• Environmental and Resource Economics Review
• /
• v.13 no.3
• /
• pp.337-366
• /
• 2004

Contingent Valuation Method (CVM), as non-market valuation approach, has been criticized on that respondents may not realistically reflect their budget constraints in answering willingness to pay (WTP) for hypothetical CV questions. This paper empirically estimates the income calibration factor associated with CV responses through combining travel cost method and contingent valuation method in a utility-theoretic framework. The joint model of recreation demand function and contingent WTP function was applied to an important case study on the Man Kyoung River system, whose water quality is at issue because of the Sae Alan Kum reclamation project. Relevant economic variables such as price, income and water quality had significant influence as anticipated by the economic theory. Equally important, the income calibration factor was not significantly different from one, suggesting that the systematic discrepancies of CV responses relative to the actual behavior was not detected at least in terms of budget exaggeration. Overall, this study supports the notion that carefully designed CVM studies can provide informative data on individuals' willingness to pay for environmental quality changes.

• Journal of Energy Engineering
• /
• v.20 no.4
• /
• pp.318-329
• /
• 2011

This study focuses on enhancing the accuracy of consumption function of Korean natural gas for city gas. It is using time-series model with time-varying coefficients taking into account the recent abnormal temperature phenomenon and the changing gross domestic product (GDP) as important variables. This study estimates the cointegrating regression model for the long-run estimation and the error correction model for the short-run estimation. The consumption function of Korean natural gas is estimated to be influenced by the time-varying coefficients of GDP and temperature. Using the estimated time-series model with time-varying coefficients, this study forecasts the consumption of natural gas for city gas from July 2011 to December 2012. The consumption in 2011 would be 18,303 thousand tons, which is little different from the imported 18,681 thousand tons. The consumption of natural gas for city gas in 2012 is forecast to be 19,213 thousand tons. The consumption model of this study is needed to extend by considering the relative prices between natural gas and its substitutes, the scale of consumers and others.

• Journal of Korean Society of Transportation
• /
• v.23 no.2
• /
• pp.25-36
• /
• 2005

In this study, we suggested a new approach method forecasting distribution demand of urban rail transit usign fuzzy control, with intend to reflect irregularity and various functional relationship between trip length and distribution demand. To establish fuzzy control model and test this model, the actual trip volume(production, attraction and distribution volume) and trip length (space distance between a departure and arrival station) of Daegu subway line 1 were used. Firstly, usign these data we established a fuzzy control model, nd the estimation accuracy of the model was examined and compared with that of generalized gravity model. The results showed that the fuzzy control model was superior to gravity model in accuracy of estimation. Therefore, wwe found that fuzzy control was able to be applied as a effective method to predict the distribution demand of urban rail transit. Finally, to increase the estimation precision of the model, we expect studies that define membership functions and set up fuzzy rules organized with neural networks.

• Journal of Digital Convergence
• /
• v.19 no.3
• /
• pp.55-64
• /
• 2021

Public libraries are a space where residents learn a wide range of knowledge and ideologies, and as they are directly connected to life, various related studies have been conducted. In most previous studies, variables such as population, traffic accessibility, and environment were found to be highly relevant to library use. In this study, it can be said that the difference from previous studies is that the book borrow demand and relevance were analyzed by reflecting the variables of cultural characteristics based on the book borrow history (1,820,407 cases) and member information (297,222 persons). As a result of the analysis, it was analyzed that as the increase in borrows for social science and literature books compared to technical science books, the demand for book borrows increased. In addition, various descriptive statistical analyzes were used to analyze the characteristics of library book borrow demand, and policy implications and limitations of the study were also presented based on the analysis results. and considering that cultural characteristics change depending on the location and time of day, it is believed that related research should be continued in the future.

