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Intelligent Transportation and Green Logistics with Big Data

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A special issue of Sustainability (ISSN 2071-1050). This special issue belongs to the section "Sustainable Transportation".

Deadline for manuscript submissions: closed (30 April 2020) | Viewed by 46555

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Prof. Dr. Xiang Li

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Guest Editor

School of Economics and Management, Beijing University of Chemical Technology, Beijing 100029, China
Interests: traffic transportation management; data driven optimization; transportation management of hazardous material
Special Issues, Collections and Topics in MDPI journals

Prof. Dr. Guoqing Zhang

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Guest Editor

Faculty of Engineering, University of Windsor, Windsor, ON N9B 3P4, Canada
Interests: supply chain management and logistics; optimization; algorithms design; data analysis; intelligent manufacturing and support systems

Prof. Dr. Xiaofeng Xu

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Guest Editor

School of Economics and Management, China University of Petroleum, Qingdao 266580, China
Interests: supply chain management and operational optimization; operation management; energy systems engineering
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Big data provides unprecedented opportunities for the development of intelligent transportation and logistics industries. Taking full advantage of big data, we can accomplish informed decision-making and management on controlling cost, improving energy-efficiency, reducing carbon emissions, etc. The main challenges are the fusion of multi-source data and the transparent management of big data. This Special Issue is devoted to the exchange of scientific ideas, research methods, and innovative applications related to ‘’Intelligent Transportation and Green Logistics with Big Data’’. At present, although some papers about ‘’Intelligent Transportation and Green Logistics with Big Data’’ have been published, most of them are scattered across various volumes of the journal. We envisage that with the proposed Special Issue will offer the reader both an in-depth and a general account of accomplishments in this area, and point out remaining challenges for further research and development.

Prof. Dr. Xiang Li
Prof. Dr. Guoqing Zhang
Prof. Dr. Xiaofeng Xu
Guest Editors

Manuscript Submission Information

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Keywords

Intelligent transportation;
Green transportation;
Reverse logistics;
Green distribution;
Joint optimization

Published Papers (11 papers)

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Research

14 pages, 625 KiB

Open AccessArticle

Adoption of Automatic Warehousing Systems in Logistics Firms: A Technology–Organization–Environment Framework

by Jingjing Hao, Haoming Shi, Victor Shi and Chenchen Yang

Sustainability 2020, 12(12), 5185; https://0-doi-org.brum.beds.ac.uk/10.3390/su12125185 - 25 Jun 2020

Cited by 26 | Viewed by 5724

Abstract

The adoption of automatic warehousing systems, a type of green technology, has been an emerging trend in the logistics industry. In this study, we develop a conceptual model using a technology–organization–environment framework to investigate the factors which influence logistics firms to adopt green technology. Our model proposes that the adoption of green technology is influenced by perceived advantage, cost, technological turbulence, business partner influence, firm size, firm scope and operational performance. The objective of this study is to identify the conditions, as well as the contributing factors, for the adoption of automatic warehousing systems in logistics firms. Data were collected from 98 firms in China, and structural equation modeling with partial least squares is adopted to analyze the data. The results suggest that high perceived relative advantage, firm size, cost, firm scope, operation performance, technological turbulence and influence of business partners are important factors affecting IT adoption in small businesses. Therefore, decision support should be provided for enterprises from the three aspects of technology, organization and environment to improve the adoption of automatic warehousing systems. Full article

(This article belongs to the Special Issue Intelligent Transportation and Green Logistics with Big Data)

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13 pages, 866 KiB

Open AccessEditor’s ChoiceArticle

A Blockchain-Based Framework for Green Logistics in Supply Chains

by Bing Qing Tan, Fangfang Wang, Jia Liu, Kai Kang and Federica Costa

Sustainability 2020, 12(11), 4656; https://0-doi-org.brum.beds.ac.uk/10.3390/su12114656 - 07 Jun 2020

Cited by 77 | Viewed by 11772

Abstract

The logistics industry around the world has proliferated over recent years as a large number of business organizations have come to recognize the importance of logistics. Cost control used to be emphasized to remain competitive, but recently green logistics has gained attention with the awareness of the integration of economy and society as a whole. Nowadays, green logistics is a useful concept to improve the sustainability of logistics operations, and its related policies and theoretical research have been investigated and explored. However, the practical applications of green logistics are impeded by real-time data sharing, which is common in the logistics industry. Blockchain technology is adopted to address this challenge and enable data sharing among related stakeholders. This paper presents a reference framework for green logistics based on blockchain to reach the sustainable operations of logistics, with the integration of the Internet of Things and big data. Finally, potential benefits and limitations are analyzed when implementing this framework. Full article

(This article belongs to the Special Issue Intelligent Transportation and Green Logistics with Big Data)

