In recent years, the implementation of ICT in various companies has become more and more popular. Although its adoption and implementation have a good impact on the company’s business, it also has a negative impact on the employees, which are also known as technostress. The goal of this research is to examine the influence of technostress on employee’s work performance. The total data collected consists of 446 participants who come from a different area, such as JABODETABEK Indonesia. The study is done online, using Google Forms, from April 28, 2024, to 30 November 2024. And be processed using Partial Least Squares Structural Equation Modeling (PLS-SEM), using Smart PLS 4.0 for assessing the quality of each variable by measuring data validation and reliability. Several variables will be examined such as techno-overload, techno-invasion, techno-uncertainty, technostress, productivity, quality of work life, exhaustion, job satisfaction, and work performance. This research uses non-probability purposive sampling with criteria as employees experienced challenges when implementing a new set of skills required for learning new software technologies. This research findings show that 11 out of the 11 hypotheses have significant impact.

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Exploring Technostress and Its Impact on Employees in IT-Driven Work Performance

  • Rommy Wijaya,
  • Alvina,
  • Erwin Halim

摘要

In recent years, the implementation of ICT in various companies has become more and more popular. Although its adoption and implementation have a good impact on the company’s business, it also has a negative impact on the employees, which are also known as technostress. The goal of this research is to examine the influence of technostress on employee’s work performance. The total data collected consists of 446 participants who come from a different area, such as JABODETABEK Indonesia. The study is done online, using Google Forms, from April 28, 2024, to 30 November 2024. And be processed using Partial Least Squares Structural Equation Modeling (PLS-SEM), using Smart PLS 4.0 for assessing the quality of each variable by measuring data validation and reliability. Several variables will be examined such as techno-overload, techno-invasion, techno-uncertainty, technostress, productivity, quality of work life, exhaustion, job satisfaction, and work performance. This research uses non-probability purposive sampling with criteria as employees experienced challenges when implementing a new set of skills required for learning new software technologies. This research findings show that 11 out of the 11 hypotheses have significant impact.