Search results

The purposes of this study are to synthesize the current research findings reported in major hospitality and tourism journals and to discuss the knowledge gaps where additional research endeavors are needed.

A systematic review approach was adopted to analyze 67 research articles about online reviews that were published between January 2000 and July 2015 in seven major hospitality and tourism journals.

This study presents a thematic framework of online review research, which was advanced by integrating the interactions among quantitative evaluation features, verbal evaluation features, reputation features and social features of online reviews with important outcomes of consumer decision-making and business performance. The thematic framework helps researchers identify the areas in extant hospitality literature of online reviews and point out possible directions for future studies.

The systematic review approach has a qualitative nature, where relevant literature was interpreted based on the authors’ domain knowledge and expertise.

Practitioners can gain a comprehensive understanding of the dynamic relationships among the key influential factors in online reviews, as presented in the thematic framework of online review research. Accordingly, managers will be able to develop effective strategies to leverage the positive impacts of online reviews to the business outcomes.

This systematic review synthesizes the findings reported in most recent publications (January 2000-July 2015; also including “Online First” articles) in seven major hospitality and tourism journals and develops an integrated research framework, anchoring on four meta-research questions and showing the dynamic relationships among the key players/factors/themes in online review research. This framework provides a visual diagram to practitioners for a better understanding of the relevant literature and assists researchers in developing new research questions for future studies.

Buyers (renters) and sellers (hosts) on peer-to-peer (P2P) room-sharing websites make purchasing/selling decisions based on each other’s demographic information published in the cyber marketplace. Nevertheless, how this reciprocal selection based on the similarities between renters and hosts may lead to a successful P2P transaction of such services has not yet been discussed. Building on the similarity–attraction paradigm, this study assessed the similarity effects between renters and hosts on the likelihood of a P2P room-sharing transaction.

A logistical regression model was employed in analysis, using a large-scale, granular online observational data set collected from Xiaozhu.com, a primary home-sharing platform in China.

Renter–host similarities in age and education significantly affect the likelihood of a P2P room-sharing transaction. As the number of listings managed by a host increases, the effect of age similarity decreases. While a renter’s experience with a room-sharing website negatively moderates the similarity effect of age, it is a factor positively moderating the similarity effect of education.

Other possible host–renter similarities were not analyzed due to the limitation of the data source. The reciprocal selection process for room-sharing services was acknowledged by integrating buyers’ and sellers’ data into one analysis.

Implications are advanced for the stakeholders of room-sharing business, including entrepreneurs running a room-sharing website, operators of short-term residential rentals and hoteliers.

This study represents a first attempt to research the buyer–seller similarity effects on the likelihood of a P2P transaction in sharing economy.

This paper aims to identify a wide array of utility-based attributes of Airbnb listings and measures the effects of these attributes on consumers’ valuation of Airbnb listings.

A hedonic price model was developed to test the effects of a group of utility-based attributes on the price of Airbnb listings, including the characteristics of Airbnb listings, attributes of hosts, reputation of listings and market competition. The authors examined attributes as they relate to the price of Airbnb listings and, therefore, estimated consumers’ willingness to pay for the specific attributes. The model was tested by using a dataset of 5,779 Airbnb listings managed by 4,602 hosts in 41 census tracts of Austin, Texas in the USA over a period from Airbnb’s launch in Texas up until November 2015.

The authors found that the functional characteristics of Airbnb listings were significantly associated to the price of the listings, and that three of five behavioral attributes of hosts were statistically significant. However, the effect of reputation of listings on the price of Airbnb listings was weak.

This study inspires what they call a factor-endowment valuation of Airbnb listings. It shows that the intrinsic attributes that an Airbnb listing endows are the primary source of consumer utilities, and thus consumer valuation of the listing is grounded on its functionality as an accommodation. This conclusion can shed light on the examination of competition between Airbnb and hotel accommodations that are built on the same or similar intrinsic attributes.

Previous literature has discussed the importance of two types of social media exposures: owned social media (OSM) exposures generated by service providers and earned social media (ESM) exposures initiated by consumers. This study aims to examine the relative effects of owned and ESM exposures on brand purchase, as well as their advertising externality to competing brands. Rooted in theory of planned behavior and advertising externality literature, this study hypothesizes that owned and ESM exposures positively influence brand purchase. Such effects, however, can spill over to competing brands that invest in social media marketing and co-exist in the market.

This study collects brand purchase records and social media messages on the Facebook brand pages of a group of service providers over 12 months. The data are assembled for time series analysis with the unit of analysis being “brand × bi-week”.

