• Industrial Engineering and Management Systems
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• v.14 no.2
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• pp.111-121
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• 2015

A correct information of customer returns ratio under e-commerce is not always shared between supply chain (SC) members. Also, it is important issue for SC members to handle the unsold products in a market. This paper discusses the impact of information sharing of customer returns ratio on an optimal sales strategy including resale of customer returns and buyback policy for a SC under e-commerce with a manufacturer and a retailer. A retailer sells a single product and resells the resalable customer returns in the same market. A manufacturer produces the products and buys back the unsold products as to their quality from the retailer. The integrated SC (ISC) determines the optimal product order quantity to maximize the expected profit of the whole SC. The decentralized SC (DSC) makes the optimal decisions for order quantity and the wholesale price of products to maximize the expected profit of each SC member. The effect of information sharing is discussed between SC members under ISC and DSC. The analysis numerically investigates how information sharing of the returns ratio affects the optimal decision and the expected profits under ISC and DSC. Besides, effect of SC coordination to encourage the shift to ISC is discussed.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.27 no.4
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• pp.59-68
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• 2004

Recently, shifting channel power is forcing supply chain to take back products. As you can imagine returned product has always been a problem for all parties in the supply chain due to the disruption in operations and a headache in processing returned products. Therefore, every member of supply chain should respond to reverse logistics activities particularly for the return handling process. Under such a strong demand of efficient and cost effective reverse logistics activities, particularly for the return handling process, the information system should be implemented and participated in intensively. This study analyzed the reverse logistics information factors for environmental conscious logistics system limited to returns from customers/consumers. The results provide reverse logistics information factors based on the return handling process which can be used as benchmarking for companies seeking implementation of an efficient return handling system.

• Journal of KIISE:Databases
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• v.31 no.2
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• pp.132-139
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• 2004

A range $Top-\kappa$ query returns top k records in order of a measure attribute within a specified region on multi-dimensional data, and it is a powerful tool for analysis in spatial databases and data warehouse environments. In this paper, we propose an algorithm for answering the query via selective traverse of a Hierarchical Max R-Tree(HMR-tree). It is possible to execute the query by accessing only a small part of the leaf nodes in the query region, and the query performance is nearly constant regardless of the size of the query region. The algorithm manages the priority queue efficiently to reduce cost of handling the queue and the proposed HMR-tree can guarantee the same fan-out as the original R-tree.

• Tribology and Lubricants
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• v.36 no.6
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• pp.324-331
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• 2020

Wedging in a frictional elastic system is defined if the state of stick exists after the external loading on the system is removed. This paper presents a method to determine the critical coefficient of wedging for an elastic frictional system by considering the separation state. Wedging is always possible if the coefficient of friction exceeds a critical value known as the critical wedging coefficient. This method requires two concepts: a necessary and sufficient condition for wedging, which can be interpreted as positive spanning sets of constraint vectors existing in the wedged system, and the minimal positive basis that enables a minimum wedging coefficient. The algorithm based on the positive spanning concept is repeatedly executed after eliminating nodes from the contact stiffness matrix, for which the separation states are impending. The simulation results show that once a node enters the separation state, it never returns to the contact state again and the critical wedging coefficient reduces during repeated algorithm execution. The benefit of this method is that the computation time permits handling models with large numbers of contact nodes. The algorithm can also numerically find the critical wedging coefficient, thereby contributing to fastening and assembly performance improvements in mechanical systems.

• Journal of Intelligence and Information Systems
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• v.5 no.1
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• pp.103-123
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• 1999

Input filtering as a preprocessing method is so much crucial to get good performance in time series forecasting. There are a few preprocessing methods (i.e. ARMA outputs as time domain filters, and Fourier transform or wavelet transform as time-frequency domain filters) for handling time series. Specially, the time-frequency domain filters describe the fractal structure of financial markets better than the time domain filters due to theoretically additional frequency information. Therefore, we, first of all, try to describe and analyze specially some issues on the effectiveness of different filtering methods from viewpoint of the performance of a neural network based forecasting. And then we discuss about neural network model architecture issues, for example, what type of neural network learning architecture is selected for our time series forecasting, and what input size should be applied to a model. In this study an input selection problem is limited to a size selection of the lagged input variables. To solve this problem, we simulate on analyzing and comparing a few neural networks having different model architecture and also use an embedding dimension measure as chaotic time series analysis or nonlinear dynamic analysis to reduce the dimensionality (i.e. the size of time delayed input variables) of the models. Throughout our study, experiments for integration methods of joint time-frequency analysis and neural network techniques are applied to a case study of daily Korean won / U. S dollar exchange returns and finally we suggest an integration framework for future research from our experimental results.

