An Individual’s Two Thinking Systems in Online C2C Auctions
Sang Cheol Park
Department of Business Administration, Daegu University, Gyeonsangbuk-do, Republic of Korea
Keywords: Two Thinking Systems, Escalation of Commitment, Cognitive Absorption, Online Auction.
Abstract: With regard to dealing with an individual decision processing approach, little empirical work has been
conducted to explain bidders’ behavior by adopting two thinking systems processes, such as the controlled
and uncontrolled thinking systems. Therefore, this research attempts to address the two thinking system
architecture of an individual’s decision in online bidding context. By constructing our research model from
the perspective of two thinking systems, this study can provide an alternative theoretical lens by which
online bidders may be viewed, thus bolstering our current understanding as to how willingness to continue
bidding is driven.
1 INTRODUCTION
For a long time, economists have maintained that
human behavior is best described by the rational
economic model, which basically holds that man is
self-interested and capable of perfectly weighing the
costs and benefits in every decision he makes, thus
enabling him to optimize the outcomes (Ariley,
2008). Although human beings do, in fact,
frequently make rational decisions; this does not
necessarily mean that they do this all, or even most
of the time. They often tend to make intuitive or
impulsive decisions, as well. For instance, people
frequently continue to make bets, even though they
know they may lose money by gambling. Therefore,
it is critically important to take both rational and
irrational aspects of decision-making into
consideration, so as to more completely understand
the decision-making processes of human beings.
Despite the effective transaction mechanism that
exists among sellers and buyers in many online
auction sites such as eBay, some bidders behave
irrationally by making continuous bids, even when
the bidding price has reached a much higher price
than the reference price. Furthermore, some bidders
tend to lose track of time while they are engaged in
auctions, use auctions to alter their moods, and
spend far more money than they had initially
expected, in a fashion similar to the gambling
situation referenced above (Peter and Bodkin, 2007).
Hence, in an effort to elucidate online bidding
behavior involving uncontrolled decision-making as
well as rational decision making, we have attempted
to address both the irrational and rational
architecture of an individual’s decision-making in
the context of online bidding.
Previous literature concerning online auctions has
relied principally on economic theories in making
predictions regarding continuous bidding behavior,
assuming the rationality of human beings. Empirical
studies of auction outcomes have principally been
described in terms of the rational decision model, in
which auction design, seller feedback, and bidder
behaviors affect auction outcomes (Bapna et al.,
2004; John and Zaichkowsky, 2003). Despite often-
voiced concerns regarding online bidding behavior
associated with the controlled and uncontrolled
decision approaches, surprisingly little research has
been conducted thus far into the factors that may
lead to such behaviors.
Hence, this study attempts to answer the following
research questions, in order to provide a more
complete picture of the bidding process and to fill
gaps in the previous relevant literature:
1) What are the controlled and uncontrolled
factors affecting bidders’willingness to continue
bidding as bidders increase?
2) To what extent do these determinants explain
a bidder’s willingness to continue bidding by
depending on product involvement?
In an effort to evaluate these research objectives, this
study has adopted a dual approach including two
types of human nature, such as the automatic and the
controlled decision-making system. According to
351
Park S..
An Individual’s Two Thinking Systems in Online C2C Auctions.
DOI: 10.5220/0005481603510357
In Proceedings of the 11th International Conference on Web Information Systems and Technologies (WEBIST-2015), pages 351-357
ISBN: 978-989-758-106-9
Copyright
c
 2015 SCITEPRESS (Science and Technology Publications, Lda.)

Thaler and Sunstein (2009), as the mechanisms
relevant to human brains are complex and
mysterious, the behavior of human beings is
frequently paradoxical, appearing simultaneously
“smart”and “dumb”. In order to systematically
approach this complexity, Thaler and Sustenin have
proposed two systems of thinking: the automotive
system based on intuitive thinking, and the
controlled (reflective) system based on rational
thinking. Some of the relevant psychological
literature also refers to these two systems as Systems
1 and 2. The automatic system is both rapid and
instinctive, and is not generally associated with
actual thinking. On the other hand, the reflective
system is the thinking system; it is more deliberate
and self-conscious than the other system. In the
context of this dual architecture of human brains,
this study has identified several constructs--such as
escalation of commitment, cognitive absorption,
perceived usefulness and ease of use--as antecedents
of willingness to continue bidding.
