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Youngsik Kwak - One of the best experts on this subject based on the ideXlab platform.

  • An Empirical Study on Asymmetric and Non-Proportional Price Response Function in the Shipment Timing Decision-Making Support System for Agricultural Products
    International Journal of u- and e-Service Science and Technology, 2015
    Co-Authors: Youngsik Kwak, Yoonjung Nam, Yoonsik Kwak, Pil Hwa Yoo, Seokil Song
    Abstract:

    STSS (Shipment Timing Decision-Making Support System for Agricultural Products) is designed to manage shipping dates to improve sales profits for agricultural products that are stored in warehouses. The purpose of this study is to increase the predictability of the Price variable among other variables included in this system to better predict wholesale Prices at the shipping dates. This study suggests the use of an asymmetric Price Response Function and a non-proportional Price Response Function, which can comprehensively trace Price changes in the next period based on Price increases or decreases at certain levels in the previous period. Additionally, the study aims to conduct an empirical analysis of the whole market as well as the market segments. The data used were wholesale Prices and delivery volumes for 15kg of fine grade Fuji apples traded at Garak Agro-Fishery Market located in Garak-dong, Seoul. The analysis was conducted by market segment, and confirmed periods when the Responses towards a given day’s Price levels were big and small when previous day’s Price levels for wholesale apples decreased or increased during the year. Through this, the best opportunity to adjust shipping dates of apples and to increase profits could be suggested.

  • A Study of Price Response Function for Asymmetric and Non-Proportional Demand Response to Price Change
    2015
    Co-Authors: Youngsik Kwak, Yoonjung Nam, Yoonsik Kwak, Pil Hwa Yoo
    Abstract:

    The purpose of this study is to propose asymmetric and nonproportional Response Function tracks demand Response to Price changes and to apply it to STSS(Shipment Timing Decision-making Support System) for conducting empirical analysis with one of four iconic Korean fruit products, apple.

  • dynamic shipment decision making support system modeling for stored apples in korea
    JOURNAL OF ADVANCED INFORMATION TECHNOLOGY AND CONVERGENCE, 2011
    Co-Authors: Youngsik Kwak
    Abstract:

    Although the retail Price management is well documented in academic field from the customers’ point of view, the report of application of wholesale Price management in practice, especially in agricultural industry, has been relatively rare from farmers’ perspectives. The researcher aims to try to full this gap by developing a shipment timing decision-making support system for stored apples based on the transaction quantity and the wholesale Price information announced by Seoul Agricultural & Marine Products Corporation through on-line. The Shipment Decision-making Support System(SDSS) consists of the dynamic Price Response Function for each product, the Price expectation effect, product line effect, substitutes Price effect, events effect, the demand curve for apples and cost Function. The resulting fluctuation of the expected sales revenue for every product they store in warehouse will be provided by the application on smart phone. The system will helpful for farmers to decide the time for shipment from warehouses to wholesale markets, and to increase the opportunities to produce more money in farmers pockets.

  • FGIT-UNESST - Shipment Timing Support System Modeling for Stored Apples in Korea
    U- and E-Service Science and Technology, 2011
    Co-Authors: Youngsik Kwak, Seokil Song
    Abstract:

    Although, in academic field, various industries has its own retail Price management system from the customers’ point of view, the report of application of wholesale Price management in practice, especially in agricultural industry, has been relatively rare from producers’ perspectives. The researcher aims to try to full this gap by developing a shipment timing support system for stored apples based on the transaction quantity and the wholesale Price information announced by Seoul Agricultural & Marine Products Corporation at on-line. The Shipment Timing Support System(STSS) consists of the dynamic Price Response Function for each product, the Price expectation effect, product line effect, substitutes Price effect, events effect, apples’ life cycle, the demand curve for apples and cost Function. The resulting fluctuation of the expected sales revenue for every product they store in warehouse will be provided by the application on smart phone. The system will helpful for farmers and wholesalers to decide the time for shipment from warehouses to wholesale markets, and to increase the opportunities to produce more money in farmers pockets.

  • Application Service Program (ASP) Price Elasticities for Korean Home Trading System
    U- and E-Service Science and Technology, 2009
    Co-Authors: Wanwoo Cho, Jaewon Hong, Ho Jang, Youngsik Kwak
    Abstract:

    Although the Price elasticities for off-line industry are well documented in academic field, the report of Price elasticities for on-line to a given brand or industry in practice have been relatively rare. The researcher aims to try to full this gap by applying a Price Response Function to Home Trading System’s on-line transaction data for the first time in Korean securities market. The different Price elasticities among seven brands were found from -0.819 to -1.811. These results suggested that marketers should understand the Price elasticity of their own HTS, before making a Price decision.

