• Journal of Distribution Science
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• v.21 no.1
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• pp.53-63
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• 2023

Purpose: Big Data analytics (BDA) has been recognized to improve firm performance because it can efficiently manage and process large-scale, wide variety, and complex data structures. This study examines the determinants of Big Data analytics adoption toward marketing and financial performance of global logistic companies in Thailand. The research framework is adopted from the technology-organization-environment (TOE) model, including technological factors (relative advantages), organizational factors (technological infrastructure and absorptive capability), environmental factors (industry competition and government support), Big Data analytics adoption, marketing performance, and financial performance. Research design, data, and methodology: A quantitative method is applied by distributing the survey to 450 employees at the manager's level and above. The sampling methods include judgmental, stratified random, and convenience sampling. The data were analyzed by Confirmatory Factor Analysis (CFA) and Structural Equation Model (SEM). Results: The results showed that all factors significantly influence Big Data analytics adoption, except technological infrastructure. In addition, Big Data analytics adoption significantly influences marketing and financial performance. Conversely, marketing performance has no significant influence on financial performance. Conclusions: The findings of this study can contribute to the strategic improvement of firm performance through Big Data analytics adoption in the logistics, distribution, and supply chain industries.

• Journal of Distribution Science
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• v.22 no.6
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• pp.57-68
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• 2024

Purpose: Dynamic capabilities are acknowledged as pivotal factors facilitating the generation of competitive advantage and performance for enterprises across diverse sectors, notably within the food processing industry. This study endeavors to explore and examine the direct and indirect impact of dynamic capability factors, encompassing innovation capability, market orientation (customer orientation, supply chain orientation, competitor orientation), and digital orientation on the business performance of Vietnamese food processing enterprises. Research design, data and methodology: Research data was collected from 239 food processing enterprise managers and analyzed using partial least square - structural equation modeling. Results: With the exception of digital orientation, the study found evidence of the role of innovation capability and market orientation (customer orientation, supply chain orientation, competitor orientation) in the overall competitive advantage of Vietnamese food processing enterprises. Furthermore, the study underscores the contributions of innovation capability, market orientation and digital orientation in fostering performance of Vietnamese food processing enterprises. It also identifies the mediating role of competitive advantage in the relationship between dynamic capabilities and performance. Conclusions: Consequently, the study proposes a number of implications for food processing enterprise managers with the aim of establishing and enhancing competitive advantage and business performance in the future.

• Proceedings of the Korean Institute of Interior Design Conference
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• 2005.10a
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• pp.81-84
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• 2005

As a works of total design program for franchise, Visual Identity Will supply harmonious batch of images to their customers in various marketing environment of franchise members. so Visual Identity will explain a concept of space-design to their clients more clear than any others. and it will help a clients to accept fran-brand more easily. Because suppling a chain of images constantly under the 'VISUAL IDENTITY' is more efficient way to market. Space-design constituted with 'systematically-organized Visual Identity plan'.! It's very usefull one to rise brand value among some works of brand marketing

• 제어로봇시스템학회:학술대회논문집
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• 2004.08a
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• pp.1859-1864
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• 2004

An effective methodology is reported for the optimal design of multisite batch production/transportation and storage networks under uncertain demand forecasting. We assume that any given storage unit can store one material type which can be purchased from suppliers, internally produced, internally consumed, transported to or from other plant sites and/or sold to customers. We further assume that a storage unit is connected to all processing and transportation stages that consume/produce or move the material to which that storage unit is dedicated. Each processing stage transforms a set of feedstock materials or intermediates into a set of products with constant conversion factors. A batch transportation process can transfer one material or multiple materials at once between plant sites. The objective for optimization is to minimize the probability averaged total cost composed of raw material procurement, processing setup, transportation setup and inventory holding costs as well as the capital costs of processing stages and storage units. A novel production and inventory analysis formulation, the PSW(Periodic Square Wave) model, provides useful expressions for the upper/lower bounds and average level of the storage inventory. The expressions for the Kuhn-Tucker conditions of the optimization problem can be reduced to two sub-problems. The first yields analytical solutions for determining lot sizes while the second is a separable concave minimization network flow subproblem whose solution yields the average material flow rates through the networks for the given demand forecast scenario. The result of this study will contribute to the optimal design and operation of large-scale supply chain system.

• Journal of Environmental Health Sciences
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• v.43 no.4
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• pp.307-313
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• 2017

Objectives: Chemicals derived from various environment media contaminates food across the food supply chain. In Korea, levels of contaminants in food have been sporadically measured by monitoring programs of different government agencies. There is difficulty with data compilation and integrated analysis across media. Therefore, the aim of this study was to propose an overall integrated database and analytical platform design for the 'ECO-FOOD NET (Environmental COntaminant reduction platform for FOOD through an interagency collaboration NETwork)', a tool to support the reduction of environmental contaminants in food. Methods: We developed a new data structure and standardized protocols for the compilation of integrated data. In addition, we conducted subject-oriented logical and physical relational database modeling and created the architecture design of the platform. Results: We established a standardized code system related to exposure media and route, analysis method and food matrix. In addition, we designed the seven software modules of 'About the System', 'Introduction to Interagency Work', 'Media-Chemicals Profiles', 'Method Bank', 'Monitoring Data Base', 'Integrated Media Analysis', and 'Risk-Benefit Analysis'. Conclusions: This study will contribute to decision-making as a tool for executing risk management, such as sustainable reduction policies of contaminants in food.

