• Korean Journal of Agricultural Science
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• v.43 no.1
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• pp.116-126
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• 2016

The objective of this study is to predict the fuel efficiency of an agricultural tractor. The fuel efficiency of the tractor during rotary tillage was predicted using numerical modeling. A numerical model was developed using Simulation X. Based on tractor power flow, numerical modeling consisted of an engine, transmission, PTO (power take off), and hydraulics. The specifications of major components utilized in the numerical model were the same as those of a 71 kW tractor (field test tractor). The load that was inputted for fuel efficiency prediction into the simulation model was obtained from a field test. Fuel efficiency predictions were conducted by comparing field test results and simulation results. In addition, it was performed by dividing the rotary tillage and steering section. Main results are as follows: first, t-values of engine torque were measured to be 0.31 in the rotary tillage and 0.92 in the steering section. Second, t-values of fuel consumption were measured to be 0.51 and 5.41 in the rotary tillage and the steering section, respectively. Finally, t-values of fuel efficiency were measured to be 1.72 and 40 in the rotary tillage and the steering section, respectively. The results show no significant differences with t-values of less than 5% in the rotary tillage. But, it shows significant differences in the steering section. Therefore, simulation for accurate fuel efficiency prediction requires a suitable algorithm or detailed design of the simulation model in the steering section.

• Journal of Korean Society of Occupational and Environmental Hygiene
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• v.15 no.1
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• pp.36-44
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• 2005

A push pull hood system is frequently applied to control contaminants evaporated from an open surface tank in recent years. Efficiency of push pull hood system is affected by various parameters, such as cross draft, vessel shapes, size of tanks surface, liquid temperature, and so on. Among these, velocity of cross draft might be one of the most influencing factor for determining the ventilation efficiency. To take account of the effect of cross draft velocities over 0.38m/s, a flow adjustment of ${\pm}$20% should be considered into the push and +20% into the pull flow system Although there are many studies about the efficiency evaluation of push pull hood system based on CFDs(Computational Fluid Dynamics) and experiments, there have been no reports regarding the influence of velocities and direction of cross-draft on push-pull hood efficiency. This study was conducted to investigate the influence of cross draft direction and velocities on the capture efficiency of the push-pull ventilation system. Smoke visualization method was used along with mock-up of push-pull hood systems to verify the ventilation efficiency by experiments. When the cross-draft blew from the same origins of the push flows, the efficiency of the system was in it's high value, but it was decreased significantly when the cross-draft came from the opposite side of push flows Moreover, the efficiency of the system dramatically decreased when the cross-draft of open surface tank was faster than 0.4m/s.

• Journal of Digital Convergence
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• v.11 no.10
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• pp.255-262
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• 2013

Data envelopment analysis(DEA) is a linear programming procedure designed to evaluate the relative efficiency of a set of peer entities called decision making units which use the same inputs to produce the same outputs. It has been widely employed in a variety of disciplines as an efficiency or performance measurement tool for comparing a set of entities such as firms, banks, hospitals, nations and organizations. The method, however, cant's make the priority of their performance when many units have efficiency score of unity or 100 percent. In this paper, we propose a new approach which combine qualitative method(graphical approach using network analysis) and quantitative method(super-efficient analysis using DEA), and present the results of an empirical analysis using the data of the Korean professional baseball players. As a result, there were 12 DMU that priority is hardly realized through DEA. However, this problem could be solved with super-efficiency analyzing. Also, more in-depth interpretation was able through integrating results of dendrogram and super-efficiency analyzing and prospecting it in qualitative, quantitative ways.

