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By market capitalisation, Bitcoin, which debuted in 2009, is the biggest cryptocurrency globally. A decentralised ledger system called blockchain is used in the creation, distribution, trading, and storage of Bitcoin, with the original goal being to address the shortcomings of fiat currency. This chapter highlights potential dangers and legal concerns when Bitcoin interacts with the actual economy and the traditional financial system. Besides, the details also discuss the platform’s design principles and attributes for a non-technical readership. When assessing its transactional potential, some recognise its potential for speculation, while others are doubtful of its admirable intent. The write-up also explores the potential of the adoption of cryptocurrencies in Southeast Asia due to the vast adoption of Bitcoins in countries such as Vietnam and the Philippines following the establishment of cryptocurrency technology and e-commerce. In addition, rankings of the cryptocurrency and legal stance from each country in Southeast Asia were exhibited as the solid foundation of cryptocurrencies existent for transaction purposes. The rise of central bank digital currencies (CBDC) and the future directions of Bitcoins were also highlighted in this write-up to spur the debate on whether cryptocurrency remains a fad of sensation or is legalised as the medium of exchange in an ever-growing digital world of commerce.

Government bonds are debt securities issued by the central government, where investors are to receive returns in the form of an annual coupon rate periodically. This leads investors tend to hold their portfolio after purchasing due to the guaranteed returns of the government bonds. However, another strategy for gaining returns is to sell the eligible portfolios in the secondary market. This research aims to investigate the factors behind investors’ decisions whether to sell their government retail bonds portfolio and the length of their portfolio hold days. Towards a secondary dataset of existing government retail bonds investors in Indonesia and secondary market rate, logistic regression analysis was employed to inspect their selling decisions, while the decision tree classification method investigated their hold days. Results show that both the decision to sell bonds portfolio in the secondary market and the period of hold days are highly affected by its comparative return performance towards other investment alternatives, represented by excess returns. This study contributes to the behavioural finance field by answering the lack of investigation for investors’ selling decisions, particularly for government retail bonds, which will enhance the understanding of portfolio rebalancing in portfolio management studies.

The aging and deterioration of engineering building structures present significant risks to both life and property. Fiber Bragg grating (FBG) sensors, acclaimed for their outstanding reusability, compact form factor, lightweight construction, heightened sensitivity, immunity to electromagnetic interference and exceptional precision, are increasingly being adopted for structural health monitoring in engineering buildings. This research paper aims to evaluate the current challenges faced by FBG sensors in the engineering building industry. It also anticipates future advancements and trends in their development within this field.

This study centers on five pivotal sectors within the field of structural engineering: bridges, tunnels, pipelines, highways and housing construction. The research delves into the challenges encountered and synthesizes the prospective advancements in each of these areas.

The exceptional performance of FBG sensors provides an ideal solution for comprehensive monitoring of potential structural damages, deformations and settlements in engineering buildings. However, FBG sensors are challenged by issues such as limited monitoring accuracy, underdeveloped packaging techniques, intricate and time-intensive embedding processes, low survival rates and an indeterminate lifespan.

This introduces an entirely novel perspective. Addressing the current limitations of FBG sensors, this paper envisions their future evolution. FBG sensors are anticipated to advance into sophisticated multi-layer fiber optic sensing networks, each layer encompassing numerous channels. Data integration technologies will consolidate the acquired information, while big data analytics will identify intricate correlations within the datasets. Concurrently, the combination of finite element modeling and neural networks will enable a comprehensive simulation of the adaptability and longevity of FBG sensors in their operational environments.

This paper summarizes and synthesizes existing research while critically assessing findings for future studies to advance the scholarship of maritime logistics and digital transformation with big data.

A bibliometric analysis was conducted on 159 journal articles from the Scopus database with search keywords “maritime*” and “big data.” This analysis helps identify research gaps by identifying themes via keyword co-occurrence, co-citation and bibliographic coupling analysis. The Theory-Context-Characteristics-Methodology (TCCM) framework was applied to understand the findings of bibliometric analysis and provide a research agenda.

The analyses identified emerging themes of the scholarship of maritime logistics and digital transformation with big data and their relationships to identify research clusters. Future research directions were provided by examining existing research's theory, context, characteristics and method.

