• Journal of Distribution Research
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• v.17 no.2
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• pp.93-115
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• 2012

This study empirically examines the impact of changes in market shares among retailing types on the price index. The retailing type is classified into 6 groups: department store, big mart, super market, convenient store, specialty merchant, and on-line store. The market shares of retailing types are calculated by the ratio of each retailing type monthly sales to total monthly retailing sales in which total retailing sales is the sum of each retailing type sales. We employed several price indices: consumer price index (CPI), CPI for living necessaries, and fresh food price index. In addition, this study used fundamental price indices based on 25 product families as well as 42 representative products. The empirical model also included several variables in order to control for the macroeconomic effects and those variables are the exchange rate, M1, an oil price, and the industrial production index. The data is monthly time-series data spanning over the period from January 2000 to December 2010. In order to test for the stability of data series, we conducted ADF test and PP test in which the model and length of lag were determined by the relevant previous literature and based on the AIC. The empirical results indicate that changes in market shares among retailing types have impacts on the price index. Table A shows that impacts differ as to which price index to use and which product families and products to use. For department store, it lowers the price of food and non-alcoholic beverages, home appliances, fresh food, fresh and vegetables, but it keeps the price high for fresh fruit. The big mart retailing type has a positive impact on the price of food, nut has a negative effect on clothing and foot wear, non-food, and fresh fruit. For super market, it has a positive impact on food and non-alcoholic beverages, fresh food, fresh shellfishes, but increases the price of CPI for living necessaries and non-food. The specialty merchant retailing type increases the price level of CPI for living necessaries and fresh fruit. For on-line store type, it keeps the price high for CPI for living necessaries and non-food as well as fresh fruit. For the analysis based on 25 product families shows that changes in market shares among retailing types also have different effects on the price index. Table B summarizes the different results. The 42 representative product level analysis is summerized in Table C and it indicates that changes in market shares among retailing types have different effects on the price index. The study offers the theoretical and practical implication to these findings and also suggests the direction for the further analysis.

• Journal of Environmental Impact Assessment
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• v.29 no.3
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• pp.157-181
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• 2020

Sediments from rivers, lakes and marine ports serve as end points for pollutants discharged into the water, and at the same time serve as sources of pollutants that are continuously released into the water. Until now, the contaminated sediments have been landfilled or dumped at sea. Landfilling, however, was expensive and dumping at sea was completely banned due to the London Convention. Therefore, this study applied contaminated sedimentation soil of 'Royal Palace Livestock Complex' as soil purification method. Soil remediation methods were applied to pretreatment, composting, soil washing, electrokinetics, and thermal desorption by selecting overseas application cases and domestically applicable application technologies. As a result of surveying the site for pollutant characteristics, Disolved Oxigen (DO), Suspended Solid (SS), Chemical Oxygen Demand (COD), Total Nitrogen (TN), and Total Phosphorus (TP) exceeded the discharged water quality standard, and especially SS, COD, TN, and TP exceeded the standard several tens to several hundred times. Soil showed high concentrations of copper and zinc, which promote the growth of pig feed, and cadmium exceeded 1 standard of Soil Environment Conservation Act. In the pretreatment technology, hydrocyclone was used for particle size separation, and the fine soil was separated by more than 80%. Composting was performed on organic and Total Petroleum Hydrocarbon (TPH) contaminated soils. TPH was treated within the standard of concern, and E. coli was analyzed to be high in organic matter, and the fertilizer specification was satisfied by applying the optimum composting conditions at 70℃, but the organic matter content was lower than the fertilizer specification. As a result of continuous washing test, Cd has 5 levels of residual material in fine soil. Cu and Zn were mostly composed of ion exchange properties (stage 1), carbonates (stage 2), and iron / manganese oxides (stage 3), which facilitate easy separation of contamination. As a result of applying acid dissolution and multi-stage washing step by step, hydrochloric acid, 1.0M, 1: 3, 200rpm, 60min was analyzed as the optimal washing factor. Most of the contaminated sediments were found to satisfy the Soil Environmental Conservation Act's standards. Therefore, as a result of the applicability test of this study, soil with high heavy metal contamination was used as aggregate by applying soil cleaning after pre-treatment. It was possible to verify that it was efficient to use organic and oil-contaminated soil as compost Maturity after exterminating contaminants and E. coli by applying composting.

