• Journal of Korea Port Economic Association
• /
• v.38 no.2
• /
• pp.139-152
• /
• 2022

In this paper, samples are collected for individual companies and the factors affecting worker wages (average annual salary) are analyzed in depth. In addition to the average annual salary of workers in a company, we would like to conduct an in-depth analysis of the average annual salary of first-time employees. Specifically, we tried to explain the size of companies, the production structure of capital and labor, and the impact of business on the average annual salary of first-time, college, and graduate school graduates by educational background of first-time employees. The difference in average annual salary of first-time employees of logistics companies is a decisive factor in the main project on sales, and first-time graduates and college graduates provided high salaries in the overseas passenger cargo transportation, port operation, and unloading management, and low salaries in the land cargo and warehouse industries. n addition, Korean logistics companies had relationships between the location of the headquarters, the number of employees, the proportion of labor costs to sales, and the four characteristic factors of the main business on sales. This fact is that Seoul-based foreign passenger cargo transportation, corporate logistics agency, complex transportation, and international transportation relay are large companies, with a low proportion of labor costs and a higher proportion of capital, technology, and information-intensive investments.

• Journal of Advanced Marine Engineering and Technology
• /
• v.37 no.2
• /
• pp.220-226
• /
• 2013

Recently, with the rapid development of factory automation and logistics system, a few workers were able to manage the broad workplace such as large vessels and warehouse. To estimate the exact location of these workers in the conventional wireless indoor localization systems, three or more fixed nodes are generally used to recognize the location of a mobile node consisting of a single node. However, these methods are inefficient in terms of node deployment because the broad workplace requires a lot of fixed nodes compared to workers(mobile nodes). Therefore, to efficiently deploy fixed nodes in these environments that need a few workers, this paper presents a novel estimation algorithm which can reduce the number of fixed nodes by efficiently recognizing the relative coordinates of two fixed nodes through a mobile node composed of three nodes. Also, to minimize the distance errors between mobile node and fixed node, rounding estimation(RE) technique is proposed. Experimental results show that the error rate of localization is improved, by using proposed RE technique, 90.9% compared to conventional trilateration in the free space. In addition, despite the number of fixed nodes can be reduced by up to 50% in the indoor free space, the proposed estimation algorithm recognizes precise location which has average error of 0.15m.