Search results

The purpose of this paper is to find the event memory characteristics hidden in trade data.

First, historical trade data are analyzed to define the events described by multi‐dimensional characteristic variables. The variables containing information are employed to build the event description patterns. Furthermore, a search engine is developed for calendar events, which can search for events in historical data and produce a collection of events. The search engine also extracts relevant system reaction phenomena described by trend distribution for each event pattern. Finally, both event patterns and system reactions construct the episodic memory model.

The event patterns and the system reactions are used to define the episodic memory model. The search methods for the episodic memory model obtained from trade data set are given.

Accessibility and availability of data are the main limitations affecting where the method can be applied.

The method is helpful for traders when judging the current trade situation from historical memory.

The paper presents a new episodic memory modeling method based on trade data.

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.

With the continuous development of intelligent technologies, knowledge graph, the backbone of artificial intelligence, has attracted much attention from both academic and industrial communities due to its powerful capability of knowledge representation and reasoning. Besides, knowledge graph has been widely applied in different kinds of applications, such as semantic search, question answering, knowledge management, and so on. In recent years, knowledge graph techniques in China are also developing rapidly and different Chinese knowledge graphs have been built to support various applications. Under the background of “One Belt One Road (OBOR)” initiative, cooperating with the countries along OBOR on studying knowledge graph techniques and applications will greatly promote the development of artificial intelligence. At the same time, the accumulated experience of China on developing knowledge graph is also a good reference. Thus, in this chapter, the authors mainly introduce the development of Chinese knowledge graphs and their applications. The authors first describe the background of OBOR, and then introduce the concept of knowledge graph and three typical Chinese knowledge graphs, including Zhishi.me, CN-DBpedia, and XLORE. Finally, the authors demonstrate several applications of Chinese knowledge graphs.

Given the importance of spatial effects in improving the accuracy of hotel demand forecasting, this study aims to introduce price and online rating, two critical factors influencing hotel demand, as external variables into the model, and capture the spatial and temporal correlation of hotel demand within the region.

For high practical implications, the authors conduct the case study in Xiamen, China, where the hotel industry is prosperous. Based on the daily demand data of 118 hotels before and during the COVID-19 period (from January to June 2019 and from January to June 2021), the authors evaluate the prediction performance of the proposed innovative model, that is, a deep learning-based model, incorporating graph convolutional networks (GCN) and gated recurrent units.

The proposed model simultaneously predicts the daily demand of multiple hotels. It effectively captures the spatial-temporal characteristics of hotel demand. In addition, the features, price and online rating of competing hotels can further improve predictive performance. Meanwhile, the robustness of the model is verified by comparing the forecasting results for different periods (during and before the COVID-19 period).

From a long-term management perspective, long-term observation of market competitors’ rankings and price changes can facilitate timely adjustment of corresponding management measures, especially attention to extremely critical factors affecting forecast demand, such as price. While from a short-term operational perspective, short-term demand forecasting can greatly improve hotel operational efficiency, such as optimizing resource allocation and dynamically adjusting prices. The proposed model not only achieves short-term demand forecasting, but also greatly improves the forecasting accuracy by considering factors related to competitors in the same region.

The originalities of the study are as follows. First, this study represents a pioneering attempt to incorporate demand, price and online rating of other hotels into the forecasting model. Second, integrated deep learning models based on GCN and gated recurrent unit complement existing predictive models using historical data in a methodological sense.

Fear appeals in advertising communication are considered by advertisers when other types of advertising appeals do not achieve expected effects. Fear appeals, by arousing the fear that something may threaten consumers’ present lives, are often adopted to persuade individuals to take a particular action. Although this topic has been widely studied, the internal operation mechanism of fear appeals in consumers has not been fully understood or agreed upon.

Three experiments were conducted where the type of fear appeal was manipulated (i.e. physical fear appeal or social ear appeal), as well as consumers’ consideration of future consequences (CFC) and mental imagery approaches.

This study examined the effects of fear appeal on mental imagery fluency and how it affects advertising effectiveness and the moderating effect of consumers’ CFC were discussed. When receiving advertisements with physical fear appeals, consumers with low CFC had greater mental imagery fluency than did those with high CFC. Furthermore, consumers’ purchase intentions could be improved by increasing consumers’ mental imagery fluency on fear appeal. Therefore, the interaction between fear appeal and CFC on purchase intention was mediated by mental imagery fluency. This study found that consumers responded differently to fear appeal advertising when they engaged in different mental imagery approaches.

