Determinants of Online Social Business Network Usage Behavior—Applying the Technology Acceptance Model and Its Extensions
- 1 Research Department, Masem Research Institute, Wiesbaden, Germany
- 2 Department of Cultural and Social Sciences, University of Giessen, Giessen, Germany
- 3 Research Department, Masem Research Institute, Wiesbaden, Germany
Abstract
Usage of online social business networks like LinkedIn and XING have become commonplace in today’s workplace. This research addresses the question of what factors drive the intention to use online social business networks. Theoretical frame of the study is the Technology Acceptance Model (TAM) and its extensions, most importantly the TAM2 model. Data has been collected via a Web Survey among users of LinkedIn and XING from January to April 2010. Of 541 initial responders 321 finished the questionnaire. Operationalization was tested using confirmatory factor analyses and causal hypotheses were evaluated by means of structural equation modeling. Core result is that the TAM2 model generally holds in the case of online social business network usage behavior, explaining 73% of the observed usage intention. This intention is most importantly driven by perceived usefulness, attitude towards usage and social norm, with the latter effecting both directly and indirectly over perceived usefulness. However, perceived ease of use has—contrary to hypothesis—no direct effect on the attitude towards usage of online social business net works. Social norm has a strong indirect influence via perceived usefulness on attitude and intention, cre ating a network effect for peer users. The results of this research provide implications for online social business network design and marketing. Customers seem to evaluate ease of use as an integral part of the usefulness of such a service which leads to a situation where it cannot be dealt with separately by a ser vice provider. Furthermore, the strong direct impact of social norm implies application of viral and peer- to-peer marketing techniques while it’s also strong indirect effect implies the presence of a network effect which stabilizes the ecosystem of online social business service vendors.
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