2 BACKGROUND
2.1 Online Bidder’s Behavior
Although auctions have been extensively studied in
previous economics and management literature
(John and Zaichkowsky, 2003), many research
questions of relevance to online auctions, such as
continuous online bidding behavior, remain. Table 1
lists several studies seeking to identify the factors
that affect auction outcomes.
One stream of empirical research is focused
principally on econometric models in which auction
design, seller feedback, or a bidder’s strategy affects
the outcomes (Angst et al., 2008; Banpa et al., 2004;
Gilkeson and Reynolds, 2003). This stream assumes
bidders’ controlled behavior.
The other stream of research describes some
irrational bidding behaviors (Park et al., 2012).
Ariely and Simonson (2003) demonstrated
previously that overpayment in online auctions can
be conceptualized as an uncontrolled bidding
behavior, as the bidders lose their self-control or
overparticipate in the bidding process. In the case of
bidders’ uncontrolled decision-making, it is possible
that even an ordinary person (not an addicted
individual) can make bids and may behave not only
in accordance with their own goal-oriented mindsets,
but also as a reaction to competitors in a bidding
process. However, neither the former nor the latter
explanation is adequate to elucidate why continuous
bidding behavior appears to occur simultaneously
from both controlled and uncontrolled decision
perspectives.
Therefore, this study attempted to explain why a
bidder continues to bid during a bidding process, via
a dual-system approach. This study considers the
controlled decision-making view to encompass
rational decision-making, whereas the automatic
decision view entails irrational decision-making.
2.2 Two Thinking Systems
The information processing approach is a framework
that provides characteristics of perception, memory,
decision, and attention. Schneider and Shiffrin
(1977) asserted that human performance, in terms of
information processing, is the consequence of two
different processes: automatic and controlled
processing. These qualitatively different processes
are reviewed with an emphasis on applications to
research. For example, automatic processing is a
rapid and parallel process, which is not limited by
short-term memory. Furthermore, it requires little
subject effort, and permits little direct subject
control, but requires extensive and consistent
training to develop. On the other hand, controlled
processing is a comparatively glacial and serial
process, which is limited by short-term memory and
also requires subject effort and permits a large
degree of subject control, although it requires little
training to develop. That is, automatic processes are
assumed to be involuntary, to require no attention,
and to be relatively rapid, whereas controlled
processes are assumed to be voluntary, to require
attention, and to be relatively slow.
Moors and De Houwer (2006) also reviewed the
characteristics that distinguish automatic processes
from controlled processes, as follows: First, one of
the most important distinctions between automatic
and controlled processes is the degree to which
actions are subject to conscious control. Control is
the ability or propensity to monitor, alter, change, or
discontinue engaging in a specific behavior. It can
reduce the degree to which a task can be
automatically performed. The second difference is
the degree to which conscious intention is present.
When peoples’ activities are automatic, they tend to
be more likely to occur autonomously―in that they
appear to occur on their own in the absence of
central control--as the actor does not actually
consciously intend to engage in those activities. A
third characteristic of the automatic process is its
inherent attentional efficiency. Generally speaking,
activities associated with automatic processes occur
WEBIST2015-11thInternationalConferenceonWebInformationSystemsandTechnologies
352

with a minimum of attentional capacity, which
leaves more capacity for the performance of other
tasks. Another major distinction between automatic
and controlled processes is a sort of increased speed
approach (Schneider and Shiffrin, 1977). As the
performance of a task may involve automatic
processes, people tend to learn to carry out their
tasks with increasing rapidity. According to the
instance-based view adopted by Logan (1998), the
way that a task is performed tends to change
fundamentally as the performers of those tasks
become increasingly practiced. The performance of
a task in the initial stage tends to be conscious and
deliberate, involving memory efforts and
information searches. After sufficient practice, the
performance of the task changes from the deliberate
mode to the quick and simple mode. Therefore,
people can perform their tasks more quickly by
optimizing the retrieval of information, which is
made possible by extensive practice. On the other
hand, automatic processes can be quite difficult to
stop or modify, owing partly to the fact that they
involve relatively little in the way of conscious
monitoring. Therefore, people frequently make
absentminded mistakes when engaged in automatic
processing.
