Search results

This study aims to explore the influence of postdisaster tourism development on the objective quality of life (QoL) of residents in Wenchuan County, simulate the long-run trend of postdisaster tourism development and QoL based on three proposed policy scenarios and formulate some practical suggestions to promote sustainable tourism development.

This study uses the system dynamic approach to develop a system dynamics (SD) model called “tourism–economy–environment–living” (TEEL) by using four subsystems: “the economic subsystem,” “the tourism subsystem,” “the environmental subsystem” and “the living subsystem.”

The results show that the influence of postdisaster tourism development on QoL is complex. Based on Butler’s destination life cycle theory, the influence of postdisaster tourism on objective QoL exhibits a nonlinear change closely tied to the development stages of tourist destinations. It showed that the QoL index increased after an initial decrease in the early stage (2009–2013) and then decreased in the later stage (2013–2019). Simulations of TEEL based on three different scenarios show that the current development path of tourism development is not ideal. The synergy scenario, highlighting the importance of the harmonious development of the TEEL, is the optimal scenario.

This study fills the gap in the literature on the influence of postdisaster tourism development on objective QoL from the perspective of SD. Modeling tourism development and objective QoL will contribute to a comprehensive understanding of whether and how tourism development can enhance residents’ QoL in disaster-affected areas.

本研究旨在探讨灾后旅游发展对汶川县居民客观生活质量（QoL）的影响, 并基于三种拟议的政策情景模拟灾后旅游发展和生活质量的长期演化趋势, 并制定一些切实可行的建议, 以促进旅游业的可持续发展。

本研究运用系统动力学方法, 通过使用四个子系统, 即“经济子系统”、“旅游子系统”“环境子系统”和“生活子系统”, 建立了一个称为“旅游-经济-环境-生活”（TEEL）的系统动力学模型。

研究结果表明, 灾后旅游发展对客观QoL的影响是复杂的。根据巴特勒的目的地生命周期理论, 灾后旅游对目标QoL的影响呈现非线性变化, 与旅游目的地的发展阶段密切相关。结果表明, QoL指数在前期（2009–2013年）出现初始下降后上升, 而后在后期（2013–2019年）下降。基于三种不同方案的TEEL模拟表明, 当前旅游发展路径并非最佳。协同方案强调了TEEL和谐发展的重要性, 是在所有方案中最佳。

本研究填补了从系统动力学角度研究灾后旅游发展对客观生活质量QoL影响的文献空白。构建旅游发展和客观QoL的系统动力模型将有助于全面了解旅游发展是否以及如何提高灾区居民的生活质量。

Este estudio tiene por objetivo explorar la influencia del desarrollo del turismo post-catástrofe en la calidad de vida (CdV) objetiva de los residentes del condado de Wenchuan, simular la tendencia a largo plazo del desarrollo del turismo tras la catástrofe y la CdV basándose en tres escenarios políticos propuestos, y formular algunas sugerencias prácticas para promover el desarrollo del turismo sostenible.o.

Este estudio utiliza el enfoque de dinámica de sistemas para desarrollar un modelo de dinámica de sistemas denominado “turismo-economía-medioambiente-vida” (TEMV) utilizando cuatro subsistemas: “el subsistema económico”, “el subsistema turístico”, “el subsistema medioambiental” y “el subsistema de vida”.

Los resultados muestran que la influencia del desarrollo del turismo post-catástrofe en la CdV objetiva es compleja. Basándose en la teoría de Butler sobre el ciclo de vida del destino, la influencia del turismo post-catástrofe en la CdV objetiva presenta un cambio no lineal estrechamente vinculado a las etapas de desarrollo de los destinos turísticos. Se demuestra que el índice de CdV aumentó después de una disminución inicial en la primera etapa (2009-2013) y luego disminuyó en la etapa posterior (2013-2019). Las simulaciones de TEMV basadas en tres escenarios diferentes muestran que la actual trayectoria de desarrollo del turismo no es ideal. El escenario de sinergia, que destaca la importancia del desarrollo armonioso del TEMV, es el escenario óptimo.

Este estudio llena la brecha existente en la literatura sobre la influencia del desarrollo del turismo post-catástrofe en la calidad de vida (CdV) objetiva desde la perspectiva de la dinámica de sistemas. La modelización del desarrollo turístico y la CdV objetiva contribuirá a una comprensión integral de si el desarrollo turístico puede mejorar, y cómo, la CdV de los residentes en las zonas afectadas por catástrofes

This study aims to investigate the effect of microalloyed Ca and Ce on microstructure and corrosion behavior of Mg-1.5Zn alloy. Mg-1.5Zn-xCa-xCe alloys were prepared by melting, extrusion and rolling processes.

The effects of adding Ca and Ce elements alone or adding Ca and Ce elements simultaneously on the microstructure and corrosion resistance of Mg-1.5Zn-xCa-xCe (x = 0 or 0.2 Wt.%) alloys were studied by scanning electron microscopy, hydrogen evolution tests and electrochemical experiments.

