Open Access
Issue
BIO Web Conf.
Volume 86, 2024
International Conference on Recent Trends in Biomedical Sciences (RTBS-2023)
Article Number 01087
Number of page(s) 9
DOI https://doi.org/10.1051/bioconf/20248601087
Published online 12 January 2024
  • D. Nan, E. Shin, G. A. Barnett, S. Cheah, and J. H. Kim, “Will coolness factors predict user satisfaction and loyalty? Evidence from an artificial neural network–structural equation model approach,” Inf Process Manag, vol. 59, no. 6, Nov. 2022, doi: 10.1016/j.ipm.2022.103108. [Google Scholar]
  • A. N. Tak, B. Becerik-Gerber, L. Soibelman, and G. Lucas, “A framework for investigating the acceptance of smart home technologies: Findings for residential smart HVAC systems,” Build Environ, vol. 245, Nov. 2023, doi: 10.1016/j.buildenv.2023.110935. [Google Scholar]
  • L. Ferreira, T. Oliveira, and C. Neves, “Consumer’s intention to use and recommend smart home technologies: The role of environmental awareness,” Energy, vol. 263, Jan. 2023, doi: 10.1016/j.energy.2022.125814. [CrossRef] [Google Scholar]
  • P. Pfeifer, T. Hilken, J. Heller, S. Alimamy, and R. Di Palma, “More than meets the eye: In-store retail experiences with augmented reality smart glasses,” Comput Human Behav, vol. 146, Sep. 2023, doi: 10.1016/j.chb.2023.107816. [CrossRef] [Google Scholar]
  • J. A. Gordon, N. Balta-Ozkan, and S. A. Nabavi, “Divergent consumer preferences and visions for cooking and heating technologies in the United Kingdom: Make our homes clean, safe, warm and smart!,” Energy Res Soc Sci, vol. 104, Oct. 2023, doi: 10.1016/j.erss.2023.103204. [CrossRef] [Google Scholar]
  • F. A. Ghansah, J. Chen, and W. Lu, “Developing a user perception model for smart living: A partial least squares structural equation modelling approach,” Build Environ, vol. 222, Aug. 2022, doi: 10.1016/j.buildenv.2022.109399. [CrossRef] [Google Scholar]
  • Y. Xie, K. Zhu, P. Zhou, and C. Liang, “How does anthropomorphism improve human-AI interaction satisfaction: a dual-path model,” Comput Human Behav, vol. 148, Nov. 2023, doi: 10.1016/j.chb.2023.107878. [PubMed] [Google Scholar]
  • E. Attié and L. Meyer-Waarden, “The acceptance and usage of smart connected objects according to adoption stages: an enhanced technology acceptance model integrating the diffusion of innovation, uses and gratification and privacy calculus theories,” Technol Forecast Soc Change, vol. 176, Mar. 2022, doi: 10.1016/j.techfore.2022.121485. [Google Scholar]
  • D. Wu, W. Feng, T. Li, and Z. Yang, “Evaluating the intelligence capability of smart homes: A conceptual modeling approach,” Data Knowl Eng, vol. 148, Nov. 2023, doi: 10.1016/j.datak.2023.102218. [Google Scholar]
  • I. Chouk and Z. Mani, “Does the learning ability of smart products lead to user resistance?,” Journal of Engineering and Technology Management - JET-M, vol. 66, Oct. 2022, doi: 10.1016/j.jengtecman.2022.101706. [Google Scholar]
  • J. Choi, “Enablers and inhibitors of smart city service adoption: A dual-factor approach based on the technology acceptance model,” Telematics and Informatics, vol. 75, Dec. 2022, doi: 10.1016/j.tele.2022.101911. [CrossRef] [Google Scholar]
  • Y. Zhao, S.-G. Sazlina, F. Z. Rokhani, J. Su, and B.-H. Chew, “The Expectations and Acceptability of a Smart Nursing Home Model Among Chinese Older Adults and Family Members: A Qualitative Study,” Asian Nurs Res (Korean Soc Nurs Sci), Sep. 2023, doi: 10.1016/j.anr.2023.08.002. [Google Scholar]
  • E. Park, “User acceptance of smart wearable devices: An expectation-confirmation model approach,” Telematics and Informatics, vol. 47, Apr. 2020, doi: 10.1016/j.tele.2019.101318. [CrossRef] [Google Scholar]
