explored the impact of this new type of experience especially in combination with
indirect (advertising) and direct (product trial) experience/Therefore, in a laboratory
experiment (n=166) this study empirically tested the sequential impact of consumer
exposure to indirect, direct, and virtual experiences on brand attitude, product knowledge,
and purchase intention when evaluating a digital video camcorder. The results indicate
that exposure to a virtual experience preceding both indirect and direct product
experience is more effective at inﬂuencing brand attitudes. However, direct experience
preceding exposure to a virtual experience was found to have the greatest impact on
product knowledge. Consumers exposed to an indirect experience preceding both virtual
and direct product experience indicated they were signiﬁcantly less likely to purchase the
test product. Implications for business-to-consumer ecommerce and Internet marketing

are discussed.

Copyright by
TERRY M. DAUGHERTY
2001

ACKNOWLEDGEMENTS

There are numerous individuals who gave their time, knowledge, and guidance to
make this dissertation possible. For her unequivocal support, I would like to thank my
advisor Dr. Bonnie Reece. For their critical analysis and helpful comments, I wish to
thank each of my committee members, Dr. Frank Biocca, Dr. Hairong Li, and Dr. Steve
Edwards.

I would also like to thank Dr. Matt Eastin, Carrie Trimble, and Harshavardhan
Gangadharbatla for their invaluable help during the data collection. For the design of
stimulus materials, I would like to thank the M.I.N.D. Lab at Michigan State University
and especially Dae Yul Choi.

Finally, my deepest gratitude goes to my wife Julie and children Michelle, Ryan
and Kelly for their unconditional emotional support and sacriﬁce throughout the course
of this dissertation. While the completion of this degree is a signiﬁcant accomplishment,
the foremost honor that gives me the greatest joy and pride is the privilege of serving as a

husband and father.

iv

TABLE OF CONTENTS

LIST OF TABLES ................................................................................................ vii
LIST OF FIGURES.......... ..................................................................................... viii
CHAPTER ONE
INTRODUCTION ................................................................................................. 1
CHAPTER TWO
LITERATURE REVIEW ...................................................................................... 6
The Internet ............................................................................................... 6
Consumer Learning ................................................................................... 9
Virtual Experience ..................................................................................... 16
Interactivity and Vividness ............................................................. 18
Presence ......................................................................................... 20
Virtual Affordances ........................................................................ 22
Personal Relevance ........................................................................ 24
CHAPTER THREE
THEORETICAL FRAMEWORK ......................................................................... 27
CHAPTER FOUR
METHODOLOGY ................................................................................................ 38
Experiment Design .................................................................................... 38
Participants ................................................................................................ 39
Independent Variables ............................................................................... 39
Stimulus .................................................................................................... 40
Product ........................................................................................... 40
Materials ........................................................................................ 42
Procedure ................................................................................................... 43
Dependent Measures .................................................................................. 45
Product Knowledge ........................................................................ 45
Brand Attitude ................................................................................ 46
Purchase Intention .......................................................................... 46
Manipulation Checks ................................................................................. 46
CHAPTER FIVE
RESULTS ............................................................................................................. 48
Data Analysis ............................................................................................ 48
Hypothesis Testing .................................................................................... 49
Post Hoc Analysis ...................................................................................... 61

CHAPTER SIX

SUMMARY AND CONCLUSIONS ..................................................................... 63
Discussion ................................................................................................. 63
Limitations ................................................................................................ 69
Conclusions ............................................................................................... 69

LIST OF REFERENCES ....................................................................................... 72

APPENDIX A ....................................................................................................... 82

APPENDIX B ....................................................................................................... 85

APPENDIX C ....................................................................................................... 92

APPENDIX D ....................................................................... 96

vi

TABLE 1: .

TABLE 2: .

TABLE 3:

TABLE 4:

TABLE 5:

TABLE 6:

TABLE 7:

TABLE8:

TABLE 9:

LIST OF TABLES

Sequences of Exposure ....................................................................... 34
Summary of Hypotheses ..................................................................... 37
Mean, Standard Deviation, and Cronbach Alpha Coefﬁcients ............. 49
for Scales

Dependent Variable Test of Normality ................................................ 51
Dependent Variable Descriptive Statistics for each Treatment ............ 52
Condition

Contrast Comparisons for Sequential Exposure Conditions for .......... 54
H1 through H6

Contrast Comparisons for Sequential Exposure Conditions for ........... 58
H7 through H15

Correlation Matrix of Dependent and Manipulation Check ................. 61
Variables

Sequential Order Effect for Indirect, Virtual and Direct Experience 62

vii

LIST OF FIGURES

FIGURE 1: Theoretical Spectrum of Consumer Learning .................................... 29

FIGURE 2: Integrated Information Response Model Incorporating Virtual .......... 32
Experience

FIGURE 3: Product Knowledge, Brand Attitude and Purchase Intention .............. 52

Across Sequential Exposure Conditions

viii

CHAPTER 1

INTRODUCTION

The development of computer technology and expansion of the Internet has
resulted in a promising but challenging mass medium. Marketers have the ability to
deliver highly targeted persuasive messages, strengthen customer relationships, and
ultimately generate sales 24 hours a day (Tedesco, 1999). While the Internet has
demonstrated a high capacity for disseminating information about products and services,
it has fallen short of expectations when consumers want to “experience” a product. In
fact, the way product information is presented in online stores is likely to reduce the
impact of brand equity. For instance, online retail environments typically only display a
list of brand names, model numbers, Specifications and/or prices (Burke, 1997). As a
result, consumers do not achieve as rich of an experience as they would in a conventional
store, such as feeling the store atmosphere, interacting with a salesperson, and seeking
sensory stimulation (Tauber, 1972). These weaknesses hinder consumer learning in
computer-mediated environments and could impact future business-to-consumer
ecommerce.

Research has documented that consumers learn about products through indirect
experience, such as advertising, and via direct experience, such as product trial
(Deighton, 1984; Hoch and Ha, 1986; Hoch and Deighton, 1989; Kempf and Smith,
1998; Smith and Swinyard, 1982; 1983). However, it has been speculated that the type of

medium may limit the effect of advertising and a more powerful medium for

communicating the details and experiences of a product, such as the Internet, could have
a stronger impact on consumer learning (Moore and Lutz, 2000).

Three-dimensional (3-D), multi-user, online environments constitute a new
revolution of interactivity by creating a compelling online experience (Waller, 1997). It
is the interactive nature of the Internet that offers marketers the greatest potential for
building stronger relationships and provides a distinct advantage over traditional mass
media (Upshaw, 1995). Furthermore, because of the interactive nature of the Internet,
marketers have the ability to offer user-controlled product interactive experiences
(Schlosser and Kanfer, 2001 ). Li, Daugherty and Biocca (2001a) recently conceptualized
this new and challenging type of consumer experience as a virtual experience. While the
term has been used in previous research (Hoffman and Novak, 1996; Klien, 1998), Li,
Daugherty and Biocca (2001a) conceptually deﬁned a virtual experience as a
psychological and emotional state consumers undergo while interacting with 3-D visual
products in a computer-mediated environment. McLuhan (1988) suggests that within any
medium there is a connection between the human mind, the technology, and the
environment that serves to immerse users. Consumers are able to experience
psychological states because the medium creates a sense of interactivity and enjoyment
resulting in increased learning, altered behaviors, and a perceived sense of control
(Hoffman and Novak, 1996). Thus, it is plausible that experiences occurring while using
the Internet are capable of creating psychological states that inﬂuence cognitive and
affective behavior. This new type of experience is a simulation of a real or physical
experience and can be construed to be located between direct experience and indirect

experience within the spectrum of consumer learning.

Because advertisers are capable of exerting inﬂuence over the consumer learning
process (Hoch and Deighton, 1989), a simulated virtual experience may extend product
familiarity, affect motivation, and decrease product ambiguity, leading to elevated levels
of arousal, enhanced Shopping enjoyment, and heightened brand preference. By creating
compelling online virtual experiences with products, marketers could potentially increase
the value of product information presented, engage consumers in an active shopping
experience, increase the number of unique and repeat trafﬁc visitors for a site, and
ultimately establish an online competitive advantage. Furthermore, the potential beneﬁts
of message framing and product customization a virtual experience provides could
enhance how consumers learn by saving time and eliminating unnecessary information.

As consumers undergo psychological and emotional states while interacting with
products incorporating 3-D visualization, a virtual experience should create a compelling
online experience and facilitate consumer learning by improving decision making
(Hoffman and Novak, 1996; Novak and Hoffman, 2000). In addition, the interactive and
vivid nature of 3-D product visualization evokes mental imagery from past ideas,
feelings, and sensations (Yuille and Catchpole, 1977). The implication is that a virtual
experience is likely to have a positive impact on learning, encourage product evaluation,
affect behavior, and provide sensory and emotional experiences that can substitute for
consumption (MacInnis and Price, 1987). Li, Daugherty and Biocca (in press) emphasize
that consumers are likely to perceive the examination of products in a virtual experience
as being richer than indirect experience and closer to direct experience because of

interactivity, Vividness, mental imagery and the psychological sensation of presence.

Nevertheless, current research and theory have failed to explore completely the
multi-media dimensions of computer-mediated communication (Soukup, 2000) and what
little work has been done has not considered the inﬂuence of sequential exposure of a
virtual experience paired with indirect or direct experiences. This is surprising
considering marketing efforts do not typically rely on one method of exposure and that
sequences of experience have been demonstrated to impact consumer learning (Berger
and Mitchell, 1989; Kempf and Smith, 1998; Marks and Kamins, 1988; Smith, 1993;
Smith and Swinyard, 1983). Theoretically, the Integrated Information Response Model
emphasizes the sequence of exposure inﬂuencing consumer learning the most occurs
when indirect experience precedes direct experience. The result is that the predisposition
created by advertising is reinforced by product trial elevating consumer learning. To
fully understand the impact of a virtual experience and the use of 3-D product “
visualization in consumer learning, the unique and distinctive characteristics that
distinguish a virtual experience from indirect and direct experience must be empirically
explored. The implications of such ﬁndings could potentially provide scholars with a
better theoretical understanding of consumer psychological processes and behavior online
as well as improve the prediction for effective persuasive Internet commmtication
strategies. Therefore, the purpose of this study is to expand the theoretical knowledge of
consumer learning by testing the impact of virtual experience on sequence of exposure
relative to indirect and direct experience. This initial step is essential in order to isolate
and determine the impact of a virtual experience in conjunction with indirect and direct

experiences. In the proceeding sections I will establish the foundation of the study from a

literature review, propose a theoretical framework, provide a detailed methodology, and

conclude with implications involving this emerging area of research.

CHAPTER 2

LITERATURE REVIEW

The Internet

At the most basic level, the Internet can be deﬁned as simply a series of networks
serving to interconnect thousands of computers across the world (Bauer, 1995). It
originated in the 19605 when the Department of Defense’s Advanced Research Projects
Agency (ARPA) set out to link computers that were incompatible together so
communication with one another would be possible. The result was the formation of the
ARPANET. In 1988, the National Science Foundation (NSF) absorbed the ARPANET
and funded the creation of a much faster network called the NSF NET (Peterson,
Balasubramanian and Bronnenberg, 1997). It was also about this time that the NSFNET
and afﬁliated parties began referring to this connection of computer networks as the
Internet (Kahn, 1995). In 1992, the ANSNET, which was a backbone network privately
owned and operated, superseded the NSF NET and the Internet became available for
commercial ventures. Information then began to be organized using hypermedia as the
World Wide Web emerged (Peterson, Balasubramanian and Bronnenberg, 1997).

The creation of any new form of media is a process that develops over time.
However, in order for any new mass medium to emerge it generally must perform some
ﬁmction better than existing media. As it turns out, the Internet is the only medium of
communication where a consumer can see a product, investigate a product in detail, and
immediately purchase the product (Meeker, 1997). This ability serves as a form of two-

way interaction, unlike the one-way exposure from traditional media (Cho, 1999;

Hoffman and Novak, 1996). Hence, the potential of the lntemet is about building
customer relationships, providing customer service, efﬁciently delivering targeted
messages, and ultimately generating sales. The result is one of the fastest growing mass
media in history. Not surprisingly, as the Internet continues to grow in the number of
users, advertisers and marketers have taken notice and solidiﬁed the Internet as an
important element in the media mix.

There are several methods for advertisers and marketers to communicate with
consumers using the Internet. The most common are through e-mail, listservs, user
discussion groups, and the Web (O’Guinn, Allen and Semenik, 1998). E-mail allows
advertisers to communicate to consumers in much the same fashion as direct mail. An
advertiser can acquire the e-mail address of numerous consumers and deliver a message
to a speciﬁc targeted group. Nonetheless, this form of advertising has not yet taken hold
due to the signiﬁcant resistance in receiving these types of messages via e-mail (Bruno,
1996). Consumer perceptions remain unreceptive towards this form of persuasive
lntemet communication because e-mail accounts are perceived as private personal forms
of communication. Furthermore, resistance also stems from the fact that consumers
typically must pay for lntemet access to receive e-mail and downloading e-mail from
solicitors is perceived as wasting both the recipient’s money and time.

In turn, listservs are electronic mailing lists that people join to receive information
about a speciﬁc topic of interest. Yet, it is still considered bad taste to openly sell
products via listservs especially when there is no connection between the mailing list’s
theme and the advertised product. Alternatively, user discussion groups, commonly

referred to as usenet groups, are a collection of more than 17,000 discussion groups

connected over the lntemet. These groups allow participants to read messages, post
messages, and answer messages that all pertain to a speciﬁc topic. Like e-mail
advertising an advertiser must be very careful when communicating a message in this
manner because a backlash could provoke hate mail, resentment, and a damaged business
reputation (O’Guinn et al., 1998). On the other hand, the Web is a graphical environment
of information that makes navigation over the lntemet simple and exciting. To advertisers
and marketers, the Web holds the greatest potential because it provides the ability to
deliver detailed in-depth messages utilizing both visual and behavioral simulations 24
hours a day (O’Guinn et al., 1998). In addition, this form of lntemet advertising
functions in much the same manner as traditional advertising (television, print, radio,
etc.) resulting in higher acceptance among consumers. As in other media, ads are
inserted into existing content with the consumer deciding whether to read or pay attention
to the ad.

Ducoffe (1996) conducted one of the ﬁrst studies on lntemet advertising in an
attempt to assess consumer perception of this new medium. From a purposive sample of
over 300 Web users, lntemet advertising ranked near the bottom relative to traditional
media such as television and newspapers in terms of value. Ducoffe (1996) stressed the
beneﬁts of this medium have not been realized with lntemet advertising currently serving
as simply a form of technological direct response advertising. However, Briggs and
Hollis (1997) argue that most advertising does not evoke an immediate response and
Internet advertising is as easily able to increase awareness and strengthen a product’s
brand image as traditional advertising. To test their belief, they conducted a ﬁeld

experiment with banner ads utilizing over 1,200 participants to measure attitude and

behavior. From one banner exposure, they reported a 50 percent increase in consumer
loyalty and as high as a 200 percent increase in awareness. These ﬁndings lend support
to the idea that lntemet advertising can effectively increase consumer learning.

Hoffman and Novak (1996) emphasized the Intemet’s potential as an efﬁcient
channel for advertising, marketing, and product distribution stems from what they refer to
as a many-to-many communication medium where consumers are able to interact with as
well as create content. Hence, consumers are able to experience a psychological state
identiﬁed as ﬂow because the medium creates a sense of interactivity and enjoyment
resulting in a loss of self-consciousness. The key consequences of this experience are
increased learning, altered behaviors, and a perceived sense of control within the

computer-mediated environment (Hoffman and Novak, 1996).

Consumer Learning

Consumers learn about products through experience. An experience is more than
Simply the passive reception of external sensations or subjective mental interpretations of
an event or situation. Rather, an experience is the result of an ongoing transaction that
gains in quality, intensity, meaning, and value integrating both psychological and
emotional conditions (Mathur, 1971). These conditions are ultimately accomplished via
the generation of thoughts and/or sensations brought together creating the experience
(Hirshman, 1984). Within any experience, psychologists have identiﬁed three common
states involving mental imagery (cognitive), emotional responses (affective), and derived
intentions (conation) (Richardson, 1984). At its Simplest, an experience is an event or

process that can occur spontaneously or voluntarily within everyday Situations but always

involves the internal awareness of something taking place (Lundh, 1979). Conceptually,
every experience stems from the interaction between an individual and an object or
environment.

