1,689 research outputs found

    A New Way to Reflect the IS Identity? Uncovering the Intellectual Core of Podcasts

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    The information systems (IS) discipline has long been critically questioning its identity to determine its central research avenues, its distinction from other disciplines, and the future directions for the field. Although this question is central to all stakeholders of the IS field, so far the debates have been conducted primarily in research papers, editorial commentaries, and opinion pieces published by influential IS scholars. Our study explores how the broader IS community engages in the discourse about IS identity by examining podcasts as an increasingly popular means of communicating IS viewpoints. We apply a podcast ethnography to study the IS podcast universe, consisting of 51 shows with 660 episodes. Our preliminary findings offer insights about the stakeholders, podcast topics, and intellectual core of the audio tracks that shed light on the role of podcasts in constructing and reflecting on IS identity

    Trust Recipes for Enhancing the Intention to Adopt Conversational Agents for Disease Diagnosis: An fsQCA Approach

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    In this study, we examine the configurations of trust-enhancing factors that determine the intention to adopt conversational agents (CAs) for disease diagnosis. After identifying trust factors influencing the behavioral intent to adopt CAs based on the information systems acceptance research field, we assigned 201 participants to use the mobile Ada application and surveyed them about their experience. Ada is a medical diagnostic CA that combines patients’ symptoms with their medical history and provides diagnostic suggestions. The collected data was analyzed using a fuzzy set qualitative comparative analysis to capture the causal complexity of trust. We identified several configurations of trust-enhancing factors affecting the intention to adopt the CA. In particular, our results show that the adoption intentions are strongly determined by trust factors associated with the performance dimension. Furthermore, we derived two propositions for the development of CAs for healthcare purposes and elaborated implications for research and practice

    Painting A Holistic Picture of Trust in and Adoption of Conversational Agents: A Meta-Analytic Structural Equation Modeling Approach

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    With their human-like nature, conversational agents (CAs) introduce a social component to human-computer interaction. Numerous studies have previously attempted to integrate this social component by incorporating trust into models such as the technology acceptance model (TAM) to decipher the adoption mechanisms related to CAs. Given the heterogeneity of these previous works, the aim of this paper is to integrate empirical evidence on the role and influence of trust within the nomological network of the TAM. For this purpose, we conduct a meta-analytic structural equation modeling approach based on 45 studies comprising k = 155 correlations, and N = 13,786 observations. Our findings highlight the multifaceted role of trust as a mediator transmitting the effects of the technology-related perceptions that drive the intention to use CAs. Our results present a comprehensive overview in a thriving research field that can guide both future theory building and the designs of more trustworthy CAs

    Beyond Digital Data and Information Technology: Conceptualizing Data-Driven Culture

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    Background: The role of a data-driven culture in improving organizational performance is widely recognized, but its conceptual definition lacks uniformity, leading to the existence of various constructs. This paper proposes a guiding framework for a data-driven culture, aiming to foster a unified understanding that aids both researchers and practitioners in the information systems (IS) field. Method: Adopting a qualitative research approach, this study conducts a systematic literature review to discern the breadth and depth of data-driven culture as portrayed in previous works. Alongside this, ten interviews were carried out with professionals well-versed in the application of data-driven strategies. Results: The study uncovers the multifaceted nature of a data-driven culture, highlighting its influence on decision-making practices within organizations. It identifies a range of characteristics relevant to the construct and consolidates these into an integrative framework, thereby developing a conceptual definition for data-driven culture. Conclusion: The paper contributes to the IS field by providing a framework that illuminates the concept of data-driven culture. This new understanding aids researchers in consistently theorizing the same phenomenon, supports the development of refined metrics for assessing data-driven culture, and paves the way for future research in this area. For practitioners, this framework delineates the characteristics of a data-driven culture and their interplay, enabling a more informed approach to cultural change efforts. Moreover, it highlights the importance of acknowledging the wider cultural context, and provides mechanisms to balance the emphasis on tools and values
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