IDEAS home Printed from https://ideas.repec.org/a/eee/jbrese/v64y2011i6p543-550.html
   My bibliography  Save this article

Understanding consumer services buyers based upon their purchase channel

Author

Listed:
  • Magnini, Vincent P.
  • Karande, Kiran

Abstract

Consumer services such as airlines and hotels include a proliferation of bookings through Internet-proprietary and Internet-third party sites. The other dominant channel for making airline and hotel purchases is via telephone. This research investigates differences in how buyers utilize the three channels in terms of internal and external price search, number of alternatives searched, brand loyalty, purchase frequency, risk of unavailability at the time of purchase, and Internet experience and usage. Results indicate that telephone buyers employ the least external search, consider the fewest number of alternatives during search, are the most brand loyal, are the most frequent buyers, and perceive the lowest level of risk of unavailability at the time of purchase. Conversely, Internet-third party buyers utilize the most external search, consider the largest number of alternatives, are the least brand loyal, are the least frequent buyers, and perceive the highest level of risk of unavailability. Managerial implications and suggestions for future research are provided.

Suggested Citation

  • Magnini, Vincent P. & Karande, Kiran, 2011. "Understanding consumer services buyers based upon their purchase channel," Journal of Business Research, Elsevier, vol. 64(6), pages 543-550, June.
    • Handle: RePEc:eee:jbrese:v:64:y:2011:i:6:p:543-550
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0148-2963(10)00110-4
    Download Restriction: Full text for ScienceDirect subscribers only
    ---><---

    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. Liu, Yuping, 2003. "Developing a Scale to Measure the Interactivity of Websites," Journal of Advertising Research, Cambridge University Press, vol. 43(2), pages 207-216, June.
    2. Urbany, Joel E, 1986. "An Experimental Examination of the Economics of Information," Journal of Consumer Research, Journal of Consumer Research Inc., vol. 13(2), pages 257-271, September.
    3. Gurumurthy Kalyanaram & Russell S. Winer, 1995. "Empirical Generalizations from Reference Price Research," Marketing Science, INFORMS, vol. 14(3_supplem), pages 161-169.
    4. Weitzman, Martin L, 1979. "Optimal Search for the Best Alternative," Econometrica, Econometric Society, vol. 47(3), pages 641-654, May.
    5. Janiszewski, Chris & Lichtenstein, Donald R, 1999. "A Range Theory Account of Price Perception," Journal of Consumer Research, Journal of Consumer Research Inc., vol. 25(4), pages 353-368, March.
    6. Stigler, George J., 2011. "Economics of Information," Ekonomicheskaya Politika / Economic Policy, Russian Presidential Academy of National Economy and Public Administration, vol. 5, pages 35-49.
    7. Biswas, Dipayan, 2004. "Economics of information in the Web economy: Towards a new theory?," Journal of Business Research, Elsevier, vol. 57(7), pages 724-733, July.
    8. Moorthy, Sridhar & Ratchford, Brian T & Talukdar, Debabrata, 1997. "Consumer Information Search Revisited: Theory and Empirical Analysis," Journal of Consumer Research, Journal of Consumer Research Inc., vol. 23(4), pages 263-277, March.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Noelia Oses & Jon Kepa Gerrikagoitia & Aurkene Alzua, 2016. "Evidence of hotels’ dynamic pricing patterns on an Internet distribution channel: the case study of the Basque Country’s hotels in 2013–2014," Information Technology & Tourism, Springer, vol. 15(4), pages 365-394, January.
    2. Sahar Karimi, 2021. "Cross-visiting Behaviour of Online Consumers Across Retailers’ and Comparison Sites, a Macro-Study," Information Systems Frontiers, Springer, vol. 23(3), pages 531-542, June.
    3. Tomasz Stanisław Szopiński & Robert Nowacki, 2015. "The Influence of Purchase Date and Flight Duration over the Dispersion of Airline Ticket Prices," Contemporary Economics, University of Economics and Human Sciences in Warsaw., vol. 9(3), September.

