Olumekor Michael, Polbitsyn Sergey N, Khan Mohammad Saud, Singh Harman Preet, Alhamad Ibrahim A
Graduate School of Economics and Management, Ural Federal University, Yekaterinburg, Russia.
School of Management, Wellington School of Business and Government, Victoria University of Wellington, Wellington, New Zealand.
PLoS One. 2025 Mar 19;20(3):e0315125. doi: 10.1371/journal.pone.0315125. eCollection 2025.
Senior citizens are the fastest growing demographic in the world. Amid an intensification of digitalisation across every sector, evidence suggests older people are slow to adopt and use many online tools and services. Moreover, despite studies showing differences in the online behaviour of older people compared to the rest of the population, established models specifically dedicated to explaining their behaviour have remained limited. Therefore, based on components of UTAUT, we propose a new conceptual model that specifically focuses on senior citizens. We introduce four new constructs: health needs, place of settlement (rural/urban), perceived trust, and perceived risk. Data were collected from 320 seniors in Russia and a structural equation modelling was used for data analysis. With a cumulative variance of 86%, the test and validation results demonstrate that our proposed model provides a better explanation of older people's online shopping behaviour than the original UTAUT model. This model provides an important framework for future studies on the digital shopping behaviours of seniors.
老年人是世界上增长最快的人口群体。在各个领域数字化不断强化的背景下，有证据表明老年人采用和使用许多在线工具及服务的速度较慢。此外，尽管研究显示老年人与其他人群在网络行为上存在差异，但专门用于解释他们行为的既定模型仍然有限。因此，基于技术接受与使用整合理论（UTAUT）的组成部分，我们提出了一个专门针对老年人的新的概念模型。我们引入了四个新的构念：健康需求、居住地点（农村/城市）、感知信任和感知风险。数据收集自俄罗斯的320名老年人，并使用结构方程模型进行数据分析。测试和验证结果表明，我们提出的模型对老年人在线购物行为的解释比原始的UTAUT模型更好，累积方差为86%。该模型为未来关于老年人数字购物行为的研究提供了一个重要框架。
