Vineberg, Rebecca (2021) The Digital Age: Exploring Age and Technology amid the COVID-19 Pandemic. Masters thesis, Concordia University.
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Abstract
The COVID-19 pandemic challenged organizations to accelerate and transform their technology landscape in order to support business continuity by introducing aspects such as remote work and process automation. Central to research on technology in the workplace is the concept of age, and how older workers adapt to technology compared to younger peers. The extant literature on age and technology in the workplace posits that older workers are less willing and able to adapt to and adopt technology, and tends to focus on factors such as neurological and physiological aging as well as motivational factors related to using technology. The following quantitative and qualitative research proposes a model of aging and technology in the workplace from a stereotype-threat perspective, and hypothesizes that subjective age can play a role in older workers’ self-perceptions of their ability to use technology. Through time-lagged research that looked at both quantitative and qualitative measures, we found support for the role of cognitive age in predicting computer anxiety and computer self-efficacy better than chronological age. In addition, we found evidence that comparative age plays a role as well, such that workers with similarly aged colleagues tend to evaluate their experiences using technology differently than workers with younger colleagues. Overall, the research supports that social and environmental factors are salient considerations that must be understood more clearly in order to truly understand the relationship between age and technology adoption.
Keywords: Age, technology, stereotype, computer anxiety, computer self-efficacy
Divisions: | Concordia University > John Molson School of Business > Management |
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Item Type: | Thesis (Masters) |
Authors: | Vineberg, Rebecca |
Institution: | Concordia University |
Degree Name: | M. Sc. |
Program: | Administration (Management option) |
Date: | 6 December 2021 |
Thesis Supervisor(s): | Dyer, Linda |
ID Code: | 990083 |
Deposited By: | REBECCA VINEBERG |
Deposited On: | 16 Jun 2022 15:19 |
Last Modified: | 16 Jun 2022 15:19 |
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