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This study aims to investigate the promoting effects of the quantity and quality of online review user-generated photos (UGPs) on perceived review usefulness. The research further tests the hindering effect of human facial presence in review photos on review usefulness.

Based on review samples of restaurants in a tourist destination Las Vegas, this study used an integrated method combining a machine learning algorithm and econometric modeling.

Results indicate that the number of UGPs depicting a restaurant’s food, drink, menu and physical environment has positive impacts on perceived review usefulness. The quality of online review UGPs can also enhance perceived review usefulness, whereas facial presence in these UGPs hinders perceived review usefulness.

Findings suggest that practitioners can implement certain tactics to potentially improve consumers’ willingness to share more UGPs and UGPs with higher quality. Review websites could develop image-processing algorithms for identifying and presenting UGPs containing core attributes in prominent positions on the site.

To the best of the authors’ knowledge, this study is the first to present a comprehensive analytical framework investigating the enhancing or hindering roles of review photo quantity, photo quality and facial presence in online review UGPs on review usefulness. Using the heuristic-systematic model as a theoretical foundation, this study verifies the additivity effect and attenuation effect of UGPs’ visual elements on judgements of online review usefulness. Furthermore, it extends scalable image data analysis by adopting a deep transfer learning algorithm in hospitality and tourism.

This study aims to investigate the influence of the reviewed establishment’s price level and the user’s social network size and reputation status on consumers’ tendency to post more visual imagery content. Furthermore, it explores the moderating effects of user experiences and geographic distance on these dynamics.

This study adopts a multi-method approach to explore both the determinants behind the sharing of user-generated photos in online reviews and their internal mechanisms. Using a comprehensive secondary data set from Yelp.com, the authors focused on restaurant reviews from a prominent tourist destination to construct econometric models incorporating time-fixed effects. To enhance the robustness of the authors’ findings, the authors complemented the big data analysis with a series of controlled experiments.

The reviewed establishments price level and the users reputation status and social network size incite corresponding motivations conspicuous display “reputation seeking” and social approval motivating users to incorporate more images in reviews. “User experiences can amplify the influence of these factors on image sharing.” An increase in the users geographical distance lessens the impact of the price level on image sharing, but it heightens the influence of the users reputation and social network size on the number of shared images.

As a result of this study, high-end establishments can increase their online visibility by leveraging user-generated visual content. A structured rewards program could significantly boost engagement by incentivizing photo sharing, particularly among users with elite status and extensive social networks. Additionally, online review platforms can enhance users’ experiences and foster more dynamic interactions by developing personalized features that encourage visual content production.

This research, anchored in trait activation theory, offers an innovative examination of the determinants of photo-posting behavior in online reviews by enriching the understanding of how the intricate interplay between users’ characteristics and situational cues can shape online review practices.

The purpose of this study is to test the local impact of COVID-19 pandemic on hotel performance at the individual property level, and further examine the roles of hotel attributes and business mix in potentially moderating or intensifying the impact of a crisis.

Using a sample of 5,090 hotel properties in Texas, USA from January 2020 to December 2021, this study estimates a monthly hotel performance model to evaluate how the pandemic affected hotels’ operational performance based on revenue per available room.

Results show that a 10% increase in the monthly number of confirmed COVID-19 cases led to a 0.522% decrease in hotel performance. Also, a series of moderators were identified within the pandemic–performance relationship: the negative impact of the pandemic was more severe among higher-end hotels and newer hotels; urbanization and localization diseconomies prevailed during the pandemic; and there was a smaller negative effect of COVID-19 on high rated hotels in the category of economy hotels.

The moderators highlighted in this paper shed light on the heterogeneity of COVID-19’s effects on hotel operations. Findings enrich the hospitality literature by considering business resilience in relation to the pandemic.

The authors proposed a conceptual model by examining the influence of threats to their freedom on tourists’ psychological distance including social distance, spatial distance, and temporal distance, which effect psychological reactance and the consequent online Airbnb booking intentions. Furthermore, media intrusiveness as a moderator determines the boundary conditions between perceived threats to their freedom and social distance, spatial distance, and temporal distance.

Data was gathered from 491 Chinese travelers to provide empirical evidence. The authors performed data analysis in Amos 26.0 using structural equation modeling (SEM) and Hayes (2013) PROCESS macro.

The findings positively reinforced all the structural relationships of the study. Notably, media intrusiveness significantly moderates the association between perceived threats to their freedom and psychological distance (i.e. social distance, spatial distance, and temporal distance).

