• Proceedings of the KIEE Conference
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• 1999.07c
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• pp.1202-1204
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• 1999

This paper proposes a value-based pricing suitable for deregulation situation in electricity market, where the value is measured based on the service quality such as system reliability. The proposed approach makes it possible to maximize social welfare, in that diversified service can produce the optimal combination set of demand and supply. The proposed pricing can also be applied to a direct load control.

• IE interfaces
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• v.25 no.1
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• pp.142-152
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• 2012

Recently, the postal service encounters the various changes in the overall mail environment including the reduction of letter volume, keen competition of the private parcel service and EMS, diversification of customers' demand and etc. In this environment, Korea Post is considering new concept of postal service in order to provide the mail service based on informatization and automation to a client and secures the predominance in competition. We analyze the current environment of postal service for applying the gCRM (Geographic Customer Relationship Management). We propose some possible application fields and present an efficient phased application plan for each field.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.38 no.2
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• pp.91-100
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• 2015

In this study, we propose an efficient two-phase heuristic policy, called an acceptance tolerance control policy, for Infrastructure as a Service (IaaS) cloud services that considers both the service provider and customer in terms of profit and satisfaction, respectively. Each time an IaaS cloud service is requested, this policy determines whether the service is accepted or rejected by calculating the potential for realizing the two performance objectives. Moreover, it uses acceptance tolerance to identify the possibility for error with the chosen decision while compensating for both future fluctuations in customer demand and error possibilities based on past decisions. We conducted a numerical experiment to verify the performance of the proposed policy using several actual IaaS cloud service specifications and comparing it with other heuristics.

• Journal of the Korea Safety Management & Science
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• v.19 no.4
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• pp.221-230
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• 2017

Recently, service quality must reflect several demands of customers who show rapid and various changes so as to be compared with the past. So, objective and rapid methods for them are necessary more. For them, first of all, service company must calculate their standard of service quality accurately by measuring service quality exactly. To measure service quality accurately, this researcher collected and analyzed data by survey for customers who are customers of logistics services, grasped potential satisfaction standard(P) by 5 point Likert scale and one survey for accurate classification of quality attributes through weighted customer satisfaction coefficient changing quality attributes by developing the study on Kano model and Timko's customer satisfaction coefficient, and suggested Potential Customer Satisfaction Improvement index(PCSI) for examining the improvement of customer satisfaction so as to utilize them as an index of differentiated and concrete measurement of service quality.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.33 no.9B
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• pp.822-831
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• 2008

This paper examines the theoretical and empirical technology diffusion processes to understand the Korean success in the internet access service markets. In order to do this, first, we propose an integrated demand diffusion model in terms of competition of inter-and intra-technologies and market structure as represented by the number of operators in the market. Second, by using the proposed model, we analyze the dynamic diffusion processes of Korean internet access services such as Narrow-band technology including Dial modem vs. Broad-band technology including ISDN, xDSL and Cable modem. The competition of inter-and intra-technologies as well as the extent of market competition has made a positive effect on the diffusion patterns of internet access demand. And also we propose, based on the proposed model and its empirical results, several implications for diffusion strategies and policies in the future of ICT market in Korea.

• Journal of Information Technology Services
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• v.17 no.3
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• pp.157-169
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• 2018

This study aims to examine the factors influencing user attitude toward Smart Home service as the demand of Smart Home service is increasing and it somewhat involves privacy risk. To this end, the research model includes five independent variables, trust in service provider, perceived privacy risk, self efficacy, interpersonal influence, and external influence, influencing the attitude toward Smart Home service. So, this study aims to analyze which variable is the most critical and influential among the five factors and suggest the direction of Smart Home industries. This study first reviews the literature on Smart Home services and describes its Korean situation. Data were collected from residents living in a smart apartment complex. The results show that (1) users have a very positive attitude toward Smart Home service in total, (2) trust in service providers, self efficacy, and interpersonal influence positively impact user attitude toward Smart Home service and interpersonal influence is the most influential variable, however, (3) perceived privacy risk and external influence dose not significantly impact it. These results imply that the role of service providers, self efficacy, and interpersonal influence are important factors on the user attitude toward Smart Home service. Finally, the study's findings and limitations are discussed and potential avenues for future research are suggested.

