• Journal of the Korean Institute of Landscape Architecture
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• v.14 no.2
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• pp.81-90
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• 1986

The full grasp of recreation demand and factors affecting on recreation demand can be very important information for park planning and management. The object-tives of this study are to investigate factors affecting the fluctuation of urban park visitors and to analyze the relationship between these factors and the daily parti-cipations. The results were as follows; 1) The peak of monthly participations comes on May, April, August and October in order. And these months are specified as school picnic period and vacation of school children. 2) In correlation analysis, the variables such as ‘Day of a week(D)’, ‘Monthly mean temp.(T)’and ‘Monthly character(M)’have high correlations with ‘No. of visitors’in order. And it is better to categorize months by its charater(picnic period in school, vacation etc) than by seasons. 3) Candidate regression model were established, as for 1984 log U= 1.51 + 0.64D1 + 0.02T + 0.36W1 - 0.23M4 + 0.003SS + 0.24Ml($R^2$=0.5326) where, U=no. of daily visitors D1 = sunday.ho1iday(1), weekday(0) T=monthly mean temperature($^{\circ}C$) W1= weather (sunny.cloudy(1) , rainy (>5mm)(0)> M4=non vacations and non school picnic period(1) , if not (0) SS=monthly sunshining hours M1=summer vacation(1), if not(0) 4) The most important variable was ‘Day of a week’(sunday.holiday or not). And temperature, weather and monthly charcter(especially picnic period of school and vacation) were in turn, hence ‘Children's grand park’shows the use pattern of park.

• Journal of Service Research and Studies
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• v.12 no.4
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• pp.82-93
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• 2022

The food service industry is a major driver of global sustainable food consumption. By understanding food consumption behavior, restaurant managers can forecast demands and reduce pre-consumer food waste. This study investigates the relationship between influencing factors and the number of customers at restaurants and cafés. These factors are weather-related factors, including rain and temperature, and school-related factors, including exams and the day of the week. Based on these four factors, 24 possible combinations were created. Three representtive days were chosen for each weekday combination. Besides, one representative day was chosen for each weekend combination. In total, 48 days were sampled throughout the year. Customer data were collected from six restaurants and cafes on a Korean university campus. Conjoint analysis was used to determine the relative importance of each variable to customer numbers. Following that, utility scores were standardized and mapped to determine the best condition when the number of customers was at its peak. In addition, each store's sales were compared using Pearson's Correlation Coefficient. The findings support that temperature and rain influences are correlated with the number of customers. Furthermore, we discovered that temperature was far more significant than rain in determining the number of customers. The paper discusses the implications of weather to forecast food and beverage demand and predict meal choices.

• Journal of Korea Trade
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• v.26 no.8
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• pp.21-36
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• 2022

Purpose - Carbon emission standards are based on the "production-based carbon emissions" generated by the production of goods in the relevant country which were the existing measurement methods. However, can such carbon emissions measurement standards be established international? For example, some of the goods produced in developing countries are produced for the demand of developed countries. The method of measuring carbon emission based on the final demand of a certain country is called "consumption-based carbon emissions." This study compares productionand consumption-based CO₂ emissions according to economic growth in ninety-three countries categorized by income level. Design/methodology - Our empirical model considers the difference between production- and consumption-based CO₂ emissions according to economic growth. Also, our model investigated whether the EKC hypothesis in most of the previous studies that had been based on production-based emissions was also established in the consumption-based emission model. Considering the continuous characteristics of CO₂, we utilized the generalized method of moments (GMM), specifically a system GMM econometric technique because CO₂ in the previous period can affect CO₂ in the present period. Findings - Our main findings can be summarized as follows: The results show that for the consumption-based CO₂ emissions model, CO₂ continuously increases as economic growth increases in the upper-middle income countries. The inverted U-shaped result was found in the case of the production-based model. However, in the lower-income countries, an inverted-U shape in which CO₂ emissions decrease at some point as the economy grows in the production-based model does not appear. On the other hand, in the consumption-based model, an inverted U-shaped result was obtained when estimating with system-GMM. Additionally, the proportion of manufacturing, energy imports, and energy consumption had an effect on both the production- and the consumption-based model regardless of the group's CO₂ emissions. On the basis of such assessments, policymakers need to consider not only production- but also consumption-based options. Originality/value - Previous studies have mainly focused on production-based CO₂ emissions, with most of them revolving around economic growth or the effect of various social and economic factors on CO₂ emissions. However, this study considers the relationship with economic growth using consumption-based emissions as a dependent variable by classifying ninety-three countries by income level.

