AI-based assistants, such as conversational agents (CAs) and social robots, are becoming increasingly important in healthcare organizations. CAs provide a scalable and cost-effective platform for organizations supporting their employees by retrieving, structuring, and analyzing information to assist work processes. This study targets how knowledge graphs as ontological models manage CA that help improve the patient flow processes and reduce patients’ waiting time in the emergency departments (EDs). We tailored the design thinking (DT) method with modelling workshops employing conceptual modelling (CM) techniques to address these issues. We incorporated a hybrid formal approach of Methontology and Tove methodologies to build design artifacts, develop a goal-oriented interactive conversational system between humans and machines, and support information systems (IS). As a result, this ontology-driven approach contribution helps developers build value-added CAs to facilitate healthcare practitioners and patients. It is helpful for quality care delivery experience and improves bottlenecks in information flow within Eds.

The study presents an innovative approach to incorporating AI-driven conversational agents (CAs) or social robots technologies into healthcare information systems (HISs) and revolutionizing healthcare delivery systems. The study aims to improve accessibility and personalization, and minimize adverse risks, especially in the emergency departments (EDs). The study investigates patient-related experiences, long waiting times, and overcrowding issues during peak hours in EDs. Design science research methodology (DSRM) principles were tailored with modelling workshop method to capture domain contextual knowledge and include practitioners' cognitive-tacit knowledge-ability into HIS to address the above-mentioned issues. The developed social robot artifact incorporates an artificial intelligence markup language (AIML) technique as a model to restore domain knowledge of EDs, which serves as a foundation for developing goal-oriented interactive conversational system artifact between humans and machines. As a result, the study contributes that CAs, considered value-added AI-driven applications such as CAs or social robots, serve as a coworker to facilitate healthcare practitioners and patients, catering to patients' needs and communication to enhance care delivery experience and improve information flow processes using interactive services within EDs. The research presents a promising solution to improve patient outcomes, reduce waiting times, and enhance communication between patients and practitioners in EDs.

The enactment of the revised Payment Services Directive (PSD2) by the European Union, has pushed banks to develop digital open banking platforms to enhance market competition and promote innovation in the banking industry. PSD2 mandates banks to offer APIs to provide access to banking data to external third-party providers (TPPs). This mandate might disrupt the role of banks since external complementors such as fintechs have the legal right to access and leverage banking data to offer innovative banking services. As such, the emergence of regulated open banking platforms engenders complex interdependent relationships between banks and fintechs. Drawing on a case of an open banking platform by Nordea Bank, we aim to examine these interdependencies with emphasis on the engagement between banks and external complementors in a regulated platform context. We conclude with insights into the lack of access control by platform owners and new conditions of platform openness. © 2023 International Conference on Information Systems, ICIS 2023: "Rising like a Phoenix: Emerging from the Pandemic and Reshaping Hu. All Rights Reserved.

This study focuses on using AI systems, specifically conversational agents (CAs), to improve information flow during peak hours in healthcare emergency departments (EDs). We customized a Cross Industry Standard Process for Data Mining CRISP-DM approach to a CRISP-Knowledge graph (CRISP-KG) for overall design research. We use a knowledge graph approach to create an intelligent knowledge base (KBs) for CAs, which can enhance their reasoning, knowledge management, and context awareness abilities. We employ a collaborative methodology and ontology design patterns to develop a formal ontological model. Our goal is to build intelligent KBs for CAs that can interact with end-users and improve care quality in EDs, using Semantic Web Rule Language (SWRL) for inference. The KG approach can assist healthcare practitioners and patients in managing information flow more efficiently in EDs, ultimately improving care outcomes. © 2023 CEUR-WS. All rights reserved.

This research work highlights the need for AI-powered applications and their usages for the optimization of information flow processes in the medical sector, from the perspective of how AI-agents can impact human-machine interaction (HCI) for acquiring relevant and necessary information in emergency department (ED). This study investigates how AI-agents can be applied to manage situations of patient related unexpected experiences, such as long waiting times, overcrowding issues, and high number of patients leaving without being diagnosed. For knowledge acquisition, we incorporated modelling workshop techniques for gathering domain information from the domain experts in the context of emergency department in Karolinska Hospital, Solna, Stockholm, Sweden, and for designing the AI-agent utilizing NLP techniques. We discuss how the proposed solution can be used as an assistant to healthcare practitioners and workers to improve medical assistance in various medical procedures to increase flow and to reduce workloads and anxiety levels. The implementation part of this work is based on the natural language processing (NLP) techniques that help to develop the intelligent behavior for information acquisition and its retrieval in a natural way to support patients/relatives’ communication with the healthcare organization efficiently and in a natural way.

