IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v14y2022i4p2156-d748970.html
   My bibliography  Save this article

Applying Affordance Factor Analysis for Smart Home Speakers in Different Age Groups: A Case Study Approach

Author

Listed:
  • Chih-Fu Wu

    (Department of Industrial Design, Tatung University, Taipei City 104, Taiwan)

  • Ying-Kit Wong

    (Graduate Institute of Design Science, Tatung University, Taipei City 104, Taiwan)

  • Hsiu-Hui Hsu

    (Department of Applied Cosmetology, Lee-Ming Institute of Technology, New Taipei City 243, Taiwan)

  • Cheng-Yu Huang

    (Department of Industrial Design, Tatung University, Taipei City 104, Taiwan)

Abstract

Many people use smart speakers at home nowadays for various reasons, such as playing music, checking news and weather, setting timers/alarms, etc. However, before smart speakers were created and available on the market, people used to have home audio systems for similar applications. Nonetheless, the control systems of smart speakers have many different appearances. Affordance is the information given by an object, which is determined by its appearance and supplies clues about its appropriate operation. Therefore, smart speakers should have affordances. Since smart speakers are the main device in the sustainable lifestyle of human beings in smart homes, this study analyzed the affordances of its appearance affect people and the result is essential to the sustainability of smart home. The present study presents a review of the smart speakers in Taiwan, focusing on the four main affordances (physical, cognitive, sensory, functional) and three different age groups (60 participants) based on four appearance categories of smart speaker control, namely, mechanical button control, no-button–no-touch control, touchscreen control, and touch sensor control. By examining the comparison of three age groups, 18–24, 25–49 and 50+, the results of one-way ANOVA showed that the smart speakers with touchscreen control and touch sensor control had a significant difference ( p < 0.01) in four main affordances among these three age groups. The smart speakers with mechanical button control and no-button–no-touch control had no significant difference ( p > 0.01) in four main affordances among these three age groups. In conclusion, age-range and cultural group affect the affordance of smart home speakers.

Suggested Citation

  • Chih-Fu Wu & Ying-Kit Wong & Hsiu-Hui Hsu & Cheng-Yu Huang, 2022. "Applying Affordance Factor Analysis for Smart Home Speakers in Different Age Groups: A Case Study Approach," Sustainability, MDPI, vol. 14(4), pages 1-22, February.
    • Handle: RePEc:gam:jsusta:v:14:y:2022:i:4:p:2156-:d:748970
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/14/4/2156/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2071-1050/14/4/2156/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Younjoo Cho & Anseop Choi, 2020. "Application of Affordance Factors for User-Centered Smart Homes: A Case Study Approach," Sustainability, MDPI, vol. 12(7), pages 1-23, April.
    2. Hasan, Rajibul & Shams, Riad & Rahman, Mizan, 2021. "Consumer trust and perceived risk for voice-controlled artificial intelligence: The case of Siri," Journal of Business Research, Elsevier, vol. 131(C), pages 591-597.
    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. 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.
    2. 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).
    3. Sohn, Stefanie, 2024. "Consumer perceived risk of using autonomous retail technology," Journal of Business Research, Elsevier, vol. 171(C).
    4. 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).
    5. Simarpreet Kaur & Sangeeta Arora, 2023. "Understanding customers’ usage behavior towards online banking services: an integrated risk–benefit framework," Journal of Financial Services Marketing, Palgrave Macmillan, vol. 28(1), pages 74-98, March.
    6. Chaturvedi, Rijul & Verma, Sanjeev & Das, Ronnie & Dwivedi, Yogesh K., 2023. "Social companionship with artificial intelligence: Recent trends and future avenues," Technological Forecasting and Social Change, Elsevier, vol. 193(C).
    7. 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.
    8. Rohit, Kumar & Shankar, Amit & Katiyar, Gagan & Mehrotra, Ankit & Alzeiby, Ebtesam Abdullah, 2024. "Consumer engagement in chatbots and voicebots. A multiple-experiment approach in online retailing context," Journal of Retailing and Consumer Services, Elsevier, vol. 78(C).
    9. Maroufkhani, Parisa & Asadi, Shahla & Ghobakhloo, Morteza & Jannesari, Milad T. & Ismail, Wan Khairuzaman Wan, 2022. "How do interactive voice assistants build brands' loyalty?," Technological Forecasting and Social Change, Elsevier, vol. 183(C).
    10. Eun Ji Lee & Sung Jun Park, 2020. "A Framework of Smart-Home Service for Elderly’s Biophilic Experience," Sustainability, MDPI, vol. 12(20), pages 1-26, October.
    11. Rongbin Yang & Santoso Wibowo, 2022. "User trust in artificial intelligence: A comprehensive conceptual framework," Electronic Markets, Springer;IIM University of St. Gallen, vol. 32(4), pages 2053-2077, December.
    12. Jan, Ihsan Ullah & Ji, Seonggoo & Kim, Changju, 2023. "What (de) motivates customers to use AI-powered conversational agents for shopping? The extended behavioral reasoning perspective," Journal of Retailing and Consumer Services, Elsevier, vol. 75(C).
    13. Guo, Wenshan & Luo, Qiangqiang, 2023. "Investigating the impact of intelligent personal assistants on the purchase intentions of Generation Z consumers: The moderating role of brand credibility," Journal of Retailing and Consumer Services, Elsevier, vol. 73(C).
    14. Alzaidi, Maram Saeed & Agag, Gomaa, 2022. "The role of trust and privacy concerns in using social media for e-retail services: The moderating role of COVID-19," Journal of Retailing and Consumer Services, Elsevier, vol. 68(C).
    15. Maria Vernuccio & Michela Patrizi & Maja Šerić & Alberto Pastore, 2023. "The perceptual antecedents of brand anthropomorphism in the name-brand voice assistant context," Journal of Brand Management, Palgrave Macmillan, vol. 30(4), pages 302-317, July.
    16. Haque, AKM Bahalul & Islam, A.K.M. Najmul & Mikalef, Patrick, 2023. "Explainable Artificial Intelligence (XAI) from a user perspective: A synthesis of prior literature and problematizing avenues for future research," Technological Forecasting and Social Change, Elsevier, vol. 186(PA).
    17. Pei Li & Chunmao Wu & Charles Spence, 2023. "Comparing the influence of visual information and the perceived intelligence of voice assistants when shopping for sustainable clothing online," Palgrave Communications, Palgrave Macmillan, vol. 10(1), pages 1-12, December.
    18. Binbin Ni & Fuzhong Wu & Qing Huang, 2023. "When Artificial Intelligence Voices Human Concerns: The Paradoxical Effects of AI Voice on Climate Risk Perception and Pro-Environmental Behavioral Intention," IJERPH, MDPI, vol. 20(4), pages 1-20, February.
    19. Chong Li & Yingqi Li, 2023. "Factors Influencing Public Risk Perception of Emerging Technologies: A Meta-Analysis," Sustainability, MDPI, vol. 15(5), pages 1-37, February.
    20. Guerreiro, João & Loureiro, Sandra Maria Correia, 2023. "I am attracted to my Cool Smart Assistant! Analyzing Attachment-Aversion in AI-Human Relationships," Journal of Business Research, Elsevier, vol. 161(C).

    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:gam:jsusta:v:14:y:2022:i:4:p:2156-:d:748970. 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: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.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.