Skip to main content
SpringerLink
Log in

A comparative analysis of factors influencing millennial travellers’ intentions to use ride-hailing

  • Original Research
  • Published:
Information Technology & Tourism Aims and scope Submit manuscript

Abstract

Ride-hailing services (e.g., Uber, Lyft) have drawn attention as a disruptive innovation in the tourism industry as they provide a new option for transport while on vacation or a business trip. Few studies have examined how travellers perceive the value of this new mode of transportation and modelled their intent to use ride-hailing services. Millennial consumers are known for their early adoption of smart technologies with different supply chains and portable internet devices (e.g., cell phones). This research examines the impact of perceived value on millennial travellers’ intentions to use ride-hailing services in two rapidly changing tourism economies embracing smart phone access to transport services. Primary data were collected with millennials located in urban universities in the US and China. Data were analysed using ordinary least squares estimates. The results revealed that price and relational value positively influenced millennial travellers’ intentions to use ride-hailing services in both samples. These influences remained significant after controlling for previous experiences with mobile technology, perceived safety, and regulations for ride-hailing services. The two millennial samples, however, exhibited different consumer factor influences. While quality and perceived regulations for ride-hailing services predicted millennial travellers’ use intentions in the US sample, previous experience of using mobile technology influenced travellers’ use intentions in the Chinese sample. As companies like Uber and Lyft expand and new providers enter the market, consumer behaviour research on perceived value can inform how business models might differ across countries and services should be tailored for each destination.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1

Similar content being viewed by others

Notes

  1. We tested the inclusion of “levels of previous experience with ride-hailing” as a ratio control variable. The results indicate this variable to be insignificant for both U.S. and Chinese samples that were self-reported ride-hailing users.

References

  • Alemi F, Circella G, Handy S, Mokhtarian P (2017) What influences travelers to use Uber? Exploring the factors affecting the adoption of on-demand ride services. TRB 96th Annual meeting Compendium of Papers, No: 17-05630

  • Amaro S, Andreu L, Huang S (2018) Millennial’s intentions to book on Airbnb. Curr Issues Tour 22(18):2284–2298

    Google Scholar 

  • Amirkiaee SY, Evangelopoulos N (2018) Why do people rideshare? An experimental study. Transp Res Part F 55:9–24

    Google Scholar 

  • Benbasat I, Barki H (2007) Quo vadis, TAM? J Assoc Inf Syst 8(4):211–218

    Google Scholar 

  • Bernardi M (2018) Millennials, sharing economy and tourism: the case of Seoul. J Tour Futures 4(1):43–56

    Google Scholar 

  • Blut M, Wang C, Schoefer K (2016) Factors influencing the acceptance of self-service technologies: A meta-analysis. J Serv Res 19(4):396–416

    Google Scholar 

  • Bomey N (2016) Millennials spurn driver’s license, study finds. USA Today. https://www.usatoday.com. Accessed 10 Apr 2020

  • Brislin RW (1970) Back-translation for cross-cultural research. J Cross Cult Psychol 1(3):185–216

    Google Scholar 

  • Brown TA (2015) Confirmatory factor analysis for applied research. Guilford Express, New York

    Google Scholar 

  • Caselli F, Coleman WJ (2001) Cross-country technology diffusion: the case of computers. Am Econ Rev 91(2):328–335

    Google Scholar 

  • Choi M, Law R, Heo CY (2018) An investigation of the perceived value of shopping tourism. J Transp Res 57(7):962–980

    Google Scholar 

  • Curran PJ, West SG, Finch JF (1996) The robustness of test statistics to nonnormality and specification error in confirmatory factor analysis. Psychol Methods 1(1):16–29

    Google Scholar 

  • Dasgupta S, Agarwal D, Ioannidis A, Gopalakrishnan S (1999) Determinants of information technology adoption: an extension of existing models to firms in a developing country. J Glob Inf Manag 7(3):30–40

    Google Scholar 

  • Dewan S, Kraemer KL (2000) Information technology and productivity: evidence from country-level data. Manag Sci 46(4):548–562

    Google Scholar 

  • Fornell C, Larcker DF (1981) Evaluating structural equation models with unobservable variables and measurement error. J Mark Res 18(1):39–50

