TY - JOUR
T1 - Engagement in proactive recommendations
T2 - The role of recommendation accuracy, information privacy concerns and personality traits
AU - Rook, Laurens
AU - Sabic, Adem
AU - Zanker, Markus
PY - 2020
Y1 - 2020
N2 - The present research explored to what extent user engagement in proactive recommendation scenarios is influenced by the accuracy of recommendations, concerns with information privacy, and trait personality. We hypothesized that people’s self-reported information privacy concerns would matter more when they received accurate (vs. inaccurate) proactive recommendations, because these pieces of advice would seem fair to them. We further hypothesized that this would particularly be the case for people high on the social personality trait Extraversion, who are by inclination prone to behaving in a more socially engaging manner. We put this to the test in a controlled experiment, in which users received manipulated proactive recommendations of high or low accuracy on their smartphone. Results indicated that information privacy concerns positively influenced a user’s engagement with proactive recommendations. Recommendation accuracy influenced user engagement in interaction with information privacy concerns and personality traits. Implications for the design of human-computer interaction for recommender systems are addressed.
AB - The present research explored to what extent user engagement in proactive recommendation scenarios is influenced by the accuracy of recommendations, concerns with information privacy, and trait personality. We hypothesized that people’s self-reported information privacy concerns would matter more when they received accurate (vs. inaccurate) proactive recommendations, because these pieces of advice would seem fair to them. We further hypothesized that this would particularly be the case for people high on the social personality trait Extraversion, who are by inclination prone to behaving in a more socially engaging manner. We put this to the test in a controlled experiment, in which users received manipulated proactive recommendations of high or low accuracy on their smartphone. Results indicated that information privacy concerns positively influenced a user’s engagement with proactive recommendations. Recommendation accuracy influenced user engagement in interaction with information privacy concerns and personality traits. Implications for the design of human-computer interaction for recommender systems are addressed.
KW - Concerns for information privacy
KW - Human-computer interaction
KW - Information privacy
KW - Personality-aware recommendations
KW - Proactive recommendation delivery
UR - http://www.scopus.com/inward/record.url?scp=85055530670&partnerID=8YFLogxK
U2 - 10.1007/s10844-018-0529-0
DO - 10.1007/s10844-018-0529-0
M3 - Article
AN - SCOPUS:85055530670
SN - 0925-9902
VL - 54
SP - 79
EP - 100
JO - Journal of Intelligent Information Systems
JF - Journal of Intelligent Information Systems
IS - 1
ER -