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The criticality of late deliveries in transportation lies in the threat of considerable multi-level supply chain costs. This study aims to reveal the dynamic capabilities playing a facilitating role in preventing delay, thus providing timely delivery, as well as developing an understanding of how and when those capabilities are activated within the supply chain network.

An exploratory study was conducted involving 16 semi-structured expert interviews with the representatives of logistics service providers and shippers. Following an interpretive phenomenology framework, the prevention phenomenon was explained.

Findings revealed two preventive capability categories in delay prevention: (1) proactive capabilities, referring to the enabling actions planned before departure, and (2) reactive capabilities, referring to actions planned after departure. Findings pinpoint that, in addition to the proactive capabilities, reactive capabilities enabled by innovative problem-solving actions are crucial for adapting to a dynamically changing environment in prevention. Moreover, this study shows that prevention capabilities are characterized by tangible and intangible resources and integration of resources with external links which constitute a delay prevention network within a wider service ecosystem.

This study stands out with its specific focus on delay prevention capabilities and enabling actions from the perspectives of logistics service providers and shippers. The premises of the resource-based view are combined with dynamic capabilities theory, leading to a proposed time-based taxonomy of proactive and reactive capabilities in supply chains, aimed at creating value and strengthening resilience.

This paper's purpose is twofold. First, based on a case study, it aims to comprehend the consequences of COVID-19 on the demand and supply shocks of the freight transportation system in Mexico. Second, it seeks to provide an integrated perspective of four transportation modes, which would help prepare public policies for future global pandemics.

Analyzing the impact of the COVID-19 pandemic on the freight transportation system, which affects national and global economies, is essential to drawing valuable insights for the future. To facilitate international comparative analysis, conducting case studies at a country level was deemed necessary. As a result, a case study was conducted in Mexico using an integrated approach involving four transportation modes.

To manage disruptions in freight flow during uncertain conditions, a comprehensive perspective on the four modes of transportation and data-driven decision-making is crucial. Under this context, three initiatives can be identified: 1) establishing a National Center for Intelligence in Logistics to improve data-driven governance; 2) appointing the “Integrated Transportation Corridor Management Manager” (ITCMM) function to coordinate multiple authorities with different acting in critical freight transport corridors, and 3) creation of a digital tool based on millions of GPS data to monitor freight flows, allowing for collective intelligence among logistics actors.

This research's limitations are related to using non-standardized databases to gather information on four transportation modes. However, this limitation is also an interesting discovery. Mexico is becoming a strategic logistics hub between North America and Latin America, especially under the “Nearshoring” trend. Unfortunately, the lack of an integrated public policy in logistics and transportation reduces Mexico's capacity to deal with disruptions and its economic competitiveness.

This research has identified practices that could be crucial in improving public policies to optimize shipping routes and reduce wait times while minimizing disruptions caused by unforeseen events. A concrete example is the digital platform called “eraclitux,” a computer tool similar to an Enterprise Resource Planning (ERP) system companies use. This tool can enable a “Control Tower” that monitors freight flow in transportation corridors under the supervision of “Integrated Transportation Corridor Management Managers.” The tool can make reactive and predictive decisions that help to enhance the logistics value provided by transportation infrastructure.

The importance of a well-coordinated and integrated public policy for freight transportation was identified to ensure better performance during disruptions. Delays in the flow of goods can significantly impact the supply of essential items such as food and medicine, ultimately affecting the population's quality of life.

Numerous studies have been conducted to determine the extent of vulnerability and the impact of COVID-19 on freight transportation. However, most of these studies assume a developed market context or a single-mode transportation approach, which only applies to some situations. To gain a comprehensive understanding of how pandemics-induced demand and supply shocks affected freight transportation in developing countries such as Mexico, this paper offers insights from a four-transportation mode perspective. Mexico is facing a challenging Nearshoring trend in manufacturing, making it a significant logistics node between North and South America.

