Start Date
16-8-2018 12:00 AM
Description
In several recent crises, digital volunteers’ organizations showed a remarkable ability to support government agencies during relief operations. Digital volunteers can collaborate and contribute remotely, supporting information collection and presentation from a variety of digital data streams sources (e.g., social media, news feeds, physical sensors). From a Representation Theory perspective, we frame their effort to help government agencies collecting actionable information as one to achieve a better (digital) representation of a crisis. However, Representation Theory (RT) has not been applied yet to a chaotic environment – such as the aftermath of a disaster – and has not been proven yet to be a valid theory of Information Systems (IS) use in that context. For RT, individuals pursue IS effective use iterating over learning and adaptation actions. Nonetheless, we posit that the time constraints of chaotic environments uniquely affect the circularity of learning-adaptation processes leading to learning driven or adaptation driven initiatives. Our paper discusses a case study of the latter type.
Recommended Citation
Bonaretti, Dario and Piccoli, Gabriele, "Digital Volunteers for Emergency Management: Lessons from the 2016 Central Italy Earthquake" (2018). AMCIS 2018 Proceedings. 6.
https://aisel.aisnet.org/amcis2018/GreenIS/Presentations/6
Digital Volunteers for Emergency Management: Lessons from the 2016 Central Italy Earthquake
In several recent crises, digital volunteers’ organizations showed a remarkable ability to support government agencies during relief operations. Digital volunteers can collaborate and contribute remotely, supporting information collection and presentation from a variety of digital data streams sources (e.g., social media, news feeds, physical sensors). From a Representation Theory perspective, we frame their effort to help government agencies collecting actionable information as one to achieve a better (digital) representation of a crisis. However, Representation Theory (RT) has not been applied yet to a chaotic environment – such as the aftermath of a disaster – and has not been proven yet to be a valid theory of Information Systems (IS) use in that context. For RT, individuals pursue IS effective use iterating over learning and adaptation actions. Nonetheless, we posit that the time constraints of chaotic environments uniquely affect the circularity of learning-adaptation processes leading to learning driven or adaptation driven initiatives. Our paper discusses a case study of the latter type.