• International conference on construction engineering and project management
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• 2022.06a
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• pp.253-260
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• 2022

Existing web-based cost databases have proved invaluable for construction cost estimating. These databases have been utilized to compute approximate cost estimates using assembly rates, unit rates, and etc. These web-based databases can be used independently with traditional cost estimation methods (manual methods) or used to support BIM-based cost estimating platforms. However, these databases are rigid, costly, and require a lot of manual inputs to reflect recent trends in prices or prices relative to a construction project's location. To address this gap, this study integrated deep learning techniques with web-based price analysis to develop a database that incorporates a project's location cost estimating standards and current cost trends in generating a cost estimate. The proposed method was tested in a case study project in Lagos, Nigeria. A cost estimate was successfully generated. Comparison of the experimental results with results using current industry standards showed that the proposed method achieved a 98.16% accuracy. The results showed that the proposed method was successful in generating approximate cost estimates irrespective of project's location.

• Journal of Korean Society of Water and Wastewater
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• v.20 no.4
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• pp.527-534
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• 2006

Demand side management(DSM) is the newly raised issues in the water resources management in recent. Many of the policy tools among demand management, the most important measures might be a pricing system. Furthermore, the responses of consumers on the price for water consumption level is the key factor for policy making. Here, we estimated panel data for 167 regions and over 7 years periods in Korea. Compare to other previous studies the price elasticities were somewhat low. The estimated price elasticity was -0.05. It was because the short term estimated period may derive lower elasticities. However, it might be a recent trend after the continuous increment of water pricing and consumers not willing to decrease their residential water consumption with increasing water pricing. According to this results, water saving effect might be much smaller than we expect with pricing policy. However, It does not imply there is no price effects on water consumption and it's still meaningful as a tool of water management.

• Journal of the military operations research society of Korea
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• v.27 no.1
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• pp.10-27
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• 2001

This paper deals with the application of PRICE model in estimating the proper acquisition cost for weapon budgeting phase. The PRICE(Parametric Review of Information for Costing and Evaluation) Hardware model is a computerized method for deriving cost estimates of electronic and mechanical hardware assemblies and systems. The model can be used in obtaining not only initial cost estimates in conceptual phase, but also detailed cost estimates in budgeting phase depending on available historical and empirical data. We analyzed first step cost estimate parameters and derived cost equations using PRICe output dta. Using weight and complexity, We can find cost variation. Sensitivity analysis shows that cost increases exponentially as complexity increases exponentially as complexity increases. We estimated KAAV\`s (Korea Amphibious Assault Vehicle) production cost using the PRICE model and compare with engineering cost estimates which is based on actual production data submitted by the production company. The result shows that tow estimates are close within $\pm2%$ differences.

• Industrial Engineering and Management Systems
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• v.10 no.1
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• pp.84-94
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• 2011

In this paper, we propose a method to provide the distribution of option price under local volatility model when market-provided implied volatility data are given. The local volatility model is one of the most widely used smile-consistent models. In local volatility model, the volatility is a deterministic function of the random stock price. Before estimating local volatility surface (LVS), we need to estimate implied volatility surfaces (IVS) from market data. To do this we use local polynomial smoothing method. Then we apply the Dupire formula to estimate the resulting LVS. However, the result is dependent on the bandwidth of kernel function employed in local polynomial smoothing method and to solve this problem, the proposed method in this paper makes use of model averaging approach by means of bandwidth priors, and then produces a robust local volatility surface estimation with a confidence interval. After constructing LVS, we price barrier option with the LVS estimation through Monte Carlo simulation. To show the merits of our proposed method, we have conducted experiments on simulated and market data which are relevant to KOSPI200 call equity linked warrants (ELWs.) We could show by these experiments that the results of the proposed method are quite reasonable and acceptable when compared to the previous works.

• Proceedings of the Korean Institute of Building Construction Conference
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• 2018.11a
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• pp.124-125
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• 2018

Recently, risk analysis studies regarding the architecture development project have been carried out by applying probabilistic method. However, it had a limit that this studies was conducted in only an apartment. Therefore, the objective of this study is to develop an optimal price estimation model that can be utilized on residential officetel project by applying Monte Carlo simulation. To achieve the objective, first, the variables are selected affecting the feasibility of an officetel based on literature review. Second, causal loop diagram is constructed by arranging the relationship between variables, then the import and expense model is suggested. Third, to carry out optimized parcel price, the range limits are set for each variables then Monte Carlo simulation is performed. In the future, the developed model is expected to help decision-makers as a tool to determine both risk and feasibility of the officetel development project.

