AN ADAPTED ELABORATE LIKELYHOOD MODEL FOR ADVERGAMES
Abstract
The latest changes in markets’ dynamics and the new techniques in branded communication
determined advertisers to adapt old promotional methods to the new advertising environment. The
present paper proposes an adapted model after the original Elaborate Likelihood Model of Petty and
Cacioppo (1981) in a attempt to help understand the way that the branded message through advergames
is decoded by consumers and how the positive or negative attitude is build through central of peripheral
processing. This model is based on players’ motivation and level of self involvement as triggering
elements for the whole process and is built using elements that previous literature found to be relevant
for branded communication and advertising in video games.
Keywords: Elaboration Likelihood Model, advergames, purchase intention
JEL Classification: M37
1. Introduction
The decline of traditional mass-media in being an efficient advertising vehicle
determined advertisers to re-orientate their methods to new and innovative approaches. A
method relatively new is advergaming. Advergames represent video games constructed
around a brand or a product that are usually offered for free on special websites designed for
this kind of games or on the official site of the brands.
In this context, video games found a place among other advertising tools as a new
technique in communication with actual and potential clients. Measuring with precision the
effects of an advertising campaign based on video games is a difficult task, but there are a
few ways to measure it. An important indicator in this matter is the purchase intention of the
consumer and the general attitude towards that brand or product. Knowing if intentions for
purchasing a product really became actual sales is difficult to realise. So, advertises use
indicators like perception over a certain brand, the attitude about it, if a consumer has the
intention of buying that product or not, to measure if an advertising campaign is efficient or
not.
Many authors tried to understand how the new media works by modifying different
traditional advertising models to the new coordinated of the advertising practices that are
used recently by the most innovative advertisers. Previous literature highlights a number of
elements that used properly in an advergame construction leads to positive results. Among
these factors are brand recall, memory on short and long run, positive brand attitude, sharing
impression and recommendation for friends and family, purchase intention and final
acquisition. Advergames proved to be efficient in driving consumer through a couple of
stages of the acquisition process and to help brands in reaching their advertising purposes.
Based on this elements founded in previous literature on the field, this paper builds an
Elaborate Likelihood Model that fits in advergames context and adapts to the specifics of
online environment. The model presented in this paper in adapted from the original model
proposed by Petty and Cacioppo (1981) and has the purpose in helping to understand the
way that the branded message transmitted through advergames is processed by consumers
and how the positive or negative attitude is build through central of peripheral processing. In
the model, players’ motivation and level of self involvement are considered triggering
elements for the whole process.
In the past researches, many authors highlighted a series of elements that are
representative for communication through video games and are important in advergaming
design. On the other hand, different authors tried to adapt different types of traditional
advertising models to new advertising techniques. Starting from these elements, the adapted
ELM presented in this paper proposes a model which could open a path in the field of
adapted advertising models for advertising through online video games in general and
advergames in particular.
2. Background
2.1 Marketing techniques for measuring purchase intention
Previous studies about purchasing considered that intention is a relevant variable for
predicting the actual purchasing. Authors that used this assumption considered that
intentions are a good indicator of consumers’ purchase behaviour (Armstrong et al., 2000;
Chandon et al., 2005; Infosino, 1986; Jamieson and Bass, 1989).
Previous literature proposed different ways of measuring the actual purchase by
instating statistical model to forecast sales. Such papers include “a unified model that takes
in to account systematic intention biases, changes in true intentions over time, and the
imperfect correlation between true intentions and actual purchasing. It also unifies stated
intentions and purchasing“(Sun and Morwitz, 2010).
In marketing, purchase intention data were used for predicting the actual sales and for
making strategic decisions regarding the new and existing product and the planes to sustain
them on the market.
The use of purchase intension data in the case of new product helps managers in testing
different product - concepts and to decide over those that deserve further development or
those who present low potential and should not be launched.
In some studies (Sewall, 1978; Silk & Urban, 1978; Urban & Hauser, 1993), authors
considered that purchase intention data are important in planning the launch of a new
product, so managers use them for deciding over the target public and ways to reach it, by
choosing the geographical markets with higher potential and the customer segment to
address to.
Other studies (Morrison, 1979) considered that purchase intentions are used for
predicting the future demand for existing products. These forecasts are used for adjusting
the production levels, the size of the sales force or the price.
