Electronic Patient Records in Managing Medication Information ‒ A Health Care Professional Perspective

Efficiently managed information is a key resource in clinical practice. Electronic patient records (EPRs) are in focal point in managing patient-specific medication information. In this multi-method-study, we combine qualitative and quantitative data to investigate Finnish physicians’ perceptions of EPRs. Physicians consider EPRs important in their clinical practice and use them in managing patients’ medication information while addressing a considerable dissatisfaction with quality of the current EPRs. Altogether the findings highlight the need for improving the quality of the systems and increasing the physicians’ satisfaction to materialize the benefits from the EPR

Customer Loyalty in Social Virtual Worlds

Social virtual worlds (SVWs) are an emerging phenomenon in terms of numbers of users as well as business environments. When it comes to the economic viability of SVWs, keeping existing customers active, i.e. customer loyalty, is a sine qua non. In this paper we investigate customer loyalty with two key variables: continuous use intention and purchase intention. We apply the expanded expectation-confirmation model by Thong et al. (2006) and empirically test our research model with data collected from 965 Canadian SVW users. Structural equation modelling is used to analyse the data. Perceived enjoyment was found to have the strongest impact on continuous use intentions whereas perceived critical mass was the main predictor of purchase intention. Finally, contrary to previous studies, satisfaction did not have a statistically significant impact on loyalty

THE INSTITUTIONAL LOGICS UNDERPINNING ORGANIZATIONAL AI GOVERNANCE PRACTICES

Recent developments in artificial intelligence (AI) promise significant benefits but also invoke novel risks and harms to individuals, organizations, and societies. The rising role of AI necessitates effective AI governance. However, translating AI ethics principles into governance practices remains challenging. Our paper recasts the “AI ethics translation problem” from a unidirectional translation process to a bidirectional interaction between multiple institutional logics and organizational AI governance practices. We conduct a theory adaptation study using the AI governance translation problem as a domain theory and institutional logics and institutional pluralism as method theories. Using this framework, we synthesize key AI governance practices from the literature and outline four central institutional logics: AI ethics principlism, managerial rationalism, IT professionalism, and regulatory oversight. The institutional logics and AI governance practices reciprocally influence one another: logics justify practices, and practices enact logics. We provide an illustrative analysis of the ChatGPT chatbot to demonstrate the framework. For future research, our conceptual study lays a framework for studying how plural institutional logics drive AI governance practices and how practices can be used to negotiate conflicting and complementary institutional logics

EXPLORING CUSTOMERS\u27 POST-ADOPTION PERCEPTIONS: A STUDY ON TRUST, COMMITMENT AND RELATED CONSTRUCTS IN B2C ONLINE SERVICE CONTEXT

Trust has shown to be an important factor both in the adoption of e-commerce but also in ongoing relationships between buyers and sellers. Information systems literature has discussed trust extensively, yet traditionally mostly focusing on the adoption phase. However, signs of increasing interest to post-adoptive phenomena, such as customer loyalty, can be seen in the recent IS and e-commerce literature. Encouraging customers to continue the relationship after the adoption has been widely seen vital for e-businesses. This holds especially true with B2C online services where the relationships are largely based on series of transactions and interactions. The paper presents a research model in which structural assurance and online self-efficacy are viewed as the antecedents of trust, whereas trust and switching costs are investigated as the determinants of commitment. We empirically investigate a sample of active users of online services and use structural equation modeling to analyze the data. The key findings are: 1. perceived structural assurance plays an important role also after the adoption, 2. online self-efficacy was notified to be a determinant of trust, and 3. switching costs are a determinant of commitment

Digital Natives’ Purchasing Behavior in Habbo Hotel

Purchasing virtual products and services in virtual worlds is a rapidly growing form of online consumer behavior, especially among the digital natives. The paper examines why teens spend real money in virtual goods and services. We empirically investigate the reasons for virtual purchasing behavior in world‟s most popular social virtual world, Habbo Hotel. Using content analysis, we classify the reasons for purchasing into four higher order gratifications, namely elevated experience, hedonic and social factors as well as functional activities. The results demonstrate that virtual purchasing is a vehicle for enhancing and customizing the valued aspects in the user experience

