IDEAS home Printed from https://ideas.repec.org/a/plo/pone00/0287663.html
   My bibliography  Save this article

Online recommenders’ anthropomorphism improves user response to hedonic and benefit-based product appeals through the recommenders’ perceived ability to learn

Author

Listed:
  • Wojciech Trzebiński
  • Beata Marciniak
  • Eliza Kulczycka

Abstract

Previous studies reveal the limited effectiveness of benefit-based and hedonic-based product recommendations provided by online recommenders, and recommender anthropomorphism is considered a remedy. This paper aims to investigate the positive effect of anthropomorphism by involving the online recommender’s perceived ability to learn as a mediator. Based on schema congruity theory, perceived benefit/hedonic appeals appropriateness is considered a dependent variable. In Study 1, subtle anthropomorphic cues within an online recommender had a positive effect on perceived benefit-appeals appropriateness through the perceived ability to learn. Study 2 demonstrated the positive relationship between perceived anthropomorphism and perceived hedonic-appeal appropriateness, with the mediating role of the perceived ability to learn. The results advance the knowledge about consumer response to online recommenders from the perspective of anthropomorphism and schema congruity theory. Marketers and consumer organizations are advised on how to deal with online recommender systems providing benefit and hedonic appeals.

Suggested Citation

  • Wojciech Trzebiński & Beata Marciniak & Eliza Kulczycka, 2023. "Online recommenders’ anthropomorphism improves user response to hedonic and benefit-based product appeals through the recommenders’ perceived ability to learn," PLOS ONE, Public Library of Science, vol. 18(6), pages 1-23, June.
    • Handle: RePEc:plo:pone00:0287663
    DOI: 10.1371/journal.pone.0287663
    as

    Download full text from publisher

    File URL: https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0287663
    Download Restriction: no
    File URL: https://journals.plos.org/plosone/article/file?id=10.1371/journal.pone.0287663&type=printable
    Download Restriction: no
    File URL: https://libkey.io/10.1371/journal.pone.0287663?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
    ---><---

