Unlocking Solo Female Travelers’ CUI of M-Travel Apps with the Moderating Lens of Their Age and Travel Frequency

Authors

DOI:

https://doi.org/10.17010/ijom/2025/v55/i8/175209

Keywords:

solo female travelers, m-travel apps, continued usage intention, utilitarian value, hedonic value.
Publication Chronology: Paper Submission Date : March 5, 2025 ; Paper sent back for Revision : May 5, 2025 ; Paper Acceptance Date : July 5, 2025 ; Paper Published Online : August 14, 2025

Abstract

Purpose : Scholarly publications called for a more in-depth investigation of Asian solo female travel experiences, especially from developing countries like India, where male-dominated ideologies and other safety issues heavily influence women’s behaviors and choices. This study developed and tested a theory-driven model that empirically examined the factors influencing solo female travelers’ continued intention to use mobile travel apps.

Methodology : The authors collected data from 276 solo female travelers to validate the hypothesis using the partial least squares structural equation modeling (PLS-SEM). Among the factors analyzed, hedonic value (HV) emerged as the most influential in shaping continued usage intentions (CUI)—surpassing UV—highlighting that enjoyment, excitement, and experiential benefits played a central role in solo female travelers’ decisions to keep using mobile travel apps. Additionally, innovativeness, perceived risk, performance expectancy (PE), effort expectancy (EE), and subjective norms significantly influenced HV and UV.

Findings : The study found that age and frequency of travel did not significantly moderate the relationships between the key predictors and CUI. The result suggested that regardless of age or travel frequency, solo female travelers shared similar expectations and motivations regarding mobile travel app usage.

Implications : This research made a meaningful theoretical contribution by offering more profound insights into the travel behavior of solo female travelers, thereby supporting the development and refinement of relevant behavioral theories. Practically, the findings provide actionable guidance for online travel agencies (OTAs), hotel providers, and hospitality tech vendors to design more targeted marketing and engagement strategies that enhance app usage among this growing traveler segment.

Originality : This paper was written in its purest form, with the idea of research developed and operationalized by the authors.

Downloads

Download data is not yet available.

Published

2025-08-14

How to Cite

Chaudhary, R., Dwivedi, S., & Vig, S. (2025). Unlocking Solo Female Travelers’ CUI of M-Travel Apps with the Moderating Lens of Their Age and Travel Frequency. Indian Journal of Marketing, 55(8), 49–68. https://doi.org/10.17010/ijom/2025/v55/i8/175209

Issue

Section

Articles

References

1) Abdin, M. S. (2020). A study to identify and profile consumer segments in the mobile telecommunication services market. Indian Journal of Marketing, 50(5–7), 46–60. https://doi.org/10.17010/ijom/2020/v50/i5-7/152119

2) Agarwal, V., Sahoo, R., & Agarwal, A. (2019). A study on factors affecting mobile phone buying behaviour in Bhubaneswar and Cuttack. Indian Journal of Marketing, 49(11), 20–38. https://doi.org/10.17010/ijom/2019/v49/i11/148274

3) Agarwal, R., & Prasad, J. (1998). A conceptual and operational definition of personal innovativeness in the domain of information technology. Information Systems Research, 9(2), 204–215. http://www.jstor.org/stable/23010927

4) Ajzen, I., & Fishbein, M. (2004). Questions raised by a reasoned action approach: Comment on Ogden (2003). Health Psychology, 23(4), 431–434. https://doi.org/10.1037/0278-6133.23.4.431

5) Ajzen, I. (1991). The theory of planned behavior. Organizational Behavior and Human Decision Processes, 50(2), 179–211. https://doi.org/10.1016/0749-5978(91)90020-T

6) Alonso-Vazquez, M., Yang, E. C., del Mar Pages Vidal, M., & Khoo, C. (2024). Going solo during the pandemic: A generational segmentation of solo female travellers. Current Issues in Tourism, 27(3), 381–395. https://doi.org/10.1080/13683500.2022.2164486

