The food service industry has grown larger with changes in the economic and socio-cultural environment. In this saturated food service industry, generation X and MZ are the main consumer forces that demand attention. That is because a generation is the main psychographic factor that reflects personal values and lifestyle based on one’s life cycle. From such a perspective, a generation in marketing has been used as a variable to predict a market by supplementing demographic factors. Accordingly, this study classified generations into generation X and generation MZ with the use of the 2019 consumer behavior survey for food by Korea Rural Economic Institute (KREI) and then investigated the factors influencing group and personal dining-out expenses. The analysis was carried out applying the Tobit model using SPSS and R. The positively influential variables on generation X's personal dining-out expenditure were male, single person, high income and simple lifestyle, whereas housewives, personal ethical consciousness, behavioral ethical consciousness, and safe dietary life were negatively influential variables. The positively influential variables on generation MZ's personal dining-out expenditures were male, dual-income, high education level, corporate and governmental ethical consciousness, while the number of family members and safe dietary life were negatively influential variables.

In this study, the factors affecting the efficiency of 48 projects of private R&D institutes were analyzed using the Tobit model. Influencing factors were selected as open R&D network size, IT industry, interaction between R&D network size and IT industry, and type of R&D network cooperation. As a result of Tobit analysis, the R&D network size, the IT industry, and the type of R&D network cooperation were found to be significant. The larger the open R&D network size, the lower the efficiency, and the IT industry showed lower R&D efficiency than other industries. In addition, cooperation with universities and research institutes showed lower R&D efficiency than cooperation with companies. As a result of these studies, companies will be able to select and focus on cooperation with the outside in relations and investment allocation.

The objective of this study is to examine the potential of cost reduction and factors affecting production cost of Korean farmers. First, the study estimates technical efficiency, allocation efficiency, and cost efficiency of Korean farmers using DEA. Then, Tobit regressions are conducted to identify factors affecting each of the three efficiency scores. The study uses the Farm Household Economy Survey data from the Korean National Bureau of Statistics for the period from 2008 to 2012. Results from DEA show that overall, technical and cost efficiency scores are low, which suggests a great potential of cost reduction for Korean farmers. The results also show relatively large differences in efficiency scores across provinces. Tobit results suggest that farm size, number of family members, operation costs, and invested capital amount are major factors affecting farm efficiencies.

PURPOSES: This study deals with the pedestrian accidents in case of Cheongju. The goals are to develop the pedestrian accident model. METHODS: To analyze the accident, count data models, truncated count data models and Tobit regression models are utilized in this study. The dependent variable is the number of accident. Independent variables are traffic volume, intersection geometric structure and the transportation facility. RESULTS : The main results are as follows. First, Tobit model was judged to be more appropriate model than other models. Also, these models were analyzed to be statistically significant. Second, such the main variables related to accidents as traffic volume, pedestrian volume, number of Entry/exit, number of crosswalk and bus stop were adopted in the above model. CONCLUSIONS: The optimal model for pedestrian accidents is evaluated to be Tobit model.

PURPOSES : The intents of the study are to identify the accident factors and to demonstrate the potentials of tobit model as a tool to study the number of accidents on arterial roads segments. METHODS : This paper uses a tobit regression as a methodology to analyze the factors affecting the number of accidents. In pursuing the above goal, this study gives particular attentions to analyzing the data of 2,446 accidents (1,610 in major arterial roads and 836 in minor arterial roads) occurred on arterial roads in 2007 to 2010. RESULTS : First, 3 accident models which were classified by total arterial roads, major arterial roads and minor arterial roads, and were all statistically significant were developed. Second, the exclusive right-turn lane as common variable, and the number of accident, traffic volume, number of lanes, link length, rate of median, number of entrances, number of pedestrian crossings, number of curves, number of bus stops and exclusive left-turn as specific variables of the models were selected. Finally, the paired sample t-test could not be rejected the null hypotheses of three types of models. CONCLUSIONS : Using data from vehicle accidents on arterial roads, the estimation results show that many factors related to roadway geometrics and traffic characteristics significantly affect to the number of accidents.