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Metropolitan areas suffer from frequent road traffic congestion not only during peak hours but also during off-peak periods. Different machine learning methods have been used in travel time prediction, however, such machine learning methods practically face the problem of overfitting. Tree-based ensembles have been applied in various prediction fields, and such approaches usually produce high prediction accuracy by aggregating and averaging individual decision trees. The inherent advantages of these approaches not only get better prediction results but also have a good bias-variance trade-off which can help to avoid overfitting. However, the reality is that the application of tree-based integration algorithms in traffic prediction is still limited. This study aims to improve the accuracy and interpretability of the models by using random forest (RF) to analyze and model the travel time on freeways.

As the traffic conditions often greatly change, the prediction results are often unsatisfactory. To improve the accuracy of short-term travel time prediction in the freeway network, a practically feasible and computationally efficient RF prediction method for real-world freeways by using probe traffic data was generated. In addition, the variables’ relative importance was ranked, which provides an investigation platform to gain a better understanding of how different contributing factors might affect travel time on freeways.

The parameters of the RF model were estimated by using the training sample set. After the parameter tuning process was completed, the proposed RF model was developed. The features’ relative importance showed that the variables (travel time 15 min before) and time of day (TOD) contribute the most to the predicted travel time result. The model performance was also evaluated and compared against the extreme gradient boosting method and the results indicated that the RF always produces more accurate travel time predictions.

This research developed an RF method to predict the freeway travel time by using the probe vehicle-based traffic data and weather data. Detailed information about the input variables and data pre-processing were presented. To measure the effectiveness of proposed travel time prediction algorithms, the mean absolute percentage errors were computed for different observation segments combined with different prediction horizons ranging from 15 to 60 min.

Are financially illiterate individuals all the same? This study aims to answer this question. Specifically, the authors investigate whether people answering incorrectly and “do not know” to the big five questions about financial knowledge (FK), all identified by previous literature as financially illiterate, are two sides of the same coin, or rather individuals with different socio-economic and demographic characteristics, and whether this leads to different levels of risk of falling victim to financial fraud.

Using a large and representative sample of Italian adults, the authors run both ordered probit and probit regressions to test the determinants of financially illiterate individuals, distinguishing between those answering FK questions incorrectly and those answering “do not know”. The authors also measure the probability of falling victim to financial fraud for the two groups. To check the robustness of our results, the authors run a multinomial regression, a structural equation model and an instrumental variable regression model.

The authors demonstrate that the socio-demographic and socio-economic characteristics of individuals selecting incorrect responses to FK questions are different from those of individuals selecting the “do not know” option. Moreover, the results show that the former are more likely to be victims of financial frauds.

The “one-size-fits-all” approach is not suitable for financial education. It is important to consider socio-demographic and socio-economic characteristics of individuals in order to identify specific targets of education programmes aiming to reduce insecurity and excessive self-confidence as well as to increase objective FK. The study’s findings also identify vulnerable groups to which financial fraud prevention schemes should be targeted.

To date, financial illiteracy has been measured as the sum of incorrect and “do not know” responses given to FK questions. This approach does not allow to observe the socio-demographic and socio-economic differences between people choosing the “do not know” option and those answering incorrectly. The paper aims to overcome this limit by investigating the socio-demographic and socio-economic characteristics of individuals selecting “do not know” and incorrect responses, respectively. The authors also investigate whether the two groups have different probabilities of being victims of financial fraud.

The bridge expansion joint (BEJ) is a key device for accommodating spatial displacement at the beam end, and for providing vertical support for running trains passing over the gap between the main bridge and the approach bridge. For long-span railway bridges, it must also be coordinated with rail expansion joint (REJ), which is necessary to accommodate the expansion and contraction of, and reducing longitudinal stress in, the rails. The main aim of this study is to present analysis of recent developments in the research and application of BEJs in high-speed railway (HSR) long-span bridges in China, and to propose a performance-based integral design method for BEJs used with REJs, from both theoretical and engineering perspectives.

The study first presents a summary on the application and maintenance of BEJs in HSR long-span bridges in China representing an overview of their state of development. Results of a survey of typical BEJ faults were analyzed, and field testing was conducted on a railway cable-stayed bridge in order to obtain information on the major mechanical characteristics of its BEJ under train load. Based on the above, a performance-based integral design method for BEJs with maximum expansion range 1600 mm (±800 mm), was proposed, covering all stages from overall conceptual design to consideration of detailed structural design issues. The performance of the novel BEJ design thus derived was then verified via theoretical analysis under different scenarios, full-scale model testing, and field testing and commissioning.

