• 자원ㆍ환경경제연구
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• 제9권4호
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• pp.747-771
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• 2000

This paper reports the results of a study to elicit willingness to pay (WTP) for changes in health risks from exposure to As, Pb, THM in tap water using experimental market method. The experimental market method, compared with other non-market valuation methods, allows us to use incentive compatible demand revealing scheme, to acquire market-like experience through repetitive auctions, and to incorporate learning process by providing new information during the session. Participants seemed to utilize the objective risk information in a 'rational' manner, and to change their WTP bids accordingly. Moreover they were able to reduce the 'ambiguity' in risk perception processes when objective risk probabilities provided are quite different from their subjective perceptions. Nonetheless, anchoring effects appeared to be still persistent in spite of market-like experience and learning opportunity. And implicit values entailed by WTP bid/risk tradeoffs indicate a wide variation in values across alternative risk reductions and overrated responses to very small risk reductions.

• 아태비즈니스연구
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• 제11권4호
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• pp.21-36
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• 2020

Purpose - This study analyzes the effect of sellers' dishonesty on various market outcomes such as seller profit, buyer profit, and market welfare, through precisely measuring the level of sellers' information disclosure and its economic impacts. As an explicit observation of sellers' dishonesty is not easy in most other settings, this study is expected to suggest unique and meaningful implications on the effect of sellers' incomplete information disclosure to researchers, managers, and policy makers. Design/methodology/approach - In order to precisely measure the level of sellers' dishonesty under information asymmetry, this study analyzes the data from an incentive-based economic experiment using z-Tree software. This experimental method enables us to focus on the strategic interactions among participants, observe the integrity of seller's information disclosure, and reproduce real market situations. Findings - The analysis of sellers' dishonesty has provided the following important and counterintuitive findings about the reality of buyer-seller interactions under information asymmetry. First, sellers' lies do not affect seller profit even when they are very intensive. Second, sellers' dishonesty negatively affects buyer profit and the entire market welfare. Third, a seller's quality claim has a positive effect on the seller profit only when a seller is being honest. Research implications or Originality - This study analyzes sellers' dishonesty using incentive-based economic experiment using z-Tree software which provides a straightforward examination on dishonest behavior of sellers, that is not readily available with other types of observational or experimental data.

• The Journal of Asian Finance, Economics and Business
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• 제8권1호
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• pp.53-59
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• 2021

This research aims to examine the model of investor herding behavior in making investment decisions in the Indonesian capital market, which is influenced by social and information impacting on the value of the Book Value Per Share (BVPS). The latest stock market conditions show that most investors make the same error pattern in making investment decisions that result in losses. The experiment involves two independent variables, namely, information about BVPS and social influence. This study used a 2×2 factorial design laboratory experimental method. Data collection was carried out through treatment of a sample of 100 individual investors listed on the Indonesia Stock Exchange. Univariate Two-Way Analysis of Variance (ANOVA) statistical tool was used to test the independent variable on the dependent variable. Research results showed that the social influence originating from expert investors is more influential than the Book Value Per Share (BVPS) information on the behavior of herding investors in making investment decisions. These findings suggest that investors know their psychological factors, thereby increasing self-control and investment analysis skills. Further research can use psychological bias and other indicators of accounting relevant information such as Earning Per Share (EPS) to test herding behavior in investment decision making in the capital market.

• 산경연구논집
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• 제9권12호
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• pp.23-29
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• 2018

Purpose - The purpose of this study is to apply a cost effective ultrasonic odor reduction method that generated micro-bubbles using ejector to the Southeast Asian wastewater market. Research design, data, and methodology - A leather maker located in Ansan-city, Gyunggi-do, South Korea was sampled from the collection tank to select experimental materials. Experimental setup consisted of circulating water tank-air ejector-ultrasonic device, and circulating wastewater. Sample analysis was performed by CODcr, T-N, T-P, and turbidity by the National Environmental Science Institute. Results - Experimental results show that it is most effective in removing odors when the frequency range of ultrasonic wave is 60~80 Khz and the output is 200 W. It showed that the concentration of complex odor dropped from a maximum of 14,422 times to a minimum of 120 times. Also, analysis of ammonia and hydrogen sulfide in specific odor substances has shown that they were reduced from 1.5 ppm to 0.4 ppm and from 0.6 ppm to 0.1 ppm, respectively. Conclusions - It is possible to shorten more than 12 hours in the treatment of micro-organisms. It can be seen that the processing time of odor after ultrasonic treatment in the pre-treatment facility is reduced by 25% when compared to the resultant micro-organisms after the chemical treatment, that is, the time of the bio-treatment of micro-organisms. Based on the results, it was confirmed that the pre-treatment method using the ultrasonic and the air ejector device of the experiment shows the effect of reducing the water pollutants and odor more effectively in a relatively short time than the conventional advanced oxidation method.

