Abstract:
The Technological advancements have profoundly affected the organizational and societal
developments, as they have enabled easy access and connectivity irrespective of the time and
location. However, the immense and excessive usage of information and communication
technology (ICT) are inevitably changing the employee’s current working lives and patterns.
It entails greater availability expectations and usage on employees which can lead towards
detrimental outcomes like technology related stress. Thus, it is important to analyze such ICT
events that are increasingly indispensable in various aspects of routine life and business. The
current study highlights the issue of ICT events like supervisor availability expectations and
work-related use of ICT after work hours, especially by focusing on media sector employees
that are highly impacted by these circumstances. This research contributes to the literature
through statistically testing the association between ICT events, technostress and employee
withdrawal intentions using quantitative analysis. Moreover, the mediating role of technostress
and moderating role of perceived interruptions overload was also analyzed in this research. A
sample data of 225 employees was collected from news media industry using non-probability
sampling techniques i.e., convenience and snowballing technique. The research findings
proved that the ICT events have positive significant association with technostress and
employee withdrawal intentions. The related theoretical and practical implications are also
proposed in this research for further researches. Through theoretically relating the transactional
stress theory with the proposed research model, it was proved that extreme and inconsiderate
usage of information and communication technology can result in technological stress.
Furthermore, this research recommends practitioners to introduce policies and procedures that
enable employees to deal with stressful environments. It was also suggested to implement the
current research model in country wise contextual setting.
