Jeffrey L. Jenkins

The CMC Interactivity Model: How Interactivity Enhances Communication Quality and Process Satisfaction in Lean-Media Groups

Process satisfaction is one important determinant of work group collaborative system adoption, continuance, and performance. We explicate the computermediated communication (CMC) interactivity model (CMCIM) to explain and predict how interactivity enhances communication quality that results in increased process satisfaction in CMC-supported work groups. We operationalize this model in the challenging context of very large groups using extremely lean CMC. We tested it with a rigorous field experiment and analyzed the results with the latest structural equation modeling techniques. Interactivity and communication quality dramatically improved for very large groups using highly lean CMC (audience response systems) over face-to-face groups. Moreover, CMC groups had fewer negative status effects and higher process satisfaction than face-to-face groups. The practical applications of lean CMC rival theoretical applications in importance because lean CMC is relatively inexpensive and requires minimal training and support compared to other media. The results may aid large global work group continuance, satisfaction, and performance in systems, product and strategy development, and other processes in which status effects and communication issues regularly have negative influences on outcomes.

Detecting Deceptive Chat-Based Communication Using Typing Behavior and Message Cues

Computer-mediated deception is prevalent and may have serious consequences for individuals, organizations, and society. This article investigates several metrics as predictors of deception in synchronous chat-based environments, where participants must often spontaneously formulate deceptive responses. Based on cognitive load theory, we hypothesize that deception influences response time, word count, lexical diversity, and the number of times a chat message is edited. Using a custom chatbot to conduct interviews in an experiment, we collected 1,572 deceitful and 1,590 truthful chat-based responses. The results of the experiment confirm that deception is positively correlated with response time and the number of edits and negatively correlated to word count. Contrary to our prediction, we found that deception is not significantly correlated with lexical diversity. Furthermore, the age of the participant moderates the influence of deception on response time. Our results have implications for understanding deceit in chat-based communication and building deception-detection decision aids in chat-based systems.

Implicit and explicit training in the mitigation of cognitive bias through the use of a serious game

We examine the mitigation of two cognitive biases through a video game.We conducted an experiment (N=708) to compare the game to an instructional video.The game was compared to outcomes testing knowledge and mitigation of the biases.Explicit instruction improved familiarity and knowledge of the biases more than implicit.More exposure through repeated play enhanced learning. Heuristics can interfere with information processing and hinder decision-making when more systematic processes that might lead to better decisions are ignored. Based on the heuristic-systematic model (HSM) of information processing, a serious training game (called MACBETH) was designed to address and mitigate cognitive biases that interfere with the analysis of evidence and the generation of hypotheses. Two biases are the focus of this paper-fundamental attribution error and confirmation bias. The efficacy of the serious game on knowledge and mitigation of biases was examined using an experiment in which participants (N=703) either played the MACBETH game or watched an instructional video about the biases. Results demonstrate the game to be more effective than the video at mitigating cognitive biases when explicit training methods are combined with repetitive play. Moreover, explicit instruction within the game provided greater familiarity and knowledge of the biases relative to implicit instruction. Suggestions for game development for purposes of enhancing cognitive processing and bias mitigation based on the MACBETH game design are discussed.

How Is Your User Feeling? Inferring Emotion Through Human-Computer Interaction Devices

City University of Hong Kong [7002626, 7004123]; Research Grants Council of the Hong Kong Special Administrative Region [CityU149512]

From Warning to Wallpaper: Why the Brain Habituates to Security Warnings and What Can Be Done About It

Abstract Warning messages are fundamental to users’ security interactions. Unfortunately, they are largely ineffective, as shown by prior research. A key contributor to this failure is habituation: decreased response to a repeated warning. Previous research has only inferred the occurrence of habituation to warnings, or measured it indirectly, such as through the proxy of a related behavior. Therefore, there is a gap in our understanding of how habituation to security warnings develops in the brain. Without direct measures of habituation, we are limited in designing warnings that can mitigate its effects. In this study, we use neurophysiological measures to directly observe habituation as it occurs in the brain and behaviorally. We also design a polymorphic warning artifact that repeatedly changes its appearance in order to resist the effects of habituation. In an experiment using functional magnetic resonance imaging (fMRI; n = 25), we found that our polymorphic warning was significantly more resistant to habituation than were conventional warnings in regions of the brain related to attention. In a second experiment (n = 80), we implemented the four most resistant polymorphic warnings in a realistic setting. Using mouse cursor tracking as a surrogate for attention to unobtrusively measure habituation on participants’ personal computers, we found that polymorphic warnings reduced habituation compared to conventional warnings. Together, our findings reveal the substantial influence of neurobiology on users’ habituation to security warnings and security behavior in general, and we offer our polymorphic warning design as an effective solution to practice

