• Asia Marketing Journal
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• v.14 no.3
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• pp.185-197
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• 2012

Caffe Bene, one of the most notable coffeehouse chain brands in Republic of Korea, gives us some thought-provoking issues in terms of sustainable success. Despite harsh competition among various coffeehouse brands, Caffe Bene has been accomplished astonishing outcomes in domestic market and now ranked 2^nd place in sales among the global coffeehouse franchise in 2010 and 2011. These achievements were possible mainly because Caffe Bene adopted distinctive shop design, maintained aggressive marketing strategy, developed new menu, and combined the unique Korean culture with ordinary concept of café to make its place attractive. However, since Korean coffeehouse market is getting saturated and consumers are becoming savvy about coffee, Caffe Bene needs to find a new solution to overcome growth stagnation. Besides, many experts pointed out that irrational increase in the number of stores might hurt its business in the aspect of managing distribution channel and providing consistent services. Also, customers of Caffe Bene have shown that it has to complement its critical weaknesses: inferior coffee taste and relatively high price for a cup of coffee. Especially, some people view that the company is shifting its high rental fee, interior cost and PPL marketing cost to consumers by charging high price for coffee. To get over the problems, Caffe Bene is currently using C/S Consumer Management System though experts are questioning about the efficacy because of the conflict between purpose of the system and the headquarters' plan. Present CEO Kim also announced that the company will complete its logistics system in the latter half of 2012 to provide stores with more high quality coffee beans to improve taste of coffee. Thus, in this case, we describe how Caffe Bene succeeded in Korean market and enumerate its key success factors. Also, we specify the long-term goals of Caffe Bene and introduce the current policies and strategies to show how the company is working on to achieve its ultimate goal. By reading and analyzing this business case, students could get useful insights regarding franchise management and think about issues on competing in a saturated market. Also, it would be worthwhile to generate creative solutions for the problems that Caffe Bene is now facing to broaden the practical perspective.

• Asia Marketing Journal
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• v.7 no.1
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• pp.67-89
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• 2005

In recent decades, product variety has increased dramatically in most industries. Rapidly evolving technologies, global competition, and sophisticated customers have contributed to an increase in product variety in many industries. In this paper, I study the impact of product variety on several businesses in the supply chain through literature review. By study of literature. this paper presents the benefits and drawbacks of increasing product variety on functions performed in several departments, such as engineering, manufacturing, purchasing, logistics and marketing. It provides a brief overview of the various techniques like modularity, component sharing, and platform-based development, which are helpful in reducing the costs, when designing for variety. It also provides a brief overview of order processing, purchased component/part variety, which are helpful in reducing the purchasing costs, and customer satisfaction, market advantage, market share, competitive advantage and demand forecast, which are useful in impact of product variety on marketing. Future research directions are discussed.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2021.11a
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• pp.74-75
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• 2021

At the 104th IMO MSC, it was decided to make a code for the operation of MASS(Maritime Autonomous Surface Ship). In addition, the government announced a roadmap for preemptive regulatory innovation for autonomous ships and identified 31 related regulatory issues and suggested improvements to revitalize the autonomous ship industry. This study aims to analyze the ship turning left on the route as a study on how to operate the route system when operating MASS. We intend to derive the current congestion degree of the special area of Busan New Port through maritime traffic survey and use simulation to derive the congestion degree of the special area due to the size of ships and increase in traffic volume. We would like to propose an appropriate amount of traffic (the number of L-converted). It is believed that the research results can be used as basic data for route operation when operating not only current ships but also MASS.

• Journal of the Society of Disaster Information
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• v.20 no.2
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• pp.398-410
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• 2024

Purpose: It is to present the development direction of the overall 'disaster management implementation process' (tentative name) for the establishment of an effective 'safety management plan' by the government and local governments. Method: To this end, prior research on the 'safety management plan' was reviewed to derive common problems, and the direction of development was suggested by incorporating the 'disaster management execution process' (tentative name) that can solve these problems with the military's 'operational execution process'. Result: Common problems of previous studies can be supplemented through the 'disaster management performance process' (tentative name) presented by this researcher. Conclusion: Through the "disaster management implementation process" (tentative name), the government's basic ideology of disaster management can be finally achieved, "confirming that it is a basic mission of the state and local governments and allowing the people to live in a society that is safe from disasters."