After all, this study can apply this dual decision
process, which includes automatic and controlled
processes, to online bidding behaviors such as
willingness to continue bidding. Within the context
of bidding surroundings, bidders tend to make
further bids when they are engaged in automatic or
controlled decision processes. Meanwhile, as bidders
are operating in accordance with the controlled
decision process, their bidding behavior tends to be
both conscious and deliberate, involving arduous
memory and information searches during the
bidding process. Therefore, bidders generally
attempt to take into consideration whether or not the
online bidding process will prove useful for them,
due to the degree of their product involvement. As
shown in Table 1, this study attempts to explain
online bidding behavior via the application of the
above two thinking systems.
As for the automatic process, this study has
identified cognitive absorption; as for the controlled
process, this study has identified the escalation of
commitment.
2.2.1 Escalation of Commitment
As mentioned previously, according to Logan’s
instance-based view, the performance of a task in its
early stages tends to be conscious, deliberate, and
Table 1: Applications of two thinking processes to online
bidding behavior.
Uncontrolled
decision
process
Application of the automatic process to
online bidding behavior
Uncontrolled
Bidders may not control their bidding
behavior during the bidding stage
Effortless
Bidders tend to automatically make
bids without efforts such as comparing
the prices of listed items.
Associate
Bidders are considering obtaining the
items as winning the bidding among
the bidding competition.
Fast
Bidders tend to make decisions more
quickly.
Unconscious
Bidders tend to precede their biddings
without consciousness.
Controlled
decision
process
system
Application of the controlled process to
online bidding behavior
Controlled
In considering bidding behavior,
bidders can control their own behavior.
Effortful
Bidders tend to make lots of efforts to
make bids with prudence.
Deductive
Bidders tend to participate in the
bidding process by recognizing the
bidding patterns of other bidders.
Slow
The speed of bidders’ decision making
is quite slow.
Self- aware
Based on the controlled thinking
system, bidders who are self-aware
tend to make decision whether they
make bids further.
arduous. After achieving sufficient practice, task
performance shifts from the deliberate mode to the
quick and simple mode. Thus, it can prove quite
difficult to halt or modify the performance of the
task. Thus, the escalation of commitment involving
continued commitment can be explained in
accordance with the characteristics of Logan’s
instance view.
Escalation has traditionally been defined as a
continued commitment to a previously selected
course of action, despite negative feedback
regarding the viability of such a course of action
(Keil et al., 2000). The models of an individual’s
escalating commitment to failing courses of action
have a long history in the disciplines of management
and psychology (Ku et al., 2005). Psychologically
speaking, the escalation of commitment is defined as
a situation in which “investment decisions have gone
astray when standing before setback or loss, [and
thus] the decision maker faces a painful
dilemma”(Fox and Hoffman, 2002). Escalation of
commitment has been previously referenced in a
AnIndividual'sTwoThinkingSystemsinOnlineC2CAuctions
353

number of situations, including loan decisions,
competitive bidding and entrapment situations.
Considering the characteristics of the escalation
of commitment, this study proposes three key
constructs derived from three prominent theories on
the basis of individuals’ judgment process in the
literature regarding escalation: the prospect theory,
the self-justification theory, and the approach
avoidance theory (Festinger, 1957; Kahneman and
Tversky, 1979).
