What drives purchase intention on Airbnb? Perspectives of consumer reviews, information quality, and media richness

doi:10.1016/j.tele.2018.03.019

Telematics and Informatics

Volume 35, Issue 5, August 2018, Pages 1512-1523

https://doi.org/10.1016/j.tele.2018.03.019 Get rights and content

Highlights

•
This study investigates the purchase intention behaviors on Airbnb.
•
The purchase intention behaviors is most affected by perceived value and satisfaction.
•
The purchase intention behaviors for gender and usage experiences are investigated.

Abstract

The owners of idle assets and their potential users create economic benefits through providing or sharing idle assets or skills, and this process has been formalized and monetized at large scales by companies such as Uber, Airbnb, USpace and others. This research seeks to understand the factors affecting the purchase intention on Airbnb users in terms of five key factors: rating, rating volume, review, information quality, and media richness. ANOVA and path analysis are used to test the relationships of these factors with perceived value, satisfaction and purchase intention. Results indicate that perceived value and satisfaction are key determinants of intention to buy, while rating volume, review, information quality, and media richness are important precursors. In addition, gender and usage experiences with Airbnb are also used to classify the sample to assess the difference between each classification. The results of this study can provide a useful reference to researchers and firms and individuals working in the sharing economy.

Introduction

The sharing economy (Felson and Spaeth, 1978) refers to the redistribution of under-used resources, allowing those in need to borrow resources cheaply while providing resource owners with benefits they might otherwise forego. Sharers directly exchange goods or services, providing economic benefits for both providers and users. The development of the internet has vastly facilitated the emergence of large-scale sharing economies, effectively consolidating economic surpluses into easily-navigated platforms to match supply and demand of various products and services at a global scale, generating new economic benefits and resolving inefficiencies associated with economic surpluses.

Airbnb, an accommodation booking website which matches house and apartment owners with short-term tenants, first entered Taiwan in 2013 and has rapidly emerged as the most popular such service. Accommodations booked through Airbnb are frequently less expensive than hotels, thus attracting many backpackers and independent travelers. People in Taiwan travel frequently, taking nearly 208 million domestic trips in 2016, along with nearly 1.5 million international trips (Tourism Bureau, Ministry of Transportation and Communications R.O.C., 2017). Increasingly, these travelers forego hotel accommodation in favor of shared apartments and homes found through online services such as Airbnb. Since it first entered the Taiwan market in 2013, Airbnb has expanded rapidly and is now the leading online private-home booking service with nearly 11,000 locations listed (H&B Business Group, 2016).

Given the growing popularity of Airbnb and similar services in Taiwan, along with the rapidly growing availability of properties, this study seeks to identify and assess factors which are likely to increase the consumer’s willingness to book accommodations through Airbnb.

Section snippets

Sharing economy

The development and spread of information and communication technologies has driven the emergence of so-called collaborative consumption (CC) through which individuals provide each other with goods and services through an online intermediary. CC can reduce transaction costs to buyers and sellers (Henten and Windekilde, 2016), while potentially reducing certain social problems, such as overconsumption, pollution and poverty (Hamari et al., 2016). The concept has spread rapidly across online

Research model

Airbnb is an online intermediary between property owners and short-term renters which has expanded very rapidly worldwide since its founding in 2008 (Clampet, 2015). Teubner et al. (2017) suggested that consumers wish to feel “a sense of belonging” even they are away from home, and that this is dependent on a sense of mutual trust between the landlord and the tenant, and this trust is established through information provided by both parties. The buyers seek information including rich-media text

Empirical results and analysis

Of a total of 350 questionnaires collected, 280 were found to be valid and complete, for an effective sample rate of 80%. Given that the questionnaire featured 32 questions, this effective sample rate satisfied the suggestion of Gorsuch (1983) that the number of samples collected should be at least 5 times the number of questions, with a minimum of 100.

