• Journal of The Korean Society of Agricultural Engineers
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• v.54 no.2
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• pp.7-14
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• 2012

To analyze any given situation, it is necessary to have information on elements which affect the situation. Particularly, there is greater variability in both frequency and magnitude of agricultural product prices as they are affected by various unpredictable factors such as weather conditions etc. This is the reason why it is difficult for the farmers to maintain their stable income through agricultural production and marketing. In this research, attempts are made to quantify the entropy of various situations inherent in the price changes so that the stability of farmers' income can be increased. Through this research, we developed an entropy model which can quantify the uncertainties of price changes using the probability distribution of price changes. The model was tested for its significance by comparing its simulation outcomes with actual ranges and standard deviations of price variations of the past using monthly agricultural product prices data. We confirmed that the simulation results reflected the features of the ranges and standard deviations of actual price variations. Also, it is possible for us to predict standard deviations for changed prices which will occur after a certain time using the information entropy obtained from relevant agricultural product price data before the time.

• Korean Journal of Organic Agriculture
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• v.21 no.2
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• pp.171-187
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• 2013

The environment-friendly agricultural product market receives consumers' great interests despite relatively few studies focused on consumers' decision making process of the environment-friendly agricultural products. This paper examines what factors influence on consumers' attitude and buying behavior on the environment-friendly agricultural product. In order to find the relative importance of each factor's influence, this study adopts multiple regression method based on the survey results of 500 people with the systematic random sampling. The results showed that consumers' favorable attitude towards the environment-friendly agricultural product were influenced by taste, freshness, food safety, and positive attitudes toward the environment-friendly agricultural product promotion. In addition, consumers' purchase intention was influenced by taste, food safety, environmental concern, and the promotion. Respondents recommend the environment-friendly agricultural product when they believe that the environment-friendly agricultural product had the values of taste, environmental concern, and promotion. Women are more active in buying and recommending the environment-friendly agricultural product; however, the price was not the statistically meaning factor. This study provides empirical data that was used for marketing and increasing the sales of the environment-friendly agricultural product. Future research was advised to examine more thoroughly on the relationships between the promotion efforts and purchase intention and the occasions when the price becomes the issue in the buying decision of the environment-friendly agricultural product.

• Journal of the Korea Society of Computer and Information
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• v.28 no.2
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• pp.201-207
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• 2023

In this paper, we propose an optimal model for mid to long-term price prediction of agricultural products using LGBM, MLP, LSTM, and GRU to compare and analyze the three strategies of the Multi-Step Time Series. The proposed model is designed to find the optimal combination between the models by selecting methods from various angles. Prior agricultural product price prediction studies have mainly adopted traditional econometric models such as ARIMA and LSTM-type models. In contrast, agricultural product price prediction studies related to Multi-Step Time Series were minimal. In this study, the experiment was conducted by dividing it into two periods according to the degree of volatility of agricultural product prices. As a result of the mid-to-long-term price prediction of three strategies, namely direct, hybrid, and multiple outputs, the hybrid approach showed relatively superior performance. This study academically and practically contributes to mid-to-long term daily price prediction by proposing an effective alternative.

• Journal of Korean Institute of Industrial Engineers
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• v.41 no.4
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• pp.359-367
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• 2015

Geographical Indication (GI) has been used with the expectation to influence customer buying behavior. In this research, we empirically investigate if such relationship exists using apple price changes in Korea along with web search traffic reflecting customers' interest in GI. The experimental results indicate that the apple price of the past, apple supply and web search traffic including GI name were significant on the prediction of price change of Chungju while web search traffic of regional name and that of product were significant for Cheongsong apples with GI. In Yeongcheon with no GI, the apple price of the past turns out to be significant only. The results indicated that interests in GI can help the price prediction but the regional name itself can play the same role, if the GI product is well known in association with the region.

• Korean Journal of Agricultural Science
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• v.32 no.1
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• pp.95-106
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• 2005

This study was focused on analyzing the impacts of e-commerce on the farmer's management behavior and suggesting alternatives for the development of e-commerce in agricultural industry. For this study, survey was conducted for 24 farmers who sell agricultural products through e-commerce in Chungnam province. The results of study are as follows; First, farmers have changed their management practices in terms of production, marketing and processing by using the information of consumers' preferences while doing e-commerce business. Second, farmers have attempted to differentiate their product through product brand and customer relationship marketing, because they recognized the importance of developing marketing techniques adapted to e-commerce system for more revenues. Third, if quality certification system of agricultural products is introduced under e-commerce, farmers would use it for their environmentally sounded farming because they expect to increase their income. Fourth, 75% of the farmers sold their product at retail price. It means that e-commerce farmers act as a price maker rather than price taker at e-commerce market, who will be encouraged to have larger business size resulting in more added value. Based on the results of study, we suggest that there should be reduction of service charge for credit card, and encouragement of B2B transaction for the economy of scale and introduction of quality certification system so as to establish e-commerce system of agricultural industry as soon as possible.

