• Proceedings of the Korean Institute of Building Construction Conference
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• 2011.05a
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• pp.207-209
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• 2011

Numerous reports show that alternative project delivery systems (PDSs) such as design-build (DB), construction management at risk (CMR), and design-build-maintain (DBM) are increasingly used in many countries. This study compared characteristics of each PDS (design-bid-build (DBB), DB, CMR, or DBM) by analyzing quantitative data from 9 research articles. In order to compare characteristics between DBB and alternative PDSs, the study is based on principal 3 factors - Time, Cost, and Quality. DB shows the best performance in the time part and also the cost performance depending on facility type and project size. The performance of quality has minor difference among different PDSs. These results support the fact that using an appropriate PDS by the characteristic of a project makes high value of efficiency and productivity.

• Korean Journal of Construction Engineering and Management
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• v.17 no.5
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• pp.89-96
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• 2016

Most data generated in construction projects is unstructured text data. Unstructured data analysis is very needed in order for effective analysis on large amounts of text-based documents, such as contracts, specifications, and RFI. This study analysed previously performed project's bid related documents (bidder inquiry) in overseas construction projects; as a results of the analysis frequent words in documents, association rules among the words, and various document topics were derived. This study suggests effective text analysis approach for massive documents with short time using text mining technique, and this approach is expected to extend the unstructured text data analysis in construction industry.

• Proceedings of the Korea Inteligent Information System Society Conference
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• 2001.01a
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• pp.73-77
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• 2001

In this paper, we propose a virtual action system based on information agents, We call the system the MultiHammer, MultiHammer can be used for studying and analyzing online actions. MuiltiHammer provides functions of implement-ing a meta online action site and an experiment environ-ment. We have been using MultiHammer as an experiment as an experiment environment for BiddinBot. BiddingBot aims at assisting users to bid simultaneously in multiple online auctions. In order to bid simultaneously in multiple online auctions. In order to analyze the behavior of BiddngBot, we need to pur-chase a lot of items. It is hard for us to prepare a lot of fund to show usability and advantage of BiddingBot. MultiHam-mer enables us to effectively analyze the behavior of BiddingBot. MultiHammer consists of three types of agents for information collecting data storing and auctioning. Agents for information wrappers. To make agent work as wrarp-pers, we heed to realize software modules for each online action site. Implementing these modules reguires a lot of time and patience. To address this problem, we designed a support mechanism for developing the modules. Agents for data storing record the data gathered by agents for informa-tion collecting. Agents for auctioning provide online services using data recorded by agents for data storing. By recording the activities in auction sites. MultiHammer can recreate any situation and trace auction for experimentation, Users can participate in virtual using the same information in real online auctions. Users also participate in real auc-tions via wrapper agents for information collecting

• Korean Journal of Construction Engineering and Management
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• v.8 no.2
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• pp.109-117
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• 2007

The construction environment has the trend of oversizing and professionalizing, the increase of the construction period, and the risk factors and the uncertain factors which are important in the construction bid. The misunderstanding and the lack of knowledge of the subcontractor result in the decrease of the profit or the deficit. In conclusion, these are supposed to give the financial burden to the subcontractor. So, it is very important to predict the construction preparation cost calculation by the risk factors in the bidding stage and to calculate the bid unit cost considering the target profit of the subcontractor in the process of the mutual agreement and performance of the contract. In these points of view, this study analyzes how the importance of the risks influencing the bidding cost calculation affect the construction cost, and this analysis can be used as the basic data to establish the suitable bid strategy of the subcontractor.

• Journal of the Korean Dietetic Association
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• v.10 no.2
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• pp.190-196
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• 2004

The purposes of this study were to investigate the importance level on factors affecting the foodservice management contract perceived by the salespersons in the foodservice company. To get the data on the perceived importance level on the affecting the foodservice management contract, the questionnaires were developed by the delphi technique and modified by the pilot test. The questionnaires consisted of 4 categories and 19 items on the factors affecting the foodservice management contract and the importance level on the factors were measured by 5-likert scale. From March 12 to April 13 in 2003, the self-administrative questionnaires were mailed to the 60 salespersons. The questionnaires were responded from the 48 salespersons(respondent rate : 77 %). As a result, the salesperson.perceived importance level of "the sales ability" was higher than those of the other categories in the private contract and the salesperson.perceived importance level of "the evaluation of the foodservice company" was higher than those of the other categories in the competitive bid. The importance of the "the evaluation of the foodservice company" between the private contract and the competitive bid was significantly different(p<.05), and the importance of "the sales ability" of the competitive bid was significantly higher than that of the private contract(p<.001).