Researchers have delineated two main types of experience associated with
consumer learning of products or services; indirect experience and direct experience
(Deighton, 1984; Hoch and Deighton, 1989; Hoch and Ha, 1986; Kempf and Smith,
1998; Smith and Swinyard, 1982; Smith and Swinyard, 1983; Smith and Swinyard, 1988;
Wright and Lynch, 1995). While indirect experience can occur from various sources
(i.e., word of mouth, Consumer Reports, etc.), the most prevalent form explored in
consumer learning is advertising. This form of experience can lend several advantages
for both consumers and advertisers. First, advertising is a mediated experience where
messages are framed to emphasize the most important product information. Second,
advertising exposure can stimulate consumer awareness for unknown products. Third,
exposure enables consumers to evaluate important information across multiple brands in
a short amount of time. Of course, advertising is a biased form of communication that is
often perceived as less credible than direct experience (Hoch and Ha, 1989). Direct
experience is an unmediated interaction between a consumer and a brand in full sensory
capacity and occurs from product sampling, trial, or purchase (Gibson, 1966). This
multi-sensory interaction also leads to several consumer and advertiser advantages
associated with direct experience. First, evidence in direct experience is self-generated
and the most trustworthy for a consumer. Second, a consmner may manage the way a
product is experienced by controlling the focus and pace of an inspection to maximize

informational input. Third, direct experience promotes better memory because

10

information is more vivid and concrete (Hoch and Ha, 1989). Fourth, this form of
learning is more likely to inﬂuence behavior because of internal attributions and
motivation (Smith and Swinyard, 1982). However, strong implications for both indirect
and direct forms of experiences have been reported under certain circumstances.

Direct experience from product trial has been found to inﬂuence higher order
effects on consumer judgements (F azio, Chen, McDonel and Sherman, 1982; Fazio and
Zanna, 1977; Olson and Dover, 1979). Smith and Swinyard (1982) proposed an
integrated information response model outlining the processes in which indirect and
direct experiences affect consumer learning. The model implies that indirect experience
offers little inﬂuence on consumer behavior because advertising is perceived as a biased
source of information. Thus, advertising is unlikely to generate reliable attitudes
resulting in low order beliefs possibly inducing product trial. One of the key features of
this model is the distinction between trial and commitment within conation. Smith and
Swinyard (1982) state that when the perceived purchase risk is low, the low order
cognitive effects produced by advertising are more likely to result in trial or even
purchase, which then serve as an information gathering technique for further evaluation.
However, when consumers are seeking to reduce high levels of perceived risk, direct
experience will generate more conﬁdently held higher order beliefs because information
acceptance from this type of experience is considered more favorable (Smith and
Swinyard, 1982).

To test this proposition, Smith and Swinyard (1983) compared audience response
measures after direct experience with a product versus indirect experience from

advertising. The results revealed that direct experience is a strong source of information

11

for consumers and that advertising alone appears unlikely to accomplish the directional
relationship from attitude to behavior. In addition, direct experience resulted in 65% of
the subjects experiencing higher order effects compared to only 36% for advertising.
Upon further analysis, only 8% of the indirect experience subjects formed positive higher
order effects compared with 43% for direct experience. Direct experience was also found
to explain three times the amount of variance (r2=.36) between attitude and behavior than
indirect experience (r2=.11) (Smith and Swinyard, 1983).

Smith and Swinyard (1988) also replicated these ﬁndings while extending the
integrated information-response model to measure expressed interest for additional
information or what they refer to as curiosity. Once more, they found direct experience
consistently produced higher order expectancies than indirect experience from
advertising. However, because a small percentage of consumers exposed to advertising
produced higher order expectancies combined with twice as many curiosity statements
than direct experience, Smith and Swinyard (1988) concluded future research should
explore how indirect experience can create cognitive levels similar with direct
experience.

Deighton (1984) developed a two-step model of advertising effectiveness to test
how advertising is able to initiate expectations, which are to be conﬁrmed or rejected
during direct experience. While in many instances beliefs about product attributes are
often attributed as an outcome of advertising, the formation of beliefs by consumers may
not depend on any communicated message but rather the conﬁrmation of those beliefs
through product knowledge from multiple sources of information. As a result, Deighton

(1984) conducted a laboratory experiment asking participants to rate the reliability of six

12

automobile manufacturers from a combination of print ads and articles in Consumer
Reports. The results indicate that reliability was not inﬂuenced by advertising alone nor
were Consumer Reports able to affect the evaluation individually. When the
advertisements were used in conjunction with the evidence presented in the Consumer
Reports, however, product evaluations increased dramatically.

Hoch and Ha (1986) extended Deighton’s (1984) original work by examining the
conditions under which advertising can inﬂuence how and what consumers learn from
direct experience. Through two separate experiments, Hoch and Ha (1986) investigated
how consumers ﬁnd and interpret information either to support existing beliefs about
products or conﬁrm expectations induced from advertising. Using a pre- and post-test
design, participants were exposed to both test and control advertisements and allowed to
inspect available brands. The results indicated that advertising is able to inﬂuence the
assimilation of information during learning when consumers are faced with ambiguous
evidence. For instance, when participants were exposed to a test ad preceding the
corresponding brand, the advertisement extended the amount of time spent examining the
product, resulting in increased product ratings. These ﬁndings are important evidence that
the combination of advertising and direct experience can inﬂuence consumer learning.

Drawing on previous consumer learning research, Hoch and Deighton (1989)
argued that learning strictly ﬁ'om direct experience is not a simple process and therefore
is subject to inﬂuence. They proposed a four-stage model of consumer learning that is
inﬂuenced by internal and external factors: hypothesizing - exposure — encoding —
integration. The stages are neither independent from each other nor do they occur

necessarily in a ﬁxed linear sequence. Rather, they emphasize that learning is a process

13

inﬂuenced by factors such as topic familiarity, internal motivation, and the ambiguity of
the environment. Furthermore, Hoch and Deighton (1989) emphasize that advertisers
and marketers have the ability to exert inﬂuence over the consumer learning process by
understanding how consumers learn from experience. Thus, effective advertising
campaigns are capable of increasing familiarity, affecting motivation, and decreasing
product ambiguity through information while inﬂuencing consumer learning along each
stage. In a sense, an interaction between indirect and direct experience is more effective
because marketers have the power to exert control over the learning process through
brand building and consumer loyalty (Hoch and Deighton, 1989).

Wright and Lynch (1995) reﬁned the theory of advertising effects by
differentiating search from experience attributes of products. The foundation of their
research was derived from Nelson’s (1974) original distinction between search and
experience product attributes. Search attributes are qualities that can easily be veriﬁed.
such as a product’s color or price; and this veriﬁcation can take place prior to purchase.
In contrast, experience attributes are characteristics that can only be veriﬁed by direct
experience, such as how a car rides or the taste of a product (Nelson, 1974). They argued
that consumers perceive search attributes as reliable before product use whereas
experience attributes are perceived as less reliable before trial given certain types of
products. The distinction is that direct experience is more effective than advertising
(indirect) in presenting experience attribute information. However, advertising is more
effective than direct experience in presenting search attribute information (Wright and
Lynch, 1995). This proposition contradicted the emerging agreement that direct

experience is always superior to indirect experience. In a laboratory experiment designed

14

to equate a balance between search and experience attributes, Wright and Lynch (1995)
conﬁrmed that direct experience was not generally superior to advertising for
communicating product information; instead, direct experience was superior in
communicating experience attributes and advertising was superior in communicating
search attributes. Speciﬁcally, they found that belief conﬁdence was greater for
experience attributes in direct experience and higher for search attributes after exposure
to advertising.

Moore and Lutz (2000) extended consumer learning to examine how indirect and
direct experience interrelate to form brand perceptions and attitudes in children. Using a
combination of positivist and interpretivist research methods, they found signiﬁcant
inﬂuences from both direct and indirect experiences. Consistent with prior research,
direct experience from product trial led to greater cognitive and affective processing
compared to advertising exposure. However, advertising was able to inﬂuence usage
experience by shifting beliefs and attitudes of older children prior to product trial (Moore
and Lutz, 2000). Nevertheless, it has been speculated that the type of medium may limit
the effect of advertising and a more powerful medium for communicating the details and
experiences of a product, such as the Internet, could have a stronger impact on consumer
learning. For example, a print ad is traditionally limited by presenting images and text
two dimensionally relying mostly on the visual senses. Television advertising is able to
extend sensory perception by combining sight, sound and motion however consumer
interaction remains passive. In contrast, the lntemet is able to combine elements found in
traditional forms of advertising with interactivity and user control to potentially produce a

stronger experience.

15

Virtual Experience

The lntemet has the ability to serve as a more powerful medium than traditional
print and broadcast media in the sense that consumers are able to interact with products in
3-D multimedia environments, thus simulating a new form of experience — virtual
experience. The conceptualization of a virtual experience has emerged because
technological developments indicate a movement toward more multi-sensory interactions
incorporating high quality visuals, stereo sound, and 3-D image (S ukup, 2000).
Information and graphics can now be presented in a mediated 3-D environment in which
consumers can interact with images, animated graphics, video, and audio. Klein (1998)
suggests the greatest value of a virtual experience is that it allows consumers to assess
product performance prior to purchase, essentially turning experience goods into search
goods. The consumer value of interactive media is that information is now more
accessible, less costly, and more customizable. By transforming experience attributes
into search attributes, a virtual experience could be perceived as being equivalent to a
direct experience and thus reduce perceived risk prior to purchase (Klein, 1998). The
premise is that experience goods have traditionally been suited for product trial and
search goods for advertising with the best medium remaining the one that communicates
the type of product information that is the most congruent (Wright and Lynch, 1995).
Yet, a virtual experience can moderate direct and indirect experience enabling marketers
to reap the beneﬁts of both types of experiences (Li, Daugherty and Biocca, 2001a).

As the notion of virtual experience evolves, vivid and imagery-based associations
are more likely to generate richer experiences and enjoy advantages of both direct and

indirect experience. Like traditional ads, 3-D product visualization enables consumers to

16

form prior hypotheses by framing information presented. However, different from
traditional forms of advertising, dynamic 3-D visualization of products is able to offer
user control over the inspection of a product, even from inside out for certain types of
products. This is an important advantage because high information control in ecommerce
environments has been found to improve consumer decision quality and knowledge
(Ariely, 2000). In fact, this type of control positions a virtual experience similarly to
direct experience because consumers are able to inspect 3-D products from different
perspectives at their own pace. This level of control is not simply a representation of an
actual product but rather a simulation of the consumption experience. The result is a
stronger impact for experience attributes compared to advertising and greater impact for
search attributes relative to product trial. Nevertheless, a major disadvantage associated
with virtual experience is the limited sensory input compared to direct experience. At
present, consumers are not able to touch, smell or taste a product on the computer even
though these actions will soon be likely with the invention of the “force-feedback”
technology (Grossman, 2000).

In an exploratory study, Li, Daugherty and Biocca (in press) addressed what
constitutes a virtual experience in order to identify key characteristics of this new type of
experience. From a sample of 30 subjects, participants were asked to verbalize what they
were thinking and feeling while interacting with 3-D products in an ecommerce
environment. The results indicate that consumers undergo similar psychological
processing when examining products in a virtual experience as in a direct experience.

Furthermore, several characteristics associated with a virtual experience were classiﬁed,

17

such as interactive enjoyment, presence, virtual affordances, and personal relevance from

interacting with 3-D visual products (Li, Daugherty and Biocca, in press).

Interactivity and Vividness

Interactivity is a multidimensional construct that can refer to numerous methods
in which users of a medium can inﬂuence the form or content of a mediated environment
(Ariely, 2000; Haubl and Trifts, 2000; Heeter, 2000). In computer-mediated
environments, interactivity has been described as both the ability to communicate with
people (person interactivity) and access information (machine interactivity) (Hoffman
and Novak, 1996). While interpersonal communication is an important advantage of the
lntemet compared to traditional media (i.e., e-mail, chatrooms, etc.), interface design and
the manner in which information is accessed are most applicable in 3-D product
visualization. In fact, the goal of many designed experiences in computer-mediated
environments is to impact, involve, and/or enable human interaction as easy as possible
(Heeter, 2000). Haubl and Trifts (2000) found that interactive design aids in ecommerce
environments have a substantial inﬂuence on consumer decision making. While their
study focused on breadth and comparisons of products in online shopping environments,
they emphasized that their results should apply across various dimensions of interactivity,
such as 3-D product visualization (Haubl and Trifts, 2000).

In turn, Vividness refers to the clarity and ability of an image to produce a sensory
rich mediated experience and is generally thought to be more persuasive. However,
studies in this area have not produced consistent ﬁndings. Furthermore, a signiﬁcant

limitation in comparison to a virtual experience is that most research investigating

18

Vividness is based on either semantics or passive imagery (Keller and Block, 1997). In a
study speciﬁcally designed to test the effects of verbal product representations versus
vivid computer realistic images, Vriens, Loosschilder, Rosbergen, and Wittink (1998)
found that pictorial representations improved understanding of design attributes.
However, they emphasized that a higher degree of realism is possible with 3-D rendered
products and would probably result in a stronger impact. Dahan and Srinivasan (2000)
set out to test this proposition in order to identify a low—cost alternative for new product
testing. Using a portable bicycle pump as the product category, actual physical products
were measured against static and animated Web representations to predict overall market
share. Surprisingly, the static and animated Web representations produced nearly
accurate market share rankings compared to direct product experience. While predicted
levels of market share were lower than the physical interaction, virtual prototypes cost
signiﬁcantly less to build and allow more concepts to be tested (Dahan and Srinivasan,
2000).

Theoretically, the interactive and vivid nature of 3-D product visualization
stimulates mental imagery within consumers in a virtual experience. Fundamentally,
imagery is evoked from the sensory experiences in memory from past ideas, feelings, and
sensations (Yuille and Catchpole, 1977). The implication from a virtual experience
context is that imagery processing is likely to have a positive impact on learning,
encourage product evaluation, affect behavior, and provide sensory and emotional
experiences that can substitute for consumption (Maclnnis and Price, 1987). The result is
heightened perception from the experience serving as a Simulation heuristic generated

from the imagery created (Schlosser and Kanfer, 2001). Thus, the more interactive and

19

vivid a 3-D product experience the richer mental imagery generated. As a result,
Interactive advertising in 3-D visualization is potentially superior over those in 2-D
graphics, a main form of advertising on the Web at present. Compared to traditional
advertising, advertising utilizing 2-D graphics common in banner ads and Web Sites is
interactive in the sense that consumers may click to ﬁnd whatever information they need
about products in real time. However, 2-D graphics are limited in terms of the degree of
interactivity because they do not allow consumers to experience a product by inspecting
it from different viewpoints. This limitation is overcome in 3-D product visualization,
where consumers are able to examine products freely just as they would in a conventional
store. In fact, the possibility to examine and modify the viewpoint in a virtual
environment creates a sense of control and has been found to increase the sense of

presence (Schubert, Regenrecht and Friedmann, 2000).

Presence

The combination of Vividness, interactivity, and sensory stimuli combine to create
a sense of presence in virtual experience. Presence, also known as telepresence, is the
experience of “being there” in the virtual environment. This perceived sense is generated
from sensory input, mental processes, and past experiences assimilated together in a
current state (Gibson, 1966). Steuer (1992) described presence as the extent to which one
feels present in a mediated environment. All media and telecommunication systems
generate a sense of being in another place by bringing the experience and objects closer
to us, allowing us indirectly to meet and experience other objects, other people, and the

experiences of others. A medium functions the best when it delivers not only information

20

but also a mediated experience. Although presence is the design goal of virtual reality,
few media theorists would argue that the sense of presence is suddenly emerging with the
debut of virtual reality, which consists of both immersive and non-immersive 3-D
visualization (Biocca, Kim and Levy, 1995). Rather, researchers see the illusion of
presence as a product of all media (Reeves and Nass, 1996), and virtual reality is a
medium that can generate the most compelling sense of presence (Biocca, 1997).

According to Biocca (1997),

When we experience our everyday sense of presence in the physical world, we

automatically generate a mental model of an external space from patterns of

energy on the sensory organs. In virtual environments, patterns of energy that
stimulate the structure to those experienced in the physical environment are used
to activate the same automatic perceptual processes that generate our stable
perception of the physical world.

Presence can be generated in a Shopper when she is interacting with either a
virtual product or a virtual environment. For instance, when a Shopper surfs through the
aisles of a virtual store she may feel as if she is walking in a conventional store. Further,
a shopper who picks up a brand from a virtual shelf has the ability to take a closer look
by zooming-in or rotating the product much as if she was examining a brand in a real
store. Shoppers are likely to gain a unique experience when they feel physically present
in such an environment. Consumer interaction with products in a virtual environment is
only one aspect of virtual experience. Tauber (1972) distinguished three activities in the
area of consumer behavior: shopping, buying, and consuming. In a conventional mall,
Shoppers may view window displays, chat with a friend or a salesperson, and see other
shoppers in addition to inspecting individual products and trying out some features of a

product. A virtual ecommerce environment is able to simulate much of these same

experiences with presence mediating the persuasive impact.

21

By manipulating the sensory saturation of a consumer’s visual perception, Kim
and Biocca (1997) were able to detect signiﬁcant differences in conﬁdence levels
regarding brand preference. More speciﬁcally, the sense of presence resulted in a
stronger experience with subjects becoming more conﬁdent in their attitudes toward the
product information presented. Kim and Biocca (1997) concluded that the virtual
experience created by presence simulated a direct experience resulting in increased
persuasion. This ﬁnding supports previous research that indicates the sense of presence
created in a mediated environment will cause a user to believe the experience occurred

ﬁrst hand, resulting in the same effect as direct experience (Lombard, 1995).

