Show simple item record

dc.contributor.advisorMbhele, Thokozani Patmond.
dc.creatorNaidoo, Kashmira.
dc.date.accessioned2016-01-19T07:01:07Z
dc.date.available2016-01-19T07:01:07Z
dc.date.created2014
dc.date.issued2016-01-19
dc.identifier.urihttp://hdl.handle.net/10413/12630
dc.descriptionM. Com. University of KwaZulu-Natal, Durban 2014.en
dc.description.abstractThe promotion-driven retail chain within the Massmart group resembles variability upstream and downstream of the supply chain. This variability may be associated with mis-alignment of supply chain activities and the in-house electronic systems of communication. Despite the implementation of a logistics network and regional distribution centres, the movement of stock from manufacturers to retail stores remains a challenge in managing out-of-stock situations at various stores. The supply chain partners across extended enterprises epitomise limited demand information sharing within the retail promotion-driven model. The foundation upon which information is currently shared emanates from long, silo-oriented forecasting periods (eight weeks), oversimplified point-of-sale data and a poorly synchronised supply chain strategy. The study aims to optimise supply chain integrated information sharing through collaborative, forecast-based performance outcomes and electronically-shared information tools across extended enterprises. Research objectives in this study aim: firstly, to examine the extent to which optimised information sharing is enhanced by integrated supply chain activities across the extended enterprise; secondly, to establish the magnitude of supply chain value-added performance outcomes in the collaborative planning, forecasting and replenishment model across functions and across enterprises; and finally, to establish the role of electronically-enabled information sharing tools in an integrated and effective supply chain structure. This study uses questionnaires to collect data from the returned sample size of 143 respondents out of an initial distribution of 165 questionnaires. This quantitative approach uses descriptive statistics and frequency distributions to analyse individual variables. Pearson correlation was chosen for bivariate analysis while multiple regression analysis further considered the relationship between information sharing and the independent variables using multivariate analysis. The findings of this study suggest that optimised information sharing across the extended enterprise is dependent on the accessibility and performance of information systems and technological tools. This result indicates that the information systems adopted should facilitate the extended supply chain collaboration and mitigate supply chain network variability from the promotion-driven model. These managerial implications indicate that supply chain efficiency and integration is the responsibility of each individual supply chain partner involved in a retail supply chain network.en
dc.language.isoen_ZAen
dc.subjectMassmart.en
dc.subjectBusiness logistics--South Africa.en
dc.subjectInformation networks--South Africa.en
dc.subjectIntellectual capital--South Africa.en
dc.subjectKnowledge management--South Africa.en
dc.subjectTheses--Management studies.en
dc.subject.otherCollaboration.en
dc.subject.otherPlanning.en
dc.subject.otherForecasting and replenishment.en
dc.subject.otherInformation sharing.en
dc.subject.otherPull-push systems and category management.en
dc.titleOptimising information sharing within the Massmart supply chain network.en
dc.typeThesisen


Files in this item

Thumbnail

This item appears in the following Collection(s)

Show simple item record