IDEAS home Printed from https://ideas.repec.org/a/spr/infosf/v10y2008i4d10.1007_s10796-008-9096-1.html
   My bibliography  Save this article

Understanding the behavior of mobile data services consumers

Author

Listed:
  • Se-Joon Hong

    (Korea University)

  • James Y. L. Thong

    (Hong Kong University of Science and Technology)

  • Jae-Yun Moon

    (Hong Kong University of Science and Technology)

  • Kar-Yan Tam

    (Hong Kong University of Science and Technology)

Abstract

Due to rapid advances in the Internet and wireless technologies, a ubiquitous computing world is becoming a reality in the form of mobile computing. At the center of this phenomenon is mobile data services which arise from the convergence of advanced mobile communication technologies with data services. Despite the rapid growth in mobile data services, research into consumers’ usage behavior is scarce. This study attempts to identify and empirically assess the factors that drive consumers’ acceptance of mobile data services. A research model based on the decomposed theory of planned behavior and incorporating factors that represent personal needs and motivations in using mobile data services is presented. The model is tested via an online survey of 811 consumers of four categories of mobile data services (i.e., communications, information content, entertainment, and commercial transactions) associated with different usage contexts. We found that attitude, social influence, media influence, perceived mobility, and perceived monetary value influence consumers’ intention to continue usage of mobile data services. In addition, perceived ease of use, perceived usefulness, and perceived enjoyment influence attitude toward continued usage of mobile data services. Finally, separate analysis of the different categories of mobile data services highlights the influence of individual usage context on consumers’ behavior.

Suggested Citation

  • Se-Joon Hong & James Y. L. Thong & Jae-Yun Moon & Kar-Yan Tam, 2008. "Understanding the behavior of mobile data services consumers," Information Systems Frontiers, Springer, vol. 10(4), pages 431-445, September.
  • Handle: RePEc:spr:infosf:v:10:y:2008:i:4:d:10.1007_s10796-008-9096-1
    DOI: 10.1007/s10796-008-9096-1
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s10796-008-9096-1
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.