The addition of Ca and Ce elements alone or the addition of Ca and Ce elements had little impact on the grain size of the rolled and annealed Mg-1.5Zn-xCa-xCe alloy, but had a greater effect on the type and quantity of the second phase.

The order of the corrosion rates for the three alloys was Mg-1.5Zn-0.2Ca < Mg-1.5Zn-0.2Ca-0.2Ce < Mg-1.5Zn-0.2Ce. Mg-1.5Zn-0.2Ca showed the best corrosion resistance, which was related to the second phase and corrosion products.

The influence of Zn concentration on microstructure and corrosion performance of the Mg–xZn alloys microalloyed with Ca and Ce was investigated through optic microscopy, scanning electron microscopy, hydrogen evolution, dynamic polarization and electrochemical impedance spectroscopy experiments.

In this paper, Mg–xZn alloys (x = 0.5∼2.0 Wt.%) microalloyed with Ca and Ce (0.2 Wt.% each) were prepared.

As the increase of Zn concentration, the number of second phase particles (Mg-Zn-Ca, Mg-Zn-Ce and Mg-Ce phases) increased, and when the Zn concentration increased to 2.0 Wt.%, the new second phase Mg-Zn phase was precipitated.

The influence of Zn concentration on corrosion mechanism of Mg-xZn alloys microalloyed with Ca and Ce was revealed. Increasing of the Zn concentration resulted in the intensification of galvanic corrosion. When Zn concentration was 0.5 Wt.%, the alloy showed the lowest corrosion rate (0.61 mm y-1), which was about 1/2 of that of Mg-2.0Zn-0.2Ca-0.2Ce alloy.

In the magnetorheological fluid (MRF) sealing, a large amount of friction heat is generated in the fluid film with micron thickness due to the viscosity dissipation, which leads to seal failure and MRF deterioration. The purpose of this study is to investigate the mechanism of temperature rise of MRF film under the action of the three-field coupling of the flow field, temperature field and magnetic field.

The fluid film was simplified as a Couette flow in this work to simulate the temperature change in the sealing fluid film under different working conditions. The corresponding experiment for test the temperature rise was also carried out, and the temperature of the characteristic point of the stationary ring was measured to validate the model.

The results show that the temperature rise is mainly affected by the rotational speed, magnetic field strength and fluid film thickness. The magnetic field enhances the convective heat transfer in the MRF film. The thinner the fluid film, the more frictional heat generated. The MRF film reaches its maximum temperature at the contact with the end face of rotating ring due to frictional heat.

A method for temperature rise analysis of MRF fluid sealing films based on Couette flow is established. It is helpful for the study of liquid film frictional heat in MRF seals.

Owing to the consumption of considerable resources in developing physical pipe prediction models and the fact that the statistical models cannot fit the failure records perfectly, the purpose of this paper is to use data mining method to analyze and predict the risks of water pipe failure via considering attributes and location of pipes in historical failure records. One of the Automatized Machine Learning (AutoML) methods, tree-based pipeline optimization technique (TPOT) was used as the key data mining technique in this research.

By considering pipeline attributes, environmental factors and historical pipeline broke/breaks records, a water pipeline failure prediction method is proposed in this research. Regression analysis, genetic algorithm, machine learning, data mining approaches are used to analyze and predict the probability of pipeline failure. TPOT was used as the key data mining technique. A case study was carried out in a specific area in China to investigate the relationships between pipeline broke/breaks and relevant parameters, such as pipeline age, materials, diameter, pipeline density and so on.

By integrating the prediction models for individual pipelines and small research regions, a prediction model is developed to describe the probability of water pipe failures and validated by real data. A high fitting degree is achieved, which means a good potential of using the proposed method in reality as a guideline for identifying areas with high risks and taking proactive measures and optimizing the resources allocation for water supply companies.

Different models are developed to have better prediction on regional or individual pipeline. A comparison between the predicted values with real records has shown that a preliminary model has a good potential in predicting the future failure risks.

This study aimed at investigating the influence of corporate governance on firm risk during the Chinese state enterprise reform. The purposes of this study are to examine the effects of board independence, state ownership and other governance variables on firm risk and to check the influence of controlling shareholder types on firm risk.

This study uses the dynamic and static panel model to estimate the effects of board independence, state ownership and other governance factors on return volatility. To examine the influence of controlling shareholder types on corporate risk-taking, this study further used the treatment effect model (or sample selection model) to analyze the effect of private, state-owned enterprise (SOE) entity, central government and local government controls on corporate risk-taking.

It was found that the enforcement of board independence significantly increases firm risk. The strategy of decentralizing state enterprises (from central government to local government) is a good way to achieve stable stock returns.

This study contributes to existing knowledge in several ways. First, it focused on independent directors rather than on the size of the corporate board. Second, it highlighted the impacts of state ownership and control on corporate risk. Instead of treating all types of state ownership as homogenous, SOEs are further classified into directly controlled and indirectly controlled, in line with prior studies.

