Setting the e-Commerce Scene: A Qualitative Investigation of the Use of Nature Imagery in User Interface Design

User experience designers often employ natural landscapes as background imagery in e-commerce user interfaces (UI). However, at this stage, there is only limited work on how nature imagery in UI design affects user perception and behaviour. In this paper, we present a qualitative study involving semi-structured interviews into the use of nature imagery in UI design. Our study builds on theories in environmental psychology and seeks to develop a theoretical framework for the role of nature imagery in user perception and behaviour. Further, building on the expertise of user experience practitioners and end users, we seek to develop theoretically-grounded design guidelines for the capture, selection, and integration of nature imagery in e-commerce UI designs

Incorporating Emotional Information in Decision Systems

Abstract – The media equation [22] states that users react to systems as they would to another person, while continuously emitting social signals. Today’s users expect systems to be empathetic and understand these social signals. Decision systems are a specific sub-branch, facing the need to incorporate affective information, to facilitate users to maximize their cognitive resources. To this end, we attempt to incorporate affective information in the form of physiology to learn users ’ decision behavior. In a controlled experiment, we record participants ’ decisions and measure physiological signals elicited from subjects. To predict the binary decision to buy or sell, three algorithms, multi-layer perceptron, radial basis function, and decision trees, are compared, and they yield recognition rates of 76%, 73 % and 77.2 % respectively. Taking these results, we propose that a decision tree with feature-level fusion, factors in affective information in this controlled context best. These results however have to be extrapolated to decision contexts that elicit emotions more strongly. Keywords—Multimodal Systems, Emotion, User Behavior

Designing Persuasive Avatars in mHealth for Arabic Culture: A Qualitative Study

Open innovation is built on the core principles of interactions, interdependence and exchange of knowledge. Clusters are believed to support organisations’ efforts to explore and source external knowledge, commercialise internal innovations and cause externalities through commercial activities. Early research on the innovation capabilities of regional clusters in Europe provides limited understandings of these cluster-based effects through which open innovation is fostered. This study investigates the role of clusters on open innovation practices relating to exploration and exploitation of external knowledge, knowledge sharing, acquisition and sale of IP rights of Indian IT organisations. The results reveal that organisations within a close geographic proximity actively participate in inbound and outbound activities and perform better in terms of innovation performance compared to the organisations outside the cluster. The findings are relevant to both the IT clusters and the IT innovation literature as this study sheds light on the role of clusters in improving an organisation’s innovation capabilities through open innovation

Opposing Effects of Response Time in Human–Chatbot Interaction

Research has shown that employing social cues (e.g., name, human-like avatar) in chatbot design enhances users’ social presence perceptions and their chatbot usage intentions. However, the picture is less clear for the social cue of chatbot response time. While some researchers argue that instant responses make chatbots appear unhuman-like, others suggest that delayed responses are perceived less positively. Drawing on social response theory and expectancy violations theory, this study investigates whether users’ prior experience with chatbots clarifies the inconsistencies in the literature. In a lab experiment (N = 202), participants interacted with a chatbot that responded either instantly or with a delay. The results reveal that a delayed response time has opposing effects on social presence and usage intentions and shed light on the differences between novice users and experienced users – that is, those who have not interacted with a chatbot before vs. those who have. This study contributes to information systems literature by identifying prior experience as a key moderating factor that shapes users’ social responses to chatbots and by reconciling inconsistencies in the literature regarding the role of chatbot response time. For practitioners, this study points out a drawback of the widely adopted “one-design-fits-all” approach to chatbot design

Opposing Effects of Response Time in Human–Chatbot Interaction: The Moderating Role of Prior Experience

Research has shown that employing social cues (e.g., name, human-like avatar) in chatbot design enhances users’ social presence perceptions and their chatbot usage intentions. However, the picture is less clear for the social cue of chatbot response time. While some researchers argue that instant responses make chatbots appear unhuman-like, others suggest that delayed responses are perceived less positively. Drawing on social response theory and expectancy violations theory, this study investigates whether users’ prior experience with chatbots clarifies the inconsistencies in the literature. In a lab experiment (N = 202), participants interacted with a chatbot that responded either instantly or with a delay. The results reveal that a delayed response time has opposing effects on social presence and usage intentions and shed light on the differences between novice users and experienced users – that is, those who have not interacted with a chatbot before vs. those who have. This study contributes to information systems literature by identifying prior experience as a key moderating factor that shapes users’ social responses to chatbots and by reconciling inconsistencies in the literature regarding the role of chatbot response time. For practitioners, this study points out a drawback of the widely adopted “one-design-fits-all” approach to chatbot design

Opposing Effects of Response Time in Human–Chatbot Interaction: The Moderating Role of Prior Experience

Research has shown that employing social cues (e.g., name, human-like avatar) in chatbot design enhances users’ social presence perceptions and their chatbot usage intentions. However, the picture is less clear for the social cue of chatbot response time. While some researchers argue that instant responses make chatbots appear unhuman-like, others suggest that delayed responses are perceived less positively. Drawing on social response theory and expectancy violations theory, this study investigates whether users’ prior experience with chatbots clarifies the inconsistencies in the literature. In a lab experiment (N = 202), participants interacted with a chatbot that responded either instantly or with a delay. The results reveal that a delayed response time has opposing effects on social presence and usage intentions and shed light on the differences between novice users and experienced users – that is, those who have not interacted with a chatbot before vs. those who have. This study contributes to information systems literature by identifying prior experience as a key moderating factor that shapes users’ social responses to chatbots and by reconciling inconsistencies in the literature regarding the role of chatbot response time. For practitioners, this study points out a drawback of the widely adopted “one-design-fits-all” approach to chatbot design