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Abstract Nowadays, due to intense competition, organizations are operating their activities in a dynamic and high uncertainty environment. From a competitive perspective, having continued profit depends on attracting new customers and retaining existing ones. Currently, all the attention has been focused on the relationship with customer and customer is considered as an essential component of the organization. The purpose of this study is to investigate 10 effective factors of Lindgreen Model on Implementation of customer relationship in agencies which belong to Mostazafan Foundation and to rank those effective factors. Lindgreen Model is one of the most comprehentive models for investigating the implementation of CRM. Those effective factors include Information Technology, People, Knowledge Management, Customer Strategy, Culture, Customer Relation Management Processe, Customer Interaction Strategy, Organization, Brand Strategy and Value-Add Strategy. The required data are gathered by distributing questionnaire among 385 customers of Aito and Perspolis agencies, using simple random sampling. The data are analyzed by Kolmogorov-Smirnov Test (k-s Test), Binomial Test and Friedman Test and also TOPSIS and Shanon’s Entropy Model. The results show that the ten factors of Lindgreen model in the implementation of customer relationship management agencies of Mostazafan Foundation are effective but their ranks are different.   Keywords: Customer Relationship Management, Lindgreen Model, Tourism Indusrty

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  Present a model for analyzing agents’ behaviors and determining their efficiency factor, while responding to calls in call centers is the main goal of this study. The aim of this model is to identify the strengths and weaknesses of the agents providing these services to customers. The proposed process defines three criteria namely F, U and Q which represent the number of responding, duration of responding to a unit call and the quality of responding to calls. After obtaining experts’ opinions, parameters were weighted. Then, based on the number of optimum clusters provided by Davis we tried to cluster the factors using K-Means. In the next stage criterion to measure the efficiency of agents were defined, and results were analyzed.  The use case carried out on 3401535 records of 158 answering agents in the call center for one of the companies affiliated to automobile industry. The results show that efficiency of agents is not relation to gender. The company does not use enough “best agents” for answering customer calls; whereas one of the highlights of Human Resource Management is the efficient use of an expert. On the other hand the results show that company should pay attention to the education and skills of hired agents who answer customer calls.    

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Nowadays, customer is known as the organizations’ most important source of information. The competitive advantage was lately obtained by innovation of product and creating a brand, but in twenty first century, companies are facing more interactions creating a competitive advantage which is obtained by gathering customer knowledge. This study intends to determine a structural model by the application of interpretive structural modeling (ISM). According to the interpretive structural modeling findings, twenty five important and effective factors on the process of implementing the customer knowledge management in the bank have been identified. The structural model analysis showed that following variables of the superior management commitment, the middle managers, organizational culture, financial resources and information technology are the main factors, and act like the foundation of the model. Any type of change on other factors which have high levels of guidance and dependency, could affect the system and system outcome could also change these variants again. The final result of factor in model expresses that executing and implementing the customer knowledge management process is effective at achieving factors such as customers' satisfaction, increase of service quality and keeping customers as a valuable asset and finally obtaining a competitive advantage.    

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E-Banking is a new type of banking service where banking services are provided using -environments. This kind of banking activity has spread throughout the world since 1991. Customers are migrating from traditional banking to modern banking with the increase of e-banking services and the provision of various tools for banking transactions. Accordingly, it is important to examine the progress of banks in these tools and the level of customer satisfaction. This study first analyzes the extent of customer satisfaction with these tools by examining customer transactions in Branch, ATM, Internet Bank and Mobile Bank Which has conducted this survey for a hundred thousand customers. After an initial analysis of the use of tools, Customers were clustered using k-Mean Method and Imperialist Competitive Algorithm with MATLAB software and grouped into seven clusters. Then the characteristics of each cluster are examined and strategies for each cluster are presented. In the final stage, we analyzed the strategies proposed by the Shapely value-based game theory approach and the most important strategies proposed.

