• Korean Journal of Agricultural Science
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• v.51 no.3
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• pp.399-412
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• 2024

This study aimed to analyze consumers' behaviors and reactions to the use-by date labeling system and provide policy implications for its efficient implementation, by utilizing 213 consumers data conducted via an Internet survey using the Google online form. We refer "pure consumption date" as the period that have passed sell-by date yet have not passed use-by date. Consumers' willingness to accept (WTA) for pure consumption date food was surveyed, which means the discount ratio of pure consumption date food compared to the original price by sell-by date. Setting the expected effects of use-by date labeling system as five: food waste reduction (waste), food purchasing cost reduction (cost), and international standardization (standard), etc., Tobit regression result showed waste had the greatest (negative) impact on consumer's WTA, while cost and standard had positive impact on consumer's WTA. The logistic regression result revealed that consumers trying to reduce grocery costs have higher probability to purchase use-by date labeling food, and further expect higher WTA. Also consumers valuing the importance of environmental protection or food quality are more likely to purchase use-by date food. Conversely consumers valuing food safety importance tend to have negative impact on purchasing use-by date food, hence expect higher WTA. It is noteworthy that consumers valuing the importance of promoting the use-by date labeling system have significantly higher probability of purchasing use-by date food. Additionally, consumers' WTA averaged 54.3%, implying that consumers are willing to purchase use-by date food when it is discounted more than 54.3% from the original price, where women expect higher WTA, the aged over 60 expect higher WTA, furthermore single-parent households expect 21.3% higher than the average WTA. However, old-aged, unmarried women, higher educated and higher income groups were negative in purchasing use-by date food. These results suggest that customized sales policy and effective promotion strategies reflecting socio-demographic characteristics of consumers would be necessary to achieve effective implementation of the newly introduced system.

• Korean Journal of Construction Engineering and Management
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• v.25 no.2
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• pp.45-55
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• 2024

This study analyzed the efficiency determinants of specialty construction companies by industry using the DEA model and the Tobit model. The analysis targets are 394 specialty construction companies as of 2022. As a result of analysis of efficiency determinants using 12 company characteristics as independent variables, the biggest problem for specialty construction companies was overall efficiency reduction due to rising labor costs. In addition, in a situation where construction companies' loan regulations are severe, the debt ratio was found to have a positive effect on efficiency. Company size had a different impact by industry, and the number of businesses held, credit score, and total capital turnover had an effect only on some industries. This study presents results that are an advance on existing research in that it strategically analyzes factors for improving the efficiency of specialty construction companies. However, it has limitations such as limiting the analysis to only specialty construction companies subject to external audit, insufficient number of companies subject to analysis by industry, and analyzing relative efficiency in the same category for each industry.

• Journal of Biosystems Engineering
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• v.34 no.1
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• pp.8-14
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• 2009

When a farmer buys a tractor, the power size of a tractor is determined by various factors such as farm size, farmer's age, farming type, topographical area of farm. Relationships between tractor selection and these factors were found. Three regression models were developed to analyze the relationship. Those models were an OLS-1 model (based on 567 samples having tractors), an OLS-2 model, and a Tobit model (both based on the 1,941 samples). Regression analysis results showed that farm size and farmer's age affected selection of power size for all models at an 1% significance level. It was also shown that some farming types also had significant relationships with the tractor power size. Upland cultivating farmers and livestock farmers had larger tractors than rice cultivating farmers, while orchard farmers had smaller tractors. As for the topographical area, only middle area had significant difference with plain area. Farmers who had a rice-transplanter or a combine had larger tractors than those who didn't.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.42 no.2
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• pp.323-330
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• 2017

The millimeter wave band is in the extremely high frequency band whose frequency and wavelength are 30-300GHz and 10-1mm respectively. When the obstacles block the propagation path which is not Line-of-Sight (LoS), due to a high propagation loss, it is hard to receive a signal in the millimeter wave band. Therefore When the path loss is measured in the millimeter wave band, the signal which is not distinguished from the noise is observed. Consequently, the path loss data which is limited in certain value is observed in the high propagation loss environment. If the original least square is implemented without taking the limitation of certain value into account, the path loss exponent may be underestimated. In this paper, the performance of Tobit Maximum Likelihood Estimation, Heckman Two-stage Model and Truncation Regression Model which can estimate properly in the censoring or truncated environments are compared.

• International Journal of Highway Engineering
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• v.14 no.6
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• pp.139-148
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• 2012

PURPOSES : The accuracy of travel time information is a key measure of effectiveness and reliability of advanced traveler information systems. This study aims at investigating drivers' perception on the acceptable level of information accuracy and their corresponding valuations. METHODS : A questionnaire survey was executed for collecting driver perception data to capture the expectation level of travel time information provided and their willingness to pay for the information. A Tobit model was adopted for exploring the relationship among the acceptable level, driver socioeconomic characteristics and travel attributes. Since drivers' willingness to pay for accurate travel time information can be different according to their travel lengths, a piecewise linear regression model was developed to capture the sensitivity of values of travel time information to travel length. RESULTS : The analysis results suggest that trip purpose and travel time are two dominant factors to determine drivers' acceptable level of travel time information. For business and short trips, drivers want more accurate information than for non-business and long trips. Drivers' willingness to pay for travel time information also varies depending on their incomes, trip purposes and travel lengths. The results also show that drivers' valuation of travel time information provided is sensitive to their travel length. For longer trips, drivers are less sensitive to travel time information and then put less value on the information provided. CONCLUSIONS : Censored nonlinear regression models are developed to estimate drivers' acceptable accuracy for travel time information and their valuation using questionnaire survey data. The findings on drivers perception to the required accuracy of travel time information and their corresponding willingness to pay can be used in the design and deployment of advanced traveler information system to improve its effectiveness and usefulness through high compliance.