While spontaneous and voluntary knowledge contribution in online communities promotes value co-creation, dysfunctional knowledge behaviors hamper the effectiveness and development of such communities. The study conceptualizes physicians' proactive knowledge sharing and knowledge withholding behaviors in physician-driven online health communities (OHCs) and integrates the theories of role identity as well as communal and exchange relationships to understand the root causes and motivations behind these two types of knowledge behaviors.

The authors collected survey data from 166 users from one of the largest physician-driven OHCs in China and applied the covariance-based structural equation modeling approach to test the hypotheses.

The findings suggest that (1) physicians' professional role identity had a positive indirect effect on proactive knowledge sharing behaviors through communal motivation, and work pressure weakened this indirect effect; and (2) professional role identity had a negative indirect impact on knowledge withholding behaviors through exchange motivation.

This study extends proactive knowledge sharing and knowledge withholding behaviors from the organizational management domain to the online environment, exploring the underlying causes and motivations behind both behaviors in the unique context of physician-driven OHCs. The findings offer practical suggestions for the effective management of OHC platforms, as well as policy implications that respond to the workforce shortage of healthcare providers, a crisis that is unfolding globally.

The Internet of Things (IoT) offers substantial potential for improving efficiency and effectiveness in various applications, notably within the domain of smart construction. Despite its growing adoption within the Architecture, Engineering, and Construction (AEC) industry, its utilization remains limited. Despite efforts made by policymakers, the shift from traditional construction practices to smart construction poses significant challenges. Consequently, this study aims to explore, compare, and prioritize the determinants that impact the acceptance of the IoT among construction practitioners.

Based on the integrated model of Unified Theory of Acceptance and Use of Technology (UTAUT2), Task-Technology Fit (TTF), and perceived risk. A cross-sectional survey was administered to 309 construction practitioners in China, and the collected data were analyzed using structural equation modeling (SEM) to test the proposed hypotheses.

The findings indicate that TTF, performance expectancy, effort expectancy, hedonic motivation, facilitating conditions, and perceived risk exert significant influence on construction practitioners’ intention to adopt IoT. Conversely, social influence and habit exhibit no significant impact. Notably, the results unveil the moderating influence of gender on key relationships – specifically, performance expectancy, hedonic motivation, and habit – in relation to the behavioral intention to adopt IoT among construction practitioners. In general, the model explains 71% of the variance in the behavioral intention to adopt IoT, indicating that the independent constructs influenced 71% of practitioners’ intentions to use IoT.

These findings provide both theoretical support and empirical evidence, offering valuable insights for stakeholders aiming to gain a deeper understanding of the critical factors influencing practitioners’ intention to adopt IoT. This knowledge equips them to formulate programs and strategies for promoting effective IoT implementation within the AEC field.

This study contributes to the existing literature by affirming antecedents and uncovering moderators in IoT adoption. It enhances the existing theoretical frameworks by integrating UTAUT2, TTF, and perceived risk, thereby making a substantial contribution to the advancement of technology adoption research in the AEC sector.

Prosocial lending in online crowdfunding has flourished in recent years, and it has become a new way to fundraise for philanthropy. However, there is almost a 70% user attrition rate in crowdfunding. The purpose of this study is to understand what the lender’s lending experience and social connection influence lender retention of online prosocial lending from a self-determination perspective.

Drawing on self-determination theory (SDT), this research utilizes a quantifiable method for factors of the lender's lending experience and social connection. Additionally, the research constructs economic models to explore the impacts of these factors acting as the necessary conditions for basic psychological needs on lender retention, using a large-scale sample of over 380,000 lenders from Kiva.

The results indicate that, from the lender's lending experience aspect, the loan narratives with more profit language in the last lending and the failure of past participation are negatively related to lender retention. Regarding the lender's social connection aspect, their friends or small lending teams are positively related to lender retention, while whether they are invited and lending team size show negative influence. Furthermore, results indicate the moderating effects of the disclosure of lending motivation.

This research explores the mechanism of lender retention of online prosocial lending, providing a self-determination perspective about how previous experience influences long-term lending behavior. The study offers significant implications for the literature on online philanthropy, SDT and user retention of online platforms. At the same time, the study provides an understanding of the effects of different aspects of SDT.

Considering the role of analysts in disseminating information, the paper explains the idiosyncratic volatility puzzle of China's stock market. As the largest developing country, China's research can provide meaningful reference for the research of financial markets in other new countries.

From the perspective of behavior, establishing a direct link between individual investor attention and stock price overvaluation.

The authors find that there is a significant idiosyncratic volatility puzzle in China's stock market. Due to the role of mispricing, individual investor attention significantly enhances the idiosyncratic volatility effect, that is, as individual investor attention increases, the greater the idiosyncratic volatility, the lower the expected return. Attention can explain the idiosyncratic volatility puzzle in China's stock market. In addition, due to the role of information production and dissemination, securities analysts can reduce the degree of market information asymmetry and enhance the transparency of market information.

China is the second largest economy in the world, and few scholars analyze it from the perspective of investors' attention. The authors believe this paper has the potential in contributing to the academia.