• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.19 no.6
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• pp.118-133
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• 2020

Research interest in the Mobility-as-a-Service (MaaS) concept for enhancing users' mobility experience is increasing. In particular, dynamic pricing techniques based on reinforcement learning have emerged since adjusting prices based on the demand is expected to help mobility services, such as taxi and car-sharing services, to gain more profit. This paper provides a simulation framework that considers more practical factors, such as demand density per location, preferred prices, the distance between users and drivers, and distance to the destination that critically affect the probability of matching between the users and the mobility service providers (e.g., drivers). The aforementioned new practical features are reflected on a data structure referred to as the Matching Matrix. Using an efficient algorithm of computing the probability of matching between the users and drivers and given a set of precisely identified high-demand locations using HDBSCAN, this study developed a better reward function that can gear the reinforcement learning process towards finding more realistic dynamic pricing policies.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.8 no.4
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• pp.1192-1207
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• 2014

Dynamic spectrum sharing is a key technology to improve spectrum utilization in wireless networks. The elastic spectrum management provides a new opportunity for licensed primary users and unlicensed secondary users to efficiently utilize the scarce wireless resource. In this paper, we present a game-theoretic framework for dynamic spectrum allocation where the primary users rent the unutilized spectrum to the secondary users for a monetary profit. In reality, due to the ON-OFF behavior of the primary user, the quantity of spectrum that can be opportunistically shared by the secondary users is limited. We model this situation with the renewal theory and formulate the spectrum pricing scheme with the Bertrand game, taking into account the scarcity of the spectrum. By the Nash-equilibrium pricing scheme, each player in the game continually converges to a strategy that maximizes its own profit. We also investigate the impact of several properties, including channel quality and spectrum substitutability. Based on the equilibrium analysis, we finally propose a decentralized algorithm that leads the primary users to the Nash-equilibrium, called DST. The stability of the proposed algorithm in terms of convergence to the Nash equilibrium is also studied.

• Journal of the Korean Operations Research and Management Science Society
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• v.25 no.2
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• pp.23-31
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• 2000

Many studies in marketing and economics have attempted to model price and sales path under the dynamic diffusion process. Most of these models have been based on a fixed product lifetime. The current business climate requiring intensive development of new products however affects the diffusion of new products and their lifetime. Many products have not enjoyed the expected life cycle at the launching stage due to intense technical development competitive reactions, and financial problems. Most diffusion models however have not taken account of the lifetime uncertainty of new product. If the products do not last over the planning horizon set by those models. the optimal price derived from them could be futile. Therefore we had better take such lifetime uncertainty into consideration when developing diffusion models, In this paper we study the impact of uncertain product lifetime on its optimal pricing path in non-competitive market. We develop an optimal pricing model under uncertain product lifetimes and conduct a simulation study to investigate their effects on the optimal pricing and corresponding sales paths. The simulation study provides some interesting findings on optimal pricing policy under uncertain product lifetime. This study could be a stepping stone for the further extended study of optimal pricing strategy with uncertain product lifetime.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.61 no.6
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• pp.804-809
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• 2012

This paper presents the economic impact of consumer participation in Real-Time Pricing (RTP). A computer model was developed to analyze the impact of real-time pricing on the average price, electricity sales, and the social welfare. Four revenue reconciliation alternative were introduced to illustrate the effect of RTP. Finally a case study was done to analyze the consequent impact of the dynamic load profile on the long-term fuel mix, and the results were compared with those of $5^{th}$ national power development plan.

• Communications for Statistical Applications and Methods
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• v.31 no.5
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• pp.585-599
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• 2024

Options pricing remains a critical aspect of finance, dominated by traditional models such as Black-Scholes and binomial tree. However, as market dynamics become more complex, numerical methods such as Monte Carlo simulation are accommodating uncertainty and offering promising alternatives. In this paper, we examine how effective different options pricing methods, from traditional models to machine learning algorithms, are at predicting KOSPI200 option prices and maximizing investment returns. Using a dataset of 2023, we compare the performance of models over different time frames and highlight the strengths and limitations of each model. In particular, we find that machine learning models are not as good at predicting prices as traditional models but are adept at identifying undervalued options and producing significant returns. Our findings challenge existing assumptions about the relationship between forecast accuracy and investment profitability and highlight the potential of advanced methods in exploring dynamic financial environments.

• Journal of Korean Society of Transportation
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• v.23 no.6 s.84
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• pp.71-80
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• 2005

With rapid development Telematics industry, the concern of dynamic road pricing system is increasing. In this study, the change of traffic flows according to traffic information and variation of congestion road prices related to the dynamic road pricing was analyzed. In this study, three facts were unfolded. First, high delay penalty and low delay penalty drivers are shown different reaction for the different congestion road prices. Second, the higher congestion road prices the more drivers convert their route from toll road to non toll road. Third, high penalty drivers are converting to toll road than low delay penalty drivers under same congestion road prices. This study has reached the conclusion that dynamic congestion pricing has a high possibility for traffic management.

• Journal of Communications and Networks
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• v.18 no.4
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• pp.658-669
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• 2016

The tremendous increase in mobile data traffic coupled with fierce competition in wireless industry brings about spectrum scarcity and bandwidth fragmentation. This inevitably results in asymmetric-valued long term evolution (LTE) spectrum allocation that stems from different timing for twice improvement in capacity between competing operators, given spectrum allocations today. This motivates us to study the economic effects of asymmetric-valued LTE spectrum allocation. In this paper, we formulate the interactions between operators and users as a hierarchical dynamic game framework, where two spiteful operators simultaneously make spectrum acquisition decisions in the upper-level first-price sealed-bid auction game, and dynamic pricing decisions in the lower-level differential game, taking into account user subscription dynamics. Using backward induction, we derive the equilibrium of the entire game under mild conditions. Through analytical and numerical results, we verify our studies by comparing the latest result of LTE spectrum auction in South Korea, which serves as the benchmark of asymmetric-valued LTE spectrum auction designs.

• 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.

• Journal of Global Scholars of Marketing Science
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• v.16 no.4
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• pp.1-11
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• 2006

Product quality of perishable food is significantly affected by the environment. Technological approaches for tracking and tracing such products have attracted increasing attentions in both research and practice. This paper studies how supermarket can maximize profits of selling perishable food through price adjustment based on real-ime product quality and values. This can be achieved by tracing the value of the perishable food based on an automatic product identification technology Radio Frequency Identification(RFID). With the support of the RFID, an optimization model can be developed to enable product tracking and tracing. The analysis of the model shows promising benefits of applying a dynamic pricing policy and obtains the optimal ordering decision in the respect of deterministic demand function.

• Management Science and Financial Engineering
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• v.19 no.1
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• pp.11-16
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• 2013

This paper derives an equilibrium asset price when there exist three kinds of traders in financial market: a risk-averse informed trader, noise traders, and risk neutral market makers. This paper is an extended version of Kyle's (1985, Econometrica) continuous time model by introducing insider's risk aversion. We obtain not only the equilibrium asset pricing and market depth parameter but also insider's value function and optimal insider's trading strategy explicitly. The comparative static shows that the market depth (the reciprocal of market pressure) increases with time and volatility of noise traders' trading.