Subsidy and pricing strategies of an agri-food supply chain considering the application of Big Data and blockchain

Abstract

Based on the advantages of Big Data and blockchain in food traceability area and information sharing area, it has attracted widespread attentions. However, it is not so popular in agricultural field, a vital reason is the scarcity of effective incentives. Government incentive as an important incentive measure is thought to be useful. To study the subsidy rules in the new background, we chose an agri-food supply chain with one producer and one retailer as research object and divided government incentive into direct incentive and indirect incentive. Then, considering the changes of consumer perceived safety on agri-food in the new environment, the demand function was revised. Furthermore, we proposed and analyzed three subsidy models and their benefit functions considering the information service inputs based on Big Data and blockchain (BBIS). Findings: (1) The subsidy models will not change the variation tendency of prices and benefits with the BBIS optimization coefficient, the BBIS investment costs from the producer and the retailer, the ascension of the unreliability coefficient of quality safety and the agri-food quality level. (2) When the subsidy coefficients about direct and indirect subsidies can meet a relationship, benefits of chain members in the indirect subsidy model are higher than them in the direct subsidy model. Findings offer a theoretical guidance for government departments to make and implement the subsidy strategies. In addition, for company, it can provide a theoretical guidance on setting pricing strategies in the new technology background.