• The Journal of Society for e-Business Studies
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• v.19 no.3
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• pp.91-105
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• 2014

This study purposed to benchmark the number of patients who visited an oriental medicine hospital from its surrounding regions using data envelopment analysis (DEA) model, and to analyze the relationships between regional characteristics and efficiency scores from DEA. Study data was collected from one oriental medicine hospital operated in a metropolitan city in Korea. Patient locations were identified at the smallest administrative district, Dong, and number of patients was calculated at the Dong level based on the address of patients in hospital information system. Socio-demographic variables of each Dong were identified from the Statistics of Korea web-sites. DEA was used to benchmark the number of patients between Dongs and to compute the efficiency scores. Tobit regression analysis model was applied to analyze the relationship between efficiency scores and regional variables. 6 Dongs were identified as efficient after DEA. In Tobit analysis, number of medical aid recipients and number of total population in each Dong was significant in explaining the differences of efficiency scores. The study model introduced the application of DEA model in benchmarking the patients between regions. It can be applied to identify the number of patients in each region which a hospital needs to improve their performances.

• Journal of Digital Convergence
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• v.12 no.12
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• pp.611-620
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• 2014

This research analyzed the operation efficiency and influence factors of housing facilities for the severely disabled in Jeolla region by using the DEA model. First, the analysis of efficiency for 2012 was carried out using the CCR model. As a result, 12 DMUs were proved to be efficient, and the average efficiency of CCR was 0.85, confirming that the efficiency of all DMUs were satisfactory. Second, regression analysis was carried out to analyze the factors affecting the efficiency of the DEA model by using the Tobit model. In this case, the inputs and calculated variables were set as independent variables whereas the efficiency as the dependent variable. As a result, the detailed variables had a low significance; the overall input variables showed a negative influence while the calculated variables tended to be a positive influence. In terms of operation efficiency, there was no meaningful result in input variables besides the number of workers. Instead of expanding the input variables, the following should be made for housing facilities of the severely disabled; more efforts should be put in to improve welfare service delivery system and operating environment and structure, and the program must be supplemented as well.

• Journal of the Korean Regional Science Association
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• v.33 no.1
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• pp.3-16
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• 2017

This paper analyzed 16 regional total factor energy efficiency (TFEE) of the Korean manufacturing sector using data envelopment analysis method for the period of 2005-2013. According to the empirical results, it is necessary to use TFEE as well as partial energy efficiency defined by the ratio of energy usage to output (energy intensity) when we compare energy efficiency. Secondly, TFEE in the Korean manufacturing sector is quite different across 16 regions. For example, Gangwon province should improve energy efficiency by 55% compared to Seoul, Gwangju, Ulsan, and Gyeongbuk which are located on production frontier. Furthermore, the estimation of panel tobit regression model showed that the higher non fossil fuel using, the higher production share of large-sized firms, the lower energy intensity, and the lower capital-labor ratio could have positive effect on TFEE.

• Journal of the Korean Home Economics Association
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• v.36 no.11
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• pp.209-218
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• 1998

The purpose of this study was to conduct the review of female labor suply, and thus, to provide useful theoretical and empirical frameworks for future studies related to female labor supply. Based on the theory of the allocation of time, the process of individual labor supply was systematically reviewed. Participation Probit/Logit, Tobit, and Selection B;ias Corrected Regression were considered in estimating the function of female labor supply which modifies the selection bias. Based on the previous empirical results, wage rate, asset income, husband's income, the level of eduction, and child-related variables such as the presence of child and the number of children might be considered for the empirical specification of female labor supply.

• Korean Journal of Agricultural Science
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• v.49 no.3
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• pp.607-617
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• 2022

As the number of households raising pets increases, the pet food industry is also growing. Since pets cannot express their intention explicitly, it appears that the owner's perception mainly affects the selection of products related to pets. In this study, consumers were categorized based on their interest in food choices and the factors influencing their interest in pet food were empirically analyzed. For the analysis, a cluster analysis, factor analysis, and Tobit analysis were conducted using consumer survey data for raising companion animals. The major findings of the study were as follows. As a result of the factor analysis and cluster analysis using questions for consumers' food consumption choices, consumer types were classified into high-interest, low-interest, and practical-seeking types. The degree of interest in pet food was high in the order of high-interest, practical-seeking, and low-interest type. Demographic characteristics such as gender, education, and household type correlate with differences in the degree of interest in pet food, and the food selection criteria of consumers also affect the degree of interest in pet food. These results show that consumers who are more interested in their food choices are more interested in pet food, and this will make possible to know pet owner's purchasing behavior for pet food.