Fateme Rahimi; mohammad vahid sebt; nasim ghanbar tehrani
Abstract
In today's competitive world, applying new techniques to business development has a great impact. The restaurant industry is no exception. Therefore, in this research, using new methods of knowledge discovery and data mining, customer data of chain restaurant is investigated. The purpose of this study ...
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In today's competitive world, applying new techniques to business development has a great impact. The restaurant industry is no exception. Therefore, in this research, using new methods of knowledge discovery and data mining, customer data of chain restaurant is investigated. The purpose of this study was to explore customer behavior patterns using data mining methods.In this study, one million and five hundred thousand customer records were reviewed in five branches of a chain restaurant and two stages of clustering modeling using RFM method and then classification modeling were performed on the data and the behavior rules chain restaurant customers were extracted. The results of this study have helped to identify the loyal and profitable customers of the chain restaurant which has led to the improvement of the profitability of the chain restaurant. One of the innovations of this research has been the communication between clustering and classification results.
Morteza Mohammadi; Tahmures Sohrabi
Abstract
The purpose of this study was to investigate the impact of electronic customer relationship management on customer satisfaction. This is a descriptive correlational study clearly based on the structural equation modeling (SEM). The participants of this study were 384 all customers who refer to the active ...
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The purpose of this study was to investigate the impact of electronic customer relationship management on customer satisfaction. This is a descriptive correlational study clearly based on the structural equation modeling (SEM). The participants of this study were 384 all customers who refer to the active electronic stores and benefit from their services and/or products. Participants completed the customer satisfaction Inventory (by Lee, and Turban, 2001) and the electronic customer relationship management Inventory (by Mogheimi, and Ramezani, 2011) Reliability and validity of these questionnaires was obtained. Results of the Pearson correlation showed that electronic customer relationship management and all customer satisfaction components are mutually correlated with each other (P<0/01(. Implementing structural equation modeling (SEM) for relationship between customer satisfaction and electronic customer relationship management tests, we found that the proposed model has a good fit and customer satisfaction is well explained by electronic customer relationship management. Also all of the model path coefficients were significant.
