• Journal of Distribution Science
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• v.14 no.10
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• pp.93-107
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• 2016

Purpose - This study aims to derive directions and implications for improving performance in operating agrifood export organizations by identifying significant performance impact factors. Research design, data, and methodology - A seemingly unrelated regression (SUR) model was estimated using data from a survey conducted among 120 exporters including 16 leading export organizations. In the SUR estimation, the export volume and price are used as dependent variables and securing the quantity of products ordered and exported, quality management, and marketing activities are considered as explanatory variables for the operation performance. Results - The amount of farmer education, the manpower in charge of marketing, and the interaction terms between whether or not they belong to a leading export organization and the item dummy for mushrooms have a significant impact on the export volume where the export volume is specified as a dependent variable. The export volume is greater with a greater amount of farmer education and greater manpower in charge of marketing from the perspective of quality management. When the export price is estimated as a dependent variable, the manpower in charge of marketing is shown to have a significant impact on the export price. Conclusions - The government needs to strengthen its support of the performance of agrifood export organizations. The analysis indicates that the education of and consulting with farmers, and the manpower number in charge of marketing are key factors in the operation performance of export organizations. Therefore, supporting the export organizations in expanding their human resources in charge of marketing can increase the export volumes for agrifoods. Given, however, that the export volume associated with joint payments, human resources specialized in quality management, and the amount of participation in export exhibitions are not significant factors, it is essential to improve the supporting policies for those areas. The manpower in charge of marketing from the perspective of marketing has a significant impact on both the export volume and export price. Thus, we identify this as the most important category that should be supported to enhance performance in export organizations.

• Journal of Korean Society of Transportation
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• v.22 no.6
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• pp.159-173
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• 2004

Using a generalized translog multiproduct cost function model, this paper examines economies of scale and scope in the vertically-integrated Korean railway industry. The paper then conceptualizes that the Korea National Railroad (KNR) produces four outputs (passenger-kilometers, ton-kilometers of freight, average length of passenger trips, and average length of freight haul) using three input factors(labor, fuel and maintenance, and rolling stock and capital). Using time series data collected from the KNR's annual records for the years from 1977 to 2002, the simultaneous equation system consisting of a cost function and two input share equatins is estimated with the Zellner's iterative seemingly unrelated regression. The findings show that the cost function corresponding to a non-Cobb-Douglas, non-homothetic, and non-homogeneous production technology adequately represents the KNR's cost structure. On the other hand, the Korean railway industry experiences sizeable overall scale economies, which result from substantial product-specific scale economies associated with passenger-kilometers and freight ton-kilometers and from scope economies associated with their joint production. In addition, the magnitude of economies of scope is influenced largely by the ratio of passenger trips, and has increased over time as the former has increased while the latter has decreased.

• Journal of Korean Society of Transportation
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• v.24 no.2 s.88
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• pp.65-78
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• 2006

This paper investigates the cost structure ot the Korea and Japan railroad industry with respect to density, scale and scope economies as well as productivity growth rate using a generalized trans)og multiproduct cost function model. The paper then assumes that the Korea and Japan railway companies pi·educe three outputs (incumbent railway passenger-kilometers. Shinkansen passenger-kilometers, ton-kilometers of freight) using four input factors (labor, fuel, maintenance, rolling stock and capital). The specified cost function includes foul other independent variables: track lengths to reflect network effects, two dummies to reflect nation and ownership effects, and time trend as a proxy for technical change. The simultaneous equation system consisting of a cost function and three input share equations is estimated with the Zellner's iterative seemingly unrelated regression. The unbalanced panel data used in the paper, a total of 154 observations. are collected from the annual records of the Korea National Railroad (KNR) for the yews $1977{\sim}2003$, Japan National Railways (JNR) for the years $1977{\sim}1984$. seven Japan Railways (JR's) for the years $1987{\sim}2003$. The findings show that the Korean and Japanese railways exhibit product-specific and overall economies of density but product-specific diseconomies of scale with respect to incumbent railway passenger-kilometers, Shinkansen-kilometers and ton-kilometers. However, the railways experience mild overall economies of scale which result from economies of scope associated with the joint production of incumbent railway/Shinkansen and feight, freight/incumbent railway and Shinkansen except Shinkansen/incumbent railway and freight. In addition, the economies of density and scale in the KNR, JR east, JR central, and JR west companies at the point of the years $1990{\sim}2003$ average is generally analogous to the above results at the point of sample average. There also appear to be economies of ssope associated with the joint Production of the incumbent railway and Shinkansen in JR central but diseconomies of scope in JR East and JR West. The findings also indicate that the productivity growth rate of the privately-owned JR's is larger than that of the government-owned KNR.