• The Journal of Asian Finance, Economics and Business
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• v.6 no.4
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• pp.179-187
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• 2019

This study aims to investigate the effects of market commonality and resource similarity on price competition and the recursive consequences in the Korean lodging market. Price comparison among hotels in the same geographic market has been facilitated through the development of information technology, rendering little search cost of consumers. While the literature implies the heterogeneous price attack and response among hotels, a limited number of empirical researches focus on the asymmetric and recursive pattern in the competitive dynamics. This study empirically examines the price interactions in the Korean lodging market based on the theoretical framework of competitive price interactions and countervailing power. Demonstrating superiority to the spatial lag model and the ordinary least squares in the estimation, the results from spatial error model suggest that the hotels with longer operational history pose an asymmetric impact on the price of the newer hotels. The asymmetry is also found in chain hotels over the independent, further implying the possibility of predatory pricing. The findings of this study provide the evidence of a hierarchical structure in the price competition, with different countervailing power by the resources of the hotels. Theoretical and managerial implications are discussed, with suggestions for future study.

• Transactions of the Korean hydrogen and new energy society
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• v.19 no.6
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• pp.552-560
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• 2008

In 1997, Korean government established the National Energy and Resources Plan, which targeted from 1997 to 2005 with strategic energy technology development. At the end of 2005, Korean government built a New National Energy and Resources Plan preparing for upcoming 10 years from 2006 until 2015 based on energy technology trees comparing with the previous plan, which based on the energy R&D projects. In this research, we prioritize the relative preferences and efficiency by an AHP/DEA CCR-I and BCC-I integrated model approach considering scale efficiency for well focused R&D and efficiency of developing Greenhouse Gas technologies as an extended research from a view point of econometrics as an extended research.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.39 no.1
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• pp.25-30
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• 2016

It is critical to forecast the maximum daily and monthly demand for power with as little error as possible for our industry and national economy. In general, long-term forecasting of power demand has been studied from both the consumer's perspective and an econometrics model in the form of a generalized linear model with predictors. Time series techniques are used for short-term forecasting with no predictors as predictors must be predicted prior to forecasting response variables and containing estimation errors during this process is inevitable. In previous researches, seasonal exponential smoothing method, SARMA (Seasonal Auto Regressive Moving Average) with consideration to weekly pattern Neuron-Fuzzy model, SVR (Support Vector Regression) model with predictors explored through machine learning, and K-means clustering technique in the various approaches have been applied to short-term power supply forecasting. In this paper, SARMA and intervention model are fitted to forecast the maximum power load daily, weekly, and monthly by using the empirical data from 2011 through 2013. $ARMA(2,\;1,\;2)(1,\;1,\;1)_7$ and $ARMA(0,\;1,\;1)(1,\;1,\;0)_{12}$ are fitted respectively to the daily and monthly power demand, but the weekly power demand is not fitted by AREA because of unit root series. In our fitted intervention model, the factors of long holidays, summer and winter are significant in the form of indicator function. The SARMA with MAPE (Mean Absolute Percentage Error) of 2.45% and intervention model with MAPE of 2.44% are more efficient than the present seasonal exponential smoothing with MAPE of about 4%. Although the dynamic repression model with the predictors of humidity, temperature, and seasonal dummies was applied to foretaste the daily power demand, it lead to a high MAPE of 3.5% even though it has estimation error of predictors.

• Journal of Korean Society of Forest Science
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• v.95 no.4
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• pp.381-387
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• 2006

This study tried to develop a model which can predict a long-term of forest recreation quantity corresponded with econometrics. Simultaneously this study was conducted with the aim of development of practical matrix which is able to apply forest recreation management with policy-control variables about forest supplement with some problem of former study using only a cross-section analysis. As the results of analyses, forest recreation quantity is affected (-) relation by distance, (+) relation by population of the origin area, the size of forest, and a destination's annual social expenditure. In addition, the distance variable is elastic, however, the other variables are inelastic. This results might correspond to a general gravity model theory about forest recreation quantity.

• KIPS Transactions on Computer and Communication Systems
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• v.1 no.3
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• pp.133-142
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• 2012

Cournot model is one of representative models among many game theoretic approaches available for analyzing competitive market models. Recent years have witnessed various kinds of attempts to model competitive electricity markets using the Cournot model. Cournot model is appropriate for oligopoly market which is one characteristic of electric power industry requiring huge amount of capital investment. When we use Cournot model for the application to electricity market, it is prerequisite to assume the downward sloping demand curve in the right direction. Generators in oligopoly market could try to maximize their profit by exercising the market power like physical or economic withholding. However advanced electricity markets also have demand side bidding which makes it possible for the demand to respond to the high market price by reducing their consumption. Considering this kind of demand reaction, Generators couldn't abuse their market power. Instead, they try to find out an equilibrium point which is optimal for both sides, generators and demand. This paper suggest a quantitative analysis between market variables based on econometrics for estimating demand responses in smart grid environment.