In advertising in particular, purchase intention information is used for pre-testing and
evaluation of the promotional plans, both for existing or new products.
In academic environment, purchase intention is considered an indicator of purchase
behaviour and used as a measure in determine the particular behavioural aspects. These
researchers fundament their studies on the theory of planed behaviour, which states that
intentions should only predict behaviour if the intentions are measured just prior to the
performance of the behaviour, and if the behaviour is under the individual's sole volitional
control (Ajzen, 1985).
Different studies found that it is a significant positive relationship between intent and
behaviour (Bemmaor, 1995; Clawson, 1971; Ferber and Piskie, 1965; Granbois and
Summers, 1975; Newberry et al., 2003; Pickering and Isherwood, 1974; Taylor et al., 1975),
while others contradict these facts by stating that the correlation for the intention–behaviour
relationship is not very strong (Sheppard et al., 1988).
In marketing research studies, a typical study may involve exposing respondents to a
new concept description and measuring both their attitude toward the concept and their
intentions to purchase it in the future. The respondents' intentions may change between the
time of the survey and the time of a subsequent actual purchase decision. In addition, a
respondent will provide his or her own intention to purchase the product, but other
individuals in the respondent's household may also play a role in the final purchase decision.
In a study conducted by Morwitz (Morwitz et al., 2007) the author found that the
strength of the relationship between respondents' stated intentions and their ultimate
purchase behaviour varies with the types of products that are studied and the way that these
data are collected. The author concluded over the factors that make the correlation between
purchase intention and actual sales:
a) For existing products than for new products;
b) For durable products than for non-durable products;
c) When respondents are asked to provide intentions to purchase specific brands or
models than when they are asked to provide intentions to buy at the product
category level;
d) When purchase levels are measured in terms of trial rates rather than total
market sales;
e) For short time horizons than for long time horizons; and
f) When intentions are collected in a comparative mode than when they are
collected monadically (autonomous).
2.2. ELM model and its use in advertising
In marketing literature, a special attention received the study of the way that consumer
involvement influences the individual response to marketing actions of companies.
In some author’s opinion (Andrew et. al, 1990), the consumer involvement refers to
“involvement direction” and the target of involvement such as an advertisement (Laczniak
et al., 1989; Wright, 1973) or a product (Bloch, 1984; Zaichkowsky, 1985, 1994). The role
of involvement is important in the individual processing of the information that the
consumer is exposed to or when he is facing the object of implication (Petty et al, 1983).
Several researchers were interest in understanding the stages that consumers go through
before they ultimately purchase a particular product. Multiple models tried to explain the
hierarchy of these stages. With this approach, first to develop a hierarchy-of-effects model
were Levidge and Steinger (1961). The authors explain the purchase process through a six
stage –model that consumers make before the actual acquisition: 1) awareness, 2)
knowledge, 3) liking, 4) preference, 5) conviction and 6) purchase.
Starting from this first study, many researchers developed and proposed numerous
studies that can explain the way that advertising works (Krugman, 1965; Ray et al., 1973;
Houston and Rothschild, 1978). The hierarchy-of-effects models have been used by many
practitioners and academicians for explaining advertising conceptual mechanisms (Preston,
1982).
Among these studies, Petty and Cacioppo (1981) proposed the Elaboration Likelihood
Model (ELM), which is considered one of the most comprehensive models that incorporates
consumers’ involvement in the processing of the information provided in the advertising
messages. This model became popular for its use as a principle in persuasion work.
The Elaboration Likelihood Model states that there are two routes through which
persuasive messages are processed: the central route, which provides complete information
and is straightforward, and the peripheral route, which uses means like catchy tunes,
colours, or celebrity endorsements. When consumers are highly involved in the
communication process they exert a complex cognitive processing effort known as high
elaboration likelihood. When this occurs, existing beliefs, initial attitude and argument
quality, which form the central cues, influence the persuasion effects.
When consumers’ level of involvement is low, they are either unable to process the
information received or are not willing to do so. In this case, the persuasion is influenced by
peripheral cues such as music, visual, or attractive sources, and the temporary attitude is
shifted or the consumer maintains his initial attitude.