First, psychological sunk costs constitute the
core component of the prospect theory. In this study,
psychological sunk costs are defined as the extent to
which the psychological losses generated from the
discontinuance of bidding are regarded as a reason
for a bidder to bid. In accordance with this
perspective, previous efforts and time for bidding
are manifestly sunk costs (Ku et al., 2005). That is,
the bidders would continue their bidding because
they had already invested time and effort in the
bidding process. As such, psychological sunk costs
lead to escalation behavior.
Secondly, the self-justification theory holds that
people tend to escalate their bid because they feel
compelled to prove the rationality of their prior
decision to others. Therefore, this study extracts the
self-justification construct derived from the self-
justification theory (Keil et al., 1995). Self-
justification is defined as the extent to which a
bidder attempts to defend himself psychologically
against perceived errors in judgment. We may
surmise that bidders continue to bid because they are
attempting to convince themselves that their initial
bid for the item was, indeed, a sound idea.
Finally, the approach avoidance theory holds that
people tend to persistently encourage their own
behavior, owing to their proximity to the goal
(Brokner and Rubin, 1985). The completion effect,
which is derived from the approach avoidance
theory, claims that the motivation to attain a goal
increases as an individual draws closer to his
original objective. In this study, this study regards
the completion effect as one of the principal
motivations for the escalation of commitment,
reflecting pressures to end an auction. The
completion effect is defined as the degree to which a
bidder perceives that a sound rationale exists for
continuing the bidding process at the end of the
auction period. Bidders tend to be willing to finish
their bidding process prior to the closing of the
auction, as a result of the pressure to complete such
a process.
2.2.2 Cognitive Absorption
This study also considers cognitive absorption to be
a determinant of the uncontrolled decision-making
process on bidders’ willingness to continue bidding.
As cognitive absorption can be a deep commitment
without controlling actions, this study can regard
cognitive absorption as one of the most salient
factors from the automatic processes perspective.
Cognitive absorption is derived from three
theoretical bases in individual psychology (Agarwal
and Karahanna, 2000): theories regarding absorption,
the state of flow (Csikszentimihalyi, 1990), and the
notion of cognitive engagement (Agarwal and
Karahanna, 2000).
First, the trait of absorption describes a state of
deep attention, in which the individual is utterly
absorbed in the event being experienced. Some have
a propensity to experience this state to a more
profound degree than others. Absorption has been
defined as an individual disposition or trait, or an
intrinsic dimension of personality, which results in
episodes of total attention in which the totality of an
individual’s attentional resources are consumed by
the object of attention. Secondly, the theory of flow
is closely related to cognitive absorption.
Csikszentimihalyi (1990) first proposed the notion
of flow experience, and developed the flow theory.
According to the definition proposed by
Csikszentimihalyi, flow is a state in which an
individual is so immersed in an activity that nothing
else seems to matter. The dimensions of flow
include intense concentration, a sense of being in
control, a loss of self-consciousness, and a
transformation of time. Furthermore, Trevino and
Webster (1992) previously noted that flow might
constitute a critical factor in interactions between
humans and computers, and further suggested that
the dimensions of flow experience in the IT context
included control, attention focus, curiosity, and
intrinsic interest.
Finally, the notion of engagement is associated
with perceived playfulness. From the perspective of
cognitive engagement, engagement is associated
with the state of playfulness, and the state of
playfulness corresponds directly to the flow
experience. Webster and Ho (1997) presented the
engagement as flow without the notion of control.
Therefore, the engagement has been proposed to be
multi-dimensional, but is limited to the dimensions
of intrinsic interest, curiosity, and attention focus.
