Search results

Although room-sharing platforms such as Airbnb have become globally prevalent business phenomena, no cross-cultural research has been conducted to examine how travelers outside the “Western Bubble” perceive and respond to this sharing economy. The purpose of this paper is to explore factors that affect Chinese travelers’ behavioral intentions toward room-sharing platforms in the sharing economy.

Based on theories of motivation, the influences on travelers of utilitarian and hedonic motivation, perceived trust and past experience were investigated. Considering the characteristics of room-sharing, utilitarian motivation is measured by service experience, information acquisition, cost saving and resource efficiency. Hedonic motivation is measured by adventure, gratification, sharing and friend-seeking. Data were collected in online survey from 445 valid samples and analyzed by partial least squares (PLS) regression approach using SmartPLS 3.0.

The findings indicate that although intensity varies, utilitarian motivation, hedonic motivation and perceived trust do have positive effects on tourists’ behavioral intentions. Past experience with room-sharing moderates these effects.

There is scant research about consumers’ behaviors toward a sharing economy in Western countries and no empirical research in this field with analyses of Chinese consumers, although China is an emerging market in the hospitality industry. None of the previous research was based on theories of motivation and trust, especially without a consideration of the moderating effect of past experience. Therefore, this study aims to narrow these gaps and to combine, organize and extend previous studies to improve the analysis of behavioral intention in the sharing economy. The value of this study lies in the research model and analysis with the backdrop of China.

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.

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.

The paper aims to discuss the so-called sharing economy from a business modeling and industrial structure perspective. The illustrative cases examined are Airbnb and Uber. The research question raised is concerned with the extent to which transaction cost theory can be used to explain the changing industrial structures in the application areas that the Internet-based platforms are addressing and how other theoretical frameworks can be helpful in understanding these developments.

As the sharing economy topic is relatively new, the paper takes its point of departure in a brief overview of the different issues discussed in the academic literature and the press regarding this emerging phenomenon. The paper presents relevant theoretical approaches to analyzing business models of sharing platforms and industrial structure implications. It, thereafter, presents the cases of Airbnb and Uber to discuss the relevance of the theories put forward.

The paper concludes by proposing a theoretical framework for analyzing the structural implications of the sharing economy based on theories on multi-sided platforms, transaction costs and substitution and complementation.

The research implications are to establish a comprehensive theory framework for analyzing the development of commercial sharing platforms.

The originality and value of the paper is related to the novelty of topic and the development of a theory framework for analyzing the business models of commercial sharing platforms. Only little has been written from an academic analytical perspective on the sharing economy, and there is a need for developing a coherent framework for analyzing these developments.

The purpose of this study is to examine Airbnb research using bibliometric methods. Using research performance analysis, this study highlights and provides an updated overview of Airbnb research by revealing patterns in journals, papers and most influential authors and countries. Furthermore, it graphically illustrates how research themes have evolved by mapping a co-word analysis and points out potential trends for future research.

The methodological design for this study involves three phases: the document source selection, the definition of the variables to be analyzed and the bibliometric analysis. A statistical multivariate analysis of all the documents’ characteristics was performed with R software. Furthermore, natural language processing techniques were used to analyze all the abstracts and keywords specified in the 129 selected documents.

Results show the genesis and evolution of publications on Airbnb research, scatter of journals and journals’ characteristics, author and productivity characteristics, geographical distribution of the research and content analysis using keywords.

Despite Airbnb having a history of 10 years, research publications only started in 2015. Therefore, the bibliometric study includes papers from 2015 to 2019. One of the main limitations is that papers were selected in October of 2019, before the year was over. However, the latest academic publications (in press and earlycite) were included in the analysis.

This study analyzed bibliometric set of laws (Price’s, Lotka’s and Bradford’s) to better understand the patterns of the most relevant scientific production regarding Airbnb in tourism and hospitality journals. Using natural language processing techniques, this study analyzes all the abstracts and keywords specified in the selected documents. Results show the evolution of research topics in four periods: 2015-2016, 2017, 2018 and 2019.

Short-term rentals are mainly of small flats, which are offered to tourists. Currently, the providers of short-term rentals, in particular Airbnb (ABB), are being criticized in several German cities, on the grounds that shares of residential flats are being removed from the housing market, due to illegitimate misuse as tourist accommodation. Thus, the conventional urban housing markets are contending with a decline in housing supply and increasing rents. This paper aims to support these findings empirically.

The paper opted first for a spatial analysis with ArcGIS for ABB in Berlin. Second, different online data requests of periods of up to two months were used to analyze the extent of misuse with regard to the Zweckentfremdungsverbot (misuse prohibition law). Third, analysis of variance was used to analyze rental growth on the ABB markets. The data were collected in different approaches from the website of airbnb.com.

The paper provides evidence that 5,555 residential flats are presently being misused by ABB (0.30 per cent of the total housing stock in Berlin) and that many providers of entire flats have more than one offer simultaneously. Moreover, the paper provides the first entire-market overview of ABB in Berlin. It is evident that the ABB market is mainly located centrally and that only a few neighborhoods have large ABB markets. Rental growth is higher in the ABB markets which have a significant share of misused flats, than in the ABB markets which have insignificant shares of misused flats.