The present study adds to social marketing literature by showing how consumers’ mental imagery fluency influence the fear appeal effectiveness, and this study’s results also enable social marketers to understand the two factors (i.e. consumers’ CFC level and mental imagery approaches) that affect the influence of fear appeals on consumers’ purchase intentions. Moreover, social marketers are recommended to provide consumers with advertising information by using various message types to facilitate consumers’ imagination of advertising appeals. This heightens the importance of consumers’ acceptance and absorption of advertising content, in turn, strengthening their purchase intentions.

The number of people using running apps has increased. Accordingly, a growing number of sports brands are launching running apps in hopes of improving their connection with consumers and thereby enhancing consumers' brand preference and purchase intention. This study adopted an integrated perspective to explore the effects of perceived usefulness, perceived ease of use and self-expression on consumers' continued use of running apps.

Convenience sampling was conducted among consumers in Taiwan (n = 251). Structural equation modeling using AMOS 21 was performed to analyze the data.

The study results revealed that (1) users' perceived usefulness, perceived ease of use and self-expression significantly positively affected continuance intention, and (2) continuance intention was significantly positively correlated with word-of-mouth (WOM) and brand intimacy. Furthermore, the study confirmed the moderating effect of consumers' relationship norms on the correlation between continuance intention and WOM and brand intimacy.

Amid the increasing emphasis on self-expression, almost all running apps endeavor to enable users to share their achievements, such as accumulated mileage and routes. However, research has rarely focused on whether these features influence consumers' continued use of running apps and whether these influences in turn affect consumers’ attitudes toward a brand. Therefore, this study explored the effect of self-expression on the continued use of running apps.

Because of an increase in consumer awareness and the ease of information dissemination on the Internet, brands have increasingly become the target of online criticism. Several factors affect consumers’ reactions to public criticism against brands that they support. The present study investigated the interactive effects of psychological ownership, agency–communion orientation, and internal attribution on self-threat in the context of such criticism.

Three studies were conducted to test several research hypotheses. The psychological ownership, agency–communion orientation, and internal attribution of the participants in this study were manipulated using an experimental scenario. Subsequently, they completed a questionnaire with items used to assess purchase intention, self-threat, and demographic variables and for performing manipulation checks.

When a brand is criticized, (1) consumers with high psychological ownership of the brand are likely to buy more of that brand’s products, (2) communion-oriented consumers with high psychological ownership of the brand experience greater self-threat relative to those with low psychological ownership, and (3) agency-oriented consumers experience a consistent level of self-threat regardless of their level of psychological ownership.

Brands should endeavor to enhance consumers’ psychological ownership of the brand to increase their support in times of crisis.

This study investigated how psychological ownership of a brand among consumers affected their reactions when a brand was criticized. The effect of self-threat as a mediating mechanism was also considered. Furthermore, agency and communion orientation were proposed as crucial moderators that should be considered in research on consumer–brand relationships.

As buyers and suppliers seek to create value, they face the challenge of creating an environment that promotes coordination and information sharing and discourages opportunism. While the literature suggested dyadic mechanisms to create such an environment, this study focuses on ties beyond the buyer–supplier dyad. Specifically, close connections to one's partner's partners (CPP) are crucial in the realization of benefits for buyers and suppliers.

Drawing from embeddedness theory and governance theory, the authors developed a contingency framework to examine when CPP are beneficial or counterproductive considering two dyadic attributes – relational capital (RC) and partner dependence. Analyses were conducted using data from a dyadic survey complemented with archival data on 106 buyer–supplier relationships (BSRs).

The study reveals that CPP both help and hurt in the realization of benefits. Stark asymmetries exist between the impact of CPP on the buyer and supplier sides. For buyers, CPP exert a direct positive effect on operational and innovation benefits. For suppliers, the effect of CPP on operational and innovation benefits is contingent on buyer dependence and RC – CPP serves as a substitute for buyer dependence and RC. There are no such contingency effects for buyers. Further analysis identifies situations for suppliers when CPP hurt the realization of benefits.

