Title
Demand Forecasting and Pricing Decision with the Entry of Store Brand under Various Information Sharing Scenarios.
Abstract
In this research, we discuss three different approaches to generate demand forecasting and pricing decision for mix of national brand and store brand products in the era of big data. We derive the equilibrium wholesale price and retail price for the national brand products, and the equilibrium retail price for the store brand products based on demand forecast under three different information scenarios, including Non information Sharing (N), Information Sharing (I), and Retailer Forecasting (R). We comprehensively discuss how information collection, information sharing, forecast accuracy under era of big data affect firms' prices and profits. Our numerical experiments illustrate and verify our analytical findings and provide further managerial insights and interpretations.
Year
DOI
Venue
2017
10.1142/S0217595917400188
ASIA-PACIFIC JOURNAL OF OPERATIONAL RESEARCH
Keywords
Field
DocType
Forecasting,information sharing,stackelberg game,store brand,pricing
Mathematical optimization,On demand,Demand forecasting,Store brand,Industrial organization,Stackelberg competition,Big data,Information sharing,Mathematics,National brand,Marketing,Profit (economics)
Journal
Volume
Issue
ISSN
34
2
0217-5959
Citations 
PageRank 
References 
2
0.36
7
Authors
3
Name
Order
Citations
PageRank
Ting Zhang122738.58
xiaowei zhu2121.57
Qinglong Gou3275.04