• Human Ecology Research
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• v.53 no.3
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• pp.279-291
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• 2015

Fair trade is international trade that pays just wages, supplies stable and eco-friendly products, and supports the sustainable development of economies. This study examined consumers 'cognition of fair trade, product intention of fair trade products, and consumer demand for fair trade education. We compare these variables between Korean and Chinese consumers and explored variables that affect consumers' cognition, purchase intentions and consumer education demand. This study randomly targeted 428 adult consumers in Seoul (219) and Beijing (209) to grasp the demand of customer education and a purchasing intention for fair trade products. The results of this study are as follows. First, participants showed a low cognition of fair trade and purchase intention, while consumer demand for fair trade education on concept, campaign and effect had a comparatively higher level. Chinese consumers showed a higher level of purchase intention, but a lower level of consumer education demand for fair trade concepts. Second, a higher education level resulted in a higher cognition of fair trade by Korean consumers and more experienced Chinese consumers had a higher cognition. Third, the cognition of fair trade affected the purchase intentions positively for both in Korean and Chinese consumers. Finally, cognition and purchase intention showed positive effects of the consumer demand for fair trade education on concept, campaign, and effect.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.60 no.7
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• pp.1339-1346
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• 2011

This paper is developed to demand management scenario of energy consumption efficiency improvement, electricity generation efficiency improvement, network efficiency improvement, change of distribution ratio, movement of energy source, change of heating system, put of CHP to quantitatively assess to impact on energy use of demand management at the national level. This scenario can be applied Energy System Management model was developed based on Energy Balance Flow. In addition, effect analysis through built demand management scenario was quantitatively evaluated integrated demand management effectiveness of energy cost saving, CO2 emission reduction and energy savings of national level by calculating to primary energy source usage change in terms of integration demand management effect more often than not a single energy source separated electricity, heat and gas.

• Korean Journal of Artificial Intelligence
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• v.10 no.1
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• pp.27-32
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• 2022

As the need for eco-friendly transportation increases due to the deepening climate crisis, many local governments in Korea are introducing shared bicycles. Due to anxiety about public transportation after COVID-19, bicycles have firmly established themselves as the axis of daily transportation. The use of shared bicycles is spread, and the demand for bicycles is increasing by rental offices, but there are operational and management difficulties because the demand is managed under a limited budget. And unfortunately, user behavior results in a spatial imbalance of the bike inventory over time. So, in order to easily operate the maintenance of shared bicycles in Seoul, bicycles should be prepared in large quantities at a time of high demand and withdrawn at a low time. Therefore, in this study, by using machine learning, the linear regression algorithm and MS Azure ML are used to predict and analyze when demand is high. As a result of the analysis, the demand for bicycles in 2018 is on the rise compared to 2017, and the demand is lower in winter than in spring, summer, and fall. It can be judged that this linear regression-based prediction can reduce maintenance and management costs in a shared society and increase user convenience. In a further study, we will focus on shared bike routes by using GPS tracking systems. Through the data found, the route used by most people will be analyzed to derive the optimal route when installing a bicycle-only road.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.66 no.8
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• pp.1181-1186
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• 2017

The purpose of Demand Response is to reduce the cost of excessive resources and equipment by spontaneous load reductions at peak loads. Having enough power consumers participating in these schemes is key to achieving the goal. Demand Response Aggregator (DRA) is responsible for recruiting demand resources and managing them to participate in reducing the load. DRAs change the price elasticity of demand functions by providing incentives to demand response, thereby affecting price formation in the electricity market. In this paper, this process is modeled to analyze the relationship between DRA's strategic bidding and market outcomes and load reductions. It analyzes the results by applying to competition between DRAs, competition between DR and Gencos, and coexistence of DR load and non-DR load. It is noteworthy that we have found a phenomenon called the Balloon Effect.

