Systemic gender barriers to ICT adoption
| 1st order barriers | 2nd order themes | Systemic influences |
|---|---|---|
| Lack of women role models | Role models | Social |
| Lack of women in senior leadership roles in the tech industry | ||
| Lack of women in the STEM disciplines | ||
| Conversations within women’s networks do not emphasise IT | Lack of emphasis | |
| Not enough talk about IT adoption in women associations and organisations | ||
| Women rely on others to make business decisions (often spouses/partners, friends) | Traditional gender role | |
| Women are under-represented in STEM programs | Credentials | Education |
| Women entrepreneurs are older and thus less tech savvy | Age | Owner characteristics |
| Younger women entrepreneurs have less barriers | ||
| Older entrepreneurs tend to delegate their need for tech to another member of the firm | ||
| It’s more of a generational issue than gender issue | ||
| Women’s lack confidence | Confidence | |
| Women lack abilities to analyse and understand data | Abilities, skills, experience | |
| Women rely on others for digital skills | ||
| Women lack experience and background in tech | ||
| Women are less inclined to take risks | Risk aversion | |
| Women are less open to new technologies | ||
| Lack of growth intention | Business orientation | |
| Women tend to under capitalise their firms and thus have less money for IT adoption | ||
| Men and women approach technology differently | ||
| Women-led businesses tend to be smaller and thus have fewer resources for IT adoption | Firm size | Firm characteristics |
| Micro-businesses have hard time seeing results brought by tech adoption | ||
| Women-owned firms are more likely to be service focussed, less likely to adopt tech | Sector | |
| Women are more likely to adopt technologies if other women in their sector do so |
| 1st order barriers | 2nd order themes | Systemic influences |
|---|---|---|
| Lack of women role models | Role models | Social |
| Lack of women in senior leadership roles in the tech industry | ||
| Lack of women in the STEM disciplines | ||
| Conversations within women’s networks do not emphasise IT | Lack of emphasis | |
| Not enough talk about IT adoption in women associations and organisations | ||
| Women rely on others to make business decisions (often spouses/partners, friends) | Traditional gender role | |
| Women are under-represented in STEM programs | Credentials | Education |
| Women entrepreneurs are older and thus less tech savvy | Age | Owner characteristics |
| Younger women entrepreneurs have less barriers | ||
| Older entrepreneurs tend to delegate their need for tech to another member of the firm | ||
| It’s more of a generational issue than gender issue | ||
| Women’s lack confidence | Confidence | |
| Women lack abilities to analyse and understand data | Abilities, skills, experience | |
| Women rely on others for digital skills | ||
| Women lack experience and background in tech | ||
| Women are less inclined to take risks | Risk aversion | |
| Women are less open to new technologies | ||
| Lack of growth intention | Business orientation | |
| Women tend to under capitalise their firms and thus have less money for IT adoption | ||
| Men and women approach technology differently | ||
| Women-led businesses tend to be smaller and thus have fewer resources for IT adoption | Firm size | Firm characteristics |
| Micro-businesses have hard time seeing results brought by tech adoption | ||
| Women-owned firms are more likely to be service focussed, less likely to adopt tech | Sector | |
| Women are more likely to adopt technologies if other women in their sector do so |
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