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There is a large number of perishable foodstuffs produced, stored, distributed and delivered daily around the world. Almost all except for root vegetables are sensitive products to temperature. Thus, adopting uninterrupted and appropriate logistics activities with predetermined range of temperature from production site until end-user is critical for ensuring required quality and safety. If a mistake is made during either transport or storage, it not only becomes risky for human health, but also generates huge food waste for the environment and negative economic impact for food providers. Therefore, this study aims to identify all potential factors affecting the cold chain performance in the food industry and to design a framework that includes these factors. This framework is also a roadmap for managers, food providers and logistics parties for sustainable cold chain management.

Considering, tangible and intangible potential criteria, the ultimate goal of this study is to identify potential criteria affecting cold food chain performance and propose a conceptual framework including 12 main criteria. Next, the importance order of each criterion and the causal relationships between them are determined. In this study, this relationship among criteria is analyzed by using fuzzy Decision-making Trial and Evaluation Laboratory (DEMATEL) approach because of its ability to solve complex problems by ensuring causal relationship among factors, additionally to determine importance order. Finally, suggestions for administrative implications are presented.

Fuzzy DEMATEL was used to explain the causal link and importance order among identified drivers. The analysis shows that five criteria (C1, C3, C8, C9 and C12) belong to cause (influential) groups and remaining seven criteria belong to effect (influenced) groups. The highest influential criterion is staff (C8) and is followed by technical issues (C9) as the second most influential factor. Additionally, top three most important factors are traceability (C7), staff (C8) and cold transportation (C5). According to the numerical results of fuzzy DEMATEL implementations, suggestions for managerial implementations are presented.

The main contribution of the study is to propose meaningful suggestions for managerial implications about sustainable cold chain in food industry for businesses and to examine causal relations between criteria and to rank criteria in descending importance order.

To the best of the authors’ knowledge, this is the first study that focuses on determining the potential criteria affecting cold supply chain performance both theoretically and empirically in the sustainability environment. What are the enablers that affect the cold food supply chain stages is the research question of this study.

Sustainable urban rail transit requires noise barriers. However, these barriers’ durability varies due to the differing aerodynamic impacts they experience. The purpose of this paper is to investigate the aerodynamic discrepancies of trains when they meet within two types of rectangular noise barriers: fully enclosed (FERNB) and semi-enclosed with vertical plates (SERNBVB). The research also considers the sensitivity of the scale ratio in these scenarios.

A 1:16 scaled moving model test analyzed spatiotemporal patterns and discrepancies in aerodynamic pressures during train meetings. Three-dimensional computational fluid dynamics models, with scale ratios of 1:1, 1:8 and 1:16, used the improved delayed detached eddy simulation turbulence model and slip grid technique. Comparing scale ratios on aerodynamic pressure discrepancies between the two types of noise barriers and revealing the flow field mechanism were done. The goal is to establish the relationship between aerodynamic pressure at scale and in full scale.

The aerodynamic pressure on SERNBVB is influenced by the train’s head and tail waves, whereas for FERNB, it is affected by pressure wave and head-tail waves. Notably, SERNBVB's aerodynamic pressure is more sensitive to changes in scale ratio. As the scale ratio decreases, the aerodynamic pressure on the noise barrier gradually increases.

A train-meeting moving model test is conducted within the noise barrier. Comparison of aerodynamic discrepancies during train meets between two types of rectangular noise barriers and the relationship between the scale and the full scale are established considering the modeling scale ratio.

The provision of air transport services in small and regional airports is a major concern worldwide as regional aviation is challenged with inadequate revenues. This chapter aims to identify the driving factors for sustaining regional airlines and airports. Nine factors are identified through literature review and expert opinion. Fuzzy-total interpretive structural modeling is used to develop a hierarchical relationship among the factors. Truncated population of the region, national subsidies, and airport infrastructure development have been found to be the strongest drivers for promoting regional airports. This hierarchical model provides a logical structure to the factors.

The novel blockchain technology can be leveraged, owing to the growth in computing power and its widespread applications. This study aims to understand the challenges of adopting blockchain technology in the financial sector, organise them into a model and classify them for systematic address.

