The Act on Distribution and Price Stabilization of Agricultural and Fisheries Product, which specifies rules and regulations on the trading system of fishery products wholesales markets, has been revised several times, mainly in order to improve the trading system. However, there is still a huge gap between the reality and law when it comes to the trading system of the fishery products wholesale market. This study aims to analyze the problems of the trading system of the fishery products wholesale market and to suggest ways to make improvement. The main problem facing the trading system of the fishery products wholesale market is sales on consignment by intermediate wholesalers, and this paper suggests two alternatives to solve the problem. First, intermediate wholesaler can be converted to market wholesalers, but it also entails other problems. The market wholesaler system has never been successfully adopted in the agricultural and fishery products wholesale market, and it is not clear which system is better between the wholesale market corporation and the market wholesaler system. Second, sales on consignment by intermediate wholesalers can be adopted with a positive view toward it. Negotiation transaction can be carried out for sales on consignment as a transaction method under the current Act on Distribution and Price Stabilization of Agricultural and Fisheries Products. However, since the act cannot provide a solution for listing, it is necessary to introduce Japan's negotiated transaction in advance system as a negotiation transaction method.
This study is on the method of direct transaction with farmers, a farmers' group and consumers through internet. Approximately the method in this study could be divided into 4 sections: 1) full information display about agricultural products of farmers, farmers' group, 2) consumers' choice about the best stuff, 3) direct transaction system by using tele-banking and 4) a delivery system in conveying method or an interview type electronic commerce system that carry out the direct visit These methods are to make the merits of the existing traditional type commerce system's to be maximized to make bull use of electronic commerce system.
Switching to organic farming practices in agricultural production reaches the end of the period it takes an average of five years. During this period, agricultural soil management to improve the investment must be sustained. Results of the survey of environment-friendly agricultural lease rates appear to approximately 54.2% lower than agricultural practices. Environmentally friendly agricultural land is leased on a long transition period of the contract cost, many buried incompleteness, uncertainty of contract fulfillment(opportunistic behavior) occurs when the transaction costs. This ultimately can hinder the spread of organic farming. Thus, the qualitative development of organic farming and land leasing in order to minimize transaction costs, should that occur. The alternative 'cooperative long-term lease contract' is a system.
Journal of Korean Society of Industrial and Systems Engineering
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v.21
no.48
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pp.263-268
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1998
An efficient agricultural marketing system is very important to producers and consumers to keep the reasonable prices. In these days, the main policy for the efficient agricultural marketing system is to enlarge the direct transaction market. But it is not easy to enlarge the direct transaction market in a few years. This paper proposes a new efficient agricultural marketing system that gives a similar effect with the direct market. The proposed system is mainly composed of three associations; producers', consumers' and retailers'association, and the function of the system is devided into material affairs and commercial affairs. The structure of the system also can be simplified as two to three steps. So the system can reduce the cost of logistics and keep the reasonable prices for both producers and consumers.
With the rapid evolution of technology, the size, number, and the type of databases has increased concomitantly, so data mining approaches face many challenging applications from databases. One such application is discovery of fraud patterns from agricultural product wholesale transaction instances. The agricultural product wholesale market in Korea is huge, and vast numbers of transactions have been made every day. The demand for agricultural products continues to grow, and the use of electronic auction systems raises the efficiency of operations of wholesale market. Certainly, the number of unusual transactions is also assumed to be increased in proportion to the trading amount, where an unusual transaction is often the first sign of fraud. However, it is very difficult to identify and detect these transactions and the corresponding fraud occurred in agricultural product wholesale market because the types of fraud are more intelligent than ever before. The fraud can be detected by verifying the overall transaction records manually, but it requires significant amount of human resources, and ultimately is not a practical approach. Frauds also can be revealed by victim's report or complaint. But there are usually no victims in the agricultural product wholesale frauds because they are committed by collusion of an auction company and an intermediary wholesaler. Nevertheless, it is required to monitor transaction records continuously and to make an effort to prevent any fraud, because the fraud not only disturbs the fair trade order of the market but also reduces the credibility of the market rapidly. Applying data mining to such an environment is very useful since it can discover unknown fraud patterns or features from a large volume of transaction data properly. The objective of this research is to empirically investigate the factors necessary to detect fraud transactions in an agricultural product wholesale market by developing a data mining based fraud detection model. One of major frauds is the phantom transaction, which is a colluding transaction by the seller(auction company or forwarder) and buyer(intermediary wholesaler) to commit the fraud transaction. They pretend to fulfill the transaction by recording false data in the online