Article

NeuroIS: Neuroscientific Approaches in the Investigation and Development of Information Systems

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The six authors comment on various facets of NeuroIS that appear relevant and important for BISE in four contributions. http://link.springer.com/article/10.1007%2Fs12599-010-0130-8/fulltext.html
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BISE – DISCUSSION
NeuroIS: Neuroscientific Approaches
in the Investigation and Development
of Information Systems
DOI 10.1007/s12599-010-0130-8
The Authors
Prof. Dr. Peter Loos ()
Institute of Business Information
Systems
Saarland University
Struhlsatzenhausweg 3
66123 Saarbrücken
Germany
loos@iwi.uni-sb.de
René Riedl
Gernot R. Müller-Putz
Jan vom Brocke
Fred D. Davis
Rajiv D. Banker
Pierre-Majorique Léger
Published online: 2010-10-20
This article is also available in Ger-
man in print and via http://www.
wirtschaftsinformatik.de: Loos P, Riedl
R, Müller-Putz GR, vom Brocke J, Davis
FD, Banker RD, Léger P-M (2010) Neu-
roIS: Neurowissenschaftliche Ansätze
in der Erforschung und Gestaltung
von Informationssystemen. WIRT-
SCHAFTSINFORMATIK. doi: 10.1007/
s11576-010-0249-8.
©Gabler Verlag 2010
1Introduction
For several years, there has been an in-
creased application of neuroscientific ap-
proaches in the North American Infor-
mation Systems (IS) discipline. Theo-
ries and methods from neuroscience con-
tributetoabetterunderstandingofhu-
man behavior. Since IS tries to explain
human behavior in the use of informa-
tion systems, neuroscientific approaches
can also contribute to a growth of knowl-
edge. In this regard, Dimoka et al. (2007,
p. 13) stated in one of the first publica-
tions on this matter: “It is just hard to be-
lieve that a better understanding of brain
functioning will not lead to better IS the-
ories.
Against the background of the increas-
ing internationalization of business and
information systems engineering (BISE),
the following discussion deals with the
issue of “NeuroIS”. The need for a dis-
cussion on NeuroIS is reinforced by the
fact that neuroscientific approaches also
gain in importance in other business and
social sciences (e.g., neuroeconomics,
Camerer et al. 2005). In the years 2009
and 2010, there have already been two
relevant scientific symposia in Austria
which explicitly focused on NeuroIS. At
this year’s conference “Gmunden Retreat
on Advances in NeuroIS” (see http://
www.NeuroIS.org), which was at-
tended by a number of experts from
the German-speaking BISE, opportu-
nities and challenges of NeuroIS were
discussed. Here, both methodical and
theory-related issues were on the agenda.
A central conclusion of the conference
was that neuroscientific approaches can
help not only to explain human behav-
ior in dealing with information, but are
also relevant for design-oriented BISE
scientists. This circumstance is of partic-
ular interest for BISE researchers in the
German-speaking area as one of their
strengths is the design and concept of
new innovative technologies.
In order to achieve a broad perspec-
tive on the issue in the course of this dis-
cussion, both North American scientists
as well as representatives of the German-
speaking BISE were invited to comment
on the topic. The following authors ac-
cepted my invitation to this discussion
(in alphabetical order):
Prof. Rajiv D. Banker, Merves Chair in
Accounting and Information Technol-
ogy, Fox School of Business and Man-
agement, Temple University, USA;
Prof. Jan vom Brocke, Hilti Chair in
Business Process Management, Uni-
versity of Liechtenstein;
Prof.FredD.Davis,DavidD.Glass
Chair in Information Systems, Sam M.
Walton College of Business, University
of Arkansas, USA;
Prof. Pierre-Majorique Léger, Asso-
ciate Professor am Department of In-
formation Technologies, HEC Mon-
tréal, Canada;
Prof. Gernot R. Müller-Putz, Asso-
ciate Professor at Institute of Knowl-
edge Discovery, Laboratory of Brain-
Computer Interfaces, Graz University
of Technology, Austria;
Prof. René Riedl, Associate Professor
at Department of Business Informatics
– Information Engineering, University
of Linz, Austria.
The six authors comment on various
facets of NeuroIS that appear relevant
and important for BISE in four contribu-
tions.
René Riedl and Gernot R. Müller-Putz
illustrate that neuroscientific approaches
may be used to explain BISE-related phe-
nomena as well as for the design of in-
novative information systems, based on
three specific examples. For instance, the
authors report on a laboratory experi-
ment based on eBay websites. In addi-
tion, the authors refer to research and
development projects in the IT industry
whichwerepresentedtothepublicas
prototypes in recent years.
