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The Diderot effect: a data-driven validation

Research output: Contribution to journal › Article › peer-review

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Abstract

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.
Original languageEnglish
Pages (from-to)535-551
Number of pages17
JournalJournal of Marketing Analytics
Volume14
Issue number2
Early online date8 Jan 2025
DOIs
Publication statusPublished - Jun 2026

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 12 - Responsible Consumption and Production
    SDG 12 Responsible Consumption and Production

Keywords

  • Diderot effect
  • Consumer Buying Behavior
  • Complementary Products
  • Generalized Sequential Pattern Algorithm
  • Biases
  • Machine Learning

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