Research On Information Service And Quality Evaluation Model Of Tea Industry

Chinese tea industry is experiencing the key transformation from a traditional industry to a modern industry, tea industry informationization has become a significant characteristic for tea industry, information service is the important content for tea industry informationization. Focus on these service features of region, season, comprehensiveness and complexity, searching a suitable information service model for tea industry is hot. Aiming at the issues of the low information quality and complex users, the analysis of information demand, information service system design, information systems integration model, the construction of cloud platform, the service quality model of cloud platform had been studied in this paper, the specific works as follows:(1) Focus on the low information quality and information service being a loser to solve the reality problems, these features of region, season, comprehensiveness and complexity had been provided, then users information demand and the key technologies had been analied for the coustruction of an optimization model of user information demand;(2) Focus on the functional and technical demand of tea industry, pertinent information service systems had been advanced, including production information system, marketing information system and management information system which are used to meet the main information demand of tea industry;(3) Based on the information service system, the service model of systems integration had been studied to verify the feasibility of service model constructed on SaaS, then choose an integration scheme. The functional framework of tea industry information cloud platform based on SaaS had been designed to fix the architecture of information cloud platform. Combined the data integration method with system integration mechanism, information cloud service platform has been designed.(4) To building an assessment indicator system for the service quality of tea industry information cloud service, R type cluster analysis and multiple linear regression had been used for analyzing the factors influencing the information service quality, providing theoretical direction for the construction of tea industry information cloud service and its function optimization.