Jan vom Brocke comments on the role
of neuroscience in design-oriented BISE
research, arguing that neuroscientific ap-
proaches can not only be used in behav-
ioral research. Building on the potentials
of design-oriented research, vom Brocke
distinguishes two major research streams:
research by design and research on de-
sign.Astotheformer,hediscussesthe
role of neuroscientific methods and the-
ories in the development and evaluation
of artifacts. As to the latter, he argues
that neuroscientific approaches can also
be used for generating and refining de-
sign theories.
Fred D. Davis and Rajiv D. Banker
focus on the integration of neurosci-
entific approaches to technology accep-
tance research. Since the 1980s, works on
the technology acceptance model (TAM)
have been published in large numbers.
The authors find, however, that in re-
cent years only incremental advances in
Business & Information Systems Engineering 6|2010 395
BISE – DISCUSSION
knowledge were achieved on the basis
of questionnaire studies. Through the
use of knowledge about conditions and
processes in the human brain as well
as the application of modern imaging
techniques like functional magnetic res-
onance imaging (fMRI), a new perspec-
tive on technology acceptance research
has been opened up that promises sub-
stantial progress.
Pierre-Majorique Léger then presents
ERPsim, an innovative approach to learn-
ing for teaching enterprise resource plan-
ning skills. It is especially noteworthy that
this approach makes use of neurophysi-
ological methods of measurement (e.g.,
galvanic skin response) in order to cap-
ture emotional reactions of SAP system
users in real time. These neurophysio-
logical data can be evaluated using a tri-
angulation with data from questionnaire
surveys and observations, resulting in a
deeper understanding of the use of ERP
systems.
This discussion intends to stimulate
the scientific discourse on the applica-
tion, potentials, and risks of neurosci-
entific approaches in BISE. The scien-
tific community is invited to participate
in this discussion. If you would like to
comment on this topic or another arti-
cle of the journal Business & Information
Systems Engineering (BISE), please send
your contribution (max. 2 DIN A4 pages)
to the editor-in-chief, Prof. Hans Ul-
rich Buhl, University of Augsburg, Hans-
Ulrich.Buhl@wiwi.uni-augsburg.de.
Prof. Dr. Peter Loos
IWi at DFKI
Saarland University, Germany
2OnthePotentialofNeuroIS:
Three Examples
In our following article on “NeuroIS” we
outline three examples, based on a Neu-
roIS definition, that can shed light on
the potential of NeuroIS for research and
development in BISE. The contribution
ends with a brief conclusion.
At the “Gmunden Retreat on the Foun-
dations of NeuroIS” in 2009, the follow-
ing definition of NeuroIS was developed
(cf. Riedl et al. 2010a, p. 245): “NeuroIS
is a subfield in the IS literature that re-
lies on neuroscience and neurophysiolog-
ical theories and tools to better under-
stand the development, use, and impact
of information technologies (IT). Neu-
roIS seeks to contribute to (i) the devel-
opment of new theories that make pos-
sible accurate predictions of IT-related
behaviors, and (ii) the design of IT ar-
tifacts that positively affect economic
and non-economic variables (e.g., pro-
ductivity, satisfaction, adoption, well be-
ing).
The definition includes the explanation
of the behavior of information systems
as well as their design, and thus meets
the dual nature of business and informa-
tion systems engineering (BISE). On the
one hand, the three examples outlined
below focus on the explanation of IT be-
havior,i.e.onansweringawhy-question
(Example 1). On the other hand, they fo-
cus on the design of systems (Examples 2
and 3).
2.1 Example 1 (eBay): Gender and Trust
in the Brain
The investigation of gender-specific dif-
ferences in the use of information sys-
tems is an important topic. One insight of
past research is that there are significant
differences between men and women in
IT behavior. A major difference is, for ex-
ample, that women generally perceive a
higher risk than men when shopping on
the Internet. Moreover, women often also
assess the trustworthiness of online shop-
ping as lower than men do.
These gender-specific differences in IT
behavior raise the question of why these
differences exist. Riedl et al. (2010b)
analyzed this issue by applying fMRI
(functional magnetic resonance imaging)
and investigated brain activation differ-
ences between men and women when
processing trustworthy and untrustwor-
thy eBay offers. The authors found that
women primarily activated limbic brain
areas (which typically focus on process-
ing emotions) and men tended to use
prefrontal brain structures (which rather
focus on rational thinking). Another re-
sult is that women activated more brain
structures than men, particularly because
women process more information and do
this in a more comprehensive and de-
tailed manner than men, who in turn
process information in a more selective
and holistic way.
The finding that gender-related differ-
ences exist in neural information pro-
cessing, which are also manifest in signif-
icant behavioral differences, has implica-
tions for the design of information sys-
tems. The content of the presented in-
formation, such as product descriptions
in online shops, but also the type of in-
formation presentation (textual, graphi-
cal, or a combination) as well as the de-
sign and colors of user interfaces may
be adapted according to the user’s sex in
order to positively influence major vari-
ables, such as technology acceptance or
user satisfaction.