With the introducing of new media and internet communication, the advertising theories
have been adapted and specific characteristic of the Internet environment and two-way
interaction from the traditional one-way exposure used by the old media.
In classical hierarchy of effects model, the persuasion process starts when consumer
become aware of a brand message through advertising exposure. In traditional media the
exposure is mostly involuntary as consumers come across an ad. Unlike this, internet
environment allows consumer to control the advertising exposure, which can be involuntary
or voluntary, depending on the types of Web advertising. In the case of online video games,
the consumer can be exposed to ads only with his consent, when we voluntary chose to play
a certain game.
In particular for the online environments, different authors applied the ELM in studied
regarding the way consumers’ response to advertising (Cho, 1999; Hershberger, 2003), and
proposed modified versions of the ELM for explaining the information processing when
consumers are exposed to web advertising.
3. Advergames and ELM adaptation
In Salen and Zimmerman (2004) opinion, a game is “a system in which players are
engage in an artificial conflict, defined by rules that result in a quantifiable outcome”. Thus,
a game is a structure in which the player is presented with a defined goal and he is
conditioned by challenges for reaching this goal”.
In the general assumption of a game design, the players accepts the game’s goals as
worth striving for and act in a way that is most likely to help them reach the game’s goal or
increase their score. When trying to accomplish the game quests, the players implicitly agree
with two important things. The first one is goal of the game, the player acting according to
game rules for reaching the goals. Second, accomplishing the game quests, player learns
how to face challenges and improves his game skills.
Yang and Wang (2008) consider that playing video games is actually a problem solving
process that implies accomplishing the quests, gaining point and complete the game.
Brands that appear in video games and use problem solving theory can become instruments
that can be used in the game for reaching the objectives of the game. In this way, brand
becomes relevant for the video game story and lead to a higher attention and more elaborate
processing of information, influencing the memory and the cognitive reaction to that brand.
As showed previously (Mau et al., 2010), excitement and connections produced during
a game session lead to a better attitude towards brand. The literature on the advergames is
growing with recent work on serious game design (Bergeron, 2006; Iuppa and Borst, 2006),
games for educational purposes (Gee, 2003; Shaffer, 2007), and more general perspectives
on games as means of persuasion (Bogost, 2007).
Persuasive communication, the first step of the Elaborate Likelihood Model (ELM)
triggers the entire processing system. If consumer is motivated to process then he will
elaborate the processing mechanism. If not, then the information will be passed in
background of thinking and will be processed in peripheral cognition (point 1). Rather a
message will take the central route or the peripheral route depends primarily on the
consumer’s level of involvement (Petty and Cacioppo, 1981).
Fig.1: Advergame Elaborate Likelihood Model
In advergaming communication the motivation and the personal involvement of the
player with the advergames is determined by the active choice of selecting the game from a
large category of available advergames and games attributed that are visible before actually
starting the game session like the design, description story and the promise of the final price
for accomplishing the game quests.
In a larger view, the existing literature approaches the consumers’ motivation in
different ways. In advertising, the consumer’s motivation is considered to be the
individual‘s desire or readiness to process brand information from an advertisement
(MacInnis et. al, 1991). In other words, a person is highly motivated when he is willing to
process the ad information. In other opinions, motivation is considered the personal
relevance of a message transmitted to public (Batra and Ray, 1985). According to this, the
desire to process the information is influenced by a range of situational circumstances, as
well as consumer characteristics.
In the same time, an intriguing and important research revealed that the personal
involvement of players in the game is in fact bad for the brand. A study about this issue
showed that the brand memory is lower when an adult person is highly involved with a
movie or game in which the brand was integrated (Grigorovici and Constantin, 2004;
Nelson et al, 2006). The reason is that, due to high involvement with the game, no cognitive
capacity remains available to process the brand. As a result, adults' brand memory is lower
in situations of high game involvement compared to low game involvement. High
involvement is correlated with high brand memory only in the case of teenagers and
children.
Consequently, when playing an advergame, high involvement with the game will
trigger a peripheral process, as the central processing will be occupied with understanding
and accomplishing the game rules and quests.
