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This study aims to examine the impact of logistics and merchant certification information on consumer behaviour in hybrid retail platforms. Furthermore, it explores the moderating role of online shopping experience on the certification effect.

The authors utilize transaction-level data from over 2.5 million consumers involving 30,000 stock keeping units (SKUs) on JD.com in March 2018. They analyse the impact of different types of certification information on consumer behaviour using ordinary linear regression and linear probability models.

The findings reveal that, compared with information without certification, (1) single logistics certification information can enhance consumers' search depth and purchase intention; (2) dual logistics and merchant certification information also has a positive impact on consumer behaviour; and (3) single certification information is more effective for inexperienced consumers, while dual certification is more effective for experienced consumers.

Theoretically, this study contributes to the literature on certification information in hybrid retail platforms and broadens information communication methods for online shopping. Our discovery is meaningful for managers in locating customers and allocating resources. In addition, we encourage online retailers to utilize certification information to engage consumer.

This paper delves into the aerodynamic optimization of a single-stage axial turbine employed in aero-engines.

An efficient integrated design optimization approach tailored for turbine blade profiles is proposed. The approach combines a novel hierarchical dynamic switching PSO (HDSPSO) algorithm with a parametric modeling technique of turbine blades and high-fidelity Computational Fluid Dynamics (CFD) simulation analysis. The proposed HDSPSO algorithm introduces significant enhancements to the original PSO in three pivotal aspects: adaptive acceleration coefficients, distance-based dynamic neighborhood, and a switchable learning mechanism. The core idea behind these improvements is to incorporate the evolutionary state, strengthen interactions within the swarm, enrich update strategies for particles, and effectively prevent premature convergence while enhancing global search capability.

Mathematical experiments are conducted to compare the performance of HDSPSO with three other representative PSO variants. The results demonstrate that HDSPSO is a competitive intelligent algorithm with significant global search capabilities and rapid convergence speed. Subsequently, the HDSPSO-based integrated design optimization approach is applied to optimize the turbine blade profiles. The optimized turbine blades have a more uniform thickness distribution, an enhanced loading distribution, and a better flow condition. Importantly, these optimizations lead to a remarkable improvement in aerodynamic performance under both design and non-design working conditions.

These findings highlight the effectiveness and advancement of the HDSPSO-based integrated design optimization approach for turbine blade profiles in enhancing the overall aerodynamic performance. Furthermore, it confirms the great prospects of the innovative HDSPSO algorithm in tackling challenging tasks in practical engineering applications.

This study aims to investigate the acoustic roughness of rails on China’s high-speed railways, with a focus on short-wavelength irregularities (less than 80 cm), which are known to significantly contribute to noise. The goal is to develop a specific acoustic roughness spectrum tailored for China’s high-speed railway system, as no such spectrum currently exists.

A long-term tracking study was conducted on major railway lines in China, monitoring rail roughness throughout the initial operational period and the rails’ service life. Data preprocessing techniques such as peak removal and curvature correction were applied for acoustic adjustments. A spatial-wavelength domain transformation was performed, providing the distribution patterns and statistical characteristics of acoustic roughness on China’s high-speed rails. Based on these analyses, a model for constructing the acoustic roughness spectrum was developed.

The study found that the acoustic roughness of China’s high-speed railway rails follows a χ² distribution with six degrees of freedom. For wavelengths greater than 8 cm, the acoustic roughness spectrum remains below the ISO specified limits. In the wavelength range of 3.2 cm to 6.3 cm, the roughness is comparable to or within the limits specified by ISO 3095:2005 and ISO 3095:2013. However, for wavelengths shorter than 2.5 cm, the roughness exceeds ISO limits.

This research fills the gap in the lack of a specific acoustic roughness spectrum for China’s high-speed railways. By establishing a tailored spectrum based on long-term data analysis, the findings provide valuable insights for noise control and rail maintenance in the context of China’s high-speed rail system.