2.2 Example 2 (Microsoft): Interaction
Between Brain and Computer
A few years ago, a patent application en-
titled “Using electroencephalograph sig-
nals for task classification and activity
recognition” by Microsoft became public
(Tan and Lee 2006).Thegoalistoiden-
tify which cognitive task is performed by
a computer user at a certain point in
time by means of brain activity measured
through electroencephalography (EEG).
To achieve this goal it is necessary, among
other things, to assign statistically distin-
guishable EEG patterns to certain mental
states of a user, particularly because the
mental states prevailing in the brain of a
user and the resulting EEG patterns are
again used as data for the processing in
technical systems (Wolpaw et al. 2002).
Business applications of such brain-
computer interfaces (BCI) are just about
to emerge. Long-term objectives of these
research and development activities pri-
marily include:
Automation of process steps in admin-
istrative processes; for example, future
systems may identify the mental state
of a user and start operations without
an input device, such as a computer
mouse, or users may intentionally ac-
tivate mechanical processing tasks by
certain thoughts.
Increasing the usability of systems; for
example, an automatic adaptation of
the content and type of representation
of information as well as the design
and the colors of user interfaces could
be based on the mental state of the
user.
The achievement of both objectives can
contribute to an increased productivity
of users, an essential factor in the use
of systems in the business context. To
date, BCI systems are developed and used
mainly in the medical field. Especially
for people who are completely paralyzed
and cannot speak, but who are at the
same time cognitively unimpaired, BCI
systems form a way to communicate (Bir-
baumer et al. 1999;Dornhegeetal.2007;
Pfurtscheller et al. 2008;Müller-Putzet
396 Business & Information Systems Engineering 6|2010
BISE – DISCUSSION
al. 2010). Other recent applications show
that thought-controlled navigation in a
simple form is possible in virtual worlds
(e.g., navigation to the left or right, up or
down).
An overall assessment of developments
in the field of brain-computer interfaces,
however, shows that commercial prod-
ucts do not exist yet. This means that
the available systems are always associ-
ated with accompanying activities of en-
gineers who implement and run the sys-
tems at the user’s site. It follows that
the mentioned long-term objectives of
the research and development activities
in the field of BCI must currently be
considered as a vision rather than a re-
ality. Nevertheless, we believe that BCI
systems have high potential particularly
in the field of human-computer interac-
tion.
2.3 Example 3 (Philips): Financial
Information Systems and Emotions
More and more people trade securities
from home via the Internet. Efficient and
secure systems form the basis of these
transactions. Findings of empirical re-
search show that financial decisions are
not optimally made if the decision-maker
is highly emotionally charged (e.g., by
fear or greed). Philips developed a proto-
type information system and presented it
to the public in 2009 under the title “Ra-
tionalizer concept: An emotion mirror-
ing system for online traders.” The sys-
tem measures the emotions of a user on
the basis of galvanic skin response and
it warns a user if he is too emotion-
ally charged. The more agitated a per-
son is, the more sweat is produced, which
in turn increases the conductance of the
skin. The system’s warning in case of
strong emotion can be used to abstain
from financial transactions at a certain
point in time. The assumption is that the
use of the system reduces unfavorable fi-
nancial decisions.
The system consists of two compo-
nents, a bracelet that is attached to the
wrist and measures emotions via skin
conductance, and a display device that
displays the strength of emotions by
light patterns and colors. The display de-
vice has the design of a bowl, which,
when standing next to a computer, ap-
pears hardly disturbing. The simplicity
of the components themselves and their
use make the system predestined for its
practical use, a fact that is less the case
with EEG (because electrodes must be at-
tached to the scalp) and with fMRI (for
which people must lie fixed in a machine
during the measurement of brain activ-
ity).
2.4 Conclusion
We outlined three examples elucidating
the diverse potentials of the use of neuro-
scientific approaches for the explanation
and design of information systems.
We believe that neuroscientific theo-
ries and methods enrich BISE and thus
contribute to the long-term growth of
knowledge, but we perceive neuroscien-
tific approaches to have a complementary
nature to existing theories and methods.
In addition, it is necessary to meet the
challenges associated with the use of neu-
roscientific approaches. Some key chal-
lenges have been discussed in the litera-
ture already, as for example sample size,
external validity, moral and ethical con-
cerns as well as cost aspects (cf. Riedl et
al. 2010a).
