• Asia pacific journal of information systems
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• v.13 no.3
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• pp.23-39
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• 2003

Recently, many organizations in various industries have introduced e-business for the purpose of adding value to their business. But, the e-business model has not existed before and so, it is difficult to analyze clear effectiveness. It frequently does not live up to an organization's expectations. It is due to an absence of environmental changes analysis in the new model, not by a new model itself. System Dynamics(SD) may provide effective results as a tool of analysis for the new model. This research shows the analysis of the effects of a simulated e channel model, which was expanded from existing channel modeling with actual data in basic materials industries. The results show average prices increasing by auction process on the e-market and an increase in sales. So, by increasing the speed of sale revolution stock expenses are reduced. Additionally, we applied a possible scenario to the developed simulation model and investigated strategic issues to draw desirable strategies with market changes.

• Journal of Korean Institute of Industrial Engineers
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• v.33 no.3
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• pp.322-328
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• 2007

Highly standardized products are suitable for automated purchasing using electronic commerce technology, where the price becomes the most important factor. Suppliers can change the prices dynamically based on the inventory level and market situation in order to maximize the sales and profit. In the virtual marketplace where multiple customers purchase multiple standardized products from multiple suppliers repetitively, customers can purchase the required amount of each item as a dynamic bidding by allocating purchase orders to the suppliers based on the current price. Customers need a method to quickly determine the optimal allocation of orders to the suppliers using the dynamically changing data to minimize the total cost. We present a LP model which minimizes the sum of the total price plus transportation cost for this problem. Simulation results using random data show meaningful reduction of the total cost.

• Land and Housing Review
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• v.14 no.1
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• pp.33-46
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• 2023

This study investigated price factors for large apartment complexes in Seoul during the COVID-19 pandemic and compared Gangnam and non-Gangnam areas, which have been recognized as heterogeneous markets. We find that the change in apartment prices in large-scale complexes did not significantly affect the individual characteristics of apartments, unlike previous studies, but was affected by macroeconomic variables such as interest rates and money. On the other hand, considering the units of the interest rate and total monetary volume variables, the effects of two variables on the apartment sales price is significantly high. In addition, the Gangnam area model analysis shows that apartment prices are greatly affected by interest rates and currency volume, and, the non-Gangnam area model analysis shows that apartment prices are greatly affected by interest rates and currency volume, but the degrees are different from the Gangnam area model. Overall, our study shows that interest rates and money supply were the main factors of apartment price changes, but apartment prices in non-Gangnam areas are more sensitive to changes in interest rates and money supply.

• Journal of the Korea Institute of Building Construction
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• v.22 no.1
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• pp.81-90
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• 2022

With apartment purchase prices rising, small and medium-sized cities have been highlighted as areas in which real estate speculation is overheated, and thus designated as target districts for adjustment. In addition, tax policy is constantly being adjusted in an attempt to stabilize real estate prices. The purpose of this study is to analyze the basic effect of tax policy on the purchase price of apartments in small and medium-sized cities. This study selected apartments in the Daejeon area that were constructed between 1990 and 2015. In addition, tax policy was divided into regulatory policy and easing policy based on tax increase and tax cut. This study analyzes the short-term difference of one year before and after the change in the purchase price of apartment houses. In addition, this study set the time when real estate policy was implemented and the actual transaction price of apartments in Daejeon as the analysis targets, and analyzed the correlation between tax policy and apartment sales prices through the NPV technique and T-test results. Through the study, it was found that most tax policies changed apartment purchase prices in the short term.