• Environmental and Resource Economics Review
• /
• v.24 no.2
• /
• pp.365-410
• /
• 2015

Block-rate structures are widely used in utility-pricing, including the Korean residential electricity sector. In the case of the current pricing structure, Korean citizens are highly concerned about incurring excessive electricity costs. For these reasons, there have been many discussions concerning mitigation of the strict pricing structure. Existing studies on the residential electricity demand function under block-rate structure have the following three issues - the consumer's budget constraint is non-linear, perceived price under block-rate structure is uncertain, block-rate structure has endogeneity in the price variable. In this context, this paper estimates the residential electricity demand function using micro-level household expenditure data and simulates the impact of alternative block-pricing schedules.

• Journal of the Korea Academia-Industrial cooperation Society
• /
• v.2 no.2
• /
• pp.121-127
• /
• 2001

The purpose of this paper is to verify and statistically analyze the effect of credit card expenditure on money demand. Statistical analysis was Performed regarding credit spending volume. Ml, M2, M3, non-monetary banking deposit (OFI) and many other parameters based on time-series data for 14 years, from 1985 to 1998. The results suggest that credit card is not the main cause of inflation or increase of money supply but it would become an economic creation on contributing to human life in the coming century. Therefore the monetary authorities must develop the credit card industry, so as to improve positive function of credit cards and to keep controlling some of its negative functions minimally.

• Journal of Korean Society of Transportation
• /
• v.22 no.4 s.75
• /
• pp.117-134
• /
• 2004

Truck traffic accounts for a substantial fraction of the traffic stream in many regions and is often the source of localized traffic congestion, potential parking and safety problems. Truck trips tend to be ignored or treated superficially in travel demand models. It reduces the effectiveness and accuracy of travel demand forecasting and may result in misguided transportation policy and project decisions. This paper presents the development of speed-flow relationships with truck impacts based on CORSIM simulation results in order to enhance travel demand model by incorporating truck trips. The traditional BPR(Bureau of Public Road) function representing the speed-flow relationships for roadway facilities is modified to specifically include the impacts of truck traffics. A number of new speed-flow functions have been developed based on CORSIM simulation results for freeways and urban arterials.

• Journal of Korean Society of Transportation
• /
• v.30 no.3
• /
• pp.107-118
• /
• 2012

The purpose of the study is to analyze the travel characteristics of freight trucks in metropolitan areas, focusing on activity generation, destination choice, and trip chaining behaviors. The results showed that the number of service companies at departure areas has a primary influence on the activity generation pattern and destination choice behavior of trucks in metropolitan areas. The number of trips within a trip chain is largest, in case where the prevailing industry in destination areas is wholesale or retail and the shipment item is food or beverage. These results imply that for the reasonable estimation of truck travel demand both the trip chaining behaviors and the industrial compositions in departure and destination areas should be separately considered for each type of commodity.

• Journal of Digital Convergence
• /
• v.12 no.6
• /
• pp.125-134
• /
• 2014

Supply Chain Management(SCM) is getting important, because size of the company is getting bigger and the kinds of product are various. In the case of manufacturing corporation, for the optimization of SCM, we have to make production and distribution plan by considering the various fluctuation in the aspect of integration. In this paper, first, It proposed the reasonable operational way of the SCM about when the customer's demanding is various and demanding expectation fluctuates in capacity standardization of producer stage. Second, the paper proposed the management way for demanding by considering confirmed demanding information, related inventory expense and demanding shortage expense when we make production and distribution plan. The paper applied the genetic algorithm proved for current usefulness. it proposed the optimal operational way for SCM by dividing into 2 ways for dealing with the duration of confirmed demanding information and various fluctuation.

• The Journal of Society for e-Business Studies
• /
• v.25 no.2
• /
• pp.49-63
• /
• 2020

The accurate prediction of box office in the early stage is crucial for film industry to make better managerial decision. With aims to improve the prediction performance, the purpose of this paper is to evaluate the use of machine learning methods. We tested both classification and regression based methods including k-NN, SVM and Random Forest. We first evaluate input variables, which show that reputation-related information generated during the first two-week period after release is significant. Prediction test results show that regression based methods provides lower prediction error, and Random Forest particularly outperforms other machine learning methods. Regression based method has better prediction power when films have small box office earnings. On the other hand, classification based method works better for predicting large box office earnings.