Employee Turnover, Retention Architecture, and the Economics of Talent Mobility

Abstract

This review examines employee turnover, retention architecture, and talent mobility as interconnected dimensions of
contemporary workforce strategy and labour-market economics. Its purpose is to clarify the determinants and forms of
employee departure, evaluate the organisational and economic consequences of talent loss, assess the effectiveness of
retention systems, and consider how workforce analytics and emerging technologies are reshaping mobility management.
An integrative review approach was adopted, synthesising multidisciplinary evidence from human resource management,
organisational behaviour, strategic management, labour economics, and people analytics, with attention to evidence from
developed and emerging economies.
The review finds that turnover is driven by interacting individual, organisational, relational, and labour-market factors rather
than by dissatisfaction alone. Regrettable departures can erode productivity, institutional knowledge, customer continuity,
and firm-specific human capital, while selected forms of mobility can improve job matching, wage progression, knowledge
diffusion, and broader resource allocation. Effective retention therefore depends on integrated systems combining career
development, supportive leadership, fair rewards, engagement, organisational commitment, job embeddedness, internal
mobility, and differentiated interventions for strategically valuable talent. Workforce analytics and predictive technologies can
strengthen early identification of turnover risk, although their effectiveness depends on data quality, contextual interpretation,
transparency, and ethical governance.
The review concludes that sustainable talent strategy requires balancing organisational continuity with the legitimate mobility
of employees. It recommends targeted retention architecture, stronger career pathways, continuous capability development,
improved managerial practice, and responsible use of predictive analytics. Future research should prioritise longitudinal,
cross-national, and causal designs examining actual mobility behaviour, hybrid work, algorithmic management, and changing
patterns of human-capital allocation across increasingly fluid, technology-mediated, and connected labour markets.