7) Anderson, K. C., Knight, D. K., Pookulangara, S., & Josiam, B. (2014). Influence of hedonic and utilitarian motivations on retailer loyalty and purchase intention: A Facebook perspective. Journal of Retailing and Consumer Services, 21(5), 773–779. https://doi.org/10.1016/j.jretconser.2014.05.007

8) Babin, B. J., Darden, W. R., & Griffin, M. (1994). Work and/or fun: Measuring hedonic and utilitarian shopping value. Journal of Consumer Research, 20(4), 644–656. http://www.jstor.org/stable/2489765

9) Batra, R., & Ahtola, O. T. (1991). Measuring the hedonic and utilitarian sources of consumer attitudes. Marketing Letters, 2(2), 159–170. http://www.jstor.org/stable/40216210

10) Bhatnagar, A., & Ghose, S. (2004). A latent class segmentation analysis of e-shoppers. Journal of Business Research, 57(7), 758–767. https://doi.org/10.1016/S0148-2963(02)00357-0

11) Bhattacherjee, A., & Premkumar, G. (2004). Understanding changes in belief and attitude toward information technology usage: A theoretical model and longitudinal test. MIS Quarterly, 28(2), 229–254. https://doi.org/10.2307/25148634

12) Chakraborty, D. (2024). Revolutionizing travel: The impact of generative AI on personalization and efficiency in the tourism industry. Indian Journal of Marketing, 54(9), 8–24. https://doi.org/10.17010/ijom/2024/v54/i9/174394

13) Chen, C.-C., & Tsai, J.-L. (2019). Determinants of behavioral intention to use the personalized location-based mobile tourism application: An empirical study by integrating TAM with ISSM. Future Generation Computer Systems, 96, 628–638. https://doi.org/10.1016/j.future.2017.02.028

14) Cheng, V. T., & Pai, C.-K. (2020). A trip planning service acceptance model for young mainland Chinese tourists. Journal of Hospitality and Tourism Technology, 11(2), 327–342. https://doi.org/10.1108/JHTT-11-2017-0121

15) Childers, T. L., Carr, C. L., Peck, J., & Carson, S. (2001). Hedonic and utilitarian motivations for online retail shopping behavior. Journal of Retailing, 77(4), 511–535. https://doi.org/10.1016/S0022-4359(01)00056-2

16) Chiu, C.-M., Hsu, M.-H., Lai, H., & Chang, C.-M. (2012). Re-examining the influence of trust on online repeat purchase intention: The moderating role of habit and antecedents. Decision Support Systems, 53(4), 835–845. https://doi.org/10.1016/j.dss.2012.05.021

17) Choi, K., Wang, Y., & Sparks, B. (2019). Travel app users' continued use intentions: It's a matter of value and trust. Journal of Travel & Tourism Marketing, 36(1), 131–143. https://doi.org/10.1080/10548408.2018.1505580

18) Correia, A., & Dolnicar, S. (2021). Women's voices in tourism research. Contributions to knowledge and letters to future generations. The University of Queensland. https://doi.org/10.14264/817f87d

19) Deci, E. L., & Ryan, R. M. (1985). The general causality orientations scale: Self-determination in personality. Journal of Research in Personality, 19(2), 109–134. https://doi.org/10.1016/0092-6566(85)90023-6

20) Deci, E. L. (1976). Notes on the theory and metatheory of intrinsic motivation. Organizational Behavior and Human Performance, 15(1), 130–145. https://doi.org/10.1016/0030-5073(76)90033-7

21) Delone, W. H., & McLean, E. R. (2003). The DeLone and McLean model of information systems success: A ten-year update. Journal of Management Information Systems, 19(4), 9–30. https://doi.org/10.1080/07421222.2003.11045748

