IDEAS home Printed from https://ideas.repec.org/p/ems/eureri/21098.html
   My bibliography  Save this paper

Consumer Acceptance of Recommendations by Interactive Decision Aids: The Joint Role of Temporal Distance and Concrete vs. Abstract Communications

Author

Listed:
  • Koehler, C.F.
  • Breugelmans, E.
  • Dellaert, B.G.C.

Abstract

Interactive decision aids (IDAs) typically use concrete product feature-based approaches to interact with consumers. Recently however, interaction designs that focus on communicating abstract consumer needs have been suggested as a promising alternative. This article investigates how temporal distance moderates the effectiveness of these two competing IDA communication designs by its effect on consumers’ mental representation of the product decision problem. Temporal distance is inherently connected to IDAs in two ways. Congruency between consumption timing (immediate vs. distant) and IDA communication design (concrete vs. abstract, respectively) increases the likelihood to accept the IDA’s advice. This effect is also achieved by congruency between IDA process timing (immediate vs. delayed delivery of recommendations) and IDA communication design (concrete vs. abstract, respectively). We further show that this process is mediated by the perceived transparency of the IDA process. Managers and researchers need to take into account the importance of congruency between the user and the interface through which companies interact with their users and can further optimize IDAs so that they better match consumers’ mental representations.

Suggested Citation

  • Koehler, C.F. & Breugelmans, E. & Dellaert, B.G.C., 2010. "Consumer Acceptance of Recommendations by Interactive Decision Aids: The Joint Role of Temporal Distance and Concrete vs. Abstract Communications," ERIM Report Series Research in Management ERS-2010-041-MKT, Erasmus Research Institute of Management (ERIM), ERIM is the joint research institute of the Rotterdam School of Management, Erasmus University and the Erasmus School of Economics (ESE) at Erasmus University Rotterdam.
  • Handle: RePEc:ems:eureri:21098
    as

    Download full text from publisher

    File URL: https://repub.eur.nl/pub/21098/ERS-2010-041-MKT.pdf
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Dellaert, Benedict G.C. & Arentze, Theo A. & Timmermans, Harry J.P., 2008. "Shopping context and consumers’ mental representation of complex shopping trip decision problems," Journal of Retailing, Elsevier, vol. 84(2), pages 219-232.
    2. Gershoff, Andrew D & Broniarczyk, Susan M & West, Patricia M, 2001. "Recommendation or Evaluation? Task Sensitivity in Information," Journal of Consumer Research, Journal of Consumer Research Inc., vol. 28(3), pages 418-438, December.
    3. Yeung-Jo Kim & Jongwon Park & Robert S. Wyer Jr., 2009. "Effects of Temporal Distance and Memory on Consumer Judgments," Journal of Consumer Research, Journal of Consumer Research Inc., vol. 36(4), pages 634-645, December.
    4. Beatty, Sharon E & Talpade, Salil, 1994. "Adolescent Influence in Family Decision Making: A Replication with Extension," Journal of Consumer Research, Journal of Consumer Research Inc., vol. 21(2), pages 332-341, September.
    5. Lynch, John G, Jr, 1982. "On the External Validity of Experiments in Consumer Research," Journal of Consumer Research, Journal of Consumer Research Inc., vol. 9(3), pages 225-239, December.
    6. Huber, Joel & Ariely, Dan & Fischer, Gregory, 2002. "Expressing Preferences in a Principal-Agent Task: A Comparison of Choice, Rating, and Matching," Organizational Behavior and Human Decision Processes, Elsevier, vol. 87(1), pages 66-90, January.
    7. Ariely, Dan, 2000. "Controlling the Information Flow: Effects on Consumers' Decision Making and Preferences," Journal of Consumer Research, Journal of Consumer Research Inc., vol. 27(2), pages 233-248, September.
    8. Diehl, Kristin & Kornish, Laura J & Lynch, John G, Jr, 2003. "Smart Agents: When Lower Search Costs for Quality Information Increase Price Sensitivity," Journal of Consumer Research, Journal of Consumer Research Inc., vol. 30(1), pages 56-71, June.
    9. Gerald Häubl & Valerie Trifts, 2000. "Consumer Decision Making in Online Shopping Environments: The Effects of Interactive Decision Aids," Marketing Science, INFORMS, vol. 19(1), pages 4-21, May.
    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. Chee Wei Phang & Atreyi Kankanhalli & Bernard C. Y. Tan, 2015. "What Motivates Contributors vs. Lurkers? An Investigation of Online Feedback Forums," Information Systems Research, INFORMS, vol. 26(4), pages 773-792, December.