The digital evolution of production and logistics systems requires seamless integration of various functions. Cyber-physical systems (CPS) can streamline operations, reduce costs and optimise freight transport dynamics. Therefore, CPS adoption is essential to transform existing logistics infrastructure by connecting logistical equipment to cyberspace. This research addresses the critical issue of low CPS adoption in logistics. By analysing the barriers, the study proposes effective strategies to increase CPS integration significantly.

This study used the technology-organisation-environment (TOE) framework and identified 18 barriers to CPS adoption in freight logistics. The barriers were then analysed using the fuzzy data-driven multi-criteria decision-making (MCDM) method, i.e. fuzzy-based decision-making trial and evaluation laboratory (Fuzzy-DEMATEL).

The computational analysis of the proposed framework shows that “the complexity of CPS and lagged data-driven logistics infrastructure” (T₁) is a major technological inhibitor to CPS adoption. The “high cost of CPS technology” (O₈) and a “lack of top management support” (O₃) are the top causal inhibitors at the organisational level. “Lack of data governance and regulatory framework” (E₂) is the main environmental inhibitor.

The causal mapping of the TOE-based barriers helps policymakers and logisticians to develop strategies or follow recommended adoption strategies to improve CPS adoption in logistics.

This study is a pioneering effort to unveil the adoption barriers of CPS in the freight logistics industry and suggest strategies for fostering adoption. This research could provide valuable insights for logistics organisations to support CPS-driven logistics modernisation.

Carbon emissions commonly serve as an indicator for environmental friendliness, and so more and more carbon emission calculators (CECs) are offered that allow an estimation of the environmental footprint of freight transport operations. Unfortunately, their exact measurement is challenging due to the availability or poor quality of necessary input data and a multitude of possible calculation methods that may result in highly inaccurate to very misleading figures.

A structured online search was conducted to identify suitable online carbon emission calculators (OCECs) for further assessment in the form of a benchmark case that includes different modes of transport from road and rail to air and sea between China and Europe. Further comparison resulted in a ranking of OCECs along the categories of transparency (routing system, data sources and calculation method), completeness (input options) and accuracy (data output).

Different predefined inputs and calculation methods employed by the OCECs assessed inevitably result in a wide spread of more or less reliable carbon footprint measurement results.

All potential users of CECs, including policymakers, actors from the transport industry and other stakeholders, are well advised to question greenhouse gas (GHG) emission statements that are not backed by transparent procedures and internationally recognized calculation standards.

This study, including a benchmark case and a ranking, offers a guideline for potential users of CEC to avoid major pitfalls coming along with the present carbon footprint measurement of freight transport operations.

The cyber-physical system (CPS) is a well proven technology for improving system performance, resilience, and interconnectivity. In emerging nations like India, the logistics industry lacks practices connecting logistical equipment with cyberspace. This paper aims to bridge this gap by identifying and evaluating the performance metrics of connectivity solutions. Its goal is to establish an appropriate infrastructure that enables seamless connectivity within the CPS-enabled logistics ecosystem.

A novel integrated decision method is employed to classify the optimal connectivity solution for CPS. It integrates Regret Theory (RT) and Preference Ranking for Organization Method for Enrichment Evaluation (PROMETHEE-1) method in a Hesitant Fuzzy (HF) environment. This method considers the psychological traits of decision-makers and effectively incorporates their hesitancy for the classification.

The findings highlight security (c10) as the foremost critical performance metric, followed by cost (c6), scalability (c9), traceability (c2) and trustworthiness (c1) to build connective infrastructure for CPS. For extensive coverage scenarios, like freight transportation, cellular connectivity (a2) emerges as the most suitable connectivity solution.

This study provides a roadmap to logistics managers for selecting a suitable connectivity infrastructure to enhance seamless connectivity in logistics operations and processes. Technology providers can utilize the findings to develop the CPS infrastructure for effective freight logistics management.

This research introduces a novel decision-making tool for making choices related to advanced technology assessment. It holds significant value in facilitating well-informed decisions in the digital transformation era.