This study investigates the use of mobile data to understand patterns of population movements and disease transmission during the Covid-19 outbreak. It also focuses on understanding the implications of using this data for individual privacy. Using a mixed-methods approach, we present 10 rich qualitative interviews and 412 surevey responses from participants across the Nordics. Our novel results show that the use of mobile data can be characterized by two main categories: validation data and complementary data. We also identify five implications for practice: sharing resources and expertise between health agencies and telecom companies; extended collaboration with multiple network operators;cross-disciplinary collaboration among multiple parties; developing data and privacy guidelines; and developing novel methods and tools to address the trade-off between maintaining individual privacy and obtaining detailed information from mobile data. These implications may inform immediate and future actions to prepare for, mitigate, and control the spread of infectious diseases using mobile data. They also show privacy-driven limitations of mobile data in terms of data accuracy, richness, and scope.

The current paper addresses one of the core yet complex issues in the study of technology in organizations: the relationship between the social and the material. Many scholars in the field of Information Systems have used the notion of affordance as a lens to investigate and theorize this relationship. However, knowledge contributions in this area are often abstract and impractical, or at least compel further conceptual development. This paper uses a relational view of affordances to study organizational social media affordances based on empirical data collected about the use of the Wiki technology at two large multinational organizations—CCC and IBM. It theorizes four key mechanisms—referring to other affordances (referential), collectively enacting significant affordances (communal), situation-dependent exploitation of affordances (situatedness), and exploiting other opportunities for action (multiplicity), that embody the interaction between the social and the material. These mechanisms make up what is labelled in this paper as ‘the affordances apparatus’. The apparatus provides a conceptual structure for the interaction between social and material features that shows operational dynamics and processes underpinning the perception, enactment and exploitation of affordances. This apparatus is the main contribution of the paper in that it gives researchers a conceptual tool for investigating affordances as relational constructs between the social and the material. It also helps in understanding how people navigate the use of technology features relative to their intentions and goals.

The Blockchain technology has attracted a huge attention from both industry and academia. Despite the fact that there are great potentials of the blockchain, it is facing a number of technical challenges and social challenges. There is a substantial body of literature on the technical challenges and a limited number of researches that addressed the social challenges and opportunities of blockchain. Drawing on a multiple case study of twenty-one firms from six different Middle Eastern countries we synthesize the blockchain technology and IT in the Middle East literature to understand the challenges and opportunities of that technology in the Middle East. Our study identifies a classification of challenges and opportunities: Fine-tune challenges, estrangement challenges, sprint opportunities and act on opportunities and four associated factors: regulation, education, collaboration and culture. In doing this, our research extends and complements existing blockchain research and contributes to the IT literature in the Middle East.

Service providers are increasingly depending and using digital infrastructure and tools provided by digital platforms to transform their services and develop digital ones that meet the needs of heterogeneous end users. However, while there is an emerging literature of developing digital services, little is known about the dynamics of transformation. Using multiple cases of firms that develop digital services, the digital service taxonomy was synthesized to understand the dynamics of transformation in developing digital services. This study identifies five main dynamics: the services experience, the service process, the service capabilities, the service environment and the service delivery.  Each of those dynamics and their associated factors are explored under the objectives of business, interaction and technology. This enables us to extend the existing literature on digital service development in particular and contributes to the research of digital innovation in general. © 2019, Springer Nature Switzerland AG.

This paper emphasizes various knowledge acquisition approaches in terms of tacit and explicit knowledge management that can be helpful to capture, codify and communicate within medical unit. The semantic-based knowledge management system (SKMS) supports knowledge acquisition and incorporates various approaches to provide systematic practical platform to knowledge practitioners and to identify various roles of healthcare professionals, tasks that can be performed according to personnel’s competencies, and activities that are carried out as a part of tasks to achieve defined goals of clinical process. This research outcome gives new vision to IT practitioners to manage the tacit and implicit knowledge in XML format which can be taken as foundation for the development of information systems (IS) so that domain end-users can receive timely healthcare related services according to their demands and needs.