Virtual A ﬂordances

Consumers inspect products in the conventional store following norms. When
they select a computer, they may turn it on to see the color of the monitor screen or
launch a program; however, they normally do not request to open the case to see what is
inside. When consumers select chairs, they are likely to sit on them but less likely to
stand on them. This type of expected interaction between consumers and products is
referred to as affordances (Schuemie and Mast, 1999). The affordances of any product
represent the perceptual cues that inﬂuence how consumers expect to interact during
direct experience. Norman (1998) explained, when we assess our immediate ‘
environment, we are aware of some of the affordances each object offers. For instance,
chairs are to sit on, doors to open or close, and lights to illuminate. An affordance is not
a property of an object as much as it is a relationship between an object and the organism

that is acting on the object. Heeter (2000) further noted, “In the design of experiences,

22

real affordances are not nearly so important as perceived ones; it is perceived affordances
that tell the user what actions can be performed on an object and, to some extent, how to
do them.”

There are various affordances common to product inspection in conventional
stores that come from the ability of the senses and motor systems to interact with
products. The ability to visually inspect a product contains some of the most common
types of affordances. Consumers learn about the Shapes, texture, and perceived functions
of a product by moving their bodies or the product to visually inspect it from different
angles. This type of information and interaction can be Simulated vividly within a 3-D
environment, where consumers can freely examine, zoom-in or zoom-out, and rotate a
product based on virtual product affordances. The perceived virtual affordances created
in 3-D product visualization are what distinguish virtual experience from an indirect
experience commonly found in traditional advertising (Li, Daugherty and Biocca, in
press).

The examination of how consumers interact with products in 3-D visualization
also suggests several basic ways of interaction called interfaces. These properties are
what help generate the affordances needed to establish a virtual experience with a product
in a virtual environment. Common in human-computer interaction literature, the success
in designing effective interfaces stems from creating appropriate affordances a user
expects in new multi-sensory computer-mediated environments (Karat, Karat, and
Ukelson, 2000). Previous communication research has addressed the role of certain
interfaces in the cognitive process. For instance, Reeves and Nass (1996) note that larger

images likely are more arousing, better remembered, and better liked than small images.

23

This ﬁnding implies the potential impact of zooming-in for inspection of 3-D visual
products. Hoffman and Novak’s (1996) elaboration of the ﬂow theory indicates the
cognitive impact of seamless sequence of responses facilitated by interactivity with the
computer and self-reinforcement, which lends support for the effect of the navigating
interface. Li, Daugherty, and Biocca (2001b) recently examined the impact of virtual
affordances and found consumer learning is enhanced when visual affordances associated
with a virtual experience enhance a consumer’s ability to acquire knowledge, form
attitudes, and inﬂuence behavior over tactile and behavioral affordances. These studies
and others (Biocca, 1997, Lombard and Dittion, 1997; Steuer, 1992,) have justiﬁed the

potential impact of interfaces in 3-D visualization in ecommerce.

Personal Relevance

In order for any consumer to perceive and evaluate a product actively, it must
hold some form of personal relevance. Krugman (1965) referred to this as a type of
involvement. The construct of involvement has been heavily explored by advertising
researchers resulting in a diverse number of conceptual approaches (Andrews, Akhter,
Durvasula and Muehling, 1992). Studies have deﬁned, examined, measured, and tested
involvement using both a theoretical and practical context to examine products,
messages, decisions, situations, and psychological states (Muehling, Laczniak and
Andrews, 1993). Hence, involvement continues to remain a signiﬁcant inﬂuence in the
processing of information (Bettman, 1979).

In examining the effects of advertising on involvement, the majority of research

has focused on situational manipulations of the construct (Laczniak, Kempf and

24

Muehling, 1999). However, recent research suggests that this traditional method may
result in inconsistent conclusions, with more permanent inﬂuences, such as product class
involvement, likely to produce stronger effects (Laczniak and Muehling, 1993; Andrews
et al., 1992; Celsi and Olson, 1988). In an attempt to understand the inﬂuence of these
different manipulations, Laczniak, Kempf and Muehling (1999) conducted a laboratory
experiment investigating the impact of product class, product knowledge, and situational
involvement on advertising. The results support the assertion that situational
manipulations of involvement levels may not be successful, and more enduring product
class involvement measures should be used in testing advertising experiments.

Cho (I999) recognized the importance of involvement in an lntemet advertising
study designed to explore the inﬂuence on information processing. The purpose of the
investigation was to test a modiﬁed version of Petty and Cacioppo's (1981) Elaboration
Likelihood Model developed for the lntemet. The Elaboration Likelihood Model (ELM)
speciﬁes conditions under which persuasion is mediated by messages and postulates that
central and peripheral routes inﬂuence persuasion. Elaboration refers to the extent in
which consumers process persuasive communication. For instance, when motivation is
high elaboration likelihood is said to be high and consumers follow the central route of
persuasion and inﬂuenced by argument-based messages. When motivation is low then
elaboration likelihood is low and consumers are inﬂuenced by the peripheral route of
persuasion, such as source attractiveness and heuristic cues (Petty and Cacioppo, 1981).
The results of Cho’s (I999) interpretation using ELM indicate that subjects are more
likely to initiate a behavioral response for high involvement products than low

involvement on the lntemet.

25

Furthermore, in a virtual experience, personal engagement is activated when
examining 3-D visual products with various levels of cognitive processing stimulating
involvement. As a result, consumers tend to perceive 3-D products as being realistic
enough to evaluate the potential beneﬁts and utility for others (Li, Daugherty and Biocca,

in press).

26

CHAPTER 3

THEORETICAL FRAMEWORK

Smith and Swinyard (1982) developed anintegrated IBfQUDEILCLEBE§PPESﬁM§el
of advertising response sequence detailing how indirect and direct experiences interact to
inﬂuence cognitive, affective, and conative effects in consumer learning. The model
illustrates exposure to advertising typically generates lower order beliefs leading to
awareness and trial. This is based on the premise that consumers do not have direct
contact or experience with a product from inspecting an advertisement. The result is low
order beliefs formed from the initial awareness are generated. “When trial is inducedvfrom
”lower PISEEPSJIEES it represents an attempt by the consumer to move toward higher order
beliefs via direct experience. This is common for low involvement inexpensive
purchases where the risk is minimal and trial before commitment offers the best means
for acquiring information (1982). In contrast, when consumers seek to reduce uncertainty
for high risk involving type products, higher order beliefs are formed primarily from
direct experience. The higher ”9.1;derbﬁeliefs, result from direct experience because
physical trial serves to reduce uncertainty and risk. The distinction between high and low
order beliefs depends on the level of involvement and personal relevance with the
product.

The model also indicates that under certain circumstances indirect experience
from advertising can lead to higher order beliefs (1982). Previous research has detailed

that higher order beliefs are generated from advertising for products high in search

attributes relying less on direct experience(Wright and Lynch, 1995). Numerous ﬁndings

27

have supported this model (Marks and Kamins, 1988; Moore and Lutz, 2000; Smith and
Swinyard, 1983; Smith, 1993; Wright and Lynch, 1995).

Theoretically, virtual experience is a vivid, involving, active, and affective
psychological state consumers encounter when interacting with 3-D products in a
computer-mediated environment (Li, Daugherty and Biocca, in press). Since virtual
experience incorporates elements of both indirect and direct experience, it intervenes
these constructs along the spectrum of consumer learning (see Figure I). For instance,
both indirect and virtual experiences are mediated occurrences that provide marketers the
ability to deliver persuasive forms of communication. In most instances however,
interactive advertising, such as 3-D product visualization, provides richer experiences
than indirect experience, including traditional advertising. Similarly, virtual experience
is also able to resemble direct experience since both provide elements of interactivity
with products. For example, the ability to visually inspect a product from all angles is
easily simulated in a 3-D environment. In addition, like direct product experience, 3-D
virtual experiences allow consumers to examine products from varying distances by
zooming-in or out during inspection (Li, Daugherty and Biocca, 2001a; 2001b).

Previous research has demonstrated that consumers are generally more conﬁdent
about evaluations when examining experiential products from direct experience and
search products from indirect experience (Wright and Lynch, 1995). However, a virtual
3-D product experience has the ability to moderate these differences and simulate
elements of both search and experience products. This occurs because virtual experience
incorporates elements of both indirect and direct experiences exceeding the limits of each

by allowing advertisers to frame product messages, provide visual simulations using

28

movement and animation, and alter products via customization. For instance, automobile
consumers browsing online can receive detailed information about engine speciﬁcations
by moving the mouse over a component, simulate the opening and closing of
compartments, and even change the color of a 3-D interactive automobile. Furthermore,
virtual experience has the ability to display all relevant information while arranging for
consumers to hear the sound of the road as they examine the tire speciﬁcations or listen to
their favorite song as they evaluate the CD player. The key for generating conﬁdently
held higher order beliefs in virtual experience is for perceived affordances of 3-D
visualizations to match or exceed physical affordances from direct experience (Li,
Daugherty and Biocca, 2001b). Thus, a virtual experience is able to incorporate beneﬁts
of both indirect and direct experiences in consumer learning, which is perhaps the

strongest advantage (see Figure 2).

Figure 1. Theoretical Spectrum of Consumer Learning

 

4 $

 

 

 

 

 

 

 

 

 

Indirect Virtual Experience Direct Experience

 

 

 

 

4

Consumer

 

 

 

 

29

Helping consumers learn has proven to be an efﬁcient marketing communication
objective and has led to the long-term proﬁt performance of many ﬁrms (Wemerfelt,
1996). As a result, measuring the effects of consumer learning should be the ultimate
goal for identifying consequences associated with interactive 3-D forms of product
advertising. In fact, greater perceptual product salience via the use of color, three
dimensions, and sound (Hutchinson and Alba, 1991) as well as interactive and vivid
content on the lntemet have been linked to increased learning (Hoffman and Novak,
1997; Hoffman and Novak, 1996). Traditionally, effective consumer learning is assumed
to be a critical mediator of consumption and ascertained from cognitive, affective, and/or
conative dimensions (Hutchinson and Alba, 1991; Lutz, 1975; Wright and Rip, 1980).
Likewise, numerous techniques for measuring advertising effectiveness are intended to
examine components of an ad from the same domains (Beerli and Santana, 1999;
Ehrenberg, 1974; Lavidge and Steiner, 1961; MacInnis and Jarworski, 1989; Petty and
Cacioppo, I981).

\Cognrtrve measures'are used to determrne the abIlIty of an advertisement, phySIcal

”pa-inn.“ a” —-

 

product, or other marketing stimulus to attract attention and ultimately transfer
information to memory. This element is fundamental in generating awareness,
establishing product knowledge, and increasing comprehension of the brand name of any
product. In addition, research has demonstrated that marketing communications are able
to inﬂuence cognitive experiences associated with consumer learning (Braun, 1999; Hoch
and Ha, 1986; Smith, 1993). Similarly, forms of interactive marketing communication

that allow control over the ﬂow of information, such as the 3-D visualization of products,

30

increase a consumer's cognitive ability to integrate, retain, and understand the
information presented (Ariely, 2000; Hoffman and Novak, 1997).

Affective measures are used to identify either established and/or created attitudes

'V'IL

 

from a marketing stimulus and/or direct product experience. The premise behind this
measure is that advertisements and experiences which are the most pleasing and
informative produce a positive transfer effect, and are better received among consumers
(Mehta, 2000). Research has shown that consumer learning styles are inﬂuenced by
attitudes (Mantel and Kardes, 1999) with attitude towards the brand serving as a
commonly used effectiveness measure in advertising (Gardner, 1985; Lutz, 1985; Batra
and Ray, 1986; Fazio, Powell and Williams, 1989; MacKenzie and Lutz, 1989). The
assumption is often that attribute based comparisons between products are what inﬂuence
consumer attitudes and decisions. However, in many instances an overall attitude-based
evaluation involving intuitions, heuristics, and general impressions about a product or
brand are made and relied upon in consumer decision making (Mantel and Kardes, 1999).
Furthermore, the importance of attitudes and the relevant measures have been linked to
evaluating the effectiveness of ecommerce sites (Chen and Wells, 1999).

Conative measures are used to anticipate a behavioral response resulting from a

W. ”-
A‘F,L.. “m~.,, F.“ L “- ‘1‘

marketing stimulus and/or product experience. Within consumer learning, conative
measures generally involve some type of behavioral intention, such as searching for
additional information, or purchase (Brucks, 1985; Hoch and Ha, 1986; Levin and Gaeth,
1988). This method commonly involves asking subjects to evaluate stimulus material

and then indicate a behavioral response. The most widely used conative measure in

31

advertising effectiveness research is intention to purchase (Beerli and Santanal, 1999;

Andrews et. al., 1992).

Figure 2. Integrated Information Response Model Incorporating Virtual Experience

 

Information Information
Source Acceptance Cognitions Affect Conation

 

Indirect ’ Low . Lower . Lower . Trial

Exnerience Order Order
‘\ Beliefs Affect

i \x

Direct . Hig . Higher . Higher . Commitment

 

Exnerience Order Order
A Beliefs Affect
I
l
I
I. .........................................................................
I
I
I
I
Virtual ________ Low ______ Lower/ ____ Lower/ _____ Trial/
Exnerience > > Order + Order > Commitment
Beliefs Affect

 

Li, Daugherty and Biocca (2001b) empirically tested the impact of consumer
learning on 3-D interactive advertising in an ecommerce environment and found that
consumer learning, measured from the cognitive, affective, and conative domains, is
enhanced when visual and behavioral affordances are appropriately simulated for the
right product. As a result, these characteristics of 3-D product visualization are likely to
further promote consumer learning. Biocca, Daugherty, and Li (2001) extended these

ﬁndings and veriﬁed that a virtual experience increases the sense of presence compared

32

to indirect experience. Furthermore, the results support the overall proposition that a
positive relationship exists between presence and the cognitive, affective, and conative
effectiveness measures.

While comparing the individual differences between indirect, virtual and direct
experience is an important ﬁrst step, previous research on 3-D product visualization and
virtual experience has failed to consider the inﬂuence of sequential exposure relative to
indirect experience and direct experience. Nevertheless, the sequence of exposure for
product experience has been shown to impact consumer learning (Marks and Kamins,
1988; Kempf and Smith, 1998; Smith, 1993; Smith and Swinyard, 1983). More
speciﬁcally, indirect experience preceding direct experience is more inﬂuential than if
direct experience precedes indirect experience (Marks and Kamins, 1988; Moore and
Lutz, 2000; Smith and Swinyard, 1983; Smith, 1993). Essentially, the predisposition
created by advertising is reinforced by product trial elevating consumer learning.
However, when product trial precedes advertising the conﬁdently held higher order
beliefs formed from direct experience overshadow the indirect experience. limiting the
overall evaluation. From an advertising perspective, the theoretical sequence of exposure
enhancing consumer learning the most occurs when indirect experience precedes direct
experience, and as a result this sequence of exposure will serve as the basis of
comparison for this research.

H1: Exposure to an indirect->direct experience sequence will result in (a)

greater product knowledge, (b) a more favorable brand attitude, and (c)
elevated purchase intent than exposure to a direct—>indirect experience

sequence.
The purpose of this study is to expand the theoretical knowledge of consumer

learning by testing the impact of virtual experience on sequence of exposure relative to

33

indirect and direct experience. Obviously, there are other factors that mediate this

relationship, such as the type of advertising message (positive/negative), yet this initial

step is to introduce virtual experience and measure the impact on consumer learning

before manipulating additional variables.

Table 1 illustrates all of the possible paired combinations when supplementing

virtual experience with indirect and direct experience. Furthermore, the diagonal cells 1,

5, and 9 symbolize sequences of exposure theoretically irrelevant for this study because

they represent frequency of exposure of the same experience rather than the sequential

interaction between indirect, direct and virtual experiences, which will not be

manipulated.

Table 1. Sequences of Exposure

 

 

 

 

 

 

 

Indirect Virtual Direct
Experience Experience Experience
Indirect I _, II I __’ V2 I _, D3
ExperIence
V‘m’ail V—>I4 v—>v5 V—>D6
Expertence
DII'CCI. D _’ I7 D _) V8 D _, D9
Experience

 

 

 

Assuming personal preferences are held constant, consumers are likely to

perceive the examination of products in a virtual experience richer than indirect

experience and closer to direct experience because of interactivity, Vividness,

involvement, presence and virtual affordances (Biocca, Li and Daugherty, 2001; Li,

34

Daugherty and Biocca, 2001a; 2001b; in press). Therefore, the impact of virtual
experience on sequence of exposure will emulate the inﬂuence expected from a direct

experience resulting in the following hypotheses.

