The First 10 Years of NeuroIS: A Systematic Literature Review of NeuroIS Publications (2007 - 2017)

NeuroIS is an emerging and promising academic field that has attracted increasing attention. The year 2017 signifies the 10th year of existence of NeuroIS as a research field in information systems area. In this study, we conduct a systematic literature review of the NeuroIS academic research publications of last 10 years (2007-2017). As a result, we categorize the existent NeuroIS literature into 8 groups, explore the correlations among various NeuroIS concepts/ constructs, and demonstrate how the study enhances our understanding of the granulated inter-relationships between pairs of NeuroIS elements. The implications of the result to the NeuroIS research community are discussed

Appreciating the Performance of Neuroscience Mining in NeuroIS research: A Case Study on Consumer's Product Perceptions in the Two UI Modes—Dark UI vs. Light UI

The goal of the current study was to provide information on the potential of neuroscience mining (NSM) for comprehending NeuroIS paradigms. NSM is an interdisciplinary field that combines neuroscience and business mining, which is the application of big data analytics, computational social science, and other fields to business problems. Therefore, NSM makes it possible to apply predictive models to NeuroIS datasets, such as machine learning and deep learning, to find intricate patterns that are hidden by conventional regression-based analysis. We predicted 28 individual EEG power spectra separated brainwave data using a Random Forest (RF) model. Next, we used NSM to precisely predict how consumers would perceive a product online, depending on whether a light or dark user interface (UI) mode was being used. The model was then used to extract more precise results that could not be obtained using more conventional linear-based analytical models using sensitivity analysis. The benefits of using NSM in NeuroIS research are as follows: (1) it can relieve the burden of the three-horned dilemma described by Runkel and McGrath; (2) it can enable more temporal data to be directly analyzed on the target variables; and (3) sensitivity analysis can be performed on a condition/individual basis, strengthening the rigor of findings by reducing sample bias that can be lost in grand averaging of data when analyzed with methods like GLM

Measurement of Heart Rate and Heart Rate Variability with Wearable Devices: A Systematic Review

Wearables are a ubiquitous trend in both commercial and academic settings as they easily enable tracking and monitoring of physiological parameters such as heart rate (HR) and heart rate variability (HRV). This paper presents a literature review to survey the existing Neuro-Information-Systems (NeuroIS) literature on HR and HRV with a focus on measurement based on wearable devices. We addressed the following four research questions: Who published HR and HRV research? What kind of HR and HRV research has been published? With which wearable devices was HR and HRV measured? How reliable and valid are HR and HRV measurements based on wearable devices? Our review provides answers to these questions and concludes that further efforts are needed to advance the field from both a theoretical and methodological perspective

Electroencephalography (EEG) as a Research Tool in the Information Systems Discipline: Foundations, Measurement, and Applications

The concept of neuro-information systems (neuroIS) has emerged in the IS discipline recently. Since the neuroIS field’s genesis, several neuroIS papers have been published. Investigating empirical papers published in scientific journals and conference proceedings reveals that electroencephalography (EEG) is a widely used tool. Thus, considering its relevance in contemporary research and the fact that it will also play a major role in future neuroIS research, we describe EEG from a layman’s perspective. Because previous EEG descriptions in the neuroIS literature have only scantily outlined theoretical and methodological aspects related to this tool, we urgently need a more thorough one. As such, we inform IS scholars about the fundamentals of EEG in a compact way and discuss EEG’s potential for IS research. Based on the knowledge base provided in this paper, IS researchers can make an informed decision about whether EEG could, or should, become part of their toolbox

Towards a NeuroIS Research Methodology: Intensifying the Discussion on Methods, Tools, and Measurement

The genesis of the Neuro-Information Systems (NeuroIS) field took place in 2007. Since then, a considerable number of IS scholars and academics from related disciplines have started to use theories, methods, and tools from neuroscience and psychophysiology to better understand human cognition, emotion, and behavior in IS contexts, and to develop neuro-adaptive information systems (i.e., systems that recognize the physiological state of the user and that adapt, based on that information, in real-time). However, because the NeuroIS field is still in a nascent stage, IS scholars need to become familiar with the methods, tools, and measurements that are used in neuroscience and psychophysiology. Against the background of the increased importance of methodological discussions in the NeuroIS field, the Journal of the Association for Information Systems published a special issue call for papers entitled “Methods, tools, and measurement in NeuroIS research” in 2012. We, the special issue’s guest editors, accepted three papers after a stringent review process, which appear in this special issue. In addition to these three papers, we hope to intensify the discussion on NeuroIS research methodology, and to this end we present the current paper. Importantly, our observations during the review process (particularly with respect to methodology) and our own reading of the literature and the scientific discourse during conferences served as input for this paper. Specifically, we argue that six factors, among others that will become evident in future discussions, are critical for a rigorous NeuroIS research methodology; namely, reliability, validity, sensitivity, diagnosticity, objectivity, and intrusiveness of a measurement instrument. NeuroIS researchers—independent from whether their role is editor, reviewer, or author—should carefully give thought to these factors. We hope that the discussion in this paper instigates future contributions to a growing understanding towards a NeuroIS research methodology

Eye-tracking for IS Research: A Literature Review

In this literature review, we describe the Information Systems (IS) research using eye-tracking. Based on a sample of 60 papers published since 2008 in journals and conference proceedings, we examine i) what is the trend in eye-tracking IS research, ii) what types of experimental design have been used, iii) what types of metrics have been collected and iv) what constructs and topics have been investigated. We found that IS research using eye-tracking is broad in its research themes but concentrated in its methods of analysis. All the research is quantitative and mostly use fixation counts on computer desktop. A limited number of articles take advantage of pupil dilation measure or mobile eye-tracking. We call for broadening the methods of collection and analysis in eye-tracking IS research

Feel, Don\u27t Think Review of the Application of Neuroscience Methods for Conversational Agent Research

Conversational agents (CAs) equipped with human-like features (e.g., name, avatar) have been reported to induce the perception of humanness and social presence in users, which can also increase other aspects of users’ affection, cognition, and behavior. However, current research is primarily based on self-reported measurements, leaving the door open for errors related to the self-serving bias, socially desired responding, negativity bias and others. In this context, applying neuroscience methods (e.g., EEG or MRI) could provide a means to supplement current research. However, it is unclear to what extent such methods have already been applied and what future directions for their application might be. Against this background, we conducted a comprehensive and transdisciplinary review. Based on our sample of 37 articles, we find an increased interest in the topic after 2017, with neural signal and trust/decision-making as upcoming areas of research and five separate research clusters, describing current research trends

Non-invasive Brain Stimulation as a Set of Research Tools in NeuroIS: Opportunities and Methodological Considerations

NeuroIS is a growing field that builds on neuroscience to improve the understanding of human interaction with information technologies and information systems. One can investigate causal relationships between brain activity patterns, cognitive processes, and behavior in a non-invasive way via using non-invasive brain stimulation (NIBS) tools, but researchers in the neuroIS community have yet to do so. We introduce NIBS, show how it can address caveats found in current research, describe the implementation of a NIBS protocol, and assess what these tools can bring to the neuroIS field