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This study aims to explore the different effects of inter-community group networks and intra-community group networks on group innovation.

The authors used a pooled panel dataset of 12,111 self-organizing innovation groups in 463 game product creative workshop communities from Steam support to test the hypothesis. The pooled ordinary least squares (OLS) model is used for analyzing the data.

The results show that network constraint is negatively associated with the innovation performance of online groups. The average path length of the inter-community group network negatively moderates the relationship between network constraint and group innovation, while the average path length of the intra-community group network positively moderates the relationship between network constraint and group innovation. In addition, both the network density of inter-community group networks and intra-community group networks can negatively moderate the negative relationship between network constraint and group innovation.

The findings of this study suggest that network structural characteristics of inter-community networks and intra-community networks have different effects on online groups’ product innovation, and therefore, group members should consider their inter- and intra-community connections when choosing other groups to form a collaborative innovation relationship.

Natural disasters profoundly influence agricultural trade sustainability. This study investigates the effects of natural disasters on agricultural production imports in China within 2002 and 2018. This exploration estimates the mediating role of transportation infrastructure and agriculture value-added and the moderating role of government effectiveness and diplomatic relations.

This investigation uses Probit, Logit, Cloglog and Ordinary Least Squares (OLS) models.

The results confirm the mediating role of transportation infrastructure and agriculture value-added and the moderating role of government effectiveness and diplomatic relations in China. According to the findings, natural disasters in trading partners heighten the risk to the agricultural imports. This risk raises, if disasters damage overall agricultural yield or transportation infrastructure. Moreover, governments’ effective response or diplomatic ties with China mitigate the risk. Finally, the effect of disasters varies by the developmental status of the country involved, with events in developed nations posing a greater risk to China’s imports than those in developing nations.

China should devise an early warning system to protect its agricultural imports by using advanced technologies such as data analytics, remote sensing and artificial intelligence. In addition, it can leverage this system by improving its collaboration with trading partners, involvement in international forums and agreement for mutual support in crisis.

The environment in which users acquire medical and health information has changed dramatically, with online health communities (OHCs) emerging as an essential means for accessing health information. It is imperative to comprehend the factors that shape the users' compliance willingness (UCW) to health information in OHCs.

This study adopted the information adoption model (IAM) and theory of planned behavior (TPB) to investigate the influence of argument quality (AQ), source credibility (SC) and subjective norms (SN) on UCW while considering the two types of online health information – mature and emerging treatments. The authors conducted an explanatory-predictive study based on a 2 (treatment types: mature vs. emerging) * 2 (AQ: high vs. low) * 2 (SC: high vs. low) scenario-based experiment, using the partial least squares structural equation modeling (PLS-SEM).

SC positively influences AQ. AQ, SC and SN contribute to information usefulness (IU). These factors positively affect UCW through the mediation of IU. SN were found to improve UCW directly. Moreover, the moderating effect of SC on AQ and IU was more substantial for emerging treatments.

The research model integrates IAM and TPB, considering information types as an additional variable. The approach and findings provide a valuable explanation for UCW to health information in OHCs.

Abnormal vibrations often occur in the liquid oxygen kerosene transmission pipelines of rocket engines, which seriously threaten their safety. Improper handling can result in failed rocket launches and significant economic losses. Therefore, this paper aims to examine vibrations in transmission pipelines.

In this study, a three-dimensional high-pressure pipeline model composed of corrugated pipes, multi-section bent pipes, and other auxiliary structures was established. The fluid–solid coupling method was used to analyse vibration characteristics of the pipeline under various external excitations. The simulation results were visualised using MATLAB, and their validity was verified via a thermal test.

In this study, the vibration mechanism of a complex high-pressure pipeline was examined via a visualisation method. The results showed that the low-frequency vibration of the pipe was caused by fluid self-excited pressure pulsation, whereas the vibration of the engine system caused a high-frequency vibration of the pipeline. The excitation of external pressure pulses did not significantly affect the vibrations of the pipelines. The visualisation results indicated that the severe vibration position of the pipeline thermal test is mainly concentrated between the inlet and outlet and between the two bellows.

The results of this study aid in understanding the causes of abnormal vibrations in rocket engine pipelines.