Relationship between rating/rating volume and purchase intention/perceived value

Ratings were found to have an insignificant impact on purchase intention, but a significant impact on perceived value, indicating that consumers do not choose a Airbnb because of the rating was 5-star or not to choose a Airbnb because of the rating was 1-star. On the contrary, higher star rating made consumers think the Airbnb was good and may be put into consideration.

On the other hand, rating volume had an insignificant impact on perceived value, but a significant impact on purchase

References (55)

L.V. Casalo et al.
Do online hotel rating schemes influence booking behaviors?
Int. J. Hospit. Managem.
(2015)
A.N. Dedeke
Travel web-site design: Information task-fit, service quality and purchase intention
Tourism Manage.
(2016)
T.H. Engler et al.
Understanding online product ratings: a customer satisfaction model
J. Retail. Consumer Serv.
(2015)
M. Ghasemaghaei et al.
Online information quality and consumer satisfaction: the moderating roles of contextual factors–A meta-analysis
Inf. Manage.
(2015)
M. Ghasemaghaei et al.
A macro model of online information quality perceptions: a review and synthesis of the literature
Comput. Hum. Behav.
(2016)
T.W. Gruen et al.
eWOM: the impact of customer-to-customer online know-how exchange on customer value and loyalty
J. Business Res.
(2006)
E.J. Lee et al.
When do consumers buy online product reviews? Effects of review quality, product type, and reviewer’s photo
Comput. Hum. Behav.
(2014)
L. Li et al.
An empirical study on the influence of economy hotel website quality on online booking intentions
Int. J. Hospit. Manage.
(2017)
Y. Liu et al.
Gender differences in information quality of virtual communities: a study from an expectation-perception perspective
Personal. Indiv. Differ.
(2017)
Y. Lu et al.
Promote physical activity among college students: using media richness and interactivity in web design
Comput. Hum. Behav.
(2014)

S. Mouakket

Factors influencing continuance intention to use social network sites: the Facebook case

Comput. Hum. Behav.

(2015)

A. Papathanassis et al.

Exploring the adoption and processing of online holiday reviews: a grounded theory approach

Tourism Manage.

(2011)

K.S. Suh

Impact of communication medium on task performance and satisfaction: an examination of media-richness theory

Inf. Manage.

(1999)

P.C. Sun et al.

The design of instructional multimedia in e-Learning: a Media Richness Theory-based approach

Comput Edu.

(2007)

I.P. Tussyadiah

Factors of satisfaction and intention to use peer-to-peer accommodation

Int. J. Hospit. Manage.

(2016)

K.L. Xie et al.

Joint effects of management responses and online reviews on hotel financial performance: a data-analytics approach

Int. J. Hospital. Manage.

(2017)

K.L. Xie et al.

The business value of online consumer reviews and management response to hotel performance

Int. J. Hospital. Manage.

(2014)

Q. Ye et al.

The influence of user-generated content on traveler behavior: an empirical investigation on the effects of e-word-of-mouth to hotel online bookings

Comput. Hum. Behav.

(2011)

S.J. Bae et al.

Shared experience in pretrip and experience sharing in posttrip: A survey of Airbnb users

Inf. Manage.

(2016)

R.P. Bagozzi et al.

On the evaluation of structural equation models

J. Acad. Market. Sci.

(1988)

R.N. Bolton et al.

A multistage model of customers' assessments of service quality and value

J. Consumer Res.

(1991)

R.N. Cardozo

An experimental study of customer effort, expectation, and satisfaction

J. Mark. Res.

(1965)

J.A. Chevalier et al.

The effect of word of mouth on sales: online book reviews

J. Mark. Res.

(2006)

Clampet J.(2015). What’s an Airbnb listing worth in 2015? from...

M. Cocosila et al.

How important is the “social” in social networking? A perceived value empirical investigation

Inf. Technol. People

(2015)

G. Cui et al.

The effect of online consumer reviews on new product sales

Int. J. Electr. Comm.

(2012)

R.L. Daft et al.

