• Journal of Korean Institute of Industrial Engineers
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• v.13 no.2
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• pp.65-77
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• 1987

Congestion occurs whenever users interfere with each other, while competing for scarce resources. In a congested market, such as a telecommunication service market, users of telecommunication services incur costs in using the service in addition to the price. The user's own time costs involved in learning to use the service, waiting for the service, and making use of the service are typically greater than the price of telecommunication services. A market equilibrium analysis is performed in which a method for user demand aggregation is developed. The effects of price changes on user demands and market demands for congested services are examined. It is found that total market demands may increase as the price for less-congested services increase under certain demand conditions. This suggests that a nonuniform pricing scheme for a congested service may improve the utilization of the congested system. The sign of price cross-elasticity for congested services is show to vary with demand conditions. A possible complementary property of congested services is found and the implication of such a property is discussed. It is argued that such a complementary property may lead to a cross subsidy in a market with congestion. Finally, comparisons between uniform pricing and nonuniform pricing policies are made. A specific numerical example is given to show that a nonuniform pricing policy may be Pareto superior to a uniform pricing policy.

• Journal of Energy Engineering
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• v.29 no.1
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• pp.85-99
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• 2020

This article analyzes the influence of sectoral system of innovation(i.e. technological regime, market demand, networks, and institution) on innovative performances(i.e. product-, process-, organizational-, marketing-, and environmental- innovation) in Korean environmental industry, conducting a multiple regression analysis based on survey data from 201 Korean environmental companies. As the results, product innovation is positively influenced by internal technology accumulation and market demand response, while not affected by external knowledge utilization, market competition, networks among market and non-market agents, government support and regulation. Process innovation is positively influenced by internal technology accumulation, networks among non-market agents and regulation, but not by external knowledge utilization, market demand response, market competition, networks among market agents, and government support. While organizational innovation is positively influenced by internal technology accumulation, external knowledge utilization and regulation, it is not affected by market demand response, market competition, networks among market and non-market agents, and government support. While marketing innovation is positively influenced by internal technology accumulation, networks among non-market agents, and government support, it is not affected by external knowledge utilization, market demand response, market competition, networks among market agents, and regulation. Environmental innovation is positively influenced by external knowledge utilization and regulation, but negatively influenced by market competition. It is not affected by internal technology accumulation, market demand response, networks among market and non-market agents, and government support. Such results suggests the following policy implications. First, it is necessary to expand the sphere of relating markets through the application of convergence technology, new regulations, and overseas markets. Second, reinforcing ecosystems among environmental market agents through demand-linked joint R&D should be revitalized. Third, it is needed to strengthen more supporting policies rather than regulation. This article has the limitation of using the survey data. And further researches on the environmental sectoral system of innovation structure itself will be tried.

• Journal of Distribution Science
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• v.11 no.9
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• pp.31-34
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• 2013

Purpose - This paper aims to explain that the Chinese distribution market will continue to bring tremendous business opportunities to commercial enterprises, given the relatively strong economic fundamentals and substantial government-led measures to boost domestic demand. Research design, data, methodology - A survey was conducted on China's retail market data during 2012. By empirically analyzing the data for retail sales of online markets and franchises, we conclude that the online retail market in China will continue to grow. Results - Based on data from 2012, 2013 is expected to be a challenging year for the retail sector, as both external and internal pressure is likely to persist. This paper outlines some major challenges facing retailers in China. Conclusions - The study shows that retailers in the Chinese market will face some major challenges: 1) the Chinese retail market is considerably affected by an uncertain economic outlook 2) an unfair environment of competition exists and 3) product safety is a serious issue. However, in the future, China's retail market will continue to bring tremendous business opportunities to commercial enterprises, given the relatively strong economic fundamentals and substantial government-led measures to boost domestic demand.

• Journal of the Korea Institute of Building Construction
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• v.14 no.6
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• pp.631-637
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• 2014

Recently, following the application of modular housing techniques to not only residential sector, but also to business sector, the scope of modular housing market b expanding. In the case of other developed countries, such markets are entering into the maturity stage, though the market in Korea is not fully formed yet. Thus, it is difficult to check its trend to estimated mid- to long-term prospects of the market. In this context, the study predicted demand of the modular housing market by using a non-linear prediction model based on time series analysis. To get the prospects for the modular housing market, the quantity of housing supply was estimated based on the estimated quantity of newly built housings, and assumed that a portion of the supplied quantity would be the demand for modular housings. Based on the assumption of demand for modular housings, several scenarios were analyzed and the prospects of the modular housing market was obtained by utilizing the non-linear prediction model.