22) Dwivedi, Y. K., Choudrie, J., & Brinkman, W.-P. (2006). Development of a survey instrument to examine consumer adoption of broadband. Industrial Management & Data Systems, 106(5), 700–718. https://doi.org/10.1108/02635570610666458

23) Ezzaouia, I., & Bulchand-Gidumal, J. (2023). The impact of information technology adoption on hotel performance: Evidence from a developing country. Journal of Quality Assurance in Hospitality & Tourism, 24(5), 688–710. https://doi.org/10.1080/1528008X.2022.2077886

24) Featherman, M. S., & Pavlou, P. A. (2003). Predicting e-services adoption: A perceived risk facets perspective. International Journal of Human-Computer Studies, 59(4), 451–474. https://doi.org/10.1016/S1071-5819(03)00111-3

25) Filieri, R., Acikgoz, F., Ndou, V., & Dwivedi, Y. (2021). Is TripAdvisor still relevant? The influence of review credibility, review usefulness, and ease of use on consumers' continuance intention. International Journal of Contemporary Hospitality Management, 33(1), 199–223. https://doi.org/10.1108/IJCHM-05-2020-0402

26) Fornell, C., & Larcker, D. F. (1981). Evaluating structural equation models with unobservable variables and measurement error. Journal of Marketing Research, 18(1), 39–50. https://doi.org/10.2307/3151312

27) Gautam, S., Malik, P., & Jain, S. (2022). Role of trusting beliefs and trust in the adoption of online reviews of hotels: Extension of the IAM model. Indian Journal of Marketing, 52(11), 8–25. https://doi.org/10.17010/ijom/2022/v52/i11/172431

28) Ghadban, S., Kamar, R., & Haidar, R. (2023). Decoding international solo women travelers' experience: A qualitative analysis of user-generated videos. Journal of Outdoor Recreation and Tourism, 44, Article ID 100648. https://doi.org/10.1016/j.jort.2023.100648

29) Hair, J. F., Ringle, C. M., & Sarstedt, M. (2013). Partial least squares structural equation modeling: Rigorous applications, better results and higher acceptance. SSRN. https://ssrn.com/abstract=2233795

30) Hair, J. F., Risher, J. J., Sarstedt, M., & Ringle, C. M. (2019). When to use and how to report the results of PLS-SEM. European Business Review, 31(1), 2–24. https://doi.org/10.1108/EBR-11-2018-0203

31) Hanif, Y., & Lallie, H. S. (2021). Security factors on the intention to use mobile banking applications in the UK older generation (55+). A mixed-method study using modified UTAUT and MTAM - with perceived cyber security, risk, and trust. Technology in Society, 67, Article ID 101693. https://doi.org/10.1016/j.techsoc.2021.101693

32) Hegde, S. D. (2024). Solo sojourns of Indian women: Narratives from travel blogs (Doctoral dissertation, Auckland University of Technology). School of Hospitality and Tourism. https://openrepository.aut.ac.nz/server/api/core/bitstreams/0c2df2b1-03a4-46e0-93ed-f0542cd1a777/content

33) Henseler, J., Ringle, C. M., & Sarstedt, M. (2015). A new criterion for assessing discriminant validity in variance-based structural equation modeling. Journal of the Academy of Marketing Science, 43(1), 115–135. https://doi.org/10.1007/s11747-014-0403-8

34) Henseler, J., Hubona, G., & Ray, P. A. (2016). Using PLS path modeling in new technology research: Updated guidelines. Industrial Management & Data Systems, 116(1), 2–20. https://doi.org/10.1108/IMDS-09-2015-0382

35) Hirschman, E. C. (1980). Innovativeness, novelty seeking, and consumer creativity. Journal of Consumer Research, 7(3), 283–295. https://www.jstor.org/stable/2489013

36) Hirschman, E. C., & Holbrook, M. B. (1982). Hedonic consumption: Emerging concepts, methods and propositions. Journal of Marketing, 46(3), 92–101. https://doi.org/10.2307/1251707

