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Recovering from Digital Addiction with the Support of a Persuasive Mobile Application: A Design Science Research Study
Get PDFDigital addiction has emerged as a global concern, encompassing unhealthy patterns of technology use that disrupt daily functioning and well-being. We present a Design Science Research study to understand the requirements of the digital addiction domain. We use the Persuasive Systems Design as a design framework, examining features like self-monitoring, simulation, rehearsal, and social learning. The study explores persuasive design in the development of applications for learning healthier digital habits and addresses the gaps in the current solutions
Enterprise Software Integration Through Boundary Resources – A Case Study in the SAP Ecosystem
Get PDFLeading enterprise software providers use a platform-based approach to realize the adaptability of their software solutions with extensions. In a platform-based approach, boundary resources enable the integration of extensions with the platform core. However, it is unclear how developers select appropriate boundary resources and their integrative capabilities. This paper investigates the decision process for developing boundary resources in the SAP ecosystem, presents a decision model for selecting appropriate platform boundary resources, and analyzes integration use cases. Our findings show that boundary resources differ greatly in their potential to integrate extensions with data and processes in the enterprise software and whether they can integrate across organizational borders
Introduction to the Minitrack on Cybersecurity in the Age of Artificial Intelligence, AI for Cybersecurity, and Cybersecurity for AI
Get PDFRethinking Youth Inclusion and Participation: Toward Civic Empowerment through Digital Tools
Get PDFYoung people under 18 make up nearly 7 million individuals in Poland, yet they remain largely excluded from political decision-making despite being heavily affected by these decisions. This paper explores the structural, educational, and technological barriers that limit youth civic participation and proposes digital pathways to enhance youth agency in local governance. Drawing on policy analysis and existing literature, the paper critically examines how civic education, institutional culture, and societal attitudes restrict young people’s influence. It argues that digital government tools, if inclusively designed, offer a vital opportunity to narrow the democratic divide for minors and foster long-term civic engagement. Framed within theories of cognitive justice and social capital formation, the article proposes a model of youth civic inclusion that goes beyond traditional political structures and integrates digital platforms, informal education, and ethical research design
Regulatory Intermediaries and Chains – the Complex Process of Sensemaking for AI Act Implementation in Finland
Get PDFThe European Union (EU) Artificial Intelligence (AI) Act entered into force in August 2024. It aims to address different risks involved with AI systems. The regulation not only concerns organizations providing or deploying AI systems, but it mandates EU Member States to comply with the AI Act and change national law, if necessary. Member States act in the role of a regulatory intermediary (RI) for the AI Act. We conducted an interpretive case study to understand how a working group tasked with Finland’s national-level AI Act implementation made sense of changes the AI Act required to the national law for designation of National Competent Authorities. We contribute to Information Systems research by shedding light on the institutional process leading to new national law, highlighting Member States' role as an RI in implementing the AI Act on a national-level and introducing the concept of a regulatory chain involving multiple RIs
Task-Technology Fit in Virtual Reality: Explaining Behavioral Intention to Use and Perceived Performance
No full textWhile Virtual Reality (VR) is becoming more popular for professional applications, empirical evidence on its task-specific suitability remains scarce. This study employs the Task-Technology Fit (TTF) model to evaluate the perceived fit of VR for workplace tasks using McGrath’s Group Task Circumplex. Results from an online survey were analyzed with Partial Least Squares Structural Equation Modeling (PLS-SEM). They indicate that TTF relates to performance perceptions and behavioral intention to use, explaining a substantial share of variance in both outcomes. The study links task taxonomies to TTF in immersive settings and shows that task and technology characteristics both contribute to perceived fit, with social presence the most salient technology factor. Practically, the findings support task-aware selection and design of VR solutions that align with task profiles. Limitations include simulated (non-headset) stimuli and a personalization-comparability trade-off introduced by task filtering
VisPile: A Visual Analytics System for Analyzing Multiple Text Documents With Large Language Models and Knowledge Graphs
Get PDFIntelligence analysts perform sensemaking over collections of documents using various visual and analytic techniques to gain insights from large amounts of text. As data scales grow, our work explores how to leverage two AI technologies, large language models (LLMs) and knowledge graphs (KGs), in a visual text analysis tool, enhancing sensemaking and helping analysts keep pace. Collaborating with intelligence community experts, we developed a visual analytics system called VisPile. VisPile integrates an LLM and a KG into various UI functions that assist analysts in grouping documents into piles, performing sensemaking tasks like summarization and relationship mapping on piles, and validating LLM- and KG-generated evidence. Our paper describes the tool, as well as feedback received from six professional intelligence analysts that used VisPile to analyze a text document corpus
Social Skills Scenarios and Emotional Affect Training Via Chatbot for Secondary Students with Autism Spectrum Disorder
Get PDFChatbots show promise in making conversational support therapy more accessible while providing a safe environment for developing social skills without judgment. This research aims to create a chatbot that generates social scenarios, ranked by difficulty customized for each user. Unlike previous approaches that relied solely on rules-based decision trees, this system incorporates natural language processing (NLP) techniques, including a two-layer neural network for word vector space creation. This advanced NLP approach enables more sophisticated feedback and unprecedented customization in social skills training. The system continuously adapts to challenge users appropriately, addressing a common limitation of existing platforms that often provide overly simplistic training scenarios. In future work, the social scenarios and trainings would be adapted to more successfully address end user accessibilit
Integrating Generative AI into Business Operations: A Comprehensive Analysis of Use Cases as Lighthouse Projects
Get PDFAs Generative AI (GenAI) applications evolve, organizations face the challenge to decide which applications to adopt. This study supports organizations by mapping 63 GenAI use cases across a company's value chain. Through a systematic literature review complemented by a multiple case study with 33 semi-structured interviews with industry experts, it seeks to provide companies with actionable insights for integrating GenAI technologies, thereby enhancing efficiency and productivity. To provide a starting point for GenAI adoption, five applications were identified as particularly high-potential lighthouse projects: Enterprise GPT/Copilot Systems, which serve as company-internal assistants for knowledge management and content generation; Customer Service Chatbots utilizing uncritical, openly accessible data to enhance customer satisfaction; Coding Assistance Tools that automate routine coding tasks, increasing developer productivity; Input Management Systems for processing and classifying incoming information like customer complaints and emails; and Marketing Copy Generators for creating personalized marketing materials efficiently
Patient Impressions of Opioid-Related Printouts, Discussions and Care in a Primary Care Clinical Decision Support System Implementation Trial
Get PDFPrimary care is a critical setting to provide care for the 75-79% of patients who have opioid use disorder (OUD) but do not receive medications for OUD. However, patient perceptions of primary care of OUD are not well understood. Patients completed surveys about their experience with opioid-related clinical decision support system (CDSS) printouts and OUD treatment in the first 7-9 months of implementation of an OUD-CDSS. Survey responses were presented overall and by reason for study eligibility. Of 277 patients completing surveys, 22% recalled seeing the printouts; of these, 85% said the printouts made them more comfortable discussing opioid risk. Of all respondents, half discussed opioids during their visit; of these, 84% felt conversations were conducted sensitively. Overall, 88% felt primary care was the right setting to discuss opioid risks. The opioid-related printouts and discussions were generally well-received, and patients felt primary care was a suitable setting for opioid-related care