It is very important that sellers provide reasonable reserve prices for auction items in internet auction systems. We recently have proposed the agent based system in order to generate reserve prices automatically, based on the case similarity of information retrieval theory and the moving average of time series analysis. However, the approaches have some problems that they can not reflect the recent trend of auction prices on the generated reserve prices properly, because they only provide the bid prices or average prices of items, by using the past auction data for sellers. In this paper, in order to overcome the problems, we propose Similarity-Based Time Series Analysis which search the past bid price through case similarity and then generate reserve prices by using time series analysis. Through performance experiments, we show that the successful bid rate of the new method can be improved by preventing sellers from making unreasonable reserve prices compared with the past methods.

Reserve price recommendation by similarity-based time series analysis for internet auction systems

In recent years, the e-commerce arena has deeply changed because of the advent of new business models and the growing weight of huge global actors like Amazon. Some business models create competition between users, and the product price tends to rise (e.g., online auctions); other models, including group-buying, make users cooperate, and the price tends to go down. The present study extends the group-buying model and proposes a cyber-physical system called e-fair, in which both sellers and buyers are grouped to negotiate on a specific product or service. E-fairs minimize the global purchase price and the shipping resources respectively with the aggregation of demand and supply as well as origins and destinations. E-fairs aggregate sellers and buyers, sources and destinations in what we call double-side aggregation. As the aggregation regards independent actors, which do not trust each other and join e-fairs in dribs and drabs, we employ a promising distributed technology as the blockchain to make the aggregation. We validated the e-fair model through a system prototype and a simulator and understood how economies of scale apply to e-fairs in different usage scenarios.

E-Fairs: a Cyber-Physical System for Aggregation and Economy of Scale in e-Commerce

In recent years, many new and interesting models of successful online business have been developed. Many of these are based on the competition between users, such as online auctions, where the product price is not fixed and tends to rise. Other models, including group-buying, are based on cooperation between users, characterized by a dynamic price of the product that tends to go down. There is not yet a business model in which both sellers and buyers are grouped in order to negotiate on a specific product or service. The present study investigates a new extension of the group-buying model, called fair, which allows aggregation of demand and supply for price optimization, in a cooperative manner. Additionally, our system also aggregates products and destinations for shipping optimization. We introduced the following new relevant input parameters in order to implement a double-side aggregation: (a) price-quantity curves provided by the seller; (b) waiting time, that is, the longer buyers wait, the greater discount they get; (c) payment time, which determines if the buyer pays before, during or after receiving the product; (d) the distance between the place where products are available and the place of shipment, provided in advance by the buyer or dynamically suggested by the system. To analyze the proposed model we implemented a system prototype and a simulator that allow to study effects of changing some input parameters. We analyzed the dynamic price model in fairs having one single seller and a combination of selected sellers. The results are very encouraging and motivate further investigation on this topic.

Fairs for e-commerce: the benefits of aggregating buyers and sellers

In this paper, we describe visualization pursuant of developing 37 Honored Ones within the Diamond World Mandala. “The 37 Honored Ones” are a collective term for 5 Buddhas and 32 Bodhisattvas that were built on the basis of Vajrasekhara Sutra. Also, as core values of Buddhism, they represent ideas of Esoteric Buddhism systematically and symbolically. “The 37 Honored Ones” are completed by the development of 4 Buddhas from Vairocana and their interaction with 16 Great Bodhisattvas and 16 Offering Bodhisattvas that were also developed from Vairocana. So, in this paper, we analyze and visualize the development of “37 Honored Ones.” This line of research is significant because it aims to convert narrative structure of the conventional Buddhism scriptures into various types of digital contents. Also, applications of the implemented visual digital contents can be as follows; educational service for Buddhist doctrines, development of the various Buddhist cultural contents, etc.

http://koreascience.or.kr:80/article/JAKO201536553330084.pdf

Visualization pursuant to Developing 37 Honoured Ones within The Diamond World Mandala