• Nuclear Engineering and Technology
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• v.45 no.2
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• pp.203-210
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• 2013

The objective of this conducted research is to study the iodine removal efficiency in a self-priming venturi scrubber for submerged and non-submerged operating conditions experimentally and theoretically. The alkaline solution is used as an absorbent, which is prepared by dissolving sodium hydroxide (NaOH) and sodium thiosulphate ($Na2S_2O_3$) in water to remove the gaseous iodine ($I_2$) from the gas. Iodine removal efficiency is examined at various gas flow rates and inlet concentrations of iodine for submerged and non-submerged operating conditions. In the non-submerged venturi scrubber, only the droplets take part in iodine removal efficiency. However, in a submerged venturi scrubber condition, the iodine gas is absorbed from gas to droplets inside the venturi scrubber and from bubbles to surrounding liquid at the outlet of a venturi scrubber. Experimentally, it is observed that the iodine removal efficiency is greater in the submerged venturi scrubber as compare to a non-submerged venturi scrubber condition. The highest iodine removal efficiency of $0.99{\pm}0.001$ has been achieved in a submerged self-priming venturi scrubber condition. A mathematical correlation is used to predict the theoretical iodine removal efficiency in submerged and non-submerged conditions, and it is compared against the experimental results. The Wilkinson et al. correlation is used to predict the bubble diameter theoretically whereas the Nukiyama and Tanasawa correlation is used for droplet diameter. The mass transfer coefficient for the gas phase is calculated from the Steinberger and Treybal correlation. The calculated results for a submerged venturi scrubber agree well with experimental results but underpredicts in the case of the non-submerged venturi scrubber.

• Journal of Korea Trade
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• v.27 no.4
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• pp.1-18
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• 2023

Purpose - The purpose of this paper is to study how flexibility and mutuality in determining trade terms impact logistics efficiency in the context of relational theory. Additionally, the effect of relational contracts on logistical efficiency relative to the value of the goods being traded is investigated. Design/methodology - According to the relational contract theory, we developed 17 factors utilizing a 7-point Likert scale to measure variables related to flexibility, mutuality, logistics efficiency, and the added value of goods. The survey occurred over four months, and was distributed directly, and via email, phone, and online Google surveys. A total of 403 surveys were collected out of 1,800 distributed, and 380 were analyzed. The principal respondents were import/export companies and members of the Korea International Trade Association and the Korea Small and Medium Business Export-Import Association. The collected data were analyzed using frequency analysis, exploratory factor analysis, and correlation analysis using SPSS ver. 26.0 statistical software, and hypothesis test results were derived using Process Macro ver. 3.5. Findings - This study provides evidence that negotiation flexibility for trade terms affects the efficiency of the logistics process, and the mutuality of such arrangements is shown to be associated with the flexibility and efficiency of logistics processes. Additionally, it has been established that companies whose trade goods possess a low degree of added value may experience increased efficiency in logistics operations if they agree to trade terms that are both flexible and mutually beneficial with their counterparts. Originality/value - This study suggests that in an environment of rapidly shifting global logistics and unpredictable related costs, trade companies may be able to improve logistics efficiency by establishing flexible, mutually beneficial trade terms when entering into contracts. Furthermore, it is suggested that companies dealing in low-value-added products may improve the logistical performance of approaching trade from a perspective of relational contracts.

• Management Science and Financial Engineering
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• v.14 no.2
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• pp.67-87
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• 2008

Data envelopment analysis (DEA) has proven to be a useful tool for assessing efficiency or productivity of organizations which is of vital practical importance in managerial decision making. While DEA assumes exact input and output data, the development of imprecise DEA (IDEA) broadens the scope of applications to efficiency evaluations involving imprecise information which implies various forms of ordinal and bounded data possibly or often occurring in practice. The primary purpose of this article is to characterize the variable efficiency in IDEA. Since DEA describes a pair of primal and dual models, also called envelopment and multiplier models, we can basically consider two IDEA models: One incorporates imprecise data into envelopment model and the other includes the same imprecise data in multiplier model. The issues of rising importance are thus the relationships between the two models and how to solve them. The groundwork we will make includes a duality study which makes it possible to characterize the efficiency solutions from the two models. This also relates to why we take into account the variable efficiency and its bounds in IDEA that some of the published IDEA studies have made. We also present computational aspects of the efficiency bounds and how to interpret the efficiency solutions.

