Women’s Support in Resilience of Online Taxi Drivers’ Families in Jakarta During COVID-19 Pandemic

Authors

  • Dhita Ayu Pradnyapasa Urban Studies Program, School of Strategic and Global Studies, Universitas Indonesia, Jakarta 10430, Indonesia
  • Renny Nurhasana Urban Studies Program, School of Strategic and Global Studies, Universitas Indonesia, Jakarta 10430, Indonesia
  • Ni Made Shellasih Center for Social Security Studies, School of Strategic and Global Studies, Universitas Indonesia, Jakarta 10320, Indonesia
  • Anita Siti Fatonah Center for Social Security Studies, School of Strategic and Global Studies, Universitas Indonesia, Jakarta 10320, Indonesia
  • Fadhilah Rizky Ningtyas Center for Social Security Studies, School of Strategic and Global Studies, Universitas Indonesia, Jakarta 10320, Indonesia

DOI:

https://doi.org/10.21512/tw.v22i2.7025

Keywords:

women support, family resilience, online taxi drivers

Abstract

The research aimed to assess women’s support to maintain the resilience of online taxi drivers’ families in Jakata during COVID-19 pandemic. The research applied a qualitative method. Data were collected by conducting interview with four participants, who were the wives of online taxi-bike drivers. Four dimensions were believed to be important for family resilience within the pandemic, namely women’s support to integrity variable, physical endurance, economic resilience, and social-psychological resilience. The research finds various important women’s support in maintaining the family resilience during COVID-19 pandemic. It is found that women as wives are able to retain good communication between family members, provide nutritious food for family members, support economic resilience by minimizing expenditures, manage to teach children at home while taking care of younger babies, and so forth. The research limitation is on the variability of the participants. It is suggested that further research implements quantitative methods to gain more data and expand the number of participants for more exploration.

Dimensions

Plum Analytics

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Published

2021-08-12
Abstract 286  .
PDF downloaded 165  .