• Title/Summary/Keyword: Demand-Supply Curve

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The Changing Patterns of Demand-Supply and Role of Mineral Resources in Economic Growth during Industrialization of the Republic of Korea (한국공업화과정(韓國工業化過程)에서의 광물자원(鑛物資源)의 수급구조변화(需給構造變化)와 경제성장(經濟成長)에 있어서의 역할(役割))

  • Yun, Suckew
    • Economic and Environmental Geology
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    • v.18 no.1
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    • pp.65-92
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    • 1985
  • A total of 12 mineral commodities significant in domestic output, economy and/or strategy of the Republic of Korea are chosen to examine the structural changes in production and demand-supply of these minerals during the last two decades of her industrialization. These include iron and manganese ores as the raw materials for iron and steel making, copper, zinc and tungsten ores among other non-ferrous metallic minerals, limestone (cement), kaolin, talc, pyrophyllite and graphite among other non-metallic minerals, and anthracite coal as the only domestic source of fossil energy. These are reviewed historically in time-series based on the statistical data which are tabulated and graphed in terms of domestic output, export, import, apparent demand-supply, its increasing rate, and self-sufficiency rate of each commodity. The increasing rates of demand-supply (IRDS) of some more important commodities are compared with those of Gross Domestic Production (GDP) and Economic Growth Rate (EGR) to evaluate how the IRDS contributed to the GDP and EGR. The major results revealed are as follows: Among the 12 commodities, the domestic output of 8 commodities appeared to have grown with steady upward trends: they are ores of lead, zinc and tungsten, limestone (cement), kaolin, talc, pyrophyllite and anthracite coal. Two commodities, ores of iron and copper, continued with unchanging or slightly declining trends and varied fluctuations, in spite of their cardinal importance to the heavy industry and strategy of Korea. The remaining two, graphite and manganese ore, have gradualy declined in domestic output in which the former has still enough resource potential but the latter has not and virtually ceased its domestic output. Trade patterns for mineral commodities in the Republic of Korea during the last two decades have changed greatly, being marked by a shift from mineral-exporting to mineral importing, mainly because of increasing consumption of mineral raw materials for industrialization rather than beceuse of decreasing output of domestic mineral commodities in quantity. In terms of trade patterns, the 12 commodities concerned in this study can be classified into the following four groups. The 1st group - ores of lead and tungsten have only been exported without imports. The 2nd group - amorphous graphite, and pyrophyllite have mainly been exported but partly been imported. The 3rd group - kaolin, talc and crystalline graphite have equally been exported and imported, but quantity of imports have rapidly been increased with time. The 4th group - ores of iron, manganese and zinc have shifted from exports to imports during the industrialization, particularly owing to the initiation of iron and steel making by the Pohang Iron and Steel Company in the middle 1970' s and the new establishment of the Onsan Zinc Refinery in the late 1970' s. All of the 12 commodities under considerations were far above 100% in self-sufficiency rate before or in the early 1960' s. Recently, however, most of them have been declined to below 100% except for those of limestone (cement) and pyrophyllite. It is particularly serious to identify that the self-sufficiency rates of the three important metallic minerals, iron, copper and manganese ores in 1982 appeared to be 5.1%, 0.5%, and 0.01%, respectively. The average self-sufficiency rate of the total domestic minerals produced in 1982 was 14.4% (in value) for that year. Mining industry appeared to be extremely high in its intermediate demand rate whereas its intermediate input rate to be quite low indicating that mineral raw materials have been exerted strong forward linkage effects upon the other industries rather than backward linkage effects. In comparing the curves of increasing rates of demand-supply of several major minerals - iron ore, manganese ore, copper ore, limestone (cement), kaolin, and anthracite coal - with those of Gross Domestic Production and Economic Growth Rate drawn on every graph, it is clearly shown that the curves of increasing rates of demand-supply comprise around 6 to 7 periods of cycles which roughly harmonious with those of the curves of GDP and EGR, except for the curve of anthracite coal of which the configuration seems to have resulted from the (artificial) government's mineral policy rather than from economic free market mechanism. The harmonic feature of these curves well suggests that the increasing rates of demand-supply of major minerals have been significantly contributed to the GDP and EGR. In addition, the wider amplitudes of the iron, manganese and copper curves than those of the limestone (cement) and kaolin curves indicate that the contribution of the former, metallic commodities, has been greater than that of the latter, non-metallic commodities.

