Systematic Review of Big Data Applications in Decoding Consumer Behaviors

  1. Qiankun Liu
  2. Ruigang Wang
  3. Muhabaiti Pareti
  4. Alessandra Castellini
  5. Maurizio Canavari

Reviewed by

Read the full article See related articles

Discuss this preprint

Start a discussion What are Sciety discussions?

Listed in

Log in to save this article

Abstract

Big data is pivotal in understanding consumer behavior and predicting consumer decisions. However, research has predominantly focused on specific consumption aspects, with a noticeable gap in systematic reviews on big data’s role in consumer behavior studies. This paper systematically reviews 127 articles to identify key topics, significance, challenges, and emerging trends in the application of big data to consumer behavior research. Our findings indicate that big data analysis in this field primarily focuses on consumer attitudes, behavior patterns, decision-making processes, and the impact of major events. Big data is categorized into structured and unstructured types, with deep learning, machine learning, and text data as essential research methods, particularly for predicting consumer trends. Future research should focus on enhancing data quality, improving model interpretability, and fostering stronger collaboration between academia and industry. This study advances the understanding of how big data can be effectively leveraged in consumer behavior research, highlighting its potential benefits and challenges.

Article activity feed

  1. PREreview

    This Zenodo record is a permanently preserved version of a Structured PREreview. You can view the complete PREreview at https://prereview.org/reviews/17254873.

    Does the introduction explain the objective of the research presented in the preprint? Yes
    Are the methods well-suited for this research? Highly appropriate
    Are the conclusions supported by the data? Highly supported
    Are the data presentations, including visualizations, well-suited to represent the data? Highly appropriate and clear
    How clearly do the authors discuss, explain, and interpret their findings and potential next steps for the research? Very clearly
    Is the preprint likely to advance academic knowledge? Highly likely
    Would it benefit from language editing? No
    Would you recommend this preprint to others? Yes, it's of high quality
    Is it ready for attention from an editor, publisher or broader audience? Yes, as it is

    Competing interests

    The author declares that they have no competing interests.

    Use of Artificial Intelligence (AI)

    The author declares that they did not use generative AI to come up with new ideas for their review.

  2. Version published to 10.20944/preprints202505.1668.v1