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Constraint-based Online Pharmacy Logistics Distributor Recommendation Research

Posted on:2018-11-26Degree:MasterType:Thesis
Country:ChinaCandidate:J J GaoFull Text:PDF
GTID:2359330518960250Subject:Logistics engineering
Abstract/Summary:PDF Full Text Request
With people constantly improve the level of consumption,people are increasingly pay more attention to health care,which has led the entire medical industry to flourish.The online pharmacies as a new drug shopping platform makes consumers'life more convenient and comfortable.However,although the online pharmacies as a new e-commerce platform,there are many problems.Mainly manifested in these aspects:in the online pharmacy logistics and distribution time is too slow and its costs are too high;the safety of distribution of drugs cannot guarantee the problems plagued the development of online pharmacies.These problems lead to consumer complaints on online pharmacy logistics now more and more high.The solution to this problem is based on consumer demand for personalization and design to meet consumer demand for logistics and distribution business.Considering that,this study is designed to obtain information of consumers and logistics distributors;then we determine three key dimensions' requirements,security requirements,economic needs of logistics and distribution business.we establish appropriate constraint to select the appropriate logistics and distribution business to consumers.In order to study the featured and recommended online pharmacy logistics and distribution business model,this study adopts case study method and invited 50 university students.We carry out satisfaction surveys for them.Experimental shows that the logistics and distribution business who used recommended model have a high degree of satisfactions in terms of timeliness,security,economy and so on.Thus proving this paper recommend the design of logistics distribution system has a significant effect in improving consumer satisfaction on logistics distribution business.
Keywords/Search Tags:online pharmacy, personalized recommendation, Logistics distributors, constraint-based recommendation algorithm
PDF Full Text Request
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