• Journal of Korean Society of Industrial and Systems Engineering
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• v.45 no.3
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• pp.214-227
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• 2022

The successful implementation of green supply chain management(GSCM) practices requires a level of cooperation that can be difficult to conduct. Despite this challenge, limited scholarly attention has been paid to exploring how the implementation of GSCM practices can be effectively facilitated and enhanced through accumulated social capital with suppliers. Based on social capital theory, this study postulates that supplier network characteristics derived from social capital with key suppliers can be critical antecedents of GSCM, which in turn enhances the firm's environmental performance. To test hypotheses, data were collected from 330 firms in 15 countries, and structural equation modeling was employed. Results show that GSCM improves environmental performance, and structural and cognitive social capitals of the supplier network act as antecedents and lead to GSCM implementation.

• The Journal of the Korea Contents Association
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• v.18 no.12
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• pp.291-298
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• 2018

Supplier selection for energy production facility is a multi-criteria decision-making problem and is of strategic importance for cost efficiency of synthetic fiber production company. The purpose of this paper is to present an approach to select best energy production facility for a synthetic fiber production company. Toward this, we derived criteria to evaluate the energy production facility and develop an Analytic Network Process model to help decision makers set priorities on multiple criteria while considering both qualitative and quantitative aspects of the problem. The application of the proposed approach indicates that it can be successfully applied to facilitate the decision making process for selecting the best supplier of the energy production facility.

• Journal of Information Processing Systems
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• v.18 no.1
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• pp.75-88
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• 2022

With the development of the sharing economy, existing recommender services are changing from user-item recommendations to user-user recommendations. The most important consideration is that all users should have the best possible satisfaction. To achieve this outcome, the matching service adds information between users and items necessary for the existing recommender service and information between users, so higher-level data mining is required. To this end, this paper proposes a user-to-user matching service (UTU-MS) employing the prediction of mutual satisfaction based on learning. Users were divided into consumers and suppliers, and the properties considered for recommendations were set by filtering and weighting. Based on this process, we implemented a convolutional neural network (CNN)-deep neural network (DNN)-based model that can predict each supplier's satisfaction from the consumer perspective and each consumer's satisfaction from the supplier perspective. After deriving the final mutual satisfaction using the predicted satisfaction, a top recommendation list is recommended to all users. The proposed model was applied to match guests with hosts using Airbnb data, which is a representative sharing economy platform. The proposed model is meaningful in that it has been optimized for the sharing economy and recommendations that reflect user-specific priorities.

• Journal of Korea Society of Industrial Information Systems
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• v.26 no.3
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• pp.9-22
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• 2021

This study proposes a supply chain network (SCN) model considering supply disruption in assembly industry. For supply disruption, supplier disruption and its route disruption are simultaneously taken into consideration in the SCN model. With the simultaneous consideration, the SCN model can achieve its flexibility and efficiency. A mathematical formulation is suggested for representing the SCN model, and a proposed hybrid genetic algorithm (pro-HGA) is used for implementing the mathematical formulation. In numerical experiment, the performance of the pro-HGA approach is compared with those of some conventional approaches using the SCN models with various scales, and a sensitivity analysis considering the change of the numbers of suppliers and backup routes is done. Experimental results show that the performances of the pro-HGA approach are superior to those of the conventional approaches, and the flexibility and efficiency of the SCN model considering supply disruption are proved. Finally, the significance of this study is summarized and a potential future research direction is mentioned in conclusion.

• IE interfaces
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• v.14 no.1
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• pp.30-38
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• 2001

Logistics network management has become one of the most important sources of competitive advantage regarding logistics cost and customer service in numerous business segments. Logistics network simulation is a powerful analysis method for designing and planning the logistics network optimally in an integrated way. This paper introduces a logistics network simulator, LONSIM, developed by author. LONSIM deploys a mix of simulation and optimization functions to model and analysis logistics network issues such as facility location, inventory policy, manufacturing policy, transportation mode, warehouse assignment, supplier assignment, order processing priority rule, and vehicle routes. LONSIM is built with AweSim 2.1 and Visual Basic 6.0, and executed in windows environment.

