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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.

This paper aims to examine the primary supply data sources that have been used for research into the sharing economy, and the advantages and limitations of these sources in the literature.

To address the research aims, this study conducted a systematic literature review and content analysis of all relevant articles. Following the review, the methodological sections of the selected papers were examined to identify the characteristics and limitations of all data sources used in the papers.

This study revealed several limitations of the use of three major data sources, namely, web scraping with self-made bots, inside Airbnb and AirDNA, for sharing economy research. The review shows that the majority of the selected papers did not acknowledge any limitations, nor did they discuss the quality of the data sources.

The findings of this paper can serve as guidelines for selecting appropriate data sources for research into the sharing economy and cautions researchers to address the limitations of the data sources used.

To the best of the authors’ knowledge, this is the first study that explores the advantages and limitations of data sources used in short-term rental market research.

Positive reviews can enrich the favorable impression of peer-to-peer accommodation products, and seizing this impression is vital for hosts. This study aims to focus on hosts’ response strategies to positive reviews and their effects.

This study categorizes hosts’ response strategies to positive reviews into cordial and tailoring responses. This study empirically analyzes the influence of these response strategies on subsequent review volumes using 1,283 valid listings and zero-inflation negative binomial regression models.

While hosts use cordial responses more, tailoring responses are more likely to drive subsequent reviews. In addition, when the host chooses entirely shared accommodation or sets a high price, the facilitating effect of the two response strategies on subsequent reviews weakens.

This study enriches the knowledge system on managerial responses by proposing two specific response strategies to positive reviews that can be adopted by peer-to-peer accommodation hosts and by finding the promoting impact of these strategies on subsequent review volumes.

This study recommends that peer-to-peer accommodation hosts adopt cordial and tailoring responses to encourage subsequent consumer reviewing behavior.

As an early attempt to explore hosts’ responses to positive reviews and their impacts on subsequent review volumes, this study provides valuable insights into further research on positive review response strategies in the digital space.

Focused on peer-to-peer accommodation sharing, this paper aims to investigate the effect of perceived value on the two dimensions of satisfaction (transaction- and experience-based) and continuance intention involved in using a platform featuring triadic relationships.

Survey data were collected from 392 Airbnb users and analysed using the partial least squares approach to structural equation modelling.

All dimensions of perceived value had a significant effect on transaction-based satisfaction. Symbolic value did not have a significant effect on satisfaction. Transaction- and experience-based satisfaction had a significant effect on continuance intention.

The findings highlight the differential effects of dimensions of perceived value for understanding customer satisfaction and continuance intention in the peer-to-peer accommodation context. The study focused on only one sector of the sharing economy, namely, the peer-to-peer accommodation sector.

The study offers fresh insights on the nexus between value perceptions and continuance intention in the context of peer-to-peer accommodation.

本文以点对点住宿共享为重点, 研究了感知价值对使用具有三元关系的平台所涉及的满意度（交易和体验）和持续使用意图两个维度的影响。

从 392 名 Airbnb 用户处收集调查数据, 并使用结构方程建模的偏最小二乘法 (PLS-SEM) 进行分析。

感知价值的所有维度对基于交易的满意度都有显着影响。象征价值对满意度没有显着影响。基于交易和体验的满意度对持续意向有显着影响。

研究结果强调了感知价值维度对理解点对点住宿环境中的客户满意度和持续意图的不同影响。该研究仅关注共享经济的一个部门, 即点对点住宿部门。

该研究对点对点住宿环境下的价值感知和持续意图之间的关系提供了新的见解。

To promote the success of peer-to-peer accommodation, this study examines the effects of online host–guest interaction as well as the interaction's boundary conditions of listing price and reputation on listing popularity.

Using 330,686 data collected from Airbnb in the United States of America, the authors provide empirical evidence to answer whether social-oriented self-presentation and response rate influence listing popularity from the perspective of social exchange theory (SET). In addition, the authors investigate how these two kinds of online host–guest interactions work with listing price and reputation to influence listing popularity.

The results reveal the positive association between online host–guest interaction and listing popularity. Notably, the authors find that listing price strengthens but listing reputation weakens the positive effects of online host–guest interactions on listing popularity in peer-to-peer accommodation.

This study is the first attempt to adopt SET to explain the importance of online host–guest interactions in influencing listing popularity as well as examine the moderating role of listing price and reputation on the above relationship.

Taking a global perspective, this paper aims to examine the impact of COVID-19 on Airbnb booking activities through three critical perspectives – the initial Wuhan lockdown, local COVID-19 cases and local lockdowns.

Using Airbnb reviews and cancellations as proxies for Airbnb bookings on a global scale, econometrics was used to examine the impacts of the initial Wuhan lockdown, local COVID-19 cases and local lockdowns on Airbnb bookings.

