Next Article in Journal
Minimum Quantity Lubrication and Carbon Footprint: A Step towards Sustainability
Previous Article in Journal
How Sharing Can Contribute to More Sustainable Cities
Article Menu
Issue 5 (May) cover image

Export Article

Open AccessArticle
Sustainability 2017, 9(5), 710; doi:10.3390/su9050710

Trust-Embedded Information Sharing among One Agent and Two Retailers in an Order Recommendation System

1
Institute of Innovation and Development, Hangzhou Dianzi University, Hangzhou 310012, China
2
School of International and Public Affairs, Shanghai Jiao Tong University, Shanghai 200030, China
*
Author to whom correspondence should be addressed.
Academic Editor: Andrea Appolloni
Received: 12 April 2017 / Revised: 24 April 2017 / Accepted: 26 April 2017 / Published: 29 April 2017
View Full-Text   |   Download PDF [3038 KB, uploaded 29 April 2017]   |  

Abstract

Trust potentially affects the decision-makers’ behaviors and has a great influence on supply chain performances. We study the information sharing process considering trust in a two-tier supply chain with one upstream agent and two retailers, where the agent recommends ordered quantities (ROQ) to retailers and the retailer decides her/his ordered quantities according to the agent’s recommendation and self-collected information. There exist three types of information sharing patterns among the agent and two retailers, i.e., both retailers share their demand prediction (Pattern 1), one retailer shares her/his demand prediction (Pattern 2) and none of the retailers share their demand prediction (Pattern 3). Thus, we build corresponding mathematical models and analyze each party’s decision strategies in each pattern, respectively. The findings in this study show that sharing information can generally promote trust among enterprises in the entire supply chain and increase their profits in return. It is found that when the accuracies of the two retailers’ predicted demand differs, their behaviors of information sharing or not sharing significantly affect their expected profits. In Pattern 1 and Pattern 3, we find that retailers’ expected profits are negatively influenced by the agent’s accuracies of demand prediction. However, the retailer’s expected profits are positively linked to the agent’s accuracies of demand in Pattern 2. Consequently, we propose a series of strategies for retailers in different decision patterns after several simulation runs. In addition, we also find that the retailer whose prediction is less accurate can also gain more profits by un-sharing his/her demand prediction when the agent’s predict accuracy is between the two retailers. View Full-Text
Keywords: supply chain; trust; information sharing; order recommendation supply chain; trust; information sharing; order recommendation
Figures

Figure 1

This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

Scifeed alert for new publications

Never miss any articles matching your research from any publisher
  • Get alerts for new papers matching your research
  • Find out the new papers from selected authors
  • Updated daily for 49'000+ journals and 6000+ publishers
  • Define your Scifeed now

SciFeed Share & Cite This Article

MDPI and ACS Style

Fu, X.; Han, G. Trust-Embedded Information Sharing among One Agent and Two Retailers in an Order Recommendation System. Sustainability 2017, 9, 710.

Show more citation formats Show less citations formats

Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Related Articles

Article Metrics

Article Access Statistics

1

Comments

[Return to top]
Sustainability EISSN 2071-1050 Published by MDPI AG, Basel, Switzerland RSS E-Mail Table of Contents Alert
Back to Top