Expanding sales and operations planning using sentiment analysis: demand and sales clarity from social media
aut.researcher | Wood, Lincoln | |
dc.contributor.author | Wood, LC | |
dc.contributor.author | Reiners, T | |
dc.contributor.author | Srivastava, HS | |
dc.date.accessioned | 2013-11-10T21:05:41Z | |
dc.date.accessioned | 2013-11-10T21:06:06Z | |
dc.date.accessioned | 2013-11-10T21:06:39Z | |
dc.date.accessioned | 2013-11-10T21:11:29Z | |
dc.date.accessioned | 2013-11-10T21:11:44Z | |
dc.date.available | 2013-11-10T21:05:41Z | |
dc.date.available | 2013-11-10T21:06:06Z | |
dc.date.available | 2013-11-10T21:06:39Z | |
dc.date.available | 2013-11-10T21:11:29Z | |
dc.date.available | 2013-11-10T21:11:44Z | |
dc.date.copyright | 2013 | |
dc.date.issued | 2013 | |
dc.description.abstract | We 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.identifier.citation | In: Proceedings of the 27th Australia New Zealand Academy of Management (ANZAM) Conference 2013, Hobart, Tasmania (Australia). | |
dc.identifier.uri | https://hdl.handle.net/10292/5840 | |
dc.publisher | Australia New Zealand Academy of Management (ANZAM) | |
dc.relation.replaces | http://hdl.handle.net/10292/5836 | |
dc.relation.replaces | 10292/5836 | |
dc.relation.replaces | http://hdl.handle.net/10292/5837 | |
dc.relation.replaces | 10292/5837 | |
dc.relation.replaces | http://hdl.handle.net/10292/5838 | |
dc.relation.replaces | 10292/5838 | |
dc.relation.replaces | http://hdl.handle.net/10292/5839 | |
dc.relation.replaces | 10292/5839 | |
dc.relation.uri | http://www.anzam.org/?attachment_id=4088 | |
dc.rights | NOTICE: 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.rights.accessrights | OpenAccess | |
dc.subject | Supply chain management | |
dc.subject | Sentiment analysis | |
dc.subject | Business analytics | |
dc.subject | Sales & operations planning | |
dc.title | Expanding sales and operations planning using sentiment analysis: demand and sales clarity from social media | |
dc.type | Conference Contribution | |
pubs.elements-id | 157400 | |
pubs.organisational-data | /AUT | |
pubs.organisational-data | /AUT/Business & Law |