• East Asian Journal of Business Economics (EAJBE)
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• v.12 no.1
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• pp.23-33
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• 2024

Purpose: This paper explores the nuanced approaches undertaken by private companies in formulating and implementing business continuity plans (BCPs) in response to the unprecedented challenges posed by the global COVID-19 pandemic. Research design, data, and methodology: Utilizing a mixed-methods research design, the study delves into the multifaceted strategies employed by private sector entities, ranging from risk assessment and remote work policies to supply chain diversification and employee well-being initiatives. Result: The findings contribute to a deeper understanding of the evolving landscape of business continuity planning during a pandemic, offering valuable insights for academia, industry practitioners, and policymakers. The research findings present a detailed account of how private companies have tailored their business continuity plans in response to the unique challenges posed by the pandemic. Conclusion: This academic exploration sheds light on the dynamic landscape of business continuity planning in private companies responding to the global pandemic. Insights into the effectiveness of remote work policies, supply chain diversification, employee safety measures, and financial strategies contribute to the understanding of best practices and areas requiring further attention. These recommendations aim to inform future business continuity planning efforts, enhance organizational resilience, and mitigate the impact of global health crises on private sector operations.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2002.05a
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• pp.449-455
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• 2002

This paper considers that advanced planning and scheduling (APS) in manufacturing and the efficient purchasing where each customer order has its due date and multi-suppliers exit We present a Make-To­Order Supply Chan (MTOSC) model of efficient purchasing process from multi-suppliers and APS with outsourcing in a supply chain, which requires the absolute due date and minimized total cost. Our research has included two states. One is for efficient purchasing from suppliers: (a) selection of suppliers for required parts; (b) optimum part lead­time of selected suppliers. Supplier selection process has received considerable attention in the business­management literature. Determining suitable suppliers in the supply chain has become a key strategic consideration. However, the nature of these decisions usually is complex and unstructured. These influence factors can be divided into quantitative and qualitative factors. In the first level, linguistic values are used to assess the ratings for the qualitative factors such as profitability, relationship closeness and quality. In the second level a MTOSC model determines the solutions (supplier selection and order quantity) by considering quantitative factors such as part unit price, supplier's lead-time, and storage cost, etc. The other is for APS: (a) selection of the best machine for each operation; (b) deciding sequence of operations; (c) picking out the operations to be outsourcing; and (d) minimizing makespan under the due date of each customer's order. To solve the model, a genetic algorithm (GA)-based heuristic approach is developed. From the numerical experiments, GA­based approach could efficiently solve the proposed model, and show the best process plan and schedule for all customers' orders.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2003.09a
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• pp.170-174
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• 2003

In this research, we consider an integrated manufacturing/distribution planning problem in supply chain (SC) which has non-integer time lags. We focus on a capacitated manufacturing planning and capacity allocation problem for the system. We develop a mixed binary integer linear programming (MBLP) model and propose an efficient heuristic procedure using an adaptive genetic algorithm, which is composed of a regeneration procedure for evaluating infeasible chromosomes and the reduced costs from the LP-relaxation of the original model. The proposed an adaptive genetic algorithm was tested in terms of the solution accuracy and algorithm speed during numerical experiments. We found that our algorithm can generate the optimal solution within a reasonable computational time.

• Journal of Korean Institute of Industrial Engineers
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• v.41 no.4
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• pp.344-351
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• 2015

Recently, an ERP (Enterprise resource Planning) system has been becoming an essential S/W tool for companies to manage their business processes and manufacturing resources. As the information exchange becomes more complex, not only corporate companies but also small- and mid- sized enterprises (SMEs) are required to build an ERP system. However, for small- and middle- sized companies, the adoption of ERP systems becomes challenging due to high cost and long installation time of the system. This paper presents a novel concept of an adaptive ERP system incorporating the ontology structure of the business supply chain information. The proposed ERP installation methodology is illustrated with an example of a door-trim manufacturing company in the automotive supply chain.

• Journal of the Korea Safety Management & Science
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• v.6 no.1
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• pp.135-146
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• 2004

This paper first addresses a distribution planning method on centrally controlled supply chain. The distribution channels are assumed to be network of arborescence form. For such distribution networks, this study proposes a distribution planning scheme when the demands for retail sites are provided for a given planning horizon. As the planning horizon rolls forward, for a new horizon, forecasted demand distributions of periods in the horizon are updated. An idea of controlling customer service level by the selection of demand to be used in the planning (Demand Used in Planning, DUP) from the forecasted values is also discussed.

