As the number of messages and social relationships embedded in social networking sites (SNS) increases, the amount of social information demanding a reaction from individuals increases as well. We observe that, as a consequence, SNS users feel they are giving too much social support to other SNS users. Drawing on social support theory (SST), we call this negative association with SNS usage 'social overload' and develop a latent variable to measure it. We then identify the theoretical antecedents and consequences of social overload and evaluate the social overload model empirically using interviews with 12 and a survey of 571 Facebook users. The results show that extent of usage, number of friends, subjective social support norms, and type of relationship (online-only vs offline friends) are factors that directly contribute to social overload while age has only an indirect effect. The psychological and behavioral consequences of social overload include feelings of SNS exhaustion by users, low levels of user satisfaction, and a high intention to reduce or even stop using SNS. The resulting theoretical implications for SST and SNS acceptance research are discussed and practical implications for organizations, SNS providers, and SNS users are drawn.

Although much research has been performed on the adoption and usage phases of the information systems life cycle, the final phase, termination, has received little attention. This paper focuses on the development of discontinuous usage intentions, i.e. the behavioural intention in the termination phase, in the context of social networking services (SNSs), where it plays an especially crucial role. We argue that users stressed by using SNSs try to avoid the stress and develop discontinuous usage intentions, which we identify as a behavioural response to SNS‐stress creators and SNS‐exhaustion. Furthermore, as discontinuing the use of an SNS also takes effort and has costs, we theorize that switching‐stress creators and switching‐exhaustion reduce discontinuous usage intentions. We tested and validated these effects empirically in an experimental setting monitoring individuals who stopped using Facebook for a certain period and switched to alternatives. Our results show that SNS‐stress creators and SNS‐exhaustion cause discontinuous usage intentions, and switching‐stress creators and switching‐exhaustion reduce these intentions.

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This paper investigates under what conditions stress fromthe use of SNS is linked to addiction to the use of the same SNS. Integrating three theoretical strands-the concept of feature-rich Information Technology (IT), the theory of technology frames, and distraction as a coping behaviour-we theorize two types of coping behaviours in response to stressors experienced from the use of SNS. These are -distraction through use of the same SNS and distraction through activities outside the use of the SNS. We hypothesize relationships between stressors from SNS use, the two coping behaviours and SNS addiction. We further articulate the role of SNS use habit. We test the hypotheses through a three-wave survey of 444 Facebook users with data collected at three different points in time. The paper's contributions are to theorize and empirically validate the psychological concept of distraction as a coping behaviour in response to stress from the use of SNS and, in doing so, explain why there may be a link between technostress from and technology addiction to the use of the same SNS.

Technology adoption research has long struggled to incorporate normative beliefs from sources in the social environment of adopters into adoption models. We study the role of social influence from different workplace referent groups, like superiors and colleagues from the same or the IT department, on the intention to adopt. An empirical analysis, using data from 152 firms, based on the Unified Theory of Acceptance and Use of Technology and related approaches reveals that social influence on adoption significantly differs with regard to both source (peer groups) and sink (adopters and non-adopters) of the influence. The results imply that a single cumulative subjective norm measure might be too naïve and that future research might considerably improve our understanding of IT adoption and non-adoption by revealing the differential impact of various peer groups on adoption intention, and also on its antecedents.

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