    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. Lurie, Nicholas H. & Wen, Na, 2014. "Simple Decision Aids and Consumer Decision Making," Journal of Retailing, Elsevier, vol. 90(4), pages 511-523.
    2. Aksoy, Lerzan & Cooil, Bruce & Lurie, Nicholas H., 2011. "Decision Quality Measures in Recommendation Agents Research," Journal of Interactive Marketing, Elsevier, vol. 25(2), pages 110-122.
    3. Suri, Rajneesh & Cai, Jane Zhen & Monroe, Kent B. & Thakor, Mrugank V., 2012. "Retailers’ Merchandise Organization and Price Perceptions," Journal of Retailing, Elsevier, vol. 88(1), pages 168-179.
    4. Punj, Girish & Moore, Robert, 2009. "Information search and consideration set formation in a web-based store environment," Journal of Business Research, Elsevier, vol. 62(6), pages 644-650, June.
    5. Gavan J. Fitzsimons & Donald R. Lehmann, 2004. "Reactance to Recommendations: When Unsolicited Advice Yields Contrary Responses," Marketing Science, INFORMS, vol. 23(1), pages 82-94, September.
    6. Tuck Siong Chung & Roland T. Rust & Michel Wedel, 2009. "My Mobile Music: An Adaptive Personalization System for Digital Audio Players," Marketing Science, INFORMS, vol. 28(1), pages 52-68, 01-02.
    7. Stefan Hoffmann & Tom Joerß & Robert Mai & Payam Akbar, 2022. "Augmented reality-delivered product information at the point of sale: when information controllability backfires," Journal of the Academy of Marketing Science, Springer, vol. 50(4), pages 743-776, July.
    8. Wagner, Gerhard & Schramm-Klein, Hanna & Steinmann, Sascha, 2017. "Consumers' attitudes and intentions toward Internet-enabled TV shopping," Journal of Retailing and Consumer Services, Elsevier, vol. 34(C), pages 278-286.
    9. Ana Alina Tudoran, 2022. "A machine learning approach to identifying decision-making styles for managing customer relationships," Electronic Markets, Springer;IIM University of St. Gallen, vol. 32(1), pages 351-374, March.
    10. Benedict G. C. Dellaert & Suzanne B. Shu & Theo A. Arentze & Tom Baker & Kristin Diehl & Bas Donkers & Nathanael J. Fast & Gerald Häubl & Heidi Johnson & Uma R. Karmarkar & Harmen Oppewal & Bernd H. S, 2020. "Consumer decisions with artificially intelligent voice assistants," Marketing Letters, Springer, vol. 31(4), pages 335-347, December.
    11. Ghiassaleh, Arezou & Kocher, Bruno & Czellar, Sandor, 2020. "Best seller!? Unintended negative consequences of popularity signs on consumer choice behavior," International Journal of Research in Marketing, Elsevier, vol. 37(4), pages 805-820.
    12. Eric Johnson & Suzanne Shu & Benedict Dellaert & Craig Fox & Daniel Goldstein & Gerald Häubl & Richard Larrick & John Payne & Ellen Peters & David Schkade & Brian Wansink & Elke Weber, 2012. "Beyond nudges: Tools of a choice architecture," Marketing Letters, Springer, vol. 23(2), pages 487-504, June.
    13. Arnold Kamis & Tziporah Stern & Daniel M. Ladik, 2010. "A flow-based model of web site intentions when users customize products in business-to-consumer electronic commerce," Information Systems Frontiers, Springer, vol. 12(2), pages 157-168, April.
    14. Murray, Kyle B. & Häubl, Gerald, 2009. "Personalization without Interrogation: Towards more Effective Interactions between Consumers and Feature-Based Recommendation Agents," Journal of Interactive Marketing, Elsevier, vol. 23(2), pages 138-146.
    15. Bonsall, Peter & Shires, Jeremy & Maule, John & Matthews, Bryan & Beale, Jo, 2007. "Responses to complex pricing signals: Theory, evidence and implications for road pricing," Transportation Research Part A: Policy and Practice, Elsevier, vol. 41(7), pages 672-683, August.
    16. Fernandes, Semila & Venkatesh, V.G. & Panda, Rajesh & Shi, Yangyan, 2021. "Measurement of factors influencing online shopper buying decisions: A scale development and validation," Journal of Retailing and Consumer Services, Elsevier, vol. 59(C).
    17. de Kervenoael, Ronan & Aykac, D. Selcen O. & Palmer, Mark, 2009. "Online social capital: Understanding e-impulse buying in practice," Journal of Retailing and Consumer Services, Elsevier, vol. 16(4), pages 320-328.
    18. Sylvie Rolland & Déborah Wallet-Wodka, 2003. "Electronic agents on the Internet: A new way to satisfy the consumer?," Post-Print halshs-00143040, HAL.
    19. Nath, Prithwiraj & McKechnie, Sally, 2016. "Task facilitative tools, choice goals, and risk averseness: A process-view study of e-stores," Journal of Business Research, Elsevier, vol. 69(5), pages 1572-1576.
    20. Diehl, Kristin & van Herpen, Erica & Lamberton, Cait, 2015. "Organizing Products with Complements versus Substitutes: Effects on Store Preferences as a Function of Effort and Assortment Perceptions," Journal of Retailing, Elsevier, vol. 91(1), pages 1-18.

    More about this item

    Keywords

    construal level theory; consumer behavior; e-commerce; ida communication design; interactive decision aids;
    All these keywords.

    JEL classification:

    • C44 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Operations Research; Statistical Decision Theory
    • M - Business Administration and Business Economics; Marketing; Accounting; Personnel Economics
    • M31 - Business Administration and Business Economics; Marketing; Accounting; Personnel Economics - - Marketing and Advertising - - - Marketing

    Statistics

    Access and download statistics

    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:ems:eureri:21098. 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: RePub (email available below). General contact details of provider: https://edirc.repec.org/data/erimanl.html .

    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.