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This study aims to identify the individual and trip characteristics that are associated with intention to use peer-to-peer accommodation, including past experience (users vs non-users), accommodation preferences, traveler personality and tripographic variables.

To compare Airbnb users and non-users, quantitative research was conducted to test for group differences. A questionnaire was designed and administered face-to-face in major tourist areas. Quota sampling was used to ensure comparable samples of Airbnb users and non-users.

While Airbnb users and non-users expressed few differences in their demographics and perceived importance of accommodation attributes, the two groups vary in their perception of Airbnb and evaluation of Airbnb compared to hotels, suggesting some positive and negative changes after experiencing Airbnb. Respondents who were more allocentric were more likely to use Airbnb. Hotels were preferred for traveling with family as well as shorter trips, while Airbnb was preferred for traveling with friends as well as longer trips.

This study identified several challenges for Airbnb and other sharing platforms, including consumers’ security concerns, potential decrease in the likelihood of repeat usage and low likelihood of using Airbnb when traveling with family.

While previous studies focused more on existing customers of peer-to-peer accommodation, this study compared users and non-users and identified key differences in their perceptions. The use of traveler personality and tripographic variables to examine intention to use Airbnb provides a unique perspective to consider Airbnb as an “allocentric destination” and the type of trips that are more compatible with the Airbnb experience.

This paper aims to provide a snapshot of key learnings about paid online peer-to-peer accommodation trading, as it relates to tourism and hospitality, and to identify future research questions.

The paper paints a picture and discusses research conducted in the past, which relates to paid online peer-to-peer accommodation, in brief. It also lists a number of specific research questions which should be investigated in future.

Some of the key topics, such as the business model of facilitators of peer-to-peer trading and the necessary regularly responses, have been extensively studied. The focus should now turn on how peer-to-peer trading of travel-related services can best be leveraged to the benefit of economies, communities and people.

The main value of this perspective paper lies in offering a succinct overview of research into paid online peer-to-peer accommodation and pointing to key questions for future research.

Due to their very different contexts, the responses made by property hosts to online reviews can differ from those posted by hotel managers. Thus, the purpose of this study is to investigate the determinants of the responding behavior of hosts on peer-to-peer property rental platforms.

This study applied a comprehensive framework based on the theory of planned behavior. Empirical models are constructed based on 89,967 guest reviews with their associated responses to reveal the responding pattern of property hosts.

Unlike hotel managers, property hosts are more likely to reply to positive than to negative reviews; moreover, when they do choose to respond to negative reviews, they are likely to do so negatively, in a “tit-for-tat” way. This study also finds that one reason for the difference of responding patterns between property hosts and hotel managers is the hosts’ lack of experience of consumer relationship management and service recovery.

This study provides a good start point for future theoretical development regarding effective responding strategy on peer-to-peer property rental platforms, as well as some useful implications for practitioners.

This study is an early attempt to analyze the impact of the particularity of emerging platforms on the responding behavior of service providers based on a comprehensive conceptual framework and empirical model thus provides a good starting point for the further investigation of effective response strategies on these emerging platforms.

This study aims to elicit the preferences of potential travelers for different property listings' attributes (online review number, positive valence rate of reviews and discount strategy) when selecting hotels and peer-to-peer (P2P) accommodation sharing on online booking platforms.

A discrete choice experiment (DCE) was conducted with 291 respondents with accommodation needs. They were asked to choose between pairs of listings.

The authors found that when booking accommodation online, complex discount strategies were not determinant both in selecting hotels and P2P accommodations. Positive valence rate of reviews has a higher impact on the selection of traditional hotels than P2P accommodations, while the number of online reviews has a higher impact on the selection of P2P accommodations than traditional hotels. The authors further discuss the effect of each attribute on online accommodation selection in terms of price ranges of the property listings.

The findings provide suggestions for platform operators and product/service providers to improve their marketing strategies and optimize their management efforts.

To the best of the authors’ knowledge, this is one of the first studies that investigate the role of property listings' attributes on the selections between hotels and P2P accommodations. The findings from this research study could be generalized to other online platforms and electronic commerce-related transactions.

