• 제목/요약/키워드: 가격점수

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Analysis of the Influence of Design Score and Price Score for Design Build Bidding (설계시공일괄입찰에서 설계점수와 가격점수의 영향력 분석)

  • Lee, Jinhak;Woo, Sungkwon;Lee, Siwook
    • Korean Journal of Construction Engineering and Management
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    • 제24권5호
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    • pp.44-51
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    • 2023
  • Selecting appropriate bidding system in construction projects considering the characteristic of project can be a make-or-break element, so the understanding for bidding system of public construction projects is ever more important from the perspective of both the owner and the contractor. The design-build bidding is commonly referred to as turnkey in Korea, and is a bidding method that is often applied to large public construction projects because it allows new technologies to be applied to the design and facilitates risk management for the owner. In this bidding method, there are only two factors (design score and price score) that affect the selection of the winning bidder, so it is important to understand the influence of each factor, but there is little research on the subject. This study aims to provide a basis for establishing bidding strategies for understanding the influence between design score and price score by analyzing various design-build bidding data of public construction projects. The results of the study show that design score is the factor that has more influence on the ranking of bidders in all three weighted evaluation methods: design-emphasized, price-emphasized, and equalized evaluation. In addition, we found that the correlation between design and price scores was not significant due to the unique bid evaluation structure in Korea.

Effects on the Apartment Price of the Score Difference of National Unit Academic Evaluation - Focused on the Case of Ulsan - (전국단위 학력평가 성적 차이가 아파트 가격에 미치는 영향 - 울산광역시 사례 -)

  • Ahn, Mun Young;Chu, Joon Suk
    • Korea Real Estate Review
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    • 제27권4호
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    • pp.63-76
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    • 2017
  • The purpose of this study is to analyze the effect of the results of a nationwide academic evaluation of middle schools and high schools on apartment prices in Ulsan City by using a hedonic pricing model. The results of the middle school and high school achievement test, the College Scholastic Ability Test (CSAT) score for high school, the national united evaluation score, and the number of successful applicants to prestigious universities have a significant effect on the apartment price formation with a positive relationship. In addition, different kinds of academic evaluation score have asymmetric effects on apartment price determination. The results of the high school achievement evaluation are more important than the results of the middle school achievement evaluation in the apartment price determination. Among the achievement evaluation results, the ratio of the students with the higher education level is more important than the ratio of the students with the lower basic education level. Furthermore, the CSAT score for Natural Sciences is more important than the CSAT score for the Humanities course.

Analysis on Bidding Behavior in Score Auction: Highway BTO Projects (수익형 민간투자사업(BTO) 입찰평가 분석: 도로사업을 중심으로)

  • Kim, Jungwook
    • KDI Journal of Economic Policy
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    • 제33권4호
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    • pp.143-177
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    • 2011
  • Upon selecting preferred bidder in Public-Private Partnership projects, multi-dimensional procurement auction, where price factor and non-price factor are evaluated, is used. This paper tries to analyze bidding data in BTO road projects. It is shown that a winner tends to get higher score in bidding evaluation, which is partly due to increase in base score as well as fiercer competition among bidders. It turns out that score margin in non-price factor was determinant in selecting winner. Also, there was no competition when the level of bonus point was set too high. For price factor, it costs 730 million KRW per score in construction subsidy by government, while it costs 2.43 billion KRW per score in toll revenue. For non-price factor, it was estimated to cost 2.30 billion KRW. Based on the results, it was suggested that we should have appropriate level of bonus point for first initiator, change in scoring rule in construction subsidy part, adjustment of base score in evaluation.

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Named Entity Recognition for Analyzing Factors of Agrifood Price Fluctuation (농식품 가격변동 요인분석을 위한 개체명 인식)

  • Park, Chan;Lee, Kung-Soon
    • Annual Conference on Human and Language Technology
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    • 한국정보과학회언어공학연구회 2020년도 제32회 한글 및 한국어 정보처리 학술대회
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    • pp.347-350
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    • 2020
  • 농식품 가격을 안정적으로 제공하기 위해 농식품 가격 변동에 대한 요인 분석이 필요하다. 본 연구는 농식품 가격 변동의 요인 분석을 위해 인과관계 템플릿을 정의하고, 요약을 위한 개체명 인식 방법을 적용한다. 농식품 일일동향 데이터에 대한 평가에서 딥러닝 기반 BiLSTM-CRF 실험 결과 F1-점수 0.93으로 베이스라인 Bi-LSTM 실험 결과 0.75에 비해 높은 성능을 보였다.

