What have hosts overlooked for improving stay experience in accommodation-sharing? Empirical evidence from Airbnb customer reviews

Lee, Carmen Kar Hang; Tse, Yiu Kuen; Zhang, Minhao; Wang, Yichuan

doi:10.1108/ijchm-12-2021-1544

Cited by 21 publications

(9 citation statements)

References 63 publications

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“…However, the role of the host in the Airbnb context varies, and good communication is crucial for building trust, while guests value privacy and safety, which are more commonly guaranteed in hotels. Lee et al (2023) identified four themes -"amenities," "host," "location," and "information"and confirmed their importance in accommodation-sharing. While locational benefits were found to be important, customers who express intentions to re-visit or recommend the experiences to others may not mention such benefits in their reviews.…”

Section: Impact On the Local Communitymentioning

confidence: 65%

“…Studies show that trust is a vital factor facilitating users' willingness to engage in interactions, and it can be developed in SE through social and technical enablers (such as social referrals, quality of information and transaction safety) that are relevant to consumer development of trust (Kong et al, 2020;Yang et al, 2019;Farmaki and Stergiou, 2019). Hosts can be considered as a vital part of the Airbnb experience (Lee et al, 2023;Del Chiappa et al, 2021;Petruzzi et al, 2020;Kiatkawsin, 2020) Social interactions help in developing trust Latif et al, 2019;Jiang et al, 2019) which can easily be developed before arriving at the destination if the host had the same nationality as the guest (Kas et al, 2022) or the guests got in touch with the host through messaging the host, and after booking is confirmed they can use social media to get to know each other (Moon et al, 2019), they would feel more satisfied when they are able to check the host's profile, ensure that the account is verified and communication is done smoothly, this will increase the satisfaction level (Sthapit et al, 2019;Zhu et al, 2019). Guests would cancel their booking if they didn't feel comfortable with any safety or communication factors (Del Chiappa et al, 2021).…”

Section: Guest-host Relationshipmentioning

confidence: 99%

“…Lee et al . (2023) identified four themes - “amenities,” “host,” “location,” and “information” - and confirmed their importance in accommodation-sharing.…”

Section: Analysis and Findingsmentioning

confidence: 99%

See 2 more Smart Citations

15 years of Airbnb's authenticity that influenced activity participation: a systematic literature review

Sakr,

Elsharnouby,

AbdelAziz

2023

JHASS

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PurposeThis paper aims to address three research questions (1) Who is the main stakeholder that shapes Airbnb experience, (2) Does Airbnb offers an authentic travel experience? and (3) What should be the future research trends in Airbnb?Design/methodology/approachThis paper uses the systematic literature review (SLR) with a well-defined protocol, research strategy and methods to answer the research questions.FindingsThe review revealed that while Airbnb plays a significant role as the platform provider, the stakeholders influencing the experiences are multifaceted. Hosts, guests, local communities and even regulatory bodies all contribute to shaping the overall Airbnb Experience ecosystem. Hosts, in particular, have a crucial role in curating and delivering unique experiences, which significantly impacts the quality and authenticity of the offerings. On the question of whether Airbnb offers an authentic travel experience, the review uncovered mixed findings. For examples, some studies emphasized the potential for Airbnb to provide authentic and local experiences, allowing travelers to engage with the community and cultural aspects of a destination. However, other studies raised concerns about the commodification and standardization of experiences, leading to a potential loss of authenticity.Originality/valueThis paper is different from previous SLR where previous research systematically reviewed; motivations to use and choose Airbnb, institutionalization of Airbnb, stakeholders of Airbnb. This paper addresses authentic experience as a factor that influences activity participation.

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Section: Impact On the Local Communitymentioning

confidence: 65%

Section: Guest-host Relationshipmentioning

confidence: 99%

See 1 more Smart Citation

15 years of Airbnb's authenticity that influenced activity participation: a systematic literature review

Sakr,

Elsharnouby,

AbdelAziz

2023

JHASS

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“…Thakur et al (2022) performed predictive modeling of Airbnb units in Rio de Janeiro using a deep neural network to identify the influential features. Combinations of hedonic modeling and quantitative techniques for discovering the rental price IJCHM 35,10 determinants of Airbnb units have been documented (Sainaghi et al, 2021;Lee et al, 2022;Wang and Rasouli, 2022). Text mining approaches have also been used to comprehend related issues driving rental prices (Yu et al, 2021;Zhang et al, 2022).…”