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16 pages, 902 KiB

Open AccessArticle

Environmental Efficiency Measurement and Convergence Analysis of Interprovincial Road Transport in China

by Hao Xu, Yeqing Wang, Hongwei Liu and Ronglu Yang

Sustainability 2020, 12(11), 4613; https://0-doi-org.brum.beds.ac.uk/10.3390/su12114613 - 05 Jun 2020

Cited by 13 | Viewed by 2065

Abstract

Although road transport plays a vital role in promoting the development of China’s national economy, it also produces much harmful output in the process of road transport. Various types of harmful output generate high social costs. In order to improve efficiency and protect the environment at the same time, a variety of undesirable outputs need to be considered when evaluating the environmental efficiency of road transport. In this paper, the performance of the road transport systems in 30 regions of China is evaluated considering multiple harmful outputs (noise, carbon emission, direct property losses), by employing the directional distance function. Further, a convergence analysis of the environmental efficiency of road transport is carried out. The empirical results show that the environmental efficiency of overall road transport in China increased from 0.8851 to 0.9633 from 2010 to 2017. Moreover, the environmental efficiency gaps between the eastern, central and western areas have narrowed over time, but still exist. Additionally, the results of σ convergence analysis show that convergence of environmental efficiency exists in the whole country and the western area, while only weak convergence exists in the eastern and central areas. Both absolute β convergence and conditional β convergence exist in the eastern, central and western areas. While the environmental efficiency improved over the study period, the environmental efficiencies of road transport in some provinces remain inefficient, which deserves more attention from those seeking to improve environmental efficiency. The paper concludes with suggestions for improving the environmental efficiency of road transport. Full article

(This article belongs to the Special Issue Intelligent Transportation and Green Logistics with Big Data)

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16 pages, 455 KiB

Open AccessArticle

Optimal Pricing in Recycling and Remanufacturing in Uncertain Environments

by Guangzhou Yan, Yaodong Ni and Xiangfeng Yang

Sustainability 2020, 12(8), 3199; https://0-doi-org.brum.beds.ac.uk/10.3390/su12083199 - 15 Apr 2020

Cited by 8 | Viewed by 2025

Abstract

With the increasing awareness of environmental protection, firms pay much more attention to the recycling and remanufacturing of used products. This paper addresses the problem of the optimal pricing in recycling and remanufacturing in uncertain environments. We consider two strategies of remanufacturing products, by which a recycled product can be repaired and sold as a second-hand product or dissembled into materials for production of new products according to its quality. As the market demand for products and the quantities of recycled products, such as fashion products and mobile phones, usually lack historical data, this paper adopts uncertainty theory to depict uncertainty in establishing the pricing model. An uncertain programming model and a series of crisp equivalent models are proposed under the assumptions of particular uncertainty distribution. Finally, numerical experiments are performed to show how various parameters influence the results of the proposed model. Full article

(This article belongs to the Special Issue Intelligent Transportation and Green Logistics with Big Data)

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14 pages, 2156 KiB

Open AccessArticle

Optimal Express Bus Routes Design with Limited-Stop Services for Long-Distance Commuters

by Hongguo Ren, Zhenbao Wang and Yanyan Chen

Sustainability 2020, 12(4), 1669; https://0-doi-org.brum.beds.ac.uk/10.3390/su12041669 - 23 Feb 2020

Cited by 7 | Viewed by 3154

Abstract

This research aimed to propose a route optimization method for long-distance commuter bus service to improve the attraction of public transport as a sustainable travel mode. Taking the express bus services (EBS) in Changping Corridor in Beijing as an example, we put forward an EBS route-planning method for long-distance commuter based on a solving algorithm for vehicle routing problem with pickups and deliveries (VRPPD) to determine the length of routes, number of lines, and stop location. Mobile phone location (MPL) data served as a valid instrument for the origin–destination (OD) estimation, which provided a new perspective to identify the locations of homes and jobs. The OD distribution matrices were specified via geocoded MPL data. The optimization objective of the EBS is to minimize the total distance traveled by the lines, subject to maximum segment capacity constraints. The sensitivity analysis was done to several key factors (e.g., the segment capacity, vehicle capacity, and headway) influencing the number of lines, the length of routes. The results suggest that the scenario with the segment capacity of 4000 passengers/h has a minimum of number and length of lines, but we recommend that the transit agency adopt 3000 passengers/h as the route segment capacity because this scenario results in minimum fleet size and minimum total operation length. Full article

(This article belongs to the Special Issue Intelligent Transportation and Green Logistics with Big Data)

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15 pages, 1469 KiB

Open AccessArticle

Temporal and Spatial Differences in the Resilience of Smart Cities and Their Influencing Factors: Evidence from Non-Provincial Cities in China

by Xiaojun Dong, Tao Shi, Wei Zhang and Qian Zhou

Sustainability 2020, 12(4), 1321; https://0-doi-org.brum.beds.ac.uk/10.3390/su12041321 - 12 Feb 2020