• Journal of Korean Society of Transportation
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• v.26 no.1
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• pp.51-63
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• 2008

Jeju-Mainland demand for air passenger is variated by the season because most of the demands stem from the leisure travel. This research is to estimate the econometrics demand models(A simple time series model and the partial adjustment model) and elasticities of each models for the Jeju-Mainland domestic routes air travel market using the time series aggregate data between the year 1996 and 2005. As the result of estimating, income elasticity was evaluated to be elastic(1.55) and fare elasticity was inelastic(-0.49${\sim}$-0.59) for A simple time series models. In the partial adjustment model's case, income elasticity was evaluated to be inelastic(0.51) in short-run whereas it was evaluated to be elastic(1.88) in long-run. Fare elasticity was evaluated to be inelastic in short-run(high-demand season: -0.13, slack season: -0.20) and long-run(high-demand season: -0.48, slack season: -0.72).

• The Journal of Society for e-Business Studies
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• v.16 no.4
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• pp.17-31
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• 2011

Damage caused by private information breach causes serious problems and huge social losses. In order to make a better policy that prevents society from suffering from the damage, we have to know about the actual size of damage. So it is needed to develop a quantitative model of private information breach that helps catching the more accurate size of damage. In our study, we suggest a method which calculate not only the costs of damage from firms' perspective but also those from individual and social perspectives. In this process, we refer to methods adopted by JNSA(Japan Network Security Association) and Ponemon Research Institue and modify it with considering our current situation. Also we try to make a new model by using new methods(web traffic analysis, survey, indirect comparison, etc.) and verify it with theories and methods from econometrics, cost accounting and theory of producer.

• Environmental Engineering Research
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• v.22 no.1
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• pp.116-124
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• 2017

The study makes an attempt to investigate the causal nexus between carbon dioxide emissions, GDP per capita, industrialization and population with an evidence from Rwanda by employing a time series data spanning from 1965 to 2011 using the autoregressive distributed lag model. Evidence from the study shows that carbon dioxide emissions, GDP per capita, industrialization and population are co-integrated and have a long-run equilibrium relationship. Evidence from the Granger-causality shows a unidirectional causality running from industrialization to GDP per capita, population to carbon dioxide emissions, population to GDP per capita and population to industrialization. Evidence from the long-run elasticities has policy implications for Rwanda; a 1% increase in GDP per capita will decrease carbon dioxide emissions by 1.45%, while a 1% increase in industrialization will increase carbon dioxide emissions by 1.64% in the long-run. Increasing economic growth in Rwanda will therefore reduce environmental pollution in the long-run which appears to support the validity of the environmental Kuznets curve hypothesis. However, industrialization leads to more emissions of carbon dioxide, which reduces environment, health and air quality. It is noteworthy that the Rwandan Government promotes sustainable industrialization, which improves the use of clean and environmentally sound raw materials, industrial process and technologies.

• The Journal of Asian Finance, Economics and Business
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• v.7 no.9
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• pp.191-200
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• 2020

This research paper examines the causal relationship between India's economic growth and sectoral contribution to Gross Domestic Product (GDP) and vice versa, in the short-run and long-run, over a 10 years time period. Johansen's method of cointegration is used to study the cointegration between the sectoral contributions to Indian GDP vis-à-vis India's economic growth. Further, the route of interconnection between economic growth and sectoral contribution is tested by using Vector Auto Regression (VAR) model. Special attention was given for investigating impulse responses of economic growth depending on the innovations in sectoral contribution using time-series data from 1960 to 2015. This paper highlighted a dynamic co-relationship among industrial sector contribution and agricultural sector contribution and economic development. In the long run, one percent change in industrial sector contribution causes an increase of 3.42 percent in the economic growth and an increase of 1.12 percent in the primary sector contribution, while in the short run industrial and service sector contributions showed significant impact on economic development and agriculture sector. The changing composition of sector contribution is going to be an important activity for the policymakers to monitor and control where the technology and integration of sectors play a significant role in economic development.

• Korean Journal of Organic Agriculture
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• v.27 no.1
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• pp.17-32
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• 2019

The objective of this study is to investigate the effect of pesticide-related accident on prices and sales of eggs and the perception of food safety accidents among consumers. For this, we analyzed the impact of the pesticide incident on consumers' purchases by separating large discount stores and eco-friendly specialty stores with econometrics methods. In addition, the value changes for each egg certification were analyzed after the accident. Perception of food safety accidents was conducted through a survey to investigate the awareness of the pesticide-related accidents, changes in purchases, and the causes of the pesticide accidents. Furthermore, the risk analysis was conducted. This results show the importance of trust and communication in food safety accidents between distributors, consumers and concerned authorities. Also, after the accident, consumers' interest and premium exist in the breeding process such as animal welfare, not only in the final product. Therefore in order to actively respond to food safety accidents such as pesticides-related accident, response and improvement are necessary considering various aspects such as risk assessment, risk management, and risk communication.