No full-text available
To read the full-text of this research,
you can request a copy directly from the authors.
Neuroscience in Design-Oriented Research: Exploring New Potentials
Abstract
Design-oriented research has evolved as a major research paradigm in the academic discipline of information systems (IS) aiming at the design of innovative and useful IT artifacts such as methods, models, constructs, and instantiations. With the concept of “user-perception” at the core of this approach, it appears promising to explore the potentials of neuroscience in design-oriented research that allow for measuring physiological effects of people interfering with artifacts. In this paper, we discuss fields of application concerning both the design and evaluation of artifacts. However, we also argue that neuroscience, despite its value for design-oriented IS research, should complement rather than substitute traditional research approaches and that results require thorough interpretation. We report on a first study that triangulates quantitative and neuroscientific data in the area of enterprise resource planning systems and indicate directions for future research.
... However, the consideration of neuroscience is still in its infancy in IS design science research. A limited number of contributions have alluded to the potential of neuroscience in design science research [e.g., 42,80], but few IS design science studies have applied neuroscience theories and tools, perhaps because of a lack of conceptual support for IS researchers who wish to engage in NeuroIS design science research. ...
... In IS design science research, both software systems (which are the focus of many TAM and TAM++ studies) and conceptual models play significant roles. While the origins of conceptual modeling can be traced back to software engineering, several additional purposes of conceptual modeling are apparent in IS, among which are data modeling, knowledge modeling, business process modeling, and enterprise modeling [80]. ...
... While neuroscience thus offers a new lens through which the design of IT artifacts can be studied (in this case, the affective one), additional aspects of design should be considered as well. In particular, for each of the strategies proposed, neuroscience theories and tools should be used to complement the traditional techniques of data collection and analysis, rather than to replace them [63,80]. However, even such complementary use may not be beneficial in all situations; IS researchers who engage in this particular field of research should reflect on whether and to what extent the application of neuroscience can support the design of IT artifacts in their individual situations. ...
... A few articles provide overviews of theories and tools and discuss the potential of NeuroIS and directives for future research [10,33,45,46], and a growing number of empirical NeuroIS papers (see: www.NeuroIS.org) have raised the importance of establishing knowledge about how to conduct and evaluate NeuroIS research. ...
... Advancing the field of IS research includes contributions to behavioral and design-oriented research, both of which are addressed by NeuroIS [33]. While NeuroIS studies in behavioral research are conducted to describe, explain, and/or predict people's IT-related behavior, NeuroIS studies in design science research are conducted to further the design and evaluation of IT artifacts [46]. Prior research has identified the potential contributions of NeuroIS studies as facilitating/enhancing existing IS theories, developing new theories, facilitating system design, evaluating system design, and improving how existing constructs are measured [22]. ...
... Here, the tool selection (phase 3 and guideline 3) plays an important role. For instance, neurophysiological tools allow measurements to be made in a wide range of contexts and interactions in socio-technical systems, such as role-plays [46]. ...
Neuroscience provides a new lens through which to study information systems. These studies, called NeuroIS studies, investigate the neuro-physiological effects related to the design, use, and impact of information systems. A major advantage of this new methodology is its ability to examine human behavior at the underlying neuro-physiological level, which was not possible before, and to reduce self-reporting bias in behavior research. Previous studies that have revisited important IS concepts like trust and distrust have challenged and extended our knowledge. An increasing number of neuroscience studies in IS have given researchers, editors, reviewers, and readers new challenges in terms of determining what makes a good NeuroIS study. While earlier papers focused on how to apply specific methods (e.g., fMRI, functional magnetic resonance imaging), this paper takes an IS perspective in deriving six phases for conducting NeuroIS research and offers five guidelines for planning and evaluating NeuroIS studies: to advance IS research, to apply the standards of neuroscience, to justify the choice of a neuroscience strategy of inquiry, to map IS concepts to bio-data, and to relate the experimental setting to IS-authentic situations. The guidelines provide guidance for authors, reviewers and readers of NeuroIS studies, and, thus, help to capitalize on the potential of neuroscience in IS research.
... In relation to this, Dimoka et al. (2007, p. 2) suggested in one of the first publications on this concern: "By directly asking the brain, not the person, neuroimaging techniques allow an objective, reliable and unbiased measurement of thoughts, beliefs, and feelings and link them to specific human processes (e.g., decisions, choices, and behavior)". Nevertheless, the plain use of neuroscientific measurement techniques will undoubtedly not be enough (Vom Brocke et al. 2011). ...
Information systems (IS) community is increasingly interested in employing neuroscience tools and methods in order to develop new theories concerning Human–computer interaction (HCI) and further understand IS acceptance models. The new field of NeuroIS has been introduced to address these issues. NeuroIS researchers have proposed encephalography (EEG), among other neuroscience instruments, as a valuable usability metric, when used effectively in appropriately designed experiments. Moreover, numerous researchers have suggested that EEG frontal asymmetry may serve as an important metric of user experience. Based on the aforementioned evidence, this study aims to integrate frontal asymmetry with Technology acceptance model (TAM). Particularly, we assumed that frontal asymmetry might predict users’ perceptions regarding Usefulness and Ease of Use. Furthermore, we hypothesized that frontal asymmetry might also affect (influence) users’ Perceived Playfulness. Specifically, 82 (43 females and 39 males) undergraduate students were chosen to use a Computer-Based Assessment (while being connected to the EEG) in the context of an introductory informatics course. Results confirmed our hypothesis as well as points of theory about Information technology (IT) acceptance variables. This is one of the first studies to suggest that frontal asymmetry could serve as a valuable tool for examining IT acceptance constructs and better understanding HCI.
