• ISSN: 2301-3567 (Print), 2972-3981 (Online)
    • Abbreviated Title: J. Econ. Bus. Manag.
    • Frequency: Quarterly
    • DOI: 10.18178/JOEBM
    • Editor-in-Chief: Prof. Eunjin Hwang
    • Executive Editor: Ms. Fiona Chu
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HOME > Archive > 2026 > Volume 14 Number 3 (2026) >
JOEBM 2026 Vol.14(3): 172-174
DOI: 10.18178/joebm.2026.14.3.931

Anchoring Bias: Cognitive Mechanisms, Cross-Domain Applications, and Empirical Validation

Chenxi Tang
Chenxi Tang
Business Enterprise and Innovative Management, Northumbria University London, London, United Kingdom
Email: 350444042@qq.com

Manuscript received April 5, 2026; accepted June 27, 2026; published September 2, 2026.

Abstract—Anchoring bias leads individuals to rely excessively on initial information during decision-making and fail to make sufficient adjustments, resulting in systematic cognitive and behavioral deviations. Rooted in the dual-process cognitive model, this bias is influenced by anchoring characteristics, individual differences, and task contexts. It widely exists in consumer behavior, financial investment, organizational management, and public policy, causing distorted judgments and efficiency losses. Empirical evidence confirms that professional experience and cognitive intervention can weaken anchoring bias to a certain extent. In the digital era, algorithm-driven anchoring has become a new form that requires more attention. This paper reviews the connotation, mechanism and applications of anchoring bias, proposes debiasing strategies, and outlines future research directions, helping individuals and organizations enhance the rationality of decision-making.

Keywords—anchoring bias, cognitive mechanism; consumer behavior, financial decision-making, organizational management

Cite: Chenxi Tang, "Anchoring Bias: Cognitive Mechanisms, Cross-Domain Applications, and Empirical Validation," Journal of Economics, Business and Management, vol. 14, no. 3, pp. 172-174, 2026.

Copyright © 2026 by the authors. This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).

 

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