Big Data Assisted Empirical Study for Business Value Identification Using Smart Technologies

Author:

Zhang Chang1,Liu Bin2,Mohammed Badamasi Sani3ORCID,Jumani Awais Khan4

Affiliation:

1. Northwest University, China

2. Xianyang Bureau of Industry and Information Technology, China

3. Al-Qalam University Katsina, Nigeria

4. ILMA university, Pakistan

Abstract

The main problem for the big data for an e-commerce site is getting a meaningful data analysis, which the big descriptive statistics consider the most crucial usage. The collection, segmentation, and analysis of customer insights are critical to developing an effective and precise tailored experience for each consumer. Analyzing and segmentation of customer insights are essential to creating an effective and personalized experience for each customer. Using price optimization (BDA-PO), big data analytics has been proposed, enabling enterprising services like tourism, shopping, transportation, and creative industries to provide variable rates for products and services using Smart Technologies for E-Business and Commerce. Price optimizing can be automated with machine learning algorithms to enhance profitability when pricing decisions are taken effectively. When pricing decisions are made correctly, it is possible to automate price optimization using machine learning algorithms.

Publisher

IGI Global

Subject

Computer Networks and Communications,Computer Science Applications

Cited by 1 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Machine learning applied to tourism: A systematic review;WIREs Data Mining and Knowledge Discovery;2024-07-04

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