IDEAS home Printed from https://ideas.repec.org/a/gam/jijerp/v19y2022i23p15727-d984664.html
   My bibliography  Save this article

Will Smart Improvements to Child Restraints Increase Their Popularity?

Author

Listed:
  • Li Jiang

    (CAS Key Laboratory of Mental Health, Institute of Psychology, Chinese Academy of Sciences, Beijing 100101, China
    Department of Psychology, University of Chinese Academy of Sciences, Beijing 100049, China)

  • Mei Zhao

    (CAS Key Laboratory of Mental Health, Institute of Psychology, Chinese Academy of Sciences, Beijing 100101, China
    Department of Psychology, University of Chinese Academy of Sciences, Beijing 100049, China)

  • Hao Lin

    (Shanghai Woyoo Electronic Technology Co., Ltd., Shanghai 201112, China)

  • Haiyuan Xu

    (Shanghai Woyoo Electronic Technology Co., Ltd., Shanghai 201112, China)

  • Xiaojiao Chen

    (CAS Key Laboratory of Mental Health, Institute of Psychology, Chinese Academy of Sciences, Beijing 100101, China
    Department of Psychology, University of Chinese Academy of Sciences, Beijing 100049, China)

  • Jing Xu

    (CAS Key Laboratory of Mental Health, Institute of Psychology, Chinese Academy of Sciences, Beijing 100101, China
    Department of Psychology, University of Chinese Academy of Sciences, Beijing 100049, China)

Abstract

In developing countries, child safety seat use remains low, which contributes to the consistently high rate of child injuries and deaths in traffic accidents. In order to protect the safety of child passengers, it is necessary to improve the public acceptance of child restraints. We improved the shortcomings of the traditional child restraints by adding some new features: 1, tightening Isofix automatically; 2, using temperature sensing, a high-temperature alarm, automatic ventilation, and cooling; 3, using pressure sensing, if the child is left alone it will set off the car alarm; 4, voice control to adjust the angle of the backrest; 5, the seat can be folded into the trunk. These functions make human-computer interaction more humane. The authors collected changes in parental acceptance of child restraints using the interview method and questionnaires. We found that acceptance increased significantly after making intelligent improvements to the child restraints. The authors used the Technology Acceptance Model to identify the key caveats influencing users’ use of intelligent child restraints. Performance expectations, effort expectations, social influence, convenience, and hedonic motivation positively and significantly impacted the willingness to use intelligent child restraints, so the authors suggest that these points should be emphasized when promoting the product. The current study findings have theoretical and practical implications for smart child restraint designers, manufacturers, sellers, and government agencies. To better understand and promote child restraint, researchers and marketers can analyze how people accept child restraint based on our research model.

