• Title/Summary/Keyword: Sales System

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A Study on the Use of LD Clause against the Seller's Breach of Delivery of Goods in the Contract for the International Sale of Goods (국제물품매매계약에서 매도인의 물품인도의무 위반에 대비한 손해배상액의 예정조항 (Liquidated Damage Clause: LD조항)의 활용에 관한 연구 - ICC Model International Sale Contract를 중심으로)

  • Oh, Won-Suk;Youn, Young-MI;Li, Jing Hua
    • THE INTERNATIONAL COMMERCE & LAW REVIEW
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    • v.50
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    • pp.3-25
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    • 2011
  • The purpose of this paper is to examine the use of LD Clause against the seller's breach of contract in connection with delivering the goods in the international sales contract, and international guarantee system using standby L/C or demand guarantee. For this purpose, the author, first, considered the outline of the buyer's remedies in cases that the seller had not performed his obligations in contract and the difficulties in the buyer's remedies. As alternatives for overcoming the difficulties, this author recommended the LD Clauses (Liquidated Damage Clauses) based on ICC Model International Sales Contract, and explained each Model Clause. To enhance the feasibility of LD Clause, this author suggested the guarantee system, like the standby L/C or demand guarantee. But these guarantee systems have several limitations in practical use. Thus, these guarantee systems would greatly contribute to Korean exportation in the future. The reason is that the Korean export structure would be more complex and the period of sales contract would be longer and longer, which result to in long-terms supply contracts. These changes would require the guarantee much urgently.

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Research on the Lubrication Characteristics of Driving Modules (구동 모듈 감속기 윤활 특성에 관한 연구)

  • Kim, EunKyum;Kim, HyunChan;Park, JunYoung
    • Tribology and Lubricants
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    • v.38 no.2
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    • pp.70-72
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    • 2022
  • In this study, we report on a power system developed as a decelerator for a driving module in an electric vehicle. The system is to be mounted in a limited space. The research focus was on development of miniaturization, light weight, and high power density. In particular, we aimed to minimize the layout of existing external components as integrated or built-in, and to maximize the power density by applying optimal cooling technology to increased requirements for developing modular power systems applicable to various OEM models. South Korean automakers ranked fourth in global electric-vehicle sales in 2020, but domestic sales are relatively slow. Despite government's expansion in subsidies for eco-friendly cars, consumers are delaying purchases after 2021 considering the cost-effectiveness of electric vehicles. In major European markets, the demand for electric vehicles exceeded the demand for diesel cars, and sales of hybrid cars, which used to represent eco-friendly cars, are slowing down as Toyota, started selling electric vehicles. In this study, the internal lubrication characteristics of a decelerator installed in an electric vehicle were analyzed in terms of the deceleration time while driving. By selecting the proper oil and oil viscosity, it was confirmed that there is no problem in lubricating the bearings and gears of the decelerator.

Multi-vehicle Route Selection Based on an Ant System

  • Kim, Dong-Hun
    • International Journal of Fuzzy Logic and Intelligent Systems
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    • v.8 no.1
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    • pp.61-67
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    • 2008
  • This paper introduces the multi-vehicle routing problem(MRP) which is different from the traveling sales problem(TSP), and presents the ant system(AS) applied to the MRP. The proposed MRP is a distributive model of TSP since many vehicles are used, not just one salesman in TSP and even some constraints exist. In the AS, a set of cooperating agents called vehicles cooperate to find good solutions to the MRP. To make the proposed MRP extended more, Tokyo city model(TCM) is proposed. The goal in TCM is to find a set of routes that minimizes the total traveling time such that each vehicle can reach its destination as soon as possible. The results show that the AS can effectively find a set of routes minimizing the total traveling time even though the TCM has some constraints.

An Analysis of Cooperation Service Level using Safety Shipment Plan (안전공급계획에 따른 판매지점들의 협조공급수준 분석)

  • Yoon Seung-Chul;Min Ji-Young
    • Journal of the Korea Safety Management & Science
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    • v.8 no.2
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    • pp.115-128
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    • 2006
  • The study analyzes those relations of customer service level of each sales branch, level of cooperations among branches, and overall system-wide service level for an item. Under the continuous review method, each sales branch places an order to the outside supplier, and the each branch receives the order quantity after elapsing a certain lead time. Under these circumstances, those branches with stockout condition may be supplied by other branches with keeping stocks to cover the shortages. This policy generally increases the system-wide customer service level for an item throughout cooperations for the safety plan among branches. Therefore, in the context of inventory policy, the decision rules to determine the proper branch levels of service and cooperation levels of service are important goals in terms of attaining desired system-wide service level. This research has suggested the method and procedure to reach above goals.

Analyzing the Technical Efficiency of Korean System Integration Firms Using DEA and Malmquist Productivity Analysis (자료포괄분석과 생산성지수분석을 이용한 국내 SI기업의 효율성 분석)

  • Kim, Kon-Shik
    • Journal of Information Technology Services
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    • v.5 no.1
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    • pp.1-16
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    • 2006
  • This paper analyzes the technical efficiencies of 40 Korean system integration firms using data envelopment analysis (DEA) and Malmquist productivity indices. Technical efficiencies on average had been decreased over the five year period and the efficiency difference between best practice firms and catch-up firms had been increased during this period, meaning that the industry structure has become matured and the possibilities for catch-up firms to be efficient are not remained so much. The differences in efficiency by the differences in ownership structures are statistically significant. It implies that the efficiencies of group-affiliated firms have come from benefits such as the captive market umbrellas, not from their own management competencies. In addition, the technical efficiency is highly correlated with captive market sales, information productivity, sales per employees, rates of value added, returns on invested capital, and EBITDA.

