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Introduction to the Minitrack on Adaptive AI and Decision Intelligence for Sustainable Systems and Green IS
No full textEntrepreneurial Digital Resilience in War: Lessons from Ukrainian SMEs
Get PDFLimited IS research is available on how SMEs achieve digital resilience in the context of major geopolitical shocks. Other than large organizations, SMEs typically lack the resources to quickly produce capabilities to resist and recover. At the same time, entrepreneurial bricolage teaches us that such organizations are used to improvisation with resources-at-hand. We turn to a study of Ukrainian entrepreneurs during the ongoing war through the lens of bricolage for the creation of digital resilience. Our interviews with Ukrainian SME founders reveal that entrepreneurs actively repurpose and recombine existing digital tools, infrastructures, and platforms to maintain operations, ensure remote work, and reconfigure business models. Our study contributes to the digital resilience literature by highlighting how resilience emerges through cumulative learning, cognitive framing, and entrepreneurial improvisation, offering new insights into managing SMEs under extreme conditions
Introduction to the Minitrack on Design, Development, and Evaluation of Next-Generation Collaboration Technologies
No full textInspiration Contagion Effects: Elevated Thoughts and Transcendent Emotions
Get PDFThis study investigates the phenomenon of inspiration contagion on Reddit’s GetMotivated subreddit, where inspirational posts may trigger similarly inspirational responses in user comments. Extending prior work on emotional contagion, the study disentangles thought contagion (the transfer of thematic ideas) from emotional contagion (the transfer of specific feelings), with a focus on self-transcendent emotions (e.g., admiration, gratitude, optimism) and motivation-related emotions (e.g., curiosity, desire, realization). Using topic modeling and mixed-effects models, our results show strong evidence for both forms of contagion. Thought contagion was strongest when comments thematically aligned with the original post, particularly in narratives about "overcoming struggles and finding motivation''. For emotional contagion, gratitude demonstrated the most powerful same-emotion transfer effect. Motivation-related emotions did not show direct transfer, but posts expressing curiosity were found to elicit admiration in comments. These findings clarify the distinct mechanism by which inspiration spreads in online communities
Tagging Lemons: The Strategic Use of AIGC Tags in Online Artwork Marketplaces
Get PDFMany platforms now host both user-generated content (UGC) and AI-generated content (AIGC), managing them through tagging mechanisms. However, little is known about how creators use these tags and what market dynamics their use may entail. This study examines the consequences of adherence to a voluntary AIGC tagging policy implemented in the online artwork marketplace. Using image-based detection and a staggered difference-in-differences design, we identify opportunistic artists who strategically omit tags on low-quality AIGC artworks to misrepresent them as human-generated. We find that such behavior helps consumers distinguish high-quality AIGC and artists, reducing sales of opportunistic artist artworks and thus mitigating adverse selection. We attribute this effect to consumers’ ability to detect speculative behavior. This explanation is corroborated by further computational image analysis. We also find that opportunistic behavior significantly lowers artwork quality, suggesting heightened moral hazard. These findings offer important theoretical and practical implications for platforms that manage AIGC
Gown, Glove, Gadget: A Qualitative Study Exploring Surgeons’ Use of Wearable Devices in the Operating Room
Get PDFThis qualitative study explores surgeon experiences using wearable biometric devices in the operating room to support surgeon wellbeing and optimize personal performance. Through semi-structured interviews with attending surgeons and trainees across surgical subspecialties, we identified four themes: (1) increased self-awareness for behavior modification, (2) integration into surgical workflows, (3) challenges with wearable biometric device usability, and (4) future opportunities and broader implications. Participants valued devices that offered intuitive and actionable insights with minimal workflow disruption. However, data complexity and fragmented app ecosystems limited participant engagement. A Strengths, Weaknesses, Opportunities, and Threats (SWOT) framework was used to translate qualitative insights into device implementation considerations. Ethical concerns, especially regarding employee privacy and data governance, were noted as potential barriers. These findings highlight both the promise and pitfalls of integrating these devices into surgical practice and suggest the need for thoughtful design, institutional support, and ethical safeguards to maximize device utility and efficacy
Dark Personalities at Work: How Service Employees’ Dark Triad Traits Shape Acceptance of Generative AI