37) Hoehle, H., & Venkatesh, V. (2015). Mobile application usability: Conceptualization and instrument development. MIS Quarterly, 39(2), 435–472. https://doi.org/10.25300/MISQ/2015/39.2.08

38) Horton, R. L. (1976). The structure of perceived risk: Some further progress. Journal of the Academy of Marketing Science, 4(4), 694–706. https://doi.org/10.1007/BF02729830

39) Hosseini, S., Macias, R. C., & Garcia, F. A. (2022). The exploration of Iranian solo female traveller's experiences. International Journal of Tourism Research, 24(2), 256–269. https://doi.org/10.1002/jtr.2498

40) Hu, L. T., & Bentler, P. M. (1998). Fit indices in covariance structure modeling: Sensitivity to underparameterized model misspecification. Psychological Methods, 3(4), 424–453. https://doi.org/10.1037/1082-989X.3.4.424

41) Im, S., Bayus, B. L., & Mason, C. H. (2003). An empirical study of innate consumer innovativeness, personal characteristics, and new-product adoption behavior. Journal of the Academy of Marketing Science, 31(1), 61–73. https://doi.org/10.1177/0092070302238602

42) Jackson, J. D., Yi, M. Y., & Park, J. S. (2013). An empirical test of three mediation models for the relationship between personal innovativeness and user acceptance of technology. Information & Management, 50(4), 154–161. https://doi.org/10.1016/j.im.2013.02.006

43) Joia, L. A., & Altieri, D. (2018). Antecedents of continued use intention of e-hailing apps from the passengers' perspective. The Journal of High Technology Management Research, 29(2), 204–215. https://doi.org/10.1016/j.hitech.2018.09.006

44) Jung, T., Dieck, M. C., Lee, H., & Chung, N. (2016). Effects of virtual reality and augmented reality on visitor experiences in museum. In A. Inversini, & R. Schegg (eds.), Information and communication technologies in tourism 2016 (pp. 621–635). Springer. https://doi.org/10.1007/978-3-319-28231-2_45

45) Kour, P., & Gupta, S. (2023). Role of loneliness in destination emotional values and travel intentions: Analysis of solo women travellers in India. International Journal of Tourism Policy, 13(1), 35–52. https://doi.org/10.1504/IJTP.2023.129168

46) Liu, Y., Li, Q., Edu, T., & Negricea, I. C. (2020). Exploring the continuance usage intention of travel applications in the case of Chinese tourists. Journal of Hospitality & Tourism Research, 47(1), 6–32. https://doi.org/10.1177/1096348020962553

47) Loureiro, S. M. C., & Roschk, H. (2014). Differential effects of atmospheric cues on emotions and loyalty intention with respect to age under online/offline environment. Journal of Retailing and Consumer Services, 21(2), 211–219. https://doi.org/10.1016/j.jretconser.2013.09.001

48) Medeiros, M., Ozturk, A. B., Okumus, B., Hancer, M., & Weinland, J. (2025). Investigating the antecedents of tourists' intention to use travel tracking mobile applications to follow other travelers' experiences. Journal of Hospitality and Tourism Technology, 16(3), 450–478. https://doi.org/10.1108/JHTT-07-2023-0208

49) Midgley, D. F., & Dowling, G. R. (1978). Innovativeness: The concept and its measurement. Journal of Consumer Research, 4(4), 229–242. http://www.jstor.org/stable/2488813

50) Mirehie, M., Liu-Lastres, B., Cecil, A., & Jain, N. (2023). Business travel, risk, and safety of female university faculty and staff. Annals of Leisure Research, 26(3), 414–432. https://doi.org/10.1080/11745398.2020.1825971

51) Mittal, S., & Kumar, V. (2024). Analyzing the role of technological capabilities and digital marketing on the performance of e-commerce-based SMEs. Indian Journal of Marketing, 54(12), 45–60. https://doi.org/10.17010/ijom/2024/v54/i12/174658

