Environmentally responsible freight transport service providers' assessment under data-driven information uncertainty

A survey of multi-criteria decision-making techniques for green logistics and low-carbon transportation systems

With the increasing severity of environmental problems, low-carbon development has become an inevitable choice. Nowadays, low-carbon green sustainable development is influenced by a variety of factors such as social, environmental, technological, and economic development levels, making its development complex, which in turn imposes challenges on decision-makers. In this context, the application of multi-criteria decision-making (MCDM) in different areas of sustainable development engineering has become a hot topic. Although many reviews of MCDM techniques already exist, there is a lack of holistic review efforts on MCDM in the field of low-carbon transport and green logistics. Considering these shortcomings in the state of the art, this paper systematically reviews more than 190 papers from 2010 to 2022, constructs a general structure of MCDM techniques for this research topic, provides a comprehensive review and analysis of it, and clarifies the current practices. Furthermore, future directions for the development of MCDM techniques for green logistics and low-carbon transportation systems are presented as well.

Impact analysis of COVID-19 outbreak on cold supply chains of perishable products using a SWARA based MULTIMOORA approach

The present study aims to analyze the impact of the COVID-19 outbreak resulting in Cold Supply Chain (CSC) disruptions and shed new light on the potential opportunities yielded from the pandemic. In addition, the work also aims to explore the most appropriate strategies to minimize CSC disruption due to the COVID-19 outbreak and to repurpose to create conditions as they were before the pandemic. The impact of the COVID-19 outbreak on CSCs has been analyzed theoretically and empirically, considering seven broader assessment criteria. To diminish the disruption due to COVID-19, eight of the most appropriate remedial strategies have been proposed in this study. A new hierarchical model was developed to articulate the analysis and consolidate various issues pertinent to CSC disruption caused by COVID-19 in one frame. The developed model was analyzed using a hybrid approach of SWARA-based MULTIMOORA methods. The SWARA method has been used to analyze the significance of considered assessment criteria, while the MULTIMOORA method has been used to analyze the mutual importance of proposed strategies. The findings of this paper show that ‘structural impact’ and ‘business and financial impact’ are the two most affected traits of CSC during the COVID-19 pandemic throughout the world. Meanwhile, the strategies ‘development of safe and healthier work scenario for partners of the cold chain’ and ‘successful monitoring and implementation of COVID-19 protocols’ are the two most important proposed strategies that might help management to mitigate the influence of the COVID-19 outbreak on CSCs. Findings of this research enable CSC managers and policy-makers to develop potential and robust plans for their operations to respond to disruptive situations like COVID-19 and turn them into opportunities for organizational growth and improving the health of society.

Uncertainties Influencing Transportation System Performances

The design and operation of transportation systems, as with any large complex technical system, are marked by indetermination—risks and uncertainties (scientific/methodologic and/or socio-economic). This paper analyzes the occurrence and consequences of uncertainties, defined as completely unknown random events (“unknown unknowns”), on transportation system performances. Interest in the topic is justified by the considerable value and long life of transportation system components. In order to reduce the effects of uncertainties, a holistic approach to all technical infrastructures in society, regardless of the flow category (material, energy, information), is necessary. Technological progress and changes in territorial activity systems historically confirm the dynamism of the competition and complementarity relations between civil and industrial infrastructures and transport infrastructures, as well as among different modal transport/traffic infrastructures. Declining discount rates are applied to compensate for the effects of uncertainties on investment project opportunities on long time horizons. There is no unanimous agreement on the discount rate values. Unforeseen exogenous events are considered differentiated/non-systemic or undifferentiated/systemic uncertainties. They can have significant consequences on the performance of a transport system, including a change in the transport market share. Therefore, an adaptive policy is required to reduce the methodological/scientific and socio-economic uncertainties that affect the design and operation of any transportation system.

A Comparative Evaluation of Multi-Criteria Analysis Methods for Sustainable Transport

The article pertains to the utilization of the application potential of MCDM/MCDA (Multi-Criteria Decision Making/Multi-Criteria Decision Analysis) methods in decision-making problems in the field of transport in light of sustainable development. The article consists of a theoretical and an empirical part. As part of the literature studies, a review was carried out on the latest applications of MCDM/MCDA methods for decision-making problems in the field of transport. In the empirical part, a multi-criteria analysis of the placement selection for a strip of expressway located in north-eastern Poland was carried out. For this purpose, a hybrid approach was used, consisting of three selected MCDM/MCDA methods: DEMATEL, REMBRANDT, and VIKOR. The ranking was compared with the results achieved in the EIA report of the investment and the results were obtained by using a different set of MCDM/MCDA methods that were proposed in the first part of the research, i.e., AHP, Fuzzy AHP, TOPSIS, and PROMETHEE. The performed multi-criteria analyses allowed for an eventual multi-dimensional evaluation of the most popular MCDM/MCDA methods currently applied in the field of transport.

A systematic and network-based analysis of data-driven quality management in supply chains and proposed future research directions

Purpose

This work aims to review past and present articles about data-driven quality management (DDQM) in supply chains (SCs). The motive behind the review is to identify associated literature gaps and to provide a future research direction in the field of DDQM in SCs.

Design/methodology/approach

A systematic literature review was done in the field of DDQM in SCs. SCOPUS database was chosen to collect articles in the selected field and then an SLR methodology has been followed to review the selected articles. The bibliometric and network analysis has also been conducted to analyze the contributions of various authors, countries and institutions in the field of DDQM in SCs. Network analysis was done by using VOS viewer package to analyze collaboration among researchers.

Findings

The findings of the study reveal that the adoption of data-driven technologies and quality management tools can help in strategic decision making. The usage of data-driven technologies such as artificial intelligence and machine learning can significantly enhance the performance of SC operations and network.

Originality/value

The paper discusses the importance of data-driven techniques enabling quality in SC management systems. The linkage between the data-driven techniques and quality management for improving the SC performance was also elaborated in the presented study.

Off-office audit of natural resource assets and water pollution: a quasi-natural experiment in China

Purpose

The purpose of this paper is to analyze the impact of the off-office audit of natural resource assets on the prevention and control of water pollution against a background of big data using a differences-in-differences model.

Design/methodology/approach

This study constructs a differences-in-differences model to evaluate the policy effects of off-office audit based on panel data from 11 cities in Anhui Province, China, from 2011 to 2017, and analyzes the dynamic effect of the audit and intermediary effect of industrial structure.

Findings

The implementation of the audit system can effectively reduce water pollution. Dynamic effect analysis showed that the audit policy can not only improve the quality of water resources but can also have a cumulative effect over time. That is, the prevention and control effect on water pollution is getting stronger and stronger. The results of the robustness test verified the effectiveness of water pollution prevention and control. However, the results of the influence mechanism analysis showed that the mediating effect of the industrial structure was not obvious in the short term.

Practical implications

These findings shed light on the effect of the off-office audit of natural resource assets on the prevention and control of water pollution, and provide a theoretical basis for the formulation of relevant environmental policies. Furthermore, these findings show that the implementation of the audit system can effectively reduce water pollution, which has practical significance for the sustainable development of China's economy against the background of big data.

Originality/value

This study quantitatively analyzes the policy effect of off-office auditing from the perspective of water resources based on a big data background, which differs from the existing research that mainly focuses on basic theoretical analysis.