Evaluating the operational resilience of small and medium-sized enterprises to flooding using a computational modelling and simulation approach: a case study of the 2007 flood in Tewkesbury
dc.contributor.author | Coates, G | |
dc.contributor.author | Alharbi, M | |
dc.contributor.author | Li, C | |
dc.contributor.author | Ahilan, S | |
dc.contributor.author | Wright, N | |
dc.date.accessioned | 2020-05-21T11:43:47Z | |
dc.date.issued | 2020-02-17 | |
dc.description.abstract | The resilience of Small and Medium-sized Enterprises (SMEs) to disruptive events is significant as this highly prevalent category of business forms the economic backbone in developed countries. This article provides an overview of the application of a computational modelling and simulation approach to evaluate SMEs’ operational resilience to flooding based on combinations of structural and procedural mitigation measures that may be implemented to improve their premises’ resistance to flooding and safeguard their business continuity. The approach integrates flood modelling and simulation with agent-based modelling and simulation (ABMS) within a modelled geographic environment. SMEs are modelled as agents based on findings of semi-structured interviews with SMEs that have experienced flooding or are at risk of flooding. In this paper, the ABMS has been applied to a new case study of the major flood event of 2007 in Tewkesbury. Further, to enable an evaluation of the operational resilience of manufacturing SMEs in terms of the relative effectiveness of flood mitigation measures, a new coefficient based on production loss is introduced. Results indicate structural mitigation measures are more effective than procedural measures. While this result is intuitive, the approach provides a means of evaluating the relative effectiveness of combinations of mitigation measures that SMEs may implement to enhance their operational resilience to flooding. | en_GB |
dc.description.sponsorship | Engineering and Physical Science Research Council (EPSRC) | en_GB |
dc.identifier.citation | Vol 378: 20190210 | en_GB |
dc.identifier.doi | 10.1098/rsta.2019.0210 | |
dc.identifier.grantnumber | EP/K012770/1 | en_GB |
dc.identifier.uri | http://hdl.handle.net/10871/121121 | |
dc.language.iso | en | en_GB |
dc.publisher | Royal Society | en_GB |
dc.rights | © 2020 The Authors. Published by the Royal Society under the terms of the Creative Commons Attribution License http://creativecommons.org/licenses/by/4.0/, which permits unrestricted use, provided the original author and source are credited. | en_GB |
dc.subject | small and medium-sized enterprises | en_GB |
dc.subject | resilience | en_GB |
dc.subject | flood modelling | en_GB |
dc.subject | agent-based modelling | en_GB |
dc.title | Evaluating the operational resilience of small and medium-sized enterprises to flooding using a computational modelling and simulation approach: a case study of the 2007 flood in Tewkesbury | en_GB |
dc.type | Article | en_GB |
dc.date.available | 2020-05-21T11:43:47Z | |
dc.identifier.issn | 1364-503X | |
dc.description | This is the final version. Available from the publisher via the DOI in this record. | en_GB |
dc.description | This article has no additional data available due to it containing confidential information related to SMEs that participated in this research. Also, in agreement with Ordnance Survey regarding MasterMap’s Address Layer, the associated data used in this research is not available. | en_GB |
dc.identifier.journal | Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences | en_GB |
dc.rights.uri | http://creativecommons.org/licenses/by/4.0/ | en_GB |
dcterms.dateAccepted | 2019-12-09 | |
rioxxterms.version | VoR | en_GB |
rioxxterms.licenseref.startdate | 2019-12-09 | |
rioxxterms.type | Journal Article/Review | en_GB |
refterms.dateFCD | 2020-01-07T15:08:45Z | |
refterms.versionFCD | AM | |
refterms.dateFOA | 2020-05-21T11:43:50Z | |
refterms.panel | B | en_GB |
refterms.depositException | publishedGoldOA | |
refterms.depositExceptionExplanation | https://doi.org/10.1098/rsta.2019.0210 |
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Published by the Royal Society under the terms of the Creative Commons Attribution License http://creativecommons.org/licenses/by/4.0/, which permits unrestricted use, provided the original author and source are credited.