The optimal e-commerce sales mode selection and information sharing strategy under demand uncertainty. (December 2021)
- Record Type:
- Journal Article
- Title:
- The optimal e-commerce sales mode selection and information sharing strategy under demand uncertainty. (December 2021)
- Main Title:
- The optimal e-commerce sales mode selection and information sharing strategy under demand uncertainty
- Authors:
- Yang, Man
Zhang, Tao
Wang, Chuan-xu - Abstract:
- Highlights: The e-commerce sales mode and information sharing are considered. Manufacturer's investment efficiency affects parties' sales mode selection. Information sharing strategy affects parties' sales mode preferences. E-retailer's prediction accuracy affects both parties' optimal decisions. Players can benefit from more accurate prediction information. Abstract: Demand forecasting is important information for all enterprises. Accurate forecast information determines the success of supply chain operations. This paper studies the selection strategy of e-commerce sales mode and information sharing strategy in a dual-channel supply chain. The manufacturer and e-retailer enter a Stackelberg competition. The e-retailer independently decides to share or not share forecasting demand information to the manufacturer. The results show that only if the investment efficiency of the manufacturer's after-sales service is high, e-retailer is willing to share demand forecasting information. Information sharing does not always add value to the e-retailer, which may lead to the 'precision trap' of the e-retailer. Moreover, forecasting accuracy always has a positive impact on the e-retailer's profit. However, the manufacturer would benefit from more accurate forecasting demand in the case of sharing information. Otherwise, prediction accuracy is negatively correlated with the manufacturer's profit. Besides, the selection strategy of e-commerce sales mode depends on the level of theHighlights: The e-commerce sales mode and information sharing are considered. Manufacturer's investment efficiency affects parties' sales mode selection. Information sharing strategy affects parties' sales mode preferences. E-retailer's prediction accuracy affects both parties' optimal decisions. Players can benefit from more accurate prediction information. Abstract: Demand forecasting is important information for all enterprises. Accurate forecast information determines the success of supply chain operations. This paper studies the selection strategy of e-commerce sales mode and information sharing strategy in a dual-channel supply chain. The manufacturer and e-retailer enter a Stackelberg competition. The e-retailer independently decides to share or not share forecasting demand information to the manufacturer. The results show that only if the investment efficiency of the manufacturer's after-sales service is high, e-retailer is willing to share demand forecasting information. Information sharing does not always add value to the e-retailer, which may lead to the 'precision trap' of the e-retailer. Moreover, forecasting accuracy always has a positive impact on the e-retailer's profit. However, the manufacturer would benefit from more accurate forecasting demand in the case of sharing information. Otherwise, prediction accuracy is negatively correlated with the manufacturer's profit. Besides, the selection strategy of e-commerce sales mode depends on the level of the manufacturer's investment efficiency. Specifically, if the manufacturer invests in after-sales service more efficiently, platform sales mode is preferred. If not, they prefer wholesale sales mode. … (more)
- Is Part Of:
- Computers & industrial engineering. Volume 162(2021)
- Journal:
- Computers & industrial engineering
- Issue:
- Volume 162(2021)
- Issue Display:
- Volume 162, Issue 2021 (2021)
- Year:
- 2021
- Volume:
- 162
- Issue:
- 2021
- Issue Sort Value:
- 2021-0162-2021-0000
- Page Start:
- Page End:
- Publication Date:
- 2021-12
- Subjects:
- Dual-channel supply chain -- Information sharing -- E-commerce sales mode -- Demand forecasting -- Dynamic game
Engineering -- Data processing -- Periodicals
Industrial engineering -- Periodicals
620.00285 - Journal URLs:
- http://www.sciencedirect.com/science/journal/03608352 ↗
http://www.elsevier.com/journals ↗ - DOI:
- 10.1016/j.cie.2021.107718 ↗
- Languages:
- English
- ISSNs:
- 0360-8352
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - 3394.713000
British Library DSC - BLDSS-3PM
British Library HMNTS - ELD Digital store - Ingest File:
- 20090.xml