To the authors’ best knowledge, the paper provides the first empirical approach regarding misuse through short-term rentals on a housing market with an innovative design and first-hand data.

This research examines the role of a therapist’s attributes, namely, expertise, sociability, likability and mind-set similarity, in building trust, satisfaction and commitment amongst visitors in Indian wellness resorts and hotels.

The text mining approach was adopted to collect a large corpus of 3,94,373 online reviews from TripAdvisor, Google Reviews and hotels.com. Reviews were taken from 1,677 resorts and hotels that deal in spa and wellness care across India. This study uses unsupervised Naïve Bayes classification and n-gram lexical TF-IDF vectorizer method to classify and find the sentiment of the reviews shared by the visitors of the wellness resorts. Additionally, multiple linear regression is performed to understand the impact of the therapist’s identified attributes on the visitor’s relationship quality.

The research found positive sentiment towards the therapist’s likability, and visitors seemed satisfied with the overall wellness service. The sentiment towards trust and commitment is low. The study also found significant links between likability and expertise in building the relationship quality between the therapist and the visitors. The expertise of the therapist enhances visitors’ trust and willingness to return. The therapist’s likability nature helps in increasing visitor satisfaction.

This study helps to understand the service personnel's level of relationship with the customer in hospitality services. Further, the study empirically verifies the important factors that build relationship quality in Indian wellness services.

The present study argues the need for greater clarity in understanding the customer perception of the services provided by wellness therapists in Indian wellness resorts and hotels. The study guides hotel managers to perform training of wellness therapists to improve customer satisfaction. Using the findings of the current study, managers can prioritize therapists’ attributes and realign their core strategies and provide satisfying wellness services to customers.

This study demonstrates the essential qualities a therapist should develop to enhance the relationship with the resort visitors and foster trust, commitment and satisfaction. The study goes a step further by using a vast database of online data for deep insights into the visitor’s view and the use of machine learning for amplifying results.

Consumers’ intentions to participate in the sharing economy have received much attention from researchers in recent times. However, little attention has been paid to consumers’ actual participation in the sharing economy. The purpose of this paper is to examine the factors that drive customers in Ghana to use Uber.

The authors used surveys as the research design. There were 500 participants who were users of Uber. Data were collected through self-administered questionnaires.

The findings of this study show that trust, customer return on investment and search convenience are the key factors that contribute to riders’ usage of Uber service. Furthermore, this study shows that consumers’ need for prestige and social connection do not play a significant role in consumers’ (riders’) usage of Uber services.

Studies investigating consumers’ participation in the sharing economy from an emerging economy context using the social exchange theory is limited. This study identifies elements of the economic and socio-emotional dimensions of the social exchange theory and the strength of their impact on people’s participation in the sharing economy.

The objective of this study was to investigate the effect of appearance, lifestyle and status similarity on interaction intensity, satisfaction with a banker and repurchase intention. Also examined was the moderating effect of client knowledge in the enhancement of customer satisfaction with a banker.

A total of 800 questionnaires using the snowball sampling technique were performed to distribute the questionnaires to bank customers at different ethnic community centers in New Zealand. A total of 377 useable questionnaires were collected for further analysis.

The findings indicated that the three types of similarity affect interaction intensity differently. Lifestyle similarity was found to positively influence interaction intensity. The similarity constructs of appearance and status were found to have an insignificant relationship with interaction intensity. The findings show that appearance similarity and interaction intensity are able to enhance customer satisfaction with a banker. Customer satisfaction with a banker has a significant relationship with repurchase intention. Client knowledge influences the degree of interaction intensity and satisfaction with a banker.

The findings of this study help bankers to understand the importance of their similarities with a customer and to design recruitment strategies and training sections to improve customer satisfaction.

This study contributes to the body of knowledge by incorporating interaction intensity, similarity and satisfaction with a bank into the repurchase intention model.

The growing trend for online peer-to-peer commerce has changed the way consumers purchase and exchange products and services across a wide variety of industries, including the craft beer industry. The lack of large scale distribution channels for local breweries has led to a growing market for social exchanges across the country. However, these barter systems remain more obscure compared to their mega counterparts in monetary exchange systems. The purpose of this paper is to evaluate how the set-up of online beer marketplaces impacts the perceptions of source attractiveness as moderated by the perceived risks to encourage exchange behaviors.

Using an established beer exchange community, members appraised the impact of avatar profiles in their decision-making process based on user congruity, product congruity and risk perceptions. The research was conducted using a 2×2 between subjects mixed factorial design.

Product attractiveness and risk perceptions influenced behavioral intentions while user attractiveness did not. This is counter to past research that emphasizes the importance of relationships in sharing economy contexts.

This research shifts the discourse for sharing economy platforms from monetizing trust to prioritizing the product. While much of the emphasis had previously been on facilitating relationships between the supplier and customers on sharing economy websites, this may indicate that there needs to be a shift to prioritizing the product.