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A Study on the Estimation Method of Daily Load Curve for the Optimization Design and Economic Evaluation of Stand-alone Microgrids Based on HOMER Simulation in Off-Grid Limiting the Supply of Electricity (제한급전하는 오프그리드의 독립형 마이크로그리드 최적 설계 및 경제성 평가를 위한 일부하곡선 추정 방안에 관한 연구)

  • Nam, Yong-Hyun;Youn, Seok-Min;Kim, Jung-Hoon;Hwang, Sung-Wook
    • The Transactions of The Korean Institute of Electrical Engineers
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    • v.68 no.1
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    • pp.27-35
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    • 2019
  • There is a growing interest in various microgrid solutions that supply electricity 24 hours a day to off-grid areas where are not connected with the main grid, and Korea has many positive effects by constructing overseas microgrids as a country operating the emission trading scheme. Since it is not clear how to obtain load curves that is one of the inputs of the HOMER used to design a microgrid optimization plan, or it is necessary to examine whether electricity is supplied to the peak load level of the areas where have not received the electricity benefits from the viewpoint of the demand management, a methodology should be developed to know the load composition ratio and the shape of the daily load curve. In this paper, the relative coefficient and average load information for each load group obtained from the survey are used besides peak load and total average load. A mathematical model is proposed to derive the load composition ratio in the form of a Quadratic Programming and the load forecasting is performed using simple linear regression with future indicators. The effectiveness of the proposed method is confirmed for the Philippine island region supported by Korea Energy Agency and the Asian Development Bank.

ASP 매출 변화에 관한 동태적 분석: SD 기법을 활용한 버전 차별화 전략을 중심으로

  • Kim, Sang-Jun;Lee, Jin-Su;Lee, Sang-Geun
    • 한국경영정보학회:학술대회논문집
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    • 2008.06a
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    • pp.454-471
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    • 2008
  • This study suggests the dynamic pricing model which reveals the organic relationship between ASP (Application Service Provider) price and the related factors, using system dynamics methodology. Basically, we applied the law of supply and demand for analyzing price changes. Then, we deducted ASP price, focusing on fixed cost and variable cost. We also researched the customer's buying behavior according to version differentiation policy. In the version policy, we set up the proposition about customer's satisfaction and willingness-to-pay, using option system. As a result, this research designed the simulation model which analyzes the changes of the sales according to version differentiations and customer's willingness-to-pay. Through this research, we can find effective version differentiation strategies. This paper also found that the larger the number of package, the greater the demand and customer's willingness-to-pay. The increase of the number of package causes the increase of the sales. The increase of the sale is not exactly relative to the number of package. Drawing S-curve, the sales was increased. This dynamic pricing model suggests the ground that the ASP price changes based on the existing version differentiation theory and the demand of customers can affect the changes of the sales. We expect that this model suggests a clear standard of ASP pricing by combining real cases.

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Demand Concentration in the Korean Digital Online Movie Market (디지털 온라인 영화시장의 수요 집중화 경향)

  • Choi, Sung-Hee
    • The Journal of the Korea Contents Association
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    • v.21 no.8
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    • pp.69-78
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    • 2021
  • With technological development including digitization, movie demand and supply in digital online movie market are increasing. This study aims to explore demand concentration of the digital online movie market, which is characterized by product variety compared to cinemas. Major findings of the empirical analysis on the TV VOD data during the recent seven years(2013 ~ 2019) are as follows. First, the analysis on 1,137 titles reveals that movie demand of theatrical market is more concentrated than that of TV VOD. Second, absolute long tail index of TV VOD, measured by the download number of indie & artistic movies(niche product), is increasing as more such movies are released in the market. However, both relative long tail index, measured by the share of indie & artistic movie demand, and top-ranked movies' share do not show consistent increase or decrease trend. Third, regression analysis exhibits that the relationship between demand concentration and market size is insignificant for TV VOD market. This study might have usefulness in that it provides empirical evidence for the nature of the Korean digital online movie market.

