Participants' socio-demographics and IoT behaviors
| Item | Category | Frequency | % | Item | Category | Frequency | % |
|---|---|---|---|---|---|---|---|
| Age | Born 1981–1989 | 17 | 04.250 | Average household Income | Less than 2,000 | 59 | 15.000 |
| Born 1990–1996 | 183 | 45.750 | 2,000 – less than 5,000 | 70 | 17.000 | ||
| Born 1997–2012 | 200 | 50.000 | 5,000 – less than 10,000 | 85 | 21.300 | ||
| Over 10,000 | 186 | 46.500 | |||||
| Gender | Female | 172 | 43.000 | Occupation | White collar | 86 | 21.500 |
| Male | 228 | 57.000 | Blue collar | 294 | 73.500 | ||
| Other | 20 | 5.000 | |||||
| Marital status | Single | 239 | 59.000 | Education | Elementary school | 1 | 0.300 |
| Married | 145 | 36.000 | High school | 63 | 15.8 | ||
| Divorced/Separated | 13 | 3.000 | College degree | 104 | 26.0 | ||
| Widowed | 3 | 0.800 | Graduate degree | 102 | 25.5 | ||
| Postgraduate degree | 107 | 26.8 | |||||
| Other | 23 | 5.8 | |||||
| Reasons for buying IoT | Social influence | 63 | 15.800 | Reasons for not buying IoT | Social influence | 16 | 4.000 |
| Ease of use | 104 | 26.000 | Lack of trust | 107 | 26.800 | ||
| Trendy | 13 | 3.300 | Lack of availability | 360 | 90.000 | ||
| Fun | 10 | 2.500 | Lack of relevance | 104 | 26.000 | ||
| Reliable | 361 | 90.300 | Not aware | 86 | 21.500 | ||
| Other | 16 | 4.000 | Expensive | 239 | 59.000 | ||
| Other | 13 | 3.000 | |||||
| IoT owned | Cars | 7 | 1.800 | IoT future purchases | Cars | 104 | 54.000 |
| Fashion/Accessories | 159 | 39.800 | Fashion/Accessories | 102 | 26.000 | ||
| Home appliance | 18 | 4.500 | Home appliance | 107 | 25.500 | ||
| Home entertainment | 107 | 26.800 | Home entertainment | 216 | 26.800 | ||
| Smart health-product | 7 | 1.800 | Smart health-product | 107 | 26.800 | ||
| others | 3 | 0.800 | others | 18 | 4.500 |
| Item | Category | Frequency | % | Item | Category | Frequency | % |
|---|---|---|---|---|---|---|---|
| Age | Born 1981–1989 | 17 | 04.250 | Average household Income | Less than 2,000 | 59 | 15.000 |
| Born 1990–1996 | 183 | 45.750 | 2,000 – less than 5,000 | 70 | 17.000 | ||
| Born 1997–2012 | 200 | 50.000 | 5,000 – less than 10,000 | 85 | 21.300 | ||
| Over 10,000 | 186 | 46.500 | |||||
| Gender | Female | 172 | 43.000 | Occupation | White collar | 86 | 21.500 |
| Male | 228 | 57.000 | Blue collar | 294 | 73.500 | ||
| Other | 20 | 5.000 | |||||
| Marital status | Single | 239 | 59.000 | Education | Elementary school | 1 | 0.300 |
| Married | 145 | 36.000 | High school | 63 | 15.8 | ||
| Divorced/Separated | 13 | 3.000 | College degree | 104 | 26.0 | ||
| Widowed | 3 | 0.800 | Graduate degree | 102 | 25.5 | ||
| Postgraduate degree | 107 | 26.8 | |||||
| Other | 23 | 5.8 | |||||
| Reasons for buying IoT | Social influence | 63 | 15.800 | Reasons for not buying IoT | Social influence | 16 | 4.000 |
| Ease of use | 104 | 26.000 | Lack of trust | 107 | 26.800 | ||
| Trendy | 13 | 3.300 | Lack of availability | 360 | 90.000 | ||
| Fun | 10 | 2.500 | Lack of relevance | 104 | 26.000 | ||
| Reliable | 361 | 90.300 | Not aware | 86 | 21.500 | ||
| Other | 16 | 4.000 | Expensive | 239 | 59.000 | ||
| Other | 13 | 3.000 | |||||
| IoT owned | Cars | 7 | 1.800 | IoT future purchases | Cars | 104 | 54.000 |
| Fashion/Accessories | 159 | 39.800 | Fashion/Accessories | 102 | 26.000 | ||
| Home appliance | 18 | 4.500 | Home appliance | 107 | 25.500 | ||
| Home entertainment | 107 | 26.800 | Home entertainment | 216 | 26.800 | ||
| Smart health-product | 7 | 1.800 | Smart health-product | 107 | 26.800 | ||
| others | 3 | 0.800 | others | 18 | 4.500 |
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