    Google Scholar 

  • Geron T (2013) California becomes first state to regulate ridesharing services Lyft, Sidecar, UberX. Forbes. https://www.forbes.com. Accessed 10 Apr 2020

  • Gill D, Byslma B, Ouschan R (2007) Customer perceived value in a cellar door visit: the impact on behavioural intentions. Int J Wine Bus Res 19(4):257–275

    Google Scholar 

  • Godelink R (2017) Millennials and the sharing economy: lessons from a buy nothing new, share everything month’s project. Environ Innov Soc Transit 23:40–52

    Google Scholar 

  • Gupta M, Esmaeilzadeh P, Uz I, Tennant VM (2019) The effects of national cultural values on individuals’ intention to participate in peer-to-peer sharing economy. J Bus Res 97:20–29

    Google Scholar 

  • Gurău C (2012) A life-stage analysis of consumer loyalty profile: comparing generation x and millennial consumers. J Consum Mark 29(2):103–113

    Google Scholar 

  • Gustke C (2016) China’s $500 billion mobile shopping mania. CNBC. https://www.cnbc.com. Accessed 10 Apr 2020

  • Guttentag D, Smith S, Potwarka L, Havitz M (2017) Why tourists choose Airbnb: a motivation-based segmentation study. J Travel Res. https://doi.org/10.1177/0047287517696980

    Article  Google Scholar 

  • Gwinner KP, Gremler DD, Bitner MJ (1998) Relational benefits in services industries: the customer’s perspective. J Acad Mark Sci 26(2):101–114

    Google Scholar 

  • Hackbarth G, Grover V, Mun YY (2003) Computer playfulness and anxiety: positive and negative mediators of the system experience effect on perceived ease of use. Inf Manag 40(3):221–232

    Google Scholar 

  • Hair JF, Black WC, Babin BJ, Anderson RE (2010) Multivariate data analysis, 7th edn. Pearson, Upper Saddle River

    Google Scholar 

  • Hamari J, Sjöklint M, Ukkonen A (2016) The sharing economy: why people participate in collaborative consumption. J Assoc Inf Sci Technol 67(9):2047–2059

    Google Scholar 

  • Hartl B, Hofmann E, Kirchler E (2016) Do we need rules for “what’s mine is yours”? Governance in collaborative consumption communities. J Bus Res 69(8):2756–2763

    Google Scholar 

  • Hu L, Bentler PM (1999) Cutoff criteria for fit indices in covariance structure analysis: conventional criteria versus new alternatives. Struct Equ Model 6(1):1–55

    Google Scholar 

  • Jiang JJ (2019) More Americans are using ride-hailing apps. Pew Research Center. https://www.pewresearch.org/fact-tank/2019/01/04/more-americans-are-using-ride-hailing-apps/

  • Jin N, Lee S, Lee H (2015) The effect of experience quality on perceived value, satisfaction, image and behavioral intention of water park patrons: new versus repeat visitors. Int J Tour Res 17(1):82–95

    Google Scholar 

  • Jones C (2016) More business travellers are ditching rental cars and turning into Uber and Lyft. USA Today. https://www.usatoday.com. Accessed 10 Apr 2020

  • Kellogg DL, Youngdahl WE, Bowen DE (1997) On the relationship between customer participation and satisfaction: two frameworks. Int J Serv Ind Manag 8(3):206–219

    Google Scholar 

  • Kim TG, Lee JH, Law R (2008) An empirical examination of the acceptance behaviour of hotel front office systems: an extended technology acceptance model. Tour Manag 29(3):500–513

    Google Scholar 

  • Lanset M (2018) Here's how much millennials spend on Uber and Lyft in major US cities every month. Business Insider. https://www.businessinsider.com. Accessed 10 Apr 2020

  • Lavieri PS, Bhat CR (2019) Investigating objective and subjective factors influencing the adoption, frequency, and characteristics of rid-hailing trips. Transp Res Part C 105:100–125

    Google Scholar 

  • Lee S, Lee WJ, Yoo KH (2020) Millennial ride-share passengers’ pro-sustainable behaviours: norm activation perspective. Asia Pac J Tour Res 25(1):15–26

