• Environmental and Resource Economics Review
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• v.14 no.3
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• pp.753-773
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• 2005

This paper is a study of the investment dynamics focusing on crude oil supply by OPEC and non-OPEC. Oil supply capacity is first determined by a leader, OPEC, and by an aggregate that represents non-OPEC producers. OPEC wants to increase a gain from oil price increase while keeping its market share relative to non-OPEC's share. An investment rule model is developed for OPEC crude oil supply capacity in response to non-OPEC's decision. In presence of oil price uncertainty, oil price threshold is derived above which it is optimal for OPEC to expand oil supply capacity since otherwise the increased supply of non-OPEC results in weakening of OPEC market share in the world oil market. In addition, a lower threshold price is derived below which OPEC triggers a capacity reduction to regain its otherwise forgone profits. A simulation is provided for calculating the capacity expansion and reduction thresholds.

• Asia-Pacific Journal of Business
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• v.15 no.3
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• pp.385-397
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• 2024

Purpose - The purpose of this study was to analyze the dynamic relationship between oil prices and macroeconomic variables (gross domestic product, consumer price index, and interest rate). Long-run and short-run effects of oil prices on these macroeconomic variables are examined. Design/methodology/approach - The vector error correction model (VECM) is used to examine the short-run and long-term causality of oil prices, and a hierarchical Bayesian vector autoregressive model (HBVAR) is used to find the impulse of oil shock and the response of other variables. Findings - First, oil prices do not have short-term causality with macroeconomic variables, but they have long-term causality with interest rates and GDP. Second, the long-term stable relationship of oil prices and other macroeconomic variables is important to find out causality. Third, oil shock increases interest rates and decreases GDP and consumer price. Research implications or Originality - The significance of this study is a new attempt to analyze the dynamic relationship between oil prices and macroeconomic variables by linking VECM and HBVAR. Although VECM can analyze the long-term relationship and short-term dynamics between oil prices and macroeconomic variables, it was difficult to identify the transmission path of the oil price shock. HBVAR is confirmed to be flexible because it can bypass the process of selecting VAR or VECM through unit root test and cointegration analysis, and it is expected to reduce uncertainty of selecting hyperparameters.

• Land and Housing Review
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• v.13 no.4
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• pp.45-53
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• 2022

This paper investigates empirically the lead-lag relation between the 'apartment price index' and 'Internet search volume'. This study uses Naver Trend Index as a proxy for Internet search volume. An increase in Internet search volume on the apartment price index indicates an increase in people's attention to an apartment. Different from previous studies exploring the relation between 'the released price index of the apartment' and 'Naver Trend Index', this study investigates the relation of the Naver Trend Index with 'the fundamental price component of an apartment' and 'the transitory price component of an apartment', respectively. The results of the Granger causality test reveal that there are bidirectional Granger causalities between the 'released price' and Naver Trend Index. In addition, the 'fundamental price component of an apartment' and Naver Trend Index have a feedback relation, while 'the transitory price component of an apartment' Granger causes the Naver Trend Index uni-directionally. The impulse response function analysis indicates that the shock of apartment prices increases Naver Trend Index in the first month. Overall, The close relationship between apartment prices and Naver Trend Index suggests that increases in the movement of apartment prices are positively associated with public attention on the apartment market.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.1
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• pp.58-73
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• 2021

Cloud Service Providers (CSPs) enable their users to access Cloud computing and storage services from anywhere in quick and flexible manners through the Internet. With the basis of 'pay-as-you-go' model, it makes the interactions between CSPs and the users play a vital role in shaping the Cloud computing market. A pool of virtualized and dynamically scalable Cloud services that delivered on demand to the users is associated with guaranteed performance and cost-provisioning. It needed a costing scheme for determining suitable charges in order to secure lease pricing of the Cloud services. However, it is hard to meet the satisfied prices for both CSPs and users due to their conflicting needs. Furthermore, there is lack of Service Level Agreements (SLAs) that allowing the users to take part into price negotiating process. The users may lose their interest to use Cloud services while reducing CSPs profit. Therefore, this paper proposes a generic costing scheme for Cloud services using General Equilibrium Theory (GET). GET helps to formulate the price function for various services' factors to match with various demands from the users. It is initially determined by identifying the market circumstances that a general equilibrium will be hold and reached. Specifically, there are two procedures of agreement made in response to (i) established equilibrium supply and demand, and (ii) service price formed and constructed in a price range. The SLAs in our costing scheme is integrated to satisfy both CSPs and users' needs while minimizing their conflicts. The price ranging strategy is deliberated to provide prices' options to the users with respect their budget limit. Meanwhile, the CSPs can adaptively charge based on users' preferences without losing their profit. The costing scheme is testable and analyzed in multi-tenant computing environments. The results from our simulation experiments demonstrate that the proposed costing scheme provides better users' satisfaction while fostering fairness pricing in the Cloud market.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.59 no.9
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• pp.1575-1580
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• 2010