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  With ever increasing competition, enterprises as well as researchers are focusing on consumer and its priorities and thus everyday, new aspects of determinants of consumer choice become clear. One of such determinants is brand perception. Perception of consumer about technology of production -which is derived from brand and packaging-, can play a great role in the consumer choice when differentiation is little. Such role is investigated in this research work. We have studied a group of food products with very low level of differentiation and correlation between demand and technology perception is elaborated. Field study has been performed in Shahrvand department stores. Results show that in simpler, more commodity type products, technology perception has a greater role in finalizing customer choice. So making a more positive perception of technology can be considered as a rather inexpensive way for gaining competitive advantage. Additionally, based on interviews, it can be claimed that technology perception consists of sub-elements such as environment friendliness perception, healthiness perception, quality perception, etc. 

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In recent years, the term "customer relationship management" has attracted much attention in the field of marketing and commerce. This study aimed to an analysis of the effect of customer relationship management dimensions on its success in service organizations with a meta-analysis approach. For this purpose, from 62 studies (from 2014 to 2018), 18 methodological and research objectives were accepted and meta-analysis was carried out on them. The research tool was a meta-analytic checklist. The findings showed that the propagation bias in the analyzed analysis is intangible. Also, the size of the impact of customer relationship management dimensions on the success of customer relationship management in service organizations was found to be 0.59 (Sig: 0/001). Accordingly, customer orientation (with an influence size of 0.601) and customer satisfaction (with a dependence size of 0.65) had the greatest impact on customer relationship management. The effect size according to Cohen's table is too high. We conclude that businesses are based on customer orientation and customer satisfaction so that the development and provision of services without considering this principle is not only difficult but impossible. Therefore, service organizations should focus all their activities and capabilities on customer satisfaction, because customers are the only source of return on investment. However, competitive markets today require all organizations to be customer-oriented.

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Financial Service Providers (FSPs) like other organizations can use ‎Customer Lifetime Value (CLV) as an instrument to achieve their targets in ‎Customer Relationship Management (CRM). Although various studies have ‎been done about this concept, CLV case studies are scarce in banking ‎industry. In this research, in order to present a model to determine CLV in ‎banking industry, customers with current account in a bank in Iran were ‎studied. Determining the relative importance of R, F and M variables that are ‎used to cluster customers, ranking the clusters of customers according to ‎their CLV and understanding the best strategies for bank to treat with each ‎cluster are among the other goals of this study. Three main variables were ‎used to apply the model; a) Recency: the length of time since the last ‎transaction (in days), b) Frequency: number of positive transactions and c) ‎Monetary: balance of account (in Rials). Also wR , wF and wM were used as ‎the relative importance of R,F and M variables. We used the ideas of experts ‎and marketing managers and the data of transactions from the random ‎samples of 382 corporate customers and 5113 individual customers, who had ‎current account in 33 branches of a bank in Tehran. The analytical Hierarchy ‎Process (AHP) was applied to determine wR , wF and wM in evaluating CLV. ‎Then WRFM model was used to cluster the customers and rank them based ‎on their CLV for two groups of corporate and individual clients Clustering ‎and Discriminant Analysis techniques were implemented for this section. ‎Finally, the best strategies for bank to treat with each cluster of the ‎customers was determined.‎ Keywords:

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The more a marketing paradigm evolves, the more long-term relationship with customers gains its importance. Nowadays, most of corporations and firms in the world, including manufacturers and servicers, increasingly gain their incomes and profits through constructing and maintaining long-term relationships with the customers. The move towards a customer-centered approach to marketing, coupled with the increasingavailability of customer transaction data, has led to an interest in understanding and estimatingcustomer lifetime value (CLV). Furthermore, as marketing endeavors to be more accountable, the need of tools and models for measuring and evaluating efforts and investments that accomplish in marketing extent, is felt. The purpose of this research is CLV analysis for customer segmentation and profitability management. This dissertation we proposes a model for CLV measurement in banking industry. Our case study is one of the branches of Iranian Melli Bank. For this purpose, we selected savings (loan) accounts for 4 years, (from 2005 to 2008), in order to run our model. The study sample included 10,000 customers picked up among the accounts. After calculating the CLV of customers, we segmented the customers based on the calculated CLV. For customer segmentation, we used Clustering technique. This conceptual model is a new approach in customer segmentation context. More Customer Profitability Management based on segmented customer sections will be explained. Based on the models explained in this dissertation programs and methods will be proposed for each of introduced segments. 