H2: Exposure to an indirect—tdirect experience sequence will result in no
difference (a) in product knowledge, (b) brand attitude, and (0) purchase
intent than exposure to an indirect—>virtual experience sequence.

H3: Exposure to a direct->indirect experience sequence will result in no
difference (a) in product knowledge, (b) brand attitude, and (c) purchase
intent than exposure to a virtual—*indirect experience sequence.

H4 Exposure to an indirect—>direct experience sequence will result in (a)
greater product knowledge, (b) a more favorable brand attitude, and (c)
elevated purchase intent than exposure to a virtual-aindirect experience
sequence.

 

H5: Exposure to an indirect—>virtual experience sequence will result in (a)
greater product knowledge, (b) a more favorable brand attitude, and (c)
elevated purchase intent than exposure to a direct-*indirect experience
sequence.

H6: Exposure to an indirect—*virtual experience sequence will result in (a)
greater product knowledge, (b) a more favorable brand attitude, and (c)
elevated purchase intent than exposure to a virtual—>indirect experience
sequence.

There has been a considerable amount of research supporting the proposition that
cognitive, affective, and conative measures are inﬂuenced by repeated exposure from
both direct experience and indirect experience (Batra and Ray, 1986; Cacioppo and Petty,
1979; Fazio et al., 1982; Mitchell and Olsen, 1977). For instance, Fazio et al. (1982)
found that attitudes based on direct experience are more accessible from memory and
more predictive of behavior when exposure is repeated. Research investigating the

inﬂuence of advertising has also demonstrated positive inﬂuences associated with

frequency of exposure (Berger and Mitchell, 1989; Sawyer, 1981). The overall

35

proposition is that repeated exposure in evaluative terms allows individuals to process

more information thus inﬂuencing consumer learning. Berger and Mitchell (1989)

demonstrated that exposure to a single direct experience resulted in more conﬁdently held

beliefs compared to a single indirect experience. Since virtual experience is theoretically

closer to direct experience, any sequential exposure involving virtual and direct

experience will increase consumer learning over sequences containing indirect

experience because virtual experience emulates more closely a direct product experience,

thus repeating exposure (see Table 2 for a complete summary of the hypotheses).

H7:

H8:

H9:

H10:

H11:

H12:

H13:

Exposure to a virtual—*direct experience sequence will result in (a) greater
product knowledge, (b) a more favorable brand attitude, and (c) elevated
purchase intent than exposure to a direct—>indirect experience sequence.

Exposure to a direct—wirtual experience sequence will result in (a) greater
product knowledge, (b) a more favorable brand attitude, and (c) elevated
purchase intent than exposure to a direct—>indirect experience sequence.

Exposure to a virtual—adirect experience sequence will result in (a) greater
product knowledge, (b) a more favorable brand attitude, and (c) elevated
purchase intent than exposure to an indirect->direct experience sequence.

Exposure to a direct—>virtual experience sequence will result in (a) greater
product knowledge, (b) a more favorable brand attitude, and (c) elevated
purchase intent than exposure to an indirect—>direct experience sequence.

Exposure to a virtual—>direct experience sequence will result in (a) greater
product knowledge, (b) a more favorable brand attitude, and (c) elevated
purchase intent than exposure to a virtual-aindirect experience sequence.

Exposure to a direct—>virtual experience sequence will result in (a) greater
product knowledge, (b) a more favorable brand attitude, and (c) elevated
purchase intent than exposure to a virtual—>indirect experience sequence.

Exposure to a virtual—adirect experience sequence will result in (a) greater

product knowledge, (b) a more favorable brand attitude, and (c) elevated
purchase intent than exposure to an indirect->virtual experience sequence.

36

H14: Exposure to a direct->virtual experience sequence will result in (a) greater
product knowledge, (b) a more favorable brand attitude, and (c) elevated
purchase intent than exposure to an indirect—>virtual experience sequence.

H15: Exposure to a virtual—>direct experience sequence will result in (a) greater

product knowledge, (b) a more favorable brand attitude, and (c) elevated
purchase intent than exposure to a direct—*virtual experience sequence.

Table 2. Summary of Hypotheses

 

Sequences of H Sequences of Sequences of

H Exposure Exposure Exposure

 

H1 I—>D > D—>I H6 I->V > V->I H11 V-+D > V—al

H3 I—aD at I—>V H7 V—aD > D-+I H12 D—>V > V—PI

H4 D—->I at V->I H8 D->V > D—al H13 V->D > I->V

H2 I—PD > V—al H9 V—PD > I—>D H14 D-PV > I—PV

H5 I—>V > D—>I H10 D—>V > I—PD H15 V—PD > D—>V

 

 

 

 

 

 

 

 

37

CHAPTER 4

METHODOLOGY

In order to investigate the implications of virtual experience within the framework
of consumer learning, the impact of sequence of exposure will be explored on the
cognitive, affective, and conative domains. The study extends the existing knowledge of
consumer learning by expanding on sequence of exposure to include the impact of virtual

experience relatively paired with indirect and direct product experiences.

Experiment Design

To test the hypotheses, _a between-subjects design was used with the type of
product evaluation experience(indirect, direct and virtual) paired together and
sequentially alternated resulting ilsiritest’conditions. Traditional advertising
effectiveness measures corresponding with the affective, cognitive and conative domains,
such as product knowledge, brand attitude, and purchase intent served as the dependent
variables (Beerli and Santana, 1999; Ehrenberg, 1974; Lavidge and Steiner, 1961;
Maclnnis and Jarworski, I989; Petty and Cacioppo, 1981).

An experimental design was selected for this study because the foremost goal is to
test theoretical propositions while expanding the body of knowledge through theory
construction. Therefore, the deductive and inductive testing of research hypotheses using
an experimental design provides the greatest amount of control and explicative power. In
addition, a between-subjects design was selected because it permits the manipulation of

more than one independent variable while calculating the inﬂuence of each independent

38

variable separately. As a result, this type of analysis easily indicates the presence or

absence of treatment effects within a single assessment.

Participants

A total of 166 undergraduate students enrolled at a major Midwestern university
participated in the experiment. The use of a student sample was deemed acceptable given
the nature of the study and product. For instance, to test the effects of a virtual
experience utilizing a 3-D product, participants were required to have prior computer
knowledge and an understanding of lntemet principles. Power analysis using the
Pearson-Hartley charts indicates the sample size was adequate to detect signiﬁcant effects

at the .05 level with a power of .90 (Keppel, 1991, p.76).

Independent Variables

The independent variables were manipulated as sequence of exposure involving a
paired combination of indirect experience (mediated traditional print advertising), virtual
experience (mediated interactive 3-D advertising), and direct experience (unmediated
product trial). The paired combination of two out of the three types of experiences was
essential to isolate and determine the impact of a virtual experience relative to indirect
and direct product experiences. Furthermore, this method allows for comparisons across
previous research testing the sequential impact of indirect and direct product experiences.
The sequence of exposure was easily manipulated by alternating the order in which
participants were exposed to the stimulus material. For instance, in the virtual experience

participants evaluated the test product via two conditions: virtual-direct sequential

39

exposure or virtual-indirect sequential exposure. For the direct experience, participants
also evaluated the test product via two conditions: direct-virtual sequential exposure or
direct-indirect sequential exposure. In turn, participants evaluated the test product in the
indirect experience condition via two methods: indirect-direct sequential exposure or

indirect-virtual sequential exposure.

Stimulus

Product

To investigate the sequential exposure of a virtual experience paired with either
an indirect or direct product experience, the test product needed (1) to be effectively
represented in each type of experience, (2) require participants to engage in information
processing, (3) contain both search and experience attributes (3) and represent an
impartial brand of interest. The ﬁrst parameter stems from the need to minimize the
differences between the stimulus materials in order to properly isolate the type of
experience as the inﬂuencing variable. Thus, the presentation of the product needed to be
as identical as possible throughout all of the conditions, with the only differences
stemming from the inherent features of each experience.

The second parameter was necessary to engage the participants in active
processing for evaluation of the test product. This is commonly achieved in consumer
behavior research by manipulating product class or situational levels of involvement
(Laczniak, Kempf and Muehling, 1999). Previous research investigating the impact of
experience in consumer learning has indicated a higher level of involvement should

produce more evaluative processes (Marks and Kamins, 1988; Smith and Swinyard,

40

1982). High involvement is deﬁned as any product requiring extensive information
gathering and problem solving from a consumer to make a purchase decision (Schiffman
and Kanuk, 1997). Therefore, the key is to successfully identify a product requiring
extensive cognitive processing.

The third requirement was important in order to balance the expected evaluation
criteria to prevent biasing one type of experience over another. Numerous products were
evaluated and considered (i.e., ring, watch, bedding material, computer, cellular
telephone, headphones, cereal, etc.) prior to the selection of a digital video camera as the
test product. A digital video camera was judge appropriate because it represents a high
involvement purchase item that can be evaluated using both experience attributes (i.e.,
weight, size, visual clarity, etc.) and search attributes (i.e. price, warranty, special effect
features, etc.). The fourth requirement was essential in order to minimize any
preconceived response bias.

A pretest (n=76) identiﬁed a digital video camcorder as a suitable test product for
the experiment. Using a six-item seven-point scale constructed from successfully tested
items for determining levels of involvement (Zaichkowsky, 1985), participants were
asked to rate the decision if they were going to purchase a digital video camcorder
(unimportant/important, of no concern, of concern to me, irrelevant/relevant, means a lot
to me/means nothing, doesn't matter/matters to me, insigniﬁcant/signiﬁcant to me) (see
Appendix A). The results indicated that participants overall felt a digital video
camcorder is slightly above-average in product purchase involvement (M = 4.11, SD =
1.11) (or = .90). To increase the legitimacy of the study, a reputable digital video

camcorder company (Panasonic) was selected and tested for preference against four

41

additional leading manufacturers (Sony, JV C, Canon, and Sharp). Participants were
asked to rate the perceived quality of each of the aforementioned digital video camcorder
brands using a seven-point scale (low quality/high quality). Pretest results showed that

Sony (M = 6.04, SD = 1.03) and Canon (M = 5.16, S_D = 1.06) were perceived as the two

 

highest quality brands of digital video camcorders presented with Panasonic (M = 4.88,
SD = 1.18) rated slightly ahead of Sharp (M = 4.59, SD = 1.40) and JVC (M = 4.33, SD =

1.41).

Materials
The ﬁrst step in developing the stimulus materials was to identify salient product

attributes using a free-elicitation technique recommended bﬁishbein and Ajzen (.1975).

'W
MH‘o—i"

 

and common in consumer learning research (Kempf and Smith, 1998; Smith, 1993).

During the pretestlparticipants were asked to write down the most important product
attributes they would consider when buying a digital video camcorder. A total of 27
different attributes were listed with an average of 5.18 per participant. Price was the
most salient attribute listed (70%) followed by size and weight (66%), special effects
such as zoom (47%), quality (43%), ease of use (41%), brand name (38%), warranty
(3 8%), video clarity (36%), and battery length (24%).

The results of the freeyelicitation technique were used to design the virtual,
indirect, and direct experience stimulus materials. Because the purpose of the study was
to isolate each experience and investigate the sequential impact of exposure, the message
content served as a control with the information held constant across each experience.

Furthermore, the message appeal was positively framed, using phrases such as “crystal

42

clear detail” and “easy to use functionality,” and combined with an informative approach
derived from the pretest of salient attributes. In addition, the Panasonic logo, slogan and
graphic image of the product were placed in identical locations throughout the stimuli.

However, there are inherent differences associated with each experience that
distinguish the stimuli. The 3-D product Web site, representing the virtual experience,
provided the ability to rotate and control product movement from all angles, allowed
users to zoom-in and out for detailed inspection, used animation to simulate movement of
the LCD display, and identiﬁed each component as the mouse moved over the product.
Each of these interactive features was identiﬁed from previous research as creating an
effective virtual experience (Li, Daugherty and Biocca 2001a; 2001b, in press).

For the indirect experience, a professionally produced two-page full spread four-
color print advertisement identical in layout and content as the Web site was constructed.
The full spread format was used because it allowed for the most accurate layout and ratio
of space between the text and visual elements of the virtual and indirect stimulus
material. Finally, the direct experience allowed the full sensory inspection of the digital
video camcorder. In order to remain consistent across stimuli, the physical product was
presented along with the exact information as each of the previous experiences using the

magazine ad (minus the product image) as a point-of-purchase display.

Procedure
The study was conducted in a laboratory setting with participants randomly
assigned to one of the six experimental conditions: (1) indirect-direct sequence, (2)

indirect-virtual sequence, (3) direct-indirect sequence, (4) direct-virtual sequence, (5)

43

virtual-indirect sequence, and (6) virtual-direct sequence. In addition, a strict protocol
was scripted and followed to minimize external inﬂuence and ensure consistency (see
Appendix B). The study began with the administration of a short survey designed to
collect background information on each participant (see Appendix C). Once the survey
was completed, participants were escorted by a research assistant into a large laboratory
and seated in an area designed for the appropriate experience corresponding to their
assigned condition. For illustrative purposes, only the virtual-direct experience sequence
condition is described in detail. Participants were instructed that the purpose of the study
was to record their evaluation of the product and to thoroughly examine the web site for
the video camcorder in order to determine how they think and feel about the product. In
addition, brief navigation instructions were given to explain how to interact with the
product. While participants were isolated and could not view alternative experiences,
they could view a second participant in the same experience but were instructed not to
communicate with one another. In order to minimize overexposure of one type of
experience yet provide enough duration not to hinder the inherent advantages associated
with direct and virtual experiences, examination times were restricted to ﬁve minutes.
Following the virtual experience, research assistants escorted participants to the second
experience station depending on their condition, which is direct experience in this
example. Approximately two to three minutes elapsed between the time a participant
exited the ﬁrst experience until beginning the second experience. Participants were
again instructed to take the next ﬁve minutes to thoroughly examine the video camcorder
to determine how they think and feel about the product. In addition, they were told that

upon completion of their examination they would be asked to complete a survey to record

44

their evaluation. This served to prime participants to engage in cognitive processing and
is consistent with previous indirect-direct experience studies (Kempf and Smith, 1998).
After the ﬁve-minute examination time, participants were asked to complete a
questionnaire containing the dependent measures (see Appendix D). This procedure was

followed identically for all of the remaining sequential exposure conditions.

Dependent Measures

The dependent variables of the study (product knowledge, brand attitude, and
purchase intention) were measured using a self-reported questionnaire including both
seven-point semantic differential and Likert-type items. Furthermore, additional

exploratory items were included but not analyzed in this study.

Product Knowledge

An established three-item scale was used to assess participants’ self-reported
product knowledge (Smith and Park, 1992). More speciﬁcally, participants were asked to
indicate their agreement (Strongly Disagree/Strongly Agree) regarding how
knowledgeable they felt about the product, the amount of additional information they
would need to make a purchase decision, and a quality judgment of the product using
seven-point Likert-type items. While Smith and Park’s (1992) original scale included a
fourth item, previous research indicated low reliability resulting in exclusion of the item

in this study (Li, Daugherty and Biocca, 2001b; Biocca, Daugherty and Li, 2001).

45

Brand Attitude

Overall brand attitude was assessed using a reliably proven and valid Six-item
scale common in advertising effectiveness measurement (Bruner, 1998). Participants
were asked to indicate how they feel about the product using seven-point semantic
differential items (bad/good, unappealing/appealing, unpleasant/pleasant,

unattractive/attractive, boring/interesting, dislike/like).

Purchase Intention

Purchase intent is a common effectiveness measure and often used to anticipate a
response behavior. In fact, the method of asking participants to evaluate an
advertisement or product and then indicate an intention is prevalent throughout the
literature (Andrews et al., 1992; Cho, 1999; Beerli and Santana, 1999; Petty, Cacioppo
and Schumann, 1983). Thus, an established four-tem seven—point semantic differential
scale (unlikely/likely, improbable/probable uncertain/certain, deﬁnitely/deﬁnitely not)
was used to measure the likelihood that participants would purchase the evaluated

product (Bearden, Lichtenstein and Teel, 1984).

Manipulation Checks

Prior to exposure to the stimulus materials, the ﬁrst questionnaire administered
was also designed to measure participant involvement with the product and prior brand
preference. Using the same six-item seven-point product involvement scale as in the
pretest, participants were asked to evaluate the personal relevance of the product

(unimportant/important, of no concern/of concern to me, irrelevant/relevant, means a lot

46

to me/means nothing, doesn't matter/matters to me, insigniﬁcant/signiﬁcant to me). In
order to determine if any personal preferences existed for the product, a seven-point
Likert-type item was used to assess the perceived quality of the product (low quality/high
quality). As a result, participants were asked to rate the perceived quality of the test
brand and four additional leading digital video camcorder brands (Sony, JV C, Panasonic,
Canon and Sharp). Because the pretest indicated price as the most salient attribute, a
three-item scale designed to measure the perceived value of the test product was included
along with the dependent variables. Participants were asked to rate their level of
agreement (strongly disagree/strongly agree) towards positive statements indicating the
product was a fair price, worth the money and a great deal (Urbany, Bearden and

Weilbaker, 1988).

