Increased use and implementation of automation, accelerated by the COVID-19 pandemic, gives rise to a new phenomenon: occupation insecurity. In this paper, we conceptualize and define occupation insecurity, as well as develop an Occupation Insecurity Scale (OCIS) to measure it. From focus groups, subject-matter expert interviews, and a quantitative pilot study, two dimensions emerged: global occupation insecurity, which refers to employees' fear that their occupations might disappear, and content occupation insecurity, which addresses employees' concern that (the tasks of) their occupations might significantly change due to automation. In a survey-study sampling 1373 UK employees, psychometric properties of OCIS were examined in terms of reliability, construct validity, measurement invariance (across gender, age, and occupational position), convergent and divergent validity (with job and career insecurity), external discriminant validity (with organizational future time perspective), external validity (by comparing theoretically secure vs. insecure groups), and external and incremental validity (by examining burnout and work engagement as potential outcomes of occupation insecurity). Overall, OCIS shows good results in terms of reliability and validity. Therefore, OCIS offers an avenue to measure and address occupation insecurity before it can impact employee wellbeing and organizational performance.
Keywords: automation; occupation insecurity; scale validation.