Examining Serendipitous Encounters and Self-Determination in Twitter-Enabled Innovation

Table 1

Sample characteristics (N = 473).

Variable	Category	Frequency
Gender	Female	200 (43%)
	Male	272 (57%)
Age	18–35 years	293 62%)
	36–50 years	152 (32%)
	51–67 years	28 (6%)
Nationality	UK	276 (58%)
	Rest of Europe	88 (19%)
	US	91 (19%)
	Other (<6 respondents per country)	18 (4%)
Education	Less than high school	4 (1%)
	Graduated high school	57 (12%)
	Trade/technical school	19 (4%)
	Some college, no degree	64 (14%)
	Associate degree	24 (5%)
	Bachelor’s degree	191 (40%)
	Advanced degree (master's, Ph.D., M.D.)	113 (24%)
Industry	Financial services/sales	85 (17.97%)
	ICT	76 (16.07%)
	Education	53 (11.21%)
	Architecture/logistics/infrastructure	40 (8.46%)
	Media/entertainment	37 (7.82%)
	Healthcare/medical/pharmaceutical	28 (5.92%)
	Business services	27 (5.71%)
	Manufacturing	24 (5.07%)
	Other, <5% each (government, biotechnologies, marketing, aerospace, research, food services, agriculture, etc.)	103 (21.78%)
Position/job title	Manager	140 (30%)
	Professional	132 (28%)
	Administrative/support personal	90 (19%)
	Top level executive	58 (12%)
	Other, <5% each (business owner, researcher, architect, freelancer, assistant, driver, editor, etc.)	53 (11%)
Twitter use experience in years	Less than a month	9 (2%)
	Less than a year	54 (11%)
	1–4 years	242 (51%)
	More than 4 years	168 (36%)