transaction processing system without actually selling products, and the seller receives money from the buyer. This leads to the overstatement of sales performance and illegal money transfers, which reduces the credibility of market. This paper reviews the environment of wholesale market such as types of transactions, roles of participants of the market, and various types and characteristics of frauds, and introduces the whole process of developing the phantom transaction detection model. The process consists of the following 4 modules: (1) Data cleaning and standardization (2) Statistical data analysis such as distribution and correlation analysis, (3) Construction of classification model using decision-tree induction approach, (4) Verification of the model in terms of hit ratio. We collected real data from 6 associations of agricultural producers in metropolitan markets. Final model with a decision-tree induction approach revealed that monthly average trading price of item offered by forwarders is a key variable in detecting the phantom transaction. The verification procedure also confirmed the suitability of the results. However, even though the performance of the results of this research is satisfactory, sensitive issues are still remained for improving classification accuracy and conciseness of rules. One such issue is the robustness of data mining model. Data mining is very much data-oriented, so data mining models tend to be very sensitive to changes of data or situations. Thus, it is evident that this non-robustness of data mining model requires continuous remodeling as data or situation changes. We hope that this paper suggest valuable guideline to organizations and companies that consider introducing or constructing a fraud detection model in the future.
To support business decision making, interests and efforts to analyze and use transaction data in different perspectives are increasing. Such efforts are not only limited to customer management or marketing, but also used for monitoring and detecting fraud transactions. Fraud transactions are evolving into various patterns by taking advantage of information technology. To reflect the evolution of fraud transactions, there are many efforts on fraud detection methods and advanced application systems in order to improve the accuracy and ease of fraud detection. As a case of fraud detection, this study aims to provide effective fraud detection methods for auction exception agricultural products in the largest Korean agricultural wholesale market. Auction exception products policy exists to complement auction-based trades in agricultural wholesale market. That is, most trades on agricultural products are performed by auction; however, specific products are assigned as auction exception products when total volumes of products are relatively small, the number of wholesalers is small, or there are difficulties for wholesalers to purchase the products. However, auction exception products policy makes several problems on fairness and transparency of transaction, which requires help of fraud detection. In this study, to generate fraud detection rules, real huge agricultural products trade transaction data from 2008 to 2010 in the market are analyzed, which increase more than 1 million transactions and 1 billion US dollar in transaction volume. Agricultural transaction data has unique characteristics such as frequent changes in supply volumes and turbulent time-dependent changes in price. Since this was the first trial to identify fraud transactions in this domain, there was no training data set for supervised learning. So, fraud detection rules are generated using outlier detection approach. We assume that outlier transactions have more possibility of fraud transactions than normal transactions. The outlier transactions are identified to compare daily average unit price, weekly average unit price, and quarterly average unit price of product items. Also quarterly averages unit price of product items of the specific wholesalers are used to identify outlier transactions. The reliability of generated fraud detection rules are confirmed by domain experts. To determine whether a transaction is fraudulent or not, normal distribution and normalized Z-value concept are applied. That is, a unit price of a transaction is transformed to Z-value to calculate the occurrence probability when we approximate the distribution of unit prices to normal distribution. The modified Z-value of the unit price in the transaction is used rather than using the original Z-value of it. The reason is that in the case of auction exception agricultural products, Z-values are influenced by outlier fraud transactions themselves because the number of wholesalers is small. The modified Z-values are called Self-Eliminated Z-scores because they are calculated excluding the unit price of the specific transaction which is subject to check whether it is fraud transaction or not. To show the usefulness of the proposed approach, a prototype of fraud transaction detection system is developed using Delphi. The system consists of five main menus and related submenus. First functionalities of the system is to import transaction databases. Next important functions are to set up fraud detection parameters. By changing fraud detection parameters, system users can control the number of potential fraud transactions. Execution functions provide fraud detection results which are found based on fraud detection parameters. The potential fraud transactions can be viewed on screen or exported as files. The study is an initial trial to identify fraud transactions in Auction Exception Agricultural Products. There are still many remained research topics of the issue. First, the scope of analysis data was limited due to the availability of data. It is necessary to include more data on transactions, wholesalers, and producers to detect fraud transactions more accurately. Next, we need to extend the scope of fraud transaction detection to fishery products. Also there are many possibilities to apply different data mining techniques for fraud detection. For example, time series approach is a potential technique to apply the problem. Even though outlier transactions are detected based on unit prices of transactions, however it is possible to derive fraud detection rules based on transaction volumes.
