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Experimental analysis of consumer channel-mix use

Author

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  • Oppewal, Harmen
  • Tojib, Dewi Rooslani
  • Louvieris, Panos

Abstract

Today's consumers have access to multiple consumer distribution channels. To remain competitive, retailers must offer different contact points to consumers. This empirical study examines channel-mix use decisions for 352 online customers' holiday booking preparations. A scenario based experimental approach studies consumer channel-mix use by channel and decision context attributes. The study models effects of time pressure, expected expenditure, channel quality, and access costs on the use of eight channel options, including traditional and online options. Over one-half of respondents use multiple channels to decide trip booking; however, most travelers book trips using the channel they initially investigated for information. Results show expected expenditure does not influence channel use; however, overall cost affects the booking's timing. Time pressures force respondents to visit a travel agent or collect additional brochures to quickly complete the purchase. Results suggest brochures fulfill an important support role.

Suggested Citation

  • Oppewal, Harmen & Tojib, Dewi Rooslani & Louvieris, Panos, 2013. "Experimental analysis of consumer channel-mix use," Journal of Business Research, Elsevier, vol. 66(11), pages 2226-2233.
    • Handle: RePEc:eee:jbrese:v:66:y:2013:i:11:p:2226-2233
    DOI: 10.1016/j.jbusres.2012.02.002
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    References listed on IDEAS

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    Citations

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    Cited by:

    1. Sajad Rezaei & Wan Khairuzzaman Wan Ismail, 2014. "Examining online channel selection behaviour among social media shoppers: a PLS analysis," International Journal of Electronic Marketing and Retailing, Inderscience Enterprises Ltd, vol. 6(1), pages 28-51.
    2. Eunhye Kim & Christian Fernando Libaque-Saenz & Myeong-Cheol Park, 2019. "Understanding shopping routes of offline purchasers: selection of search-channels (online vs. offline) and search-platforms (mobile vs. PC) based on product types," Service Business, Springer;Pan-Pacific Business Association, vol. 13(2), pages 305-338, June.
    3. Marcial López-Pastor & Jesús García-Madariaga & Joaquín Sánchez & Jose Figueiredo, 2020. "Demand Impact for Prices Ending with “9” and “0” in Online and Offline Consumer Goods Retail Trade Channels," International Review of Management and Marketing, Econjournals, vol. 10(6), pages 58-78.
    4. Chorus, Caspar & van Cranenburgh, Sander & Dekker, Thijs, 2014. "Random regret minimization for consumer choice modeling: Assessment of empirical evidence," Journal of Business Research, Elsevier, vol. 67(11), pages 2428-2436.
    5. Andrzej Dudek & Daria Elżbieta Jaremen & Izabela Michalska-Dudek, 2020. "Socio-economic factors determining the ROPO trend in the travel industry," Tourism Economics, , vol. 26(6), pages 873-907, September.
    6. Arnaud Riviere & Rémi Mencarelli & Bertrand Belvaux & Jessie Pallud, 2016. "Channel proliferation and perceived value of the digital offer in the newspaper industry: a complementary effect? [Multiplication des canaux et valeur perçue de l’offre digitale dans la presse écri," Post-Print hal-01591784, HAL.
    7. Oppewal, Harmen & Huybers, Twan & Crouch, Geoffrey I., 2015. "Tourist destination and experience choice: A choice experimental analysis of decision sequence effects," Tourism Management, Elsevier, vol. 48(C), pages 467-476.

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