IDEAS home Printed from https://ideas.repec.org/a/pal/palcom/v11y2024i1d10.1057_s41599-024-02600-w.html
   My bibliography  Save this article

Abstract or concrete? The effects of language style and service context on continuous usage intention for AI voice assistants

Author

Listed:
  • Hai Lan

    (Southwestern University of Finance and Economics)

  • Xiaofei Tang

    (Southwestern University of Finance and Economics)

  • Yong Ye

    (Southwestern University of Finance and Economics)

  • Huiqin Zhang

    (Chengdu University of Technology)

Abstract

The unprecedented growth in voice assistants (VAs) provided with artificial intelligence (AI) challenges managers aiming to harness various new technologies to enhance the competitiveness of their products. This article thus investigates how VAs can more effectively improve the user experience by focusing on the attributes of service contexts, matching a utilitarian-dominant (hedonic-dominant) context with concrete (abstract) language in VA–human interactions. Through such matching, VA companies can potentially create a beneficial congruity effect, leading to more favorable evaluations. The results of three studies therefore suggest that users prefer VAs with abstract language in a hedonic-dominant service context, but that VAs with concrete language are more competitive in a utilitarian-dominant service context. Furthermore, the perception of processing fluency mediates this effect. Accordingly, these findings provide a better understanding of AI–human interactions and open a straightforward path for managers or technology providers to enhance users’ continuous usage intention.

Suggested Citation

  • Hai Lan & Xiaofei Tang & Yong Ye & Huiqin Zhang, 2024. "Abstract or concrete? The effects of language style and service context on continuous usage intention for AI voice assistants," Palgrave Communications, Palgrave Macmillan, vol. 11(1), pages 1-13, December.
  • Handle: RePEc:pal:palcom:v:11:y:2024:i:1:d:10.1057_s41599-024-02600-w
    DOI: 10.1057/s41599-024-02600-w
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1057/s41599-024-02600-w
    File Function: Abstract
    Download Restriction: Access to full text is restricted to subscribers.

