Societal and Ethical Impacts of Internet of Things: A Cluster Analysis and Statistical Analysis Approach

Abstract

The Internet of Things (IoT) is a rapidly expanding technology that has enhanced automation, connectivity, and decision making in the home, healthcare, industry, financial services, and smart city sectors. But on-going data gathering and algorithmic surveillance have sparked privacy concerns, ethical responsibility issues, digital stress, and public impact issues. This study explores the relationship between privacy concern, ethical risk, digital stress, and societal impact with users' intention to use IoT technologies. The two-stage research approach was used. A systematic literature review followed by keyword co-occurrence analysis was carried out to identify key themes of research using VOS viewer. Second, the data gathered from 120 respondents were statistically analysed by descriptive data analysis, multiple regression and analysis of variance by IBM SPSS. The bibliometric analysis resulted in the identification of four thematic clusters: AI for IoT intelligence, ethical/privacy issues, human-centric IoT applications, and smart digital infrastructure. The regression model was statistically significant with an R-square value of around 38.1% for the intention to adopt the IoT. In addition to privacy and societal factors, these were important factors for predicting IoT acceptance, while digital stress appeared to have less predictive power. The study combines the thematic mapping approach with empirical validation and underscores the need for privacy protection, ethical-by-design development, transparent governance, and socially responsible deployment of the IoT.