The causes of different vibration frequencies in the complex pipelines of rocket engines and the propagation characteristics of external vibration excitation were obtained.

This study aims to explore the synergistic effect of oxide nanoparticles (ZnO, Fe₂O₃, SiO₂) and cerium nitrate inhibitor on anti-corrosion performance of epoxy coating. First, cerium nitrate inhibitors are absorbed on the surface of various oxide nanoparticles. Thereafter, epoxy nanocomposite coatings have been fabricated on carbon steel substrate using these oxide@Ce nanoparticles as both nano-fillers and nano-inhibitors.

To evaluate the impact of oxides@Ce nanoparticles on mechanical properties of epoxy coating, the abrasion resistance and impact resistance of epoxy coatings have been examined. To study the impact of oxides@Ce nanoparticles on anti-corrosion performance of epoxy coating for steel, the electrochemical impedance spectroscopy has been carried out in 3% NaCl solution.

ZnO@Ce3+ and SiO2@Ce3+ nanoparticles provide more enhancement in the epoxy pore network than modification of the epoxy/steel interface. Whereas, Fe2O3@Ce3+ nanoparticles have more to do with modification of the epoxy/steel interface than to change the epoxy pore network.

Incorporation of both oxide nanoparticles and inorganic inhibitor into the epoxy resin is a promising approach for enhancing the anti-corrosion performance of carbon steel.

This study aims to investigate low-carbon footprint travel choices, considering both destination attributes and climate change perceptions, and examine the impacts of nudging (a communication tool to alter individuals’ choices in a predictable way) on tourists’ preferences for carbon mitigation in destinations.

A discrete choice experiment questionnaire was administered to a sample of 958 Hong Kong respondents. Hybrid choice modeling was used to examine the respondents’ preferences for destination attributes and to explain preference heterogeneity using tourists’ climate change perceptions. The respondents’ willingness to pay for the destination attributes was also calculated to measure the monetary value of the attributes.

Destination type, carbon emissions and travel cost had significant effects on tourists’ choices of destination. Nudging increased tourists’ preference for low-carbon footprint choices. Tourists with higher climate change perceptions were more likely than others to select low-carbon destinations with carbon offset projects.

The findings of this study provide an impetus for destination management organizations to support local carbon offset projects, implement policies that mitigate carbon emissions and develop sustainable tourism to fulfill tourists’ demand for low-carbon footprint travel choices. Based on the findings, policymakers could promote sustainable tourism by publishing relevant climate change information on social media.

This study addressed a gap in the literature on tourist travel choice by considering carbon emission-related attributes and climate change perceptions and by confirming the role of nudging in increasing the choice of low-carbon destinations.

This paper aims to disentangle Chinese-English-rich resources linguistic and speaker timbre features, achieving cross-lingual speaker transfer for Cambodian.

This study introduces a novel approach: the construction of a cross-lingual feature disentangler coupled with the integration of time-frequency attention adaptive normalization to proficiently convert Cambodian speaker timbre into Chinese-English without altering the underlying Cambodian speech content.

Considering the limited availability of multi-speaker corpora in Cambodia, conventional methods have demonstrated subpar performance in Cambodian speaker voice transfer.

The originality of this study lies in the effectiveness of the disentanglement process and precise control over speaker timbre feature transfer.

Surface acoustic wave (SAW) sensors have attracted great attention worldwide for a variety of applications in measuring physical, chemical and biological parameters. However, stability has been one of the key issues which have limited their effective commercial applications. To fully understand this challenge of operation stability, this paper aims to systematically review mechanisms, stability issues and future challenges of SAW sensors for various applications.

This review paper starts with different types of SAWs, advantages and disadvantages of different types of SAW sensors and then the stability issues of SAW sensors. Subsequently, recent efforts made by researchers for improving working stability of SAW sensors are reviewed. Finally, it discusses the existing challenges and future prospects of SAW sensors in the rapidly growing Internet of Things-enabled application market.

A large number of scientific articles related to SAW technologies were found, and a number of opportunities for future researchers were identified. Over the past 20 years, SAW-related research has gained a growing interest of researchers. SAW sensors have attracted more and more researchers worldwide over the years, but the research topics of SAW sensor stability only own an extremely poor percentage in the total researc topics of SAWs or SAW sensors.

