Determinants of Visitors’ Willingness to Pay for Enhanced Ecosystem Services in Mudumalai Tiger Reserve, Tamil Nadu, India: A Contingent Valuation Approach

• Published in: The journal of environment & development Vol. 33; no. 3; pp. 443 - 474
• Main Authors: V, Rajkumar, S, Boopathi
• Format: Journal Article
• Language: English
• Published: Los Angeles, CA SAGE Publications 01-09-2024; SAGE PUBLICATIONS, INC
• Subjects: Change agents; Conservation; Contingent valuation; Ecosystem services; Ecosystems; Education; Environmental awareness; Environmental changes; Externality; Family size; Financial support; Human-environment relationship; Mitigation; Prioritizing; Regression analysis; Regression models; Services; Side effects; Valuation; Visitors; Wildcats; Wildlife; Wildlife conservation; Wildlife refuges; Willingness to pay; Tamil Nadu India; India; enhanced ecosystem services; willingness to pay; externalities; contingent valuation method; logit regression model; Mudumalai Tiger Reserve
• ISSN: 1070-4965; 1552-5465
• DOI: 10.1177/10704965241241867

This study examined the factors influencing visitors’ willingness to pay for improved ecosystem services through the conservation of the Mudumalai Tiger Reserve (MTR) in the Nilgiris District, Tamil Nadu, India. The MTR plays a crucial role in providing and protecting various ecosystem services. However, it is vulnerable to negative externalities and drivers of ecosystem change, which affect the quality and quantity of ecosystem services, leading to the loss of valuable ecosystem services. To address this issue, it is necessary to understand the adverse effects of externalities and drivers of ecosystem change, as well as to consider people’s preferences. To investigate the factors influencing visitors’ willingness to pay for enhanced ecosystem services in MTR, this study used a dichotomous choice-contingent valuation method and a logit regression model. The study found that 64% of visitors expressed concern about mitigating adverse impacts and were willing to provide financial support. The results of the logit regression analysis further revealed that factors such as family size, respondent education, monthly family income, environmental awareness, and bid price significantly influenced visitors’ willingness to pay. To enhance ecosystem benefits and address the challenges in tiger conservation within the reserve, our study suggests that several measures need to be implemented, including prioritizing education, awareness, the mitigation of human–wildlife conflict, and income-linked and dynamic pricing strategies.