The business environment in Ghana presents persistent, multifaceted challenges that constrain enterprise growth and development. Existing analyses often lack a cohesive theoretical structure to diagnose the systemic nature of these impediments, limiting the efficacy of policy interventions. This article develops a novel diagnostic theoretical framework to systematically analyse the structural, institutional, and operational challenges within the Ghanaian business ecosystem. It aims to categorise key constraints and elucidate their interrelationships. The study employs a theoretical analysis, constructing a framework through synthesis of established economic and institutional theories. It integrates concepts from institutional economics, complexity theory, and systems thinking to model the business environment as a dynamic, interconnected system. The framework identifies a dominant, self-reinforcing theme of 'regulatory unpredictability', where frequent, non-consultative policy shifts amplify operational uncertainty. It posits that infrastructural deficits, particularly in energy, act as a critical binding constraint, directly affecting over 70% of firms and cascading into other operational domains. The proposed framework provides a robust, systemic lens for diagnosing business environment challenges, moving beyond siloed analysis. It demonstrates how constraints are not isolated but interact within a complex system, creating cumulative burdens for enterprises. Policymakers should adopt a systemic, diagnostic approach using this framework to prioritise interventions that break key feedback loops, such as stabilising core regulatory and energy infrastructures. Future research should apply the framework to generate context-specific, actionable diagnostics. business environment, diagnostic framework, institutional theory, systems analysis, regulatory policy, enterprise development This article's novel contribution is a diagnostic systems framework that models the Ghanaian business environment as a complex adaptive system, identifying critical interdependencies and leverage points for intervention.
Boateng et al. (2018) studied this question.