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Nowadays, communications, products, services and costs are customized through the internet technology. The main theory to continue competitiveness in the organizations is customer relationship management (CRM). CRM enables organizations to efficiently interact with customers and gather, store and examine their data for providing a complete view of them. On the other hand, the subject of cloud computing has increasingly become the bridge for the success of the CRM implementation. Therefore, this study aims to investigate the impact of cloud computing (new cloud facility, knowledge of information technology (IT), cloud security and cost) on the success of CRM systems.

The model and the questioners-based data are analyzed using the Smart PLS 3.0. The data were gathered based on 80 employees of three main agricultural companies in Iran.

The obtained results have indicated that all of the considered factors, new cloud facilities, knowledge of IT, cloud security and cost, play an important role in CRM systems’ success. Also, the evaluation and examination of the consistency and validity of the model are performed through the structural equation model.

First, the authors have conducted a study in a single region. It cannot be guaranteed that the results can be generalized to other regions. Second, for this cross-sectional study, the research design was conducted that showed constant relationships between variables. The research done for this study is cross-sectional. Third, because of time and financial restrictions, the authors have gathered data using a sample from a single location.

Proposing a new model for investigating of the impact of cloud computing (new cloud facility, knowledge of Information Technology (IT), cloud security and cost) on the success of CRM systems is the main originality of this paper.

This paper aims to propose a new method for evaluating the success of the recommender systems based on customer history, product classification and prices criteria in the electronic commerce. To evaluate the validity of the model, the structural equation modeling technique is employed.

A method has been suggested to evaluate the impact of customer history, product classification and prices on the success of the recommender systems in electronic commerce. After that, the authors investigated the relationship between these factors. To achieve this goal, the structural equation modeling technique was used for statistical conclusion validity. The results of gathered data from employees of a company in Iran is indicated the impact of the customer history on the success of recommender systems in e-commerce which is related with the user profile, expert opinion, neighbors, loyalty and clickstream. These factors positively influence the success of recommender systems in ecommerce.

The obtained results demonstrated the efficiency and effectiveness of the proposed model in term of the success of the recommender systems in the electronic commerce.

In this paper, the effective factors of success of recommender systems in electronic commerce are pointed out and the approach to increase the efficiency of this system is applied into a practical example.