The aim of this paper is to develop recommendations for the value-sensitive design of social virtual reality (VR) applications with respect to the interaction between customers and customer service representatives, considering the value-sensitive design approach. Based on a systematic literature search, 125 relevant hits could be found, which especially assigns the values of openness, security, and liability to problems and categorizes them into six problem areas. These values of openness, security, and liability and problem fields form the requirements for a value-sensitive design of social VR applications. Based on these requirements, preliminary design principles were derived in two evaluation cycles, each assessed using an online survey (Survey 1 with 221 participants and Survey 2 with 310 participants) and presented in the form of instantiation. One main finding of the paper can help counteract discrimination in social VR applications within the interaction between customers and customer service representatives.

Scholars are increasingly using generative artificial intelligence (AI) chatbots, like ChatGPT, in research, though concerns remain about ethics, data privacy, bias, and intellectual property. This study adopts a design science research approach to explore how generative AI chatbots can support academic teaching and research, bridging theory and practice. A literature review and expert interviews identified key requirements and design principles that support virtues such as uniqueness, generalizability, and reproducibility. We also introduce a prototype, “AcademiaBot,” to demonstrate these principles in action. Our findings suggest that AI chatbots can significantly aid scholarly work if users are informed and ethical concerns are addressed. Responsible usage can help AI augment human research efforts without compromising integrity. This study provides valuable design knowledge, ensuring AI-based chatbots remain a beneficial tool for scholars.

Abstract In homecare, networks are formed by professional, semiprofessional, and informal actors, who collaborate to care for people in need. Modern information and communication technology (ICT) might play an important role to enhance cooperation in homecare networks. Through infrastructuring work, the authors seek to build a comprehensive understanding of the types of collaboration complexity in homecare networks to determine if, when and which technologies are most suitable. This paper examines how homecare networks can be classified according to collaboration complexity. A four-stage research design was followed to develop a taxonomy for homecare collaboration. The taxonomy was applied to 21 care networks, and five types of homecare networks were identified. The taxonomy considers network, tasks, and communication particularities across 13 dimensions, each of which includes three characteristics. Three clusters were identified as more likely than the others to benefit from increased technology use. The taxonomy and archetypes highlight which homecare network types could benefit from increased technology use. Additionally, the taxonomy allows for an iterative re-evaluation of networks to initiate measures for improvement.

This paper explains how gamification influences the macro- and micro-level social structures in an industrial organization. Based on qualitative content analysis applied in an interpretative case study, we demonstrate how the implementation of a gamification application successively leads to a number of changes in the micro- and macro-level social structures of the investigated organization. The workers in the gamified work process changed their focus of attention, developed new goals and identities, and altered their social interaction; these changes in turn led to modifications in the organizational practices and identities in the sense of work routines and acceptance of the organizational structure during the sample period. With our explanations on how gamification can transform an organization at least temporarily, we contribute to the research stream that proposes a more holistic view of gamification. Our findings also advocate for a more comprehensive view of which people are part of the gamified environment.

Cloud storage has seen an increasing rise in demand and diffusion. Consequently, the cloud storage market is also becoming an increasingly commoditised market. That is, homogenous products are offered at equal prices, and this offer makes it more difficult for cloud storage providers to generate revenue and differentiate themselves from their competitors. Therefore, it is vital for providers to precisely understand customer preferences so that these can be targeted with appropriate services. To examine these preferences, we conduct a choice experiment and analyse choice decisions gathered from 340 German students by means of a conjoint analysis. We perform an individual-level analysis of preferences, which reveals significant differences and heterogeneity within the sample. By using a subsequent cluster analysis, we identify three distinct customer segments that also show significant differences in, for example, the perceptions of information privacy and risks. Our findings contribute to the literature by uncovering the preference structure and trade-offs that users make in their choice of storage services when employed for the purpose of archiving. We conclude the study with a discussion of practical implications that can aid cloud storage providers in service design decisions, and highlight the limitations associated with our research approach and drawn sample.