René Riedl
Department of Business Informatics
University of Linz, Austria
Gernot R. Müller-Putz
Institute of Knowledge Discovery
Graz University of Technology, Austria
3 On the Role of Neuroscience in
Design-Oriented Research
3.1 Introduction
Design-oriented research concerns the
design process of IT artifacts, i.e., con-
structs, models, methods and instantia-
tions (March and Smith 1995;Hevneret
al. 2004). The design of process models at
an enterprise-wide scale provides a good
example for today’s business practice.
It comes along with several challenges
like: What modeling language/technique
is the most appropriate? What is the right
level of detail? How to safeguard the com-
prehensibility of process models devel-
oped for people from different cultural
backgrounds? And, to what extent do
they perceive these models as useful for
their individual work at all?
In design-oriented BISE research, par-
ticularly two lines of inquiry to approach-
ing such issues can be distinguished: On
the one hand, artifacts (e.g., process vari-
ations) can be designed and evaluated
in an iterative process in order to iden-
tify solutions that will prove to be useful
in certain types of applications. On the
other hand, the study of the design pro-
cess itself can be at the core of design-
oriented research (e.g., design decisions
in the modeling process). Table 1opposes
the two approaches to one another, re-
ferred to as research by design and research
on design. The table further illustrates the
benefits that might be realized through
the use of neuroscientific methods.
3.2 Research by Design
Research by design in particular focuses
on the design and evaluation of artifacts.
That being said, the outcome of such re-
search is a specific artifact, together with
insight about its usefulness in a certain
application context (e.g., to what extent
did a process description developed in a
certain modeling language prove useful
Table 1 Roles of neuroscientific methods and theories in research by design and research on design
Research by Design Research on Design
Approach Carrying out design and evaluation processes Reflecting on design and evaluation processes
Statement Relation between artifact and perceived utility Relations between design decisions and the quality of the artifact
as well as quality of the artifact and results
Objective Development of innovative and purposeful artifacts Acquisition of knowledge about design and evaluation processes
Role of neuroscientific
methods and theories
– Evaluation of artifacts – Development of new design theories
– Use of theories from neuroscience – Evaluation of existing design theories
Business & Information Systems Engineering 6|2010 397
BISE – DISCUSSION
in a particular case organization?). This
approach, which has been widely spread
in the German-speaking BISE commu-
nity in the past few years, appears par-
ticularly suitable when only a few suc-
cess factors of the design process can be
determined ex ante (e.g., the technical,
cultural, task-specific, and demographic
backgrounds of the employees). Neuro-
science can provide both methods eval-
uating and theories grounding the design
of IT artifacts.
3.2.1 Evaluation of Artifacts
At the most basic level, the evaluation of
an artifact allows the researcher to make
statements about its usefulness. Fellow
researchers have proposed the use of tra-
ditional qualitative and quantitative ap-
proaches, such as case study research and
simulations, for the evaluation of arti-
facts (Hevner et al. 2004). Not only in
design-oriented research, however, the
use of such methods goes along with sev-
eral challenges (Riedl et al. 2010). The
results of observations and interviews,
for example, are often subjective, as they
might be influenced by the hidden inten-
tions of the informants. In contrast, mea-
surement methods of neuroscience pro-
vide innovative and more objective ways
to monitor the actual cognitive effects of
individual recipients. Past PET (positron
emission tomography) studies, for exam-
ple, measured cognitive load (e.g., Haier
et al. 1992), and fMRI (functional mag-
netic resonance imaging) was used to
identify specific brain regions that are as-
sociated with “cognitive conflict” (e.g.,
Botvinick et al. 2004), such as the ante-
rior cingulate cortex (ACC). Hence, neu-
roscience could be used to further inves-
tigate various phenomena related to the
perception of artifacts.
Both costs and authenticity associated
with neuroscientific measurements re-
quire specific attention. As to the for-
mer, it can be expected that techno-
logical progress will enable cheaper and
more mobile measurements in the fu-
ture. Today, however, there are already
some “lightweight” measurement meth-
ods (e.g., galvanic skin response, pupil
behavior, heart rate), which can comple-
ment the more sophisticated techniques
such as fMRI. Such techniques make it
possible to gain physiometrical informa-
tion related to the use of artifacts not only
in experimental settings but also in the
professional work environment. As to the
latter, the legitimate use of the results ob-
tained through neuroscientific measure-
ments appears similarly important. This
not only refers to ethical considerations,
but further concerns the interpretation
of results. That being said, direct mea-
surements in the head (or body) should
not be considered more objective and su-
perior to traditional approaches per se.
Researchers should rather bear in mind
that such results refer to individual sub-
jects (usually about 15 to 20 subjects
in fMRI studies) and require thorough
interpretation. Neuroscientific measure-
ments should thus rather be used to com-
plement the results of traditional meth-
ods in the sense of triangulation.
