• Korea Trade Review
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• v.47 no.5
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• pp.161-179
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• 2022

This paper aims to examine the role of government's support in facilitating small and medium sized enterprises (SMEs)' green dynamic capabilities and green SCM practices in a global market. It also investigates whether government support, green dynamic capabilities, and green SCM practices affect export competitiveness. To develop those hypotheses, prior studies and in-depth interviews were conducted and data was collected from Korean manufacturing companies that export abroad and then developed the structural equation model. The hypotheses test results revealed that green dynamic capabilities through government support positively affect export competitiveness and green SCM practices through green dynamic capabilities have positive effects on export competitiveness. Finally, this study is valuable in that it directly and indirectly confirmed the effect of eco-friendly government support on export competitiveness.

• Journal of Distribution Science
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• v.22 no.6
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• pp.107-114
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• 2024

Purpose: The current research investigates historical and future trends of tourist distribution channels in the tourism services business. The research examines historical patterns, current shifts, and new technologies in electricity distribution to offer insight into the distribution dynamics and advice for companies and regulators. Research design, data and methodology: The research in this case specifically employed the PRISMA approach when it comes to the data collection and research methodology. (PRISMA). The process is specifically made up of four steps, such as (1) Identification of Relevant Studies, (2) Screening and Selection Procedures, (3) Data Synthesis and Analysis, and (4) Reporting of Findings. Results: The fast-changing technology offers all opportunities to innovate the sector of tourism services. These upcoming technologies are not just reconstructing the way customers interact and operate but they are also creating room for development. Besides "the utilization of new technologies such as artificial intelligence, augmented reality, virtual reality, and blockchain, the current state of tourism distribution channels also implies some other possible consequences. Conclusions: These research results show that we should not be reluctant about adopting new technologies, we should expand direct booking systems, promote eco-friendly tourism, and use data analytics in order to provide personalized experiences.

• International Commerce and Information Review
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• v.18 no.2
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• pp.131-150
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• 2016

As global partnership is recently getting important in order to establish supply chain network in global managing environment, companies tend to improve quality and warranty in SCM(Supply Chain Management) by certifying ISO(International Organization for Standardization). This research investigated structural relationship how strategic and operational ISO application level and trust, immersion, collaborative factors in partnership process affect to companies business performance. This research was surveyed with 147 manufacturing companies in South Korea and conducted empirical analysis using Structural equation model. The research hypothesis and model was derived from the basis of existing theory and empirical research, and obtained the following results. Firstly, the strategic ISO level showed positive(+) effect on trust and immersion factor. Second, the operational ISO level showed positive(+) effect on trust and collaborative factor. Third, trust factor in the partnership process showed positive(+) effect on immersion factor. Lastly, collaborative factor in partnership process showed positive(+) effect on companies business performance. Implication for this research is that companies must consider ISO application in establishing partnership and companies require prolonged effort using trust, immersing, collaborative factors into partnership process to improve business performance.

• Korea Trade Review
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• v.42 no.2
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• pp.319-344
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• 2017

The international standard certification evaluates the extend to which the supplier satisfies the international standard certification standards of the supplier of the product and the service, recognizes the quality assurance ability and reliability of the supplier, thereby resolving the international trade regulation that can occur to various fields and strengthening the network of the global partnership it is making an important contribution. Therefor, in this study, the survey was conducted on 153 companies of Korean import and export companies. The research method was empirically analyzed by the structural equation model. The results of the hypothesis test of this study are as follows. First, resource management factors among the international standard certification factors in the global trade supply chain integration had a positive effects on CRM satisfaction. Second, the measurement, analysis and improvement factors of international standard certification factors had a positive effects on CRM satisfaction. Third, CRM satisfaction has a positive effects on business performance. Through this study, it is concluded that the Korean import and export companies have an important role in improving the business performance of the global trade partners.

• Journal of Korea Multimedia Society
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• v.11 no.2
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• pp.269-280
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• 2008

The information flow through RFID techniques such as, standardized EPC and EPCglobal network suggests new change in the method of cooperating and sharing information in the supply chain. Common function should be prepared for communication, security techniques, and business processes based on the EPCglobal standard to introduce efficient RFID techniques. And the standard architecture which can deal with the RFID environment flexibly is quite necessary. Therefore, this paper suggests Enterprise Application Framework (EAF) for developing efficient and secure RFID applications. EAF offers essential services to develop RFID enterprise systems : a communication environment which uses various standard communication protocols, a security function based on PKI, and abstract business services for flexible introduction of RFID businesses. It simplifies the RFID business integration, minimizes the development complexity, and thus EAF is expected to reduce the cost of RFID application development. EAF guarantees constructing secure RFID applications due to PKI-based security mechanism.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2012.06a
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• pp.273-274
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• 2012

