IDEAS home Printed from https://ideas.repec.org/a/spr/joamsc/v47y2019i5d10.1007_s11747-019-00664-8.html
   My bibliography  Save this article

Effects of dominance transitions on advice adherence in professional service conversations

Author

Listed:
  • Helen Si Wang

    (The University of Hong Kong)

  • Chi Kin (Bennett) Yim

    (The University of Hong Kong)

Abstract

For many professional services, advice adherence is a necessary condition for achieving service success for both customers and service providers. Despite their pivotal roles in value co-creation, typical conversational interactions often lead to low adherence. We propose that enabling a “dominance transition,” from provider dominance in the pre-advice stage to customer dominance in the post-advice stage, enhances advice adherence because it increases customers’ perceived common ground. Furthermore, providers’ consultation focus, customers’ prior knowledge, and customers’ perceived adherence effort moderate this process. Using mixed methods, including both empirical modeling and controlled and field experiments, we validate the proposed model in various contexts (healthcare, financial services, and fitness and wellness counseling). The findings establish several theoretical contributions and offer managerial implications for improving advice adherence by managing dominance transitions in conversational interactions more effectively through training service providers or even programming AI chatbots.

Suggested Citation

  • Helen Si Wang & Chi Kin (Bennett) Yim, 2019. "Effects of dominance transitions on advice adherence in professional service conversations," Journal of the Academy of Marketing Science, Springer, vol. 47(5), pages 919-938, September.
  • Handle: RePEc:spr:joamsc:v:47:y:2019:i:5:d:10.1007_s11747-019-00664-8
    DOI: 10.1007/s11747-019-00664-8
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s11747-019-00664-8
    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/s11747-019-00664-8?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. Yaniv, Ilan & Kleinberger, Eli, 2000. "Advice Taking in Decision Making: Egocentric Discounting and Reputation Formation," Organizational Behavior and Human Decision Processes, Elsevier, vol. 83(2), pages 260-281, November.
    2. Ilan Yaniv & Shoham Choshen-Hillel, 2012. "When guessing what another person would say is better than giving your own opinion: Using perspective-taking to improve advice-taking," Discussion Paper Series dp622, The Federmann Center for the Study of Rationality, the Hebrew University, Jerusalem.
    3. Camacho, N.M.A. & de Jong, M.G. & Stremersch, S., 2014. "The Effect of Customer Empowerment on Adherence to Expert Advice," ERIM Report Series Research in Management ERS-2014-005-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.
    4. Temerak, M.S. & Winklhofer, H. & Hibbert, S.A., 2018. "Facilitating customer adherence to complex services through multi-interface interactions: The case of a weight loss service," Journal of Business Research, Elsevier, vol. 88(C), pages 265-276.
    5. Sniezek, Janet A. & Van Swol, Lyn M., 2001. "Trust, Confidence, and Expertise in a Judge-Advisor System," Organizational Behavior and Human Decision Processes, Elsevier, vol. 84(2), pages 288-307, March.
    6. Camacho, Nuno & De Jong, Martijn & Stremersch, Stefan, 2014. "The effect of customer empowerment on adherence to expert advice," International Journal of Research in Marketing, Elsevier, vol. 31(3), pages 293-308.
    7. Bonaccio, Silvia & Dalal, Reeshad S., 2006. "Advice taking and decision-making: An integrative literature review, and implications for the organizational sciences," Organizational Behavior and Human Decision Processes, Elsevier, vol. 101(2), pages 127-151, November.
    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. Mariani, Marcello M. & Hashemi, Novin & Wirtz, Jochen, 2023. "Artificial intelligence empowered conversational agents: A systematic literature review and research agenda," Journal of Business Research, Elsevier, vol. 161(C).
    2. Tang, Chuanyi & Guo, Lin & Gruen, Thomas, 2024. "A goal-driven framework for compliance-dependent services: Pathways to customer satisfaction and well-being," Journal of Business Research, Elsevier, vol. 177(C).
    3. Mark Anthony Camilleri & Ciro Troise, 2023. "Live support by chatbots with artificial intelligence: A future research agenda," Service Business, Springer;Pan-Pacific Business Association, vol. 17(1), pages 61-80, March.

