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Bonyadi Naeini, A., Yousef, S., Faezirad, M. (2016). Dynamic clustering of customers by Data Envelopment Analysis (DEA) - Discriminant Analysis (DA) and Artificial Neural Network (SOM). , 14(40), 165-187. doi: 10.22054/jims.2016.3914
Ali Bonyadi Naeini; Saeed Yousef; Mohammad Ali Faezirad. "Dynamic clustering of customers by Data Envelopment Analysis (DEA) - Discriminant Analysis (DA) and Artificial Neural Network (SOM)". , 14, 40, 2016, 165-187. doi: 10.22054/jims.2016.3914
Bonyadi Naeini, A., Yousef, S., Faezirad, M. (2016). 'Dynamic clustering of customers by Data Envelopment Analysis (DEA) - Discriminant Analysis (DA) and Artificial Neural Network (SOM)', , 14(40), pp. 165-187. doi: 10.22054/jims.2016.3914
Bonyadi Naeini, A., Yousef, S., Faezirad, M. Dynamic clustering of customers by Data Envelopment Analysis (DEA) - Discriminant Analysis (DA) and Artificial Neural Network (SOM). , 2016; 14(40): 165-187. doi: 10.22054/jims.2016.3914

Dynamic clustering of customers by Data Envelopment Analysis (DEA) - Discriminant Analysis (DA) and Artificial Neural Network (SOM)

مطالعات مدیریت صنعتی
Article 7, Volume 14, Issue 40, April 2016, Pages 165-187    PDF (1.19 M)
Document Type: Research Paper
DOI: 10.22054/jims.2016.3914
Authors
Ali Bonyadi Naeini; Saeed Yousef; Mohammad Ali Faezirad
Abstract
Today evaluation of customers to classify the quality of providing services is one of the main challenges of decision-makers in different organizations. It is difficult to respond to all customers’ demands because of increasing volume of them. On the other hand, in current competitive markets, customers are considered as capital of organizations. This issue results in purposefully study on different groups of customers in competitive markets. One of the effective ways to study the customers and provide the optimism service to them is grouping the market and clustering the customers. In this research first customers classified in appropriate clusters using neural network techniques SOM in order to provide purposefully service , so each customer can deliver proper service according to its cluster. Then by the proposed model in the paper the membership of each client in the appropriate cluster can be predicted by using DEA-DA technique. This model has provided dynamic clustering process for organizations so that by which new customers will be assessed at any moment and their proper cluster is determined with reasonable accuracy.
Keywords
Clustering; Discriminant Analysis (DA); data envelopment analysis (DEA); Artificial Neural Network; self-organizing map (SOM)
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