• Proceedings of the KIEE Conference
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• summer
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• pp.671-673
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• 2004

Demand Response Programs (DRP) are critical to the operation of efficient and competitive energy markets. and provide critical market improvements to Independent System Operators (ISO). To all energy market Participants, they Provide savings and cost reductions when end users have the ability to respond to wholesale prices. Now, in the competitive electricity market, DRP is classified by Emergency and Economic DRP to reduce costs and maintain reliability. In this paper, we survey the trend of Demand Response Program over the world and compare the practical performance among the markets in US.

• Journal of Electrical Engineering and Technology
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• v.8 no.1
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• pp.46-52
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• 2013

Economic properties of an integrated wind power plant (WPP) and the demand response (DR) programs in the sample electricity market are studied. Time of use (TOU) and direct load control (DLC) are two of the DR programs that are applied in the system. The influences of these methods and the incentive payments by market operator's (MOs) with variable elasticity are studied. It is observed that DR with TOU and DLC programs together yields better revenue and energy saving for MOs.

• Proceedings of the Korea Inteligent Information System Society Conference
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• 2003.05a
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• pp.255-263
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• 2003

A multi-agent system designed to represent newly deregulated electricity markets in the USA is aimed at testing the capability of the multi-agent model to replicate the observed price behavior in the wholesale market and developing a smart business intelligence which quickly searches the optimum offer strategy responding to the change in market environments. Simulation results show that the optimum offer strategy is to withhold expensive generating units and submit relatively low offers when demand is low, regardless of firm size; the optimum offer strategy during a period of high demand is either to withhold capacity or speculate for a large firm, while it is to be a price taker a small firm: all in all, the offer pattern observed in the market is close to the optimum strategy. From the firm's perspective, the demand-side participation as well as the intense competition dramatically reduces the chance of high excess profit.

• Journal of Korea Port Economic Association
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• v.38 no.3
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• pp.87-104
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• 2022

Considering the complex structure and high volatility in the shipping market, it is important to investigate the connectedness amongst influencing factors. This study explores the dynamic relationship between supply-demand factors and shipping freight indices. We choose Capesize and Panamax in the bulk carrier market and use quarterly data of GDP, world fleet, BCI, and BPI from 1999 to 2021. Applying the wavelet analysis and wavelet Granger causality test, the simultaneous examination of co-movement and causality between two factors and the shipping market in both the time and frequency domains is achieved. We find that co-movement and causality vary across time and frequencies, thereby existing dynamic relationships between variables. Second, compared to multiple coherencies using demand and supply factors together, partial coherencies indicate noticeable causalities. It implies that analyzing demand and supply factors separately is essential. Finally, shipping freight indices show a high correlation with the demand factor in a good market and with the supply factor in a bad market. Generally, GDP positively leads shipping freights in the recovery phase while the world fleet negatively leads shipping freights in the downturn. The research is meaningful in that the rarely-applied wavelet analysis is adopted in the shipping market and that it gives a reasonable ground to explain the role of supply and/or demand factors in different phases of the market cycle.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.54 no.8
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• pp.418-428
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• 2005

In this paper, a new probabilistic generation modeling method which can address the characteristics of changed electricity industry is proposed. The major contribution of this paper can be captured in the development of a probabilistic generation modeling considering generator maintenance outage and in the classification of market demand into multiple demand clusters for the applications to electricity markets. Conventional forced outage rates of generators are conceptually combined with maintenance outage of generators and, consequently, effective outage rates of generators are newly defined in order to properly address the probabilistic characteristic of generation in electricity markets. Then, original market demands are classified into several distinct demand clusters, which are defined by the effective outage rates of generators and by the inherent characteristic of the original demand. We have found that generators have different effective outage rates values at each classified demand cluster, depending on the market situation. From this, therefore, it can be seen that electricity markets can also be classified into several groups which show similar patterns and that the fundamental characteristics of power systems can be more efficiently analyzed in electricity markets perspectives, for this classification can be widely applicable to other technical problems in power systems such as generation scheduling, power flow analysis, price forecasts, and so on.

• Korean Journal of Agricultural Science
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• v.49 no.3
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• pp.679-690
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• 2022

As the supply and demand of pork has become a significant concern in Korea, controlling it has become a critical challenge for the industry. However, compared to the demand for pork, which has relatively stable consumption, it is not easy to maintain a stable supply. As the preparation of measures for a supply-demand crisis response and supply control in the pig industry has emerged as an important task, it has become necessary to establish a stable supply model and create an appropriate manual. In this study, a pork supply prediction model is constructed using reported data from the pig traceability system. Based on the derived results, a method for determining the supply-demand crisis stage using a statistical approach was proposed. From the results of the analysis, working days, African swine fever, heat wave, and Covid-19 were shown to affect the number of pigs graded in the market. A test of the performance of the model showed that both in-sample error rate and out-sample error rate were between 0.3 - 7.6%, indicating a high level of predictive power. Applying the forecast, the distribution of the confidence interval of the predicted value was established, and the supply crisis stage was identified, evaluating supply-demand conditions.