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dc.contributor.advisorLackes, Richard-
dc.contributor.authorKhushnood, Muhammad-
dc.date.accessioned2014-11-17T13:32:55Z-
dc.date.available2014-11-17T13:32:55Z-
dc.date.issued2014-
dc.identifier.urihttp://hdl.handle.net/2003/33688-
dc.identifier.urihttp://dx.doi.org/10.17877/DE290R-6726-
dc.description.abstractThe purpose of the study is to enhance the fundamental understanding by studying supply chain resilience across manufacturing and transportation processes; the effect of disruption vulnerability and adaptive capability on resilience of supply chain processes; the effect of supply chain processes resilience on the overall supply chain; and in turn its effect on supply chain risk costs. In this study, the existing model of supply chain resilience has been developed into an extended model in the context of international garments supply chain. Garments manufacturing firms in Pakistan and Turkey and customers in Germany are surveyed through structured questionnaire. Partial Least Squared Structural Equation Modelling (PLS SEM) has been used for model estimation. The outer and inner models are evaluated for soundness. The direct, mediated, and moderated causal relationships among the constructs of the model have been examined. The study results in the realization of empirical study of supply chain resilience framework in the context of locations. Assumptions regarding the location of supply chain entity and resilience have been analyzed with the help of descriptive statistics. The findings are of interest for the academics, practitioners, and managers from the perspective of getting more insight and making decisions on supply chain partners, especially in the context of conditions location.en
dc.language.isoende
dc.subjectResilienceen
dc.subjectSupply Chainen
dc.subjectInternational garmentsen
dc.subject.ddc330-
dc.subject.ddc300-
dc.titleCausal model and analysis of international garments supply chain resilience with partners in Germany, Pakistan and Turkeyen
dc.typeTextde
dc.contributor.refereePishchulov, Grigory-
dc.date.accepted2014-10-29-
dc.type.publicationtypedoctoralThesisde
dc.subject.rswkSupply Chain Management / Bekleidungsindustrie / Sicherheitsplanung / Risikomanagementen
dcterms.accessRightsopen access-
Appears in Collections:Lehrstuhl Wirtschaftsinformatik

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