• Environmental and Resource Economics Review
• /
• v.21 no.2
• /
• pp.237-269
• /
• 2012

This study applies a discrete-continuous choice model to a national survey data set of automobile uses to investigate the potential impacts of a bonus-malus system for new cars in Korea. Not only the impacts on the discrete choice of automobile type and class but also those on the continuous decision making of car operation are analyzed. The characteristics of automobiles and individuals that determine car choice and operation are identified. The simulation based on the estimation result shows that an appropriately designed bonus-malus system can induce a reduction in energy consumption and $CO_2$ emission substantially without additional government expenditure.

• The Journal of The Korea Institute of Intelligent Transport Systems
• /
• v.10 no.5
• /
• pp.113-123
• /
• 2011

Recently, the global warming problem has arised around world, many nations has set up a various regulations for decreasing $CO_2$. In particular, $CO_2$ emissions reduction effect is very powerful in transport part, so there is a rising interest about development of green car, or electric vehicle in auto industry. For this reason, it is important to make a strategy for charging infra and forcast electric power demand, but it hasn't introduced about demand forecasting electric vehicle. Thus, this paper presents a demand forecasting for electric vehicles using choice based multigeneration diffusion model. In this paper, it estimates innovation coefficient, immitation coefficient in Bass model by using hybrid car market data and forecast electric vehicle market by year using potential demand market through SP(Stated Preference) experiment. Also, It facilitates more accurate demand forecasting electric vehicle market refelcting multigeneration diffusion model in accordance with attribute progress in development of electric vehicle. Through demand forecasting methodology in this paper, it can be utilized power supply and building a charging infra in the future.

• Environmental and Resource Economics Review
• /
• v.28 no.2
• /
• pp.231-276
• /
• 2019

This paper analyzed the impact of the penetration of EV(electric vehicle) and FCEV(fuel cell electric vehicle) into the automobile industry, using a static CGE approach. There are contrasting view on the economic impact of EV/FCEV penetration: negative economic impact due to shrunken intermediate inputs versus positive impact because of input saving technical progress. Regarding environment, there is no clear consensus whether EV or FCEV will contribute to the reduction of $CO_2$ emissions in Korea. This study attempts to provide an answer to these questions. By giving shocks to the input coefficients of automobile industries and automobile using sectors, as well as to the final demands for energies. we integrated the Bass diffusion model into the CGE framework, The result suggests that the EV penetration has adverse impact on the $CO_2$ emission while the FCEV penetration has positive impact. On the other hand, both EV and FCEV have positive impacts on GDP. When considering automobile manufacturing sectors only, adverse impacts on $CO_2$ are demonstrated both for EV and FCEV. However, since the size of $CO_2$ increase is small, these results does not alter the overall effects.

• Journal of the Korea Academia-Industrial cooperation Society
• /
• v.11 no.8
• /
• pp.2750-2757
• /
• 2010

Recently, there have been a number of voices from industry that automotive education at the college is too theoretical and so college graduates are lack of practical ability to apply the automotive idea to actual systems. In order to educate engineering students design qualities in creative problem solving, this paper reports the results of employing engineering design projects in a Motor sports course of at A College. This paper presents design creterion and manufacture process of $CO_2$ model dragster, measures $CO_2$ model dragster speed and aerodynamic drag. In order to investigate the impact of engineering design on student's learning, a survey was conducted in 2008 spring semester. According to the results of survey analyses, student's key competencies and satisfaction reports high values on engineering design projects.

• Journal of Korean Society of Transportation
• /
• v.30 no.2
• /
• pp.117-126
• /
• 2012

The transportation sector accounts for 33% of the total $CO_2$ emissions. Effective control measures for reducing $CO_2$ emissions are urgently needed to address global warming. Objective and reliable methods to estimate $CO_2$ emissions are a prerequisite for the implementation of such effective control measures. However, existing models have not been successful. Even though the average-speed model is one of the most convenient and useful methods for estimating $CO_2$ emissions, it cannot distinguish between a variety of roads as well as traffic conditions in the model. The results of this study found that there may be significant discrepancies between emissions estimated by the current average-speed model and those measured in real driving conditions. This paper proposed the subdivision of emission factors in the average-speed model depending on both traffic and road conditions.

• Journal of Korean Society of Transportation
• /
• v.32 no.2
• /
• pp.93-105
• /
• 2014

This study evaluated the relative efficiency of mobile emission reduction countermeasures through a Data Envelopment Analysis (DEA) approach and determined the priority of countermeasures based on the efficiency. Ten countermeasures currently applied for reducing greenhouse gases and air pollution materials were selected to make a scenario for evaluation. The reduction volumes of four air pollution materials(CO, HC, NOX, PM) and three greenhouse gases($CO_2$, $CH_4$, $N_2O$) for the year 2027, which is the last target year, were calculated by utilizing both a travel demand forecasting model and variable composite emission factors with respect to future travel patterns. To estimate the relative effectiveness of reduction countermeasures, this study performed a super-efficiency analysis among the Data Envelopment Analysis models. It was found that expanding the participation in self car-free day program was the most superior reduction measurement with 1.879 efficiency points, followed by expansion of exclusive bus lanes and promotion of CNG hybrid bus diffusion. The results of this study do not represent the absolute data for prioritizing reduction countermeasures for mobile greenhouse gases and air pollution materials. However, in terms of presenting the direction for establishing reduction countermeasures, this study may contribute to policy selection for mobile emission reduction measures and the establishment of systematic mid- and long-term reduction measures.

