Assessing pro-environmental behaviors and implications for integrated conservation in protected areas: A study of visitors and entrepreneurs in the Asinara National Park, Italy


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Understanding pro-environmental behaviors in protected areas is vital for effective resource management, visitor management, infrastructure development, and conservation strategies. Therefore, this study aims to assess environmentally friendly practices and behaviors (eco-practices) of visitors (demand side) and entrepreneurs and tour operators (supply side) to explore the implications for the long-term sustainability of the protected area. The study utilizes the shared value framework and the value-belief-norm theory extended to environmentalism to investigate the relevant values for pro-environmental behaviors. The paper focuses on the Asinara National Park in Italy. It employs a partial least squares-structural equation model to analyze the pro-environmental behavior and willingness to commit to conservation goals. The findings reveal that visitors demonstrate a willingness to commit to eco-practices in a protected area based upon non-extractive cultural ecosystem services (path coefficient = 0.196*) and accept earmarked taxation (path coefficient = 0.254***), which indicates their loyalty and satisfaction with their visit. On the other hand, entrepreneurs are motivated by internally adopted ecological practices (path coefficient = 0.509***) and altruistic reasons (path coefficient = 0.377**). In conclusion, the study emphasizes aligning service and facility supply with demand and the mission of protected areas to achieve balanced and sustainable resource management. By understanding and promoting pro-environmental behaviors, long-term resilience can be ensured for protected areas, benefiting both the environment and the visitors.

We would like to thank the participants of the XI Workshop on Institutions, Individual Behavior and Economic Outcomes, Session Environmental and Ecological Economics, Corte (France) and at the Research Meeting Seminar, Burgundy School of Business, Dijon (France) for their helpful comments. We also thank Fondazione di Sardegna (Economia e Benessere tra Società e Istituzioni), grant 2022–2023, Programme 2014–2020 INTERREG V-A Italy – France Maritime (grant EcoSTRIM), and Fondo di Ateneo UNISS 2020 for financial support.

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    • Figure 1. Conceptual framework (on the demand side)
    • Figure 2. Conceptual framework (on the supply side)
    • Figure 3. Methodological approach
    • Figure A1. Bar chart of loadings of demand items
    • Figure A2. Demand structural model
    • Figure A3. Bar chart of loading supply items
    • Figure A4. Supply structural model
    • Table 1. Main statistics: PLS-SEM for the demand side
    • Table 2. Measurement model (demand side)
    • Table 3. Structural model – Standardized path coefficients (Bootstrap)
    • Table 4. Main statistics: PLS-SEM for the supply side
    • Table 5. Measurement model (supply side)
    • Table 6. Structural model relationships (supply side)
    • Table A1. Description of the items employed in the model specification (demand side)
    • Table A2. Description of the items employed in the model specification (supply side)
    • Table A3. Descriptive statistics demand side – Socio-demographic characteristics
    • Table A4. Descriptive statistics supply side – Socio-demographic characteristics
    • Table A5. Descriptive statistics supply side – Business information
    • Table A6. Descriptive statistics supply sample – Activities
    • Conceptualization
      Marta Meleddu, Manuela Pulina, Marco Vannini, Marilena Vecco
    • Data curation
      Marta Meleddu, Manuela Pulina
    • Formal Analysis
      Marta Meleddu, Manuela Pulina
    • Funding acquisition
      Marta Meleddu, Marco Vannini
    • Methodology
      Marta Meleddu, Manuela Pulina
    • Project administration
      Marta Meleddu, Marco Vannini
    • Writing – original draft
      Marta Meleddu, Manuela Pulina, Marco Vannini, Marilena Vecco
    • Investigation
      Manuela Pulina
    • Supervision
      Manuela Pulina, Marco Vannini
    • Validation
      Marco Vannini, Marilena Vecco
    • Visualization
      Marilena Vecco