Ability to process a particular message (point 2) depends on internal factors, like
knowledge, previous experience, skills and personal schemata, as well as external factors as
the information attributes and content. Information attributes refers to the way that the
message is packaged, if the information is logic and easy to decode. If internal and external
factors are in accordance then that person will elaborate the process and will allocate
multiple cognitive resources for processing that message. If the two major factors are in
conflict, the message will be transfer to peripheral processing system.
When processing information, people use a personal way of acting and thinking about
things around them. Every time they process a new message, the information is processed in
the same way and people use each time the same pattern of thinking, named schemata.
Schemata represent an abstract structure of knowledge stored in the memory of a person
which influences all information processing. It is in fact a series of mental templates that
give a person’s knowledge about other people, situations or objects, and are formed from
prior knowledge and experiences.
The schemata concept, originally from psychological sciences, was adopted for
marketing communication to help understand the way that consumers analyse and
understand brand information transmitted through different communication channels.
In brand message processing, schemata influence overall information encoding.
Depending on how similar are the messages with the peoples’ existing objectives, they
choose to process the messages or ignore it (Wyer et al., 1982). After that, they will try to
adapt the information to their own schemata (Mandler, 1982).
In terms of advertising, people use schemata learned in time for deciding what message
to develop and which to dismiss from the large amount of messages that they get in contact
with every day. A great number of studies found that events which are slightly congruent
induce extensive processing and thinking, leading to positive evaluation of the message
(Campbell and Goodstein, 2001; Mandler, 1982; Meyers-Levy and Tybout, 1989).
Incongruent content, search attributes and experience in online environment are
elements that can trigger peripheral processing as peoples’ mind is set to dismiss all
information that don’t fit logically in the main context. Wright and Lynch (1995) concluded
that a consumer’s cognitive response tends to be stronger when the product is dominated by
search attributes rather than experience attributes (Nelson, 1974; 1981), leading to central or
peripheral processing. The reason is in the cognitive capacity of a consumer, limited during
the exposure time to advergames, which can reduce cognitive capacity and so be overcome
by the increased search attributes of the product.
When following a central route people base their attitude about the brand on logic
arguments, but when the level of involvement is low they follow a peripheral route which
will make them form their attitude based on other message elements. Peripheral processing
of a message (point 3) implies that a person is processing the information received in
conjunction with the main information centrally processed.
Video game environment creates situations that imply high levels of cognitive load.
Incongruence asks for higher cognitive elaboration so player will ignore all incongruent
advertising insertions and focus only on the game story line. In an experiment which
involves advertisements featuring multiple products and different cognitive loads, authors
(Lee and Shen, 2006) found that in conditions with high cognitive processing loads,
participants process congruent advertisements more easily.
In peripheral processing, telepresence can help consumer in decoding the advergaming
message and helps him form an opinion on the brand. Telepresence is defines as a feeling of
“being there” and was used as a determinant of brand recall in computer mediated
environment (Steuer, 1992; Grigorovici and Constantin, 2004; Nelson et al., 2006), and
advertising judgment (Nicovich, 2005) in the game environment. The argument behind these
studies is that direct experience is superior in persuading consumers than indirect experience
(Fazio and Zanna, 1981). Also, it is considered that mediation makes virtual experience feel
more similar and resembling to real environment (Klein, 2003).
In a video game context, telepresence is also used to determine the mediated experience
(Grigorovici and Constantin, 2004; Nelson et al., 2006; Nicovich, 2005) that users might
feel during a game. Previous studies also determined that interactivity and media richness
are determinants for telepresence in an advertisement context (Coyle and Thorson, 2001; Li
et al, 2002), giving a right context for testing consumer cognitive (Klein, 2003) and affective
responses (Coyle and Thorson, 2001; Nelson et al, 2006) to the brand.
Similar result regarding the level of telepresence and players’ involvement in the game
play was found by Nelson (Nelson et al., 2006) and Grigorovici and Constantin (2004) who
state that 3D web-based gaming environments could enhance the level of presence of
participants
In referring to the game context, Nelson (2002) observed that user control is a very
important feature of interactivity that results in a player’s feeling of being highly involved
with the brand, induces telepresence (Steuer, 1992) and forms a stronger and more positive
attitude toward the product (Roehm and Haugtvedt, 1999). This may lead to a positive
peripheral attitude shift (point 8). The forming of peripheral attitude can occur also in the
negative sense. When feeling persuaded, people tend to block the message and to reinterpret
it.