A Study on Water Demand Forecasting Methods Applicable to Developing Country (개발도상국에 적용 가능한 물수요 예측 방법 연구)

  • Sung-Uk Kim;Kye-Won Jun;Wan-Seop Pi;Jong-Ho Choi
    • Journal of Korean Society of Disaster and Security
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    • v.16 no.4
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    • pp.75-84
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    • 2023
  • Many developing countries face challenges in estimating long-term discharge due to the lack of hydrological data for water supply planning, making it difficult to establish a rational water supply plan for decision-making on water distribution. The study area, the Bandung region in Indonesia, is experiencing rapid urbanization and population concentration, leading to a severe shortage of freshwater. The absence of water reservoir prediction methods has resulted in a water supply rate of approximately 20%. In this study, we aimed to propose an approach for predicting water reservoirs in developing countries by analyzing water safety and potential water supply using the MODSIM (Modified SIMYLD) network model. To assess the suitability of the MODSIM model, we applied the unit hydrograph method to calculate long-term discharge based on 19 years of discharge data (2002-2020) from the Pataruman observation station. The analysis confirmed alignment with the existing monthly optimal operation curve. The analysis of power plant capacity revealed a difference of approximately 0.30% to 0.50%, and the water intake safety at the Pataruman point showed 1.64% for Q95% flow and 0.47% for Q355 flow higher. Operational efficiency, compared to the existing reservoir optimal operation curve, was measured at around 1%, confirming the potential of using the MODSIM network model for water supply evaluation and the need for water supply facilities.

Demand Shifting or Ancillary Service?: Optimal Allocation of Storage Resource to Maximize the Efficiency of Power Supply (Demand Shifting or Ancillary Service?: 효율적 재생발전 수용을 위한 에너지저장장치 최적 자원 분배 연구)

  • Wooyoung Jeon
    • Environmental and Resource Economics Review
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    • v.33 no.2
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    • pp.113-133
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    • 2024
  • Variable renewable energy (VRE) such as solar and wind power is the main sources of achieving carbon net zero, but it undermines the stability of power supply due to high variability and uncertainty. Energy storage system (ESS) can not only reduce the curtailment of VRE by load shifting but also contribute to stable power system operation by providing ancillary services. This study analyzes how the allocation of ESS resources between load shifting and ancillary service can contribute to maximizing the efficiency of power supply in a situation where the problems caused by VRE are becoming more and more serious. A stochastic power system optimization model that can realistically simulate the variability and uncertainty of VRE was applied. The analysis time point was set to 2023 and 2036, and the optimal resource allocation strategy and benefits of ESS by varying VRE penetration levels were analyzed. The analysis results can be largely summarized into the following three. First, ESS provides excellent functions for both load shifting and ancillary service, and it was confirmed that the higher the reserve price, the more limited the load shifting and focused on providing reserve. Second, the curtailment of VRE can be a effective substitute for the required reserve, and the higher the reserve price level, the higher the curtailment of VRE and the lower the required amount of reserve. Third, if a reasonable reserve offer price reflecting the opportunity cost is applied, ESS can secure economic feasibility in the near future, and the higher the proportion of VRE, the greater the economic feasibility of ESS. This study suggests that cost-effective low-carbon transition in the power system is possible when the price signal is correctly designed so that power supply resources can be efficiently utilized.

