رویکرد هوش کسب و کار(هوش تجاری) برای حمایت از ایجاد استراتژی مدیریت خدمات ISP
|کد مقاله||سال انتشار||تعداد صفحات مقاله انگلیسی||ترجمه فارسی|
|674||2008||16 صفحه PDF||سفارش دهید|
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Publisher : Elsevier - Science Direct (الزویر - ساینس دایرکت)
Journal : Expert Systems with Applications, Volume 35, Issue 3, October 2008, Pages 739–754
The recent deregulation of telecommunication industry by the Taiwanese government has brought about the acute competition for Internet Service Providers (ISP). Taiwan’s ISP industry is characterized by the heavy pressure for raising revenue after hefty capital investments of last decade and the lack of knowledge to develop competitive strategies. To attract subscribers, all ISP dealers are making an all-out effort to improve their service management. This study proposes a Business Intelligence process for ISP dealers in Taiwan to assist management in developing effective service management strategies. We explore the customers’ usage characteristics and preference knowledge through applying the attribute-oriented induction (AOI) method on IP traffic data of users. Using the self-organizing map (SOM) method, we are able to divide customers into clusters with different usage behavior patterns. We then apply RFM modeling to calibrate customers’ value of each cluster, which will enable the management to develop direct and effective marketing strategies. For network resource management, this research mines the facility utilization over various administrative districts of the region, which could assist management in planning for effective network facilities investment. With actual data from one major ISP, we develop a BI decision support system with visual presentation, which is well received by its management staff.
Following the wave of global liberalization on telecommunication, the Taiwanese government deregulated the telecommunication industry in 1997. Soon after, a host of ISP (Internet Service Provider) companies entered the market to provide value-added services over the network infrastructure and compete for customers. Over the years, network bandwidth has been upgraded from narrowband to broadband, and the network population has grown substantially. It has since grown from 3% of national households at the end of 1996 to 38% at the end of 2002, and reaching 43% in June of 2006 (Institute for Information Industry, 2006). The growth shows a very steep curve in the first few years and a somewhat slower pace lately. During this period of fast growth, one can imagine the fury of ISP dealers in trying to offer various products with different fee schemes to attract subscribers. Initially, pricing strategies did work in recruiting new subscribers. However, after these years, the marketing emphasis may have shifted from product and cost orientation to that of customer needs. Users have started realizing that service quality may be more important than slight differences in fees. At the same time, ISP management has also realized the well-known fact that, the cost of developing a new customer is five to seven times the cost of retaining an existing one (Wayland & Cole, 1997). Management discovered that the need of network stability, data security, usage convenience, and personal preference should be high on the customers’ service agenda. This is also evidenced by McCue’s (2006) ISP satisfaction survey, which indicated that reliability is the most important factor for 78% of business customers (McCue, 2006), and more than half of them indicated they would switch to another ISP to get improved reliability. Thus, how to develop a service management strategy, which recognizes the shift from market share to percentage of life-long customers, has become a major issue for all ISP companies. The service management for the Telecom industry, in general, consists of customer and product management and resource management (Ericsson, 2005). It aims to ensure that customers experience quality and perceive the value of services delivered, and improve operational readiness for short time-to-market of new innovative services, as well as enhances utilization of existing network facilities. In order to develop a relevant management strategy in this increasingly competitive ISP market, management must understand customers’ needs and preferences and network facility utilization, before any proactive actions for customer care can be devised.
نتیجه گیری انگلیسی
This research examines the issue of developing an effective service management strategy that Taiwan’s ISP management is currently facing and proposes a BI process that could assist management in discovering in-depth knowledge of customer usage behaviors and network facility utilization. With IP traffics of each individual user as data, this process emphasizes significantly on data preprocessing and subsequent modeling. We present appropriate technologies along with each phase of the process to aid management in implementation, which includes a decision support system to assist management who are otherwise not capable of integrating various methodologies together. With the cooperation of a major ISP company in Taiwan, we demonstrated the detailed implementation of this process. The focus of this process is to discover insight knowledge of users’ network usage behaviors, the characteristics of their monetary contribution, and facility utilizations; so that services that are proactive and personalized may be developed. We applied data warehouse to facilitate the retrieval of data with different dimensionality, data mining to discover network behaviors knowledge, and RFM to characterize users’ monetary contribution. The mining results of nine customer clusters for the region reveal usage patterns that were unknown to the management before; hence this research does present a brand new concept to the company management in providing personalized services. These findings identify degree of usage, time of usage, and day of usage of each group and are of important information to both service department and sales department. These departments need to re-align resources of both work force and working hours. The analysis of RFM model on usage patterns provides further significant knowledge to management, which could lead them to formulate proper marketing strategies. For the network resource management, we apply data mining to find out network flow distribution among districts of the region, and map that district flow to the routers that service the region. Thus, any future investment on router and related resources will be more effectual and cost effective. For this particular case, we developed a decision support system that integrates all methodologies of the BI process together; so that management could perform analysis when they need to and on subjects they are interesting in. The result of system evaluation has indicated very positive responses from the management staff.