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Author Meshal Alharbi; Graham Coates pdf  isbn
openurl 
  Title Assessing Flood Recovery of Small Businesses using Agent-Based Modelling and Simulation Type Conference Article
  Year 2019 Publication Proceedings of the 16th International Conference on Information Systems for Crisis Response And Management Abbreviated Journal Iscram 2019  
  Volume Issue Pages  
  Keywords SMEs; agent-based modelling and simulation; flooding; short-term recovery; manufacturing and retail.  
  Abstract In developed countries, small and medium-sized enterprises (SMEs) represent the majority of all businesses, e.g. 99.9% in the UK. Given this significant proportion, any disruption to the operation of SMEs will have a negative impact on a nation?s economy. In the context of flooding, this paper reports on the use of agent-based modelling and simulation (ABMS) to assess SMEs immediate response and short-term recovery. In particular, it focuses on the interactions between manufacturing SMEs and mutual aid partners, and retail SMEs and companies specializing in refurbishing premises. Results show that a manufacturing SME with a mutual aid partner can reduce loss in production by approximately 6% over a 7 working day period. In relation to retail

SMEs, those with employees able to be allocated to refurbish its premises recovered faster than SMEs employing a refurbishment company, potentially one day earlier.
 
  Address Durham University, United Kingdom;Newcastle University, United Kingdom  
  Corporate Author Thesis  
  Publisher Iscram Place of Publication Valencia, Spain Editor Franco, Z.; González, J.J.; Canós, J.H.  
  Language English Summary Language English Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN 2411-3387 ISBN 978-84-09-10498-7 Medium  
  Track T1- Analytical Modeling and Simulation Expedition Conference 16th International Conference on Information Systems for Crisis Response and Management (ISCRAM 2019)  
  Notes Approved no  
  Call Number Serial 1920  
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