• The Journal of the Korea Contents Association
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• v.19 no.7
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• pp.36-46
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• 2019

If stock market is efficient, any well-devised trading rule can't consistently outperform the average stock market returns. This study aims to verify whether the strategy based on bid-ask volume information can beat the stock market. I suggested a day trading strategy using order imbalance indicator and empirically analyzed its profitability with the KOSPI 200 index futures data from 2001 to 2018. Entry rules are as follows: If BSI is over 50%, enter buy order, otherwise enter sell order, assuming that stock price rises after BSI is over 50% and stock price falls after BSI is less than 50%. The empirical results showed that the suggested trading strategy generated very high trading profit, that is, its annual return runs to minimum 71% per annum even after the transaction costs. The profit was generated consistently during 18 years. This study also improved the suggested trading strategy applying the genetic algorithm, which may help the market practitioners who trade the KOSPI 200 index futures.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.26 no.6D
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• pp.975-983
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• 2006

This study analyzed bidding data for construction projects ordered by the Public Procurement Service under the lowest bidding system since 2001 by using statistical technique in terms of construction types, company sizes, bidding prices. This study brings out construction company's bidding practices and problems caused by the current lowest bidding system and suggests the way to mitigate the problems and to improve the lowest bidding system. The analysis shows the problem of winning a bid in abnormally low price under the lowest bidding system, feared at the start, was realized. As bidding practice has polarized with low and high price, the analysis shows that the lowest bid system's market has a high possibility to be distorted by construction companies' bid strategies. To complement the lowest bidding system's problem, the analysis shows that introduction of the bidding system using particulars where bidders estimate construction quantities and unit prices by themselves is needed.

• Journal of Information Technology Services
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• v.13 no.2
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• pp.185-194
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• 2014

Recently, as value for practical use of big data is evaluated, companies and organizations that create benefit and profit are gradually increasing with application of big data. But specifical and theoretical study about possible risk factors as introduction of big data is not being conducted. Accordingly, the study extracts the possible risk factors as introduction of big data based on literature reviews and classifies according to big data processing, data collection, data storage, data analysis, analysis data visualization and application. Also, the risk factors have order of priority according to the degree of risk from the survey of experts. This study will make a chance that can avoid risks by bid data processing and preparation for risks in order of dangerous grades of risk.

• The KIPS Transactions:PartD
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• v.9D no.5
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• pp.955-962
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• 2002

Commercial internet auction systems have been successfully used recently. In those systems, because reserve prices of auction items are given by sellers only, the success bid rate can be decreased due to the large difference between the reserve price and the normal price. In this paper, we propose an agent that generates reserve prices to sellers based on past auction data and item prices gathered from the web. Through performance experiments, we show that the successful bid rate increases by preventing sellers from making unreasonable reserve prices. Using the pricing agent, we design and implement an XML-based auction system on the web.

• International conference on construction engineering and project management
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• 2011.02a
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• pp.534-541
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• 2011

Risk evaluation approaches for bidding on international construction projects are typically partitioned into three stages: country selection, project classification, and bid-cost evaluation. However, previous studies are frequently under attack in that they have several crucial limitations: 1) a dearth of studies about country selection risk tailored for the overseas construction market at a corporate level; 2) no consideration of uncertainties for input variable per se; 3) less probabilistic approaches in estimating a range of cost variance; and 4) less inclusion of covariance impacts. This study thus suggests a three-staged risk evaluation model to resolve these inherent problems. In the first stage, a country portfolio model that maximizes the expected construction market growth rate and profit rate while decreasing market uncertainty is formulated using multi-objective genetic analysis. Following this, probabilistic approaches for screening bad projects are suggested through applying various data mining methods such as discriminant logistic regression, neural network, C5.0, and support vector machine. For the last stage, the cost overrun prediction model is simulated for determining a reasonable bid cost, while considering non-parametric distribution, effects of systematic risks, and the firm's specific capability accrued in a given country. Through the three consecutive models, this study verifies that international construction risk can be allocated, reduced, and projected to some degree, thereby contributing to sustaining stable profits and revenues in both the short-term and the long-term perspective.