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Customer value refers to the potential interaction of customer and enterprise in the certain periods of time. As companies recognize customer value it can provide customized services for different customers, they can achieve to an effective customer relationship management. This research focuses on Banking Industry and integrates data mining techniques and management issues in order to systematically analyze the customer values. First it applies Fuzzy Analytical Hierarchy Processing (FAHP) in order to weighting variables and then imports DFMT model to the k-means technique, for clustering customers according to the specific criteria. Using proposed scoring model establishes the customer value pyramid and categorizes customers in four spectrums. The customer value pyramid helps to separately determining of each customer value to giving appropriate services to them in proportion with the class value. The statistical population was 285 customers of Tejarat bank branches of Zanjan city in Iran. In the resulted customer pyramid, the first spectrum is the Platinum customer which is composed of two rows of the pyramid called H1 and H2. These two rows in pyramid have the highest value and have the most profitability for the bank. Second spectrum, is called golden customers which has three rows in pyramid called H3, H4, H5. Third spectrums are Silver customers which are laid in H6, H7, H8 rows of spectrum. Forth spectrum, are leaden customers that are H9 and H10 rows of customer pyramid. This spectrum receives and wastes resources of the bank and bank should respect and bear high risks.

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Interaction of companies with customers in the form of customer relationship management has changed significantly. Identifying characteristics of different customers and allocating resources to them according to their value to the firm has become one of the main concerns in customer relationship management. The purpose of this paper is to provide an appropriate model for customer segmentation based on some of the most important financial and demographics characteristics influencing factors of customer lifetime value (CLV). The process proposed in this study was performed in Saman insurance company. After determining RFM model indices, which include date, frequency and monetary of purchase, AHP method used for weighting them among 180000 customers. The optimal number of clusters based on the silhouette and impact of RFM indicators was done by using Two-step algorithm and then customers classified through K-Means clustering algorithm. Results provided a platform to analyze the characteristics of customers in three main sections. Also, by prioritizing clusters based on the RFM indices, valuable customers were identified. Finally, some suggestions were presented to the company to improve its customer relationship management system.

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 Lean production system is a new management approach and a business strategy that results in the elimination of waste (costs and time) and improvement of the performance and overall value of an organization. The main objective of this study was to investigate factors influencing implementation of Lean Production Principle (LPP) and its relation with the performance of Small and Medium-sized Food Industry Enterprises (SMFIEs) in Khuzestan Province. This study was a kind of descriptive-correlation and causal-relation that was conducted through a survey technique. Statistical population of the study consisted of all managers in Small and Medium Enterprises (SMEs) in Khuzestan food industry (N= 307). By using Krejcie and Morgan’s tables and stratified random sampling method, 170 person were selected as sample, of which 161 person completed the research questionnaires (return rate 94.7%). The results show that among the eight factors that influence the implementation of LPP, three variables of “customer relationship management”, "human resource management”, and “employees’ empowerment” have the most direct effects on LPP and, ultimately, the highest total effect on SMFIEs performance. The implementation of LPP could explain about 31 percent of variances in SMFIEs performance. Conducting justification and education workshops not only enhances the knowledge of SMFIEs managers, but also helps implement the LPP and, subsequently, improves the performance of SMFIEs.

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Developing leadership skills is essential for creating innovative strategies for competing in complex environment and for the success in business. Successful leaders empower their followers to achieve goals. On the other hand, by developing concepts related to marketing, organizations' attitudes toward customers to create sustainable relationships are also changing, and in today's dynamic and competitive markets, industries and services need ways to meet environmental challenges and deliver waste-free products and services to customers. Assessing the existing background, a lack of research in this field is felt especially about the mediating role of entrepreneurial leadership. The present study is descriptive-correlation based on the applied purpose as well as on the nature and method. In the analysis of Kolmogorov-Smirnov test results, the data distribution was not normal; therefore, Smart PLS software was used for the data analysis. The PLS method for fitting and evaluating the validity of structural equation models covers three parts: measurement, structure, and general model. The results showed that the conceptual model has a good fit. Also, to test the research hypotheses, the path coefficient and statistical value of t were used, which were all confirmed, and we concluded that in using lean leadership, customer relationship is necessary, and on the other hand, having leaders with entrepreneurial spirit can be very effective in lean system and ultimately leads to good communication with customers.