• Perspectives in Nursing Science
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• v.13 no.2
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• pp.81-87
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• 2016

Purpose: The aim of this study is to review the nurse demand forecasting methods in empirical studies published during 1991~2014 and suggest ideas to improve the validity in nurse demand forecasting. Methods: Previous studies on nurse demand forecasting methodology were categorized into four groups: time series analysis, top-down approach of workforce requirement, bottom-up approach of workforce requirement, and labor market analysis. Major methodological properties of each group were summarized and compared. Results: Time series analysis and top-down approach were the most frequently used forecasting methodologies. Conclusion: To improve decision-making in nursing workforce planning, stakeholders should consider a variety of demand forecasting methods and appraise the validity of forecasting nurse demand.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.57 no.8
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• pp.1342-1348
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• 2008

One important objective of the electricity market is to decrease the price by ensuring stability in the market operation. Interconnected to this is another objective; namely, to realize sustainable consumption of electricity by equitably distributing the effects and benefits of participating in the market among all participants of the industry. One method that can help achieve these objectives is the ^{(R)}$demand-response program, - which allows for active adjustment of the loadage from the demand side in response to the price. The demand-response program requires a customer baseline load (CBL), a criterion of calculating the success of decreases in demand. This study was conducted in order to calculate undistorted CBL by analyzing the correlations between such external or seasonal factors as temperature, humidity, and discomfort indices and the amounts of electricity consumed. The method and findings of this study are accordingly explicated.

• Proceedings of the KIEE Conference
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• 2008.04c
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• pp.161-162
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• 2008

승객 여정선택형(On-demand Journey) 도시철도 시스템의 특징과 역할에 대하여 기술하고 기존 시스템과 차이점을 비교하여 대중교통 시스템으로서 새로운 서비스 개념의 도시철도시스템을 정의하였다. 아울러 국내외 기술개발 현황과 문제점에 대하여 기술하였다. 또한 미래의 교통수단으로서 전망에 대하여 기후변화 협약 및 지속가능한 교통수단으로서 개발가능성을 토대로 승객 여정선택형(On-demand Journey) 시스템 개념을 설정하였다.

• Information and Communications Magazine
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• v.13 no.5
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• pp.69-76
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• 1996

VOD 서비스는 가장 유망한 ATM 서비스의 하나로 간주되고 있으며 거의 모든 시럼 서비스에서 제공되고 있다. VOD 서비스는 응용분야 및 프로그램의 내용에 따라 여러 가지로 불리우고 있으며, 이러한 이유로 사람에 따라 서로 다른 뜻으로 쓰이는 경우가 많은 점을 고려하여 DAVIC 표준에서는 더 구체적으로 VOD 서비스를 분류하였다. DAVIC에 정의된 19가지의 서비스 중에서 VOD 서비스와 관련있는 것을 보면 Movies On Demand(MOD), Near Video On Demand(MOD), Karaoke On Demand(MOD), News On Demand(MOD)등이 있으며, 이외에도 유사한 서비스들이 있다. 본 고에서는 VOD 서비스를 제공하기 위하여 필요한 기술인 압축/복원, 전송 방식, 비디오 서버, Settop Box 등에 관하여 기술하였으며, 마지막으로 VOD 서비스 제공 예를 보였다.

• Journal of Institute of Control, Robotics and Systems
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• v.22 no.12
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• pp.991-994
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• 2016

This paper presents a load management method based on OpenADR of smart grid. Previous demand side algorithm is restricted on reducing peak power. But, in this paper we suggest a method of performing the energy-saving control according to the power price utilizing building automatic control system installed on the customer side in the case of hourly differential pricing signal is transmitted to the open automated demand response system. And, we showed the integrated demand management software for 3 buildings.

• Environmental and Resource Economics Review
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• v.16 no.1
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• pp.99-127
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• 2007

When the margin between available capacity and demand is thin in a liberalized electricity market, prices rise steeply and system reliability is threatened. The principal response to these circumstances is often an assumption that price spikes and electricity shortages are the result of a failure to build sufficient new supplying facilities. It is, of course, often the case that additional investments in generation and network facilities would improve reliability, and such investments are often needed. But focusing on additional generation and transmission facilities for restoring balance to the grid overlooks the essential fact that reliability is a function of the relationship between supply and demand, imposing unnecessary costs on electric system. When the relationship is out of balance, the search for solutions must consider not only investments supply-side resources but also cost-effective demand-side resources such as accelerated load management, efficiency measures, and price-responsive load programs. Integrating demand resources into electricity markets can add enormous value to the electric system, widening the capacity margin, lowering costs and enhancing system reliability at the same time. This paper studies several challenges now facing electricity markets: demand-side management-especially, economic effects of demand response, potential reliability problems, market and system operation, CBP market improvements and so on. The paper concludes with a series of policy recommendations in five areas: (i) The Effects of efficient improvement to incorporate demand responses and demand-side resources into modem electricity markets, (ii) Fosteing price based demand response and (iii) improving incentive based demand response, (iv) strengthen demand response analysis and valuation, (v) integrating demand response into resource planning and adopting enabling technologies.