.png){kind=icon}
.png){kind=icon}
Return
The Diderot effect: a data-driven validation
.png){kind=icon}
PRE
AI
DOI：10.1057/s41270-024-00371-6.png)
.png){kind=icon}
Original request for help.png){kind=icon}
Share.png){kind=icon}
Save
Abstract
En 中文
Although it is theorized that consumer decisions are commonly irrational and based on systematic biases, there remains a need for more data-driven research to validate and expand upon these assumptions fully. This study is one of the few that, based on analysis and interpretation of complex data instead of qualitative methods, validates one of those biases, the Diderot effect. This study presents a conceptual model and a pioneering research approach combining indirect data and machine learning techniques to validate the manifestation of the Diderot effect on the purchase process of products of a specific category through an online retailer. Results showed that a laptop computer could be one of those products and that consumers might be more predisposed to making unforeseen purchases when they are already in a spending mindset. The findings highlight opportunities for marketing professionals to leverage the Diderot effect, creating value for consumers and organizations.
Keywords:
Diderot effect
Consumer Buying Behavior
Complementary Products
Generalized Sequential Pattern Algorithm
Biases
Machine Learning
Journal
IF:
3.5
Papers:
385
Citations:
1.2K