  • “User Satisfaction and Technology Adoption in Smart Homes: A User Experience Test - Search | ScienceDirect.com.” Accessed: Oct. 28, 2023. [Online]. Available: https://www.sciencedirect.com/search?qs=User%20Satisfaction%20and%20Technology%20Adoption%20in%20Smart%20Homes%3A%20A%20User%20Experience%20Test [Google Scholar]
  • S. J. Philip, T. (Jack) Luu, and T. Carte, “There’s No place like home: Understanding users’ intentions toward securing internet-of-things (IoT) smart home networks,” Comput Human Behav, vol. 139, Feb. 2023, doi: 10.1016/j.chb.2022.107551. [CrossRef] [Google Scholar]
  • N. Baumgartner, K. Weyer, L. Eckmann, and W. Fichtner, “How to integrate users into smart charging – A critical and systematic review,” Energy Res Soc Sci, vol. 100, Jun. 2023, doi: 10.1016/j.erss.2023.103113. [CrossRef] [Google Scholar]
  • M. El Barachi, T. A. Salim, M. W. Nyadzayo, S. Mathew, A. Badewi, and J. Amankwah-Amoah, “The relationship between citizen readiness and the intention to continuously use smart city services: Mediating effects of satisfaction and discomfort,” Technol Soc, vol. 71, Nov. 2022, doi: 10.1016/j.techsoc.2022.102115. [CrossRef] [Google Scholar]
  • A. Kumar, P. K. Bala, S. Chakraborty, and R. K. Behera, “Exploring antecedents impacting user satisfaction with voice assistant app: A text mining-based analysis on Alexa services,” Journal of Retailing and Consumer Services, vol. 76, p. 103586, Jan. 2024, doi: 10.1016/J.JRETCONSER.2023.103586. [CrossRef] [Google Scholar]
  • S. Gøthesen, M. Haddara, and K. N. Kumar, “Empowering homes with intelligence: An investigation of smart home technology adoption and usage,” Internet of Things (Netherlands), vol. 24, Dec. 2023, doi: 10.1016/j.iot.2023.100944. [Google Scholar]
  • C. Mao and D. Chang, “Review of cross-device interaction for facilitating digital transformation in smart home context: A user-centric perspective,” Advanced Engineering Informatics, vol. 57, Aug. 2023, doi: 10.1016/j.aei.2023.102087. [Google Scholar]
  • D. Cao, Y. Sun, E. Goh, R. Wang, and K. Kuiavska, “Adoption of smart voice assistants technology among Airbnb guests: A revised self-efficacy-based value adoption model (SVAM),” Int J Hosp Manag, vol. 101, Feb. 2022, doi: 10.1016/j.ijhm.2021.103124. [PubMed] [Google Scholar]
  • A. Mishra, A. Shukla, and S. K. Sharma, “Psychological determinants of users’ adoption and word-of-mouth recommendations of smart voice assistants,” Int J Inf Manage, 2021, doi: 10.1016/j.ijinfomgt.2021.102413. [Google Scholar]
  • B. Priya and V. Sharma, “Exploring users’ adoption intentions of intelligent virtual assistants in financial services: An anthropomorphic perspectives and socio-psychological perspectives,” Comput Human Behav, vol. 148, Nov. 2023, doi: 10.1016/j.chb.2023.107912. [CrossRef] [Google Scholar]
  • S. H. Yoon, G. Y. Park, and H. W. Kim, “Unraveling the relationship between the dimensions of user experience and user satisfaction: A smart speaker case,” Technol Soc, vol. 71, Nov. 2022, doi: 10.1016/j.techsoc.2022.102067. [Google Scholar]
  • B. Dhiman, D. Zindani, D. Chakrabarti, and G. Singh, “A user-centric assessment of solar-photovoltaic-home- lighting systems in rural parts of Assam, India,” Energy for Sustainable Development, vol. 76, p. 101290, Oct. 2023, doi: 10.1016/j.esd.2023.101290. [CrossRef] [Google Scholar]
  • A. A. Soren and S. Chakraborty, “Adoption, satisfaction, trust, and commitment of over-the-top platforms: An integrated approach,” Journal of Retailing and Consumer Services, vol. 76, Jan. 2024, doi: 10.1016/j.jretconser.2023.103574. [CrossRef] [Google Scholar]
  • V. S. Rana et al., “Correction: Assortment of latent heat storage materials using multi criterion decision making techniques in Scheffler solar reflector,” International Journal on Interactive Design and Manufacturing (IJIDeM), p. 1, 2023. [Google Scholar]
