Search results

This paper aims to formulate the most probable future scenario for the accommodation sharing sector within the next five to ten years. It addresses the following six thematic aspects: relevance, different forms of accommodation sharing, users, hosts, platforms, and finally, industry regulation.

This study identifies the most likely holistic future scenario by conducting a two-stage Delphi study involving 59 expert panelists. It addresses 33 projections for six thematic sections of the accommodation sharing industry: relevance, different forms of accommodation sharing, users, hosts, platforms, and finally, industry regulation.

The results indicate that the number of shared accommodations and users of home-sharing will increase. Moreover, the cost advantage is the predominant driver for users to engage in the accommodation sharing segment, and for the hosts, the generation of an extra income is the primary incentive. Finally, the regulation within this industry is expected to be more effective in the foreseeable future.

The results are critical, not only to advance our theoretical understanding and stimulate critical discussions on the long-term development of accommodation sharing but also to assist governments and policymakers who have an interest in developing and regulating this sector and developers seeking business opportunities.

While there is ample knowledge about the past and current development of accommodation sharing in tourism, little is understood about its potential future development and implications for consumers, the economy, and society. To date, no scientific research is available that develops scenarios about the future of accommodation sharing.

This study aims to explore the relationships between consumer data vulnerability, peer privacy concerns and consumers' continued usage intention of sharing accommodation platforms, as well as the moderating effects of the various benefits perceived by consumers.

Data were collected from 327 consumers of sharing accommodation platforms in China. Partial least squares (PLS)-structural equation modeling (SEM) was conducted to test the research hypotheses.

The results suggest that both consumer data vulnerability and peer privacy concerns have negative effects on consumer's continued usage intention of sharing accommodation platforms, which can be further mitigated by consumer perceived economic, social and emotional benefits. This study also finds that consumer data vulnerability has a positive effect on consumer's peer privacy concerns.

This study gives that managers of sharing accommodation platforms a better understanding of how consumers respond to their data vulnerability on sharing accommodation platforms. In addition, this study also highlights the measures that platforms may employ to mitigate the negative influence of consumer data vulnerability and consumers' peer privacy concerns, as well as the measures to reduce consumers' peer privacy concerns.

While previous studies mainly examined the driving forces of consumers' engagement in sharing accommodation, this study focuses on the impediment. With communication privacy management theory to explore the relationships between consumer data vulnerability, peer privacy concerns and continued usage intention of sharing accommodation platforms, as well as the moderating effects of consumers' perceived benefits, this study facilitates a more comprehensive understanding of consumers' engagement in sharing accommodation.

With the development of the sharing economy, the collaborative consumption model has become more popular and has changed the way people engage in tourism. This study aims to explore. consumer experience in different types of rooms on a shared accommodation platform.

In this study, the authors divided the rooms on the shared accommodation platform into a budget type and a luxury type according to the room price and used content analysis to analyze 15,710 online reviews published on Xiaozhu.

This study found that consumer expectations varied depending on the room type. “Host,” “room,” “transportation and location” and “value” were the four common topics that consumers paid attention to in both room types. “Environment” and “objective conditions” were the particular focuses of the budget room consumers. However, consumers cared about “aesthetics” and “accommodation purpose” when staying in luxury rooms. These results reflected the influence of room prices on consumer experiences.

To the best of the authors’ knowledge, this study is one of the first to compare the consumer experience in rooms at different price points based on the evidence provided in online reviews. Latent Dirichlet allocation (LDA) analysis was used to extract the underlying topics from the online reviews, which provided more exciting results. This study leads to a comprehensive understanding of the consumer experience from the perspective of expectation theory, enriching the prior research on shared accommodation platforms.

研究目的: 随着共享经济的发展, 协同消费模式越来越流行, 改变了人们从事旅游的方式。本研究旨在探索共享住宿平台上不同类型房间的消费者体验。

在这项研究中, 我们根据房价将共享住宿平台上的房间分为经济型和豪华型, 并使用内容分析分析了在Xiaozhu上发布的 15,710 条在线评论。

我们发现消费者的期望因房间类型而异。 “房主”、“房间”、“交通与位置”、“价值”是消费者在两种房型中关注的四个共同话题。 “环境”和“客观条件”是经济型房消费者特别关注的焦点。然而, 消费者在入住豪华客房时, 更关心的是“美学”和“住宿目的”。这些结果反映了房价对消费者体验的影响。

这项研究是根据在线评论提供的证据比较不同价位客房的消费者体验的首批研究之一。潜在狄利克雷分配（LDA）分析用于从在线评论中提取潜在主题, 这提供了更令人兴奋的结果。我们的研究从期望理论的角度对消费者体验进行了全面的理解, 丰富了以往关于共享住宿平台的研究。

In recent years, short-term sharing accommodation platforms such as Airbnb have made rapid forays in populous cities worldwide, impacting neighborhoods profoundly. Emerging work has focused on demand-side motivations to engage in the sharing economy. The purpose of this paper is to analyze rarely examined supply-side motivations of providers.

