• Journal of Information Technology Applications and Management
• /
• v.24 no.2
• /
• pp.81-96
• /
• 2017

Forecasting long-term mobile service demand is inevitable to establish an effective frequency management policy despite the lack of reliability of forecast results. The statistical forecasting method has limitations in analyzing how the forecasting result changes when the scenario for various drivers such as consumer usage pattern or market structure for mobile communication service is changed. In this study, we propose a dynamic model of the mobile communication service market using system dynamics technique and forecast the future demand for long-term mobile communication subscriber based on the dynamic model, and also experiment on the change pattern of subscriber demand under various scenarios.

• Journal of the Korea Safety Management & Science
• /
• v.19 no.3
• /
• pp.97-107
• /
• 2017

This research studies on the demand forecasting for service parts considering parts life cycle, that gets relatively less attentions in the field of forecasting. Our goal is to develop forecasting method robust across many situations, not necessarily optimal for a limited number of specific situations. For this purpose, we first extensively analyze the drawbacks of the existing forecasting methods, then we propose the new demand forecasting method by using these findings and reinforcement leaning technique. Using simulation experiments, we proved that the proposed forecasting method is better than the existing methods under various experimental environments.

• Journal of Intelligence and Information Systems
• /
• v.15 no.4
• /
• pp.37-51
• /
• 2009

One of the critical issues in the management of manufacturing companies is the efficient process of planning and operating service resources such as human, parts, and facilities, and it begins with the accurate service demand forecasting. In this research, service and sales data from the LCD monitor manufacturer is considered for an empirical study on Product Life Cycle (PLC) based service demand forecasting. The proposed PLC forecasting approach consists of four steps : understanding the basic statistics of data, clustering models using a self-organizing map, developing respective forecasting models for each segment, comparing the accuracy performance. Empirical experiments show that the PLC approach outperformed the traditional approaches in terms of root mean square error and mean absolute percentage error.

• Journal of the Korea Safety Management & Science
• /
• v.18 no.4
• /
• pp.161-169
• /
• 2016

In this research, we propose efficient demand forecasting scheme for intermittent demand. For this purpose, we first extensively analyze the drawbacks of the existing forecasting methods such as Croston method and Syntetos-Boylan approximation, then using these findings we propose the new demand forecasting method. Our goal is to develop forecasting method robust across many situations, not necessarily optimal for a limited number of specific situations. For this end, we adopt combining forecasting method that utilizes unbiased forecasting methods such as simple exponential smoothing and simple moving average. Various simulation results show that the proposed forecasting method performed better than the existing forecasting methods.

• Journal of the Korea Society of Computer and Information
• /
• v.7 no.1
• /
• pp.94-102
• /
• 2002

In this paper, we present a forecasting model for the spectrum demand which will be used for the mid/long-term spectrum forecasting in Korea. In specific, we present the bottom-up model with considering the customer not the previous top-down method. The Proposed model consists of service definition. classification of service characteristics, drawing representative service characteristic , forecasting of service demand, mapping with spectrum resource, verification and spectrum forecasting. The carried actions in each step is described in detail. For the validation of the model an example for the PCS environments is shown. traverse stepping stones for a variety of legitimate reasons.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
• /
• 2007.06a
• /
• pp.495-498
• /
• 2007

Recently, as REID Tag and Reader has been attached to, and wireless internet has been added to a mobile phone, the commercialization of Mobile RFID Service to obtain necessary information on daily life and use various applications by using mobile communication infra is drawing nearer. A new returns by Mobile RFID Service can be expected, however, the exact demand forecasting for the Mobile RFID Service is essential to induce mass investment from related communication enterprises. This study tries to get a foothold in enlarging the investment from related communication enterprises through demand forecasting for the Mobile RFID Service and to be helpful to the decision on their investment by predicting the demand on the service various Mobile RFID Service Models.

• Journal of Intelligence and Information Systems
• /
• v.18 no.4
• /
• pp.43-57
• /
• 2012

