Today, organizations spend significant budgets for creating and maintaining relationships with their clients to maintain and improve its position in competitive markets. Since, marketing managers have challenges for allocation of available budgets and selection of best innovative actions, the efficient analysis of Customer behavior to allocate resources is essential. This paper proposes a two-stage model for portfolio Customer management using DEA and robust optimization. In the first stage, the performance of all Customers is evaluated by robust BCC model and appropriate Customers are selected as candidates for the optimal resources allocation. In the next stage, the optimal allocation is done with the objective of maximization Customer lifetime value to marketing expenses ratio. The proposed model was implemented for Customers of Bhban manufacturing company that operates in the medicine industry and the results were analyzed. The main contribution of this research is use of data envelopment analysis and robust optimization for Customer performance evaluation simultaneously. The results showed that using this approach, Customers who are candidates for the final basket in resource allocation have more expected value than other approaches in the literature.

Due to the effective role of Markov models in Customer relationship management (CRM), there is a lack of comprehensive literature review which contains all related literatures. In this paper the focus is on academic databases to find all the articles that had been published in 2011 and earlier. One hundred articles were identified and reviewed to find direct relevance for applying Markov models in CRM. Forty four articles were selected and categorized on two major subclasses: articles which had used Markov chain models (MCM) in CRM and those which had applied hidden Markov models (HMM) in CRM. Findings of this paper indicate that applying HMM in CRM is approximately rare, since it contains 27.2% of the total number of published articles. To complete investigation a two-step framework has been suggested for using HMM in busy Customer portfolio management. It is for the first time that two important concepts (busy Customer and HMM) are used to achieve a common goal. Also the model parameters have been estimated in order to analyze a real firm’s data.

Considering the possible restrictions on the provision of facilities, bank managers need to facilitate the decision-making process of allocating bank's funds in the form of Islamic facilities and contracts. It thus requires them to take into account the goals of optimizing the efficiency and minimizing default risk. In this research, three nonlinear programming models (two objective functions and one objective function) and an ideal programming model were used to optimize the convenience portfolio of the Ansar bank. Given the number of constraints, the variables and the nature of the models, a genetic algorithm was used to solve the problem. In mathematical modeling, the problem of optimizing the loan portfolio of bank is considered to be policy limits, budget and capital adequacy. As the results showed, the optimal solution presented with the actual amount of the allocated facility to the bank's micro-banking group has difference in terms of profit and default risk. Also, these answers could improve the balance of facilities in the type of contracts and Customer groups in relation to lending, along with other constraints. Among the models presented, a model that minimizes default risk in itself enjoyed the best performance compared to other introduced models.

The main objective of this study is portfolio selection criteria analysis using Dematel of Criteria Decision Making Techniques. Society of the research is the finance and investment of manager belongs to the all stock companies. And instrument used questionnaires to a total of 15 questionnaires distributed among experts in capital markets, and finally 10 questionnaires were collected to answer research questions and data analysis methods were used Dematel. The analysis criteria using the techniques presented Dematel determined that the eight criteria for the selection of the portfolio, the measure of sales growth for the most affect on other criteria, and the biggest factor is the weight of the entire system. Also the price earnings ratio is more affected than other measures. Sales growth is a weighted measure of the total system. That is the most important criterion and has the greatest influence on the sorrow of the whole system.The results of this study can be used for investment companies, financial manager’s banksand banking insurance agencies, researchers and general investors have implications.

The present study proposes a Customer Behavior Mining Framework on the basis of data mining techniques in a telecom company. This framework takes into account the Customers’ behavior patterns and predicts the way they may act in the future. Firstly, clustering technique is used to implement portfolio analysis and previous Customers are divided based on socio-demographic features using k-means algorithm. Then, the cluster analysis is conducted based on two criteria, i. e., the number of hours the telecom services used and the number of the services selected by Customers of each group. Six groups of Customers are identified in three levels of attractiveness according to the results of the Customer portfolio analysis. The second phase has been devoted to mining the future behavior of the Customers. Predicting the level of attractiveness of newcomer Customers and also the churn behavior of these Customers are accomplished in the second phase. This framework effectively helps the telecom managers mine the behavior of their Customers. This may lead to develop appropriate tactics according to Customers’ attractiveness and their churn behavior. Improving managers’ abilities in Customer relationship management is one of the obtained results of the study.