In the existing era, international trade is boosted by maritime freight movement. The academicians and Government are concerned about environmental contamination caused by maritime goods that transit global growth and development. Digital technologies like blockchain help the maritime freight business to stay competitive in the digital age. This study aims to illuminate blockchain technology (BCT) adoption aspects to alleviate early industry adoption restrictions.

This study adopts a two-stage approach comprising of structural equation modeling (SEM) with artificial neural networks (ANN) to analyze critical factors influencing the adoption of BCT in the sustainable maritime freight industry.

The SEM findings from this study illustrate that social, organizational, technological and infrastructual and institutional factors affect BCT execution. Furthermore, the ANN technique uses the SEM data to determine that sustainability enabled digital freight training (S3), initial investment cost (O5) and trust over digital technology (G1) are the most essential blockchain deployment factors.

The hybrid approach aims to help decision-makers and policymakers examine their organizational blockchain adoption goals to construct sustainable, efficient and effective maritime freight transportation.

Express freight transportation is in rapid development currently. Owing to the higher speed of express freight train, the deformation of the bridge deck worsens the railway line condition under the action of wind and train moving load when the train runs over a long-span bridge. Besides, the blunt car body of vehicle has poor aerodynamic characteristics, bringing a greater challenge on the running stability in the crosswind.

In this study, the aerodynamic force coefficients of express freight vehicles on the bridge are measured by scale model wind tunnel test. The dynamic model of the train-long-span steel truss bridge coupling system is established, and the dynamic response as well as the running safety of vehicle are evaluated.

The results show that wind speed has a significant influence on running safety, which is mainly reflected in the over-limitation of wheel unloading rate. The wind speed limit decreases with train speed, and it reduces to 18.83 m/s when the train speed is 160 km/h.

This study deepens the theoretical understanding of the interaction between vehicles and bridges and proposes new methods for analyzing similar engineering problems. It also provides a new theoretical basis for the safety assessment of express freight trains.

This paper aims to review the literature on the relationship between the implementation and performance of 4.0 industrial revolution (IR) technologies and explores the extent to which the effects of several internal and external contingency factors on these relationships have been considered by the existing empirical studies.

To achieve its purposes, this study follows a systematic review of the literature and explores the published empirical research on implementation and performance links of 4.0 IR technologies and the effects of contingency factors on these links in mainly three main databases.

The findings of this study reveal that in general several contingency factors tend to have significant effects on the implementation and performance links of 4.0 IR in several contexts. This study also shows that the effects of these contingencies the effects of contingency factors on the implementation and performance links of 4.0 IR technologies are receiving growing attention from researchers and have been studied in different approaches but the moderation approach was the highest.

The review of the literature conducted in this study refers to those studies published mostly by three main databases (i.e. Scopus, Web of Sciences, and Science Direct), and only those papers published in English, and thus does not contain publications out of these restrictions.

This is one of the early literature review studies to explore and discuss the current state of research on the effects of contingency factors on the relationships between the implementation and performance of 4.0 IR technologies in the contexts of logistics and supply chain management.

This study aims to investigate how the adoption of sustainable manufacturing practices by companies can positively impact their reputation and environmental performance. Additionally, it aims to explore the specific relationships between these factors within the unique context of manufacturing companies in Tunisia.

The research uses an online questionnaire survey methodology targeted at manufacturing companies in Tunisia. This approach provides detailed insights into the current landscape of sustainable manufacturing practices within the region.

The study underscores the increasing significance of sustainable manufacturing practices for companies striving to align with environmental sustainability while meeting stakeholder expectations. It reveals that embracing these practices can indeed yield favorable impacts on both a company’s environmental performance and its overall reputation.

While the study sheds light on the relationships between sustainable practices, environmental performance and reputation, it acknowledges certain limitations. These limitations might include the scope of the survey, potential biases in responses or constraints within the Tunisian manufacturing context, impacting the generalizability of findings.

This research holds unique value by offering insights into the complex interplay between sustainable manufacturing practices, environmental performance and corporate reputation in a developing country context like Tunisia. The study contributes to a deeper understanding of these dynamics, benefiting both academia and industry practitioners interested in fostering sustainability within the manufacturing sector.