Do Individual Characteristics Influence the Types of Technostress Reported by Workers?

ABSTRACT

Based on the perspective that the diversity of the workforce has implications for attitudes and behaviors at the individual and group levels, this article examines the role of individual differences related to gender, age, formal education, and length of professional experience in the levels of stress caused by the use of information technology (IT) in the daily activities of workers. This phenomenon, termed in the literature as technostress, is studied by identifying and measuring the factors that create technostress (the technostress creator factors: techno-uncertainty, techno-invasion, techno-overload, and techno-complexity). The technostress phenomenon is related to the most varied types of disorders in workers and losses in organizations, such as fatigue, dissatisfaction, anxiety, and reduced productivity. To achieve the goal of this research, we applied structural equation models in a sample of 927 questionnaires completed by 14 different Brazilian public institutions that were distributed among all regions of the country and that were strongly dependent on IT for their main business processes. The results indicate that workers’ demographic characteristics relate to one another differently and specifically with the various forms of manifestation of technostress. More precisely, older workers or those with longer professional experience reported greater difficulties with the increase of technological complexity for the execution of tasks (techno-complexity). Women reported being subject to higher levels of techno-complexity and techno-uncertainty, while men indicated feeling greater effects from techno-overload and techno-invasion. We did not detect differences related to the levels of formal education of workers. This study presents the implications of the results for theory and for the everyday life of modern organizations that are increasingly dependent on the use of IT.

KEYWORDS:

• Technostress
• Individual Differences
• Diversity
• Structural Equation Models
• MIMIC

Additional information

Notes on contributors

Danilo Magno Marchiori

Danilo Magno Marchiori is a Ph.D. candidate in Management at University of Beira Interior (Portugal) and MSc. in Management at FUCAPE Business School, Vitória/ES (Brazil). He is a research fellow in NECE-UBI (Núcleo de Estudos em Ciências Empresariais).

Emerson Wagner Mainardes

Emerson Wagner Mainardes is a Ph.D. in Management, Associate Professor at FUCAPE Business School, Vitória/ES, Brazil. He is a teacher and researcher in Management and Marketing. He is a research fellow in NECE (Núcleo de Estudos em Ciências Empresariais). Expertise: Innovation and Marketing.

Ricardo Gouveia Rodrigues

Ricardo Gouveia Rodrigues is a Professor at University of Beira Interior and deputy director of the Research Centre NECE-UBI. He holds a Ph.D. in Business. His main research interests are Entrepreneurship and Marketing. He has over 40 international publications, participated in several projects and coordinated an international project on impact of Entrepreneurship Education.