More Harm than Good? How Messages that Interrupt Can Make Us Vulnerable

System-generated alerts are ubiquitous in personal computing and, with the proliferation of mobile devices, daily activity. While these interruptions provide timely information, research shows they come at a high cost in terms of increased stress and decreased productivity. This is due to dual-task interference (DTI), a cognitive limitation in which even simple tasks cannot be simultaneously performed without significant performance loss. Although previous research has examined how DTI impacts the performance of a primary task (the task that was interrupted), no research has examined the effect of DTI on the interrupting task. This is an important gap because in many contexts, failing to heed an alert—the interruption itself—can introduce critical vulnerabilities.Using security messages as our context, we address this gap by using functional magnetic resonance imaging (fMRI) to explore how (1) DTI occurs in the brain in response to interruptive alerts, (2) DTI influences message security disregard, and (3) the effects of DTI can be mitigated by finessing the timing of the interruption. We show that neural activation is substantially reduced under a condition of high DTI, and the degree of reduction in turn significantly predicts security message disregard. Interestingly, we show that when a message immediately follows a primary task, neural activity in the medial temporal lobe is comparable to when attending to the message is the only task.Further, we apply these findings in an online behavioral experiment in the context of a web-browser warning. We demonstrate a practical way to mitigate the DTI effect by presenting the warning at low-DTI times, and show how mouse cursor tracking and psychometric measures can be used to validate low-DTI times in other contexts.Our findings suggest that although alerts are pervasive in personal computing, they should be bounded in their presentation. The timing of interruptions strongly influences the occurrence of DTI in the brain, which in turn substantially impacts alert disregard. This paper provides a theoretically grounded, cost-effective approach to reduce the effects of DTI for a wide variety of interruptive messages that are important but do not require immediate attention.

How users perceive and respond to security messages: a NeuroIS research agenda and empirical study

Users are vital to the information security of organizations. In spite of technical safeguards, users make many critical security decisions. An example is users’ responses to security messages – discrete communication designed to persuade users to either impair or improve their security status. Research shows that although users are highly susceptible to malicious messages (e.g., phishing attacks), they are highly resistant to protective messages such as security warnings. Research is therefore needed to better understand how users perceive and respond to security messages. In this article, we argue for the potential of NeuroIS – cognitive neuroscience applied to Information Systems – to shed new light on users’ reception of security messages in the areas of (1) habituation, (2) stress, (3) fear, and (4) dual-task interference. We present an illustrative study that shows the value of using NeuroIS to investigate one of our research questions. This example uses eye tracking to gain unique insight into how habituation occurs when people repeatedly view security messages, allowing us to design more effective security messages. Our results indicate that the eye movement-based memory (EMM) effect is a cause of habituation to security messages – a phenomenon in which people unconsciously scrutinize stimuli that they have previously seen less than other stimuli. We show that after only a few exposures to a warning, this neural aspect of habituation sets in rapidly, and continues with further repetitions. We also created a polymorphic warning that continually updates its appearance and found that it is effective in substantially reducing the rate of habituation as measured by the EMM effect. Our research agenda and empirical example demonstrate the promise of using NeuroIS to gain novel insight into users’ responses to security messages that will encourage more secure user behaviors and facilitate more effective security message designs.

Proposing the Affect-Trust Infusion Model (ATIM) to Explain and Predict the Influence of High- and Low-Affect Infusion on Web Vendor Trust

Trust is just as essential to online business as it is to offline transactions but can be more difficult to achieve - especially for newer websites with unknown web vendors. Research on web-based trust development explains that web vendor trust can be created by both cognitive and affective (e.g., emotion-based) influences. But under what circumstances will emotion or cognition be more dominate in trust establishment? Theory-based answers to these questions can help online web vendors design better websites that account for unleveraged factors that will increase trust in the web vendor. To this end, we use the Affect Infusion Model and trust transference to propose the Affect-Trust Infusion Model (ATIM) that explains and predicts how and when cognition, through perceived website performance (PwP), and positive emotion (PEmo) each influence web vendor trust. ATIM explains the underlying causal mechanisms that determine the degree of affect infusion and the subsequent processing strategy that a user adopts when interacting with a new website. Under high-affect infusion, PEmo acts as a mediator between PwP and vendor trust; under low-affect infusion, PwP primarily impacts trust and PEmo is dis-intermediated. We review two distinct, rigorously validated experiments that empirically support ATIM. To further extend the contributions of ATIM, we demonstrate how use of specific contextual features-rooted in theory and that drive ones choice of affect infusion and cognitive processing-can be leveraged into a methodology that we propose to further enhance user-centered design (UCD). We further detail several exciting research opportunities that can leverage ATIM.

What Do We Really Know about How Habituation to Warnings Occurs Over Time?: A Longitudinal fMRI Study of Habituation and Polymorphic Warnings

A major inhibitor of the effectiveness of security warnings is habituation: decreased response to a repeated warning. Although habituation develops over time, previous studies have examined habituation and possible solutions to its effects only within a single experimental session, providing an incomplete view of the problem. To address this gap, we conducted a longitudinal experiment that examines how habituation develops over the course of a five-day workweek and how polymorphic warnings decrease habituation. We measured habituation using two complementary methods simultaneously: functional magnetic resonance imaging (fMRI) and eye tracking. Our results show a dramatic drop in attention throughout the workweek despite partial recovery between workdays. We also found that the polymorphic warning design was substantially more resistant to habituation compared to conventional warnings, and it sustained this advantage throughout the five-day experiment. Our findings add credibility to prior studies by showing that the pattern of habituation holds across a workweek, and indicate that cross-sectional habituation studies are valid proxies for longitudinal studies. Our findings also show that eye tracking is a valid measure of the mental process of habituation to warnings.

Using Wearable Devices for Non-invasive, Inexpensive Physiological Data Collection

Using sensors to gather physiological data about users can provide valuable insights for Information Systems (IS) research that are not availed through traditional measures. While useful in many laboratory settings, many of these physiological sensors (e.g., fMRI, EEG, EKG, etc.) are impractical and severely limited in other scenarios due to (1) prohibitive cost, (2) small sample size, (3) invasiveness, and (4) the difficulty to match psychological traits to physiological measures. In this study, we demonstrate how inexpensive consumer-grade wearable technologies overcome these first three limitations while we extend existing research on exploring the fourth limitation.