... And especially in IS design science, for which human cognitive perceptions and decision making play a critical role, neuroscience provides great potential in contributing to the enhancement of IS design science methodology. The intersection between NeuroIS and IS design science has been investigated extensively since 2010[32][33][34][35]. In this paper, we adopt[29]'s NeuroIS Design Science Model to illustrate the neural foundation for IS design science. ...
In this paper, we proposed a neuroscience-based general framework for IS visual systems design that uses neuroscience as the bridge that systematically integrates the principles of design aesthetics and principles of positivistic functionalities into a comprehensive model. Based on our general conceptual model, we also provide a detailed typological framework for the practical IS visual systems design.
Bu çalışmanın amacı, nörostrateji kavramını stratejik yönetim alanına katkıları temelleri, gelişim seyri, tanımı ve sınırlılıkları üzerinden tartışmaya açmaktır. 2011 yılında Powell’ın öncü teorik çalışmasıyla alanyazında yer bulmuş olan nörostrateji, beyin haritalama ve görüntüleme araç ve yöntemleri aracılığı ile yönetsel aktörün karar verme anında aktive olan beyin bölgelerini inceleyen ve beyni değerlendiren bir alandır. Stratejik yönetim alanının bugün geldiği noktada bilişsel özellikler, algı, stratejik seçim, karar verme, davranış gibi konuların önem kazandığı görülmektedir. Nörostrateji, stratejik yönetim alanının odağını değiştirmeden stratejik yönetimin aktörlerin davranışlarını ve stratejik karar alma süreçlerini diğer bir ifade ile örtülü tutumlarını, otomatik bedensel tepkilerini, bilinçsiz bir şekilde işleyen beyin süreçlerini, aktörlerin nasıl düşündüklerini, hissettiklerini ve hareket ettiklerini kapsayan belirli araştırma sorularını yanıtlamak ve ek yanıtlar oluşturmak noktasında ilgili alanyazına katkı sunmaktadır. Bunu yaparken nörobilimsel araçların desteğini almaktadır. Bireylerin davranışlarının sosyal bağlamdan etkilendiğini ancak bu etkilerin altında yatan mekanizmaların hala tam olarak anlaşılamadığı gerçeği göz önünde bulundurulursa bu noktada kat edilmesi gereken yol olduğu açıkça görülebilmektedir. O halde stratejik yönetimde disiplinlerarası uygulama olarak kabul edilen nörobilimden ve nöröbilim araçlarından yararlanmak gerekmektedir. Böylece ilgili alan aktörlerin mikro temellerini ve karmaşık sosyal olguları analiz etme imkanı yakalayabilecektir. Bu çalışmada nörostratejinin ayırıcı özelliklerinin net bir şekilde ortaya konulması ve tanımının genişletilmesi gerektiğine yönelik yeni bir tartışma önerisinde bulunulmaktadır.
Recently, physiological signals such as eye-tracking and gesture analysis, galvanic skin response (GSR), electrocardiograms (ECG), and electroencephalograms (EEG) have been used by design researchers to extract significant information to describe the conceptual design process. We study a set of video-based design protocols recorded on subjects performing design tasks on a sketchpad while having their EEG monitored. We propose empirical approaches to quantify effort, fatigue, and concentration during the conceptual design process. To perform this analysis, we extract EEG features that convey information on effort, fatigue, and concentration. We argue that all three are relevant in the conceptual design process. Such an analysis has the merit of being fully automated, readily integrable in engineering systems and not being subjected to the subjectivity of the domain expert performing the analysis like in subjective rating frameworks. Our analysis leads to four hypotheses: (1) effort and fatigue are subjected to ice-breaking and end of task phenomena; (2) fatigue and effort follow a capacity model; (3) fatigue is multidimensional; and (4) concentration follows a modal shift model.
In this paper, we proposed a neuroscience-based general framework for IS visual systems design that uses neuroscience as the bridge that systematically integrates the principles of design aesthetics and principles of positivistic functionalities into a comprehensive model. Based on our general conceptual model, we also provide a detailed typological framework for the practical IS visual systems design.
In design research, recently an increasing number of experiments have been conducted that successfully applied quantitative biometric measurement methods to investigate design-related research questions. These methods are heart rate variability (HRV), skin conductance response (SCR), electroencephalography (EEG), functional magnetic resonance imaging (fMRI) as well as remote and mobile eye tracking (ET). Within the scope of these experiments, a variety of different biometric measurement systems have been used, each able to record specific raw data and each using characteristic measures to detect and specify particular patterns of human behaviour. This chapter explores how these biometrical measurement systems work, what exactly they measure, and in which ways collected raw data can be analysed to obtain meaningful results. By using the example of selected design studies, the benefits as well as the limitation of the aforementioned biometric measurement methods are discussed and reflected in regard to their present and future role in experimental design research.
