Mahdi Hosseini; Alireza Mooghali; Mohammad Ali Sarlak; Gholamhossein Deljo
Volume 4, Issue 8 , August 2017, , Pages 888-897
Abstract
The purpose of the present research is to evaluate and validate the Jihadi organization model. Regarding the significance of inherent models in management and organization field and according to the necessity of using authentic models in the organizations, the Jihadi model was selected as an inherent ...
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The purpose of the present research is to evaluate and validate the Jihadi organization model. Regarding the significance of inherent models in management and organization field and according to the necessity of using authentic models in the organizations, the Jihadi model was selected as an inherent model for evaluation and validation. It includes three behavioral, contextual, and structural dimensions of 23 components and 135 indicators. The model was evaluated using field method in Tehran municipality organization. Four districts of Tehran municipality were randomly selected through two-step clustering sampling method, of which 375 employees were selected as research sample for questionnaire distribution. Analyses using structural equation modeling, confirmatory factor analysis, path analysis, and fitting analysis demonstrated the Jihadi organization model is totally fitted and validated. Thus, it is recommended that further studies frequently verify the proposed model and apply in the organization if it is validated again.
Dariush Farid; Hojjatollah Sadeghi; Elahe Hajigol; Nadiya Zarmehr Parirooy
Volume 3, Issue 8 , August 2016, , Pages 534-543
Abstract
This research predicts through studying significant factors in customer relationship management and applying data mining in bank. Financial institutions and other firms in competitive market need to follow proper understanding of customer behavior. Customers’ data are analyzed to identify specific ...
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This research predicts through studying significant factors in customer relationship management and applying data mining in bank. Financial institutions and other firms in competitive market need to follow proper understanding of customer behavior. Customers’ data are analyzed to identify specific opportunities and investment, to classify and predict the behaviors; further, data are eventually used for decision-making. Therefore, data mining as knowledge exploring (discovery) approach plays a significant role through a variety of algorithms. This study classifies bank customers by using decision tree algorithm. Three decision tree models including ID3, C4.5, and CART were applied for classifying and finally for prediction. Results of simple sampling method and k-fold cross validation show that forecast accuracy of C4.5 decision tree using simple sampling was higher than other models. Thus, predicting customers’ behavior through C4.5 decision tree was considered the ideal prediction for bank.