The findings contribute significantly to the field of social psychology, advertising, and consumer behavior derive prolific implications for policymakers and sharing economy platforms. Lastly, by identifying limitations, this research opens doors for future scholars.

Governments' acute precautionary measures in response to the COVID-19 outbreak have confined individual freedom across the globe. This study illuminates how tourists conceive these preventative measures as perceived threats to their freedom, and subsequently engage psychological reactance.

World Heritage Sites (WHSs), as crucial tourist attractions, have been demonstrated to promote inbound tourism development; however, no study has analyzed its impact on the origin distribution of inbound tourist flows (ODITFs), leaving a research gap. This study aims to apply power law to assess ODITFs and explore the impact of WHSs on ODITFs.

This study applied the power law of rank-size distribution to calculate ODITFs in 167 countries/regions from 1997 to 2018 and used the panel data model to analyze the effect of WHSs on ODITFs.

WHSs could positively impact ODITFs to be more even. Among them, a cultural WHS shows a more pronounced effect on ODITFs, while the effect of natural WHSs is negligible.

This study advances knowledge about the impact of WHSs on inbound tourism from the standpoint of ODITFs, contributing to the inbound tourist flows theory and tourist attraction theory. In a realistic sense, WHSs, as crucial tourist attractions, could make ODITFs more even, implying that destination management organizations could gain higher growth of incremental tourists from tail markets rather than head markets when increasing tourist attractions.

全球视角下联合国教科文组织世界遗产（whs）对入境游客源地分布的影响

世界遗产地（WHS）作为重要的旅游景点, 已被证明可以促进入境旅游的发展。然而, 目前没有研究分析其对入境游客源地分布（ODITF）的影响。本文旨在应用幂律评估入境游客源地分布, 并探讨世界遗产对入境游客源地分布的影响。

本研究应用序位-规模分布的幂律计算1997年至2018年167个国家/地区的入境游客源地分布, 并使用面板数据模型分析世界遗产对入境游客源地分布的影响。

世界遗产可以对入境游客源地分布产生积极影响, 使入境游客源地分布更加均匀。其中, 世界文化遗产对入境游客源地分布的影响更为显着, 而世界自然遗产的影响可以忽略不计。

本文从入境游客源地分布的角度, 推进了世界遗产对入境旅游影响的认识, 为入境旅游流理论和旅游景点理论做出了贡献。在现实意义上, 世界遗产作为重要的旅游景点, 可以使入境游客源地分布更加均衡, 这意味着目的地管理组织在增加旅游景点时, 可以从尾部市场获得更多的游客增量。

El impacto del Patrimonio de la Humanidad de la UNESCO en la distribución del origen de los flujos turísticos entrantes desde una perspectiva global

Resumen

se ha demostrado que el Patrimonio de la Humanidad de la UNESCO, como atracciones turísticas cruciales, promueven el desarrollo del turismo receptor; sin embargo, ningún estudio ha analizado su impacto en la distribución del origen de los flujos turísticos entrantes (DOFTE), lo que deja un vacío en la investigación. Este documento tiene como objetivo aplicar la ley de potencias para evaluar la DOFTE y explorar el impacto del Patrimonio sobre ella.

este estudio aplicó la ley de potencias de la distribución del tamaño del rango para calcular la DOFTE en 167 países/regiones desde 1997 hasta 2018 y utilizó el modelo de datos de panel para analizar el impacto del Patrimonio de la Humanidad en la DOFTE.

el Patrimonio de la Humanidad podría influir positivamente en la DOFTE para que sea más uniforme. Entre ellos, el Patrimonio cultural muestra un efecto más pronunciado sobre la DOFTE, mientras que el efecto del Patrimonio natural es insignificante.

este artículo avanza en el conocimiento del impacto del Patrimonio de la Humanidad en el turismo entrante desde la perspectiva de la DOFTE, contribuyendo a la teoría de los flujos turísticos entrantes y a la teoría de la atracción turística. En un sentido realista, el Patrimonio de la Humanidad, como atracciones turísticas cruciales, podrían hacer que la DOFTE fuera más uniforme, lo que implica que las organizaciones de gestión de destinos (OGD) podrían obtener un mayor crecimiento de turistas incrementales procedentes de los mercados secundarios en lugar de los mercados principales al aumentar las atracciones turísticas.