Suggested Citation

  • Li Jiang & Mei Zhao & Hao Lin & Haiyuan Xu & Xiaojiao Chen & Jing Xu, 2022. "Will Smart Improvements to Child Restraints Increase Their Popularity?," IJERPH, MDPI, vol. 19(23), pages 1-21, November.
  • Handle: RePEc:gam:jijerp:v:19:y:2022:i:23:p:15727-:d:984664
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1660-4601/19/23/15727/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/1660-4601/19/23/15727/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Merhi, Mohamed & Hone, Kate & Tarhini, Ali, 2019. "A cross-cultural study of the intention to use mobile banking between Lebanese and British consumers: Extending UTAUT2 with security, privacy and trust," Technology in Society, Elsevier, vol. 59(C).
    2. Patricia Baudier & Chantal Ammi & Matthieu Deboeuf-Rouchon, 2020. "Smart home : highly-educated students' acceptance," Post-Print hal-02292941, HAL.
    3. Alalwan, Ali Abdallah, 2018. "Investigating the impact of social media advertising features on customer purchase intention," International Journal of Information Management, Elsevier, vol. 42(C), pages 65-77.
    4. Ledyard Tucker & Charles Lewis, 1973. "A reliability coefficient for maximum likelihood factor analysis," Psychometrika, Springer;The Psychometric Society, vol. 38(1), pages 1-10, March.
    5. Baudier, Patricia & Ammi, Chantal & Deboeuf-Rouchon, Matthieu, 2020. "Smart home: Highly-educated students' acceptance," Technological Forecasting and Social Change, Elsevier, vol. 153(C).
    6. Duarte, Paulo & Pinho, José Carlos, 2019. "A mixed methods UTAUT2-based approach to assess mobile health adoption," Journal of Business Research, Elsevier, vol. 102(C), pages 140-150.
    7. Ye Jin & Xiao Deng & Pengpeng Ye & Ji Peng & Juanjuan Peng & Lin Lei & Yan Yu & Leilei Duan, 2020. "The Awareness and Attitude of Parents towards the Legislation of Child Restraint in Two Cities of China," IJERPH, MDPI, vol. 17(7), pages 1-12, April.
    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. Tzu-Hsin Chu & Cheng-Min Chao & Hsieh-Hsi Liu & Der-Fa Chen, 2022. "Developing an Extended Theory of UTAUT 2 Model to Explore Factors Influencing Taiwanese Consumer Adoption of Intelligent Elevators," SAGE Open, , vol. 12(4), pages 21582440221, December.
    2. Wang, Guoqiang & Tan, Garry Wei-Han & Yuan, Yunpeng & Ooi, Keng-Boon & Dwivedi, Yogesh K., 2022. "Revisiting TAM2 in behavioral targeting advertising: A deep learning-based dual-stage SEM-ANN analysis," Technological Forecasting and Social Change, Elsevier, vol. 175(C).
    3. Tu, Gengyang & Faure, Corinne & Schleich, Joachim & Guetlein, Marie-Charlotte, 2021. "The heat is off! The role of technology attributes and individual attitudes in the diffusion of Smart thermostats – findings from a multi-country survey," Technological Forecasting and Social Change, Elsevier, vol. 163(C).
    4. Große-Kreul, Felix, 2022. "What will drive household adoption of smart energy? Insights from a consumer acceptance study in Germany," Utilities Policy, Elsevier, vol. 75(C).
    5. Pal, Debajyoti & Zhang, Xiangmin & Siyal, Saeed, 2021. "Prohibitive factors to the acceptance of Internet of Things (IoT) technology in society: A smart-home context using a resistive modelling approach," Technology in Society, Elsevier, vol. 66(C).
    6. Sahut, Jean Michel & Lissillour, Raphael, 2023. "The adoption of remote work platforms after the Covid-19 lockdown: New approach, new evidence," Journal of Business Research, Elsevier, vol. 154(C).
    7. Ávila-Robinson, Alfonso & Islam, Nazrul & Sengoku, Shintaro, 2022. "Exploring the knowledge base of innovation research: Towards an emerging innovation model," Technological Forecasting and Social Change, Elsevier, vol. 182(C).
    8. Kolny Beata, 2023. "Young Consumers Towards an Ecological Approach to Life in the Age of Smart Homes and Devices," Marketing of Scientific and Research Organizations, Sciendo, vol. 47(1), pages 105-126, March.
    9. Baudier, Patricia & Ammi, Chantal & Hikkerova, Lubica, 2022. "Impact of advertising on users’ perceptions regarding the Internet of things," Journal of Business Research, Elsevier, vol. 141(C), pages 355-366.
    10. Giovanni Baldi & Antonietta Megaro & Luca Carrubbo, 2022. "Small-Town Citizens’ Technology Acceptance of Smart and Sustainable City Development," Sustainability, MDPI, vol. 15(1), pages 1-18, December.
    11. Neves, C. & Oliveira, T. & Santini, F., 2022. "Sustainable technologies adoption research: A weight and meta-analysis," Renewable and Sustainable Energy Reviews, Elsevier, vol. 165(C).
    12. Chen-Wei Yu & Cheng-Min Chao & Che-Fu Chang & Rueg-Juen Chen & Po-Chung Chen & Yi-Xuan Liu, 2021. "Exploring Behavioral Intention to Use a Mobile Health Education Website: An Extension of the UTAUT 2 Model," SAGE Open, , vol. 11(4), pages 21582440211, October.
    13. Struckell, Elisabeth & Ojha, Divesh & Patel, Pankaj C. & Dhir, Amandeep, 2021. "Ecological determinants of smart home ecosystems: A coopetition framework," Technological Forecasting and Social Change, Elsevier, vol. 173(C).
    14. Culot, Giovanna & Orzes, Guido & Sartor, Marco & Nassimbeni, Guido, 2020. "The future of manufacturing: A Delphi-based scenario analysis on Industry 4.0," Technological Forecasting and Social Change, Elsevier, vol. 157(C).
    15. Kolny Beata, 2022. "Young Consumers Towards Smart Homes," Marketing of Scientific and Research Organizations, Sciendo, vol. 44(2), pages 105-125, June.
    16. Ferreira, Laura & Oliveira, Tiago & Neves, Catarina, 2023. "Consumer's intention to use and recommend smart home technologies: The role of environmental awareness," Energy, Elsevier, vol. 263(PC).
    17. Ponzoa, José M. & Gómez, Andrés & Villaverde, Silvia & Díaz, Vicente, 2021. "Technologically empowered? perception and acceptance of AR glasses and 3D printers in new generations of consumers," Technological Forecasting and Social Change, Elsevier, vol. 173(C).
    18. Mora, Luca & Gerli, Paolo & Ardito, Lorenzo & Messeni Petruzzelli, Antonio, 2023. "Smart city governance from an innovation management perspective: Theoretical framing, review of current practices, and future research agenda," Technovation, Elsevier, vol. 123(C).
    19. Radhwan Sneesl & Yusmadi Yah Jusoh & Marzanah A. Jabar & Salfarina Abdullah, 2022. "Revising Technology Adoption Factors for IoT-Based Smart Campuses: A Systematic Review," Sustainability, MDPI, vol. 14(8), pages 1-27, April.
    20. Ong, Ardvin Kester S. & Kurata, Yoshiki B. & Castro, Sophia Alessandra D.G. & De Leon, Jeanne Paulene B. & Dela Rosa, Hazel V. & Tomines, Alex Patricia J., 2022. "Factors influencing the acceptance of telemedicine in the Philippines," Technology in Society, Elsevier, vol. 70(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:jijerp:v:19:y:2022:i:23:p:15727-:d:984664. 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.