• Industrial Engineering and Management Systems
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• v.13 no.1
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• pp.52-66
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• 2014

Promotion of a closed-loop supply chain requires disassembly systems that recycle end-of-life (EOL) assembled products. To operate the recycling disassembly system, parts selection is environmentally and economically carried out with non-destructive or destructive disassembly, and the recycling rate of the whole EOL product is determined. As the number of disassembled parts increases, the recycling rate basically increases. However, the labor cost also increases and brings lower profit, which is the difference between the recovered material prices and the disassembly costs. On the other hand, since the precedence relationships among disassembly tasks of the product also change with the parts selections, it is also required to optimize allocation of the tasks in designing a disassembly line. In addition, because information is required for such a design, the recycling rate, profit of each part and disassembly task times take precedence among the disassembly tasks. However, it is difficult to obtain that information in advance before collecting the actual EOL product. This study proposes and analyzes an optimal disassembly system design using integer programming with the environmental and economic parts selection (Igarashi et al., 2013), which harmonizes the recycling rate and profit using recyclability evaluation method (REM) developed by Hitachi, Ltd. The first stage involves optimization of environmental and economic parts selection with integer programming with ${\varepsilon}$ constraint, and the second stage involves optimization of the line balancing with integer programming in terms of minimizing the number of stations. The first and second stages are generally and mathematically formulized, and the relationships between them are analyzed in the cases of cell phones, computers and cleaners.

• Journal of Institute of Control, Robotics and Systems
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• v.10 no.6
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• pp.537-544
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• 2004

An effective methodology is reported for determining the optimal lot size of batch processing and storage networks which include uncertain demand forecasting. We assume that any given storage unit can store one material type which can be purchased from suppliers, internally produced, infernally consumed, transported to or from other sites and/or sold to customers. We further assume that a storage unit is connected to all processing and transportation stages that consume/produce or move the material to which that storage unit is dedicated. Each processing stage transforms a set of feedstock materials or intermediates into a set of products with constant conversion factors. A batch transportation process can transfer one material or multiple materials at once between sites. The objective for optimization is to minimize the probability averaged total cost composed of raw material procurement, processing setup, transportation setup and inventory holding costs as well as the capital costs of processing stages and storage units. A novel production and inventory analysis formulation, the PSW(Periodic Square Wave) model, provides useful expressions for the upper/lower bounds and average level of the storage inventory. The expressions for the Kuhn-Tucker conditions of the optimization problem can be reduced to two sub-problems. The first yields analytical solutions for determining lot sires while the second is a separable concave minimization network flow subproblem whose solution yields the average material flow rates through the networks for the given demand forecast scenario. The result of this study will contribute to the optimal design and operation of the global supply chain.

• Journal of Appropriate Technology
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• v.6 no.2
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• pp.94-102
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• 2020

Renewable energy (RE) is essential to comprise sustainable societies, especially, in rural villages of developing countries. Furthermore, application of off-grid RE systems to health care can improve the quality of life. In this research, a RE-based vaccination supply management system was constructed to enlarge the cold-chain in developing countries for the safe storage and delivery of vaccines. The system was comprised of the construction of RE plants and development of vaccine carriers. RE plants were constructed and connected to health posts in local villages. The cooling mechanism of vaccine carriers was improved and monitoring devices were installed. The effect of the system on vaccine cold-chain was evaluated from the field test and topographical analysis in the southern village of Nepal. RE plants were normally operated for the vaccine refrigerator in the health post. The modified vaccine carriers had a longer operation time and better temperature control via monitoring and RE-based recharging functionality. The topographical analysis estimated that the system can cover larger region. The system prototype showed great potential regarding the possibility of a sustainable and enlarged cold-chain. Thus, RE-based vaccine supply management is expected to facilitate vaccine availability while minimizing waste in the supply chain.

• Proceedings of the Korean Society for Quality Management Conference
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• 2006.11a
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• pp.151-154
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• 2006

본 연구는 공급사슬관리하에서 부품 및 원재료 공급기업에서 고객기업인 제조기업의 주문 사항과 공급기업내 생산관련 제약사항을 동시에 고려하여 최적의 생산 체제를 구축할 수 있는 방법론을 제시한다. 본 연구에서는 수주 및 비용 데이터베이스로부터 주문 및 생산관련 데이터를 SOM 신경망분석을 통해 그룹핑하고 고객기업군별로 특성분석을 통해 이에 맞는 생산체제를 구축할 것을 제안하였다. 공급사슬관리 환경하에서 원재료/부품 공급기업이 고객기업의 주문 요구와 내부 생산상의 제약을 동시에 고려함으로써 SCM 적용 성과를 극대화할 수 있다는 점에서 본 연구는 의미가 있다.

• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.396-396
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• 2000

Multiperiod optimization is the key step to tackle the supply chain optimization problems. Taking supply and demand uncertainty or prediction into consideration during the process synthesis phase leads to the maximization of the profit for the long range time horizon. In this study, new algorithm based on the Genetic Algorithms is proposed for multiperiod optimization formulated in MINLP, GDP and hybrid MINLP/GDP. In this study, the focus is given especially on the design of the Genetic Algorithm suitable to handle disjunctive programming with the same level of MINLP handling capability. Hybridization with the Simulated Annealing is tried. and many heuristics are adopted for this purpose.