The primary focus of NeuroIS research from a methodological perspective is set on methods and research design, data collection, and data analysis. In this paper, we address a practical problem, related to the data collection phase, namely the choice of a data collection instrument, or a NeuroIS tool. Before making a tool decision, researchers have to carefully study the features of each device, based on specified requirements, in order to select the most suitable tool. Thus, the tool choice becomes a multi-criteria decision making problem. In this paper, we propose an Analytic Hierarchy Process (AHP)-based approach for the selection of a NeuroIS tool. We introduce a framework based on a step-by-step procedure of decision hierarchy creation, followed by the construction of a list of potential measurement tools, and the execution of the AHP decision making process.
Engineering-oriented empirical tacit knowledge (ETK) is a kind of tacit knowledge originated from domain expert’s experience combined with practice cases and scenarios. It is an important source of organisation knowledge. However, due to operational and technical obstacles, this kind of knowledge is not sufficiently harnessed and put into practical use. To deal with this problem, a novel two-stage acquisition method is proposed in this paper. The acquisition method consists of two phases, the stage from ETK in the mind of expert to ETK in initial state, and the stage from ETK in initial state to structured ETK. It constructs a complete tacit knowledge acquisition process from the domain expert’s experience to the structured tacit knowledge. The objective is achieved by taking the following procedures: Firstly, present the concept of engineering-oriented ETK and a five-dimension representation model of ETK. Secondly, construct a two-stage ETK acquisition framework. Finally, describe an engineering decision case to validate the feasibility of the proposed approach. Satisfactory results are reached for the study.
NeuroIS is an emerging field in Information Systems (IS) that makes use of neuroscience and neurophysiological tools and theories to better understand the development, adoption, and impact of information technologies (IT). The Gmunden Retreat on NeuroIS is an annual academic conference taking place in June, with the objective to promote the successful development of the field. The event is taking place in Gmunden, Austria, a much frequented health and summer resort providing an inspiring environment for the retreat.
Design science has evolved as a major research paradigm in the information systems (IS) discipline, which aims to design innovative and useful IT artifacts, such as conceptual models and software systems. Despite the increasing attention paid to the cognitive and emotional mechanisms that underlie the perception of such artifacts, research that explores the neurobiological determinants of these mechanisms has only recently begun to emerge. The primary argument for the use of neurobiological approaches in IS design science research is that IT artifact design — and, ultimately, human-computer interaction in general — may significantly benefit from neuroscience theories, concepts, methods, and data. In particular, the consideration of neuroscience may improve IT artifacts’ alignment with users’ perceptual and information processing mechanisms, particularly the brain. Against this background, this article presents a taxonomy of application strategies for neuroscience in IS design science research. It describes three major areas of application and explains that conducting research in an area comes with a specific set of requirements (e.g., applicability, costs, accessibility, and knowledge relevant to planning and conducting a research project). Therefore, if an IS design science scholar decides to draw upon neuroscience, the taxonomy transparently explains possible working areas and corresponding requirements. The taxonomy is described based on example studies published in the IS literature and on contributions that appeared in outlets pertaining to related disciplines, such as affective computing and neuroergonomics. The article concludes that, if neuroscience is considered a valuable complement to the more traditional approaches, it has the potential to become a major reference discipline for IS design science research.
Recent years have seen an increased uptake of business process management technology in industries. This has resulted in organizations trying to man-age large collections of business process models. One of the challenges facing these organizations concerns the retrieval of models from large business pro-cess model repositories. For example, in some cases new process models may be derived from existing models, thus finding these models and adapting them may be more effective and less error-prone than developing them from scratch. Since process model repositories may be large, query evaluation may be time consuming. Hence, we investigate the use of indexes to speed up this evaluation process. To make our approach more applicable, we con-sider the semantic similarity between labels. Experiments are conducted to demonstrate that our approach is efficient.
Quality is one of the main topics in current conceptual modelling research, as is the field of business process modelling. Yet, widely acknowledged academic contributions towards an understanding or measurement of business process model quality are limited at best. In this paper I argue that the development of methodical theories concerning the measurement or establishment of process model quality must be preceded by methodological elaborations on business process modelling. I further argue that existing epistemological foundations of process modelling are insufficient for describing all extrinsic and intrinsic traits of model quality. This in turn has led to a lack of holistic understanding of process modelling. Taking into account the inherent social and purpose-oriented character of process modelling in contemporary organizations I present a socio-pragmatic constructionist methodological framework for business process modelling and sketch out implications of this perspective towards an understanding of process model quality. I anticipate that, based on this research, theories can be developed that facilitate a more comprehensive and adequate evaluation of the 'goodness' of a business process model.
Due to the increased availability of both neuroscience methods and theories, Information Systems (IS) scholars have begun to investigate the potential of neuroscience for IS research. This new field of research is referred to as NeuroIS. Moreover, large technology companies (e.g., Microsoft and Philips) started research programs to evaluate the potential of neuroscience for their business. The application of neuroscientific approaches is also expected to significantly contribute to advancements in human-computer interaction (HCI) research. Against this background, a panel debate is organized to discuss the potential of neuroscience for HCI studies. The panel hosts an intellectual debate from different perspectives, both conceptually (from behaviorally-oriented research to design science research) and methodologically (from brain imaging to neurophysiological techniques), thereby outlining many facets that neuroscience offers for HCI research. The panel concludes that neuroscience has the potential to become an important reference discipline for the field of HCI in the future.
