Information Overload in Big Data Environments: A Systematic Review

doi:N/A

eISSN: 2202-4859 / ISSN: None

Revenue Law Journal

2026, Volume 32, ISSUE 2 : 1-7

Research Article

Information Overload in Big Data Environments: A Systematic Review

Aryan Kumar

Lillian M. Chen

Marco Alberto

Department of Information Systems, Eastern Institute of Technology, India

School of Data Science, Pacific University, Singapore

Faculty of Information Management, European School of Business Research, Italy

Abstract

Information overload has become a critical concern in the era of big data, where organizations face challenges in processing, analyzing, and interpreting massive volumes of data. This systematic review examines the antecedents, consequences, and mitigation strategies for information overload in big data environments. By reviewing 85 peer-reviewed articles published between 2010 and 2025, the study categorizes the key sources of overload, identifies organizational and individual-level outcomes, and evaluates technological and managerial solutions. The findings emphasize the need for intelligent data filtering, adaptive visualization, automated decision-support systems, and cognitive-aligned interface design. The review contributes a synthesized model for understanding information overload in big data contexts and proposes future research directions.

Keywords

Information overload

Big data

Data analytics

Cognitive load

Decision-making

Systematic review

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