et al., 2025), and the opacity of algorithms in AI systems generates asymmetric information that systematically disadvantages consumers (Zheng et al., 2025). This project, which seeks to contribute to theory on technology-mediated consumer vulnerability (Basu et al., 2023; Laamanen et al., 2025; Leandro & Botelho, 2025), algorithmic opacity in AI systems (Zheng et al., 2025), digital agency frameworks (Stewart et al., 2024), and justice perspectives on transparency and control (Waseem et al., 2024), investigates how technology dependence affects consumer vulnerability in digital marketing ecosystems, with a particular focus on how consumers navigate privacy vulnerability in personalised advertising ecosystems. The doctoral researcher will employ a mixed-method design, which will combine qualitative and quantitative methods.

Supervisors

Dr Benjamin Afreh
Dr. Babatunde Musiliu Abina

et al., 2025), and the opacity of algorithms in AI systems generates asymmetric information that systematically disadvantages consumers (Zheng et al., 2025). This project, which seeks to contribute to theory on technology-mediated consumer vulnerability (Basu et al., 2023; Laamanen et al., 2025; Leandro & Botelho, 2025), algorithmic opacity in AI systems (Zheng et al., 2025), digital agency frameworks (Stewart et al., 2024), and justice perspectives on transparency and control (Waseem et al., 2024), investigates how technology dependence affects consumer vulnerability in digital marketing ecosystems, with a particular focus on how consumers navigate privacy vulnerability in personalised advertising ecosystems. The doctoral researcher will employ a mixed-method design, which will combine qualitative and quantitative methods.

Supervisors

Dr Benjamin Afreh
Dr. Babatunde Musiliu Abina