52) Neluhena, M., Chandralal, L., & Dahanayake, T. (2023). Female solo travels to South Asian destinations and sustaining loneliness. Tourism and Hospitality Research, 24(4), 577–587. https://doi.org/10.1177/14673584231173508

53) Omran, W., Ramos, R. F., & Casais, B. (2024). Virtual reality and augmented reality applications and their effect on tourist engagement: A hybrid review. Journal of Hospitality and Tourism Technology, 15(4), 497–518. https://dx.doi.org/10.1108/JHTT-11-2022-0299

54) Osman, H., Brown, L., & Phung, T. M. (2019). The travel motivations and experiences of female Vietnamese solo travellers. Tourist Studies, 20(2), 248–267. https://doi.org/10.1177/1468797619878307

55) Otegui-Carles, A., Araújo-Vila, N., & Fraiz-Brea, J. A. (2022). Solo travel research and its gender perspective: A critical bibliometric review. Tourism and Hospitality, 3(3), 733–751. https://doi.org/10.3390/tourhosp3030045

56) Overby, J. W., & Lee, E.-J. (2006). The effects of utilitarian and hedonic online shopping value on consumer preference and intentions. Journal of Business Research, 59(10–11), 1160–1166. https://doi.org/10.1016/j.jbusres.2006.03.008

57) Özsungur, F. (2022). A research on the effects of successful aging on the acceptance and use of technology of the elderly. Assistive Technology, 34(1), 77–90. https://doi.org/10.1080/10400435.2019.1691085

58) Palos-Sanchez, P., Saura, J. R., Velicia-Martin, F., & Cepeda-Carrion, G. (2021). A business model adoption based on tourism innovation: Applying a gratification theory to mobile applications. European Research on Management and Business Economics, 27(2), Article ID 100149. https://doi.org/10.1016/j.iedeen.2021.100149

59) Pangriya, R. (2023). Consumers' readiness and acceptance of beacon technology. Indian Journal of Marketing, 53(8), 66–82. https://doi.org/10.17010/ijom/2023/v53/i8/172976

60) Ramli, N. A., Latan, H., & Nartea, G. V. (2018). Why should PLS-SEM be used rather than regression? Evidence from the capital structure perspective. In N. K. Avkiran, & C. M. Ringle (eds.), Partial least squares structural equation modeling: Recent advances in banking and finance (pp. 171–209). Springer. https://doi.org/10.1007/978-3-319-71691-6_6

61) Richter, N. F., Carrion, G. A., Roldán, J. L., & Ringle, C. M. (2016). European management research using partial least squares structural equation modeling (PLS-SEM). European Management Journal, 34(6), 589–597. https://doi.org/10.1016/j.emj.2016.08.001

62) Rigdon, E. E. (2012). Rethinking partial least squares path modeling: In praise of simple methods. Long Range Planning, 45(5–6), 341–358. https://doi.org/10.1016/j.lrp.2012.09.010

63) Rodríguez-Torrico, P., Prodanova, J., San-Martín, S., & Jimenez, N. (2020). The ideal companion: The role of mobile phone attachment in travel purchase intention. Current Issues in Tourism, 23(13), 1659–1672. https://doi.org/10.1080/13683500.2019.1637828

64) Rogers, E. M. (2003). Diffusion of innovations (5th ed.). Free Press.

