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 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.