Although SAW sensors have been attracting researchers worldwide for decades, researchers mainly focused on the new materials and design strategies for SAW sensors to achieve good sensitivity and selectivity, and little work can be found on the stability issues of SAW sensors, which are so important for SAW sensor industries and one of the key factors to be mature products. Therefore, this paper systematically reviewed the SAW sensors from their fundamental mechanisms to stability issues and indicated their future challenges for various applications.

The COVID-19 pandemic has significantly impacted global tourism, with international travel bearing the burden of restrictions. Domestic tourism has also faced substantial challenges. This paper aims to analyse the impact of the COVID-19 pandemic on domestic tourism in Spain, focusing on travel from Madrid (the country’s capital) to other tourist destinations.

Mobile phone data has been used to study the evolution of tourist trips over the summers of 2019, 2020 and 2021. Regression models are used to explain the number of visitors at destinations.

The pandemic not only caused a drastic drop in tourist flows but also disrupted the overall pattern of the domestic flow system. Winning destinations were typically areas in proximity to Madrid and less densely populated destinations, while urban destinations were major losers. The preferences of domestic tourists varied notably by income group, but the decrease in trip volumes showed only marginal differences.

The paper demonstrates the potential of mobile phone data analysis to study the uneven impact of external shocks, such as the COVID-19 pandemic, on tourist destinations. This approach considers spatial resilience heterogeneity within regions or provinces. By incorporating income information, the analysis introduces a social dimension to highly detailed spatial data, surpassing traditional studies conducted at the regional or national levels.

COVID-19大流行对全球旅游业产生了重大影响，国际旅行受到了限制的影响最为严重。国内旅游也面临着重大挑战。本文分析了COVID-19大流行对西班牙国内旅游的影响，重点关注从马德里（该国首都）到其他旅游目的地的旅行。

本研究使用移动电话数据研究了2019年、2020年和2021年夏季旅游出行的演变。采用回归模型解释了各目的地游客数量。

大流行不仅导致了旅游流量急剧下降，还扰乱了国内流动系统的总体模式。获胜的目的地通常是马德里附近的地区和人口较稀少的目的地，而城市目的地是主要的输家。国内游客的偏好在收入群体之间有明显差异，但旅行量的减少只显示出边际差异。

本文展示了使用移动电话数据分析研究外部冲击（如COVID-19大流行）对旅游目的地的不均匀影响的潜力。该方法考虑了区域或省份内的空间弹性异质性。通过整合收入信息，该分析为高度详细的空间数据引入了社会维度，超越了传统在区域或国家水平进行的研究。

This study aims to empirically analyse the influence mechanism of perceived interactivity in real estate APP which affects consumers' psychological well-being. With the growing application of human–machine interaction in real estate APP, it is crucial to utilize human–machine interaction to stimulate perceived interactivity between humans and machines to positively impact consumers' psychological well-being and sustainable development of real estate APP. However, it is unclear whether perceived interactivity improves consumers' psychological well-being.

This study proposes and examines a theoretical model grounded in the perceived interactivity theory, considers the relationship between perceived interactivity and consumers' psychological well-being and explores the mediating effect of perceived value and the moderating role of privacy concerns. It takes real estate APP as the research object, analyses the data of 568 consumer samples collected through questionnaires and then employs structural equation modelling to explore and examine the proposed theoretical model of this study.

The findings are that perceived interactivity (i.e. human–human interaction and human–information interaction) positively influences perceived value, which in turn affects psychological well-being, and that perceived value partially mediates the effect of perceived interaction on psychological well-being. More important findings are that privacy concerns not only negatively moderate human–information interaction on perceived value, but also negatively moderate the indirect effects of human–information interaction on users' psychological well-being through perceived value.

This study expands the context on perceived interaction and psychological well-being in the field of real estate APP, validating the mediating role and boundary conditions of perceived interactivity created by human–machine interaction on consumers' psychological well-being, and suggesting positive implications for practitioners exploring human–machine interaction technologies to improve the perceived interaction between humans and machines and thus enhance consumer psychological well-being and span sustainable development of real estate APP.