NeuroIS: Hype or Hope?

This panel discusses the opportunities and challenges of applying cognitive neuroscience theories, methods, and tools to inform IS theories, methods, and data (termed “NeuroIS”). Given the ability of cognitive neuroscience to localize the functionality of brain areas that underlie higher-order human processes using functional neuroimaging tools, many social scientists in economics, psychology, and marketing use such tools to derive many interesting insights by opening the “black box” of the brain. Recently in the IS discipline, there have been some attempts to explore the potential of cognitive neuroscience for IS research (e.g., Dimoka, Pavlou, and Davis 2007). The purpose of this panel is to explore the potential of cognitive neuroscience and functional neuroimaging tools for IS research, and consistent with the theme of this year’s ICIS, suggest whether and how NeuroIS may help IS academics conduct IT research that really matters. This panel will host an intellectual debate on the opportunities and challenges of employing cognitive neuroscience and functional neuroimaging tools in IS research. The panelists come from different disciplines (Marketing, IS, Neuroscience), theories (technology adoption, IS economics, IT productivity, design science), and methods (behavioral/organizational, economics, technical), and they will discuss how IS theories and methods in their respective areas can be complemented by cognitive neuroscience theories and neuroimaging data. They will also debate the potential of physiological data for IS research, the pros and cons of functional neuroimaging tools, and whether NeuroIS can help IS researchers do research that they could not do with other means. The panel will have a broad appeal to IS researchers who may be interested in the potential of cognitive neuroscience for IS research but they are concerned about the challenges associated with using neuroimaging tools. The panel will debate whether NeuroIS can help IS researchers learn more than they already know, and whether, how, and when cognitive neuroscience will prove beneficial for IS research. The panel will also debate whether and how NeuroIS can contribute to IS research, whether and how the IS field can benefit by cognitive neuroscience theories, and what research questions could arise from using neuroimaging tools in IS research. The panel’s ultimate goal is to gauge whether NeuroIS is “hype or hope,” aiming to conclude whether NeuroIS could provide valuable opportunities for IS research, or whether the challenges associated with neuroimaging tools will impede their wide usage

Users Aren’t (Necessarily) Lazy: Using NeuroIS to Explain Habituation to Security Warnings

Warning messages are one of the last lines of defense in information security, and are fundamental to users’ security interactions with technology. Unfortunately, research shows that users routinely ignore security warnings. A key contributor to this disregard is habituation, the diminishing of attention through frequent exposure. However, previous research has examined habituation indirectly by observing its influence on security behavior, rather than measuring habituation itself. We contribute by using functional magnetic resonance imaging (fMRI) to directly observe habituation as it occurs in the brain. Our results show that with repeated exposure to warnings, neural activity in the visual processing centers sharply decreases. We also show that this process occurs for images of both security warnings and general software applications, although habituation is more severe for security warnings. Our findings suggest that habituation is not due to users’ laziness or carelessness, but is a natural consequence of how the brain works

The potential of using Neuro-IS to understand consumer's approach-avoidance motivation in online grocery retail

There is a request for research to examine consumer-purchasing behavior in online grocery retailing. By definition, behavior includes both cognition and observable responses. Neuro-Information Systems (NeuroIS) is a framework that offers a reliable measurement of consumer behavior, through direct observation of the brain using neuroscientific techniques. This paper discusses a potential application of using electroencephalography (EEG) to measure approach-avoidance motivation in online grocery retail contexts. A review of the literature on approach-avoidance, web atmospherics, and frontal asymmetry is conducted, to form appropriate linkages between theory and its application to the online grocery context. Additionally, this paper provides an example for exploring the potential of NeuroIS in an online setting, to demonstrate potential benefits when it comes to understanding and predicting consumer motivation in an online grocery retail context.submittedVersio

Brownie: A Platform for Conducting NeuroIS Experiments

In the NeuroIS field, experimental software needs to simultaneously present experimental stimuli to participants while recording, analyzing, or displaying neurophysiological measures. For example, a researcher might record a user’s heart beat (neurophysiological measure) as the user interacts with an e-commerce website (stimulus) to track changes in user arousal or show a user’s changing arousal levels during an exciting game. In this paper, we identify requirements for a NeuroIS experimental platform that we call Brownie and present its architecture and functionality. We then evaluate Brownie via a literature review and a case study that demonstrates Brownie’s capability to meet the requirements in a complex research context. We also verify Brownie’s usability via a quantitative study with prospective experimenters who implemented a test experiment in Brownie and an alternative software. We summarize the salient features of Brownie as follows: 1) it integrates neurophysiological measurements, 2) it incorporates real-time processing of neurophysiological data, 3) it facilitates research on individual and group behavior in the lab, 4) it offers a large variety of options for presenting experimental stimuli, and 5) it is open source and easily extensible with open source libraries. In summary, we conclude that Brownie is innovative in its potential to reduce barriers for IS researchers by fostering replicability and research collaboration and to support NeuroIS and interdisciplinary research in cognate areas, such as management, economics, or human-computer interaction

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

Humans versus Agents: Competition in Financial Markets of the 21st Century

Information systems have revolutionized the nature of markets. Traditionally, markets inherently comprised the strategic interaction of human traders only. Nowadays, however, automated trading agents are responsible for at least 60% of the US trading volume on financial stock markets. In this respect, financial markets of the 21st century are different to markets of previous centuries. Fuelled by discussions on their possible risks, there is a need for research on the effects of automated trading agents on market efficiency and on human traders. In order to systematically investigate these issues, we introduce a market framework for human-computer interaction. This framework is then applied in a case study on a financial market scenario. In particular, we plan to conduct a NeuroIS experiment in which we analyze overall market efficiency as well as the trading behavior and emotional responses of human traders when they interact with computerized trading agents

The Potential of Neuroscience for Human-Computer Interaction Research

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

A Design Framework and AI System for Affective Destination Image Generation to Influence Tourists’ Emotional Response

Affective destination images have received considerable attention from tourism marketing researchers as evidence suggests that affective components in destination images affect tourists’ emotional responses, which in turn influence their behavioural intentions toward the destination. Therefore, tourism practitioners seek solutions to influence the emotional effects of affective destination images for B2C communication. This paper presents a design science research project to develop an AI system to assist practitioners in generating affective destination images that potentially trigger the desired emotional responses of tourists. By leveraging knowledge and techniques from NeuroIS, this paper also proposes a framework of scientific experiments to assess how the generated affective destination images by the AI system affect tourists’ emotional experiences

Mediators of the relationship between self-control and pathological technology use: Negative affect and cognitive failures, but not self-efficacy

The widespread adoption of technologies such as smartphones, the Internet, and social media has been associated with the emergence of pathological technology use (e.g., Internet addiction). Prevalence rates of pathological technology use vary widely across age groups, cultures, and medium, although it is not uncommon for rates of mild to moderate pathological use to exceed 20%-30%. These relatively high prevalence rates have motivated researchers to identify the predictors of pathological use. The current study focuses on the relationship be- tween self-control and pathological technology use, and demonstrates that negative affect and cognitive failures, but not self-efficacy, partially mediate the association between self-control and pathological technology use. These findings re- veal some of the pathways by which poor self-control could lead to elevated levels of pathological technology use