• Journal of People, Plants, and Environment
• /
• 제22권6호
• /
• pp.583-591
• /
• 2019

This study was conducted to examine the effects of wet storage solution, transport period and temperature on vase life and quality of cut flowers in standard chrysanthemum 'Jinba'. Immediately after transport, the fresh weight and flower diameter of cut flowers did not show a difference according to wet storage solutions regardless of the transport period, but as the transport period increased, the fresh weight and flower diameter increased. The flower bud stage at harvest was maintained due to the small changes in flower diameter, and the freshness of leaves was better when transported at 5℃ than at 25℃. When transported at 25℃, the longer the transport period, the lower the quality of cut flowers as some petals opened up and showed early flowering after transport. In preservative solutions, quality of cut flowers transported at 25℃ was lower than that at 5℃ due to fresh weight and diameter according to the longer transport period. The vase life of cut flowers was 1.0 day, 0.8 day, and 7.3 days longer when transported for 3, 5, and 7 days respectively at 5℃ than at 25℃. The quality of cut flowers was better due to increase in fresh weight and flower diameter, as well as vase life in wet storage solutions of ClO₂ and Chrysal OVB than in tap water, regardless of transport period and temperature. There was no difference in fresh weight and vase life between ClO₂ and Chrysal OVB, but flower diameter was greater in ClO₂ than in Chrysal OVB. Therefore, for long-term transport of cut standard chrysanthemum 'Jinba', wet storage transport in ClO₂ at 5℃ was found effective in maintaining the quality and vase life of cut flowers.

• Journal of Navigation and Port Research
• /
• 제47권3호
• /
• pp.155-166
• /
• 2023

Trend analysis and time series analysis were conducted to predict the demand of manpower under the smartization of shipping and port logistics with transportation survey data of Statistic Korea during the period from 2000 to 2020 and Statistical Yearbook data of Korean Seafarers from 2004 to 2021. A linear regression model was adopted since the validity of the model was evaluated as the highest in forecasting manpower demand in the shipping and port logistics industry. As a result of forecasting the demand of manpower in autonomous ship, remote ship management, smart shipping business, smart port, smart warehouse, and port logistics service from 2021 to 2035, the demand for smart shipping and port logistics personnel was predicted to increase to 8,953 in 2023, 20,688 in 2030, and 26,557 in 2035. This study aimed to increase the predictability of manpower demand through objective estimation analysis, which has been rarely conducted in the smart shipping and port logistics industry. Finally, the result of this research may help establish future strategies for human resource development for professionals in smart shipping and port logistics by utilizing the demand forecasting model described in this paper.

• Journal of Korea Port Economic Association
• /
• 제39권4호
• /
• pp.43-65
• /
• 2023

Recently, with the increasing international interest on environmental issues, efforts have been made to reduce greenhouse gas emissions due to ship fuel, however, the dependence on fossil fuel is expected to continue for a while. Since fuel costs account for a high portion of the total operating cost of a ship, it is necessary to analyze the influence of oil prices on the shipping markets. The purpose of this study is to evaluate the relationship between the international oil prices and the four major shipping markets for bulk carriers. This study employed WTI as the oil price variable while monthly data from 2017 to 2020 from the four major shipping markets by classifying freight rates, charter rates, newbuilding prices, and secondhand prices were also considered in multiple ship sizes of capesize, panamax, supramax, and handysize. Firstly, the results of the correlation analysis using the VAR model indicate that changes in international oil prices have a statistically positive (+) significant effect on BCIS only in the second time lag, on BSIS at all lags, and on BHIS only in the first staggered period. Secondly, as a result of correlation analysis using the VECM model, in the case of BPIC, BHIC, BCIN, and BHIR, the cointegration coefficient value has a negative (-) significant effect at the 5% significance level in the cointegration relationship with international oil prices. Further, in the case of the dynamic correlation, the increase in oil price in the first period of the lag leads to a decrease in the BCIN newbuilding prices while the increase in the oil price in the first and second period in the lag leads to a decrease in the BHIR used ship prices.