Lester C. Hunt - One of the best experts on this subject based on the ideXlab platform.

  • transportation oil demand consumer preferences and asymmetric Prices
    Journal of Economic Studies, 2011
    Co-Authors: David C. Broadstock, Alan Collins, Lester C. Hunt
    Abstract:

    Purpose - The aim of this paper is to establish the role of asymmetric Price decompositions in UK road transportation fuel demand, make explicit the impact of the underlying energy demand trend, and disaggregate the estimation for gasoline and diesel demand as separate commodities. Design/methodology/approach - Dynamic UK transport oil demand Functions are estimated using the Seemingly Unrelated Structural Time Series Model with decomposed Prices to allow for asymmetric Price Responses. Findings - The importance of starting with a flexible modelling approach that incorporates both an underlying demand trend and asymmetric Price Response Function is highlighted. Furthermore, these features can lead to different insights and policy implications than might arise from a model without them. As an example, a zero elasticity for a Price-cut is found (for both gasoline and diesel), implying that Price reductions do not induce demand for road transportation fuel in the UK. Originality/value - The paper illustrates the importance of joint modelling of gasoline and diesel demand incorporating both asymmetric Price Responses and stochastic underlying energy demand trends.

  • Transportation Oil Demand Consumer Preferences and Asymmetric Price Responses: Some UK Evidence
    2010
    Co-Authors: David C. Broadstock, Alan Collins, Lester C. Hunt
    Abstract:

    The aim of this paper is to (i) establish the role of asymmetric Price decompositions in UK road transportation fuel demand, (ii) make explicit the impact of the underlying energy demand trend and (iii) disaggregate the estimation for gasoline and diesel demand as separate commodities. Dynamic UK transport oil demand Functions are estimated using the Seemingly Unrelated Structural Time Series Model with decomposed Prices to allow for asymmetric Price Responses. The importance of starting with a flexible modelling approach that incorporates both an underlying demand trend and asymmetric Price Response Function is highlighted. Furthermore, these features can lead to different insights and policy implications than might arise from a model without them. As an example, a zero elasticity for a Price-cut is found (for both gasoline and diesel) implying that Price reductions do not induce demand for road transportation fuel in the UK. The paper illustrates the importance of joint modelling of gasoline and diesel demand incorporating both asymmetric Price Responses and stochastic underlying energy demand trends.

Jonathan Ullman - One of the best experts on this subject based on the ideXlab platform.

  • EC - Multidimensional Dynamic Pricing for Welfare Maximization
    Proceedings of the 2017 ACM Conference on Economics and Computation, 2017
    Co-Authors: Aaron Roth, Aleksandrs Slivkins, Jonathan Ullman
    Abstract:

    We study the problem of a seller dynamically pricing d distinct types of indivisible goods, when faced with the online arrival of unit-demand buyers drawn independently from an unknown distribution. The goods are not in limited supply, but can only be produced at a limited rate and are costly to produce. The seller observes only the bundle of goods purchased at each day, but nothing else about the buyer's valuation Function. Our main result is a dynamic pricing algorithm for optimizing welfare (including the seller's cost of production) that runs in time and a number of rounds that are polynomial in d and the approximation parameter. We are able to do this despite the fact that (i) the Price-Response Function is not continuous, and even its fractional relaxation is a non-concave Function of the Prices, and (ii) the welfare is not observable to the seller. We derive this result as an application of a general technique for optimizing welfare over divisible goods, which is of independent interest. When buyers have strongly concave, Holder continuous valuation Functions over d divisible goods, we give a general polynomial time dynamic pricing technique. We are able to apply this technique to the setting of unit demand buyers despite the fact that in that setting the goods are not divisible, and the natural fractional relaxation of a unit demand valuation is not strongly concave. In order to apply our general technique, we introduce a novel Price randomization procedure which has the effect of implicitly inducing buyers to "regularize'' their valuations with a strongly concave Function. Finally, we also extend our results to a limited-supply setting in which the number of copies of each good cannot be replenished.

