• The Research Journal of the Costume Culture
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• v.32 no.1
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• pp.38-57
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• 2024

This study utilizes social big data to investigate the factors influencing the awareness, attitude, and behavior toward vegan fashion consumption among global and Korean consumers. Social media posts containing the keyword "vegan fashion" were gathered, and meaningful discourse patterns were identified using semantic network analysis and sentiment analysis. The study revealed that diverse factors guide the purchase of vegan fashion products within global consumer groups, while among Korean consumers, the predominant discourse involved the concepts of veganism and ethics, indicating a heightened awareness of vegan fashion. The research then delved into the factors underpinning awareness (comprehension of animal exploitation, environmental concerns, and alternative materials), attitudes (both positive and negative), and behaviors (exploration, rejection, advocacy, purchase decisions, recommendations, utilization, and disposal). Global consumers placed great significance on product-related information, whereas Korean consumers prioritized ethical integrity and reasonable pricing. In addition, environmental issues stemming from synthetic fibers emerged as a significant factor influencing the awareness, attitude, and behavior regarding vegan fashion consumption. Further, this study confirmed the potential presence of cultural disparities influencing overall awareness, attitude, and behavior concerning the acceptance of vegan fashion, and offers insights into vegan fashion marketing strategies tailored to specific cultures, aiming to provide vegan fashion companies and brands with a deeper understanding of their consumer base.

• Environmental and Resource Economics Review
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• v.16 no.1
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• pp.99-127
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• 2007

When the margin between available capacity and demand is thin in a liberalized electricity market, prices rise steeply and system reliability is threatened. The principal response to these circumstances is often an assumption that price spikes and electricity shortages are the result of a failure to build sufficient new supplying facilities. It is, of course, often the case that additional investments in generation and network facilities would improve reliability, and such investments are often needed. But focusing on additional generation and transmission facilities for restoring balance to the grid overlooks the essential fact that reliability is a function of the relationship between supply and demand, imposing unnecessary costs on electric system. When the relationship is out of balance, the search for solutions must consider not only investments supply-side resources but also cost-effective demand-side resources such as accelerated load management, efficiency measures, and price-responsive load programs. Integrating demand resources into electricity markets can add enormous value to the electric system, widening the capacity margin, lowering costs and enhancing system reliability at the same time. This paper studies several challenges now facing electricity markets: demand-side management-especially, economic effects of demand response, potential reliability problems, market and system operation, CBP market improvements and so on. The paper concludes with a series of policy recommendations in five areas: (i) The Effects of efficient improvement to incorporate demand responses and demand-side resources into modem electricity markets, (ii) Fosteing price based demand response and (iii) improving incentive based demand response, (iv) strengthen demand response analysis and valuation, (v) integrating demand response into resource planning and adopting enabling technologies.

• Journal of the Korea Computer Industry Society
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• v.6 no.2
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• pp.241-248
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• 2005

Conventional estimating methods forecast the future that it usually using the past statistical numerical value. In order to forecast the farming price, it must need many effort and accuracy knowledge. Therefore, to solve the these problems, this paper to improve forecasting farming price using fuzzy rules and neural network as a preprocessing. Also, we developed an intelligent farming expert system for real time forecasting as a postprocessing about unexpectable conditions. Computer simulation results proved reducing pricing error which proposed farming price expecting system better than conventional demand forecasting system does not using fuzzy rules.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2000.10a
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• pp.302-305
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• 2000

The operation of a networked computing system (NCS), such as Internet, can be viewed as a resource allocation problem, and can be analyzed using the techniques of mathematical modeling. We define a general NCS and translate that setup into a model of an economy. The preferences of users are taken as primitives, and servers in the network are viewed as productive firms with priority input queues. Each sewer charges a rental price for its services by priority class. We characterize optimal system allocation, and derive formulae for supporting rental prices and priority premia such that the aggregated individual user demands do not exceed optimal levels and waiting-time expectations are correct. Our economic approach has the added benefit of providing a sound basis for evaluating NCS investment alternatives, using a process analogous to free entry and exit in free-enterprise economies.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2005.05a
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• pp.746-752
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• 2005