Cited by 27 | Viewed by 3154

Abstract

Based on the sample data of 81 non-provincial smart cities in China in 2017, the comprehensive evaluation index of the resilience of sample cities is calculated by using the entropy method, and the spatial differences of different factors on the resiliency are analyzed by using the geographical weighted regression (GWR) model. The conclusions are as follows: Firstly, the comprehensive evaluation index of the resilience of smart cities presents a spatial distribution characteristic of decreasing from the east to the west. At the same time, the resilience comprehensive index, the public infrastructure resilience capacity index, the economic development resilience index, the social security resilience index, and the ecological environment resilience index of smart cities have obvious agglomeration effects on their geographical spaces. Secondly, the public infrastructure resilience capacity index and the ecological environment resilience index are both low with a discrete distribution, while the economic development resilience index and the social security resilience index are both high with a concentrated distribution. Thirdly, different factors have significantly positive effects on the resilience of smart cities. In particular, the public infrastructure capacity resilience index decreases from the north to the south with the spatial distribution pattern of concentration, the economic development resilience index and the ecological environment resilience index of smart cities decrease from the east to the west with a concentrated spatial distribution pattern, and the social security resilience index of smart cities decreases from the southwest to the northeast with a concentrated spatial distribution pattern. Therefore, it is necessary to enhance awareness of smart cities, strengthen the driving force of science and technology innovation, strengthen public infrastructure and service construction, and continuously improve the rapid resilience of smart cities. Full article

(This article belongs to the Special Issue Intelligent Transportation and Green Logistics with Big Data)

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14 pages, 1118 KiB

Open AccessArticle

Supply-Chain Pricing and Coordination for New Energy Vehicles Considering Heterogeneity in Consumers’ Low Carbon Preference

by Bengang Gong, Xuan Xia and Jinshi Cheng

Sustainability 2020, 12(4), 1306; https://0-doi-org.brum.beds.ac.uk/10.3390/su12041306 - 11 Feb 2020

Cited by 20 | Viewed by 3101

Abstract

Given consumers’ willingness to pay different prices for new energy vehicles (NEVs) and traditional vehicles, we construct a utility model of ordinary and green consumers. We establish pricing game models for centralized and decentralized decisions in an NEV’s supply chain in order to study the impact of changes in consumers’ low carbon preference heterogeneity on supply chain pricing and member profit. The results show that consumers’ low carbon preferences and the ratio of green consumers increases with the ex-factory and selling prices of NEVs. An increase in the percentage of green consumers under centralized decision-making will reduce the total profit of the supply chain. Manufacturers’ profits under decentralized decision-making are greater than the dealers’ profits, and the sum of the two members’ profits under decentralized decision-making is less than the total profit of the supply chain under centralized decision-making. We design a revenue-sharing contract to eliminate the double marginal effect. Full article

(This article belongs to the Special Issue Intelligent Transportation and Green Logistics with Big Data)

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16 pages, 2131 KiB

Open AccessArticle

Coordinating a Green Agri-Food Supply Chain with Revenue-Sharing Contracts Considering Retailers’ Green Marketing Efforts

by Li Cui, Siwei Guo and Hao Zhang

Sustainability 2020, 12(4), 1289; https://0-doi-org.brum.beds.ac.uk/10.3390/su12041289 - 11 Feb 2020

Cited by 29 | Viewed by 4801

Abstract

Serious environmental issues have drawn the attention of the agricultural sector. Consumers’ concerns about their personal health and food safety have stimulated the demand for green agri-food, which has also made it important to focus on the green agri-food supply chain to improve the food quality and reduce the associated environmental concerns. This paper discusses coordination issues of the green agri-food supply chain under the background of farmers’ green farming and retailers’ green marketing, and the impact of a revenue-sharing contract on key decisions of supply chain participants. On the basis of the two-echelon green agri-food supply chain composed of a farmer and a retailer, a revenue-sharing contract was established that takes the cost of farmer’s green farming and retailer’s green marketing into account. Through the comparison of the model results, it is concluded that the revenue-sharing contract is beneficial to not only increase the greening level, but also improve both the farmer’s profit and the retailer’s profit. Moreover, the effectiveness of the revenue-sharing contract is positively correlated with consumers’ sensitivity to the greening level. Finally, the conclusion is verified by numerical simulation and some management suggestions are given. Full article

(This article belongs to the Special Issue Intelligent Transportation and Green Logistics with Big Data)

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23 pages, 1569 KiB

Open AccessArticle

How to Coordinate Economic, Logistics and Ecological Environment? Evidences from 30 Provinces and Cities in China

by Wei Zhang, Xinxin Zhang, Mingyang Zhang and Woyuan Li

Sustainability 2020, 12(3), 1058; https://0-doi-org.brum.beds.ac.uk/10.3390/su12031058 - 02 Feb 2020

