Decision-Making Styles in Metaverse: Effects of Immersion and Embodiment

2023 | Americas Conference on Information Systems | Citations: 0

Authors: Bampouni, Elpida; Xi, Nannan; Hamari, Juho

Abstract: Decision-making is a vital skill of our daily cognitive arsenal. The rise of vi ... Expand

Abstract: Decision-making is a vital skill of our daily cognitive arsenal. The rise of virtual reality (VR) worlds like the metaverse, have created a new need to investigate human behavior under a technologically novel and multisensory prism. In this study, we experimentally investigate types of decision-making in artificial realities mediated by different levels of immersion (PC monitor vs. VR HMD) and sense of embodiment (self-motion vs. self-anchored). Participants (N=183) conducted a daily-life decision-making task of financial allocation, based on evaluating either a 3D graph or 2D graph containing price information across different periods. Five decision-making styles are evaluated including Rational, Intuitive, Dependent, Avoidant, and Spontaneous. Our results indicate that decision-making styles do not differ between diverse virtual realities, and instead remain similar to the control condition. However, due to the flexible nature of decision-making it is possible that content and environmental factors are still likely to influence decisionmaking in VR experiences. Collapse

Topics: virtual reality decision making virtual world

Methods: experiment multivariate analysis of variance survey experimental group survey design

Emotion in Motion: Experiment on Affective Responses to Virtual Realities

2023 | Americas Conference on Information Systems | Citations: 0

Authors: Bampouni, Elpida; Xi, Nannan; Hamari, Juho

Abstract: The rise of metaverse platforms pave the path for a future where many human act ... Expand

Abstract: The rise of metaverse platforms pave the path for a future where many human activities will be conducted in a virtual reality (VR). Therefore, it is necessary to investigate whether and how users emotionally respond to fully digitalized realities when conducting daily activities. In this study, we focus on two core features: immersion and sense of embodiment through self-motion. We conduct a large-scale experiment to examine the effects of virtual realities on emotional traits (PANAS). We use high (VR head-mounted-display) and low (PC monitor) immersive environments, as well as different levels of self-motion (high/low), compared to a 2D control. Students (N=183) were randomly assigned in one of 5 virtual conditions to complete a daily non-emotionally charged task. Two analyses were conducted based on the same experiment. The findings indicate that immersion and embodiment are not direct emotional elicitors on their own, and affect valence and arousal are likely content related. Collapse

Topics: virtual reality decision making extended reality virtual world

Methods: experiment multivariate analysis of variance experimental group survey parametric test

Gender, Pay Transparency, and Competitiveness: Why Salary Information Sometimes, but Not Always, Mitigates Gender Gaps in Salary Negotiations

2023 | Group Decision and Negotiation | Citations: 0

Authors: Bear, Julia B.; Pinkley, Robin; Barsness, Zoe; Mazei, Jens; Bhatia, Nazli; Sleesman, Dustin J.

Abstract: Although pay transparency is a widely accepted remedy for the gender pay gap, re ... Expand

Abstract: Although pay transparency is a widely accepted remedy for the gender pay gap, research has devoted little attention to the specific types of salary information that are available to job seekers and whether the framing of this information moderates gender differences in negotiation outcomes. We first conducted an exploratory study to investigate whether men and women differ in how much they rely on and perceive the usefulness of various sources of salary information. A survey of experienced MBA students revealed that, relative to women, men tend to place greater value on sources that involve direct social comparisons (e.g., professional networks) as opposed to more aggregate, general sources (e.g., websites). We then conducted a controlled experiment using a hypothetical job offer negotiation to determine whether framing salary information in terms of social comparison moderates gender gaps in salary requests. Our results supported a moderated mediation model, revealing that men requested higher salaries than women when presented with upward social comparison information (i.e., what a more qualified employee earns), but not downward (i.e., what a less qualified employee earns) or lateral comparison information (i.e., what a similarly qualified employee earns). These effects were driven by heightened competitiveness among men. We also discovered that both men and women experienced the greatest boost in competitiveness and salary requests when presented with downward social comparison information. Overall, salary information is effective in reducing gender gaps, but the effects are nuanced, as they depend on the social comparison inherent to the information. Collapse

Topics: IT career website

Methods: archival research parametric test ANOVA theory development experiment

AI Agents as Team Members: Effects on Satisfaction, Conflict, Trustworthiness, and Willingness to Work With

2023 | Journal of Management Information Systems | Citations: 5

Authors: Dennis, Alan R.; Lakhiwal, Akshat; Sachdeva, Agrim

Abstract: Organizations are beginning to deploy artificial intelligence (AI) agents as mem ... Expand

