Transforming Business Sustainability: Spherical Model Innovation for Client Engagement and Growth

Shereen; Mahmoud; Heba R.

doi:https://doi.org/10.54216/JSDGT.020102

International Journal of Neutrosophic Science | 2023

Neutrosophic Pre-compactness

The purpose of this article is to study some covering properties in neutrosophic topological spaces via neutrosophic pre-open sets. We define neutrosophic pre-open cover, neutrosophic pre-compactness, neutrosophic countably pre-compactness and neutrosophic pre-Lindel¨ofness and study various properties connecting them. We study some properties involving neutrosophic continuous and neutrosophic pre-continuous functions. We also define neutrosophic pre-base, neutrosophic pre-subbase, neutrosophic pre&lowast;-open function, neutrosophic pre-irresolute function and study some properties. In addition to that, we define and study neutrosophic local pre-compactness.

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Sudeep Dey mail -

Gautam Chandra Ray mail

link https://doi.org/10.54216/IJNS.210110

Volume & Issue

Vol. Volume 21 / Iss. Issue 1

Details open_in_new

International Journal of Neutrosophic Science | 2023

Neutrosophic hesitant fuzzy UP (BCC)-filters

In this paper, we introduce the concept of neutrosophic hesitant fuzzy UP (BCC)-filters of UP (BCC)-algebras. The characteristic neutrosophic hesitant fuzzy UP (BCC)-filters have also been studied. The relationship between neutrosophic hesitant fuzzy UP (BCC)-filters and their level subsets is provided. The Cartesian product of neutrosophic hesitant fuzzy UP (BCC)-filters is also supplied. Finally, we also find the property of the homomorphic pre-image of neutrosophic hesitant fuzzy UP (BCC)-filters.

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Aiyared Iampan mail -

S. Yamunadevi mail -

P. Maragatha Meenakshi mail -

N. Rajesh mail

link https://doi.org/10.54216/IJNS.210111

Volume & Issue

Vol. Volume 21 / Iss. Issue 1

Details open_in_new

International Journal of Neutrosophic Science | 2023

On Some Novel Results About Weak Fuzzy Complex Matrices

The objective of this paper is to study the algebraic properties of weak fuzzy complex matrices, where many elementary properties will be obtained such as the invertibility, the determinants, and the eigen values and vectors. In addition, a full solution of linear systems of weak fuzzy complex equations will be provided as an effective and easy algorithm. Also, many examples to clarify the validity of our approach.

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Yaser Ahmad Alhasan mail -

Abuobida Mohammed A. Alfahal mail -

Raja Abdullah Abdulfatah mail -

Giorgio Nordo mail -

Musaddak M. Abdul Zahra mail

link https://doi.org/10.54216/IJNS.210112

Volume & Issue

Vol. Volume 21 / Iss. Issue 1

Details open_in_new

International Journal of Advances in Applied Computational Intelligence | 2022

An Attentive Convolutional Recurrent Network for Fake News Detection

With the rapid growth of social media and online news platforms, the spread of fake news has become a major problem, leading to misinformation and distrust. In this paper, we propose an attentive convolutional recurrent network (ACRN) for fake news detection, which combines convolutional learning and recurrent learning capabilities to capture both local and global temporal information. Additionally, we incorporate attention mechanisms to focus on important features and reduce noise. We evaluate our model on a publicly available dataset and compare it with state-of-the-art methods. The results show that our ACRN model outperforms the existing methods in terms of accuracy, precision, recall, and F1-score. We also perform an ablation study to demonstrate the effectiveness of our attention mechanisms. Our proposed ACRN model can applied as a reliable computation intelligence tool for detecting fake news and improving the accuracy of news verification.

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Ahmed Sleem mail -

Ibrahim Elhenawy mail

link https://doi.org/10.54216/IJAACI.020101

Volume & Issue

Vol. Volume 2 / Iss. Issue 1

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American Journal of Business and Operations Research | 2021

Applying Big Data Analytics to Retail for Improved Supply Chain Visibility

Retail supply chains generate huge volumes of data that can provide valuable insights if analyzed effectively. This paper explores how retailers can leverage Big Data analytics techniques on supply chain data to gain enhanced visibility into their operations. We examine three use cases of data-driven supply chain visibility: (1) predictive replenishment to anticipate future demand and optimize inventory levels; (2) personalized assortment optimization to tailor product selections for local customer segments; and (3) optimized order fulfillment to improve delivery times and reduce transportation costs. We analyze how retailers can apply machine learning algorithms and statistical analysis on point-of-sale data, inventory data, customer data and external data sources to uncover hidden patterns and drive data-driven decisions in these areas. The results include reduced excess inventory, fewer stock-outs, higher in-store product availability, lower fulfillment costs and improved customer experience. Data-driven supply chain visibility allows retailers to transition from a reactive, speculative business model to a predictive, personalized model that enhances competitiveness.

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Alshaimaa A. Tantawy mail -

Zenat Ahmed mail -

Mahmoud M. Ali mail

link https://doi.org/10.54216/AJBOR.040104

Volume & Issue

Vol. Volume 4 / Iss. Issue 1

Details open_in_new

American Journal of Business and Operations Research | 2020

An Intelligent Approach for Demand Forecasting in E-commerce

With the growth of e-commerce, accurate demand forecasting has become a critical aspect of successful business operations. Traditional demand forecasting techniques such as time-series analysis, moving averages, and exponential smoothing have been used for years, but they have limitations in capturing the complex and dynamic nature of e-commerce demand. In this paper, we explore innovative approaches to demand forecasting in e-commerce. Specifically, we discuss the use of tree-based Machine Learning (ML) techniques as well as advanced statistical models such as Bayesian networks and hierarchical models. We provide a case study of successful implementations of innovative demand forecasting techniques in e-commerce companies. The  results show that our approach can significantly improve inventory management and logistics strategies, leading to increased profitability and customer satisfaction.