The persuasion knowledge model (Friestad and Wright, 1994; 1995) says that, a
consumer’s consciousness of being persuaded could motivate them to resist an
advertisement by avoiding it or by a “change of meaning in how they interpret the message”
(point 8).Prior research indicates that online game players spend time chatting and engaging
in social exchange that does not have a specific game benefit (Griffiths et al, 2003).
When the brand is integrated in the game context, understanding the message implies a
higher focus and needs to access the information about the brand that already exists in the
consumer’s memory, not allowing the elaboration of new opinions. If the player has already
formed an opinion about a brand previously to game, he will change very hard his beliefs. In
this case, he will not further process brand information and will remain with the impression
he already have about that brand (point 6). This happens also when a player forms an
opinion about an advergame based on his first interaction with the game as he will tend to
keep this opinion.
From another point of view, the change of initial attitude does not happened in the case
of pre-existing negative attitude. As authors discovered (Nelson et al, 2004), that consumers
that have a negative attitude about advertising in general will also have a negative reaction
to advertising in video games. They observed that players tend to be more positive about
brand they see in game. Also they concluded that product placement is more efficient when
this is done in a subtle way, as player tend to reject inappropriate advertising. The study
(Nelson et al, 2004) revealed that between attitude to advertising and purchase behaviour is
a weak correlation. These findings were confirmed in a study focused on Hispanic people
regarding the attitude about advergames (Hernandez et al., 2004).that
Previous studies showed that playing an advergame request higher levels of
involvement and attention than other types of media (Grigorovici and Constantin, 2004; Lee
and Faber, 2007). This indicated that a message will most of the time be processed centrally
(point 4) and the complex action will be analysed based on arguments, like game design,
interaction level and thematic connection between brand and video game.
Through repetition, a player can modify his attitude about a brand, leading to a change
in cognitive structure (point 5). This implies the forming a strong impression about the
advergame and the brand, which will be reinforced by playing again the game.
In many studies, the advergames were treated as an extension of the brand implying that
the meaning transfer occurs when consumer associate a conditioned stimulus such as the
brand, with a feature that is unconditioned, such as the game (Winkler and Buckner, 2006).
In this way, the positive feeling from the game play will transfer to the brand, resulting in
positive brand attitude (point 7). A direct consequence of this is that users’ experiences
from virtual environment when they are feeling mediated in the ‘real-world experience’
results in increased sales (Papadopoulou, 2007).
Conclusions
In understanding how consumers are processing branded information transmitted
through advergames a useful tool can be the adapted ELM model. We could see that the
nature of video games determines bought a central or a peripheral processing, depending on
the players motivation and level of self involvement.
Elements like thematic correlation between video game and brand, integration of the
product in game the story and the narrative structure of the game usually trigger central
processing. Unlike the central processing which is based on logical arguments, the
peripheral processing relies on elements as special sounds, design and colours, game action,
story line and interaction elements.
Considering these elements a brand can direct consumers towards one of the routs and
influence general attitude regarding the brand or the product, and trigger purchase intention.
For this to happen, brands have to be careful in the way they transmit the message so it
could be easy and correctly decoded by consumers. If the brand is deeply inserted into the
storyline of the game the players may be confused and could associate other meaning to the
product. Players would then not be influenced by the advergame and they will remain
indifferent to the brand or will keep their previous image about the brand.
Repeating the game experience and replaying the game affects players in two ways.
When consumers interpret the information using the central route, they form strong opinion
about the brand and reinforce their previous impression, tending to keep this opinion on the
long run. If they interpret the message through peripheral ways then consumers will be
susceptible of changing their opinions and attitude regarding that brand. Brands can use this
in directing consumers, on their second game experience towards central processing and so
reinforce consumers’ mental image about that brand.
Acknowledgment
This work was possible with the financial support of the Sectorial Operational
Programme for Human Resources Development 2007-2013, co-financed by the European
Social Fund, under the project number POSDRU/107/1.5/S/77946 with the title „Doctorate:
an Attractive Research Career”.
References
Ajzen, I. (1985) From intentions to actions: A theory of planned behaviour, J. Kuhl & J.