Abstract This study presents a new method,to effectively determine requirements for information systems involving widely dispersed end users, such as customers, suppliers, business partners, and other end-users outside the organization, and demonstrates the efficacy of the method,in a case study. Recently more IS have been targeted towards users outside the organization, making effective requirements engineering (RE) difficult. Outside users may have little relationship with the firm, are more costly to reach, may have different world views, and may not be available for iterative RE efforts. We identified seven problems associated with RE for wide audience end users and seven associated desirable characteristics for RE method that would address them. We reviewed IS, RE, and manufacturing literature to identify methods,that addressed these characteristics and found three methods,that supported four to five of the desired characteristics.We developed a method, wide audience requirements engineering (WARE), intended to support all seven characteristics.Major WARE features include a flexible, structured interviewing process (laddering), cognitive modeling (CSC), interpretive analysis, and a presentation tool that allows managers to view the requirements at several levels of aggregation by âÄúdrilling downâÄù all the way to the original interviews. We used WARE to develop the requirements for a major information system, directed at outside users, at Helsingin Sanomat, FinlandâÄôs largest newspaper. The demonstration showed,that WARE was effective for its intended purpose. The requirements developed using WARE became,the basis for a three year development,roadmap,for the system. The use of WARE helped managers and developers understand user preferences, reasoning, and priorities. Keywords: Requirements Gathering and Analysis, Critical Success Chains, CSC, Laddering, Wide Audience End-users (WARE), Requirements Engineering, Requirements Elicitation, Systems Analysis, Means-ends Analysis Permanent URL: http://sprouts.aisnet.org/4-27 Reference: Tuunanen, T., Peffers, K., Gengler, C. (2004). "Wide Audience Requirements
provide an introduction to psychophysiological research on the skeletomotor system / begin by reviewing the history of this research and by articulating some of the major issues, limitations, and advantages of surface electromyography (EMG) / review briefly the physiological basis of the EMG, and we summarize and update the recent guidelines for surface EMG recording in humans by Fridlund and Cacioppo (1986)
discussion of the social context for EMG recording and of psychophysiological principles, paradigms, and applications that have emerged from research on the skeletomotor system
a major theme in this chapter is that technical competence in recording EMG activity is necessary but not sufficient for securing scientifically meaningful data (PsycINFO Database Record (c) 2012 APA, all rights reserved)
This article aims to discuss the use of common neurophysiological tools, such as psychophysiological tools (e.g., EKG, eye tracking) and neuroimaging tools (e.g., fMRI, EEG) in Information Systems (IS) research. There is much interest in the social sciences in capturing objective data directly from the human body, and this interest has also been gaining momentum in IS research (termed NeuroIS). This article first introduces several commonly-used neurophysiological tools, and it then discusses several application areas and research questions where IS researchers can benefit from neurophysiological data toward developing a research agenda for NeuroIS. The proposed research areas are presented within four fundamental levels of analysis - individuals, groups, organizations, and markets - that are typically used to examine the use of IT.The article concludes with a set of recommendations on how to use neurophysiological tools in IS research along with practical suggestions for establishing NeuroIS as a viable sub-field in the IS literature.
We compare EER and OO data models from the point of view of design quality. Quality is measured in terms of (a) correctness of the conceptual schemas being designed, (b) time to complete the design task, and (c) designers' preferences of the models. Result of an experimental comparison of the two models reveal that the EER model surpasses the OO model for designing unary and ternary relationships, it takes less time to design EER schemas, and the EER model is preferred by designers. We conclude that even if the objective is to implement an OO database schema, the recommended procedure is to: (1) create an EER conceptual scheme, (2) map it to an OO schema, and augment the target schema with behavioral constructs that are unique to the OO approach.
The aim of the paper is to discuss the use of knowledge models to formulate general applications. First, the paper presents the recent evolution of the software field where increasing attention is paid to conceptual modelling. Then, the current state of knowledge modelling techniques is described where increased reliability is available through the modern knowledge-acquisition techniques and supporting tools. The knowledge structure manager (KSM) tool is described next. First, the concept of knowledge area is introduced as a building block where methods to perform a collection of tasks are included together with the bodies of knowledge providing the basic methods to perform the basic tasks. Then, the CONCEL language to define vocabularies of domains and the LINK language for methods formulation are introduced. Finally, the object-oriented implementation of a knowledge area is described and a general methodology for application design and maintenance supported by KSM is proposed. To illustrate the concepts and methods, an example of system for intelligent traffic management in a road network is described. This example is followed by a proposal of generalization for reuse of the resulting architecture. Finally, some concluding comments are made regarding the feasibility of using the knowledge modelling tools and methods for general application design.
Research in IT must address the design tasks faced by practitioners. Real problems must be properly conceptualized and represented, appropriate techniques for their solution must be constructed, and solutions must be implemented and evaluated using appropriate criteria. If significant progress is to be made, IT research must also develop an understanding of how and why IT systems work or do not work. Such an understanding must tie together natural laws governing IT systems with natural laws governing the environments in which they operate. This paper presents a two dimensional framework for research in information technology. The first dimension is based on broad types of design and natural science research activities: build, evaluate, theorize, and justify. The second dimension is based on broad types of outputs produced by design research: representational constructs, models, methods, and instantiations. We argue that both design science and natural science activities are needed to insure that IT research is both relevant and effective.
This paper introduces the idea of drawing upon the cognitive neuroscience literature to inform IS research (herein termed “NeuroIS”). Recent advances in cognitive neuroscience are uncovering the neural bases of cognitive, emotional, and social processes, and they offer new insights into the complex interplay between IT and information processing, decision making, and behavior among people, organizations, and markets.
