Authors :
Abhishek Tiwary; Ajay Singh; Rajdeep Dey
Volume/Issue :
Volume 8 - 2023, Issue 9 - September
Google Scholar :
https://bit.ly/3TmGbDi
Scribd :
https://tinyurl.com/mry4vr4p
DOI :
https://doi.org/10.5281/zenodo.8355295
Abstract :
This paper delves into the intricate web of gendered differences in the perception of job insecurity
within knowledge process organizations, with a specific focus on the disruptive influence of Robotic
Process Automation (RPA). The digital transformation era has seen a surge in automation technologies,
and RPA, in particular, has had a significant impact on the workforce landscape. This study aims to
shed light on how this transformation is experienced differently by male and female employees.
Using a robust linear regression analysis, this research examines the data collected from a
substantial sample size of 1034 employees across various knowledge process organizations. The analysis
encompassed multiple facets of job insecurity, including the fear of job displacement, career stagnation,
and overall job satisfaction, as affected by the integration of RPA into their work environment.
Our findings reveal intriguing gender disparities in the perception of job insecurity. Male
employees tend to exhibit higher levels of job satisfaction in the face of RPA adoption, possibly due to
perceived opportunities for up skilling and career growth.
Furthermore, the study opens up opportunities to study potential factors contributing to these
disparities, such as the gender composition of job roles, access to training opportunities, and
management support. Understanding these nuances is crucial for organizations seeking to address
gender-related challenges in the wake of automation.
In conclusion, this research contributes to the growing body of literature on the impact of
automation on the workforce and extends it by highlighting the gendered dimensions of job insecurity.
It underscores the importance of implementing gender-sensitive policies and support mechanisms to
ensure an inclusive and equitable transition in knowledge process organizations facing the automation
wave.
This paper invites further discussions and empirical investigations to foster a more comprehensive
understanding of the gendered dynamics in the age of automation and, consequently, promote fairer
and more adaptive workplaces for all employees.
This paper delves into the intricate web of gendered differences in the perception of job insecurity
within knowledge process organizations, with a specific focus on the disruptive influence of Robotic
Process Automation (RPA). The digital transformation era has seen a surge in automation technologies,
and RPA, in particular, has had a significant impact on the workforce landscape. This study aims to
shed light on how this transformation is experienced differently by male and female employees.
Using a robust linear regression analysis, this research examines the data collected from a
substantial sample size of 1034 employees across various knowledge process organizations. The analysis
encompassed multiple facets of job insecurity, including the fear of job displacement, career stagnation,
and overall job satisfaction, as affected by the integration of RPA into their work environment.
Our findings reveal intriguing gender disparities in the perception of job insecurity. Male
employees tend to exhibit higher levels of job satisfaction in the face of RPA adoption, possibly due to
perceived opportunities for up skilling and career growth.
Furthermore, the study opens up opportunities to study potential factors contributing to these
disparities, such as the gender composition of job roles, access to training opportunities, and
management support. Understanding these nuances is crucial for organizations seeking to address
gender-related challenges in the wake of automation.
In conclusion, this research contributes to the growing body of literature on the impact of
automation on the workforce and extends it by highlighting the gendered dimensions of job insecurity.
It underscores the importance of implementing gender-sensitive policies and support mechanisms to
ensure an inclusive and equitable transition in knowledge process organizations facing the automation
wave.
This paper invites further discussions and empirical investigations to foster a more comprehensive
understanding of the gendered dynamics in the age of automation and, consequently, promote fairer
and more adaptive workplaces for all employees.
