Factors influencing organisational efficiency in a smart-logistics ecological chain under e-commerce platform leadership

Open interoperability model for Society 5.0's infrastructure and services

As the Internet of Things (IoT) is considered the foundation of digital transformation in everyday life, the Industrial IoT (IIoT) is considered its business counterpart. Together with the Physical Internet (PhI), they represent the foundation of smart production and logistics as part of the new digitized Society 5.0. Smart grids of different kinds with applications, ranging from power distribution to transportation, represent the infrastructure of smart cities and communities. Like with the PhI, they rely on the acceptance and integration of their services to fully unleash their potential. Hence, apart from the open interoperability model, which enables the interoperability and operational transparency of the IoT and IIoT, consistent design and development of their diverse augmented services is crucial for their wider acceptance as well as their safe and sustainable utilization.

Intelligent logistics systems in E-commerce and transportation

Smart coordination of production, logistics, transport and governance aims to move, store, supply and use physical objects throughout the world in a manner that is economically, environmentally and socially efficient, secure and sustainable. To achieve this, intelligent Logistics Systems (iLS) are needed, providing for transparency and interoperability in Society 5.0's smart environments by Augmented Logistics (AL) services. iLS are high-quality Autonomous Systems (AS), represented by intelligent agents that can easily take part in and learn from their environments. Smart logistics entities, such as smart facilities, vehicles, intermodal containers and distribution hubs represent the infrastructure of the Physical Internet (PhI). In this article the role of iLS in e-commerce and transportation is discussed. New behavioural, communication and knowledge models of iLS and their AL services in relation to the PhI OSI model are presented.

Institutional and Cultural Aspects of Logistic Management in the Chinese E-Commerce Sector

Electronic business relies heatedly on a predictive tool to provide consumers with the products online in a brief moment. E-commerce activities are handled by many buyers globally compared to conventional distribution, and with a broader range of products but a limited amount. This article aims to help the information review systemically manage consumer relationships in institutional and cultural aspects of the logistic management (ICA-LM) model. In preparation for the ICA-LM to be adequate to discuss static and dynamic attributes for removing precious secret information, the neural network and the class label are integrated. In this way, real-life client needs are defined and potential clients listed with limited time to generate client relationship maintenance (CRM) feedback for clients. The research in Hong Kong, a transportation management firm prototype, shows and validates CRM information gathering in the developing e-commerce logistics sector in the actual world.

The application of Industry 4.0 technologies in sustainable logistics: a systematic literature review (2012-2020) to explore future research opportunities

Nowadays, the market competition becomes increasingly fierce due to diversified customer needs, stringent environmental requirements, and global competitors. One of the most important factors for companies to not only survive but also thrive in today's competitive market is their logistics performance. This paper aims, through a systematic literature analysis of 115 papers from 2012 to 2020, at presenting quantitative insights and comprehensive overviews of the current and future research landscapes of sustainable logistics in the Industry 4.0 era. The results show that Industry 4.0 technologies provide opportunities for improving the economic efficiency, environmental performance, and social impact of logistics sectors. However, several challenges arise with this technological transformation, i.e., trade-offs among different sustainability indicators, unclear benefits, lifecycle environmental impact, inequity issues, and technology maturity. Thus, to better tackle the current research gaps, future suggestions are given to focus on the balance among different sustainability indicators through the entire lifecycle, human-centric technological transformation, system integration and digital twin, semi-autonomous transportation solutions, smart reverse logistics, and so forth.