3.2.2 Use of Theories from Neuroscience
On many issues related to the percep-
tion (or creation) of artifacts, neurosci-
entific findings already exist that can be
used in research by design (e.g., the above
mentioned findings regarding “cognitive
load” and “cognitive conflict”). This is
especially worth mentioning as these re-
sults can inform the design of artifacts –
without conducting any additional neu-
roscientific measurements. The selection
process of modeling languages, for ex-
ample, may be grounded in knowledge
about the information processing capac-
ity of the recipients (e.g., regarding the
processing of objects, numbers, and other
characters). Studies on different cognitive
stylescouldalsobeusedinorderenable
the refinement of models in a rather mul-
tiperspective way. Similarly, findings on
the rational and creative cognitive per-
formance could provide a valuable ba-
sis for the design of models. In this con-
text, Riedl (2009), for example, highlights
the question to what extent the cogni-
tive style of people may have an influence
on the choice of either object-oriented
or flow-oriented languages. A wide range
of similar questions can be studied ac-
cordingly using neuroscientific theories,
methods, and tools.
Once NeuroIS studies, as outlined
above, are increasingly carried out in
BISE research, an evaluation and further
development of neuroscientific theories
can also be achieved. This is particularly
the case if questions arise from BISE re-
search that have not been studied in neu-
rosciencesofar.Thisconsiderationleads
to the second main application domain of
NeuroIS in design-oriented research: the
design (and further development) of the-
ories in “research on design.
3.3 Research on Design
Research on design studies the design
processes of artifacts rather than artifacts
as such (e.g., how to design process mod-
els in a specific notation?). This approach
to design-oriented research is particularly
discussed in studies on design theories
(e.g., Gregor and Jones 2007; Walls et al.
2004). A design theory can be consid-
ered a specific type of theory that pro-
vides normative statements about typical
design processes (i.e., “howtodosome-
thing”; Gregor 2006, p. 628).
As to the various influences relevant in
different design processes, multiple de-
sign theories are very likely to be needed
that may serve as a pool of theories. With
each theory relating to a certain aspect of
design a combination of different theo-
ries may help to understand a certain de-
sign process appropriately. Following this
approach, methods of neuroscience may
particularly contribute to research on de-
sign by both further developing and eval-
uating design theories.
3.3.1 Development of New Design
Theories
The evaluation of artifacts with the help
of methods from neuroscience can pro-
vide new insight on design processes of
artifacts. Such findings may include spe-
cific design issues particularly relevant in
BISE research (e.g., the selection of mod-
eling languages or methods). Here, the
focus should not to be limited to the per-
ception of artifacts. It will also be inter-
esting to see how earlier phases of the de-
sign process can be studied, for example,
the creative development and collabora-
tive discussion of possible solutions.
3.3.2 Evaluation of Existing Design
Theories
Finally, also contemporary insights about
design processes can be evaluated and
possibly extended by neuroscientific
methods. This holds not only for de-
sign theories in the strict sense, but also
for other theory types (e.g., the Technol-
ogy Acceptance Model). Here, it again
appears particularly promising – just as
for research by design – to combine tra-
ditional research strategies and methods
with neuroscientific approaches to ac-
complish our findings.
398 Business & Information Systems Engineering 6|2010
BISE – DISCUSSION
3.4 Conclusion
Design-oriented research in BISE in-
cludes both the implementation and
evaluation of artifacts and the reflections
on such an endeavor. These two perspec-
tives on design-oriented research – re-
search by design and research on design
– are intertwined. In research by design,
both artifacts and design theories can be
evaluated with the help of neuroscien-
tific approaches. In research on design,
it appears reasonable to first assess how
existing neuroscientific theories can con-
tribute to the development and evalua-
tion of design theories.
In particular, interdisciplinary research
projects appear suited to make best
use of neuroscientific methods. BISE re-
searchers can then pose questions for
which appropriate experimental designs
are developed together with neuroscien-
tists. On the basis of such cooperation,
a more intense methodological discus-
sion on NeuroIS may take place in the
medium term. This, however, particu-
lar requires the development of generally
accepted quality criteria and procedures
that can be used both in the work of au-
thors and reviewers. As in other areas, the
mere application of neuroscientific mea-
surement techniques will certainly not be
sufficient. Instead, BISE researchers will
have to learn to use the new possibili-
ties in a way that enables them to develop
new knowledge surrounding the design
and use of information systems. Then,
the potentials are enormous as neuro-
science provides an entirely new kind of
approach to study our objects of research
in IS.
Jan vom Brocke
Martin Hilti Chair in
Business Process Management
University of Liechtenstein
4 The Technology Acceptance
Model and Cognitive
Neuroscience
The Technology Acceptance Model
(TAM) is a leading theoretical model
for explaining, predicting, and influenc-
ing information technology adoption.