Beckmann (Eds.), Action control: From cognition to behaviour, Berlin: Springer–Verlag,
pp. 11−39.
Andrews, J. C., Durvasula, S., Akhter, S. H. (1990) A framework for conceptualizing and
measuring the involvement construct in advertising research, Journal of Advertising (19),
pp. 27–40.
Armstrong, J. S., Morwitz, V. G., Kumar, V. (2000) Sales forecasts for existing consumer
products and services: Do purchase intentions contribute to accuracy?, International Journal
of Forecasting, 16, 383−397.
Barry, Thomas (1987) The Development of the Hierarchy of Effects: A Historical
Perspective, Journal of Current Issues and Research in advertising, James H. Leigh and
Claude R Martin, Jr., eds.
Batra, R., Ray M., (1985) How advertising works at contact, In: L.F. Alwitt and A.A.
Mitchell, eds., Psychological processes and advertising effects: Theory, research and
Application, Hillside, NJ: Lawrence Erlbaum Associates, pp.13-43.
Bemmaor, A. C. (1995) Predicting behaviour from intention-to-buy measures: The
parametric case, Journal of Marketing Research, 32, 176−191.
Bergeron, B.P. (2006) Developing Serious Games, Hingham, Mass.: Charles River Media.
Bloch, P. H. (1984) Product involvement as leisure behaviour, Advances in Consumer
Research, 11, 197–202.
Bogost, I. (2007) Persuasive Games: The Expressive Power of Videogames. Cambridge,
MA: MIT Press.
Campbell, Margaret C., Goodstein, Ronald C. , (2001) The Moderating Effect of Perceived
Risk on Consumers' Evaluations of Product Incongruity: Preference for the Norm, Journal
of Consumer Research, 28 (3), 439-449.
Chandon, P., Morwitz, V. G., Reinartz, W. J. (2005) Do intentions really predict behaviour?
Self-generated validity effects in survey research, Journal of Marketing, 69: 1−14.
Cho, C.-H. (1999) How advertising works on the WWW: Modified Elaboration Likelihood
Model, Journal of Current Issues and Research in Advertising, 21: 33–50.
Clawson, C. J. (1971) How useful are 90 day purchase probabilities? Journal of Marketing,
No 35: 43−47.
Ferber, R., Piskie, R. A. (1965) Subjective probabilities and buying intentions, Review of
Economics and Statistics, 47: 322−325.
Coyle, J. R., & Thorson, E. (2001) The effects of progressive levels of interactivity and
vividness in web marketing sites. Journal of Advertising, 30(3), 65–78.
Fazio, R. H., Zanna, M. P., (1981) Direct experience and attitude - behaviour consistency, L.
Berkowitz (Ed.). Advances in experimental social psychology, Vol. 14, pp. 161–202, New
York: Academic Press.
Friestad, M., Wright, P. (1994) The persuasion knowledge model: How people cope with
persuasion attempts, Journal of Consumer Research, 21(1), 1–31.
Friestad, M., Wright, P. (1995) Persuasion knowledge: Lay people’s and researchers’ beliefs
about the psychology of advertising, Journal of Consumer Research, 22(1), 62–74.
Gee, J.P. (2003) What Video Games Have to Teach us About Learning and Literacy, New
York: Palgrave Macmillan.
Granbois, D., Summers, J. O. (1975) Primary and secondary validity of consumer purchase
probabilities, Journal of Consumer Research, 1: 31−38.
Griffiths, M. D., Davies, M. N. O., & Chappell, D. (2003) Breaking the stereotype: The case
of online gaming. Cyber Psychology & Behaviour, 6(1), 81–91.
Grigorovici, D., Constantin, C. (2004) Experiencing interactive advertising beyond rich
media: Impacts of AD type and presence on brand effectiveness in 3D gaming immersive
virtual environments, Journal of Interactive Advertising, No.5.
Hernandez, Monica D., Chapa, S., Minor, M.S., Maldonado, C., Barranzuela, F. (2004)
Hispanic Attitudes toward Advergames: A Proposed Model of their Antecedents, Journal of
Interactive Advertising, 5 (1).
Hershberger, E. K. (2003) eELM: A replication and enhancement of the Elaboration
Likelihood Model for computer mediated environments, Doctoral dissertation, Georgia State
University.
