• Journal of Environmental Policy
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• v.7 no.1
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• pp.101-118
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• 2008

In this study, we estimate the labor demand function of environmental industry with environmental industry survey of Ministry of Environment. To do this, we apply the panel estimation technique. We follow the widely accepted estimation methods: panel generalized least square, panel generalized least square with heteroskedasticity/auto-correlation, random effect model and random effect model with auto-correlation. On the average, each industry is estimated at the elasticity of sales on labor demand from 0.193 to 0.259. It means that the increase of sales by 214billion won can create around $1,600{\sim}2,300$ jobs, and this is merely a direct effect. So when we consider the whole effect of labor demand increase including indirect derived job creation, the labor demand increase will be higher than this. So it is desirable for the government to support the development of environmental industry for sustainable development.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.43 no.2
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• pp.14-24
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• 2020

Google Trends is a useful tool not only for setting search periods, but also for providing search volume to specific countries, regions, and cities. Extant research showed that the big data from Google Trends could be used for an on-line market analysis of opinion sensitive products instead of an on-site survey. This study investigated the market share of tumor necrosis factor-alpha (TNF-α) inhibitor, which is in a great demand pharmaceutical product, based on big data analysis provided by Google Trends. In this case study, the consumer interest data from Google Trends were compared to the actual product sales of Top 3 TNF-α inhibitors (Enbrel, Remicade, and Humira). A correlation analysis and relative gap were analyzed by statistical analysis between sales-based market share and interest-based market share. Besides, in the country-specific analysis, three major countries (USA, Germany, and France) were selected for market share analysis for Top 3 TNF-α inhibitors. As a result, significant correlation and similarity were identified by data analysis. In the case of Remicade's biosimilars, the consumer interest in two biosimilar products (Inflectra and Renflexis) increased after the FDA approval. The analytical data showed that Google Trends is a powerful tool for market share estimation for biosimilars. This study is the first investigation in market share analysis for pharmaceutical products using Google Trends big data, and it shows that global and regional market share analysis and estimation are applicable for the interest-sensitive products.

• Journal of Korean Society of Rural Planning
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• v.12 no.4 s.33
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• pp.23-32
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• 2006

Recently, Owing to booming of leisure activities and national enforcement of 5-day workweek system, Korean government has been promoting rural tourism policy of which operating project's title is Green Rural Experience Village, Rural Traditional Theme Village, etc. In this study, ken investigation result on Green Rural Experience Village sites, an estimation model of returns by green-tourism activities was developed. The model was constructed through factor analysis and regression analysis method. Regression model developed can estimate green-tourism revenue by investment budget, homepage preengagement sales, homepage visitors, capacity of eating and drinking facilities, capacity of lodging facilities. The model developed was applied in sample villages. With these results, estimation revenue was recorded average 138.3% of survey revenue, and statistical significance was good(correlation coefficient $R^2$ = 0.8255, level of significance : 0.000), and the range of relative error was recorded largely from -7.1% to 158.6%, and average relative error was 38.3% and good. And, the model developed in this study have the critical point in aspects of insufficient data, but the results will be used in green-tourism policies and projects, and revenue estimation about each village in the present and future is limited, but in province or the whole country the application is good.

• KDI Journal of Economic Policy
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• v.12 no.4
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• pp.47-69
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• 1990

Using an aggregator model, we look into the possibilities for substitution between Korea's exports, imports, domestic sales and domestic inputs (particularly labor), and substitution between disaggregated export and import components. Our approach heavily draws on an economy-wide GNP function that is similar to Samuelson's, modeling trade functions as derived from an integrated production system. Under the condition of homotheticity and weak separability, the GNP function would facilitate consistent aggregation that retains certain properties of the production structure. It would also be useful for a two-stage optimization process that enables us to obtain not only the net output price elasticities of the first-level aggregator functions, but also those of the second-level individual components of exports and imports. For the implementation of the model, we apply the Symmetric Generalized McFadden (SGM) function developed by Diewert and Wales to both stages of estimation. The first stage of the estimation procedure is to estimate the unit quantity equations of the second-level exports and imports that comprise four components each. The parameter estimates obtained in the first stage are utilized in the derivation of instrumental variables for the aggregate export and import prices being employed in the upper model. In the second stage, the net output supply equations derived from the GNP function are used in the estimation of the price elasticities of the first-level variables: exports, imports, domestic sales and labor. With these estimates in hand, we can come up with various elasticities of both the net output supply functions and the individual components of exports and imports. At the aggregate level (first-level), exports appear to be substitutable with domestic sales, while labor is complementary with imports. An increase in the price of exports would reduce the amount of the domestic sales supply, and a decrease in the wage rate would boost the demand for imports. On the other hand, labor and imports are complementary with exports and domestic sales in the input-output structure. At the disaggregate level (second-level), the price elasticities of the export and import components obtained indicate that both substitution and complement possibilities exist between them. Although these elasticities are interesting in their own right, they would be more usefully applied as inputs to the computational general equilibrium model.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.38 no.3
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• pp.8-13
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• 2015