본 논문에서는 다층 퍼셉트론 신경망 학습을 위한 새로운 두 단계 학습방법을 제안하고 이를 옵션 가격결정 모형에 응용하였다. 제안된 신경망 학습 알고리즘의 첫번째 단계는 Levenberg-Marquardt 알고리즘을 이용하여 빠르게 국소최적해를 찾는 것이고 두 번째 단계는 첫 번째 단계에서 찾은 국소최적해가 원하는 수준에 미치지 못할 경우 선형탐색 터널링을 이용해서 더 나은 해를 찾는 것이다. 이 두 단계를 반복적으로 수행함으로써 연결가중치 공간에서 구하고자 하는 해를 빠르고 안정적으로 찾을 수 있다. 현재 옵션가격결정 모형으로 많이 이용되고 있는 Black-Scholes 모형의 문제점을 극복하기 위해서 제안된 신경망 모형을 옵션가격결정 문제에 사용하였다. 이 모형을 KOSPI200 옵션 데이터로 실험한 결과 Black-Scholes 모형에 비해 검증오차를 60% 가량 줄일 수 있었다.

• Industrial Engineering and Management Systems
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• v.8 no.4
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• pp.201-212
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• 2009

This study analyzed the structure of pricing in the automobile auction market by using real trade data. We focused on the bidding behavior of bidders and the contract price of exhibits. First, we proposed a relational framework among exhibits, number of bidders, and the contract price. Next, we utilized a neural network model to estimate the number of bidders and the contract price. Subsequently, we investigated the relationship between the number of bidders and the contact price, and evaluated our method through an analysis that employed verifying data. Lastly, we listed our suggestions for bidding in auction markets.

• Management Science and Financial Engineering
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• v.16 no.2
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• pp.1-15
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• 2010

Digital convergence which means the convergence of industry areas related to digital technologies is an important phenomenon in business, which will decide the fates of firms in the near future. The only firms which can create synergy effects from digital convergence are expected to be the winners in the fierce competition of digital convergence era. In our analysis, we examine the strategy of an integrated firm which has businesses in two different industry areas which are related to each other. By using a game theoretical model, we show how the integrated firm can win over two single separated firms which have business in only one industry area each by leveraging the two businesses the integrated firm has. In our welfare analysis, we also show that this convergence may be even beneficial to consumers, which seems counter-intuitive to social concerns about anti-competitive behaviors by integrated firms. Additionally, we study comparison between industry convergence and product convergence.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 1996.04a
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• pp.328-332
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• 1996

B-ISDN is expected to be a main vehicle of future telecommunications. There has been a series fo studies on the demand and the market prospect of B-ISDN services. It is true, however, that they lacked some economic reality since the price of services has been overlooked which is a critical economic factor. In this study, we analyze some aspects of the tariff system of B-ISDN services. First, we explore and summarize the billing parameters of B-ISDN services from diverse characteristics of services and ATM network. These parameters are essential if the services are to be charged based on usage. Secondly, we discuss what factors be considered in the design fo B-ISDN services tariff systems from various points of view shch as traffic charactristics, information types and connection types, etc. The results of this study will offer fundamental insights in the design of B-ISDN service pricing scheme and provide reference for efficient services providing.

• Journal of the Korean Operations Research and Management Science Society
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• v.34 no.1
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• pp.85-100
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• 2009

An online marketplace, such as eBay, is an example of two-sided markets. In online marketplaces, there are transactions between sellers and buyers and direct competition effects among sellers and among buyers. Previous research on two-sided market has not handle these competition effects and mostly focused on indirect network externalities between sellers and buyers. We analyze the fee structure of an online marketplace considering direct competition effects among sellers and among buyers. We find that when fees for sellers and buyers can be imposed, an auction or fixed-pricing rule can be chosen according to the characteristics of a product traded. But when only fees for sellers can be imposed, an auction can be taken as a trading mechanism solely.

• Journal of Korea Multimedia Society
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• v.14 no.12
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• pp.1549-1558
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• 2011

In this paper, we address the problem of bandwidth sharing among multiple primary users and multiple secondary users in a cognitive radio network. In cognitive radio networks, effective spectrum assignment for primary and secondary users is a challenge due to the available broad range of radio frequency spectrum as well as the requisition of harmonious coexistence of both users. To handle this problem, firstly, Bertrand game model is used to analyze a spectrum pricing in which multiple primary users emulate with each other to acquire maximal profit. After that, we employ Cournot game to model the spectrum sharing of secondary users to obtain optimal profit for each user also. Simulation results show that our scheme obtains optimal solution at Nash equilibrium.