  • K. Kumar et al., “From Homogeneity to Heterogeneity: Designing Functionally Graded Materials for Advanced Engineering Applications,” in E3S Web of Conferences, EDP Sciences, 2023, p. 01198. [Google Scholar]
  • M. Z. ul Haq et al., “Waste Upcycling in Construction: Geopolymer Bricks at the Vanguard of Polymer Waste Renaissance,” in E3S Web of Conferences, EDP Sciences, 2023, p. 01205. [Google Scholar]
  • M. Z. ul Haq et al., “Eco-Friendly Building Material Innovation: Geopolymer Bricks from Repurposed Plastic Waste,” in E3S Web of Conferences, EDP Sciences, 2023, p. 01201. [Google Scholar]
  • M. Z. ul Haq et al., “Geopolymerization of Plastic Waste for Sustainable Construction: Unveiling Novel Opportunities in Building Materials,” in E3S Web of Conferences, EDP Sciences, 2023, p. 01204. [Google Scholar]
  • G. Upadhyay et al., “Development of Carbon Nanotube (CNT)-Reinforced Mg Alloys: Fabrication Routes and Mechanical Properties,” Metals (Basel), vol. 12, no. 8, Aug. 2022, doi: 10.3390/MET12081392. [CrossRef] [Google Scholar]
  • S. Bali et al., “A framework to assess the smartphone buying behaviour using DEMATEL method in the Indian context,” Ain Shams Engineering Journal, 2023, doi: 10.1016/J.ASEJ.2023.102129. [Google Scholar]
  • Y. Kaushik, V. Verma, K. K. Saxena, C. Prakash, L. R. Gupta, and S. Dixit, “Effect of Al2O3 Nanoparticles on Performance and Emission Characteristics of Diesel Engine Fuelled with Diesel–Neem Biodiesel Blends,” Sustainability (Switzerland), vol. 14, no. 13, Jul. 2022, doi: 10.3390/SU14137913. [Google Scholar]
  • J. Singh, P. Bhardwaj, R. Kumar, S. Dixit, K. Kumar, and V. Verma, “Phase Transformation Analysis of Fe- Substituted Cr2O3 Nanoparticles Using Rietveld Refinement,” Lecture Notes in Mechanical Engineering, pp. 311–322, 2023, doi: 10.1007/978-981-19-4147-4_33. [Google Scholar]
  • K. Zheng Yang et al., “Application of coolants during tool-based machining – A review,” Ain Shams Engineering Journal, 2022, doi: 10.1016/J.ASEJ.2022.101830. [Google Scholar]
  • H. D. Nguyen et al., “A critical review on additive manufacturing of Ti-6Al-4V alloy: Microstructure and mechanical properties,” Journal of Materials Research and Technology, vol. 18, pp. 4641–4661, May 2022, doi: 10.1016/J.JMRT.2022.04.055. [CrossRef] [Google Scholar]
  • Siddique, A., Kandpal, G. and Kumar, P., 2018. Proline accumulation and its defensive role under diverse stress condition in plants: An overview. Journal of Pure and Applied Microbiology, 12(3), pp.1655-1659. [CrossRef] [Google Scholar]
  • Singh, H., Singh, J.I.P., Singh, S., Dhawan, V. and Tiwari, S.K., 2018. A brief review of jute fibre and its composites. Materials Today: Proceedings, 5(14), pp.28427-28437. [CrossRef] [Google Scholar]
  • Akhtar, N. and Bansal, J.G., 2017. Risk factors of Lung Cancer in nonsmoker. Current problems in cancer, 41(5), pp.328-339. [CrossRef] [PubMed] [Google Scholar]
  • Mahajan, N., Rawal, S., Verma, M., Poddar, M. and Alok, S., 2013. A phytopharmacological overview on Ocimum species with special emphasis on Ocimum sanctum. Biomedicine & Preventive Nutrition, 3(2), pp.185-192. [CrossRef] [Google Scholar]
  • Vinnik, D.A., Zhivulin, V.E., Sherstyuk, D.P., Starikov, A.Y., Zezyulina, P.A., Gudkova, S.A., Zherebtsov, D.A., Rozanov, K.N., Trukhanov, S.V., Astapovich, K.A. and Turchenko, V.A., 2021. Electromagnetic properties of zinc–nickel ferrites in the frequency range of 0.05–10 GHz. Materials Today Chemistry, 20, p.100460. [CrossRef] [Google Scholar]

Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.

Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.

Initial download of the metrics may take a while.