Enterprises business model evaluating system and method based on cloud computing

Abstract

The invention discloses an enterprise business model evaluating system and a method based on cloud computing. The system comprises a client, a server and a data base module, the server is connected with the client through a network, the data base module is connected with the server, the client comprises an enterprise information input module which is used for submitting enterprise product and technology data, market data, value chain data, dynamic capability data, profitability data and former achievement data to the server according to a preset enterprise parameter model, then the data are stored into the data base module, the data base module further stores a preset data base, the preset data base is used for storing parameters of evaluation cases for follow-up comparison, the server comprises a parameter acquiring module and an evaluation module, and the data processing is performed in the server. According to the enterprise business model evaluating system and the method based on cloud computing, the preset data base is arranged, so that the evaluation efficiency can be improved, simultaneously the evaluation is standardized, and the conviction of the evaluation result is enhanced.

Description

technical field [0001] The invention belongs to the technical field of computers and networks, and relates to an enterprise evaluation service system, in particular to a cloud computing-based enterprise business model evaluation system; meanwhile, the invention also relates to a cloud computing-based enterprise business model evaluation method. Background technique [0002] Nowadays, the number of enterprises is increasing, and the existing methods for evaluating the advantages and disadvantages of enterprises are usually based on artificial evaluation based on some data. [0003] The disadvantages of human evaluation are: firstly, there are a lot of enterprise data, including operating data, business prospect data, etc., and it takes a lot of time to sort out artificially, which leads to low evaluation efficiency; secondly, different evaluation elements and standards are different for different people. It is easy to lead to different evaluation results of the same enterpris...

AI Technical Summary

Problems solved by technology

[0003] The disadvantages of human evaluation are: firstly, there are a lot of enterprise data, including operating data, business prospect data, etc., and it takes a lot of time to sort out artificially, which leads to low evaluation efficiency; secondly, different evaluation elements and standards are different for different people. It is easy to lead to different evaluation results of the same enterprise by different people, and the evaluation is not very convincing.

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