| By: |
Hafsa Lemsieh (UH2MC - Université Hassan II [Casablanca]);
Ibtissam Abarar |
| Abstract: |
In that emerging digital era, Artificial Intelligence technology headed by
machine learning, digital-smart technologies as well as the Big Data that
allows predictive analysis has a significant influence over many people
precisely those who are not all conscious and aware that the datasets are
assembled from their online interactions and activities, consequently it can
be used to anticipate and manipulate their purchasing psychology and behavior
out of their control. In these terms, this study is going to present the
literature that is in relation basically with the approach to the contribution
of the artificial intelligence technology in manipulating the purchasing
behavior based on the psychological factor. To guide this in deep study we
will include multiple sources of the secondary data, going from journal
articles, conference papers, internet sources and so on. The main objective is
to bridge and eliminate the gap in this somehow empty field of research. The
theoretical conclusions will offer an insight about the main importance in
terms of implementing the artificial intelligence tools in the field and the
department of marketing as a successful way to understand the consumers
preferences and their journey in terms of purchasing. The goal is to provide
predictive analysis and to know precisely how to manipulate the psychology of
consumers in order to influence their behavior. The generation Z are a real
opportunity to achieve this aim since they are digitally native and most of
their purchasing decisions occurs through the use of their smartphones as they
rely on social media for collecting and gathering any kind of information |
| Keywords: |
Artificial intelligence, Consumer behaviour, Digital Marketing, Manipulation, Psychology., Artificial intelligence Consumer behaviour Digital Marketing Manipulation Psychology. JEL Classification: M31 M15 D91 Type du papier: Theoretical Research, Psychology. JEL Classification: M31, M15, D91 Type du papier: Theoretical Research |
| Date: |
2024–06–23 |
| URL: |
https://d.repec.org/n?u=RePEc:hal:journl:hal-04629533 |