    Google Scholar 

  • Li F (2016) Chinese use of ride hailing apps rising. China Daily. http://www.chinadaily.com.cn/business/motoring/2016-06/06/content_25621768.htm. Accessed 10 Apr 2020

  • Lobel O (2016) The law of the platform. Minnesota Law Rev 101(1):87–166

    Google Scholar 

  • Lu J, Yu C, Liu C, Wei J (2017) Comparison of mobile shopping continuance intention between China and USA from an espoused cultural perspective. Comput Hum Behav 75:130–146

    Google Scholar 

  • MacCallum RC, Browne MW, Sugawara HM (1996) Power analysis and determination of sample size for covariance structure modelling. Psychol Methods 1(2):130–149

    Google Scholar 

  • Malhotra NK, Kim SS, Patil A (2006) Common method variance in IS research: a comparison of alternative approaches and a reanalysis of past research. Manag Sci 52(12):1865–1883

    Google Scholar 

  • Malik G, Rao AS (2019) Extended expectation-confirmation model to predict continued usage of ODR/ride hailing apps: role of perceived value and self-efficacy. Inf Technol Tour 21:461–482

    Google Scholar 

  • Marshall A (2019) A third of Americans use ride-hail, Uber and Lyft need more. Wired. https://www.wired.com/story/uber-lyft-ride-hail-stats-pew-research/

  • Mayzlin D, Dover Y, Chevalier J (2014) Promotional reviews: an empirical investigation of online review manipulation. Am Econ Rev 104(8):2421–2455

    Google Scholar 

  • Meuter ML, Bitner MJ, Ostrom AL, Brown SW (2005) Choosing among alternative service delivery modes: an investigation of customer trial of self-service technologies. J Mark 69(2):61–83

    Google Scholar 

  • Min S, So KKF, Jeong M (2019) Consumer adoption of the Uber mobile application: insights from diffusion of innovation theory and technology acceptance model. J Travel Tour Mark 36(7):770–783

    Google Scholar 

  • Möhlmann M (2015) Collaborative consumption: determinants of satisfaction and the likelihood using a sharing economy option again. J Consum Behav 14:193–207

    Google Scholar 

  • Mousavi R, Hazarika B, Chen K, Rienzo T (2020) The role of dissonance reduction and co-creation strategies in shaping smart services satisfaction—the case of Uber. Behav Inf Technol. https://doi.org/10.1080/0144929X.2020.1795258

    Article  Google Scholar 

  • Mozur P (2016) Didi Chuxing and Uber, popular in China, are now legal, too. New York Times. https://www.nytimes.com. Accessed 10 Apr 2020

  • Muthén, LK, Muthén BO (2015) Mplus User’s Guide, 7th edn. Los Angeles

  • Nguyen-Phuoc DQ, Su DN, Tran PTK, Le DTT, Johnson LW (2020) Factors influencing customer’s loyalty towards ride-hailing taxi services—a case study of Vietnam. Transp Res Part C 134:96–112

    Google Scholar 

  • OECD (2016) OECD tourism trends and policies 2016. OECD Publishing, Paris. https://doi.org/10.1787/tour-2016-en

    Book  Google Scholar 

  • Orcher LT (2014) Conducting research: social and behavioral science methods, 2nd edn. Pyrczak Publishing, Los Angeles

    Google Scholar 

  • Parasuraman A, Colby CL (2015) An updated and streamlined technology readiness index: tri 2.0. J Serv Res 18(1):59–74

    Google Scholar 

  • Parasuraman A, Zeithaml VA, Malhotra A (2005) E-S-QUAL: a multiple-item scale for assessing electronic service quality. J Serv Res 7(3):213–233

    Google Scholar 

  • Phocuswright (2016) Mobile, millennials and emerging markets: the next wave in global travel. http://www.phocuswright.com/Free-Travel-Research/Mobile-Millennials-and-Emerging-Markets-The-Next-Wave-in-Global-Travel. Accessed 10 Apr 2020

  • Podsakoff PM, MacKenzie SB, Lee JY, Podsakoff NP (2003) Common method biases in behavioral research: a critical review of the literature and recommended remedies. J Appl Psychol 88(5):879–903