• The Journal of Art Theory & Practice
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• no.2
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• pp.191-213
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• 2004

The trend of "Blockbuster Exhibitions" over the past decade has led to the unfortunate reality that museums, losing sight of their role as an Academic organization, are becoming increasingly influenced by the corporate world. In my dissertation entitled "The Commercialization of Blockbuster Exhibitions in Museums," I explore the modern tendency toward Blockbuster exhibitions in art museums and the negative impact of those exhibitions on the art world. Museums of the modern day have expanded their territory from the traditional venue of public education to the hybrid cultural space. This mission, evident in the museum's attempt to satisfy audiences with the offering of diverse activities, has changed the concept of the museum, giving priority to the desire for financial gain. From the viewpoint of this new museology, the museum considers Blockbuster exhibitions as the safest method to increase ticket sales. As a program that openly reveals the commercialism of the museum, I explore the Blockbuster show and its strategies as a means of exposing the influence of the corporate world on art. A key component to the Blockbuster exhibition is the "hype" that is created to attract an audience. This devotion to increased publicity distracts from what should be the goal of public education, as the primary focus leans towards the desire for a large number of visitors. Consequently, this unavoidably standardized exhibition is presented to the public in a manner that deprives the audience of a unique experience. With large crowds and increased ticket prices, it is difficult to form a genuine appreciation of the artwork. In addition to the profit gained by increased ticket prices and the commercial sales of "souvenirs" from the museum gift shop, Blockbuster shows are used as a means to attract the attention of corporate sponsors. As explained in my dissertation, the importance that the museum places on corporate sponsorship as a capital resource is evident, however the degree to which the museum allows itself to he influenced by the desire for capital gain poses a threat to its function as an academic organization. Circumstances in American museum history, in particular, have influenced the transition from academic resource to corporation within museology. In keeping with the nation's tendency towards capitalism, art museums in the United States were initially established and developed by individual capitalists who applied principals of corporate operation to museum management. As a result, in modern days, We witness the influence of enterprise on museum programs, while corporate management may be able to guarantee immediate fiscal benefits, however, it is unable insure the future of the museum. In Slim, my dissertation discusses the mechanism of the commercialized "Blockbuster Exhibition" and the impact that it has on the future of the museum as an industry. This research provides an opportunity to reconsider the role of the museum as an academic institution, particularly in regard to the need to decrease the capitalization of exhibitions and refocus their influence on the art world as an educational resource.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2021.10a
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• pp.582-583
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• 2021

As the production of new and renewable energy such as solar and wind power has diversified, microgrid systems that can simultaneously produce and consume have been introduced. . In general, a decrease in electricity prices through solar power is expected in summer, so producer protection is required. In this paper, we propose a transparent and safe gift power transaction system between users using blockchain in a microgrid environment. A futures is simply a contract in which the buyer is obligated to buy electricity or the seller is obliged to sell electricity at a fixed price and a predetermined futures price. This system proposes a futures trading algorithm that searches for futures prices and concludes power transactions with automated operations without user intervention by using a smart contract, a reliable executable code within the blockchain network. If a power producer thinks that the price during the peak production period (Hajj) is likely to decrease during production planning, it sells futures first in the futures market and buys back futures during the peak production period (Haj) to make a profit in the spot market. losses can be compensated. In addition, if there is a risk that the price of electricity will rise when a sales contract is concluded, a broker can compensate for a loss in the spot market by first buying futures in the futures market and liquidating futures when the sales contract is fulfilled.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2021.10a
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• pp.584-585
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• 2021

As the production of new and renewable energy such as solar and wind power has diversified, microgrid systems that can simultaneously produce and consume have been introduced. In general, a decrease in electricity prices through solar power is expected in summer, so producer protection is required. In this paper, we propose a transparent and safe gift power transaction system between users using blockchain in a microgrid environment. A futures is simply a contract in which the buyer is obligated to buy electricity or the seller is obliged to sell electricity at a fixed price and a predetermined futures price. This system proposes a futures trading algorithm that searches for futures prices and concludes power transactions with automated operations without user intervention by using a smart contract, a reliable executable code within the blockchain network. If a power producer thinks that the price during the peak production period is likely to decrease during production planning, it sells futures first in the futures market and buys back futures during the peak production period to make a profit in the spot market. losses can be compensated. In addition, if there is a risk that the price of electricity will rise when a sales contract is concluded, a broker can compensate for a loss in the spot market by first buying futures in the futures market and liquidating futures when the sales contract is fulfilled.

