Search results

With the aid of naturalistic simulations, this paper aims to investigate human behavior during manual and autonomous driving modes in complex scenarios.

The simulation environment is established by integrating virtual reality interface with a micro-simulation model. In the simulation, the vehicle autonomy is developed by a framework that integrates artificial neural networks and genetic algorithms. Human-subject experiments are carried, and participants are asked to virtually sit in the developed autonomous vehicle (AV) that allows for both human driving and autopilot functions within a mixed traffic environment.

Not surprisingly, the inconsistency is identified between two driving modes, in which the AV’s driving maneuver causes the cognitive bias and makes participants feel unsafe. Even though only a shallow portion of the cases that the AV ended up with an accident during the testing stage, participants still frequently intervened during the AV operation. On a similar note, even though the statistical results reflect that the AV drives under perceived high-risk conditions, rarely an actual crash can happen. This suggests that the classic safety surrogate measurement, e.g. time-to-collision, may require adjustment for the mixed traffic flow.

Understanding the behavior of AVs and the behavioral difference between AVs and human drivers are important, where the developed platform is only the first effort to identify the critical scenarios where the AVs might fail to react.

This paper attempts to fill the existing research gap in preparing close-to-reality tools for AV experience and further understanding human behavior during high-level autonomous driving.

This work aims to systematically analyze the inconsistency in driving patterns between manual and autopilot modes in various driving scenarios (i.e. multiple scenes and various traffic conditions) to facilitate user acceptance of AV technology.

A close-to-reality tool for AV experience and AV-related behavioral study. A systematic analysis in relation to the inconsistency in driving patterns between manual and autonomous driving. A foundation for identifying the critical scenarios where the AVs might fail to react.

The new age of entrepreneurs recognizes crowdfunding as an innovative and effective means of obtaining funding from backers. However, attracting backers is challenging and related scholarly knowledge lacking. Therefore, this study investigates the diverse factors influencing backer funding intention in reward-based crowdfunding.

This study conducted an online survey of 401 registered backers from two reward-based crowdfunding platforms in Taiwan. Data were analyzed using covariance-based structural equation modeling.

Results show that entrepreneur activeness has a negative effect on perceived risk but positively, while entrepreneur activeness and platform interactivity have a positive effect on backer engagement and backer value creation. Although it had no significant impact on backer engagement, project novelty positively influenced backer value creation. Perceived risk had no influence on either backer engagement or backer value creation. Backer engagement positively influenced backer value creation and backer funding intention, with the former having a positive impact on the latter.

This study provides a multi-perceptual lens by proposing an integration of diverse factors such as entrepreneurial- (entrepreneur activeness), project- (project novelty and perceived risk) and platform-related characteristics (platform interactivity) as antecedents to backer funding intention. By integrating a service-dominant logic perspective into the stimulus-organism-response model, this study highlights the essence of value creation by perceiving backers as value co-creators.

The purpose of this paper is to propose a new three-node triangular element in the framework of the numerical manifold method (NMM), which is designated by Trig3-MLScns.

The formulation uses the improved parametric shape functions of classical triangular elements (Trig3-0) to construct the partition of unity (PU) and the moving least square (MLS) interpolation method to construct the local approximation function.

Compared with the classical three-node element (Trig3-0), the Trig3-MLScns element has a higher order of approximations, much better accuracy and continuous nodal stress. Moreover, the linear dependence problem associated with many PU-based methods with high-order approximations is eliminated in the present element. A number of numerical examples indicate the high accuracy and robustness of the Trig3-MLScns element.

The proposed element inherits the individual merits of the NMM and the MLS.

Eddy currents are inevitable in magnetic resonance imaging (MRI) systems. These currents are mainly induced by gradient fields. This study aims to propose a fast analytical method to calculate eddy currents induced by frequently switching gradient fields in a traditional C-shape MRI system.

Fourier decomposition and magnetic vector potentials were used to calculate the eddy currents. Calculations with the proposed analytical method revealed the spatial distribution and temporal evolution of eddy currents.

Calculation and Maxwell simulation results were consistent. The agreement between calculation and simulation results indicates that increasingly sophisticated structures could be developed. The calculated results could guide the design of improved gradient coils.

Eddy currents induced by gradient current are decomposed into currents induced by each time-harmonic component, and then adding them together to obtain complete contribution of the eddy current. The analytical method was used to characterize the properties of symmetric and asymmetric eddy currents induced by gradient coils in MRI systems. The analytical method can be used to improve the gradient shield during the design of the gradient coil in the MRI system.

The purpose of this paper is to investigate the factors that determine two forms of crowdfunding campaign success: success in securing the necessary financial resources and personal success in terms of the entrepreneur’s satisfaction. Specifically, it studies factors linked to the relationship between entrepreneurs and funders (co-creation and feedback) and factors linked to the campaign’s content (dimensions of corporate social responsibility (CSR)).

An empirical study of 52 crowdfunding entrepreneurs was conducted. Data were gathered using a structured questionnaire. Fuzzy-set qualitative comparative analysis was performed.

