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dc.contributor.authorMarin-Garcia, Juan A.
dc.contributor.authorAlfalla Luque, Rafaela
dc.contributor.authorMedina-López, Carmen
dc.date.accessioned2013-10-10T10:56:32Z
dc.date.available2013-10-10T10:56:32Z
dc.date.issued2013-07
dc.identifier.citationMarin-Garcia, Juan A.; Alfalla Luque, Rafaela; Medina-López, Carmen. Supply chain integration scales validation and benchmark values. "Journal of Industrial Engineering and Management", Juliol 2013, vol. 6, núm. 2, p. 423-440.
dc.identifier.issn2013-0953
dc.identifier.urihttp://hdl.handle.net/2099/13880
dc.description.abstractPurpose: The clarification of the constructs of the supply chain integration (clients, suppliers, external and internal), the creation of a measurement instrument based on a list of items taken from earlier papers, the validation of these scales and a preliminary benchmark to interpret the scales by percentiles based on a set of control variables (size of the plant, country, sector and degree of vertical integration). Design/methodology/approach: Our empirical analysis is based on the HPM project database (2005-2007 timeframe). The international sample is made up of 266 plants across ten countries: Austria, Canada, Finland, Germany, Italy, Japan, Korea, Spain, Sweden and the USA. In each country. We analized the descriptive statistics, internal consistency testing to purify the items (inter-item correlations, Cronbach’s alpha, squared multiple correlation, corrected item-total correlation), exploratory factor analysis, and finally, a confirmatory factor analysis to check the convergent and discriminant validity of the scales. The analyses will be done with the SPSS and EQS programme using the maximum likelihood parameter estimation method. Findings: The four proposed scales show excellent psychometric properties. Research limitations/implications: with a clearer and more concise designation of the supply chain integration measurement scales more reliable and accurate data could be taken to analyse the relations between these constructs with other variables of interest to the academic l fields. Practical implications: providing scales that are valid as a diagnostic tool for best practices, as well as providing a benchmark with which to compare the score for each individual plant against a collection of industrial companies from the machinery, electronics and transportation sectors. Originality/value: supply chain integration may be a major factor in explaining the performance of companies. The results are nevertheless inconclusive, the vast range of results obtained are due, amongst other things, to the fact that there is no exactness to the group of scales used, no-one has yet published an analysis of the measurement models nor clear benchmarks as to the variety of the scales used.
dc.format.extent18 p.
dc.language.isoeng
dc.publisherSchool of Industrial and Aeronautic Engineering of Terrassa (ETSEIAT). Universitat Politècnica de Catalunya (UPC)
dc.rightsAttribution-NonCommercial 3.0 Spain
dc.rights.urihttp://creativecommons.org/licenses/by-nc/3.0/es/
dc.subjectÀrees temàtiques de la UPC::Economia i organització d'empreses::Direcció d'operacions::Modelització de transports i logística
dc.subject.lcshBusiness logistics
dc.subject.lcshPhysical distribution of goods -- Management
dc.subject.otherscale validation
dc.subject.otherquestionnaire
dc.subject.otherreliability
dc.subject.othervalidity
dc.subject.otherpsichometric properties
dc.subject.othersupply chain integration
dc.titleSupply chain integration scales validation and benchmark values
dc.typeArticle
dc.subject.lemacLogística (Indústria)
dc.subject.lemacDistribució de mercaderies -- Direcció i administració
dc.identifier.dlB-28744-2008
dc.description.peerreviewedPeer Reviewed
dc.rights.accessOpen Access
local.citation.authorMarin-Garcia, Juan A.; Alfalla-Luque, Rafaela; Medina-López, Carmen
local.citation.publicationNameJournal of Industrial Engineering and Management
local.citation.volume6
local.citation.number2
local.citation.startingPage423
local.citation.endingPage440


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