• The Journal of The Korea Institute of Intelligent Transport Systems
• /
• v.12 no.1
• /
• pp.121-135
• /
• 2013

This paper propose an efficient algorithm for selecting electric bus charging facility location. In nature, the optimal charging facility location problem is similar to Set Covering Problem. Set Covering Problem is the problem of covering all the rows of an $m{\times}n$ matrix of ones and zeros by a subset of columns with a minimal cost. It has many practical applications of modeling of real world problems. The Set Covering Problem has been proven to be NP-Complete. In order to overcome the computational complexity involved in seeking optimal solutions, this paper present an enhanced greedy algorithm and simulated annealing algorithm. In this paper, we apply the developed algorithm to Seoul's public bus system.

• Journal of Engineering Education Research
• /
• v.11 no.1
• /
• pp.85-100
• /
• 2008

The purpose of this study is development of 'F1 in Schools Program' for elementary school student and validation of the program. Fifteen students were originally chosen from the W elementary school in Cheongju, Chungcheogbuk-Do. The children were tested on their understanding of science and 'F1 in Schools Program'. After developing the 'F1 in Schools Program', it was used in the classroom to evaluate applicability and to examine the responses from students, parents and schools. The program consists of 60 classes and the time of each class is 40 minutes. This study was conducted for 10 days from January 22nd, 2007 to February 2nd, 2007. CAD(Computer Aided Design), CFD(Computation Fluid Dynamics), CAM(Computer Aided manufacturing) and CNC Machine were used in this study and proved to be good materials for students in that they increased the students' participation and imagination. However, the children's cognitive and creative abilities as well as manuals written in English hampered the process. Most students, parents, schools seemed to be satisfied with use of the program. However, the schools showed that there was not enough understanding of the program as a whole. The processes with which students build and inspect using the $CO_2$Model Car not only improves the processing of the model but also enhanced the students scientific understanding related to the car speed.

• Korean Management Science Review
• /
• v.28 no.3
• /
• pp.1-13
• /
• 2011

Hub-and-spoke transportation network is a powerful and useful network structure that takes full advantage of economies of scale on routes between hubs. In recent studies, the network structure is extended to hybrid hub-andspoke that allows direct transportation between spokes. In this study, we considered more extended network structure which is called hybrid multiple hub-and-spoke that has multiple hubs and allows direct transportation between spokes. We developed a mathematical optimization model for automotive service parts transportation planning under hybrid multiple hub-and-spoke network structure. The model suggests a long-term transportation route planning and a short-term vehicle assignment planning. The model is verified by simulation and validated in real world application to Hyundai Mobis automotive service parts transportation planning. From the simulation result, the model reduced the transportation cost about 24.7%, the total distance about 6.8% and the CO2 emissions about 8.8%. In real world application for 6 months from July to December 2010, the model reduced the transportation cost about 9.1% by changing the long-term transportation route without daily vehicle assignment planning.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
• /
• v.9 no.6
• /
• pp.129-144
• /
• 2014

This study is to examine the effect of mutualistic benevolence, altruistic benevolence, and communication on affective commitment, calculative commitment, and switching intentions and investigate how two commitment dimensions play mediating roles between two benevolence constructs and communication, and switching intentions. For these purposes the author developed a structural model which consists of several constructs. In this model, benevolence factor that consists of mutualistic benevolence and altruistic benevolence, and communication were proposed to affect two commitment constructs and result in, increase switching intentions. Thus, two commitment constructs(e.g., affective and calculative commitment) were proposed as core mediating variables between mutualistic benevolence, altruistic benevolence, and communication, and switching intentions. The data were collected from 210 automobile parts buyers and were analyzed using frequency, reliability, and confirmatory factor analysis and SEM (structural equation model) with SPSS/WIN 20.0 and AMOS 20.0. The data were analyzed with structural equation modeling with AMOS 20.0 and SPSS Win/PC 20.0. The result of the overall model analysis appeared as follows: ${\chi}2=224.885$, d.f=123(${\chi}2/df=1.828$), p=0.000, GFI=.898, AGFI=.859, IFI=.967, NFI=.930, TLI=.958, RMSEA=.063, CFI=.966. Since the result of the overall model analysis demonstrated a good fit, we could further analyze our data. The findings can be summarized as follows: According to structural equation modeling analysis, firstly, mutualistic benevolence has direct effects on calculate commitment and affective commitment. Secondly, altruistic benevolence has a positively direct effect on calculate commitment. Thirdly, communication has a statistically direct effect on affective commitment. Fourthly, calculative commitment has direct effects on affective commitment and switching intentions. Lastly, affective commitment has a direct effect on switching intentions.