When reviewing the literature relevant to the notion
of cognitive absorption, there appears to be
considerable overlap among studies, despite certain
WEBIST2015-11thInternationalConferenceonWebInformationSystemsandTechnologies
354

discrepancies in conceptualization. Consistent with
prior research arguing for a multi-dimensional
conceptualization of this construct, Agarwal and
Karahanna (2000) defined cognitive absorption as “a
state of involvement with software” that occurs in
five dimensions: temporal dissociation, focused
immersion, heightened enjoyment, control, and
curiosity. Their definitions of the sub-constructs of
cognitive absorption are as follows:
“Temporal dissociation was defined as the inability
to register the passage of time while engaged in
interaction. Focused immersion was defined as the
experience of total engagement where other
attentional demands are ignored. Heightened
enjoyment was defined as capturing the pleasurable
aspects of the interactions. Control was defined as
representing the user’s perception of being in charge
of the interaction. And finally, curiosity was defined
as tapping into the extent to which the experience
arouses an individual’s sensory and cognitive
curiosity”(Agarwal and Karahanna, 2000).
In the online bidding context, Peter and Bodkin
(2007) asserted that some bidders tend to lose track
of time while they are engaged in online auctions,
use auctions to alter their moods, and spend far more
money than they initially expected. Thus, this study
can apply cognitive absorption to explain online
bidders’behavior, since it is a combination of the
retention and maintenance of one’s curiosity, the
feeling of being in control, losing track of time,
being focused, and having fun (Agarwal and
Karahanna, 2000). As this definition has been
broadly accepted by researchers in the field,
therefore, this study has also adopted this definition
of cognitive absorption, which consists of temporal
dissociation, focused immersion, heightened
enjoyment, control, and curiosity as the primary
factors that influence bidder’s willingness to
continue bidding as an uncontrolled decision process
in the context of the online auction.
2.2.3 Product Involvement
Product involvement can be considered a critical
function in the consumer persuasive process
(Zaichkowsky, 1985). It has been referred to as
perceived personal importance or the degree of
perceived personal relevance toward a specific
object (Zaichkowsky, 1985).
According to the theoretical background of
product involvement, it is a psychological construct
proposed by Sherif and Cantril (1947), who
described involvement as the state of an organism
when presented with any ego-central stimulus, or
when any stimulus is either consciously or
subconsciously related to the ego. They also
presented what is known as social judgment theory,
which explained individuals’ contrast and
assimilation effects in terms of the adaptation level
(latitude of rejection, latitude of non-commitment,
and latitude of acceptance). In particular, the theory
also predicts that as involvement (the perceived
relevance or importance of an issue) increases, the
latitude of acceptance decreases and the latitude of
rejection increases. Namely, the range of decisions
that are regarded as acceptable or unacceptable
varies depending on the level of involvement. Thus,
the central idea of this theory is that attitude change
is mediated by the judgmental processes and effects
used to persuade people.
Next, the elaboration likelihood model (ELM)
could be a theoretical basis of product involvement.
ELM involves multiple persuasion processes, such
as changes in attitudes (Petty et al., 1983). This
theory holds that a specific variable can function to
either increase or reduce persuasion, depending on
its contextual role (Petty et al., 1983). According to
ELM, when individuals’ levels of motivation or
personal relevance are low, their attitude can be
altered by relatively low-effect processes, which are
referred to as the peripheral route to persuasion. On
the other hand, individuals’ attitudes can be altered
by relatively high-effect processes which are
referred to as the central route to persuasion, when
their motivation or own level of relevance is high.
Namely, people tend to follow the central route
when their attitudes change due to relatively large
quantities of issue-relevant elaboration, while people
are more likely to follow the peripheral route when
attitudes change as the result of relatively low
quantities of issue-relevant elaboration. In sum, the
central route involves attitude changes requiring a
great deal of effort and thought to make a decision,
whereas the peripheral route involves attitudinal
changes when elaboration is low (Petty et al., 1983).
By applying the ELM into our research context,
highly-involved bidders tend to make further bids, as
they tend to be more interested in their own
perception of the relevance of a product. On the
other hand, less-involved bidders often attempt to
react via the peripheral route, such as the attributes
of cognitive absorption, rather than the relevance of
the product’s attributes during the auction.