• KOREAN JOURNAL OF PACKAGING SCIENCE & TECHNOLOGY
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• v.29 no.3
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• pp.175-179
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• 2023

This paper analyzes the vibration characteristics within the cargo compartment of a three-wheeled cargo bike when used on both regular roads and dedicated bicycle lanes. When cargo is loaded into the cargo compartment of a cargo bike and driven on the road, the shocks and vibrations transmitted from the ground can potentially affect the transported goods and even lead to product damage. As the vibration characteristics applied to the cargo compartment may vary depending on the condition of the road, vibration sensors were attached to the cargo bike's cargo compartment for data collection during operation on different road types. According to KS T ISO 13355 standards, the cargo bike can withstand vibrations within the range of 10 Hz to 60 Hz when operating on both bicycle lanes and regular roads. However, it is observed that there are peaks exceeding the profile in the frequency range of 3-6 Hz. In the 70-200 Hz range, the profile is exceeded on both regular roads and bicycle lanes, with a tendency for higher exceedance on bicycle lanes. The Grms value within the frequency range of KS T ISO 13355 is 5.926 m/s² (0.604 Grms). When operating on bicycle lanes with cargo, the Peak envelope optimization PSD value is 6.553 Grms, while on bicycle lanes, it is 7.708 Grms, indicating a difference of at least tenfold.

• Journal of Navigation and Port Research
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• v.48 no.1
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• pp.27-33
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• 2024

Following the COVID-19 pandemic, congestion within container terminals has led to a significant increase in waiting time and turnaround time for external trucks, resulting in a severe inefficiency in gate-in and gate-out operations. In response, port authorities have implemented a Vehicle Booking System (VBS) for external trucks. It is currently in a pilot operation. However, due to issues such as information sharing among stakeholders and lukewarm participation from container transport entities, its improvement effects are not pronounced. Therefore, this study proposed a deep learning-based predictive model for external trucks turnaround time as a foundational dataset for addressing problems of waiting time for external trucks' turnaround time. We experimented with the presented predictive model using actual operational data from a container terminal, verifying its predictive accuracy by comparing it with real data. Results confirmed that the proposed predictive model exhibited a high level of accuracy in its predictions.

• The Journal of Fisheries Business Administration
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• v.55 no.2
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• pp.1-16
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• 2024

This study analyzes the impact of import country environments on Korean fishery exports. To achieve the research objective, focusing on trade facilitation and import market aspects, the import country environment was modeled and analyzed by panel gravity analysis technique. In the basic export model considering only the trade facilitation aspect, agriculture and institutional factors had a significant impact on Korean fishery exports. However, when considering both trade facilitation and import market aspects, it was found that import market aspect had a greater influence on Korean fishery exports than trade facilitation aspect. Specifically, the import market factor that had the most positive impact on Korean fishery exports was the GDP of the import country. GDP, representing the economic scale of the country, indicates consumer purchasing power through per capita GDP. Hence, a higher GDP level implies a higher consumer purchasing power, suggesting a higher potential consumption of fishery products. The second positive factor influencing Korean fishery exports was food imports in the import country. Therefore, to expand Korean fishery exports, it is essential to target countries with high levels of GDP and food imports. Conversely, factors negatively affecting Korean fishery exports were merchandise imports and population in the import country. Therefore, countries with high levels of these negative factors should be managed as demarketing targets. Additionally, trade facilitation variables, which have relatively smaller influence, such as transparency and institutions, also significantly impact Korean fishery exports. While transparency has a positive effect, institution has a negative effect. Thus, to expand Korean fishery exports, strategies should focus on countries with high transparency and less stringent institutional regulations.