Information richness

(1983)

Cited by (205)

Generation Z and Indonesian Social Commerce: Unraveling key drivers of their shopping decisions
2024, Journal of Open Innovation: Technology, Market, and Complexity
The landscape of social media has greatly evolved, which created new opportunities, especially in the field of e-commerce. This has led to the development of social commerce (s-commerce), where social media is used for online shopping and business activities, especially for Generation Z (Gen-Z). This study aims to determine the factors that drive Gen-Z's intention to make purchases on s-commerce from the perspective of social cognitive theory. Prior studies have investigated the factors influencing the utilization of s-commerce by Gen-Z, focusing on aspects related to technology, trust, and the s-commerce construct. In contrast, research in Indonesia pertaining the shopping behavior of Gen-Z tends to concentrate more on e-commerce platforms, little of them focusing on s-commerce. Therefore, bridging this gap is crucial. This study gathered data from 204 Gen-Z users of s-commerce. The collected data underwent analysis using Structural Equation Modeling (SEM) procedures. The findings revealed that the intention to purchase among these users is directly impacted by various factors including the quality of information provided, subjective norms, expectations of hedonic outcomes, expectations of utilitarian outcomes, and the users' self-efficacy. This research offers valuable insights and implications for enhancing the shopping experience of Gen-Z through s-commerce. The findings underscore the importance of tailoring s-commerce strategies to meet the unique preferences and behaviors of this demographic. This study highlights that businesses can better engage Gen-Z by understanding what drives their buying decisions. As Gen-Z is tech-savvy and socially connected, knowing these key factors helps businesses create more effective strategies. This research also opens doors for further studies on how s-commerce is changing and its effects on young consumers.
Visual cues and consumer's booking intention in P2P accommodation: Exploring the role of social and emotional signals from hosts' profile photos
2024, Tourism Management
While previous studies have examined social and emotional value through textual cues, the precise impact of these values conveyed by hosts' facial images, as depicted in their profile photos, on consumer booking intentions is unclear. This study aims to fill this gap by exploring how these values from hosts' facial images affect consumer's booking intentions. To this end, we proposed a deep learning framework to evaluate the social and emotional signals conveyed through hosts' facial images. Then, using data from 44,583 listings in six major US cities, we find a positive correlation between the social signal and consumer's booking intention, while the emotional signal shows a U-shaped relationship. Additionally, the impact of social and emotional signals differs across room type, with non-entire rental consumers more likely to be influenced by social signals and entire room consumers by emotional signals. Our findings emphasize the significance of non-functional values in P2P accommodation.
Power of agglomeration on electronic word–of–mouth in the restaurant industry: Exploring the moderation role of review quality difference
2024, Journal of Retailing and Consumer Services
This study evaluates the impact of electronic word–of–mouth (eWOM) based on an extended research model, bridging the information value concept from agglomeration theory with transparency theory. Particularly, it aims to understand how various agglomeration theory aspects, such as store density, product type concentration, and store quality, interact with online reviews’ quality to influence eWOM volume. The study employs a Tobit model to estimate the agglomeration effects on eWOM volume. For nine years (2010–2018), data was collected from 11,234 monthly users at 4004 restaurants in the Phoenix area. This study explores the nuanced effects of store and quality agglomeration on eWOM within the restaurant industry, demonstrating that increased agglomeration positively impacts eWOM by lowering competition and search costs, while ambiguous quality among establishments dampens eWOM. Notably, it reveals that review quality’s influence on eWOM varies with agglomeration type, being minimal for store agglomeration, reducing positive impacts in product agglomeration, yet significantly boosting the benefits of quality agglomeration. By integrating agglomeration and transparency theories and breaking down agglomeration into detailed components, this research highlights the pivotal role of high-quality reviews in mitigating the negative effects of geographical proximity, thus providing fresh insights into eWOM dynamics in the restaurant sector.
Professionalisation and performance of Airbnb hosts in rural regions
2024, International Journal of Hospitality Management
This paper explores the professionalisation and performance aspects of Airbnb hosts in rural regions in Denmark, Iceland, and Norway. More specifically, based upon the professionalisation of hosts, which represents a proxy for the scale of their entrepreneurial engagement, the host landscape in the rural regions is investigated, resulting in different host profiles, including individual single- and multiple-listing hosts, and small and large tourism companies. The paper subsequently estimates the service quality performance of Airbnb hosts in relation to their professionalisation in rural regions through a u-shaped relationship, with the professionalisation influencing the performance evaluation of the hosts by the users. This twofold empirical analysis amends the extant literature, as it provides both a more nuanced and more comprehensive description of the nature and scale of Airbnb host engagement in rural regions, and points to the vast entrepreneurial opportunities for private households and companies on the platform.
Standing head and shoulders above others? Complementor experience-based design and crowdfunding success on digital platforms
2023, Technovation
The proliferation and development of crowdfunding platforms have gradually enabled a disruptive way to finance new ventures through their use. Employing an integrated empirical approach and computerized text analysis, this study aims to investigate how the configuration of multiple complementor experience-based design features affects a complementor’s engagement on crowdfunding platforms. The results indicate that content entrainment, interactive engagement and social connectivity improve crowdfunding success on digital platforms. Moreover, by further refining the linguistic and psychological components, we discover that introducing function words, designing specific content related to clout, authenticity, leisure, religion and biological process, and improving word tone also enhance project funding ratio. Using these findings as a guide, we provide a series of recommendations for fundraisers to better present their crowdfunding projects by employing complementor experience-based designs on crowdfunding platforms.
One pie, many recipes: The role of artificial intelligence chatbots in influencing Malaysian solo traveler purchase intentions
2023, Tourism Management Perspectives
Artificial intelligence (AI) chatbots are pervasive in the travel industry and have significantly alleviated solo travelers' concerns in trip planning and booking. However, many existing AI chatbots have yet to meet the expectations of solo travelers, especially when they demand more personalized information to assist in travel decision-making. Based on complexity theory, this research examines the factors that stimulate solo travelers' purchase intentions when using AI chatbots, particularly covering the three main aspects of marketing efforts, communication quality, and affective characteristics. Drawing from a sample of 281 solo travelers, partial least squares-structural equation modeling (PLS-SEM) and fuzzy-set qualitative comparative analysis (fsQCA) are used to examine the proposed relationships. The PLS-SEM results illustrate that interaction, entertainment, trendiness, communication competence, and satisfaction have significant direct effects on purchase intentions. The fsQCA results further revealed four solutions exhibiting high purchase intentions among solo travelers. Different core, peripheral, and necessary causal conditions in each configuration path were identified. The findings enrich the AI chatbot literature by examining the underlying reasons why solo travelers react differently to this emerging technology and produce practical recommendations for designing AI chatbot systems.

