An Assessment of Factors Influencing Farmers’ Preferences for Human Wildlife Conflict Insurance: A Case Study of Taita Taveta County, Kenya

Abstract

Human-wildlife conflict (HWC) threatens rural livelihoods and conservation efforts in Kenya, particularly in communities near protected areas. In Taita Taveta County, households adjacent to Tsavo East and West National Parks frequently experience crop destruction, livestock predation, property damage, and occasional human injuries. These conflicts reduce agricultural productivity, threaten food security, and erode household income, highlighting the need for sustainable mitigation and risk management mechanisms. Traditional compensation schemes have often been ineffective, prompting interest in insurance-based approaches. This study analyzed the prevalence, socio-economic impacts, and insurance preferences associated with HWC in Taita Taveta County. Specifically, it assessed HWC prevalence, identified preferred features of HWC insurance, examined socio-economic effects, and determined factors influencing insurance preferences. The study applied Random Utility Theory (RUT) to understand decision-making under uncertainty and used the Contingent Valuation Method (CVM) to estimate farmers’ willingness to pay (WTP). A case study design and mixed-methods approach were employed. Data were collected from 397 households using structured questionnaires and from 12 focus group discussions (FGDs). Purposive and multi-stage sampling ensured representative coverage. Quantitative data were analyzed with descriptive statistics and logistic regression, while qualitative data were thematically analyzed. Results indicated that 90.7% of households experienced at least one form of HWC. Crop destruction was 78.3%, livestock predation 28.2%, and property loss 39.3%, with elephants causing most crop and property damage and carnivores such as lions, hyenas, and leopards responsible for livestock predation. Farmers preferred co-managed public–private insurance schemes at 56.2%, market price-based compensation at 86.2%, multi-peril coverage including crops and livestock at 91.5%, and mobile money payouts at 91.9%, with an acceptable annual premium of KES 350–410. Logistic regression revealed that household income, previous wildlife losses, herd size, insurance awareness, and WTP significantly influenced insurance preferences. The study concludes that HWC continues to impose significant socio-economic challenges. It recommends establishing affordable, inclusive, co-managed insurance schemes to enhance adaptive capacity, protect livelihoods, and promote human-wildlife coexistence.