Demand Response is a well-known means usually operated by the system operator(SO) or the electricity retailers in order to reduce the peak loads or cut the price in electricity market. KPX(Korea Power eXchange), the SO in Korea has been operating the demand bidding program(or the demand resource market) since it was firstly introduced as the pilot project in 2008. The results has proved to be effective to enhance demand response. This paper describes the basic concepts and the operation results of the program.

• Transactions on Control, Automation and Systems Engineering
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• v.3 no.3
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• pp.152-158
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• 2001

This paper proposes a simple feedforward compensator in order to decrease the amount of undershoots and overshoots on the step response in nonminimum phase systems. The compensator makes the step type input be a ramp input with saturation for 0$\leq$t<${\alpha}$. It is shown in this paper that the compensated system has small amount of undershoot and overshoot at the price of rise time compared to the system without compensator. Also, provided the system is properly stable, the influence of the design parameter ${\alpha}$ on the step response of the nonminimum phase system is investigated in the case of Type A, and Type B undershoot, which gives a guideline for the compensator design.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2004.05a
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• pp.183-188
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• 2004

Nowadays optical disc drives have become necessary. As the equipment is popular to use, competition of price and rotating rate have been harder and harder. Shock response analysis for the optical disk drives is rarely studied. In this paper the optical disk drive has 5-DOF system and each motion is presented by using Lagrange Equation. As the motion of the Pick up lens is important to read and write data, it needs to consider the pickup and disk. The lumped parameter model is compared with finite element model in order to make sure of the result. Results of the shock response analysis from various shock inputs are gotten.

• Proceedings of the KIEE Conference
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• 2002.11b
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• pp.384-386
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• 2002

As restructuring in power industry has introduced competitive markets, a new method on demand side management has been developed. Many programs using the method were developed with providing several choices for customer. Nowadays the programs are called demand response as the load management is done by customer's responding to the market price signal. It was proven that the method was effective for demand control with the active consumer's attending for the program. This paper analyses the perspective and the requirement for designing the demand response system.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.65 no.7
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• pp.1128-1134
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• 2016

Demand response provides customer load reductions based on high market prices or system reliability conditions. One type of demand response, price-based program, induces customers to respond to changes in product rates. However, there are large-scale general and industrial customers that have difficulty changing their energy consumption patterns, even with rate changes, due to their electricity demands being commercial and industrial. This study proposes an in-house pricing model for large-scale general and industrial customers, particularly those with multiple business facilities, for self-regulating demand-side management and cost reduction. The in-house pricing model charges higher rates to customers with lower load factors by employing peak to off-peak ratios in order to reduce maximum demand at each facility. The proposed scheme has been applied to real world and its benefits are demonstrated through an example.

• Journal of Digital Convergence
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• v.19 no.11
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• pp.255-266
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• 2021

Investment demand for factory facilities has increased due to the balloon effect caused by housing price regulation. This study investigated the impact of the real estate market and macroeconomic factors on the bid price ratio of apartment auctions and factory auctions, focusing on the metropolitan area. To this end, we reviewed theories and previous studies on real estate auctions, and examined how macroeconomic variables affect bid price ratio of apartments and factories using the panel vector autoregressive model. It was found that the increase in the apartment bid price ratio increases as the participation in apartment auctions increases. However, as the factory bid price ratio increases, the factory bid price ratio does not increase, it was confirmed that the positive (+) relationship between the successful bid price ratio and the bid price ratioe does not exist, unlike previous studies. Based on the analysis results, it is suggested that the real estate market and macroeconomic factors should be considered for the stable operation of the related relevant auction system. This study has limitations in that it is limited to the metropolitan area. In the future, research that expands the scope of research to the whole country and provinces should be conducted.