Houston, M.J., Rothschild, M.L., (1978) Conceptual and Methodological Perspectives on
Involvement, Research Frontiers in Marketing: Dialogues and Directions, Subhash C. Jain,
ed., Chicago: American Marketing Association, 184-187.
Infosino, W. J. (1986) Forecasting new product sales from likelihood of purchase Ratings
Marketing Science, 5:372−384. Iuppa, N.V., Borst, T. (2006) Story and Simulations for
Serious Games: Tales From the Trenches, Amsterdam; Boston: Elsevier.
Jamieson, L. F., Bass, F. M. (1989) Adjusting stated intention measures to predict trial
purchase of new products: A comparison of models and methods, Journal of Marketing
Research, 26: 336−345.
Morrison, D. G. (1979) Purchase intentions and purchase behaviour, Journal of Marketing,
43, 65−74.
Klein, L. R. (2003) Creating virtual product experiences: The role of tele-presence, Journal
of Interactive Marketing, 17(1), 41.
Krugman, Herbert E. (1965) The Impact of Television Advertising: Learning without
Involvement, Public Opinion Quarterly, 29, 349-356.
Laczniak, R. N., Muehling, D. D., Grossbart, S. (1989) Manipulating message involvement
in advertising research, Journal of Advertising, 18: 28–38.
Lavidge, Robert C. and Gary Steiner (1961) A Model for Predictive Measurements of
Advertising Effectiveness, Journal of Marketing, 25: 59-62.
Lee, Sang Yeal, Shen. Fuyuan (2006) Joint Advertising and Brand Congruity: Effects on
Memory and Attitudes, in American Academy of Advertising Conference Proceedings, 7374.
Lee, M., Faber, R. J., (2007) Effects of product placement in on-line games on brand
memory: A perspective of the limited-capacity model of attention, Journal of Advertising,
26(4), 75–90.
Li, H., Daugherty, T., & Biocca, F. (2002) Impact of 3-D advertising on product knowledge,
brand attitude, and purchase intention: The mediating role of presence. Journal of
Advertising, 31(3), 43–57.
MacInnis, D.J., Moorman,C., Jawarski, B.J., (1991) Enhancing and measuring consumers’
motivation, opportunity and ability to process brand information from ads, Journal of
Marketing, 55, 4, 32-53
Mandler, George (1982) The Structure of Value: Accounting for Taste, in Affect and
Cognition: The 17th Annual Carnegie Symposium, M.S. Clark and S.T. Fiske, eds.
Hillsdale, NJ: Lawrence Erlbaum Associates, 3-36.
Mau, G., Silberer, G., Gödecke, J. (2010) Game outcome and in-game advertising effects, in
R. Terlutter, S. Diehl, & S. Okazaki (Eds.), Advances in advertising research: Cutting edge
international research (Vol. 1) (pp. 159–170). Heidelberg: Springer-Gabler Verlag.
Meyers-Levy, Joan, Tybout, Alice M., (1989), Schema Congruity as a Basis for Product
Evaluation, Journal of Consumer Research, 16 (1), 39-54.
Morwitz, V.G., Stackel, J.H., Gupta, A. (2007) When do purchase intentions predict sales?,
International Journal of Forecasting 23: 347–364.
Nelson, P. (1974) Advertising as information, Journal of Political Economy, 83, 729–754.
Nelson, P. J. (1981) Consumer information and advertising, M. Galatin & R. D. Leiter
(Eds.), Economics of information, Boston: M. Nijhoff Publishers, pp. 42–60.
Nelson, M. R. (2002) Recall of brand placement in computer/video games, Journal of
Advertising Research, 42(2), 80–92.
Nelson Heejo Keum, Yaros, Ronald A. (2004) Advertainment or Adcreep? Game Players'
Attitudes toward Advertising and Product Placements in computer Games, Journal of
Interactive Advertising, 5 (1).
Nelson, M. L. (2005) Exploring consumer response to advergaming, .P. Haugtvedt, K. A.
Machleit, & R. F. Yalch (Eds.), Online consumer psychology: Understanding and
influencing consumer behaviour in the virtual world (pp. 167–194). Mahwah, NJ: Lawrence
Erlbaum.
