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This study aims to investigate and compare the characteristics of three topologies of moving-magnet linear oscillating actuator (LOA) based on their mover position. Positive aspects and consequences of every topology are demonstrated. Three topologies of axially magnetized moving-magnet LOA; outer mover, inner mover (IM) and dual stator (DS) are designed and examined. Due to its characteristically high thrust density and more mechanical strength, axially magnetized tubular permanent magnets (PMs) are used in these topologies.

LOAs are designed and optimized using parametric sweep, in term of design parameters and output parameters like thrust force, stroke and operating resonance frequency of the LOA. All the pros and cons of each topology are investigated and compared. Output parameters of the LOAs are compared using same size of the investigated LOAs. Mover mass, which plays a vital role in resonant operation, is analyzed for IM and DS designs. Investigated LOAs are compared with conventional designs of LOA for compressor in refrigeration system with regards of motor constant, stroke and thrust per PM mass.

This paper analyzes three topologies of moving-magnet LOAs. The basic difference between investigated LOAs is the radius of tubular-shaped mover from its central axis. All the design parameters are compared and concluded that thrust per PM mass of IMLOA is maximum. OMLOA provides maximum motor constant of value 180 N/A. DSLOA provides thrust force with motor constant 120 N/A and required intermediate materials of PMs. All the three designs give the best results in terms of motor constant and thrust per PM mass, compared to conventional designs of LOA.

This paper determines the impact of mover position from its central axis in a tubular-shaped moving-magnet LOA. This work is carried out in correspondence of latest papers of LOA.

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 study aims to investigate the impact of job burnout on job satisfaction and the intention to change occupation within the accounting profession. It also examines the mediating role of psychological well-being.

A descriptive research design was used in this study. Survey data were physically collected from 230 accounting employees in the private sector. Structural equation modeling was used to test the theoretical model.

The results showed that job burnout significantly affects psychological well-being and that psychological well-being significantly mediates the relationship between job burnout and job satisfaction, as well as between job burnout and the intention to change occupation.

This study has significant implications for accounting organizations, suggesting the adoption of strategies to promote psychological well-being. These initiatives have the potential to enhance job satisfaction and reduce accountants’ intention to change their profession.

This study contributes to the existing literature by highlighting the mediating role of psychological well-being in linking job burnout with job satisfaction and the intention to change occupation among accounting professionals.

In practical engineering, oil filters often work under asymmetric cyclic loading. In order to improve the prediction accuracy of fatigue life of the oil filters under asymmetric cyclic loading, the effect of strain ratio and low cycle fatigue plastic deformation on fatigue life need to be considered. This paper aims to discuss the aforementioned objective.

First, strain-controlled fatigue tests with strain ratios of 0, 0.5 and −1 were carried out on the oil filter material 2A70-T6 aluminum alloy, and the test data were used to obtain strain fatigue life curves at three strain ratios. Then, based on the idea of the constant life curve method, the average value of the ratio of the strain amplitude corresponding to different strain ratios under the same partial life was defined as the strain ratio factor. Finally, the elastic-plastic factor was modified by the strain ratio factor, and a new fatigue life prediction model considering the effect of strain ratio was proposed.

The proposed model was validated, respectively, by fatigue test data of 2A70-T6 aluminum alloy, 2124-T851 aluminum alloy and oil filter and the results of the proposed model were compared with the Coffin–Manson equation, Morrow model and Smith–Watson–Topper (SWT) model, showing that the proposed model had higher applicability and accuracy.

In this work, a strain ratio factor is established based on the idea of the constant life curve method, and the strain ratio factor is used to modify the introduced elastic-plastic factor, and then a new fatigue life prediction model considering the influence of strain ratio and low cycle fatigue plastic deformation on material fatigue damage accumulation is proposed. The results show that the prediction results of the proposed model are in good agreement with the experimental data, and the proposed model has good fatigue life prediction ability considering the influence of strain ratio and lays a foundation for the fatigue life prediction of the oil filter.

Incorporating dynamic spatial effects exhibits considerable potential in improving the accuracy of forecasting tourism demands. This study aims to propose an innovative deep learning model for capturing dynamic spatial effects.

A novel deep learning model founded on the transformer architecture, called the spatiotemporal transformer network, is presented. This model has three components: the temporal transformer, spatial transformer and spatiotemporal fusion modules. The dynamic temporal dependencies of each attraction are extracted efficiently by the temporal transformer module. The dynamic spatial correlations between attractions are extracted efficiently by the spatial transformer module. The extracted dynamic temporal and spatial features are fused in a learnable manner in the spatiotemporal fusion module. Convolutional operations are implemented to generate the final forecasts.

The results indicate that the proposed model performs better in forecasting accuracy than some popular benchmark models, demonstrating its significant forecasting performance. Incorporating dynamic spatiotemporal features is an effective strategy for improving forecasting. It can provide an important reference to related studies.

