Why travelers use Airbnb again?

Mao, Zhenxing; Lyu, Jiaying

doi:10.1108/ijchm-08-2016-0439

Cited by 265 publications

(168 citation statements)

References 62 publications

Supporting

Mentioning

136

Contrasting

Unclassified

Order By: Relevance

“…Oliver [25] also defines customer loyalty as "a deeply held commitment to re-buy or re-patronize a preferred product or service consistently in future". Consumer loyalty is regarded as the goal in the service industry because loyal customers bring numerous benefits to a firm [4,8]. The central idea of these definitions is that consumer loyalty is connected to devoted behavior to a certain product, service, or brand.…”

Section: Consumer Loyaltymentioning

confidence: 99%

“…According to the social exchange theory, customers' long-term relationships with firms are derived from dedication-and constraint-based mechanisms [5]. Dedication-based mechanisms are defined as consumers' desire to develop and maintain a sustainable relationship with their current service firm; constraint-based mechanisms refer to forces constraining customers to maintain their relationship with a given service firm, strengthening the lock-in effect [6][7][8][9]. Proponents of dedication-based mechanisms use affective commitment or consumer satisfaction to predict and explain customer loyalty in various service contexts.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Attracted to or Locked In? Explaining Consumer Loyalty toward Airbnb

Kim

2020

Sustainability

View full text Add to dashboard Cite

In an increasingly complex and dynamic environment, understanding the fundamental mechanisms of customer loyalty toward Airbnb has become very appealing to both researchers and providers in recent years. Most prior studies on Airbnb have focused mainly on dedication-based mechanisms, such as consumer satisfaction or attitude. However, little is currently known about how the theoretical view for adapting dedication-based and constraint-based mechanisms establishes Airbnb consumer loyalty and affects by attributes, such as authentic experience, trust in Airbnb, and social benefits—that is, the vital predictors of affective commitment. It explores social benefits, relative attractiveness, and price fairness as the key antecedents of calculative commitment. This study identifies the relationship using a structural equation modeling method and empirical data collected from 156 Airbnb consumers who use it more than twice. The analysis results show that consumer loyalty toward Airbnb is shaped by dedication- and constraint-based mechanisms. The findings indicate that both affective and calculative commitments significantly affect customer loyalty in the context of Airbnb. Authentic experience, trust in Airbnb, and social benefits significantly affect affective commitment to Airbnb. While both social benefits and relative attractiveness play an important role in enhancing calculative commitment to Airbnb, price fairness is not significantly related to it. Theoretical and practical implications and future research directions are subsequently discussed.

show abstract

Section: Consumer Loyaltymentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Attracted to or Locked In? Explaining Consumer Loyalty toward Airbnb

Kim

2020

Sustainability

View full text Add to dashboard Cite

show abstract

“…E-wom has a positive effect on buyback intent and decreases mistrust [67][68][69]. This is especially valuable in a context where so far there has been major uncertainty when it comes to making transactions.…”

Section: Hypothesis (H3 B )mentioning

confidence: 99%

Repeat Consumer Behavior on Smart P2P Tourism Platforms

et al. 2019

View full text Add to dashboard Cite

Despite the key role played by frequent consumers interacting on smart P2P (peer to peer) tourism platforms, there are hardly any studies on the explanatory variables of their frequency of use. This paper aims to understand the motivational and sociodemographic factors that bring about repeat consumers in collaborative accommodation and transport services. In order to test various assumptions, a set of logistic regressions were made where the dependent variable is the frequency of use and the independent variables are sociodemographic and motivational factors. The results suggest that many consumer attributes recognized as being typical of collaborative platforms, such as young people traveling with friends for leisure who are interested in low prices, have changed. We found that, due to the consolidation of these smart business models, the frequency of use increases with age and for those who travel for work reasons. In addition, it is worth noting the existence of a positive relationship between consumers who provide reviews on these platforms and their frequency of use.Sustainability 2019, 11, 7082 2 of 13 company in the "Global 500 Rankings 2019" [7] with the highest brand value, ranking above Marriott International, the world's hotel leader. In addition, it has managed to overtake Booking.com, one of the main online hosting booking platforms [8]. Uber's fleet in New York is now three-fold larger than the number of yellow taxis [2].This sustained growth contradicts initial perceptions that these were temporary business models, aimed at a young audience, which were hardly going to be able to compete with traditional tourist services. The contextual factors that contributed to the rapid development of this business model, such as the globalization of society caused by the Internet [9-11], the boost from millennials [2,12,13], and the global economic crisis that favored the reuse of resources [14] are less influential now. Therefore, no one doubts that collaborative tourism is here to stay and will continue to grow [5,15].The consolidation of these smart tourism business models has been supported by the highest degree of satisfaction and recommendation of these services versus the traditional ones [16,17]. Both domestic [18] and European studies [5] show the greatest tendency for users to recommend collaborative platforms.Smart P2P tourism platforms are adapting their products to better fit the needs of consumers than traditional services, which creates the perception of quality and thus increases its frequency of use [12,[19][20][21][22]. This increased frequency of use causes greater confidence in the product and service [23][24][25], which is particularly relevant, since consumer insecurity and mistrust have been established as some of the most important reasons for the non-use of collaborative platforms [22,26,27]. In addition, the frequency of use is usually related to the service recommendation (e-wom) [28][29][30][31].Despite the success of these smart models, there are few studies focused on P2P accommod...

show abstract

“…Consumer's willingness to (re)purchase services or products from a company involves a decision making process (Han, Hsu, & Sheu, 2010). The variables in this decision making process include unique perceived variables linking to experience, value, risk, word of mouth, and familiarity (Mao & Lyu, 2017). Recent research on willingness focuses on investigating the most influential factors to choose P2PA over hotels such as price, safety, security, and facility (Mao & Lyu, 2017;Young, Corsun, & Xie, 2017).…”

Section: Literature Reviewmentioning

confidence: 99%

“…The variables in this decision making process include unique perceived variables linking to experience, value, risk, word of mouth, and familiarity (Mao & Lyu, 2017). Recent research on willingness focuses on investigating the most influential factors to choose P2PA over hotels such as price, safety, security, and facility (Mao & Lyu, 2017;Young, Corsun, & Xie, 2017). Though other perceived variables connecting to destination and personal specific attributes should not be omitted, these previous works looked at perceived variables mainly on P2PA attributes.…”

Section: Literature Reviewmentioning

confidence: 99%

The value of P2PA to travelers: Evidence from the Hong Kong market

Lau

Chui

Lin

et al. 2019

Journal of Tourism Research

View full text Add to dashboard Cite

We investigated potential peer‐to‐peer accommodation (P2PA) rental customers with an online survey with 254 Hong Kong residents. The results indicated a different user spectrum covering relatively young, unmarried people in civilian posts, with high levels of education and low levels of income. Prospects preferred to use considered unsafe P2PA in safe destinations. We examined the factors affecting the respondents' willingness to use P2PA rentals with multifactor binary logistic regression analysis. We developed a model on how P2PA, destination, and personal attributes affect decision making to provide a useful point of reference for future researchers and industry practitioners.

show abstract

Why travelers use Airbnb again?

Cited by 265 publications

References 62 publications

Attracted to or Locked In? Explaining Consumer Loyalty toward Airbnb

Attracted to or Locked In? Explaining Consumer Loyalty toward Airbnb

Repeat Consumer Behavior on Smart P2P Tourism Platforms

The value of P2PA to travelers: Evidence from the Hong Kong market

Contact Info

Product

Resources

About