Interpretive Structural Modeling (ISM) has been carried out along with MICMAC (Matrice d’impacts croisés multiplication appliquée á un classment) analysis to hierarchically structure blockchain adoption problems and categorise the challenges into four classes-autonomous, dependent, linkage and independent for better addressing. The study also uses content analysis using NVivo software.

The digraph depicts the hierarchical challenge model. Vulnerability to financial crimes and glitches, privacy issues and geopolitical tensions due to cross-border transactions are the dependent variables. Complex architecture to comprehend, code and fix, the need for new financial intermediaries, complexity in auditing and the lack of unified governance and coordination among institutions and regulators are the independent variables. The digraph, which is also justified by the qualitative content analysis, is beneficial for stakeholders to systematically address the interdependent challenges associated with blockchain implementations in finance to foster its favourable adoption.

The challenges in the adoption of blockchain should be resolved to allow the implementation of this technology in various finance domains. This study enables organisations to carry out resource planning and systematically address these challenges to leverage the advantages of blockchain.

The results of the present study can help in promoting the proliferation of blockchain for faster, cost-effective, transparent and secure financial transactions and foster innovative and new business models for economic growth.

The development of technology has brought about significant changes in the financial sector. Blockchain is a technological advancement that aims to bring security and transparency to transactions. There has been no research leveraging ISM-MICMAC to hierarchically organise and classify the blockchain challenges in the financial sector, a critical one. The research also uses content analysis which is seldom found along with ISM-MICMAC.

In this study, a multi-criteria decision-making (MCDM) approach for evaluating airworthiness factors were presented. The purpose of this study is to develop an acceptable rationale for operational activities in civil and military aviation and for design, production and maintenance activities in the aviation industry that can be used in-flight safety programs and evaluations.

In aviation, while the initial and continuing airworthiness of aircraft is related to technical airworthiness, identifying and minimizing risks for avoiding losses and damages are related to operational airworthiness. Thus, the airworthiness factors in civil and military aviation were evaluated under these two categories as the technical and operational airworthiness factors by the analytic hierarchy process and analytic network process. Three technical and five operational airworthiness criteria for civil aviation, three technical and nine operational airworthiness criteria for military aviation were defined, evaluated, prioritized and compared in terms of flight safety.

The most important technical factor is the “airworthiness status of the aircraft” both in civil (81.9%) and military (77.6%) aviation, which means that aircraft should initially be designed for safety. The most significant operational factors are the “air traffic control system” in civil (30.9%) and “threat” in the military (26.6%) aviation. The differences within factor weights may stem from the design requirements and acceptable safety levels (frequency of occurrences 1 in 10⁷ in military and 1 in 10⁹ in civil aircraft design) of civil and military aircraft with the mission achievement requirements in civil and military aviation operations. The damage acceptance criteria for civil and military aircraft are different. The operation risks are accepted in the military and acceptance of specific tasks and the risk levels can vary with aircraft purpose and type.

This study provides an acceptable rationale for safety programs and evaluations in aviation activities. The results of this study can be used in real-world airworthiness applications and safety management by the aviation industry and furthermore, critical factor weights should be considered both in civil and military aviation operations and flights. The safety levels of airlines with respect to our airworthiness factor weights or the safety level of military operations can be computed.

This is the first study considering technical and operational airworthiness factors as an MCDM problem. Originality and value of this paper are defining critical airworthiness factors for civil and military aviation, ranking these factors, revealing the most important ones and using MCDM methods for the evaluations of airworthiness factors for the first time. In civil aviation flight safety is the basic tenet of airworthiness activities in risk analysis, on the other hand in military aviation high levels of risks are to be avoided in peace training or operational tasks. However, even high risks have to be accepted during the war, if the operational requirements impose, as mission achievement is vital. The paper is one of a kind on airworthiness evaluations for flight safety.