This study aims to testify the effects of green marketing on peer-to-peer (P2P) accommodation consumers’ repurchase intention and positive word-of-mouth (WOM) towards P2P accommodation platforms through the mediation of trust and consumer identification.

A questionnaire survey was applied to collect data from a sample of 488 consumers in China who had used P2P accommodation platforms in the past six months. Partial least squares structural equation modelling was used to analyse the data.

The study found that consumers’ perception of green marketing orientation of P2P accommodation platforms significantly increased consumer trust in the platform and consumer identification with the platform, which in turn each positively influenced repurchase intention and positive WOM to the platform. Furthermore, consumer trust had a positive effect on consumer identification and both trust and identification mediated the relationship between green marketing and repurchase intention and that between green marketing and positive WOM.

The findings of this study provide P2P accommodation platform operators with important insights to apply green marketing and focus on consumer trust and identification in sustaining their business and coping with the intense market competition.

This study contributes to better understanding of the impact of green business practices on consumers in sharing economy and offers practical implications on sustainable P2P accommodation practices.

This study aims to provide a critical reflection of the application of image recognition techniques in visual information mining in hospitality and tourism.

This study begins by reviewing the progress of image recognition and advantages of convolutional neural network-based image recognition models. Next, this study explains and exemplifies the mechanisms and functions of two relevant image recognition applications: object recognition and facial recognition. This study concludes by providing theoretical and practical implications and potential directions for future research.

After this study presents different potential applications and compares the use of image recognition with traditional manual methods, the main findings of this critical reflection revolve around the feasibility of the described techniques.

Knowledge on how to extract valuable visual information from large-scale user-generated photos to infer the online behavior of consumers and service providers and its influence on purchase decisions and firm performance is crucial to business practices in hospitality and tourism.

Visual information plays a crucial role in online travel agencies and peer-to-peer accommodation platforms from the side of sellers and buyers. However, extant studies relied heavily on traditional manual identification with small samples and subjective judgment. With the development of deep learning and computer vision techniques, current studies were able to extract various types of visual information from large-scale datasets with high accuracy and efficiency. To the best of the authors’ knowledge, this study is the first to offer an outlook of image recognition techniques for mining visual information in hospitality and tourism.

The online travel environment continues to expand as the numerous peer-to-peer (P2P) marketplaces that comprise the “sharing economy” have also multiplied and expanded, resulting in a move from the traditional hospitality industry to a new digital ecosystem. The purpose of this paper is to examine the effects of different antecedents and the relationships between benefit factors. It does so by simulating the behavior that leads to consumer loyalty and repurchase intentions within a P2P marketplace transaction.

The analysis is based on survey data from 456 respondents located in different regions, collected via a web-based survey questionnaire. A two-step approach employing confirmatory factor analysis, followed by structural equation modeling, was conducted to evaluate the measurement and structural models, as recommended by Anderson and Gerbing.

The findings of this study partially confirm the relationship between benefit factors (monetary, hedonic and location benefits) and consumer repurchase intentions. The benefit factors display a positive influence on consumer satisfaction, which mediates the relationship between loyalty and repurchase intentions. Hence, the study contributes to scholarly efforts to better understand why consumers choose to purchase through P2P platforms.

The findings of this study can provide P2P intermediaries and hosts with the empirical evidence of consumer behavioral changes. Nowadays, in practice, consumers have the ability to compare products and offers. As such, for a consumer to remain loyal to a particular supplier, the offer must satisfy the service and experience that the consumer has in mind, as many alternative offers exist.

This study seeks to identify the behavioral factors that cause even loyal consumers to move from the traditional hospitality industries to P2P platforms, despite the probability of losing any loyalty benefits gained in the traditional industries.

Peer-to-peer (P2P) vacation accommodation has recently emerged as a disruptive new form of tourism development. Its potential negative impacts (economic, socio-cultural and environmental) may make residents feel at risk. Therefore, this paper aims to explore residents’ risk perceptions related to the growth of P2P vacation accommodation.