The paper reviews the emerging cognitive neuroscience literature to propose a set of seven opportunities that IS researchers can use to inform IS phenomena, namely (1) localizing the neural correlates of IS constructs, (2) capturing hidden mental processes, (3) complementing existing sources of IS data with brain data, (4) identifying antecedents of IS constructs, (5) testing consequences of IS constructs, (6) inferring the temporal ordering among IS constructs, and (7) challenging assumptions and enhancing IS theories.
The paper proposes a framework for exploring the potential of cognitive neuroscience for IS research and offers examples of potentially fertile intersections of cognitive neuroscience and IS research in the domains of design science and human-computer interaction. This is followed by an example NeuroIS study in the context of e-commerce adoption using fMRI, which spawns interesting new insights. The challenges of using functional neuroimaging tools are also discussed. The paper concludes that there is considerable potential for using cognitive neuroscience theories and functional brain imaging tools in IS research to enhance IS theories.
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
Toward materializing the recently identified potential of cognitive neuroscience for IS research (Dimoka, Pavlou and Davis 2007), this paper demonstrates how functional neuroimaging tools can enhance our understanding of IS theories. Specifically, this study aims to uncover the neural mechanisms that underlie technology adoption by identifying the brain areas activated when users interact with websites that differ on their level of usefulness and ease of use. Besides localizing the neural correlates of the TAM constructs, this study helps understand their nature and dimensionality, as well as uncover hidden processes associated with intentions to use a system. The study also identifies certain technological antecedents of the TAM constructs, and shows that the brain activations associated with perceived usefulness and perceived ease of use predict selfreported intentions to use a system. The paper concludes by discussing the study’s implications for underscoring the potential of functional neuroimaging for IS research and the TAM literature.
Extant explanations of why users behave in particular ways toward information technologies have tended to focus predominantly on instrumental beliefs as drivers of individual usage intentions. Prior work in individual psychology, however, suggests that holistic experiences with technology as captured in constructs such as enjoyment and flow are potentially important explanatory variables in technology acceptance theories. In this paper, we describe a multidimensional construct labeled cognitive absorption and defined as a state of deep involvement with software. Cognitive absorption, theorized as being exhibited through the five dimensions of temporal dissociation, focused immersion, heightened enjoyment, control, and curiosity, is posited to be a proximal antecedent of two important beliefs about technology use: perceived usefulness and perceived ease of use. In addition, we propose that the individual traits of playfulness and personal innovativeness are important determinants of cognitive absorption. Based on the conceptual definition of this construct, operational measures for each dimension are developed. Using the World Wide Web as the target technology, scale validation indicates that the operational measures have acceptable psychometric properties and confirmatory factor analysis supports the proposed multi-dimensional structure. Structural equation analysis provides evidence for the theorized nomological net of cognitive absorption. Theoretical and practical implications are offered.
Despite that formal and informal quality aspects are of significant importance to business process modeling, there is only little empirical work reported on process model quality and its impact factors. In this paper we investigate understandability as a proxy for quality of process models and focus on its relations with personal and model characteristics. We used a questionnaire in classes at three European universities and generated several novel hypotheses from an exploratory data analysis. Furthermore, we interviewed practitioners to validate our findings. The results reveal that participants tend to exaggerate the differences in model understandability, that self-assessment of modeling competence appears to be invalid, and that the number of arcs in models has an important influence on understandability.
The paper motivates, presents, demonstrates in use, and evaluates
a methodology for conducting design science (DS) research in information
systems (IS). DS is of importance in a discipline oriented to the
creation of successful artifacts. Several researchers have pioneered
DS research in IS, yet over the past 15 years, little DS research
has been done within the discipline. The lack of a methodology to
serve as a commonly accepted framework for DS research and of a template
for its presentation may have contributed to its slow adoption. The
design science research methodology (DSRM) presented here incorporates
principles, practices, and procedures required to carry out such
research and meets three objectives: it is consistent with prior
literature, it provides a nominal process model for doing DS research,
and it provides a mental model for presenting and evaluating DS research
in IS. The DS process includes six steps: problem identification
and motivation, definition of the objectives for a solution, design
and development, demonstration, evaluation, and communication. We
demonstrate and evaluate the methodology by presenting four case
studies in terms of the DSRM, including cases that present the design
of a database to support health assessment methods, a software reuse
measure, an Internet video telephony application, and an IS planning
method. The designed methodology effectively satisfies the three
objectives and has the potential to help aid the acceptance of DS
research in the IS discipline.
Noninvasive brain imaging was used to observe 18 subjects, each making 90 choices of three brands on a virtual (video) supermarket visit. Package height provided a control for the main experiment. Brain activations in brand choice differed from those for height discrimination, and choice times were faster when one brand was more familiar. Brand choice appeared to involve silent vocalization. Decision processes took approximately 1 s and can be seen as two halves. The first period seems to involve problem recognition and here male brain patterns differed from female. The second half concerned the choice itself. No male/female differences were observed but a different pattern was evoked where one brand was familiar and the other two were not. The right parietal cortex was strongly activated in this case. This research pioneers new techniques using relatively few subjects and against a limited theoretical background. As such it must be classified as exploratory.
Purpose – Financial information about costs and return on investments are of key importance to strategic decision-making but also in the context of process improvement or business engineering. In this paper we propose a value-oriented approach to business process modeling based on key concepts and metrics from operations and financial management, to aid decision making in process re-design projects on the basis of process models.