TAM theorizes that adoption is driven by
users’ intentions, and that intentions are
influenced by users’ perceptions of sys-
tems’ usefulness and ease of use. Practical
interventions such as the choice of sys-
tem design characteristics and training
techniques can influence adoption due
to their influence on perceived useful-
ness and ease of use. Over the more than
twenty years since its introduction, there
have been numerous extensions and re-
finements to the basic model, including
adaptations to specific contexts (some-
times referred to as TAM++; Venkatesh
et al. 2007). Nevertheless, several recent
reviews observe that the core model is
powerful and parsimonious.
Despite the success of TAM++,itsex-
planatory power is far from perfect, and
it is increasingly difficult to gain new in-
sights about technology acceptance using
traditional behavioral experiments and
surveys. Therefore some researchers have
begun to leverage cognitive neuroscience
knowledge and techniques to try to ad-
vance knowledge in this area.
A recent preliminary study (Dimoka
and Davis 2008) sought to identify the
neural correlates of the TAM constructs.
Six participants were asked to browse
two e-commerce websites, one low and
the other high in usefulness and ease of
use. Then the participants responded to
several traditional self-report questions
about their perceived usefulness and per-
ceived ease of use of each website while
undergoing fMRI scanning. For the pos-
itive website, usefulness questions ac-
tivated the caudate nucleus and ante-
rior cingulate cortex, which are associ-
ated with reward processing; for the neg-
ative website usefulness questions acti-
vated the insular cortex, which is asso-
ciated with negative emotions regarding
fear of loss. For both websites, questions
about ease of use activated the dorso-
lateralprefrontalcortex,whichisassoci-
ated with sequential execution of opera-
tions during cognitive processing. There
were significant differences in activation
between the positive and negative web-
sites for the usefulness areas, and a bor-
derline significant difference for the ease
of use area. In turn, the activation of these
areas predicted post-scan self-reports of
purchase intentions (R2=0.48). This
study illustrates the feasibility of identi-
fying neural correlates of usefulness and
ease of use that are influenced by the
quality differences between two websites,
are consistent with self-reported values
of these perceptions, and which in turn
are predictive of behavioral intentions.
While this is a hopeful starting point, IS
researchers are looking to cognitive neu-
roscience to advance beyond the already
established determinants of technology
adoption.
TAM theorizing has been strongly in-
fluenced by models from social psychol-
ogy that emphasize conscious, deliberate
decision making processes, such as the
Theory of Reasoned Action (TRA) and
the Theory of Planned Behavior (TPB).
However, recent theorizing in psychol-
ogy, behavioral economics, and neuro-
science (e.g., Camerer et al. 2005;Lieber-
man 2007) indicates that behavior is ac-
tually driven by two different systems,
a controlled system, sometimes called the
C system referring to the “c” in reflec-
tive, and an automatic system, sometimes
called the X system referring to the “x”
in reflexive. Whereas the C system is con-
scious, serial, effortful, and slow, the X
system is unconscious, parallel, effortless,
and fast. Contrary to traditional theoriz-
ing, the X system has often been found
to be as important, or even more impor-
tant, than the C system in driving behav-
ior. Further, intelligent human behavior
is usually better understood in terms of
the interplay between the C and X sys-
tems rather than either the C or X sys-
tem in isolation. Perhaps due to their
reliance on conscious self-reported con-
structs, traditional intention models such
as TAM, TRA, and TPB have emphasized
the C system and deemphasized the X
system.
The quest for deeper knowledge about
the X system and its relationship to the
CsystemisonekeyreasonwhyISre-
searchers are looking to cognitive neuro-
science to advance TAM research. The X
system is highly relevant for many con-
structs and phenomena that TAM re-
searchers are increasingly interested in,
such as habit and automaticity, cog-
nitive skill, emotions, social influence,
multi-tasking, attentional control, im-
plicit learning, knowledge collaboration,
and goal regulation. In general, cognitive
neuroscience promises to open up new
avenues for advancing knowledge about
the key processes driving user adoption
behavior and offer new insights into how
to design better systems by exploiting
new insights about the mental processes
underlying their use.
Such dual processing systems as the X
and C systems also help explain the in-
teraction between individuals as captured
in behavioral economics models that in-
clude both self-interest and regard for
preferences of others (Fehr and Schmidt
1999). Neuroscience studies are begin-
ning to indicate separation in the parts of
the brain that process self-interested and
other-regarding preferences that lead to
Business & Information Systems Engineering 6|2010 399
BISE – DISCUSSION
social concerns such as fairness in eco-
nomic decisions. Understanding how the
neural processes giving rise to the differ-
ent preferences interact with each other
can help us predict technology adoption
decisions that simultaneously account for
preferences of multiple individuals in so-
cial settings (Ho and Su 2010).
