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Older Adult Segmentation According to Residentially-Based Lifestyles and Analysis of Their Needs for Smart Home Functions

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  • Jiyeon Yu

    (Madrid HCI Lab, Research Group on Human-Computer Interaction and Advanced Interactive Systems, Universidad Politécnica de Madrid (UPM), Boadilla del Monte, 28660 Madrid, Spain)

  • Angelica de Antonio

    (Madrid HCI Lab, Research Group on Human-Computer Interaction and Advanced Interactive Systems, Universidad Politécnica de Madrid (UPM), Boadilla del Monte, 28660 Madrid, Spain)

  • Elena Villalba-Mora

    (Centre for Biomedical Technology (CTB), Universidad Politécnica de Madrid (UPM), Pozuelo de Alarcón, 28223 Madrid, Spain
    Centro de Investigación Biomédica en Red en Bioingeniería, Biomateriales y Nanomedicina (CIBER-BBN), 28029 Madrid, Spain)

Abstract

Globally, the percentage of older people in the general population is growing. Smart homes have the potential to help older adults to live independently and healthy, improving their quality of life, and relieving the pressure on the healthcare and social care systems. For that, we need to understand how older adults live and their needs. Thus, this study aims to analyze the residentially-based lifestyles (RBL) of older adults and segment them to compare and analyze the real needs of smart home functions for each group. To identify a person’s RBL, a questionnaire was designed to include questions about activities at home, social events, quality of life, etc. This study surveyed 271 older Koreans. As a result of the survey on RBL, five groups with different characteristics were clustered. Finally, each groups’ features and the differences in their needs for smart home functions were compared and analyzed. The priority of needed functions for each group was found to be significantly different. In a total of 26 smart home functions, there were meaningful differences in the needs for 16 functions among the groups. This study presents the results in South Korea, according to older adults’ RBL and their smart home needs.

Suggested Citation

  • Jiyeon Yu & Angelica de Antonio & Elena Villalba-Mora, 2020. "Older Adult Segmentation According to Residentially-Based Lifestyles and Analysis of Their Needs for Smart Home Functions," IJERPH, MDPI, vol. 17(22), pages 1-21, November.
    • Handle: RePEc:gam:jijerp:v:17:y:2020:i:22:p:8492-:d:445950
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    References listed on IDEAS

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    1. Marikyan, Davit & Papagiannidis, Savvas & Alamanos, Eleftherios, 2019. "A systematic review of the smart home literature: A user perspective," Technological Forecasting and Social Change, Elsevier, vol. 138(C), pages 139-154.
    2. Xiaona Zhang & Ruyi Xia & Shu Wang & Wei Xue & Jian Yang & Shuliu Sun & Guihua Zhuang, 2018. "Relative Contributions of Different Lifestyle Factors to Health-Related Quality of Life in the Elderly," IJERPH, MDPI, vol. 15(2), pages 1-13, February.
    3. Changliang Du, 2019. "Study on Lifestyle Evaluation Systems for the Health of Chinese Elderly," IJERPH, MDPI, vol. 16(2), pages 1-9, January.
    4. Eissens van der Laan, M.R. & van Offenbeek, M.A.G. & Broekhuis, H. & Slaets, J.P.J., 2014. "A person-centred segmentation study in elderly care: Towards efficient demand-driven care," Social Science & Medicine, Elsevier, vol. 113(C), pages 68-76.
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    1. Wenwei Huang & Yinghan Lin & Hongyang Li, 2024. "Research on Aging-adaptive Auxiliary Construction of Smart Communities," SAGE Open, , vol. 14(2), pages 21582440241, May.
    2. Yi-Kyung Hong & Ze-Yu Wang & Ji Young Cho, 2022. "Global Research Trends on Smart Homes for Older Adults: Bibliometric and Scientometric Analyses," IJERPH, MDPI, vol. 19(22), pages 1-24, November.

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