Product Line Pricing Effect Modeling for Shipment Timing Support System for Stored Apple

Kwak, Youngsik; Nam, Yoonjung; Kwak, Yoonsik; Lee, Young-Hun

doi:10.14257/ijsh.2013.7.6.16

Cited by 2 publications

(5 citation statements)

References 2 publications

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“…In case of micro variable, the researchers used the same independent variables Kwak et al used at aggregate level for excellent grade Fuji apple [6]. We expect that the results from this study can be compared with the results from the Kwak et al's results.…”

Section: Modelingmentioning

confidence: 79%

Production Volume Effect on Daily Wholesale Price of Stored Apple for Shipment Timing Decision-Making Support System

Kwak¹,

Nam²,

Kwak³

2014

Advanced Science and Technology Letters

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The purpose of this study is to develop a forecasting model of daily wholesale price with macro and micro variables for 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's online system. This study identified two operational definitions for production volume and applied two variables to dynamic price forecasting modeling for stored apple at daily base, empirically. Researchers could conclude that the apple production volume at a given year affected the daily price level significantly.

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Section: Modelingmentioning

confidence: 79%

Production Volume Effect on Daily Wholesale Price of Stored Apple for Shipment Timing Decision-Making Support System

Kwak¹,

Nam²,

Kwak³

2014

Advanced Science and Technology Letters

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“…A price response function model used by Kwak et al, (2011Kwak et al, ( , 2013Kwak et al, ( , 2014 in the STSS for apples is shown in equation (1).…”

Section: Study On Price Response Functions Based On Prospect Theorymentioning

confidence: 99%

“…Dynamic price response function refers to a function that traces the effects of prices in the past, which changes with a time lag, on current or future prices and demand. Therefore, this study conducted modeling by changing the form of equation ( 5) to equation (6) to enable price changes in the past to predict future ones. c2 in equation ( 6) is the non-proportional calculation of the effect of a price increase from the previous period to the present one on prices in the following period.…”

Section: Study On Price Response Functions Based On Prospect Theorymentioning

confidence: 99%

“…However, existing STSS studies do not reflect the non-proportional response effect when the amount of the increase or decrease grows larger. Gutenberg's model reflects this phenomenon in existing studies of pricing, however, it can't be found in STSS studies (Kwak, et al, 2011(Kwak, et al, , 2013.…”

Section: Introductionmentioning

confidence: 96%

“…Many researchers have suggested variables that predict price levels at certain periods in the STSS and tested their significance. The variables include the total shipment quantity at previous day, wholesale prices at previous day, national holiday effect, the days elapsed after shipping of newly harvested products, substitution price level, the day-of-the-week effects and so on (Kwak, et al, 2011(Kwak, et al, , 2013(Kwak, et al, , 2014. Among those agricultural product variables from prior studies, this study focuses on improving the marginal point of a price variable used in the existing STSS.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

An Empirical Study on Asymmetric and Non-Proportional Price Response Function in the Shipment Timing Decision-Making Support System for Agricultural Products

Kwak¹,

Nam²,

Kwak³

et al. 2015

IJUNESST

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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.

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Product Line Pricing Effect Modeling for Shipment Timing Support System for Stored Apple

Abstract: Abstract

Cited by 2 publications

References 2 publications

Production Volume Effect on Daily Wholesale Price of Stored Apple for Shipment Timing Decision-Making Support System

Production Volume Effect on Daily Wholesale Price of Stored Apple for Shipment Timing Decision-Making Support System

An Empirical Study on Asymmetric and Non-Proportional Price Response Function in the Shipment Timing Decision-Making Support System for Agricultural Products

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