• Journal of Korean Society of Transportation
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• v.30 no.4
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• pp.85-94
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• 2012

Modern freight transport pursues not only the reduction of logistic costs but also aims at green logistics and efficient shipments. In order to accomplish these goals, various policies regarding the multimodal shipment and stopover to logistic facilities have widely been made. Such situation requires changes in existing methods for analyzing freight demand. However, the reality is that a reliable freight demand forecast is limited, since in the transport research field there is no robust freight demand model that can accommodate transshipments at logistic facilities. This study suggested a novel method to analyze freight demand, which can consider transshipments in multi-modal networks. Also, the applicability of this method was discussed through an example test.

• Journal of Korean Society of Transportation
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• v.27 no.4
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• pp.31-40
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• 2009

Some road charges toll to finance the cost or to manage traffic congestion. With a growth of PPI projects, toll roads would be increase continuously. Tolls have a considerable influence on user's route choice, and sometimes can affect to the departure time and even to mode choice. For modelling toll roads, user's WTP or VOT has an important role and it is general that VOT is equivalent to the wages of workers. The current way of modelling technique yields various toll price elasticity from low to high. When there exist few alternative routes, unrealistic result that all traffic assigned to some shortest path may occur. The toll price elasticity can be influenced by alternative route and congestion level, but some result shows nearly unrealistic patterns. The model to forecast more realistic toll road demand is very essential for estimating toll revenue, choice of optimal toll level & collecting location and establishing toll charge strategy. This paper reviewed some literatures about toll road modelling and tested case study about the assignment technique with different VOT. The case study shows that using different VOT yields more realistic result than the use of single VOT.

• Journal of Energy Engineering
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• v.27 no.4
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• pp.36-49
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• 2018

This study analyzed the public preference and acceptance regarding renewable energy projects through Choice Based Conjoint Analysis. The results show that the surveyed respondents consider the leading authority of the projects, as the most important factor when considering participating in renewable energy initiatives. Following this, the mode of participation and profit distribution and the power plant location are also viewed as important, whereas participation through decision making regarding the projects was less important. Also when participating in renewable energy projects, respondents tend to prefer to financially participating through loans or owning shares rather than volunteering support for the business such as sharing information, stating one's views, or providing cooperation and coordination. Therefore, the focus is on distributional justice, such as financial investment and profit distribution, rather than procedural justice, for instance decision making. When analyzing the part-worths utilities for the participation attribute, the respondents most preferred to receiving dividends based on earnings by owning shares with the local government in charge of the entire projects. As a consequence, the results suggest that it is important to have local government get involved and have trust-worthy governing systems in place for the initiation of the public participating-renewable energy projects.

• Journal of the Korea Convergence Society
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• v.12 no.6
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• pp.65-74
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• 2021

Since 2020, the GuangXi government of China has focused on the deep integration of tea industry with leisure and cultural tourism, popular science education, health care and elderly care industries. Among the output value targets of the tertiary industry, the GuangXi government plans to achieve 25 billion yuan, and the tea industry is developing rapidly. Through questionnaire survey, field research and interview, this paper studies the differences of demand behavior and selection attributes of tea products among consumers in different years, and finally studies the evolution pattern of service mode of tea industry in GuangXi. The results show that there are obvious differences in life and work style, shopping habits, service design, user experience, social needs and personality needs of each generation consumers in different years. Based on the analysis of demand and behavior habits of tea products, the evolution pattern of service mode of tea industry in GuangXi is studied. Based on the above results, according to the differences of consumers' choice of tea products in different years, the service mode of tea industry in GuangXi is improved The development of tea industry in service design, user experience level is worthy of in-depth attention.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.36 no.1
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• pp.105-114
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• 2016

With approximately 20 million transportation card data entries of the metropolitan districts being generated per day, application of the data to management and policy interventions is becoming an issue of interest. The research herein attempts a model of the possibility of dynamic demand change predictions and its purpose is thereby to construct a Dynamic Passengers Trip Assignment Model. The model and algorithm created are targeted at city rail lines operated by seven different transport facilities with the exclusion of travel by bus, as passenger movements by this mode can be minutely disaggregated through card tagging. The model created has been constructed in continuous time as is fitting to the big data characteristic of transport card data, while passenger path choice behavior is effectively represented using a perception parameter as a function of increasing number of transfers. Running the model on 800 pairs of metropolitan city rail data has proven its capability in determining dynamic demand at any moment in time, in line with the typical advantages expected of a continuous time-based model. Comparison against data measured by the eye of existing rail operating facilities to assess changes in congestion intensity shows that the model closely approximates the values and trends of the existing data with high levels of confidence. Future research efforts should be directed toward continued examination into construction of an integrated bus-city rail system model.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.18 no.3
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• pp.703-710
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• 2017

Third-generation (3G) devicesare next-generation devices that allow the use of intelligent services and applications through the Internet of Things (IoT). As the market forexisting smart devices like smartphones and tablet PCs enters the stage of stagnation, the world is now focusing on 3G devices, parts, and services. This study is intended to measure the user's benefits from the various attributes of 3G devices by applying an economic valuation method. For this purpose, the conjoint analysis method was applied, which is one of the representative valuation methods. To apply conjoint analysis, the following attributes of 3G devicesare considered: mode of use, power efficiency, life care, and price. By applying the mixed logit model, the marginal willingness-to-pay(WTP) for each attribute was derived. The results are statistically significant. Respondents showed a high preference or complete flexibility in the mode of use attribute. And they were also found to have WTP for improvements in the life care attribute. The implications and quantitative results of this study are expected to be useful for policies and strategies in the 3G device market.