Changes in Korean Maternity Protection Law and Labor Market Outcomes for Young Women (모성보호법 개정과 가임기 여성의 노동시장 성과)

  • Kim, Inkyung
    • Journal of Labour Economics
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    • v.33 no.3
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    • pp.47-88
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    • 2010
  • Focusing on the Korean experience, particularly a recent amendment which extends maternity leave and increases financial benefits during maternity and childcare leave, this paper evaluates how such an expansion of benefits affects the employment and the hourly wages of young wages of childbearing age. Empirical results from a difference--in-difference-in-differences model having older warren, older men, and young men simultaneously as the control group suggest that neither the employment nor the hourly wages of young women are affected. This implies that the law change does not cause shifts in the labor supply curve and the labor demand curve for young women.

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General Introduction of American Ginseng Indigenous in USA and Canada

  • Park, Chung-Heon;Bang, Kyung-Hwan;Park, Chun-Geun;Sung, Jung-Sook;Song, Won-Seob
    • Plant Resources
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    • v.6 no.3
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    • pp.165-169
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    • 2003
  • American ginseng (Panax quinquefolium) is herbaceous perennial plants indigenous to North American forests. This is highly valued as medicinal herbs with a long history of collection from wild populations since 1716. Wild American ginseng distributed from Quebec in Canada to northern Florida in USA. A heavy concentration is found in the Appalachian mountains, although wild American ginseng is considered endangered. The price paid for field cultivated ginseng has dropped dramatically in the past 10 years, while the price for wild or woods cultivated ginseng has rised significantly. The price curve for ginseng resembles a roller coaster, reflecting not only supply and demand but many other factors. This information will be useful to understand American ginseng compared to Korean ginseng.

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A Conceptual Framework of IoT Case Study (IoT 사례분석을 위한 개념적 틀 제시)

  • Jeon, Ka Young;Lee, Jang Hyuk;Oh, Jungsuk
    • Asia-Pacific Journal of Business Venturing and Entrepreneurship
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    • v.10 no.3
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    • pp.123-131
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    • 2015
  • With a prospective of rapid deployment of IOT, a systematic approach to derive a business strategy for various possible scenarios of IOT applications is in great demand. In this paper, a conceptual framework that can be utilized for the purpose of assessing the market potential and of setting up an initial business strategy for IOT deployment is suggested. The framework consists of utilization of well-known value curve analysis, ecosystem analysis and house of quality tools. The value curve analysis is utilized to identify value-enhancing components of consumers as well as relative strengths of suppliers. The ecosystem analysis is used to identify relevant players of the supply chain and their mutual relationships. The house of quality is suitable for developing the initial business strategy of the supplier by converting consumer requirements identified by value curve analysis into technical requirements for the supplier. In this paper, we applied our proposed framework to two services that have high potentiality of being benefited by IOT: car-sharing service and telehealth service.

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Estimation of regional flow duration curve applicable to ungauged areas using machine learning technique (머신러닝 기법을 이용한 미계측 유역에 적용 가능한 지역화 유황곡선 산정)

  • Jeung, Se Jin;Lee, Seung Pil;Kim, Byung Sik
    • Journal of Korea Water Resources Association
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    • v.54 no.spc1
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    • pp.1183-1193
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    • 2021
  • Low flow affects various fields such as river water supply management and planning, and irrigation water. A sufficient period of flow data is required to calculate the Flow Duration Curve. However, in order to calculate the Flow Duration Curve, it is essential to secure flow data for more than 30 years. However, in the case of rivers below the national river unit, there is no long-term flow data or there are observed data missing for a certain period in the middle, so there is a limit to calculating the Flow Duration Curve for each river. In the past, statistical-based methods such as Multiple Regression Analysis and ARIMA models were used to predict sulfur in the unmeasured watershed, but recently, the demand for machine learning and deep learning models is increasing. Therefore, in this study, we present the DNN technique, which is a machine learning technique that fits the latest paradigm. The DNN technique is a method that compensates for the shortcomings of the ANN technique, such as difficult to find optimal parameter values in the learning process and slow learning time. Therefore, in this study, the Flow Duration Curve applicable to the unmeasured watershed is calculated using the DNN model. First, the factors affecting the Flow Duration Curve were collected and statistically significant variables were selected through multicollinearity analysis between the factors, and input data were built into the machine learning model. The effectiveness of machine learning techniques was reviewed through statistical verification.