The study highlights the importance of CPP to foster efficiency and innovation within BSRs and illustrates how their impact varies across contingency conditions and across the parties within a dyad.

The tourist gaze remains a key concept in tourism research. The purpose of this paper is to comprehend the theoretical and empirical development of the tourist gaze notion and its contributions to tourism knowledge, identifying potential research directions by reviewing and analyzing articles that have defined, refined and applied the concept of the tourist gaze.

The study identified 109 relevant research papers primarily through the Web of Science and Scopus databases. Google Scholar, ResearchGate.net and Academia.edu were used to capturing additional work not indexed in the key databases. Qualitative content analysis was used to map the evolution of the concept, distinguish between different perspectives and identify gaps in the tourist gaze literature.

This “state of the art” paper on tourist gaze outlines Foucault’s original work on gaze and power, which underpins subsequent theorization within tourism. The study identifies how the tourist gaze operates in different contexts and circumstances allowing the development of gaze theory. Importantly, the evolution of the gaze theory is presented after analyzing the knowledge gaps, the contexts in which it was used, the methodologies with which it was applied. Based on the findings, the study proposes future works of gaze with the use of technology, science, nature and social media.

This paper is among one of the first states of the art papers in tourism literature that comprehensively analyzes the works on the tourist gaze, tracing its evolution and identifying future research directions to address gaps in existing knowledge.

旅游凝视仍然是当今旅游研究中的关键概念之一。本文的主要目的是理解旅游凝视的理论与实践及其对旅游知识的的贡献, 通过回顾性分析识别其潜在的研究方向。

该研究主要通过Web of Science和Scopus数据库检索确定的109篇相关研究论文进行分析。为了保证研究的完整性分析, 本文也使用了Google Scholar, ResearchGate.net和Academia.edu检索了有关旅游凝视的研究成果并补充到分析数据库中。本文采用了定性的内容分析法用于分析旅游凝视概念的演化、区别不同的观点, 并识别旅游凝视文献的不足之处。

研究总结了福柯关于凝视与权力的原创性研究, 强调他的相关工作为随后的旅游研究的理论化奠定了基础。本文识别了该理论在不同的旅游情景和环境下所产生的影响。特别是基于知识的鸿沟与不足, 分析了旅游凝视理论的演化过程、研究内容针对性以及所涉及方法论的应用。基于本文的结论, 本文提出了未来旅游凝视理论在技术、科学、自然与社会媒体方面的研究方向。

本文是全面分析旅游凝视学术成果、追溯其演变、确定其未来研究方向, 并弥补现有相关知识不足的一篇重要的综述性论文。

la mirada del turista sigue siendo un concepto clave en la investigación sobre el turismo. El objetivo principal de este trabajo es comprender el desarrollo teórico y empírico de la noción de mirada turística y sus aportes al conocimiento del turismo, identificando posibles direcciones de investigación a través de la revisión y análisis de artículos que han definido, afinado y aplicado el concepto de mirada turística.

El estudio identificó 109 artículos de investigación relevantes principalmente a través de las bases de datos Web of Science y Scopus. Se utilizaron Google Scholar, ResearchGate.net y Academia.edu para capturar trabajo adicional no indexado en las bases de datos. El análisis de contenido cualitativo se utilizó para mapear la evolución del concepto, distinguir entre diferentes perspectivas e identificar brechas en la literatura sobre la mirada turística.

El estudio del "estado del arte" sobre la mirada de los turistas, describe el trabajo original de Foucault sobre la mirada y el poder, que sustenta la teorización posterior en el turismo. El estudio identifica cómo opera la mirada del turista en diferentes contextos y circunstancias, permitiendo el desarrollo de la teoría de “la mirada”. Es importante destacar que la evolución del concepto de mirada se presenta luego de analizar las brechas de conocimiento, los contextos en los que se utilizó, las metodologías con las que se aplicó. Con base en los hallazgos encontrados, el estudio propone futuros trabajos “de mirada” con el uso de la tecnología, la ciencia, la naturaleza y las redes sociales.

Este artículo es uno de los primeros trabajos de revisión de la literatura sobre el turismo que analiza de manera integral los trabajos sobre la mirada del turista, rastreando su evolución e identificando futuras direcciones de investigación para abordar las brechas en el conocimiento existente.