Using a blend of fixed-effects models and seemingly unrelated regressions, this study finds that both owned and ESM exposures positively affect brand purchase, the purchase effect of OSM exposures is greater than ESM exposures, OSM exposures generate not only more purchase of the focal brand but also positive advertising externality to competing brands, whereas ESM exposures locks up the advertising effect to the focal brand without spilling over to competing brands.

This study advances the understanding about the externality of social media exposures in an increasingly competitive market where multiple brands invest in social media marketing and co-exist. Important implications on the strategic use of social media exposures to drive brand purchase while competing with similar brands are provided.

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 paper aims to examine the factors contributing to the helpfulness of online hotel reviews and to measure the impact of manager response on the helpfulness of online hotel reviews.

This investigation used a linear regression model that drew upon 56,284 consumer reviews and 10,797 manager responses from 1,405 hotels on TripAdvisor.com for analysis.

The helpfulness of online hotel reviews is negatively affected by rating and number of sentences in a review, but positively affected by manager response and reviewer experience in terms of reviewer status, years of membership, and number of cities visited. Manager response moderates the influence of reviewer experience on the helpfulness of online hotel reviews.

Using the data from hotels in five major cities in Texas, the results may not be necessarily generalized to other markets, but the important role that manager response plays in online reviews is assessed with big data analysis.

The results suggest hospitality managers should strategically identify opinion leaders among reviewers and proactively influence the helpfulness of the reviews by providing manager response. Additionally, this study makes recommendations to webmasters of social media platforms in terms of advancing the algorithm of featuring the most helpful online reviews.

This study is at the frontier of research to explain how hotel managers can proactively identify opinion leaders among consumers and use manager response to influence the helpfulness of consumer reviews. Additionally, the results also provide new insights to the influence of reviewer demographic background on the helpfulness of online reviews. Finally, this study analyzed a large data set on a scale that was not available in traditional guest survey studies, responding to the call for big data applications in the hospitality industry.

The purpose of this study is to examine the effects of host attributes and travelers’ frequency of past stays and their interaction on the likelihood of repeat purchase of home-sharing services at both the host and listing levels.

A combination of econometrics analyses using a large-scale, granular online observational data set collected from a home-sharing platform was performed.

Travelers exhibit salient loyalty to home-sharing services. At the host level, host attributes including acceptance rate and listing capacity positively affect travelers’ likelihood of repeat purchase; such effects diminish as travelers’ frequency of past stays with a host/listing increases. At the listing level, confirmation efficiency and acceptance rate are critical, and travelers’ frequency of past stays matters.

Responding to the call for more research on customer loyalty of sharing economy, this study instantiated on a home-sharing website in China and adds a unique perspective to the research domain, but its findings may not be generalized in other settings.

This study identifies the factors affecting customers’ repeat purchase behaviors at both the host and listing levels, allowing the hosts, webmasters of home-sharing websites and even hoteliers to advance specific tactics to promote repeat purchase among travelers.

Loyalty was measured with real-time internet-enabled observational data about travelers’ actual repeat purchase behavior on a home-sharing website, rather than assessing consumers’ behavioral intentions through the conventional survey method. Two specific levels of customer loyalty were analyzed, including the ones towards a service provider (host) and a service product (listing).

When shopping for hotels online, consumers usually follow a sequential process of search, click-through and book. How to maximize consumer conversion on the path to purchase and prevent potential customers from giving up the online search remains an important topic to hotel marketers and online travel agents (OTAs). The purpose of this study is to understand how informational cues displayed in an online hotel search process, including quality indicators, brand affiliation, incentives (discounted price and promotion) and position in the search results, influence consumer conversion from one stage to another.

The authors collected clickstream data of hotel search from Expedia. The data include information on individual consumers’ click-through and booking, as well as events leading up to the conversions (or failure to convert) from search, click-through to book. It contains 940,164 hotels searched and displayed in 39,574 online search queries made by users in a regional US market between November 1, 2012 and June 20, 2013. The modeling strategy comprised the Heckman model and random effects model, which integrated sequential consumer behavior in different problem-solving stages while accounting for heterogeneity across different hotels online.

The authors find that consumers rely on informational cues displayed online to make decisions about hotel booking. Specifically, consumers tend to click through hotels with higher consumer-generated ratings and industry-endorsed ratings. However, they tend to rely on consumer-generated ratings rather than industry-endorsed ratings when committing to a booking. Moreover, consumers are strongly responsive to incentives (discounted price and promotion) when clicking-through and booking a hotel. Finally, the likelihood of consumer conversions from search to click-through and booking is higher for hotels with brand affiliation and higher positions in the search results.

This research provides critical managerial implications of online search for hotel marketers and OTAs. The results inform hotel marketers and OTAs on how consumers respond to informational cues displayed in their search process and how these informational cues influence consumer conversion from one stage to another. The sequential problem-solving process of search, click-through and booking disclosed in this study also helps hotel marketers to identify customer conversion opportunities using effective informational cues.