One of the most usual indicators to measure the performance of any inventory policy is the mean physical stock. In general, when estimating the mean physical stock in periodic review inventory systems, approximate approaches are often utilized by practitioners and researchers. The mean physical stock is generally calculated by a simple approximation. Still these simple methods are frequently used to analyze various single stockpoint and multi-echelon inventory systems. However, such a simple approximation can be very inaccurate. This is particularly true for low service levels. Even though exact methods to calculate the mean physical stock have been derived, they are available for specific cases only and computationally not very efficient, and therefore less useful in practice. In literature, approximate approaches, such as the simple, the linear, and Simpson approximations, were derived for the periodic review inventory systems that allow backorders. This paper modifies the approximate approaches for the lost sales case and evaluates the modified approximate approaches. Through computational experiments, average (and maximum) percentage deviations of mean physical stock between the exact method and the modified approximations are compared in the periodic review inventory system with lost sales. The same comparison between the modified and the original approximations are also conducted, in order to examine the performance of modified approximations. The results show that all modified approximations perform well for high service levels, but also that the performance may deteriorate fast with decreasing service level. The modified Simpson approximation is clearly better. In addition, the comparison between the modified and the original approximations in the periodic review inventory system with lost sales shows that the modified approximation outperforms the original approximation.

• Journal of the Korean Society for Railway
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• v.18 no.6
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• pp.630-638
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• 2015

The total number of passengers on the KTX since its construction in 2004 surpassed 500 million in October, 2015. The operation of KTX made it possible to reach anywhere in a country in half a day, which subsequently altered people's lifestyle. As the KTX has become an important mode of transportation, there is a growing interest in the optimal size and location of its stations. Currently, the stations are constructed through public-private partnerships since a sufficient amount of budget is hard to secure only from the public sector; however, because railway stations are traditionally aimed at promoting public interests, an emphasis on the profitability of the private sector could compromise public interests. At this juncture, this study separately computes the number of users based on each of the two primary functions of the stations-as a railway station and as a sales facility-and estimates the numbers of people according to various transportation modes that are taken to access the stations. This estimation is applied to the case of Dongdaegu Station, which will open in 2016. Such an application helps to predict and respond to possible congestion as brought about by the expansion of the sales facility.

• Journal of Technology Innovation
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• v.25 no.4
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• pp.239-261
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• 2017

This paper analyzes how corporate product innovation affects firms' revenue and financial stability, and thereby draws the implications for the corporate strategy for sustainable growth. Corporate product innovation is defined as the development of new products within the firm, including bought-in products. Corporate revenue is measured by per capita sales and its growth rate, while financial stability is measured by debt-to-equity ratio and liquidity ratio. In the empirical analysis, the two-stage estimation method was used to control for the endogeneity of new product development. The data are drawn from the first (2005) to the sixth (2015) wave of the Human Capital Corporate Panel (HCCP) Survey, which are matched to the data from the Korea Investors Service (KIS). The results of the first-stage estimation indicate that product innovation of the firm is promoted by the firm's knowledge capital stock, human resources investment, and market-leading strategy. The second-stage estimation results indicate a positive relationship between the firm's level of activity in product innovation and short-term revenue (per capita sales and its growth), and financial stability (lower debt-to-equity ratio and higher liquidity ratio). These findings confirm that the firm's investment in technology innovation and subsequent product innovation are important strategies to enhance both short-term corporate revenue and long-term financial stability.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.20 no.44
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• pp.243-255
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• 1997

Forecasting the future values of an observed time series is an important problem in many areas, including economics, traffic engineering, production planning, sales forecasting, and stock control. The purpose of this paper is aimed to discover the more efficient forecasting model through the parameter estimation and residual analysis among the quantitative method such as Winters' exponential smoothing model, Box-Jenkins' model, and Kalman filtering model. The mean of the time series is assumed to be a linear combination of known functions. For a parameter estimation and residual analysis, Winters', Box-Jenkins' model use Statgrap and Timeslab software, and Kalman filtering utilizes Fortran language. Therefore, this paper can be used in real fields to obtain the most effective forecasting model.

• Korean Management Science Review
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• v.23 no.3
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• pp.41-61
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• 2006

This study is to propose a sales forecasting framework for new products in the prelaunch phase where no saies data are available. For the purpose we first develop an extended Bass model with the dynamic market potential and then propose an estimation method based on the market survey and scenario methodology. The proposed parameter estimation method is different from previous studies in that most of them have only Proposed the management judgments or analogies. We also apply the proposed model to satellite DMB market in Korea to verify the model.

• Journal of Korean Institute of Industrial Engineers
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• v.28 no.4
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• pp.368-378
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• 2002

As more companies are equipped with data aquisition systems for their products, huge amount of field warranty data has been accumulated. We focus on the case when the field data for a given product comprise with the number of sales and the number of the first failures for each period. The number of censored items and their ages are assumed to be given. This type of data are incomplete in the sense that the age of a failed item is unknown. We construct a model for this type of data and propose an algorithm for nonparametric maximum likelihood estimation of the product reliability. Unlike the nonhomogeneous Poisson process(NHPP) model, our method can handle the data with censored items as well as those with small population. A few examples are investigated to characterize our model, and a real field warranty data set is analyzed by the method.