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A Study on Collusion Effects for Bid Award in Public Construction Works (공공 건설공사 담합이 낙찰에 미치는 영향 분석 연구)

  • Kim, Myeongsoo
    • Korean Journal of Construction Engineering and Management
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    • 제21권1호
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    • pp.12-20
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    • 2020
  • To estimate collusion effects on bid award in Public Construction works, this paper uses Logit Model, which is a choice variable model. Price, design, competition, and other factors are included, with a special focus on collusion, as independent variables in the model. The empirical results are as follows. First, collusion has little effects on bid award, but great impacts on bidding behavior. Secondly, the score of design is the most important and significant factors among all variables. Thirdly, competition has also significant effects on bid award. Finally it is analyzed that institutional framework and characteristics of public work have some effects on bidding award.

A Survey of Korean Housewives' Perception on the Commercial Korean Basic Side Dishes in Busan Area (시판 밑반찬에 대한 부산지역 주부의 인식조사)

  • Lyu, Eun-Soon;Lee, Dong-Sun;Chung, Sun-Kyung
    • Journal of the Korean Society of Food Science and Nutrition
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    • 제35권4호
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    • pp.440-447
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    • 2006
  • The perception of Korean housewives was investigated on commercial Korean basic side dishes. The questionnaires were distributed to 464 housewives in Busan area. According to the survey, the housewives preferred discount stores (44.1%) to purchase basic side dishes. The reasons for purchasing them were convenience (54.6%) and readiness in small amount (23.1%). The housewives had high perception scores on saying cooking time (4.90/5.00), the possibility of purchasing when they need (3.93/5.00), and convenient use (3.85/5.00). However, they doubted the propriety of making use of chemical seasoning (2.15/5.00), the original place of raw food materials (2.21/5.00), and shelf life control (2.44/5.00). The satisfaction scores on the commercial basic side dishes were 3.06/5.00 in braised perilla leaves, 2.98/5.00 in braised soybean, 2.96/5.00 in pickled garlic, and 2.96/5.00 in stir-fried/muchim dried fish. The priorities on the improvement demand for the basic side dishes were appeared in order of the sanitary preparation, the consistent tastes, the proper amounts of chemical seasonings, and sanitary distribution systems.

Sentiment Analysis of News Based on Generative AI and Real Estate Price Prediction: Application of LSTM and VAR Models (생성 AI기반 뉴스 감성 분석과 부동산 가격 예측: LSTM과 VAR모델의 적용)

  • Sua Kim;Mi Ju Kwon;Hyon Hee Kim
    • The Transactions of the Korea Information Processing Society
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    • 제13권5호
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    • pp.209-216
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    • 2024
  • Real estate market prices are determined by various factors, including macroeconomic variables, as well as the influence of a variety of unstructured text data such as news articles and social media. News articles are a crucial factor in predicting real estate transaction prices as they reflect the economic sentiment of the public. This study utilizes sentiment analysis on news articles to generate a News Sentiment Index score, which is then seamlessly integrated into a real estate price prediction model. To calculate the sentiment index, the content of the articles is first summarized. Then, using AI, the summaries are categorized into positive, negative, and neutral sentiments, and a total score is calculated. This score is then applied to the real estate price prediction model. The models used for real estate price prediction include the Multi-head attention LSTM model and the Vector Auto Regression model. The LSTM prediction model, without applying the News Sentiment Index (NSI), showed Root Mean Square Error (RMSE) values of 0.60, 0.872, and 1.117 for the 1-month, 2-month, and 3-month forecasts, respectively. With the NSI applied, the RMSE values were reduced to 0.40, 0.724, and 1.03 for the same forecast periods. Similarly, the VAR prediction model without the NSI showed RMSE values of 1.6484, 0.6254, and 0.9220 for the 1-month, 2-month, and 3-month forecasts, respectively, while applying the NSI led to RMSE values of 1.1315, 0.3413, and 1.6227 for these periods. These results demonstrate the effectiveness of the proposed model in predicting apartment transaction price index and its ability to forecast real estate market price fluctuations that reflect socio-economic trends.

