What drives the use of ridehailing in California? Ordered probit models of the usage frequency of Uber and Lyft

Alemi, Farzad; Circella, Giovanni; Mokhtarian, Patricia L.; Handy, Susan

doi:10.1016/j.trc.2018.12.016

Cited by 179 publications

(133 citation statements)

References 13 publications

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“…The population under study consists of all individuals ranging between the ages of 18-65, living in Spain, who have a profile on a social network and/or instant messaging service: Facebook, Instagram, Youtube, Twitter, and WhatsApp, the best known and the most followed platforms according to the iab.spain's 2019 Annual Social Network Study. In addition, people who are more active on social networks and who own smartphones tend to have a higher frequency of use on collaborative tourism platforms [37].…”

Section: Methodsmentioning

confidence: 99%

“…The same cannot be said about the profile of the collaborative tourist because research on this topic is almost non-existent. The reason for this, as some authors have pointed out, may be the differences in profiles, depending on the country concerned [26,37].…”

Section: Theory and Hypothesesmentioning

confidence: 99%

“…This is especially valuable in a context where so far there has been major uncertainty when it comes to making transactions. In addition, people who are more active on social networks and who own smartphones tend to have a higher frequency of use on collaborative tourism platforms [37], so they become key revitalizers of such platforms. However, no study has found a significant relationship between reviewers (who rate the service positively or negatively) and their frequency of use of these platforms.…”

Section: Hypothesis (H3 B )mentioning

confidence: 99%

“…In this sense, trust has been a key factor affecting consumer behavior on online platforms [70]. The lack of security and regulation has been an obstacle that has negatively affected the attitude of consumers, thus becoming a barrier to the use of these platforms [26,27,37]. According to Huang, Liu, Lai, and Li [71], the significant difference of perceived risks and behavioral intentions between users and non-users means that experiencing P2P accommodation can significantly reduce tourists' risk perception and increase their purchase intentions.…”

Section: Hypothesis (H3 B )mentioning

confidence: 99%

“…Understanding the impact of such models on the tourism and hospitality industry is still in its early stage in the European Union [32]. Although there are works on motivational factors for the use of the collaborative economy [21,22,[33][34][35], research on the variables that affect consumer repetition is scarce [36,37]. In addition, the evolution of the contextual factors that contributed to the development of these models motivates the need for new empirical evidence on the factors that are consolidating them.…”

mentioning

confidence: 99%

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Repeat Consumer Behavior on Smart P2P Tourism Platforms

et al. 2019

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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...

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Section: Methodsmentioning

confidence: 99%

Section: Theory and Hypothesesmentioning

confidence: 99%

Section: Hypothesis (H3 B )mentioning

confidence: 99%