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Reputational Risk Management in the Era of Information Asymmetry: A Behavioral Model of Relational Quality (IRSQ)

Submitted:

24 July 2026

Posted:

27 July 2026

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Abstract
This article redefines risk in the financial sector, specifically concerning life insurance, by focusing on the behavioral determinants of stakeholder decisions. Under conditions of high information asymmetry, characteristic of credence goods, traditional qualitative models demonstrate significant cognitive gaps, failing to adequately address the mechanisms of building institutional trust. The primary objective of the article is to analyze the "authenticity gap," defined as the behavioral dissonance between an organization's declarative strategies (e.g., in the area of ESG) and the subjective perception of their credibility by clients. The study utilizes the Integrated Relational Service Quality (IRSQ) model, which serves as a tool for measuring behavioral risk, representing a further stage of development from the SERVQUAL model and the Customer Service Quality Index (WJOK). The IRSQ model enables the mathematical parameterization of cognitive dissonances that lead to the erosion of social capital. Based on empirical research conducted on a sample of 647 respondents, it was demonstrated that in the face of crises (including the COVID-19 pandemic), it is the behavioral dimension of relational quality that functions as a key moderator of institutional resilience. The results prove that the proactive use of IRSQ tools allows for the mitigation of greenwashing risk by addressing cognitive mechanisms of authenticity verification. The article provides novel evidence that, in the era of the information society, reputational risk management must be inextricably linked to a behavioral model of relational quality, thus constituting an essential element supporting the management of financial enterprises (property and life insurance). This study is a continuation of research [Przybytniowski, 2020, 2022, 2023, 2024, 2026]
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Copyright: This open access article is published under a Creative Commons CC BY 4.0 license, which permit the free download, distribution, and reuse, provided that the author and preprint are cited in any reuse.
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