• Asia Marketing Journal
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• v.19 no.1
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• pp.19-34
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• 2017

Despite the importance of the impact of network structure on the relationships between firms and firm performance, few studies have investigated these effects. This study investigates how network openness influences the relationships between TSI, opportunism, technological uncertainty, and supplier performance. We also try to figure out how network openness functions as a governance mechanism.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2004.10a
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• pp.565-565
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• 2004

Due to limitation of resources and increasing concerns about environment, reverse logistics has received growing attention in recent years. In this paper, we propose three types of reverse logistics networks based on reuse of returnable containers, materials recycling process and remanufacturing for parts reuse. First, the sender in the re-usable item network supplies containers for the recipient and orders either new containers from external supplier or returnable containers cleaned from the container depot. Second, the recycling center in the proposed recycling network collects either end of life products from customer or faulty goods from manufacturer, collected products are dismantled into materials and materials go into recycling process. Finally, the manufacturer in the proposed remanufacturing network has two alternatives for supplying parts: either ordering the required parts to external supplier or overhauling disassembled parts and bringing them back 'as new' conditions. In this product recovery environment, we build optimal order quantity models to minimize the total logistics costs related to reverse logistics network. The validity of the proposed model is investigated through comprehensive computational experiments.

• Journal of the Korean Professional Engineers Association
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• v.42 no.6
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• pp.36-41
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• 2009

Smart Grid is grafting IT(information technology) techniques on existing electric power network, supplier and the consumer to do real-time exchange of information lead to both direction and energy efficiency optimization, it is a next potential electric power network method. Because of applying various distributed electric power sources, the electric power network system will follow in size and it is dispersive and it will operate independently, and it become the intelligent electric power network, which in consumer demand reacts at real-time, because of using various sensors. In this article explain concept, features, and contemporary background of Smart Grid, and describe improve reliability of the electric power quality.

• Journal of Sensor Science and Technology
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• v.27 no.5
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• pp.352-356
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• 2018

This paper relates to a technology for monitoring a liquefied gas storage tank in the special gas field where demand is increasing owing to the continuous growth of related fields such as the semiconductor, display, and ICT convergence electronics industries. We have proposed a system for real - time monitoring using wireless sensor network technology, and implemented a system consisting of a sensor unit, transmitter module, and receiver module to be attached to a liquefied gas storage tank. The system was applied to LCO2 tanks among various liquefied gas storage tanks to verify the feasibility. The storage tanks employed in the experiments has capacities of 16,179 l and was 1,920 mm in inner diameter. Furthermore, the density was 1.03 g/l. The measured data were compared with reference data on the remaining gas level versus the $CO_2$ height of the surface, expressed using a conventional water meter, provided by an existing storage tank supplier. The experimental results show that the data is similar to the standard data provided by the tank supplier, and has a high accuracy and reliability within an error range of 0.03%.

• Proceedings of the Korean Information Science Society Conference
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• 2004.10c
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• pp.370-372
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• 2004

본 논문에서는 개방형 운영체제인 리눅스상에서 package streaming service를 제공하는 Network Streaming Service(통칭 NSS)를 설계하는 문제를 다룬다. NSS는 client가 serve 측에 설치된 소프트웨어 package를 마치 client 자신의 local disk상에 이미 인스톨된 패키지를 실행하는 것처럼 동작하도록 해준다. NSS는 client측의 NSS Mounter, Package Streaming Consumer, NSS Configurator와 server측의 NSS Load Balancer, Package Streaming Supplier, NSS Manager, Accounting & Security Manager로 구성되며 local disk caching과 background prefetching 기능을 사용하여 향상된 서비스를 제공한다.