• Proceedings of the KIEE Conference
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• summer
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• pp.710-712
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• 2004

Generation companies(Genco) submit the supply functions as a bidding function to a bid market in a competitive electricity market. The profits of Gencos vary in accordance with the bid functions, so the selection of a bidding function plays a key role in increasing their profits. This paper presents an analysis of the selection of the supply function from the viewpoint of Nash equilibrium(NE). Four types of bidding function parameters are used for analizing the electricity market. The competition of selecting bidding parameters is modeled as subgame and overall game in this research. The NEs in both game are computed by using analytic method and payoff matrix method. It is verified in case studies for the NE of overall game to satisfy the equilibrium condition.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.53 no.1
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• pp.56-66
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• 2004

As deregulation evolves, pricing electricity becomes a major issue in the electric industry. Participants of competitive marketplace are able to improve their profits substantially by adequately pricing the electricity. In this paper, game theory is applied to analyze the price-clearing in the generation bidding competition and the competition is modeled as the noncooperative and complete information. The result of this analysis can be useful in understanding spot price-clearing of electricity and generating entity's strategic behavior in the competitive electricity market.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.55 no.6
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• pp.259-264
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• 2006

This paper addresses the collusive bidding that functions as a potential obstacle to a fully competitive wholesale electricity market. Cooperative game is formulated and the equation of its Nash Equilibrium (NE) is derived on the basis of the supply function model. Gencos' willingness to selectively collude is expressed through a bargain theory. A Collusion Incentive Index(CII) for representing the willingness is defined through computing the Gencos' profits at NE. In order to keep the market non-cooperative, the market operator has to know the highest potentially collusive combination among the Gencos. Another index, which will be called the Collusion Monitoring Index(CMI), is suggested to detect the highest potential collusion and it is calculated using the marginal cost functions of the Gencos without any computation of NE. The effectiveness of CMI for detecting the highest potential collusion is verified through application on many test market cases.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.57 no.7
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• pp.1157-1166
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• 2008

This paper presents a new approach for the evaluation of location marginal prices (LMPs) considering demand-side bidding (DSB) in a competitive electricity market. The stabilization of the electric power supply and demand balance is one of the major important activities in electric power industry. In this paper, we present an analytical method for calculation of LMPs considering DSB, which has opportunity to compete with generating units, as England & Wales Pool's DSB scheme[1]. Also, we propose a new approach that LMP considering DSB is divided into three components. The proposed approach can be used for the evaluation of demand-side bidding into the electricity market and the assessment of the influence of DSB on total production costs and LMPs as well as three components.

• KIEE International Transactions on Power Engineering
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• v.4A no.4
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• pp.243-253
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• 2004

As deregulation evolves, pricing electricity becomes a major issue in the electric power industry. Participants in the competitive marketplace are able to improve their profits substantially by effectively pricing the electricity. In this paper, game theory is applied to analyze price-clearing in the generation bidding competition with the competition modeled as the non-cooperative and complete information game. The result of this analysis can be useful in understanding spot price-clearing of electricity as well as GENCOs' strategic behavior in the competitive electricity market.

• Proceedings of the KIEE Conference
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• 2001.07a
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• pp.507-508
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• 2001

Power transactions are considered as noncooperative game in that participants compete each other to win the bidding game, and as cooperative game in that they have to cooperate to apply the result of bidding game to the physically interconnected power system. This paper applies both noncooperative and cooperative game theories in analyzing the entire process of power transaction.

• The Journal of Information Systems
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• v.25 no.4
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• pp.63-85
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• 2016

Purpose While the popularity of C2C auction platforms such as eBay is gradually decreased, this domain is still undermined to explain online bidding behaviors. Online bidders sometimes engage in impulsive bidding due to some of the online auction characteristics. Therefore, this study develops and tests a model of the impulsive bidding exhibited by online bidders in C2C auction platforms. Based on S-O-R framework, our model posits that both perceived time-pressure and competition intensity affect cognitive absorption which ultimately influences the impulsive bidding. Design/methodology/approach This study collected survey data from 214 C2C auction participants, who have prior experience on impulsive bidding and tested both measurement model and structural model by using CB-SEM (covariate-based structural equation modelling) technique. In this study, by using AMOS 20.0, we tested the measurement model for its overall fit, item reliability, and validity and further conducted the structural model to test our proposed hypotheses. Findings Based on our results, we found that perceived tim-pressure and competition intensity were positively related to cognitive absorption. We also found that the cognitive absorption was positively associated with impulsive bidding behavior. In this study, by developing our research model in S-O-R framework, we provide an alternative theoretical mechanism to describe online impulsive bidding behavior.

