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The purpose of this paper is to investigate the impact of online service quality on swift guanxi that influences customer repurchase intention and the moderating role of gender in the relationship between online service quality and swift guanxi.

Based on survey data obtained from 274 college students, structural equation modeling was used to test the research hypotheses.

The results show that the dimensions of online service quality (i.e. perceived control, convenience and customer service) are positively related to buyer-seller swift guanxi, which influences repurchase intention. Additionally, men are driven mainly by perceived control and service convenience when establishing swift guanxi, whereas women care more about customer service.

Online service quality is the key factor underlying customer repurchase intention. In addition, gender differences exist in many aspects of online shopping including information processing, perceived service, and perceived risk. This is one of the first empirical studies that empirically examine the effects of three dimensions of online service quality on swift guanxi and take gender differences into consideration. Based on the conceptual and empirical evidence, this study provides the practical and theoretical implications of these findings.

Studies on developed economies showed that imposing taxes on animal-based foods could effectively reduce agricultural greenhouse gas emissions (AGHGEs), while this taxation may not be appropriate in developing countries due to the complex nutritional status across income classes. Hence, this study aims to explore optimal tax rate levels considering both emission reduction and nutrient intake, and examine the heterogenous effects of taxation across various income classes in urban and rural China.

The authors estimated the Quadratic Almost Ideal Demand System model to calculate the price elasticities for eight food groups, and performed three simulations to explore the relative optimal tax regions via the relationships between effective animal protein intake loss and AGHGE reduction by taxes.

The results showed that the optimal tax rate bands can be found, depending on the reference levels of animal protein intake. Designing taxes on beef, mutton and pork could be a preliminary option for reducing AGHGEs in China, but subsidy policy should be designed for low-income populations at the same time. Generally, urban residents have more potential to reduce AGHGEs than rural residents, and higher income classes reduce more AGHGEs than lower income classes.

This study fills the gap in the literature by developing the methods to design taxes on animal-based foods from the perspectives of both nutrient intake and emission reduction. This methodology can also be applied to analyze food taxes and GHGE issues in other developing countries.

The control of weld penetration in gas tungsten arc welding (GTAW) is required for a “teach and playback” robot to overcome the gap variation in the welding process. This paper aims to investigate this subject.

This paper presents a robotic system based on the real‐time vision measurement. The primary objective has been to demonstrate the feasibility of using vision‐based image processing to measure the seam gap in real‐time and adjust welding current and wire‐feed rate to realize the penetration control during the robot‐welding process.

The paper finds that vision‐based measurement of the seam gap can be used in the welding robot, in real‐time, to control weld penetration. It helps the “teach and playback” robot to adjust the welding procedures according to the gap variation.

The system requires that the seam edges can be accurately identified using a correlation method.

The system is applicable to storage tank welding of a rocket.

The control algorithm based on the knowledge base has been set up for continuous GTAW. A novel visual image analysis method has been developed in the study for a welding robot.

The purpose of this paper is to propose the strategic choice of innovative university library, including its definitions, structure framework. As a case study, the construction practice and idea development of the innovative library in Shanghai Jiao Tong University are also to be introduced and explained.

The paper combines the methods of scenario analysis and theoretical explanation, modeling presentation and case study.

A model of innovative university library and IC²@SJTUL, a kind of new mode adapting to it are put forward in the paper. These modes apply to university libraries, which need innovation and support training of innovative users.

At present the necessary have been built but environments for IC²@SJTUL its effects need practice testing.

The basic definition and structure framework of an innovative university library are designed in this paper. The pioneer concept, i.e. IC², is demonstrated and the new mode of IC²@SJTUL is also presented.

Free trial is an effective strategy to gaining users’ data so as to strengthen and optimize product design. The purpose of this paper is to understand the IT companies' dynamic decision-making behavior in the free trial of IT products and services context based on a three-stage theoretical framework and users' decision-making behavior in the respective stage.

A three-stage methodology is proposed to clarify relevant decision problems and actions in each stage from IT companies' and users' perspectives, respectively. It then investigates relating variables on IT companies' decision-making based on extant research and users' decision-making.

