saeed masoodipoor
Volume 23, Issue 4 , December 2019, , Pages 102-129
Abstract
Resolving the problem of poverty requires treatment of people in need of help to help the needy. Social charity marketing is used as one of the most effective and effective tools for encouraging and encouraging contacts to help the needy. In the process of social marketing planning, market segmentation ...
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Resolving the problem of poverty requires treatment of people in need of help to help the needy. Social charity marketing is used as one of the most effective and effective tools for encouraging and encouraging contacts to help the needy. In the process of social marketing planning, market segmentation is necessary for homogeneous and similar groups. This will lead to the design and provision of a tailor-made marketing program for each department. The present research seeks to base four indices of monthly assistance, daily assistance, amount of donation and the amount of income on the category of generosity. For this purpose, using cluster sampling method, 474 people from five regions of Tehran were selected. A hierarchical clustering technique was used to analyze the data. The results of the research show that there are five types of generosity behavior in the sample, for which each appropriate social marketing mix should be used to create a successful program for charitable contributions.
maghsood amiri; mojtaba aghaei
Volume 21, Issue 3 , December 2017, , Pages 1-23
Abstract
In choosing an alternative among many, decision makers usually take into account multiple criteria’s, which are sometimes in line with each other and sometimes conflicting. When there is dependencies between criteria, MCDM techniques such as ANP, AHP and DEMATEL could be applied. Another approach ...
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In choosing an alternative among many, decision makers usually take into account multiple criteria’s, which are sometimes in line with each other and sometimes conflicting. When there is dependencies between criteria, MCDM techniques such as ANP, AHP and DEMATEL could be applied. Another approach is to classify criteria that are correlated with each other. In this study a new approach of set covering problem to this end has been used. Our objective is setting these criteria into clusters so that their correlation in each cluster to be maximized, and also their correlation with others be minimized. In order to validate our proposed model, factor analysis method used. Data gathered from 9 industries related to 26 foreign countries. Finally, results of both models were almost similar. The results show that efficiency of the proposed method (set covering) for grouping variables is acceptable and this method in future research can be used to classify variables (when there is a correlation between variables).
Ebrahim Teimoury; Mohammad Fathian; Anis Farshian Abbasi
Volume 21, Issue 3 , December 2017, , Pages 73-95
Abstract
Nowadays, web-based services like E-Commerce and E-Banking make fundamental changes to the ways of using internet and human's life. Web shares direct media with low costs between services of businesses and their customers. Businesses need to record, study and analyze their users' behavior and interests ...
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Nowadays, web-based services like E-Commerce and E-Banking make fundamental changes to the ways of using internet and human's life. Web shares direct media with low costs between services of businesses and their customers. Businesses need to record, study and analyze their users' behavior and interests in order to adapt content and interface of their web site with users' interest for targeted marketing and advertising and then complete the process of personalization. For this purpose and for analysis of users’ behavior and making recommendations based on the users’ behavior, web mining approaches can be used. In this paper, a model was developed which can be applied for analyzing and predicting users' behaviors of a specific web site. First, users were clustered with affinity propagation algorithm and then, their behaviors were analyzed using sequential pattern mining algorithm called CM-SPADE. In the next step, for each cluster, Users' profile was created. Then by using these profiles, recommendations can be made for new users. At last, the represented model was evaluated and the final results was acceptable.
Hassan Rezapour; Mohammad Rezapour; Mohammad Mehdi Sepehri
Volume 17, Issue 4 , January 2014, , Pages 139-160
Abstract
Determining how to assess learners and contents of e-learning are essential activities in its processes. These activities are conducted by a professor or teaching assistant and they determine student assessment methods, such as holding an online test or periodic homework assignment. if the organizers ...
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Determining how to assess learners and contents of e-learning are essential activities in its processes. These activities are conducted by a professor or teaching assistant and they determine student assessment methods, such as holding an online test or periodic homework assignment. if the organizers can be aware of the effectiveness of each activity in the quality of learning,then besides saving considerable time and resources to stakeholders courses, which transfer the content useful and realistic assessment of students and will ultimately improve e-learning. In this paper, first we use unsupervised techniques of data mining for clustering and describe the present status of learners, and extract hidden rules in e-learning data using rule mining and will discover the effective contents in desired results. Next, using supervised methods we predict results of courses. Using real data of an electronic course provided and with designing four different methods for data sampling and training system, predictions were performed and the methods were validated with an accuracy rate of 92.86%. We have shown that the methods of this study can help teachers for a better understanding of learners and impact of such training activities required, such as describe characteristics of learners based on the discovery of hidden patterns in the scores of their acquired and determine the most effective learning activities and decide about real measures of learners.
Arash Shahin; reza salehzadeh; - -
Volume 16, Issue 1 , May 2012, , Pages 73-91
Abstract
The purpose of this paper is to propose an integrated model of clustering, AHP and Kano approaches. Based on customer segmentation and value achievement of each segment, the new model is expected to recommend appropriate service for each segment. Statistical population of this research includes customers ...
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The purpose of this paper is to propose an integrated model of clustering, AHP and Kano approaches. Based on customer segmentation and value achievement of each segment, the new model is expected to recommend appropriate service for each segment. Statistical population of this research includes customers of Saman Bank of Qom. After random sampling, 144 questionnaires have been used for data analysis. After data collection, the clustering approah has been used and clusters have been prioritized by the AHP approach and finally, the needs of each cluster have been determined using with the Kano methodology and appropriate service has been recommended for each cluster. The number of clusters has been addressed as four and the clusters have been prioritzed as the second, the third, the first and the fourth cluster. In the first cluster, customers' needs are distinguished as more, one-dimensional, attractive and indifferent; in the second and third clusters as more must-be; and in the fourth cluster as more one-dimensional. The results imply that the integratoin of the three approaches forms an empowered technique by which, an organization can achieve competitive advantage through market segmentation, valueable customer recognition/satisfaction
