Factors and issues affecting electronic insurance adoption in an emerging market

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This study examines the factors and issues affecting the adoption of electronic insurance (EI) in the Jordanian insurance sector. The methodology of the study is based on convenience sampling, thus, the sample consists of 175 respondents familiar with E-services, with different backgrounds, professions, businesses, income groups, sectors, and regions. Questionnaires were distributed and disseminated electronically using SurveyMonkey. The study employs both descriptive and ANOVA analyses to analyze the responses. The results show that EI promotes sustainability, reduces costs, saves time and holds some operational benefits beneath. The ANOVA results show that the impact of income and age on sustainability, cost-effectiveness, and operational benefits is significant at least at the 5% significance level. Respondents are also aware that EI may involve issues and challenges related to security and privacy, customer-related issues such as lack of knowledge about repositories, and insurer-related issues such as data shifting. The ANOVA results indicate that gender affects customers’ perceptions of EI adoption regarding customer-related issues; its effect is significant at the 5% level of significance. On the other hand, age and income level are important factors that shape respondents’ perceptions of EI in Jordan. Age is only significant for security-related issues, and income level is a deciding factor in insurer-related issues; their effect is strong and highly significant at the 5% and 1% levels, respectively.

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    • Table 1. Demographic profile of respondents*
    • Table 2. Summary of various factors affecting EI adoption in Jordan (20 statements) covering the dimensions of sustainability, cost-effectiveness, and operational benefit
    • Table 3. Summary of the responses to various issues and challenges in EI in Jordan (14 statements) covering the dimensions of security, customer, and insurer-related issues
    • Table 4. Analysis of Variance (ANOVA) between Gender variable and customer perceptions of EI
    • Table 5. Analysis of Variance (ANOVA) between Age variable and customer perceptions of EI
    • Table 6. Analysis of Variance (ANOVA) between Income level variable and customer perceptions of EI
    • Table 7. Analysis of Variance (ANOVA) between Gender variable and perceived issues in using EI
    • Table 8. Analysis of Variance (ANOVA) between Age variable and perceived issues in using EI
    • Table 9. Analysis of Variance (ANOVA) between Income level variable and perceived issues in using EI
    • Conceptualization
      Maen F. Nsour, Samer A. M. AL-Rjoub
    • Investigation
      Maen F. Nsour, Mohammad Tayeh
    • Validation
      Maen F. Nsour, Samer A. M. AL-Rjoub, Husam Kokash
    • Writing – original draft
      Maen F. Nsour, Samer A. M. AL-Rjoub
    • Data curation
      Samer A. M. AL-Rjoub
    • Formal Analysis
      Samer A. M. AL-Rjoub, Mohammad Tayeh, Husam Kokash
    • Methodology
      Samer A. M. AL-Rjoub, Mohammad Tayeh, Husam Kokash
    • Project administration
      Samer A. M. AL-Rjoub, Mohammad Tayeh
    • Software
      Samer A. M. AL-Rjoub, Husam Kokash
    • Supervision
      Samer A. M. AL-Rjoub, Mohammad Tayeh
    • Writing – review & editing
      Mohammad Tayeh, Husam Kokash