    References listed on IDEAS

    as
    1. Christian Hildebrand & Anouk Bergner, 2021. "Conversational robo advisors as surrogates of trust: onboarding experience, firm perception, and consumer financial decision making," Journal of the Academy of Marketing Science, Springer, vol. 49(4), pages 659-676, July.
    2. Nicolas Pfeuffer & Alexander Benlian & Henner Gimpel & Oliver Hinz, 2019. "Anthropomorphic Information Systems," Business & Information Systems Engineering: The International Journal of WIRTSCHAFTSINFORMATIK, Springer;Gesellschaft für Informatik e.V. (GI), vol. 61(4), pages 523-533, August.
    3. Adam, Martin & Wessel, Michael & Benlian, Alexander, 2020. "AI-based chatbots in customer service and their effects on user compliance," Publications of Darmstadt Technical University, Institute for Business Studies (BWL) 119304, Darmstadt Technical University, Department of Business Administration, Economics and Law, Institute for Business Studies (BWL).
    4. Nicolas Pfeuffer & Alexander Benlian & Henner Gimpel & Oliver Hinz, 2019. "Anthropomorphic Information Systems," Business & Information Systems Engineering: The International Journal of WIRTSCHAFTSINFORMATIK, Springer;Gesellschaft für Informatik e.V. (GI), vol. 61(4), pages 523-533, August.
    5. Rijsdijk, S.A. & Hultink, E.J. & Diamantopoulos, A., 2007. "Product Intelligence: Its Conceptualization, Measurement and Impact on Consumer Satisfaction," ERIM Report Series Research in Management ERS-2007-006-ORG, 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.
    6. Dokyun Lee & Kartik Hosanagar, 2021. "How Do Product Attributes and Reviews Moderate the Impact of Recommender Systems Through Purchase Stages?," Management Science, INFORMS, vol. 67(1), pages 524-546, January.
    7. Sun, Yongqiang & Yang, Chaofan & Shen, Xiao-Liang & Wang, Nan, 2020. "When digitalized customers meet digitalized services: A digitalized social cognitive perspective of omnichannel service usage," International Journal of Information Management, Elsevier, vol. 54(C).
    8. Schreiner, Timo & Rese, Alexandra & Baier, Daniel, 2019. "Multichannel personalization: Identifying consumer preferences for product recommendations in advertisements across different media channels," Journal of Retailing and Consumer Services, Elsevier, vol. 48(C), pages 87-99.
    9. Wien, Anders Hauge & Peluso, Alessandro M., 2021. "Influence of human versus AI recommenders: The roles of product type and cognitive processes," Journal of Business Research, Elsevier, vol. 137(C), pages 13-27.
    10. Gelbrich, Katja & Hagel, Julia & Orsingher, Chiara, 2021. "Emotional support from a digital assistant in technology-mediated services: Effects on customer satisfaction and behavioral persistence," International Journal of Research in Marketing, Elsevier, vol. 38(1), pages 176-193.
    11. Pankaj Aggarwal & Ann L. McGill, 2007. "Is That Car Smiling at Me? Schema Congruity as a Basis for Evaluating Anthropomorphized Products," Journal of Consumer Research, Journal of Consumer Research Inc., vol. 34(4), pages 468-479, June.
    12. 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.
    13. Chinchanachokchai, Sydney & Thontirawong, Pipat & Chinchanachokchai, Punjaporn, 2021. "A tale of two recommender systems: The moderating role of consumer expertise on artificial intelligence based product recommendations," Journal of Retailing and Consumer Services, Elsevier, vol. 61(C).
    14. repec:plo:pone00:0199948 is not listed on IDEAS
    15. repec:plo:pone00:0127747 is not listed on IDEAS
    16. Ahn, Jungyong & Kim, Jungwon & Sung, Yongjun, 2022. "The effect of gender stereotypes on artificial intelligence recommendations," Journal of Business Research, Elsevier, vol. 141(C), pages 50-59.
    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. Ertugrul Uysal & Sascha Alavi & Valéry Bezençon, 2022. "Trojan horse or useful helper? A relationship perspective on artificial intelligence assistants with humanlike features," Journal of the Academy of Marketing Science, Springer, vol. 50(6), pages 1153-1175, November.
    2. Lucia-Palacios, Laura & Pérez-López, Raúl, 2021. "Effects of Home Voice Assistants' Autonomy on Instrusiveness and Usefulness: Direct, Indirect, and Moderating Effects of Interactivity," Journal of Interactive Marketing, Elsevier, vol. 56(C), pages 41-54.
    3. Ulrich Gnewuch & Stefan Morana & Marc T. P. Adam & Alexander Maedche, 2022. "Opposing Effects of Response Time in Human–Chatbot Interaction," Business & Information Systems Engineering: The International Journal of WIRTSCHAFTSINFORMATIK, Springer;Gesellschaft für Informatik e.V. (GI), vol. 64(6), pages 773-791, December.