SKU recommender system for retail stores that carry identical brands using collaborative filtering and hybrid filtering (협업 필터링 및 하이브리드 필터링을 이용한 동종 브랜드 판매 매장간(間) 취급 SKU 추천 시스템)

  • Joe, Denis Yongmin;Nam, Kihwan
    • Journal of Intelligence and Information Systems
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    • v.23 no.4
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    • pp.77-110
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    • 2017
  • Recently, the diversification and individualization of consumption patterns through the web and mobile devices based on the Internet have been rapid. As this happens, the efficient operation of the offline store, which is a traditional distribution channel, has become more important. In order to raise both the sales and profits of stores, stores need to supply and sell the most attractive products to consumers in a timely manner. However, there is a lack of research on which SKUs, out of many products, can increase sales probability and reduce inventory costs. In particular, if a company sells products through multiple in-store stores across multiple locations, it would be helpful to increase sales and profitability of stores if SKUs appealing to customers are recommended. In this study, the recommender system (recommender system such as collaborative filtering and hybrid filtering), which has been used for personalization recommendation, is suggested by SKU recommendation method of a store unit of a distribution company that handles a homogeneous brand through a plurality of sales stores by country and region. We calculated the similarity of each store by using the purchase data of each store's handling items, filtering the collaboration according to the sales history of each store by each SKU, and finally recommending the individual SKU to the store. In addition, the store is classified into four clusters through PCA (Principal Component Analysis) and cluster analysis (Clustering) using the store profile data. The recommendation system is implemented by the hybrid filtering method that applies the collaborative filtering in each cluster and measured the performance of both methods based on actual sales data. Most of the existing recommendation systems have been studied by recommending items such as movies and music to the users. In practice, industrial applications have also become popular. In the meantime, there has been little research on recommending SKUs for each store by applying these recommendation systems, which have been mainly dealt with in the field of personalization services, to the store units of distributors handling similar brands. If the recommendation method of the existing recommendation methodology was 'the individual field', this study expanded the scope of the store beyond the individual domain through a plurality of sales stores by country and region and dealt with the store unit of the distribution company handling the same brand SKU while suggesting a recommendation method. In addition, if the existing recommendation system is limited to online, it is recommended to apply the data mining technique to develop an algorithm suitable for expanding to the store area rather than expanding the utilization range offline and analyzing based on the existing individual. The significance of the results of this study is that the personalization recommendation algorithm is applied to a plurality of sales outlets handling the same brand. A meaningful result is derived and a concrete methodology that can be constructed and used as a system for actual companies is proposed. It is also meaningful that this is the first attempt to expand the research area of the academic field related to the existing recommendation system, which was focused on the personalization domain, to a sales store of a company handling the same brand. From 05 to 03 in 2014, the number of stores' sales volume of the top 100 SKUs are limited to 52 SKUs by collaborative filtering and the hybrid filtering method SKU recommended. We compared the performance of the two recommendation methods by totaling the sales results. The reason for comparing the two recommendation methods is that the recommendation method of this study is defined as the reference model in which offline collaborative filtering is applied to demonstrate higher performance than the existing recommendation method. The results of this model are compared with the Hybrid filtering method, which is a model that reflects the characteristics of the offline store view. The proposed method showed a higher performance than the existing recommendation method. The proposed method was proved by using actual sales data of large Korean apparel companies. In this study, we propose a method to extend the recommendation system of the individual level to the group level and to efficiently approach it. In addition to the theoretical framework, which is of great value.

T-Commerce Sale Prediction Using Deep Learning and Statistical Model (딥러닝과 통계 모델을 이용한 T-커머스 매출 예측)

  • Kim, Injung;Na, Kihyun;Yang, Sohee;Jang, Jaemin;Kim, Yunjong;Shin, Wonyoung;Kim, Deokjung
    • Journal of KIISE
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    • v.44 no.8
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    • pp.803-812
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    • 2017
  • T-commerce is technology-fusion service on which the user can purchase using data broadcasting technology based on bi-directional digital TVs. To achieve the best revenue under a limited environment in regard to the channel number and the variety of sales goods, organizing broadcast programs to maximize the expected sales considering the selling power of each product at each time slot. For this, this paper proposes a method to predict the sales of goods when it is assigned to each time slot. The proposed method predicts the sales of product at a time slot given the week-in-year and weather of the target day. Additionally, it combines a statistical predict model applying SVD (Singular Value Decomposition) to mitigate the sparsity problem caused by the bias in sales record. In experiments on the sales data of W-shopping, a T-commerce company, the proposed method showed NMAE (Normalized Mean Absolute Error) of 0.12 between the prediction and the actual sales, which confirms the effectiveness of the proposed method. The proposed method is practically applied to the T-commerce system of W-shopping and used for broadcasting organization.