The empirical study was conducted in Mallorca (Spain) among 529 residents and a cluster analysis was carried out.

Results indicate clearly differentiated sociodemographic and attitudinal profiles, which can be classified into four tourist types. The conclusions of the paper suggest implications for tourist managers.

In the field of tourism studies, risk perception has been explored from the perspective of both tourists and hosts. To date, however, residents’ perception of risk has received little attention. Given the importance of resident-tourist interaction in fostering successful destinations this paper focusing on this arena.

The sharing economy has caught great attention from researchers and policymakers. However, due to the dearth of available data, not much empirical evidence has been provided. This paper aims to empirically assess the impacts of Airbnb on hotel performances in South Africa.

Using South Africa as a case study, the study measures the impacts of Airbnb on hotel performances on three key metrics, namely, room prices, occupancy and Revenue per available room (RevPAR). A difference-in-difference model is estimated using a population-based data set of 809 hotels from 2016 to 2018.

The results reveal that despite Airbnb significantly and negatively impacting on hotel occupancies it has a non-significant effect on hotel prices and RevPAR. Although from the theoretical perspective a disruptive innovation business model such as Airbnb can possibly have a negligible effect on hotel performances because it may attract a different group of customers and create a new market, the empirical findings of this study fail to support this theoretical hypothesis. Consequently, the findings diverge with newly developed knowledge in other markets and point to nuanced and contextual complementary effects.

Although some interesting findings are revealed into his study, some caveats remain. For instance, the study relied on data from hotels not from Airbnb. If the data of Airbnb can become available, it would be interesting to further examine whether the aggregated RevPAR of Airbnb can compensate for the aggregated loss of hotel RevPAR. This type of analysis could provide a broader evaluation scope regarding the overall effect of Airbnb on hotel performances. Moreover, if a longer time series data set of hotels in the post-Airbnb time period could become available, it would be interesting to further investigate the time-varying dynamic effects of Airbnb on hotel performances.

While hotels have launched a campaign to portray Airbnb as being commercial operators looking to compete illegally with hotels for the same segment of customers, this study shows that the rhetoric has been exaggerated. Airbnb, and more broadly, vacation rentals do not represent a war with hotels. They represent an answer to a different need. Indeed, the study reveals that Airbnb’s offer is a mere supplement to the market contrary to media rhetoric that it is meant to substitute hotels. The study has several implications for practitioners. First, these results are important because they serve as evidence against news articles that claim Airbnb is driving hotels out of business. They also show that if current trends continue, employees in the hotel industry in South Africa do not need to be concerned about losing their jobs because of Airbnb’s emergence. It is also important information for investors who may be concerned that Airbnb is hurting the hotel industry’s bottom line. Second, as the share of Airbnb listings on the accommodation market varies dramatically between cities, it is likely that eventual regulations/restrictions should be introduced in the provincial levels, while most of the cities continue benefiting from the increasing number of Airbnb visitors.

To the best of the author’s knowledge, this study is the first in South Africa to provide empirical evidence that Airbnb is significantly changing consumption patterns in the hotel industry, as opposed to generating purely incremental economic activity.

This study aims to address the following three questions: What are the main factors influencing co-creation behaviour among peers in a peer-to-peer (P2P) platform? What are the key consequences of such behaviour? and What are the main factors that positively influence a sense of commitment among peers in a P2P platform?

This study used a positivist paradigm to scrutinise the causal associations between the scale validation and causal configurations of influential factors by using fuzzy set qualitative comparative analysis.

Findings indicate that the significance of co-creation behaviour in enhancing the sense of commitment in a P2P platform. The implications for hospitality managers and researchers are discussed.

The findings of this research provide interesting insights for peer providers in a peer platform on how to enhance co-creation. They also offer guidelines on how to build a positive sense of commitment in the peer platform.

By investigating co-creation behaviour at the peer level, this research offers a unique theoretical contribution. Drawing on complexity theory, the research also proposes two tenets supporting the managerial contribution by identifying and clarifying how co-creation behaviour and related constructs can lead to a sense of commitment between peers in a P2P platform.