65) Saadé, R., & Bahli, B. (2005). The impact of cognitive absorption on perceived usefulness and perceived ease of use in online learning: An extension of the technology acceptance model. Information & Management, 42(2), 317–327. https://doi.org/10.1016/j.im.2003.12.013

66) Savita, U., & Sheoran, U. (2020). Preferences and behaviour toward e-gadgets: A study of consumers in Chandigarh. Indian Journal of Marketing, 50(5–7), 22–34. https://doi.org/10.17010/ijom/2020/v50/i5-7/153071

67) Shankar, R. S. (2020). Impact of cognitive and affective image on tourists' travel motivation. Indian Journal of Marketing, 50(5–7), 35–45. https://doi.org/10.17010/ijom/2020/v50/i5-7/152118

68) Somasiri, S., Murray, N., & Dresler, E. (2022). Solo female travellers: Solitude as a solo travel need and intrusive experiences in Asia. Asia Pacific Journal of Tourism Research, 27(11), 1127–1143. https://doi.org/10.1080/10941665.2023.2166417

69) Sujood, Siddiqui, S., & Bano, N. (2023). An investigation of factors affecting solo travel intention among marginalized groups: A case of Indian Muslim women. Tourism Recreation Research, 48(6), 1014–1034. https://doi.org/10.1080/02508281.2023.2174925

70) Talwar, S., Dhir, A., Kaur, P., & Mäntymäki, M. (2020). Why do people purchase from online travel agencies (OTAs)? A consumption values perspective. International Journal of Hospitality Management, 88, Article ID 102534. https://doi.org/10.1016/j.ijhm.2020.102534

71) Talwar, S., Talwar, M., Kaur, P., & Dhir, A. (2020). Consumers' resistance to digital innovations: A systematic review and framework development. Australasian Marketing Journal, 28(4), 286–299. https://doi.org/10.1016/j.ausmj.2020.06.014

72) Thong, J. Y., Hong, S.-J., & Tam, K. Y. (2006). The effects of post-adoption beliefs on the expectation-confirmation model for information technology continuance. International Journal of Human-Computer Studies, 64(9), 799–810. https://doi.org/10.1016/j.ijhcs.2006.05.001

73) Topsakal, Y., & Çuhadar, M. (2024). Usage intention of tourists regarding the acceptance of artificial intelligence enhanced tour guides apps. Current Issues in Tourism, 1–17. https://doi.org/10.1080/13683500.2024.2375361

74) van der Heijden, H. (2004). User acceptance of hedonic information systems. MIS Quarterly, 28(4), 695–704. https://doi.org/10.2307/25148660

75) Venkatesh, V., Morris, M. G., Davis, G. B., & Davis, F. D. (2003). User acceptance of information technology: Toward a unified view. MIS Quarterly, 27(3), 425–478. https://doi.org/10.2307/30036540

76) Venkatesh, V., Thong, J. Y., & Xu, X. (2012). Consumer acceptance and use of information technology: Extending the unified theory of acceptance and use of technology. MIS Quarterly, 36(1), 157–178. https://doi.org/10.2307/41410412

77) Venkatesh, V., Thong, J. Y., & Xu, X. (2016). Unified theory of acceptance and use of technology: A synthesis and the road ahead. Journal of the Association for Information Systems, 17(5), 328–376. https://doi.org/10.17705/1jais.00428

78) Weck, M., & Afanassieva, M. (2023). Toward the adoption of digital assistive technology: Factors affecting older people's initial trust formation. Telecommunications Policy, 47(2), Article ID 102483. https://doi.org/10.1016/j.telpol.2022.102483

79) Weng, G. S., Zailani, S., Iranmanesh, M., & Hyun, S. S. (2017). Mobile taxi booking application service's continuance usage intention by users. Transportation Research Part D: Transport and Environment, 57, 207–216. https://doi.org/10.1016/j.trd.2017.07.023

80) Yang, E. C. (2021). What motivates and hinders people from travelling alone? A study of solo and non-solo travellers. Current Issues in Tourism, 24(17), 2458–2471. https://doi.org/10.1080/13683500.2020.1839025

81) Zhou, T. (2008). The impact of perceived value on user acceptance of mobile commerce. In 2008 International Symposium on Electronic Commerce and Security (pp. 237–240). IEEE. https://doi.org/10.1109/ISECS.2008.9