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Job demands and technology overload influencing work stress in organizations during the COVID-19 pandemic
Aslib Journal of Information Management ; 2022.
Article in English | Web of Science | ID: covidwho-2191291
ABSTRACT
PurposeThis study is based on the stimulus-organism-response (SOR) model to examine how job demands and technology overload affect work stress for workers using video conferencing apps (VCAs) in organizations during the COVID-19 pandemic. Moreover, the moderating effect of technology self-efficacy was tested in the model on the relationship between technology overload and work stress.Design/methodology/approachAn online survey was conducted to investigate workers on PTT forums in Taiwan. A sample was obtained of 253 workers, and structural equation modeling was conducted using AMOS to test the hypotheses.FindingsJob demands positively affect work stress through information overload, communication overload and system feature overload. Moreover, high technology self-efficacy may weaken the relationship between technology overload and work stress.Research limitations/implicationsThe study may have sample bias because our sample was obtained from an online survey on social networking sites. Regarding the theoretical implications, this study demonstrated that technology overload, as an internal organism, is a critical mediator influencing the relationship between job demands (stimulus) and work stress (response). Thus, this study extended the applicability of the SOR model in the context of working with VCAs in organizations.Practical implicationsCompany managers need to effectively control the information amount, communication interruptions and system features of social media at optimum levels for workers. Moreover, companies should recruit workers with high technology self-efficacy or provide technology training and technology-related consulting to those with low technology self-efficacy.Originality/valueThe extant work stress knowledge is extended to workers using VCAs in organizations.
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Full text: Available Collection: Databases of international organizations Database: Web of Science Language: English Journal: Aslib Journal of Information Management Year: 2022 Document Type: Article

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Full text: Available Collection: Databases of international organizations Database: Web of Science Language: English Journal: Aslib Journal of Information Management Year: 2022 Document Type: Article