47

CHAPTER 5

RESULTS

Data Analysis

Participants (n=166) were recruited from introductory communication courses at a
large Midwestern university and included a diverse number of academic majors. The
sample consisted of 84 women (50.6%) and 82 men (49.4%) with an average age of 21.8
(_S_I_)_ = 2.35). In addition, the majority of participants were upper classmen including 108
seniors (65.1%), 43 juniors (25.9%), 12 sophomores (7.2%) and 3 freshmen (1.8%).
Results of the involvement measure indicated that participants overall felt the digital
video camcorder was personally relevant and a moderately involving product (M = 4.12,
S_D = 1.12) (or = .93). Consistent with the pretest, Sony (M = 6.09, S_D = .98) and Canon
(M = 5.33, SD = 1.28) were perceived as the two highest quality digital video camcorder
brands with Panasonic (M = 5.10, S_D = 1.16) rated slightly ahead of Sharp (M = 4.72,
S_D = 1.30) and WC (M = 4.60, S_D =1.12).

All of the scales were tested for internal consistency and a speciﬁed factor
structure based on theory-driven indicators using conﬁrmatory factor analysis and found
to be unidimensional (CFA) (Hunter and Gerbing, 1982). Furthermore, reliability
assessment was conducted using Cronbach’s Alpha with each scale exceeding the
generally accepted guideline of .70 (Hair, Anderson, Tatharn and Black, 1998, p.118)
(see Table 3). Composite measures for each of the scales were then constructed to
represent the multiple items and used in the subsequent analysis to reduce measurement

error.

48

In order for the univariate test procedures to be valid, the dependent variables
must meet several criteria: (1) all observations must be independent, (2) the variables
must be normally distributed and (3) the variances of all conditions must be equal
(Keppel, 1991, p.95). The independence assumption was met through random
assignment of each participant into one of the six treatment conditions. As a result, cells
were adequately balanced with I -*D and D—al sequential exposure conditions containing
27 participants each followed by 28 each in the I-aV, V—>I, V->D, and D—aV conditions.
Visual examination of Q-Q plots for the dependent variables of each condition as well as
the Kolmogorov-Smimov statistical test indicated normality of the data is a reasonable
assumption (see Table 4). In turn, results of the Levene test for homoscedasticity conﬁrm
there are no signiﬁcant differences of variance for brand attitude (F (5,160) = .95, p >
.05), product knowledge (F (5,160) = 1.86, p >05), and purchase intention (F (5,160) =

1.19, p > .05), across conditions.

Table 3. Mean, Standard Deviation, and Cronbach Alpha
Coefﬁcients for Scales

 

 

 

Variable Mean Std. Dev. (1
Product Involvement 4.12 1.12 .93
Product Knowledge 4.25 1.18 .74
Brand Attitude 4.81 1.27 .94
Purchase Intention 3.13 1 .25 .87
Hypothesis Testing

 

The results show signiﬁcant main effects for product knowledge, F (5,165) =

3.04, p < .05, 02 = .09, brand attitude, F (5,165) = 16.52, p < .01, 02 = .34, and purchase

49

intention, F (5,165) = 2.66, p < .05, n2 = .08, suggesting the dependent measures were
affected differently across the treatment conditions. Furthermore, participants indicated
the highest level of product knowledge when exposed to a direct experience preceding a
virtual experience (M = 4.63, SD = 1.24) (see Table 5). However, exposure to a virtual
experience preceding both indirect (M = 5.48, SD = .92) and direct (M = 5.55, S_D = .97)
experiences accounted for the strongest impact on brand attitude. Subsequently,
participants exposed to a virtual experience preceding an indirect experience (M = 3.58,
S_D = 1.36) indicated they were more likely to purchase the test product (see Figure 3).

Univariate contrast comparisons were conducted to test the proposed hypotheses.
The ﬁrst set of planned contrasts tested the effect of a virtual experience when replacing
an indirect or direct product experience on each of the dependent variables. Previous
research has established that the theoretical sequence of exposure enhancing consumer
learning the most occurs when indirect experience precedes direct experience (Marks and
Kamins, 1988; Moore and Lutz, 2000; Smith and Swinyard, 1983; Smith, 1993).
Therefore, the ﬁrst set of hypotheses simply predicted this relationship.

The results presented in Table 6 show that participants felt more knowledgeable
and brand attitude was more favorable when exposed to an indirect—adirect sequence
rather than a direct—aindirect sequence, supporting Hla and Hlb. However, ch was
rejected as participants indicated they were signiﬁcantly more likely to purchase the
product after exposure to a direct-indirect sequence than the hypothesized

indirect—*direct sequence.

50

Table 4. Dependent Variable Test of Normality

 

 

Variable Condition Statistic (If p <

Product

Knowledge
I—PD .153 27 .1 1
D-al .153 27 .1 1
I—>V .155 28 .08
V-—>I .128 28 .20
V—>D .124 28 .20
D—aV .1 19 28 .20

Brand

Attitude
I—aD .097 27 .20
D—aI .145 27 .16
I—aV .148 28 .12
V—aI .1 14 28 .20
V—aD .121 28 .20
D—aV .154 28 .09

Purchase

Intention
I—>D .092 27 .20
D—>I .134 27 .20
I—>V .102 28 .20
V—>I .1 17 28 .20
V—aD .l 14 28 .20
D—aV .128 28 .20

 

51

Figure 3. Product Knowledge, Brand Attitude and Purchase Intention across Sequential
Exposure Conditions

7 .

 

 

 

 

I-D D-I I-V V-I V~D D—V

—I—Product Knowledge — i— - Brand Attitude - - O - - Purchase Intent

Table 5. Dependent Variable Descriptive Statistics for each Treatment Condition

 

Sequential Exposure
I—>D D—>I I—PV V—>I V—>D D—>V

 

 

Product Knowledge
Mean 4.31 3.51 4.38 4.36 4.31 4.63
St. Deviation 1.25 1.26 1.12 1.18 .75 1.24
Brand Attitude
Mean 4.83 3.31 4.64 5.48 5.55 4.97
St. Deviation 1.19 1.09 1 .04 .92 .97 1.04

Purchase Intention

Mean 2.67 3.39 2.67 3.58 3.23 3.22
St. Deviation 1.05 1.24 1.21 1.36 1.04 1.38

 

52

Based on the proposition that a virtual experience will function more closely as a
direct experience, the second set of hypotheses predicted an indirect—adirect exposure
sequence should result in no differences in product knowledge, brand attitude, or
purchase intention than an indirect—*virtual exposure sequence. The results indicate that
there were no signiﬁcant differences detected for the dependent variables supporting H2a,
H2b and H2c.

Similarly, hypothesis set three states there should be no differences in product
knowledge, brand attitude, or purchase intention when participants experience a
direct—aindirect exposure sequence versus a virtual—>indirect exposure sequence.
However, the results Show that participants indicated signiﬁcantly greater product
knowledge and more favorable brand attitudes when examining the product in a
virtual—indirect sequence compared to a direct—indirect sequence causing H3a and H3b
to be rejected. The ﬁndings indicate no signiﬁcant differences between a direct—aindirect
exposure sequence and a virtual—>indirect exposure sequence for purchase intention
supporting H3c.

Maintaining the assumption that a virtual experience emulates the inﬂuence
expected from direct experience, the impact on the dependent variables for an
indirect->direct sequence and an indirect—>virtual sequence should be stronger than a
virtual—*indirect sequence and direct—aindirect sequence. For the fourth set of
hypotheses, the results demonstrate the opposite of the predicted relationships.
Participants indicated they felt marginally more knowledgeable aﬁer exposure to the
virtual-+indirect sequence relative to the indirect—9direct sequence. Furthermore, brand

attitude and purchase intention were signiﬁcantly greater when participants experienced

53

the virtual—aindirect sequence compared to the indirect—’direct sequence. Thus, H4a,

H4b, and H4c were rejected.

Table 6. Contrast Comparisons for Sequential Exposure Conditions for H1 through H6

 

 

 

Independent Variables
I—->D D-al I—>V V—>I V—>D D—>V F p <
Product
Knowledge
Hla 4.31 3.51 - - - - 6.6 .02
H2a 4.31 - 4.38 - - - .05 .86
H3a - 3.51 - 4.36 - - 7.5 .00
H4a 4.31 - - 4.36 - - .02 .88
H5a - 3.51 4.38 - - - 8.0 .00
H6a - - 4.38 4.36 - - .00 .94
Brand
Attitude
Hlb 4.83 3.31 - - - - 28. .00
H2b 4.83 - 4.64 - - - .42 .51
H3b - 3.31 - 5.48 - - 59. .00
H4b 4.83 - - 5.48 - - 5.4 .03
H5b - 3.31 4.64 - - - 22. .00
H6b - - 4.64 5.48 - - 9.0 .00
Purchase
Intention
ch 2.67 3.39 - - - - 4.7 .04
H2c 2.67 - 2.67 - - - .00 .99
H3c - 3.39 - 3.58 - - .33 .56
H4c 2.67 - - 3.58 - - 7.6 .00
H5c - 3.39 2.67 - - - 4.7 .04
H6c - - 2.67 3.58 - - 7.7 .00

 

54

The results of the ﬁfth set of hypotheses Show that product knowledge and brand
attitude were greater when participants were exposed to an indirect—avirtual exposure
sequence compared to a direct—Pindirect sequence, supporting H5a and HSb. However,
hypothesis H5c was rejected because participants indicated they were signiﬁcantly more
likely to purchase the product after exposure to adirect—aindirect sequence than the
hypothesized indirect—avirtual sequence.

Hypothesis set six predicted that an indirect—wirtual exposure sequence would
have a stronger positive impact on the dependent variables than a virtual->indirect
exposure sequence. The results indicate that participants perceived no signiﬁcant
differences for product knowledge across the indirect-avirtual sequence compared to the
virtual—aindirect with only marginal directional support. In contrast, signiﬁcant
differences for brand attitude and purchase intention were detected in the opposite
direction meaning participants perceived the test product as more favorable and indicated
they were more likely to purchase after a virtual-aindirect exposure sequence rather than
an indirect—>virtual exposure sequence. Hence, H6a, H6b, and H6c were rejected.

The next set of hypotheses are based on the proposition that sequential exposure
involving the combination of a virtual and direct experience will increase consumer
learning because virtual experience behaves more like product trial, and repeated
exposure in evaluative terms allows individuals to process more information (Berger and
Mitchell, 1989; Fazio et al., 1982). Hypothesis set seven states that a virtual-’direct
exposure sequence will result in greater product knowledge, more favorable brand
attitudes, and elevated purchase intent over a direct-aindirect exposure sequence. The

results verify that product knowledge and brand attitude were higher for participants in

55

the virtual—adirect sequence than in the direct—>indirect exposure sequence supporting
H7a and H7b (see Table 7). However, H7c was rejected because the mean scores were
opposite the predicted direction for purchase intention, with participants indicating they
were marginally more likely to purchase after exposure to a direct—aindirect rather than a
virtual—adirect sequence. No statistical signiﬁcance differences were detected.

For hypothesis set eight, exposure to a direct—>virtual sequential experience was
predicted to have a greater impact on product knowledge, brand attitude and purchase
intention than a direct—aindirect sequence. The combination of a virtual with direct
experience resulted in participants reporting increased product knowledge and more
favorable brand attitudes over a virtual~>indirect sequence supporting H8a and H8b.
However, H8c was again rejected because the mean values were opposite the predicted
direction as participants indicated they were more likely to purchase the product after a
virtual-aindirect sequence than a direct—avirtual exposure.

The next set of hypotheses state that exposure to a virtual-adirect experience
sequence will increase product knowledge, brand attitude and purchase intention above
an indirectedirect sequence. Contrast comparisons support the prediction for brand
attitude (H9b), as well as provide marginal support for purchase intention (H9c), with a
virtual—>direct sequence positively inﬂuencing participants over an indirect->direct
sequence. Yet, participants literally reported no differences between the two conditions
pertaining to how knowledgeable they felt about the product and H9a was rejected.

By simply reversing the sequential exposure combination of virtual and direct
experiences, the tenth set of hypotheses assert that a direct—>virtual experience sequence

will result in greater product knowledge, more favorable brand attitudes and elevated

56

purchase intention than an indirect—*direct sequence. While product knowledge and
brand attitude did not statistically differ across the treatment conditions, the means were
in the hypothesized direction. Nevertheless, statistical analysis indicates that only
purchase intention is marginally elevated after a direct—>virtual experience relative to an
indirect—*direct experience. Therefore, H10a, H10b, and H10c are rejected.

Exposure to a virtual-+direct experience sequence was predicted by hypotheses
set eleven to increase product knowledge, brand attitude, and purchase intent over a
virtual—*indirect sequence. Again, the premise is that the combinations of virtual and
direct experiences together serve as repeated exposures since a virtual experience follows
more closely with product trial. The ﬁndings reveal that no signiﬁcant differences were
detected between a virtual—>direct sequence and a virtual—aindirect sequence for any of
the dependent measures, leading to the rejection of H1 1a, H1 1b, and H1 1c. While the
observed mean values for purchase intention were in the hypothesized direction,
surprisingly the direction reversed with participants indicating higher levels of product

knowledge and brand attitude after exposure to the virtual—aindirect sequence.

57

Table 7. Contrast Comparisons for Sequential Exposure Conditions for H7 through H15

 

 

 

Independent Variables
l——>D D->I I->V V—PI V—>D D—>V F p <

Product

Knowledge
H7a - 3.51 - - 4.31 - 6.7 .01
H8a - 3.51 - - - 4.63 13. .01
H9a 4.31 - - - 4.31 - .00 .99
H10a 4.31 - - - - 4.63 1.0 .30
H1 la - - - 4.36 4.31 - .02 .88
H12a - - - 4.36 - 4.63 .79 .37
H13a - - 4.38 - 4.31 - .05 .82
H14a - - 4.38 - - 4.63 .66 .42
H15a - - - - 4.31 4.63 1.1 .30

Brand

Attitude
H7b - 3.31 - - 5.55 - 65. .00
H8b - 3.31 - - - 4.97 34. .00
H9b 4.82 - - - 5.55 - 6.6 .02
H10b 4.82 - - - - 4.97 .25 .61
Hllb - - - 5.48 5.55 - .06 .80
H12b - - - 5.48 - 4.97 3.3 .06
H13b - - 4.64 - 5.55 - 10. .00
H14b - - 4.64 - - 4.97 1.3 .24
H15b - - - - 5.55 4.97 4.3 .04

Purchase

Intention
H7c - 3.39 - - 3.23 - .22 .64
H8c - 3.39 - - - 3.22 .25 .62
H9c 2.67 - - - 3.23 - 2.9 .08
HIOc 2.67 - - - - 3.22 2.8 .09
Hllc - - - 2.67 3.23 - 1.1 .29
H12c - - - 2.67 - 3.22 1.1 .28
H13c - - 3.58 - 3.23 - 2.9 .08
H14c - - 3.58 - - 3.22 2.8 .09
H15c - - - - 3.23 3.22 .00 .99

 

58

To test the twelfth set of hypotheses, product knowledge, brand attitude and
purchase intention comparisons were made between participants exposed to a
direct—avirtual exposure sequence and a virtual—tindirect sequence. While the mean
values for product knowledge and purchase intention are in the predicted direction, no
signiﬁcant differences were detected between evaluations made following a
direct—>virtual exposure sequence versus a virtual-*indirect sequence. Surprisingly, a
moderately signiﬁcant difference was detected for brand attitude except the direction
supported the virtual—>indirect exposure sequence rather than the predicted
direct-’Virtual sequence. Thus, H12a, H12b, and H12c were rejected.

Hypothesis set thirteen predicts that a virtual—adirect experience sequence will
result in elevated product knowledge, more favorable brand attitude, and increased
purchase intention among participants than when exposure to an indirect—wirtual
sequence. However, participants indicated they felt slightly more knowledgeable after
the indirect—>virtual sequence rather than the hypothesized virtual—*direct exposure
sequence. While the difference in direction should be noted for rejecting H13a, the value
is marginal resulting in a lack of signiﬁcance. Participants on the hand reported
signiﬁcantly higher levels of brand attitude for the virtual-*direct experience exposure
sequence than the indirect—>virtual sequence supporting H13b. Possibly a more
interesting ﬁnding is the marginal signiﬁcance for increased purchase intention after
exposure to an indirect—*virtual exposure sequence rather than the proposed
virtual—’direct sequence. Thus, H13c was rejected.

The fourteenth set of hypotheses reversed the combination of direct and virtual

experiences to predict that a direct—>virtual experience sequence would positively impact

59

product knowledge, brand attitude and purchase intention over the indirect—>virtual
sequence. The data however failed to support H14a, H14b, or H14c. The effect on
product knowledge and brand attitude, as indicated by the mean values, was in the
hypothesized direction yet not statistically strong enough to be considered signiﬁcant. In
contrast, marginal support was detected in the opposite direction for participants
indicating they are more likely to purchase the test product after exposure to an
indirect-+virtual experience sequence rather than the hypothesized direct—avirtual
sequence.