The oversea export of agricultural-product about item and quantity has not increased recently; especially the fresh-product has a tough issue because of period of production, price large fluctuations, customs clearance, quarantine, and uncertainty about actual locality, we need the information based construction to exchange information quickly about whole range of export and to focus capacity of participation subject for increasing the export. In this study we design the agricultural-product transaction information system based on crowdsourcing to transact the agricultural-product and the information of influencing benefit directly, and the information offering about export-procedure from participation of customs clearance, finance, distribution, buyer, and producer's guild, etc. We expect the producer's guild about agriculture that has not participate the trade to be able to export the agricultural-product and the stabilization of price to transact the product of collapsed or boomed through the agricultural-product information system based on crowdsourcing.
KSII Transactions on Internet and Information Systems (TIIS)
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v.13
no.8
/
pp.4212-4226
/
2019
In this paper, a design and implementation for direct deal distribution platform is proposed to bypass the complex traditional distribution structure of agricultural market, as one of the fields where distribution patterns have changed. In the case of domestic agricultural distribution, demand and supply are unstable since the sales market is excessively concentrated in the designated wholesale market. Besides sales must go through multiple stages of distribution leading to problems in freshness and stability of agricultural products and downward pressure on profit margins for producers. To solve the above mentioned issues, we propose a cloud service convergence direct deal distribution platform based on asynchronous-driven Node.js. The proposed platform can facilitate a variety of direct trading functions and also access to visualization information related to agricultural products, which may increase user confidence at an intermediary-free direct transactions platform. First, we describe the requirements of intermediary-free direct transactions of agricultural products and transaction entities. Next the database structure and transaction functions are designed and then implemented according to those requirements. Finally, an API based cloud convergence service structure is designed to provide the analyzed information to ensure a trustworthy system.
The objective of this study is to investigate the determinants of trust between the producer and the distributor, focusing on relational norms (mutuality, flexibility, and solidarity) and environmental munificence, in agricultural marketing channels. More specifically, followings are investigated in cucumber marketing channels ; (a) the effects of environmental munificence on relational norms, and (b) tile effects of relational norms on trust. The major findings of this study are as follows ; (1) The cucumber producers' perceived output sector munificience positively affected the mutuality and solidarity of the relational norms. (2) The mutuality and solidarity of the relational norms positively affected the trust. Therefore, the efficient marketing transaction system, mutual efforts for a fair regard between producers and middlemen, and the development of sound moral and trading custom are required in the Korean agricultural market. And also the active roles of government to develop the infrastructure of agricultural marketing and the proper roles of agricultural cooperatives to keep transaction activity fair should be clarified and proactively conducted.
Journal of agricultural medicine and community health
/
v.49
no.1
/
pp.59-70
/
2024
Objectives: This research analyzed and compared housing transaction prices and depression rates according to housing types before and after the COVID-19 pandemic. Methods: Data on housing transaction prices and depression rates from 2018 to 2022 in 25 districts of Seoul, South Korea, were utilized. Dummy variables were employed to account for potential confounders influencing the relationship between the variables. Statistical analysis was conducted using R, and the relationship between depression rates and housing transaction prices was examined through Ordinary Least Squares (OLS) and panel data regression analysis. Results: The results of OLS and one-way random effects models indicated a significant relationship between apartment (p<.05) and officetel (p<.001) transaction prices and depression. However, detached/semi-detached and row/townhouse transaction prices did not exhibit a significant relationship with depression. Conclusion: It was observed that as apartment and officetel transaction prices increased in Seoul before and after the COVID-19 pandemic, depression rates also increased. Considering that changes in housing prices by housing type in South Korea may impact the mental health of local residents, it is deemed necessary to consider healthy housing and housing prices as comprehensive determinants of mental health.
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