• Journal of the Korea Organic Resources Recycling Association
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• v.32 no.3
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• pp.19-29
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• 2024

Total organic carbon (TOC) represents the total amount of organic carbon contained in water and is a key water quality parameter used, along with biochemical oxygen demand (BOD) and chemical oxygen demand (COD), to quantify the amount of organic matter in water. In this study, a model to predict TOC was developed using XGBoost (XGB), a representative ensemble machine learning algorithm. Independent variables for model construction included water temperature, pH, electrical conductivity, dissolved oxygen concentration, BOD, COD, suspended solids, total nitrogen, total phosphorus, and discharge. To quantitatively analyze the impact of various water quality parameters used in model construction, the feature importance of input variables was calculated. Based on the results of feature importance analysis, items with low importance were sequentially excluded to observe changes in model performance. When built by sequentially excluding items with low importance, the performance of the model showed a root mean squared error-observation standard deviation ratio (RSR) range of 0.53 to 0.55. The model that applied all input variables showed the best performance with an RSR value of 0.53. To enhance the model's field applicability, models using relatively easily measurable parameters were also built, and the performance changes were analyzed. The results showed that a model constructed using only the relatively easily measurable parameters of water temperature, electrical conductivity, pH, dissolved oxygen concentration, and suspended solids had an RSR of 0.72. This indicates that stable performance can be achieved using relatively easily measurable field water quality parameters.

• Journal of Korean Society of Transportation
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• v.30 no.1
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• pp.135-147
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• 2012

The benefit of traffic information on variable message sign can be divided into two. At the public level, the benefit of ATIS is the travel time saving, which is not only induced from ATIS, but also mixed with that of ATMS. In the economic appraisal of ITS, the benefit of ATIS has so far been regarded as the derived benefit from ATMS. At the user level, the benefit of ATIS is reduced driver uncertainty through the forward traffic status information. User can benefit from the information on VMS and therefore may have the willingness to pay for it. Recently attempt to qualify the value of information on VMS was increased, but there was a danger of distorting or over-estimates of the ATIS benefit because the related studies didn't consider the time-dependent attributes of traffic information and provided the single value. Estimates of the time-varying value should be needed for a rigorous economic appraisal of ATIS. In this study, we varied the value of information on VMS according to peak and non peak trip and verified the hypothesis that time-varying of value was statistically significant.

• Journal of Korea Port Economic Association
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• v.33 no.3
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• pp.35-52
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• 2017

Interest and demand in heavy cargo logistics is increasing and becoming more diverse as economic scales have expanded and manufacturing activity has increased. Although cargo moves via maritime and/or land transportation, there is currently insufficient research on the actual condition of heavy cargo logistics. The purpose of this study is to carry out an in-depth analysis of heavy cargo laws, systems, logistics patterns, and current transportation status. By proposing measures to solve existing problems, this study aims to make an important and ongoing contribution to the scarcely studied field of heavy cargo logistics. The result of regression analysis on the main seven factors show that transportation frequency and law/system structure have a positive effect on working conditions. Furthermore, the result of correlation analysis on the main seven factors show that the cargo weight variable is highly positively correlated with cargo size. Also, the working conditions variable is highly positively correlated with the law/system structure. Detailed proposal measures to solve existing problems are summarized as follows. First, it is necessary to establish a clear concept of heavy cargo as numerous existing definitions differ. Second, laws and provisions relating to maritime and land transportation of heavy cargo need to be established and consolidated as current applicable legislation is insufficient. Third, the classification system for heavy cargo transportation needs improvement. Fourth, it is necessary to improve transportation performance statistics and the aggregate criteria system. Finally, the management system of heavy cargo also needs improvement.

• The KIPS Transactions:PartB
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• v.9B no.6
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• pp.835-844
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• 2002

The number of channels available to a video server is limited since the number of channels a video server can support is determined by its communication bandwidth. Several approaches such as batching, piggybacking and patching have been proposed to reduce I/O demand on the video server by sharing multicast data. Patching has been shown to be efficient in the matter of the cost for VOD systems. Unlike conventional multicast techniques, patching is a dynamic multicast scheme which enables a new request to join an ongoing multicast. In addition, true VOD can be achieved since a new request can be served immediately without having to wait for the next multicast. In this paper. we propose two types of channel reservation patching algorithm : a fixed channel reservation patching and a variable channel reservation patching. To immediately schedule the requests for popular videos, these algorithms reserve the channels of video server for the fixed number of popular videos or for the variable number of popular videos which is determined dynamically according to the load of video server. The performance of the proposed algorithms is evaluated through simulations, and compared with that of simple patching. Our performance measures are average defection rate, average latency, service fairness and the amount of buffered data according to video server loads. Simulation results show that the proposed channel reservation patching algorithms provide better performance compared to simple patching algorithm.