• Journal of the Korean Regional Science Association
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• v.9 no.1
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• pp.65-78
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• 1993

In this study, the significant and enduring concentration of federal R&D spending in metro-scale clusters across the nation is treated as evidence of the operation of a distinct industrial infrastructure defined by the ability of R&D performers to attract external funding and pursue the sophisticated project work demanded. It follows, then, that the agglomerative potential of these R&D concentrations -- performers and their support infrastructures -- requires a search for economic impacts guided by a different stimulative effects attributable to federal R&D spending may be that substantial subnational economic impacts are routinely obscured and diluted by research designs that seek to discover impacts either at the level of nation-scale economic aggregates or on firms or specific industries organized spatially. Therefore, this study proceeds by seeking to link the locational clustering of federal contract R&D spending to more localized economic impacts. It tests a series of models(X-IV) designed to trace federal contract R&D spending flows to economic impacts registered at the level of metro-regional economies. By shifting the focus from funding sources to recipient types and then to sector-specific impacts, the patterns of consistent results become increasingly compelling. In general, these results indicated that federal R&D spending does indeed nurture the development of an important nation-spanning advanced industrial production and R&D infrastructure anchored primarily by two dozed or so metro-regions. However, dominated as it is by a strong defense-industrial orientation, federal contract R&D spending would appear to constitute a relatively inefficient national economic development policy, at least as registered on conventional indicators. Federal contract R&D destined for the support of nondefense/civilian(Model I), nonprofit(Model II), and educational/research(Mode III) R&D agendas is associated with substantially greater regional employment and income impacts than is R&D funding disbursed by the Department of Defense. While federal R&D support from DOD(Model I) and for-profit(Model II) and industrial performer(Model III) contract R&D agendas are associated with positive regional economic impacts, they are substantially smaller than those associated with performers operating outside the defense industrial base. Moreover, evidence that the large-business sector mediates a small business sector(Model VI) justifies closer scrutiny of the relative contribution to economic growth and development made by these two sectors, as well as of the primacy typically accorded employment change as a conventional economic performance indicator. Ultimately, those regions receiving federal R&D spending have experienced measurable employment and income gains as a result. However, whether or not those gains could be improved by changing the composition -- and therefore the primary missions -- of federal R&D spending cannot be decided by merely citing evidence of its economic impacts of the kind reported here. Rather, that decision turns on a prior public choice relating to the trade-offs deemed acceptable between conventional employment and income gains, the strength of a nation's industrial base not reflected in such indicators, and the reigning conception of what constitutes national security -- military might or a competitive civilian economy.

• Journal of Korean Society of Transportation
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• v.34 no.6
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• pp.510-522
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• 2016

In studies involving public transport, social welfare improvement is simply explained by the increase in public transport demand. However, the increase in the demand for public transport is mostly observed by the change in the frequency of public transport service, and in-vehicle crowding in public transport has not been an object of concern. This study examines and tries to reveal the cause of the changes of the social welfare and in-vehicle crowding of the changing public transport from imposing congestion pricing. We observe that congestion pricing increases in-vehicle crowding in public transport. This predictable phenomenon is more exacerbated in case of not operating bus-only lane. It should be noted that in-vehicle crowding is more increased in suburban, but in First-best toll system it tends to get worse less than it in other congestion pricing systems. We identify that the change of in-vehicle crowding is affected by the change of proximity of the housing to workplace, the number of commuting trips, and unpredictable distortion effect of the congestion charge.

• Geomechanics and Engineering
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• v.12 no.4
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• pp.723-738
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• 2017

Rock is a heterogeneous material, which introduces complexity in the analysis of rock slopes, since both the existing discontinuities within the rock mass and the intact rock contribute to the degradation of strength. Rock failure is often catastrophic due to the brittle nature of the material, involving the sliding along structural planes and the fracturing of rock bridge. This paper proposes an advanced discretization method of rock mass based on block theory. An in-house software, GeoSMA-3D, has been developed to generate the discrete fracture network (DFN) model, considering both measured and artificial joints. Measured joints are obtained from the photogrammetry analysis on the excavation face. Statistical tools then facilitate to derive artificial joints within the rock mass. Key blocks are searched to provide guidance on potential reinforcement measures. The discretized blocky system is subsequently implemented into a discontinuous deformation analysis (DDA) code. Strength reduction technique is employed to analyze the stability of the slope, where the factor of safety can be obtained once excessive deformation of slope profile is observed. The combined analysis approach also provides the failure mode, which can be used to guide the choice of strengthening strategy if needed. Finally, an illustrated example is presented for the analysis of a rock slope of 20 m height inclined at $60^{\circ}$ using combined GeoSMA-3D and DDA calculation.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.17 no.4
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• pp.26-40
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• 2018

The aim of this research is to analyze factors affecting bicycle accidents using the PLS structural equation. Accident types in this study were categorized into total accidents, serious injuries including death, and light injuries which occurred at nationwide Si Gun Gu. It was found that urbanization was the main factor for bicycle accidents through the accident models developed in this study. Population, ratio of economically active population, density of intersections, ratio of urbanized area, commercial and industrial land-uses, number of drive license holders, number of education institutions, number of parks were the main factors causing bicycle accidents. Besides, length of bicycle roads, number of bicycles, and ratio of bicycle as mode choice also increased bicycle accidents.