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dc.contributor.authorPappas, Ilias
dc.contributor.authorPapavlasopoulou, Sofia
dc.contributor.authorMikalef, Patrick
dc.contributor.authorGiannakos, Michail
dc.description.abstractSocial Networking Sites (SNSs) play an important role in our daily lives and the number of their users increases regularly. To understand how users can be satisfied in the complex digital environment of SNSs, this study examines how motivations and emotions combine with each other to explain high satisfaction. Users’ motivations comprise four attributes, entertainment, information, social-psychological, and convenience. Emotions are divided into their two main categories, that is positive and negative emotions. We draw on complexity and configuration theories, present a conceptual model along with propositions and perform a fuzzy-set qualitative comparative analysis (fsQCA). Through an empirically study with 582 SNSs users, we present eight combinations (configurations) of motivations and emotions that lead to high satisfaction, which highlight the role of high convenience, followed by entertainment and information motivations in being satisfied with SNSs. High satisfaction can be achieved both when positive and negative emotions are high and low, depending on how they combine users’ motivations. None of the factors are indispensable to explain high satisfaction on their own, instead they are insufficient but necessary parts of the causal combinations that explain high satisfaction. This study contributes in SNSs literature by extending current knowledge on how motivations and emotions combine to increase satisfaction, and by identifying specific patterns of users for whom these factors are important and influence greatly their satisfaction.en_US
dc.rightsNavngivelse 4.0 Internasjonal*
dc.titleIdentifying the combinations of motivations and emotions for creating satisfied users in SNSs: An fsQCA approachen_US
dc.typePeer revieweden_US
dc.typeJournal articleen_US
dc.source.journalInternational Journal of Information Managementen_US
dc.description.localcode© 2020 The Authors. Published by Elsevier Ltd. This is an open access article under the CC BY license (

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Navngivelse 4.0 Internasjonal
Except where otherwise noted, this item's license is described as Navngivelse 4.0 Internasjonal