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<p>This study examines how financial planning among self-employed workers functions not merely as an individual skill but as a socially embedded capability shaped by institutional conditions, digital infrastructures, occupational heterogeneity, and behavioral routines. Framed within social economics, the study explores how the literature has conceptualized the relationships among financial planning, economic vulnerability, distributive stability, resilience, and well-being in increasingly precarious, digitalized labor markets. A systematic review of 272 peer-reviewed articles published between 2008 and 2025 was conducted using bibliographic coupling, qualitative content analysis, bibliometric mapping, and multinomial Least Absolute Shrinkage and Selection Operator (LASSO) modeling. To strengthen computational traceability, reproducibility, and methodological credibility, the LASSO model was audited and re-estimated in Python using coded evidence extracted from full-text articles. The findings suggest that the literature converges on three interdependent domains that shape financial planning among self-employed workers: capability, behavioral architecture, and contextual enablers. Digital literacy emerged as a relevant classifier of planning horizons within the coded literature; however, this result should be interpreted as a classification pattern in the reviewed studies rather than as a direct behavioral predictor in real-world settings. The study synthesizes fragmented evidence into a triadic framework that links micro-level financial practices to broader issues of vulnerability, social protection, risk redistribution, economic agency, and distributive outcomes. By reframing financial planning as a socio-economic capability rather than solely an individual competence, the article contributes to the field of social economics and highlights directions for future research using primary microdata and longitudinal designs.</p>

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Financial planning as a socio-economic capability in self-employment: explaining resilience and vulnerability

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2026年7月6日

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  • Lívia Cristine da Silva Paulino,
  • Wesley Vieira da Silva,
  • Rodrigo Pereyra de Sousa Coelho,
  • Fabíola Kaczam,
  • Claudimar Pereira da Veiga

摘要

This study examines how financial planning among self-employed workers functions not merely as an individual skill but as a socially embedded capability shaped by institutional conditions, digital infrastructures, occupational heterogeneity, and behavioral routines. Framed within social economics, the study explores how the literature has conceptualized the relationships among financial planning, economic vulnerability, distributive stability, resilience, and well-being in increasingly precarious, digitalized labor markets. A systematic review of 272 peer-reviewed articles published between 2008 and 2025 was conducted using bibliographic coupling, qualitative content analysis, bibliometric mapping, and multinomial Least Absolute Shrinkage and Selection Operator (LASSO) modeling. To strengthen computational traceability, reproducibility, and methodological credibility, the LASSO model was audited and re-estimated in Python using coded evidence extracted from full-text articles. The findings suggest that the literature converges on three interdependent domains that shape financial planning among self-employed workers: capability, behavioral architecture, and contextual enablers. Digital literacy emerged as a relevant classifier of planning horizons within the coded literature; however, this result should be interpreted as a classification pattern in the reviewed studies rather than as a direct behavioral predictor in real-world settings. The study synthesizes fragmented evidence into a triadic framework that links micro-level financial practices to broader issues of vulnerability, social protection, risk redistribution, economic agency, and distributive outcomes. By reframing financial planning as a socio-economic capability rather than solely an individual competence, the article contributes to the field of social economics and highlights directions for future research using primary microdata and longitudinal designs.