    4. Marikyan, Davit & Papagiannidis, Savvas & Rana, Omer F. & Ranjan, Rajiv & Morgan, Graham, 2022. "“Alexa, let’s talk about my productivity”: The impact of digital assistants on work productivity," Journal of Business Research, Elsevier, vol. 142(C), pages 572-584.
    5. 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.
    6. Jansen, Thomas & Moura, Francisco Tigre, 2024. "WOM, eWOM and WOMachine: The evolution of consumer recommendations through a systematic review of 194 studies," IU Discussion Papers - Marketing & Communication 3 (Juni 2024), IU International University of Applied Sciences.
    7. Gallin, Steffie & Portes, Audrey, 2024. "Online shopping: How can algorithm performance expectancy enhance impulse buying?," Journal of Retailing and Consumer Services, Elsevier, vol. 81(C).
    8. Darima Fotheringham & Michael A. Wiles, 2023. "The effect of implementing chatbot customer service on stock returns: an event study analysis," Journal of the Academy of Marketing Science, Springer, vol. 51(4), pages 802-822, July.
    9. Thomas P. Novak & Donna L. Hoffman, 2019. "Relationship journeys in the internet of things: a new framework for understanding interactions between consumers and smart objects," Journal of the Academy of Marketing Science, Springer, vol. 47(2), pages 216-237, March.
    10. Sara Moussawi & Marios Koufaris & Raquel Benbunan-Fich, 2021. "How perceptions of intelligence and anthropomorphism affect adoption of personal intelligent agents," Electronic Markets, Springer;IIM University of St. Gallen, vol. 31(2), pages 343-364, June.
    11. Mengjun Li & Ayoung Suh, 2022. "Anthropomorphism in AI-enabled technology: A literature review," Electronic Markets, Springer;IIM University of St. Gallen, vol. 32(4), pages 2245-2275, December.
    12. Yang, Yikai & Zheng, Jiehui & Yu, Yining & Qiu, Yiling & Wang, Lei, 2024. "The role of recommendation sources and attribute framing in online product recommendations," Journal of Business Research, Elsevier, vol. 174(C).
    13. Thuy Duong Oesterreich & Eduard Anton & Julian Schuir & Alexander Brehm & Frank Teuteberg, 2023. "How can I help you? Design principles for task-oriented speech dialog systems in customer service," Information Systems and e-Business Management, Springer, vol. 21(1), pages 37-79, March.
    14. Stefan Stieglitz & Milad Mirbabaie & Nicholas R. J. Möllmann & Jannik Rzyski, 2022. "Collaborating with Virtual Assistants in Organizations: Analyzing Social Loafing Tendencies and Responsibility Attribution," Information Systems Frontiers, Springer, vol. 24(3), pages 745-770, June.
    15. Jonas Wanner & Lukas-Valentin Herm & Kai Heinrich & Christian Janiesch, 2022. "The effect of transparency and trust on intelligent system acceptance: Evidence from a user-based study," Electronic Markets, Springer;IIM University of St. Gallen, vol. 32(4), pages 2079-2102, December.
    16. Thure Georg Weimann & Hannes Schlieter & Alfred Benedikt Brendel, 2022. "Virtual Coaches," Business & Information Systems Engineering: The International Journal of WIRTSCHAFTSINFORMATIK, Springer;Gesellschaft für Informatik e.V. (GI), vol. 64(4), pages 515-528, August.
    17. Lane Peterson Fronczek & Martin Mende & Maura L. Scott & Gergana Y. Nenkov & Anders Gustafsson, 2023. "Friend or foe? Can anthropomorphizing self-tracking devices backfire on marketers and consumers?," Journal of the Academy of Marketing Science, Springer, vol. 51(5), pages 1075-1097, September.
    18. Cong-Minh Dinh & Sungjun (Steven) Park, 2024. "How to increase consumer intention to use Chatbots? An empirical analysis of hedonic and utilitarian motivations on social presence and the moderating effects of fear across generations," Electronic Commerce Research, Springer, vol. 24(4), pages 2427-2467, December.
    19. Stephan Diederich & Alfred Benedikt Brendel & Lutz M. Kolbe, 2020. "Designing Anthropomorphic Enterprise Conversational Agents," Business & Information Systems Engineering: The International Journal of WIRTSCHAFTSINFORMATIK, Springer;Gesellschaft für Informatik e.V. (GI), vol. 62(3), pages 193-209, June.
    20. Molaie, Mir Majid & Lee, Wonjae, 2022. "Economic corollaries of personalized recommendations," Journal of Retailing and Consumer Services, Elsevier, vol. 68(C).

    More about this item

    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:plo:pone00:0287663. 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: plosone (email available below). General contact details of provider: https://journals.plos.org/plosone/ .

    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.