• Journal of the Korean Solar Energy Society
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• v.30 no.3
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• pp.81-89
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• 2010

The photovoltaic industry is one of the main research areas for regenerable energy usage and green growth policy of the Korean government. R&D programs of MEST(Ministry of Education, Science and Technology) and MKE(Ministry of Knowledge Economy) are concentrating on the development of fundamental and applicable technology which can be carried out by a so-called "Big company" consortium. So it is essential to discover and support R&D projects for small and medium enterprises(SMEs) in the photovoltaic industry. R&D projects should be funded effectively to enhance the competitiveness of the SMEs. It is a complicated process as to decide what R&D projects or key element technologies should be selected and how to support them. In this paper, the supply chain analysis is adopted as a critical tool for selecting the research areas and topics for the SMEs, which can be done by analyzing the number of the SMEs, the level of imports and the localization possibility for each supply chain element. We define the strategic products for the SMEs to deduct core technologies for each strategic product. R&D projects definition sheets are proposed for each core technology. All the decision making processes are authorized by a committee which consists of experts for academia, industries and the research field. The efficacy of the proposed framework is described throughout the photovoltaic industry.

• Journal of Digital Convergence
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• v.11 no.7
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• pp.83-95
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• 2013

Supply chain management for engineering project focuses on planning acquisitions, identifying and choosing the right suppliers and subcontractors, planning and negotiating appropriate contracts, and administering the collaboration with the suppliers and subcontractors. This paper aims to identify the determinants of SCM performance of the suppliers and subcontractors participating in the project-based supply chain. This study proposes the absorptive capacity, fairness of suppliers' evaluation, the quality of collaboration and incentives as major research variables, and collected the survey responses from the suppliers and subcontractors having experiences with major engineering projects. The statistical results indicate that the incentives, absorptive capacity and the quality of collaboration influence SCM performance of suppliers, and that the fairness of suppliers' evaluation has some impact on the incentives and the absorptive capacity. But on the contrary to our expectation, the incentives have no significant impact on the level of absorptive capacity.

• IE interfaces
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• v.16 no.4
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• pp.441-449
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• 2003

In this paper we propose a distribution planning method aiming the use in the real-life situations. The assumed form of the distribution network is arborescence. At every node in the distribution network, orders are placed periodically. At each renewal of planning horizon, demand informations of periods in the horizon are updated. The objective of the problem is to minimize the total cost, which is the sum of holding and backorder costs of all sites during planning horizon. For such a situation, this study addressed an effective distribution plan when demands for demand-sites are provided for a given planning horizon.

• Journal of Korean Institute of Industrial Engineers
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• v.31 no.2
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• pp.120-126
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• 2005

Until now, the traditional production models and logistics have developed a broader strategic approach called supply chain. However, there are some obstacles to apply industry practice because of unrealistic assumptions. The most serious of them is that they assume the lead times are integer multiples of the planning time grid. This assumption makes it difficult to express the processing and transportation lags correctly. Thus, in this paper, we propose a new methodology for the integrated production/distribution model having non-integer time lags using the concept of dynamic production function. In case that the time lags are integer or non-integer, the dynamic production function reflects well the situation under given environments. Experiments show that the proposed model can express the real system more accurately than the prior model can.

• Proceedings of the Korea Society for Simulation Conference
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• 2000.11a
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• pp.165-173
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• 2000

Analytic models have been developed to solve integrated production-distribution problems in supply chain management (SCM). As one of major constraints in analytic models, capacity, which is the total operation time in this paper has mostly been known or disregarded assuming infinite capacity. Also, as major factors, machine processing time to fabricate or assemble a part or product at a certain machine center in production system and vehicle processing time to deliver a product to a customer by a certain vehicle in distribution system have been fixed and regarded as a static factor, But in the real systems significant differences exit between capacity and the required time to achieve the production-distribution plan and between processing time and consumed time to process a part or product. In this paper, capacity and processing times in the analytic model are considered as dynamic factors and adjusted by the results from independently developed simulation model, which includes general production-distribution characteristics. Through experiments, we obtain the more realistic solutions reflecting stochastic natures by performing the iterative analytic-simulation procedure.