• The Journal of the Convergence on Culture Technology
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• v.9 no.2
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• pp.533-543
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• 2023

This study explores the influence of the COVID-19 pandemic on the Korean art market and contrasts the classic hedonic method of art price prediction with the Artificial Neural Network technique. The empirical analysis of this paper utilizes 14,639 observations of Korean art auction data from 2015 to 2021. There are three types of variables in this study: artist-related, artwork-related, and sales-related. Previous studies have suggested that these three types of variables influence art prices. The empirical findings in this research are in twofold. First, in terms of RMSE and R², the Artificial Neural Network outperforms the hedonic model. Both techniques discover that sales and artwork variables have a greater impact than artist-related attributes. Second, when the primary factors of art price are controlled, Korean art prices are found to fall dramatically in 2020, shortly following the onset of COVID-19, but to rebound in 2021. The main lesson in this study is that the Artificial Neural Network enhances art price prediction and reduces information asymmetry in the Korean art market even in the face of unanticipated turmoil such as the COVID-19 outbreak.

• Journal of Service Research and Studies
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• v.14 no.1
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• pp.27-43
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• 2024

The market share of online platform services in the used car market continues to expand. And The used car online platform service provides service users with specifications of vehicles, accident history, inspection details, detailed options, and prices of used cars. SUV vehicle type's share in the domestic automobile market will be more than 50% in 2023, Sales of Hybrid vehicle type are doubled compared to last year. And these vehicle types are also gaining popularity in the used car market. Prior research has proposed a used car price prediction model by executing a Machine Learning model for all vehicles or vehicles by brand. On the other hand, the popularity of SUV and Hybrid vehicles in the domestic market continues to rise, but It was difficult to find a study that proposed a used car price prediction model for these vehicle type. This study selects a used car price prediction model by vehicle type using vehicle specifications and options for Sedans, SUV, and Hybrid vehicles produced by domestic brands. Accordingly, after selecting feature through the Lasso regression model, which is a feature selection, the ensemble model was sequentially executed with the same sampling, and the best model by vehicle type was selected. As a result, the best model for all models was selected as the CBR model, and the contribution and direction of the features were confirmed by visualizing Tree SHAP Value for the best model for each model. The implications of this study are expected to propose a used car price prediction model by vehicle type to sales officials using online platform services, confirm the attribution and direction of features, and help solve problems caused by asymmetry fo information between them.

• Korean Journal of Community Nutrition
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• v.11 no.2
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• pp.253-260
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• 2006

The purpose of this study was to suggest menu pricing strategy based on understanding about customer perceived value of products and services. The technique known as PSM (Price Sensitivity Measurement) was used for analysis of price sensitivity for 3 menu items of a family restaurant in Seoul. A questionnaire was developed through literature review and modified after pilot test. Questionnaires for the main survey were distributed to 250 customers on their visit to the restaurant, and a total of 138 questionnaires were used for analysis (55.2%). The statistical analysis of price sensitivity was conducted using PSM, and descriptive analyses were conducted using SPSS Win (12.0). The main results of this study were as follows: the price sensitivity of beef tenderloin steak was higher than two other menus and the stress range of teriyaki chicken was almost 0, that is, the price sensitivity of teriyaki chicken was very low. Present menu prices of 3 menu items were within the range of acceptable prices, but had some distances from the optimal pricing point. From the result of this study, it was concluded that price adjustment or price promotion strategy would be effective for increase in sales of beef tenderloin steak, and marketing strategies to enhance consumers' perceptions of value should be conducted for all menu items by situations. Overall, PSM technique could be a helpful tool for researchers and managers of foodservice organizations to understand how consumers' perceptions of value are affected by the interaction of price and quality.