Bitte verwenden Sie diesen Link, um diese Publikation zu zitieren, oder auf sie als Internetquelle zu verweisen: https://hdl.handle.net/10419/230781 
Erscheinungsjahr: 
2019
Schriftenreihe/Nr.: 
IRTG 1792 Discussion Paper No. 2019-005
Verlag: 
Humboldt-Universität zu Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series", Berlin
Zusammenfassung: 
Software-as-a-service applications are experiencing immense growth as their comparatively low cost makes them an important alternative to traditional software. Following the initial adoption phase, vendors are now concerned with the continued usage of their software. To analyze the influence of different measures to improve continued usage over time, a longitudinal study design using data from a SaaS vendor was implemented. By employing a linear mixed model, the study finds several measures to have a positive effect on a software’s usage penetration. In addition to these activation measures performed by the SaaS vendor, software as well as client characteristics were likewise examined but did not display significant estimates. In summary the study contributes novel insights into the scarcely researched field of influencing factors on SaaS usage continuance.
Schlagwörter: 
Linear Mixed Models Software-as-a-Service Usage Continuance
JEL: 
C00
Dokumentart: 
Working Paper

Datei(en):
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