Design/methodology/approach – We suggest a theoretically founded extension to current process modeling approaches, and delineate a framework as well as methodical support to incorporate financial information into process re-design. We use two case studies to evaluate the suggested approach.
Findings – Based on two case studies, we show that the value-oriented process modeling approach facilitates and improves managerial decision-making in the context of process re-design.
Research limitations / implications – We present design work and two case studies. More research is needed to more thoroughly evaluate the presented approach in a variety of real-life process modeling settings.
Practical implications – We show how our approach enables decision makers to make investment decisions in process re-design projects, and also how other decisions, for instance in the context of enterprise architecture design, can be facilitated.
Originality/value – This study reports on an attempt to integrate financial considerations into the act of process modeling, in order to provide more comprehensive decision making support in process re-design projects.
Until now, economic theory has not systematically integrated the influence of emotions on decision-making. Since evidence from neuroscience suggests that decision-making as hypothesized in economic theory depends on prior emotional processing, interdisciplinary research under the label of "neuroeconomics" arose. The key idea of this approach is to employ recent neuroscientific methods in order to analyze economically relevant brain processes. This paper aims to provide an overview of the current state of neuroeconomic research by giving a brief description of the concept of neuroeconomics, outlining methods commonly used and describing current studies in this new research area. Finally, some future prospects and limitations are discussed.
Who knows what I want to do? Who knows what anyone wants to do? How can you be sure about something like that? Isn't it all a question of brain chemistry, signals going back and forth, electrical energy in the cortex? How do you know whether something is really what you want to do or just some kind of nerve impulse in the brain. Some minor little activity takes place somewhere in this unimportant place in one of the brain hemispheres and suddenly I want to go to Montana or I don't want to go to Montana. (White Noise, Don DeLillo) 1.
This book combines the two methodologies of enterprise modeling and enterprise integration and advocates a systematic engineering approach called Enterprise Engineering, for modeling, analysing, designing and implementing integrated enterprise systems. Three main themes are explored in this book. The most significant enterprise modeling and integration architectures are presented. Enterprise modeling principles are then introduced and state-of-the-art methods to model various aspects of an enterprise system are discussed and compared. The final part is devoted to enterprise integration principles and techniques.
Conceptual data modelling (CDM) refers to the phase of the information systems development process that involves the abstraction and representation of the real world data pertinent to an organization. When CDM is properly and rigorously performed, the delivered system is expected to be functionally richer, less error-prone, more fully attuned to meet user needs, more able to adjust to changing user requirements and less expensive. However, there is little evidence that conceptual data modelling for the enterprise is actually conducted. There is the feeling that the 'corporate reality' is much different. In many organizations, CDM is never employed. In others, it is applied in a haphazard, project-to-project basis, thus leading to considerable redundancy. The academic community has mainly focused on proposing semantic data models but has not demonstrated a rigorous basis for conceptual data modelling. Specifically, the community has failed to show how a conceptual data model can map to an accurate logical data model. It is the purpose of this paper to discuss and compare the perspectives of academic and practitioner communities regarding the application of conceptual data modelling.
In order to exploit knowledge embedded in databases and to migrate from data to knowledge management environments, conceptual modeling languages must offer more expressiveness than traditional modeling languages. This paper proposes the conceptual graph formalism as such a modeling language. It shows through an example and a comparison with Telos, a semantically rich knowledge modeling language, that it is suited for that purpose. The conceptual graph formalism offers simplicity of use through its graphical components and small set of constructs and operators. It allows easy migration from database to knowledge base environments. Thus, this paper advocates its use.
Engagement in training and educational presentations facilitates learning. This paper describes engagement and proposes that it is conceptually similar to the state of playfulness, a construct increasingly applied to studies of human-computer interactions. It then describes how multimedia technologies can influence listeners' engagement during presentations. Results from pilot and main studies suggest that students' engagement in multimedia presentations can be increased by developing presentations that provide more challenge, feedback, presenter control, and variety. The paper concludes by discussing implications for research and practice.
The aim of this research essay is to examine the structural nature of theory in information systems. Despite the importance of theory, questions relating to its form and structure are neglected in comparison with questions relating to epistemology. The essay addresses issues of causality, explanation, prediction, and generalization that underlie an understanding of theory. A taxonomy is proposed that classifies information systems theories with respect to the manner in which four central goals are addressed: analysis, explanation, prediction, and prescription. Five interrelated types of theory are distinguished: (1) theory for analyzing, (2) theory for explaining, (3) theory for predicting, (4) theory for explaining and predicting, and (5) theory for design and action. Examples illustrate the nature of each theory type. The applicability of the taxonomy is demonstrated by classifying a sample of journal articles. The paper contributes by showing that multiple views of theory exist and by exposing the assumptions underlying different viewpoints. In addition, it is suggested that the type of theory under development can influence the choice of an epistemological approach. Support is given for the legitimacy and value of each theory type. The building of integrated bodies of theory that encompass all theory types is advocated.
Research provides increasing evidence that women and men differ in their decisions to trust. However, information systems research does not satisfactorily explain why these gender differences exist. One possible reason is that, surprisingly, theoretical concepts often do not address the most obvious factor that influences human behavior: biology. Given the essential role of biological factors-and specifically those of the brain-in decisions to trust, the biological influences should naturally include those related to gender. As trust considerations in economic decision making have become increasingly complex with the expansion of Internet use, understanding the related biological/brain functions and the involvement of gender provides a range of valuable insights.