This study aims to evaluate how positive experiences affect satisfaction and brand loyalty toward specific brand products for travel services by collecting 489 structured questionnaires from those patronizing seven world-renowned brand travel agencies in Taiwan. As for data analysis, it uses a structural equation model (SEM) to examine causal relationships among the proposed constructs. This study suggests that marketers of brand products utilize this consumer mentality, pursue the meaning of symbol development strategies for products and appeal to more consumers to boost consumption. In addition, offering a positive experience and ensuring satisfaction is a valid strategy for creating brand life cycle advantages for travel services.

Intumescent coatings are nowadays a dominant passive system used to protect structural materials in case of fire. Due to their reactive swelling behaviour, intumescent coatings are particularly complex materials to be modelled and predicted, which can be extremely useful especially for performance-based fire safety designs. In addition, many parameters influence their performance, and this challenges the definition and quantification of their material properties. Several approaches and models of various complexities are proposed in the literature, and they are reviewed and analysed in a critical literature review.

Analytical, finite-difference and finite-element methods for modelling intumescent coatings are compared, followed by the definition and quantification of the main physical, thermal, and optical properties of intumescent coatings: swelled thickness, thermal conductivity and resistance, density, specific heat capacity, and emissivity/absorptivity.

The study highlights the scarce consideration of key influencing factors on the material properties, and the tendency to simplify the problem into effective thermo-physical properties, such as effective thermal conductivity. As a conclusion, the literature review underlines the lack of homogenisation of modelling approaches and material properties, as well as the need for a universal modelling method that can generally simulate the performance of intumescent coatings, combine the large amount of published experimental data, and reliably produce fire-safe performance-based designs.

Due to their limited applicability, high complexity and little comparability, the presented literature review does not focus on analysing and comparing different multi-component models, constituted of many model-specific input parameters. On the contrary, the presented literature review compares various approaches, models and thermo-physical properties which primarily focusses on solving the heat transfer problem through swelling intumescent systems.

The presented literature review analyses and discusses the various modelling approaches to describe and predict the behaviour of swelling intumescent coatings as fire protection for structural materials. Due to the vast variety of available commercial products and potential testing conditions, these data are rarely compared and combined to achieve an overall understanding on the response of intumescent coatings as fire protection measure. The study highlights the lack of information and homogenisation of various modelling approaches, and it underlines the research needs about several aspects related to the intumescent coating behaviour modelling, also providing some useful suggestions for future studies.

This research aims to examine how decision-makers’ demographic traits affect the integration of foreign workforce into Tirolean (Austria) companies. With continuous world migrations, Tirol experiences a great inflow of foreign workforce. While integrating into the workforce, the foreign workers interact with various decision-makers whose demographic traits (e.g., age, gender, nationality) potentially influence the success of the integration process. To gather data on the integration levels of a foreign workforce, the author conducted a questionnaire. Furthermore, several statistical analyses were run to determine if the relationship between demographic characteristics and integration success exists. The study reveals that demographic characteristics influence decision-makers’ acceptance of expatriates, as well as their recruitment, integration, and training and development outcomes. The empirical results indicate the strength of relationships identified through analyses. The study is limited to geographical, as well as the scope of the sample size, as the data are obtained from Tirol only. In addition, the results from the study serve as a basis for future discussions and research.

The purpose of this study is to understand whether the spectator’s emotional attachment to esports’ players is key for the sponsoring brand’s outcomes. A theoretical model based on the attachment, social influence and brand communities’ literature is proposed.

Data were collected through an online survey from a sample of 1,355 regular esports viewers. The proposed conceptual model was evaluated using partial least squares-structural equation modeling (PLS-SEM).

The results showed that emotional attachment to esports players exerts a large effect on the viewer’s engagement with the community and his or her intention to view its content for longer. These two variables are key in explaining the viewer’s intention to perform positive behaviors toward the sponsoring brand, such as recommendation, purchase intentions and co-creation.