Finally, the ﬁfteenth set of hypotheses state that a virtual-*direct experience
sequence heighten product knowledge, increase brand attitude and elevate purchase
intention above a direct—>virtual experience sequence. While both include the beneﬁt of
repeated exposure from the combination of virtual and direct experiences, the
predisposition created by the exposure of a virtual experience ﬁrst should be reinforced
by the direct experience increasing the evaluation. The results provide partial support for
the set of hypotheses. Higher levels of product knowledge were reported for the
direct-avirtual exposure sequence rather than the virtual—>direct sequence, which is
opposite the predicted direction resulting in the rejection of H15a. However, participants
reported higher levels of brand attitude after evaluating the test product in the
virtual—adirect exposure sequence contrasted to the direct-*virtual sequence, supporting
H15b. Hypothesis 15c was rejected because there were essentially no reported

differences in levels of purchase intention across the two treatment conditions.

60

Post Hoc Analysis

Further analysis of the data reafﬁrms the unexpected results regarding purchase
intention. In addition, the ﬁnding of no relationship for purchase intention between
product knowledge or brand attitude signiﬁes an unforeseen discrepancy considering all
three are highly correlated with product value (see Table 8). While the value of any
product can depend on a number of factors, the most salient product attribute indicated
from the pretest was price. Since the product value scale used in the data collection
primarily focused on price (fair price/worth the money/ great deal), analysis of covariance
was conducted controlling for participants' perceived product value. F (5,165) = 5.85, p <
.05, n2 = .18.

Finally, a virtual experience appears to be driving a ﬁrst order effect. Table 9
demonstrates that the average scores for the dependent variables are higher when a virtual
experience precedes either an indirect or direct experience compared to when an indirect
or direct experience sequence is examined ﬁrst. In contrast, the average scores are

slightly higher when a direct experience follows either an indirect or virtual experience.

Table 8. Correlation Matrix of Dependent and Manipulation Check Variables

 

 

Brand Purchase Product Brand Product

Attitude Intention Involv. Pref. Value
Product Knowledge .37W -.006 .32M -.20* .19*
Brand Attitude .14 .06 -.01 .49**
Purchase Intention .32** .23* .34"
Product Involvement -.02 .17*
Brand Preference .06

 

**p<.05 **p<.01

61

Table 9. Sequential Order Effect for Indirect, Virtual and Direct Experience

 

Order Sequence Product Knowledge Brand Attitude Purchase Intention Mean

 

First I —+ D 4.31 4.83 2.67 3.93
I -> V 4.38 4.64 2.67 3.89
V --> I 4.36 5.48 3.58 4.47
V —a D 4.31 5.55 3.23 4.37
D -* I 3.51 3.31 3.39 3.40
D —+ V 4.63 4.97 3.22 4.27
Second D —> I 3.51 3.31 3.39 3.40
V ->I 4.36 5.48 3.58 4.47
I —* V 4.38 4.64 2.67 3.89
D -> V 4.63 4.97 3.22 4.27
I -> D 4.31 4.83 2.67 3.93
V —’ D 4.31 5.55 3.23 4.37

 

62

CHAPTER 6

SUMMARY AND CONCLUSIONS

Discussion

The purpose of this study was to expand the theoretical knowledge of consumer
learning by testing the sequential impact of a virtual experience when paired with a direct
or indirect experience. Rather than provide absolute evidence in support of a virtual
product experience, this study extends our understanding of the cognitive, affective, and
conative outcomes traditionally associated with consumer learning to include the
combination of this new type of consumer experience.

Previous research has documented the theoretical sequential effect of indirect and
direct product experience on consumer learning (Marks and Kamins, 1988; Moore and
Lutz, 2000; Smith and Swinyard, 1983; Smith, 1993). The Integrated Information
Response Model illustrates that exposure to forms of advertising generates lower order
beliefs, which are then validated from positive trial resulting in higher order beliefs.
Consumer knowledge, attitudes, and behavioral intentions formed through indirect
experience are essentially reinforced by product trial elevating the previously formed
lower order beliefs. However, when a positive direct experience via product trial
precedes advertising, the beliefs formed from the trial diminish the impact of the indirect
experience generated by advertising. As a result, the sequential impact of an
indirect-+direct experience on cognitive, affective, and conative measures is greater than

the effect of a direct—aindirect sequence. The results of this study largely support the

63

model for product knowledge and brand attitude yet fall short for predicting purchase
intention.

AS evident from the results presented in the preceding chapter, participants
evaluating the test product attained higher order cognitive and affective beliefs from the
indirect—adirect sequential exposure combination than from the direct—>indirect
sequence. The positive information presented in the magazine ad prior to product trial
served to increase participants’ reported level of product knowledge and brand attitude.
In contrast, when product trial preceded exposure to the magazine ad, product knowledge
and brand attitude beliefs were signiﬁcantly lower. These results support Smith and
Swinyard's (1982) Information Integration Response Model of consumer learning.
However, higher order cognitive and affective beliefs did not lead to conation as the
model predicts. In fact, the ﬁndings were the exact opposite with higher levels of
reported commitment occurring for the direct—>indirect sequential exposure than
indirect—edirect exposure. Speciﬁcally, participants indicated they were Signiﬁcantly
more likely to purchase the test product when the initial exposure was product trial rather
than the magazine ad.

One possible explanation for this occurrence could be that the test product was
perceived primarily as an experiential good. Previous research in consumer learning has
indicated that product trial is more effective at inﬂuencing consumer behavior for
experiential products with advertising serving as a more effective inﬂuence for search or
information products (Wright and Lynch, 1995). However, this explanation seems

unlikely when considering the results of the cognitive and affective measures.

64

A more plausible explanation is that the price of the test product exceeded the
maximum cost participants were willing to pay for the product. Research investigating
the impact of price on perceived product value has documented the importance of
plausible reference prices in consumer behavior (Urbany, Bearden, and Weilbaker, 1988).
While college students represent a more technologically inclined population familiar with
digital video cameras, the perceived value of the test product more than likely exceed the
reference price they were willing to pay, especially when you consider the most salient
attribute reported in the pretest was price. The results of the post hoc analysis offer some
support for this rationale yet additional research testing a reduced price for the test
product is needed to conﬁrm the explanation.

The principal purpose of the study was to expand the theoretical knowledge of
consumer learning by testing the impact of virtual experience on sequence of exposure
relative to indirect and direct experience. One proposition is that 3-D product evaluation
in a virtual experience will be richer than indirect experience and closer to direct
experience because of interactivity, Vividness, involvement, presence and virtual
affordances (Biocca, Li and Daugherty, 2001; Li, Daugherty and Biocca, 2001a; 2001b;
in press). Therefore, a virtual experience was expected to emulate the behavior of direct
experience resulting in the reinforcement of cognitive, affective, and conative measures
for an indirect—>virtual exposure sequence.

As previously reported, the results largely support the proposed model for product
knowledge and brand attitude when participants were exposed to an indirect experience
followed by a virtual experience compared to a direct—aindirect sequence yet contradicts

the expected hypothesized effect for purchase intention. This is evident since an

65

indirect—+virtual exposure sequence resulted in higher levels of product knowledge and
brand attitude compared to a direct—>indirect sequence, with no signiﬁcant differences
compared to an indirect—adirect exposure sequence. However, when a virtual experience
preceded indirect experience, there were surprisingly no signiﬁcant differences for
reported product knowledge when compared to an indirect—*direct sequence and brand
attitude was actually signiﬁcantly higher for the virtual-+indirect sequence. The
expected effect would result in an indirect—adirect exposure sequence elevating product
knowledge, increasing brand attitude, and inﬂuencing purchase intention over a
virtual—indirect sequence yet this did not occur.

One possible explanation is that because a virtual experience incorporates
elements of both indirect and direct experience, the combination of information cues and
the simulation of sensory experience reinforce advertising effectiveness. Evidence of this
effect could also be construed from the result that an indirect-*virtual exposure sequence
did not signiﬁcantly increase product knowledge and brand attitude over a
virtual—>indirect sequence. While the means values were marginally higher in the
hypothesized direction for product knowledge, reported brand attitude was actually
signiﬁcantly higher for the virtual—aindirect sequence. Yet, because this effect was not
seen for product knowledge more research is needed to conﬁrm this ﬁnding.

There has been a considerable amount of research supporting the proposition that
repeated exposure in evaluative terms allows individuals to process more information
resulting in increases in cognitive, affective and conative measures (Berger and Mitchell,
1989; Mitchell and Olsen, 1977; Sawyer, 1981). The recurrent exposure involving direct

experience is enhanced even stronger and more predictive of behavior over indirect

66

experience (F azio et al., 1982). Therefore, because a virtual experience is theoretically
closer to direct experience, any sequential exposure involving the combination of virtual
and direct experiences together (i.e. V—tD or D—>V) would increase consumer learning
over all other sequential exposures. The study ﬁndings indicate partial support for this
proposition. For instance, in terms of increasing product knowledge, a virtual—tdirect
sequence and a direct—>virtual sequence were only found to be signiﬁcantly greater than
a direct—>indirect exposure sequence. Since previous research has documented the value
of advertising when evaluating search information oriented products (Wright and Lynch,
1995), perhaps increases in product knowledge would be greater for a virtual—adirect
sequence when testing a more experientially driven product. However, in terms of
increasing brand attitude, the strongest impact resulted primarily from the virtual—>direct
exposure sequence. As one might expect, both the virtual—+direct sequence and
direct—>virtual sequence resulted in more favorable brand attitudes than the
direct—>indirect sequence. When compared with the indirect—direct exposure sequence,
a virtual->direct sequence was perceived as increasing higher order brand attitude beliefs.
While there were no signiﬁcant differences for the direct—avirtual sequence compared to
the indirect—>direct, the mean values were in the hypothesized direction. AS expected,
Similar results were detected when comparing the virtual—>direct sequence and
direct—>virtual sequence with the virtual—>indirect exposure sequence. A surprising
ﬁnding though continues to be the comparison of treatment conditions with the
virtual—>indirect experience. For instance, there were no signiﬁcant differences detected
between the virtual—+direct sequence and the virtual—aindirect sequence. Yet, when

compared to the direct->virtual exposure sequence a marginally signiﬁcant ﬁnding was

67

detected but in the opposite direction with participants indicating more favorable brand
attitudes for the virtual—>indirect exposure sequence. The implications of these results
strongly suggest a virtual experience combined with advertising could be considered as
an alternative to product sampling for increasing brand attitudes but further research is
needed to reafﬁrm these results. Of course, this could potentially represent some type of
novelty or enjoyment effect. For purchase intention, there were marginally signiﬁcant
differences when comparing virtual—’direct and direct-avirtual sequences against an
indirect—adirect sequence. Furthermore, the indirect—>virtual exposure sequence resulted
in elevated purchase intentions compared to the virtual—adirect and direct—avirtual
sequences; however these results should be interpreted with caution considering the
aforementioned concerns regarding the price of the test product.

Fundamentally, the results of this study have established a virtual experience as
an alternative consumer experience previously unexplored in consumer learning research.
The data suggests that this new type of experience resembles more closely a direct
product experience than a traditional indirect experience, such as a print advertisement.
Theoretically, the increased visual sensory immersion and perceived control from
examining a 3-D interactive product simulates the same sensory input expected when
evaluating a physical product, under these test conditions. An important and interesting
ﬁnding is that the sequential combination of a virtual experience exceeded the expected

combination of indirect and direct experiences.

68

Limitations

Inherent within any study are limitations that affect the overall validity and
reliability of the results. With regard to this study, there are obvious limitations that
should be considered when interpreting the research ﬁndings. One limitation is the use of
a student sample in combination with conducting a laboratory experiment. This type of
experiment restricts the external validity and should be kept in mind when interpreting
the results. While strong consideration and planning took part in the selection of an
apprOpriate test product, the use of a student sample combined with an expensive brand
of digital camcorder more than likely inﬂuenced the behavior measure. Furthermore, the
product category was selected because it matched the necessary virtual affordances as
well as combined various experience attributes. However, the selection of different
product categories incorporating more heavily search or experience attributes could
impact the results. As a result, these ﬁndings are certainly not generalizable to all
products and Situations.

Another limitation is that lntemet access and computer performance was
controlled in this study with participants not exposed to the effects of slow download
times or poor computer performance. Ordinary consumers using slower connections
from a home computer may not spend as much time examining the product as subjects

did in the lab. This could have an impact in reducing product learning and brand attitude.
Conclusions

Taking into account the exploratory nature of this study, the primary purpose was

not simply to provide absolute evidence in support of one type of sequential exposure

69

over another but rather to expand the body of knowledge and position virtual experience
within consumer learning. The results provide moderate support for the proposition that
consumers are able to learn from examining 3-D visual products in online ecommerce
environments. Because marketers are capable of exerting inﬂuence over the consumer
learning process (Hoch and Deighton, 1989), a virtual experience may extend product
knowledge, affect brand attitude, and inﬂuence purchase by enhancing the online
shopping experience. Furthermore, the veriﬁed relationship between cognitive, affective
and conative effectiveness measures reinforces the need for marketers to consider the
impact of indirect and direct sequential exposure to include a virtual product experience.

Consideration of these ﬁndings suggests that a virtual experience in combination
with indirect or direct experience is capable of increasing product knowledge and
inﬂuencing brand attitude over the direct-+indirect sequence. While the impact of an
indirect—>direct sequence was not always statistically different than a virtual experience,
this fact does not mean a sequential exposure involving a virtual experience is less
effective. Based on this study, the results indicate that for product knowledge there were
no differences between the indirect—>direct exposure sequence with increases in brand
attitude that show encouraging results. As a result, it is realistic to conclude that under
these experimental conditions a virtual experience emulated the expected outcome from a
direct product experience while exceeding it in some instances.

The ability to establish a virtual experience is not beyond the capabilities of
ecommerce environments and technological conditions are almost ripe for advertisers and
marketers to take advantage of this unique experience. Through continued research, the

key is to fully develop and explore the psychological and emotional states created in a

70

virtual experience. By creating 3-D interactive products, marketers are able to provide
consumers with a unique experience transcending traditional direct product inspection
and surpassing in some instances inspection from traditional advertising. The underlying
reason is that virtual experiences allow for vicarious learning because consumers are
actively engaged in the inspection and control of a 3-D product rather than a passive
observer common to more traditional forms of advertising.

To fully understand the impact of utilizing 3-D products in consumer learning,
more theoretical research is needed designed to explore the unique and distinctive
characteristics that separate virtual experience from other types of experiences. In
addition, research designed to explore the impact of message content appeals, low
involvement products, and alternative types of sensory immersion (auditory) are essential
to fully understand the potential impact a virtual experience offers marketers. Finally,
this study represents a single laboratory experiment into a new and relatively unexplored
area. Therefore replications and extensions of this work are needed to verify and validate

the results.

71

REFERENCES

72

REFERENCES

Andrews, J. Craig, Syed H. Akhter, Srinivas Durvasula, and Darrel Muehling. (1992).
The effects of advertising distinctiveness and message content involvement on
cognitive and affective responses to advertising. Journal of Current Issues and
Research in Advertising, 14(Spring), 45—58.

Ariely, Dan. (2000). Controlling the information ﬂow: Effects on consumers’ decision
making and preferences. Journ_al of Consumer Research, 27(2), 233-249.

Batra, Rajeev and Michael L. Ray. (1986). Situational effects of advertising repetition:
The moderating inﬂuence of motivation, ability, and opportunity to respond.
Journal of Consumer Research. 12(March), 432-445.

Bauer, W. S. (1995). Government investment in telecommunications infrastructure. In
National Research Council: The changing nature of telecommunications:
Information infrastructure. 179-194. Washington, DC: National Academy Press.

Bearden, W. 0., D. R. Lichtenstein, and J. E. Teel. (1984). Comparison price, coupon,
and brand effects on consumer reactions to retail newspaper advertisements.
Journal of Retailing. 60(2), 11-34.

Beerli, Asuncion, and Josefa D. Martin Santana. (1999). Design and validation of an
instrument for measuring advertising effectiveness in the printed media. Journal
of Current Issues and Research in Advertising. 21(2), 11-30.

Berger, Ida and Andrew Mitchell. (1989). The effect of advertising on attitude
accessibility, attitude conﬁdence, and the attitdue-behavior relationship. Journal
of Consumer Research. 2(September), 269-279.

Bettman, James R. (1979). An Information Processing Theory of Consumer Choice.
Reading, MA: Addison-Wesley.

Biocca, Frank. (1997). Cyborg's dilemma: Progressive embodiment in virtual
environments. low] of Computer Mediated-Communication. 3(2), [Online]
Available http://jcmc.huji.ac.il/vol3/issue2/biocca2.html.

