• Journal of the Korea Academia-Industrial cooperation Society
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• v.8 no.1
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• pp.143-150
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• 2007

Using a panel data of Korea for $1979{\sim}2002$, this study investigates the determinants of the service sector employment share in Korea. In order to analyze the impact of macroeconomic factors on the service sector's employment share we estimate a simple panel model which is in line with Baumol's model. The panel GMM estimation results show that: 1) The increase in the share of service-related jobs in total employment tends to rise with GDP per capita, which confirms demand-bias hypothesis proposed by Clark. 2) We find that a crucial role in this process has been played by the productivity gap. As Baumol's hypothesis or Baumolis disease, the expansion of the employment share in services relative to industry is the direct consequence of services' lower productivity performances.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.8 no.2
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• pp.344-351
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• 2004

This paper describes a modeling of service composition manager based on TINA (Telecommunication Information Networking Architecture). The service composition function is mainly motivated by the desire to easily generate new service using existing services from retailers or third party service providers. The TNA-C (Consortium) specification for the service composition does not include the detailed composition procedures and its object models. In this paper, we propose a model of components for the service composition, which adapts a static composition feature in a single provider domain To validate the proposed modeling, we implemented prototype service composition function, which combines two multimedia services; a VOD (Video On Demand) service and a VCS (Video Conference Service) service. As a result, we obtain the specification of the detailed composition architecture between a retailer domain and a third-party service provider domain.

• Journal of Korea Society of Industrial Information Systems
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• v.22 no.5
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• pp.85-100
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• 2017

The Delivery Companies are Facing the Difficulty in their Delivery Services due to the Continuously Increasing Delivery Demand and Insufficient Supply of Delivery Persons to Satisfy the Demand. In Such Circumstances, the Delivery Companies have been Implementing the CSV Service by Introducing the Senior Parcel Delivery Service Creating Jobs for Senior Citizens. This Paper Investigated the Impact of the Quality of Senior Parcel Delivery Service, CSV Activities, and Individual Characteristic Factors of Consumers on the Customers' Confidence and Intention to Use the Delivery Service of Delivery Companies. For the Empirical Analysis, the Online/Offline Questionnaire Survey was Executed with the Individuals who used the Delivery Service and 216 Samples were Finally Selected for Empirical Analysis. In Accordance with the Analysis Results, the Speed, the Quality of Senior Parcel Delivery Service, had Significant Impact on the Customers' Confidence, but Safety had no Significant Impact on it. Next, the Sincerity of CSV Activity by Senior Parcel Delivery Service Companies Showed the Significant Impact on the Customers' Confidence. However, the Adequacy of CSV Activity had No Significant Impact on the Customers' Confidence. Furthermore, the Consumption Value and Ethical Consumption Propensity, the Individual Features of Consumers, Demonstrated the Significant Impact on the Customers' Confidence and also on the Customers' Confidence on and their Intention to use Senior Parcel Delivery Service Companies.

• Journal of Smart Tourism
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• v.3 no.2
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• pp.5-13
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• 2023

Because of increasing anxiety about infectious diseases and the demand for contactless service caused by the COVID-19 pandemic, it has become crucial for the tourism and hospitality sector to understand customers' psychological mechanism of contactless service during and post COVID-19. Thus, this paper proposes a conceptual model by integrating trust in the framework of the behavioral immune system. Interestingly, our study found that anxiety about infectious diseases during the COVID-19 pandemic has not only increased hotel customers' desire for contactless service and changed their behavioral intentions, but it has also impacted customers' trust in hotel service robots. Therefore, irrespective of how the hotel service environment changes, trust in technology has become the most fundamental factor for hotel customers' attitudes toward adopting technology. Based on the results, this paper provides salient theoretical and practical implications.

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

• Proceedings of the KSR Conference
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• 1998.05a
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• pp.211-218
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• 1998

The demand prediction becomes an essential mean to utilize efficiently finite traffic facilities and to provide the optimized schedules for transportation system. The demand prediction is one of the critical complex management schemes for distibuting resources of transportation service by means of computer system. The construction of a prediction model is based on data granulization, followed by processing the raw input data and evaluating the predicted output values. A large number of economic-social parameters are also to be implemented in conventional prediction models which are only based on a sequence of past data. The proposed prediction models are classified by static and dynamic characteristics and its performances are evaluated utilizing computer simulation.