This study improves the understanding about the effects of the viewer’s emotional bond with esports players and the bond’s impact on the development of positive behaviors toward the sponsoring brand.

El objetivo de este estudio es comprender cómo el apego emocional del espectador hacia el jugador de esports es determinante para los resultados de la marca patrocinadora. Para ello se propone un modelo teórico basado en la literatura sobre el apego, la influencia social, y las comunidades de marca.

Se recopilaron datos de una muestra de 1.355 espectadores habituales de esports mediante una encuesta online. El modelo conceptual propuesto se evaluó con la técnica de ecuaciones estructurales por el método de mínimos cuadrados parciales (PLS-SEM).

Los resultados muestran que el apego emocional hacia el jugador de esports ejerce un gran efecto tanto en el compromiso del espectador con la comunidad como en su intención de permanecer más tiempo visionando sus contenidos. Estas dos variables son clave para explicar la intención del espectador de realizar comportamientos positivos hacia la marca patrocinadora como son la recomendación, la intención de compra y la cocreación.

Este estudio contribuye a mejorar la comprensión sobre los efectos del vínculo emocional del espectador con los jugadores de esports y su impacto en el desarrollo de comportamientos positivos hacia la marca patrocinadora.

Investigation of the anomalies associated with crashes and jackpots in the Chinese stock market.

We propose a logit model to predict the events of crashes and jackpots in the Chinese stock market. The model introduces a new variable of the price-to-sales ratio and takes into account the market states, Up and Down.

The anomalies associated with crashes and jackpots are not related to variations in economic conditions, but are associated with limits to arbitrage. High-liquidity stocks have strong mispricing effects. The institutions’ speculative trading will push liquid stock prices further away from their fundamentals but avoid buying illiquid stocks with a higher probability of price crashes and jackpots.

We propose a logit model to predict the extreme events of both crash and jackpot in the Chinese stock market. Our model effectively disentangles from CRASHP and JACKP. Compared with the traditional model, it substantially enhances in-sample and out-sample predictions. Based on the predictions of the extreme events, we find two strong and robust pricing effects associated with ex ante CRASHP and JACKP in the Chinese stock market.

In recent years, the incidence of cardiovascular disease has continued to rise, and early screening and prevention are especially critical. Phonocardiography (PCG) and electrocardiography (ECG), as simple, cost-effective and non-invasive tests, are important tools for clinical analysis. However, it is difficult to fully reflect the complexity of the cardiovascular system using PCG or ECG tests alone. Combining the multimodal signals of PCG and ECG can provide complementary information to improve the detection accuracy. Therefore, the purpose of this paper is to propose a multimodal signal classification method based on continuous wavelet transform and improved ResNet18.

The classification method is based on the ResNet18 backbone, and the ResNet18 network is improved by embedding the global grouped coordinate attention mechanism module and the improved bidirectional feature pyramid network. Firstly, a data acquisition system was built using a MEMS-integrated PCG-ECG sensor to construct a private data set. Second is the time-frequency transformation of PCG and ECG synchronized signals on public and private data sets using continuous wavelet transform. Finally, the time-frequency images are categorized.

The global grouped coordinate attention mechanism and bidirectional feature pyramid network modules proposed in this paper significantly enhance the model’s performance. On public data sets, the method achieves precision, sensitivity, specificity, accuracy and F1 score of 97.96%, 98.51%, 97.58%, 98.08% and 98.23%, respectively, which represent improvements of 3.54%, 3.92%, 4.18%, 4.03% and 3.72% compared to ResNet18. Additionally, it demonstrates a clear advantage over existing mainstream algorithms. On private data sets, the method’s five metrics are 98.15%, 98.76%, 98.08%, 98.42% and 98.45%, further validating the model’s generalization ability.

The method proposed in this paper not only improves the accuracy and efficiency of the test but also provides an effective solution for early screening and prevention of cardiovascular diseases.