최근에 전자상거래 분야에서는 다양한 에이전트를 시스템에 적용함으로써 전자상거래를 보다 활성 화시키려는 연구가 늘어나고 있다. 그러나 현재의 이러한 연구들은 판매자의 실제 이익보다는 구매자 의 선호도에 따른 물품을 추천하는데 있고, 가격과 이윤을 다룬 연구가 있어도 이 가격이 실제 이윤에 미치는 영향을 파악하기 어려운 문제가 있었다. 따라서 본 논문에서는 이러한 문제를 해결하기 위하여 원가 회계 이론에 기반한 원가 산정법들 중에서 고저점법, 산포도법, 학습 곡선법의 비교ᆞ분석을 통 하여 원가를 보다 정확히 산정하는 방법을 알아내고, 판매자는 이를 반영하여 입찰가를 결정함으로써 적정 이윤을 얻을 수 있도록 한다. 이를 위해 본 논문에서는 각 원가 산정법을 적용한 에이전트의 성 능 실험을 하였고, 비교적 우수한 성능을 보인 학습 곡선법을 통해서 적정 이윤을 보장하면서도 낙찰 율을 향상시킬 수 있음을 보인다.

Generating Bid Prices for Group Buying Systems Using Learning Curve

Internet group buying systems have been widely used recently. In those systems, because the reserve price is provided by the buyer, the success rate can be decreased if the reserve price is set too low compared with the normal price. Otherwise, an unsuitable successful bid can be made if the reserve price is set too high based on inaccurate information. Likewise, the seller's providing too high a bid price can deteriorate his/her own successful bid rate, whereas a successful bid with too low a price may make no profit in the sale. Therefore, pricing agents that recommend adequate prices based on the past buying and selling history data can be helpful. In this paper, we propose two kinds of agents. One suggests reserve prices to buyers based on the past buying history database of the system. The other recommends bid prices to a seller based on the past bidding history data of the company using the cost accounting theory. Through performance experiments, we show that the successful bid rate can increase by preventing buyers from making unreasonable reserve prices. Also, we show that, for the seller, the rate of successful bids with appropriate profits can increase. Using the pricing agents, we design and implement an XML-based group buying system. Because it is based on XML standards, it has advantages such as interoperability and extendibility compared with previous proprietary electronic commerce systems.

Pricing Agents for a Group Buying System

https://www.koreascience.kr:443/article/JAKO201616853628387.pdf

Research on Online Video Content Distributors in China

While the cultural contents industry plays main role in global contents market recently, the market of Buddhist cultural property contents is still in insufficient state. Specially, despite most cultural properties is Buddhist cultural property in Korea, there is a lot of difficult problems in preserving, restoring and designing its prototype as cultural property. So, this research intends to contribute to the development of Buddhist design and Buddhist culture contents by developing the Pagoda Dharani contents using the Ten-storied Stone Pagoda on the Site of Wongaksa. The first thing is designing the Pagoda Dharani using the Ten-storied Stone Pagoda on the Site of Wongaksa. Also, using the Pagoda Dharani, we design and implement the Pagoda Dharani contents on the web. In this paper, by using the proposed the Pagoda Dharani contents, the previous activation problem of the Buddhist culture contents can be resolved.

/pdf/production-and-application-of-pagoda-dharani-contents-using-3l44m574no.pdf

Production and Application of Pagoda Dharani Contents Using the Ten-storied Stone Pagoda of Wongaksa Temple Site

Internet bid systems are being widely used of late. In these systems, the seller sets the bid price. When the bid price is set too high compared with the normal price, chances of a successful bid may decrease. When it is set too low, however, based on inaccurate information, it can result in a successful bid yet one with no profit at all. To resolve this problem, an agent is proposed that automatically generates bid prices for sellers based on the similarity of the bidding parameters using past bidding information as well as on various costing methods such as the high-low point method, the scatter diagram method, and the learning curve method. Performance experiments have shown that the number of successful bids with appropriate profits can be increased using the bid pricing agent. Among the costing methods, the learning curve method has shown the best performance. The manner of designing and implementing the bid pricing agent is also discussed.

Efficient bid pricing based on costing methods for internet bid systems

Telematics services are being widely used recently. However, data sharing is restricted because data representations among telematics severs and terminals are not yet standardized. Moreover, changes of some data items can cause the modification of telematics software. To resolve the problem, we define an XML-based markup language, called tele-XML, for the standard representation of telematics data, and design a framework and related schema for the tele-XML. We also implement API libraries and program modules for the processing of tele-XML documents. By using the proposed representation and processing scheme, the previous problem can be resolved.

Design and Implementation of a Markup Language for Exchanging Telematics Data

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