Biocca, Frank, Hairong Li, and Terry Daugherty. (2001). Experiential ecommerce:
Relationship of physical and social presence to consumer learning, attitudes, and
decision-making. Presented at Presence, 4th Annual International Workshop on
Presence in Philadelphia, PA, May 21 - 23.

73

Biocca, Frank, Taeyong Kim, and Matthew Levy. (1995). The vision of virtual reality. In
Communication in the Age of Virtual Realig. 3-14. F. Biocca and M. Levy (Eds).

Hillsdale, NJ: Lawrence Erlbaum Associates,lnc.

Braun, Kathryn A. (1999). Postexperience advertising effects on consumer memory.
Journal of Consumer Research. 25(4), 319-334.

Briggs, Rex and Nigel Hollis. (1997) Advertising on the web: Is there response before
click-through? Journal of Advertisirg Research. 37(March/April). 33-45.

Brucks, Merrie. (1985). The effects of product class knowledge on information search
behavior. Jomal of Consumer Research. 12(June), 1-16.

Bruner, Gordon C. (1998). Standardization & justiﬁcation: Do and scales measure up?.
Journal of Current Issues and Research in Advertising 20(1), 1-18.

Bruno, R. L. (1996, February). Net.news. Netguide, 16.

Burke, Raymond R. (1997). Do you see what I see? The future of virtual Shopping.
Journal of the Academy of Marketing Science, 25(4), 352-360.

Cacioppo, John T. and Richard E. Petty. (1979). Effects of message repetition and

position on cognitive response, recall and persuasion. Journal of Personality an_d
Social Psychology. 37(1), 97-109.

Celsi, Richard L. and Jerry C. Olson. (1988). The role of involvement in attention and
comprehension processes. JouLnal of Consumer Research. 15(September), 210-
224.

Chen, Qimei and William D. Wells. (1999). Attitude toward the site. Journal of
Advertising Research. 39(5), 27-37.

Cho, Chan-Hoan. (1999). How advertising works on the www: Modiﬁed elaboration
likelihood model. Journal of Current Issues and Research in Advertising,
2_1(Spring), 33-50.

Dahan, Ely and V. Srinivasan. (2000). The predictive power of intemet-based product
concept testing using visual depiction and animation. Journal of Product

Innovation Maﬂgement. 17, 99-109.

Deighton, John. (1984). The interaction of advertising and evidence. Journal of
Consumer Research, 11(December), 763-770.

Ducoffe, Robert H. (1996). Advertising value and advertising on the web. Journal of
Advertising Research. 5(September/October), 21-34.

74

Ehrenberg, Andrew S. C. (1974). Repetitive advertising and the consumer. Journal of
Advertising Research. 14(2), 25-34.

Fazio, Russell H., Jeaw-Mei Chen, Elizabeth C. McDonel, and Steven J. Sherman.
(1982). Attitude accessibility, attitude-behavior consistency, and the strength of
the object evaluation association. Journal of Experimental Social Psychology,
_1_8(4), 339-357.

Fazio, Russell H., Martha C. Powell and Carol J. Williams. (1989). The role of attitude
acdeessibility in the attitude-to-behavior process. Journal of Consumer Research.
16(December), 280-288.

Fazio, Russell H., and M. P. Zanna. (1977). On the predictive validity of attitudes: The
role of direct experience and conﬁdence. Journal of Personality. 46. 228-43.

(Fishbein, Martin and I. Ajzen. (1975). Belief. Attitude. Intention. and Behavior: An
_- Introduction to Theog and Research. Reading, MA: Addison-Wesley Publishing
Company.

Gardner, M. P. (1985). Does attitude toward the ad affect brand attitude under
brand evaluation set? Jouraal of Marketing Research. 22(May), 192-198.

Gibson, J. J. (1966). The Senses Considered as Perceptual Systems. Boston: Houghton
Mifﬂin.

Grossman, Lev. (2000). Your technology. Time, Sep 18, 93.

Hair, Joseph F., Rolph B. Anderson, Ronald L. Tatham, and William C. Black. (1998).
Multivariate Data Analysis, 5th ed. Upper Saddle River, NJ: Prentice Hall.

Haubl, Gerald and Valerie Trifts. (2000). Consruner decision making in online dhopping
environmnets: The effects of interactive decision aids. Marketing Science. 19(1):
4-21.

Heeter, Carrie. (2000). Interactivity in the context of designed experience. Journal of
Interaractive Advertising. 1(1). [Online] Available http://www.jiad.org.

Held, R. M., and N. I. Durlach. (1992). Telepresence. Presence 1(1), 109-112.

 

Hirschman, Elizabeth C. (1984). Experience seeking: A subjectivist perspective of
consumption. Journal of Business Research. 12, 115-136.

Hoch, Stephen J ., and John Deighton. (1989). Managing what consumers learn from
experience. Jougn_al of Marketingg53(April), 1-20.

75

Hoch, Stephen J. and Young-Won Ha. (1986). Consumer learning: Advertising and the
ambiguity of product experience. Journal of Consumer Research. 13(September),
221-233.

Hoffman, Donna L. and Thomas P. Novak. (1997). A aew marketing paradigm for
electronic commerce. Information Society. 13(1), 43-54.

Hoffman, Donna L. and Thomas P. Novak. (1996). Marketing in hypermedia computer-
based environments: Conceptual foundations. Journal of Marketing, 60(July), 50-
68.

Hunter, J .E. and Gerbing, D.W. (1982). Machiavellian beliefs and personality: Construct
invalidity of the machavellianism dimension. Journal of Persoaality and Social
Psychology. 43, 1293 - 1305.

Hutchinson, J. Wesley and Joseph W. Alba. (1991). Ignoring irrelevant information:
Situational determinants of consumer learning. Joumal of Consumer Research.
18(December), 325-345.

Ijsselsteijn, WA. and H. De Ridder. ( 1998). Measuring temporal variations in presence
[Online]. Available http://www.tue.nl/ipo/people/ij sselsteijn/btpapter.htm.

Kahn, R. E. (1995). The role of the govemmnet in the evolution of the intemet. In

National Academy of Engineering, Revolution in the US. Information
Infrastructure. Washington, DC: National Academy Press. 1-12.

 

Karat, John, Clare-Marie Karat, and Jacob Ukelson. (2000). Affordances, motivations,
and the design of user interfaces: Creating tools that enable rather than restrict add

value to the product and loyalty from the customer. Commurﬂrtions of the ACM.
43(8), 49-51.

Keller, Punam Anand and Lauren G. Block. (1997). Vividness effects: A resource-
matching perspective. Jouﬂal of Consumer Research. 24(4), 295-304.

Kempf, Deanna S. and Robert E. Smith. (1998). Consumer processing of product trial
and the inﬂuence of prior advertising. A structural modeling approach. Journal of
Marketing Research, 35(August), 325- 338.

Keppel, Geoffrey. (1991). Design and Aaalysis: A Researcher's Handbook. Englewood
Cliffs, NJ: Prentice Hall.

 

Klein, Lisa R. (1998). Evaluating the potential of interactive media through a different
lens: Search versus experience goods. Journal of Business Research, (41), 195-
203.

76

Kim, Taeyong and Frank Biocca. (1997). Telepresence via television: Two dimensions of
telepresence may have different connections to memory and persuasion. Journal
of Computer Mediated Communication 3(2). [Online] Available
http://www.ascusc.org/jcmc/vol3/issue2/kim.html.

 

Krugman, Herbert E. (1965). The impact of television advertising: Learning without
involvement. Public Opinion Quarterly. 29(Fall), 349-356.

Laczniak, Russell N., DeAnna S. Kempf, and Darrel D. Muehling. (1999). Advertising
message involvement: The role of enduring and situational factors. Journal of
Current Issues gd Research in Advertising. 21(Spring), 51-61 .

Laczniak, Russell N. and Darrel D. Muehling. (1993). The relationship between
experimental manipulations and tests of theory in an advertising message context.
Journal of Advertising. 22(3), 59-74.

Lavidge, Robert J. and Gary A. Steiner. (1961). A model for predictive measurements of
advertising effectiveness. Journal of Marketing, 25(October), 59-62.

Lessiter, Jane, Jonathan Freeman, Ed Keogh, and Jules Davidoff. (2000). Development of
a new cross-media presence questionnaire: The itc-sense of presence inventory.
Presented at Presence, 3rd International Workshop on Presence, Technical
University of Delft, Delft, Netherlands, 27-28 March.

Levin, Irwin P. and Gary J. Gaeth. (1988). How consumers are affected by the framing of
attribute information before and after consuming the product. Journal of
Consumer Research, 15(December), 374-378.

 

Li, Hairong, Terry M. Daugherty, and Frank Biocca. (2001a). Feeling the presence of
products: Consumer learning from virtual experience. Presented at the American
Marketing Association Winter Educators Conference. Scottsdale, AZ, February
16-19.

Li, Hairong, Terry M. Daugherty, and Frank Biocca. (2001b). Types and effects of
affordances in consumer learning: An empirical study of virtual experience.
Presented at the American Academy of AdvertisiagAnnual Conference. Salt

Lake City, UT, March 29-April 1.

Li, Hairong, Terry M. Daugherty, and Frank Biocca. (in Press). Characteristics of virtual
experience in ecommerce: A protocol analysis. Journal of Interactive Marketing,
15(3)-

Lombard, Matthew. (1995). Direct response to people on the screen: Television and
personal Space. Communication Research 22(3), 228-324.

 

77

Lombard, Matthew and Theresa Dittion. (1997). At the heart of it all: The concept of

presence. Journal of Computer-Mediated Communication 3 (2). [Online]
Available http://www.ascusc.org/jcmc/vol3/issue2/lombard.html.

Lundh, L. G. (1979). Introspection, consciousness, and human information processing.
Scandinayian Journal of Pachology, (20), 223-38.

Lutz, Richard J. (1985). Affective and cognitive antecedents of attitude toward the ad: A
conceptual framework. In Psychological Processes and Advertising Effects:
Theog, Research and Application, L.F. Alwitt and AA. Mitchell, eds. Hillsdale,
NJ: Lawrence Erlbaum Associates, 45-63.

Lutz, Richard J. (1975). Changing brand attitudes through modiﬁcation of cognitive
structure. Joumal of Consumer Research. 1(March), 49-59.

MacKenzie, Scott B. and Richard J. Lutz. (1989). An empirical examination of the
structural antecedents of attitude toward the ad in an advertising pretesting
context. Journal of Marketing, 53(April), 48-65.

Maclnnis, Deborah J. and Bernard J. Jaworski. (1989). Information processing from
advertisements: Toward an integrative framework. Joanal of Marketing,
ﬂ(0ctober)j, 1-23.

Maclnnis, Deborah J. and Linda L. Price. (1987). The role of imagery in information
processing: Review and extensions. Journal of Consumer Researcha13(March),
473-491.

Mantel, Susan R, and Frank R. Kardes. (1999). The role of direction of comparison,

attribute-based processing, and attitude-based processing in consumer preference.
Jouraal of Consumer Research. 25(4), 335-352.

Marks, Lawrence and Michael Kamins. (1988). The use of product sampling and
advertising: Effects of sequence of exposure and degree of advertising claim
exaggeration on consumer' belief strength, belief conﬁdence, and attitudes.
Journal of Marketing Research, 25(August), 266-282.

Mathur, D. C. (1971). Naturalistic Philosophies of Experience. St. Louis, MO: Warren H.
Green, Inc.

McLuhan, M., and E. McLuhan. (1988). laws of media: The new science. Toronto
University: University of Toronto Press.

Meeker, Mary. (1997). The lntemet Advertising Report. New York, NY: HarperBusiness.

Mehta, Abhilasha. (2000). Advertising attitudes and advertising effectiveness. Journal of
Advertising Research. 40(3), 67-72.

78

Mitchell, Andrew and Jerry C. Olson. (1977). Cognitive effects of advertising repetition.
In Advances in Consumer Research 4, ed. William D. Perreault, Jr. Atlanta, GA:
Association for Consumer Research, 213-220.

Moore, Elizabeth S. and Richard J. Lutz. (2000). Children, advertising and product
experience: A multimethod inquiry. Journal of Consumer Research. 27(1), 31-48.

Muehling, Darrel D., Russell N. Laczniak, and J. Craig Andrews. (1993). Deﬁning,
operationalizing, and using involvement in advertising research: A review.
Jourml of Current Issues and Research in Advertising, 15(1), 21-57.

Nelson, Phillip. (1974). Advertising as information. Journal of Political Economy. 729-
754.

Norman, Donald. (1998). The Invisible Computer: Why Good Products Can Fail. the
Personal Computer is so Complex and Information Appliances are the Solution.
Cambridge: MIT Press.

Novak, Thomas P. and Donna L. Hoffman. (2000). Measuring the customer experience in
online environments: A structural modeling approach. Marketing Science. 19(1),
22-42.

O’Guinn, Thomas C., Chris T. Allen, and Richard J. Semenik. (1998). Advertising.
Cincinnati, OH: South-Westem College Publishing.

Olson, Jerry C. and Phillip A. Dover. (1979). Disconﬁrmation of consumer expectations
through product trial. Jouraal of Applied Psychology. 64(April), 179-189.

Peterson, R., S. Balasubramanian and B. Bronnenberg. (1997). Exploring the
implications of the intemet for consumer marketing. Journal of the Academy of
Marketing Science. 24. 329-346.

Petty, Richard E. and John T. Cacioppo. (1981). Attitudes and Persuasion: Classic and
Contemporary Approaches. Dubuque, IA: William C. Brown.

Petty, Richard. B, John T. Cacioppo and David Schumann. (1983). Central and
peripheral routes to advertising effectiveness: The moderating role of
involvement. Journal of Consumer Research. 10(September), 135-146.

Reeves, Byron, and Clifford Nass. (1996). The Media Equation. Palo Alto, CA: CSLI
Publications.

Richardson, Alan. (1984). The Experiential Dimension of Psychology. Queensland,
Australia: University of Queensland Press.

79

Sawyer, Alan G. (1981). Repetition, cognitive responses, and persuasion. In Cognitive
Responses in Persuasion, ed. Richard E. Petty et al. Hillsdale, NJ: Lawrence
Erlbaum Associates, 237-261.

Schlosser, Ann E. and Alaina Kanfer. (2001). Impact of product interactivity on
searchers’ and browsers’ judgments: Implications for commercial web site
effectiveness. Presented at the Society for Consumer Psychology Winter
Conference, Scottsdale, AZ. February 15-17.

Schiffman, Leon G. and Leslie Lazar Kanuk. (1997). Consumer Behavior, 6th ed., Upper
Saddle River, NJ: Prentice Hall, Inc.

Schuemie, Martijin J. and Charles Van Der Mast. (1999). Presence: Interacting in vr?.
Presented at the Twentieth Workshop on Language Technology. [Online]
Available http://is.twi.tudelft.nl/~schuemie/interactions.pdf.

Schubert, Thomas, Holger Regenbrecht, and Frank F riedmann. (2000). Real and illusory
interaction enhance presence in virtual environments. Presented at Presence: 3rd
International Workship on Presence. Delft, The Netherlands March 27-28.

Smith, Daniel C. and C. Whan Park. (1992). The effects of brand extensions on market
share and advertising efﬁciency. Journal of Marketing Research. 29(August), 296-
313.

Smith, Robert E. (1993) Integrating information from advertising and trial: Processes and
effects on consumer response to product information. Journal of Marketing
Research, 30(May), 204-219.

 

Smith, Robert E. and William R. Swinyard. (1982). Information response models: An
integrated approach. Journal of Marketirpg, 46(Winter), 81-93.

Smith, Robert E. and William R. Swinyard. (1983). Attitude-behavior consistency: The
impact of product trial versus advertising. Journal of Consumer Research.
29(August), 257-267.

Smith, Robert E. and William R. Swinyard. (1988). Cognitive response to advertising and
trial: Belief strength, belief conﬁdence and product curiosity. Journal of
Advertising. 17(3), 3-14.

Soukup, Charles (2000). Building a theory of multi-media cmc. New Media & Society.
2(4), 407-425.

Steuer, Jonathan. (1992). Deﬁning virtual reality: Dimensions determining telepresence.
Journal of Communication 42(4), 73-93.

 

Tauber, Edward M. (1972). Why do people shop? Journal of Marketing, 36(Oct.), 46-59.

80

Tedesco, Richard. (1999). Internet. Broadcasting & Cable. 129(1), 50.
Upshaw, L. (1995). The keys to building cyberbrands. Advertising Age, (May 29).

Urbany, Joel E., William O. Bearden, and Dan C. Weilbaker. (1988). The effect of
plausible and exaggerated reference prices on consumer perceptions and price
search. Journal of Consumer Research. 15(June), 95-110.

Vriens, Marco, Gerard H. Loosschilder, Edward Rosbergen, and Dick R. Wittink. (1998).
Verbal versus realistic pictorial representations in conjoint analysis with design
attributes. Journal of Product Innovation Management, 15, 455-467.

