Smart urban transport and logistics: A business analytics perspective

Abstract

New technologies and innovative business models are leading to connected, shared, autonomous, and electric solutions for the tomorrow of urban transport and logistics (UTL). The efficiency and sustainability of these solutions are greatly empowered by the capability of understanding and utilizing the tremendous amount of data generated by passengers, drivers, and vehicles. In this study, we first review the innovative applications in UTL and several related research areas in the operations management (OM)/operations research (OR) literature. We then highlight the sources, types, and uses of data in different applications. We further elaborate on business analytics techniques and software developed to facilitate the planning and management of UTL systems. Finally, we conclude the paper by reflecting on the emerging trends and potential research directions in data‐driven decision making for smart UTL.

Data-Driven Optimization of Urban Traffic using AI and Real-Time Analysis

“…Although the data-driven optimization of urban traffic is the main emphasis of this literature analysis, it is crucial to recognize other study fields that are equally relevant and offer insightful information. He, Liu, and Shen [11] explored business analytics-based smart urban logistics and transportation, underscoring the potential of datadriven decision-making for streamlining several facets of urban transportation systems.Subburaj et al's study [12] on the use of traffic-sensitive routing for effective garbage collection is remarkable. The authors provide a routing algorithm that takes advantage of changing traffic patterns and optimizes garbage collection routes by taking current traffic circumstances into account.…”

Emerging research problems in different business domains: An analytics perspective

“…Finally, He et al (2022) survey recent research articles and categorize smart urban transport and logistics (UTL) studies based on their research topics into the following: (a) driving and commuting, (b) freight and logistics, (c) last-mile delivery, and (d) public services. These studies include analytical, empirical, predictive, and optimization models for technological applications of electric vehicles (EVs), autonomous vehicles, and drones, as well as for operational contexts of vehicle sharing, ride-hailing, meal Production and Operations Management and grocery delivery, healthcare delivery, and humanitarian logistics.…”

Analyzing Barriers to Internet of Things (IoT) Adoption in Humanitarian Logistics: An ISM–DEMATEL Approach

“…Improvements in humanitarian organizations' efficiency and effectiveness have been essential to the continuation of HL activities, and modern means of communication and technologies have played a crucial role in this regard [23][24][25][26][27][28][29][30]. Recently, the emergence of the Internet of Things (IoT) has been considered a key enabler for HL [31,32].…”