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Improving decisions support for operational disruption management in freight transport
Chalmers University of Technology, Sweden.ORCID iD: 0009-0008-2210-4368
2020 (English)In: Research in Transportation Business and Management (RTBM), ISSN 2210-5395, E-ISSN 2210-5409, Vol. 37Article in journal (Refereed) Published
Abstract [en]

In this study, the operational management of disruptions is investigated in transport chains with a focus on phases after disruptions have occurred. Instead of focusing on strategies mitigating risk before disruption occurs this paper considers the recovery phase of a disruption at operational level. The purpose of this paper is to provide insights for operational disruption management to achieve improved decision support for the recovery phase. A qualitative method of a case study is used in this paper for the transport around a distribution centre at a FMCG company in Sweden with data collected from semi-structured interviews and observations. The analysis of the findings proposes different types of detection in the recovery phase, which give insights for how to perform early recovery actions. The study contributes to disruption management in transport chains through insights on how to achieve early recovery actions by combining the different detection types with the phases of prediction and action. Instead of focusing on strategies mitigating risk before disruption occurs this paper considers the recovery phase of a disruption at operational level. This is shown to be important to understand reactive or proactive actions in the recovery phase. Transport managers can use the proposed detection types in this paper to detect disruptions in order to respond to disruptions earlier instead of developing competences of fire-fighting for occurred impacts

Place, publisher, year, edition, pages
Elsevier Ltd , 2020. Vol. 37
National Category
Mechanical Engineering
Identifiers
URN: urn:nbn:se:ri:diva-71727DOI: 10.1016/j.rtbm.2020.100540Scopus ID: 2-s2.0-85089140605OAI: oai:DiVA.org:ri-71727DiVA, id: diva2:1837340
Available from: 2024-02-13 Created: 2024-02-13 Last updated: 2024-02-13Bibliographically approved

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