当在线酒店预定时, 消费者往往遵循一系列流程, 搜索, 点击查询, 到最后预定。对于酒店营销商和线上旅游社（OTAs）来说, 如何最大化提高消费转化, 使得消费者不会半途中断, 最后预定酒店, 是一个重要话题。本论文的研究目的就是理解酒店在线搜索过程中, 信息线索如何影响每个阶段的消费转化, 其中涉及的因素有：信息质量、品牌、激励（折扣和促销）、以及搜索结果排名等。

研究样本数据采集于Expedia酒店搜索点击流。其中包括个人消费者点击和预定信息、以及由搜索、点击查询到预定过程中的消费转化（或者中途转化失败）的各种事件。样本容量包括940,164家酒店, 其涉及到由美国局部市场消费者在2012年11月1日到2013年6月20日之间做出的39,574条搜索结果。 我们采用Heckman模型和随机效应模型来整合不同线性时间上的消费者行为, 同时考虑不同酒店的多样性。

研究发现消费者使用在线信息线索来做酒店预订决策。具体来说, 消费者倾向于对于消费者评价高和行业认证高的酒店进行点击查询。然而, 相比行业认证, 消费者更倾向于借鉴消费者评价, 来做出最后预定决策。此外, 在点击查询和预定时, 消费者对于激励（折扣和促销）反应强烈。最后, 品牌和搜索排名靠前的酒店往往获得从搜索、点击查询到最后预定中更高的消费转化率。

本论文对酒店营销商和OTAs有重要的在线搜索启示。研究结果向酒店营销商和OTAs证明消费者在搜索过程中对信息线索如何反应, 以及这些信息线索如何影响每个阶段之间的消费转化。本论文展示的从搜索、点击查询、到预定的线性决策过程对于酒店营销商们有着重大帮助, 帮助其使用信息线索找出各种消费转化机遇。

The purpose of this study was to investigate travelers’ preferences for peer-to-peer (P2P) accommodations or hotels when traveling for leisure or business purposes given the rise of P2P accommodations in the form of Airbnb, Vacation Rentals by Owners (VRBO) One Fine Stay, etc.

VRBO hosts in Denver, Colorado, USA provided contact information for 788 travelers who stayed with them over the prior three years. These travelers received an email survey and the opportunity to be entered in a drawing for one of three US$250 gift cards.

P2P usage was driven by leisure travel. The most influential factors in the choice of P2P over hotel were price, location, party size, dwelling size and trip length. When choosing a hotel for business travel, the influential factors were location, safety and security, price and knowing what one will receive in the way of facility and services.

The external validity of the findings is limited as the study was conducted in one US city using travelers of only one P2P accommodations platform.

Hotels may want to leverage their loyalty programs and stress the importance of safety and security when traveling as a means of competing with P2P accommodations.

Given limited empirical research on P2P accommodations, this study provides an informative first look at the preferences and behaviors of travelers using P2P accommodations and points to a growing loyalty to P2P accommodations versus hotels in the leisure segment.

Trust has been widely recognized as the crucial factor of consumer purchase intention when shopping on peer-to-peer short-term rental platforms where hosts and renters are strangers. However, the specific attributes of hosts that help build trust with potential renters and drive their purchase of short-term rentals remain unknown. This study aims to explore the effects of host attributes on renter purchases made on Xiaozhu.com, one of the top short-term rental platforms in China, while controlling for short-term rental characteristics.

A crawler program was developed by Python to collect the host attributes and their short-term rental characteristics of 935 hosts in Beijing from November 18, 2015 to February 14, 2016. The authors use Poisson regression models to estimate the effects of host attributes on renter reservations. They also conduct a series of robustness checks for the estimated results.

The authors found that host attributes such as the time of reservation confirmation, the acceptance rate of renter reservations, the number of listings owned, whether a personal profile page is disclosed and gender of the host significantly affect renter reservations, whereas the response rate of the host does not influence renters when purchasing short-term rentals online.

This study identifies which host attributes are perceived as trustworthy and affect renters’ purchase decisions, a topic of both theoretical and practical importance but currently less researched. The findings add to emerging literature by providing insights on trust-building in the peer-to-peer economy. Useful suggestions are also provided on strengthening the trust mechanism on short-term rental platforms to facilitate peer-to-peer transactions. Notably, the study is the first attempt to examine the perception of Chinese users toward short-term rentals despite its global prevalence. The analytical insights revealed from large scale but granular online observations data of host attributes and actual renter reservations greatly supplement findings of extant literature using survey and experiment approaches.