جستجوی مقالات مرتبط با کلیدواژه « customer relationship management » در نشریات گروه « صنایع »

Customer relationship management is a rotational process of corporate organizations with their customers, including the production, collection and analysis of data analysis and the use of results to improve services. Organizations use business intelligence to collect this data continuously and use it in knowledge management, analysis and in the decision-making process.

The main purpose of this research is to identify business intelligence on customer relationship management using knowledge management in the shipping industry of the Islamic Republic of Iran.

The present study is based on the applied purpose and its method is survey type. Data collection methods are a combination of library, field, and survey methods. The research tool was a questionnaire developed by researchers that validation and reliability were used by 15 experts, after the Likert score and were tested in 127 people. Factor analysis of changes and hypothesis testing were performed using SPSS and Smart PLS software. Findings showed that in the shipping industry of the Islamic Republic of Iran, Business intelligence has a significant impact on knowledge management successBusiness intelligence has a bearing on the success of customer relationship managementKnowledge management is related to the success of management in relation to conceptual management

Now a days Customer knowledge is one of the most interesting topics for every organizations in order to gain competitive advantage. Competitive advantage can be achieved through creation of new knowledge. The point is that it is important to know that how information about customers is collected and lead to create new knowledge. In this paper, we consider the levels of support for customer knowledge creation processes by customer relationship management (CRM) in the case. All CRM systems that used in the organization were identified and categorized based on semi-structured interviews with experts in various fields. Then the process of knowledge creation that is created by each system were identified. The survey showed that analytical CRM systems support combination process, operational CRM systems support socialization and externalization processes, and collaborative CRM systems support socialization process. On the other hand, collaborative and analytical CRM systems support internalization process by creating learning opportunities.

The main purpose of this paper is to propose an integrated model by using the existing important factors influencing customer satisfaction and customer loyalty. Its foremost theory contribution is using the most cited related literature and verifying the model in the automobile industry in Iran. In theory testing, for the model in a specific case study, by using an explanatory approach, experts' focus group prioritized the factors. After considering all existing factors in the relevant literature, results showed 9 factors to be included in the integrated model. ``Brand Equity'', ``Product Quality'', ``Service Quality'', ``Service Recovery'', ``Perceived Value''; ``Employee Satisfaction'', ``Effective Customer Relations'', ``Physical Environment'', and ``Distribution Channels'' are among the most used factors in customer satisfaction literature. For each factor, relevant literature was reviewed to develop an operational definition. The relevant factors with case conditions were selected and tested for the initial assessment of the validity and reliability of the integrated model. Test results showed that the proposed model may have an appropriate level of validity and reliability in this particular case study. Overall, the selected factors can predict more than 74% of customer satisfaction and more than 87% of customer loyalty changes.

In today's competitive world in which customers are thought of as competitive advantages, customer relationship management is one of the most fundamental determinants of organizational success. Correct knowledge and evaluation of performance resulting from using this model is a concern of scholars and corporate managers around the world. Since relationship with customers in service organizations such as Iranian Gas Company is more tangible and relevant, customer relationship management enjoys greater significance. The general theme of newer models and frameworks of performance is an attempt to connect performance indices to organizations long-run strategy and landscape. The aim of this paper is to evaluate the performance of North Khorasan Gas Company in the process of customer relationship management on the basis of CRM Balanced Scorecard as a based model on balanced Scorecard framework using multiple-criteria decision-making. In this study, in order to determine these factors in each of the four perspectives of CRM Scorecard, after extracting the primary factors from literature review and interviewing experts, an Analytic Network Process (ANP) model was used to rank criteria and DEMATEL was employed to identify the relationships among main variables. The analysis of resulting data was performed in software (EXCEL and Superdesision software) environment. According to the obtained results, in North Khorasan Gas Company the customer perspective among the four perspectives of CRM Scorecard is a high rank aspect.

One of the four basic elements for Customer Relationship Management is services and product’s warranty is included in after-sales services and producers provide it with product. These services can satisfy customers and encourage them to buy so ultimately affect customer loyalty in most developed countries and producer have a significant percentage income from the after sales services. The main challenge of enterprises is a strategy for customer relationship management. Studies show that the organizations that use the balanced score card approach in implementing their strategy are successful. BSC with customer relationship management become key success factors and performance measures and ultimately provide executable plans. So we define an after sales problem in customer relationship management with balanced score card. Then we use TOPSIS for proposed indexes and examine them. The results show that customer perspective has the highest score and customer satisfaction is the first key index.

Now a days Customer knowledge is one of the most interesting topics for every organizations in order to gain competitive advantage. Competitive advantage can be achieved through creation of new knowledge. The point is that it is important to know that how information about customers is collected and lead to create new knowledge. In this paper, we consider the levels of support for customer knowledge creation processes by customer relationship management (CRM) in the case. All CRM systems that used in the organization were identified and categorized based on semi-structured interviews with experts in various fields. Then the process of knowledge creation that is created by each system were identified. The survey showed that analytical CRM systems support combination process, operational CRM systems support socialization and externalization processes, and collaborative CRM systems support socialization process. On the other hand, collaborative and analytical CRM systems support internalization process by creating learning opportunities.

In recent years, many companies have integrated the activities of customer relationship management with knowledge management together as one concept. In fact, the knowledge management is major parameter in customer relationship management. The potential of bilateral relationship between these two fields and also the critical function of knowledge management in success of customer relationship management, has attracted the attention of researchers to this matter recently. The term of “customer knowledge management” is the combination of knowledge management and customer relationship management. The customer knowledge management requires applying different approaches through considering wide variety of key variables in these fields. The considered key variables for each customer knowledge management model are different according to its model. Generally, many models have been presented for customer knowledge management, including conceptual, process and system model. In this paper, we intend to develop process model which achieved from combination of business engineering model, six business processes based on customer relationship management systems, and four aspects of knowledge management in principle business activities, namely marketing, sales and services.

Customer classification using k-means algorithm for optimizing the transportation plans is one of the most interesting subjects in the Customer Relationship Management context. In this paper, the real-world data and information for a spare-parts distribution company (ISACO) during the past 36 months has been investigated and these figures have been evaluated using k-means tool developed for spare-part demand similarity function in different regions of the country. Similarity function for customer behavior in different regions has been defined. Based on this function and with help of k-means algorithm, customers have been grouped and similar customers were put in the same groups. Customer similarity function has been developed through 5 steps and has been defined individually based on each factors of Euclidean distance, customer's order time and bulk value of the order. Then, these three factors have been combined and DCB function has been defined. In the final step, different weights have been allocated to different years and seasons and BCD function has been improved. The grouping process has been improved for three functions of Euclidean distance, DCB and BCD. This process was executed using the R software and the improved BCD function was recognized as the optimum grouping function. Then, using DMT model, customer behavior has been analyzed at each part and the proper distribution policies have been defined. Results indicate a significant cost reduction (32%) in spare-parts distribution costs for ISACO