• Journal of Distribution Science
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• v.16 no.3
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• pp.79-86
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• 2018

Purpose - Many retail stores tend to use scarcity-laden message in order to influence consumers, where scarcity refers to insufficiency of product supply or time of availability. For example, inside stores, the displayed products are often accompanied by scarcity message such as 'exclusive offer, limited time only.' According to past research, scarcity has a positive effect on product evaluation, since scarcity can acts as a signal of consumer demand, and thus product quality. Prior studies argue that consumers face a scarce product, they logically infer that other consumers buying the product in large numbers cause the scarcity. We propose that scarcity can be interpreted as a sales tactic artificially created by retail stores in order to increase sales of product. Research design, data, and methodology - We use a persuasion knowledge perspective framework to develop our hypotheses. In the present research, we show that product curation type is a key variable that moderates consumer response to scarcity, and thus the scarcity effect on product evaluation. Results - In this research, we showed when scarcity-laden message was used inside the store using consumer-centric curation message, scarcity had a positive effect on product evaluation. In contrast, when scarcity-laden message was used inside the store using marketer-centric curation message, the positive of scarcity message on product evaluation was diluted. Conclusions - Our study makes two important contributions to the literature on consumer response to scarcity. First, we identify a variable - namely, product curation type - that determines when either 'scarcity = good' or 'scarcity = marketing tactic' interpretation is likely to be dominant. Second, we cite persuasion knowledge perspective to explain the moderating function of product curation type in a retail store-related scarcity context. This research is relevant to practitioners, such as brand manager, retail environment manager, and advertising agencies, for the effective use for the scarcity-laden message in retail. The proposed moderator can operate in many real-life situations in retail where consumers are exposed to scarcity. And curation message related to scarcity has been facilitated by the inner-retail activities. These factors of the marketplace indicate that the boundary conditions of scarcity can have a significant effect on real-life consumer judgment.

• Journal of Digital Convergence
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• v.15 no.6
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• pp.9-17
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• 2017

The opening of public data has been perceived as a critical factor in deciding a country's rise or fall. Since the global economic crisis, countries around the globe have expanded the supply of public data as a new growth engine to create significant economic effects. As a result, there has been a rising demand for a study on the influence of public data in the private sectors. This study attempted to achieve the following objectives. First, the effects of independent variables-system quality, information quality, information security, social influence, innovation and assistance by the public organization- on the intention to use the public data was examined. Second, the effects of the mediating variables - Perceived Ease of Use (PEU) and Perceived Usefulness (PU) - on the independent variables and intention to use (dependent variable) were investigated. Third, after selecting utilization type, frequency of public data usage and frequency of occupational & e-government service usage as moderating variables, their effects on the relationship between the independent variables and dependent variable (intention to use them in the private sector) were studied. It is expected that the study results would be useful in developing strategies aimed to utilize public data in the private sectors.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.6 no.2
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• pp.45-55
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• 1986

This study proposes the explanatory indices of urban traffic for the purpose of solving the ambiguity of selection of the explanatory variables, which always raises problems in case of the travel-demand forecasting in the urban transportation planning, and develops optimal urban traffic generation models. The multiple regression models for objective traffic generation are developed by using the proposed explanatory inidces. Objective variables that can be explained by one explanatory variable are modified into simple regression type (Y=bX) in order to ensure the nonnegativity of traffic generation. Similarities are noted in the generaton characteristics of generated traffic from homogeneous land-use activity. Objective variables that can not be explained by multiple variable, such as trip attraction of school and trip generation of social-recreation, are classified by the characteristics of each zone. And traffic generation forecasting models are built as homogeneous zone group, the validity of each model being tested by a statistical method. It is desired that the forecasting precision is in improved by easy and simple method. Accordingly, trip generation rates are calculated from each land-use activity, and trip generation rates for practical application are proposed by considering their stability.