• Journal of Intelligence and Information Systems
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• v.22 no.2
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• pp.81-96
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• 2016

As the internet has become widespread and easy to access everywhere, it is common for people to search information via online search engines such as Google and Naver in everyday life. Recent studies have used online search volume of specific keyword as a measure of the internet users' attention in order to predict disease outbreaks such as flu and cancer, an unemployment rate, and an index of a nation's economic condition, and etc. For stock traders, web search is also one of major information resources to obtain data about individual stock items. Therefore, search volume of a stock item can reflect the amount of investors' attention on it. The investor attention has been regarded as a crucial factor influencing on stock price but it has been measured by indirect proxies such as market capitalization, trading volume, advertising expense, and etc. It has been theoretically and empirically proved that an increase of investors' attention on a stock item brings temporary increase of the stock price and the price recovers in the long run. Recent development of internet environment enables to measure the investor attention directly by the internet search volume of individual stock item, which has been used to show the attention-induced price pressure. Previous studies focus mainly on Dow Jones and NASDAQ market in the United States. In this paper, we investigate the relationship between the individual investors' attention measured by the internet search volumes and stock price changes of individual stock items in the KOSDAQ market in Korea, where the proportion of the trades by individual investors are about 90% of the total. In addition, we examine the difference between industries in the influence of investors' attention on stock return. The internet search volume of stocks were gathered from "Naver Trend" service weekly between January 2007 and June 2015. The regression model with the error term with AR(1) covariance structure is used to analyze the data since the weekly prices in a stock item are systematically correlated. The market capitalization, trading volume, the increment of trading volume, and the month in which each trade occurs are included in the model as control variables. The fitted model shows that an abnormal increase of search volume of a stock item has a positive influence on the stock return and the amount of the influence varies among the industry. The stock items in IT software, construction, and distribution industries have shown to be more influenced by the abnormally large internet search volume than the average across the industries. On the other hand, the stock items in IT hardware, manufacturing, entertainment, finance, and communication industries are less influenced by the abnormal search volume than the average. In order to verify price pressure caused by investors' attention in KOSDAQ, the stock return of the current week is modelled using the abnormal search volume observed one to four weeks ahead. On average, the abnormally large increment of the search volume increased the stock return of the current week and one week later, and it decreased the stock return in two and three weeks later. There is no significant relationship with the stock return after 4 weeks. This relationship differs among the industries. An abnormal search volume brings particularly severe price reversal on the stocks in the IT software industry, which are often to be targets of irrational investments by individual investors. An abnormal search volume caused less severe price reversal on the stocks in the manufacturing and IT hardware industries than on average across the industries. The price reversal was not observed in the communication, finance, entertainment, and transportation industries, which are known to be influenced largely by macro-economic factors such as oil price and currency exchange rate. The result of this study can be utilized to construct an intelligent trading system based on the big data gathered from web search engines, social network services, and internet communities. Particularly, the difference of price reversal effect between industries may provide useful information to make a portfolio and build an investment strategy.

• Economic and Environmental Geology
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• v.56 no.6
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• pp.729-744
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• 2023

The value of lithium has significantly increased due to the rising demand for electric cars and batteries. Lithium is primarily found in pegmatites, hydrothermally altered tuffaceous clays, and continental brines. Globally, groundwater-fed salt lakes and oil field brines are attracting attention as major sources of lithium in continental brines, accounting for about 70% of global lithium production. Recently, deep groundwater, especially geothermal water, is also studied for a potential source of lithium. Lithium concentrations in deep groundwater can increase through substantial water-rock reaction and mixing with brines. For the exploration of lithim in deep groundwater, it is important to understand its origin and behavior. Therefore, based on a nationwide preliminary study on the hydrogeochemical characteristics and evolution of thermal groundwater in South Korea, this study aims to investigate the distribution of lithium in the deep groundwater environment and understand the geochemical factors that affect its concentration. A total of 555 thermal groundwater samples were classified into five hydrochemical types showing distinct hydrogeochemical evolution. To investigate the enrichment mechanism, samples (n = 56) with lithium concentrations exceeding the 90th percentile (0.94 mg/L) were studied in detail. Lithium concentrations varied depending upon the type, with Na(Ca)-Cl type being the highest, followed by Ca(Na)-SO₄ type and low-pH Ca(Na)-HCO₃ type. In the Ca(Na)-Cl type, lithium enrichment is due to reverse cation exchange due to seawater intrusion. The enrichment of dissolved lithium in the Ca(Na)-SO₄ type groundwater occurring in Cretaceous volcanic sedimentary basins is related to the occurrence of hydrothermally altered clay minerals and volcanic activities, while enriched lithium in the low-pH Ca(Na)-HCO₃ type groundwater is due to enhanced weathering of basement rocks by ascending deep CO₂. This reconnaissance geochemical study provides valuable insights into hydrogeochemical evolution and economic lithium exploration in deep geologic environments.