Trust, Social Presence and Customer Loyalty in Social Virtual Worlds

Social virtual worlds (SVWs) have drawn substantial attention in business and academia. This research focuses on how trust affects customer loyalty in the SVW setting. Specifically, this study pinpoints how trust in SVW staff and other users influences the continuous use and purchase behaviour in SVWs. Additionally, we examine the influence of social presence on the two aspects trust and customer loyalty. The research model is tested with PLS using a sample of 2111 Finnish Habbo users. The two facets of trust are important antecedents on customer loyalty, yet differing in their effect. Social presence is a strong determinant of trust but also a direct antecedent of customer loyalty. Together, trust and social presence account for a considerable amount of variance in continuous use and purchase intention

Responsible Artificial Intelligence Systems Critical considerations for business model design

Commercializing responsible artificial intelligence (RAI) involves translating ethical principles for developing, deploying, and using AI into business models. However, prior studies have reported tensions between commercial interests (e.g., development speed or accuracy) and societal interests (e.g., privacy or human rights) that can undermine RAI’s value proposition. Conceptually, we distinguish two business model development perspectives on AI and responsibility: innovating responsible business models leveraging AI and designing RAI business models. Taking the second perspective, we investigate the value proposition of RAI through business model design by employing a two-stage research approach consisting of focus groups and member checking. Empirically, we present the learnings from identifying the design elements for RAI business models. These include two themes that can underlie such business models: providing vs. enabling RAI systems and the observation that the tensions in RAI’s value proposition are paradoxical, not dilemmas. With our conceptual groundwork and empirical insights, we make three contributions that offer critical considerations for RAI business model design. First, we conceptualize two pathways for designing RAI business models: a corner path to commercialized RAI systems vs. direct path to commercialized RAI systems. We argue that these paths have distinct implications for the responsible in RAI. Second, we reflect the sociotechnical nature of RAI systems by emphasizing the criticality of the social for responsibility. Third, we outline a research agenda for developing RAI business models

Verkkopankin käyttö ja asiakasuskollisuus asiakkuudenhallinnan näkökulmasta : case:Nordea Pankki Suomi Oyj

Siirretty Doriast

Machine Learning System Development in Information Systems Development Praxis

Advancements in hardware and software have propelled machine learning (ML) solutions to become vital components of numerous information systems. This calls for research on the integration and evaluation of ML development practices within software companies. To investigate these issues, we conducted expert interviews with software and ML professionals. We structured the interviews around information systems development (ISD) models, which serve as conceptual frameworks that guide stakeholders throughout software projects. Using practice theory, we analyzed how software professionals perceive ML development within the context of ISD models and identified themes that characterize the transformative impact of ML development on these conceptual models. Our findings show that developer-driven conceptual models, such as DevOps and MLOps, have been embraced as common frameworks for developers and management to understand and guide the ML development processes. We observed ongoing shifts in predefined developer roles, wherein developers are increasingly adopting ML techniques and tools in their professional work. Overall, our findings underscore that ML technologies are becoming increasingly prominent in software projects across industries, and that the incorporation of ML development in ISD models is an ongoing, largely practice-driven, process

SLEEP TRACKING AS A STRESSOR: EXPERIENCES FROM SMART RING USERS

Lack of sleep hygiene is a widespread problem that drives the demand for sleep-tracking technologies. Prior research discussed the dark side of self-tracking technologies, but research specifically on sleep-tracking technologies is scarce. This study explores what potential stressors users attribute to sleep tracking executed through a smart ring. We conducted 38 semi-structured interviews and used thematic analysis to identify eight potential stressors in the context of sleep tracking. These stressors include complexity, invasion, inaccuracy, unreliability, data-feelings discrepancy, the pursuit of perfect data, vague guidance and interpretations, and overload with multiple self-tracking technologies. We further theorize these potential stressors using the person-technology fit model. The paper contributes to the nascent IS research on technostress in the context of sleep tracking