Volume 3, Issue 4 (2014)
ORMR 2014, 3(4): 115-136 |
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ebadi jalal M, hosseini M. Presenting a Model for Analyzing Behaviors of Answering Agents to Customers' Calls in Call Centers: Case Study on Call Center Agents' Data of One of the Companies Affiliated To Automobile Industry. ORMR 2014; 3 (4) :115-136
URL: http://ormr.modares.ac.ir/article-28-2228-en.html
URL: http://ormr.modares.ac.ir/article-28-2228-en.html
1- M.A. student of IT Engineering, IT Group - Industrial Engineering Department K. N. Toosi University of Technology, Tehran, Iran
2- Assist Professor, IT Group - Industrial Engineering Department K. N. Toosi University of Technology, Tehran, Iran
2- Assist Professor, IT Group - Industrial Engineering Department K. N. Toosi University of Technology, Tehran, Iran
Abstract: (9693 Views)
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.
Keywords: call center, K-means clustering, Customer relationship management, Human Resource Management
Article Type: scientific research |
Subject:
a
Received: 2014/02/25 | Accepted: 2014/10/6 | Published: 2015/02/20
Received: 2014/02/25 | Accepted: 2014/10/6 | Published: 2015/02/20
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