• 가정과삶의질연구
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• 제14권4호
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• pp.27-40
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• 1996

The wide range of price found in food market allows consumer reduce the cost of food purchases through comparison shopping into one more stores. Littles known however about how much can be saved by comapring price for a whole market basket of food items. This paper present evidence relating to the comparison shopping through the theories on price is dispersion and show validity constructing methods of food market basket. It is found that the savings of comparison shopping to consumers are likely to be gains in food Markets and three market basket on foods suggest in study found to be validity.

• 한국컴퓨터정보학회논문지
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• 제12권4호
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• pp.179-189
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• 2007

고객이 제품을 구매할 때에는 항시 구매패턴이 생기기 마련인데, 이러한 구매패턴을 찾아 나가는 과정을 장바구니 분석이라 부른다. 장바구니 분석은 Microsoft Association Algorithm에서는 두 가지 단계로 구성되어 있는데, 첫 번째 단계는 빈발항목집합을 찾아내는 과정이고, 두 번째 단계는 첫 번째 단계에서 찾은 빈발항목집합을 근거로 하여 이들의 중요도를 비교하는 단순한 계산과정이다. 빈발항목집합을 찾아내는 첫 번째 단계는 장바구니 분석에 있어서 핵심부분임에도 불구하고, OLAP 큐브에 적용할 때에는 추적분석이 불가능해지거나 허구의 빈발항목집합이 생성되는 등 여러 문제가 발생하게 된다. 본 연구에서는 장바구니 분석에 있어서 추적분석을 가능하게 하고 실제의 빈발항목집합만을 생성시키는 새로운 OLAP 큐브 구조의 설계법을 제안하고 있다.

• Industrial Engineering and Management Systems
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• 제13권4호
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• pp.421-431
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• 2014

The market basket data in the form of a binary user-item matrix or a binary item-user matrix can be modelled as a binary classification problem. The binary logistic regression approach tackles the binary classification problem, where principal components are predictor variables. If users or items are sparse in the training data, the binary classification problem can be considered as a cold-start problem. The binary logistic regression approach may not function appropriately if the principal components are inefficient for the cold-start problem. Assuming that the market basket data can also be considered as a special regression problem whose response is either 0 or 1, we propose three supervised learning approaches: random forest regression, random forest classification, and elastic net to tackle the cold-start problem, comparing the performance in a variety of experimental settings. The experimental results show that the proposed supervised learning approaches outperform the conventional approaches.

• Asian Journal of Business Environment
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• 제5권1호
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• pp.37-41
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• 2015

Purpose - The study was designed to explore and examine the business relationships of the owners and the employees of Market Basket to analyze the implications of their recent turbulence and decisions. This article focused on two issues - business profit and labor union - to describe the uniqueness of this case. Design, methodology, data, and approach - This article, based on its purpose, applied all three approaches of case studies that are identified and described by Stake (1995), instrumental, intrinsic, and collective, to present the core nature of the issue and to improve and gain a clear understanding of this particular phenomenon. Results - The analysis of this case clearly indicates that seemingly dichotomous concepts of profit and employee welfare are not necessarily antithetical to each other Conclusions - The instant case of Market Basket serves as a testimonial for the rejection of the basic premises of corporate profits and labor unions. This case serves as a model and a practical example for many large retailers, especially the family operated retailers, and workers throughout the world.

• Journal of Information Technology Applications and Management
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• 제9권4호
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• pp.65-78
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• 2002

We propose a new application method of the datamining technique that might help building an efficient trade strategy in the stock market, where the analysis of the huge database is essential. The proposed method utilizes the association rules among the price changes of individual stock from the market basket analysis (a datamining technique typically used in the Marketing field) in building the strategy We also apply the proposed method to the daily stock prices in Korean stock market, from Jan. 2000 to Dec. 2001. The application results show that the proposed method gives an significantly higher yield rate than the actual stock chage rate.

• 대한가정학회지
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• 제31권2호
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• pp.15-25
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• 1993

This article studied on price dispersion of food market in Kwangju. Both item and market basket price dispersion were surveyed, and this price dispersion was compared with the perceptive price dispersion. This survey was conducted from April. 8.1992 to 22. On findings, price dispersion is very big in item and market basket. Most Consumers' perception was inaccurate and typically underestimated. This findings suggest that consumers are victims of contributors to informally imperfect markets.

• 유통과학연구
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• 제21권4호
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• pp.121-129
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• 2023

Purpose: Market basket analysis is one of the most frequently used methods in the retail industry today as a technique to discover the product association. It is empirically analyzed how these product associations differ regionally in the case of the United States. Research design, data, and methodology: Based on the purchasing data of consumer panels collected from 49 US states, the association rules for each state was extracted with the corresponding lift values indicating product association. The difference in lift values in 49 states by the association rule was compared and tested for 49 states and for 4 census regions (Northeast, Midwest, South, West). Results: The association rules of 3/4 of the same association rules show positive associations or negative associations depending on the lift values of the states. There were significant differences in the lift values for 49 states, and for 4 census regions. These significant differences in the lift values were found to be related to the distance between states and whether states belong to the same census region. Conclusions: Retail product associations shown by market basket analysis may vary depending on regional distance or regional heterogeneity. It is necessary to pay attention to these points in multi-store environment.

• Journal of information and communication convergence engineering
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• 제16권1호
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• pp.52-59
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• 2018

Odoo is an enterprise resource planning information system providing modules to support the basic business function in companies. This research will look into the development of an additional module at Odoo. This module is a data mining module using Market Basket Analysis (MBA) using FP-Growth algorithm in managing OLTP of sales transaction to be useful information for users to improve the analysis of company business strategy. The FP-Growth algorithm used in the application was able to produce multidimensional association rules. The company will know more about their sales and customers' buying habits. Performing sales trend analysis will give a valuable insight into the inner-workings of the business. The testing of the module is using the data from X Supermarket. The final result of this module is generated from a data mining process in the form of association rule. The rule is presented in narrative and graphical form to be understood easier.

• Management Science and Financial Engineering
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• 제12권2호
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• pp.71-85
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• 2006

Collaborative filtering, among other recommender systems, has been known as the most successful recommendation technique. However, it requires the user-item rating data, which may not be easily available. As an alternative, some collaborative filtering algorithms have been developed recently by utilizing the market basket data in the form of the binary user-item matrix. Viewing the recommendation scheme as a two-class classification problem, we proposed a new collaborative filtering scheme using a regularized discriminant analysis applied to the binary user-item data. The proposed discriminant model was built in terms of the major principal components and was used for predicting the probability of purchasing a particular item by an active user. The proposed scheme was illustrated with two modified real data sets and its performance was compared with the existing user-based approach in terms of the recommendation precision.

• Agribusiness and Information Management
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• 제4권2호
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• pp.14-21
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• 2012

Since the Free Trade Agreements (FTAs) with Chile, the EU, and the U.S., Korean agricultural produce markets have turned into a fierce competition landscape. Under these competitive circumstances, marketing is critical. The objective of the research presented herein is to understand the characteristics of customer preferences after locating trends of purchased items. So This research establishes sustainable strategies for Korean agricultural produce. This investigation used market-basket analysis techniques and panel data for its research. Market-basket analysis is a technique which attempts to find groups of items that are commonly found together. The results show that, for one year, processed food using wheat, processed marine products, and pork are commonly bought together and that yogurt and milk also are bought together. The characteristics of customers buying these items are 44 years old and live in a four-person household with two children. These customers do not live with their parents.