This research is grounded in bibliometric analysis and the TCCM framework to understand the scholarly evolution, giving managers and academics retrospective and prospective insights.

This study aims to characterize the lubrication condition under sliding-rolling contact using three indicators, including the oil film thickness and two perpendicular (vertical and tangential) vibrations. The lubrication deterioration can then be detected when sliding occurs in rolling contact.

An experimental study is presented to identify the lubrication deterioration under sliding-rolling contact. Sliding-rolling experiments with controlled loads, slip ratios and speeds are carried out on a roller-ring test rig. The deterioration of lubrication condition is analyzed by the transient oil film thickness and two perpendicular vibration signals, respectively.

The oil film thickness and the vibration signal play different roles in characterizing different lubrication deterioration conditions. Specifically, the degree of lubrication deterioration with slight solid-contact is indicated by the rapid reduction in oil film thickness. The degree of lubrication deterioration with severe solid-contact is reflected by two perpendicular (vertical and tangential) vibrations. Furthermore, the tangential vibration can indicate the occurrence of sliding in rolling contact.

A full characterization of the lubrication deterioration under sliding-rolling contact can be accomplished by integrating both the oil film thickness and two perpendicular vibration monitoring.

The peer review history for this article is available at: https://publons.com/publon/10.1108/ILT-07-2024-0244/

In recent years, the frequency of emergencies, such as natural disasters and public health crises, has markedly increased globally. These occurrences have introduced new challenges to national public security systems and emergency management capabilities. Post-disaster humanitarian logistic operations involve the collection of emergency relief resources to mitigate the impact of disasters in affected areas. Effective coordination among governments, enterprises and charities is essential to enhance the efficiency of these operations. This study employs evolutionary game theory to explore the strategic interactions and behavioral patterns among these key stakeholders during the collection of emergency materials.

A tripartite evolutionary game model involving governments, enterprises and charities is developed. Subsequently, to validate the theoretical findings, a scale-free network is constructed for the purpose of numerical simulations. As this network evolves, both the edges between nodes and the strategy choices of the nodes also change. Numerical simulations are conducted using the network to examine the sensitivity of factors influencing strategic choices among game stakeholders.

According to the model simulation results, penalties significantly influence government regulation strength, while enterprise philanthropic behavior is mainly affected by penalties, profit transfer benefits and trust loss. For charities, strategic choices are primarily driven by penalties, tax subsidies, illegal operation benefits and charitable costs. The findings provide a theoretical basis for governments, enterprises and charities to select the sensible strategy.

Our study establishes a dynamic network of edges and nodes evolving over time to analyze the strategic evolutionary paths of governments, enterprises and charities from a micro perspective. The results assist governments, enterprises and charities in making more strategic decisions.

The purpose of this paper is to present the design and implementation of a genetic algorithm (GA), using a large language model (LLM) for optimizing the delivery scheduling process in warehouses of third-party logistics (3PL) companies, within the context of a simplified case study, and to highlight the main directions for implementing this methodology in business realities.

Using a simplified case study of an international 3PL company, this study applies a GA developed in RStudio by LLM to generate test scenarios and input data. The GA was optimized to minimize the time and distance of movement in the process of preparing goods for shipment, demonstrating its effectiveness in improving warehouse delivery scheduling.

The study confirms that the GA, supported by LLM, significantly improves the delivery planning process in the warehouse. Specifically, the implementation of the GA led to notable improvements in scheduling efficiency and a reduction in the distance traveled within the warehouse. These enhancements enable more efficient generation, evaluation and optimization of logistic scenarios. Additionally, the use of LLM greatly facilitates the creation and refinement of complex algorithms like GA, through automation and innovative approaches in logistics.

The study highlights limitations related to data quality, the dynamic nature of logistic operations, computational complexity and the need for generalization of results. It also points out the lack of research in business realities that demonstrate the effectiveness of combining the benefits of LLM and GA in practice.

This paper makes a significant contribution to the literature by demonstrating the capabilities of advanced technologies such as GA and LLM in 3PL logistics. It presents an innovative approach to optimizing logistic processes, offering perspectives for further innovations and automation in supply chain management. It also indicates new opportunities for 3PL companies in terms of improving operational and cost efficiency, emphasizing the importance of continuously seeking innovative solutions in the face of increasing market demands.

