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Abstract：Without doubt, administering inclusive financial assistance to relieve the poor of poverty has been put under spot light recently. This present study itry to apply data mining, cloud computing, artificial intelligence and financial technologies to promote the project of inclusive finance in rural areas to help the financially disadvantaged groups. While implementing inclusive finance in rural areas, both supply and demand sides should be considered in order to form a comprehensive development of inclusive finance. Through administering financial services in poor and remote areas can benefit the financial disadvantaged groups in rural areas in the long run.

Few previous researches have considered the integration of three echelons, which is the central focus of this paper. This study focuses specifically on the decisions of frequent deliveries of an order, under a three-echelon distribution system of multiple manufacturers, one distribution center (DC), and several retailers. The authors develop a fully-integrated model by multiple objective decision making method. The main goal is to find solution of the model which optimizes both objectives functions simultaneously. In addition, typical partial-integrated model is defined as quantity of products by which manufacturers produced and transported according to the result that achieves the minimum total cost of the DC and the retailers. Compared with fully-integrated model, the total relevant cost is significantly less than the total cost of a typical partial-integrated policy. The results of this study indicate that companies should consider the changes necessary to support fully integration; the total relevant cost within the supply chain can be significantly reduced when compared with a typical partial-integration.