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This study aims to investigate the safety and liability of autonomous vehicles (AVs), and identify the contributing factors quantitatively so as to provide potential insights on safety and liability of AVs.

The actual crash data were obtained from California DMV and Sohu websites involved in collisions of AVs from 2015 to 2021 with 210 observations. The Bayesian random parameter ordered probit model was proposed to reflect the safety and liability of AVs, respectively, as well as accommodating the heterogeneity issue simultaneously.

The findings show that day, location and crash type were significant factors of injury severity while location and crash reason were significant influencing the liability.

The results provide meaningful countermeasures to support the policymakers or practitioners making strategies or regulations about AV safety and liability.

This paper aims to investigate the impact of day trading on market quality on the Taiwan stock market with the implementation of a unique policy change. This paper examines 396 listed stocks from June 2015 to October 2016, a period when the stock market in Taiwan officially approved selected stocks for day trading for all investors. Within the sample period, the empirical findings show that day trading increases the bid–ask spread, price depth and stock volatility, indicating that day trading activities not only cause higher transaction costs and trading risk but also raise the market’s ability to absorb price impact. This paper considers two-stage regression and tests the exogenous shock because of further relaxation for day trading to deal with the possible endogenous problem and the main findings remain consistent. Since early 2014, the Taiwan stock market has been experiencing a distinct growth in trading volume after unwinding the day trading; however, the results show that the impacts of stock day trading on market quality are not all positive.

The purpose of this study is to examine the effects of nitrogen (N) deposition on clonal growth in a rhizome clonal plant, Leymus chinensis (Trin.) Tzvel.

The study established seven N concentration gradients (0, 2, 4, 8, 16, 32 and 64 g N m⁻²) to simulate the continuous increase in N deposition for the cultivation of L. chinensis seedlings and assess the response mechanism of the cloned L. chinensis plant at different N levels by analyzing the aboveground and belowground plant appearance traits, parent ramets and daughter ramets of resource allocation and biomass allocation.

The results of this study showed that the different N treatment levels could promote clonal growth and had certain regularity under the seven treatments. The addition of N could significantly increase the ramet number, rhizome length, rhizome spacer length, biomass of mother ramets, daughter ramets and belowground L. chinensis population when the N addition was greater than 4 g m⁻²; however, the clonal growth ability of L. chinensis decreased and the rhizome length, ramet number, stem and leaf biomass of daughter ramets and stem biomass of mother ramets significantly decreased when the N addition was greater than 32 g N m⁻².

With global warming, atmospheric N deposition is increasing and it is of great significance to explore the response mechanism of different N levels for the growth of clone plants. This study provides basic data and a theoretical basis for the survival prediction of cloned plants under the background of a global climate change strategy and has important theoretical and practical significance for the scientific management of grasslands in the future.

This study explored the students' perception of their adoption and acceptance of virtual learning (VL), the factors affecting the adoption of educational technologies and the correlation between their intention, perceived behavioral control and care competence in caring for older adults.

A cross-sectional survey was conducted. Surveys were administered to evaluate the participants who were involved in VL on geriatric care during coronavirus disease 2019 (COVID-19) pandemic. A total of 315 nursing students participated in the survey, and 287 valid questionnaires were collected (response rate: 91.11%).

A total of 287 participants (mean age 21.09, SD 1.44 years; 242/287, 84.3% female) were included in the study. The variables of intention to use technologies were positively correlated with care competence (r = 0.59, p < 0.001). The results revealed that the major predictors were perceived ease-of-use (PEOU) (β = 0.28, 95% confidence interval (CI) 0.16–0.40) and perceived usefulness (PU) (β = 0.22, CI 0.09–0.35) which were significantly positive predictors of competence in geriatric care.

Nursing students lack in clinical knowledge and situational experience in geriatric care; therefore, their perceptiveness, expressions and reflection on the process of providing care to hospitalized older patients should be increased. These results indicated that students improved in geriatric healthcare after/during the VL program during COVID-19 pandemic.

