Smart Logistics (SL) offers a competitive advantage for e-commerce by utilizing Information and Communication Technologies (ICT) such as IoT, AI, Blockchain, Cloud computing, 5G, etc. This technology automates, optimizes, and enables real-time tracking and monitoring of shipments, predicts, and prevents delays, and optimizes delivery routes and schedules. It also provides greater visibility and control, allowing e-commerce businesses to react quickly and efficiently to changes in demand or supply. The purpose of this study is to investigate the impact of digitalization on trade logistics in e-commerce, emphasizing the significance of smart logistics for the e-commerce industry. We reviewed 288 articles published in the last decade in the Scopus database to assess the maturity of research in this area. For researchers, this study provides a better understanding of smart e-commerce logistics and identifies research gaps in the literature. For e-commerce professionals, it can help them adopt the latest technological trends in their logistics. Through a systematic literature review and network analysis approach, the study has contributed by identifying 5 clusters related to ICT application fields in e-commerce and 5 clusters related to important ICT enablers in smart logistics. We also identified several research gaps and areas for future study, including the underutilization of computer vision technology and the need for further research on product quality inspection and accessibility for people with disabilities. Additionally, we suggest exploring the power of deep learning to solve Vehicle Routing Problems (VRP) and optimizing sensing data volume for minimizing costs associated with data storage and transfer. This study provides a comprehensive overview of the state of the art in smart logistics for e-commerce and serves as a guide for future research in this field.

With growing evidence of advanced technologies-assisted smart processes, it is fundamental to comprehend whether manufacturing systems are adequate to manage flexibility and complexity to enhance the monitoring of smart factories. Smart manufacturing (SM) is evolving as a new version of traditional manufacturing, revealing the magnitude and power of smart technologies such as Artificial Intelligence (AI) and the Internet of Things (IoT). The wide applicability of these technologies is allowing important innovations across all industries. As the manufacturing industry has gained benefits, the current boosts of Smart Manufacturing are experiencing exceptional levels of interest. However, providing suitable SM systems and identifying the priority of requirements may vary according to different scenarios. To this end, this study presents a systematic survey of the current SM research trends. Furthermore, this paper aims to present a consistent and comprehensive vision of existing efforts in smart manufacturing and discussed the remaining open issues.

Optimization of order dispatch operations and delivery time prediction is a major concern in supply chains, mainly for e-commerce, which requires the implementation of advanced solutions to reduce delivery time, minimize costs and maximize customer satisfaction. In practice, they fail to warrant scalable and sustainable solutions as the numbers of orders become larger. For that, proper prediction and optimization for delivery operations are required for optimal logistics management. This paper presents an advanced logistics service, which warrants dynamic coordination among all the actors in the smart logistics environment. The proposed advanced shipping system consists of two main parts: the delivery prediction model to compute the expected arrival time, and a hybrid optimization model to tackle path issues. We demonstrate that the advanced system consistently outperforms conventional standard dispatching methods, which means that the proposed approach effectively contributes to optimizing the distribution chain and reducing costs.

The finance sector is one of those that have had a dramatic change after the integration of technology and more so Artificial Intelligence, Big Data, Text Mining and Cloud computing which has also given way to the development of e-finance where electronic channels together with digital technologies are used to deliver financial services. E-finance takes advantage of these new technologies to provide easy, efficient, and innovative financial services to people. This makes it possible for DFI to reduce expenses, make data-informed decisions and improve their experience for clients but also opens access to financial services for people in emerging markets. Advances need to ensure data protection and secrecy for the well and confidence in financial industry as well: research will scrutinize effects due technological progress on AI plus Big Data, Text Mining or Cloud Computing within Finance. This paper attempts a comprehensive review of literature through scholarly articles and papers published over the past thirteen years (2013–2025) available through Google Scholar and SCOPUS. The research methodology proceeded by choosing and crossing keywords related to technology and fintech, based on a bibliometric analysis of the past and current literature of related fields, the frequency of citation, and usage in emerging AI, Big Data, Text Mining, and Cloud computing trends in finance. Wide coverage was pursued by considering expert-reviewed high-ranking keywords drawn from the core areas of the field. The results identify the top publishers and journals holding significant influence in the field of E-finance. Moreover, this paper will also shed light on the possible benefits of text mining in finance which include improving customer satisfaction as well as detecting and preventing fraudulent transactions and risks mitigation. Results underscore the co-dependence between Finance, Technology, AI, Big Data, Text Mining, Cloud. And how they fit with each other; it further proposed a new methodology that detailed using multi-source datasets. However, these findings form valuable insights into the growing importance of emerging technologies upon the finance industry and current key trends in this area.