Two major types of BEJs, deck-type and through-type, are used in HSR long-span bridges in China. Typical BEJ faults were found to mainly include skewness of steel sleepers at the bridge gap, abnormally large longitudinal frictional resistance, and flexural deformation of the scissor mechanisms. These faults influence BEJ functioning, and thus adversely affect track quality and train running performance at the beam end. Due to their simple and integral structure, deck-type BEJs with expansion range 1200 mm (± 600 mm) or less have been favored as a solution offering improved operational conditions, and have emerged as a standard design. However, when the expansion range exceeds the above-mentioned value, special design work becomes necessary. Therefore, based on engineering practice, a performance-based integral design method for BEJs used with REJs was proposed, taking into account four major categories of performance requirements, i.e., mechanical characteristics, train running quality, durability and insulation performance. Overall BEJ design must mainly consider component strength and the overall stiffness of BEJ; the latter factor in particular has a decisive influence on train running performance at the beam end. Detailed BEJ structural design must stress minimization of the frictional resistance of its sliding surface. The static and dynamic performance of the newly-designed BEJ with expansion range 1600 mm have been confirmed to be satisfactory, via numerical simulation, full-scale model testing, and field testing and commissioning.

This research provides a broad overview of the status of BEJs with large expansion range in HSR long-span bridges in China, along with novel insights into their design.

This study aims to introduce the achievements and benefits of applying wheel/rail-force–based maintenance interval extension of the C80 series wagon in China.

Chinese wagons' existing maintenance strategy had left a certain safety margin for the characteristics of widely running range, unstable service environment and submission to transportation organization requirements. To reduce maintenance costs, China railway (CR) has attempted to extend the maintenance interval since 2020. The maintenance cycle of C80 series heavy haul wagons is extended by three months (no stable routing) or 50,000 km (regular routing). However, in the meantime, the alarming rate of the running state, a key index to reflect the severe degree of hunting stability, by the train performance detection system (TPDS) for the C80 series heavy haul wagons has increased significantly.

The present paper addresses a big data statistical way to evaluate the risk of allowing the C80 series heavy haul wagons to remain in operation longer than stipulated by the maintenance interval initial set. Through the maintenance and wayside-detector data, which is divided into three stages, the extension period (three months), the current maintenance period and the previous maintenance period, this method reveals the alarming rate of hunting was correlated with maintenance interval. The maintainability of wagons will be achieved by utilizing wagon performance degradation modeling with the state of the wheelset and the often-contact side bearing. This paper also proposes a statistical model to return to the average safety level of the previous maintenance period's baseline through correct alarming thresholds for unplanned corrective maintenance.

The paper proposes an approach to reduce safety risk due to maintenance interval extension by effective maintenance program. The results are expected to help the railway company make the optimal solution to balance safety and the economy.

This paper sets out to corroborate the existing literature on investors' risk tolerance and to assess how the 2008 financial crisis has affected risk tolerance among Italian investors.

Based on a unique dataset of real-world portfolio choices made by 1,245 Italian investors over a period of 15 years (from 2003 to 2017), this paper presents two steps of analysis. In step 1, the whole period 2003–2017 is considered with the aim to integrate and corroborate the existing literature on the topic of risk tolerance, considering a complete economic and financial cycle. Step 2 took 2008 as the pivotal point between pre-crisis (2003–2008) and crisis (2009–2017) with the aim to observe the influence on risk appetite of the economic and financial effects of the crisis.

The results obtained confirm that men are more risk tolerant than women and older people are less risk-taking than their younger counterparts, although the relationship between age and risk tolerance is not necessarily linear. Moreover, our paper demonstrates that a crisis scenario has an influence on Italian investors' risk tolerance.

Our results are of interest to financial advisors, financial planners, asset managers, psychologists, behavioral researchers and more in general to providers of financial products and services.

The results presented in this paper are relevant and original because they are based on real investors who made real choices concerning their portfolio asset allocations.

Ride comfort is one of the important factors affecting passenger health. Therefore, the elevator industry usually uses the International Organization for Standardization (ISO) 18738-1 standard to evaluate elevator ride quality and optimize elevator design. However, this method has certain limitations in its evaluation of comfort due to the problem of boundary division. The ISO 2631-4 standard is used as a general method of comfort evaluation in the current rail transit system, but it has not been applied in the elevator industry. In order to explore the difference and connection between the two standards, the author aims to conduct a detailed analysis on this.

Based on the elevator internet, a large amount of measured data of normal and abnormal vibration of elevator car were collected and analyzed and preprocessed; based on ISO 18738-1:2012 standard and ISO 2631-4:2001 standard, the differences of ride comfort assessment methods in the two standards were analyzed, and the ride comfort assessment study of elevator under normal and abnormal vibration conditions was carried out.

The experimental results show that the comfort assessment results of ISO 2631-4:2001 standard and ISO18738-1:2012 standard are consistent under two vibration conditions. At the same time, ISO 2631-4:2001 can not only provide a more accurate quantitative description of comfort, but also roughly determine the comfort interval of each vibration, which can provide theoretical reference for elevator vibration classification and car comfort design.