Abstract: Organizations are beginning to deploy artificial intelligence (AI) agents as members of virtual teams to help manage information, coordinate team processes, and perform simple tasks. How will team members perceive these AI team members and will they be willing to work with them? We conducted a 2 x 2 x 2 lab experiment that manipulated the type of team member (human or AI), their performance (high or low), and the performance of other team members (high or low). AI team members were perceived to have higher ability and integrity but lower benevolence, which led to no differences in trustworthiness or willingness to work with them. However, the presence of an AI team member resulted in lower process satisfaction. When the AI team member performed well, participants perceived less conflict compared to a human team member with the same performance, but there were no differences in perceived conflict when it performed poorly. There were no other interactions with performance, indicating that the AI team member was judged similarly to humans, irrespective of variations in performance; there was no evidence of algorithm aversion. Our research suggests that AI team members are likely to be accepted into teams, meaning that many old collaboration research questions may need to be reexamined to consider AI team members. Collapse

Topics: artificial intelligence video conference IT supported collaboration pandemic digital innovation

Methods: theory development computational algorithm statistical power analysis mediation analysis multivariate analysis of variance

Theories: theory of affordance

Effort as investment in healthcare dialogue-based agents: On the role of means-goal configurations

2023 | Decision Support Systems | Citations: 0

Authors: Ghasemi, Ehsan; Sheikh-Zadeh, Alireza; Song, Jaeki

Abstract: The recent pandemic and resultant increase in clinical caseload have brought dia ... Expand

Abstract: The recent pandemic and resultant increase in clinical caseload have brought dialogue-based agents (DBAs) to the forefront of attention in the healthcare industry. The ability of these agents to accomplish a variety of sequential and related tasks within a single application software has made them more effortful and complex. While effort requirements and complexity of information systems are generally considered negative attributes, the potential effect of user effort investment on user perceptions and decisions is less investigated. Within the framework of goal systems theory, this study explores how perceived effort could be appropriated to enhance users’ positive perceptions and willingness to accept healthcare DBAs outputs. We find evidence for the positive role both in the perceived effort before and after the actual use of healthcare DBAs as well as in user goal magnitude and means-goal configuration on perceptions of usefulness and probability of considering outputs. Collapse

Topics: technology adoption mobile application user experience decision making mobile phone

Methods: experiment regression analysis method experimental group linear regression analysis descriptive statistic

Theories: general systems theory

Explanation matters: An experimental study on explainable AI

2023 | Electronic Markets | Citations: 0

Authors: Hamm, Pascal; Klesel, Michael; Coberger, Patricia; Wittmann, H. Felix

Abstract: Explainable artificial intelligence (XAI) is an important advance in the field o ... Expand

Abstract: Explainable artificial intelligence (XAI) is an important advance in the field of machine learning to shed light on black box algorithms and thus a promising approach to improving artificial intelligence (AI) adoption. While previous literature has already addressed the technological benefits of XAI, there has been little research on XAI from the user’s perspective. Building upon the theory of trust, we propose a model that hypothesizes that post hoc explainability (using Shapley Additive Explanations) has a significant impact on use-related variables in this context. To test our model, we designed an experiment using a randomized controlled trial design where participants compare signatures and detect forged signatures. Surprisingly, our study shows that XAI only has a small but significant impact on perceived explainability. Nevertheless, we demonstrate that a high level of perceived explainability has a strong impact on important constructs including trust and perceived usefulness. A post hoc analysis shows that hedonic factors are significantly related to perceived explainability and require more attention in future research. We conclude with important directions for academia and for organizations. Collapse

Topics: explainable artificial intelligence artificial intelligence perceived ease of use perceived usefulness digital dashboard

Methods: experimental group experiment parametric test experimental task ANOVA

Theories: information systems theory trust theory

The puzzle of experience vs. memory: Peak-end theory and strategic gamification design in M-commerce

2023 | Information & Management | Citations: 0

Authors: Li, Manning; Jiang, Zhenhui (Jack); Ma, Guanghui

Abstract: As businesses increasingly use gamified mobile marketing campaign (GMMC) systems ... Expand

Abstract: As businesses increasingly use gamified mobile marketing campaign (GMMC) systems to engage mobile shop­ pers, gamification in m-commerce systems warrants more attention in both IS research and design practices. Inspired by peak-end theory, this study focused on the puzzling differences between user experience vs. memory and empirically examined the impact of different experience orders of cognitive load on user perceptions and behavioral intentions. Overall, the outcomes of this research suggest that appropriate applications of the peakend effect, moderated via users’ regulatory focus styles, can alleviate the negative mental utility imagery of users, reducing their perceived uncertainties and opt-out intentions from the GMMC. Important implications for research and practice are then discussed. Collapse

