Semantic Scholar Open Access 2024 5 sitasi

Domesticating technology: Learning from the use of mobile phone of small women rural entrepreneurs in India during COVID-19

Debjani Chakraborty Chhavi Garg

Abstrak

The COVID-19 pandemic and the worldwide lockdowns that followed the same have led to drastic changes in our lifestyles. While the lockdowns marked a global transition to a world of online services and products, the change was neither easy nor smooth for many. From lack of access to technology to the absence of skills to use it, the act of “going digital” was littered with challenges for people across the world. In the South-Asian country of India, this lack of access was further amplified by the presence of a gender digital divide. Among the women from various factions of the society, one such category affected by it was female entrepreneurs from small rural areas in India. These entrepreneurs were cut off from their clientele owing to a nationwide lockdown in the country imposed to curb the spread of COVID-19. Most of these women had no prior experience with technology (which is mobile phones in their case) but they not only negotiated access but used it to sustain and grow their entrepreneurial endeavors in a short duration of time. This study, through in-depth qualitative interviews with female entrepreneurs from small rural areas in India maps their usage patterns and their negotiations for domesticating mobile phones. The research found that the first two stages of domestication theory (appropriation and objectification) were easier to navigate for the women entrepreneurs, but gender expectations from them made the last two stages of incorporation and conversion challenging.

Penulis (2)

D

Debjani Chakraborty

C

Chhavi Garg

Format Sitasi

Chakraborty, D., Garg, C. (2024). Domesticating technology: Learning from the use of mobile phone of small women rural entrepreneurs in India during COVID-19. https://doi.org/10.1177/20501579241246721

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Informasi Jurnal
Tahun Terbit
2024
Bahasa
en
Total Sitasi
Sumber Database
Semantic Scholar
DOI
10.1177/20501579241246721
Akses
Open Access ✓