• The Journal of Asian Finance, Economics and Business
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• v.7 no.7
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• pp.403-412
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• 2020

The main purpose of this paper is to explore how green supply chain management (GSCM) and its evaluative factors have affected green supply chain management practice and performance in industrial zone. This study proposes a structural equation model of the relationships among four factors: internal awareness (IA); suppliers' pressure (SP); customers' awareness (CA); and regulations pressure (RP) and their effect on GSCM practice (PA) and GSCM performance (PE). We used a survey questionnaire to elicit perceptions/opinions about GSCM from three level of managers of 322 companies in Bac Ninh Province's industrial zones, Vietnam. PLS-SEM 3.0 software was applied to analyze and verify the gathered data, and the proposed hypothesis model. The results of path analysis show that internal awareness and customers' awareness are positively related to the GSCM practice and GSCM performance. However, suppliers' pressure and regulations pressure just impacted on GSCM practice. As a result, the testing of the relationship between GSCM practice and GSCM performance has been verified and supported. The findings of this study can help manager of companies in industrial zone understand the structure of GSCM, associate with the green supply chain management practice and green supply chain management performance, and be successful in green management organizations.

• IE interfaces
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• v.21 no.3
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• pp.343-353
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• 2008

Vendor-managed inventory(VMI) is a supply chain strategy to improve the inventory turnover and customer service in supply chain management. Unfortunately, many VMI programs fail because they simply transfer the transactional aspects of placing replenishment orders from customer to vendor. In fact, such VMI programs often degrade supply chain performance because vendors lack capability to plan the VMI operations effectively in an integrated way under the dynamic, complex, and stochastic VMI supply chain environment. This paper presents a decision support system, termed DSSV, for VMI in the retail supply chain. DSSV supports the market forecasting, vendor's production planning, retailer's inventory replenishment planning, vehicle routing, determination of the system operating parameter values, retailer's purchase price decision, and what-if analysis. The potential benefits of DSSV include the provision of guidance, solution, and simulation environment for enterprises to reduce risks for their VMI supply chain operations.

• Journal of Distribution Science
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• v.14 no.4
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• pp.21-31
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• 2016

Purpose - This study examines how consignment and Vendor-Managed Inventory perform as supply chain collaboration programs. By using three key collaborative features, this study defines the collaboration programs and develops theoretical models of different supply chain systems. Research design, data and methodology - This study conducts sophisticated analysis on the supply chain systems by applying simulation modeling based on time-phased operations. The simulation model represents a two-stage supply chain system where a supplier sells a single item to a buyer, and it incorporates various operations. Results - In general, the simulation outcomes support that more advanced collaboration programs outperform less advanced ones. The analysis on the simulation outcomes identifies the significant value of information sharing in both collaboration programs. The specific conditions where the particular collaboration system outperforms the others are recognized. Conclusions - The outcome of this study supports that the supply chain system can improve its performance by having more collaborative features. This study provides business practitioners with guidelines to identify the circumstances that the specific collaboration program can fully exploit its advantages.

• Journal of the Korean Operations Research and Management Science Society
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• v.31 no.1
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• pp.73-82
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• 2006

Supply chain management (SCM) has been regarded as one of the most critical issues in the current business environment. Moreover, supply chain partnerships between suppliers and buyers in SCM have had a significant impact on supply chain performance. In this paper, we conduct a quantitative analysis for supplier-buyer's profit sharing and pricing policies based on supply chain partnerships. For this purpose, we assume that a two echelon supply chain with a single supplier and a single buyer is given and the buyer faces deterministic demand which is not only a function of buyer's selling price, but also strictly decreasing, concave, and twice differentiable function. Then we will prove the following. Firstly, without supply chain partnerships, there exist supplier and buyer's selling prices per unit such that their total profits are maximized, under the assumption that buyer's order quantity is exactly equal to the demand buyer faced. Secondly, buyer's selling price per unit which maximizes supply chain's total profit with supply chain partnerships is lower than buyer's selling price per unit which maximizes buyer's total profit without supply chain partnerships. Thirdly, given supplier's selling price per unit. buyer's total profit without supply chain part nerships is greater than that with supply chain partnerships, whereas the opposite case happens for supplier's total profit. Finally, there exists supplier's selling price per unit which makes the maximum total profits for both supplier and buyer with supply chain partnerships greater than those obtained for any given supplier's selling price per unit without supply chain partnerships.

• Industrial Engineering and Management Systems
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• v.7 no.1
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• pp.78-89
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• 2008

The need for holistic modeling efforts for returns that capture the extended closed loop supply chain (CLSC) system at strategic as well as operational level has been clearly recognized by the industry and academia. Strategic decision-makers need comprehensive models that can guide them in efficient decision-making to increase the profitability of the entire forward and return chain. Therefore, determination of a near optimal design configuration, which includes the environmental, economical and technological capability factors, is important in strategic decision-making effort that affect the profitability of the closed loop supply chain. In this paper, we adopted an improved system dynamics methodology to tackle strategic issues that affect various performance measures, like market, time/cost, environment etc., for closed loop supply chains. After studying real life implementation issues in CLSC design, we presented guidelines for the PBM (Participative Business Modeling) methodology and presented its extension for the strategic dynamic system modeling of return chains. Finally, we demonstrated the measurement of operational performance by extending SD (system dynamic) application to closed loop supply chain management.