• The Journal of Asian Finance, Economics and Business
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• v.7 no.6
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• pp.297-304
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• 2020

This paper applies the Data Envelopment Analysis (DEA) to compute the managerial efficiency of 30 insurance companies listed on the Saudi stock exchange for the duration of four years from 2015 to 2018. The companies taken as a sample of study included both conventional and Takaful insurance companies. The insurance sector of KSA is one of the largest sectors in the country, contributing a substantial percentage in the non-oil economy. Efficiency measurement and evaluation will provide a venue to introspect and benchmark frontiers to the sector. In the present study, we have utilized the basic Banker Charnes Cooper and Charnes Copper Rhodes models of DEA. Two inputs, namely, general & administrative expenses and policy & acquisition costs, and two outputs (Net premium earned and Investment Income & other incomes) were taken for efficiency calculations. The final outcomes of the study reveal that a good number of insurance companies operating in KSA are found to be efficient on managerial efficiency scale. Three firms remain the leader on the frontier of the managerial efficiency. And no company found with zero (0) efficiency or a negative efficiency. It is expected that the outcome of the study will provide benchmarks to managers and a road map to further improvement.

• The Journal of Industrial Distribution & Business
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• v.10 no.2
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• pp.7-15
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• 2019

Purpose - The industrial structure upgrading can play an important role in promoting the carbon emission efficiency. Thus, this paper attempts to study the impact of industrial structure upgrading on carbon emission efficiency in order to reduce carbon emissions. Research design, data, and methodology - This paper selects panel data of 30 provinces and municipalities (autonomous regions) in China from 2001 to 2016, and divides them into three regions. The Moore index is used to measure the industrial structure upgrading, the non-radial SBM model based on undesired output is used to measure the slack variable to calculate the total factor carbon emission efficiency. Finally the impact of industrial structure upgrading on the carbon emission efficiency are analyzed. Results - It is found that the Moore index and the carbon emission efficiency in the eastern region is the highest in the three regions. Conclusions - The influence of various influencing factors on carbon emission efficiency is different between regions. The Moore index has a positive effect on the carbon emission efficiency in the eastern region, and has a negative influence coefficient on the central region. The effect on the western region is not obvious.

• Journal of Technology Innovation
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• v.13 no.2
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• pp.207-222
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• 2005

A prerequisite for making R&D more productive is to able to measure its productivity. Most of the previous studies on this topic have attempted to measure R&D productivity at the firm or industry levels. In this study, however, R&D productivity is measured at the national level to provide R&D policy implications, particularly for Asian countries. Contrary to the previous studies where total factor productivity was adopted, this study employs the data envelopment analysis (DEA) approach to measure R&D productivity. DEA is a multi-factor productivity analysis model for measuring the relative efficiency of each Decision Making Unit (DMU). In addition to the basic DEA model that includes all inputs and outputs, five additional models are constructed by combining single input with all outputs and single output with all inputs in order to measure specialized R&D efficiency. In this study, the twenty-seven countries are classified into four clusters based on the output-specialized R&D efficiency: inventors, merchandisers, academicians, and duds. Then, the characteristics of the Asian countries with respect to R&D efficiency are identified. It is found that Singapore ranks high in total efficiency, and Japan in patent-oriented efficiency. Meanwhile, China, Korea, and Taiwan are found to be relatively inefficient in R&D. We expect that the findings from this study will be able to provide directions for R&D policy-making of the Asian countries.

• Journal of Environmental Policy
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• v.11 no.1
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• pp.75-97
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• 2012

The purpose of the paper is to estimate the functions of the energy input efficiency and the energy intensity efficiency, and measure their energy efficiencies for the reduction of greenhouse gases focusing on OECD countries. The efficiency of the traditional energy intensity was rarely connected with the energy efficiencies of the stochastic frontier function. It seems that the energy efficiency by the function of energy input efficiency sensitively responds to the order of GDP, capital stock, labor, and energy input quantity as explanatory variables. In the future, we need to reduce energy quantities by the optimal mix of inputs, and pursuit low-carbon economic growth through the production of the goods consuming small energy.