Green Product Pricing and Order Strategies in a Supply Chain under Demand Forecasting

In this paper, we investigate price and order strategies for innovative green products using demand forecasting and sharing. We formulate the problem using a Stackelberg game and propose a dynamic contract that specifies an initial wholesale price, a minimum order quantity, a demand sharing agreemen...

Full description

Bibliographic Details
Main Authors: Yiling Fang, Xinhui Wang, Jinjiang Yan
Format: Article
Language:English
Published: MDPI AG 2020-01-01
Series:Sustainability
Subjects:
Online Access:https://www.mdpi.com/2071-1050/12/2/713
id doaj-fc61e057d62c4a689679c35c8a401590
record_format Article
spelling doaj-fc61e057d62c4a689679c35c8a4015902020-11-25T03:32:38ZengMDPI AGSustainability2071-10502020-01-0112271310.3390/su12020713su12020713Green Product Pricing and Order Strategies in a Supply Chain under Demand ForecastingYiling Fang0Xinhui Wang1Jinjiang Yan2Business School, Sichuan University, Chengdu 610064, ChinaSchool of Computer Science and Technology, Southwest Minzu University, Chengdu 610041, ChinaBusiness School, Sichuan University, Chengdu 610064, ChinaIn this paper, we investigate price and order strategies for innovative green products using demand forecasting and sharing. We formulate the problem using a Stackelberg game and propose a dynamic contract that specifies an initial wholesale price, a minimum order quantity, a demand sharing agreement, and a decisions adjustment agreement. We arrived at the following main findings and implications. First, the manufacturer offers a higher or lower wholesale price than the initial one depending on the variation in the market status. Also, the retailer’s ordering decisions will increase with the wholesale price, which contradicts the common assumption that ordering decisions decrease with the wholesale price. Interestingly, if the market improves, the manufacturer obtains a higher profit margin than the retailer; if the market worsens, the manufacturer suffers more loss of profit margin than the retailer. Second, when the cost of information sharing is smaller than an upper bound, demand forecasting and sharing are always beneficial to the manufacturer. However, the value of demand forecasting and sharing for the retailer is significantly affected by the market status variation. Third, high information accuracy will not necessarily increase the profits of the manufacturer and the retailer, even if the market status is better than expected. Finally, numerical examples show the parameters’ effects. We have several main managerial insights. When the shared demand information is received from the retailer, the manufacturer can determine wholesale price strategies according to the retailer’s demand forecast. Moreover, if the manufacturer wants to ensure profitability, they should not choose retailers with a higher capability of demand forecasting.https://www.mdpi.com/2071-1050/12/2/713green productsdemand forecastingstackelberg gameinformation accuracysupply chain
collection DOAJ
language English
format Article
sources DOAJ
author Yiling Fang
Xinhui Wang
Jinjiang Yan
spellingShingle Yiling Fang
Xinhui Wang
Jinjiang Yan
Green Product Pricing and Order Strategies in a Supply Chain under Demand Forecasting
Sustainability
green products
demand forecasting
stackelberg game
information accuracy
supply chain
author_facet Yiling Fang
Xinhui Wang
Jinjiang Yan
author_sort Yiling Fang
title Green Product Pricing and Order Strategies in a Supply Chain under Demand Forecasting
title_short Green Product Pricing and Order Strategies in a Supply Chain under Demand Forecasting
title_full Green Product Pricing and Order Strategies in a Supply Chain under Demand Forecasting
title_fullStr Green Product Pricing and Order Strategies in a Supply Chain under Demand Forecasting
title_full_unstemmed Green Product Pricing and Order Strategies in a Supply Chain under Demand Forecasting
title_sort green product pricing and order strategies in a supply chain under demand forecasting
publisher MDPI AG
series Sustainability
issn 2071-1050
publishDate 2020-01-01
description In this paper, we investigate price and order strategies for innovative green products using demand forecasting and sharing. We formulate the problem using a Stackelberg game and propose a dynamic contract that specifies an initial wholesale price, a minimum order quantity, a demand sharing agreement, and a decisions adjustment agreement. We arrived at the following main findings and implications. First, the manufacturer offers a higher or lower wholesale price than the initial one depending on the variation in the market status. Also, the retailer’s ordering decisions will increase with the wholesale price, which contradicts the common assumption that ordering decisions decrease with the wholesale price. Interestingly, if the market improves, the manufacturer obtains a higher profit margin than the retailer; if the market worsens, the manufacturer suffers more loss of profit margin than the retailer. Second, when the cost of information sharing is smaller than an upper bound, demand forecasting and sharing are always beneficial to the manufacturer. However, the value of demand forecasting and sharing for the retailer is significantly affected by the market status variation. Third, high information accuracy will not necessarily increase the profits of the manufacturer and the retailer, even if the market status is better than expected. Finally, numerical examples show the parameters’ effects. We have several main managerial insights. When the shared demand information is received from the retailer, the manufacturer can determine wholesale price strategies according to the retailer’s demand forecast. Moreover, if the manufacturer wants to ensure profitability, they should not choose retailers with a higher capability of demand forecasting.
topic green products
demand forecasting
stackelberg game
information accuracy
supply chain
url https://www.mdpi.com/2071-1050/12/2/713
work_keys_str_mv AT yilingfang greenproductpricingandorderstrategiesinasupplychainunderdemandforecasting
AT xinhuiwang greenproductpricingandorderstrategiesinasupplychainunderdemandforecasting
AT jinjiangyan greenproductpricingandorderstrategiesinasupplychainunderdemandforecasting
_version_ 1724566958457749504