Social media overload,exhaustion, and use discontinuance: Examining the effects of information overload,system feature overload,and social overload |
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| Institution: | 1. School of Information Management, Wuhan University, Wuhan, China 430072;2. Department of Information and Knowledge Management, Tampere University, Tampere, Finland;3. Aalto University School of Business, Espoo Finland;4. Department of Information and Knowledge Management, Tampere University, Tampere, Finland;5. Faculty of Information Technology, University of Jyväskylä, Jyväskylä, Finland;1. School of Public Health, Department of Health Sciences (DISSAL), University of Genoa, Genoa, Italy;2. Department of Neuroscience, Rehabilitation, Ophthalmology, Genetics, Maternal and Child Health (DINOGMI), Section of Psychiatry, University of Genoa, Genoa, Italy;3. Department of Neurosurgery, Galliera Hospital, Genoa, Italy;4. Neurosciences Critical Care Unit, Addenbrooke''s Hospital, Cambridge, UK;5. Brain Physics Lab, Division of Neurosurgery, Department of Clinical Neurosciences, University of Cambridge, UK;6. Department of Neurology, Christian Doppler Klinik, Paracelsus Medical University, Salzburg, Austria;7. Department of Neurology, Franz Tappeiner Hospital, Merano, Italy;8. Center for Cognitive Neuroscience, Salzburg, Austria;9. Department of Public Health Technology Assessment, UMIT — University for Health Sciences, Medical Informatics and Technology, Hall i.T., Austria;10. Department of Neurological, Biomedical, and Movement Sciences, University of Verona, Italy;1. Harvard T.H. Chan School of Public Health, Harvard University, Boston, MA, United States;2. Division of Cardiology, Department of Medicine, University of Arkansas for Medical Sciences, Little Rock, AR, United States;3. Computational Oncology, Department of Epidemiology and Biostatistics, Memorial Sloan Kettering Cancer Center, New York, NY, United States |
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| Abstract: | While users’ discontinuance of use has posed a challenge for social media in recent years, there is a paucity of knowledge on the relationships between different dimensions of overload and how overload adversely affects users’ social media discontinuance behaviors. To address this knowledge gap, this study employed the stressor–strain–outcome (SSO) framework to explain social media discontinuance behaviors from an overload perspective. It also conceptualized social media overload as a multidimensional construct consisting of system feature overload, information overload, and social overload. The proposed research model was empirically validated via 412 valid questionnaire responses collected from Facebook users. Our results indicated that the three types of overload are interconnected through system feature overload. System feature overload, information overload, and social overload engender user exhaustion, which in turn leads to users’ discontinued usage of social media. This study extends current technostress research by demonstrating the value of the SSO perspective in explaining users’ social media discontinuance. |
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