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Samah I. Abdel Aal mail

link https://doi.org/10.54216/AJBOR.010203

Volume & Issue

Vol. Volume 1 / Iss. Issue 2

Details open_in_new

American Journal of Business and Operations Research | 2021

Enhancement Operations Management in Supply Chain based on Intelligent Support Techniques: A Case study.

The onset of the information technology revolution, economic globalization, and high customer expectations have all contributed to significant developments in businesses supply chain management (SCM). Due to the plethora of data generated throughout the entire supply chain has transformed how SCM analysis is conducted. Also, Retailers, in particular face the challenge of managing SC effectively to meet customer demands while reducing costs. Herein, we suggest an approach to optimize SCM using retail analysis techniques. As one of the most well-known artificial intelligences (AI) approaches and machine learning (ML) applications in SCM are the main goals of this study. By constructing conceptual framework, data analytics, ML, and optimization techniques are integrated to generate Intelligent Support Techniques (ISTs) for analyzing SC data and identify opportunities for improvement. We apply retail analysis techniques such as demand forecasting, inventory management, and assortment planning to optimize supply chain operations. The efficiency of our ISTs verified through employing it in a real-world case study of a large retail chain. Our results show that the suggested ISTs can lead to significant improvements in supply chain performance, including increased sales, reduced inventory costs, and improved customer satisfaction.

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Mona Mohamed mail

link https://doi.org/10.54216/AJBOR.020201

Volume & Issue

Vol. Volume 2 / Iss. Issue 2

Details open_in_new

American Journal of Business and Operations Research | 2021

Optimizing Supply Chain Management with Retail Analysis Technique

The success of any business organization depends on efficient supply chain management (SCM) that ensures the timely delivery of products to customers. The retail analysis technique (RAT) has emerged as a powerful tool for optimizing SCM by enabling companies to identify and analyze sales trends, inventory levels, and customer demand patterns. This paper explores the use of retail analysis techniques in SCM and how they can be leveraged to enhance the efficiency and effectiveness of supply chain operations.  We then present a unified RAT framework that integrates data mining, predictive analytics, and machine learning for optimizing SCM. Additionally, the paper presents a case study of a company that has successfully implemented retail analysis techniques in its SCM practices. The case study highlights the specific strategies and tactics that the company used to optimize its supply chain operations and achieve significant improvements in efficiency and performance. Our analysis shows that RAT is an effective technique for optimizing SCM, and companies that implement it can gain a competitive advantage in the marketplace.

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Shereen Zaki mail -

Mahmoud M. Ismail mail -

Mahmoud M. Ibrahim mail

link https://doi.org/10.54216/AJBOR.020202

Volume & Issue

Vol. Volume 2 / Iss. Issue 2

Details open_in_new

American Journal of Business and Operations Research | 2021

Transforming E-commerce Operations: An Intelligent Business Intelligence Approach for Improving Customer Transaction Management

 In the fast-paced world of e-commerce, understanding customer behavior is essential for success. Business intelligence (BI) tools provide valuable insights into customer transactions and can be used to model and predict customer behavior. This paper explores the use of BI techniques for modeling customer transaction behavior in e-commerce. We discuss the various types of BI tools available and their use in analyzing customer data. We then outline a framework for using BI to develop a customer transaction behavior model, including data collection, preprocessing, feature selection, and model selection. Finally, we present a case study in which we apply this framework to a real-world e-commerce dataset and demonstrate the effectiveness of our approach in predicting customer behavior. Our results show that BI techniques can be an effective tool for modeling customer behavior in e-commerce, providing valuable insights for businesses looking to optimize their operations and increase customer satisfaction.

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Abdullah Ali Salamai mail

link https://doi.org/10.54216/AJBOR.020203

Volume & Issue

Vol. Volume 2 / Iss. Issue 2

Details open_in_new

Journal of Sustainable Development and Green Technology | 2023

Transforming Business Sustainability: Spherical Model Innovation for Client Engagement and Growth

The shift towards a more sustainable economy has led consumer-facing companies to set ambitious Spherical economy objectives. However, there is a lack of understanding of the innovation activities taking place within these organizations to achieve these goals, specifically in the context of waste management strategies. This study aims to fill this gap by investigating the crucial tasks performed by Spherical Business Model Innovation (SBMI) innovators in companies with a consumer focus. Using a dynamic capabilities perspective, we examine the innovative actions in line with the SBMI phases of visioning, perception, seizing, and transforming. The research inquiry is focused on identifying the procedures and resources that aid businesses in developing flexible skills throughout the SBMI process. We conduct in-depth interviews with target respondents in three businesses and use thematic analysis to map the data to the four SBMI phases. Our findings supplement the existing literature on SBMI innovation efforts and provide additional guidance for corporate operators seeking to transform their businesses sustainably through the adoption of SBMI practices.

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Shereen Zaki mail -

Mahmoud Ismail mail -

Heba R. Abdelhady mail

link https://doi.org/10.54216/JSDGT.020102

Volume & Issue

Vol. Volume 2 / Iss. Issue 1

Details open_in_new