Section: Literature Reviewmentioning

confidence: 99%

An ensemble machine learning framework for Airbnb rental price modeling without using amenity-driven features

Ghosh

Jana

Abedin

2023

IJCHM

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Purpose The prediction of Airbnb listing prices predominantly uses a set of amenity-driven features. Choosing an appropriate set of features from thousands of available amenity-driven features makes the prediction task difficult. This paper aims to propose a scalable, robust framework to predict listing prices of Airbnb units without using amenity-driven features. Design/methodology/approach The authors propose an artificial intelligence (AI)-based framework to predict Airbnb listing prices. The authors consider 75 thousand Airbnb listings from the five US cities with more than 1.9 million observations. The proposed framework integrates (i) feature screening, (ii) stacking that combines gradient boosting, bagging, random forest, (iii) particle swarm optimization and (iv) explainable AI to accomplish the research objective. Findings The key findings have three aspects – prediction accuracy, homogeneity and identification of best and least predictable cities. The proposed framework yields predictions of supreme precision. The predictability of listing prices varies significantly across cities. The listing prices are the best predictable for Boston and the least predictable for Chicago. Practical implications The framework and findings of the research can be leveraged by the hosts to determine rental prices and augment the service offerings by emphasizing key features, respectively. Originality/value Although individual components are known, the way they have been integrated into the proposed framework to derive a high-quality forecast of Airbnb listing prices is unique. It is scalable. The Airbnb listing price modeling literature rarely witnesses such a framework.

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“…Vayghan et al (2022) analyze the underlying consumer values that encourage app users to interact with it more and keep using it to book hotels. Lee et al (2023) affirm that in accommodation sharing, the host must ensure that guests have a positive experience so they would express the intention to return (behavioral loyalty) and recommend it to others (attitudinal loyalty) on the Internet.…”

Section: Introductionmentioning

confidence: 99%

Do sustainability motivations drive satisfaction and engagement in the sharing economy, or is it just price and convenience? Some answers in a collaborative housing context

Alarcón‐del‐Amo

Lorenzo-Romero

Gómez-Borja

2023

JHTI

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PurposeThis study aims to understand the motivations behind using Airbnb as a collaborative housing platform brand, their impact on satisfaction and engagement, and how the latter affects brand electronic Word of Mouth (eWOM) and brand loyalty. It also analyzes the potential moderating effect of the use intensity of collaborative housing platforms for the proposed causal relationships.Design/methodology/approachAn online survey was addressed to active users of Airbnb with a final sample of 405 users. Data were analyzed using a covariance-based structural equation modeling (SEM) to test the causal model and a multigroup SEM to test the moderator effect of the intensity of use.FindingsThe results show that convenience affects brand satisfaction and hedonic motivation influences brand engagement, and both affect return intention and eWOM. In contrast, sustainability motivations seem unrelated both with satisfaction and engagement. Furthermore, the mechanism by which people reach loyalty in terms of return intention varies according to their usage intensity. Thus, the engagement–intention way is stronger for more intensive brand users. In contrast, the satisfaction–intention mechanism is significantly stronger for those with more sporadic use.Practical implicationsThe management of collaborative housing platforms should promote tools and actions that favor enjoyment and fun since they increase engagement. On the other hand, it should be interesting to communicate the idea of the convenience of the applications, such as availability for a great offer, ease of contracting, or saving time, since this type of motivation directly correlates with customer satisfaction.Originality/valueThe motivational and behavioral heterogeneity demonstrated in this research can make it easier for people to be reached through different communication strategies and arguments both by the collaborative housing platforms and by public agencies with interests in city tourism management.

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What have hosts overlooked for improving stay experience in accommodation-sharing? Empirical evidence from Airbnb customer reviews

Cited by 21 publications

References 63 publications

15 years of Airbnb's authenticity that influenced activity participation: a systematic literature review

15 years of Airbnb's authenticity that influenced activity participation: a systematic literature review

An ensemble machine learning framework for Airbnb rental price modeling without using amenity-driven features

Do sustainability motivations drive satisfaction and engagement in the sharing economy, or is it just price and convenience? Some answers in a collaborative housing context

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