AI-driven personalization and consumer engagement : examining the roles of trust and privacy concerns through the stimulus-organism-response framework
Asmus, Ava (2026)
Pro gradu -tutkielma
2026
School of Business and Management, Kauppatieteet
Kaikki oikeudet pidätetään.
Julkaisun pysyvä osoite on
https://urn.fi/URN:NBN:fi-fe20260729113019
https://urn.fi/URN:NBN:fi-fe20260729113019
Tiivistelmä
This study aims to further understand the relationships between AI-driven personalization, consumer trust, privacy concerns, and consumer engagement. With the use of the Stimulus-Organism-Response (S-O-R) framework as the theoretical backing for the examining of these roles in the digital marketing context, here, AI-driven personalization is the stimulus, trust and privacy concerns are organismic responses, and consumer engagement is the behavioral response. Four hypotheses were developed using previous literature to test these relationships of the effects of perceived personalization on trust and privacy concerns, and the effects of trust and privacy concerns on consumer engagement.
A quantitative research method was used and an online survey was created using the 5-point Likert scale with questions relating to each of the 4 constructs of the framework. This had 80 respondents from the data collected and was then analyzed with the following statistical methods: descriptive statistics, correlation analysis, reliability testing, and regression analysis.
The results showed that perceived AI-driven personalization has a significant positive effect on consumer trust. However, the other hypotheses were not significant; trust did not significantly influence consumer engagement, perceived personalization did not significantly influence privacy concerns, and privacy concerns did not significantly affect engagement. Even though responses had high levels of privacy concerns, it did not reduce the level of reported engagement.
This study contributes to literature both on AI personalization and consumer behavior through the scope of the study being in Finland and looking at the integrated aspects of trust and privacy concerns in these relationships through the S-O-R framework. This, overall, shows the importance of relevant personalization that still values transparency practices in digital marketing spaces.
A quantitative research method was used and an online survey was created using the 5-point Likert scale with questions relating to each of the 4 constructs of the framework. This had 80 respondents from the data collected and was then analyzed with the following statistical methods: descriptive statistics, correlation analysis, reliability testing, and regression analysis.
The results showed that perceived AI-driven personalization has a significant positive effect on consumer trust. However, the other hypotheses were not significant; trust did not significantly influence consumer engagement, perceived personalization did not significantly influence privacy concerns, and privacy concerns did not significantly affect engagement. Even though responses had high levels of privacy concerns, it did not reduce the level of reported engagement.
This study contributes to literature both on AI personalization and consumer behavior through the scope of the study being in Finland and looking at the integrated aspects of trust and privacy concerns in these relationships through the S-O-R framework. This, overall, shows the importance of relevant personalization that still values transparency practices in digital marketing spaces.