• Journal of Korean Society of Rural Planning
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• v.21 no.3
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• pp.33-45
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• 2015

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.

• Journal of Advanced Technology Convergence
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• v.3 no.2
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• pp.17-23
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• 2024

In this paper, we analyzed the impact of temperature and precipitation on agricultural product prices and predicted the prices of major agricultural products using TensorFlow. As a result of the analysis, the rise in temperature and precipitation had a significant effect on the rise in prices of cabbage, radish, green onion, lettuce, and onion. In particular, prices rose sharply when temperature and precipitation increased simultaneously. The prediction model was useful in predicting agricultural product price changes due to climate change. Through this, agricultural producers and consumers can prepare for climate change and prepare response strategies to price fluctuations. The paper can contribute to understanding the impact of climate change on agricultural product prices and exploring ways to increase the stability and sustainability of agricultural product markets. In addition, it provides important data to increase agricultural sustainability and ensure economic stability in the era of climate change. The research results will also provide useful insights to policy makers and can contribute to establishing effective agricultural policies in response to climate change.

• East Asian Journal of Business Economics (EAJBE)
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• v.8 no.3
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• pp.43-56
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• 2020

Purpose - This study was carried out to analyze the influential factors of how consumers methodize purchasing agricultural products via direct market. It further utilizes the Discrete Choice Model to analyze consumer decision specifically with regards to individual markets and store attributes. Research design and methodology - This study will use the multinomial logit model to interpret the influential factors behind selecting a specific market to purchase from. This study establishes 'online direct-purchase' as the base category with 'direct farm markets', 'local foods direct markets', 'produce boxes (CSA)' as substitutes. Results - Firstly, the variety of products, price and freshness had a positive influence on choosing 'direct farm markets' while convenience of payment and transportation had a negative influence. Second, freshness and store attributes had a positive influence on choosing 'local foods direct markets' but product price and packaging, location accessibility had a negative influence. And although product creditability had a positive influence on purchasing 'produce boxes (CSA)', product price had a negative influence. Conclusions - Accordingly, there is a need for the South Korean government to encourage the adoption of mobile payment through smartphone applications in direct farm markets to vitalize direct agricultural purchasing. However, this does need to be approached cautiously as price has a conflicting affect for each method of purchase.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.12
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• pp.3923-3942
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• 2022

Environment, price, regulation, and other factors influence the price of agricultural products, which is a social signal of product supply and demand. The price of many agricultural products fluctuates greatly due to the asymmetry between production and marketing details. Horticultural goods are particularly price sensitive because they cannot be stored for long periods of time. It is very important and helpful to forecast the price of horticultural products which is crucial in designing a cropping plan. The proposed method guides the farmers in agricultural product production and harvesting plans. Farmers can benefit from long-term forecasting since it helps them plan their planting and harvesting schedules. Customers can also profit from daily average price estimates for the short term. This paper study the time series models such as ARIMA, SARIMA, and neural network models such as BPN, LSTM and are used for wheat cost prediction in India. A large scale available data set is collected and tested. The results shows that since ARIMA and SARIMA models are well suited for small-scale, continuous, and periodic data, the BPN and LSTM provide more accurate and faster results for predicting well weekly and monthly trends of price fluctuation.

• Journal of Agricultural Extension & Community Development
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• v.30 no.1
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• pp.43-52
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• 2023

This study aims to examine the effects of GDP as a proxy variable of income, consumer price index as a proxy variable of price, and foot-and-mouth disease and avian influenza as derby variables on rural tourism demand. The independent variables in this research were gross domestic product(GDP), consumer price index(CPI), and dummy variable(DM) such as food & mouth disease & highly pathogenic avian influenza. Results showed that GDP affected tourism demand positively whereas DM influenced negatively. The study suggested that it was important for policy-mconsider GDP and DM when making decision on strategic tourism management. In conclusion, first, gross domestic product was found to have a statistically significant effect on rural tourism demand. Second, avian influenza was found to have a statistically negative effect on rural tourism demand. The results of this study can be used to establish a reasonable rural tourism policy in the future economic dimension.