• Journal of applied mathematics & informatics
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• v.42 no.4
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• pp.831-854
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• 2024

The transportation problem (TP) is one of the earliest and the most significant implementations of linear programming problem (LPP). It is a specific type of LPP that mostly works with logistics and it is connected to day-to-day activities in our everyday lives. Nowadays decision makers (DM's) aim to reduce the transporting expenses and simultaneously aim to reduce the transporting time of the distribution system so the bi-objective transportation problem (BOTP) is established in the research. In real life, the transportation parameters are naturally uncertain due to insufficient data, poor judgement and circumstances in the environment, etc. In view of this, neutrosophic bi-objective transportation problem (NBOTP) is introduced in this paper. By introducing single-valued trapezoidal neutrosophic numbers (SVTrNNs) to the co-efficient of the objective function, supply and demand constraints, the problem is formulated. The DM's aim is to determine the optimal compromise solution for NBOTP. The extended weighted possibility mean for single-valued trapezoidal neutrosophic numbers based on [40] is proposed to transform the single-valued trapezoidal neutrosophic BOTP (SVTrNBOTP) into its deterministic BOTP. The transformed deterministic BOTP is then solved using the dripping method [10]. Numerical examples are provided to illustrate the applicability, effectiveness and usefulness of the solution approach. A sensitivity analysis (SA) determines the sensitivity ranges for the objective functions of deterministic BOTP. Finally, the obtained optimal compromise solution from the proposed approach provides a better result as compared to the existing approaches and conclusions are discussed for future research.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.47 no.3
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• pp.95-103
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• 2024

The diversity of smart EV(electric vehicle)-related industries is increasing due to the growth of battery-based eco-friendly electric vehicle component material technology, and labor-intensive industries such as logistics, manufacturing, food, agriculture, and service have invested in and studied automation for a long time. Accordingly, various types of robots such as autonomous mobile robots and collaborative robots are being utilized for each process to improve industrial engineering such as optimization, productivity management, and work management. The technology that should accompany this unmanned automobile industry is unmanned automatic charging technology, and if autonomous mobile robots are manually charged, the utility of autonomous mobile robots will not be maximized. In this paper, we conducted a study on the technology of unmanned charging of autonomous mobile robots using charging terminal docking and undocking technology using an unmanned charging system composed of hardware such as a monocular camera, multi-joint robot, gripper, and server. In an experiment to evaluate the performance of the system, the average charging terminal recognition rate was 98%, and the average charging terminal recognition speed was 0.0099 seconds. In addition, an experiment was conducted to evaluate the docking and undocking success rate of the charging terminal, and the experimental results showed an average success rate of 99%.

• East Asian Economic Review
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• v.28 no.3
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• pp.359-388
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• 2024

With the escalation of global trade, the Chinese commodity futures market has ascended to a pivotal role within the international shipping landscape. The Shanghai Containerized Freight Index (SCFI), a leading indicator of the shipping industry's health, is particularly sensitive to the vicissitudes of the Chinese commodity futures sector. Nevertheless, a significant research gap exists regarding the application of Chinese commodity futures prices as predictive tools for the SCFI. To address this gap, the present study employs a comprehensive dataset spanning daily observations from March 24, 2017, to May 27, 2022, encompassing a total of 29,308 data points. We have crafted an innovative deep learning model that synergistically combines Long Short-Term Memory (LSTM) and Convolutional Neural Network (CNN) architectures. The outcomes show that the CNN-LSTM model does a great job of finding the nonlinear dynamics in the SCFI dataset and accurately capturing its long-term temporal dependencies. The model can handle changes in random sample selection, data frequency, and structural shifts within the dataset. It achieved an impressive R² of 96.6% and did better than the LSTM and CNN models that were used alone. This research underscores the predictive prowess of the Chinese futures market in influencing the Shipping Cost Index, deepening our understanding of the intricate relationship between the shipping industry and the financial sphere. Furthermore, it broadens the scope of machine learning applications in maritime transportation management, paving the way for SCFI forecasting research. The study's findings offer potent decision-support tools and risk management solutions for logistics enterprises, shipping corporations, and governmental entities.