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Information Journal Paper

Title

REVIEW AND ANALYSIS OF MARKET BASKETS AND THE ORDER OF GOODS IN CHAIN STORES

Pages

  161-184

Abstract

 Basket analysis is one of the most important applications in DATA MINING with a focus on buying patterns discovered through transaction data. In many stores, exchanges and sales are the only source of DATA MINING. DATA MINING is the extraction of knowledge from raw data. By mining the desired data in databases, useful information and knowledge is provided. DATA MINING is used in various applications and used as a tool for analyzing customer manager relationships. Given the importance of applying DATA MINING techniques to extract knowledge from huge volumes of sales data and the impact of this information on profitability and improvement of customer manager relationships, this article aims at the use of DATA MINING techniques to analyze the customers’ basket in one of the branches of chain stores in the city of Arak. The results show that applying DATA MINING techniques to discover items that are purchased together leads to an increase in the customer satisfaction and, in turn, store profitability. In this regard, the association algorithm is used to discover the customers’ buying pattern. Finally, certain strategies are proposed to improve the performance of shops and stores.

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  • Cite

    APA: Copy

    GHAFARI ASHTIANI, PEYMAN, & DAVOUDI, MASOUMEH. (2017). REVIEW AND ANALYSIS OF MARKET BASKETS AND THE ORDER OF GOODS IN CHAIN STORES. JOURNAL OF BUSINESS ADMINISTRATION RESEARCH, 8(16 ), 161-184. SID. https://sid.ir/paper/197140/en

    Vancouver: Copy

    GHAFARI ASHTIANI PEYMAN, DAVOUDI MASOUMEH. REVIEW AND ANALYSIS OF MARKET BASKETS AND THE ORDER OF GOODS IN CHAIN STORES. JOURNAL OF BUSINESS ADMINISTRATION RESEARCH[Internet]. 2017;8(16 ):161-184. Available from: https://sid.ir/paper/197140/en

    IEEE: Copy

    PEYMAN GHAFARI ASHTIANI, and MASOUMEH DAVOUDI, “REVIEW AND ANALYSIS OF MARKET BASKETS AND THE ORDER OF GOODS IN CHAIN STORES,” JOURNAL OF BUSINESS ADMINISTRATION RESEARCH, vol. 8, no. 16 , pp. 161–184, 2017, [Online]. Available: https://sid.ir/paper/197140/en

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