The Consequences of Technostress for End Users in Organizations: Conceptual Development and Empirical Validation

Abstract

T he research reported in this paper studies the phenomenon of technostress, that is, stress experienced by end users of Information and Communication Technologies (ICTs), and examines its influence on their job satisfaction, commitment to the organization, and intention to stay. Drawing from the Transaction-Based Model of stress and prior research on the effects of ICTs on end users, we first conceptually build a nomological net for technostress to understand the influence of technostress on three variables relating to end users of ICTs: job satisfaction, and organizational and continuance commitment. Because there are no prior instruments to measure constructs related to technostress, we develop and empirically validate two second order constructs: technostress creators (i.e., factors that create stress from the use of ICTs) and technostress inhibitors (i.e., organizational mechanisms that reduce stress from the use of ICTs). We test our conceptual model using data from the responses of 608 end users of ICTs from multiple organizations to a survey questionnaire. Our results, based on structural equation modeling (SEM), show that technostress creators decrease job satisfaction, leading to decreased organizational and continuance commitment, while Technostress inhibitors increase job satisfaction and organizational and continuance commitment. We also find that age, gender, education, and computer confidence influence technostress. The implications of these results and future research directions are discussed.

Conceptual Framework: AIS Technostress and Its Effect on Professionals’ Job Outcomes

“…Again, findings of previous studies on job satisfaction of technostress were mostly based on general technostress (Kumar et al, 2014;Ragu-Nathan et al, 2008;Ayyagari, 2007; which therefore might not be transferable or applicable to the use of AIS because of its unique characteristics from other technologies. Besides, literature review failed to locate any technostress studies on antecedents of AIS technostress to job satisfaction.…”

“…Secondly, to measure the task performance, a five-item instrument used by Williams &Anderson (1991) used by (Bellia, 2007) is adopted with a Cronbach coefficient alpha of .91. Thirdly, to measure technostress creators a twenty three-item instrument developed by Ragu-Nathan, Tarafdar, Ragu-Nathan, & Tu (2008), used by is adopted with a Cronbach coefficient alpha of .86 and it has been frequently used in the previous research in this field. Fourthly, to measure technostress inhibitors a combination of eighteen-item instrument used by Ragu-Nathan, Tarafdar, Ragu-Nathan, & Tu (2008) used by Tarafdar et al (2011) is adopted with a Cronbach coefficient alpha of .86.…”

“…Technostress, like stress field of research is yet to be studied extensively by scholars (Lee, Jin, & Choi, 2012;Tarafdar, Tu, Ragu-Nathan, & Ragu-Nathan, 2007). Previously, research studies on technostress mostly focus on general technology usage, that is, from stressor-strain with moderating factors between the variables (Ragu-Nathan, Tarafdar, Ragu-Nathan, & Tu, 2008;Tarafdar, Tu, Ragu-Nathan, & Ragu-Nathan, 2007). Ayaggari et al, (2011) introduces a new theoretical approach (T-P Model) of investigating the characteristics of www.ccsenet.org/ass Asian Social Science Vol.…”

The factors that influence customer e-services adoption

“…Constant changes and complex customisations increase techno-stress [19]. Techno-stress creators are those factors that introduce stress into an information technology environment [20].…”

“…Technostress inhibitors, on the other hand, are ways to prevent techno-stress. For instance, technical support and help desks reduce techno-stress [19]. Techno-stress creators and inhibitors would unquestionably influence the adoption of e-services.…”