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Big data analysis on the business process and management for the store layout and bundling sales

机译:有关商店布局和捆绑销售的业务流程和管理的大数据分析

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Purpose In the retailing industry, database is the time and place where a retail transaction is completed. E-business processes are increasingly adopting databases that can obtain in-depth customers and sales knowledge with the big data analysis. The specific big data analysis on a database system allows a retailer designing and implementing business process management (BPM) to maximize profits, minimize costs and satisfy customers on a business model. Thus, the research of big data analysis on the BPM in the retailing is a critical issue. The paper aims to discuss this issue. Design/methodology/approach This paper develops a database, ER model, and uses cluster analysis, C&R tree and the a priori algorithm as approaches to illustrate big data analysis/data mining results for generating business intelligence and process management, which then obtain customer knowledge from the case firm's database system. Findings Big data analysis/data mining results such as customer profiles, product/brand display classifications and product/brand sales associations can be used to propose alternatives to the case firm for store layout and bundling sales business process and management development. Originality/value This research paper is an example to develop the BPM of database model and big data/data mining based on insights from big data analysis applications for store layout and bundling sales in the retailing industry.
机译:目的在零售行业中,数据库是完成零售交易的时间和地点。电子商务流程越来越多地采用数据库,该数据库可以通过大数据分析获得深入的客户和销售知识。通过对数据库系统进行特定的大数据分析,零售商可以设计和实施业务流程管理(BPM),以实现利润最大化,成本最小化并满足客户对业务模型的需求。因此,零售业中BPM的大数据分析研究是一个关键问题。本文旨在讨论这个问题。设计/方法/方法本文开发了一个数据库,ER模型,并使用聚类分析,C&R树和先验算法作为方法来说明大数据分析/数据挖掘结果以生成业务智能和流程管理,从而获得客户知识从案例公司的数据库系统中获取。调查结果大数据分析/数据挖掘结果(例如客户资料,产品/品牌展示分类和产品/品牌销售关联)可用于为案例公司提出替代方案,以用于商店布局以及捆绑销售业务流程和管理开发。独创性/价值本研究论文是一个示例,它基于大数据分析应用程序的见解,开发了数据库模型和大数据/数据挖掘的BPM,以用于零售业中的商店布局和捆绑销售。

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