View all citing articles on Scopus

View full text

What drives purchase intention on Airbnb? Perspectives of consumer reviews, information quality, and media richness

Highlights

Abstract

Introduction

Section snippets

Sharing economy

Research model

Empirical results and analysis

Relationship between rating/rating volume and purchase intention/perceived value

Int. J. Hospit. Managem.

Tourism Manage.

J. Retail. Consumer Serv.

Inf. Manage.

Comput. Hum. Behav.

J. Business Res.

Comput. Hum. Behav.

Int. J. Hospit. Manage.

Personal. Indiv. Differ.

Comput. Hum. Behav.

Comput. Hum. Behav.

Tourism Manage.

Inf. Manage.

Comput Edu.

Int. J. Hospit. Manage.

Int. J. Hospital. Manage.

Int. J. Hospital. Manage.

Comput. Hum. Behav.

Shared experience in pretrip and experience sharing in posttrip: A survey of Airbnb users

Inf. Manage.

On the evaluation of structural equation models

J. Acad. Market. Sci.

A multistage model of customers' assessments of service quality and value

J. Consumer Res.

An experimental study of customer effort, expectation, and satisfaction

J. Mark. Res.

The effect of word of mouth on sales: online book reviews

J. Mark. Res.

How important is the “social” in social networking? A perceived value empirical investigation

Inf. Technol. People

The effect of online consumer reviews on new product sales

Int. J. Electr. Comm.

Information richness