• The Journal of Information Systems
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• v.26 no.3
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• pp.171-185
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• 2017

Purpose Recently, there has been an increase in attempts to analyze social phenomena, consumption trends, and consumption behavior through a vast amount of customer data such as web search traffic information and social buzz information in various fields such as flu prediction and real estate price prediction. Internet portal service providers such as google and naver are disclosing web search traffic information of online users as services such as google trends and naver trends. Academic and industry are paying attention to research on information search behavior and utilization of online users based on the web search traffic information. Although there are many studies predicting social phenomena, consumption trends, political polls, etc. based on web search traffic information, it is hard to find the research to explain and predict tourism demand and establish tourism policy using it. In this study, we try to use web search traffic information to explain the tourism demand for major cities in Gangwon-do, the representative tourist area in Korea, and to develop a nowcasting model for the demand. Design/methodology/approach In the first step, the literature review on travel demand and web search traffic was conducted in parallel in two directions. In the second stage, we conducted a qualitative research to confirm the information retrieval behavior of the traveler. In the next step, we extracted the representative tourist cities of Gangwon-do and confirmed which keywords were used for the search. In the fourth step, we collected tourist demand data to be used as a dependent variable and collected web search traffic information of each keyword to be used as an independent variable. In the fifth step, we set up a time series benchmark model, and added the web search traffic information to this model to confirm whether the prediction model improved. In the last stage, we analyze the prediction models that are finally selected as optimal and confirm whether the influence of the keywords on the prediction of travel demand. Findings This study has developed a tourism demand forecasting model of Gangwon-do, a representative tourist destination in Korea, by expanding and applying web search traffic information to tourism demand forecasting. We compared the existing time series model with the benchmarking model and confirmed the superiority of the proposed model. In addition, this study also confirms that web search traffic information has a positive correlation with travel demand and precedes it by one or two months, thereby asserting its suitability as a prediction model. Furthermore, by deriving search keywords that have a significant effect on tourism demand forecast for each city, representative characteristics of each region can be selected.

• Journal of the Korean Operations Research and Management Science Society
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• v.38 no.3
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• pp.23-35
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• 2013

It is very important that the calculation of railroad track capacity in infrastructure investment analysis and train operation planning. The dwelling time is one of the factors that influence in railroad track capacity. Current research in dwelling time has been focusing on theoretical investigation, the state of the research in effective variable (dwelling time etc) is insufficient. In this paper, we clearly draw the concept of railroad track capacity and the estimate on modeling of relationship railway demand and dwelling time. Also, we compare and analyze the variation of railroad track capacity according to transit railway demand in Gyeongin Line (Guro~Inchon). This paper is expected to contribute for improving on the in-using equations and methods in train operation planning as well as for improving level of service on railway user.

• Economic and Environmental Geology
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• v.54 no.5
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• pp.515-533
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• 2021

Based on the supply location, demand location, and transportation network, aggregate supply-demand characteristics and aggregate distribution status were analyzed from the results of the closest distance, service areas, and location-allocation scenarios using GIS network analysis. As a result, it was found that the average transport distance of aggregates from the supplier was 6 km on average, the average range of 7 km for sand, and 10 km for gravel was found to reach the destination. In particular, the simulated service area covers about 92% in Seoul-Gyeonggi Province, 85% in Busan-Ulsan-Gyeongnam Province, and more than 90% in Daejeon-Sejong-Chungnam Province. These results have a significant implication in quantitatively interpreting primary data on aggregate supply-demand. Furthermore, these results suggest the possibility of a wide-area quantitative analysis of aggregate supply regions necessary for establishing a basic aggregate plan. The results also evaluated by the site-allocation scenario show that aggregate supply may be possible through companies less than 200 with large-amounts quarries, which is the 700 companies currently supplying small amounts of aggregates on the country. Therefore, in terms of distribution of aggregates, a policy approach is needed to form an appropriate market for regions with high and low density of aggregate supply services, and the necessity of regional distribution and re-evaluation is suggested through an aggregate supply analysis demand across the country. Furthermore, in analyzing the supply-demand network for the aggregate market, additional research is needed to establish long-term policies for the aggregate industry and related industries.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.8
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• pp.2783-2804
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• 2021

In the network function virtualization environment, dynamic changes in network traffic will lead to the dynamic changes of service function chain resource demand, which entails timely dynamic adjustment of service function chain resource configuration. At present, most researches solve this problem through virtual network function migration and link rerouting, and there exist some problems such as long service interruption time, excessive network operation cost and high penalty. This paper proposes a dynamic adjustment method of service function chain resource configuration for the dynamic changes of network traffic. First, a dynamic adjustment request of service function chain is generated according to the prediction of network traffic. Second, a dynamic adjustment strategy of service function chain resource configuration is determined according to substrate network resources. Finally, the resource configuration of a service function chain is pre-adjusted according to the dynamic adjustment strategy. Virtual network functions combination and virtual machine reusing are fully considered in this process. The experimental results show that this method can reduce the influence of service function chain resource configuration dynamic adjustment on quality of service, reduce network operation cost and improve the revenue of service providers.