• Journal of Korea Port Economic Association
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• v.27 no.3
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• pp.13-39
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• 2011

Many previous studies on the subject of supply chain have consistently claimed that they need collaboration among the partners of supply chains in order to enhance supply chain performance. The purpose of research is to examine the causal linkages among relational characteristics, collaboration, performance in the logistics firm and this research focuses on two types collaboration(operational collaboration and strategic collaboration) as the mediation variable between relational characteristics and supply chain performance. To test the above research questions, we collected data from logistics firm(N=164). The proposed structural model was tested using the PLS(Partial Least Square) statistical program. The research results are as follows. Trust, and information sharing have positive influences on operational collaboration, and operational collaboration have also positive influences on supply chain performance. Duration and information sharing have positive influences on strategic collaboration. However, strategic collaboration has non-positive influences on supply chain performance. The effect of relational characteristics on supply chain performance is mediated by operational collaboration.

• Journal of Korea Trade
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• v.27 no.1
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• pp.19-41
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• 2023

Purpose - Conventional supply chains (SCs) must identify facilitating roles, such as port or terminal operators, shipping companies, and freight forwarders in executing the various logistical activities that support the organizational strategies of shippers. Meanwhile, supply chain collaborative practices can engender a willingness to share relevant and mutually helpful information. To this end, this study seeks to identify the impact of supply chain integration (SCI) on information sharing (IS) and the operational performance (OP) of Korea's container-shipping industry from the perspective of social capital. Design/methodology - We established the research model for this study based on previous studies. In administering the survey, we obtained 149 valid responses from employees working in liner-shipping companies and freight forwarders in Korea. With the collected questionnaires, the study's hypotheses were tested using SPSS 26.0 and AMOS 26.0 Findings - The results indicate the existence of a mediated relationship where the impact of SCI on OP is mediated by IS. The effect of external integration (EI) on OP is fully mediated by information quality (IQ) and information-sharing content (ISC). Furthermore, EI, IQ and ISC partially mediate the relationship between internal integration (II) and OP. Originality/value - This study expands SCI contexts, where ISC and IQ respectively serve as bridges between EI and OP which has crucial implications for container-shipping companies in terms of improving their performance.

• Journal of Korea Society of Industrial Information Systems
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• v.23 no.5
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• pp.33-41
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• 2018

Most important thing when designing and implementing a supply chain network is to consider various problems which may occur in real world situation. In this paper, we propose a supply chain network considering two problems (environmental factor and transportation types) under real world situation. CO2 emission amount as environmental factor is considered since it is usually generated from production and transportation processes. Normal delivery, direct delivery and direct shipment as transportation types are also considered since many customers ask various transportation types for delivery or shipment of their products under on-line or off-line purchase environment. The proposed supply chain network considering environmental factor and transportation types is represented in a mathematical formulation and implemented using hybrid genetic algorithm (HGA) approach. In numerical experiments, several scales of supply chain networks are presented and implemented using HGA approach. The performance of the HGA approach is compared with those of some conventional approaches under various measures of performance. Finally, it is proved that the performance of the HGA approach is superior to those of the others.

• Korea Trade Review
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• v.44 no.4
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• pp.169-188
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• 2019

This study aims to analyze the effects of the smart technologies acceptance on global supply chain innovation and export performance in Korean small and medium trading companies. As the world prepares for the advent of the 4th industrial revolution the level of smart technology acceptance by Korean small and medium trading companies has not yet reached the level that is compatible with the change of international paradigm. In this respect, this study aims to promote the acceptance of smart technologies and suggest a need of more practical policy for securing international market competitiveness through innovation of global supply chain structure of Korean trading companies. According to the empirical research results, the smart technology acceptance had a significant effect on both the internal supply chain innovation and the export performance. Also, the external supply chain innovation significantly affected export performance. These results suggested that Korean trading companies need to be more active and positive in accepting smart technology so that they can gain more competitive advantage in the 4th industrial revolution era.

• International Journal of Computer Science & Network Security
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• v.22 no.12
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• pp.37-50
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• 2022

Modern supply chains include multiple activities from collecting raw materials to transferring final products. These activities involve many parties who share a huge amount of valuable data, which makes managing supply chain systems a challenging task. Current supply chain management (SCM) systems adopt digital technologies such as the Internet of Things (IoT) and blockchain for optimization purposes. Although these technologies can significantly enhance SCM systems, they have their own limitations that directly affect SCM systems. Security, performance, and scalability are essential components of SCM systems. Yet, confidentiality and scalability are one of blockchain's main limitations. Moreover, IoT devices are lightweight and have limited power and storage. These limitations should be considered when developing blockchain-based IoT-SCM systems. In this paper, the requirements of efficient supply chain systems are analyzed and the role of both IoT and blockchain technologies in providing each requirement are discussed. The limitations of blockchain and the challenges of IoT integration are investigated. The limitations of current literature in the same field are identified, and a secure and scalable blockchain-based IoT-SCM system is proposed. The proposed solution employs a Hyperledger fabric blockchain platform and tackles confidentiality by implementing private data collection to achieve confidentiality without decreasing performance. Moreover, the proposed framework integrates IoT data to stream live data without consuming its limited resources and implements a dualstorge model to support supply chain scalability. The proposed framework is evaluated in terms of security, throughput, and latency. The results demonstrate that the proposed framework maintains confidentiality, integrity, and availability of on-chain and off-chain supply chain data. It achieved better performance through 31.2% and 18% increases in read operation throughput and write operation throughput, respectively. Furthermore, it decreased the write operation latency by 83.3%.