This study aims to address the lack of discrimination between fully efficient decision-making units in nonparametric efficiency analysis models by introducing a new ranking technique that incorporates contextual variables.

The proposed method combines Data Envelopment Analysis (DEA) and Ordinary Least Squares (OLS). First, DEA evaluates the partial efficiency of each unit, considering all inputs and only one output. Next, OLS removes the influence of contextual variables on the partial efficiencies. Finally, a ranking criterion based on modified partial efficiencies is formulated. The method is applied to data from 100 Chinese banks, including state-owned, commercial and industrial institutions, for the year 2020.

The ranking results show that the top six positions are assigned to highly esteemed banks in China, demonstrating strong alignment with real-world performance. The method provides a comprehensive ranking of all units, including nonextreme efficient ones, without excluding any. It resolves infeasibility issues that arise during the ranking of efficient units and ensures uniqueness in efficiency scores, leading to a more reliable and robust ranking process. Contextual variables exerted a greater influence on the first partial efficiency compared to the second. Notably, Total Capital Adequacy (TCA) significantly impact bank efficiency.

This study introduces a novel ranking method that effectively integrates contextual variables into DEA-based efficiency analysis, addressing limitations of existing methods. The practical application to Chinese banks demonstrates its utility and relevance.

This study aims to synthesize Prussian blue {Fe^III₄[Fe^II(CN)₆]₃} pigment by reacting ferric chloride with different ferrocyanides through the same procedure. The influence of the ferrocyanide used on resulting pigment properties is studied.

Prussian blue is commonly synthesized by direct or indirect methods, through iron salt and ferrocyanide/ferricyanide reactions. In this study, the direct, single-step process was pursued by dropwise addition of the ferrocyanide into ferric chloride (both as aqueous solutions). Two batches – (K-PB) and (Na-PB) – were prepared by using potassium ferrocyanide and sodium ferrocyanide, respectively. The development of pigment was confirmed by an identification test and characterized by spectroscopic techniques. Pigment properties were determined, and light fastness was observed for acrylic emulsion films incorporating dispersed pigment.

The two pigments differed mainly in elemental detection owing to the dissimilar ferrocyanide being used; IR spectroscopy where only (Na-PB) showed peaks indicating water molecules; and bleeding tendency where (K-PB) was water soluble whereas (Na-PB) was not. The pigment exhibited remarkable blue colour and good bleeding resistance in several solvents and showed no fading in 24 h of light exposure though oil absorption values were high.

This article is a comparative study of Prussian blue pigment properties obtained using different ferrocyanides. The dissimilarity in the extent of water solubility will influence potential applications as a colourant in paints and inks. K-PB would be advantageous in aqueous formulations to confer a blue colour without any dispersing aid but unfavourable in systems where other coats are water-based due to their bleeding tendency.

The present study aims to examine the households’ attitudes and intentions to adopt an indoor air purifier against the smog crisis in India by using a comprehensive theoretical framework based on the combination of the Protective Action Decision Model (PADM) and the Theory of Planned Behavior (TPB). The United Nations Sustainable Development Goals (SDGs) 2030 also emphasized ensuring a healthy and safe life, especially by achieving SDG-3, SDG-11 and SDG-13.

Using purposive sampling, the data were collected through a survey questionnaire distributed to 382 households, and study hypotheses were assessed by using partial least squares structural equation modeling employing SmartPLS.

The results revealed that mental health risk perception (MHRP) was the most influential determinant of households’ attitudes toward adopting air purifiers, followed by smog knowledge, physical health risk perception (PHRP), information seeking and product knowledge. Notably, results revealed that households’ attitude is a leading determinant of their adoption intention toward the air purifier compared to subjective norms (SN) and perceived behavioral control (PBC).

To the best of the authors’ knowledge, the present study is the first to provide new insights into an individual’s protective behavior response toward ecological hazards by examining the households’ adoption intention toward the air purifier against the smog crisis using PADM and TPB model inclusively. In addition, the present study analyzes the impact of both PHRP and MHRP on individuals’ protective behavior separately. Also, this study provides theoretical contributions and important practical implications for the government, manufacturers and air purifier sellers.