To address this gap and to illuminate understanding of how Airbnb supply is configured and influenced, this study examines spatial patterns and socioeconomic influences on participation in the sharing accommodation economy by Airbnb hosts in New York City (NYC). An exploratory conceptual model of host participation is induced, which posits associations of demographic, economic, employment, social capital attributes, and attitudes toward trust and sustainability with host participation, measured by Airbnb property density in neighborhoods. Methods employed include ordinary least squares (OLS) regression, k-means cluster analysis and spatial analytics.

Spatially, clusters of high host densities are in Manhattan and northern Brooklyn and there is little proportionate change longitudinally. OLS regression findings reveal that gender ratio, black race/ethnicity, median household income, and professional, scientific, and technical occupation, and attitudes toward sustainability for property types are dominant correlates of property density, while host trust in customers is not supported.

These results along with differences between Queens and Manhattan boroughs have implications for hosts sharing their homes and for city managers to formulate policies and regulate short-term rental markets in impacted neighborhoods.

The study is novel in conceptualizing and analyzing the supply-side provider motivations of the sharing accommodation economy. Geostatistical analysis of property densities to gauge host participation is novel. Value stems from new insights on NYC’s short-term homesharing market.

The peer-to-peer (P2P) accommodation-sharing market has developed rapidly on the strength of information technology in recent years. Matching providers and customers in an information technology (IT)-enabled platform is a key determinant of both parties' experiences and the healthy development of the platform. However, previous research has not sufficiently explained the mechanism of provider–customer matching in accommodation sharing, especially at the psychological level. Based on field cognitive style theory, this study examines how the match and mismatch affect customers' online and offline satisfaction and whether a significant difference exists between online and offline satisfaction under different matching patterns.

The authors test the proposed theoretical model using 122 provider–customer dyad data collected through a field study.

The results suggest that customers' online and offline satisfaction under match is significantly higher than that under mismatch. In addition, customers' online satisfaction is significantly higher than their offline satisfaction under mismatch, but there is no significant difference between the two under match. The perceived price fairness also plays a moderating role in the case of mismatch.

In summary, these findings provide a novel understanding about the matching patterns and their outcomes in the accommodation-sharing context and expand the contents and applications of field cognitive style theory and matching theory. This study will help these IT-enabled platforms to provide personalized matching services at the psychological level, thereby enhancing user experience and corporate competitiveness. 10; 10;

Trust has emerged as a crucial research topic in the sharing economy. However, scholarship on trust in sharing accommodation remains limited. By using stakeholder theory, this study aims to provide a systematic framework for integrating trust among multiple stakeholders and identify potential knowledge gaps and future research directions for trust in sharing accommodation.

The authors select papers using a combination of multiple keywords from EBSCOhost and Web of Science. The analysis includes 172 journal papers published between 2011 and 2021. The authors conduct a systematic review through thematic content analysis, and each paper is analyzed using manual coding.

The analysis shows that key stakeholders for trust building in sharing accommodation include consumers, hosts, platforms, residents and governments, with most studies focusing on the consumer perspective. The study integrates various trust antecedents and outcomes from the above multistakeholder. Second, this study summarizes the most commonly used theories, and more diversified theories could be applied to future research. Third, this study finds that most studies use quantitative methods, and researchers should introduce more integrated methodologies such as machine learning on a large scale. Furthermore, the current research disciplinary paradigm should be extended to multidisciplinary and interdisciplinary approaches to promote innovation in trust research. Finally, the COVID-19 pandemic has brought both challenges and opportunities to industry as well as researchers, and more institutional rather than commercial perspectives need to be addressed.

The study contributes to the trust and the sharing economy literature by providing a systematic framework for integrating trust from multistakeholder perspectives. The study also points out several future research directions by combining micro and macro multistakeholder perspectives, identifying more diversified theories and methodologies and specifying multidisciplinary and interdisciplinary approaches.

The study advances knowledge by providing a systematic framework for integrating trust among multiple stakeholders and proposing future research directions for trust in sharing accommodation.