• Korea Journal of Hospital Management
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• v.15 no.1
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• pp.13-26
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• 2010

A Health Promotion Center (HPC) whose capacity is partially idle causes inefficiency in resource usage of a country as well as the hospital itself. Meanwhile, Increased demand in HPC would lead to increased revenue for the HPC as well as reduced national expenditures on healthcare. We introduced a way to enhance revenue by Revenue Management (RM) on HPC services, in which demand forecasting and pricing strategies are considered. In addition, a real data analysis had been performed to evaluate the usefulness of the proposed approach.

• 한국IT서비스학회:학술대회논문집
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• 2006.11a
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• pp.360-365
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• 2006

VoD (Video-on-Demand) 서비스는 가입자가 원하는 컨텐츠를 실시간으로 전송하는 서비스의 형태이다. 오늘날은 방대한 양의 멀티미디어 데이터를 효율적으로 압축하고 보다 빠르게 전송할 수 있는 시스템의 발달이 가속화되고 있고 이는 VoD 서비스의 증가로도 이어지고 있다. 그러므로 가입자가 원하는 컨텐츠를 보다 효과적으로 제공할 수 있는 VoD 서비스의 방법을 찾는 것은 중요한 일이다. 본 논문에서는 기존의 NVoD (Near-VoD) 서비스 또는 TVoD (True-VoD) 서비스 만을 제공함으로서 생길 수 있는 단점을 없애고 장점만 살릴 수 있는 방법을 제안하였다. 이는 기존의 가입자단에 Buffer를 제공하여 NVoD를 TVoD화 함으로서 가능하게 하였다. 또한, 본 논문에서 제안한 방법이 필요한 버퍼의 크기를 제시하고 전체적인 알고리즘을 제시하여 이를 구체화 하였다.

• Health Policy and Management
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• v.1 no.1
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• pp.136-152
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• 1991

The study was conducted to project supply and demand of the physicians from year 1991 to year 2010 based on the analysis of supply and demand of the physicians up to year 1989. Results of the study will provide information for the physicians manpower planning of the 7th 5-year Economic Social Development Planning(1992-1996) and contribute to the overall health manpower planning for the 21the century. It is projected that physician will be oversupplied from the very near future based on the current productivity or underestimated based on the optimal productivity. Thus, it is desirable not to change size of training and education during the 7the 5-year planning period and re-examine the status of the physician manpower at the end of the 7th 5-year period taking into consideration medical services utilization pattern, patients' satisfaction, and physicians' productivity.

• Journal of Korea Society of Digital Industry and Information Management
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• v.10 no.3
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• pp.127-141
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• 2014

A Vehicle Tracking System consists of GPS tracking device which fits into the vehicle and captures the GPS location information at regular intervals to a central GIS server, and GIS tracking server providing three major responsibilities: receiving data from the GPS tracking unit, securely storing it, and serving this information on demand of the user. GPS based tracking systems supporting a multi-session processing among RMA, RM, and RCP can make a quick response to various services including other vehicle information between RSU and OBU on demand of the user. In this paper we design RSU lower layers and RCP applications in OBU for a multisession processing simulation and test message processing transactions among RMA-RM and RM-RCP. Furthermore, we implement the additional functions of handling access commands simultaneously on multiple service resources which are appropriate for the experimental testing conditions. In order to make a multi-session processing test, it reads 30 resource data,0002/0001 ~ 0002/0030, in total and then occurs 30 session data transmissions simultaneously. We insert a sequence number field into a special header of dummy data as a corresponding response to check that the messages are received correctly. Thus, we find that GIS service system with a multi-session processing is able to provide additional 30 services in a same speed of screen presentation loading while identifying the number of session processing of Web GIS service, the number of OBU service, and the speed of screen presentation loading by comparing a single session and a multi-session of GIS service system.