To enhance the competitive advantage in a constantly changing business environment, an enterprise management must make the right decision in many business activities based on both internal and external information. Thus, providing accurate information plays a prominent role in management's decision making. Intuitively, historical data can provide a feasible estimate through the forecasting models. Therefore, if the service department can estimate the service quantity for the next period, the service department can then effectively control the inventory of service related resources such as human, parts, and other facilities. In addition, the production department can make load map for improving its product quality. Therefore, obtaining an accurate service forecast most likely appears to be critical to manufacturing companies. Numerous investigations addressing this problem have generally employed statistical methods, such as regression or autoregressive and moving average simulation. However, these methods are only efficient for data with are seasonal or cyclical. If the data are influenced by the special characteristics of product, they are not feasible. In our research, we propose a forecasting framework that predicts service demand of manufacturing organization by combining Case-based reasoning (CBR) and leveraging an unsupervised artificial neural network based clustering analysis (i.e., Self-Organizing Maps; SOM). We believe that this is one of the first attempts at applying unsupervised artificial neural network-based machine-learning techniques in the service forecasting domain. Our proposed approach has several appealing features : (1) We applied CBR and SOM in a new forecasting domain such as service demand forecasting. (2) We proposed our combined approach between CBR and SOM in order to overcome limitations of traditional statistical forecasting methods and We have developed a service forecasting tool based on the proposed approach using an unsupervised artificial neural network and Case-based reasoning. In this research, we conducted an empirical study on a real digital TV manufacturer (i.e., Company A). In addition, we have empirically evaluated the proposed approach and tool using real sales and service related data from digital TV manufacturer. In our empirical experiments, we intend to explore the performance of our proposed service forecasting framework when compared to the performances predicted by other two service forecasting methods; one is traditional CBR based forecasting model and the other is the existing service forecasting model used by Company A. We ran each service forecasting 144 times; each time, input data were randomly sampled for each service forecasting framework. To evaluate accuracy of forecasting results, we used Mean Absolute Percentage Error (MAPE) as primary performance measure in our experiments. We conducted one-way ANOVA test with the 144 measurements of MAPE for three different service forecasting approaches. For example, the F-ratio of MAPE for three different service forecasting approaches is 67.25 and the p-value is 0.000. This means that the difference between the MAPE of the three different service forecasting approaches is significant at the level of 0.000. Since there is a significant difference among the different service forecasting approaches, we conducted Tukey's HSD post hoc test to determine exactly which means of MAPE are significantly different from which other ones. In terms of MAPE, Tukey's HSD post hoc test grouped the three different service forecasting approaches into three different subsets in the following order: our proposed approach > traditional CBR-based service forecasting approach > the existing forecasting approach used by Company A. Consequently, our empirical experiments show that our proposed approach outperformed the traditional CBR based forecasting model and the existing service forecasting model used by Company A. The rest of this paper is organized as follows. Section 2 provides some research background information such as summary of CBR and SOM. Section 3 presents a hybrid service forecasting framework based on Case-based Reasoning and Self-Organizing Maps, while the empirical evaluation results are summarized in Section 4. Conclusion and future research directions are finally discussed in Section 5.

• Journal of Korean Society of Industrial and Systems Engineering
• /
• v.42 no.3
• /
• pp.109-115
• /
• 2019

Most demand forecasting studies for telecommunication services have focused on estimating market size at the introductory stage of new products or services, or on suggesting improvement methods of forecasting models. Although such studies forecast business growth and market sizes through demand forecasting for new technologies and overall demands in markets, they have not suggested more specific information like relative market share, customers' preferences on technologies or service, and potential sales power. This study focuses on the telecommunication service industry and explores ways to calculate the relative market shares between competitors, considering competitive situations at the introductory stage of a new mobile telecommunication service provider. To reflect the competitive characteristics of the telecommunication markets, suggested is an extended conjoint analysis using service coverage and service switching rates as modification variables. This study is considered to be able to provide strategic implications to businesses offering existing service and ones planning to launch new services. The result of analysis shows that the new service provider has the greatest market share at the competitive situation where the new service covers the whole country, offers about 50% of existing service price, and allows all cellphones except a few while the existing service carrier maintains its price and service and has no response to the new service introduction. This means that the market share of the new service provider soars when it is highly competitive with fast network speed and low price.

• Korean Management Science Review
• /
• v.19 no.2
• /
• pp.125-137
• /
• 2002

The telecommunications market is expanding rapidly and becoming more substitutive. In this environment, demand forecasting is very difficult, yet important for both practitioners and researchers. in this paper, we adopt the modeling approach proposed dy Jun and Park ［6］. The basic premise is that demand patterns result from choice behavior, where customers choose a product to maximize their utility. We apply a choice-based substitutive diffusion model to the Korean mobile telecommunication service market where digital service has completely replaced analog service. In comparison with Bass-type multigeneration models. our model provides superior fitting and forecasting performance. The choice-based model is useful in that it enables the description of such complicated environments and provides the flexibility to include marketing mix variables such as price and advertising in the regression analysis.

• Korean Management Science Review
• /
• v.25 no.1
• /
• pp.29-41
• /
• 2008

In the mobile communication service market, this study represents an attempt to forecast the subscribers of the IMT-2000 service market using the questionnaire of experts which is the qualitative technique is used. In this study, by using the substitution model of next generations among products in order to analyze the IMT-2000 demand of service, a demand was predicted. And by estimating the market demand prospect in which it becomes the important factor of the IMT-2000 service diffusion according to each bandwidth frequency the politically necessary approaching direction about the frequency was presented. It will be able to become the important part to not only the business carrier but also the policy maker to examine a prospect toward the subscriber of the IMT-2000 service. As a result, the market demand was exposed to be most big when the SKT 800MHz, and the KTF 800(900)MHz were used as the additional frequency. And it was likely to reach to the IMT-2000 number of subscribers to about 35.750 thousand peoples in the future at 2015.