• Journal of KIISE:Databases
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• v.35 no.4
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• pp.333-344
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• 2008

In recent years, the web services composition has received much attention. By web services composition, we mean providing a new service that does not exist on the repository. In this paper, we propose a new system called PSR for web services composition search using a relational database. We also propose algorithms for pre-computing web services composition using joins and indices. We store ontologies from web services in RDBMS, so that the PSR system returns web services composition in order of similarity with user query through the degree of the ontology matching. We demonstrated that our pre-computing web services composition approach in RDBMS yields lower execution time and good scalability when handling a large number of web services and user queries.

• Informatization Policy
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• v.31 no.2
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• pp.65-81
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• 2024

The scale of e-procurement through online shopping malls of public institutions including government comprehensive shopping malls is increasing day by day. This study aims to examine how public officials evaluate products, delivery, and post service of online shopping malls for public institutions and to explore ways of improving their satisfaction. The results from a survey conducted among public officials of public institutions who have experience using online shopping malls of public institutions showed generally high satisfaction levels, although there was dissatisfaction with product diversity. Perception of delivery quality was generally positive, but there was room for improvement in delivery service. Furthermore, employing structural equation modeling, the study examined the influences on satisfaction and intention to reuse. Perceived product quality, delivery quality, and delivery service quality were confirmed to influence satisfaction considerably. Therefore, more efforts should be directed towards managing the information and quality of products to prevent returns, exchanges, and repairs and, in case of issues, handling them promptly and transparently.

• Journal of Digital Convergence
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• v.16 no.9
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• pp.81-90
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• 2018

The purpose of this study is to examine the current status of automobile logistics in the domestic automobile industry and to derive and evaluate the factors to improve the quality of automobile logistic services to final consumers. To that end, we selected the relevant factors through literature review and expert interviews, and conducted a survey with consumers and experts. The quality of automobile logistic service was evaluated using the Importance-Performance Analysis (IPA) method. The results show that the "kindness of shipping staff" is high on the importance of customers but low on the importance of employees. On the other hand, factors that have high customer satisfaction but low staff satisfaction include "rapid handling of complaints", "transportation accuracy of receipt", "kindness of delivery staff", and "automobile manual guide and explanation of internal functions". This study has academic and industrial significance in that it has derived important factors for evaluating the quality of automobile logistics services and suggests improvement measures for experts and consumers who actually work in the industrial field. Future research should investigate measures to minimize the returns and complaints of shipment offices which have not been examined in this study.

• Journal of Korea Port Economic Association
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• v.24 no.4
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• pp.313-327
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• 2008

The purpose of this paper is to show the empirical measurement way for predicting the seaport efficiency by using SBM with Wilcoxson signed-rank test under CRS(constant returns to scale) condition for 20 Korean ports during 1994-2003 for 2 inputs(birthing capacity, cargo handling capacity) and 3 outputs(Export and Import Quantity, Number of Ship Calls, Port Revenue). The main empirical results of this paper are as follows. First, forecasting data have well reflected the real data according to the Wilcoxon signed rank test, because p values have exceeded the 0.05 significance level. Second, SBM has shown the effectiveness for predicting the ports efficiency even though the predicting powers are different according to the levels of p values. The policy implication to the Korean seaports and planner is that Korean seaports should introduce the new methods like SBM method with Wilcoxon signed rank test for predicting the port performance and enhancing the efficiency.

• Journal of Korea Port Economic Association
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• v.26 no.3
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• pp.18-41
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• 2010

The purpose of this paper is to show the empirical measurement way for predicting the seaport efficiency by using Super SBM(Slack-based Measure) with Wilcoxson signed-rank test under CRS(constant returns to scale) condition for 20 Korean ports during 11 years(1997-2007) for 3 inputs(port investment amount, birthing capacity, and cargo handling capacity) and 5 outputs(Export and Import Quantity, Number of Ship Calls, Port Revenue, Customer Satisfaction Point for Port Service and Container Cargo Throughput). The main empirical results of this paper are as follows. First, Super SBM model has well reflected the real data according to the Wilcoxon signed rank test, because p values have exceeded the significance level. Second,Super-SBM has shown about 87% of predicting ratio for the ports efficiency and the optimal size of investment in domestic seaport. The policy implication to the Korean seaports and planner is that Korean seaports should introduce the new methods like Super-SBM method with Wilcoxon signed rank test for predicting the efficiency of port performance and the optimal size of investment as indicated by Panayides et al.(2009, pp.203-204).