For financial and personal success, all factors, except the social dimension of CSR, are necessary conditions. Two configurations are sufficient for entrepreneurs to achieve financial success. The first configuration that is sufficient for personal success is the same as the first configuration for financial success. The second configuration for personal success is similar to the second configuration for financial success, except that it also includes financial success itself.

Entrepreneurs should invest in CSR and seek to improve the quality of their relationships with their funders. Crowdfunding platforms should design and manage co-creation and feedback tools that are capable of providing deep knowledge of users’ opinions and concerns whilst generating value. The limitations of this study are that only the reward-based crowdfunding model was considered, and the data covered just two platforms.

This study contributes to the literature by presenting empirical analysis of the factors that influence financial success and personal success in reward-based crowdfunding. It examines aspects that strictly refer to the content of the project and aspects that refer to the entrepreneur–funder relationship. Specifically, the roles of the four dimensions of CSR were considered. Moreover, the fsQCA method provides a fresh approach to research in this area.

The purpose of this paper is to design a qualitative model of crowdfunding dynamics through the document model building (DMB).

Methodology in this paper is the qualitative system dynamics through DMB. In DMB, the authors identify the variables that are drivers of its growth and collapse, and the model will be developed by using the systematic review of the literature.

Designing of the dynamics of crowdfunding model through DMB. Identifying variables that are drivers of crowdfunding growth and collapse. Determining leverage points in crowdfunding diffusion.

This paper, for the first time, with the aim of identifying and explaining the efficient positive and negative dynamics in this method, examines crowdfunding systematically and structurally.

Many European businesses are small and medium enterprises (SMEs), contributing significantly to the well-being of local economies and regions. Even so, SMEs face many challenges in fostering innovation and improving performance. Furthermore, the raw material consumption is increasing globally, necessitating the development of strategies that will reduce the number of raw materials extracted and imported while improving the sustainability of small and medium-sized businesses. Consequently, promoting circular economy (CE) strategies, such as industrial symbiosis (IS) partnerships, whereby waste products from other industries serve as a source of raw materials for companies, is critical. Identifying and analysing enablers or drivers that support IS collaborations among SMEs is necessary to achieve this goal. In this regard, the purpose of this study will explore the enablers of IS among SMEs considering sustainability dimensions (environmental, social and economic). As facing a decision-making (DM) problem, the multiple attribute decision-making (MADM) approach was applied in a hesitant fuzzy (HF) environment in this research to answer the research questions. In this regard, in phase 1, IS enablers were identified and extracted using a literature review and experts’ opinions. In phase 2, the hesitant fuzzy Delphi (HFD) method was implemented to screen and finalise the enablers identified. In phase 3, casual relations among final enablers were determined using the hesitant fuzzy ANP (HF-ANP) method. Finally, in phase 4, the relative importance of enablers was calculated using the hesitant fuzzy best–worst method (HF-BWM). Consequently, this study provided potential strategies for IS that can be implemented quickly and used by local authorities to support SMEs in achieving circular waste management.

Gradient coils designed by conventional target field methods usually have a complex physical structure and these methods are not convergent for complex routing area problems. This study aims to design a multi-coil (MC) gradient system arranged on a complex routing area including two cylindrical surfaces with different radii for a head magnetic resonance imaging scanner.

A MC system model is established. In this model, the sub-coils are evenly distributed on two cylindrical wiring surfaces, and the radii of coils are the same on one cylindrical surface. With the target magnetic field set, the currents in every individual coil are solved by constrained least-squares fitting based on the Levenberg–Marquardt method.

The magnetic field nonlinearity generated by designed coils is validated as 4.50% and 3.57% for X-gradient coil and Z-gradient coil, respectively, which satisfy the mainstream nonlinearity standards. The analysis of the optimization results indicates that hardware requirements can be considerably reduced by connecting coils with the same currents in series.

High-linearity gradient magnetic fields are generated on complex routing areas by adopting the MC structure. In addition, the requirements for current sources and amplifiers are considerably reduced.

The purpose of this paper is to construct a price index for Chinese oil paintings and analyze the financial performance of investing in Chinese oil paintings and its potential for portfolio diversification in Chinese financial markets.

A hedonic regression model is applied to construct a semiannual price index for Chinese oil paintings from 2000 to 2014. The CAPM model, downside β and standard portfolio optimization are used for analyzing portfolio diversification.

The hedonic regression shows that the majority of hedonic variables, such as dimension, artist’s reputation, living status, medium and auction houses, are statistically significant in estimation. Not only the return from oil painting investments is higher than other equities, but also the β coefficient of the CAPM model and downside β indicate that Chinese oil painting may be a good hedging instrument against stock market risk. Furthermore, the portfolio optimizations under standard assumptions suggest that oil paintings as an alternative investment provide diversification benefit.

This paper provides a new and comprehensive analysis of characteristics and risks of investing in the Chinese oil paintings.