  • Multidimensional Dynamic Pricing for Welfare Maximization
    arXiv: Data Structures and Algorithms, 2016
    Co-Authors: Aaron Roth, Aleksandrs Slivkins, Jonathan Ullman
    Abstract:

    We study the problem of a seller dynamically pricing $d$ distinct types of indivisible goods, when faced with the online arrival of unit-demand buyers drawn independently from an unknown distribution. The goods are not in limited supply, but can only be produced at a limited rate and are costly to produce. The seller observes only the bundle of goods purchased at each day, but nothing else about the buyer's valuation Function. Our main result is a dynamic pricing algorithm for optimizing welfare (including the seller's cost of production) that runs in time and a number of rounds that are polynomial in $d$ and the approximation parameter. We are able to do this despite the fact that (i) the Price-Response Function is not continuous, and even its fractional relaxation is a non-concave Function of the Prices, and (ii) the welfare is not observable to the seller. We derive this result as an application of a general technique for optimizing welfare over \emph{divisible} goods, which is of independent interest. When buyers have strongly concave, Holder continuous valuation Functions over $d$ divisible goods, we give a general polynomial time dynamic pricing technique. We are able to apply this technique to the setting of unit demand buyers despite the fact that in that setting the goods are not divisible, and the natural fractional relaxation of a unit demand valuation is not strongly concave. In order to apply our general technique, we introduce a novel Price randomization procedure which has the effect of implicitly inducing buyers to "regularize" their valuations with a strongly concave Function. Finally, we also extend our results to a limited-supply setting in which the number of copies of each good cannot be replenished.

Seungjae Lim - One of the best experts on this subject based on the ideXlab platform.

  • Price forecasting model of the FPD market with existing technological variance - Case: Global FPD TV market
    Expert Systems with Applications, 2010
    Co-Authors: Myoung Kwan Yoo, Seungjae Lim
    Abstract:

    Beginning the 21st century, the FPD (Flat Panel Display) market has been growing massively. It is difficult for the market to establish pricing strategies according to the development of technology and the change of market due to technological variances and diverse sizes of products such as the LCD, PDP, Braun tube, and projection television (TV) in the FPD market. The preexisting methods for pricing, used to forecast the future Price of products, take into consideration the prime cost, value of brand, and Functions of products applied by the same technology. In the market, however, the rapidly changing technology becomes an obstacle to the establishment of pricing strategies considering market competition. In order to overcome the preceding limitations, we propose a new method for forecasting the appropriate gap between the Prices of products based on different technology and size. The purpose of this PBS (Pricing Based on Simulation) method is to contribute to setting up an effective pricing strategy in the FPD market. This method consists of surveys, estimated Price Response Function, analysis of the appropriate gap between product Prices, prediction of future market competition, and establishment of strategies. By implying the PBS method to the global FPD market in year 2005, we deduced the Price Response Function and the appropriate gap between product Prices for the future. According to the real FPD market from 2005 to 2006, the statistical marketing data shows significant similarity in movement to the forecasting result by the method. Therefore, the PBS method can be utilized effectively when products using newly developed technology is introduced to the market in the future.

Stefan Minner - One of the best experts on this subject based on the ideXlab platform.

  • The impact of dynamic pricing on the economic order decision
    European Journal of Operational Research, 2009
    Co-Authors: Sandra Transchel, Stefan Minner
    Abstract:

    This paper analyzes the impact of dynamic pricing on the single product economic order decision of a monopolist retailer. Items are procured from an external supplier according to the economic order quantity (EOQ) model and are sold to customers on a single market without competition following the simple monopolist pricing problem. Coordinated decision making of optimal pricing and ordering is influenced by operating costs – including ordering and inventory holding costs – and the demand rate obtained from a Price Response Function. The retailer is allowed to vary the selling Price, either in a fixed number of discrete points in time or continuously. While constant and continuous pricing have received much attention in the literature, problems with a limited number of Price changes are rather rare. This paper illustrates the benefit of dynamically changing Prices to achieve operational efficiency in the EOQ model, that is to trigger high demand rates when inventories are high. We provide structural properties of the optimal time instants when the Price should be changed. Taking into account costs for changes in Price, it provides numerical guidance on number, timing, and size of Price changes during an order cycle. Numerical examples show that the benefits of dynamic pricing in an EOQ framework can be achieved with only a few Price changes and that products being unprofitable under static pricing may become profitable under dynamic pricing.

  • OR - Simultaneous Dynamic Pricing and Lot-sizing Decision for a Discrete Number of Price Variations
    Operations Research Proceedings, 1
    Co-Authors: Sandra Transchel, Stefan Minner
    Abstract:

    We investigate the impact of a dynamic pricing strategy on the economic ordering decision where a discrete number of Price changes within each order cycle is allowed. Customer reaction to Prices is modelled by a linear Price Response Function and the ordering process is subject to variable procurement cost and setup cost. Inventories are subject to holding cost. The objective is to maximize average profit by choosing the optimal lot-size and pricing strategy.