Accommodation sharing is a major trend shaping the hospitality industry, and Airbnb is the most prominent sharing platform driving this growth. While price convenience is reported as one of the main strengths of Airbnb accommodations, only a few studies have examined price determinants. In particular, it is unclear whether hosts dynamically adjust prices for shared accommodation based on their experience with price management and on the level of market demand. The purpose of this paper is to fill this gap by suggesting and testing a comprehensive hedonic pricing model.

Data from all 1,056 Airbnb listings for accommodations available in the city of Verona, Italy on four booking dates in 2016 are collected and analysed through regression analysis.

The results highlight that price is significantly related to the level of the host’s accumulated experience and the level of market demand on a specific booking date. The findings provide support for the ability of hosts to dynamically adjust prices for their accommodations.

Drawing on the innovator’s dilemma theory, this study suggests some strategies that traditional hotels may adopt to react to the disruptive nature of Airbnb.

This is one of the few studies to address hosts’ pricing strategies and specifically consider price adjustments owing to variations in host experience and market demand.

Despite the importance of hosts who contribute to the success of accommodation sharing through sharing underutilized space with guests, current literature sheds little light on what exactly incentivizes hosts to grow their properties. The purpose of this study is to investigate the effects of multifaceted motivations including financial benefits, online social interaction and membership seniority and their interplay on hosts’ multiple listing behavior.

The study is instantiated on real-world business data collected from an accommodation-sharing platform in China. The data set includes 3,199 observations of 252 multi-listing hosts in Beijing who managed 815 properties from September 2012 to October 2016.

The study discloses that financial benefits, online social interaction and membership seniority significantly incentivize hosts to list multiple properties on the accommodation-sharing platform. In particular, the social incentive is the most important driver among the three. With a 1 per cent increase in online social interactions, the number of properties operated by a host would increase by 13.5 per cent. While the financial benefits and online social interaction motivate hosts to engage in the multi-listing behavior, such effects are significantly mitigated as the membership seniority increases.

This study adds to the extant literature a unique yet less researched perspective of supply expansion driven by hosts. It also provides important practical implications for managing multiple properties for a healthy and viable accommodation-sharing community.

While a majority of the extant research on the sharing economy primarily takes a consumer-related perspective, this study addresses a different and original topic about hosts’ multiple-listing behavior that drives the supply of accommodation sharing. It is a first empirical investigation of the increase of accommodation sharing supply with host motivations explained.

This research is motivated by the increasing need for international interactions during the gradual recovery of the tourism industry. By recognizing the paucity of research on cultural closeness and accommodation categories, this research aims to illuminate the influencing mechanisms of psychological closeness and travelers’ willingness to book an accommodation-sharing property while booking an accommodation.

The authors employ a mixed-methods approach, including an experiment and semistructured interviews.

Results show that hosts’ higher cultural identity congruence leads to travelers’ higher willingness to book an accommodation-sharing property. Psychological closeness mediates the positive effect of cultural identity congruence on travelers’ willingness to book. The authors further explore the moderating role of room types (entire room vs. private room) and find that the mediation effect is stronger for booking an entire room.

The current research underlines the importance of cultural identity congruence and accommodation type on travelers’ willingness to book an accommodation-sharing property and psychological closeness.

The hosts' third-party certifications in the sharing accommodation platforms have largely overlooked how the provision of such certification information could facilitate the trust-building process and subsequently influence consumers' purchase intention. Adopting an institution-based trust perspective, the authors differentiate various types of hosts' certification information (i.e. financial certification and social certification) and examine their role in the trust-building process between the hosts and the customers on sharing accommodation platforms.

This study uses the property-month level data of Airbnb Beijing from January 2019 to June 2020. Econometric analyses are adopted to evaluate the impact of institution-based trust on consumers' purchase intention. Specifically, the ordinary least square is used to testify the relationship between institution-based trust and purchase intention.

The empirical results show that the information on institution-based trust increases the likelihood that customers would reach purchase decisions. More importantly, results show that both financial certification and social certification affect consumers' purchase intention. The results further show that listings' attributes moderate the relationship between institution-based trust and customer purchase intention. Moreover, the authors find that “Superhost” and “Experience” positively moderate such relationships.

This paper confirms that the host certification fosters institution-based trust and reveals the impact of hosts' certification on consumers' purchase intentions. This study is among one of the first studies to incorporate institution-based trust into the trust formation on the sharing economy platform, which can improve the understanding of trust in the sharing economy context. The authors emphasize the importance of trust types on sharing economy platforms.