In this study, the authors argue that the IT companies have to make the offering, implementation and retention decision in different stage during the whole free trial process. Each decision is determined by several variables from their own and users, namely the offering decision is determined by product characteristics, network effects, product life cycle and WOM (word of mouth); the implementation decision is determined by the quality of products and services, trial type, incentive measures on user's usage and communication strategy; and the retention decision is determined by the product and price strategy.

The results are practical and can be used by IT companies as a decision basis or reference to make reliable decisions so that IT companies can take target measures to ensure the effectiveness of their free trial strategy so as to meet their users' needs based on products designed by data driven. Thus, the ultimate goal of supply chain management is achieved.

In this study, the decision-making process in the free trial of IT products and services context is investigated as a whole for the first time. From the IT companies' perspective, the process includes offering, implementation and retention decision stages, which are continuous and inseparable. The variables that determine IT companies' decision-making are identified based on users' decision and action. Hence, it represents a brand-new whole process perception to clearly understand the dynamic of the IT companies' decision-making. Considering users' decision and action, the final decisions of the IT companies will be more practical in respect of motivating, retaining and upgrading users.

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.

The purpose of this paper is to provide a short review of tourism forecasting literature and general summary of the trends and developments in tourism forecasting and point out directions for future research in the next 75 years.

This is a general literature overview.

Key trends are identified for next 75 years.

First overview in tourism forecasting that provides foresight on long-term future trends (over next 75 years).

The aim of this paper is to provide a narrative review of previous research on tourism demand modelling and forecasting and potential future developments.

A narrative approach is taken in this review of the current body of knowledge.

Significant methodological advancements in tourism demand modelling and forecasting over the past two decades are identified.

The distinct characteristics of the various methods applied in the field are summarised and a research agenda for future investigations is proposed.

本文旨在对先前关于旅游需求建模和预测的研究进行叙述性回顾并对未来潜在发展进行展望。

本文采用叙述性回顾方法对当前知识体系进行了评论。

本文确认了过去二十年旅游需求建模和预测方法论方面的重要进展。

本文总结了该领域应用的各种方法的独特特征, 并对未来研究提出了建议。

El objetivo de este documento es ofrecer una revisión narrativa de la investigación previa sobre modelización y previsión de la demanda turística y los posibles desarrollos futuros.

En esta revisión del marco actual de conocimientos sobre modelización y previsión de la demanda turística y los posibles desarrollos futuros,se adopta un enfoque narrativo.

Se identifican avances metodológicos significativos en la modelización y previsión de la demanda turística en las dos últimas décadas.

Se resumen las características propias de los diversos métodos aplicados en este campo y se propone una agenda de investigación para futuros trabajos.

The control of weld penetration in gas tungsten‐arc welding (GTAW) is required for fully automated systems to overcome variations in the welding process. The surface depression of weld pool, or weld pool height, has a close relationship with width of the backside bead in the full‐penetrated weld. The purpose of this paper is to inspect the pool height.

A fast linear approach, based on shape from shading (SFS) algorithm, was employed to reconstruct a 3D shape of welding pool from a 2D image, which was obtained from a real welding pool. Then the pool height can be extracted. Furthermore, three methods were introduced to improve the above algorithm.

The reconstructed pool height was in good agreement with the real height of weld pool from experiments.

The algorithm requires a uniform reflection on the pool surface.

This method is applicable to inspect weld pool height in GTAW. It is a basis for future work on control of weld penetration.

A faster SFS algorithm has been introduced to extract weld pool height in real‐time. Moreover, the algorithm was improved to fit for extracting the surface shape of weld pool.

The weld seam detection is required for a welding robot to preplan the weld seam track before the actual welding. The purpose of this paper is to investigate this subject in natural lighting conditions.

This paper presents an efficient algorithm of weld seam detection for butt joint welding from a single image. The basic idea of the approach is to find a pair of weld seam edges in local area first. Then, starting from the two endpoints of each edge, search for the remnant edge by iterative edge detection and edge linking.

The proposed method is insensitive to the variance of the background image and can apply to most shapes of weld seams in butt joint welding.

The proposed method is designed only for butt joint welding, and it is performed before actual welding.

The system is applicable to preplan the weld trajectory for most shapes of weld seams in butt joint welding. In addition, the proposed technique may have some potential applications in the field of tailor‐welded blanks.

The proposed algorithm is based on local image processing and detects the whole weld seam from a single image without giving any initial seam, which is insensitive to the variance of the background image and has low‐computation cost.