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The sharing economy enables apartment owners to generate income from their assets. “Agoda Homes” is an online travel agent (OTA) that directly competes with Airbnb. A destination has to discover its competitiveness, but few studies have provided an overview of accommodation attributes in each destination, which are crucial to shaping its brand image. This paper aims to illustrate firm-generated content or attributes that apartment owners list about their properties on an OTA platform to comprehend factual information about apartments in each destination with various star ratings and user ratings and to formulate a research model for future studies.

Informational content and accommodation attributes for apartments are automatically collected using a Web scraping tool (the Data Miner). Descriptive statistics and text analysis (word cloud and word frequency) are used to analyze data.

Findings reveal the primary location, facilities, cleanliness and safety attributes for all apartments in each destination, along with star ratings and user ratings. A research framework for scholars is also suggested. Guidelines for stakeholders in the tourism industry are additionally furnished.

This work concentrates on apartments, which have received less attention in the tourism literature. The study gathers factual data from a website to mitigate respondent bias issues inherent in the traditional survey methods.

Artificial intelligence is one of the most significant and active fields of study in the last few years. Artificial intelligence-derived robotic technologies known as chatbots are gaining interest from both academic and industry sectors. By analyzing the development and patterns of research on the chatbot phenomena within the tourism field, this study seeks to develop a theoretical framework for the interaction between chatbots and tourism.

The Web of Science (WoS) database’s 33 articles on chatbots related to travel and hospitality were examined between 2019 and 2024 using VOSviewer software for bibliometric and thematic content analysis.

Research on chatbots for tourism and hospitality appears to be in its early stages. The factors influencing tourists' intentions to use chatbots have been thoroughly researched; the attitudes, perceptions and behavioral intentions of destinations, travel agencies and restaurant patrons regarding chatbots were examined, and it was found that the quantitative research approach was dominant. In addition, the majority of the studies are based on a particular theory or model.

This is one of the first attempts to directly comprehend and depict the interconnected structures of studies on the interaction between chatbots and tourism through the use of network analysis. Furthermore, the study’s findings can offer academics a comprehensive viewpoint and a reference manual for more accurate assessment and oversight of the chatbot-tourism interaction. Regarding the lack of research on the topic and the fragmented structure of the studies that exist, it is imperative to provide both a comprehensive overview and a roadmap for future investigations into the usage of chatbots in the travel and hospitality sector.

The importance of service firms cooperating with digital platforms is widely acknowledged. The authors study three contractual relationships (fixed-cost, cost-sharing, and profit-sharing) between service firms (specifically hotels) and digital platforms in a highly fragmented service supply chain to examine which of these contract types optimizes profits.

The authors extend prior models analyzing the optimal expected total profit from the travel service firm (hotel)–digital platform relationship, providing new insights into each contract type’s ability to coordinate decentralized systems and optimize profits for both parties.

This study finds that fixed cost contracts cannot coordinate the decentralized system. Cost-sharing contracts can coordinate the decentralized system but only allow one channel profit split. In contrast, profit-sharing contracts may not always perfectly coordinate the decentralized system but support alternative profit allocations. Practically, both profit-sharing and cost-sharing contracts are preferable to fixed-cost contracts.

The paper includes implications for travel service firm managers to consider when structuring contracts with digital platforms to focus on profit optimization. Profit-sharing contracts are most preferable when cost and revenue data are fully shared between parties, while cost-sharing contracts are preferable over fixed-cost contracts.

This study extends prior investigations into the utility of different contract types on the optimal profit of a travel service firm (hotel)-digital platform provider relationship. The research fills a gap in the literature concerning the contracts used in these relationship types.

The COVID-19 pandemic has significantly impacted global tourism, with international travel bearing the burden of restrictions. Domestic tourism has also faced substantial challenges. This paper aims to analyse the impact of the COVID-19 pandemic on domestic tourism in Spain, focusing on travel from Madrid (the country’s capital) to other tourist destinations.

Mobile phone data has been used to study the evolution of tourist trips over the summers of 2019, 2020 and 2021. Regression models are used to explain the number of visitors at destinations.

The pandemic not only caused a drastic drop in tourist flows but also disrupted the overall pattern of the domestic flow system. Winning destinations were typically areas in proximity to Madrid and less densely populated destinations, while urban destinations were major losers. The preferences of domestic tourists varied notably by income group, but the decrease in trip volumes showed only marginal differences.

The paper demonstrates the potential of mobile phone data analysis to study the uneven impact of external shocks, such as the COVID-19 pandemic, on tourist destinations. This approach considers spatial resilience heterogeneity within regions or provinces. By incorporating income information, the analysis introduces a social dimension to highly detailed spatial data, surpassing traditional studies conducted at the regional or national levels.