• Environmental and Resource Economics Review
• /
• 제23권1호
• /
• pp.1-19
• /
• 2014

Weather seems to influence industries in a variety of ways. On a day-to-day basis, it is the most volatile external factor influencing consumer and market behavior. And, because weather is constantly changing, industries must deal with a continuously shifting array of opportunities and risks. This study aims to examine how climate and weather changes and information, as external environmental factors, have affected the Korean industries, particularly marine shipping and logistics. To find out the economic value of marine weather information, we use measurable results of VVOS(Vessel and Voyage Optimization Services) in the ocean shipping, which the marine weather software tool can save fuel costs up to 4%. When the fuel saving is same as VVOS's performance, the saving of Korean flag ship is estimated about 62 billion won and the saving of total flag ship is estimated about 519 billion won. However, coastal shipping companies have been struggling with the heavy weather factors, such as wave height, wave period and wind. Major findings are that wind and wave height have a significant negative effect on cargo transport, while wave period has a significant positive effect on cargo transport. And to conclude, when we use efficiently the marine weather information, we can increase cargo transport and save fuel costs etc.

• Journal of Korea Port Economic Association
• /
• 제28권1호
• /
• pp.179-201
• /
• 2012

Since 1993, M&A activities have been frequent in Liner shipping market. This study examines the effect of M&A on stock price reaction for acquiring firms listed on the market. The study covers the period from 1993 to 2009 and uses 61 daily closing prices of the acquiring firms before and after the M&A announcement day and is analyzed through the market-adjusted model in an event study. After calculating short-term performance using abnormal returns(AR) and cumulative average abnormal returns(CAR) before and after 30 days from the day of event, the results on the test show that the firm's values slightly increased through the M&A, but it does not attest to the statistical significance. In addition, this study investigates the AR difference between estimating windows and post-event windows for the 3 cases of each period before and after 30 days, 15 days, and 7 days from the event day to analyse the impact of M&A on the addition of acquiring firm's value. Our findings suggest that the M&A between Liner shipping companies is targeted for the long-term business strategy instead of the instant rise in the value of the firm involved.

• Journal of Korean Society for Quality Management
• /
• 제50권4호
• /
• pp.701-716
• /
• 2022

Purpose: This study aims to predict the dry cargo transportation market economy. The subject of this study is the BDI (Baltic Dry Index) time-series, an index representing the dry cargo transport market. Methods: In order to increase the accuracy of the BDI time-series, we have pre-processed the original time-series via time-series decomposition and data augmentation techniques and have used them for ANN learning. The ANN algorithms used are Multi-Layer Perceptron (MLP), Recurrent Neural Network (RNN), and Long Short-Term Memory (LSTM) to compare and analyze the case of learning and predicting by applying time-series decomposition and data augmentation techniques. The forecast period aims to make short-term predictions at the time of t+1. The period to be studied is from '22. 01. 07 to '22. 08. 26. Results: Only for the case of the MAPE (Mean Absolute Percentage Error) indicator, all ANN models used in the research has resulted in higher accuracy (1.422% on average) in multivariate prediction. Although it is not a remarkable improvement in prediction accuracy compared to uni-variate prediction results, it can be said that the improvement in ANN prediction performance has been achieved by utilizing time-series decomposition and data augmentation techniques that were significant and targeted throughout this study. Conclusion: Nevertheless, due to the nature of ANN, additional performance improvements can be expected according to the adjustment of the hyper-parameter. Therefore, it is necessary to try various applications of multiple learning algorithms and ANN optimization techniques. Such an approach would help solve problems with a small number of available data, such as the rapidly changing business environment or the current shipping market.