    Google Scholar 

  • Rogers EM (2003) Diffusion of innovations. Free Press, New York

    Google Scholar 

  • Sánchez J, Callarisa L, Rodríguez RM, Moliner MA (2006) Perceived value of the purchase of a tourism product. Tour Manag 27(3):394–409

    Google Scholar 

  • Schiopu AF, Pădurean AM, Tală ML, Nica A (2016) The influence of new technologies on tourism consumption behavior of the millennials. Amfiteatru Econ J 18(10):829–846

    Google Scholar 

  • Smith A (2016) Shared, collaborative and on demand: the new digital economy. https://www.pewresearch.org/internet/2016/05/19/on-demand-ride-hailing-apps/. Accessed 12 Dec 2020

  • Smith JB, Colgate M (2007) Customer value creation: a practical framework. J Mark Theor Pract 15(1):7–23

    Google Scholar 

  • Sweeney JC, Soutar GN (2001) Consumer perceived value: the development of a multiple item scale. J Retail 77(1):203–220

    Google Scholar 

  • Synder T (2020) Back to school statistics. Institute of Education Science. https://nces.ed.gov/fastfacts/display.asp?id=372. Accessed 13 Dec 2020

  • Tornatzky LG, Fleischer M (1990) The processes of technological innovation. Lexington Books, Lexington

    Google Scholar 

  • Tussyadiah IP (2016) Factors of satisfaction and intention to use peer-to-peer accommodation. Int J Hosp Manag 55:70–80

    Google Scholar 

  • Tussyadiah IP, Pesonen J (2018) Drivers and barriers of peer-to-peer accommodation stay—an exploratory study with American and Finnish travellers. Curr Issues Tour 21(6):703–720

    Google Scholar 

  • University of Michigan Transportation Research Institute (2016) More Americans of all ages spurning driver’s licenses. http://www.umtri.umich.edu. Accessed 10 Apr 2020

  • UNWTO (2016) Global report on the power of youth travel. UNWTO, Madrid

    Google Scholar 

  • UNWTO (2017) New platform tourism services (or the so-called sharing economy): understand, rethink and adapt. UNWTO, Madrid

    Google Scholar 

  • Veiga C, Santos MC, Águas P, Santos JAC (2017) Are millennials transforming global tourism? Challenges for destinations and companies. Worldw Hosp Tour Themes 9(6):603–616

    Google Scholar 

  • Venkatesh V, Morris MG, Davis GB, Davis FD (2003) User acceptance of information technology: toward a unified view. MIS Q 1:425–478

    Google Scholar 

  • Wang X, He F, Yang H, Gao HO (2016) Pricing strategies for a taxi-hailing platform. Transp Res Part E 93:212–231

    Google Scholar 

  • Williams P, Soutar GN (2009) Value, satisfaction and behavioral intentions in an adventure tourism context. Ann Tour Res 36(3):413–438

    Google Scholar 

  • Yang K, Jolly LD (2009) The effects of consumer perceived value and subjective norm on mobile data service adoption between American and Korean consumers. J Retail Consum Serv 16(6):502–508

    Google Scholar 

  • Zhu K, Kraemer KL (2005) Post-adoption variations in usage and value of e-business by organizations: cross-country evidence from the retail industry. Inf Syst Res 16(1):61–84

    Google Scholar 

Download references

Author information

Authors and Affiliations

  1. School of Community Resources and Development, Centre for Sustainable Tourism, Arizona State University, 411 N. Central Ave. Suite 550, Mail Code: 4020, Phoenix, AZ, 85004, USA

    Seojin Lee, Woojin Lee & Christine A. Vogt

  2. Department of Event Economy and Management, Tourism College, Beijing Union University, Beijing, China

    Ying Zhang

Authors
  1. Seojin Lee
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Woojin Lee
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Christine A. Vogt
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Ying Zhang
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Woojin Lee.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Supplementary Information

Below is the link to the electronic supplementary material.

Supplementary file1 (DOCX 34 KB)

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Lee, S., Lee, W., Vogt, C.A. et al. A comparative analysis of factors influencing millennial travellers’ intentions to use ride-hailing. Inf Technol Tourism 23, 133–157 (2021). https://doi.org/10.1007/s40558-021-00194-6

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s40558-021-00194-6

Keywords

Search

Navigation