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...
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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 |
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