    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. Jodlbauer, Barbara & Jonas, Eva, 2011. "Forecasting clients' reactions: How does the perception of strategic behavior influence the acceptance of advice?," International Journal of Forecasting, Elsevier, vol. 27(1), pages 121-133, January.
    2. Kausel, Edgar E. & Culbertson, Satoris S. & Leiva, Pedro I. & Slaughter, Jerel E. & Jackson, Alexander T., 2015. "Too arrogant for their own good? Why and when narcissists dismiss advice," Organizational Behavior and Human Decision Processes, Elsevier, vol. 131(C), pages 33-50.
    3. Albert E. Mannes, 2009. "Are We Wise About the Wisdom of Crowds? The Use of Group Judgments in Belief Revision," Management Science, INFORMS, vol. 55(8), pages 1267-1279, August.
    4. Van Swol, Lyn M., 2011. "Forecasting another's enjoyment versus giving the right answer: Trust, shared values, task effects, and confidence in improving the acceptance of advice," International Journal of Forecasting, Elsevier, vol. 27(1), pages 103-120, January.
    5. Jodlbauer, Barbara & Jonas, Eva, 2011. "Forecasting clients’ reactions: How does the perception of strategic behavior influence the acceptance of advice?," International Journal of Forecasting, Elsevier, vol. 27(1), pages 121-133.
    6. Gino, Francesca, 2008. "Do we listen to advice just because we paid for it? The impact of advice cost on its use," Organizational Behavior and Human Decision Processes, Elsevier, vol. 107(2), pages 234-245, November.
    7. Robert M. Gillenkirch & Julia Ortner & Sebastian Robert & Louis Velthuis, 2023. "Designing incentives and performance measurement for advisors: How to make decision-makers listen to advice," Working Papers 2304, Gutenberg School of Management and Economics, Johannes Gutenberg-Universität Mainz.
    8. Van Swol, Lyn M., 2011. "Forecasting another’s enjoyment versus giving the right answer: Trust, shared values, task effects, and confidence in improving the acceptance of advice," International Journal of Forecasting, Elsevier, vol. 27(1), pages 103-120.
    9. Lourenço, Carlos J.S. & Dellaert, Benedict G.C. & Donkers, Bas, 2020. "Whose Algorithm Says So: The Relationships Between Type of Firm, Perceptions of Trust and Expertise, and the Acceptance of Financial Robo-Advice," Journal of Interactive Marketing, Elsevier, vol. 49(C), pages 107-124.
    10. Winkler, Jens & Moser, Roger, 2016. "Biases in future-oriented Delphi studies: A cognitive perspective," Technological Forecasting and Social Change, Elsevier, vol. 105(C), pages 63-76.
    11. Back, Camila & Morana, Stefan & Spann, Martin, 2023. "When do robo-advisors make us better investors? The impact of social design elements on investor behavior," Journal of Behavioral and Experimental Economics (formerly The Journal of Socio-Economics), Elsevier, vol. 103(C).
    12. Blunden, Hayley & Logg, Jennifer M. & Brooks, Alison Wood & John, Leslie K. & Gino, Francesca, 2019. "Seeker beware: The interpersonal costs of ignoring advice," Organizational Behavior and Human Decision Processes, Elsevier, vol. 150(C), pages 83-100.
    13. Philipp Ecken & Richard Pibernik, 2016. "Hit or Miss: What Leads Experts to Take Advice for Long-Term Judgments?," Management Science, INFORMS, vol. 62(7), pages 2002-2021, July.
    14. Önkal, Dilek & Sinan Gönül, M. & Goodwin, Paul & Thomson, Mary & Öz, Esra, 2017. "Evaluating expert advice in forecasting: Users’ reactions to presumed vs. experienced credibility," International Journal of Forecasting, Elsevier, vol. 33(1), pages 280-297.
    15. See, Kelly E. & Morrison, Elizabeth W. & Rothman, Naomi B. & Soll, Jack B., 2011. "The detrimental effects of power on confidence, advice taking, and accuracy," Organizational Behavior and Human Decision Processes, Elsevier, vol. 116(2), pages 272-285.
    16. Gehrig, Thomas & Güth, Werner & Leví0nský, René & Popova, Vera, 2010. "On the evolution of professional consulting," Journal of Economic Behavior & Organization, Elsevier, vol. 76(1), pages 113-126, October.
    17. Yildiz, H. Emre, 2016. "“Us vs. them” or “us over them”? On the roles of similarity and status in M&As," International Business Review, Elsevier, vol. 25(1), pages 51-65.
    18. Logg, Jennifer M. & Minson, Julia A. & Moore, Don A., 2019. "Algorithm appreciation: People prefer algorithmic to human judgment," Organizational Behavior and Human Decision Processes, Elsevier, vol. 151(C), pages 90-103.
    19. Amaral, Christopher & Kolsarici, Ceren, 2020. "The financial advice puzzle: The role of consumer heterogeneity in the advisor choice," Journal of Retailing and Consumer Services, Elsevier, vol. 54(C).
    20. Carlson, Keith & Kopalle, Praveen K. & Riddell, Allen & Rockmore, Daniel & Vana, Prasad, 2023. "Complementing human effort in online reviews: A deep learning approach to automatic content generation and review synthesis," International Journal of Research in Marketing, Elsevier, vol. 40(1), pages 54-74.

    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:joamsc:v:47:y:2019:i:5:d:10.1007_s11747-019-00664-8. 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.