Nelson, M., Yaros., R.A., Keum, H., (2006), Examining the influence of telepresence on
spectator and player processing of real and fictitious brands in a computer game, Journal of
Advertising, 35, 1, 87–99.
Newberry, C. R., Kleinz, B. R., Boshoff, C. (2003) Managerial implications of predicting
purchase behaviour from purchase intentions: A retail patronage case study, Journal of
Services Marketing, 17: 609−618.
Nicovich, S. G. (2005) The effect of involvement on ad judgment in a video game
environment: The mediating role of presence, Journal of Interactive Advertising, 6(1).
Papadopoulou, P., Applying virtual reality for trust-building e-commerce environments,
Virtual Reality, 2007, 11(2), pp. 10 - 12.
Petty, R.E., Cacioppo, J T., (1981) Central and Peripheral Routes to Persuasion:
Applications to Advertising, Advertising and Consumer Psychology, L. Percy and A. G.
Woodside, eds., Lexington, MA: Lexington Books, pp.3-24.
Petty, R. E., Cacioppo, J. T., Schumann, D. (1983) Central and peripheral routes to
advertising effectiveness: The moderating role of involvement, Journal of Consumer
Research, 10, 135–146.
Preston, Ivan L (1982) The Association Model of the Advertising Communication Process,
Journal of Advertising, 11: 3-15.
Pickering, J. F., Isherwood, B. C. (1974) Purchasing probabilities and consumer buying
behaviour, Journal of the Market Research Society, 16: 203−226. Ray, Michael L, Sawyer,
T., Heeler, Strong, Reed (1973) Marketing Communication and the Hierarchy of Effects,
New Models for Mass Communication Research, Peter Clark, ed., 147-176.
Roehm, H. A., Haugtvedt, C. P. (1999) Understanding interactivity of cyberspace
advertising, In D. W. Schumann & E. Thorson (Eds.), Advertising and the world wide web,
NJ: Lawrence Erlbaum, pp. 27–39.
Mahwah, S.K., Zimmerman, E. (2004) Rules of Play - Game Design Fundamentals,
London: MIT Press.
Sewall, M. A. (1978) Market segmentation based on consumer ratings of proposed product
design, Journal of Marketing Research, 15, 557−564.
Shaffer, D.W. (2007) How Computer Games Help Children Learn, New York: Palgrave
Macmillan.
Sheppard, B. H., Hartwick, J., Warshaw, P. R. (1988) The theory of reasoned action: A
meta-analysis of past research with recommendations for modifications and future research,
Journal of Consumer Research, 15:325−343.
Silk, A. J., & Urban, G. L. (1978) Pre-test market evaluation of new packaged goods: A
model and measurement methodology, Journal of Marketing Research, 14, 1−29.
Steuer, J. (1992) Defining virtual reality: Dimensions determining telepresence, Journal of
Communication, 42(4), 73–93.
Sun, B., Morwitz, V.G., (2010) Stated intentions and purchase behaviour: A unified model,
International Journal of Research in Marketing 27: 356–366.
Taylor, J.W., Houlahan, J. J. ,Gabriel, A. C. (1975) The purchase intention question in new
product development, Journal of Marketing, 39: 90−92.
Urban, L. G., Hauser, J. R. (1980) Design and marketing of new products, Englewood
Cliffs, NJ: Prentice-Hall.
Winkler, T., Buckner, K. (2006) Receptiveness of gamers to embedded brand messages in
advergames: Attitudes towards product placemen, Journal of Interactive Advertising, 7(1)
Wright, P. L. (1973) The cognitive process mediating acceptance of advertising, Journal of
Marketing Research, 9: 53–62.
Wright, A. A., Lynch, J. G. Jr., (1995) Communication effects of advertising versus direct
experience when both search and experience attributes are present, Journal of Consumer
Research, 21(4), 708–718.
Yang, Heng-Li, Wang ,Cheng-Shu, (2008) Product Placement of Computer Games in
Cyberspace, Cyber Psychology and Behaviour, 11, 4, 399–404.
Zaichkowsky, J. L. (1985) Measuring the involvement construct, Journal of Consumer
Research, 12: 341–351.
Zaichkowsky, J. L. (1994) The personal involvement inventory: Reduction, revision, and
application to advertising, Journal of Advertising, 23: 59–69.