• 자원ㆍ환경경제연구
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• 제17권3호
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• pp.135-166
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• 2008

비시장재의 변화에 의한 후생변화 측정치로서 쓰이는 지불의사(WTP)와 수용의사(WTA) 개념은 경제이론적으로는 소득효과가 크지 않다면 서로 크게 다르지 않을 것이라고 예측되고 있다. 그러나 실증분석결과들은 WTA 측정치가 WTP의 측정치보다 훨씬 큰 것으로 관찰되고 있다. 본 연구는 우리나라에서는 처음으로 실험시장접근법을 사용하여 비시장재의 하나인 먹는 물에 잔류가능성이 있는 유해물질(비소, 납, 트리할로메탄 중의 하나)로부터의 건강위험변화에 대한 WTP와 WTA를 측정하고 이 두 측정치에 차이가 존재하는지 실증적으로 분석하였다. 대학생들 15명씩의 참가자들을 대상으로 총 여섯 번의 실험시장을 개설하였다. 시장거래경험의 유무에 따른 차이를 검증하고자 사적 시장재인 캔디바 실험경매도 도입하였고, 반복경험에 따른 학습효과를 관찰하기 위하여 20번의 실험경매를 시도하였고, 정보제공효과를 관찰하기 위하여 10번째 경매 후에 객관적 건강위험에 관한 확률정보를 제공하였다. 시장재 비시장재의 구분없이 첫 번째 실험경매에서는 WTA가 통계적으로 유의하게 WTP를 초과하였다. 실험경매가 진행됨에 따라 사적 시장재는 WTA와 WTP의 차이가 사라지고 시장평균가격에 수렴하였다. 그러나 비시장재인 건강위험변화에 대한 결과는 혼재되어 있었다. 건강위험이 가장 큰 비소에 대해서는 건강위험 감소에 대한 WTP가 건강위험 증가에 대한 WTA보다 통계적으로 유의하게 적었다. 반면에 건강위험이 상대적으로 적은 납과 트리할로메탄에 대해서는 WTP와 WTA의 평균이 같다는 귀무가설을 기각할 수 없었다. 실험참가자들은 실험경매 중간에 제공된 건강위험정보에 대해 합리적으로 반응하였고, 실험경매가 진행됨에 따라 경험획득에 의한 학습효과도 긍정적이었다. WTP는 실험 초반에 학습효과가 주로 관찰된 반면에 WTA 측정치는 실험경매 후반에 학습효과가 관찰되었다.

• Management Science and Financial Engineering
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• 제20권1호
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• pp.21-26
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• 2014

A lot of researches have been conducted to estimate the volatility smile effect shown in the option market. This paper proposes a method to approximate an implied volatility function, given noisy real market option data. To construct an implied volatility function, we use Gaussian Processes (GPs). Their output values are implied volatilities while moneyness values (the ratios of strike price to underlying asset price) and time to maturities are as their input values. To show the performances of our proposed method, we conduct experimental simulations with Korean Equity-Linked Warrant (ELW) market data as well as toy data.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제17권10호
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• pp.2809-2821
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• 2023

Effective recommendation of similar business groups is a critical factor in obtaining market information for companies. In this study, we propose a novel method for enhancing similar business group recommendation by incorporating derivative criteria and web crawling. We use employment announcements, employment incentives, and corporate vocational training information to derive additional criteria for similar business group selection. Web crawling is employed to collect data related to the derived criteria from 'credit jobs' and 'worknet' sites. We compare the efficiency of different datasets and machine learning methods, including XGBoost, LGBM, Adaboost, Linear Regression, K-NN, and SVM. The proposed model extracts derivatives that reflect the financial and scale characteristics of the company, which are then incorporated into a new set of recommendation criteria. Similar business groups are selected using a Euclidean distance-based model. Our experimental results show that the proposed method improves the accuracy of similar business group recommendation. Overall, this study demonstrates the potential of incorporating derivative criteria and web crawling to enhance similar business group recommendation and obtain market information more efficiently.