It is hoped that the present study would make an invaluable contribution to existing research on education in general and on the quality of care in geriatric nursing as limited studies have been published so far.

In this paper the interconnectedness among financial institutions and the level of systemic risks of four types of Chinese financial institutions are investigated.

By the means of RAS algorithm, the interconnection among financial institutions are illustrated. Different methods, including Linear Granger, Systemic impact index (SII), vulnerability index (VI), CoVaR, and MES are used to measure the systemic risk exposures across different institutions.

The results illustrate that big banks are more interconnected and hold the biggest scales of inter-bank transactions in the financial network. The institutions which have larger size tend to have more connection with others. Insurance and security companies contribute more to the systemic risk where as other institutions, such as trusts, financial companies, etc. may bring about severe loss and endanger the financial system as a whole.

Since other institutions with low levels of regulation may bring about higher extreme loss and suffer the whole system, it deserves more attention by regulators considering the contagion of potential risks in the financial system.

This study builds a valuable contribution by examine the systemic risks from the perspectives of both interconnection and tail risk measures. Furthermore; Four types financial institutions are investigated in this paper.

This paper aims to investigate the quality of printed surfaces and manufacturing tolerances by comparing the cylindrical cavities machined in parts obtained by fused deposition modeling (FDM) with the holes manufactured during the printing process itself. The comparison focuses on the results of roughness and tolerances, intending to obtain practical references when making assemblies.

The experimental approach focuses on the comparison of the results of roughness and tolerances of two manufacturing strategies: geometric volumes with a through-hole and the through-hole machined in volumes that were initially printed without the hole. Throughout the study, both alternates are explained to make appropriate recommendations.

The study shows the best combinations of technological parameters, both machining and three-dimensional printing, which have been decisive for obtaining successful results. These conclusive results allow enunciating recommendations for use in the industrial environment.

This paper fulfills an identified need to study the dimensional accuracy of the geometries obtained by additive manufacturing, as no experimental evidence has been found of studies that directly address the problem of the FDM-printed part with geometric and dimensional tolerances and desirable surface quality for assembly.

The type 120 emergency valve is an essential braking component of railway freight trains, but corresponding diaphragms consisting of natural rubber (NR) and chloroprene rubber (CR) exhibit insufficient aging resistance and low-temperature resistance, respectively. In order to develop type 120 emergency valve rubber diaphragms with long-life and high-performance, low-temperatureresistant CR and NR were processed.

The physical properties of the low-temperature-resistant CR and NR were tested by low-temperature stretching, dynamic mechanical analysis, differential scanning calorimetry and thermogravimetric analysis. Single-valve and single-vehicle tests of type 120 emergency valves were carried out for emergency diaphragms consisting of NR and CR.

The low-temperature-resistant CR and NR exhibited excellent physical properties. The elasticity and low-temperature resistance of NR were superior to those of CR, whereas the mechanical properties of the two rubbers were similar in the temperature range of 0 °C–150 °C. The NR and CR emergency diaphragms met the requirements of the single-valve test. In the low-temperature single-vehicle test, only the low-temperature sensitivity test of the NR emergency diaphragm met the requirements.

The innovation of this study is that it provides valuable data and experience for future development of type 120 valve rubber diaphragms.

This paper examines the impact of corporate digital transformation on employee satisfaction. Therefore, this study extends our understanding of the economic consequences of corporate digital transformation from employees’ perspectives.

The data used to construct our main proxy of employee satisfaction are collected from Kanzhun.com, which provides reviews by rank-and-file employees on their employers. This study uses a large sample of Chinese firms and adopts various empirical methods to examine the impact of digital transformation on employee satisfaction.

We find a significant positive relationship between corporate digital transformation and employee satisfaction. Moreover, we document that the relationship between corporate digital transformation and employee satisfaction is more pronounced in firms with higher labor intensity and in state-owned enterprises (SOE).

