| Summary: | 碩士 === 元智大學 === 資訊管理研究所 === 91 === In the recent years, increasing numbers of the enterprises are investing in customer service implementation strategies and practices. Hence the call center plays a important role in an interactive channel between the enterprises and their customers. In this research, we use case study to the company supply teleservices and technologies, the major account of this company is TCC telecommunication cooperation. The primary purpose of the call center could be to receive calls for handling customer service questions and issues that typically have been placed to an 080 number or 888 short call. Followed increasing drastically numbers of the customer using the cellular phone, the traffic of incoming call to the center also increased and the organization had faced to extend. Until now there are almost 2000 employee work for the center. The managers have to distribute properly resource in the budget, included in sufficient personnel to answer calls, sufficient network service lines or trunks, and arrangement of center terminal equipment. The goal is to increase customer satisfaction and the first step to reach the goal is forecasting traffic accurately .
In this paper, forecasting model is constructed for incoming call volume to the center . Using an iterative procedure developed by seasonal Box-Jenkins approach. Data covering the period of January 2000 through June 2001 were used to develop the model. Forecasting with 95 percent probability limits were calculated for one year from July 2001, and were compared with the actual observations, the properties of the model are discussed in detail.
In order to improve the accuracy, an idea raised on the interview is how the monthly increasing numbers of the customer impact the traffic of incoming call to the center. Collecting the monthly data from the Ministry of Communication, data covering the period of May 2000 through December 2001. Originally constructed the forecasting model with transfer function, the cross correlation function technique is demonstrated to the customer-traffic relationship, with particular focus on the customer lag structure. The result shown that the numbers of the customer in the third month will significantly effect upon the present call volume .
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