    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. Efthymios Lykopoulos & Georgios Voucharas & Dimitrios Xefteris, 2022. "Pandora’s rules in the laboratory," Experimental Economics, Springer;Economic Science Association, vol. 25(5), pages 1492-1514, November.
    2. Pantelis P. Analytis & Amit Kothiyal & Konstantinos Katsikopoulos, 2014. "Multi-attribute utility models as cognitive search engines," Judgment and Decision Making, Society for Judgment and Decision Making, vol. 9(5), pages 403-419, September.
    3. DeSarbo, Wayne S. & Choi, Jungwhan, 1998. "A latent structure double hurdle regression model for exploring heterogeneity in consumer search patterns," Journal of Econometrics, Elsevier, vol. 89(1-2), pages 423-455, November.
    4. repec:cup:judgdm:v:9:y:2014:i:5:p:403-419 is not listed on IDEAS
    5. Huang, Yanliu & Hutchinson, J. Wesley, 2013. "The roles of planning, learning, and mental models in repeated dynamic decision making," Organizational Behavior and Human Decision Processes, Elsevier, vol. 122(2), pages 163-176.
    6. Bart J. Bronnenberg & Jean-Pierre H. Dubé, 2016. "The Formation of Consumer Brand Preferences," NBER Working Papers 22691, National Bureau of Economic Research, Inc.
    7. Choudhary, Vidyanand & Currim, Imran & Dewan, Sanjeev & Jeliazkov, Ivan & Mintz, Ofer & Turner, John, 2017. "Evaluation Set Size and Purchase: Evidence from a Product Search Engine," Journal of Interactive Marketing, Elsevier, vol. 37(C), pages 16-31.
    8. Smith, Gerald E. & Venkatraman, Meera P. & Dholakia, Ruby Roy, 1999. "Diagnosing the search cost effect: Waiting time and the moderating impact of prior category knowledge," Journal of Economic Psychology, Elsevier, vol. 20(3), pages 285-314, June.
    9. Lemieux, James & Peterson, Robert A., 2011. "Purchase deadline as a moderator of the effects of price uncertainty on search duration," Journal of Economic Psychology, Elsevier, vol. 32(1), pages 33-44, February.
    10. Maity, Moutusy & Dass, Mayukh & Malhotra, Naresh K., 2014. "The Antecedents and Moderators of Offline Information Search: A Meta-Analysis," Journal of Retailing, Elsevier, vol. 90(2), pages 233-254.
    11. Jun B. Kim & Paulo Albuquerque & Bart J. Bronnenberg, 2010. "Online Demand Under Limited Consumer Search," Marketing Science, INFORMS, vol. 29(6), pages 1001-1023, 11-12.
    12. Jie Jennifer Zhang & Bing Jing, 2007. "The Impacts of Shopbots on Online Consumer Search," Working Papers 07-34, NET Institute, revised Sep 2007.
    13. Hoeffler, Steve & Ariely, Dan & West, Pat, 2006. "Path dependent preferences: The role of early experience and biased search in preference development," Organizational Behavior and Human Decision Processes, Elsevier, vol. 101(2), pages 215-229, November.
    14. Bronnenberg, Bart & Dube, Jean-Pierre, 2016. "The Formation of Consumer Brand Preferences," CEPR Discussion Papers 11648, C.E.P.R. Discussion Papers.
    15. Stephan Seiler & Fabio Pinna, 2017. "Estimating Search Benefits from Path-Tracking Data: Measurement and Determinants," Marketing Science, INFORMS, vol. 36(4), pages 565-589, July.
    16. Biswas, Dipayan, 2004. "Economics of information in the Web economy: Towards a new theory?," Journal of Business Research, Elsevier, vol. 57(7), pages 724-733, July.
    17. Frank J. van Rijnsoever & Martin J. Dijst & Carolina Castaldi, 2009. "Involvement and use of multiple search channels in the automobile purchase process," Innovation Studies Utrecht (ISU) working paper series 09-06, Utrecht University, Department of Innovation Studies, revised Apr 2009.
    18. Hector Chade & Lones Smith, 2006. "Simultaneous Search," Econometrica, Econometric Society, vol. 74(5), pages 1293-1307, September.
    19. Raluca M. Ursu & Qingliang Wang & Pradeep K. Chintagunta, 2020. "Search Duration," Marketing Science, INFORMS, vol. 39(5), pages 849-871, September.
    20. Shuk Ying Ho & David Bodoff & Kar Yan Tam, 2011. "Timing of Adaptive Web Personalization and Its Effects on Online Consumer Behavior," Information Systems Research, INFORMS, vol. 22(3), pages 660-679, September.
    21. Luyi Yang & Laurens G. Debo & Varun Gupta, 2019. "Search Among Queues Under Quality Differentiation," Management Science, INFORMS, vol. 65(8), pages 3605-3623, August.

    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:eee:jbrese:v:64:y:2011:i:6:p:543-550. 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: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/jbusres .

    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.