• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.15 no.3
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• pp.33-46
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• 2020

This study analyzes the entrepreneurship education phenomena for agri-food entrepreneurs whose main business is the production of agricultural products and the sale of processed products, using the qualitative study Strauss & Corbin(1998)'s evidence theory approach. From the entrepreneur's point of view, I would like to summarize the phenomena that appear in education, and to prepare a theoretical basis for explaining the phenomena. The importance of entrepreneurship education is emphasized to cultivate the ability to develop and provide products tailored to customers. The necessity of education leads to an increase in demand according to the situational awareness of the founders, and the quantitative increase in entrepreneurship education in the agri-food sector is a clear trend. Inevitably, the need for various discussions on systematic and effective entrepreneurship education is raised. For the study, an interview was conducted with preliminary or entrepreneur who have experienced entrepreneurship education in the agri-food sector. As a research method, I use Strauss & Corbin(1998)'s approach and analyze qualitative data using QSR's NVIVO 12 program. Through this study, it was found that contextual and systematic entrepreneurship education in the agri-food sector has the effect of strengthening competitiveness and strengthening sales. There is a need for follow-up management of trainees. Strengthening the competitiveness of start-ups is based on training professional manpower through education and linking regions with cities. Strengthening sales is based on product planning and market development. This study explores entrepreneurship education in the agri-food sector, which has not been actively conducted in the past. Exploratory analysis on the experiences of the founders of agri-food sector as education demanders has an important meaning for understanding the phenomenon of start-up education.

• Food Science of Animal Resources
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• v.27 no.1
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• pp.122-126
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• 2007

Expenditure on meat and meat products has been increased in Korea due to the increase of income and the change of diet. From raising farm animals to eating the meat, various hazardous elements can make their ways into the meat and meat products. Recently the issues on food safety and hygiene are drawing a lot of attention, and the current system for managing the safety of foods is still needed to be improved. This survey was aimed to monitor the current situation of country-of-origin labels and hygiene for the meat markets at 4 regions Korea. The survey was performed by collecting samples from whole- sale and retail stores in the nation, which were selling beef. The markets were divided into groups as to territory and the size of the market (Large size, Medium size, and Small size). In terms of size distribution, small butcher shops occupied the highest percentage. On the itemized suitability test of unpacked and packed beef, all the market of 4 regions showed good agreements. However, such labels indicating the methods of cooking and storage were not properly posted on the products. Especially for Ho-nam region, corrections are needed. The results of monitoring sanitation conditions for the butcher shops at 4 regions in Korea showed relatively low suitability. Especially, there were serious lack of knowledge about wearing the sanitation clothing, caps, and shoes. The problem with food safety is so complicated that producer, consumer, food manufacturer, the press, the government, and scholar should solve altogether. It is necessary to educate farmers, food handlers, consumers, etc. and provide them with an accurate information and knowledge.

• Journal of Intelligence and Information Systems
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• v.23 no.4
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• pp.111-126
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• 2017

Recommender systems based on association rule mining significantly contribute to seller's sales by reducing consumers' time to search for products that they want. Recommendations based on the frequency of transactions such as orders can effectively screen out the products that are statistically marketable among multiple products. A product with a high possibility of sales, however, can be omitted from the recommendation if it records insufficient number of transactions at the beginning of the sale. Products missing from the associated recommendations may lose the chance of exposure to consumers, which leads to a decline in the number of transactions. In turn, diminished transactions may create a vicious circle of lost opportunity to be recommended. Thus, initial sales are likely to remain stagnant for a certain period of time. Products that are susceptible to fashion or seasonality, such as clothing, may be greatly affected. This study was aimed at expanding association rules to include into the list of recommendations those products whose initial trading frequency of transactions is low despite the possibility of high sales. The particular purpose is to predict the strength of the direct connection of two unconnected items through the properties of the paths located between them. An association between two items revealed in transactions can be interpreted as the interaction between them, which can be expressed as a link in a social network whose nodes are items. The first step calculates the centralities of the nodes in the middle of the paths that indirectly connect the two nodes without direct connection. The next step identifies the number of the paths and the shortest among them. These extracts are used as independent variables in the regression analysis to predict future connection strength between the nodes. The strength of the connection between the two nodes of the model, which is defined by the number of nodes between the two nodes, is measured after a certain period of time. The regression analysis results confirm that the number of paths between the two products, the distance of the shortest path, and the number of neighboring items connected to the products are significantly related to their potential strength. This study used actual order transaction data collected for three months from February to April in 2016 from an online commerce company. To reduce the complexity of analytics as the scale of the network grows, the analysis was performed only on miscellaneous goods. Two consecutively purchased items were chosen from each customer's transactions to obtain a pair of antecedent and consequent, which secures a link needed for constituting a social network. The direction of the link was determined in the order in which the goods were purchased. Except for the last ten days of the data collection period, the social network of associated items was built for the extraction of independent variables. The model predicts the number of links to be connected in the next ten days from the explanatory variables. Of the 5,711 previously unconnected links, 611 were newly connected for the last ten days. Through experiments, the proposed model demonstrated excellent predictions. Of the 571 links that the proposed model predicts, 269 were confirmed to have been connected. This is 4.4 times more than the average of 61, which can be found without any prediction model. This study is expected to be useful regarding industries whose new products launch quickly with short life cycles, since their exposure time is critical. Also, it can be used to detect diseases that are rarely found in the early stages of medical treatment because of the low incidence of outbreaks. Since the complexity of the social networking analysis is sensitive to the number of nodes and links that make up the network, this study was conducted in a particular category of miscellaneous goods. Future research should consider that this condition may limit the opportunity to detect unexpected associations between products belonging to different categories of classification.