The proposed model leverages high-frequency data to achieve accurate predictions at the micro level by incorporating dynamic spatial effects. Destination managers should fully consider the dynamic spatial effects of attractions when planning and marketing to promote tourism resources.

This study incorporates dynamic spatial effects into tourism demand forecasting models by using a transformer neural network. It advances the development of methodologies in related fields.

纳入动态空间效应在提高旅游需求预测的准确性方面具有相当大的潜力。本研究提出了一种捕捉动态空间效应的创新型深度学习模型。

本研究提出了一种基于变压器架构的新型深度学习模型, 称为时空变压器网络。该模型由三个部分组成：时空转换器、空间转换器和时空融合模块。时空转换器模块可有效提取每个景点的动态时间依赖关系。空间转换器模块可有效提取景点之间的动态空间相关性。提取的动态时间和空间特征在时空融合模块中以可学习的方式进行融合。通过卷积运算生成最终预测结果。

结果表明, 与一些流行的基准模型相比, 所提出的模型在预测准确性方面表现更好, 证明了其显著的预测性能。纳入动态时空特征是改进预测的有效策略。它可为相关研究提供重要参考。

所提出的模型利用高频数据, 通过纳入动态空间效应, 在微观层面上实现了准确预测。旅游目的地管理者在规划和营销推广旅游资源时, 应充分考虑景点的动态空间效应。

本研究通过使用变压器神经网络, 将动态空间效应纳入旅游需求预测模型。它推动了相关领域方法论的发展。

La incorporación de efectos espaciales dinámicos ofrece un considerable potencial para mejorar la precisión de la previsión de la demanda turística. Este estudio propone un modelo innovador de aprendizaje profundo para capturar los efectos espaciales dinámicos.

Se presenta un novedoso modelo de aprendizaje profundo basado en la arquitectura transformadora, denominado red de transformador espaciotemporal. Este modelo tiene tres componentes: el transformador temporal, el transformador espacial y los módulos de fusión espaciotemporal. El módulo transformador temporal extrae de manera eficiente las dependencias temporales dinámicas de cada atracción. El módulo transformador espacial extrae eficientemente las correlaciones espaciales dinámicas entre las atracciones. Las características dinámicas temporales y espaciales extraídas se fusionan de manera que se puede aprender en el módulo de fusión espaciotemporal. Se aplican operaciones convolucionales para generar las previsiones finales.

Los resultados indican que el modelo propuesto obtiene mejores resultados en la precisión de las previsiones que algunos modelos de referencia conocidos, lo que demuestra su importante capacidad de previsión. La incorporación de características espaciotemporales dinámicas supone una estrategia eficaz para mejorar las previsiones. Esto puede proporcionar una referencia importante para estudios afines.

El modelo propuesto aprovecha los datos de alta frecuencia para lograr predicciones precisas a nivel micro incorporando efectos espaciales dinámicos. Los gestores de destinos deberían tener plenamente en cuenta los efectos espaciales dinámicos de las atracciones en la planificación y marketing para la promoción de los recursos turísticos.

Este estudio incorpora efectos espaciales dinámicos a los modelos de previsión de la demanda turística mediante el empleo de una red neuronal transformadora. Supone un avance en el desarrollo de metodologías en campos afines.

This study aims to understand how different levels of streamer channels influence luxury brand sales in live streaming commerce. This study also seeks to understand the conditions under which luxury brands may benefit more from different level streamer channels.

Panel data were collected from 17 international luxury brands on the Douyin live streaming platform in an 18 week period from August to December 2020 and analyzed by using a two-way fixed effects model.

The authors compared different mega-, macro- and micro-streamer channels within live streaming commerce and found that the densities of mega- and macro-streamer channels had significant positive impacts on luxury brand sales in live streaming commerce. Moreover, the effects of the density of streamer channel on luxury brand sales were moderated by such variables as product line breadth, product line depth, product type (star/non-star) and product price (high/low). The authors found that product line breadth and depth could reduce the positive impact of the densities of mega- and macro-streamer channels on luxury brand sales. For star products and high-priced products, the relationship between the density of mega-streamer channel and luxury brand sales was more likely to be observed than for non-star products and low-priced products. The relationship between the density of macro-streamer channel and luxury brand sales was more likely to be observed in low-priced products than in high-priced products.

The findings make important contributions to the literature in that the authors expand the influencer-brand fit theory by proposing a new model of effects of the densities of mega-, macro- and micro-streamer channels on sales performance across different luxury products to improve our understanding of the fit among influencers, brands and products. This helps luxury brands make basic decisions of “who sells” and “sells what” when engaging in live streaming commerce.

Customers' co-design behavior is an important source of knowledge for product innovation. Firms can regulate the focus of information interaction with customers to set goals and motivate their co-design behavior. Drawing on regulatory fit theory and construal level theory, the authors build a research model to study whether the fit between the regulatory focus of firms' task invitations (promotion focus vs prevention focus) and their feedback focus (self-focused vs other-focused) can enhance co-design behavior by improving customers' experiences (perceived meaning, active discovery and perceived empowerment).