• Journal of Navigation and Port Research
• /
• 제40권5호
• /
• pp.337-343
• /
• 2016

The core decisions of bulk shipping businesses can be summarized as the timing and the choice of period for which carrying capacity is traded. In particular, frequent decisions to trade freight either with repeated spot transactions or with a one-off long-term deal critically impact business performance. Even though a variety of freight trading strategies can be employed to facilitate the decisions, chartering practitioners have not been active in utilizing these strategies, and academic research has rarely proposed applicable solutions. The specific properties of freight as a tradable commodity are not properly reflected in existing studies, and limitations have been reported in their application to the real world. This research focused on the establishment of applicable freight trading strategies by taking into account two properties of freight: time perishability and term-dependant pricing. In addition to traditional trading strategies, artificial neural networks were applied for the first time to the test of freight trading strategies. The performances of the trading strategies were measured and compared to produce a remarkable outperformance of the ANN. This research is expected to make a significant contribution to chartering practices by enhancing the quality of chartering decisions and eventually enabling the effective management of freight rate risk. In addition to methodological expansion, the result will propose a way to approach the controversial issue of freight market efficiency.

• International Journal of Advanced Culture Technology
• /
• 제8권1호
• /
• pp.62-70
• /
• 2020

As an effective means of price discrimination, some suppliers offer trade credit to the distributors in order to stimulate the demand for the product they produce. The availability of the delay in payments from the supplier enables discount of the distributor's selling price from a wider range of the price option in anticipation of increased customer's demand. Since the distributor's lot-size is affected by the demand for the customer, the distributor's lot-size and the selling price determination problem is interdependent and must be solved at the same time. Also, in many common business transactions, the distributor pays the shipping cost for the order and hence, the distributor's ordering cost consists of a fixed ordering cost and the shipping cost that depend on the order quantity. In this regard, we deal with the joint lot-size and price determination problem when the supplier allows delay in payments for an order of a product. The positive effects of credit transactions can be integrated into the EOQ (economic order quantity) model through the consideration of retailing situations, where the customer's demand is a function of the distributor's selling price. It is also assumed that the distributor's order cost consists of a fixed ordering cost and the variable shipping cost. We formulate the distributor's mathematical model from which the solution algorithm is derived based on properties of an optimal solution. A numerical example is presented to illustrate the algorithm developed.

• Journal of Korea Port Economic Association
• /
• 제21권3호
• /
• pp.115-148
• /
• 2005

In the liner market, a strategy is hard to sustain as competitors can easily imitate the strategy. For examples, when a number of shipping companies pursue this space exchange strategy in a liner market, their competitors are likely to build a cooperative alliance, following similar strategic pattern without any difficulty. Such strategic imitations are universal in international liner market. Therefore, the success of global alliance requires following critical considerations. First, the strategy of global alliance should be designed the way it gives the liner operators an economy of scale, which could be a key advantage in the competitive market. Second, thorough global alliance the lines should be able to improve their transport service through the reduction of operating costs and the business rationalization. The international alliance today is characterized by a strategic cooperation among a limited number of 'mega-carriers'. Such cooperation between the large-sized operators has come in many different forms. However, the trend has been towards the space exchange agreement, where a carrier on a route offers to another carrier a fixed number of spaces for a fixed period of time. the major carriers have been entered into groupings by integrating their services structures to increase market power. With reference to the above, this study has the following primary objectives: (1) to explore the present status of global alliance in liner shipping industry, (2) to prospect the future trend of the global alliance.

• Journal of Digital Convergence
• /
• 제14권6호
• /
• pp.157-165
• /
• 2016

The purpose of this study was to analyze the effect of the shipping industry real economy index on the stock prices of domestic shipping companies. The parameters used in this analysis were the stock price of H Company in South Korea and shipping industry real economy indices including BDI, CCFI and HRCI. The period analysis was from 2012 to 2015. The weekly data for four years of the stock price index of shipping companies, BDI, CCFI, and HRCI were used. The effects of CCFI and HRCI on the stock price index of domestic shipping companies were analyzed using the VAR model, and the effects of BDI on the stock price index of domestic shipping companies were analyzed using the VECM model. The VAR model analysis results showed that CCFI and HRCI had negative effects on the stock price index, and the VECM model analysis results showed that BDI also had a negative effect on the stock price index.