Skip to main content

Write a PREreview

Systematic Review of Big Data Applications in Decoding Consumer Behaviors

Posted
Server
Preprints.org
DOI
10.20944/preprints202505.1668.v1

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.

You can write a PREreview of Systematic Review of Big Data Applications in Decoding Consumer Behaviors. A PREreview is a review of a preprint and can vary from a few sentences to a lengthy report, similar to a journal-organized peer-review report.

Before you start

We will ask you to log in with your ORCID iD. If you don’t have an iD, you can create one.

What is an ORCID iD?

An ORCID iD is a unique identifier that distinguishes you from everyone with the same or similar name.

Start now