Table 1

Sample description

VariablesFrequencies (n = 256)
Gender 
Women 152 (59.4%) 
Men 104 (40.6%) 
Age 
<20 years 4 (1.6%) 
20–29 years 63 (24.6%) 
30–39 years 96 (37.5%) 
40–49 years 82 (32.0%) 
50+ years 11 (4.3%) 
Education 
Middle school degree 4 (1.6%) 
High school degree 97 (37.9%) 
Bachelor/Master’s degree 138 (53.9%) 
Doctoral and other postgraduate degrees 17 (6.6%) 
Occupation 
Student 45 (17.6%) 
Employee 137 (53.5%) 
Self-employed 31 (12.1%) 
Unemployed 5 (2.0%) 
Other 38 (14.8%) 
Why did you interact with a chatbot? 
Asking information 89 (34.6%) 
Buying products/services 41 (16.0%) 
Asking for assistance 91 (35.6%) 
Making complaints 35 (13.8%) 
To what sector do your most frequent chatbots belong? 
Fashion 21 (8.4%) 
Personal (health)care 16 (6.2%) 
Technology 72 (28.0%) 
Telecommunications 75 (29.4%) 
Travel and entertainment 34 (13.1%) 
Financial and insurance services 38 (14.9%) 
VariablesFrequencies (n = 256)
Gender 
Women 152 (59.4%) 
Men 104 (40.6%) 
Age 
<20 years 4 (1.6%) 
20–29 years 63 (24.6%) 
30–39 years 96 (37.5%) 
40–49 years 82 (32.0%) 
50+ years 11 (4.3%) 
Education 
Middle school degree 4 (1.6%) 
High school degree 97 (37.9%) 
Bachelor/Master’s degree 138 (53.9%) 
Doctoral and other postgraduate degrees 17 (6.6%) 
Occupation 
Student 45 (17.6%) 
Employee 137 (53.5%) 
Self-employed 31 (12.1%) 
Unemployed 5 (2.0%) 
Other 38 (14.8%) 
Why did you interact with a chatbot? 
Asking information 89 (34.6%) 
Buying products/services 41 (16.0%) 
Asking for assistance 91 (35.6%) 
Making complaints 35 (13.8%) 
To what sector do your most frequent chatbots belong? 
Fashion 21 (8.4%) 
Personal (health)care 16 (6.2%) 
Technology 72 (28.0%) 
Telecommunications 75 (29.4%) 
Travel and entertainment 34 (13.1%) 
Financial and insurance services 38 (14.9%) 

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