The authors conducted two online between-subjects experiments to validate the proposed research model.

The two online experiments reveal that customers' experiences are enhanced when the feedback focus is congruent with the regulatory focus of the firm's task invitations. Specifically, self-focused feedback has a stronger positive effect on customers' experiences in the prevention focus context. Other-focused feedback has a stronger positive effect on customers' experiences in the promotion focus context. Moreover, customers' experience significantly and positively affects co-design behavior (i.e. co-design effort and knowledge contribution).

This work provides theoretical and practical implications for firms to improve the effectiveness of information interaction with their customers and eventually ensure the sustainability of co-design.

This paper aims to study a new halogen-free fame-retardant curing agent 1-aminoethylidenediphosphonate (AAEDP).

The AAEDP was synthesized by phosphoric acid, acetonitrile and ammonia. The chemical structures of AAEDP were characterized by proton nuclear magnetic resonance, mass spectrometry and Fourier transform infrared spectrometer. Thermal gravimetric analysis (TGA) and scanning electron microscope (SEM) would study the thermal properties and the char residues of AAEDP/EP. The thermal stability, mechanical and flame properties and morphology for the char layer of composite materials were separately investigated using TGA, tensile and charpy impact tests, limiting oxygen index (LOI), UL-94 HB flammability standard (UL-94) and SEM.

The results showed that the AAEDP had been prepared successfully. When the intumescent flame retardant was added into the EP, the LOI of composite material was improved.

The AAEDP can be prepared successfully and can improve the flame resistance of composite material.

The AAEDP has excellent flame-retardant properties and produce no toxic fumes when burnt in case of fire.

The results showed that the phosphorus content of AAEDP was 2.958 Wt.%; the impact and tensile strength of the composite material were 6.417 kJ m⁻² and 38.0 MPa, respectively; and the LOI and UL-94 were 29.7% and V-0 ranking, respectively. The TGA results indicated that the carbon residue ratio can be increased by 1000°C in air. The denser and more uniform structure of residual carbon prevents heat transfer and diffusion, restricts the production of combustible gas and reduces the rate of heat release.

This study aims to explore how and when learning from others promotes creative performance over the contributor’s tenure in the context of open innovation communities.

The authors analyze a publicly available data set that includes 25,923 innovative items developed by 2,194 contributors from an open innovation community of an online game spanning eight years. Logistic regression model is used for analyzing the data.

The results show that multicultural experiences are negatively related to contributor’s creative performance, and this negative relationship weakens as contributor’s tenure increases. While diverse skills are positively related to contributor’s creative performance, and this positive relationship strengthens as contributor’s tenure increases.

This research highlights the importance of online team collaboration in knowledge transfer through learning from others in open innovation communities. By identifying two outcomes of learning from others through online team collaboration, the authors demonstrate the double-edged role of learning from others and advance the understanding on how the effect of learning from others varies over the contributor’s tenure. These results expand the understanding of online team collaboration and provide a new perspective for research on learning from others.

This study aims to explore the mediating effect of digital options on the relationship between emerging information technology investments (ITIs) and firm performance (FP). In particular, it analyses the performance impacts of investments in five emerging technologies of IT or non-IT firms.

Secondary data are collected from Chinese A-share listed companies from 2010 to 2018. The authors propose an econometric model focusing on the impact of ITIs on a firm’s market value and profit. A propensity score matching model is applied to control endogeneity.

The ITIs’ effect on FP is found to be completely mediated by digital options, and the reach of digital options plays a more positive role in the relationship between ITIs and Tobin’s Q, whereas the richness of digital options is stronger between ITIs and return on net assets (ROE). The group study shows that the impact of process technologies such as cloud computing and the Internet of Things has a more profound impact on Tobin’s Q, and the knowledge technologies represented by artificial intelligence, blockchain and big data strongly affect ROE. In addition, the positive relationship between ITIs and FP is unrelated to IT/non-IT firms.

First, the data are based on 219 publicly announced emerging ITIs in China and thus may not be generalizable to other cultural/national contexts. Second, there is a lack of a large sample data set of emerging ITI information in China, and the duration of this study is constrained to the relatively short rise of emerging technologies.

This study provides firm decision-makers with practical implications. The results imply that the effect of ITIs on FP depends on digital options, so both IT firms (e.g., Big Tech giants) and non-IT firms (e.g., incumbents) should discover how to balance firm value and profit in their management of emerging technology investment projects with digital options thinking.

To the best of the authors’ knowledge, this is the first empirical study to investigate the relationship between ITIs and FP from the perspective of digital options, exploring five emerging technologies and considering firm life, size, and state ownership in a sample of Chinese listed firms.