E-Commerce for Future & Trends
Volume 10, Issue 2 (2023)
Published
Table of contents
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Statistical Analysis of Influence of AI and Information Technology on Supply Chain Management of Indian Automobile Industries
Abstract: The main objective of this paper is to access effect of E-Business processes and Artificial Intelligence (AI) on Supply Chain Management (SCMG) on Indian Automotive Industries (IAIN). AI comes with revolution in all Information Technology related processes. Implementation of E-Business Processes with AI (EBPAI) will lead to a drastic improvement in management of supply chain which will improve Supply Chain Performance (SCP) as well as customer satisfaction. Since from last …
Published in E-Commerce for Future & Trends · Vol. 10, Issue 2, 2023 · pp. 1–7 Read article
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Analyzing Potential Leads Data to Improve Marketing Strategies
Abstract: To develop a lead scoring model using multiple machine learning models and create a user-friendly web application, the first step is to clearly define the problem and collect relevant data from various sources such as CRM, website, social media, email campaigns, etc. After cleaning and pre-processing the data, identify the essential features that can affect the lead score and split the data into training and testing sets. Next, select a …
Published in E-Commerce for Future & Trends · Vol. 10, Issue 2, 2023 · pp. 18–25 Read article
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Impact of ML in Evolution of Recommender Systems: A Review
Abstract: Recommender systems have become indispensable tools in today's digital era, catering to the overwhelming demand for personalized recommendations in various domains such as e-commerce, content streaming, and social media. The continuous growth of data and user interactions has necessitated the integration of advanced machine learning (ML) techniques to enhance the accuracy and efficiency of these systems. This study provides a thorough analysis of current developments in machine learning methods used …
Published in E-Commerce for Future & Trends · Vol. 10, Issue 2, 2023 · pp. 26–32 Read article
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Stock Price Prediction Using Data Science Techniques
Abstract: This study centers around persuasively presenting the potential to forecast the stability of future market stocks. Previous research has delved into predicting the trajectory of future market trends, leading to fluctuations in stock data, which opens avenues for refinement. The proposed model employs data science methodologies to predict the stock price index's value. This is achieved by contrasting supervised classification data science learning algorithms that predict either stock price increases …
Published in E-Commerce for Future & Trends · Vol. 10, Issue 2, 2023 · pp. 33–41 Read article
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Stock Trading Algorithm with Technical Indicators Using Python for Indian Stocks
Abstract: In the financial markets, algorithmic trading has become a potent instrument that enables traders to automate their tactics and profit from market inefficiencies. In this paper, we describe a Python-based algorithmic trading model that makes use of technical indicators and evaluate its performance in comparison to the well-known buy-and-hold approach. By analysing historical price data, these indicators provide insights into the market trends and potential entry or exit points for …
Published in E-Commerce for Future & Trends · Vol. 10, Issue 2, 2023 · pp. 8–17 Read article