105 research outputs found
Are business users social? A design experiment exploring information sharing in enterprise social systems
A ampliação das estruturas de controle por meio das tecnologias de informação e comunicação: a onipresença do "pan-óptico eletrônico" no setor bancário
Team Boundary Spanning: Strategic Implications for the Implementation and use of Enterprise Social Media
International Collaborative Learning Experience through Global Engineering Design Projects: A Case Study
How Events Affect Trust: A Baseline Information Processing Model with Three Extensions
Part 2: Short PapersInternational audienceThis article addresses how trust changes over time. We introduce a social psychology-based Information Processing Model (IPM) that explains how trust changes over time based on three cognitive mechanisms: attention, attribution, and judgment. This model is contrasted with the traditional incremental progression model of trust change. We also explain three extensions of the model. These models are then simulated and the results suggest that incremental progression may be inconsistent with established psychological theory
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Artificial Intelligence in Information Systems: State of the Art and Research Roadmap
Many would argue that artificial intelligence (AI) is not only technology but also a paradigmatic shift in the relationship between humans and machines. Much literature assumes that AI-powered practices substantially differ from and profoundly change organizational structures, communication, affordances, and ecosystems. However, AI research remains fragmented and often lacks clarity. While the information systems (IS) discipline can play a pivotal role in AI’s emergence and use, the discipline needs a clear direction that specifies how it can contribute and its key research themes and questions. This paper draws on a professional development workshop that we organized at the 2020 International Conference on Information Systems and the discussions that followed. We summarize and synthesize how AI has impacted organizational practices over five decades and provide views from various perspectives. We identify weaknesses in the current AI literature as measured against conceptual clarity, theoretical glue, cumulative tradition, parsimony, and applicability. We also identify direct actions that the IS research community can undertake to address these issues. Finally, we propose a next-step research agenda to guide AI research in the coming years. © 2022 by the Association for Information Systems.Immediate accessThis item from the UA Faculty Publications collection is made available by the University of Arizona with support from the University of Arizona Libraries. If you have questions, please contact us at [email protected]
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