Civil engineering structures are regularly confronted with failures that can lead to catastrophic consequences. It is important, after a failure, to be able to identify the origin and the sequence of factors that led to it. This failure analysis by experts, called forensic engineering investigation, generally leads to the drafting of an expert report. These reports do not inform on the processes that guided the experts to a conclusion and the uncertainties involved. This paper aims to propose a new methodological approach to formalize the opinions of experts in forensic engineering.

The research consists in combining abstract argumentation with the theory of imprecise probabilities to take into account epistemic and stochastic uncertainties to support forensic engineering investigation.

A model and a tool to support forensic analysis are presented. An application on the collapse of the Brumadinho dam highlights the interest of the chosen approach.

This work is the first use of the abstract argument framework in civil engineering, and so in forensic engineering. Furthermore, it provides an innovative model based on imprecise probability for AAF.

Blockchain is one of the most significant emerging technologies that is set to transform many aspects of industry and society. However, it has several major technical, social, legal, environmental and ethical complexities that offer significant challenges for mainstream use within the public sector. The coronavirus disease 2019 (COVID-19) pandemic has compelled many public sector employees to work remotely, highlighting a number of challenges to blockchain adoption within the Indian context signifying the pertinence of this research topic in the post-pandemic era. This study offers insight to researchers and policymakers alike on how such challenges are interdependent within this important subject.

We explored 16 unique sets of challenges selected from the literature and gathered data from nine experts from government settings, healthcare and education sectors and academia who have significant knowledge and experience of blockchain implementation and use in their respective organisations. The implementation of Interpretive Structural Modelling (ISM) and Matriced' Impacts Croise's Multiplication Appliquée a UN Classement (MICMAC) provided a precise set of driving, linkage and dependent challenges that were used to formulate the framework.

The developed ISM framework is split into six different levels. The results suggest that the bottom level consists of challenges such as “Lack of standards (C9)” and “Lack of validation (C10)” form the foundation of the hierarchical structure of blockchain adoption. However, the topmost level consists of a highly dependent challenge termed “adoption of blockchain in the public sector (C16)”. The research filters the selected set of five challenges to develop a parsimonious model and formulated six propositions to examine the impact of “lack of standard (C9)”, “lack of validation (C10)” on “security issues (C3)” and “privacy concerns (C2)”, which eventually determine individuals' “reluctance to use blockchain technology (C12)”.

This research fills a key gap in exiting research by exploring the key challenges in blockchain adoption within the public sector by developing a valuable framework to model this important topic. To the best of our knowledge, this is the first paper to address these challenges and develop a parsimonious model for challenges of blockchain adoption in the public sector settings.

The rapid advancement of digital technologies has fundamentally changed the competitive dynamics of the logistics service industry and forced incumbent logistics service providers (LSPs) to digitalize. As many LSPs still struggle in advancing their digital transformation (DT), the purpose of this study is to discover barriers and identify organizational elements and associated leading practices for DT success at LSPs.

This study utilizes a two-stage approach. Stage 1 is devoted to a literature review. Stage 2, based on multiple case studies, analyzes information collected across nine international and global LSPs.

This research derives a practice-based definition of DT in the logistics service industry, and it has identified five barriers, eight success factors and associated leading practices for DT. The main obstacles LSPs struggle with, are the complexity of the logistics network and lack of resources, while the main success factor is a leader having and executing a DT vision, and creating a supportive organizational culture.

The results contribute to the emerging field of DT within the logistics and supply chain management literature and provide insights for practitioners regarding how to effectively implement it in a complex industry.

The authors analyze DT from the perspective of LSPs, traditionally not viewed as innovative companies. This study compares their DT with that of other companies.

Over the last 2 decades, supply chain sustainability research has become a highly dynamic and fruitful study area. This field has garnered significant attention due to its potential to reshape decision-making processes within supply chains. At the same time, the practical side of supply chain operations remains intensely competitive in today’s business landscape. Furthermore, the current academic research aims to outline effective strategies for achieving sustainability across supply chains, particularly in the manufacturing sector. In response to these challenges, this research has conducted an integrated multi-criteria decision-making approach to evaluate sustainable supply chain performance from the triple bottom line perspective, including financial, environmental, and social performance.