Many relevant studies on product involvement
have illustrated that the degree of involvement can
affect the consumers’ learning process (Doong et al.,
2010). According to Novak et al. (2000), product
involvement exerts a significant impact on a
AnIndividual'sTwoThinkingSystemsinOnlineC2CAuctions
355

consumer’s experiences and behavior in the context
of online purchasing. From our review of the
relevant literature, this study can surmise that there
exists a significant role in product involvement in
terms of the process of bidding decision-making in
the online auction.
Thus, this study anticipates that online bidders
with high levels of product involvement tend to
make multiple bids based on controlled decision-
making, whereas bidders with a lesser degree of
product involvement are more likely to be affected
by cognitive absorption based on uncontrolled
(automatic) decision-making, as opposed to the
essential characteristics of a product.
3 RESEARCH MODEL
In an effort to evaluate a bidder’s willingness to
continue bidding, this study explores herein why
online bidders make more bids during the bidding
process on the basis of uncontrolled and controlled
processes. This study regards the construct of
cognitive absorption as proposed by Agarwal and
Karahanna (2000) to be a reflective construct, as it
consists of multiple dimensions, whereas the
escalation of commitment deriving from three
different theories--prospect theory, justification
theory, and approach avoidance theory--will be
regarded as a formative construct.
This study also regards product involvement as
the critical role in bidders’ decision-making process,
like controlled or uncontrolled factors. The
dependent variable in this study, the willingness to
continue to bid, is defined as the extent to which a
bidder intends to bid again, even though the bidding
process already evidences poor prospects for
success. The relevant research model is shown in
Figure 1.
4 EXPECTED CONTRIBUTIONS
This study attempts to explain the bidder’s bidding
behavior from the perspectives of controlled and
uncontrolled decision-making processes. Much of
the previous work conducted thus far regarding
online auctions has neglected to examine online
bidding behavior from both controlled and
uncontrolled decision-making perspectives.
In comparison with each characteristic of these
two processes, this study applied them to online
bidding behavior by illustrating the escalation of
Figure 1: A proposed research model.
commitment from the controlled process view as
well as by presenting cognitive absorption from the
automatic process view. By applying these
constructs to online auction surroundings, this study
attempted to present both controlled and
uncontrolled decision processes in order to
determine why bidders continue to make bids. This
may constitute a significant theoretical improvement
in tracing the determinants of a bidder’s willingness
to continue bidding. The principal contribution of
this study, in fact, was that both views have been
clarified and refined, and thus can now better
explain a bidder’s behavior.
In particular, this study evaluated the concept of
the escalation of commitment from three prominent
theories on the basis of an individual’s judgment
process in the escalation literature: the prospect
theory, the approach avoidance theory, and the self-
justification theory as representative constructs,
involving the controlled decision process
perspective.
Additionally, this study has proposed that online
bidders’ behaviors can be evaluated on the basis of
their cognitive absorption, on the basis of the
uncontrolled decision process perspective. As this
study attempted to apply cognitive absorption, which
consists of five sub-constructs in the uncontrolled
decision process, this study found that bidders might
precede their bidding unconsciously during the
auction.
REFERENCES
Ariley, D., 2008. Predictably irrational- the hidden forces
that shape our decisions, Harper.
WEBIST2015-11thInternationalConferenceonWebInformationSystemsandTechnologies
356

Angst, C. M., Agarwal, R. and Kuruzovich, J. H., 2008,
Bid or buy? individual shopping traits as predictors of
strategic exit in on-line auctions. International Journal
of Electronic Commerce, 13(1), 59-84.
Ariely, D. and Simonson, I. 2003. Buying, bidding,
playing, or competing? - value assessment and
decision dynamics in online auctions, Journal of
Consumer Psychology, 13(1), 113-123.
Agarwal, R. and Karahanna, R., 2000, Time flies when
you’re having fun: cognitive absorption and beliefs
about information technology usage, MIS Quarterly,
24(4), 665-694.