Bagozzi (2007) argues that future re-
search efforts to broaden and deepen
TAM should address the intention-
behavior linkage (in particular goal set-
ting and self-regulation), group, cultural,
and social aspects of technology accep-
tance, and the role of emotions. These are
all areas where new insights and meth-
ods from cognitive neuroscience offer
promising avenues for progress. Exam-
ples of constructs that appear promising
for investigation using cognitive neuro-
science include enjoyment, flow, cogni-
tive absorption, skill, habit, fatigue, bore-
dom, trust, risk, frustration, anger, cogni-
tive workload, vigilance, disengagement,
multitasking, and technostress.
Cognitive neuroscience is refining and
advancing the theoretical foundations of
traditional reference disciplines for IS re-
search, including psychology, economics,
and organizational behavior. It should
be possible to take advantage of knowl-
edge flowing from cognitive neuroscience
for refining IS theories and hypotheses
which can then be tested using traditional
behavioral methods, without necessarily
relying on brain measurements per se.
Neuroscience techniques further open up
opportunities for measuring important
constructs that are difficult or impossible
to tap using traditional approaches.
Fred D. Davis
Sam M. Walton College of Business
University of Arkansas, USA
Rajiv D. Banker
Fox School of Business and Management
Temple University, USA
5 ERPsim: A Simulation Platform
for Experimental Research in
NeuroIS
One of the challenges in using an exper-
imental approach in NeuroIS research is
the difficulty to create realistic IT organi-
zational environments where end-users’
behaviors can be monitored and analyzed
in real time. A simulation technology de-
veloped at HEC Montréal, called ERP-
sim, was designed to address this chal-
lenge (Léger 2006;Légeretal.2007). This
technology allows for the simulation of
realistic collaboration scenarios through
the use of a real-life ERP system. End-
users are placed in a situation where they
must make decisions and manage the op-
eration of their enterprises using a real-
lifeERPsystem(SAP),suchasthoseused
in large organizations. One key character-
istic of ERPsim is that all decisions made
by the participants must be entered into
the ERP system and, in order to make
those decisions, all of the information re-
quired must be extracted through stan-
dard reports of the ERP system. As such,
onecanthinkofERPsimasaflightsimu-
lator for ERP system where end-users are
flying a real corporate information sys-
tem in a virtual business environment.
Until recently, ERPsim has been mainly
used for end-user training purposes.
More than 100 universities worldwide
and numerous Fortune 1000 organiza-
tions are using ERPsim to train end-users
inordertobetterunderstandthevalue
of enterprise systems (more information
is available at http://erpsim.hec.ca). In
addition to its pedagogical applications,
ERPsim can contribute to research on
ERP-related concepts, using the simula-
tor to gather data that were previously
difficult to obtain. Cronan et al. (2009a,
2009b)andLégeretal.(2009,2010)are
examples of studies using ERPsim to con-
duct experimental researches.
For NeuroIS researchers, ERPsim offers
the possibility to collect neurophysiolog-
ical data while subjects are immersed in a
realistic business situation in which end-
users are using an ERP system to make
decisions and to resolve complex busi-
ness problems. For example, it is possi-
ble to capture end-users’ biosignals, such
as electrodermal activity (EDA), electro-
cardiogram (ECG), facial electromyogra-
phy (EMG), and electroencephalogram
(EEG). In contrast to more sophisticated
tools, such as fMRI, these neurophysio-
logical techniques also objectively mea-
sure a user’s behaviors and emotional
reactions. However, compared to fMRI,
neurophysiological techniques are less in-
trusive because participants in an experi-
ment usually sit in front of computers in
a normal environment rather than lying
in a brain scanning machine (Riedl et al.
2010).
The biosignals derived from neuro-
physiological techniques can be triangu-
lated against other empirical evidences,
such as the usage data in the ERP sys-
tem (i.e., clickstream data) and survey
data. ERP systems, such as SAP, log all
transactions performed by every users
in the system. By mapping these differ-
ent data sources (clickstream, survey, and
biosignals) on the same timeline, it be-
comes possible to obtain a rich longitu-
dinal dataset that includes the end-user’s
psychophysiological reactions during the
ERP experience, the self-perceived atti-
tudes and beliefs related to this interac-
tion,aswellasadetailedrecordofhisac-
tions and decisions executed in the ERP
system during the experiment.
This effort in providing a methodolog-
ical tool enabling multi-method experi-
mental researches is consistent with the
call for more triangulations in IT re-
search and in the use of neurophysiologi-
cal measurement tools to seek convergent
validity of current IT psychometric tools
(Dimoka et al. 2010). The main objec-
tive is not to replace the existing IT vali-
dated constructs, but to complement and
enrich them with other sources of em-
pirical evidences which were previously
hard to collect in a valid and reliable way.