One significant limitation is that corporate digital transformation is constructed based on word frequency analysis. This approach may be influenced by variations in corporate disclosure practices and might not accurately capture the true extent of corporate digital transformation. This limitation is not only present in our research but is also pervasive in many other studies that utilize similar methodologies. Therefore, our results should be interpreted with this caveat in mind.

Our study suggests that corporate digital transformation enhances employee satisfaction, providing direct evidence for managers and regulators to promote corporate digital transformation. Through digital transformation, companies can not only improve operational efficiency but also foster employee satisfaction. This dual benefit underscores the importance of investing in corporate digital transformation for long-term success.

Our study suggests that corporate digital transformation enhances employee satisfaction, providing direct evidence for managers and regulators to promote corporate digital transformation. Through digital transformation, companies can not only improve operational efficiency but also foster employee satisfaction. This dual benefit underscores the importance of investing in corporate digital transformation for long-term success.

Our study contributes to the literature on the economic consequences of corporate digital transformation and extends existing research on the determinants of employee satisfaction. Additionally, it provides a novel measurement of employee satisfaction for a large sample of Chinese firms.

The current education paradigm is often criticized for fostering human dependence and failing to reduce environmental impacts. This has led researchers to propose alternative approaches. One alternative approach, place-based education, integrates a specific location’s natural and social context into learning experiences. By deepening students’ connection to their surroundings, place-based environmental education aims to enhance students’ sense of interdependence with a place and their place attachment in cognitive and affective dimensions. While widely practiced, its effectiveness remains largely unevaluated, particularly in the East Asian context. The gap hinders the development of impactful pedagogical approaches for educators.

The authors examine a river environmental education program located upstream of Taiwan’s capital, offering a valuable case study within the East Asian context. The program’s design is analyzed, and its impact on enhancing students’ place attachment is assessed through a pre- and post-survey approach.

The results indicate a substantial increase in students’ place attachment following program participation, particularly pronounced among children with limited prior experience with the river. Importantly, this increase is comparable to or exceeds those observed in similar studies from other regions.

The considerable increase in place attachment observed in this program demonstrates its effectiveness in fostering environmental connections, particularly among children with limited prior experience. The magnitude of the increase might be partially attributable to the interdependent orientation of Taiwanese culture. This suggests that place-based education might yield significant positive outcomes in other non-Western countries with strong interdependent cultural orientations.

With the help of “self-learning” algorithms and high computing power, companies are transforming Big Data into artificial intelligence (AI)-powered information and gaining economic benefits. AI-powered information and Big Data (simply data henceforth) have quickly become some of the most important strategic resources in the global economy. However, their value is not (yet) formally recognized in financial statements, which leads to a growing gap between book and market values and thus limited decision usefulness of the underlying financial statements. The objective of this paper is to identify ways in which the value of data can be reported to improve decision usefulness.

Based on the authors' experience as both long-term practitioners and theoretical accounting scholars, the authors conceptualize and draw up a potential data value chain and show the transformation from raw Big Data to business-relevant AI-powered information during its process.

Analyzing current International Financial Reporting Standards (IFRS) regulations and their applicability, the authors show that current regulations are insufficient to provide useful information on the value of data. Following this, the authors propose a Framework for AI-powered Information and Big Data (FAIIBD) Reporting. This framework also provides insights on the (good) governance of data with the purpose of increasing decision usefulness and connecting to existing frameworks even further. In the conclusion, the authors raise questions concerning this framework that may be worthy of discussion in the scholarly community.

Scholars and practitioners alike are invited to follow up on the conceptual framework from many perspectives.

The framework can serve as a guide towards a better understanding of how to recognize and report AI-powered information and by that (a) limit the valuation gap between book and market value and (b) enhance decision usefulness of financial reporting.

This article proposes a conceptual framework in IFRS to regulators to better deal with the value of AI-powered information and improve the good governance of (Big)data.