The initial stage involves selecting the crucial criteria (short-term and long-term) and alternatives for sustainable supply chain performance (SSCP) from experts and conducting an in-depth literature review. Initially, there were 17 criteria, but after a pilot test with co-authors and online discussions with experts, the number of criteria was subsequently reduced to 9. In the second phase, the Best-Worst Method (BWM) was applied to rank and prioritize the criteria. The third and final stage examined the causal relationship between the identified criteria, utilizing the Decision-Making Trial and Evaluation Laboratory (DEMATEL) technique.

Based on BWM analysis results, the top three criteria in terms of prominence are: (1) return on investment (ROI), (2) product quality, and (3) manufacturing lead time. Out of the three alternatives, financial performance (FP) is the most crucial dimension for SSCP, followed by environmental performance (ENP) and social performance (SP). On the other hand, the DEMATEL approach showed that work health and safety (short-term criterion), asset utilization (long-term criterion), energy consumption (long-term criterion), waste disposal (long-term criterion), manufacturing lead time (short-term criterion), and on-time delivery (short-term criterion) are categorized within the cause group, while criteria such as return on investment (ROI) (long-term criterion), customer-service level (short-term criterion), and product quality (long-term criterion) fall into the effect group.

The proposed study has certain drawbacks that pave the way for future research directions. First, it is worth noting the need for a larger sample size to ensure the reliability of results, the potential inclusion of additional criteria to enhance the assessment of sustainability performance, and the consideration of a qualitative approach to gain deeper insights into the outcomes. In addition, fuzziness in qualitative subjective perception could be imperative when collecting data to ensure its reliability, as translating experts’ perceptions into exact numerical values can be challenging because human perceptions often carry elements of uncertainty or vagueness. Therefore, fuzzy integrated MCDM frameworks are better suited for future research to handle the uncertainties involved in human perceptions, making it a more appropriate approach for decision-making in scenarios where traditional MCDM methods may prove insufficient.

The proposed framework will enable decision-makers to gain deeper insights into how various decision criteria impact SSCP, thus providing a comprehensive evaluation of SSCP that considers multiple dimensions, such as financial, environmental, and social performance within the manufacturing sector.

The proposed study is the first empirical study to integrate both BWM and DEMATEL approaches to evaluate sustainable supply chain performance in the manufacturing context.

The COVID-19 pandemic has impacted the construction industry, yet still, it is unclear from existing studies about the critical challenges imposed on quality assurance (QA), particularly Cross-border Construction Logistics and Supply Chain (Cb-CLSC). Thus, this study aims to identify and examine the critical challenges of QA of Cb-CLSC during the COVID-19 pandemic.

The aim is achieved via an embedded mixed-method approach pragmatically involving a desk literature review and engaging 150 experts across the globe using expert surveys, and results confirmed by semi-structured interviews. The approach is based on Interpretive Structural Modelling (ISM) as its foundation.

The study revealed ten critical challenges of QA, with the top four including “the shortage of raw construction material (C7)”, “design changes (C6)”, “collaboration and communication difficulties (C1)” and “changes in work practices (C10)”. However, examining the interrelationships among the critical challenges using ISM confirmed C7 and C10 as the most critical challenges. The study again revealed that the critical challenges are sensitive and capable of affecting themselves due to the nature of their interrelationship based on MICMAC analysis. Hence, being consistent with why all the challenges were considered critical amid the pandemic. Sentiment analysis revealed that the critical challenges have not been entirely negative but also positive by creating three areas of opportunities for improvement: technology adoption, worker management, and work process management. However, four areas of challenges in the QA include cost, raw material, time, and work process, including inspection, testing, auditing, communication, etc.

The finding provides a convenient point of reference to researchers, policymakers, practitioners, and decision-makers on formulating policies to enhance the effectiveness of construction QA during the pandemic through to the post-pandemic era.

The study enriches the extant literature on QA, Cb-CLSC, and the COVID-19 pandemic in the construction industry by identifying the critical challenges and examining the interrelationships among them. This provides a better understanding of how the construction QA has been affected by the pandemic and the opportunities created.