To show empirically that online trust is associated with activity changes in certain brain areas, we used functional magnetic resonance imaging (fMRI). In a laboratory experiment, we captured the brain activity of 10 female and 10 male participants simultaneous to decisions on trustworthiness of eBay offers. We found that most of the brain areas that encode trustworthiness differ between women and men. Moreover, we found that women activated more brain areas than did men. These results confirm the empathizing- systemizing theory, which predicts gender differences in neural information processing modes.
In demonstrating that perceived trustworthiness of Internet offers is affected by neurobiology, our study has major implications for both IS research and management. We confirm the value of a category of research heretofore neglected in IS research and practice, and argue that future IS research investigating human behavior should consider the role of biological factors. In practice, biological factors are a significant consideration for management, marketing, and engineering attempts to influence behavior.
Design work and design knowledge in Information Systems (IS) is important
for both research and practice. Yet there has been comparatively
little critical attention paid to the problem of specifying design
theory so that it can be communicated, justified, and developed cumulatively.
In this essay we focus on the structural components or anatomy of
design theories in IS as a special class of theory. In doing so,
we aim to extend the work of Walls, Widemeyer and El Sawy (1992)
on the specification of information systems design theories (ISDT),
drawing on other streams of thought on design research and theory
to provide a basis for a more systematic and useable formulation
of these theories. We identify eight separate components of design
theories: (1) purpose and scope, (2) constructs, (3) principles of
form and function, (4) artifact mutability, (5) testable propositions,
(6) justificatory knowledge (kernel theories), (7) principles of
implementation, and (8) an expository instantiation. This specification
includes components missing in the Walls et al. adaptation of Dubin
(1978) and Simon (1969) and also addresses explicitly problems associated
with the role of instantiations and the specification of design theories
for methodologies and interventions as well as for products and applications.
The essay is significant as the unambiguous establishment of design
knowledge as theory gives a sounder base for arguments for the rigor
and legitimacy of IS as an applied discipline and for its continuing
progress. A craft can proceed with the copying of one example of
a design artifact by one artisan after another. A discipline cannot.
Business process modelling has gained widespread acceptance as a valuable design and management technique for a variety of purposes. While there has been much research on process modelling techniques and corresponding tools, there has been little empirical research into the success factors of effective process modelling, and the post hoc evaluation of process modelling success. This paper reports on the first attempt to identify process modelling success factors and measures, as empirically evidenced in case studies of nine process modelling projects in three leading Australian organizations.
Regional cerebral glucose metabolic rate (GMR) quantified with positron emission tomography (PET) with 18-fluoro-2-deoxyglucose (FDG) was measured twice in 8 young men performing a complex visuospatial/motor task (the computer game Tetris), before and after practice. After 4-8 weeks of daily practice on Tetris, GMR in cortical surface regions decreased despite a more than 7-fold increase in performance. Subjects who improved their Tetris performance the most after practice showed the largest glucose metabolic decreases after practice in several areas. These results suggest that learning may result in decreased use of extraneous or inefficient brain areas. Changes in regional subcortical glucose metabolic rate with practice may reflect changes in cognitive strategy that are a part of the learning process.
Administered a questionnaire containing items of varied content believed to be related to hypnotizability to 481 female undergraduates. 2 subsamples of 142 and 171 Ss, respectively, also completed Block's Ego Resiliency and Ego Control questionnaire scales and the Group Scales of Hypnotic Susceptibility. Analysis of the combined questionnaire data yielded 3 replicated higher order factors: the familiar dimensions of Stability and Introversion and a 3rd factor, Absorption. Absorption is interpreted as a disposition for having episodes of "total" attention that fully engage one's representational (i.e., perceptual, enactive, imaginative, and ideational) resources. This kind of attentional functioning is believed to result in a heightened sense of the reality of the attentional object, imperviousness to distracting events, and an altered sense of reality in general, including an empathically altered sense of self. Only Absorption was consistently correlated with hypnotizability. Absorption appears to be of interest for the study of hypnosis and personality. (38 ref)
A biocybernetic system has been developed as a method to evaluate automated flight deck concepts for compatibility with human capabilities. A biocybernetic loop is formed by adjusting the mode of operation of a task set (e.g., manual/automated mix) based on electroencephalographic (EEG) signals reflecting an operator's engagement in the task set. A critical issue for the loop operation is the selection of features of the EEG to provide an index of engagement upon which to base decisions to adjust task mode. Subjects were run in the closed-loop feedback configuration under four candidate and three experimental control definitions of an engagement index. The temporal patterning of system mode switching was observed for both positive and negative feedback of the index. The indices were judged on the basis of their relative strength in exhibiting expected feedback control system phenomena (stable operation under negative feedback and unstable operation under positive feedback). Of the candidate indices evaluated in this study, an index constructed according to the formula, beta power/(alpha power + theta power), reflected task engagement best.