Cited by 37 | Viewed by 4090

Abstract

With the rapid development of economy, the scale of the logistics industry is also expanding rapidly, which brings great convenience to economy and trade, and becomes one of the pillar industries of national economy. However, with the development of economy and logistics, the problem of ecological environment is becoming more and more prominent. Through the design of economic development, logistics development, and the ecological environment index system, the economic development, logistics development and eco-environment development level of 30 provinces and cities in China from 2008 to 2017 are analyzed by using the entropy method and coupling coordination degree model, and the spatial characteristics of regional economic development, logistics development, and ecological environment are analyzed by using ArcGIS software. The results show that the coupling coordination of economic development, logistics development and ecological environment in most provinces and cities in China is at the mediate coupling level, and only Shanghai, Anhui, and Fujian in the Eastern region have reached the high-quality coupling level; there are significant temporal and spatial differences in the coupling and coordinated development between economic development, logistics development and ecological environment. The level of coupling coordination in the western region has always been at a low level, while the level of coupling coordination in most of the central and eastern regions is relatively high. There are situations where the level of coupling coordination is not high; the coordinated growth of economic development, logistics development, and ecological environment is mainly driven by economic development and logistics development. However, the level of ecological environment has been lagging behind the level of economic and logistics development. In the future development, it is necessary to give full play to the role of the logistics industry in economic development, weigh the relationship between the development of the logistics industry and ecological environmental protection, actively develop green logistics, and the level of coordinated development among economic development, logistics development and ecological environment. Full article

(This article belongs to the Special Issue Intelligent Transportation and Green Logistics with Big Data)

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22 pages, 1927 KiB

Open AccessArticle

A p-Robust Green Supply Chain Network Design Model under Uncertain Carbon Price and Demand

by Ruozhen Qiu, Shunpeng Shi and Yue Sun

Sustainability 2019, 11(21), 5928; https://0-doi-org.brum.beds.ac.uk/10.3390/su11215928 - 24 Oct 2019

Cited by 5 | Viewed by 2277

Abstract

The problem of designing a multi-product, multi-period green supply chain network under uncertainties in carbon price and customer demand is studied in this paper. The purpose of this study is to develop a robust green supply chain network design model to minimize the total cost and to effectively cope with uncertainties. A scenario tree method is applied to model the uncertainty, and a green supply chain network design model is developed under the p-robustness criterion. Furthermore, the solution method for determining the lower and upper bounds of the relative regret limit is introduced, which is convenient for decision-makers to choose the corresponding supply chain network structure through the tradeoff between risk and cost performance. In particular, to overcome the large scale of the model caused by a high number of uncertain scenarios and reduce the computational difficulty, a scenario reduction technique is applied to filter the scenarios. Numerical calculations are executed to analyze the influence of relevant parameters on the performance of the designed green supply chain network. The results show that the proposed p-robust green supply chain network design model can effectively deal with carbon and demand uncertainties while ensuring cost performance, and can offer more choices for decision-makers with different risk preferences. Full article

(This article belongs to the Special Issue Intelligent Transportation and Green Logistics with Big Data)

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25 pages, 1491 KiB

Open AccessArticle

Interaction Analysis and Sustainable Development Strategy between Port and City: The Case of Liaoning

by Jiaguo Liu, Jinxia Zhou, Fan Liu, Xiaohang Yue, Yudan Kong and Xiaoye Wang

Sustainability 2019, 11(19), 5366; https://0-doi-org.brum.beds.ac.uk/10.3390/su11195366 - 28 Sep 2019

Cited by 21 | Viewed by 3356

Abstract

Although port-city interaction and sustainability are becoming increasingly essential, prospering regional economy and facilitating international shipping trade, problems of their mismatch and incoordination have also been aroused. Thus, research on their relationship is necessary to generate profound enlightenment on how to achieve healthy and benign development for ports and cities. In this paper, a typical Chinese port-city group, six ports and their corresponding port cities in Liaoning are selected as research objects. Firstly, a grey relative relational model and a coupling coordination degree model based on entropy weight method are applied to analyse the port-city interactive trend and degree as well as exploring the relative impacts among internal factors in port and city subsystems. Then, a sustainability analysis box of correlation–coordination is constructed to further investigate the sustainable development status. Finally, strategies for the port-city sustainable development are proposed. The results indicate the six port-city systems have not strongly correlated and are in the stage of coordinated development. Only Dalian and Yingkou have realized sustainable development. Thus, there is still much room for improvement. Measures such as resources integration and dislocation development should be taken into account to optimize the sustainable and coordinated development of the port-city systems. Full article

(This article belongs to the Special Issue Intelligent Transportation and Green Logistics with Big Data)

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