• Journal of Navigation and Port Research
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• v.39 no.6
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• pp.545-552
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• 2015

This study One of the key elements of corporate competitiveness in the modern world of unlimited competition is human resource management. The reason that the world's leading companies are devoting a lot of investment and effort for good human resource development and management is that human resource can impact firm survival. In particular, there is little research on the internal and external environmental stimuli and job stress in the employee of small business which are often led to turnover, while they have suffered from chronic shortage of manpower. The purpose of this study is to determine the turnover factors in the small logistics companies and contribute to stable maintenance of workforce, facilitating human resource management and minimizing turnover. This study empirically analyzed the factors of the turnover in the organization of logistics companies from Busan Port, South Korea, which became one of the national infrastructure and the fifth world largest harbor. The conclusion proposed the development and direction of the human resource management which could promote the job environment improving the turnover factors and creating sustainable work condition through conducting preventive measures. The results indicated that the highest turnover rates was found in the category of field work, and the highest turnover group was from the 'less than one year', which implies that high turnover rates after and during job training might be greater cost to the companies than early turnover. The most common reasons for the high employee turnover were 'excessive workload' and 'dissatisfaction with wages'. Followed reasons including 'troubles with managers' and 'failure in organizational adaptation' can be understood in line with worse working conditions of the small logistic companies. It turned out that the preventive programs of the logistic enterprises had little effect through 'incentives system' and 'improving wage system' which are mainly conducted. The human resource managers appreciated the importance of 'wage raise' and 'benefits improvement'. This study is aimed at contributing to efficient human resource management through understanding of the turnover causes and human resource managers applying preventive measures. In particular, this can benefit small port logistics companies securing competitiveness and promoting persistent growth and development.

• 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.