• 한국컴퓨터정보학회논문지
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• 제17권9호
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• pp.17-27
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• 2012

여러 오픈마켓에서 판매자가 동일한 상품을 등록할 시에 각 오픈마켓마다 다른 기준으로 제공되는 카테고리로 인하여 카테고리 선정에 어려움이 발생한다. 본 논문에서는 판매자가 오픈마켓에서 상품 등록 시 다른 오픈마켓에서 기 판매하고 있는 상품의 카테고리와 의미적으로 가장 연관성이 높은 카테고리를 추천하는 방법을 제안한다. 이때 입력받은 카테고리를 의미 분석하는 방법으로 형태소 분석, Wiki 낱말사전, WordNet, Google 번역 서비스를 사용하여 추출된 색인어로 카테고리를 검색한 후, 의미적 연관성 측정을 통하여 가장 의미가 비슷한 카테고리를 추천하는 방법이다. 실험 결과로 색인어 기반의 검색방법 보다 제안하는 의미분석 검색방법이 정확한 검색결과를 보여주어 시스템의 신뢰도를 향상시켰으며, 카테고리를 선택하는데 드는 시간비용을 절감해주는 것을 보인다.

• 한국전자거래학회지
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• 제4권3호
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• pp.63-76
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• 1999

Internet-based electronic trade has been growing fast. But most users are not yet familiar with the system and find it very difficult to purchase and sell the products in the cyber market place. To handle these problems, agent-based virtual market place system has been proposed where agents instead of individuals participate in trading of goods. Most of the proposed models have been in the two general categories. The first is the direct transaction among sellers and buyers, and the second is the agent-based transaction. However, the transaction is not fair and the best deal can't be guaranteed for both models. In this paper, we propose a new broker based synchronous transaction algorithm which is fair to both parties and guarantees the best deal. Our algorithm is implemented using Visual C++ and the experimental results show that our method is better than the two traditional transaction models in every performance metrics, Number of transactions are increased up to 21% and price adjustment is up to 280% better for some transactions.

• 한국경영과학회:학술대회논문집
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• 한국경영과학회 1997년도 추계학술대회발표논문집; 홍익대학교, 서울; 1 Nov. 1997
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• pp.105-108
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• 1997

Previous studies in stock market predictions using artificial intelligence techniques such as artificial neural networks and case-based reasoning, have focused mainly on spot market prediction. Korea launched trading in index futures market (KOSPI 200) on May 3, 1996, then more people became attracted to this market. Thus, this research intends to predict the daily up/down fluctuant direction of the price for KOSPI 200 index futures to meet this recent surge of interest. The forecasting methodologies employed in this research are the integration of genetic algorithm and artificial neural network (GAANN) and the integration of genetic algorithm and case-based reasoning (GACBR). Genetic algorithm was mainly used to select relevant input variables. This study adopts the categorical data preprocessing based on expert's knowledge as well as traditional data preprocessing. The experimental results of each forecasting method with each data preprocessing method are compared and statistically tested. Artificial neural network and case-based reasoning methods with best performance are integrated. Out-of-the Model Integration and In-Model Integration are presented as the integration methodology. The research outcomes are as follows; First, genetic algorithms are useful and effective method to select input variables for Al techniques. Second, the results of the experiment with categorical data preprocessing significantly outperform that with traditional data preprocessing in forecasting up/down fluctuant direction of index futures price. Third, the integration of genetic algorithm and case-based reasoning (GACBR) outperforms the integration of genetic algorithm and artificial neural network (GAANN). Forth, the integration of genetic algorithm, case-based reasoning and artificial neural network (GAANN-GACBR, GACBRNN and GANNCBR) provide worse results than GACBR.