    File URL: https://libkey.io/10.1057/s41599-024-02600-w?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. Hakkyun Kim & Akshay R. Rao & Angela Y. Lee, 2009. "It's Time to Vote: The Effect of Matching Message Orientation and Temporal Frame on Political Persuasion," Journal of Consumer Research, Journal of Consumer Research Inc., vol. 35(6), pages 877-889, April.
    2. De Angelis, Matteo & Tassiello, Vito & Amatulli, Cesare & Costabile, Michele, 2017. "How language abstractness affects service referral persuasiveness," Journal of Business Research, Elsevier, vol. 72(C), pages 119-126.
    3. Simona Botti & Ann L. McGill, 2011. "The Locus of Choice: Personal Causality and Satisfaction with Hedonic and Utilitarian Decisions," Journal of Consumer Research, Journal of Consumer Research Inc., vol. 37(6), pages 1065-1078.
    4. McLean, Graeme & Osei-Frimpong, Kofi & Barhorst, Jennifer, 2021. "Alexa, do voice assistants influence consumer brand engagement? – Examining the role of AI powered voice assistants in influencing consumer brand engagement," Journal of Business Research, Elsevier, vol. 124(C), pages 312-328.
    5. 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.
    6. Yuan, Chunlin & Zhang, Chenlei & Wang, Shuman, 2022. "Social anxiety as a moderator in consumer willingness to accept AI assistants based on utilitarian and hedonic values," Journal of Retailing and Consumer Services, Elsevier, vol. 65(C).
    7. Liu, Xing (Stella) & Yi, Xiao (Shannon) & Wan, Lisa C., 2022. "Friendly or competent? The effects of perception of robot appearance and service context on usage intention," Annals of Tourism Research, Elsevier, vol. 92(C).
    8. Roy, Rajat & Naidoo, Vik, 2021. "Enhancing chatbot effectiveness: The role of anthropomorphic conversational styles and time orientation," Journal of Business Research, Elsevier, vol. 126(C), pages 23-34.
    9. Romain Cadario & Chiara Longoni & Carey K. Morewedge, 2021. "Understanding, explaining, and utilizing medical artificial intelligence," Nature Human Behaviour, Nature, vol. 5(12), pages 1636-1642, December.
    10. Sheehan, Ben & Jin, Hyun Seung & Gottlieb, Udo, 2020. "Customer service chatbots: Anthropomorphism and adoption," Journal of Business Research, Elsevier, vol. 115(C), pages 14-24.
    11. Yuanyuan Zhou & Zhuoying Fei & Yuanqiong He & Zhilin Yang, 2022. "How Human–Chatbot Interaction Impairs Charitable Giving: The Role of Moral Judgment," Journal of Business Ethics, Springer, vol. 178(3), pages 849-865, July.
    12. Yael Shani-Feinstein & Ellie J Kyung & Jacob Goldenberg, 2022. "Moving, Fast or Slow: How Perceived Speed Influences Mental Representation and Decision Making [Seeing the Big Picture: The Effect of Height on the Level of Construal]," Journal of Consumer Research, Journal of Consumer Research Inc., vol. 49(3), pages 520-542.
    13. repec:oup:jconrs:v:47:y:2021:i:5:p:787-806. is not listed on IDEAS
    14. Kull, Alexander J. & Romero, Marisabel & Monahan, Lisa, 2021. "How may I help you? Driving brand engagement through the warmth of an initial chatbot message," Journal of Business Research, Elsevier, vol. 135(C), pages 840-850.
    15. DaHee Han & Adam Duhachek & Nidhi Agrawal, 2016. "Coping and Construal Level Matching Drives Health Message Effectiveness viaResponse Efficacy or Self-Efficacy Enhancement," Journal of Consumer Research, Journal of Consumer Research Inc., vol. 43(3), pages 429-447.
    16. Seo Young Kim & Bernd H. Schmitt & Nadia M. Thalmann, 2019. "Eliza in the uncanny valley: anthropomorphizing consumer robots increases their perceived warmth but decreases liking," Marketing Letters, Springer, vol. 30(1), pages 1-12, March.
    17. Pantano, Eleonora & Pizzi, Gabriele, 2020. "Forecasting artificial intelligence on online customer assistance: Evidence from chatbot patents analysis," Journal of Retailing and Consumer Services, Elsevier, vol. 55(C).
    18. Smriti Kumar & Elizabeth G. Miller & Martin Mende & Maura L. Scott, 2022. "Language matters: humanizing service robots through the use of language during the COVID-19 pandemic," Marketing Letters, Springer, vol. 33(4), pages 607-623, December.
    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. 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. Zhang, Yaqiong & Wang, Shifu, 2023. "The influence of anthropomorphic appearance of artificial intelligence products on consumer behavior and brand evaluation under different product types," Journal of Retailing and Consumer Services, Elsevier, vol. 74(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.
    4. Zhu, Yimin & Zhang, Jiemin & Wu, Jifei & Liu, Yingyue, 2022. "AI is better when I'm sure: The influence of certainty of needs on consumers' acceptance of AI chatbots," Journal of Business Research, Elsevier, vol. 150(C), pages 642-652.
    5. Li, Meichan & Wang, Rui, 2023. "Chatbots in e-commerce: The effect of chatbot language style on customers’ continuance usage intention and attitude toward brand," Journal of Retailing and Consumer Services, Elsevier, vol. 71(C).
    6. Tao Zhang & Chao Feng & Hui Chen & Junjie Xian, 2022. "Calming the customers by AI: Investigating the role of chatbot acting-cute strategies in soothing negative customer emotions," Electronic Markets, Springer;IIM University of St. Gallen, vol. 32(4), pages 2277-2292, December.
    7. Justina Sidlauskiene & Yannick Joye & Vilte Auruskeviciene, 2023. "AI-based chatbots in conversational commerce and their effects on product and price perceptions," Electronic Markets, Springer;IIM University of St. Gallen, vol. 33(1), pages 1-21, December.
    8. Peng, Leiqing & Luo, Mengting & Guo, Yulang, 2023. "Deposit AI as the “invisible hand†to make the resale easier: A moderated mediation model," Journal of Retailing and Consumer Services, Elsevier, vol. 75(C).
    9. 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.
    10. Pelau Corina & Barbul Maria & Bojescu Irina, 2022. "A conceptual comparative approach on personal AI assistants and external service robots," Proceedings of the International Conference on Business Excellence, Sciendo, vol. 16(1), pages 1466-1474, August.
    11. Zogaj, Adnan & Mähner, Philipp M. & Yang, Linyu & Tscheulin, Dieter K., 2023. "It’s a Match! The effects of chatbot anthropomorphization and chatbot gender on consumer behavior," Journal of Business Research, Elsevier, vol. 155(PA).
    12. Song, Mengmeng & Xing, Xinyu & Duan, Yucong & Cohen, Jason & Mou, Jian, 2022. "Will artificial intelligence replace human customer service? The impact of communication quality and privacy risks on adoption intention," Journal of Retailing and Consumer Services, Elsevier, vol. 66(C).
    13. Liu, Xing (Stella) & Wan, Lisa C. & Yi, Xiao (Shannon), 2022. "Humanoid versus non-humanoid robots: How mortality salience shapes preference for robot services under the COVID-19 pandemic?," Annals of Tourism Research, Elsevier, vol. 94(C).
    14. Xuequn Wang & Xiaolin Lin & Bin Shao, 2023. "Artificial intelligence changes the way we work: A close look at innovating with chatbots," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 74(3), pages 339-353, March.
    15. Chunlin Yuan & Shuman Wang & Yue Liu, 2023. "AI service impacts on brand image and customer equity: empirical evidence from China," Journal of Brand Management, Palgrave Macmillan, vol. 30(1), pages 61-76, January.
    16. Lee, Kuo-Wei & Li, Chia-Ying, 2023. "It is not merely a chat: Transforming chatbot affordances into dual identification and loyalty," Journal of Retailing and Consumer Services, Elsevier, vol. 74(C).
    17. Yuan, Chunlin & Zhang, Chenlei & Wang, Shuman, 2022. "Social anxiety as a moderator in consumer willingness to accept AI assistants based on utilitarian and hedonic values," Journal of Retailing and Consumer Services, Elsevier, vol. 65(C).
    18. 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.
    19. Rahman, Muhammad Sabbir & Bag, Surajit & Hossain, Md Afnan & Abdel Fattah, Fadi Abdel Muniem & Gani, Mohammad Osman & Rana, Nripendra P., 2023. "The new wave of AI-powered luxury brands online shopping experience: The role of digital multisensory cues and customers’ engagement," Journal of Retailing and Consumer Services, Elsevier, vol. 72(C).
    20. Zhao, Jingyou & Hu, Enhua & Han, Mingyan & Jiang, Keshen & Shan, Hongmei, 2023. "That honey, my arsenic: The influence of advanced technologies on service employees’ organizational deviance," Journal of Retailing and Consumer Services, Elsevier, vol. 75(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:pal:palcom:v:11:y:2024:i:1:d:10.1057_s41599-024-02600-w. 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: https://www.nature.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.