Customer reviews for demand distribution and sales nowcasting: a big data approach
Published 2016 View Full Article
- Home
- Publications
- Publication Search
- Publication Details
Title
Customer reviews for demand distribution and sales nowcasting: a big data approach
Authors
Keywords
Big data, Sales nowcasting, Short-run operation, Demand distribution
Journal
ANNALS OF OPERATIONS RESEARCH
Volume -, Issue -, Pages -
Publisher
Springer Nature
Online
2016-08-24
DOI
10.1007/s10479-016-2296-z
References
Ask authors/readers for more resources
Related references
Note: Only part of the references are listed.- A survey of big data research
- (2015) Hua Fang et al. IEEE NETWORK
- Big Data in product lifecycle management
- (2015) Jingran Li et al. INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY
- Harvesting big data to enhance supply chain innovation capabilities: An analytic infrastructure based on deduction graph
- (2015) Kim Hua Tan et al. INTERNATIONAL JOURNAL OF PRODUCTION ECONOMICS
- Predicting consumer product demands via Big Data: the roles of online promotional marketing and online reviews
- (2015) Alain Yee Loong Chong et al. INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH
- The Data-Driven Newsvendor Problem: New Bounds and Insights
- (2015) Retsef Levi et al. OPERATIONS RESEARCH
- Mechanisms to Induce Buyer Forecasting: Do Suppliers Always Benefit from Better Forecasting?
- (2015) Thunyarat Bam Amornpetchkul et al. PRODUCTION AND OPERATIONS MANAGEMENT
- Special Issue ofProduction and Operations Managementon “Big Data in Supply Chain Management”
- (2015) Nada R. Sanders et al. PRODUCTION AND OPERATIONS MANAGEMENT
- Public Mood and Consumption Choices: Evidence from Sales of Sony Cameras on Taobao
- (2015) Qingguo Ma et al. PLoS One
- Advances in nowcasting influenza-like illness rates using search query logs
- (2015) Vasileios Lampos et al. Scientific Reports
- Distributionally Robust Convex Optimization
- (2014) Wolfram Wiesemann et al. OPERATIONS RESEARCH
- Nowcasting the Spread of Chikungunya Virus in the Americas
- (2014) Michael A. Johansson et al. PLoS One
- A Hybrid Sales Forecasting Scheme by Combining Independent Component Analysis with K-Means Clustering and Support Vector Regression
- (2014) Chi-Jie Lu et al. TheScientificWorldJOURNAL
- Big data, bigger dilemmas: A critical review
- (2014) Hamid Ekbia et al. Journal of the Association for Information Science and Technology
- Big Data
- (2013) Hans Ulrich Buhl et al. Business & Information Systems Engineering
- A multivariate intelligent decision-making model for retail sales forecasting
- (2013) Z.X. Guo et al. DECISION SUPPORT SYSTEMS
- Clickstream Data and Inventory Management: Model and Empirical Analysis
- (2013) Tingliang Huang et al. PRODUCTION AND OPERATIONS MANAGEMENT
- The Effect of Online Consumer Reviews on New Product Sales
- (2012) Geng Cui et al. INTERNATIONAL JOURNAL OF ELECTRONIC COMMERCE
- Impact of Reseller's Forecasting Accuracy on Channel Member Performance
- (2012) Ying-Ju Chen et al. PRODUCTION AND OPERATIONS MANAGEMENT
- A Sales Forecast Model for Short-Life-Cycle Products: New Releases at Blockbuster
- (2012) Casey Chung et al. PRODUCTION AND OPERATIONS MANAGEMENT
- An intelligent fast sales forecasting model for fashion products
- (2010) Yong Yu et al. EXPERT SYSTEMS WITH APPLICATIONS
- A distribution-free newsvendor model with balking and lost sales penalty
- (2010) Yi Liao et al. INTERNATIONAL JOURNAL OF PRODUCTION ECONOMICS
- Demand Forecast Sharing in Supply Chains
- (2009) Birendra K. Mishra et al. PRODUCTION AND OPERATIONS MANAGEMENT
- Structural Estimation of the Newsvendor Model: An Application to Reserving Operating Room Time
- (2008) Marcelo Olivares et al. MANAGEMENT SCIENCE
Publish scientific posters with Peeref
Peeref publishes scientific posters from all research disciplines. Our Diamond Open Access policy means free access to content and no publication fees for authors.
Learn MoreBecome a Peeref-certified reviewer
The Peeref Institute provides free reviewer training that teaches the core competencies of the academic peer review process.
Get Started