    File URL: https://libkey.io/10.1007/s10796-008-9096-1?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Se-Joon Hong & Kar Yan Tam, 2006. "Understanding the Adoption of Multipurpose Information Appliances: The Case of Mobile Data Services," Information Systems Research, INFORMS, vol. 17(2), pages 162-179, June.
    2. Moschis, George P & Moore, Roy L, 1982. "A Longitudinal Study of Television Advertising Effects," Journal of Consumer Research, Journal of Consumer Research Inc., vol. 9(3), pages 279-286, December.
    3. Kieran Mathieson, 1991. "Predicting User Intentions: Comparing the Technology Acceptance Model with the Theory of Planned Behavior," Information Systems Research, INFORMS, vol. 2(3), pages 173-191, September.
    4. Ajzen, Icek, 1991. "The theory of planned behavior," Organizational Behavior and Human Decision Processes, Elsevier, vol. 50(2), pages 179-211, December.
    5. Wanda J. Orlikowski & C. Suzanne Iacono, 2001. "Research Commentary: Desperately Seeking the “IT” in IT Research—A Call to Theorizing the IT Artifact," Information Systems Research, INFORMS, vol. 12(2), pages 121-134, June.
    6. Fred D. Davis & Richard P. Bagozzi & Paul R. Warshaw, 1989. "User Acceptance of Computer Technology: A Comparison of Two Theoretical Models," Management Science, INFORMS, vol. 35(8), pages 982-1003, August.
    7. Campbell, Margaret C & Keller, Kevin Lane, 2003. "Brand Familiarity and Advertising Repetition Effects," Journal of Consumer Research, Journal of Consumer Research Inc., vol. 30(2), pages 292-304, September.
    8. Shirley Taylor & Peter A. Todd, 1995. "Understanding Information Technology Usage: A Test of Competing Models," Information Systems Research, INFORMS, vol. 6(2), pages 144-176, June.
    9. Suri, Rajneesh & Long, Mary & Monroe, Kent B., 2003. "The impact of the Internet and consumer motivation on evaluation of prices," Journal of Business Research, Elsevier, vol. 56(5), pages 379-390, May.
    10. Bruner, Gordon II & Kumar, Anand, 2005. "Explaining consumer acceptance of handheld Internet devices," Journal of Business Research, Elsevier, vol. 58(5), pages 553-558, May.
    11. Robert Kraut & Tridas Mukhopadhyay & Janusz Szczypula & Sara Kiesler & Bill Scherlis, 1999. "Information and Communication: Alternative Uses of the Internet in Households," Information Systems Research, INFORMS, vol. 10(4), pages 287-303, December.
    12. Iii, Randolph J. Trappey & Woodside, Arch G., 2005. "Consumer Responses to Interactive Advertising Campaigns Coupling Short-Message-Service Direct Marketing and TV Commercials," Journal of Advertising Research, Cambridge University Press, vol. 45(4), pages 382-401, December.
    13. Dholakia, Ruby Roy & Dholakia, Nikhilesh, 2004. "Mobility and markets: emerging outlines of m-commerce," Journal of Business Research, Elsevier, vol. 57(12), pages 1391-1396, December.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Nedra, Bahri-Ammari & Hadhri, Walid & Mezrani, Mariem, 2019. "Determinants of customers' intentions to use hedonic networks: The case of Instagram," Journal of Retailing and Consumer Services, Elsevier, vol. 46(C), pages 21-32.
    2. Garima Malik & A. Sajeevan Rao, 2019. "Extended expectation-confirmation model to predict continued usage of ODR/ride hailing apps: role of perceived value and self-efficacy," Information Technology & Tourism, Springer, vol. 21(4), pages 461-482, December.
    3. Rajak, Manindra & Shaw, Krishnendu, 2021. "An extension of technology acceptance model for mHealth user adoption," Technology in Society, Elsevier, vol. 67(C).
    4. Yang, Kiseol, 2012. "Consumer technology traits in determining mobile shopping adoption: An application of the extended theory of planned behavior," Journal of Retailing and Consumer Services, Elsevier, vol. 19(5), pages 484-491.
    5. Gérard Cliquet & Christine Gonzalez & Élodie Huré & Karine Picot-Coupey, 2013. "Validation d’un modèle d’intention de magasiner avec le smartphone : implications pour les concepteurs de services mobiles," Economics Working Paper Archive (University of Rennes 1 & University of Caen) 201342, Center for Research in Economics and Management (CREM), University of Rennes 1, University of Caen and CNRS.
    6. Hasan, Rajibul & Lowe, Ben & Petrovici, Dan, 2020. "Consumer adoption of pro-poor service innovations in subsistence marketplaces," Journal of Business Research, Elsevier, vol. 121(C), pages 461-475.
    7. Venkatesh, Viswanath & Maruping, Likoebe M. & Brown, Susan A., 2006. "Role of time in self-prediction of behavior," Organizational Behavior and Human Decision Processes, Elsevier, vol. 100(2), pages 160-176, July.
    8. Muhammad Ali & Syed Ali Raza & Chin-Hong Puah & Mohd Zaini Abd Karim, 2017. "Islamic home financing in Pakistan: a SEM-based approach using modified TPB model," Housing Studies, Taylor & Francis Journals, vol. 32(8), pages 1156-1177, November.
    9. Viswanath Venkatesh, 2000. "Determinants of Perceived Ease of Use: Integrating Control, Intrinsic Motivation, and Emotion into the Technology Acceptance Model," Information Systems Research, INFORMS, vol. 11(4), pages 342-365, December.
    10. Gao, Tao (Tony) & Rohm, Andrew J. & Sultan, Fareena & Pagani, Margherita, 2013. "Consumers un-tethered: A three-market empirical study of consumers' mobile marketing acceptance," Journal of Business Research, Elsevier, vol. 66(12), pages 2536-2544.
    11. Tsourela Maria & Roumeliotis Manos, 2017. "Technology-Based Services Adoption: A Comparison of the Major Applications," International Journal of Innovation and Technology Management (IJITM), World Scientific Publishing Co. Pte. Ltd., vol. 14(03), pages 1-24, June.
    12. Lara Stocchi & Naser Pourazad & Nina Michaelidou & Arry Tanusondjaja & Paul Harrigan, 2022. "Marketing research on Mobile apps: past, present and future," Journal of the Academy of Marketing Science, Springer, vol. 50(2), pages 195-225, March.
    13. Nripendra P. Rana & Yogesh K. Dwivedi & Banita Lal & Michael D. Williams & Marc Clement, 2017. "Citizens’ adoption of an electronic government system: towards a unified view," Information Systems Frontiers, Springer, vol. 19(3), pages 549-568, June.
    14. Valentin Ngadi, 2016. "Factors Affecting The Adoption Of The Personality Of Design [Les Facteurs Determinants De La Diffusion/Adoption De La Personnalite Du Design]," Working Papers hal-01296338, HAL.
    15. Z Irani & Y K Dwivedi & M D Williams, 2009. "Understanding consumer adoption of broadband: an extension of the technology acceptance model," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 60(10), pages 1322-1334, October.
    16. Andrei OGREZEANU, 2015. "Models Of Technology Adoption: An Integrative Approach," Network Intelligence Studies, Romanian Foundation for Business Intelligence, Editorial Department, issue 5, pages 55-67, June.
    17. Rishi Manrai & Kriti Priya Gupta, 2023. "Investor’s perceptions on artificial intelligence (AI) technology adoption in investment services in India," Journal of Financial Services Marketing, Palgrave Macmillan, vol. 28(1), pages 1-14, March.
    18. Hossain Md. Motaher & Zahidul Islam K. M. & Masud Abdullah Al & Biswas Sukanta & Hossain Md. Alamgir, 2021. "Behavioral intention and continued adoption of Facebook: An exploratory study of graduate students in Bangladesh during the Covid-19 pandemic," Management, Sciendo, vol. 25(2), pages 153-186, December.
    19. ETTIS Saïd Aboubaker & ELDABET Mahmoud Mohamed, 2022. "The Move Towards Cashless Society: How To Improve Consumers’ Use Of Bank Cards In Retail Stores?," Studies in Business and Economics, Lucian Blaga University of Sibiu, Faculty of Economic Sciences, vol. 17(1), pages 24-10, April.
    20. Valentin Ngadi, 2016. "Factors Affecting The Adoption Of The Personality Of Design [Les Facteurs Determinants De La Diffusion/Adoption De La Personnalite Du Design]," CEPN Working Papers hal-01296338, HAL.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:spr:infosf:v:10:y:2008:i:4:d:10.1007_s10796-008-9096-1. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.