Unlocking Online Reputation – On the Effectiveness of Cross-Platform Signaling in the Sharing Economy

With the ever-growing popularity of sharing economy platforms, complementors increasingly face the challenge to manage their reputation on different plat- forms. The paper reports the results from an experimental online survey to investigate how and under which condi- tions online reputation is effective to engender trust across platform boundaries. It shows that (1) cross-platform sig- naling is in fact a viable strategy to engender trust and that (2) its effectiveness crucially depends on source–target fit. Implications for three stakeholders are discussed. First, platform complementors may benefit from importing rep- utation, especially when they have just started on a new platform and have not earned on-site reputation yet. The results also show, however, that importing reputation (even if it is excellent) may be detrimental if there occurs a mismatch between source and target and that, hence, fit is of utmost importance. Second, regulatory authorities may consider reputation portability as a means to make platform boundaries more permeable and hence to tackle lock-in effects. Third, platform operators may employ cross-plat- form signaling as a competitive lever

In Stars We Trust – A Note on Reputation Portability Between Digital Platforms

Complementors accumulate reputation on an ever-increasing number of online platforms. While the effects of reputation within individual platforms are well-understood, its potential effectiveness across platform boundaries has received much less attention. This research note considers complementors’ ability to increase their trustworthiness in the eyes of prospective consumers by importing reputational data from another platform. The study evaluates this potential lever by means of an online experiment, during which specific combinations of on-site and imported rating scores are tested. Results reveal that importing reputation can be advantageous – but also detrimental, depending on ratings’ values. Implications for complementors, platform operators, and regulatory bodies concerned with online reputation are considered

User Assistance for Intelligent Systems

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Design Blueprint for Stress-Sensitive Adaptive Enterprise Systems

Stress is a major problem in the human society, impairing the well-being, health, performance, and productivity of many people worldwide. Most notably, people increasingly experience stress during human-computer interactions because of the ubiquity of and permanent connection to information and communication technologies. This phenomenon is referred to as technostress. Enterprise systems, designed to improve the productivity of organizations, frequently contribute to this technostress and thereby counteract their objective. Based on theoretical foundations and input from exploratory interviews and focus group discussions, the paper presents a design blue-print for stress-sensitive adaptive enterprise systems (SSAESes). A major characteristic of SSAESes is that bio-signals (e.g., heart rate or skin conductance) are integrated as real-time stress measures, with the goal that systems automatically adapt to the users’ stress levels, thereby improving human-computer interactions. Various design interventions on the individual, technological, and organi- zational levels promise to directly affect stressors or moderate the impact of stressors on important negative effects (e.g., health or performance). However, designing and deploying SSAESes pose significant challenges with respect to technical feasibility, social and ethical accept- ability, as well as adoption and use. Considering these challenges, the paper proposes a 4-stage step-by-step implementation approach. With this Research Note on technostress in organizations, the authors seek to stimulate the discussion about a timely and important phenomenon, particularly from a design science research perspective

Using Live Biofeedback for Decision Support: Investigating Influences of Emotion Regulation in Financial Decision Making

The influence of emotions on decision making is widely accepted, however, research investigat-ing emotions within decision support systems is scarce. Previous research showed that via emo-tion regulation decision makers can significantly improve their decisions. However, a sound perception of emotions is a foundation for beneficial emotion regulation. In this paper, we pro-pose the use of live biofeedback–the provision of real-time information about a person’s current physiological state–as a potential feature for decision support systems in online environments. We developed a research model and hypothesize that live biofeedback can moderate (i) the in-fluence of the decision environment on decision makers’ physiological states and (ii) the deci-sion makers’ perceptions of their emotional states. Within the current research a live biofeed-back prototype for decision support in the context of financial trading was implemented. We aim at testing the hypothesized moderating effects of the developed decision support system in the controlled environment of a laboratory market experiment

Design Science Research Modes in Human-Computer Interaction Projects

In this editorial, we introduce the special issue on design science research in human-computer interaction with four papers extended from the 2020 European Conference on Information Systems and propose a conceptual model for such research projects. Research in the interdisciplinary human-computer interaction (HCI) discipline advances knowledge of how humans interact with technologies, systems, information, and work structures. Design science research (DSR) methods support three distinct modes in HCI projects. In the interior mode, researchers build and evaluate novel technical solutions with a focus on improved system interfaces to support effective human use. Next, in the exterior mode, researchers build and evaluate novel behavioral solutions with a process focus on interactions that increase human capabilities. Lastly, in the gestalt mode, researchers build and evaluate novel composite solutions that improve synergies between technologies and human behaviors. We pose a comprehensive model for identifying the DSR modes of HCI research with related artifacts, evaluation techniques, design theories, and research impacts

Digital Human Representations for Health Behavior Change: A Structured Literature Review

Organizations have increasingly begun using digital human representations (DHRs), such as avatars and embodied agents, to deliver health behavior change interventions (BCIs) that target modifiable risk factors in the smoking, nutrition, alcohol overconsumption, and physical inactivity (SNAP) domain. We conducted a structured literature review of 60 papers from the computing, health, and psychology literatures to investigate how DHRs’ social design affects whether BCIs succeed. Specifically, we analyzed how differences in social cues that DHRs use affect user psychology and how this can support or hinder different intervention functions. Building on established frameworks from the human-computer interaction and BCI literatures, we structure extant knowledge that can guide efforts to design future DHR-delivered BCIs. We conclude that we need more field studies to better understand the temporal dynamics and the mid-term and long-term effects of DHR social design on user perception and intervention outcomes

A Bibliometric Review of Digital Nudging within Digital Food Choice Environments

People increasingly make choices about their food intake in digital environments (e.g., online food delivery, online grocery shopping, online school canteens). Given the critical role of diet quality as a key driver for non-communicable disease, it is vital to understand how to design such systems to facilitate healthy food choice through digital nudging. To better understand the impact of digital technologies on food choice, we need to understand the knowledge structure of previous literature. A systematic review of literature identified 83 relevant publications which have been included in this study. Bibliometric analyses were used to map out the knowledge structure, historical roots, and evolution. Reference year spectroscopy, co-word analysis and co-citation analysis were used. Findings show digital nudging is a rapid growing field with strong historical roots in psychology. Additionally, current literature is utilizing psychological theories during the development of digital technologies aimed at nudging consumers towards healthier food options