Ainsworth Efficiency-Driven Welfare Framework for Poultry Systems

Thesis Abstract

Poultry production systems face escalating pressures to balance economic efficiency with animal welfare, disease risk, and environmental sustainability, yet there remains a lack of integrated frameworks that quantify welfare alongside productivity in a coherent decision-support model. This study develops and tests the Ainsworth Efficiency-Driven Welfare Framework, a theory-informed model that synthesizes welfare indicators, production efficiency metrics, and risk-adjusted economic outcomes to guide system design and management decisions in commercial poultry operations. The aim is to operationalize welfare and efficiency as co-equal dimensions and to provide a parsimonious yet robust framework capable of guiding policy and on-farm practice toward optimized outcomes. Specific objectives are to (i) identify a parsimonious set of welfare indicators with proven sensitivity to management changes; (ii) quantify the trade-offs and synergies between welfare metrics and production efficiency across broiler, layer, and breeder operations; (iii) develop a composite Welfare-Efficiency Index (WEI) and validate it against field performance data; (iv) examine the moderating role of management practices, housing systems, and biosecurity on the WEI; and (v) generate evidence-based recommendations for risk-adjusted decision-making under different economic scenarios. The methodology adopts a mixed-methods, multi-site, cross-sectional design. The population comprises commercial poultry farms across three production types (broilers, layers, breeders) in three major agro-ecological zones. A stratified random sample will include 60 farms (20 per production type) with proportional representation of cage, free-range, and conventional housing. Quantitative data will be collected via structured on-farm assessments, routine production records, and environmental monitoring over a 12-month period, yielding a dataset of at least 10,800 farm-week observations. Instruments include a validated welfare indicator protocol capturing physical health, behavioral expression, mortalities, lameness, and feather condition; environmental sensors for stocking density, temperature-humidity index, air quality, and ammonia; and production metrics such as feed conversion ratio, daily gain, egg production and quality, and mortality rates. Qualitative insights will be obtained through semi-structured interviews with farm managers and veterinarians to elucidate management decision processes and perceived welfare challenges. Validity and reliability will be ensured through pilot testing, inter-rater reliability checks (Cohen’s kappa > 0.70), and instrument calibration. Data analysis will proceed in three stages. First, descriptive statistics will characterize the welfare and efficiency profiles across production types and housing systems. Second, multivariate regression and structural equation modeling will test the theoretical pathways among welfare indicators, environmental conditions, production efficiency, and economic outcomes, with WEI as the latent endogenous construct. Third, a cluster analysis will identify farm typologies, while sensitivity analyses will explore robustness to data missingness and measurement error. ANOVA will compare WEI across housing systems and production types, and moderation analyses will assess the influence of management practices on the welfare-efficiency relationship. The theoretical grounding draws on the Capability Approach and the Biocultural Welfare Theory, integrating with the Five Domains of Welfare and the Russell-Nash efficiency framework to justify a composite WEI and to interpret trade-offs. Ainsworth’s framework will be operationalized into measurable indicators and scoring rules, enabling cross-case comparison and decision-support. Expected findings include (i) distinct welfare-efficiency profiles by production type and housing system, with higher WEI scores associated with lower morbidity and mortality, improved behavioral adequacy, and favorable FCR and egg quality in modern enriched housing; (ii) a demonstrable positive association between WEI and net farm profitability under stable market conditions, and improved resilience under biosecurity shocks; (iii) identification of management practices (e.g., optimized stocking density, thermal comfort, enriched environments) that maximize WEI without compromising production economics. The study contributes to knowledge by delivering a validated, theory-based framework that harmonizes welfare science with economic performance, offering a transferable tool for researchers, policymakers, and practitioners to evaluate and optimize poultry systems. Recommendations include adoption of the WEI in routine farm audits, refinement of welfare-sensitive pricing and incentive schemes, and targeted training to implement practices that simultaneously enhance welfare and efficiency. The framework is intended to be adaptable to emerging welfare indicators and evolving production technologies, ensuring relevance for future sustainability assessments in poultry production.