Towards a VUCA-Responsive Livestock Genetics Enterprise Framework: A Conceptual Model from Chivara Farm, Zimbabwe

The study sought to develop a VUCA-Responsive Livestock Genetics Enterprise Framework (VLGEF) to explain and guide the emergence, adaptation, and scaling of livestock genetics enterprises in volatile, uncertain, complex, and ambiguous (VUCA) environments, using Chivara Farm in Zimbabwe as an embedded case. Situated within the transforming post-land reform agricultural landscape and influenced by climate variability, disease outbreaks such as Foot-Mouth Disease (FMD), and growing diaspora investment flows, the study adopts a qualitative, theory-building research approach grounded in an interpretivist paradigm. A single case study design is employed, drawing on secondary data, practitioner insights, and documented experiential knowledge to construct an analytically rich narrative of enterprise development. The study integrates five complementary theoretical lenses, Chaos Theory, Innovation Management, Strategic Decision-Making Theory, the Viable System Model (VSM), and Entrepreneurial Orientation, to enable theoretical triangulation and conceptual synthesis. Through abductive reasoning, these perspectives are combined to develop the VLGEF, a multi-layered framework linking the livestock system context, VUCA environmental pressures, a central genetic value engine, strategic capability configurations, governance structures, and adaptive decision-making processes. The findings demonstrate that sustainable scaling of livestock genetics enterprises depends on the integration of systematic genetic recording, decentralised breeder networks, phased artificial intelligence adoption, diaspora-oriented investment models, and robust biosecurity and governance systems. The study further reveals that resilience and competitiveness are achieved not through linear growth, but through adaptive learning cycles, non-linear strategic responses, and the co-evolution of biological, technological, and organisational capabilities. The proposed framework contributes to both theory and practice by offering a context-sensitive, systems-oriented model for enterprise development in African agriculture and other emerging market settings. The study concludes that livestock genetics enterprises can play a transformative role in enhancing productivity, climate resilience, and inclusive agricultural development when supported by integrated innovation, governance, and market strategies. However, the framework remains conceptually derived and case-specific; therefore, further research is recommended to empirically validate the VLGEF across multiple contexts, test its applicability in different livestock systems, and explore the operationalisation of AI-enabled genetic platforms, diaspora financing mechanisms, and policy integration strategies within broader agricultural development programmes.