Introducing Renewable Portfolio Standard(RPS) in Korea : Demands and Obstacles (RPS제도 국내도입에 관한 연구)

  • Boo Kyung-Jin;Heo Eunnyeong
    • 한국신재생에너지학회:학술대회논문집
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    • 한국신재생에너지학회 2005년도 춘계학술대회
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    • pp.573-576
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    • 2005
  • 대표적인 신$\cdot$재생에너지의 시장확대 정책으로 RPS와 기준가격의무구매제가 주요 선진국에서 실시되고 있으며 자국의 자원부존과 경제사회여건에 맞춰 적합한 정책수단을 선택하고 있음. RPS 실시국가에서 RPS는 특별법으로 제정되어 실시효과를 극대화하고 있으며, 신$\cdot$재생에너지발전 인중서의 거래를 포함시켜 시너지효과를 거두고 있음. RPS의 단일의 최적모델은 존재하지 않으며 기본설계와 세부사항은 각 국의 고유의 자원부존 여건 및 경제사회적 특징에 따라 달라짐. RPS의 국내도입이 전력시장과 국민경제에 미치는 영향은 그리 크지 않으며 외부효과를 감하면 편익을 초래함. 또한 수요조사결과 RPS에 대한 선호도가 비교적 높게 나타나며 산$\cdot$ 재생에너지발전의 시장확대 수단으로 높은 점수를 매기고 있음 그러나 RPS의 기본설계를 신중히 가져가야 할 것이며, 법제도 정비에 임해서는 기존에 실시되고 있는 기준가격우선구매제도(발전차액보전)의 고려해야 함.

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Predicting the Future Price of Export Items in Trade Using a Deep Regression Model (딥러닝 기반 무역 수출 가격 예측 모델)

  • Kim, Ji Hun;Lee, Jee Hang
    • KIPS Transactions on Software and Data Engineering
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    • 제11권10호
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    • pp.427-436
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    • 2022
  • Korea Trade-Investment Promotion Agency (KOTRA) annually publishes the trade data in South Korea under the guidance of the Ministry of Trade, Industry and Energy in South Korea. The trade data usually contains Gross domestic product (GDP), a custom tariff, business score, and the price of export items in previous and this year, with regards to the trading items and the countries. However, it is challenging to figure out the meaningful insight so as to predict the future price on trading items every year due to the significantly large amount of data accumulated over the several years under the limited human/computing resources. Within this context, this paper proposes a multi layer perception that can predict the future price of potential trading items in the next year by training large amounts of past year's data with a low computational and human cost.

An Analysis of Non-linear Effects of Impact Factors on Housing Price (주택매매가격 영향요인의 비선형적 효과 분석)

  • Chang, Youngjae
    • Journal of the Korean Data Analysis Society
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    • 제20권6호
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    • pp.2953-2966
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    • 2018
  • Housing prices are closely related to various variables that indicate macroeconomic conditions. In this paper, empirical analysis based on data is performed referring to previous studies. Focusing on the policy interest rate among the factors affecting the housing price, the non-linear impulse responses of other variables to the interest rate shock are analyzed. Using the random forest algorithm, the variable importance scores of the macroeconomic variables presented in the previous studies are calculated. After selecting the variables through this process, the impulse responses are calculated using a model that can capture non-linearity. According to the model, the responses of housing prices to the policy rate is only significant when the rate is raised. Especially, the impulse response is amplified when the shock increases due to the non-linear characteristics that can not be captured by the traditional VAR methodology. The analysis results suggest that the interest rate as a policy instrument should be approached from a more cautious perspective.