Human resource churning;, Mitigation strategies;, Qualitative method;, Content analysis;, Interviews.


Introduction: Given the multiplicity of definitions about the concept of human resource churning, we took as a premise, the costs associated with the replacement of workers from voluntary departures from organisations. As this is a subject that has not yet been widely explored in Portugal, this study aims to expand the theoretical framework, as well as the empirical studies; Goals; Methods: This qualitative study aims to identify the main precedents of human resource churning and the strategic measures applied by organisations to mitigate it. In order to make the objective feasible, the research question was: what is the origin of churning in organisations and what are the mitigation measures? As a data collection method, 20 semi-structured interviews were conducted with human resources directors from various sectors of activity, which were analysed through content analysis in order to extract the main variables, emphasising the development of a theoretical model and its analysis; Results: In order to analyse this model, 3 propositions were defined and proceeded to their substantiation, using the literature on the subject and the information obtained through the interviews, it was possible to analyse the veracity of the defined propositions. It was possible to predict that human resource churning precedents negatively influence the occurrence of human resource churning; that mitigation measures have a positive influence on human resource churning and that mitigation measures have a positive influence on human resource churning precedents; Conclusions: The greater the investment in the application and/or development of policies and practices of human resources retention, the lower the churning rate will be, and therefore the costs derived from the replacement of workers will be reduced.


Adams, J. (2006). The Many Costs of Employee Churn. Supply House Times, 1, 26-28.

Bardin, L. (2011). Análise de conteúdo. Edições 70.

Biscourp, P. & Kramarz, F. (2007). Employment, Skill Structure and International Trade: Firm-Level Evidence for France. Journal of International Economics, 72(1), 22–51.

Burgess, S., Lane, J. & Stevens, D. (2000). Job flows, worker flows, and churning. Journal of Labor Economics, 18, 473-502.

Burgess, S., Lane, J. & Stevens, D. (2001). Churning dynamics: an analysis of hires and separations at the employer level. Labour Economics, 8, 1-14.

Cappelli, P. & Neumark, D. (2004). External Churning and Internal Flexibility: Evidence on the functional flexibility and core-periphery hypotheses. Industrial Relations, 43(1), 148-182.

Carlomagno, M. & Rocha, L. (2016). Como criar e classificar categorias para fazer análise de conteúdo: uma questão metodológica. Revista Eletrônica de Ciência Política, 7(1), 173-178.

Degbey, W.; Rodgers, P.; Kromah, M. & Weber, Y. (2021). The impact of psychological ownership on employee retention in mergers and acquisitions. Human Resource Management Review, 31(3), 1-16.

Duhautois, R.; Gilles, F. & Petit, H. (2016). Decomposing the relationships between wage and churning. International Journal of Manpower, 37, 660-683.

Ekawati, D. (2019). Predictive Analytics in Employee Churn: A systematic literature review. Journal of Management Information and Decision Sciences, 22(4), 387-397.

Eppelsheimer. J. & Moller, J. (2019). Human capital spillovers and the churning phenomenon: analyzing wage effects from gross in-and outflows of high skilled workers. Elsivier. Regional Science and Urban Economics, 78, 1-19.

Hudson, C. (2015). Churning in the Human Services: Nefarious Practice or Policy of “Creative Destruction”? New England Journal of Public Policy, 27(1), 1-11.

Ilmakunnas, P. e Maliranta, M. (2005). Worker Inflow, Outflow, and Churning. Applied Economics, 37(10), 1115-1133.

Kamalaveni, M.; Ramesh, S. & Vetrivel, T. (2019) A Review of Literature on Employee Retention. International Journal of Innovative Research in Management Studies (IJIRMS), 4(4),1-10.

Katz, L. & Kearney, M. (2008). Trends in U.S. Wage Inequality: Revising the Revisionists. The Review of Economics and Statistics, 90(2), 300–323.

Kerr, A. (2018). Job flows, worker flows and churning in South Africa. South African Journal of Economics, 86(1), 141-166.

Mobley, W. H. (1992). Turnover: causas, consequências e controle. Porto Alegre: Ortiz.

Moreira, G.; Oliveira, M.; Lopes, A. & Pantoja, M. (2018). Concepção de suporte organizacional e intenção de rotatividade com base na literatura. Sociedade e Cultura, 21(1), 219-231.

Moulana, M.; Priyanka, Y.; Ismail, M. & Priyanka, A. (2020). Early prediction of employee churn. Test Engineering e Management, 83, 18302-18307.

Pirrolas, O. & Correia, P. (2020). O churning aplicado à gestão de recursos humanos: a importância de um modelo de previsão. Lex Humana, 12(1), 59-68.

Pirrolas, O. & Correia, P. (2021). The theoretical-conceptual model of churning in human resources: the importance of its operationalization. Sustainability, 13(9), 1-11.

Pirrolas, O. & Correia, P. (2022a). As Principais Causas de Churning de Recursos Humanos. In, Temas Emergentes em Ciências Empresariais: Novas abordagens nas áreas científicas dos Recursos Humanos, Marketing e Turismo, Empreendedorismo e Inovação. Vol.2, Lisboa, Portugal: Edições Sílabo.

Pirrolas, O. & Correia, P. (2022b). About churning. Academia Letters, 1, 5114, 1-8.

Pirrolas, O. & Correia, P. (2022c). Literature Review on Human Resource Churning—Theoretical Framework, Costs and Proposed Solutions. Social Sciences, 11(489), 2-15.

Quivy, R., & Campenhoudt, L. (2013). Manual de investigação em ciências sociais. (6ª Edição). Gradiva.

Rodrik, D. (1998). Why Do more Open Economies Have Bigger Governments?. Journal of Political Economy, 106(5), 997–1032.

Saradhi, V. & Palshikar, G. (2010). Employee Churn Prediction. Expert Systems whith Applications, 38(3), 1999-2006.

Schumpeter, J. (1976). Capitalism, socialism and democracy. 5ª edição. George Allen e Unwin (Publishers) LDA.

Weber, S. & Luzzi, G. (2014). From Lifetime Jobs to Churning? Swiss Society of Economics and Statistics, 150 (3) 227–260.

Yigit, I. & Shourabizadeh, H. (2017). An Approach for Predicting Employee Churn by Using Data Mining. IEEE. Artificial Intelligence and Data Processing Symposium International (IDAP), p.1-4.



How to Cite

Olga Alexandra Chinita Pirrolas, & Pedro Miguel Alves Ribeiro Correia. (2023). PRECEDENTS OF HUMAN RESOURCE CHURNING AND ITS MITIGATION: A STUDY OF THE PORTUGUESE REALITY. New Trends in Qualitative Research, 19, e814.