• International conference on construction engineering and project management
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• 2015.10a
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• pp.77-81
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• 2015

The unit price contracting is the standard contracting method for highway projects in the U.S. As a result, state highway agencies have collected a large amount of historical bid data that they can use to determine engineer's estimates for future projects. The estimator must carefully consider various characteristics of a new project such as its location to determine an engineer's estimate as accurate as possible before bid letting. Higher cost estimates can result in the loss of the available budget and lower cost estimates may lead to deferral and delay of projects. The study uses the historical bid data obtained from Iowa Department of Transportation and develops a Geographic Information System (GIS) tool to visually show the variation of unit prices over the map using a spatial interpolation technique. The interpolation map can be used to estimate the unit price of the item at any location across Iowa. This noble method allows the estimator to effectively and fully utilize the historical bid data in a very time efficient manner and determine more accurate cost estimation.

• Journal of the Korean Geographical Society
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• v.38 no.6
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• pp.949-960
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• 2003

The marginal implicit price of air quality can be measured by taking a partial derivative of hedonic price function (HPF) with respect to the level of air quality. It has been pointed out that the size of the marginal implicit price varies with the use of different function forms, different estimation methods, and the different ways of measuring air quality level in estimating HPF. In addition to these factors, this study shows theoretically and empirically the way housing properties are represented on a digital map could differentiate the size of marginal implicit price of air quality when GIS is used to measure location attributes of the housing properties in the Korean apartment market. Furthermore, this study shows that the degree of difference in the marginal implicit price due to the manner in which housing properties are represented on a digital map can be larger than the degree of difference in the marginal implicit price due to using different function forms and estimation methods. The major implication from the results of this study is that one should carefully try diverse ways of representing housing properties in the Korean apartment market on a digital map in the process of estimating HPF, as he or she usually tries diverse function forms and estimation methods, to see if the value of the marginal implicit price of air quality varies substantially.

• Journal of Korean Society for Quality Management
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• v.47 no.4
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• pp.687-700
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• 2019

Purpose: The purpose of this study is to investigate the interaction effects between price determinants of artworks. We expand the methodology in art market by applying machine learning techniques to estimate the price of artworks and compare linear regression and machine learning in terms of prediction accuracy. Methods: Moderated regression analysis was performed to verify the interaction effects of artistic characteristics on price. The moderating effects were studied by confirming the significance level of the interaction terms of the derived regression equation. In order to derive price estimation model, we use multiple linear regression analysis, which is a parametric statistical technique, and k-nearest neighbor (kNN) regression, which is a nonparametric statistical technique in machine learning methods. Results: Mostly, the influences of the price determinants of art are different according to the auction types and the artist 's reputation. However, the auction type did not control the influence of the genre of the work on the price. As a result of the analysis, the kNN regression was superior to the linear regression analysis based on the prediction accuracy. Conclusion: It provides a theoretical basis for the complexity that exists between pricing determinant factors of artworks. In addition, the nonparametric models and machine learning techniques as well as existing parameter models are implemented to estimate the artworks' price.

• Asian Journal of Business Environment
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• v.10 no.1
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• pp.19-28
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• 2020

Purpose: This research aims to investigate the impact of corporate integrity on stock price crash risk. Research design, data, and methodology: Taking 1419 firms listed in Shenzhen Stock Exchange in China as a sample, this paper empirically analyzed the relationship between corporate integrity and stock price crash risk. The main integrity data was hand-collected from Shenzhen Stock Exchange Website. Other financial data was collected from CSMAR Database. Results: Findings show that corporate integrity can significantly decrease stock price crash risk. After changing the selection of samples, model estimation methods and the proxy variable of stock price crash risk, the conclusion is still valid. Further research shows that the relationship between corporate integrity and stock price crash risk is only found in firms with weak internal control and firms in poor legal system areas. Conclusions: Results of the study suggest that corporate integrity has a significant influence on behaviors of managers. Business ethics reduces the likelihood of managers to overstate financial performance and hide bad news, which leads to the low likelihood of future stock price crashes. Meanwhile, corporate integrity can supplement internal control and legal system in decreasing stock price crash risks.

• The Journal of Fisheries Business Administration
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• v.47 no.1
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• pp.1-20
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• 2016

The purpose of this study is to assess the effects of outlook project for olive flounder, from the view point of price stabilization, market efficiency, and causality of the prices in different distribution channels. Analytical results show that the volatility of producer price of olive flounder has been significantly mitigated after the implementation of the outlook project. The market efficiency is estimated to be improved after implementing the outlook project although there is an inefficiency on price determination process in some producing regions. The causality test on the producer and wholesale price shows that producing stage leads the wholesale stage in forming the prices. It is found that Jeju leads the flounder price on the size of 500g and 2kg, while Wando leads the price of 1kg size. These estimation result as whole indicate that outlook project for olive flounder has accomplished the intended goals.