Waller, M. (1997). If reality is the best metaphor, it must be virtual. Diacritics. 27(3), 90-
104.

Wemerfelt, Birger. (1996). Efﬁcient marketing communication: Helping the customer
learn. Journal of Marketing Research. 33(May), 239-246.

Wright, Peter and Peter D. Rip. (1980). Product class advertising effects on ﬁrst time
buyers' decision strategies. Journal of Consumer Researcla7(September), 176-

188.
Wright, Alice A. and John G. Lynch-Jr. (1995). Communication effects of advertising
versus direct experience when both search and experience attributes are present.

Journal of Consumer Research. 21(March), 708-718.

Yuille, John C. and Michael J. Catchpole. (1977). The role of imagery in models of
cognition. Journal of Mental Imagery, 1, 171-180.

Zaichkowsky, Judith L. (1985). Measuring the involvement construct. Journal of
Consumer Research. 12(3), 341-352.

81

APPENDIX A

82

APPENDIX A

Pretest Survey

Completion of the survey will take approximately 15 minutes and your responses will
remain anonymous. While you may refuse to participate at any time, you are indicating
your voluntary agreement to participate by completing and returning this questionnaire. If
you have any question about the survey and study please contact Terry Daugherty at
(517) 355-8371, fax (517)432-2589, daughe13@msu.edu. In addition, if you have
questions about your rights and the use of human subjects in research please contact
David Wright, phone (517) 355-2180, fax (517)353-2976, ucrihs@msu.edu. Thank you
for your assistance!

 

1. If you were planning on purchasing a digital video camcorder, how would you rate the
evaluation of this product to you personally? As:

Unimportant 1 2 3 4 5 6 7 Important

Of no Of concern
concern 1 2 3 4 5 6 7 to me
Irrelevant 1 2 3 4 5 6 7 Relevant
Means a lot 1 2 3 4 5 6 7 Means nothing
Doesn't matter 1 2 3 4 5 6 7 Matters to me
Signiﬁcant

Insigniﬁcant 1 2 3 4 5 6 7 to me

2. Please rate your perceived quality of the following digital video camcorder brands.

Low High
Quality Quality
Sony 1 2 3 4 5 6 7
JV C l 2 3 4 5 6 7
Canon 1 2 3 4 5 6 7
Panasonic 1 2 3 4 5 6 7
Sharp 1 2 3 4 5 6 7

83

APPENDIX A - CONTINUED

3. Now imagine you are going to purchase a new digital video camcorder from a
reputable company. This will be a signiﬁcant purchase because you will be able to
record all of the meaningful things in your life and because you expect the product to cost
at least $1,000. As a result of this purchase, please list the most important product
attributes you would consider and evaluate in making your decision.

 

84

APPENDIX B

85

APPENDIX B

Experiment Protocol

. Ask each participant to sign-in

. Ask each participant to read and Sign consent form

. Assign subject to experimental condition (check appropriate ID number)

 

 

Condition Code ID # Condition Code @311
D-I 200, 201, etc. D-V 600, 601, etc.
I-V 300, 301, etc. I-D 100, 101, etc
V-D 500, 501 , etc V-1 400, 401, etc.

. Read introduction and administer Survey A

. Collect Survey A when all scheduled participants are ﬁnished and escort all
participants together into the laboratory and corresponding starting condition.

. Read instructions and begin experiment

. After 5 minutes, ask participants if they have any questions and then proceed to the
next experience appropriate for their condition.

. After 5 minutes, ask participants if they have any questions. Then read instructions
and administer Survey B.

. Once everyone is ﬁnished with Survey B debrief participants and thank them for their
participation.

86

APPENDIX B - CONTINUED

I-D Condition
The purpose of this study is to record your evaluation of the product in the Full
Spread Magazine Advertisement (meaning two full pages)— a video camcorder.
Please take the next few minutes to thoroughly examine the ad in order to
determine how you think and feel about the product.
Do you have any questions?
I will be back in ﬁve minutes to give you additional instruction-begin.

(After ﬁve minutes ask participants to proceed to the next condition)

Now please take the next ﬁve minutes to thoroughly examine the video camcorder
in order to determine how you think and feel about the product.

Do you have any questions?
I will be back in ﬁve minutes to administer a survey designed to record your
evaluation-begin

D - I Condition
The purpose of this study is to record your evaluation of the product - a video
camcorder. Please take the next few minutes to thoroughly examine the video
camcorder in order to determine how you think and feel about the product.
Do you have any questions?
I will be back in ﬁve minutes to give you additional instruction-begin.
(After ﬁve minutes ask participants to proceed to the next condition)
Now please take the next ﬁve minutes to thoroughly examine the Full Spread
Magazine Advertisement (meaning two full pages) for the video camcorder in
order to determine how you think and feel about the product.

Do you have any questions?

I will be back in ﬁve minutes to administer a survey designed to record your
evaluation-begin

87

APPENDIX B - CONTINUED

I - V Condition
The purpose of this study is to record your evaluation of the product in the Full
Spread Magazine Advertisement (meaning two full pages)— a video camcorder.
Please take the next few minutes to thoroughly examine the ad in order to
determine how you think and feel about the product.
Do you have any questions?
I will be back in ﬁve minutes to give you additional instruction-begin.
(After ﬁve minutes ask participants to proceed to the next condition)
Now please take the next ﬁve minutes to thoroughly examine the web site for the
video camcorder in order to determine how you think and feel about the product.
Navigation Instructions

There are three special features at your disposal to examine the product:

(1) To rotate the camcorder click and hold down the left mouse button while
moving the mouse in any desired direction.

(2) To zoom in or out click and hold down the right mouse button while either
pulling the mouse towards you or pushing the mouse further away from your
body.

(3) There are also information cues that tell you the components of the camera
when you move the mouse over them and you can even open the LCD display on
the side of the camera by clicking on it.

 

You may also open the LCD display on the side of the camcorder by clicking on
it.

Do you have any questions?

I will be back in ﬁve minutes to administer a survey designed to record your
evaluation-begin

88

APPENDIX B - CONTINUED

V-I Condition
The purpose of this study is to record your evaluation of the product in web site—
a video camcorder. Please take the next few minutes to thoroughly examine the
web site for the video camcorder in order to determine how you think and feel
about the product.
Navigation Instructions

There are three special features at your disposal to examine the product:

(1) To rotate the camcorder click and hold down the left mouse button while
moving the mouse in any desired direction.

(2) To gram in or out click and hold down the right mouse button while either
pulling the mouse towards you or pushing the mouse further away from your
body.

(3) There are also information cues that tell you the components of the camera
when you move the mouse over them and you can even open the LCD display on
the side of the camera by clicking on it.

You may also open the LCD display on the side of the camcorder by clicking on
it.

Do you have any questions?

I will be back in ﬁve minutes to give you additional instruction-begin.

(After ﬁve minutes ask participants to proceed to the next condition)

Now please take the next ﬁve minutes to thoroughly examine the Full Spread
Magazine Advertisement (meaning two full pages) for the video camcorder in
order to determine how you think and feel about the product.

Do you have any questions?

I will be back in ﬁve minutes to administer a survey designed to record your
evaluation-begin

89

APPENDIX B - CONTINUED

V-D Condition
The purpose of this study is to record your evaluation of the product in web site—
a video camcorder. Please take the next few minutes to thoroughly examine the
web site for the video camcorder in order to determine how you think and feel
about the product.
Navigation Instructions

There are three special features at your disposal to examine the product:

(1) To rotate the camcorder click and hold down the left mouse button while
moving the mouse in any desired direction.

 

(2) To Q03; in or out click and hold down the right mouse button while either
pulling the mouse towards you or pushing the mouse further away from your
body.

(3) There are also information cues that tell you the components of the camera
when you move the mouse over them and you can even open the LCD display on
the side of the camera by clicking on it.

You may also open the LCD display on the side of the camcorder by clicking on
it.

Do you have any questions?
I will be back in ﬁve minutes to give you additional instruction-begin.
(After ﬁve minutes ask participants to proceed to the next condition)

Now please take the next ﬁve minutes to thoroughly examine the video camcorder
in order to determine how you think and feel about the product.

Do you have any questions?

I will be back in ﬁve minutes to administer a survey designed to record your
evaluation-begin.

90

APPENDIX B - CONTINUED

D-V Condition
The purpose of this study is to record your evaluation of the product — a video
camcorder. Please take the next few minutes to thoroughly examine the video
camcorder in order to determine how you think and feel about the product.
Do you have any questions?
I will be back in ﬁve minutes to give you additional instruction-begin.
(After ﬁve minutes ask participants to proceed to the next condition)
Now please take the next ﬁve minutes to thoroughly examine the web site for the
video camcorder in order to determine how you think and feel about the product.
Navigation Instructions

There are three special features at your disposal to examine the product:

(1) To rotate the camcorder click and hold down the left mouse button while
moving the mouse in any desired direction.

(2) To zoom in or out click and hold down the right mouse button while either

pulling the mouse towards you or pushing the mouse further away from your
body.

(3) There are also information cues that tell you the components of the camera
when you move the mouse over them and you can even open the LCD display on

the side of the camera by clicking on it.

You may also open the LCD display on the side of the camcorder by clicking on
it.

Do you have any questions?

I will be back in ﬁve minutes to administer a survey designed to record your
evaluation-begin.

91

APPENDIX C

92

APPENDIX C

Survey A
The purpose of this questionnaire is to record background and preference information.
Completion of the survey will take approximately 10 minutes and your responses will remain

anonymous.

Thank you for your assistance!

 

1. Please tell us about yourself:
Gender: female male

How old are you?

What class are you? freshman senior
sophomore graduate student
junior

2. Please indicate your level of agreement with the following statements about yourself.

Strongly Strongly
Disagree Agree
When I feel happy, it is a strong type of exuberance. l 2 3 4 5 6

I would prefer complex to simple problems. I 2 3 4 5 6

My emotions tend to be more
intense than those of most people. 1 2 3 4 5 6

I like to have the responsibility of

handling a situation that requires a lot of thinking. 1 2 3 4 5 6
I get overly enthusiastic. l 2 3 4 5 6
Thinking is not my idea of fun. I 2 3 4 5 6
Sad movies deeply touch me. 1 2 3 4 5 6

I would rather do something that requires little thought
than something that is sure to challenge my thinking. 1 2 3 4 5 6

When something good happens, I am
usually much more jubilant than others. 1 2 3 4 5 6

93

APPENDIX C - CONTINUED

Strongly Strongly
Disagree Agree

1 try to anticipate and avoid situations where
There is a likely chance I will have to think in depth. 1 2 3 4 5 6 7

When I’m happy, I feel very energetic. 1 2 3 4 5 6 7
I ﬁnd satisfaction in

deliberating hard and for long hours. I 2 3 4 5 6 7
When I succeed at something,

my reaction is calm contentment. l 2 3 4 5 6 7
I only think as hard as I have to. l 2 3 4 5 6 7
When I do feel anxiety, it is normally very strong. 1 2 3 4 5 6 7

I prefer to think about small,
daily projects to long-tenn ones. 1 2 3 4 5 6 7

When I am excited over something,
I want to share my feelings with everyone. 1 2 3 4 5 6 7

I like tasks that require little
thought once I have learned them. 1 2 3 4 5 6 7

My heart races at the
anticipation of some exciting event. 1 2 3 4 5 6 7

The idea of relying on thought
to make my way to the top appeals to me. 1 2 3 4 5 6 7

When I know I have done something very well,
I feel relaxed and content rather than excited or elated. 1 2 3 4 5 6 7

I really enjoy a task that involves
coming up with new solutions to problems. 1 2 3 4 5 6 7

When I’m happy, I bubble over with energy. 1 2 3 4 5 6 7

Learning new ways to
think doesn’t excite me very much. 1 2 3 4 5 6 7

When I accomplish something
difﬁcult, I feel delighted or elated. l 2 3 4 5 6 7

94

APPENDIX C - CONTINUED

I prefer my life to be
ﬁlled with puzzles that I must solve.

Seeing a picture of some violent car accident
in a newspaper makes me feel sick to my stomach.

The notion of thinking abstractly is appealing to me.
My negative moods are mild in intensity.

I would prefer a task that is intellectual,
difficult, and important to one that is

somewhat important but does not require much thought.

When I do something wrong
I have strong feelings of shame and guilt.

I feel relief rather than satisfaction after
completing a task that required a lot of mental effort.

When things are going good,
I feel “on top of the world.”

I usually end up deliberating about
issues even when they do not affect me personally.

Strongly
Disagree

3 4
3 4
3 4
3 4
3 4
3 4
3 4
3 4
3 4

3. Please rate your perceived quality of the following video camcorder brands:

Low

Quality
Sony 1 2 3 4
J VC 1 2 3 4
Panasonic 1 2 3 4
Canon 1 2 3 4
Sharp I 2 3 4

4. Rate your level of computer experience:

None
1 2 3 4 5

95

High
Quality
6 7
6 7
6 7
6 7
6 7
Expert
7

APPENDIX D

96

APPENDIX D

Survey B
The purpose of this questionnaire is to record your evaluation of the product and
experience you have just had. Completion of the survey will take approximately 10

minutes and your responses will remain anonymous.

Thank you for your assistance!

 

1. Your mood. Please reﬂect how you currently feel by marking an X on the most
appropriate number.

Sad : : : : : : : : Happy

Bad mood : : : : : : : : Good mood

Irritable : : : I : : : : : Pleased

Depressed : : : : : : : : Cheerful

2. Product knowledge. Indicate your level of agreement with the following statements by
circling the most appropriate number.

Strongly Strongly
Disagree Agree

I feel very knowledgeable about the product I

just examined. ......................................... 1 2 3 4 5 6 7

If I had to purchase the product today, I would
need to gather very little information in order to
make a wise decision. ................................ 1 2 3 4 5 6 7

I feel very conﬁdent about my ability to judge the
quality of this product. ............................... l 2 3 4 5 6 7

97

APPENDIX D - CONTINUED

3. Product value. Indicate your level of agreement with the following statements by
circling the most appropriate number.

Strongly Strongly
Disagree Agree
The product offer represents an
extremely fair price. .................................... 1 2 3 4 5 6 7
At the price, this product is probably
worth the money. ........................................ 1 2 3 4 5 6 7
This product appears to be a great deal. ............... 1 2 3 4 5 6 7

4. Product evaluation. For each of the items below, circle the number that best describes
your overall feelings about the product you have evaluated.

Bad 1 2 3 4 5 6 7 Good
Unappealing 1 2 3 4 5 6 7 Appealing
Unpleasant 1 2 3 4 5 6 7 Pleasant
Unattractive 1 2 3 4 5 6 7 Attractive
Boring l 2 3 4 5 6 7 Interesting
Dislike 1 2 3 4 5 6 7 Like

5. Certainty of your responses. How certain are you of the accuracy of the responses you
gave in the previous question regarding your feelings toward the product?
Conﬁdent : : : : : : : : Not conﬁdent

Not sure : : : : : : : : Sure

Uncertain I I I I I I I I Certain

98

APPENDIX D - CONTINUED

6. Product involvement. How would you evaluate the relationship of this product to you?

Unimportant : : : : : : : : Important

Of no concern : : : : : : : : Of concern to
me

Irrelevant : : : : : : : : Relevant

 

Means a lot : : : : : : : : Means nothing
to me 1 2 3 4 5 6 7
Doesn’t matter: : : : : : : : Matters to me

 

Insigniﬁcant : : : : : : : : Signiﬁcant to
me

7. Purchase intention. How likely would you purchase this product?

 

Unlikely l 2 3 4 5 6 7 Likely
Improbably 1 2 3 4 5 6 7 Probable
Uncertain 1 2 3 4 5 6 7 Certain

Deﬁnitely 1 2 3 4 5 6 7 Deﬁnitely Not

99

APPENDIX D - CONTINUED

8. Imageg in your mind. How would you describe the imagery that occurred while
examining the materials?

Strongly Strongly

Lsagm Am:
The imagery was very
Clear 1 2 3 4 5 6 7
Vivid l 2 3 4 S 6 7
Intense 1 2 3 4 5 6 7
Lifelike 1 2 3 4 5 6 7
Sharp 1 2 3 4 5 6 7
Well-deﬁned 1 2 3 4 5 6 7

9. Viewingexperience. Please indicate how you felt during your viewing session placing
an X in the most appropriate space.

Stimulated : : : : : : : : Relaxed

Excited : : : : : : : : Calm

 

F renzied : : : : : : : : Sluggish

Jittery : : : : : : : : Dull

Wide-awake : : : : : : : : Sleepy

Aroused : : : : : : : : Unaroused

100

APPENDIX D - CONTINUED

10. Your conﬁdence. Finally, please indicate your overall level of conﬁdence in the
ratings that you have given during this evaluation.

 

 

Uncertain Certain
1 2 3 4 5 6 7
Not sure Sure
I 2 3 4 5 6 7
Not conﬁdent : : : : : : : : Conﬁdent

 

Thank you again!

101