Get PDFAs generative AI (Gen-AI) tools are increasingly used in service settings, understanding what drives or hinders individual employees’ acceptance is essential for successful implementation. While technical readiness and ethical concerns are frequently discussed, little is known about how personality traits such as narcissism, Machiavellianism, and psychopathy shape trust and acceptance of Gen-AI at work. This study investigates the influence of Dark Triad traits on trust in Gen-AI—differentiated as human-like vs. functional trust—and their impact on acceptance in the service sector. A mixed-methods design was applied, combining a quantitative survey (N = 329, analyzed via SEM and PROCESS) with ten follow-up expert interviews, analyzed using thematic analysis. Narcissism was positively linked to both trust dimensions and Gen-AI acceptance, while Machiavellianism reduced trust and acceptance. Psychopathy showed more complex and partially contradictory effects. Expert interviews provided deeper insights, suggesting that narcissists embrace Gen-AI for self-promotion, while Machiavellians remain skeptical due to control concerns. The findings highlight the importance of personality-aware AI adoption strategies. Organizations should foster transparency and support trust-building to address different personality-driven motivations and barriers
Emergence of Decentralized Data Ecosystems as Meta-organizations
Get PDFMost research on data ecosystems focuses on proprietary models governed by a single actor, offering limited insights into how decentralized data ecosystems can be collectively organized and governed. Drawing on a case study of Gaia-X, a large-scale European initiative, this study examines how a decentralized data ecosystem can emerge as a meta-organization. We analyze three interlinked features of meta-organizations—sources of authority, drivers of engagement, and coordination and governance mechanisms—while also identifying a fourth dimension: the role of technological architecture. Our findings reveal a paradigm shift in organizational authority from control-based to legitimacy-based forms; a dual incentive system tailored to data complementors and coordinators; and a governance model that is decentralized, interdependent, and self-organizing. Furthermore, we identify a novel layered technology architecture composed of a core protocol layer and a core extension layer, both of which support generativity and collective innovation. These findings advance the understanding of how decentralized data ecosystems can be structured and governed without a dominant keystone actor, contributing to research on meta-organizations, digital infrastructures, and data governance
"Our special price is only once, and then there will be no more" The Language Magic in Live Streams: How Vocal and Semantic Features of Influencers Dynamically Trigger Purchases
Get PDFLive streaming enables real-time interactive shopping, which makes the streamer's performance crucial for sales. However, the impact of streamers' verbal interactions on consumer decisions hasn't been fully studied. Using the Elaboration Likelihood Model (ELM) and Fear of Missing Out (FOMO) integrated framework, this research explores how streamers' vocal and semantic features affect sales, and how these effects differ among streamer types. We collected data from 552 live streams by 96 popular streamers on the Douyin e-commerce platform from March to May 2025, conducting real-time analysis with multimodal minute-level data. Results show that streamers' vocal and semantic features positively impact sales. Specifically, speech rate and scarcity-creating statements from mid-sized and small streamers have a bigger sales effect, while celebrity streamers rely more on brand effects than verbal skills. This study offers an in-depth view of the differential impact of streamers' verbal features on consumer decisions in live-streaming shopping and gives strategy guidance for industry practitioners
From Detection to Discovery: A Joint Learning Framework for Medical Knowledge Discovery and Depression Detection Using User-generated Content
Get PDFResearchers have long recognized that integrating domain knowledge into machine learning can enhance the efficiency of disease detection using user-generated content. However, a critical yet often overlooked aspect of research on combining machine learning with user-generated content is knowledge discovery: extracting new knowledge directly from user-generated content using machine learning techniques, thereby contributing back to medical knowledge. In this study, we use depression as a research case and develop a joint learning and knowledge graph-based framework, namely, Joint Depression Detection and Knowledge Completion (JDeC), to facilitate the iterative loops of predicting depression and discovering new medical knowledge from user-generated content. Specifically, we create a closed-loop joint training framework that combines ontology-based knowledge graph construction and learning, knowledge learning from user generated content on social media, and knowledge completion by integrating recognized entities from user generated content into the domain ontology