Companies are facing challenges to have high competitiveness because of continuous oil price rising and CO2 emissions regulations. Thus, companies are trying hard to construct effective logistics and operation system to achieve high customer service quality and saving cost. Also the ec-friendly idustrial complex is needed. Busan is in process to construct GILC(Global Industry Logistics City) in west Busan province to achieve high competitiveness and support lack of industrial complex. To construct this kind of logistics industrial complex, it needs logistics system through proper policy and freight transportation co-operation. Especially, efficient management through logistics hierarchy construction in industrial complex is very important for low cost and eco-friendly point of view. Therefore, this paper aims to analyze logistics system and suggest operation model to present logistics complex construction base data.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2014.06a
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• pp.221-222
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• 2014

Companies are facing challenges to have high competitiveness because of continuous oil price rising and CO2 emissions regulations. Thus, companies are trying hard to construct effective logistics and operation system to achieve high customer service quality and saving cost. Also the ec-friendly idustrial complex is needed. Busan is in process to construct GILC(Global Industry Logistics City) in west Busan province to achieve high competitiveness and support lack of industrial complex. To construct this kind of logistics industrial complex, it needs logistics system through proper policy and freight transportation co-operation. Especially, efficient management through logistics hierarchy construction in industrial complex is very important for low cost and eco-friendly point of view. Therefore, this paper aims to analyze logistics system and suggest operation model to present logistics complex construction base data.

• Journal of the Korea Safety Management & Science
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• v.14 no.4
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• pp.153-168
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• 2012

It has been recognized as an important issue to design optimally a firm's logistics network for minimizing logistics cost and maximizing customer service. It is, however, not easy to get an optimal solution by analyzing trade-off of cost factors, dynamic and interdependent characteristics in the logistics network decision making. Although there has been some developments in a system which helps decision making for logistics analysis, it is true that there is no system for enterprise-wise's on-site support and methodical logistics decision. Specially, E-biz process along with information technology has been made dramatic advance in a various industries, there has been much need for practical education closely resembles on-site work. The software developed by this study materializes efficient algorithm suggested by recent studies in key topics of logistics such as location and allocation problem, traveling salesman problem, and vehicle routing problem and transportation and distribution problem. It also supports executing a variety of experimental design and analysis in a way of the most user friendly based on Java. In the near future, we expect that it can be extended to integrated supply chain solution by adding decision making in production in addition to a decision in logistics.

• International Journal of Computer Science & Network Security
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• v.23 no.9
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• pp.1-7
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• 2023

Demand prediction is an essential component of any business or supply chain. Large retailers need to keep track of tens of millions of items flows each day to ensure smooth operations and strong margins. The demand prediction is in the epicenter of this planning tornado. For business processes in retail companies that deal with a variety of products with short shelf life and foodstuffs, forecast accuracy is of the utmost importance due to the shifting demand pattern, which is impacted by an environment of dynamic and fast response. All sectors strive to produce the ideal quantity of goods at the ideal time, but for retailers, this issue is especially crucial as they also need to effectively manage perishable inventories. In light of this, this research aims to show how Machine Learning approaches can help with demand forecasting in retail and future sales predictions. This will be done in two steps. One by using historic data and another by using open data of weather conditions, fuel, Consumer Price Index (CPI), holidays, any specific events in that area etc. Several machine learning algorithms were applied and compared using the r-squared and mean absolute percentage error (MAPE) assessment metrics. The suggested method improves the effectiveness and quality of feature selection while using a small number of well-chosen features to increase demand prediction accuracy. The model is tested with a one-year weekly dataset after being trained with a two-year weekly dataset. The results show that the suggested expanded feature selection approach provides a very good MAPE range, a very respectable and encouraging value for anticipating retail demand in retail systems.

• International Journal of Computer Science & Network Security
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• v.23 no.8
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• pp.210-216
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• 2023

Demand prediction is an essential component of any business or supply chain. Large retailers need to keep track of tens of millions of items flows each day to ensure smooth operations and strong margins. The demand prediction is in the epicenter of this planning tornado. For business processes in retail companies that deal with a variety of products with short shelf life and foodstuffs, forecast accuracy is of the utmost importance due to the shifting demand pattern, which is impacted by an environment of dynamic and fast response. All sectors strive to produce the ideal quantity of goods at the ideal time, but for retailers, this issue is especially crucial as they also need to effectively manage perishable inventories. In light of this, this research aims to show how Machine Learning approaches can help with demand forecasting in retail and future sales predictions. This will be done in two steps. One by using historic data and another by using open data of weather conditions, fuel, Consumer Price Index (CPI), holidays, any specific events in that area etc. Several machine learning algorithms were applied and compared using the r-squared and mean absolute percentage error (MAPE) assessment metrics. The suggested method improves the effectiveness and quality of feature selection while using a small number of well-chosen features to increase demand prediction accuracy. The model is tested with a one-year weekly dataset after being trained with a two-year weekly dataset. The results show that the suggested expanded feature selection approach provides a very good MAPE range, a very respectable and encouraging value for anticipating retail demand in retail systems.