EconPapers    
Economics at your fingertips  
 

Use of twitter data for waste minimisation in beef supply chain

Nishikant Mishra () and Akshit Singh ()
Additional contact information
Nishikant Mishra: University of East Anglia
Akshit Singh: University of East Anglia

Annals of Operations Research, 2018, vol. 270, issue 1, 337-359

Abstract: Abstract Approximately one third of the food produced is discarded or lost, which accounts for 1.3 billion tons per annum. The waste is being generated throughout the supply chain viz. farmers, wholesalers/processors, logistics, retailers and consumers. The majority of waste occurs at the interface of retailers and consumers. Many global retailers are making efforts to extract intelligence from customer’s complaints left at retail store to backtrack their supply chain to mitigate the waste. However, majority of the customers don’t leave the complaints in the store because of various reasons like inconvenience, lack of time, distance, ignorance etc. In current digital world, consumers are active on social media and express their sentiments, thoughts, and opinions about a particular product freely. For example, on an average, 45,000 tweets are tweeted daily related to beef products to express their likes and dislikes. These tweets are large in volume, scattered and unstructured in nature. In this study, twitter data is utilised to develop waste minimization strategies by backtracking the supply chain. The execution process of proposed framework is demonstrated for beef supply chain. The proposed model is generic enough and can be applied to other domains as well.

Keywords: Big data; Beef supply chain; Waste minimisation; Twitter analytics (search for similar items in EconPapers)
Date: 2018
References: View references in EconPapers View complete reference list from CitEc
Citations Track citations by RSS feed

Downloads: (external link)
http://link.springer.com/10.1007/s10479-016-2303-4 Abstract (text/html)
Access to the full text of the articles in this series is restricted.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:spr:annopr:v:270:y:2018:i:1:d:10.1007_s10479-016-2303-4

Ordering information: This journal article can be ordered from
http://www.springer.com/journal/10479

Access Statistics for this article

Annals of Operations Research is currently edited by Endre Boros

More articles in Annals of Operations Research from Springer
Bibliographic data for series maintained by Sonal Shukla ().

 
Page updated 2018-12-15
Handle: RePEc:spr:annopr:v:270:y:2018:i:1:d:10.1007_s10479-016-2303-4