• Proceedings of the Korean Institute of Building Construction Conference
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• 2007.11a
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• pp.109-113
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• 2007

This paper introduces a system, Simulation based Stochastic Markup Estimation System (S2ME), for estimating optimum markup for a project. The system was designed and implemented to better represent the real world system involved in construction bidding. The findings obtained from the analysis of existing assumptions used in the previous quantitative markup estimation methods were incorporated to improve the accuracy and predictability of the S2ME. The existing methods has four categories of assumption as follows; (1) The number of competitors and who is the competitors are known, (2) A typical competitor, who is fictitious, is assumed for easy computation, (3) the ratio of bid price against cost estimate (B/C) is assumed to follow normal distribution, (4) The deterministic output obtained from the probabilistic equation of existing models is assumed to be acceptable. However, these assumptions compromise the accuracy of prediction. In practice, the bidding patterns of the bidders are randomized in competitive bidding. To complement the lack of accuracy contributed by these assumptions, bidding project was randomly selected from the pool of bidding database in the simulation experiment. The probability to win the bid in the competitive bidding was computed using the profile of the competitors appeared in the selected bidding project record. The expected profit and probability to win the bid was calculated by selecting a bidding record randomly in an iteration of the simulation experiment under the assumption that the bidding pattern retained in historical bidding DB manifest revival. The existing computation, which is handled by means of deterministic procedure, were converted into stochastic model using simulation modeling and analysis technique as follows; (1) estimating the probability distribution functions of competitors' B/C which were obtained from historical bidding DB, (2) analyzing the sensitivity against the increment of markup using normal distribution and actual probability distribution estimated by distribution fitting, (3) estimating the maximum expected profit and optimum markup range. In the case study, the best fitted probability distribution function was estimated using the historical bidding DB retaining the competitors' bidding behavior so that the reliability was improved by estimating the output obtained from simulation experiment.

• Journal of the Korean Society of Food Science and Nutrition
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• v.41 no.6
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• pp.861-869
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• 2012

This study was conducted to investigate the purchasing status and to compare supplier performance evaluations between competitive bidding and negotiated contracts in school foodservice in Changwon, Korea. A total of 190 questionnaires were distributed and 167 (return rate 87.9%) were collected from June 29 to September 28, 2010, and then a total of 151 (analysis rate 79.5%) were used for the final analysis. First, 91.4% of food product purchases for school meals were contracted through competitive bidding, especially limited competitive bidding. It mainly consisted of agricultural products, processed food, and eco-friendly agricultural products (fruit). Second, 78.8% of schools purchased food products by negotiated contracts, while single negotiation accounted for 59.7%. Food products by negotiated contract consisted of meat, kimchi, and fish. Third, the purchase status of competitive bidding and negotiated contracts showed a significant difference in agricultural products (p<0.001), fish (p<0.001), meats (p<0.001), poultry (p<0.001), antibiotic-free poultry (p<0.001), eco-friendly grain (p<0.001), eco-friendly agricultural products (fruit) (p<0.001), eco-friendly processed food (p<0.001), processed products (p<0.001), milk (p<0.001) and general grain (p<0.001) except for kimchi. Fourth, comparative analysis of supplier performance evaluation (on a 5-point Likert scale) of school foodservice showed that price of product of competitive bidding (3.73) was significantly higher than that of negotiated contract (2.95) (p<0.001), and the overall performance level of the negotiated contract (3.85) was significantly higher than that of competitive bidding (3.61) (p<0.01). The supplier performance evaluation levels of product packaging (p<0.01), product quality at the time of delivery (p<0.001), hygiene of products (p<0.001), consistency to specification (p<0.001), swiftness of return and exchange (p<0.001), emergency delivery (p<0.001), service of delivery staff (p<0.05), and handling of complaints (p<0.001) of negotiated contracts were significantly higher than those of competitive bidding of school foodservice. In conclusion, school foodservice selected food suppliers both by adopting competitive bidding and negotiated contracts. And there was a significant difference of school foodservice supplier performance between competitive bidding and negotiated contracts in Changwon, Korea.

• Proceedings of the KIEE Conference
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• 2000.07a
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• pp.400-402
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• 2000

This paper presents a game theoretic approach for power transactions analysis in a competitive market. The considered competitive power market is regarded as PooICo model, and the participating players are restricted by only two generating entities for simplicity in this paper. The analysis is performed on the basis of marginal cost based relations of bidding price and bidding generations. That is, we assume that the bidding price of each player is determined by the marginal cost when the bidding generation is pre-determined. This paper models the power transaction as a two player game and analyzes by applying the Nash eauilibrium idea. The generalized game model for power transactions covering constant-sum(especially zero-sum), and nonconstant-sum game is developed in this paper. Also, the analysis for each game model are performed in the case studies. Here, we have defined the payoff of each player as the weighted sum of both player's profits.