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dc.contributor.authorWood, LC
dc.contributor.authorReiners, T
dc.contributor.authorSrivastava, HS
dc.date.accessioned2013-11-10T21:05:41Z
dc.date.accessioned2013-11-10T21:06:06Z
dc.date.accessioned2013-11-10T21:06:39Z
dc.date.accessioned2013-11-10T21:11:29Z
dc.date.accessioned2013-11-10T21:11:44Z
dc.date.available2013-11-10T21:05:41Z
dc.date.available2013-11-10T21:06:06Z
dc.date.available2013-11-10T21:06:39Z
dc.date.available2013-11-10T21:11:29Z
dc.date.available2013-11-10T21:11:44Z
dc.date.copyright2013
dc.date.issued2013-11-11
dc.identifier.citationIn: Proceedings of the 27th Australia New Zealand Academy of Management (ANZAM) Conference 2013, Hobart, Tasmania (Australia).
dc.identifier.urihttp://hdl.handle.net/10292/5840
dc.description.abstractWe outline the use of sentiment analysis as a tool for demand planning in sales and operations planning (S&OP). First, we explain how S&OP functions and the reliance on cooperation or collaboration with other firms to gain information. We introduce sentiment analysis and show its value in determining marketplace-changes which feed into supply chains. We show how sentiment analysis supports data acquisition independent of other firms in the supply chain; incorporated into S&OP, these data can support preparation for changing requirements. While demonstrated in marketing, this concept remains unproven in supply chain research. We believe this is the first assertion and examination of how sentiment analysis can support effective S&OP but further empirical research is required to validate this concept.
dc.publisherAustralia New Zealand Academy of Management (ANZAM)
dc.relation.replaceshttp://hdl.handle.net/10292/5836
dc.relation.replaces10292/5836
dc.relation.replaceshttp://hdl.handle.net/10292/5837
dc.relation.replaces10292/5837
dc.relation.replaceshttp://hdl.handle.net/10292/5838
dc.relation.replaces10292/5838
dc.relation.replaceshttp://hdl.handle.net/10292/5839
dc.relation.replaces10292/5839
dc.relation.urihttp://www.anzam.org/?attachment_id=4088
dc.rightsNOTICE: this is the author’s version of a work that was accepted for publication. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. A definitive version was subsequently published in (see Citation). The original publication is available at (see Publisher's Version).
dc.subjectSupply chain management
dc.subjectSentiment analysis
dc.subjectBusiness analytics
dc.subjectSales & operations planning
dc.titleExpanding sales and operations planning using sentiment analysis: demand and sales clarity from social media
dc.typeConference Contribution
dc.rights.accessrightsOpenAccess
pubs.elements-id157400


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