A system was evaluated for use in adaptive automation using two experiments with electroencephalogram (EEG) indices based on the beta, alpha, and theta bandwidths. Subjects performed a compensatory tracking task while their EEG was recorded and converted to one of three engagement indices: beta/(alpha + theta), beta/alpha, or 1/alpha. In experiment one, the tracking task was switched between manual and automatic modes depending on whether the subject's engagement index was increasing or decreasing under a positive or negative feedback condition. Subjects were run for three consecutive 16-min trials. In experiment two, the task was switched depending on whether the absolute level of the engagement index for the subject was above or below baseline levels. It was hypothesized that negative feedback would produce more switches between manual and automatic modes, and that the beta/(alpha + theta) index would be most effective. The results confirmed these hypotheses. Tracking performance was better under negative feedback in both experiments; also, the use of absolute levels of engagement in experiment two resulted in better performance. There were no systematic changes in these effects over three 16-min trials. The implications for the use of such systems for adaptive automation are discussed.
The performance of an adaptive automation system was evaluated using a cognitive vigilance task. Participants responded to the presence of a green "K" in an array of two, five, or nine distractor stimuli during a 40-min vigil. The array with the target stimulus was presented once each minute. Participants EEG was recorded and an engagement index (EI = 20 x beta/(alpha + theta)) was derived. In the negative feedback condition, increases in the EI caused the number of stimuli in the array to decrease while decreases in the EI caused the number of stimuli to increase. For the positive feedback condition, increases in the index caused an increase in the array size (AS) while decreases caused a decrease in the array size. Each experimental participant had a yoked control partner who received the same pattern of changes in array irrespective of their engagement index. A vigilance decrement was seen only for the positive feedback, experimental group.
One hypothesis concerning the human dorsal anterior cingulate cortex (ACC) is that it functions, in part, to signal the occurrence of conflicts in information processing, thereby triggering compensatory adjustments in cognitive control. Since this idea was first proposed, a great deal of relevant empirical evidence has accrued. This evidence has largely corroborated the conflict-monitoring hypothesis, and some very recent work has provided striking new support for the theory. At the same time, other findings have posed specific challenges, especially concerning the way the theory addresses the processing of errors. Recent research has also begun to shed light on the larger function of the ACC, suggesting some new possibilities concerning how conflict monitoring might fit into the cingulate's overall role in cognition and action.
This article outlines a framework of creativity based on functional neuroanatomy. Recent advances in the field of cognitive neuroscience have identified distinct brain circuits that are involved in specific higher brain functions. To date, these findings have not been applied to research on creativity. It is proposed that there are four basic types of creative insights, each mediated by a distinctive neural circuit. By definition, creative insights occur in consciousness. Given the view that the working memory buffer of the prefrontal cortex holds the content of consciousness, each of the four distinctive neural loops terminates there. When creativity is the result of deliberate control, as opposed to spontaneous generation, the prefrontal cortex also instigates the creative process. Both processing modes, deliberate and spontaneous, can guide neural computation in structures that contribute emotional content and in structures that provide cognitive analysis, yielding the four basic types of creativity. Supportive evidence from psychological, cognitive, and neuroscientific studies is presented and integrated in this article. The new theoretical framework systematizes the interaction between knowledge and creative thinking, and how the nature of this relationship changes as a function of domain and age. Implications for the arts and sciences are briefly discussed.
Although organizational research has made tremendous strides in the last century, recent advances in neuroscience and the imaging of functional brain activity remain underused. In fact, even the use of well-established psychophysiological measurement tools is comparatively rare. Following the lead of social cognitive neuroscience, in this review, we conceptualize organizational cognitive neuroscience as a field dedicated to exploring the processes within the brain that underlie or influence human decisions, behaviors, and interactions either (a) within organizations or (b) in response to organizational manifestations or institutions. We discuss organizational cognitive neuroscience, bringing together work that may previously have been characterized rather atomistically, and provide a brief overview of individual methods that may be of use. Subsequently, we discuss the possible convergence and integration of the different neuroimaging and psychophysiological measurement modalities. A brief review of prior work in the field shows a significant need for a more coherent and theory-driven approach to organizational cognitive neuroscience. In response, we discuss a recent example of such work, along with three hypothetical case studies that exemplify the link between organizational and psychological theory and neuroscientific methods.
An overview of knowledge engineering research, practice, theories,
methodologies, and tools is presented, and parallels are drawn with
analogous phenomena and activities in requirements engineering.
Knowledge based systems are distinguished from other advanced
information systems by their reflective emphasis on meta information
processing about the basis of system operation. In terms of requirements
elicitation, this corresponds to an emphasis on maintaining an audit
trail from requirements through design, implementation, use and
maintenance that supports continuing user involvement in system
specification, design and evolution. Examples of knowledge elicitation
methodologies and tools are provided, and it is suggested that they all
have some applicability in requirements elicitation for advanced
information system development. It is concluded that closer
collaboration between the knowledge engineering and requirements
engineering communities will be mutually beneficial
Using a Business Simulation Game to Develop IT Competency
- P.-M Léger
- P Charland
- J Robert
- G Babin
Descarte’s Error. Grosset/Putnam
- A Damasio
Using Electroencephalograph Signals for Task Classification and Activity Recognition. Microsoft Corporation, US Patent & Trademark Office, Serial No.: 349859, United States Patent Application No
- D S Tan
- J C Lee
The Technology Acceptance Model and Cognitive Neuroscience Business &
- F Davis
- R Banker
- P Loos
- R Riedl
- G R Müller-Pütz
- J Vom Brocke
- F D Davis
- R D Banker
- Léger
Design Research Workshop: A Proactive Research Approach. Presentation delivered at IRIS 26
- M Rossi
- M Sein