Topics: electronic data interchange marketing management user experience gamification systems design

Methods: experiment electroencephalography survey multivariate analysis of variance survey design

Theories: technology acceptance model flow theory self determination theory theory of planned behavior

A Design Theory for Certification Presentations

2023 | ACM SIGMIS Database | Citations: 0

Authors: Lins, Sebastian; Becker, Jan-Michael; Lyytinen, Kalle; Sunyaev, Ali

Abstract: Prior information system research remains inconsistent of the effects of system ... Expand

Abstract: Prior information system research remains inconsistent of the effects of system certifications. In their current use, certifications are often reduced to graphical seals. This approach fails to incorporate detailed assurance information emanating from the certification process. To address this gap, we adopt a design science approach and deploy a four-phase research design to clarify how to design impactful IS certification presentations. First, we identify sources of users' limited understanding of seals and formulate a design proposal for a certification presentation by drawing upon the elaboration likelihood model. In the second phase, we formulate and validate a set of design meta-requirements and guidelines to improve certification presentation, using cognitive load theory and Toulmin's model of argumentation as kernel theories. In the third phase, new certification presentations that comply with the proposed guidelines are developed and evaluated for their effectiveness. We show that presentations that augment seal-based certification presentations with richer assurance information improve certification effectiveness. This increases users' assurance and trust perceptions when the presentations align with the users' cognitive information processing needs in ways that reduce their cognitive load and enhance argument quality of assurance information. Collapse

Topics: cloud computing website information privacy concern cloud storage data quality

Methods: experiment design guideline experimental group survey design artifact

Theories: argumentation theory dual-system theory cognitive load theory elaboration likelihood model

What Disrupts Flow in Office Work? The Impact of Frequency and Relevance of IT-Mediated Interruptions

2023 | Management Information Systems Quarterly | Citations: 0

Authors: Nadj, Mario; Rissler, Raphael; Adam, Marc; Knierim, Michael; Li, Maximilian; Maedche, Alexander; Riedl, René

Abstract: Flow, the holistic sensation people experience when they act with total involve ... Expand

Abstract: Flow, the holistic sensation people experience when they act with total involvement, is a known driver for desired work outcomes like task performance. However, the increasing ubiquity of IT at work can disrupt employees' flow. Thus, the impact of IT-mediated interruptions on flow warrants more attention in research and practice. We conducted a NeuroIS laboratory experiment focusing on a typical office work task-an invoice matching task (i.e., matching customer payments to invoices). We manipulated interruption frequency (low, high) and content relevance (irrelevant, relevant) to study the impact of interruptions on self-reported flow, its dimensions, and high-frequency heart rate variability (HF-HRV; calculated from electrocardiography recordings) as a proxy for parasympathetic nervous system (PNS) activation. We found that content relevance moderated the relationship between interruption frequency and self-reported flow and that these results vary along flow dimensions. Content relevance also moderated the relationship between interruption frequency and PNS activation. Furthermore, selfreported flow was positively associated with both perceived and objective task performance, while PNS Collapse

Topics: task productivity cognitive absorption Python technostress information system use

Methods: electrocardiography NeuroIS multivariate analysis of variance experiment descriptive statistic

Theories: flow theory

Why Users Accept Discriminatory Pricing: The Roles of AI Agent's Presence and Explanation

2023 | International Conference on Information Systems | Citations: 0

Authors: PENG, XIAO; Peng, Xixian; Xu, David (Jingjun)

Abstract: Discriminatory pricing practices have raised consumers' negative reactions. Thi ... Expand

Abstract: Discriminatory pricing practices have raised consumers' negative reactions. This study investigates how AI agent's presence and the use of explanations impact consumers' acceptance of discriminatory pricing. A scenario-based experiment revealed that AI agent's presence negatively moderates the negative relationship between offer unfavorability and offer acceptance, which is mediated by perceived justice and invasion of privacy. Moreover, this research indicated that for unfavored price, environmentbased explanation is more effective than user-based explanation and the positive effect of AI agent's presence on offer acceptance is more pronounced when providing user-based explanations. This study contributes to price management literature and AI decision literature by illustrating how the AI agent's presence asymmetrically shapes consumers' perceptions of offer outcomes, enriching our understanding of consumer responses to AI. The findings have implications for firms managing discriminatory pricing, offering insights into optimal AI agents and explanation utilization for enhancing customer experience and business performance. Collapse

Topics: artificial intelligence price management privacy Uber consumer behavior

Methods: statistical hypothesis test ANOVA parametric test survey moderation analysis

Theories: distributive justice theory procedural justice theory attribution theory