This approach opens the door to investi-
gations that were not previously possible.
In one of our current research pro-
grams, we are investigating the psy-
chophysiological correlates of cognitive
absorption (CA). This construct corre-
sponds to a state of deep involvement
with a software program and has theo-
retical roots in the concept of absorp-
tion (Tellegen and Atkinson 1974), the
notion of flow (Csikszentmihalyi 1990),
and the notion of cognitive engagement
(Webster and Ho 1997). CA has widely
been studied over the last decade in the
IT literature using psychometric instru-
ment developed by Agarwal and Kara-
hanna (2000).
The paradox of measuring CA with
psychometric tools is that it requires ask-
ing a subject to self evaluate the level of
absorption over several Likert scale items.
Obviously, such an approach implies the
subject to be taken out of his cognitive
absorption state in order to answer this
survey. To circumvent this problem, re-
searchers in the field of video game devel-
opment have started using psychophys-
iological measures to infer the cogni-
tive and emotional states of gamers. For
example, Nacke (2009)reportscorrela-
tions between ECG, EDA and EEG with
a self-perceived game experience con-
struct. Building on these approaches, our
ongoing research investigates the corre-
lation between several psychophysiolog-
ical measures and the different dimen-
sions of the CA construct, and our goal
is to eventually try to predict perceptions
400 Business & Information Systems Engineering 6|2010
BISE – DISCUSSION
of CA based on objective psychophysio-
logical measurement.
The ERPsim research platform opens
the possibility to triangulate many psy-
chometric measures used in previous
studies with neurophysiological signals
addressing untapped research questions
in IT. The ERPsim Lab is currently work-
ing on extending its platform to di-
rectly integrate the psychophysiological
equipment of a Montréal-based company
called Thought Technology Ltd.Theob-
jective is to ultimately provide the Neu-
roIS community with a flexible research
tool to conduct experimental researches
in complex IT environments, while col-
lecting a rich set of data pertaining to the
behaviors and emotions of users while in-
teracting with IT.
Pierre-Majorique Léger
Department of Information Technologies
HEC Montréal, Canada
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... 73-74)). In NeuroIS studies, neurophysiological data are typically collected in combination with self-reported data to study existing systems' use and impact, as well as to inform the design of new systems; hence contributing to both behavioral and design-oriented IS research Loos et al., 2010;Riedl, Banker, et al., 2010). In this new strategy of inquiry, researchers use data from the human body to measure the effects of human interactions with technology more directly; revealing the mechanisms underlying human behavior, particularly affective and other non-conscious processes (Dimoka, Pavlou, & Davis, 2011;Riedl & Léger, 2016;vom Brocke & Liang, 2014). ...
... In contrast to prior calls for research on neuro-adaptive systems (e.g. Loos et al., 2010;Riedl, Banker, et al., 2010;vom Brocke, Riedl, et al., 2013), here we indicate specific avenues for future research. We identify the following research questions, which serve as grand challenges in order to make high impact contributions to neuro-adaptive systems through NeuroIS: ...
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... ERPsim is a business simulation based on SAP (Léger 2006). ERPsim provides a simulation environment with enough granularity to provide a platform for experimental research in NeuroIS (Loos et al. 2010). The simulation was modified to allow a task that required several monitoring and decision cycles. ...
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Chapter
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Chapter
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Chapter
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Data
Two paradigms characterize much of the research in the Information Systems discipline: behavioral science and design science. The behavioral-science paradigm seeks to develop and verify theories that explain or predict human or organizational behavior. The design-science paradigm seeks to extend the boundaries of human and organizational capabilities by creating new and innovative artifacts. Both paradigms are foundational to the IS discipline, positioned as it is at the confluence of people, organizations, and technology. Our objective is to describe the performance of design-science research in Information Systems via a concise conceptual framework and clear guidelines for understanding, executing, and evaluating the research. In the design-science paradigm, knowledge and understanding of a problem domain and its solution are achieved in the building and application of the designed artifact. Three recent exemplars in the research literature are used to demonstrate the application of these guidelines. We conclude with an analysis of the challenges of performing high-quality design-science research in the context of the broader IS community.
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People exhibit peer-induced fairness concerns when they look to their peers as a reference to evaluate their endowments. We analyze two independent ultimatum games played sequentially by a leader and two followers. With peer-induced fairness, the second follower is averse to receiving less than the first follower. Using laboratory experimental data, we estimate that peer-induced fairness between followers is two times stronger than distributional fairness between leader and follower. Allowing for heterogeneity, we find that 50 percent of subjects are fairness-minded. We discuss how peer-induced fairness might limit price discrimination, account for low variability in CEO compensation, and explain pattern bargaining. (JEL C72, D63 )