Bapna, R., Goes, P., Gupta, A., and Jin, Y. 2004. User
heterogeneity and its impact on electronic auction
market design: an empirical exploration, MIS
Quarterly, 28(1), 21-43.
Brokner, J. and Rubin, J. Z 1985. Entrapment in
Escalating Conflict. NewYork NY: Springer-Verlag.
Csikszentimihalyi, M. 1990. Flow: the psychology of
optimal experience, Harper and Row, New York.
Doong, H-S, Wang, H-C., and Foxall, G. R. 2010.
Psychological traits and loyalty intentions toward e-
Government services. International Journal of
Information Management, 30(5), 457-464.
Festinger, L. 1957, A theory of cognitive dissonance,
Standford, C.A: Standford University Press. .
Fox, D. and Hoffman, M. 2002. Escalation behavior as a
specific case of goal-directed activity: a persistence
paradigm. Basic and Applied Social Psychology,
24(4), 273-285.
Gilkeson, J. H. and Reynolds, K. 2003. Determinants of
internet auction success and closing price: an
exploratory study, Psychology and Marketing, 20(6),
537-566.
John, C. L. and Zaichkowsky, J. L. 2003. Bidding
behavior at the auction, Psychology & Marketing,
20(4), 303-322.
Kahneman, D. and Tversky, A. 1979. Prospect theory: an
analysis of decisions under risk, Econometrica, 47(2),
263-291.
Keil, M., Truex, D. P., and Mixon, R. 1995. The effects of
sunk cost and project completion on information
technology project escalation, IEEE Transactions on
Engineering Management, 42(4), 372-381.
Keil, M., Tan, B. C. Y., Wei, K. K., Saarinen, T.,
Tuunainen, V. and Wassennaar, A. 2000, A cross-
cultural study on escalation of commitment behavior
in software projects, MIS Quarterly, 24(2), 299-325.
Ku, G., Malhotra, D. and Murnighan, J.K. 2005. Toward a
competitive arousal model of decision-making: a study
of auction fever in live and internet auction,
Organizational Behavior and Human Decision Process
, 96(2), 89-103.
Logan, G. D. 1988. Toward an instance-based theory of
automatization, Psychological Review, 95, 492-527.
Moors, A. and De Houwer, J. 2006. Automaticity: a
theoretical and conceptual analysis, Psychological
Bulletin, 132, 297-326.
Park, S. C. Keil, M., Kim, J. U. and Bock, .G. W. 2012.
Understanding overbidding behavior in C2C auctions:
an escalation theory perspective, European Journal of
Information Systems, 21(6), 643-663.
Peters, C. and Bodkin, C. D. 2007. An exploratory
investigation of problematic online auction behaviors:
experiences of eBay users, Journal of Retailing and
Consumer Services, 14(1), 1-16.
Petty, R. E., Cacioppo, J. T., and Schmann, D. 1983.
Central and peripheral routes to advertising
effectiveness: The moderating role of involvement.
Journal of Consumer Research, 10, 135-145.
Schneider, W. and Shiffrin, R.M. 1977. Controlled and
automatic human information processing I: Detection,
search and attention, Psychological Review, 84, 1-66.
Sherif and Cantril 1947, The psychology of ego-
involvements, social attitudes and identifications,
Wiley & Sons, Inc. & Chapman & Hall, Limited (New
York & London).
Thaler, R. H. and Sunstein, C. R. 2009. Nudge: improving
decisions about health, wealth and happiness, Penguin
Books, Revised and Expanded Edition.
Trevino, L. K. and Webster, J. 1992. Flow in computer-
mediated communication: electronic mail and voice
mail evaluation and impacts, Communications
Research, 19(5), 539-573.
Zaichkowsky, J. L. 1985. Measuring the involvement
construct. Journal of Consumer Research, 12(3), 341-
352.
AnIndividual'sTwoThinkingSystemsinOnlineC2CAuctions
357