The impact of green marketing on consumers’ attitudes: A moderating role of green product awareness

  • Received April 20, 2023;
    Accepted September 7, 2023;
    Published September 28, 2023
  • Author(s)
  • DOI
    http://dx.doi.org/10.21511/im.19(3).2023.20
  • Article Info
    Volume 19 2023, Issue #3, pp. 237-253
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This work is licensed under a Creative Commons Attribution 4.0 International License

This study aims to determine the impact of green marketing (green perceived value), green products (green buildings), and environmental concerns on Jordanian consumers’ attitudes toward buying green buildings in Jordan. The research population includes all consumers in Amman, the capital of Jordan, who might be interested in buying such buildings. A convenience sample is used to collect data from the respondents by distributing the questionnaire among 400 consumers using Google Forms. 357 questionnaires were found valid for statistical analysis. The results of the multiple regression test showed that R equals 0.815, which indicated that green marketing and consumers’ attitudes toward buying green buildings in Jordan are positively and highly correlated, with a percentage of 81.5%. R square equals 0.664, indicating that the variation in green marketing explains 66.4% of the variance in consumers’ attitudes toward green buildings in Jordan. Moreover, the hierarchical multiple regression test showed that there is an increase in R and R2 values in the existence of product awareness as a moderating variable between green marketing and consumers’ attitudes toward buying green buildings in Jordan.

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    • Figure 1. Conceptual model
    • Figure 2. Regression weights for independent variable
    • Figure 3. Regression weights and coefficients of determinations for the research model
    • Table 1. Sample characteristics
    • Table 2. EFA analysis for research variables
    • Table 3. Matrix of correlation between research variables
    • Table 4. Model fit indicators of research variables
    • Table 5. Model fit indicators
    • Table 6. Reliability test (Cronbach’s alpha) for all variables
    • Table 7. Means for research variables
    • Table 8. Suitability of research data to test hypotheses using VIF
    • Table 9. Normal distribution of research variables
    • Table 10. Multiple linear regressions analysis for H1
    • Table 11. Hierarchical multiple regression analysis for H2
    • Table A1. Research questionnaire
    • Conceptualization
      Antoun Sahioun, Abdallah Q. Bataineh
    • Data curation
      Antoun Sahioun
    • Investigation
      Antoun Sahioun, Abdallah Q. Bataineh
    • Resources
      Antoun Sahioun, Abdallah Q. Bataineh, Ibrahim A. Abu-AlSondos, Hossam Haddad
    • Validation
      Antoun Sahioun
    • Writing – original draft
      Antoun Sahioun, Abdallah Q. Bataineh
    • Formal Analysis
      Abdallah Q. Bataineh
    • Methodology
      Abdallah Q. Bataineh, Hossam Haddad
    • Supervision
      Abdallah Q. Bataineh
    • Writing – review & editing
      Abdallah Q. Bataineh, Hossam Haddad
    • Funding acquisition
      Ibrahim A. Abu-AlSondos, Hossam Haddad
    • Project administration
      Ibrahim A. Abu-AlSondos
    • Software
      Ibrahim A. Abu-AlSondos, Hossam Haddad
    • Visualization
      Ibrahim A. Abu-AlSondos