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<p>Technology evolution has prompted us to transition towards a digital-centric life, which in turn has brought about significant risks in cyber systems. Cyber insurance helps mitigate this risk by transferring it to third parties. Despite its high prominence, its adoption rate is meagre. Accordingly, this study empirically examined the antecedent factors for individuals’ adoption of cyber insurance using a mixed-method approach combining qualitative and quantitative methodologies. Subsequently, a contextualized model is developed and informed by established theories and previously identified antecedents. Additionally, this model will be tested with a large-scale survey of Indian citizens using partial least squares structural equation modelling (PLS-SEM). Furthermore, this paper compares and contrasts the results of a fuzzy-set qualitative comparative analysis (fsQCA) to PLS-SEM results. The findings support a wide array of hypotheses regarding cyber insurance adoption and underline the significance of various crucial factors involved in the formation of policy decisions.</p>

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Cyber Insurance Adoption at Individual Level: A Mixed Method Study

  • 期刊论文

  • 发表日期：

    2026年3月19日

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  • Subinoy Banerjee,
  • Saini Das

摘要

Technology evolution has prompted us to transition towards a digital-centric life, which in turn has brought about significant risks in cyber systems. Cyber insurance helps mitigate this risk by transferring it to third parties. Despite its high prominence, its adoption rate is meagre. Accordingly, this study empirically examined the antecedent factors for individuals’ adoption of cyber insurance using a mixed-method approach combining qualitative and quantitative methodologies. Subsequently, a contextualized model is developed and informed by established theories and previously identified antecedents. Additionally, this model will be tested with a large-scale survey of Indian citizens using partial least squares structural equation modelling (PLS-SEM). Furthermore, this paper compares and contrasts the results of a fuzzy-set qualitative comparative analysis (fsQCA) to PLS-SEM results. The findings support a wide array of hypotheses regarding cyber insurance adoption and underline the significance of various crucial factors involved in the formation of policy decisions.