The authors designed an Internet of Things (IOT)-based elevator vibration signal acquisition method to address the shortcomings of the previous elevator ride comfort assessment methods, which can realize the dynamic assessment of elevator ride comfort; by comparing the assessment results of elevator ride comfort under normal vibration and abnormal vibration, the feasibility of ISO 2631-4:2001 for elevator ride comfort assessment was fully verified. In addition, the experimental results also give the influence of abnormal vibration on elevator riding comfort under the stages of start-stop, uniform speed, acceleration and deceleration, which can provide theoretical support for elevator vibration suppression and comfort transformation.

The application of smart contract can greatly reduce transaction costs and improve transaction efficiency. The existing smart contract are expensive, single application scenario and inefficient. This paper aims to propose a new smart contract model to solve these problems.

By investigating the research history, models and platforms, this paper summarizes the shortcomings of existing smart contracts. Based on the content and architecture of traditional contract, a smart contract model with wider application scope is designed.

In this paper, several models are used to describe the operation mechanism of smart contracts. To facilitate computer execution, a decomposition method is proposed, which divides smart contracts into several sub-contracts. Then, the advantages and deployment methods of smart contract are discussed. On this basis, a specific example is given to illustrate how the application of smart contract will change our life.

Smart contract is gradually applied to more fields. In this paper, the structure and operation mechanism of smart contract system in reality are given, which will be beneficial to the application of smart contract to more complex systems.

The paper is to explore crowdfunding success determinants from the reward menu design aspect, distinguishing from extant studies focusing on characteristics of project creators or crowdfunding projects and funding dynamics. Both the number of reward options and price differentiation of rewards are considered.

The authors use the quadratic model to identify a curvilinear relationship between the number of reward options and crowdfunding success, by running regressions on data collected from one of the most influential reward-based crowdfunding platforms in China. In addition, they explore the moderating effect of price differentiation on the curvilinear relationship.

The authors find an inverted U-shape relationship between the number of reward options and the optimal number of options is around 10. In addition, they find that the curvilinear relationship is moderated by reward price differentiation.

This paper has managerial implications for crowdfunding project creators and platform managers. To achieve better crowdfunding outcomes, a proper number of reward options with diversified reward prices should be provided.

The paper contributes to the literatures in antecedents of crowdfunding success from reward menu design aspect based on theories in investment and purchasing decision making. It is different from existing studies focusing on the characteristics of project creators and crowdfunding projects or funding dynamics. It also parallels retirement contribution plan design studies by exploring the reward menu design in the crowdfunding context.

Homestay is an alternative product to mass tourism where tourists are accommodated with local family allowing the tourist to learn local culture and lifestyle. The changing tourists' preferences influence the phenomenon of this accommodation trend for unique experiences, increasing competition in the market, and the rapid development in communication technology. This paper aims to observe the current state of the homestay situation in Brunei. This research utilized qualitative in-depth semi-structured interviews with a total sample of 23 respondents consisting of homestay operators, local community and tourism officers. The findings are that homestay in Brunei experienced issues with licensing and standards due to unending bureaucracy and unclear instructions, an elusive search of successors for long-term sustainability, and issues on participatory management within the community. This paper contributes valuable insights to developing strategies for the sustainability of homestay tourism, particularly for the stakeholders involved, such as homestay operators, policymakers and tourism practitioners.

This paper aims to study the influence of aerodynamics force of trains passing each other on the dynamic response of vehicle bridge coupling system based on numerical simulation and multi-body dynamics and put forward the speed threshold for safe running of train under different crosswind speeds.

The computational fluid dynamics method is adopted to simulate the aerodynamic force in the whole process of train passing each other by using dynamic grid technology. The dynamic model of vehicle-bridge coupling system is established considering the effects of aerodynamic force of train passing each other under crosswind, the dynamic response of train intersection on the bridge under crosswind is computed and the running safety of the train is evaluated.

The aerodynamic force of trains' intersection has little effects on the derailment factor, lateral wheel-rail force and vertical acceleration of train, but it increases the offload factor of train and significantly increases the lateral acceleration of train. The crosswind has a significant effect on increasing the derailment factor, lateral wheel-rail force and offload factor of train. The offload factor of train is the key factor to control the threshold of train speed. The impact of the aerodynamic force of trains' intersection on running safety cannot be ignored. When the extreme values of crosswind wind speed are 15 m·s⁻¹, 20 m·s⁻¹ and 25 m·s⁻¹, respectively, the corresponding speed thresholds for safe running of train are 350 km·h⁻¹, 275 km·h⁻¹ and 200 km·h⁻¹, respectively.

The research can provide a more precise numerical method to study the running safety of high-speed trains under the aerodynamic effect of trains passing each other on bridge in crosswind.