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Paper Type

Complete

Description

The increasing recurrence of crises threatens the continuity of services provided by public service organizations (PSOs) to their communities, especially those in need. Beyond contingency plans, PSOs must rely on robust support information systems able to withstand transitions between day-to-day activities and crisis response with as minimal interruptions as possible. Through the analysis of experiences of use of social media analytics as a support system in PSOs, this study proposes a set of attributes that take place while transitioning between non-crisis and crisis states. The sociotechnical nature of transitions calls for a zoomed-out analysis based on shared patterns that could lead to generalization in the future. The results of our study contribute towards understanding how continuity and equilibrium are exercised in volatile and dynamic environments. In addition, our results could help organizations self-assess their social media analytics teams or other support systems within the proposed parameters.

Paper Number

1900

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SIG EGov

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Aug 10th, 12:00 AM

Attributes of Continuity in Support Information Systems: A Study of Social Media Listening Experiences

The increasing recurrence of crises threatens the continuity of services provided by public service organizations (PSOs) to their communities, especially those in need. Beyond contingency plans, PSOs must rely on robust support information systems able to withstand transitions between day-to-day activities and crisis response with as minimal interruptions as possible. Through the analysis of experiences of use of social media analytics as a support system in PSOs, this study proposes a set of attributes that take place while transitioning between non-crisis and crisis states. The sociotechnical nature of transitions calls for a zoomed-out analysis based on shared patterns that could lead to generalization in the future. The results of our study contribute towards understanding how continuity and equilibrium are exercised in volatile and dynamic environments. In addition, our results could help organizations self-assess their social media analytics teams or other support systems within the proposed parameters.

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