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Article
Author(s)
Roger Shihjung Chen
Tzung-Shiun Li
Full-Text PDF XML 683 Views
DOI:10.17265/1548-6591/2020.05.002
Affiliation(s)
Chinese Culture University, Taiwan
Central Police University, Taiwan
ABSTRACT
Actors in the real world
are affected by multiple relations, and therefore, so are actions in the web of
collaboration. As such, it is crucial to take account of these multiple,
intertwined relations when evaluating any network constituted by various types
of cooperative and collaborative activity: For example, the collaborative
decision-making carried out in municipal disaster preparedness and management.
Occupying the front line of disaster management, municipal governments rely on
multiple actors and a variety of resources in their efforts to respond swiftly
and effectively; and how well such an organization assembles these various
aspects of its collaborations will determine how robust its organizational
resilience is. However, collaborative relations are often embedded in
cross-layer interactions, which makes them hard to perceive, and may lead to
blind spots in emergency-planning education and training. By applying social network
analysis—specifically,
a multiplex network approach—this paper aims to identify and verify the
characteristics embedded in the multiplex network that delineate collaborative
decision-making in a municipal disaster-management setting. Its results show
that decision-making collaboration among New Taipei’s municipal agencies tasked
with disaster preparedness and reduction constitutes a complex multiplex network,
containing cross-layer effects derived from trust, resources, and
decision-making interactions. The study concludes that a clear understanding of
municipal decision-making in the context of disaster preparation and response
needs to take account of the multiple dimensions of agency collaboration and
the interdependencies that emerge from those dimensions.
KEYWORDS
multiplex network, collaboration, municipal disaster preparedness, exponential random graph model (ERGM), resilience
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