The authors find that local lockdowns result in a 57.8% fall in global booking activities. Every doubling of newly infected cases is associated with a 4.16% fall in bookings. The sensitivity of bookings to COVID-19 decreases with geographic distance to Wuhan and increases with government stringency of lockdown policies and human mobility within a market.

The empirical evidence from this research can provide governments with insights into more accurate assessment of the financial loss of Airbnb hosts so that proper support can be offered based on the financial needs because of due to sudden lockdown.

This research contributes to new knowledge on peer-to-peer accommodation during a time of crisis and provides much needed global evidence to understand the impacts of COVID-19 on the accommodation industry.

This paper aims to provide a critical synthesis of the interface of corporate social responsibility (CSR) and peer-to-peer (P2P) accommodation to offer insights that contribute to theory and practice of CSR in hospitality.

By using key CSR models, this paper reflects on the nexus between CSR and P2P accommodation (with a focus on Airbnb) to identify opportunities and challenges with regard to CSR implementation in P2P accommodation and, thereby, progress the research agenda on the topic.

This contribution will hopefully enable policymakers to improve the accountability of stakeholders related to P2P accommodation in terms of the sector’s impacts on local communities while contributing to the progression of the research agenda on CSR in hospitality.

Because this contribution is meant to be a “critical reflection paper”, the main purpose is to flesh out a commentary offering recommendations on how to account for CSR in relation to P2P accommodation and primarily Airbnb. As such, this paper aims to prompt future empirical research on the topic. Naturally, the major downside of this type of paper is the lack of an empirical approach.

This paper advances theory on hospitality-related CSR, enabling policymakers to improve the stakeholders’ accountability related to P2P accommodation in terms of the sector’s impacts on local communities.

Despite the increasing importance of CSR in hospitality, minimal academic attention has been paid insofar to CSR in the P2P accommodation sector. This inattention is surprising given the rapid expansion of the sector which, in turn, has imposed significant pressures on local communities.

Although extant studies have investigated the antecedents of negative electronic word of mouth (eWOM), they treated it as a unidimensional concept without classification. To bridge this knowledge gap, this paper distinguishes rational negative eWOM (RNW) from emotional negative eWOM (ENW) and leverages the consumer value framework to investigate their drivers in the context of peer-to-peer accommodation platforms (PPAPs).

This study collected data through an online survey of 437 PPAP users. Partial least squares (PLS) were used to validate the proposed hypotheses. Further, the path coefficients comparison method was adopted to distinguish the different impacts of consumer values on RNW and ENW.

This research showed that self-presentation exerted a positive impact on RNW, but its relationship with ENW was insignificant. Anger and regret were, respectively, positively related to ENW and RNW. Besides, altruism exerted a positive effect on RNW, whereas it had a negative effect on ENW.

First, this paper makes a fresh attempt to categorize negative eWOM into RNW and ENW. Second, this paper draws upon the consumer value framework to dissect varied motivations for posting RNW versus ENW on PPAPs. Third, this paper empirically verifies the differential influences that consumer values exert on RNW and ENW.

The purpose of this study is to identify individuals’ preferences for the information attributes of Airbnb, a representative peer-to-peer (P2P) accommodation platform. In the sharing economy, platforms are considered to be the principal intermediaries in supply and demand, and these platforms have distinctly different attributes from traditional accommodation reservation systems.

The present study used a choice experiment, which is a method for systematically identifying attributes’ preferences in the form of marginal willingness-to-pay (MWTP). Amazon Mechanical Turk, a crowdsourcing marketplace, was used for data collection, and 243 respondents ultimately participated in the survey.

Results showed that respondents’ choices were positively affected by the number of pictures of an accommodation, host experience, cancellation policy and local information but negatively affected by cost. Regarding MWTPs, host experience had the highest value (US$84.25), followed by cancellation policy (US$40), photos (US$26.67) and local information (US$10.92).

These study results could provide strategic guidance for guiding the development of P2P accommodation platforms by providing a prioritized list of preferred attributes for Airbnb.

本研究旨在识别个人对Airbnb这一代表性P2P住宿平台信息属性的偏好。在共享经济中, 平台被视为供需的主要中介, 而这些平台与传统住宿预订系统有明显不同的属性。

本研究采用选择实验法（CE）, 这是一种系统地确定属性偏好的方法, 表现为边际支付意愿（MWTP）。数据采集使用了Amazon Mechanical Turk（MTurk）, 最终有243名受访者参与了调查。

结果显示, 受访者的选择受到住宿图片数量、房东经验、取消政策和本地信息的积极影响, 而受到价格的负面影响。关于边际支付意愿, 房东经验具有最高价值（84.25美元）, 其次依次为取消政策（40美元）、照片（26.67美元）和本地信息（10.92美元）

通过提供优先考虑的 Airbnb 偏好属性列表, 本研究结果可以为引导P2P住宿平台的发展提供战略指导.