Exploring Big Data Analytics for Supply Chain Management

Research output: Chapters, Conference Papers, Creative and Literary WorksRGC 32 - Refereed conference paper (with host publication)peer-review

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Author(s)

Related Research Unit(s)

Detail(s)

Original languageEnglish
Title of host publicationInternational Conference on Management, Economics and Social Development (ICMESD 2016)
PublisherDEStech Publications, Inc.
Pages1111-1117
ISBN (Electronic)9781605953496, 978-1-60595-349-6
Publication statusPublished - May 2016

Conference

Title2nd Annual International Conference on Management, Economics and Social Development (ICMESD 2016)
LocationJUNYI Dynasty Hotel
PlaceChina
CityWuhan
Period13 - 15 May 2016

Abstract

Despite a lot of research has been conducted for supply chain management, very few studies are performed on applying big data analytics to enhance supply chain management and the logistics of product delivery. The main research contribution of our work presented in this paper is the design of a novel big data analytics framework which exploits parallel aspect-oriented sentiment analysis method for supporting the physical logistics of products. The managerial implication of our research work is that logistics firms can apply the proposed big data analytics methodology to better forecast product demands, and hence facilitates supply chain management.

Research Area(s)

  • Big data analytics, Sentiment analysis, Supply chain management

Bibliographic Note

Research Unit(s) information for this publication is provided by the author(s) concerned.

Citation Format(s)

Exploring Big Data Analytics for Supply Chain Management. / CHENG, Otto K.M.; LAU, Raymond Y.K.
International Conference on Management, Economics and Social Development (ICMESD 2016). DEStech Publications, Inc., 2016. p. 1111-1117.

Research output: Chapters, Conference Papers, Creative and Literary WorksRGC 32 - Refereed conference paper (with host publication)peer-review