COVID-19大流行对全球旅游业产生了重大影响，国际旅行受到了限制的影响最为严重。国内旅游也面临着重大挑战。本文分析了COVID-19大流行对西班牙国内旅游的影响，重点关注从马德里（该国首都）到其他旅游目的地的旅行。

本研究使用移动电话数据研究了2019年、2020年和2021年夏季旅游出行的演变。采用回归模型解释了各目的地游客数量。

大流行不仅导致了旅游流量急剧下降，还扰乱了国内流动系统的总体模式。获胜的目的地通常是马德里附近的地区和人口较稀少的目的地，而城市目的地是主要的输家。国内游客的偏好在收入群体之间有明显差异，但旅行量的减少只显示出边际差异。

本文展示了使用移动电话数据分析研究外部冲击（如COVID-19大流行）对旅游目的地的不均匀影响的潜力。该方法考虑了区域或省份内的空间弹性异质性。通过整合收入信息，该分析为高度详细的空间数据引入了社会维度，超越了传统在区域或国家水平进行的研究。

The study explores the possibility of developing a valid scale for integrated management of heritage sites to bring a holistic approach to heritage properties' conservation practices.

The study followed the exploratory sequential method. An in-depth interview was adopted for exploring indicators, and a questionnaire survey was administered for descriptive analysis.

Cultural resources conservation strategies have been analyzed from a tourist, local communities and stakeholder's perspective with local-specific indicators. The study indicates that a multi-dimensional approach that integrates tourists, local communities and other stakeholders-based indicators can be developed at the destination level for the integrated management of heritage properties. Tourist-centric, local community-specific and stakeholder-oriented approaches could act as catalysts for more pragmatic conservation practices in the local areas based on the site-specific indicators.

The study is limited to lesser-known heritage sites located in the southern provincial states of India. The technical conservation strategies on the structure and architecture are not part of the study. Theoretical implications on the study of this kind can contribute to the literature as it throws light on future studies seeking local-centric conservation and management practices of heritage sites hitherto less explored in the domain of conservation science. The scale provides insight into the appropriate form of intervention that the local communities, tourists and other stakeholders can do at the heritage sites, hence the possibility of garnering the attention of other discipline strivings towards the conservation of heritage sites and to apply along with other relevant variables. It is expected that the study might expedite the knowledge accumulation in conservation science.

The scale can be used in a similar context for the integrated management of heritage sites. The study can assist the policymakers and planners in seeking the support of stakeholders, local communities and tourists for the implementation of heritage conservation and management programs. Such a local-centric management strategy promoting responsible consumption and production could contribute to SDG 12. Further, the study can also contribute towards SDG 11.4, which calls for strengthening the effort to protect and safeguard cultural and natural heritage. This scale can be a tool for destination management organizations (DMOs) to understand the level of intervention of local communities, tourists and other stakeholders at the heritage site.

The integrated management approach of heritage conservation immensely helps the lesser-known heritage sites the world over as such structures are out of the focal point of government funding and other conservation efforts. The synergy of the integrated approach could protect lesser-known unfunded heritage sites, and thereby, the cultural reflections of the community concerned can be made available for future visitors’ consumption.

The study attempted to understand the conservation approaches for lesser-known heritage sites with the support of both demand and supply-side stakeholders. Such a collaborative approach is the first of this kind in the conservation of heritage sites in India.

This paper aims to assess the sense-of-community role in affecting young Muslim loyalty towards Muslim-majority tourism destinations. Specifically, this research assesses the sense of community dimension in the halal tourism context and evaluates its effects on destination satisfaction, image and loyalty.

This research used a quantitative approach by using data from 376 young Indonesian Muslim tourists with past travel experiences to destinations where Muslims are the majority. The dimension of the sense of community was evaluated using exploratory factor analysis. The association between variables was tested using partial least square-structural equation modelling.

The finding exhibits three notable sense of community dimensions: membership, influence and need fulfilment and emotional connection. Emotional connection shapes, directly and indirectly, destination loyalty, while influence and need fulfilment affect destination loyalty by satisfaction and destination image mediating role. Lastly, membership has no impact on developing destination loyalty.

This study offers tourism destinations in Muslim-majority countries an opportunity to draw and create loyalty among young Muslim tourists. Besides offering superior halal services and products, Muslim-majority tourism destinations need to develop young Muslim tourists' emotional connection to the destinations.

To the best of the authors’ knowledge, this is the first empirical examination of the sense of community's role in influencing tourist loyalty, specifically in halal tourism.

This research paper aims to investigate the predictors and outcomes of immersive technology adoption in tourism.

PLS-SEM is used for data collected from tourists visiting the UAE and Egypt to examine predictors and consequences of adoption.

It is revealed that perceived ease of use, enjoyment, immersion, usefulness and attitude towards technology predict immersive technology adoption. It is also revealed that the adoption affects tourists’ perceived value and engagement, which, in turn, affects tourists’ satisfaction and loyalty.

The study has integrated a research model that combines both antecedents and consequences of immersive technology adoption where few empirical investigations were revealed to draw conclusions on this research area. Also, missing relations have been included and tested in the research model.